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Business Research A Guide to Planning, Conducting, and Reporting Your Study

• Donald R. Cooper
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“ Business Research: A Guide to Planning, Conducting, and Reporting Your Study is a worthy entry into this field of research texts. It provides a carefully thought out and tightly organized plan for conducting research across a variety of business and non-business fields. Rather than a cook book, it presents a sound theoretical approach to doing research firmly grounded in an understanding of the scientific method. It carries the student from problem inception to finished report in a highly readable and entertaining way. It can be recommended to any instructor who wants a text for a research methods course that is flexible and easy to use.”

“Donald Cooper provides a roadmap for success by supplying his readers with the essential tools needed to succeed in conducting and reporting research in the ever changing business environment we live in today.”

“This book provides clear, concise and practical guides to the whole research process from beginning to end. It is an effective reference for students and anyone learning how to do research. It covers each and every step of the research process thoroughly from exploring research question and problem all the way to writing the results.”

“An excellent guide for the novice or experienced researcher. This book is written with scholarship, integrity, and intelligence. The author has provided an excellent writing style and examples.  The material is easy to understand and presented in a fashion that students will enjoy.”

“I believe this to be a vast improvement over traditional research texts. The language is easy to understand making the work more accessible to students.”

“[Cooper] provides the step-by-step research process and explains the relevance and importance of each step. Additionally, the use and write-up of the data to inform readers of research is critical.”

“This text provides a comprehensive coverage on business research.”

“The textbook helps the serious researcher think better about research design.”

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• A concise and effective APA style how-to guide with over 26 exhibits that includes writing examples using permissions for articles and a 2016 thesis.
• Robust pedagogical features include learning objectives, key terms, discussion questions, comparison tables for a business report vs. an academic report, and over 500 references.
• An appendix includes an example of an original PowerPoint Business Research Proposal.   

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2. Self-Defense Tools for Research: Preparation, Reasoning, and Terminology

8. Experimental Designs

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Home Market Research

Business Research: Methods, Types & Examples

Content Index

Business research: Definition

Quantitative research methods, qualitative research methods, advantages of business research, disadvantages of business research, importance of business research.

Business research is a process of acquiring detailed information on all the areas of business and using such information to maximize the sales and profit of the business. Such a study helps companies determine which product/service is most profitable or in demand. In simple words, it can be stated as the acquisition of information or knowledge for professional or commercial purposes to determine opportunities and goals for a business.

Business research can be done for anything and everything. In general, when people speak about business research design , it means asking research questions to know where the money can be spent to increase sales, profits, or market share. Such research is critical to make wise and informed decisions.

LEARN ABOUT: Research Process Steps

For example: A mobile company wants to launch a new model in the market. But they are not aware of what are the dimensions of a mobile that are in most demand. Hence, the company conducts business research using various methods to gather information, and the same is then evaluated, and conclusions are drawn as to what dimensions are most in demand.

This will enable the researcher to make wise decisions to position his phone at the right price in the market and hence acquire a larger market share.

LEARN ABOUT:  Test Market Demand

Business research: Types and methodologies

Business research is a part of the business intelligence process. It is usually conducted to determine whether a company can succeed in a new region, to understand its competitors, or simply select a marketing approach for a product. This research can be carried out using steps in qualitative research methods or quantitative research methods.

Quantitative research methods are research methods that deal with numbers. It is a systematic empirical investigation using statistical, mathematical, or computational techniques . Such methods usually start with data collection and then proceed to statistical analysis using various methods. The following are some of the research methods used to carry out business research.

LEARN ABOUT: Data Management Framework

Survey research

Survey research is one of the most widely used methods to gather data, especially for conducting business research. Surveys involve asking various survey questions to a set of audiences through various types like online polls, online surveys, questionnaires, etc. Nowadays, most of the major corporations use this method to gather data and use it to understand the market and make appropriate business decisions.

Various types of surveys, like cross-sectional studies , which need to collect data from a set of audiences at a given point of time, or longitudinal surveys which are needed to collect data from a set of audiences across various time durations in order to understand changes in the respondents’ behavior are used to conduct survey research. With the advancement in technology, surveys can now be sent online through email or social media .

For example: A company wants to know the NPS score for their website i.e. how satisfied are people who are visiting their website. An increase in traffic to their website or the audience spending more time on a website can result in higher rankings on search engines which will enable the company to get more leads as well as increase its visibility.

Hence, the company can ask people who visit their website a few questions through an online survey to understand their opinions or gain feedback and hence make appropriate changes to the website to increase satisfaction.

