case study of organisational innovation

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Article contents

Organizational innovation.

• Fariborz Damanpour Fariborz Damanpour Rutgers Business School, Newark and New Brunswick
• https://doi.org/10.1093/acrefore/9780190224851.013.19
• Published online: 22 August 2017

Innovation is a complex construct and overlaps with a few other prevalent concepts such as technology, creativity, and change. Research on innovation spans many fields of inquiry including business, economics, engineering, and public administration. Scholars have studied innovation at different levels of analysis such as individual, group, organization, industry, and economy. The term organizational innovation refers to the studies of innovation in business and public organizations.

Studies of innovations in organizations are multidimensional, multilevel, and context-dependent. They investigate what external and internal conditions induce innovation, how organizations manage innovation process, and in what ways innovation changes organizational conduct and outcome. Indiscreet application of findings from one discipline or context to another, lack of distinction between generating (creating) and adopting (using) innovations, and likening organizational innovation with technological innovation have clouded the understanding of this important concept, hampering its advancement. This article organizes studies of organizational innovation to make them more accessible to interested scholars and combines insights from various strands of innovation research to help them design and conduct new studies to advance the field.

The perspectives of organizational competition and performance and organizational adaptation and progression are introduced to serve as platforms to position organizational innovation in the midst of innovation concepts, elaborate differences between innovating and innovativeness, and decipher key typologies, primary sets of antecedents, and performance consequences of generating and adopting innovations. The antecedents of organizational innovation are organized into three dimensions of environmental (external, contextual), organizational (structure, culture), and managerial (leadership, human capital). A five-step heuristic based on innovation type and process is proposed to ease understanding of the existing studies and select suitable dimensions and factors for conducting new studies. The rationale for the innovation–performance relationship in strands of organizational innovation research, and the employment of types of innovation and performance indicators, is articulated by first-mover advantage and performance gap theory, in conjunction with the perspectives of competition and performance and of adaptation and progression. Differences between effects of technological and nontechnological innovation and stand-alone and synchronous innovations are discussed to articulate how and to what extent patterns of the introduction of different types of innovation could contribute to organizational performance or effectiveness. In conclusion, ideas are proposed to demystify organizational innovation to allure new researches, facilitate their learning, and provide opportunities for the development of new studies to advance the state of knowledge on organizational innovation.

• innovation and organization
• and innovation
• process of innovation
• typologies of innovation
• antecedents of innovation
• innovation and firm performance
• technological innovation
• managerial innovation

Introduction

Research on innovation spans many fields of inquiry including science and engineering, humanities and art, and social sciences. In academia, innovation has been probed at different levels of analysis: individual, group, organization, industry, economy. The term organizational innovation refers to the studies of innovation in organizations, including both business and public organizations. Organizational innovation research examines what external and internal conditions induce innovation, how organizations manage innovation process, and in what ways innovation changes organizational conduct and outcome.

Innovation in organizations is conceived both as process and outcome. Research on innovation as outcome aims to identify the contextual, organizational, and managerial conditions under which organizations innovate. Research on innovation as process aims to identify how organizations create, develop, adopt, implement, and use innovation. Outcome and process research are denoted as studies of innovativeness and innovating , respectively. The studies of innovativeness are primarily large-sample studies of multiple innovations in organizations. The studies of innovating are mainly case studies of one or few innovations in organizations.

The term organizational innovation is simple and easily understandable, but research on organizational innovation is complex—multilevel, multidimensional, and context-dependent. First, innovation overlaps with several other concepts—creativity, invention, imitation, organizational and technological change—and is often used as an umbrella concept covering all. Conceptual diversity and indiscriminate use confounds the antecedents and outcomes of organizational innovation. Second, organizations can both generate (create) and adopt (use) innovations. Generation and adoption are distinct processes that occur typically at different parts or units of organizations. They are not necessarily induced in similar environmental contexts or organizational conditions, and are not necessarily affected by the same sets of antecedents. Third, organizations generate and adopt different types of innovation—product, process, technological, and managerial, major or minor. Many authors do not distinguish between innovation types, and use the term innovation while studying only one type (especially technological and product). The role and importance of innovation types differ along the value chain (Porter, 1985 ), suggesting that the contextual and organizational conditions that could motivate their adoption are not similar. Fourth, myriad theoretical perspectives and approaches (rational, institutional, political, cultural, learning, interpretive, interactional), each constrained by its disciplinary discourse and methodological disposition, are applied to ground studies of organizational innovations (Crossan & Apaydin, 2010 ; Damanpour & Gopalakrishnan, 1998 ; Sturdy, 2004 ; Van de Ven & Rogers, 1988 ). They offer competing explanations of motivation for and consequences of the generation and adoption of innovation in organizations.

However, despite the complexity of the construct and diversity of research on it, the term innovation is applied broadly and the research findings are interpreted generally. Lack of due attention to the differences emanating from disciplinary approaches, levels of analysis, generation or adoption, innovation types, and external and internal contexts challenge a common understanding of organizational innovation. Accordingly, basic questions of importance to practice such as “what are the characteristics of innovative organizations” and “how do innovations affect organizational conduct or outcome” remain unanswered. The goal of this article is to carve out the key facets and dimensions of organizational innovation, coalesce its elements, and combine insights from existing research to inform and help guide future research on its dimensions, antecedents, and outcomes. While the article draws insights from innovation research in economics, psychology, and sociology, its primary disciplinary focus is organization studies, and in particular management of innovation in organizations. 1

The rest of this article is organized as follows. First, two general perspectives for studying innovations in organizations are offered. The definition of innovation and its distinction from the related concepts are presented next. This is followed with an overview of generation, adoption, and typologies of innovation in organizations, and of their salient antecedents. Finally, consequences of innovation for organizational conduct and outcome, and ideas for future research on organizational innovation are discussed.

Perspectives of Organizational Innovation

Academic research on innovation in social sciences has markedly increased since the 1950s (Crossan & Apaydin, 2010 ; Fagerberg, 2005 ). Innovation, however, is a much older term and its meaning, understanding, and terminology have changed over time. Godin ( 2015a ) chronicles emergence, evolvement, conceptualization, and application of innovation leading to its contemporary understanding. Innovation has a positive connotation and is viewed as a practical construct with beneficial outcome for its generators and adopters. Organizations generate and adopt different types of innovations that are deemed to be of value to meeting their short-term and long-terms goals and making their operation efficient and effective. Accordingly, the domain of research on organizational innovation encompasses organizational activities and mechanisms for the creation (generation) and application (adoption) of new technological or nontechnological ideas and practices across their value chain.

Two primary perspectives of innovations in organizations were introduced in the 20th century . The first perspective focused mainly on the generation of new commercialized, technology-based products and processes (Damanpour & Wischnevsky, 2006 ; Fagerberg, Mowery, & Nelson, 2005 ; Godin, 2008 ). Organizations innovate to improve efficiency and productivity, increase market share and profitability and to generate economic wealth for their owners. The second perspective was introduced in sociology and flourished in organization management in the second half of the 20th century alongside the advent of organizations as open systems. Organizations introduce innovations to adapt to environmental change and achieve strategic intents for maintaining and improving performance (Hage & Aiken, 1970 ; Becker & Whisler, 1967 ; Mohr, 1969 ; Zaltman, Duncan, & Holbek, 1973 ). Whereas both perspectives consider organization as a vehicle for innovation, from the first perspective innovation is mainly to increase productivity and serve product, service, and performance outcomes, and from the second perspective innovation is mainly a means of organizational change and improvement to stay in business and thrive. The two perspectives are viewed here as conjoining, not competing, and are termed as “competition and performance” and “adaptation and progression” perspectives of organizational innovation.

Organization Competition and Performance

This perspective is rooted in Schumpeter’s work and focuses mainly on the development and launch of new products and technological processes by organizations, where the newness is gauged at the level of product class or market. Schumpeter ( 1934 , 1983 ) defined innovation (new combination) as a novel output and distinguished among five types of innovation: new products (new goods and new quality of goods), new methods of production, new markets, new sources of supply, and new ways to organize business (Fagerberg, 2005 ; Schumpeter, 1983 ). 2 These typologies were introduced in the context of economic development and technological change, where innovation concerns radical, discontinuous change due to the occurrence of productive revolutions driven by new firms through technology push (Damanpour & Wischnevsky, 2006 ; Schumpeter, 1983 ). This work is known as Schumpeter’s entrepreneurial model of innovation (or Mark I), which champions entrepreneurial start-ups and their contributions to economic growth (Barras, 1986 ; Fagerberg, 2005 ). Innovation is the essence of new, independent companies creating new industries or acting as major agents of change in established industries (Barras, 1990 ; Sanidas, 2005 ).

In his later work, Schumpeter also noted the role of incumbents—established firms—as a source of innovation for economic development (Barras, 1986 ; Fagerberg, 2005 ; Schumpeter, 1950 ). This work is referred to as Schumpeter’s corporate model of innovation (or Mark II), where established firms are the vehicles for innovation because they possess scientific knowledge and management expertise, production means and other complementary assets, better access to capital, and often some degree of monopoly power, which increase the likelihood of investing in innovation (Barras, 1990 ; Damanpour & Wischnevsky, 2006 ; Sanidas, 2005 ). According to this view, established organizations (like start-ups) drive efficiency and effectiveness through innovation and create economic wealth for owners/investors, and eventually the society at large.

Schumpeter’s innovation models have mostly been applied to the generation of new technology-based products and processes. When entrepreneurial opportunities—situations in which new businesses, products, processes, and services can be introduced (Shane & Venkataraman, 2000 )—exist, individuals and organizations alike engage in innovation (Damanpour & Wischnevsky, 2006 ). Entrepreneurs (members of a large and dynamic population of innovators) pursue these opportunities by starting new organizations; incumbents (members of a small and stable population of innovators) pursue them by forming new businesses, alliances, and joint ventures. The primary motivation for seizing new opportunities for both individuals and organizations is to increase productivity and profitability and to create economic wealth and growth (Drucker, 1985 ).

In organization management, the competition and performance perspective of innovation is prominent in business policy and strategy, global (international) business, and technological and strategic entrepreneurship (Grant, 1996 ; Teece, Pisano, & Shuen, 1997 ; Hitt, Ireland, Camp, & Sexton, 2001 ; Lengnick-Hall, 1992 ). 3 However, the focus of this perspective on innovation as technological advancement in the industrial (commercial) entities restricts its application to other types of innovation and broader types of organizations. Hence, it alone is not sufficient to fully comprehend organizational innovation.

Organization Adaptation and Progression

Organizations in all sectors, whether commercial or noncommercial, private or public, innovate to operate efficiently and perform effectively. Organizations introduce all types of innovations, whether technological or nontechnological, product or process, radical or incremental. Innovation is not only to gain competitive advantage over rivals, it is also a means of organizational adaptation and progression. Sustained performance or effectiveness can be gained not only by generating innovation (new to market or industry) but also by adopting innovation (new to the adopting organization). While organizations can develop competencies to generate one or few types of innovation, they can adopt all kinds of innovations along their value chain (Baldridge & Burnham, 1975 ; Hage & Aiken, 1970 ; Ross, 1974 ).

The adaptation and progression perspective assumes that organizations innovate to respond to environmental change, renew business portfolios, and serve their customers or clients effectively in order to achieve strategic positions and boost long-term performance (Damanpour & Gopalakrishnan, 1998 ; Roberts & Amit, 2003 ). It gained currency in the second half of the 20th century after the importation of system theory to organization studies (Ackoff & Emery, 1972 ; Churchman, 1968 ; von Bertalanfy, 1951 , 1968 ), advancement of behavioral theory of the firm and contingency theory (Burns & Stalker, 1961 ; Cyert & March, 1963 ; Lawrence & Lorsch, 1967 ), and the advent of the long-term planning and business strategy (Ackoff, 1970 ; Ansoff, 1968 ; Schendel, Ansoff, & Channon, 1980 ). Organization is defined as an open system that is composed of interdependent parts (subsystems) and is embedded in an environment with which it exchanges and interacts (Ackoff, 1981 ; Emery & Trist, 1960 ; Scott, 1992 ). The environment is also a system, albeit larger and more complex than the organization, with its own subsystems and environment. It is usually divided into two levels: general (macro) environment, and transactional (micro, operating, competitive) environment (Daft, 2001 ; Mintzberg, 1979 ). Changes in either environment prompt organizational actions to maintain external fit (balance with environmental components) and internal fit (harmony among internal subsystems). Effectiveness of the organization requires carrying out the systemic processes of maintaining, adapting, and progressing (Evan, 1976 ). Organizations can adapt to environmental changes, shifts, or jolts via developmental, transitional, or transformational change (Burke, 2002 ; Jick, 1993 ). They may even choose to preempt changes in their competitive environment by investing in the state-of-the-art technologies, processes, and services to gain competitive advantage. Independent of the type and extent of change, innovation is viewed as a means of coping with and influencing the environment.

The adaptation and progression perspective offers that organizations are motivated to innovate because of (1) pressures from the external environment due to competition, deregulation, isomorphism, resource scarcity, and customer demands, and (2) internal organizational choices for gaining distinctive competencies, reaching a higher level of aspiration, and increasing the extent and quality of their products and services. Innovations are instruments of organizational change for effective performance. The adaptation and progression perspective partially overlaps with a few other theoretical perspectives of innovation in organizations. 4 However, it provides a unique platform to coalesce insights from several strands of organization and innovation management literatures to explain innovation as a process and an outcome in organizations.

Conceptions of Innovation in Organizations

Godin ( 2008 ) reviewed the history of innovation as a category and identified over ten concepts (discovery, invention, imitation, technology, creativity, change, etc.) that have been used to portray innovation over time. Among them, I have selected three that are closely associated with or taken for organizational innovation: technological innovation, organizational creativity, and organizational change.

I discuss the peripheries of innovation with technology, creativity, and change and offer a pathway to help determine how innovation can be distinguished from the overlapping concepts. I rely on the notion of low- and high-order concepts, which is derived from the classification of systems into levels (Boulding, 1956 ), where the complexity of the system increases from a lower-level system to a higher-level system. A high-order concept embodies a low-order concept similar to a system (organization) including its subsystems (units or parts). The low–high order portrays the hierarchy of goals of systems, the means–end relationship where the actions of a lower-order system affect the behavior of a higher-order system (like the effect of a part on the whole).

Innovation and Technology

Public perception of innovation equates innovation with new technology or technical invention, and understands innovation in organizations as technological innovation. Innovation researchers have exacerbated this misunderstanding by using the term innovation to portray technology-based product and process innovations. 5 While the importance of technology and technological innovation for organization adaptation, competition, and performance is undeniable, taking technological innovation for innovation in general is simply wrong. The concept of innovation is broader than technical invention, and technological innovation is only one type of innovation that organizations generate or adopt. 6

Tushman and Anderson ( 1986 , p. 440) define technology as tools, devices, and knowledge that create new products or services (product technology) and mediate between inputs and outputs (process technology). Technology affects organizational efficiency, facilitates the conversion of inputs into outputs, and reduces inefficiencies in the development, production, and delivery of products and services. The product and process technologies represent physical technologies. New physical technologies may drive the introduction of technology-based product or process innovations. In this vein, technology (technical invention) is a lower-order concept than technological innovation. Similarly, technological innovation can be viewed as a lower-order concept than technological change.

The definition of technological change in business and management is diverse. For instance, technological change reflects significant advances in technological performance within a technological regime (Lawless & Anderson, 1996 ); changes within uniform and differentiated technological systems leading to technological development of industries (Barnett, 1990 ); and technological breakthroughs or discontinuities leading to a dominant design (Wade, 1996 ). Godin’s ( 2015b ) study of the conceptual history of technological change offered two general meanings for it: (1) a narrower meaning—change in the methods and techniques of production; and (2) a broader meaning—change in the society due to technology. I adopt the broader meaning and posit that technological change occurs due to cumulative effects of multiple technologies and technological innovations over time. In this vein, technological change is a concept suitable to the level of product class, industry, and economy, not the organization. At the macro level, technological change can impact development of new industries, economic growth, level of employment, and societal prosperity (Ahlstrom, 2010 ; Edquist, Hommen, & McKelvey, 2001 ; Nelson & Winter, 1982 ).

In summary, I view technology as a lower-order concept than technological innovation, itself one among several types of innovations organizations generate or adopt. Technological change is a higher concept than organizational innovation, is the outcome of a series of innovations in contexts such as industry, product class, region, and economy, and is not discussed in this article.

Innovation and Creativity

Creativity is a concept that is imported to organization management from psychology, where it has been studied primarily at the individual level. Ford ( 1996 ) compared creativity with conformity and proposed a theory of creative individual actions as opposed to habitual individual actions. He defined creativity as the outcome of a particular individual action that is judged novel and valuable (Ford, 1996 ). Amabile ( 1988 ) states that innovation is “creativity plus implementation.” She distinguishes creativity from innovation by relating creativity to the production of novel and useful ideas by individuals and small groups and innovation to the successful implementation of those ideas (Amabile, 1988 ). This view suggests that creativity is a subprocess of innovation process, associates creativity more closely to the generation than the adoption of innovation, and has prevailed among the studies of creativity in organizations (Anderson, Potočnik, & Zhou, 2014 ; Baer, 2012 ; Woodman, Sawyer, & Griffin, 1993 ).

Research on technological innovation has related creativity to technical invention. For instance, in the 25th anniversary publication of R&D Management , Roberts ( 1988 ) characterizes innovation as “invention plus exploitation,” where invention is linked with the creative work of scientists and technologists. OECD’s definition of R&D also links it with technical invention, associating the connotation of creativity to innovation through invention (Godin, 2014 ). The oversized role of R&D on innovation prompted organizational psychologists to study scientists and engineers in R&D functions of organizations (Andrews & Farris, 1967 ; Pelz & Andrews, 1966 ; Pelz, 1956 ). Studies of creativity at work and in organizations gained currency (West & Farr, 1990 ; King, 1990 ; Scott & Bruce, 1994 ), eventually adding the term organizational creativity to innovation vocabulary in business and management. For instance, Woodman et al. ( 1993 ) define organizational creativity as the creation of useful and valuable new ideas, products, services, and processes by individuals working together in an organization, and conceive organizational creativity as a subset of the broader concept of organizational innovation. According to these authors, the difference between organizational creativity and organizational innovation is that the former includes creating new ideas and practices, but the latter can also include the adaptation of preexisting ideas and practices (Woodman et al., 1993 ). This distinction associates newness to creativity, but not to innovation. 7

However, novelty or newness is a commonly accepted component of the definition of innovation across disciplinary fields. Moreover, organizational creativity cannot be distinguished from organizational innovation by stressing the importance of cooperative actions of individuals, because organizational members’ interactions are intrinsic to nearly all organizational activities. By definition organizations are social systems, and their activities depend on human actions. The creative behavior of individuals and small groups is necessary for every organizational action, including innovation.

Overall, in the context of organizations, I posit that creativity is a subset or a subprocess of innovation. Creative ideas, behaviors, and outcomes of individuals and small groups can help solve problems that arise throughout the innovation process. That is, they influence both the generation and adoption of innovations in organizations.

Innovation and Change

Change is a shift or transfer from one state (prior to change) to another state (after the change) (Nadler & Tushman, 1997 ). It is an observation of differences in time in any dimension of organization (Van de Ven & Rogers, 1988 ). Organizational change is the introduction of activities that are different from those currently in use (Burke, 2002 ; Daft & Becker, 1978 ; Wischnevsky, Damanpour, & Mendez, 2011 ). It occurs when organizations evolve from old behaviors and methods of operation to new ones. Thus, by definition change and innovation are distinguished primarily by the newness or novelty of the idea or actions to the focal organization.

Newness is a term relative to the unit of adoption (Rogers, 1995 ), and its notion varies in different streams of innovation research (Gopalakrishnan & Damanpour, 1997 ; Crossan & Apaydin, 2010 ). Traditionally, in innovation diffusion research, newness is perceived in relation to the individual adopter (Rogers, 1995 ); in technology and strategic management, it is newness to a product class or an industry (Roberts, 1988 ; Tornatzky & Fleischer, 1990 ); and in innovation management, it is newness to an organizational unit (plant, business, division, department) or the entire organization (Kimberly & Evanisko, 1981 ; Ettlie, 1988 ). In most empirical studies, what constitutes newness is left as an empirical question, an issue for managers (respondents to surveys) or a panel of experts (academics and experts) to resolve. Thus, newness is determined subjectively through judgment of adopters or professional elites, exacerbating the distinction between innovation and change.

The processes of innovation and change are considerably similar. Organizations adopt both innovation and change, and each can be grouped as major or minor. The difference between the two concepts would need to be established conceptually. I thus view innovation as a subset or a subprocess of organizational change, mirroring the distinction that was made between creativity and innovation.

Innovation in Organizations

Technology, creativity, and change intersect with innovation but are different concepts. In the context of organizations, creativity is a lower-order concept to innovation and innovation is a lower-order concept to organizational change. Innovation is a means to organizational change, although change can occur without innovation. Whereas the intersection of innovation and creativity associates more closely with the generation of innovation, the intersection of innovation and organizational change associates more closely with the adoption of innovation (details below). 8 Technology is an element or component of innovation: Some innovations are technology-based; others are not. Technological innovation is only a type of organizational innovation and should not be mistaken for it.

The locus of innovation and its related concepts in organizations differs. Creativity is a concept associated with individuals and small teams, innovation and change with units and organizations, and technological change with product class and industry. Loose application of these concepts and indiscriminate interpretation of research findings of one to the others causes confusion and could impede an understanding of innovating and innovativeness in organizations.

Innovation in organizations is a systematic (focused, purposeful, and organized) activity (Drucker, 1985 ). The creative ideas and actions of individuals and small groups, as well as the organizational capabilities to manage the innovation process, influence organizational innovations. Moreover, both physical (hard, tangible) and social (soft, intangible) technologies can advance organizational capacity for innovations (Tether & Tajar, 2008 ). In terms of the means-end relationship, therefore:

Technology (physical) ➔ technological innovation ➔ technological change 9 Creativity (individual and group) ➔ organizational innovation ➔ organizational change

The Process of Generation and Adoption of Innovation

The innovation process is usually conceptualized as a sequential process, including recognition of problem/opportunity, development, production, commercialization, adoption, and implementation (Rogers, 1995 ; Angle & Van de Ven, 1989 ). 10 The wide-scope view of the process of innovation in organizations assumes that innovation is developed and implemented in the same organization. But innovations can be developed and commercialized by one organization, and adopted and used by others (Damanpour & Wischnevsky, 2006 ). In this vein, Tornatzky and Fleischer ( 1990 ) grouped the innovation process into two processes of “developing” and “using.” Klein and Sorra ( 1996 ) also distinguished between “source-based” and “user-based” process, where innovation in the former is a new product or practice an organization (or a unit of it) produces, and in the latter it is the first-time adoption of a product or practice by an organization (or a unit of it). 11

Most studies of innovation in organizations do not discern between generation and adoption, and refer to both as innovation process. However, generation and adoption are distinct processes, with different phases and characteristics (Damanpour & Gopalakrishnan, 1998 ). 12 Generation is a process that results in the introduction of a new product, service, process, or practice to the market. It covers all organizational activities related to creating new ideas, getting them to work, and supplying them to the market for use by individuals and/or organizations (Roberts, 1988 ). The generation process includes recognition of opportunity, research, design, piloting and testing, commercial development, production, marketing, and distribution (Tornatzky & Fleischer, 1990 ; Roberts, 1988 ). Adoption is the process of choosing and using a product, service, process, or practice that is new to the adopting organization. Adoption basically means that the innovation is developed elsewhere, not in the adopting organization (Angle & Van de Ven, 1989 ). The adoption process includes problem perception, searching for solutions, evaluating and selecting one solution, initial implementation, sustained implementation, and eventually termination (Angle & Van de Ven, 1989 ; Hage & Aiken, 1970 ; Tornatzky & Fleischer, 1990 ). While in generation new and existing ideas are combined in a novel way to produce a configuration that was previously unknown, in adoption ideas new to the adopting organization are identified, acquired, and adapted to fulfill recognized needs or solve existing problems (Damanpour & Wischnevsky, 2006 ). The adoption is complete when organizational members or clients use the innovation regularly.

Research on the generation process has typically focused on the generation of technological innovations. For instance, in Roberts’ ( 1988 ) characterization of innovation (invention plus exploitation), invention is marked by a new discovery (usually at the laboratory) and exploitation consists of the commercial development and conversion of that discovery into a useful application. Prominent in business policy, technology management, and economics, this view assumes that innovations are driven by technical invention (Godin, 2008 ). However, as Brozen ( 1951 ) points out, even the generation of technological innovation (change in the productive methods of technological possibilities) need not be the result of technical invention (change in technological possibilities). Moreover, organizational innovation includes nontechnological innovation, whose generation has not been scrutinized in organization studies. A notable exception is Birkinshaw, Hamel, and Mol’s ( 2008 ) four-stage process framework (motivation, invention, implementation, theorization, and labeling) for the generation of management innovations.

The generation of innovation requires more in-depth specialized knowledge than adoption. Thus, organizations can obtain expertise in generating a certain type of innovation. However, they can adopt a greater variety of innovation types, making innovation adoption a more commonly researched subject in innovation management. The adoption process has been grouped into two general stages of initiation and implementation, which are separated by the adoption decision (Rogers, 1995 ; Zaltman et al., 1973 ). 13 Initiation consists of activities that pertain to recognizing a need, searching for solutions, becoming aware of existing innovations, identifying suitable innovations, and proposing a few for adoption (Duncan, 1976 ; Rogers, 1995 ). In this phase organizations learn of the innovation’s existence, evaluate its suitability, solicit advice from internal and external constituents, and make the adoption decision (Birkinshaw et al., 2008 ; Meyer & Goes, 1988 ). Implementation consists of activities that pertain to modifying the innovation, preparing the organization for its use, trial use, acceptance of the innovation by the users, and continued use until the innovation’s use is routinized (Duncan, 1976 ; Rogers, 1995 ).

In summary, organizations can both generate and adopt innovations. In generation, the newness of innovation relates to an organizational population; in adoption, it relates to an organization. The process of generation and adoption are not alike. The generation process can be characterized more like a creative process, the adoption process more like a problem-solving process. The generation process is relatively disorderly, more like a random process of chance or chaotic events; the adoption process is relatively orderly, more like a periodic and sequential progression of phases (Cheng & Van de Ven, 1996 ; Damanpour & Wischnevsky, 2006 ). The generation process is usually slower and takes longer to complete than the adoption process. Since the stages and the characteristics of generation and adoption differ, the distinction between them is necessary to understand how organizations can innovate and what factors motivate innovating.

Typologies of Organizational Innovation

The primary approach for reducing the complexity of innovation to study its antecedents and consequences has been to develop typologies. For instance, Schumpeter ( 1934 ) grouped innovation into five types, and Zaltman et al. ( 1973 ) listed approximately 20 types. Since then, more innovation types have been introduced, including architectural, business model, exploratory, exploitative, open, green, and so on. Among the typologies of innovation, three have been most widely studied: product–process, technical (technological)-managerial (administrative), and radical–incremental (Damanpour & Aravind, 2012b ). Meeus and Edquist ( 2006 ) offered a taxonomy by juxtaposing the first two typologies. These authors distinguished between two types of product innovations—product (innovation in goods) and service (innovation in services)—and two types of process innovations—technological process (technical) and organizational (managerial). 14 Meeus and Edquist’s taxonomy does not account for the openness of innovation. Tether and Tajar’s ( 2008 ) model of firm-based innovation does. Tether and Tajar’s model is based on three dimensions of change—changes to what the firm produces (product) versus changes to how the firm operates (process), changes to physical technologies (technical) versus changes to social technologies (administrative), and the locus of change, intrafirm (organic) versus interfirm (open).

I organize the discussion of innovation types into four pairs: product–process, technical–managerial, radical–incremental, and organic–open. The resulting eight types of innovation provide a general framework for studying the majority of innovations organizations generate and adopt.

Product and Process Innovation

Product and process innovations are the most commonly studied innovation types. Academic research on this typology has generally focused on industrial innovations, specifically on R&D-based innovations (Damanpour, 2010 ; Tether & Tajar, 2008 ). This orientation has resulted in the understanding of product and process innovations as two types of technological innovations.

Product innovation is defined as the introduction of a new product or service to meet an external user need, and process innovation as the introduction of new elements in a firm’s production or service operation in order to produce a product or render a service (Damanpour, 2010 ; Schilling, 2013 ; Utterback, 1994 ). Product innovations have an external focus and are primarily market-driven; process innovations have an internal focus and are mainly techniques of producing and marketing goods or services. The drivers of product innovations are customer need and demand, and firms’ aspiration to compete and grow. The drivers of process innovations are reduction in delivery time, increase in operational flexibility, and lowering of production costs. Hence, while product innovations are embodied in the outputs of an organization and may result in product differentiation and market expansion, process innovations are oriented toward the efficiency or effectiveness of production and may decrease production costs or increase product quality (Damanpour, 2010 ; Schilling, 2013 ; Utterback, 1994 ).

Henderson and Clark ( 1990 ) expanded the product–process typology based on two dimensions of “core concept” and “linkage between core concepts and components,” and introduced architectural innovation in contrast to component innovation. Component innovation entails changes to one or more components of a product system without significantly changing the overall design. Architectural innovation entails changing the overall design of the system or the way components interact (Henderson & Clark, 1990 ; Schilling, 2013 ). Architectural innovations may require changes in the underlying components. In introducing architectural innovations, Henderson and Clark ( 1990 , p. 12) portray their conceptual model as “a framework for defining innovation.” However, architectural innovation is merely a subset or a subtype of technological product innovation and has rarely been applied to other types of innovation organizations generate or adopt.

Most studies of innovation in organizations do not distinguish service innovations from product innovations. Generally, services offered by organizations in the service sector are conceptualized to be similar to products introduced by organizations in the manufacturing sector (Damanpour & Aravind, 2012b ; Miles, 2005 ; Meeus & Edquist, 2006 ). In this vein, like product innovations, the drivers of service innovations are clients’ demand for new services and executives’ desire to create new services for existing markets or to find new market niches for existing services (Miles, 2005 ). However, service innovations are not necessarily technology-based (Tether & Tajar, 2008 ), and firms in both goods and service industries can introduce them. Accordingly, service innovation is defined as the introduction of a new service to increase the effectiveness and quality of the organization’s output, whether a product or a service, to the customers or clients (Damanpour & Aravind, 2012b ).

Technical and Managerial Innovation

The technical–managerial typology was introduced in organization management in contrast to the product–process typology that dominated the studies of innovation in economics and technology management. The distinction between technical (technological) and managerial (administrative) innovations relates to a more general distinction between technology and social structure (Evan, 1966 ). Technical and managerial innovations are respectively associated with the organizations’ technical and social systems (Damanpour & Evan, 1984 ) and technical and administrative cores (Daft, 1978 ). Evan ( 1966 , p. 51) defined technical and administrative innovations as ideas for new product, process, and service, and ideas for new personnel policy, reward system, resource allocation, and structuring, respectively. Technical innovations are directly related to the primary work activity of the organization and produce changes mainly in its operating systems. Administrative innovations are indirectly related to the organization’s primary work activity and affect mainly its management systems (Daft, 1978 ; Damanpour & Evan, 1984 ; Kimberly, 1981 ). Recently, the term management innovation has replaced the term administrative innovation. Management innovations are departures from management principles, processes, and practices that alter the way the work of management is performed, change how managers do what they do, and constitute the rules and routines by which work gets done inside organizations (Birkinshaw et al., 2008 ; Hamel, 2006 ). They reflect approaches to devising strategy, structure, and processes that are new to the organization (Kimberly, 1981 ; Vaccaro, Jansen, Van Den Bosch, & Volberda, 2012 ; Walker et al., 2011 ). 15

While this new term has renewed interest in research on managerial innovation, the state of knowledge on this innovation type is in its infancy. The domain of managerial innovation is wide; the concept is complex, ambiguous, and difficult to measure; and rival theoretical arguments on motivation for its generation, adoption, and performance consequences exist (Birkinshaw et al., 2008 ; Damanpour & Aravind, 2012a ; Sturdy, 2004 ). A variety of terms have been used to describe managerial innovations. In a literature review, Černe, Kaše, & Škerlavaj ( 2016 ) identified ten nontechnological innovations, the majority of which represent managerial innovation. The definitions and characteristics of the terms for managerial innovations show that they overlap markedly (Černe et al., 2016 , pp. 71, 79). Černe et al. ( 2016 ) also conducted a cocitation analysis of nontechnological innovations and found considerable similarity in their intellectual structure. Multiplicity of terminology, combined with lack of established typologies and measurements of managerial innovations, has constrained the advancement of this important type of innovation (Armbruster, Bikfalvi, Kinkel, & Lay, 2008 ; Damanpour, 2014 ). For technological innovations, for instance, product and process innovations have been commonly accepted as subtypes, indicators for their measurement are established (patents, R&D expenditure, scientific publications, etc.), and historical data sets for their measurement exist. For the development of data sets of managerial innovations at par with those for technological product and process innovations, commonly accepted terminology, typology, and measurement indicators should be selected and followed.

Radical and Incremental Innovation

The radical–incremental typology is primarily applied to technological product and process innovations at both industry/product class and organizational level. At the level of industry, technology can be disruptive or sustaining depending on whether it is based on entirely new knowledge and obsoletes the existing products and processes or it improves the performance of products and processes along the existing dimensions of performance (Christensen, 1997 ). Innovation can be competence-destroying , when it departs from the organization’s existing competencies, or competence-enhancing , when it builds on and improves existing competencies (Tushman & Anderson, 1986 ). At the organizational level, radical and incremental innovations are distinguished by the extent to which they change internal activities or outputs of the organization. As such, radical innovations are those that cause fundamental changes in organizational activities and result in a clear departure from existing products, processes, and practices, and incremental innovations are those that result in minor changes in the existing activities, products, processes, and practices (Damanpour, 1991 ; Dewar & Dutton, 1986 ; Ettlie, Bridges, & O’Keefe, 1984 ).

More recently, the radical–incremental typology has been augmented by the exploratory–exploitative typology. The new typology is based on the exploration-exploitation in organizational learning (March, 1991 ). Exploration refers to the application of learning to produce new products and technologies, and exploitation refers to the application of learning to refine the organization’s existing products and improve its processes (March, 1991 ). The essence of exploration is experimentation with new ideas; it is associated with divergent thinking and flexibility. The essence of exploitation is the refinement of existing ideas; it is associated with convergent thinking and focus (March, 1991 ). Exploratory and exploitative innovations reflect the results of exploration and exploitation for an organization’s innovative actions (Bierly, Damanpour, & Santoro, 2009 ; Jansen, Van Den Bosch, & Volberda, 2006 ).

Whereas the radical–incremental and the exploration–exploitation typologies have been applied mainly to technological innovations, they are also applicable to other innovation types. Both typologies are based on innovation radicalness , an attribute of innovation defined as (1) the extent to which the innovation departs from existing knowledge, or (2) the degree of change the innovation creates in organizational conduct or outcome (Damanpour & Wischnevsky, 2006 ). At the organization level, change can be a result of the introduction of technological or nontechnological innovations and the nature of knowledge can be technological or nontechnological. The dimension of radicalness can also assist in separating generation (more radical) from adoption (more incremental), and innovation (more radical) from change (more incremental). In particular, the application of radicalness to nontechnological innovation will be helpful in screening its subtypes and identifying a few at par with product and process innovations (subtypes of technological innovation) to further theory and measurement of nontechnological innovations.

Organic and Open Innovation

Organic innovation refers to in-house development of a new product, process, or service, when the focal organization invents, develops, and commercializes the innovation. Chesbrough ( 2003 ) called a company’s full control of the innovation process “closed innovation,” and introduced open innovation , an approach where the tight control is relaxed and the company brings in partners through various means of interorganizational cooperation (strategic alliances, joint ventures, consortia) in one or more aspect of the generation of innovation (Chesbrough, 2003 ). The flexibility in developing and commercializing internal and external ideas in cooperation with other firms expedites the generation of new products and processes for the current market and facilitates entering new markets (Chesbrough, 2003 ). Open innovation is an important concept that has captured a timely management practice that has been induced by the demise of large in-house R&D organizations (Economist, 2007 ), globalization of business operations and services, and the advance in information technology.

The concept of open innovation has been embraced in strategy and technology management. While early writings focused mainly on the ideation aspect of innovation generation (e.g., emphasis on crowdsourcing as a key means of open innovation), research on open innovation has been expanded to include the development, utilization, and retention of knowledge inside and outside of an organization’s boundary throughout the innovation generation process (Chesbrough & Appleyard, 2007 ; Lichtenthaler, 2011 ). Theoretically, open innovation has followed the concept of absorptive capacity, which highlighted the importance of external sources of knowledge for the generation of technological innovations (Cohen & Levinthal, 1990 ). Strategy scholars have probed the impact of the breadth and depth of external sources for innovation and its performance outcomes (Laursen & Salter, 2006 ; Leiponen & Helfat, 2010 ). This research has focused mainly on the generation of technological innovations along the perspective of organization competition and performance.

To enrich open innovation’s theoretical domain and integrate it with the extant literature on organizational innovation, the concept should be augmented to enable its application along the perspective of organization adaptation and progression. That is, the application of the concept should include the generation of nontechnological innovation, as well as the adoption of innovations. For instance, Birkinshaw et al. ( 2008 ) developed a conceptual model for the generation of management innovations and discussed the dual role of internal and external sources of information. Mol and Birkinshaw ( 2014 ) examined the forms of external involvement on the generation of management innovation. Damanpour, Sanchez, and Chiu ( 2017 ) discussed the dual role of internal and external knowledge sources on the adoption of management innovations. These studies suggest that there is room to extend and expand open innovation to generation and adoption of all types of innovations, in goods and services, and in business and public organizations.

Whereas comparative studies of antecedents and consequences of product and process, technical and managerial, and radical and incremental innovations have been conducted, research on motivators and outcomes of organic versus open innovations are scarce. Large-sample comparative studies of this pair of innovation type are needed to develop a stronger theoretical foundation for the role of innovation openness on organizational conduct and outcome. From an adaptation and progression perspective, organizations as social systems are inherently open systems. The openness property of an organization is crucial to innovation activities because innovation in essence cannot occur in isolation inside a firm’s boundary. Some form of interdependencies with suppliers, customers, research institutions, and even competitors are needed because individual companies are unable to keep up with the pace of the development of technical and managerial knowledge, even in modestly complex and dynamic environments. In general, the more complex the physical or social technologies that constitute the innovation and the more dynamic the external environment of the organization, the more porous the organization–environment boundary and the greater the need for sourcing knowledge through different means of organization–environment relations. 16 Future research should ground innovation openness in the behavioral theories of organization in order to clarify the dynamic of internal and external sources, and develop mechanisms for facilitating cooperation, preventing conflicts, and managing the diversity of knowledge sources (Damanpour et al., 2017 ).

Antecedents of Organizational Innovation

Business and public managers are keen to understand conditions under which their organization can successfully innovate. Consequently, studies of the antecedents of organizational innovation constitute the largest body of this research. These studies have focused more on innovativeness than innovating, and on innovation adoption than generation. The majority have also examined organizational innovation as a single construct, although a considerable minority have distinguished between factors that predict pairs of innovation types. While innovation is recognized as a multilevel and multidimensional construct (Baldridge & Burnham, 1975 ; Damanpour & Schneider, 2006 ; Kimberly & Evanisko, 1981 ; Sears & Baba, 2011 ), most studies have examined a set of factors associated with one level (individual, group, organization) and one dimension (industry, internal structure, personal attributes).

I focus on three dimensions that embody the majority of organizational innovation antecedents: environmental (external, contextual), organizational (structure, culture), and managerial (leadership, human capital). 17 Myriad number of variables have been associated with each dimension, and qualitative and quantitative reviews to identify salient antecedents have been conducted. For parsimony, I rely mainly on the review studies to discuss factors within each dimension.

Environmental Antecedents

The review studies of environmental antecedents of innovation have identified different sets of factors. For instance, in a systematic review of publications on organizational innovation during 1981–2008 , Crossan and Apaydin ( 2010 , p. 1182) identified organization, technology, market, and innovation types as environmental antecedents. In another systematic review of publications during 1983–2003 , Damanpour and Aravind ( 2006 , p. 58) identified competition, concertation, technological opportunity, appropriability conditions, and growth of demand as contextual antecedents of innovation. The difference between the two reviews is threefold. First, Crossan and Apaydin’s review is based on articles published mainly in management journals, whereas Damanpour and Aravind’s review is based on publications mainly in economic journals. Second, Damanpour and Aravind’s review includes only technological innovations; Crossan and Apaydin’s review includes both technological and nontechnological innovations. Third, the focus of studies in Damanpour and Aravind’s review is mainly the generation of innovations; in Crossan and Apaydin’s review it is the adoption of innovations. As such, the original publications in the two reviews come from different disciplinary fields, resulting in dissimilar sets of variables as salient environmental antecedents of innovation.

Context dependency has also been shown in two recent systematic reviews that focused on innovation adoption. Černe et al. ( 2016 ) reviewed nontechnological innovations within 1975–2011 in the business context, and identified market orientation, dynamism, and competitiveness as typical antecedents. De Vries, Bekkers, and Tummers ( 2016 ) reviewed innovation in the public context during 1990–2014 and reported environmental pressures (institutional, political, public, media), participation in networks, and extent of regulation as usual environmental antecedents. In general, while typical environmental variables in public organizations are urbanization, deprivation, ethnicity, political orientation, and community affluence (Boyne, 2002 ; Damanpour & Schneider, 2009 ; Walker, 2008 ), in business organizations they are market competition, industry structure, governmental regulation, technological intensity, supplier power, and customer demand (Cohen & Levin, 1989 ; Roberts & Amit, 2003 ; Schilling, 2013 ).

The differences between environmental antecedents in these four reviews illustrate the crucial role of academic discipline, generation versus adoption, and innovation type in predicting organizational innovation. One way to partially bridge such differences toward coalescing environmental factors that affect organizational innovation is to rely on more general constructs (e.g., environmental uncertainty) and examine the influence of its components (e.g., complexity, dynamism, and diversity) on organizational innovation (Daft, 2001 ; Damanpour & Gopalakrishnan, 1998 ; Mintzberg, 1979 ; Tidd, 2001 ). Reliance on general constructs, however, could cloud the specificity of the findings.

Organizational Antecedents

Although environmental conditions and events motivate and influence organizations to engage in innovation, internal organizational conditions reflect their intent and capacity to do so. Organizations are managed entities, setting goals and priorities, and designing structure and processes to conduct their activities. Innovation is also a managed activity. It is a choice that requires financial and human resources, supportive climate and culture, and enabling structure, processes, and systems. Hence, organizational determinants of innovation have been examined more than environmental and managerial antecedents, especially in organization management.

Damanpour and Aravind ( 2012b ) conducted a systematic review of the antecedents of organizational innovation in 1990–2009 , compared their results with those reported in an earlier meta-analysis of publications in 1971–1988 , and found the findings from the two reviews are generally consistent. They identified seven salient antecedents supported in the empirical studies in both periods: professionalism, specialization, technical knowledge resources, functional differentiation, management attitude toward change, and internal and external communication (p. 502). Crossan and Apaydin’s ( 2010 ) review added organizational culture, learning, and strategy (mission, goals, resource allocation) to these structural variables (p. 1182). However, a systematic review of publications in strategic management of innovation ( 1992–2010 ) offered a different set of antecedents. Keupp, Palmie, & Gassmann ( 2012 ) grouped organizational antecedents into intended/emergent initiatives (R&D investment, technology sourcing, competitive strategy), internal organization (size, culture, structural integration), managerial/ownership issues (human resources, ownership, process management), and resources (prior performance, knowledge and capabilities, slack) (p. 374). With the exception of internal organization, the set of variables from Keupp et al.’s review corresponds closely with organizational antecedents of the generation of technological product and process innovations in Damanpour and Aravind’s ( 2006 , p. 58) review (firm size, profit, capital intensity, diversification, ownership, and technical knowledge resources). Thus, similar to environmental antecedents, organizational predictors of innovation are disciplinary-based, and are contingent on generation and adoption and innovation types. Organizational size is an exception, however.

Firm size is the most widely researched antecedent of innovation across disciplinary fields. The size–innovation association is governed by two sets of compelling arguments. On the one hand, small organizations are more innovative because they can make quicker decisions to go ahead with new and ambitious projects, and have less bureaucratic and more flexible structure, greater ability to adapt and improve, and less difficulty in accepting and implementing change (Damanpour, 2010 ; Nord & Tucker, 1987 ; Stevenson & Jarillo, 1990 ). On the other hand, large organizations are more innovative because they can risk failure and absorb the costs, have diverse professional skills allowing cross-fertilization of ideas, higher technical potential and knowledge, and better scale economies for raising capital and marketing new products and processes (Damanpour, 2010 ; Hitt, Hoskisson, & Ireland, 1990 ; Nord & Tucker, 1987 ). While empirical results from single studies remain inconsistent (Cohen & Levin, 1989 ), the findings from systematic reviews report a positive relationship between size and innovation. For instance, Damanpour ( 2010 ) found that size positively affects both product and process innovations. Similarly, in a meta-analytic review that included all types of innovation, Camisón, Lapiedra, Segarra, and Boronat ( 2004 , p. 331) found a positive association between organizational size and innovation (r=.15, p<.05). 18

Chandy and Tellis’s ( 2000 ) study on the influence of firm size on the introduction of 64 radical product innovations in consumer durables and office products from 1851 to 1998 provides historical evidence regarding the two competing arguments on the size–innovation relationship. These authors found that while 73% of radical product innovations were generated by nonincumbents before World War II, the incumbents significantly outnumbered nonincumbents (74% to 26%) for the innovations generated after the war (Chandy & Tellis, 2000 , p. 8). The results from this longitudinal analysis suggest that by the middle of the 20th century the share of innovations introduced by larger firms surpassed those introduced by smaller firms. More recent cumulative evidence on the size-innovation relationship that suggest otherwise has not been reported.

Managerial Characteristics

Top managers or strategic leaders influence innovation because they modulate the process of scanning the environment for threats and opportunities, formulate policy to respond to environmental change, control resources, and shape capabilities to enable innovation activity (Bantel & Jackson, 1989 ; Damanpour & Schneider, 2006 ; Elenkov, Judge, & Wright, 2005 ). They are also responsible for instituting values supportive of innovation, empowering middle and line managers, motivating members and improving their morale, and encouraging innovation actions and establishing rewards for them (Damanpour & Schneider, 2006 ; Hoffman & Hegarty, 1993 ; West & Anderson, 1996 ).

Prior research has explored three sets of managerial characteristics on innovations in organizations: demographic (age, gender, education, experience), personality (agreeableness, authoritarianism, openness to experience), and behavioral (inspirational motivation, championing innovation, contingent rewards). Studies in business and public management have generally identified transformational leadership, change-oriented behavior, favorable attitude and disposition toward change, and skills and ability to create a climate supportive of innovation as key managerial characteristics (Crossan & Apaydin, 2010 ; de Vries et al., 2016 ; Ekvall & Arvonen, 1991 ). Managers with these attributes build feelings of confidence among organization members, promote the generation of new ideas, and facilitate replacing existing practices with new ones (Damanpour & Schneider, 2006 ; Madjar, Oldham, & Pratt, 2002 ; Mumford, 2000 ). They also promote the implementation of innovation by allocating resources, laying the social and technical groundwork, building coalitions among different constituencies, and assisting coordination and conflict resolution among units and members (Damanpour & Schneider, 2006 ; Dewar & Dutton, 1986 ; Mumford, 2000 ).

Quantitative reviews of the influence of managerial characteristics on organizational innovation have not been conducted. However, the articles in a two-part special issue of Leadership Quarterly on Leading for Innovation point out that leadership makes a major difference in the generation of ideas for new products and practices, and highlights how leaders could manage creative people to conduct creative work in creative ventures (Mumford, Scott, Gaddis, & Strange, 2002 ; Mumford & Licuanan, 2004 ). However, effective leadership of creative efforts of individuals and small teams is necessary but not sufficient for organizational innovation. In organizational settings, the selection of good ideas could be more crucial than the mere generation of new ideas (Grant, 2016 ). Hence, in addition to the generation of ideas, research on leadership for innovation should probe the process of selecting an idea from the portfolio of ideas, account for the effect of environmental and organizational factors on idea creation and selection, and explore whether the role of organizational leader differs in the process of generation of innovations of different types.

To make sense of multiple dimensions and numerous factors that could affect innovation in organizations, I suggest a sequence of decisions in selecting the dimensions and deciphering the antecedents. The first and perhaps most important decision is to identify organizational type, whether goods or services, business or public, low-tech or high-tech, and so on. Meta-analytical studies have reported significant differences between the antecedent–innovation relationships in different types of organizations (Camisón et al., 2004 ; Damanpour, 1991 ). Second, factors that influence the generation of innovation may not be compatible with those that influence the adoption of innovation. As such, a distinction between innovation-generating and innovation-adopting organizations is necessary. Third, while a set of antecedents may predict the process of innovation (innovating), a different set may predict organizational ability to innovate continually (innovativeness). Fourth is the distinction between innovation types, especially the technological–nontechnological and the radical–incremental, for the identification of salient antecedents of each type. Fifth, the relative importance of the environmental, organizational, and managerial characteristics in different types of organizations may differ. Current studies have not tested such differences, future studies should. Finally, the complexity of innovation constrains offering a common theory of organizational innovation. A possible approach researchers may pursue could be to focus on the antecedents of pairs of innovation types along firms’ value chains (Porter, 1985 ; Schilling, 2013 ). For example, antecedents of: (1) product–process pair for inbound versus outbound logistics; (2) technical–managerial pair in firm infrastructure versus human resource management; and (3) radical–incremental pair in technology development versus operations.

Organizational Innovation and Firm Performance

The widespread popularity of innovation stems from the assumption that its introduction results in positive (intended, expected, desired) outcomes. Rogers ( 1995 ) referred to this view as “pro-innovation bias.” While innovation is risky and its success is not certain, scholars and practitioners alike postulate that innovation strategies and activities boost firm performance. Empirical studies of the generation and adoption of innovations in organizations have usually supported this expectation (Bowen, Rostami, & Steel, 2010 ; Calantone, Harmancioglu, & Droge, 2010 ; Rosenbusch, Brinckmann, & Bausch, 2011 ; Walker, Chen, & Aravind, 2015 ). Studies of innovation failure are scarce.

The rationale for the favorable influence of innovation on firm conduct and outcome is offered by the first-mover advantage and performance gap theory (Damanpour, Walker, & Avellaneda, 2009 ; Keupp et al., 2012 ; Lam, 2005 ). The first-mover advantage imbedded in strategic management stresses the importance of generating new products and services for firm competitiveness and growth (Lieberman & Montgomery, 1988 ). Firms adopt first-mover strategy to become dominant in a product class or market and gain superior performance over time (Cohen & Levinthal, 1990 ; Roberts & Amit, 2003 ). First-mover strategy prompts organizations to engage in innovation activity, enables them to be aware of the latest developments, absorbs new and related knowledge, and increases the likelihood of benefiting from innovation activities in the long term (Bierly et al., 2009 ; Lieberman & Montgomery, 1988 ; Roberts & Amit, 2003 ).

Performance gap is defined as the perceived difference between an organization’s potential and actual accomplishments (Damanpour et al., 2009 ; Zaltman et al., 1973 ). Performance gap creates a need for organizational change, which in turn provides motivation to introduce innovation to produce change and reduce the perceived gap. The domain of performance gap theory is broader than that of first-mover advantage. While first-mover advantage applies to business organizations, performance gap applies to all types of organizations, whether business or public, service or manufacturing, low- or high-performance (Damanpour et al., 2009 ). The first-mover theory suits the generation of new products and services; performance gap theory is applicable to the adoption of any type of innovation, although it can also induce the generation of innovation.

Technological and Nontechnological Innovations and Performance

The conceptual confusion surrounding innovation and technology and misrepresentation of innovation as solely technology-based new products and processes has resulted in the perception that firm performance is affected by technological, but not necessarily by nontechnological, innovations. Studies of technological innovations in organizations are often espoused by the theories of economies of organization, which in management is referred to as rational (technical-efficiency) approach. The studies of nontechnological innovations, however, are governed by multiple theoretical approaches. Sturdy ( 2004 ) identified five such approaches (political, cultural, institutional, dynamic, and dramaturgical or rhetorical) for managerial innovations and compared them with the rational approach. He argued that the alternative approaches marginalize managerial rationality, might lead to empirical neglect, and portray rational management as bounded and emotional (Sturdy, 2004 ). In organization studies, the main alternative to the rational approach has been the institutional approach, often under the label of management fad and fashion (Damanpour, 2014 ).

To induce innovation, the rational perspective emphasizes on the influence of market dynamism and competition; the institutional perspective emphasizes pressures from regulators, parent organizations, and network members (Ashworth, Boyne, & Delbridge, 2009 ; Sturdy, 2004 ). Institutional pressures impel organizations toward conformity with rules and norms of their fields and heighten the importance of pursuit of legitimacy in organizational actions (Ansari, Fiss, & Zajac, 2010 ; Ang & Cummings, 1997 ). These pressures would more strongly affect nontechnological than technological innovations. For instance, organizational leaders are uncertain about technical efficiency of managerial innovations and rely on their currency in the population (Abrahamson, 1991 ; Burns & Wholey, 1993 ). Hence, the adoption of managerial innovations would result in social approval and reputation (social gain) rather than performance outcome (economic gain) (Abrahamson, 1991 ; Greve, 1995 ). Staw and Epstein ( 2000 ) provided empirical evidence for this view. They studied three administrative practices (quality, empowerment, and teams) and the implementation of TQM, and found that organizations that adopted them did not show higher economic performance (returns on asset, equity, and sales) but were more admired, perceived to be more innovative, and rated higher in management quality in their population (Staw & Epstein, 2000 , p. 523).

However, a recent quantitative review of the relationship between managerial innovation and firm performance provided evidence for a positive effect. Walker et al. ( 2015 ) integrated the empirical findings from 44 articles published in peer-reviewed journals via two different quantitative procedures, examined moderating effects of several factors, and found that the adoption of managerial innovations positively affects organizational performance. Further, using data from a subsample of 22 articles, Walker et al. ( 2015 ) integrated the empirical findings for the technological innovation–performance association and found a positive relationship also. 19 A comparison of a matched sample of associations of technological and managerial innovations with organizational performance showed that the two types of innovations affect performance similarly (Walker et al., 2015 ).

Overall, while managerial (nontechnological process) innovations are considered to be economically and socially important (Arrow, 1962 ; Edquist et al., 2001 ; Sanidas, 2005 ), and their introduction is deemed necessary to rejuvenate organizational strategy, structure, and systems (Birkinshaw et al., 2008 ; Stata, 1989 ; Volberda, Van Den Bosch, & Heij, 2013 ), research on this type of innovation lags behind technological innovation, and its influence on performance is deemed to be less predictable. Managerial innovations are operationally complex (difficult to implement and use), pervasive (changing administrative structure, authority, and power), and adaptable (modified during the adoption process) (Ansari et al., 2010 ; Damanpour, 2014 ). 20 Tidd ( 2001 ) argued that establishing a strong empirical relationship between innovation and performance is difficult because of technological and market contingencies, and methodological shortcomings (measurement of both constructs). For technological innovations surrogate measures such as patents and R&D expenditure are available and accepted; for nontechnological innovations easily quantifiable surrogate measures have not yet been developed (Armbruster et al., 2008 ; Damanpour & Aravind, 2012a ; Evangelista & Vezzani, 2010 ). Convincing empirical evidence on the stronger effect of one type above the other type has not yet emerged. Theoretical arguments, however, point to their combinative rather than stand-alone effects on performance outcomes.

Combinative Effects of Innovation Types

On the one hand, according to the first-mover advantage theory and based on the logic of organization competition and performance, superior performance occurs when a (technological) product or process new to a product class is introduced in the market and is received well by customers. Positive performance outcomes induce organizations to invest in excelling at the type of innovation for which they have been successful. Prior experience with a certain body of knowledge encourages further absorption of the same type of knowledge because organizations can more easily integrate, explore, and exploit the absorbed knowledge to create new opportunities that would further result in performance advantages (Bierly et al., 2009 ; Cohen & Levinthal, 1990 ; Roberts & Amit, 2003 ). Most studies of performance consequences of innovation follow this logic and focus on one type of innovation, often product or technological.

On the other hand, according to the performance gap theory and based on the logic of organizational adaptation and progression, sustained performance requires the introduction of different types of innovations over time to help adapt organizations to the external and internal changes (Damanpour et al., 2009 ; Roberts & Amit, 2003 ). Innovation types are interdependent, the introduction of one type could prompt the introduction of another type, and an understanding of contributions of each type requires an understanding of its relations with the other types. Performance consequences of innovation could best be captured by longitudinal studies that include the introduction of compatible sets of innovation types (product and process, technological and nontechnological, radical and incremental) across organizational parts or subsystems (Damanpour, 2014 ).

Georgantzas and Shapiro ( 1993 ) defined synchronous innovation as the adoption of compatible technological and managerial innovations, examined the influence of four descriptive models of synchronous innovation (independent, moderating, mediating, and interactive) on organizational performance, and found that the independent effect of each innovation type on performance is negligible without synchronous innovation (p. 161). Roberts and Amit ( 2003 ) extended the notion of synchronous innovation to compositions of innovation types. These authors investigated the influence of three compositions (focus, commitment, and divergence) of three types of innovations (product, process, and distribution) on performance in retail banking organizations longitudinally and found that long-term performance depends on the history of innovation activity in organizations rather than occasional success of stand-alone innovations (Roberts & Amit, 2003 ). Damanpour et al. ( 2009 ) also investigated three compositions (focus, consistency, and divergence) of three different types of innovation (technological, administrative, and service) in public service organizations and confirmed Roberts and Amit’s conclusion. Longitudinal, empirical evidence from these studies challenges the notion that firm performance is enhanced by focus on excelling at a specific type of innovation, whether product, service, process, technical, or managerial. Instead, in line with adaptation and progression view they suggest that sustained performance requires harmonious modifications of various organizational subsystems via the introduction of complementary innovation types (Ballot, Fakhfakh, Galia, & Slater, 2015 ; Battisti & Iona, 2009 ; Hervas-Oliver & Sempere-Ripoll, 2014 ; Naranjo-Gil, 2009 ).

Theoretical support for complementarity of innovation types and their combinative performance effects can be found in organization and strategic management. The perspective of organizations as socio-technical systems is an early example. This perspective theorized that the relationship between organizational subsystems is not strictly a one-to-one relationship; rather, it is a correlative relationship representing a coupling of dissimilarities, where changes in one subsystem necessitate corresponding changes in the other subsystems (Emery & Trist, 1960 ). The social and technical systems interact continuously and are inclined toward a dynamic equilibrium in relation to the external environment (Boonstra & Vink, 1996 ; Trist & Murray, 1993 ). Any change in one system sets certain constraints and requirements, and necessitates a corresponding change in the other system. Considering technical and administrative innovations as means of changing the technical and social systems, organizational performance requires a balanced introduction of both types (Damanpour & Evan, 1984 ).

Theories and perspective in strategic management also allude to the complementary role of innovation types. For example, the resource-based and knowledge-based views underscore the roles of external and internal sources of knowledge and the firm’s capability to integrate them to gain distinctive competencies (Barney, 2001 ; Grant, 1996 ). Theories of operational and combinative capabilities also imply that innovating across organizational functions and systems could ensure renewal of competencies to build, reconfigure, and integrate internal and external experiences to cope with the dynamics of environmental change (Eisenhardt & Martin, 2000 ; Helfat & Winter, 2011 ; Van den Bosch, Volberda, & de Boer, 1999 ). The application of these views to innovation activity at the firm level underlines the synergistic use of organizations’ technological, operational, and managerial knowledge resources, motivating the synchronous introduction of innovation types across organizational parts to gain sustained performance outcomes (Damanpour, 2014 ).

The complexity of both innovation and performance constructs combined with myriad indicators for their measurement has prevented rigorous evidence on conditions and the extent to which the generation or adoption of innovation contributes to organizational performance. However, two important trends have emerged. First, since organizations generate and adopt innovation continually over time, an assessment of the true impact of innovation on performance requires longitudinal research. Second, research on performance consequences of innovation has shifted from the stand-alone to synchronous innovations. The synchronous view departs from the prevailing logic that espouses autonomous strategies of innovation types for competitive advantage and submits that innovation types, along with organizational subsystems, are interdependent and their complementary introduction could best influence organizational conduct and outcome (Damanpour, 2014 ). In this vein, the notion of internal fit , which espouses congruency in the behavior of organizational parts, also applies to the introduction of types of innovations in organizations to facilitate external fit , which espouses congruency in the behavior of organizations with their competitive and institutional environments.

Conclusions and Future Research

A student in a doctoral seminar on the management of innovation observed that each article he reads adds one more star to the innovation galaxy, but the new star, as bright as it might be, does not improve his understanding of innovation. This student’s predicament is not unique to him or to innovation studies. Researchers may face similar predicaments in organizational sciences, where theories are incompatible, findings inconsistent, and the body of knowledge indigestible (Zammuto & Connolly, 1984 , p. 32). Research in management commonly pursues a scattered pattern where empirical studies are rarely replicated and can differ greatly in terms of definitions of key constructs, the nature of the phenomenon studied, and measurement instruments (Tsang & Kwan, 1999 ). Organizational studies are diverse and fragmented and theoretical and methodological consensus are not in sight (Hambrick, 1994 ; Pfeffer, 1993 ).

Assuming that diversity in innovation management research is unavoidable and consensus rather impossible, this article has mapped this research, identified major dimensions and their key components, discussed differences among components, and offered ideas to avoid unsuitable inferences. This section concludes by proposing steps to scan organizational innovation research, identify issues in the existing studies, and develop new studies. The study of innovation in organizations is theoretically and practically important, and ample opportunities exist for additional research to help explain how organizations innovate and in which contexts innovation could contribute to their conduct and outcomes. To advance the state of knowledge, innovation scholars should set out to demystify the innovation galaxy to allure new scholars and facilitate their learning rather than confusing them in the name of generating new theories (Hambrick, 2007 ).

Disciplinary Differences in Conceptualization of Innovation

Research on innovation from the economic perspective treats organization as a black box often recognized by its small or large size, sector or industry. Organizational innovation research, however, requires opening the black box, observing operational and administrative activities occurring in it, and explaining what set of activities could lead to innovation and how. Whereas insights from multiple disciplinary fields enrich research on innovation in organizations, the differences in conceptualizations, levels of analysis, and methodological predispositions should be accounted for. The absorption and integration of theories and findings from another discipline require a deliberate effort to articulate relevance and applicability. Otherwise, disciplinary differences will result in fragmentation and confusion rather than contribution and understanding.

Intradisciplinary differences also exist among subfields of innovation management, but the absorption and application of knowledge from one subfield to another is more feasible. For instance, to bridge the differences between innovation research from micro and macro organizational behavior, Crossan and Apaydin ( 2010 ) propose a unifying approach at a meso level to link managerial actions with innovation conduct and outcome. In another example, Keupp et al. ( 2012 ) identify theoretical inconsistencies and knowledge gaps in the strategic management of innovation, encourage strategy scholars to take notice and use insights from other subfields of innovation management, and advise them to scrutinize commonalities and differences in the definition and operationalization of innovation. Innovation strategy research would need to move beyond its mere focus on technological innovations and their singular impact on firm performance. Research on other types of innovation and how different types can be introduced and managed strategically can provide valuable insights for understanding management of innovation in strategy and other subfields of organization management.