Learn More:  Business Survey Template

Correlational research

Correlational research is conducted to understand the relationship between two entities and what impact each one of them has on the other. Using mathematical analysis methods, correlational research enables the researcher to correlate two or more variables .

Such research can help understand patterns, relationships, trends, etc. Manipulation of one variable is possible to get the desired results as well. Generally, a conclusion cannot be drawn only on the basis of correlational research.

For example: Research can be conducted to understand the relationship between colors and gender-based audiences. Using such research and identifying the target audience, a company can choose the production of particular color products to be released in the market. This can enable the company to understand the supply and demand requirements of its products.

Causal-Comparative research

Causal-comparative research is a method based on the comparison. It is used to deduce the cause-effect relationship between variables. Sometimes also known as quasi-experimental research, it involves establishing an independent variable and analyzing the effects on the dependent variable.

In such research, data manipulation is not done; however, changes are observed in the variables or groups under the influence of the same changes. Drawing conclusions through such research is a little tricky as independent and dependent variables will always exist in a group. Hence all other parameters have to be taken into consideration before drawing any inferences from the research.

LEARN ABOUT: Causal Research

For example: Research can be conducted to analyze the effect of good educational facilities in rural areas. Such a study can be done to analyze the changes in the group of people from rural areas when they are provided with good educational facilities and before that.

Another example can be to analyze the effect of having dams and how it will affect the farmers or the production of crops in that area.

LEARN ABOUT: Market research trends

Experimental research

Experimental research is based on trying to prove a theory. Such research may be useful in business research as it can let the product company know some behavioral traits of its consumers, which can lead to more revenue. In this method, an experiment is carried out on a set of audiences to observe and later analyze their behavior when impacted by certain parameters.

LEARN ABOUT: Behavioral Targeting

For example: Experimental research was conducted recently to understand if particular colors have an effect on consumers’ hunger. A set of the audience was then exposed to those particular colors while they were eating, and the subjects were observed. It was seen that certain colors like red or yellow increase hunger.

Hence, such research was a boon to the hospitality industry. You can see many food chains like Mcdonalds, KFC, etc., using such colors in their interiors, brands, as well as packaging.

Another example of inferences drawn from experimental research, which is used widely by most bars/pubs across the world, is that loud music in the workplace or anywhere makes a person drink more in less time. This was proven through experimental research and was a key finding for many business owners across the globe.

Online research / Literature research

Literature research is one of the oldest methods available. It is very economical, and a lot of information can be gathered using such research. Online research or literature research involves gathering information from existing documents and studies, which can be available at Libraries, annual reports, etc.

Nowadays, with the advancement in technology, such research has become even more simple and accessible to everyone. An individual can directly research online for any information that is needed, which will give him in-depth information about the topic or the organization.

Such research is used mostly by marketing and salespeople in the business sector to understand the market or their customers. Such research is carried out using existing information that is available from various sources. However, care has to be taken to validate the sources from where the information is going to be collected.

For example , a salesperson has heard a particular firm is looking for some solution that their company provides. Hence, the salesperson will first search for a decision maker from the company, investigate what department he is from, and understand what the target company is looking for and what they are into.

Using this research, he can cater his solution to be spot on when he pitches it to this client. He can also reach out to the customer directly by finding a means to communicate with him by researching online.’

LEARN ABOUT: 12 Best Tools for Researchers

Qualitative research is a method that has a high importance in business research. Qualitative research involves obtaining data through open-ended conversational means of communication. Such research enables the researcher to not only understand what the audience thinks but also why he thinks it.

In such research, in-depth information can be gathered from the subjects depending on their responses. There are various types of qualitative research methods, such as interviews, focus groups, ethnographic research, content analysis, and case study research, that are widely used.

Such methods are of very high importance in business research as they enable the researcher to understand the consumer. What motivates the consumer to buy and what does not is what will lead to higher sales, and that is the prime objective for any business.

Following are a few methods that are widely used in today’s world by most businesses.

Interviews are somewhat similar to surveys, like sometimes they may have the same types of questions used. The difference is that the respondent can answer these open-ended questions at length, and the direction of the conversation or the questions being asked can be changed depending on the response of the subject.

Such a method usually gives the researcher detailed information about the perspective or opinions of its subject. Carrying out interviews with subject matter experts can also give important information critical to some businesses.

For example: An interview was conducted by a telecom manufacturer with a group of women to understand why they have less number of female customers. After interviewing them, the researcher understood that there were fewer feminine colors in some of the models, and females preferred not to purchase them.

Such information can be critical to a business such as a  telecom manufacturer and hence it can be used to increase its market share by targeting women customers by launching some feminine colors in the market.