Using innovation as a sweeping word that crosses disciplines will enlarge and further complicate the innovation galaxy. Authors should be cognizant of innovation as understood and defined in various disciplines and refrain from irrelevant importation and loose generalization. Reviewers and editors of academic journals should be more cognizant of authors’ limitations, and their own, refrain from discouraging repetitions, seeking new theory in every single submission, and protecting their personal investments in certain theoretical perspectives and methodologies (Starbuck, 2016 ). For a start, the type of innovation a paper studies and the context of the study should be included in the paper’s title. This simple act mitigates the major conceptual confusion in innovation research: mistaking technology for innovation. The context of innovation studies in the subfields of organization studies differs. The primary purpose, innovation issue, and key actors in small and large, and in business and public, organizations differ. For example, the central actor in a small start-up firm is the entrepreneur, but in medium-size and large organizations individual actors’ influence is mitigated by organizational culture, structure, power, and politics. In a business organization the ultimate outcome is often market share or financial outcome, in a government organization it is the reach and quality of services to citizens. These differences make the distinction between organizational types and innovating and innovativeness necessary for understanding, interpreting, and learning from the vast body of knowledge on innovation in organizations.

Generation, Adoption, and Organizational Type

In addition to the assumption that innovation is merely technology-based, many innovation studies also assume that innovation is a unitary process, and thus bypass the differences between generating and adopting innovations. Organizations can be generator of innovation, adopter of innovation, or both. They may also generate innovation for their own use, for external markets, or both. A distinction of the type of relationship between innovation and organization is necessary for deciphering the existing research and associating the conditions that prompt innovation in a certain type of organization (Kimberly, 1986 ).

Research on structuring for innovation has proposed several dual or ambidextrous structures based on initiation and implementation stages of adoption (Duncan, 1976 ), technical and administrative types of innovation (Daft, 1978 ), and radical and incremental types of innovation (Tushman & O’Reilly, 2002 ). Damanpour and Wischnevsky ( 2006 ) distinguished between organizations for generating innovations and organizations for adopting innovations. The innovation-generating organization, whether a new firm created by an entrepreneur or a self-contained unit of a large organization, requires the ability to accumulate knowledge and diffuse it inside the organization, motivate individuals’ and teams’ creative actions, and overcome technological and organizational obstacles to generate innovations expeditiously. The innovation-adopting organization mainly exploits current knowledge to seize new strategic opportunities or to solve existing organizational problems. It adopts new technologies, products, and practices available in the market, and applies them to improve its products, services, practices, and systems (Damanpour & Wischnevsky, 2006 ). These authors concluded that the typical questions of how to innovate, what conditions induce or drive innovativeness, and how innovation impacts performance should be broken into two sets of questions: one for generating innovations, another for adopting innovations.

The distinction between organizational types in general, and ambidextrous structures in particular, can help organize the existing research. Recognition of the differences between innovation generating and adopting organizations, for instance, is useful for separating the conditions that drive generation versus adoption, for aligning the studies of innovation in strategy with those in organization management, and helping to distinguish innovation activities for gaining competitive advantage from those for sustaining competitiveness.

Emerging Field of Nontechnological Innovations

Research on managerial innovation dates back to the 1960s–1980s. Birkinshaw et al.’s ( 2008 ) article rejuvenated interest in this innovation type, resulting in a considerable number of new studies. For instance, European Academy of Management has thus far sponsored three thematic conferences on management innovation, and two special issues edited by Volberda and colleagues (Volberda et al., 2013 ; Volberda, Van Den Bosch, & Mihalache, 2014 ) have been published. Recent articles have focused on theoretical perspectives, creation, adoption, and antecedents of managerial innovation, and have articulated future research avenues (Birkinshaw et al., 2008 , pp. 839–842; Damanpour, 2014 , pp. 1276–1279; Volberda et al., 2013 , p. 8; Volberda et al., 2014 , pp. 1258–1260). However, lack of consensus on the definition and measurement of managerial innovations remains an obstacle to the advancement of this untapped area of innovation research.

The OECD ( 2005 ) Oslo Manual added two types of nontechnological (organizational and marketing) innovations to technological (product and process) innovations, which were surveyed since 1993 . OECD’s organizational innovation (synonymous with managerial innovation as defined in this paper) is grouped into three types: business practices for organizing procedures, methods of organizing work responsibilities and decision-making , and methods of organizing external relations . It groups marketing innovation into four types: aesthetic design or packaging of good or service, techniques for product promotion ; methods for product placement , and methods for pricing goods or services. Data on organizational and marketing innovations are collected by seven dichotomous questions via Community Innovation Survey (CIS) since 2004 . Empirical studies have selectively included OECD’s organizational and marketing innovations in their operationalization of nontechnological innovations (Černe et al., 2016 ; Damanpour, 2014 ).

Černe et al. ( 2016 ) recommends coalescing various types of nontechnological innovations under one umbrella category. The category includes ancillary, business model, marketing, and open innovations, in addition to managerial innovation. Marketing innovation is an established innovation type, and has its own relatively large literature. It overlaps with the studies of product innovations, and relates mainly to the generation of innovations. Marketing and management are also two separate functional areas within business schools and are viewed as different specialties in business and management. However, in-depth comparative review analyses of managerial and marketing innovations may show that they do have a similar theoretical foundation and intellectual structure. Future research can explore such ideas and issues on the composition of nontechnological innovations.

Open innovation has been applied in strategic management and can be more easily integrated with the studies of innovation in other subfields of management. However, since closed innovation is an anomaly and cannot exist by definition, open innovation, similar to radicalness of innovation, can be regarded as a continuum rather than a type. Innovation openness , the extent to which organizations involve external players in various stages of generation or adoption of innovation, is applicable to all types of innovation, as is innovation radicalness. Future research on innovation openness should go beyond technological innovations in the goods sector and examine forms of external involvement for nontechnological innovations in services and public organizations. External partners, whether individuals or organizations, can participate and influence the creation and utilization of all types of innovation. For example, Birkinshaw et al. ( 2008 ) discussed roles of internal and external players in the development of management innovations and argued that external players (academic and nonacademic experts) have a more prominent role than internal players. Future research can also investigate the consequences of innovation openness. Innovation openness via strategic alliances and joint ventures is not a panacea for success. Cooperative innovation mode should be compatible with organizational culture and strategy, and interfirm differences should be managed effectively (Lichtenthaler, 2011 ). The success of innovation openness is not just a function of strategy formulation; instead, it depends heavily on organizational competencies for strategy implementation. Boeing’s experience in the design and production of the 787 Dreamliner is a revealing example (HBS Case #9-305-101).

Innovation from Garage, Innovation from Office

In the late 19th century Gabriel Trade, a sociologist, portrayed innovation as imitation concerning social transformation; in the early 20th century Joseph Schumpeter, an economist, set the ground for portraying innovation (new combination) as technical invention concerning economic development (Godin, 2008 ). Schumpeter’s entrepreneurial model of innovation underlined the role of entrepreneurs for bringing technical and social change, and personal and economic prosperity. In North America, innovation as a function of entrepreneurs continues to fascinate researchers, practitioners, and the general public. Young people, often without formal education or college dropouts, come up with an innovative product or service, launch and manage a new business, and gain enormous success. A contemporary example of this idealized model of innovation is the story of Steve Jobs and Apple, Inc. The corporate model of innovation, along with continued growth and global dominance of large corporations in the second half of the 20th century , brought attention to “innovation from office,” but did not replace “innovation from garage” in the public imagination.

Research on innovation in organizations has been influenced by both views. However, in medium-size or large organizations where the entrepreneurial stage has passed, formal structure and processes have been devised, and the leaders are professional managers, not owner-managers, innovation from office is essential. Managing innovation in a new enterprise in the early stages of its life cycle is different from that of a medium-size or large organization in the later stages. In the postentrepreneurial stages, for instance, the central actor for innovation is not the owner-manager or the CEO only. Influences of individual actors in innovation activities are mitigated by the organization’s culture and structure. Hence, reliance on the competition and performance perspective to explain innovation in medium-size and large organizations is inadequate. This perspective would need to be augmented or replaced with the adaptation and progression perspective in accordance with types and contexts of organizations. In this vein, research on organizational innovation would need to move beyond the 20th-century paradigm—that sustained long-term performance of organizations is based on the introduction of commercialized technology-based new products and processes—to a 21st-century paradigm in which continuous high performance pivots on the complementary effects of sets of innovation types guided by environmental demands and managerial aspirations.

Early steps toward the new paradigm have been taken. For instance, research on the relationship between innovation types has moved from a sequential pattern (product leads process, technical leads managerial) to a synchronous pattern (product and process intersect, technical and managerial complement), and from a focus on the importance of technological innovations for organizational effectiveness to one that also includes nontechnological innovations. Better theory and more empirical evidence are needed, however. Future studies of organizational innovation can contribute by continuing and advancing these new research trends by developing theory and investigating the dynamics of innovation types and their combinative effects on organizational conduct and outcome in a variety of contexts. The studies should also inform practitioners how to design and manage organizations for innovation, create and maintain a proinnovation culture and climate across organizational parts, drive continuous improvement of operations, systems, and human knowledge, and ensure that innovation not only benefits the organization but also does not harm the people and the environment.

Acknowledgement

The author thanks Rachel Bocquet, Benoît Godin, and the reviewers and editors of the Oxford Research Encyclopedia for Business and Management for their helpful comments.

• Abernathy, W. J. , & Utterback, J. M. (1978). Patterns of industrial innovation. Technology Review , 80 , 40–47.
• Abrahamson, E. (1991). Managerial fads and fashion: The diffusion and rejection of innovation. Academy of Management Review , 16 , 586–612.
• Ackoff, R. L. (1970). A concept of corporate planning . New York: Wiley-Interscience.
• Ackoff, R. L. (1981). Creating the corporate future . New York: John Wiley.
• Ackoff, R. L. , & Emery, F. E. (1972). On purposeful systems: An interdisciplinary analysis of individual and social behavior as a system of purposeful events . Chicago: Aldine-Atherton.
• Ahlstrom, D. (2010). Innovation and growth: How business contributes to society. Academy of Management Perspective, August , 10–23.
• Aiken, M. , & Hage, J. (1971). The organic organization and innovation. Sociology , 5 , 63–82.
• Allan, T. A. , & Sosa, M. L. (2004). 50 years of engineering management through the lens of the IEEE Transactions. IEEE Transactions on Engineering Management , 51 (4), 391–395.
• Amabile, T. M. (1988). A model of creativity and innovation in organizations. In L. L. Cummings & B. M. Staw (Eds.), Research in organizational behavior (Vol. 10, pp. 123–167). Greenwich, CT: JAI Press.
• Anderson, N. , Potočnik, K. , & Zhou, J. (2014). Innovation and creativity in organizations: A state-of-the-science review, prospective commentary, and guiding framework. Journal of Management , 40 (5), 1297–1333.
• Andrews, F. M. , & Farris, G. F. (1967). Supervisory practices and innovation in scientific teams, Personnel Psychology , 20 (4), 497–515.
• Ang, S. , & Cummings, L. L. (1997). Strategic response to institutional influences on information systems outsourcing. Organization Science , 8 (3), 235–256.
• Angle, H. L. , & Van de Ven, A. H. (1989). Suggestions for managing the innovation journey. In A. H. Van de Ven , H. L. Angle , & M. S. Poole (Eds.), Research on the management of innovation: The Minnesota studies (pp. 663–697). New York: Oxford University Press.
• Ansari, S. M. , Fiss, P. C. , & Zajac, E. (2010). Made to fit: How practices vary as they diffuse. Academy of Management Review , 35 , 67–92.
• Ansoff, H. I. (1968). Corporate strategy: An analytic approach for business policy and growth . New York: McGraw-Hill.
• Armbruster, H. , Bikfalvi, A. , Kinkel, S. , & Lay, G. (2008). Organizational innovation: The challenge of measuring non-technical innovation in large-scale surveys. Technovation , 28 , 644–657.
• Arrow, K. J. (1962). The economic implications of learning by doing. The Review of Economic Studies , 29 (3), 155–173.
• Ashworth, R. , Boyne, G. , & Delbridge, R. (2009). Escape from the iron cage? Organizational change and isomorphic pressures in the public sector. Journal of Public Administration Research and Theory , 19 , 165–187.
• Baer, M. (2012). Putting creativity to work: The implementation of creative ideas in organizations. Academy of Management Journal , 55 , 1102–1119.
• Baldridge, J. V. , & Burnham, R. A. (1975). Organizational innovation, individual, organizational, and environmental impacts. Administrative Science Quarterly , 20 , 165–176.
• Ballot, G. , Fakhfakh, F. , Galia, F. , & Slater, A. (2015). The fateful triangle: Complementarities in performance between products, process and organizational innovation in France and the UK. Research Policy , 44 , 217–232.
• Bantel, K. A. , & Jackson, S. E. (1989). Top management and innovations in banking: Does the composition of the top management team make a difference. Strategic Management Journal , 10 (S), 107–124.
• Barnett, W. P. (1990). The organizational ecology of a technological system. Administrative Science Quarterly , 35 , 31–60.
• Barney, J. B. (2001). Is the resource-based view a useful perspective for strategic management research? Yes. Academy of Management Review , 26 , 41–56.
• Barras, R. (1986). Towards a theory of innovation in services. Research Policy , 15 , 161–173.
• Barras, R. (1990). Interactive innovation in financial and business services: The vanguard of the service revolution. Research Policy , 19 (3), 215–237.
• Battisti, G. , & Iona, A. (2009). The intra-firm diffusion of complementary innovations: Evidence from the adoption of management practices by British establishments. Research Policy , 38 , 1326–1339.
• Becker, S. W. , & Whisler, T. M. (1967). The innovative organization: A selective view of current theory and research. Journal of Business , 40 (4), 462–469.
• Bierly, P. , Damanpour, F. , & Santoro, M. (2009). The application of external knowledge: Organizational conditions for exploration and exploitation. Journal of Management Studies , 46 (3), 481–509.
• Birkinshaw, J. , Hamel, G. , & Mol, M. (2008). Management innovation. Academy of Management Review , 33 (4), 825–845.
• Boonstra, J. J. , & Vink, M. J. (1996). Technological and organizational innovation: A dilemma of fundamental change and participation. European Journal of Work and Organizational Psychology , 5 (3), 351–376.
• Boulding, K. (1956). General system theory: The skeleton of science. General Systems (Yearbook of the Society for the Advancement of General Systems Theory) , 1 , 11–17.
• Bowen, F. E. , Rostami, M. , & Steel, P. (2010). Timing is everything: A meta-analysis of the relationship between organizational performance and innovation. Journal of Business Research , 63 , 1179–1185.
• Boyne, G. A. (2002). Public and private management: What’s the difference? Journal of Management Studies , 39 , 97–129.
• Brozen, Y. (1951). Research, technology, and productivity. In L. R. Tripp (Ed.), Industrial productivity (pp. 25–49). Champaign, IL: Industrial Relations Research Association.
• Burke, W. W. (2002). Organization change: Theory and practice. Thousand Oaks, CA: SAGE.
• Burns, L. R. , & Wholey, D. R. (1993). Adoption and abandonment of matrix management programs: Effects of organizational characteristics and interorganizational networks. Academy of Management Journal , 36 (1), 106–138.
• Burns, T. , & Stalker, G. M. (1961). The management of innovation . London: Tavistock.
• Calantone, R. J. , Cavusgil, S. T. , & Zhao, Y. (2002). Learning orientation, firm innovation capability, and firm performance. Industrial Marketing Management , 31 (6), 515–524.
• Calantone, R. J. , Harmancioglu, N. , & Droge, C. (2010). Inconclusive innovation returns: A meta-analysis of research on innovation in new product development. Journal of Product Innovation Management , 27 , 1065–1081.
• Camisón, C. , Lapiedra, R. , Segarra, M. , & Boronat, M. (2004). A meta-analysis of innovation and organizational size. Organization Studies , 25 , 331–361.
• Černe, M. , Kaše, R. , & Škerlavaj, M. (2016). Non-technological innovation research: Evaluating the intellectual structure and prospects of an emerging field. Scandinavian Journal of Management , 32 , 69–85.
• Chandy, R. K. , & Tellis, G. L. (2000). The incumbent’s curse? Incumbency, size, and radical product innovation, Journal of Marketing , 64 , 1–17.
• Cheng, Y. , & Van de Ven, A. H. (1996). Learning the innovation journey: Order out of chaos. Organization Science , 7 , 593–614.
• Chesbrough, H. W. (2003). The era of open innovation. Sloan Management Review , 44 (3), 35–41.
• Chesbrough, H. W. , & Appleyard, M. M. (2007). Open innovation and strategy. California Management Review , 50 (1).
• Christensen, C. M. (1997). The innovation’s dilemma . Boston: Harvard Business School Press.
• Churchman, C. W. (1968). The systems approach . New York: Delacorte Press.
• CIS . (2010). The Community Innovation Survey . Luxembourg: Eurostat.
• Cohen, W. M. , & Levin, R. C. (1989). Empirical studies of innovation and market structure. In R. Schmalansee & R. D. Willing (Eds.), Handbook of industrial organization (Vol. 2, pp. 1059–1107). Oxford: Elsevier.
• Cohen, W. M. , & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly , 35 , 128–152.
• Crossan, M. M. , & Apaydin, M. (2010). A multi-dimensional framework of organizational innovation: A systematic review of the literature, Journal of Management Studies , 47 (6), 1154–1191.
• Cyert, R. , & March, J. (1963). A behavioral theory of the firm . Englewood Cliffs, NJ: Prentice-Hall.
• Daft, R. L. (1978). A dual-core model of organizational innovation. Academy of Management Journal , 21 , 193–210.
• Daft, R. L. (2001). Organization theory and design . Cincinnati, OH: South-Western.
• Daft, R. L. , & Becker, S. W. (1978). The innovative organization . New York: Elsevier.
• Damanpour, F. (1987). The adoption of technological, administrative, and ancillary innovations: Impact of organizational factors, Journal of Management , 13 , 675–688.
• Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal , 34 , 555–590.
• Damanpour, F. (1992). Organizational size and innovation. Organization Studies , 13 , 375–402.
• Damanpour, F. (2010). An integration of research findings of effects of firm size and market competition on product and process innovations. British Journal of Management , 21 , 996–1010.
• Damanpour, F. (2014). Footnotes to research on management innovation. Organization Studies , 39 (5), 1265–1285.
• Damanpour, F. , & Aravind, D. (2006). Product and process innovations: A review of organizational and environmental determinants. In J. Hage & M. Meeus (Eds.), Innovation, science, and institutional change: A research handbook (pp. 38–66). Oxford: Oxford University Press.
• Damanpour, F. , & Aravind, D. (2012a). Managerial innovation: Conceptions, processes, and antecedents. Management and Organization Review , 8 (2), 423–454.
• Damanpour, F. , & Aravind, D. (2012b). A review of research on organizational structure and innovation: From organic to ambidextrous structure. In M. D. Mumford (Ed.), Handbook of organizational creativity (pp. 483–513). Boston: Academic Press.
• Damanpour, F. , & Evan, W. M. (1984). Organizational innovation and performance: The problem of organizational lag. Administrative Science Quarterly , 29 , 392–409.
• Damanpour, F. , & Gopalakrishnan, S. (1998). Theories of organizational structure and innovation adoption: The role of environmental change. Journal of Engineering and Technology Management , 15 , 1–24.
• Damanpour, F. , Sanchez, F. , & Chiu, H. H. (2017). Management Innovativeness: Effects of internal and external involvement and implementation actions. Paper presented at the European Academy of Management, Glasgow.
• Damanpour F. , & Schneider, M. (2006). Phases of the adoption of innovation in organizations: Effects of environment, organization, and top managers. British Journal of Management , 17 , 215–236.
• Damanpour, F. , & Schneider, M. (2009). Characteristics of innovation and innovation adoption in public organizations: Assessing the role of management. Journal of Public Administration Research and Theory , 19 , 495–522.
• Damanpour, F. , Walker, R. M. , & Avellaneda, C. N. (2009). Combinative effects of innovation types and organizational performance: A longitudinal study of services organizations. Journal of Management Studies , 46 (4), 650–675.
• Damanpour, F. , & Wischnevsky, J. D. (2006). Research on innovation in organizations: Distinguishing innovation-generating from innovation-adopting organizations. Journal of Engineering and Technology Management , 23 , 269–291.
• De Vries, H. , Bekkers, V. , & Tummers, L. (2016). Innovation in the public sector: A systematic review and future research agenda. Public Administration , 94 (1), 146–166.
• Dewar, R. D. , & Dutton, J. E. (1986). The adoption of radical and incremental innovations: An empirical analysis. Management Science , 32 , 1422–1433.
• Drucker, P. F. (1985). The discipline of innovation. Harvard Business Review , 63 (3), 67–72.
• Duncan, R. B. (1976). The ambidextrous organization: Designing dual structures for innovation. In R. H. Kilmann , L. R. Pondy , & D. P. Slevin (Eds.), The management of organizational design: Strategy implementation , 1 , 167–188. New York: North-Holland.
• Economist . (2007, March 1). The rise and fall of corporate R&D.
• Edquist, C. , Hommen, C. L. , & McKelvey, M. (2001). Innovation and employment: Process versus product innovation . Cheltenham, U.K.: Edward Elgar.
• Eisenhardt K. , & Martin, J. A. (2000). Dynamic capabilities: What are they? Strategic Management Journal , 21 , 1105–1121.
• Ekvall, G. (1996). Organizational climate for creativity and innovation. European Journal of Work and Organizational Psychology , 5 , 105–123.
• Ekvall, G. , & Arvonen, J. (1991). Change-centered leadership: An extension of the two-dimensional model. Scandinavian Journal of Management , 7 , 17–26.
• Elenkov, D. S. , Judge, W. , & Wright, P. (2005). Strategic leadership and executive innovation influence: An international multi-cluster comparative study, Strategic Management Journal , 26 , 665–682.
• Emery, F. E. , & Trist, E. L. (1960). Socio-technical system. In C. W. Churchman & M. Verhulst (Eds.), Management science: Models and techniques (pp. 83–97). Oxford: Pergamon.
• Ettlie, J. E. (1988). Taking charge of manufacturing: How companies are combining technological and organizational innovations to compete successfully . San Francisco: Jossey-Bass.
• Ettlie, J. E. , Bridges, W. P. , & O’Keefe, R. D. (1984). Organization strategy and structural differences for radical versus incremental innovation. Management Science , 30 , 682–695.
• Evan, W. M. (1966). Organizational lag. Human Organization , 25 , 51–53.
• Evan, W. M. (1976). Organization theory and organizational effectiveness: An exploratory analysis. Organization and Administrative Science , 7 , 15–28.
• Evangelista, R. , & Vezzani, A. (2010). The economic impact of technological and organizational innovations: A firm level analysis. Research Policy , 39 (10), 1253–1263.
• Fagerberg, J. (2005). Innovation: A guide to the literature. In J. Fagerberg , D. C. Mowery , & R. R. Nelson (Eds.), The Oxford handbook of innovations (pp. 1–26). Oxford: Oxford University Press.
• Fagerberg, J. , Mowery, D. C. , & Nelson, R. R. (2005). The Oxford handbook of innovations . Oxford: Oxford University Press.
• Ford, C. M. (1995). Creativity is a mystery: Clues from the investigators’ notebooks. In C. M. Ford & D. A. Gioia (Eds.), Creative action in organizations (pp. 12–49). Thousand Oaks, CA: SAGE.
• Ford, C. M. (1996). A theory of individual creative action in multiple social domains. Academy of Management Review , 21 , 1112–1142.
• Georgantzas, N. C. , & Shapiro, J. H. (1993). Viable theoretical forms of synchronous product innovation. Journal of Operations Management , 11 , 161–183.
• Godin, B. (2008). Innovation: The history of a category. Project on the Intellectual History of Innovation, Working Paper No. 1. Montreal: INRS (Institut national de la recherche scientifique).
• Godin, B. (2014). Innovation and creativity: A slogan, nothing but a slogan. In C. Antonelli & A. N. Link (Eds.), Routledge handbook of the economics of knowledge (pp. 7–19). London: Routledge.
• Godin, B. (2015a). Innovation contested: The idea of innovation over the centuries. London: Routledge.
• Godin, B. (2015b). Technological change: What do technology and change stand for? Project on the Intellectual History of Innovation, Working Paper No. 24. Montreal: INRS.
• Gopalakrishnan, S. , & Damanpour, F. (1994). Patterns of generation and adoption of innovations in organizations: Contingency models of innovation attributes. Journal of Engineering and Technology Management , 11 , 95–116.
• Gopalakrishnan, S. , & Damanpour, F. (1997). A review of innovation research in economics, sociology, and technology management. Omega , 25 , 15–28.
• Gordon, R. (2016). The rise and fall of American growth . Princeton, NJ: Princeton University Press.
• Grant, A. (2016). Originals . New York: Viking.
• Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal , 17 , 109–122.
• Greve, H. R. (1995). Jumping ship: The diffusion of strategy abandonment. Administrative Science Quarterly , 40 , 444–473.
• Hage, J. , & Aiken, M. (1970). Social change in complex organizations . New York: Random House.
• Hambrick, D. (1994). What if the academy actually mattered? Academy of Management Review , 19 , 11–16.
• Hambrick, D. C. (2007). The field of management’s devotion to theory: Too much of a good thing? Academy of Management Journal , 50 (6), 1346–1352.
• Hamel, G. (2006). The why, what and how of management innovation. Harvard Business Review , 84 (2), 72–84.
• Helfat, C. E. , & Winter, S. G. (2011). Untangling dynamic and operational capabilities: Strategy for the (n)ever-changing world. Strategic Management Journal , 29 , 79–81.
• Henderson, R. M. , & Clark, K. B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly , 35 , 9–30.
• Hervas-Oliver, J.-L. , & Sempere-Ripoll, F. (2014). Disentangling the influence of technological process and product innovations. Journal of Business Research , 68 , 109–118.
• Hitt, M. A. , Hoskisson, R. E. , & Ireland, R. D. (1990). Mergers and acquisitions and managerial commitment to innovation in m-form firms. Strategic Management Journal , 11 (S), pp. 29–47.
• Hitt, M. A. , Ireland, R. D. , Camp, S. M. , & Sexton, D. L. (2001). Strategic entrepreneurship: Entrepreneurial strategies for wealth creation. Strategic Management Journal , 22 , 479–491.
• Hoffman, R. C. , & Hegarty, W. H. (1993). Top management influence on innovations: Effects of executive characteristics and social culture. Journal of Management , 19 , 549–574.
• Jansen, J. J. P. , Van Den Bosch, F. A. J. , & Volberda, H. W. (2006). Exploratory innovation, exploitative innovation, and performance: Effects of organizational antecedents and environmental moderators. Management Science , 52 (11), 1661–1674.
• Jick, T. (1993). Managing change . New York: McGraw-Hill.
• Keupp, M. M. , Palmie, M. , & Gassmann, O. (2012). The strategic management of innovation: A systematic review and paths for future research. International Journal of Management Review , 14 , 367–390.
• Kimberly, J. R. (1981). Managerial innovation. In P. C. Nystrom and W. H. Starbuck (Eds.), Handbook of organizational design (pp. 84–104). New York: Oxford University Press.
• Kimberly, J. R. (1986). The organization context of technological innovation. In D. D. Davis (Ed.), Managing technological innovation (pp. 23–43). San Francisco: Jossey-Bass.
• Kimberly, J. R. , & Evanisko, M. (1981). Organizational innovation: The influence of individual, organizational, and contextual factors on hospital adoption of technological and administrative innovations. Academy of Management Journal , 24 , 679–713.
• King, N. (1990). Innovation at work: The research literature. In M. A. West & J. L. Farr (Eds.), Innovation and creativity at work (pp. 15–59). New York: Wiley.
• Klein, K. J. , & Sorra, J. S. (1996). The challenge of innovation implementation. Academy of Management Journal , 21 , 1055–1080.
• Lam, A. (2005). Organizational innovation. In J. Fagerberg , D. C. Mowery , & R. R. Nelson (Eds.), The Oxford handbook of innovations (pp. 115–147). Oxford: Oxford University Press.
• Lawless, M. W. , & Anderson, P. C. (1996). Generational technological change: Effects of innovation and local rivalry on performance. Academy of Management Journal , 39 , 1185–1217.
• Lawrence, P. R. , & Lorsch, J. W. (1967). Organization and environment . Homewood, IL: Irwin.
• Laursen, K. , & Salter, A. (2006). Open for innovation: The role of openness in explaining innovation performance among U.K. manufacturing firms. Strategic Management Journal , 27 , 131–150.
• Leiponen, A. , & Helfat, C. E. (2010). Innovation objectives, knowledge sources, and the benefit of breadth. Strategic Management Journal , 31 , 224–236.
• Lengnick-Hall, C. A. (1992). Innovation and competitive advantage: What we know and what we need to learn. Journal of Management , 18 (2), 399–429.
• Lichtenthaler, U. (2011). Open innovation: Past research, current debates, and future direction. Academy of Management Perspectives , 25 (1), 75–93.
• Lieberman, M. B. , & Montgomery, D. B. (1988). First mover advantages. Strategic Management Journal , 9 (S1), 41–58.
• Madjar, N. , Oldham, G. R. , & Pratt, M. G. (2002). There’s no place like home? The contributions of work and non-work creativity support to employees’ creative performance. Academy of Management Journal , 45 , 757–767.
• March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science , 2 , 71–87.
• Meeus, M. T. H. , & Edquist, C. (2006). Introduction to Part I: Product and process innovation. In J. Hage & M. Meeus (Eds.), Innovation, science, and institutional change (pp. 23–37). Oxford: Oxford University Press.
• Meyer, A. D. , & Goes, J. B. (1988). Organizational assimilation of innovations: A multilevel contextual analysis. Academy of Management Journal , 31 , 897–923.
• Miles, Ian . (2005). Innovation in services. In J. Fagerberg , D. C. Mowery , & R. R. Nelson (Eds.), The Oxford handbook of innovations (pp. 433–458). Oxford: Oxford University Press.
• Mintzberg, H. (1979). The structuring of organizations . Englewood Cliffs, NJ: Prentice-Hall.
• Mohr, L. B. (1969). Determinants of innovation in organizations, American Political Science Review , 63 , 111–126.
• Mol, M. J. , & Birkinshaw, J. (2014). The role of external involvement in the creation of management innovations. Organization Studies , 35 , 1287–1312.
• Mumford, M. D. (2000). Managing creative people: Strategies and tactics for innovation. Human Resources Management Review , 10 , 313–355.
• Mumford, M. D. , & Licuanan, B. (2004). Leading for innovations: Conclusions, issues, and directions. Leadership Quarterly , 15 , 163–171.
• Mumford, M. D. , Scott, G. M. , Gaddis, B. , & Strange, J. M. (2002). Leading creative people: Orchestrating expertise and relationships. Leadership Quarterly , 13 , 705–750.
• Nadler, D. A. , & Tushman, M. L. (1997). Implementing new designs: Managing organizational change. In M. L. Tushman & P. Anderson (Eds.), Managing strategic innovation and change (pp. 595–606). New York: Oxford.
• Naranjo-Gil, D. (2009). The influence of environmental and organizational factors on innovation adoption: Consequences for performance in public sector organizations. Technovation , 29 (12), 810–818.
• Nelson, R. , & Winter, S. (1982). An evolutionary theory of economic change . Cambridge, MA: Harvard University Press.
• Nord, W. R. , & Tucker, S. (1987). Implementing routine and radical innovations . Lexington, MA: Lexington Books.
• OECD (2005). Oslo manual: The measurement of scientific and technological activities. Paris: OECD.
• Pelz, D. C. (1956). Some social factors related to performance in a research organization. Administrative Science Quarterly , 1 (3), 310–325.
• Pelz, D. C. , & Andrews, F. M. (1966). Scientists in organizations: Productive climate for research and development . New York: Wiley.
• Pfeffer, J. (1993). Barriers to the advance of organizational science: Paradigm development as a dependent variable. Academy of Management Review , 18 , 599–620.
• Piketty, T. (2014). Capital in the twenty-first century . Cambridge, MA: Harvard University Press.
• Poole, M. S. (1981). Decision development in small groups I: A comparison of two models. Communication Monographs , 48 , 1–24.
• Poole, M. S. (1983). Decision development in small groups II: A study of multiple sequences in decision-making. Communication Monographs , 50 , 206–232.
• Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. New York: Free Press.
• Roberts, E. B. (1988). Managing invention and innovation. Research Management , 31 , 11–29.
• Roberts, P. W. , & Amit, R. (2003). The dynamics of innovative activity and competitive advantage: The case of Australian retail banking, 1981 to 1995. Organization Science , 14 , 107–122.
• Rogers, E. M. (1995). Diffusion of innovations . New York: Free Press.
• Rosenberg, N. (1982). Inside the black box: Technology and economics . London: Cambridge University Press.
• Rosenbusch, N. , Brinckmann, J. , & Bausch, A. (2011). Is innovation always beneficial? A meta-analysis of the relationship between innovation and performance in SMEs. Journal of Business Venturing , 26 , 441–457.
• Ross, P. F. (1974). Innovation adoption by organizations. Personnel Psychology , 27 (1), 21–47.
• Sanidas, E. (2005). Organizational innovations and economic growth: Organosis and growth of firms, sectors, and countries . Cheltenham, U.K.: Edward Elgar.
• Sapprasert, K. , & Clausen, T. H. (2012). Organizational innovation and its effects. Industrial and Corporate Change , 21 (5), 1283–1305.
• Schendel, D. , Ansoff, I. , & Channon, D. (1980). Statement of editorial policy. Strategic Management Journal , 1 (1), 1–5.
• Schilling, M. A. (2013). Strategic management of technological innovation . New York: McGraw-Hill Irwin.
• Schroeder, R. G. , Linderman, K. , Liedtke, C. , & Choo, A. S. (2008). Six sigma: Definition and underlying theory. Journal of Operations Management , 26 , 536–554.
• Schumpeter, J. A. (1934). The theory of economic development . Cambridge, MA: Harvard University Press.
• Schumpeter, J. A. (1983). The theory of economic development . New Brunswick, NJ: Transaction Publishers.
• Schumpeter, J. A. (1950). Capitalism, socialism and democracy . New York: Harper & Row.
• Scott, W. R. (1992). Organizations: Rational, natural and open systems . Englewood Cliffs, NJ: Prentice-Hall.
• Scott, S. G. , & Bruce, R. A. (1994). Determinants of innovative behavior: A path model of individual innovation in the workplace. Academy of Management Journal , 37 , 580–607.
• Sears, G. J. , & Baba, V. V. (2011). Toward a multistage, multilevel theory of innovation. Canadian Journal of Administrative Sciences , 28 , 357–372.
• Shane, S. , & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review , 25 , 217–226.
• Starbuck, W. H. (2016). 60th anniversary essay: How journals could improve research practices in social sciences. Administrative Science Quarterly , 61 (2), 165–183.
• Stata, R. (1989). Organizational learning: The key to management innovation. Sloan Management Review , 30 , 63–74.
• Staw, B. , & Epstein, L. (2000). What bandwagons bring? Effects of popular management techniques on corporate performance, reputation, and CEO pay. Administrative Science Quarterly , 45 (3), 523–556.
• Stevenson, H. H. , & Jarillo, J. C. (1990). A paradigm of entrepreneurship: Entrepreneurial management. Strategic Management Journal , 11 (S): 17–27.
• Sturdy, A. (2004). The adoption of management ideas and practices. Management Learning , 35 (2), 155–179.
• Teece, D. J. , Pisano, G. , & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal , 18 , 509–533.
• Tether, B. S. , & Tajar, A. (2008). The organizational-cooperation mode of innovation and its prominence amongst European service firms. Research Policy , 37 , 720–739.
• Tidd, J. (2001). Innovation management in context: Environment, organization and performance. International Journal of Management Review , 3 (3), 169–183.
• Tornatzky, L. G. , & Fleischer, M. (1990). The process of technological innovation . Lexington, MA: Lexington Books.
• Tornatzky, L. G. , & Klein, K. J. (1982). Innovation characteristics and innovation adoption–implementation: A meta-analysis of findings. Transactions on Engineering Management , 29 (1), 28–45.
• Trist, E. , & Murray, H. (1993). The social engagement of social science: A Tavistock anthology, Vol. 1: The social-psychological perspective . Philadelphia: University of Pennsylvania Press.
• Tsang, E. W. K. , & Kwan, K. (1999). Replication and theory development in organizational science: A critical realistic perspective. Academy of Management Review , 24 , 759–780.
• Tushman, M. L. , & Anderson, P. (1986). Technological discontinuities and organizational environments. Administrative Science Quarterly , 31 , 439–465.
• Tushman, M. L. , & O’Reilly, C. A. (2002). Winning through innovation . Boston: HBS Press.
• Utterback, J. M. (1994). Mastering the dynamics of innovation . Cambridge, MA: Harvard Business Press.
• Vaccaro, I. G. , Jansen, J. J. P. , Van Den Bosch, F. A. J. , & Volberda, H. (2012). Management innovation and leadership: The moderating role of organizational size. Journal of Management Studies , 49 (1), 28–51.
• Van de Ven, A. H. , Angle, H. L. , & Poole, M. S. (1989). Research on the management of innovation: The Minnesota studies . New York: Oxford University Press.
• Van de Ven, A. H. , & Rogers, E. M. (1988). Innovations and organizations. Communication Research , 15 , 632–651.
• Van Den Bosch, F. A. J. , Volberda, H. W. , & de Boer, M. (1999). Coevolution of firm absorptive capacity and knowledge environment: Organizational forms and combinative capabilities. Organization Science , 10 , 551–568.
• Volberda, H. W. , Van Den Bosch, F. A. , & Heij, C. V. (2013). Management innovation: Management as fertile ground for innovation. European Management Review , 10 (1), 1–15.
• Volberda, H. W. , Van Den Bosch, F. A. , & Mihalache, O. R. (2014). Advancing management innovation: Synthesizing processes, levels of analysis, and change agents. Organization Studies , 35 (9), 1245–1264.
• Von Bertalanfy, L. (1951). General system theory: A new approach to unity of science, Human Biology , 23 , 303–361.
• Von Bertalanfy, L. (1968). General system theory: Foundations, development, applications . New York: G. Braziller.
• Wade, J. (1996). A community-level analysis of sources and rates of technological variation in the microprocessor market. Academy of Management Journal , 39 (5), 1218–1244.
• Walker, R. M. (2008). Empirical evaluation of innovation types and organizational and environmental characteristics: Towards a configuration approach. Journal of Public Administration Research and Theory , 18 , 591–615.
• Walker, R. , Chen, J. , & Aravind, D. (2015). Management innovation and firm performance: An integration of research findings, European Management Journal , 33 (5), 407–422.
• Walker, R. M. , Damanpour, F. , & Devece, C. A. (2011). Management innovation and organizational performance: Mediating role of planning and control. Journal of Public Administration Research and Theory , 21 , 367–386.
• West, M. A. , & Anderson, N. R. (1996). Innovation in top management teams. Journal of Applied Psychology , 81 , 680–693.
• West, M. A. , & Farr, J. L. (1990). Innovation and creativity at work . New York: Wiley.
• Whittington, R. , Pettigrew, A. , Peck, S. , Fenton, E. , & Conyon, M. (1999). Change and complementarities in the new competitive landscape: A European panel study, 1992–1996. Organization Science , 10 , 583–600.
• Wischnevsky, J. D. , & Damanpour, F. (2006). Organizational transformation and performance: An examination of three perspectives. Journal of Managerial Issues , 18 , 104–128.
• Wischnevsky, J. D. , Damanpour, F. , & Mendez, F. (2011). Influence of environmental factors and prior changes on the organizational adoption of changes in products and in technological and administrative processes. British Journal of Management , 22 (1), 132–149.
• Wolfe, R. A. (1994). Organizational innovation: Review, critique, and suggested research directions. Journal of Management Studies , 31 , 405–431.
• Woodman, R. W. , Sawyer, J. E. , & Griffin, R. W. (1993). Toward a theory of organizational creativity. Academy of Management Review , 18 (2), 293–321.
• Zajac, E. J. , Kraatz, M. S. , & Bresser, R. K. F. (2000). Modeling the dynamics of strategic fit: A normative approach to strategic change. Strategic Management Journal , 21 , 429–453.
• Zaltman, G. , Duncan, R. , & Holbek, J. (1973). Innovations and organizations . New York: Wiley.
• Zammuto, R. F. , & Connolly, T. (1984). Coping with disciplinary fragmentation. Organizational Behavior and Teaching Review , 9 , 30–37.

1. As research on innovation in organizations has developed in the second half of the 20th century, this article focuses on a more recent understanding of innovation as a concept in business and management. For a historical evolution of innovation as a term, label, action, goal, and concept across multiple disciplinary fields see Godin ( 2008 , 2014 , 2015a ).

2. It should be noted that this is Schumpeter’s most commonly cited definition of innovation. He has offered other definitions such as new combinations of the means of production or change in the inputs or outputs of production. For details see Godin ( 2008 , pp. 35–36) and Godin ( 2014 , pp. 13–15). Also, Schumpeter’s fifth innovation type—defined as “the carrying out of the new organization of any industry, like the creation of a monopoly position . . . or the breaking up of a monopoly position” (Schumpeter, 1983 , p. 66)—is not synonymous with organizational innovation as defined in this article.

3. Since Schumpeter’s early work in the beginning of the 20th century, it is generally viewed that innovation is a positive force not only for its producers but for the society as well. Yet, productivity growth has been mainly an outcome of automation, and the extent to which economic wealth spreads beyond entrepreneurs and corporations to the society at large is uncertain. For example, two recent economic analyses question the continued validity of the ripple-down of economic wealth (Gordon, 2016 ; Piketty, 2014 ).

4. For example, Lam ( 2005 ) classifies three perspectives: organizational structure and design; organizational cognition and learning; and organizational change and adaptation. In the context of organizational transformation and performance, Wischnevsky and Damanpour ( 2006 ) also offer three perspectives: rational and performance gap; population ecology and the liability of newness; and institutionalism and the mimetic pressure. Crossan and Apaydin ( 2010 ) listed five sets of theoretical perspectives used in the highly cited articles in their review: institutional; economics and evolution; network; resource-based view and dynamic capabilities; and learning, knowledge management, adaptation, and change.

5. Many studies either do not clearly identify the type of innovation or focus on product and process innovations. For example, Crossan and Apaydin’s ( 2010 , p. 1162) review of 524 articles on innovation published in 10 business and economic journals found that 50% of the articles were unclear or did not identify the type of innovation that was studied, and 39% were related to technology, product/service, and process innovations.

6. Godin ( 2008 , p. 8) offers the conjunction of two primary factors for the prominence of technological innovations: (1) the culture of thing, and industrial development through technology; and (2) the influence of the (academic) conceptual frameworks of technology on policies for economic growth. For more detailed aggregation of these factors see Godin ( 2008 , pp. 19–22).

7. Indeed, Woodman et al.’s ( 1993 ) propositions regarding the effects of slack resources, internal and external communication, and organic structure on organizational creative performance (production of organizational creativity) are similar to the effects of these factors on innovation as found in the studies of innovations in organizations (see Damanpour & Aravind, 2012b ).

8. Similarly, Godin ( 2008 ) in his historical analysis of the emergence of innovation as a concept suggests that the view of innovation as a novel or new idea, artifact, or behavior has emerged in order to resolve the tension between invention —the process of coming up with new ideas (generation)—and imitation —the process of putting those ideas into positive practice (adoption).

9. A parallel order can be offered for social technologies: social technology → social innovation → social change. Social change , change at the level of society including both economic and social/cultural domains, could be the outcome or the results of both technological and nontechnological changes. Like technological change, it is a higher concept than innovation and is not a focus of this article.

10. The innovation process can be conceived to follow a unitary or a multiple sequence pattern (Poole, 1981 ). The unitary sequence pattern generally assumes that the process is orderly and occurs in a linear sequence; the multiple sequence pattern assumes that the process is more random and the stages and the sequence of their occurrence cannot be predicted (Gopalakrishnan & Damanpour, 1994 ). Both patterns have been found useful in describing the innovation process in organizations. However, the multiple sequence pattern is more applicable to studies of innovating ; the unitary sequence pattern to the studies of innovativeness .

11. When an organization develops innovations for its own use, usually one unit (R&D, product development, design) develops and another unit (manufacturing, marketing, human resources) uses the innovation.

12. At the level of innovation, the process includes three sequential phases: generation, diffusion, and adoption. Diffusion is a process in which an innovation is communicated through certain channels among the members of a social system (Rogers, 1995 ). Diffusion connects generation to adoption, is studied at the level of population, and is not viewed as an organizational process. Hence, it is not discussed in this article.

13. Damanpour and Schneider ( 2006 ) consider adoption decision as a separate phase that includes evaluating the proposed ideas from technical, financial and strategic perspectives, making the decision to accept an idea as the desired solution and allocating resources for its acquisition, alteration, and assimilation. It is the phase in which organizational leaders (managers, committees, boards) decide to adopt the innovation and allocate resources to it.

14. As is common in economics, Meeus and Edquist ( 2006 ) use the term organizational innovation to refer to nontechnological innovations, whether product or process. In this article, the term organizational innovation refers to both technological and nontechnological innovations that organizations generate or adopt.

15. In management, organizational innovation is understood in two ways. In a more specific way, it means nontechnological, managerial innovation (Damanpour & Aravind, 2012a ). In a broader way, as in this article, it refers to innovations in organizations, whether technological or nontechnological (Crossan & Apaydin, 2010 ; Damanpour, 1991 ; Lam, 2005 ).

16. Innovations in the organization–environment relations are referred to as ancillary innovations (Damanpour, 1987 ). Ancillary innovations pertain to working with and learning from partners (service providers, suppliers, clients, customers, public agencies, and professional and educational institutions) across organizational boundaries (Černe et al., 2016 ; Damanpour, 1987 ; Tether & Tajar, 2008 ). They are a type of nontechnological innovation (Černe et al., 2016 ), and resemble Tether and Tajar’s ( 2008 ) organization–cooperation mode of innovation.

17. A fourth dimension—attributes or characteristics of innovation—is also used in innovation research to predict the speed of diffusion and/or the rate of adoption of innovation in social systems. Wolfe ( 1994 ) provided definitions of 18 attributes and identified approximately 20 more with different names but similar definitions. Rogers ( 1995 ) identified five primary innovation attributes, of which four (relative advantage, compatibility, trialability, and observability) positively, and one (complexity) negatively affect the adoption of innovation. In a quantitative review of the innovation attribute–adoption relationship from 75 studies, Tornatzky and Klein ( 1982 ) found that compatibility, relative advantage, and complexity had the most consistent significant relationships with innovation adoption. The level of analysis of innovation attributes research is primarily the innovation, not the organization.

18. Camisón et al.’s review included 87 correlations from 53 studies. In an earlier and smaller meta-analysis (36 correlations, 20 original studies), Damanpour ( 1992 ) found a larger magnitude of mean correlation between size and innovation (r=.32, p<.05, p. 384). The low magnitude of the mean correlation in Camisón et al.’s ( 2004 ) analysis can be attributed to the greater diversity of measurements of size and innovation in the original studies.

19. This finding is similar to the finding from Rosenbusch et al.’s ( 2011 ) meta-analytical review of 42 articles on the innovation–performance relationship in SMEs. The original articles in the two reviews do not overlap because the selection procedure in the two reviews differs. Rosenbausch et al.’s original studies include merely technological innovations; innovation types in Walker et al.’s ( 2015 ) original studies are more varied. While Rosenbusch et al.’s review subscribes to the first-mover advantage view of innovation and performance, Walker et al.’s review falls mainly within the performance gap view.

20. For example, a TQM program has many elements such as service design, employee involvement, customer focus, and so on (Schroeder et al., 2008 , p. 547). An organization may choose to adopt a couple of these elements only or adopt some of them initially and others at a later time.

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• Published: 16 October 2023

Knowledge sharing and innovation performance: a case study on the impact of organizational culture, structural capital, human resource management practices, and relational capital of real estate agents

• Chung-Chang Lee   ORCID: orcid.org/0000-0001-9984-2002 1 ,
• Wen-Chih Yeh 2 ,
• Zheng Yu 3 &
• Yuan-Chen Luo 1  

Humanities and Social Sciences Communications volume  10 , Article number:  707 ( 2023 ) Cite this article

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• Theatre and performance studies

This study focused on the factors that influence innovation performance in housing agents. Based on a worldwide literature review on the topic of innovation performance, we defined relational capital, knowledge sharing at the individual level, and organizational culture, structural capital, and human resource management practices at the organizational level to carry out the analysis using hierarchical linear modeling. The survey subjects were housing agents in Kaohsiung City, Taiwan. A total of 1130 questionnaires were distributed to 113 agencies. Of a total of 444 collected surveys, 40 unanswered questionnaires were invalid and three with fewer than three answers were eliminated. The final number of valid questionnaires was 401. The response rate of effective questionnaires was 35.49%. The results show that organizational culture can indirectly affect innovation performance through knowledge sharing, indicating that there is a partial mediating effect. Structural capital can indirectly affect innovation performance through knowledge sharing, demonstrating a complete mediating effect. Relational capital can indirectly affect innovation performance through knowledge sharing, having a partial mediating effect. Human resource management practices did not have a confounding effect on innovation performance.

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Introduction.

Innovation performance reflects an organization’s ability to transform innovation inputs into outputs and to acquire achievements and outcomes through the innovation process. Wang and Lee ( 2018 ) regarded innovation strategies as applying innovation to maximize an enterprise’s value. West and Anderson ( 1996 ) pointed out that innovation is crucial to social or organizational development and advancement. Innovation performance includes employee growth, team cohesion, effective internal communication, and continuous improvements in other related performances. In the technology sector, Ma et al. ( 2023 ) showed that innovation performance can be better generated when companies proactively accept external information and engage in intra-organizational knowledge transfer with the acquired information. Taking a service-oriented approach, Yiu et al. ( 2020 ) suggested that innovation performance can be enhanced through mutual learning, in which knowledge sharing and transfer occur between partners within an organization.

These arguments highlight the importance of innovation performance in various industries.

Most of the research on innovation performance in the real estate agency industry is centered on the financial and service aspects (Hameed et al., 2021 ; Rajapathirana and Hui, 2018 ). The financial aspect is measured through various factors, including performance-based bonuses, business performance, the number of transactions, and organizational financial status (see Yu and Liu, 2004 ; Lee and You, 2007 ; Meslec et al., 2020 ). Real estate agents aim toward achieving strong individual performances for the sake of their own bonuses (Mallik and Harker, 2004 ; Bradler et al., 2019 ; Manzoor et al., 2021 ; Lee et al., 2023 ). The service aspect is measured through factors such as research satisfaction and service quality (see Wu, 1999 ; Wang, 2004 ; Ullah and Sepasgozar, 2019 ; Yeh et al., 2020 ).

In the real estate agency industry, direct sales business operators may adopt the competition strategy of branch cooperation, as the internal systems and organization inside a branch are closely associated. Organizational culture includes the values, forms, and traditions conveyed by the organization to all its members (Ouchi, 1981 ). Narver and Slater ( 1990 ) suggested that organizational culture can be measured through the three components of market orientation: customer orientation, competitor orientation, and interdepartmental coordination. Lee and Sheng ( 2022 ) suggested that shared beliefs, expectations, values, norms, and routine tasks influence the relationship and methods of cooperation between organizational members, effectively creating different organizational values. Since the real estate agency industry is a part of the service industry, having a customer orientation is conducive to improving the quality of interactions between employees and customers (Bitner et al., 1994 ; Bowen and Schneider, 1985 ). Interdepartmental coordination is also associated with the human resources within the organization. Competition among enterprises has intensified in response to globalization, which highlights the importance of human resource management. In this 21st-century global economy driven by services, knowledge, technology, innovation, and globalization, human resource management (HRM) remains among the main models of competition management in local and foreign companies as well as emerging or established markets (Thite, 2015 ). Dessler ( 2000 ) stressed the importance of HRM for an enterprise. The functions of HRM include talent recruitment and selection, promotion and allocation, training and development, remuneration and benefits, labor relations, employment security, and labor safety. Well-executed HRM practices allow employees to improve organizational cohesion, teamwork, and organizational climate through self-directed work teams, inter-team cooperation, decision-making authorization, trustworthy organizational communications, and flexible management (Evans and Davis, 2005 ). To accurately and effectively allocate and leverage human resources, the real estate agency industry must rely on productive HRM practices (Wu, 2007 ). Therefore, adopting suitable HRM practices effectively improves elements such as employee training and development procedures (periodically arranging suitable internal and external training programs), performance evaluation (firm-specific evaluation criteria), and compensation and benefit packages (merit pay). Consequently, employees effectively enhance their innovative behavior at the individual and organizational levels through knowledge sharing, thus reducing their turnover (Hsu et al., 2021 ).

This study seeks to examine whether HRM evokes employees’ enthusiasm toward their jobs through motivational human resource activities such as human resource planning, training and development, remuneration and benefits, and employee relations, thereby increasing knowledge sharing and innovation performance within the organization. Additionally, it investigates whether the value generated from intangible intra-organizational assets and knowledge is key to an enterprise’s success. Such intangible assets and knowledge-creation mechanisms are collectively known as structural capital (Chen, 2007 ). Excellent structural capital not only improves an organization’s value but is also conducive to its development and enables it to gain continuous competitive advantages that can be converted into higher performances (Bontis et al., 2000 ; De Pablos, 2004 ). Structural capital includes an organization’s internal creativity and encompasses the development of new products, trade secrets, patents, and so on, which are also referred to as innovation capital. An organization’s internal infrastructure, including its management fad, corporate culture, management procedures, and information systems, is also known as process capital and represents major assets of structural capital (Saswat, 2018 ).

Moreover, real estate agent services are closely associated with the people involved. Of the personal relationship factors, relational capital is among the most important traits that real estate agents should possess. There are four types of intellectual capital: human capital, innovation capital, organizational capital, and relational capital (Tseng and Goo, 2005 ). In particular, relational capital refers to relationships that involve interpersonal trust and mutual identification (Cabrera and Cabrera, 2005 ). Numerous researchers have emphasized the important role of relational capital-associated factors in an organization’s business performance (Kogut and Zander, 1996 ; Uzzi, 1996 ; Saswat, 2018 ). Employees’ willingness to share knowledge is also based on the beliefs and behaviors associated with strong social interactions (Kim et al., 2013 ). Knowledge sharing is the mutual learning and understanding promoted through interaction and conversation between people (Lin and Wang, 2005 ). Knowledge sharing is crucial for externalizing individual knowledge within the organization, ensuring that employees who require such knowledge can effectively execute their work tasks. In other words, knowledge sharing is the transmission of knowledge to others anywhere, anytime (Wu and Lin, 2007 ). Several barriers also exist to knowledge sharing and organizational innovation. Firstly, an employee who feels that knowledge sharing is tedious and time-consuming may choose to hide knowledge so that they can save time and focus on their own tasks. Next, some knowledge is essentially confidential or sensitive information (such as personal connections or the knowledge to perform a task), and an employee can retain their competitive advantage by hiding this knowledge. Lastly, employees may worry that others will be skeptical of or criticize them for the knowledge that they share (Chen and Chen, 2022 ). Based on these arguments, we posit that individual relational capital is a key factor that affects personal knowledge sharing and innovation performance.

This study focused on organizational culture among real estate agents. Organizational culture can be described as a meaningful system with complex and profound effects. The complex and profound effects of organizational culture are mainly displayed through morals and values (Ke and Wei, 2008 ). Organizational culture is the sharing of values or beliefs to regulate the behaviors of organizational members (Geiger, 2017 ). For an enterprise or organization, human resources are an important internal resource while structural capital is a key internal element that creates value (Robbins, 2006 ). Previously, few studies within Taiwan and abroad have investigated the organizational level variables of organizational culture, structural capital, and HRM practices collectively. Unlike previous studies, this study examined the influence of these variables on knowledge sharing and innovation performance. In essence, relational capital, as part of intellectual capital, emphasizes connections with the external environment (Bontis, 1999 ). In this study, we categorized relational capital, knowledge sharing, and innovation performance as individual-level variables and collectively examined them alongside the aforementioned organizational-level variables. The goal was to investigate whether these two levels of variables positively affect innovation performance. Additionally, we considered HRM practices as a confounding variable that affects the influence of knowledge sharing on innovation performance.

Real estate agencies in Taiwan are commonplace. Countless real estate agency branches can be found nationwide, where many frontline real estate agents carve out their careers. In the past, the real estate industry in Taiwan was notorious for its sales tactics that often resulted in disputes. After the promulgation of the Real Estate Broking Management Act in 1999, the industry became professionally institutionalized. Due to the impacts of economic downturns, real estate agencies in recent years have turned to marketing their own brands. The industry adopted an atypical compensation scheme, based on commission. The industry is also known for its long work hours, challenging tasks, and high turnover. Thus, the means to enhance its innovation performance has gained much interest in academia and industry, most of which is directed at the organization’s internal business and management models. The influences of organizational culture, structural capital, HRM practices, relational capital, and knowledge sharing on innovation performance can shed light on the intra-organizational modes of operation of a real estate company, thus enabling research on and evaluation of the innovation performance of different industries.

Literature review and research hypotheses

Thanks to technological advancements, millennials (the demographic cohort currently aged 29 to 35 years) prefer to acquire consumer-related information from online platforms and visit physical stores after receiving marketing information online (Chang et al., 2023 ). As the popularity of artificial intelligence (AI) and the platform economy grows, the real estate agency industry has developed its own strategy, called property technology (PropTech), in response to technological advancements. PropTech refers to the consolidation of technology and real estate, whereby various emerging information and communications technologies are introduced into various fields of the real estate industry, enhancing the business efficiency of the overall industry and opening up new opportunities for innovative developments (Kuo, 2022 ). Lin ( 2021 ) identified several impacts of PropTech on the real estate agency industry: 1. Enhancing the efficiency of real estate transactions by increasing the convenience of acquiring information by sellers and buyers; 2. Providing new information rapidly and promoting transactions, such as generating empathetic responses through virtual reality settings in online platforms; 3. Unbundling real estate agents’ work tasks, in which traditional full-service tasks are split into several smaller ones, such as assigning dedicated personnel to assist house sellers or handling the company’s online business. This strategy provides a new stage for knowledge sharing and innovation in the business. This study will analyze the relationships between organizational culture and other internal factors in the industry.

The essence of organizational innovation is the means to effectively and adequately foster an excellent organizational culture that positively and significantly influences its performance (Daft, 2004 ; Lemon and Sahota, 2004 ). Hurley and Hult ( 1998 ) found that an organizational culture rooted in innovation can provide the organizational resources to help the organization leverage innovation to their advantage for progress. Organizational innovation is a part of organizational culture and is the precursor to innovation. Shahzad et al. ( 2017 ) revealed that organizational innovation performance is supported and influenced by organizational culture. Deal and Kennedy ( 1984 ) pointed out that a well-performing enterprise must have an excellent organizational culture as it is the main reason behind organizational innovation performance. Srisathan et al. ( 2020 ) examined the influence of organizational culture on open innovation performance using a sample of 300 Thai and Chinese small and medium-sized enterprises (SMEs). They demonstrated the significant influence of organizational culture on innovation performance concerning marketing, operations, customer orientation, and capital management. Aboramadan et al. ( 2020 ) contended that organizational culture positively influences market innovation and technology innovation. Srisathan et al. ( 2020 ) argued that organizational culture positively influences innovation performance through organizational sustainability. We propose H1 as follows:

H1: Organizational culture has a significant and positive influence on innovation performance .

Edvinsson and Malone ( 1997 ) described structural capital as an intangible organizational asset that cannot be taken away by employees when they resign. Furthermore, structural capital reflects an organization’s ability to function as one and is made up of organizational capital, process capital, and innovation capital. De Pablos ( 2004 ) observed that structural capital improves organizational value. Lin et al. ( 2011 ) conceptualized structural capital as an organization’s capacity to solve problems and create value in its general systems and procedures. Consequently, structural capital improves an organization’s competitiveness and innovation performance. Structural capital also reflects the mechanisms and capabilities within an organization that allow it to integrate and utilize all of its resource production procedures. Organizations need to apply for legal protection and patents for the components of structural capital, such as manufacturing processes, trade secrets, and business secrets. The core of structural capital is the common knowledge that is retained in the organization after an employee begins their tenure (Grasenick and Low, 2004 ; Roos et al., 1997 ). Ji et al. ( 2017 ) argued that structural capital positively affects innovation performance directly and indirectly (through intellectual capital). When examining the associations between structural capital and performance in the Mexican and Peruvian public administrations, Pedraza et al. ( 2022 ) found that structural capital is an intangible asset for public and private organizations because it positively and significantly affects organizational resources, capacities, and innovation performance. Therefore, organizations must establish their internal structural capital management strategies to improve innovation performance at the individual and organizational levels.