Another example would be to interview a subject matter expert in social media marketing. Such an interview can enable a researcher to understand why certain types of social media advertising strategies work for a company and why some of them don’t.

LEARN ABOUT: Qualitative Interview

Focus groups

Focus groups are a set of individuals selected specifically to understand their opinions and behaviors. It is usually a small set of a group that is selected keeping in mind the parameters for their target market audience to discuss a particular product or service. Such a method enables a researcher with a larger sample than the interview or a case study while taking advantage of conversational communication.

Focus group is also one of the best examples of qualitative data in education . Nowadays, focus groups can be sent online surveys as well to collect data and answer why, what, and how questions. Such a method is very crucial to test new concepts or products before they are launched in the market.

For example: Research is conducted with a focus group to understand what dimension of screen size is preferred most by the current target market. Such a method can enable a researcher to dig deeper if the target market focuses more on the screen size, features, or colors of the phone. Using this data, a company can make wise decisions about its product line and secure a higher market share.

Ethnographic research

Ethnographic research is one of the most challenging research but can give extremely precise results. Such research is used quite rarely, as it is time-consuming and can be expensive as well. It involves the researcher adapting to the natural environment and observing its target audience to collect data. Such a method is generally used to understand cultures, challenges, or other things that can occur in that particular setting.

For example: The world-renowned show “Undercover Boss” would be an apt example of how ethnographic research can be used in businesses. In this show, the senior management of a large organization works in his own company as a regular employee to understand what improvements can be made, what is the culture in the organization, and to identify hard-working employees and reward them.

It can be seen that the researcher had to spend a good amount of time in the natural setting of the employees and adapt to their ways and processes. While observing in this setting, the researcher could find out the information he needed firsthand without losing any information or any bias and improve certain things that would impact his business.

LEARN ABOUT:   Workforce Planning Model

Case study research

Case study research is one of the most important in business research. It is also used as marketing collateral by most businesses to land up more clients. Case study research is conducted to assess customer satisfaction and document the challenges that were faced and the solutions that the firm gave them.

These inferences are made to point out the benefits that the customer enjoyed for choosing their specific firm. Such research is widely used in other fields like education, social sciences, and similar. Case studies are provided by businesses to new clients to showcase their capabilities, and hence such research plays a crucial role in the business sector.

For example: A services company has provided a testing solution to one of its clients. A case study research is conducted to find out what were the challenges faced during the project, what was the scope of their work, what objective was to be achieved, and what solutions were given to tackle the challenges.

The study can end with the benefits that the company provided through its solutions, like reduced time to test batches, easy implementation or integration of the system, or even cost reduction. Such a study showcases the capability of the company, and hence it can be stated as empirical evidence of the new prospect.

Website visitor profiling/research

Website intercept surveys or website visitor profiling/research is something new that has come up and is quite helpful in the business sector. It is an innovative approach to collect direct feedback from your website visitors using surveys. In recent times a lot of business generation happens online, and hence it is important to understand the visitors of your website as they are your potential customers.

Collecting feedback is critical to any business, as without understanding a customer, no business can be successful. A company has to keep its customers satisfied and try to make them loyal customers in order to stay on top.

A website intercept survey is an online survey that allows you to target visitors to understand their intent and collect feedback to evaluate the customers’ online experience. Information like visitor intention, behavior path, and satisfaction with the overall website can be collected using this.

Depending on what information a company is looking for, multiple forms of website intercept surveys can be used to gather responses. Some of the popular ones are Pop-ups, also called Modal boxes, and on-page surveys.

For example: A prospective customer is looking for a particular product that a company is selling. Once he is directed to the website, an intercept survey will start noting his intent and path. Once the transaction has been made, a pop-up or an on-page survey is provided to the customer to rate the website.

Such research enables the researcher to put this data to good use and hence understand the customers’ intent and path and improve any parts of the website depending on the responses, which in turn would lead to satisfied customers and hence, higher revenues and market share.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

• Business research helps to identify opportunities and threats.
• It helps identify research problems , and using this information, wise decisions can be made to tackle the issue appropriately.
• It helps to understand customers better and hence can be useful to communicate better with the customers or stakeholders.
• Risks and uncertainties can be minimized by conducting business research in advance.
• Financial outcomes and investments that will be needed can be planned effectively using business research.
• Such research can help track competition in the business sector.
• Business research can enable a company to make wise decisions as to where to spend and how much.
• Business research can enable a company to stay up-to-date with the market and its trends, and appropriate innovations can be made to stay ahead in the game.
• Business research helps to measure reputation management
• Business research can be a high-cost affair
• Most of the time, business research is based on assumptions
• Business research can be time-consuming
• Business research can sometimes give you inaccurate information because of a biased population or a small focus group.
• Business research results can quickly become obsolete because of the fast-changing markets

Business research is one of the most effective ways to understand customers, the market, and competitors. Such research helps companies to understand the demand and supply of the market. Using such research will help businesses reduce costs and create solutions or products that are targeted to the demand in the market and the correct audience.