On this basis, structural capital is conducive to an enterprise’s innovation performance. We propose H2 as follows:

H2: Structural capital has a significant and positive influence on innovation performance

Relational capital refers to an organization’s establishment, maintenance, and development of relationships with its customers, suppliers, and partners (Molyneux, 1998 ). Bontis ( 1998 ) suggested that customer-based relationship capital represents the potential ability of an organization to own external intangible assets and is embedded within the organization’s external customer relationships. Tu ( 2009 ) demonstrated that relational capital positively influences knowledge integration, which in turn positively and significantly influences innovation performance. Nonaka and Takeuchi ( 1995 ) contend that knowledge innovation stems from interpersonal interactions; exchanges between organizational members promote the creation of innovative knowledge and thereby trigger innovation performance. Onofrei et al. ( 2020 ) studied the influence of relational capital on innovation performance in supply chains using a sample of 557 manufacturing plants across 10 countries. The results showed that suppliers and customers who build strong relational capital effectively enhanced the company’s innovation performance, which is also the best way to maintain one’s competitive advantage in the global supply chain. Onofrei et al. ( 2020 ) found that relational capital positively affects innovation performance. Duan et al. ( 2023 ) suggested that relational capital positively affects innovation performance through trust, reciprocity, and transparency. We propose H3 as follows:

H3: Relational capital has a significant and positive influence on innovation performance

Calantonea et al. ( 2002 ) argued that when an organization creates an environment that is highly conducive to learning, its innovativeness and innovation performance can be improved through the active knowledge interaction processes. Lin ( 2007 ) revealed that an organization can further achieve innovation through knowledge sharing after it acquires the necessary information. Bavik et al. ( 2018 ) posited that through knowledge sharing, employees are provided the relevant information to help them achieve individual innovation. The results of the study by Perry-Smith and Shalley ( 2003 ) suggested that information exchange and knowledge sharing between team members are positively associated with innovation performance. Shi et al. ( 2022 ) investigated the effects of knowledge sharing, collaborative innovation, and building information modeling (BIM) application on innovation performance in the construction supply chain by creating and validating the rationality of a relationship model entailing all four factors. The relationships between the factors not only were useful for understanding the role of knowledge sharing in collaborative innovation in the construction supply chain but also had positive effects on developing BIM functions. Wang and Hu ( 2020 ) agreed that knowledge sharing positively influences innovation performance. Hanifah et al. ( 2022 ) highlighted that knowledge sharing has a significant impact on firm innovation performance. We propose H4 as follows:

H4: Knowledge sharing has a significant and positive influence on innovation performance

According to Tushman and O’Reilly ( 1996 ), an enterprise should foster an innovative organizational culture, as the values of cultural factors affect behavior, which in turn affects knowledge creation and sharing. McDermott and O’Dell (2001) examined organizational culture and knowledge sharing and found that the core values of an organization must be closely associated with knowledge sharing. An organization would create its own culture of knowledge sharing and convert it into a tangible asset alongside its business objectives. Svelby and Simons ( 2002 ) stressed that embodying organizational culture during its creation process is conducive to knowledge sharing. Caruso ( 2017 ) suggested that knowledge sharing is the sharing of information, techniques, and professionalism between organizational members; it is a valuable intangible asset and is affected by organizational culture. Earl and Scott ( 1999 ) showed that creating a culture that is conducive to the promotion of knowledge sharing within the organization improves knowledge acquisition skills at the individual and aggregate levels, thus significantly increasing knowledge value. Gooderham et al. ( 2022 ) used the ability, motivation, and opportunity (AMO) approach to examine how organizational culture and national culture affect knowledge sharing in multinational enterprises. The research encompassed 11 countries and regions in northern, central, and eastern Europe and southeast Asia. A questionnaire was administered to 11,484 people employed in 1235 departments. The results showed that organizational and natural cultures were both important factors for understanding knowledge sharing due to their positive influences. Knowledge sharing is conducive to understanding the intrinsic motivations of employees, and managers can broaden its range through organizational culture, thus promoting long-term organizational development. We propose H5 as follows:

H5: Organizational culture has a significant and positive influence on knowledge sharing

Joia ( 2000 ) pointed out that structural capital comprises the structure and strategies necessary for an organization to function, and its influence is realized through the organization’s internal operations. Bontis ( 1999 ) classified intellectual capital as human resource capital, structural capital, and relational capital, and investigated ways to associate between internal organizational knowledge and the external environment. Yli-Renko et al. ( 2001 ) suggested that individual members who hold advantageous positions in their organizations can help their organizations accumulate knowledge and assets through knowledge sharing. This imperceptibly improves the knowledge and competence of other employees and leaders, and their sharing behaviors become conducive to organizational growth. Kim and Shim ( 2018 ) found that the density of social capital, including structural capital, has a positive influence on knowledge sharing between small and medium enterprise employees. In a study on the influence of social capital on knowledge sharing in online user communities, Yan et al. ( 2019 ) highlighted a significant bidirectional relationship between social capital (structural, cognitive, and relational) and knowledge sharing, mainly manifested in the knowledge sharing behaviors of core participants in the community. Structural capital positively influences knowledge sharing through expansion and conversion. We propose H6 as follows:

H6: Structural capital has a significant and positive influence on knowledge sharing

McFadyen and Cannella ( 2004 ) pointed out that the strength of the relations in relational capital influences knowledge sharing and innovation. Hooff and Huysman ( 2009 ) revealed that relational capital positively influences knowledge sharing. Lai ( 2013 ) found that the stronger the relationships (the higher the relational capital), the more likely employees are to exhibit cooperative behaviors and promote knowledge sharing. Kim et al. ( 2013 ) demonstrated a strong association between relational social capital and knowledge sharing. Allameh ( 2018 ) described the three dimensions of social capital as structural, relational, and perceptional social capital, all of which positively affect knowledge sharing. Qiao and Wang ( 2021 ) opined that relational capital concurrently positively influences explicit knowledge sharing and tacit knowledge sharing. Hanifah et al. ( 2022 ) examined relational capital, knowledge sharing, and innovation performance in the Malaysian manufacturing sector. They identified internal and external relational capital as determinants of innovation performance against the backdrop of the competitiveness and survivalist challenges of the manufacturing sector. Knowledge sharing also mediated innovation performance, and relational capital positively influenced knowledge sharing. We propose H7 as follows:

H7: Relational capital has a significant and positive influence on knowledge sharing

Valle et al. ( 2000 ) argued that human resource training should be in line with corporate strategies in order to achieve optimal organizational performance. An enterprise that adopts innovative strategies and design training programs that correspond to these innovative strategies can enhance their innovation performance. Enterprises can improve employees’ knowledge, skills, and competence by managing specific human resources, thus improving their employees’ contributions to the organization and further enhancing innovation performance (Valle et al., 2000 ; Youndt and Snell, 2004 ). According to research, human resource management practices include providing authorization to employees, encouraging employee engagement, and enhancing organizational innovation (Garaus et al. 2016 ). Human resource management activities play a key role in improving market share, individual activeness, and service innovation (Anderson et al. 2014 ; Ardito and Messeni, 2017 ). Using a sample of 129 companies, Papa et al. (2020) examined the effects of knowledge acquisition, employee retention, and HRM practices on innovation performance. The results showed that companies are under immense pressure due to increasing innovation models and means of knowledge acquisition. Leaders who can promptly adapt to such external changes can consolidate the HRM practices of their company, thereby reducing employee turnover and promoting innovation performance. We propose H8 as follows:

H8: Human resource management practices have a significant and positive influence on innovation performance

To enhance employees’ knowledge, skills, and competence, enterprises can leverage the managerial strengths of specified human resources, thereby strengthening employees’ contributions to the organization and subsequently to organizational performance (Sanz-Valle et al., 1999 ; Youndt and Snell, 2004 ). Schneider and Reichers ( 1983 ) mentioned that positive interactions between organizational members create an environment conducive to information sharing within the organization. This environment allows high-performing employees to enhance their leadership skills, thus improving organizational performance through employees’ awareness of knowledge sharing. A team’s ability to showcase their performance or achieve knowledge sharing and innovation depends on the degree to which their organization’s human resource management effectively stimulates team operations (McHugh, 1997 ). Papa et al. ( 2020 ) demonstrated the positive effects of knowledge sharing on innovation performance, while HRM enhances the relationship between knowledge sharing and innovation performance. Regarding the positive effects of knowledge sharing on innovation performance, studies have also shown that the influence of knowledge sharing on innovation performance is moderated by the HRM practices adopted (Kim and Park, 2017 ; Jada Mukhopadhyay and Titiyal, 2019 ). Haq et al. ( 2021 ) examined the influence of HRM practices on knowledge sharing and innovation performance in 213 manufacturing plants in China. The results showed that HRM practices indeed influence knowledge sharing, and knowledge sharing directly influences innovation performance. Supplier knowledge sharing complements intra-organizational knowledge sharing, and HRM practices interfere with the relationship between knowledge sharing and innovation performance. We propose H9 as follows:

H9: The influence of knowledge sharing on innovation performance is moderated by HRM practices

Regarding mediation effects, we have proposed three hypotheses about knowledge sharing as a mediator variable. Firstly, we explained why knowledge sharing was assigned as a mediator variable, followed by proposing the three hypotheses. Bagherzadeh et al. ( 2019 ) examined the influence of outside-in open innovation (OI) on innovation performance while considering the mediating roles of knowledge sharing and innovation strategy. The results revealed that knowledge sharing and innovation strategy fully mediated the relationship between outside-in OI and innovation performance. Hanifah et al. ( 2022 ) studied the influences of intellectual capital and entrepreneurial orientation on innovation performance in SMEs, with knowledge sharing as a mediator. The results showed that human capital, as well as external relational capital, had a positive correlation with both knowledge sharing and innovation performance mediated by knowledge sharing. Hanifah et al. ( 2022 ) studied relational capital, knowledge sharing, and innovation performance in the Malaysian manufacturing sector. They showed that internal and external relational capital were determinants of innovation performance, while knowledge sharing mediated the influence of innovation performance, and relational capital positively influenced knowledge sharing.

The means of creating appropriate and effective organizational culture underpins organizational innovation. Research has demonstrated the positive and significant influence of organizational culture on organizational innovation and innovation performance (Daft, 2004 ; Lemon and Sahota, 2004 ). Shahzad et al. ( 2017 ) revealed that organizational innovation performance is supported and influenced by organizational culture. Sveiby and Simons ( 2002 ) stressed that realizing organizational culture while establishing it is conducive to knowledge sharing. Caruso ( 2017 ) agreed that organizational culture influences knowledge sharing. Bavik et al. ( 2018 ) suggested that employees can acquire the necessary knowledge through knowledge sharing and thus achieve personal innovation. Perry-Smith and Shalley ( 2003 ) revealed that information exchange and knowledge sharing between team members positively influence innovation performance. We propose H10 as follows:

H10: Knowledge sharing mediates the influence of organizational culture on innovation performance.

De Pablos ( 2004 ) demonstrated that good structural capital empowers organizational value. Lin et al. ( 2011 ) defined structural capital as the ability to resolve organizational problems and create value in the organization’s system and procedures as a whole, thus enhancing organizational competitiveness and firm innovation performance. Yli-Renko et al. ( 2001 ) contended that members who hold advantageous positions in the organization’s structural capital framework can contribute to its accumulation of knowledge assets by leveraging sharing environments where leaders and subordinates share knowledge and capabilities. Kim and Shim ( 2018 ) showed that the density of social capital, which includes structural capital, positively influenced knowledge sharing among SME employees. Lastly, knowledge sharing positively and significantly influenced innovation performance. We propose H11 as follows:

H11: Knowledge sharing mediates the influence of structural capital on innovation performance.

Nonaka and Takeuchi ( 1995 ) suggested that interpersonal interactions and exchanges between organizational members generate innovative knowledge and subsequently promote innovation performance. Tu’s (2009) empirical results showed that relational capital positively influences knowledge integration abilities, which positively and significantly influences innovation performance. Moreover, the empirical study by Kim et al. ( 2013 ) demonstrated a strong link between relational social capital and knowledge donation. Allameh ( 2018 ) identified the structural, relational, and cognitive dimensions of social capital, all of which positively influence knowledge sharing. Lastly, knowledge sharing positively and significantly influences innovation performance. We propose H12 as follows:

H12: Knowledge sharing mediates the influence of relational capital on innovation performance.

Study framework

We designed a study framework consisting of a hierarchical linear model for analysis and estimation as shown in Fig. 1 . The main reason for using hierarchical linear modeling is because traditional single-level regression analysis is prone to bias. Wen and Chiou ( 2009 ) pointed out that in the traditional approach, organizational level and individual level variables are placed into a single regression model, which likely violates the assumption of independence. The standard error of the estimated regression coefficient analyzed through traditional regression analysis is also excessively small and may reject the null hypothesis, resulting in type 1 error inflation. Therefore, hierarchical linear modeling was used for data analysis in this study with the goal of demonstrating the relationships between all the organizational level and individual level variables, as well as the interactions between different levels.

The study framework.

The empirical model

Analytical strategies and levels.

In hierarchical linear mediation analyses, several configurations exist such as 1 → 1 → 1, 2 → 1 → 1, and 2 → 2 → 1 (Krull and MacKinnon, 1999 ). The mediating effect models in this study were the 1 → 1 → 1 and 2 → 1 → 1 configurations. These three numbers represent the independent variable, mediator variables, and outcome variables, respectively. The mediating effect models in this study were (1) organizational culture → knowledge sharing → innovation performance; (2) structural capital → knowledge sharing → innovation performance; and (3) relational capital → knowledge sharing → innovation performance.

In this study, the individual variables (innovation performance and knowledge sharing) were assigned as outcome variables. First, prior to conducting a hierarchical linear analysis, a null model must be used to check for significant differences in the individual innovation performance (PERFORMANCE) and knowledge sharing (KNOWLEDGE), as well as to estimate the amount of between-branch variance that constitutes the total variance in the individual innovation performance and knowledge sharing. The model settings are shown in Eqs. ( 1 ) to ( 2 ):

where PERFORMANCE ij represents the individual innovation performance of the i th person in the j th branch; β 0 j represents the mean innovation performance of the j th branch; r ij indicates the within-group error, with a mean of 0; the variance σ 2 is independent, homogenous, and normally distributed; γ 00 represents the total mean score of the individual innovation performance; u oj represents the difference in the mean individual innovation performance and the total mean score of the individual innovation performance of each branch; u oj is the between-group error, which is independent and has a mean of 0; τ 00 is the variance and is independent, homogenous, and normally distributed; and r ij and u oj are assumed to be independent of each other. We further examined the ICC of the null model ( ICC  =  τ 00 / τ 00  +  σ 2 ) to determine the necessity to perform HLM analysis. Heck and Thomas ( 2009 ) suggested that HLM can be used for estimation and analysis when the ICC is greater than or equal to 0.05. The same settings were applied to the knowledge sharing (KNOWLEDGE) null model, and shall not be elaborated on further.

Hierarchical linear mediation model

Based on the construction of the hierarchical linear mediation model, random effects were used to set the Level1 intercept. The mediation models were: (1) Organizational culture → knowledge sharing → innovation performance; (2) Structural capital → knowledge sharing → innovation performance; (3) Relational capital → knowledge sharing → innovation performance. Regarding mediation effect testing, the ordered regression coefficient test proposed by Baron and Kenny ( 1986 ) is a popular method. This study followed Baron and Kenny’s ( 1986 ) three-step test method in which the first step was to test the influence of the independent variables on the dependent variables, namely the influences of organizational culture ( CULTURE ), structural capital ( STRUCTURE ), and relational capital ( RELATION ) on innovation performance ( PERFORMANCE ), as shown in Eqs. ( 3 ) through ( 5 ). The second step was to test the influence of the independent variables on the mediator variables, namely the influences of organizational culture ( CULTURE ), structural capital ( STRUCTURE ), and relational capital ( RELATION ) on knowledge sharing ( KNOWLEDGE ). Lastly, the other variables were included in the model, and the influences of organizational culture ( CULTURE ), structural capital ( STRUCTURE ), HRM practices ( RESOURCE ), relational capital ( RELATION ), and knowledge sharing ( KNOWLEDGE on innovation performance ( PERFORMANCE ) were estimated, as shown in Eqs. ( 9 ) to ( 12 ). Sex ( SEX ), job tenure ( EXP ), and business model ( MANAGE ) were set as control variables. The first step is as follows:

where β 0 j is the Level1 intercept; β 1 j ~ β 3 j represent the coefficients of the Level1 independent variables; γ 00 is the total mean innovation performance; γ 01 is the coefficient of organizational culture ( CULTURE ); γ 02 is the coefficient of structural capital ( STRUCTURE ); μ 0 j is the between-group error, which is independent and has a mean of 0; and τ 00 is the variance and is independent, homogenous, and normally distributed. Fixed effects were applied to Eq. ( 5 ), without a random error. The estimations for Eqs. ( 3 ) through ( 5 ) are presented in Model 1 in Table 3 . If γ 10 , γ 01 , or γ 02 was significant, then the second step was used for estimation.

The estimations for Eqs. ( 6 ) through ( 8 ) are presented in Model 2 in Table 3 . If γ 10 , γ 01 , or γ 02 was significant, then the third step was used for estimation.

The estimations for Eqs. ( 9 ) through ( 12 ) are presented in Model 3 in Table 3 . If γ 20 was not significant, then there were no mediation effects; if γ 20 was significant alongside any of γ 10 , γ 01 , γ 02 , or γ 03 , then there were partial mediation effects; if γ 20 was significant, but γ 10 , γ 01 , γ 02 , or γ 03 , were not, then there were complete mediation effects.

Questionnaire design

The questionnaire in this study consisted of two sections. The first section covered the participants’ basic information, including sex, age, tenure in the real estate agency, and job position. The second section covered items related to the three organizational-level variables (organizational culture, structural capital, and HRM practices) and the three individual-level variables (structural capital, knowledge sharing, and innovation performance).

The items pertaining to organizational culture were designed according to the studies by Schein ( 1993 ), Wilkins and Ouchi ( 1983 ). Organizational culture consists of three sub-dimensions: artifacts, espoused values, and basic assumptions. According to Schein ( 1993 ), artifacts are all the concrete observations of a company, such as language, style, ceremonies, and office settings; espoused values are the common beliefs, ethics, and behavioral norms shared by the organization, which consist of organizational strategies, objectives, philosophies, and values; basic assumptions refer to the unconscious beliefs that organizational members hold and are the original source of values and organizational action that profoundly influence how organizational members perceive, think about, and interact with the world. Each sub-dimension consists of three items, for a total of nine items. Next, the items pertaining to structural capital were designed according to the studies by Edvinsson and Malone ( 1997 ) and Jaw ( 2004 ). Structural capital consists of three sub-dimensions: organizational capital, innovation capital, and process capital. Organizational capital refers to a company’s investments in systems and instruments that enhance the transfer of knowledge inside the organization as well as improve the means to supply and disseminate knowledge. This capital reflects an organization’s ability to systematize, synthesize, and arrange itself and the systems for enhancing production. Innovation capital refers to an organization’s capacity to innovate and protect trade rights, intellectual property, and other intangible assets and its ability to develop and expedite the launch of new products and services. Process capital includes work procedures, special methods, and employee programs for expanding or enhancing product manufacturing or service efficiency. The above sub-dimensions consist of three, three, and two items, respectively, for a total of eight items. The items pertaining to HRM practices were designed according to the studies by Bae et al. ( 1998 ), and Sun et al. ( 2007 ). HRM practices consist of human resource planning, training and development, and remuneration and benefits, and each sub-dimension includes two or three items, for a total of eight items. Finally, the items pertaining to relational capital were designed according to the studies by Sarkar et al. ( 2001 ). Relational capital consists of mutual trust, commitment, and information exchange, and each sub-dimension includes two or three items, for a total of eight items.

The items pertaining to knowledge sharing were designed according to the studies by Spencer ( 2003 ); Hendrinks ( 1999 ); Bock and Kim ( 2002 ); Bock et al. ( 2005 ); Betz ( 1987 ); Subramanian and Nilakanta ( 1996 ); Becerra-Fernandez and Sabherwal ( 2001 ); Nonaka and Takeuchi ( 1995 ). Knowledge sharing was divided into three sub-dimensions: knowledge sharer, knowledge recipient, and knowledge sharing intentions, each consisting of two or three items, for a total of eight items. The items pertaining to innovation performance were designed according to the studies by Amabile ( 1988 ); Drejer ( 2004 ); and Bilderbeek et al. ( 1998 ). Innovation performance consisted of stimulating innovation and service innovation, which included three and two items, respectively, for a total of five items. All items were measured on a five-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). Please refer to Table 1 for the detailed questionnaire items.

Cronbach’s α is currently the most common method of measuring the reliability of each dimension. A Cronbach’s α of greater than 0.8 indicates high reliability (Hair et al., 2011 ), which was the case for all dimensions in this study. As a measure of construct validity, the factor loading of each item in this study was significant, thus validating the construct validity of the scale. We further performed measurements using convergent validity, which is based on the factor loading of each item in each dimension. According to Hair et al. ( 2006 ), a good convergent validity should be greater than 0.5, which was the case in our study.

Data collection, descriptive statistics, and data treatment

Data collection.

Convenience sampling was adopted in this study to survey real estate agents from seven real estate agency chains in Kaohsiung City: Sinyi Realty, HandB Housing, Taiching Realty, Taiwan Realty, Yung Ching Realty, CTBC Real Estate, and U-Trust Realty. The surveyed area consisted of the commercial hubs of Sanmin, Zuoying, Lingya, Gushan, and Xinxing districts. The questionnaire was administered in person to the participants before mid-May 2021, and then via mail after mid-May 2021 because of the COVID-19 pandemic situation. The survey period lasted from May 1 to July 31, 2021. A total of 1130 questionnaires were distributed (530 in person, 600 via mail), and 444 were recovered (115 from Sanmin district, 104 from Zuoying district, 66 from Lingya district, 58 from Gushan district, and 101 from Xinxing district). 40 invalid questionnaires were removed for missing items or no response to sex and tenure. The Level 2 variables were in units of branches, and the variance data were the aggregate of the Level 1 individual data. To ensure representativeness, three questionnaires were removed because their branches had returned less than three responses. This left a total of 401 valid questionnaires, or an effective response rate of 35.49%.

Armstrong and Overton ( 1977 ) proposed the non-response bias test process for examining whether significant differences exist in the response rate in the options for sex, marital status, and education level, which was used in each of the two batches of recovered samples. The non-response bias reflects the consistency between the distribution of the actual recovered samples and the population data structure. We split the 401 recovered samples into two groups based on the code number; the first group consisted of 310 responses recovered in person, and the second consisted of 91 responses recovered via mail. We then tested the differences in the demographic backgrounds (sex, marital status, and education level) of the two groups, but found no significant differences. Thus, no serious non-response bias was found in the questionnaire.

Descriptive statistics

In the valid sample, men accounted for 53.9% (216 participants) of the responses while women accounted for 46.1% (185 participants) of the responses. The largest group of participants (29.5%, 116) were in the 30–40 years age group, followed by those in the 41–50 years age group (27.2%, 107). Regarding marital status, unmarried participants accounted for 47.9% (190) while married participants accounted for 47.6% (189) of the responses. Regarding tenure, the largest percentage of the participants had been working for between one and five years (42.1%, 169), followed by those working for less than a year (23.7%, 95). Regarding income, the largest percentage of participants (22.5%, 88) earned between NT$460,000–600,000, followed by those who earned less than NT$300,000 (18.9%, 74). Regarding job positions, the majority (82.3%, 326) of the participants were salespersons, while agents constituted 4.5% (18). Regarding education level, the majority of the participants had received university or two/four-year technical college educations (57.2%, 224), while those who received a senior (vocational) high school education or less made up 21.4% of participants (84). The majority (74.6%, 299) of the participants were working in franchise office branches, followed by those working in direct sales offices (25.4%, 102).

Data processing

Control variables.

In a regression analysis, the influence of control variables such as sex, tenure, and business model must be considered. Gender differences reflect physiological differences and can affect which employees are assigned different work tasks, which may influence their innovation performance. Therefore, we used sex as a control variable in the regression model. Many companies nowadays desire to achieve higher innovation performance. Most employees with longer tenures are older and are less responsive toward accepting new things; on the other hand, employees with shorter tenures are mostly fresh graduates or younger employees with less work experience. They tend to be more enthusiastic about their jobs since they have just entered the workforce and are more likely to develop new ideas; therefore, they have better innovation performance than employees with longer tenures. For this reason, we used tenure as a control variable in the regression model. The real estate industry in Taiwan consists of direct sales and franchise stores. the former is directly operated by the headquarters of a real estate company, and the employed agents and salespersons are dispatched to these direct sales offices after receiving training at the headquarters. The headquarters is responsible for guaranteeing the resources and service contents at each branch office. On the other hand, franchise stores consist of independent branch offices that need to pay a regular franchise fee to the headquarters in exchange for resources such as the headquarters’ brand image, educational training, or advertising. Each franchise is equivalent to a standalone company that must bear its own losses, and its business system and service contents differ as well. Since the innovation performance of both business models may differ, we also used the business model as a control variable in the regression model.

Aggregation issues

In this study, organizational culture, structural capital, and HRM practices were assigned as Level 2 variables. The data was a shared construct since it was collected from each real estate agent. In addressing the treatment of shared construct data, Klein et al. ( 1994 ) indicated that prior to conducting a multi-level analysis, it is necessary to examine the appropriateness of consolidating individual variables to the aggregate level. We used the intraclass correlation test (ICC(1)) approach proposed by James ( 1982 ) and the reliability of the mean test (ICC(2)) approach proposed by Bliese ( 1998 ) to examine the between-group differences. An ICC(1) greater than 0.5 indicates aggregation within organizational members, and the mean is the score of the organizational variable (Bliese, 2000 ; Heck and Thomas, 2009 ); an ICC(2) greater than 0.7 indicates a high reliability for using the group mean of individual data as a contextual variable, and that significant differences exist between the mean of each group (Dixon and Cunningham, 2006 ). The formulas are shown below:

where MS b is the between-group difference, MS w is the within-group difference, N g is the arithmetic mean of the group size.

There were 55 branches in Level 2, and the calculated ICC (1) of organizational culture and structural capital was 0.998 (>0.5), indicating that the individual variables of structural capital and organizational culture can be integrated into the aggregate level. The ICC (1)s of organizational culture and structural capital were both 0.999 (>0.07), which shows that the group means of individual organizational culture and structural capital are highly reliable contextual variable indicators with significant between-group heterogeneity. The ICC (2) of HRM practices was 0.999 (>0.07), which shows that HRM practices are a highly reliable contextual variable indicator with a significant between-group heterogeneity.

We recovered 401 questionnaires from 55 branches. We then used the within-group interrater reliability r wg (James et al., 1984 , 1993 ) to determine the within-group agreement, which reflects the degree of agreement of an individual in a particular population toward a particular variable (Bliese, 2000 ). The within-group agreement is present when r wg,j exceeds 0.7 (James et al., 1984 ). The formula is as follows:

where J is the number of questionnaire items; r wg ( j ) is the within-group agreement coefficient for judges’ mean scores based on the j th item; \(sx_j^2\) is the mean of the observed variances on the j th item; and \(\sigma _E^2\) is the expected variance of a hypothesized null distribution.

The results showed that the mean r wg ( j ) of the 55 branches in relation to organizational culture, structural capital, and HRM practices was 0.973, 0.966, and 0.950, respectively, and all were larger than 0.7. This shows that the within-group agreements were present in the variables of organizational culture, structural capital, and HRM practices, and were strongly correlated. Thus, the organizational members were in agreement regarding organizational culture, structural capital, and HRM practices. Therefore, our consolidation of organizational culture, structural capital, and HRM practices as organizational-level variables was adequate.

Empirical results

Prior to HLM analysis, we needed to examine whether significant differences exist between the individual innovation performance and knowledge sharing between branches, and we also had to estimate the proportion by which the total variance of innovation performance and knowledge sharing is shaped through the differences between branches.

As shown in Table 2 , the estimated variance of the random effects of personal innovation performance was 0.086 and was significant at the 1% level. This shows that significant differences exist in the individual innovation performance at each branch. The intraclass correlation was 0.208 (=0.086/(0.086 + 0.328)), which means that 20.8% of the variance of individual innovation performance consisted of the interclass (between branches) differences, while 79.2% of the variance consisted of intraclass (within a branch) differences. Next, the estimated variance of the random effects of knowledge sharing was 0.068 and was significant at the 1% level. This shows that significant differences exist in the levels of knowledge sharing at each branch. The intraclass correlation was 0.189 (=0.068/(0.068 + 0.292)), which means that 18.9% of the variance of knowledge sharing can be explained by the differences between branches, while 81.1% of the variance can be explained by the differences between agents. Therefore, we further applied HLM for analysis and estimation.

According to Table 3 and Fig. 2 , the estimation results of Model 1 showed that the estimated coefficient of relational capital was 0.643 and was significant at the 1% level. The estimated coefficient of organizational culture was 0.556 and was significant at the 1% level. The estimated coefficient of structural capital was 0.381 and was significant at the 5% level. These results showed that the three-step mediation effects testing had passed the first step. The estimation results of Model 2 showed that the estimated coefficient of organizational culture was 0.327 and was significant at the 1% level. The empirical results support H5 . The estimated coefficient of structural capital was 0.504 and was significant at the 1% level. The empirical results support H6 . The empirical results support H7 . These results indicated that the three-step mediation effects testing had passed the second step.

The empirical results.

The estimation results of Model 3 showed that the estimated coefficient of knowledge sharing was 0.580 and was significant at a 1% level. The empirical results support H4 . The estimated coefficient of organizational culture was 0.605 and was significant at a 1% level. The empirical results support H1 . The results support H1, H4, and H5, as well as H10 . The estimated coefficient of structural capital was 0.04 but did not attain a significant level. The empirical results do not support H2 . Good structural capital creates organizational value (De Pablos, 2004 ). The empirical results support H2, H4, and H6, as well as H11 . The estimated coefficient of relational capital was 0.250 and was significant at a 1% level. The empirical results support H3 . The empirical results support H3, H4, and H7, as well as H12 .

The estimated coefficient of HRM practices was 0.317 and was significant at a 5% level. The empirical results support H8 . The estimated coefficient of the influence of knowledge sharing on innovation performance through the moderating variable of HRM practices was −0.048 and did not attain a significant level. This shows that HRM practices do not moderate the influence of knowledge sharing on innovation performance. The empirical results do not suppor t H9 .

Theoretical implications

This showed that the stronger the real estate agents’ understanding of organizational culture, the better their understanding of knowledge sharing. The empirical results suppor t H5 and validate Sveiby and Simons’ ( 2002 ) study, which showed that an organizational culture characterized by trust and cooperation increases knowledge sharing and innovation performance. In addition, the process of implementing organizational culture is conducive to the indication of intra-organizational knowledge sharing. This indicates that the real estate agents’ knowledge sharing is significantly influenced by their strong understanding of structural capital. The empirical results support H6 . This finding also demonstrates that organizational members create partnerships rooted in mutual respect through long-term relationships or friendships, as well as that the trust-based structural capital shaped by this cooperative climate promotes organizational members’ willingness to share knowledge (Granovetter, 1992 ). This indicates that real estate agents with a stronger understanding of relational capital have a stronger understanding of knowledge sharing as well. The empirical results support H7 . This finding supports Lai’s ( 2013 ) argument that the higher the relational capital, the more likely organizational members are to engage in cooperation and the more likely they are to share knowledge. A stronger and closer relational capital increases the depth, breadth, and efficiency of knowledge sharing (Lane and Lubatkin, 1998 ).

The empirical results support H4. This finding is in line with Lin’s ( 2007 ) demonstration of the relationship between knowledge sharing and innovation performance. The study revealed that knowledge sharing is essential for information acquisition and, subsequently, innovation. This further indicates that the stronger the real estate agents’ understanding of knowledge sharing, the better their innovation performance. Indeed, knowledge sharing has mediating effects. This indicates that real estate agents’ understanding of organizational culture significantly influences their innovation performance. The empirical results suppo rt H1 . Huang ( 2018 ) showed that a good organizational culture is a determinant of innovation performance. The cultures shaped by an organization play an important role in their innovation performance; organizational culture has significant and direct effects on innovation performance. The results support H1, H4, and H5, as well as H10 . Alavi and Leidner ( 2001 ) highlighted that organizational culture is an important factor affecting knowledge management and organizational learning, is a determinant of organizational value, and promotes knowledge sharing and innovation. Fernandez et al. ( 2011 ) revealed that organizational culture enhances service innovation through knowledge sharing between colleagues. The key to building a strong and proactive organizational culture lies within the knowledge sharing and knowledge management behaviors between colleagues. This increases the likelihood that an organization will create innovative strategies (Al-Refaie, 2015 ). Organizational culture indirectly influences innovation performance through knowledge sharing and has a partial mediating effect.

The empirical results do not suppor t H2 . Good structural capital creates organizational value (De Pablos, 2004 ). Employees with a poorer perception toward their organization’s structural capital are incapable of significantly increasing the innovation performance of the organization. Our results revealed that structural capital has no significant or direct influence on innovation performance. This reflects the reality of the real estate industry since all agents are constantly competing, whether or not they are in the same organization. Consequently, they remain passive or are not attracted to the internal culture and vision of their organization or developing new skills. Regarding the enhancement of their personal and professional skills, each company has its own regulations on employee training. Some large and renowned brands provide internal and external training programs to their employees gratis, whereas smaller and independent brands operate on an out-of-pocket policy. Under such circumstances, structural capital fails to ideally influence innovation performance. The empirical results support H4 and H6, as well as H11 . De Pablos ( 2004 ) wrote that structural capital consolidates individual and group knowledge to generate organizational knowledge during the learning process. An employee who is more willing to share knowledge would gain a higher level of personal achievement. Our results showed that structural capital indirectly influences innovation performance through knowledge sharing, with complete mediation effects. This indicates that real estate agents with a stronger understanding of relational capital have a higher innovation performance. The empirical results suppor t H3 and show that relational capital has a direct influence on innovation performance. The empirical results support H3, H4, and H7, as well as H12 . Nahapiet and Hoshal ( 1998 ) suggested that relational capital promotes innovation in knowledge sharing through the exchange of intangible assets. Tu ( 2009 ) indicated that relational capital serves as a medium for knowledge flow; the knowledge advantage created through knowledge sharing and consolidation enhances the mutual trust, commitment, and bilateral communication between partners, thus increasing their innovation performance. Our results indicate that relational capital indirectly influences innovation performance through knowledge sharing, and the mediation effects were partial.

This suggests that real estate agents with a stronger understanding of HRM practices have a higher innovation performance. The empirical results suppor t H8 . Lazear ( 1996 ) pointed out that employees who express a higher interest in HRM practices and strategies understand more about their organization and innovation performance. The findings therefore suggest that the positive effects of employee recruitment, selection, training, human resource planning, remuneration scheme design, and employee engagement activities can improve an organization’s market performance, overall performance, and innovation (Hartog and Verburg, 2004 ; Andries and Czarnitzki, 2014 ). This shows that HRM practices do not moderate the influence of knowledge sharing on innovation performance. The empirical results do not suppo rt H9 . Previous studies have shown that HRM practices promote knowledge sharing on innovation performance (Lazzarotti et al., 2015 ). Knowledge-sharing activities among employees must be modified through HRM approaches such as designing training programs, reward systems, work teams, etc., so as to increase the willingness of employees to share their knowledge and experiences with others and thereby influence the individual innovation behaviors of employees and improve their innovation performance and creativity (Cano and Cano, 2006 ). Since the real estate agents had a weak understanding of HRM practices. This is because, in reality, many real estate agents do not have a base salary and must depend on making successful transactions by communicating and coordinating with their clients. Therefore, they tend to neglect the HRM practices in their organization. Our empirical results fail to support the aforementioned arguments.

Managerial implications

Our empirical results demonstrated that the indirect influence of organizational culture on innovation performance was partially mediated by knowledge sharing, the indirect influence of structural capital on innovation performance was fully mediated by knowledge sharing, and the indirect influence of relational capital on innovation performance was partially mediated by knowledge sharing. Real estate agents with a more positive perception of HRM practices showed better innovation performance.

First, managers should actively foster an organizational culture to enhance employees’ innovation performance. Measures include encouraging harmonious and friendly interactions between colleagues, creating a productive workplace climate, ensuring fair and equal treatment of all employees, emphasizing interpersonal relations, and establishing robust and comprehensive company policies.

Next, employees’ innovation performance can be enhanced by accumulating structural capital, such as allocating adequate funds and time to encourage employees to acquire new knowledge, establishing all-inclusive HR training programs, using various approaches to help employees develop their innovative capacity, and providing high-quality services that meet customer demands.

Employees can also improve their innovation performance by accumulating structural capital, such as establishing mutual trust between colleagues, treating one another with integrity, sharing knowledge, communicating frequently, and exchanging informal and formal information.

Lastly, HRM practices can be used to improve employees’ innovation performance. This includes setting well-defined career paths in the organization, assisting employees in applying their training contents into practice, giving compensation based on an employee’s contributions, and emphasizing impartiality.

Conclusions and recommendations

This study applied hierarchical linear modeling to explore the influences of organizational culture, structural capital, human resource management practices, relational capital, and knowledge sharing on the innovation performance of real estate agents. Organizational culture, structural capital, and human resource management practices were assigned as organizational-level variables while relational capital, knowledge sharing, and innovation performance were assigned as individual-level variables. First, we studied the influences of organizational culture, structural capital, and relational capital on innovation performance; afterward, we used knowledge sharing as a mediator variable to examine how it is influenced by organizational culture, structural capital, and relational capital. Lastly, we explored the influences of organizational culture, structural capital, human resource management practices, relational capital, and knowledge sharing on innovation performance, as well as whether human resource management practices moderated the influence of knowledge sharing on innovation performance. After testing the null model of the hierarchical linear model, we found that innovation performance and knowledge sharing differed significantly across the office branches, indicating that hierarchical linear modeling was suitable for analysis.

Based on the empirical results, organizational culture indirectly influences innovation performance through knowledge sharing. In other words, organizational culture has a partial mediating effect on innovation performance. Structural capital directly influences innovation performance through knowledge sharing, with a complete mediating effect. Relational capital indirectly influences innovation performance through knowledge sharing, with a partial mediating effect. The stronger the real estate agents’ understanding of human resource management practices, the higher their innovation performance. Human resource management practices did not moderate the influence of knowledge sharing on innovation performance, and our empirical results were not supported. From a theoretical perspective, the impacts of organizational culture in higher education on job satisfaction have been studied previously (see Islamy et al.,, 2020 ), although the model merely consisted of organizational culture, job satisfaction, and knowledge sharing. Moreover, Kutieshat and Farmanesh ( 2022 ) only considered the exogenous variable of new HRM practices when studying innovation performance. Our study expands and enhances the completeness of this theoretical framework by adding the variables of structural capital and relational capital, thus achieving better empirical support. Concerning the research subjects, studies on innovation in the real estate industry (see Benefield et al., 2019 ) have mostly observed the effects of real estate agencies and technology based on housing prices. On the other hand, our study employed latent variables and performed measurements from a psychological level, thereby broadening the research on the real estate industry.

This study was administered to participants in Kaohsiung City, Taiwan; therefore, the results cannot be extrapolated beyond the range of the study area. The control variables in the hierarchical linear model only included sex, tenure, and business model; job position was excluded, and the questionnaire was not directed at supervisors. Therefore, we were unable to explore whether job positions or supervisors’ opinions toward the organization or individual employees differed. Furthermore, we only focused on the human resource planning, training and development, and remuneration and benefits sub-dimensions of human resource management practices. We recommend future studies to explore the other sub-dimensions of human resource management practices, such as performance evaluation and non-financial remuneration schemes. Due to manuscript length restrictions and time and monetary constraints, we did not examine the behaviors of house buyers. As a result of technological advancements and social developments, our lifestyles and behaviors are profoundly influenced by science and technology, which may also alter the preferences of house buyers. Therefore, we suggest that future studies can focus on the impacts of technology (such as AI) on house-buyers’ behaviors or how AI moderates the relationship between knowledge sharing and innovation performance.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Aboramadan M, Albashiti B, Alharazin H, Zaidoune S (2020) Organizational culture, innovation and performance: a study from a non-western context. J Manag Dev 39(4):437–451

Article   Google Scholar  

Alavi M, Leidner DE (2001) Review: knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Q 25(1):107–136

Allameh SM (2018) Antecedents and consequences of intellectual capital: the role of social capital, knowledge sharing and innovation. J Intellect Cap 19(5):858–874

Al-Refaie A (2015) Effects of human resource management on hotel performance using structural equation modeling. Compute Hum Behav 43:293–303

Amabile TM (1988) A model of creativity and innovation in organizations. Res Organ Behav 10(1):123–167

Anderson N, Potočnik P, Zhou J (2014) Innovation and creativity in organizations: a state-of-the-science review. J Manag Stud 40(5):1297–1333

Google Scholar  

Andries P, Czarnitzki D (2014) Small firm innovation performance and employee involvement. Small Bus Econ 43(1):21–38

Ardito L, Messeni PA (2017) Breadth of external knowledge sourcing and product innovation: the moderating role of strategic human resource practices. Eur Manag J 35(2):261–272

Armstrong JS, Overton TS (1977) Estimating nonresponse bias in mail surveys. J Market Res 14:396–402

Bae J, Chen SJ, Lawler JJ (1998) Variations in human resource management in Asian countries: MNC home-country and host-country effect. Int J Hum Resour Manag 9(4):653–669

Bagherzadeh M, Markovic S, Cheng J, Vanhaverbeke W (2019) How does outside-in open innovation influence innovation performance? Analyzing the mediating roles of knowledge sharing and innovation strategy. IEEE Trans Eng Manag 67(3):740–753

Baron RM, Kenny DA (1986) The moderator mediator variable distinction in social psychological research: conceptual, strategic, and statistical consideration. J Pers Soc Psychol 51:1173–1182

Article   PubMed   CAS   Google Scholar  

Bavik YL, Tang PM, Shao R, Lam LW (2018) Ethical leadership and employee knowledge sharing: Exploring dual-mediation paths. The Leadership Q 29(2): 322–332

Becerra-Fernandez I, Sabherwal R (2001) Organizational knowledge management: a contingency Perspective. J Manag Inf Syst 18(1):23–56

Benefield JD, Sirmans CS, Sirmans GS (2019) Observable agent effort and limits to innovation in residential real estate. J Real Estate Res 41(1):1–36

Betz F (1987) Managing technology-competing through new ventures-innovation and corporate research: Prentice Hall

Bilderbeek R, den Hertog P, Marklund G, Miles I (1998) Services in innovation: Knowledge Intensive Business Services (KBIS) as co-producers of innovation, Sl4S Synthesis Paper no. 3, STEP Group

Bitner MJ, Booms BH, Mohr LA (1994) Critical service encounters: the employee’s viewpoint. J Market 54:71–84

Bliese PD (1998) Group size, ICC values, and group-level correlations: a simulation. Organ Res Method 1(4):355–373

Bliese PD (2000) Within-group agreement, non-independence, and reliability: implications for data aggregation and analysis. In: Klein KJ, Kozlowski SW (eds). Multilevel theory, research, and methods in organizations. Jossey-Bass, Inc., San Francisco, CA, pp. 349–381

Bock GW, Kim YG (2002) Breaking the myths of rewards: an exploratory study of attitudes about knowledge sharing. Inf Resour Manag J 15(2):14–21

Bock GW, Zmud RW, Kim YG, Lee JN (2005) Behavioral intention formation in knowledge sharing: examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Q Inf Technol Knowl Manag 29:87–111

Bontis N (1998) Intellectual capital: an exploratory study that develops measures and models. Manag Decis 36(2):63–76

Bontis N (1999) Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field. Int J Technol Manag 18(5-8):433–463

Bontis N, Keow WCC, Richardson S (2000) Intellectual capital and business performance in Malaysian industries. J IntellectCap 1(1):85–100

Bowen DE, Schneider B (1985) Boundary-spanning-role employees and the service encounter: some guidelines for future management and research. In: Czepiel John, Solomon MichaelR, Surprenant CarolF (eds.) The service encounter. Lexington Books, New York, pp. 127–147

Bradler C, Neckermann S, Warnke AJ (2019) Incentivizing creativity: a large-scale experiment with performance bonuses and gifts. J Labor Econ 37(3):793–851

Cabrera EF, Cabrera A (2005) Fostering knowledge sharing through people management practices. Int J Hum Resour Manag 16:720–735

Calantonea RJ, Cavusgil ST, Zhao Y (2002) Learning orientation, firm innovation capability, and firm performance. Ind Market Manag 31(6):515–524

Cano CP, Cano PQ (2006) Human resources management and its impaction innovation performance in companies. Int J Technol Manag 35(1-4):11–28

Caruso SJ (2017) A foundation for understanding knowledge sharing: organizational culture, informal workplace learning, performance support, and knowledge management. Contemp Issue Educ Res 10(1):45–52

Chang TY, Lee CC, Lin HC (2023) A study on the influence of experiential marketing on repurchase intention of O2O operation model-with consumer decision -making as mediating. Manag Inf Comput 12(1):37–48

Chen TH, Chen HF (2022) Turning old to enable new: a case study on knowledge sharing of reverse mentoring for organizational innovation. Sun Yat-sen Manag Rev 30(2):325–366

Chen YH (2007) The strategy of value innovation of intellectual capital. J China Inst Technol 37:159–171

Daft RL (2004) Organization theory and design, 8th edn. Thomson/South-Western, Mason, Ohio

De Pablos PO (2004) Measuring and reporting structural capital: lessons form European learning firms. J Intellect Cap 5(4):629–647

Deal TE, Kennedy AA (1984) Corporate cultures. Common Wealth Publishing, NY

Dessler G (2000) Human resource management. Prentice-Hall, Upper Saddle River, N. J

Dixon MA, Cunningham GB (2006) Data aggregation in multilevel analysis: a review of conceptual and statistical issues. Meas Phys Educ Exerc Sci 10(2):85–107

Drejer I (2004) Identifying innovation in surveys of services: a Schumpeterian perspective. Res Policy 33(3):551–562

Duan Y, Chen Y, Liu S, Wong CS, Yang M, Mu C (2023) The moderating effect of leadership empowerment on relational capital and firms’ innovation performance in the entrepreneurial ecosystem: evidence from China. J Intellect Cap 24(1):306–336

Earl lJ, Scott IA (1999) Opinion: what is a chief knowledge officer? I Sloan Manag Rev 40(2): 29–38

Edvinsson L, Malone MS (1997) Intellectual capital: realizing your company’s true value by finding its hidden roots. Harper Collins Publishers, Inc, New York

Evans WR, Davis WD (2005) High-performance work systems and organizational performance: the mediating role of internal social structure. J Manag 3:758–755

Fernández JE, Torres-Ruiz JM, Diaz-Espejo A, Montero A, Álvarez R, Jiménez MD, Cuervab MV Cuevas J (2011) Use of maximum trunk diameter measurements to detect water stress in mature ‘Arbequina’ olive trees under deficit irrigation. Agric Water Manag 98(12):1813–1821

Garaus C, Güttel WH, Konlechner S, Koprax I, Lackner H, Link K, Müller B (2016) Bridging knowledge in ambidextrous HRM systems: empirical evidence from hidden champions. Int J Hum Resour Manag 27(3):355–381

Geiger RS (2017) Beyond opening up the black box: investigating the role of algorithmic systems in Wikipedian organizational culture. Big Data Soc 4(2):2053951717730735

Gooderham PN, Pedersen T, Sandvik AM, Dasí À, Elter F, Hildrum J (2022) Contextualizing AMO explanations of knowledge sharing in MNEs: the role of organizational and national culture. Manag Int Rev 62:859–884

Granovetter MS (1992) Problems of explanation in economic sociology. In: Nohria N, Eccles R (eds.) Networks and organizations: structure, form and action. Harvard Business School Press, Boston, pp. 25–56

Grasenick K, Low J (2004) Shaken, not stirred: defining and connecting indicators for the measurement and valuation of intangibles. J Intellect Cap 5(2):268–281

Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL (2006) Multivariate data analysis, 6th edn. Pearson University Press, Upper Saddle River, NJ

Hair JF, Ringle CM, Sarstedt M (2011) PLS-SEM: indeed a silver bullet. J Market Theor Pract 19(2):139–152

Hameed WU, Nisar QA, Wu HC (2021) Relationships between external knowledge, internal innovation, firms’ open innovation performance, service innovation and business performance in the pakistani hotel industry. Int J Hosp Manag 92:102745

Hanifah H, Abd Halim N, Vafaei-Zadeh A, Nawaser K (2022) Effect of intellectual capital and entrepreneurial orientation on innovation performance of manufacturing SMEs: mediating role of knowledge sharing. J Intellect Cap 23(6):1175–1198

Haq MZU, Gu M, Huo B (2021) Enhancing supply chain learning and innovation performance through human resource management. J Bus Ind Market 36(3):552–568

Hartog DN, Verburg RM (2004) High performance work systems, organisational culture and firm effectiveness. Hum Resour Manag J 14(1):55–78

Heck RH, Thomas SL (2009) An introduction to multilevel modeling techniques, 2nd edn. Routledge, New York

MATH   Google Scholar  

Hendrinks P (1999) Why share knowledge? The influence of ICT on the motivation for knowledge sharing. Knowl Process Manag 6(2):91–100

van den Hooff BJ, Huysman MH (2009) Managing knowledge sharing: emergent and engineering approaches. Inf Manag 46:1–8

Hsu SW, Chang HH, Yen WS, Chen WL (2021) Study of the moderating effect of perceived organizational support on the relationship between human resource management practices and organizational performance. Int J Commer Strateg 13(1):31–50

Huang YP (2018) The study of knowledge management, organizational culture and innovational performance in Taiwan industries, Master’s thesis, Hwa Hsia University of Technology Graduate Institute of Information Management

Hurley RF, Hult TM (1998) Innovation, market orientation, and organizational learning: an integration and empirical examination. J Market 62(3):42–45

Islamy F, Yuniarsih T, Ahman E, Kusnendi K (2020) The role of organizational culture, knowledge sharing and job satisfaction in higher education. Manag Sci Lett 10(16):3957–3966

Jada UR, Mukhopadhyay S, Titiyal R (2019) Empowering leadership and innovative work behavior: a moderated mediation examination. J Knowl Manag 23(5):915–930

James L (1982) Aggregation bias in estimates of perceptual agreement. J Appl Psychol 67(2):219–229

Article   MathSciNet   Google Scholar  

James RL, Demaree RG, Wolf G (1984) Estimating within-group interrater reliability with and without response bias. J Appl Psychol 69(1):85–98

James RL, Demaree RG, Wolf G (1993) An assessment of within-group interrater agreement. J Appl Psychol 78(2):306–309

Jaw BS (2004) The management of intellectual capital and organizational learning capability, Master’s thesis, National Sun Yat-sen University Institute of Human Resource Management

Ji H, Sui YT, Suo LL (2017) Understanding innovation mechanism through the lens of communities of practice (COP). Technol Forecast Soc Change 118:205–212

Joia LA (2000) Measuring intangible corporate assets: linking business strategy with intellectual capital. J Intellect Cap 1:68–84

Ke W, Wei KK (2008) Organizational culture and leadership in ERP implementation. Decis Support Syst 45(2):208–218

Kim N, Shim C (2018) Social capital, knowledge sharing and innovation of small- and medium-sized enterprises in a tourism cluster. Int J Contemp Hosp Manag 30(6):2417–2437

Kim TT, Lee G, Paek S, Lee S (2013) Social capital, knowledge sharing and organizational performance: what structural relationship do they have in hotels? Int J Contemp Hosp Manag 25(5):683–704

Kim W, Park J (2017) Examining structural relationships between work engagement, organizational procedural justice, knowledge sharing, and innovative work behavior for sustainable organizations. Sustainability 9(2):205

Klein KJ, Dansereau F, Hall RJ (1994) “Levels issues in theory development, data collection, and analysis. Acad Manag Rev 19(2):195–229

Kogut B, Zander U (1996) What firms do? Coordination, identity, and learning. Organ Sci 7(5):502–518

Kozlowski SWJ, Klein KJ (2000) A multilevel approach to theory and research in organizations: contextual, temporal, and emergent processes. Multilevel Theory Research and Methods in Organizations. Jossey-Bass/Wiley. pp. 3–90

Krull JL, MacKinnon DP (1999) Multilevel mediation modeling in group-based intervention studies. Eval Rev 23:418–444

Kutieshat R, Farmanesh P (2022) The impact of new human resource management practices on innovation performance during the COVID 19 crisis: a new perception on enhancing the educational sector. Sustainability 14(5):2872

Article   CAS   Google Scholar  

Kuo RC (2022) Problem analysis of competition law in property technology (PropTech): An emphasis on housing information. Southern Taiwan University of Sci & Tech Law Rev 9(1):169–198

Lai YR (2013) The relationship between team members’ relational capital and knowledge sharing - Social interaction perspective, Master’s thesis, National Central University Graduate Institute of Human Resource Management

Lane PJ, Lubatkin M (1998) Relative absorptive capacity and interorganizational learning. Strateg Manag J 19(5):461–477

Lazear EP (1996) Performance pay and productivity (No. w5672), National Bureau of Economic Research

Lazzarotti V, Manzini R, Pellegrini L (2015) Is your open-innovation successful? The mediating role of a firm’s organizational and social context. Int J Hum Resour Manag26(19):2453–2485

Lee CC, Sheng YS (2022) Exploring the relationship between leadership behavior and job performance from a practical point of view—taking organizational culture as an intervene variable. Manag Inf Comput 11(1):187–198

CAS   Google Scholar  

Lee CC, Yeh WC, Yu Z, Xu RG, Hong QE, Shi PC (2023) The influence of transformational leadership, transactional leadership, ethical climate, and emotional intelligence on the performance of housing agents: The mediation effect of trust in supervisor. J Taiwan Agric Res 25(1):23–61

Lee CC, You SM (2007) The type of management, structure of earnings and performance of salespersons in the housing brokerage market. J Build Plan 14:1–18

Lemon M, Sahota PS (2004) Organizational culture as a knowledge repository for increased innovative capacity. Techinovation 24:483–498

Lin CC, Wang CC (2005) Knowledge sharing within an organization from perspectives of social exchange and transaction cost. J Hum Resour Manag 5(2):95–119

Lin CI (2021) The impacts of technological developments on the real estate brokerage industry. Land Issues Research Quarterly 20(1):58–72

Lin CT, Chen YC, Kang T (2011) The effect of learning orientation on firm performance: structural capital as a mediator. Yu Da Acad J 28:57–76

Lin H (2007) Knowledge sharing and firm innovation capability: an empirical study. Int J Manpower 28(3/4):315–332

Ma C, Li B, Chen Y (2023) Parent–subsidiary company geographic distance and corporate innovation performance: inhibitive or stimulative? Emerg Market Financ Trade 59(8):1–26

Mallik S, Harker PT (2004) Coordinating supply chains with competition: capacity allocation in semiconductor manufacturing. Eur J Operat Res 159:330–347

Article   MathSciNet   MATH   Google Scholar  

Manzoor F, Wei L, Asif M (2021) Intrinsic rewards and employee’s performance with the mediating mechanism of employee’s motivation. Front Psychol 12:563070

Article   PubMed   PubMed Central   Google Scholar  

McDermott R, O’Dell C (2001) Overcoming cultural barriers to sharing knowledge. J Knowl Manag 5(1):76–85

McFadyen M, Cannella A (2004) Social capital and knowledge creation: diminishing returns of the number and strength of exchange relationships. Acad Manag J47(5):735–746

McHugh PP (1997) Team-based work systems: lessons from the industrial relations literature. Hum Resour Plan 20(3):44–47

Meslec N, Curseu PL, Fodor OC, Kenda R (2020) Effects of charismatic leadership and rewards on individual performance. Leadership Q 31(6):101423

Molyneux A (1998) IC and the ASCPA: seeking competitive advantage. Australian CAP 68(5):27–28

Nahapiet J, Hoshal S (1998) Social capital, intellectual capital, and the organizational advantage. Acad Manag Rev 23(2):242–266

Narver C, Slater SF (1990) The effect of a market orientation on business profitability. J Market 54:20–35

Nonaka I, Takeuchi H (1995) The knowledge-creating company: how Japanese companies create the dynamics of innovation. Oxford University Press, New York

Book   Google Scholar  

Onofrei G, Nguyen HM, Zhang M, Fynes B (2020) Building supply chain relational capital: the impact of supplier and customer leveraging on innovation performance. Bus Strateg Environ 29(8):3422–3434

Ouchi WG (1981) Organizational paradigms: a commentary on Japanese Management and Theory Z Organizations. Organ Dyn 9(4):36–43

Papa A, Dezi L, Gregori GL, Mueller J, Miglietta N (2020) Improving innovation performance through knowledge acquisition: the moderating role of employee retention and human resource management practices. J Knowl Manag 24(3):589–605

Pedraza MNA, De la Gala VB, Estudios G (2022) The mediating role of structural capital in the relationship between human capital and performance in the public administrations of Mexico and Peru. J Manag Econ Iberoamerica 38(164):320–333

Perry-Smith JE, Shalley CE (2003) The social side of creativity: a static and dynamic social network perspective. Acad Manag Rev 28(1):89–106

Qiao S, Wang Q (2021) The effect of relational capital on organizational performance in supply Chain: the mediating role of explicit and tacit knowledge sharing. Sustainability 13(19):10635

Rajapathirana RJ, Hui Y (2018) Relationship between innovation capability, innovation type, and firm performance. J Innov Knowl 3(1):44–55

Robbins SP (2006) Essentials of organizational behavior. Prentice-Hall, NJ

Roos J, Roos G, Dragonetti NC, Edvinsson L (1997) Intellectual capital: navigating new business landscape. Macmillan Business, Hampshire

Sanz-Valle R, Sabater-Sanchez R, Aragon-Sanchez A (1999) Human resource management and business strategy links: an empirical study. Int J Hum Resour Manag 10(4):655–671

Sarkar MB, Echambadi R, Cavusgil ST, Aulakh PS (2001) The influence of complementarity, compatibility, and relationship capital on alliance performance. J Acad Market Sci 29(4):358–373

Saswat B (2018) Role of human and structural capital on performance through human resource practices in Indian Microfinance Institutions: a mediated moderation approach. business strategy and the environment, https://doi.org/10.1002/kpm.1666

Schein EH (1993) ‘On dialogue, culture, and organizational learning. Organ Dyn 22(2):40–51

Schneider B, Reichers AE (1983) On the etiology of climates. Personnel psychology 36(1):19–39

Shahzad F, Xiu G, Shahbaz M (2017) Organizational culture and innovation performance in Pakistan’s software industry. Technol Soc 51:66–73

Shi Q, Wang Q, Guo Z (2022) Knowledge sharing in the construction supply Chain: collaborative innovation activities and BIM application on innovation performance. Eng Construct Architect Manag 29(9): 3439–3459

Spencer JW (2003) Firms’ knowledge‐sharing strategies in the global innovation system: empirical evidence from the flat panel display industry. Strateg Manag J 24(3):217–233

Srisathan WA, Ketkaew C, Naruetharadhol P (2020) The intervention of organizational sustainability in the effect of organizational culture on open innovation performance: a case of Thai and Chinese SMEs. Cogent Bus Manag 7(1):1717408

Subramanian A, Nilakanta S (1996) Organizational innovativeness: exploring the relationship between organizational determinants of innovation, types of innovations, and measures of organizational performance. Omega 24(6):631–647

Sun L-Y, Samuel A, Kenneth S (2007) High-performance human resource practices, citizenship behavior, and organizational performance: a relational perspective. Acad Manag J 50:3

Sveiby KE, Simons R (2002) Collaborative climate and effectiveness of knowledge work-an empirical study. J Knowl Manag 6(5):420–433

Thite M (2015) International human resource management in multinational corporations from emerging markets. In: Horwitz F, Budhwar P (eds.) Handbook of human resource management in emerging markets. Edward Elgar, Cheltenham, pp. 97–121

Tseng CY, Goo YJJ (2005) Intellectual capital and corporate value in an emerging economy: empirical study of Taiwanese manufacturers. RandD Manag 35(2):187–201

Tushman ML, O’Reilly CA (1996) Winning through innovation: a practical guide to leading organizational change and renewal. Harvard Business School Press, Boston, Mass

Tu CJ (2009) The effect of relationship capital on knowledge integration capability and organizational innovation performances: Absorptive capability as a moderator. Taiwan Business Performance J 3(1):121–149

Ullah F, Sepasgozar SM (2019) Chapter 27: A study of information technology adoption for real-estate management: a system dynamic model. In: Innovative production and construction: transforming construction through emerging technologies. Faculty of Built Environment, The University of New South Wales, Sydney, NSW 2052, Australia, pp. 469–486

Uzzi B (1996) The sources and consequences of embeddedness for the economic performance of organizations: the network effect. Am Sociol Rev 61:674–698

Valle R, Martín F, Romero PM, Dolan SL (2000) Business strategy, work processes and human resource training: are they congruent? J Organ Behav 21(3):283–297

Wang C, Hu Q (2020) Knowledge sharing in supply Chain. Networks: effects of collaborative innovation activities and capability on innovation performance. Technovation 94:102010

Wang H, Lee TS (2018) The moderating effects of innovation strategy on product innovation performance given the organizational learning. J Chin Trend Forward 14(2):55–73

Wang SH (2004) The study on the interrelation among creation of customer value, cognition of customer’s needs satisfaction and customer loyalty of the real-estate brokerage, Master’s thesis, Dayeh University Department of International Business Management

Wen FH, Chiou HJ (2009) Methodology of multilevel modeling: the key issues and their solutions of hierarchical linear modeling, NTU. Manag Rev 19(2):263–294

West MA, Anderson NR (1996) Innovation in top management teams. J Appl Psychol 81(6):680–693

Wilkins AL, Ouchi WG (1983) Efficient cultures: exploring the relationship between culture and organizational performance. Adm Sci Q 28:468–481

Wu CC (2007) The study of the relationship among human resource development, job satisfaction and job performance—an example of the real estate brokers, Master’s thesis, National Taiwan University of Science and Technology Graduate Institute of Management

Wu JS (1999) A study on the interrelation between customer satisfaction and customer loyalty of the real estate broking, Master’s thesis, Feng Chia University Department of Land Management

Wu S, Lin TC (2007) Exploring knowledge sharing behavior of is personnel with theory of planned behavior. J Inf Manag 14(2):75–110

Yan J, Leidner DE, Benbya H, Zou W (2019) Social capital and knowledge contribution in online user communities: one-way or two-way relationship?. Decis Support Syst https://doi.org/10.1016/j.dss.2019.113131

Yeh WC, Lee CC, Yu C, Wu PS, Chang JY, Huang JH (2020) The impact of the physical attractiveness and intellectual competence on loyalty. Sustainability 12(10):3970. https://doi.org/10.3390/su12103970

Yiu HL, Ngai EWT, Lei CF (2020) Impact of service-dominant orientation on the innovation performance of technology firms: roles of knowledge sharing and relationship learning. Decis Sci Inst 51(3):620–655

Yli-Renko H, Autio E, Sapienza H (2001) Social capital, knowledge acquisition, and knowledge exploitation in young technology-based firms. Strateg Manag J 22:587–613

Youndt MA, Snell SA (2004) Human resource configurations, intellectual capital, and organizational performance. J Manag Issue 16(3):337–360

Yu RR, Liu YS (2004) Incentives of compensation schemes within workgroups: an empirical study on the real estate brokers in Taiwan. Taiwan Econ Rev 32(4):395–416

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Lee, CC., Yeh, WC., Yu, Z. et al. Knowledge sharing and innovation performance: a case study on the impact of organizational culture, structural capital, human resource management practices, and relational capital of real estate agents. Humanit Soc Sci Commun 10 , 707 (2023). https://doi.org/10.1057/s41599-023-02185-w

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Multilingual abstract

Please see Additional file 1 for translation of the abstract into Arabic.

Introduction

This paper’s focus is on organizational innovations and on how the creation, diffusion, and sustaining of organizational innovations can be conceptualized from a system perspective. Organizational innovations are here defined as new organizational methods in business practices, workplace organization, or external relations (OECD 2005 ).

Organizational innovations typically aim at increasing operational efficiency and employee satisfaction or at improving an organization’s innovativeness. In fact, organizational innovations are often necessary for technical innovations (Freeman 1982 ; Leonard-Barton 1988 ; Tushman and O’Reilly 1997 ; Teece 2007 ; Volberda et al. 2013 ).

According to Ganter and Hecker ( 2014 ), many attempts at adaptation to environmental change are pertaining to organizational innovations. In a global marketplace, continuously changing due to rapid technological development, organizations need to make even more effective use of organizational innovations in order to uphold their competitiveness.

There are several examples of complex organizational innovations, such as Divisionalization (“M-form”), Total Quality Management (TQM), Toyota Production System (TPS), and Lean Production (“Lean”), that all have led to competitive advantages for the organizations that have embraced them (Womack and Jones 2003 ; Liker 2004 ; Birkinshaw et al. 2008 ).

However, in spite of the fact that organizational innovations create long-term competitive advantages and are important for technical innovations, they “remain poorly managed and poorly understood” (Birkinshaw and Mol 2006 ). One major reason is that most innovation research has focused on technical innovation, while research on organizational innovation has been conducted to a lesser extent (Birkinshaw et al. 2008 ; Ganter and Hecker 2013 ). Previous research has therefore identified a need to develop a more comprehensive model to better understand the mechanisms catalyzing organizational development and change (Frambach and Schillewaert 2002 ; Ganter and Hecker 2013 and 2014).

In order to increase our understanding of organizational innovation, the purpose of this paper is therefore to develop a more comprehensive model for studying the creation, diffusion, and sustaining of organizational innovations by using a system perspective.

The comprehensive model has a wider and more general use than organizational development and change of “firms.” The model can also be used to explain and better understand the creation, diffusion, and sustainability of organizational change and development of most organizations, including governmental entities and universities. The model is therefore applicable across the Triple Helix model. The ambition of the paper is therefore to provide insights to practitioners in all three helices, firms, universities, and governmental entities, aiming at a more systematic approach to organizational development and change in their own organization in order to be competitive in a rapidly changing world.

The two following sections in this paper focus on Methodology and Literature review . The literature review covers two main parts; first, the concept of organizational innovation will be defined and explored, and second, previous research on how organizational innovations are created, diffused, and sustained will be presented. Findings from our empirical case studies presented in Alänge and Steiber ( 2009 , 2011 ) are part of and integrated in the literature review. Next, a comprehensive model for studying the creation, diffusion, and sustaining of organizational innovations will be presented. Finally, the paper ends by presenting some key conclusions and recommendations for future research.

Methodology

This section introduces the different steps to develop a comprehensive model for the creation, diffusion, and sustaining of organizational innovations. The development of the model follows an abductive approach (Dubois and Gadde 2002 ), where an initial literature review resulted in a tentative analytical framework, that was subsequently tested in empirical studies providing inputs to refine the framework, which was contrasted to recent literature, ultimately resulting in the development of the comprehensive model presented in this paper.

Our starting point is a focus on organizational innovations and on how the creation, diffusion, and sustaining of organizational innovations can be conceptualized from a system perspective. Seminal work on understanding innovation from a system perspective has primarily been focused on technical innovation (Freeman 1987 ; Porter 1990 ; Carlsson and Stankiewicz 1991 ; Lundvall 1992 ; Nelson 1993 ; Etzkowitz and Leydesdorff 1995 ). Footnote 1 The model for catalyzing organizational development and change presented in this paper originates from this line of research on technical innovation systems (Alänge et al. 1998 ) but has evolved through empirical research studies of complex organizational innovations such as TQM, Toyota Production System, and Lean conducted between 1993 and 2011 (Alänge and Jarnehammar 1995 ; Alänge and Steiber 2009 , 2011 ). The process to develop the comprehensive model is described in more detail below.

First, an analytical framework for the diffusion Footnote 2 of organizational innovations was developed (Alänge et al. 1998 ) based on a literature review conducted on the diffusion of both technical and organizational innovations (e.g., Kimberley 1981 ; Rogers 1995 ; Teece 1980 ) and with a strong influence of the then emerging literature on innovation systems (e.g., Carlsson and Stankiewicz 1991 ; Carlsson and Jacobsson 1994 ; Lundvall 1992 ). Taking the inspiration from theories developed for technical innovations, a major step was to identify characteristics of organizational innovation and how these potentially could influence the innovation and diffusion process. Thus, in the tentative framework issues to consider when analyzing the diffusion of organizational innovations were emphasized (Alänge et al. 1998 ).

Second, the analytical framework was then tested by applying it to the complex organizational innovation TQM, in two contrasting case studies of a professional kitchen manufacturing firm and a hospital. This resulted not only in the confirmation of the relevance of major parts of the assumptions and the concepts in the framework, but also in the refutation of some assumptions (e.g., limited “testability” and lack of “systematic search”). The result was an improved understanding and a modified analytical framework (Alänge and Steiber 2011 ). However, this study also identified one area that a previous theory to a large extent had omitted: the role of the governance structure above the CEO (boards and owners) when it comes to the diffusion and sustaining of complex organizational innovations.

Thus, the roles of boards in sustaining the three major organizational innovations TQM, TPS, and Lean were then explored in Alänge and Steiber ( 2009 ), once again with a longitudinal perspective covering time periods of 10–20 years in three different empirical cases analyzed (a steel company, a truck manufacturer, and a hospital). As had been assumed, the importance of the board level for sustaining organizational innovations was empirically verified and Alänge and Steiber ( 2009 ) showed that theories (e.g., agency theory) and perceptions of the relationship between board and CEO can potentially influence the sustainability of organizational innovations.

In order to further develop the framework, the findings from these empirical studies (Alänge and Steiber 2009 , 2011 ) were then contrasted to and discussed in relation to other more recent research on the creation, diffusion, and sustaining of organizational innovation from a system perspective (e.g., Frambach and Schillewaert 2002 ; Buchanan et al. 2005 ; Birkinshaw et al. 2008 ; Ganter and Hecker 2013 ). This second literature review broadened the focus on both the creation and on the sustaining of organizational innovations and confirmed the view that the three concepts creation, diffusion, and sustaining are intertwined (Steiber 2012 ).

Subsequently, by including the broadened focus on “sustaining of innovations” in a study for the Swedish Innovation agency “VINNOVA,” the framework was used for a comparative analysis of seven European and North American programs for the dissemination of organizational innovations (contributing to innovativeness and increased competitiveness among existing firms). This study showed that the model was also useful in analyzing both similarities and differences between the seven different national/international programs (Steiber and Alänge 2013a ).

Finally, by integrating the findings from the literature reviews with findings from the empirical cases (Alänge and Steiber 2009 , 2011 ; Steiber and Alänge 2013a ), the comprehensive model for studying the creation, diffusion, and sustaining of organizational innovations was developed in this paper.

Literature review

In spite of the fact that organizational innovations have been found to be important for organizations’ long-term competitive advantages, the creation and diffusion of organizational innovations have been subject to less research focus compared to technical innovations (Edquist 1992 ; Birkinshaw et al. 2008 ; Ganter and Hecker 2013 ). Further, the question of how to sustain an organizational innovation once implemented has received even less research attention, so that there is currently no established research tradition in this area (Buchanan et al. 2005 ). In order to better understand how organizational innovations are created, diffused, and sustained, this literature review consists of three main parts. First, the concept of organizational innovation will be defined and explored. Second, previous research on how organizational innovations are created and diffused will be presented. Third, previous research on how organizational innovations are sustained will be presented.

• Organizational innovation

An organizational innovation Footnote 3 can according to OECD ( 2005 , p. 51) be defined as:

A new organisational method in business practices, workplace organisation or external relations. Organisational innovations can be intended to increase an organization’s performance by reducing administrative costs or transaction costs, improving workplace satisfaction (and thus labour productivity), gaining access to non-tradable assets (such as non-codified external knowledge) or reducing costs of supplies.

The above can serve as a general definition of organizational innovation. Within the concept of “business practices,” we include organizational elements such as leadership, management processes (e.g., reporting and budget processes), culture, human resource management, mechanisms for learning, and external and internal corporate communication. Organizational innovation can refer to either “new-to-the-state-of-the-art” meaning that it has no known precedent or “new to the specific organization” (Mol and Birkinshaw 2009 ). In line with the OECD ( 2005 ), in this paper, we consider organizational innovations as “new to the organization.” Footnote 4

Further, organizational innovations can vary in complexity. Some affect a certain business process (such as re-engineering the purchasing process), while others affect every single part of an organization. According to Hamel ( 2006 , p 74), an organizational innovation creates long-term competitive advantages if it meets one or more of three conditions:

The innovation is based on a novel principle that challenges management orthodoxy; it is systematic, encompassing a range of processes and methods; and it is part of an ongoing program of invention, where progress compounds over time.

The three organizational innovations (TQM, TPS, Lean) investigated in the empirical studies utilized for this paper (Alänge and Steiber 2009 , 2011 ) could all affect every single part of an organization and also fulfill Hamel’s ( 2006 ) three criteria.

The creation and diffusion of organizational innovations

Four primary perspectives have been used when studying organizational innovations (Birkinshaw et al. 2008 , p. 827). These are the institutional perspective where institutional conditions influence the creation and diffusion of organizational innovations, the fashion perspective where fashion setters continuously redefine both their and fashion followers’ collective beliefs about which management techniques lead to rational management progress, the cultural perspective where the organization’s culture influences the creation and diffusion of organizational innovations, and the rational perspective where managers take on a role in creating and implementing organizational innovations. In addition to these four perspectives, a fifth perspective was used in Alänge et al. ( 1998 ). This is the perspective of innovation systems, which in turn is partly influenced by the institutional perspective (e.g., Lundvall 1992 ). According to Birkinshaw et al. ( 2008 ), the research community has tended to use one of these different perspectives, or a combination of them (e.g., Kimberley 1979 ; Birkinshaw et al. 2008 ), when studying organizational innovations. This paper is primarily based on a combination of two perspectives: the rational perspective (Birkinshaw et al. 2008 ) and the innovation systems perspective (Alänge et al. 1998 ). The main reason for this is the belief that managers take on a leading and at least “bounded rational” (Simon 1979 ) role in the creation, diffusion, and sustaining of an organizational innovation, and the innovation systems perspective is useful in terms of better understanding the three concepts, specifically when the innovation systems perspective (most commonly focused on inter-firm/organization diffusion of innovations) is complemented with literature dealing with intra-firm/organization diffusion and change management in general (Alänge et al. 1998 ).

Creation of organizational innovations

Several attempts have been made to explore the concept “creation of organizational innovations” (e.g., Birkinshaw and Mol 2006 ). In the Birkinshaw et al. ( 2008 ) model Footnote 5 the creation of organizational innovations is influenced by four sets of factors: the environmental context, the organizational context, and external and internal change agents. The environmental context is described as: “The broad set of stimuli – exogenous to the focal organization – that shapes the management discourse and thereby influences the priorities and efforts of external change agents as they engage with organizations.” (p. 833). The organizational context is the: “Administrative and social mechanisms that management can manipulate to shape the behavior of actors in the organization … and will have a direct impact (positive or negative) on the ability of internal change agents to pursue the core activities associated with management innovation.” (p. 833). External change agents are considered to be: “Management intellectuals, idea entrepreneurs, independent consultants, academics and gurus proactive in creating interest in, influencing the development of, and legitimizing the effectiveness and retention of new management practices.” (p. 832). Finally, internal change agents are considered to be: “Employees of the innovating company proactive in creating interest in, experimenting with, and validating the management innovation in question” (p. 832).

Ganter and Hecker ( 2013 ) compared their findings on antecedents of organizational innovation with the model developed by Birkinshaw et al. ( 2008 ). Ganter and Hecker emphasized the importance of factors in the organizational context and what they labeled “knowledge-based relations,” which could be interpreted as the external and internal change agents in the model of Birkenshaw et al. However, Ganter and Hecker ( 2013 ) also saw a need to extend the Birkinshaw et al. ( 2008 ) model with factors characterizing the firm’s competitive environment such as the intensity of competition, the speed of technological change, and the brevity of the product life cycle.

The Birkinshaw et al. ( 2008 ) model consists of four steps: motivation, invention, implementation, and theorizing and labeling. The “motivation” step is concerned with factors that create the motives, and thereby the desirability, to change the organization. The next step, “invention,” involves experimentation. This step includes activities such as developing a solution, thinking through the consequences of the new idea, linking the idea to empirical data, and testing it in practice. The following step, “implementation,” covers all activities after the test until the new innovation is fully operational. Finally, the last step, “theorizing and labeling,” aims to build a rationale for why the innovation should be adopted, giving the innovation a name and communicating the rationale and the innovation internally as well as externally. Kimberley ( 1979 ) found that the first “release” of the innovation puts important constraints on later developments of organizational innovations. This finding means that the original innovation and later re-inventions of that innovation are path-dependent; in other words, the initial “release” of an organizational innovation will shape later releases of it. However, Lounsbury and Crumley ( 2007 ) comment upon that latter stages of practice creation, where new sets of activities are theorized (in order to facilitate their spread), tend to be emphasized, bracketing the earliest moments when the possibility of a new practice first emerges and is recognized as an opportunity for some social group. They therefore argued for a more comprehensive institutionalist approach to the problem of practice creation that extends the scope of analysis to organizational activities and processes that occur prior to theorization efforts and diffusion-driven taken-for-grantedness.

As with technical innovations (Rosenberg 1976 ; Ehrnberg and Jacobsson 1991 ; Rogers 1995 ), earlier research (Alänge et al. 1998 ) Footnote 6 found that the creation and diffusion of organizational innovations formed two intertwined concepts, which made it hard to study the creation of organizational innovations separately from their inter-firm and intra-firm diffusion. However, Birkinshaw et al. ( 2008 ) explored the creation of management innovations without considering diffusion. Consequently, they defined management innovations as “new-to-the-state-of-the-art,” rather than “new to the firm,” and stated that the literature on inter-firm diffusion is of limited value for explaining the creation of management innovations. This would indicate that the process of creating management innovations starts more or less inside the boundary of the firm or other organizations, rather than within an innovation system. This is surprising, since Birkinshaw et al. ( 2008 ) discussed the importance of the external context and external change agents.

However, when the Alänge et al. ( 1998 ) analytical framework was tested empirically to study the diffusion of organizational innovations, a number of theoretical assumptions proved to be incorrect, and new findings were identified (Alänge and Steiber 2011 ). First, due to the tacit nature of organizational innovations, two aspects were found to be important with regard to the innovation itself. First, as assumed in Alänge et al. ( 1998 ), the separation between the innovation process and the diffusion process was even less relevant for organizational innovations than for technical innovations. Second, organizational innovations were re-invented (Rogers 1995 ) and standardized (Alänge et al. 1998 ) while diffusing. The organizational innovation was therefore continuously re-invented through the inter-firm and intra-firm diffusion processes. This observation is also in contrast to the static definition of organizational innovation by the OECD ( 2005 , p. 53), which makes the following comment on the meaning of organizational innovations:

Changes in business practices, workplace organisation or external relations that are based on organisational methods already in use…are not organisational innovations … However, organisational changes that are implemented … are an innovation if they represent the first implementation of a new organisational method in business practices, workplace organisation or external relations.

Furthermore, Alänge and Steiber ( 2011 ) found that the standardizations of the innovation itself, as well as of its implementation, were enacted at both national and firm/organization levels. Bridging institutions and consultants (Bessant and Rush 1995 ; Wright et al. 2012 ) were found to play an important role in the process of standardizing (or re-standardizing) the organizational innovation at the national level, while early adopters influenced the initial standardization of the innovation at the level of the firm/organization. In comparison, Ganter and Hecker ( 2013 ) did not find that market sources (consultants) were important, while professional sources (industry organizations, professional associations, etc.) played a major role among knowledge-based relations in their German sample.

Diffusion of organizational innovations

The model by (Birkinshaw et al. 2008 , p. 832) is similar to the diffusion model developed in Jarnehammar ( 1995 ) and used by Alänge and Steiber ( 2011 ), which focused on both the inter-firm and intra-firm diffusion processes of organizational innovations. Jarnehammar’s ( 1995 ) model included four steps in the diffusion process: desirability, feasibility, first trial, and implementation. Desirability, feasibility, and first trial are covered in Birkinshaw et al.’s ( 2008 ) motivation and invention steps, while the implementation step is similar between the two models. The main difference between the two models is the theorizing and labeling step (Strang and Meyer 1993 ), which is not presented as a step but is covered by the term “standardization” in the model presented by Jarnehammar ( 1995 ). The close match between the two models, which had different purposes, is perhaps not surprising as Birkinshaw et al. ( 2008 ) implicitly included thoughts of both inter-firm and intra-firm diffusion in their model.

So, what can be learned from studies on the concept of the diffusion of innovations? Previous studies on this subject focus largely upon the diffusion of technical innovations, while scholars have less frequently studied the diffusion of organizational innovations (Teece 1980 ; Rogers 1995 ; Lynch 2007 ; Birkinshaw et al. 2008 ). This gap in the research literature has therefore been emphasized as an area to be addressed (Lynch 2007 ; Birkinshaw et al. 2008 ).

Already, Teece ( 1980 ) raised the question of whether the diffusion of organizational innovations is characterized by the same considerations as the diffusion of technical innovations, and if so, it might be possible to re-use lessons from the area of the diffusion of technical innovations. However, organizational innovations have some intrinsic features that are quite different from those of technical innovations (Alänge et al. 1998 ). Organizational innovations are more tacit in nature than technical innovations; there is no traditional market for organizational innovations, and no traditional calculation model for calculating return on investment for organizational innovations. Further, although organizational innovations commonly affect the daily work situation of many people in an organization, companies rarely have a formal position or formal strategies in place for organizational innovations as they would an R&D manager and R&D strategies for technical innovations. As a result, the market mechanisms function poorly, the search and learning processes may be less conscious and systematic, standardization of the innovations is based on subjective interpretations of early adopters, and top management commitment and the process of intra-firm diffusion of organizational innovations become more important than in the case of technical innovations.

In spite of the intrinsic feature differences identified, Alänge et al. ( 1998 ) concluded that insights from studies on technical innovations could be effectively applied to a study of the diffusion of organizational innovations. However, Alänge et al. ( 1998 ) drew a number of implications for the study of the diffusion of organizational innovations. Due to organizational innovations’ higher degree of tacitness, they are less observable and testable compared to technical innovations, especially if the organizational innovation is also complex—for instance, if it affects many parts of the organization. In addition, organizational innovations can be assumed to affect a higher number of people and are harder to evaluate, as there is no traditional financial calculation method in the case of this type of innovation. As a result, the process of standardization, top management support and “belief” in the relative advantages, and compatibility between the new innovation and previously adopted innovations play a more important role for organizational innovations than for technical innovations.

Further, the interdependence between innovations, the subjective determination of boundaries around an innovation, and the continuous re-invention of the innovation are all more relevant to consider compared with the case of technical innovations (Alänge et al. 1998 ). Further, networks play an important role in both cases for the diffusion of innovations (Frambach and Schillewaert 2002 ); however, in the case of organizational innovations, interpersonal networks are the main channels for diffusion. Due to a lack of a traditional market, the local institutional setup, user networks, consulting firms, and movements of people all play an important role for the diffusion of organizational innovations.

When testing the Alänge et al. ( 1998 ) analytical framework empirically, Alänge and Steiber ( 2011 ) found that the internal context was influential in several ways. To begin with, the characteristics of the search and learning processes for organizational innovations were indeed cumulative and path-dependent, and also conscious and systematic, and affected both by the local environment and by international “weak ties” (Granovetter 1973 ). Each organization initially focused on sub-components that were most familiar to them, which created a form of inertia through interdependences with earlier or parallel organizational innovations. The finding that the search and learning processes were conscious and systematic, local and international, was contrary to the original assumption in Alänge et al. ( 1998 ). Further, the perceived organizational distance affected the search and learning processes in two ways. First, a large organizational distance blocks the initial perceptions of desirability and feasibility. Second, a large organizational distance at a process level hinders diffusion during first trial and implementation.

Moreover, inertia and resistance towards the organizational innovation constitute an influencing factor, but were not found to exist to any larger extent than in the case of technical innovations. Some explanations for this refer to the commitment of, and communication from, top management and the use of pilot studies of sub-components. Such use of pilot studies contradicts Teece’s ( 1980 ) assumption that an incremental implementation is less likely for organizational innovations. The organizational innovation in our studies was later adjusted to the local context, based on experiences from pilot tests and the implementation process. In addition to lowering the transfer and implementation costs, the standardization also decreased resistance towards the change among the organizational members.

In addition, due to the possibility of observing and testing the innovation, or part of it, the transfer and implementation costs were perceived as manageable. On the other hand, decision criteria for investing in an organizational innovation were not discussed in the selected theoretical literature. However, based on the empirical findings in Alänge and Steiber ( 2011 ), the assumption that there is a lack of more traditional calculation models for investments in organizational innovations seemed to be correct. The decision to invest was instead influenced by a number of triggers during different steps in the diffusion process. For example, the desirability was influenced by demand from the corporate group management, perceived crises, fads, awareness of role-model organizations (such as Toyota), market demands, the work of national bridging institutions, and user networks, while perceived feasibility was influenced by aspects such as user networks at a low organizational distance, previously adopted organizational innovations, the CEO’s previous experience, and the work of national bridging institutions. The final decision to test and later implement the innovation was then primarily based on the CEO’s belief in the benefits of the organizational innovation. This belief had to be sustained in order to sustain the innovation. In the empirical studies, the top managements’ beliefs persisted over time, but theoretically this belief could also have been negatively affected by the same triggers as those that created the desire and feasibility for the innovation, or by unreasonably high internal inertia.

The external context, or in Rogers’ ( 1995 ) words, “the social structure,” was found to influence the rate of diffusion of organizational innovations. The institutional setup , the existence of international and national fads (Abrahamson 1996 ), the existence of new market needs , the presence of consulting firms and non-market-mediated interpersonal contacts through user networks (which include links to firms/organizations at a limited organizational distance implementing the same innovation), and movement of people all influenced the rate of diffusion of a major organizational innovation and substituted a traditional market. As a consequence, individuals’ networks, such as with standardization and industry organizations, companies that already had adopted the innovations, and people with experience of the innovation, played a profound role in the case of organizational innovations (Rogers 1995 ; Alänge and Steiber 2011 ).

However, the inertia and path dependency of the external context itself also influenced the rate of diffusion. The importance of local norms and historical experience has been emphasized by Rogers ( 1995 ), as well as research focusing on national and regional innovation systems (Lundvall 1992 ; Saxenian 1996 ; Cooke 2001 ). According to Rogers, relatively few studies have been conducted on how the social structure affects the diffusion of innovations; thus, both the local institutional setup and the importance of norms and historical experience on a nation and/or region’s innovativeness should be considered in a conceptualization of the creation, diffusion, and sustaining of organizational innovations. In addition, there is an interaction between technical systems/artifacts and social systems that affects all change processes (Cummings and O’Connell 1978 ; Tichy 1983 ; Langstrand and Elg 2012 ; Bayerl et al. 2013 ), and it has been emphasized that the cultural and political systems and the technical design (social and technical systems) need to be considered simultaneously (Tichy 1983 ; Alänge 1992 ). Hence, both the setup and inertia of the local innovation system and individual firm/organization characteristics, such as user competence and top management behavior, play important roles for unlearning/learning in the diffusion of organizational innovations (Alänge et al. 1998 ).

Sustaining organizational innovations

Sustaining an organizational innovation emphasizes that a firm or organization should maintain a particular organizational innovation for a certain time period, which could be a sign of inertia (Buchanan et al. 2005 ). However, as pointed out above, innovations are constantly re-invented, and thus the concept of “sustaining” has to be elaborated upon. According to Buchanan et al. ( 2005 ), sustaining could refer to an improvement trajectory, rather than to a particular organizational innovation. According to the authors, this implies a more dynamic perspective on sustaining organizational change. The static view of sustaining a particular organizational innovation would then be only temporarily relevant.

After conducting a review of the literature on sustaining organizational change, Buchanan et al. ( 2005 ) identified four sets of factors that all play a role: 1) external context that includes factors such as turbulence and uncertainty in the external environment; 2) internal context that refers to a firm’s history and therefore its receptiveness to change; 3) substance of change (e.g., whether the organizational innovation is perceived as important for the firm), change process and timing ; and 4) seven organizational factors (managerial, leadership, cultural, organizational, individual, political, and financial) that influence sustaining (factors that can be configured and interact in different ways). The relative importance of each set (and each factor within each set) was not identified by the authors, but Buchanan et al. ( 2005 ) emphasized that the interplay between the factors plays an important role.

Buchanan et al. ( 2005 ) identified a number of factors similar to those found in studies on the creation and diffusion of organizational innovations. The external context and the firm’s inertia and path dependency seem to play a role in all three processes. In addition, the innovation’s perceived importance for the organization and the timing of the innovation matter in all three processes. Two aspects are partly new in Buchanan et al.’s ( 2005 ) model: first, the change process as such, which was not discussed by Birkinshaw et al. ( 2008 ) and was discussed only indirectly as an issue of standardization in the “implementation” step in (Alänge et al. 1998 ); and second, the external turbulence and uncertainty, which was identified as an inhibitor for sustaining an organizational innovation. The latter finding is of interest, as it could mean that it would be harder for a firm to sustain a particular organizational innovation in a rapidly changing industry than in a case in which the industry is more mature. This in turn means that the focus would be on an improvement trajectory, instead of a particular organizational innovation, which could be of even higher relevance for firms in rapidly changing industries and could therefore fit well with the ideas regarding the constant renewal that is necessary in rapidly changing industries developed by Brown and Eisenhardt ( 1997 , 1998 ). Sustaining of a particular organizational innovation therefore can only be temporal and seems to be less relevant in rapidly changing environments.

The improvement trajectory can be viewed as a number of synergistic and complementary organizational innovations, since the firm and its search and learning processes are path-dependent. For this reason, the initial innovation puts constraints on later development within the organization (Kimberley 1979 ). In the event that a later implemented organizational innovation is not synergistic with, or complementary to, the already-implemented innovation, the new innovation might be seen as the start of a new improvement trajectory. Standardization, road maps, and narratives could be used to either strengthen a certain trajectory or communicate and make sense of a new direction (Shiba et al. 1993 ; Alänge 1994 ; Berendse et al. 2006 ). At certain points in time, influenced by external and internal changes, it could be assumed that a given trajectory is partly (or totally) broken, and therefore partly (or fully) exchanged with a trajectory that has a new goal, and therefore a new direction—for example, if a firm changes its focus from cost-cutting to innovation. However, the shift from one trajectory to another can be very problematic when the values/beliefs, skills, practices, and systems that were once core capabilities turn into core rigidities (Leonard-Barton 1992 ), and there is also a need to consider the role of unlearning to catalyze learning processes in order to change beliefs and routines in organizations (Akgün et al. 2007 ).

Alänge and Steiber ( 2011 ) found that the importance of top management involvement and visible support in order to implement organizational innovations was of greater magnitude than in the case of technical innovations, as a major organizational change takes years to implement and affects a large number of people within the organization. However, top management commitment alone was not enough for sustaining an organizational innovation. Alänge and Steiber ( 2011 ) also identified the need for a more long-term view in order to sustain organizational innovations—a view that goes beyond the time that the average CEO stays at the helm.

This observation pointed to the importance of including owners and boards in the matter of organizational innovations, a finding that has not been emphasized in earlier research. In fact, very little has been written overall about boards’ roles in the creation, diffusion, and sustaining of organizational innovations. The empirical finding in Alänge and Steiber ( 2009 ), however, was that boards affect the sustaining of major organizational innovations. They identified a number of issues critical for creating board commitment for sustaining a major organizational innovation: board competence and experience, board meeting dynamics, provider of critical resources, and the process for replacing CEOs. However, underlying theories (Principal–Agency theory, Stewardship theory, and Resource Dependence theory) on how to best govern a firm or other organizations were found to affect boards’ perceptions of their mission and main roles. The dominant theory, Principal–Agency theory, may negatively affect boards’ involvement in, and commitment to, sustaining a major organizational innovation, while the other two theories enable both a closer relationship between the board and CEO, and more active board roles, such as, for example, the role as a resource provider. In fact, boards could have an important role to play not only in sustaining an organizational innovation, or trajectory, but also in the creation and diffusion of organizational innovations. Boards can be assumed to affect investment decisions on any innovation, and to provide access to resources and networks, and thereby facilitate inter-firm diffusion of ideas. Finally, boards can ensure macro-stability when organizational innovations require many years to be fully implemented. According to Alänge and Steiber ( 2009 ), a board must therefore have insight into how it affects the sustaining of implemented organizational innovations. Further, a board must view itself as an organizational body that can and must provide critical resources to the firm/organization. As a consequence, a board must proactively gather knowledge about the firm/organization and its industry and create an effective board group and work processes based on norms that support a strategic, collaborative, innovative, and open environment within the board and between the board and CEO. In addition, a board must take responsibility for creating a process that ensures a certain organizational trajectory can be sustained in case the CEO is replaced.

A comprehensive model

Based on the literature reviews and input from the two empirical studies (Alänge and Steiber 2009 , 2011 ) with a longitudinal perspective, we will now introduce a comprehensive model for the creation, diffusion, and sustaining of organizational innovations. As the creation, diffusion, and sustaining of an organizational innovation can be viewed as three intertwined concepts, they should not be explored in isolation. Therefore, in order to study these three aspects in an integrated way, a comprehensive model is suggested. This model includes five steps : desirability, feasibility, first trial, implementing, and sustaining. These five steps are subject to three sets of influencing factors: set 1, the characteristics of the innovation itself; set 2, the internal context; and set 3, the external context and diffusion channels. Further, each step is influenced by triggers, visualized as flashes in the model. The triggers could be valid for one or several steps. The model and its main components are presented in Fig.  1 .

A conceptual model for the creation, diffusion, and sustaining of organizational innovations

Drawing the model as a static, two-dimensional linear model creates a dilemma, since the creation, diffusion, and sustaining of organizational innovations are not linear concepts but rather are highly intertwined, due to the fact that the innovation is constantly re-invented. For this reason, it is necessary to add a dynamic perspective to the model. In Fig.  1 , the five steps desirability, feasibility, first trial, implementing, and sustaining are therefore visualized as a circular pattern around an organizational improvement trajectory . The re-invention of the innovation is path-dependent and cumulative due to internal inertia among top managers and employees. Thus, the desirability and perceived feasibility of a new organizational innovation as well as the decisions if to trial and if to implement are affected by previously chosen organizational innovations. In cases where a follow-up innovation substitutes or competes with an implemented organizational innovation, a totally new organizational improvement trajectory may result. Therefore, the concept of “sustaining” does not refer to a particular organizational innovation, but rather to an organizational improvement trajectory. This trajectory is also influenced by the organization’s inertia and path dependency and thus affects the search and learning processes for future organizational innovations.

On a national and even international level, there are organizational improvement trajectories as well, where organizational innovations diffuse between firms or organizations and are gradually re-invented, and at a certain point in time are challenged by new organizational innovations based on a new way of thinking in management (Lundgren and Alänge 2000 ; Alänge and Steiber 2011 ). When national/international improvement trajectories are based on complex organizational innovations, such as TQM and Lean, there can also be a considerable overlap in terms of content between parallel trajectories. These national/international improvement trajectories naturally have a considerable influence on an individual organization’s improvement trajectory (Alänge and Steiber 2011 ).

The inner circle in Fig.  1 represents the internal context in an organization. Here, the top management and the board are crucial for sustaining, and also in some cases creating, the improvement trajectory. Top management’s own inertia, user competence, and commitment to the innovation and the organizational improvement trajectory are important and can either limit or increase the internal inertia/path dependency and resistance towards change. Here, top management can use communication, for example, in the form of narratives and road maps to limit internal inertia and resistance to a desired organizational change. Further, the search and learning processes are cumulative and path-dependent, but could break potential inertia by becoming more conscious and systematic in the desirability and feasibility steps.

The two outer circles represent the external context and diffusion channels that transfer knowledge and experience into the organization. The outermost circle area depicts the external environment in the form of institutional setup, local norms, history, and existing weak ties that the organization has through its employees with networks that are active outside the local context. The external environment also represents factors such as the sector characteristic competitive pressure and dynamic, due to e.g. pace in technological development. The dotted area represents diffusion channels such as movement of people (including CEOs), boards, user networks, bridging institutions, universities, and consultants. These diffusion channels could all play a role in “showing” and “proving” what is desirable and feasible.

The triggers (visualized as flashes in Fig.  2 ) for each step in the five-step process could typically be a perceived crisis, a new market or owner demand (which in turn could have been triggered by technological development and lower entry barrier in a certain sector), imitation of organizational concepts developed by other companies in the user network, management previous experience and beliefs in the innovation, standardization work done by bridging institutions, consultants and university professors, and management fads. An example of a trigger that influences several steps is “management beliefs,” which in turn is partly based on management’s experience of the innovation. An example of a trigger that was found to be more related to a single step was “consultant experience,” which was commonly found in the first trial step and less so in earlier or later steps.

A comprehensive model for the creation, diffusion, and sustaining of organizational innovations

The comprehensive model, now including all factors mentioned in the discussion above, is presented in Fig.  2 .

As could be seen in the comprehensive model in Fig.  2 , an organization is triggered by e.g. a new market or owner demand or a perceived crisis (triggers: text in italics ). This in turn creates a desire to conduct an organizational development and change. The search and learning process for feasible organizational concepts, e.g., Lean Production or TQM, is cumulative, path-dependent, and to a certain degree conscious and systematic. The search and learning process is triggered and influenced by managers’ previous experience, imitation of other organizations (often with a low organizational distance), earlier adopted and implemented organizational innovations (inertia and path dependency), and also the characteristics of the new innovation as such, e.g., if it is well standardized and therefore is easier to “observe.” However, also external factors such as history, local norms, competitive pressure, and the so-called weak ties (see the outermost circle in Fig.  2 ) could affect perceived “feasibility” of the new innovation. The institutional setup influence as well as knowledge and experience of universities and consultants and the work of bridging organizations matter as “diffusion channels” (see uppercase text in dotted circle). When the organization perceives a certain organizational innovation as feasible, the next step is to conduct a first trial. In this step, the innovation is partly re-invented and internally standardized in order to better fit with the specific organization. Factors such as user competence, inertia, and path dependency in the internal context are affecting this re-inventing process. In this step, university professionals and consultants could play an important role as a trigger and as a diffusion mechanism for knowledge and experience of the new innovation. Based on lessons learned during first trial, the innovation is once again re-invented and internally standardized, which makes an implementation possible as it reduces resistance to change. However, also during implementation, internal inertia and path dependency are influencing how the new innovation is re-invented and standardized. The process of continuous re-invention and standardization of the new innovation is continuing throughout implementation and later in order to sustain the implemented innovation. During these two steps “implementing” and “sustaining,” management beliefs on the innovation do play an important role. Visible benefits from the new innovation are important in order to strengthen management beliefs and increase internal overall support for change. Boards as a diffusion mechanism for knowledge and experience of new organizational innovations could play an important role as both an initial trigger to organizational change and for sustaining an implemented change in the organization. For this reason, the user competence among board members regarding the new organizational innovation and their belief in its business value for the organization is important (Alänge and Steiber 2009 ).

As commented upon in the “ Methodology ” section, the framework presented in Fig.  2 was used in a study for the Swedish Innovation agency “VINNOVA” (a comparative analysis of seven European and North American national/international programs for the dissemination of organizational innovations contributing to increased competitiveness among existing firms). This study (Steiber and Alänge 2013a ) showed that the framework was useful for analyzing both similarities and differences between the seven different programs. For example, the five steps in the intra-firm diffusion process were all valid and relevant when analyzing a program’s design (see Fig.  2 ). Steps such as “Desirability” and “Feasibility” were in several programs positively influenced by strategically designed awareness activities and training for (potentially) participating organizations and their managers. Issues such as user competence, inertia, and path dependency on an organizational level also affected the “Desirability” and “Feasibility” steps. For this reason, some of the programs choose to actively promote the disseminated organizational innovation as a concept that “complements” the adopting organization’s existing product development process, rather than “replacing” it. Further, the external context, such as history, culture, and local institutional setup, influenced the dissemination of the specific organizational innovation. In fact, the local resources’ part of the institutional setup showed to play a crucial role in the dissemination of the specific organizational innovations. In most cases, these local resources, e.g., in the form of consultants, research institutes, and industry associations, needed both education and training, even in cases when the organizational innovation was more standardized, such as Lean Production. Finally, the primary diffusion mechanisms identified in the seven programs were universities, consultants, people, user networks (role models), research institutes, and industry associations. However, also local governmental organizations as well as non-profit organizations showed to play a role as diffusion channels.

Seen from a triple helix perspective, any organization from either one helix (industry, university, or government) has its own improvement trajectory, which is influenced by other organizations (and their improvement trajectories) both from within the same and other helices. During dissemination processes, there is a need for a certain degree of regional/national agreement (or consensus space, cf. Etzkowitz and Ranga 2012 ) concerning the characteristics of organizational innovations (such as TQM or Lean) and of their dissemination processes. In the case this regional/national agreement or consensus space exists between key actors from the three helices, the regional or national dissemination process for a certain organizational innovation could be expected to become more effective. The Triple Helix dynamics could therefore be expected to directly influence the effectiveness of the creation, diffusion, and sustaining of an organizational innovation. Further, the Triple Helix dynamics could be assumed to play an even more important role in the case the new organizational innovation is hard to observe and test; when it is complex, that is, it affects most parts of a firm or organization; when the knowledge about the new innovation is low among players in the institutional setup, e.g., universities and consultants; and where there is a low compatibility between the new innovation and what has been previously adopted and implemented by firms and organizations in the specific region or nation.

One illustrative example, of how a Triple Helix dynamics benefitted the dissemination of a complex organizational innovation, is the initiation of the “Production Leap,” one of the seven programs investigated in the VINNOVA study (Steiber and Alänge 2013a ). This program was initiated by a combination of actors—the Royal Academy of Engineering Sciences, a labor union and an employer organization—becoming aware of the increased international competition for small- and medium-sized enterprises (SMEs) and reaching consensus of a need for a national program to disseminate “Lean Production” to Swedish SMEs. The characteristics of this organizational innovation and of its dissemination process showed to be in continual development through various collective learning processes and hence can be described as a trajectory not only on a regional/national level but also on a program level (Steiber and Alänge 2013a ).

Conclusions and future research

The purpose of this paper was to develop a comprehensive model for studying and better understanding the creation, diffusion, and sustaining of organizational innovations by using a system perspective. One important finding is that previous research, including our own from several empirical case studies, clearly converges towards certain “steps” in an organizational change process, as well as to certain “sets of influencing factors” that can support or hinder the inter-firm and intra-firm dissemination process of an organizational innovation.

A first conclusion is therefore that the model could be visualized as five steps (desirability, feasibility, first trial, implementing, and sustaining) that are in turn influenced by three main sets of influencing factors: the characteristics of the innovation itself, the internal context, and the external context together with different types of diffusion channels transferring knowledge from external sources to the organization.

However, drawing the model as a static, two-dimensional linear model creates a dilemma, which leads us to our second conclusion, namely that the creation, diffusion, and sustaining of organizational innovations are not linear, sequential concepts but rather are highly intertwined, due to the fact that the organizational innovation is constantly re-invented. For this reason, it does not make sense to speak of or study each concept in isolation as both Birkinshaw et al. ( 2008 ) and Buchanan et al. ( 2005 ) did.

The third conclusion is that the concept “sustaining” of organizational innovations refers to an organization’s improvement trajectory, rather than to a particular organizational innovation. This means that a major organizational innovation such as TQM exists therefore over time in several “releases” in an adopting organization. Each release is valid only temporarily, since it is constantly re-invented as a result of continuous external and internal triggers for change. Further, the improvement trajectory is path-dependent and cumulative due to internal inertia among top managers and employees, so the decision to adopt new organizational innovations is affected by the historically chosen ones.

Finally, national or even international organizational improvement trajectories (both TQM and Lean and potentially in the future “Innovation Management” are all examples of major organizational innovations that have been key concepts in international and national organizational improvement trajectories) naturally have a considerable influence on an individual organization’s improvement trajectory (Alänge and Steiber 2011 ).

This paper is planned to be the first of two. The follow-up paper will serve the purpose of verifying the model developed in this paper by testing it on another type of organizational innovation, different from TQM, TPS, and Lean that were studied in Alänge and Steiber ( 2009 , 2011 ). By doing this, we can verify if the characteristics of an organizational innovation affect the applicability of the comprehensive model. TQM, TPS, and Lean were all developed in a context of continuous improvement with the aim of achieving quality and efficiency, and they all draw strongly on the experiences of Toyota in Japan. The organizational innovation chosen for the follow-up paper is the Google Model, which focuses primarily on continual innovation and has been developed in the Internet industry in Silicon Valley, USA. In recent years, the Google Model has been branded as a unique management model, and publications such as “The Google Way: How One Company is Revolutionizing Management As We Know it” (Girard 2009 ), “Googled: The End of the World as We Know It” (Auletta 2009 ), and “A Corporate System for Continuous Innovation: The case of Google Inc.” (Steiber and Alänge 2013b ) support a picture of the Google Model as an organizational innovation.

The suggestion for future research is to further validate and refine this more comprehensive model by testing it not only on more types of organizational innovations but also on more types of organizations, e.g., within the university and government helices. In addition, there is a need to identify the importance of differences in underlying institutional environments by testing it in other countries than Sweden.

It would also be valuable to further explore the value of using a concept such as an organizational improvement trajectory to explain a firm’s or other organizations’ organizational development, and its conscious and unconscious choices when adopting organizational innovations.

Finally, it would be of value to further test the model by using other perspectives, e.g., an open innovation perspective where organizational innovations might be created, diffused, and/or sustained either as a result from a learning process when a firm or organization is co-creating collaboratively with external partners, or as a direct result from the co-creation and collaboration process. In addition, Steiber and Alänge ( 2013a ) indicate that the Triple Helix dynamics do influence the dissemination process of organizational innovations. It would therefore also be of value to test how the Triple Helix dynamics influence the creation, diffusion, and sustaining of organizational innovations.

This part of the research literature is using a national or regional innovation system perspective, i.e., the same perspective as we have chosen (together with a rational perspective); see the “ The creation and diffusion of organizational innovations ” section. Research literature using other perspectives, e.g., an open innovation or more general co-creating and knowledge networking perspective, e.g. Savage 1996 (Fifth Generation Management), Amidon 1997 (Knowledge Innovation), and Mercier-Laurent 2011 (Innovation Ecosystems), were not included in this review of literature on the creation, diffusion, and sustaining of technical innovations.

In Alänge et al. ( 1998 ), organizational innovation was found hard to separate from inter-firm diffusion as it was constantly re-invented/re-created during the diffusion process. This was also the case in the intra-firm diffusion process, with respect to implementing and sustaining the organizational innovation.

In this paper, the concepts “organizational innovations,” “administrative innovations,” and “managerial innovations” are used interchangeably.

However, important to notice is that an organizational innovation that is “new to the organization” still can be disruptive, e.g., for the specific industry that the organization act in. In addition, a “new to the organization” innovation can support both incremental and more disruptive technical innovations developed and implemented by the organization. One such example is the dissemination, adaptation, and implementation of methods and tools for “Innovation Management.” Broadly, Innovation Management could be viewed as how to manage and organize not only for a more effective innovation process but also for securing a higher level of impact from generated innovations. The optimal case is when an organization can generate both incremental and disruptive innovations.

The model is based on an earlier model by Birkinshaw and Mol ( 2006 ). However, this previous model separated motivation into two steps—dissatisfaction with the status quo and inspiration—which the authors claimed usually comes from outside the firm. Further, the model did not include an “implementation” step.

In Alänge et al. ( 1998 ), it was found that innovation and diffusion cannot be distinguished in a meaningful way, but that the diffusion curve should be seen as an envelope curve, superimposed with a number of minor diffusion curves.

Abrahamson E (1996) Management fashion. Acad Manage Rev 21(1):254–285

Google Scholar  

Akgün AE, Byrne JC, Lynn GS, Keskin H (2007) Organizational unlearning as changes in beliefs and routines of organizations. J Organ Change Manage 20(6):794–812

Article   Google Scholar  

Alänge S (1992) Total Quality Management as a tool for organizational change – the case of Motorola. CIM Working Papers WP 1992:01

Alänge S (1994) The new paradigm for industrial practices: Total Quality Management in 1994. CIM Working Papers WP 1994-01

Alänge S, Steiber A (2009) The board’s role in sustaining major organizational change – an empirical analysis of three change programs. Int J Qual Serv Scie 1(3):280–293

Alänge S, Steiber A (2011) Diffusion of organizational innovations: an empirical test of an analytical framework. Technol Anal Strateg Manage 23(8):881–897

Alänge S, Jacobsson S, Jarnehammar A (1998) Some aspects of an analytical framework for studying the diffusion of organizational innovations. Technol Anal Strateg Manage 10(1):3–21

Amidon DM (1997) Innovation strategy for the knowledge economy: the Ken awakening. Butterworth-Heinemann, Newton, MA

Auletta K (2009) Googled: the end of the world as we know it. The Penguin Press, New York

Bayerl PS, Jacobs G, Denef S et al (2013) The role of macro context for the link between technological and organizational change. J Organ Change Manage 26(5):793–810

Berendse M, Duijnhoven H, Veenwijk M (2006) Editing narratives of change: identity and legitimacy in complex innovative infrastructure organizations. Interv Res 2(1–2):73–89

Bessant J, Rush H (1995) Building bridges for innovation: the role of consultants in technology transfer. Res Policy 24:97–114

Birkinshaw J, Mol M (2006) How management innovation happens. MIT Sloan Manage Rev 47(4):81–88

Birkinshaw J, Hamel G, Mol MJ (2008) Management innovation. Acad Manage Rev 33(4):825–845

Brown SL, Eisenhardt KM (1997) The art of continuous change: linking complexity theory and time-paced evolution in relentlessly shifting organizations. Adm Sci Q 42:1–34

Brown SL, Eisenhardt KM (1998) Competing on the edge: strategy as structured chaos. Harvard Business School Press, Boston

Buchanan D, Fitzgerald L, Ketley D, Gollop R, Jones JL, Lamont SS, Neath A, Whitby E (2005) No going back: a review of the literature on sustaining organizational change. Int J Manage Rev 7(3):189–205

Carlsson B, Jacobsson S (1994) Technological systems and economic policy: the diffusion of factory automation in Sweden. Res Policy 23:235–248

Carlsson B, Stankiewicz R (1991) On the nature, function, and composition of technological systems. J Evol Econ 2(1):93–118

Cooke P (2001) Regional innovation systems, clusters, and the knowledge economy. Oxford University Press, Oxford, pp 945–974

Cummings LL, O’Connell MJ (1978) Organizational innovation: a model and needed research. J Bus Res 6:33–50

Dubois A, Gadde L-E (2002) Systematic combining: an abductive approach to case research. J Bus Res 55(7):553–560

Edquist C (1992) Technological and organizational innovations, productivity and employment. World Employment Programme Research Working Paper WEP 2-22/WP 233 http://www.ilo.org/public/libdoc/ilo/1992/92B09_223_engl.pdf Accessed 17 November 2013

Ehrnberg E, Jacobsson S (1991) Technological discontinuities, industry structure and firm strategy – the case of machine tools and flexible manufacturing systems. Department of Industrial Management and Economics, Chalmers University of Technology, Gothenburg

Etzkowitz H, Leydesdorff L (1995) The Triple Helix: university-industry-government relations. A laboratory of knowledge based economic development. EASST Rev 14(1):11–19

Etzkowitz H, Ranga M (2012) ‘Spaces’: a triple helix governance strategy for regional innovation. In: Rickne A et al (eds) Innovation governance in an open economy: shaping regional nodes in a globalized world. Routledge, London, pp 51–68

Frambach RT, Schillewaert N (2002) Organizational innovation adoption - a multi-level framework of determinants and opportunities for future research. J Bus Res 55:163–176

Freeman C (1982) The economics of industrial innovation, 2nd edn. Frances Pinter, London

Freeman C (1987) Technology policy and economic performance: lessons from Japan. Pinter Publications, London

Ganter A, Hecker A (2013) Deciphering antecedents of organizational innovation. J Bus Res 66:575–584

Ganter A, Hecker A (2014) Configurational paths to organizational innovation: qualitative comparative analyses of antecedents and contingencies. J Bus Res 67:1285–1292

Girard B (2009) The Google WAY: how one company is revolutionizing management as we know it. No Starch Press, San Francisco

Granovetter MS (1973) The strength of weak ties. Am J Sociol 78:1360–1380

Hamel G (2006) The why, what, and how of management innovation. Harv Bus Rev 84(2):72–84

Jarnehammar A (1995) Towards a framework for analysing the diffusion of organizational innovations. Licentiate dissertation, Chalmers University of Technology, Gothenburg

Kimberley JR (1979) Issues in the creation of organizations: initiation, innovation, and institutionalization. Acad Manage J 22(3):437–457

Kimberley JR (1981) Managerial innovation. In: Nystroem PC, Starbuck WH (eds) Handbook of organisational design. Oxford University Press, New York

Langstrand J, Elg M (2012) Non-human resistance in changes towards lean. J Organ Change Manage 25(6):853–866

Leonard-Barton D (1988) Implementation as mutual adaptation of technology and organization. Res Policy 17:251–267

Leonard-Barton D (1992) Core capabilities and core rigidities: a paradox in managing new product development. Strateg Manage J 13(Special Issue):111–125

Liker JK (2004) The Toyota way: 14 management principles from the world’s greatest manufacturer. McGraw-Hill, New York

Lounsbury M, Crumley ET (2007) New practice creation: an institutional perspective on innovation. Organ Stud 28:993–1012

Lundgren R, Alänge S (2000) Diffusion of organisational innovations – quality management in Sweden. CIM Working Papers WP 2000:02

Lundvall B-Å (ed) (1992) National systems of innovation: towards a theory of innovation and interactive learning. Anthem Press, London

Lynch LM (2007) The adoption and diffusion of organizational innovation: evidence for the US economy. IZA Discussion Paper No. 2819

Mercier-Laurent E (2011) Innovation ecosystems. John Wiley & Sons, Hoboken, NJ

Book   Google Scholar  

Mol MJ, Birkinshaw J (2009) The sources of management innovation: when firms introduce new management practices. J Bus Res 62:1269–1280

Nelson R (ed) (1993) National innovation systems - a comparative analysis. Oxford University Press, New York

OECD (2005) Oslo manual: guidelines for collecting and interpreting innovation data, 3rd edn. http://www.keepeek.com/Digital-Asset-Management/oecd/science-and-technology/oslo-manual_9789264013100-en#page51 Accessed 1 November 2013

Porter M (1990) The competitive advantage of nations. Macmillan, London

Rogers EM (1995) Diffusion of innovations, 4th edn. Free Press, New York

Rosenberg N (1976) Perspectives on technology. Cambridge University Press, Cambridge, MA

Savage CM (1996) 5th Generation management: co-creating through virtual enterprising, dynamic teaming, and knowledge networking, revised edition. Butterworth-Heinemann, Woburn, MA

Saxenian AL (1996) Regional advantage: culture and competition in Silicon Valley and Route 128. Harvard University Press, Boston

Shiba S, Walden D, Graham A (1993) A new American TQM: four practical revolutions in management. Taylor & Francis, Oxford

Simon H (1979) Rational decision making in business organization. Am Econ Rev 69(4):493–513

Steiber A (2012) Organizational innovations: a conceptualization of how they are created, diffused and sustained. PhD dissertation, Chalmers University of Technology, Gothenburg

Steiber A, Alänge S (2013a) Diffusion of organisational innovations: learning from selected programmes. Vinnova Report VR 2013:07, Vinnova (Swedish Governmental Agency for Innovation Systems), Stockholm

Steiber A, Alänge S (2013b) A corporate system for continuous innovation: the case of Google I nc. Eur J Innov Manage 16(2):243–264

Strang D, Meyer JW (1993) Institutional conditions for diffusion. Theory Soc 22:487–511

Teece D (1980) The diffusion of administrative innovation. Manage Scie 26:464–470

Teece D (2007) Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strateg Manage J 28:1319–1350

Tichy NM (1983) Managing strategic change: technical, political and cultural dynamics. John Wiley & Sons, New York

Tushman ML, O’Reilly C III (1997) Winning through innovation: a practical guide to leading organizational change and renewal. Harvard Business School Press, Boston

Volberda HW, Van den Bosch FAJ, Heij CV (2013) Management innovation: management as fertile ground for innovation. Eur Manage Rev 10:1–15

Womack JP, Jones DT (2003) Lean thinking: banish waste and create wealth in your corporation, 2nd edn. Simon Schuster, London

Wright C, Sturdy A, Wylie N (2012) Management innovation through standardization: consultants as standardizers of organizational practice. Res Policy 41:652–662

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This chapter builds off the first chapter on Innovation in Large Organizations that focused on explaining how innovation can be holistically fostered and then used to combat emerging threats that organizations face. It explored literature-based best practices for cultivating innovation and with those insights developed a model. This chapter explores case studies related to the five insights developed from the model created in the previous chapter. The case studies in particular work to explore the first two intertwined insights: (1) Innovative strategies can help organizations better respond to emerging threats. (2) Innovative problem-solving requires innovative culture. The focus of the case studies is split across three main issue-sets: supply chain disruption, financial crime and export control, and cyber threats. These case studies highlight how innovation can help organizations facing dynamic threats. Across the case studies, solid support is found for the first two hypotheses as well as some support for insights three and five from the previous chapter. Organizations can hopefully use these case studies to inform future strategies to adopt for the purpose of countering existing and future threats.

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Anonymous. (2022a). Innovation in large organizations: Cyber security firm [Online interview].

Google Scholar  

Anonymous. (2022b). Innovation in large organizations: Financial Institution [Telephone interview].

Bhattacharyya, S., Jha, S., Tharakunnel, K., & Westland, J. C. (2011). Data mining for credit card fraud: A comparative study. Decision Support Systems, 50 (3), 602–613. https://doi.org/10.1016/j.dss.2010.08.008

Article   Google Scholar  

Chatfield, A. T., & Reddick, C. G. (2017). Cybersecurity innovation in Government. In Proceedings of the 18th Annual International Conference on Digital Government Research . doi: https://doi.org/10.1145/3085228.3085233 .

CO-OP Financial Services. (2017). Security innovations for the changing face of fraud (Rep.). CO-OP Financial Services.

Estevez, A., Allen, G., & Reinsch, W. (2022). Improving export controls enforcement using data science and artificial intelligence . Lecture Presented in CSIS.

Forbes, P. (2020a, July 22). No store did more: How H-E-B became a model of emergency preparedness . Retrieved 2022, from https://www.texasmonthly.com/news-politics/how-heb-became-emergency-preparedness-model/

Forbes, P. (2020b, March 26). Inside the story of how H-E-B planned for the pandemic . Retrieved 2022, from https://www.texasmonthly.com/food/heb-prepared-coronavirus-pandemic/

IBM. (2019). Large Global Bank . Retrieved 2022, from https://www.ibm.com/case-studies/large-global-bank-security

IBM. (2022). Cost of a Data Breach (Rep.). IBM. doi: https://www.ibm.com/reports/data-breach

IBM Security Services. (2019). Penetration testing: Protect critical assets using an attacker’s mindset (Rep.). IBM.

Michaels, D. (2020, May 04). SEC ramps up whistleblower awards . Retrieved 2022, from https://www.wsj.com/articles/sec-ramps-up-whistleblower-awards-11588614514

Nasdaq Index Research. (2021). Cybersecurity & innovation: The key to a secure future (Rep.). Nasdaq.

Peikin, S. (2020, May 12). Keynote address: Securities enforcement forum west 2020 . Retrieved 2022, from https://www.sec.gov/news/speech/keynote-securities-enforcement-forum-west-2020#_ftn20

Reeves, A. (2022). Innovation in large organizations: CovertSwarm [Online interview].

Sondhi, K. (2022). Innovation in large organizations: Trellix [Online interview].

Sportsman, N. (2022). Innovation in large organizations: Praetorian [Online interview].

Sun, M. (2020, June 01). Tips to SEC surge as working from home emboldens whistleblowers . Retrieved 2022, from https://www.wsj.com/articles/tips-to-sec-surge-as-working-from-home-emboldens-whistleblowers-11591003800

Sun, M. (2021a, April 16). SEC whistleblower program shows value of speaking up, departing chief says . Retrieved 2022, from https://www.wsj.com/articles/sec-whistleblower-program-shows-value-of-speaking-up-departing-chief-says-11618607640

Sun, M. (2021b, August 07). SEC pauses enforcement of some whistleblower program rules . Retrieved 2022, from https://www.wsj.com/articles/sec-pauses-enforcement-of-some-whistleblower-program-rules-11628297604

Sun, M. (2021c, May 18). Anti-money-laundering whistleblower program struggles to get off ground . Retrieved 2022, from https://www.wsj.com/articles/anti-money-laundering-whistleblower-program-struggles-to-get-off-ground-11621362937

Sun, M. (2021d, September 16). SEC issues $114 million to two whistleblowers . Retrieved 2022, from https://www.wsj.com/articles/sec-issues-114-million-to-two-whistleblowers-11631749599

Sun, S. L., Zhang, Y., & Zhu, Z. (2021). Turning disruption into growth opportunity: The red team strategy. Journal of Business Strategy, 43 , 365. https://doi.org/10.1108/jbs-05-2021-0087

U.S. Securities and Exchange Commission. (2021). 2021 Annual report to congress: Whistleblower program (Rep.). U.S. Securities and Exchange Commission. https://www.sec.gov/files/owb-2021-annual-report.pdf

Vultaggio, D. (2022). Innovation in large organizations: Arizona Beverages [Telephone interview].

West, D. (2022, March 09). Using AI and machine learning to reduce government fraud . Retrieved 2022, from https://www.brookings.edu/research/using-ai-and-machine-learning-to-reduce-government-fraud/

Wrona, K. (2017). Innovation in nato: Lessons learned and recommendations. Information & Security: An International Journal, 36 . https://doi.org/10.11610/isij.3603v

Zhu, X., Ao, X., Qin, Z., Chang, Y., Liu, Y., He, Q., & Li, J. (2021). Intelligent financial fraud detection practices in post-pandemic era. The Innovation, 2 (4), 100176. https://doi.org/10.1016/j.xinn.2021.100176

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Kirby, C. (2023). Innovation in Large Organizations: Structuring Organizations to Combat Emerging Threats: Exploration Through Case Studies. In: Gruber, C.W., Trachik, B. (eds) Fostering Innovation in the Intelligence Community. Annals of Theoretical Psychology, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-031-29807-3_9

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• Christopher A. Bartlett
• Carole Carlson

Booking.com

• Stefan Thomke
• Daniela Beyersdorfer

Innovation at Uber: The Launch of Express POOL

• Chiara Farronato
• Alan MacCormack

Racial Discrimination on Airbnb (A)

• Michael Luca
• Scott Stern
• Hyunjin Kim

GitLab and the Future of All-Remote Work (A)

• Prithwiraj Choudhury
• Emma Salomon

TCS: From Physical Offices to Borderless Work

Creating a virtual internship at goldman sachs.

• Iavor Bojinov

Unilever's Response to the Future of Work

• William R. Kerr
• Emilie Billaud
• Mette Fuglsang Hjortshoej

AT&T, Retraining, and the Workforce of Tomorrow

• Joseph B. Fuller
• Carl Kreitzberg

Leading Change in Talent at L'Oreal

• Lakshmi Ramarajan
• Vincent Dessain
• Emer Moloney
• William W. George
• Andrew N. McLean

Eve Hall: The African American Investment Fund in Milwaukee

• Steven S. Rogers
• Alterrell Mills

United Housing - Otis Gates

• Mercer Cook

The Home Depot: Leadership in Crisis Management

• Herman B. Leonard
• Marc J. Epstein
• Melissa Tritter

The Great East Japan Earthquake (B): Fast Retailing Group's Response

• Hirotaka Takeuchi
• Kenichi Nonomura
• Dena Neuenschwander
• Meghan Ricci
• Kate Schoch
• Sergey Vartanov

Insurer of Last Resort?: The Federal Financial Response to September 11

• David A. Moss
• Sarah Brennan

Under Armour

• Rory McDonald
• Clayton M. Christensen
• Daniel West
• Jonathan E. Palmer
• Tonia Junker

Hunley, Inc.: Casting for Growth

• John A. Quelch
• James T. Kindley

Bitfury: Blockchain for Government

• Mitchell B. Weiss
• Elena Corsi

Deutsche Bank: Pursuing Blockchain Opportunities (A)

• Lynda M. Applegate
• Christoph Muller-Bloch

Maersk: Betting on Blockchain

• Scott Johnson

Yum! Brands

• Jordan Siegel
• Christopher Poliquin

Bharti Airtel in Africa

• Tanya Bijlani

Li & Fung 2012

• F. Warren McFarlan
• Michael Shih-ta Chen
• Keith Chi-ho Wong

Sony and the JK Wedding Dance

• John Deighton
• Leora Kornfeld

United Breaks Guitars

David dao on united airlines.

• Benjamin Edelman
• Jenny Sanford

Marketing Reading: Digital Marketing

• Joseph Davin

Social Strategy at Nike

• Mikolaj Jan Piskorski
• Ryan Johnson

The Tate's Digital Transformation

Social strategy at american express, mellon financial and the bank of new york.

• Carliss Y. Baldwin
• Ryan D. Taliaferro

The Walt Disney Company and Pixar, Inc.: To Acquire or Not to Acquire?

• Juan Alcacer
• David J. Collis

Dow's Bid for Rohm and Haas

• Benjamin C. Esty

Finance Reading: The Mergers and Acquisitions Process

• John Coates

Apple: Privacy vs. Safety? (A)

• Henry W. McGee
• Nien-he Hsieh
• Sarah McAra

Sidewalk Labs: Privacy in a City Built from the Internet Up

• Leslie K. John

Data Breach at Equifax

• Suraj Srinivasan
• Quinn Pitcher
• Jonah S. Goldberg

Apple's Core

• Noam Wasserman

Design Thinking and Innovation at Apple

• Barbara Feinberg

Apple Inc. in 2012

• Penelope Rossano

Iz-Lynn Chan at Far East Organization (Abridged)

• Anthony J. Mayo
• Dana M. Teppert

Barbara Norris: Leading Change in the General Surgery Unit

• Boris Groysberg
• Nitin Nohria
• Deborah Bell

Adobe Systems: Working Towards a "Suite" Release (A)

• David A. Thomas
• Lauren Barley
• Jan W. Rivkin

Starbucks Coffee Company: Transformation and Renewal

• Nancy F. Koehn
• Kelly McNamara
• Nora N. Khan
• Elizabeth Legris

JCPenney: Back in Business

• K. Shelette Stewart
• Christine Snively

Home Nursing of North Carolina

Castronics, llc, gemini investors, angie's list: ratings pioneer turns 20.

• Robert J. Dolan

Basecamp: Pricing

• Frank V. Cespedes
• Robb Fitzsimmons

J.C. Penney's "Fair and Square" Pricing Strategy

J.c. penney's 'fair and square' strategy (c): back to the future.

• Jose B. Alvarez

Osaro: Picking the best path

• James Palano
• Bastiane Huang

HubSpot and Motion AI: Chatbot-Enabled CRM

• Thomas Steenburgh

GROW: Using Artificial Intelligence to Screen Human Intelligence

• Ethan S. Bernstein
• Paul D. McKinnon
• Paul Yarabe

Arup: Building the Water Cube

• Robert G. Eccles
• Amy C. Edmondson
• Dilyana Karadzhova

(Re)Building a Global Team: Tariq Khan at Tek

Managing a global team: greg james at sun microsystems, inc. (a).

• Thomas J. DeLong

Organizational Behavior Reading: Leading Global Teams

Ron ventura at mitchell memorial hospital.

• Heide Abelli

Anthony Starks at InSiL Therapeutics (A)

• Gary P. Pisano
• Vicki L. Sato

Wolfgang Keller at Konigsbrau-TAK (A)

• John J. Gabarro

The 2010 Chilean Mining Rescue (A)

• Faaiza Rashid

IDEO: Human-Centered Service Design

• Ryan W. Buell
• Andrew Otazo
• Benjamin Jones
• Alexis Brownell

David Neeleman: Flight Path of a Servant Leader (A)

• Matthew D. Breitfelder

Coach Hurley at St. Anthony High School

• Scott A. Snook
• Bradley C. Lawrence

Shapiro Global

• Michael Brookshire
• Monica Haugen
• Michelle Kravetz
• Sarah Sommer

Kathryn McNeil (A)

• Joseph L. Badaracco Jr.
• Jerry Useem

Carol Fishman Cohen: Professional Career Reentry (A)

• Myra M. Hart
• Robin J. Ely
• Susan Wojewoda

Alex Montana at ESH Manufacturing Co.

• Michael Kernish

Michelle Levene (A)

• Tiziana Casciaro
• Victoria W. Winston

John and Andrea Rice: Entrepreneurship and Life

• Howard H. Stevenson
• Janet Kraus
• Shirley M. Spence

Partner Center

Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

• Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
• Fifty four percent of raw case users came from outside the U.S..
• The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
• Twenty-six of the cases in the list are raw cases.
• A third of the cases feature a woman protagonist.
• Orders for Yale SOM case studies increased by almost 50% compared to 2020.
• The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

Division of Energy and Innovation

• UH Energy and Innovation

News and Events

Uh energy establishes energy coalition alumni advisory board.

Alumni Group Focused on Student Success, Leadership Development

By Ed Bailey | Communications Manager, UH Energy

Sometimes, in order to pay it forward, you must go back to where it began.

Such is the case for the Energy Coalition (EC), the University of Houston’s energy-focused student organization with more than 5,000 members, making it the largest such organization in the nation. A trio of Coogs have come together to form an advisory board that will help connect students and alumni to opportunities within industry while supporting their professional development.

“The ECAB is comprised of industry thought leaders from various backgrounds with a love for the university as alumni being a common thread,” said Neha Bhat (’21, M.B.A. ’22), inaugural board chair who led the Energy Coalition from 2021 to 2022. “Our focus comes from the needs of current and former Energy Coalition members as well as where we see the industry trending towards. Subsequently, the members of our board all share a similar interest to promote the success of the Energy Coalition (EC) as alumni of UH.”

Bhat, a risk and financial advisor at Deloitte, is joined on the board by Oscar Herdocia (’01), energy transition and sustainability advisor at Shell and Kamalpreet Kaur (’19), commercial leader for low carbon solutions, CCUS and hydrogen at NOV.

The board had been in the works since 2022, during Bhat’s graduate studies at UH. With the support of Kaur and Oscar, Bhat reached out to UH Vice President of Energy and Innovation Ramanan Krishnamoorti and UH Energy Program Director Deidra Perry to bring the vision to life.

“The board came from a need for a strong alumni connection between UH Energy, the EC and alums as well as the desire of past EC members to give back,” Bhat said. “For me personally, I owe a great deal to the EC for my career and passion for the energy industry.”

Through site tours, such as the Shell Technology Hub trip in March, mentorship programs and networking opportunities, the ECAB assists the EC in providing students keen insight to industry’s most pressing issues and the latest innovations in the works to address them.

Bhat said this is only the beginning of what she expects will be a springboard that further spotlights the Energy Coalition and the University of Houston as a hub for talent with cutting-edge ideas and needed foresight to move industry forward in the Energy Capital of the World.

“The board aims to expose students and curious alumni to conversations about the future of energy,” she said. “We’re honored to serve the EC community and broader energy ecosystem. The interest this board has garnered over the past year from other passionate alumni will undoubtedly fuel the success of this board and more importantly, the Energy Coalition. After all, what better way to help grow the industry than by cultivating future leaders at the Energy University?”

To learn more about the ECAB, visit their webpage here .