In-house business research can enable senior management to build an effective team or train or mentor when needed. Business research enables the company to track its competitors and hence can give you the upper hand to stay ahead of them.

Failures can be avoided by conducting such research as it can give the researcher an idea if the time is right to launch its product/solution and also if the audience is right. It will help understand the brand value and measure customer satisfaction which is essential to continuously innovate and meet customer demands.

This will help the company grow its revenue and market share. Business research also helps recruit ideal candidates for various roles in the company. By conducting such research, a company can carry out a SWOT analysis , i.e. understand the strengths, weaknesses, opportunities, and threats. With the help of this information, wise decisions can be made to ensure business success.

LEARN ABOUT:  Market research industry

Business research is the first step that any business owner needs to set up his business to survive or to excel in the market. The main reason why such research is of utmost importance is that it helps businesses to grow in terms of revenue, market share, and brand value.

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Article contents

Qualitative designs and methodologies for business, management, and organizational research.

• Robert P. Gephart Robert P. Gephart Alberta School of Business, University of Alberta
•  and  Rohny Saylors Rohny Saylors Carson College of Business, Washington State University
• https://doi.org/10.1093/acrefore/9780190224851.013.230
• Published online: 28 September 2020

Qualitative research designs provide future-oriented plans for undertaking research. Designs should describe how to effectively address and answer a specific research question using qualitative data and qualitative analysis techniques. Designs connect research objectives to observations, data, methods, interpretations, and research outcomes. Qualitative research designs focus initially on collecting data to provide a naturalistic view of social phenomena and understand the meaning the social world holds from the point of view of social actors in real settings. The outcomes of qualitative research designs are situated narratives of peoples’ activities in real settings, reasoned explanations of behavior, discoveries of new phenomena, and creating and testing of theories.

A three-level framework can be used to describe the layers of qualitative research design and conceptualize its multifaceted nature. Note, however, that qualitative research is a flexible and not fixed process, unlike conventional positivist research designs that are unchanged after data collection commences. Flexibility provides qualitative research with the capacity to alter foci during the research process and make new and emerging discoveries.

The first or methods layer of the research design process uses social science methods to rigorously describe organizational phenomena and provide evidence that is useful for explaining phenomena and developing theory. Description is done using empirical research methods for data collection including case studies, interviews, participant observation, ethnography, and collection of texts, records, and documents.

The second or methodological layer of research design offers three formal logical strategies to analyze data and address research questions: (a) induction to answer descriptive “what” questions; (b) deduction and hypothesis testing to address theory oriented “why” questions; and (c) abduction to understand questions about what, how, and why phenomena occur.

The third or social science paradigm layer of research design is formed by broad social science traditions and approaches that reflect distinct theoretical epistemologies—theories of knowledge—and diverse empirical research practices. These perspectives include positivism, interpretive induction, and interpretive abduction (interpretive science). There are also scholarly research perspectives that reflect on and challenge or seek to change management thinking and practice, rather than producing rigorous empirical research or evidence based findings. These perspectives include critical research, postmodern research, and organization development.

Three additional issues are important to future qualitative research designs. First, there is renewed interest in the value of covert research undertaken without the informed consent of participants. Second, there is an ongoing discussion of the best style to use for reporting qualitative research. Third, there are new ways to integrate qualitative and quantitative data. These are needed to better address the interplay of qualitative and quantitative phenomena that are both found in everyday discourse, a phenomenon that has been overlooked.

• qualitative methods
• research design
• methods and methodologies
• interpretive induction
• interpretive science
• critical theory
• postmodernism
• organization development

Introduction

Qualitative research uses linguistic symbols and stories to describe and understand actual behavior in real settings (Denzin & Lincoln, 1994 ). Understanding requires describing “specific instances of social phenomena” (Van Maanen, 1998 , p. xi) to determine what this behavior means to lay participants and to scientific researchers. This process produces “narratives-non-fiction division that link events to events in storied or dramatic fashion” to uncover broad social science principles at work in specific cases (p. xii).

A research design and/or proposal is often created at the outset of research to act as a guide. But qualitative research is not a rule-governed process and “no one knows” the rules to write memorable and publishable qualitative research (Van Maanen, 1998 , p. xxv). Thus qualitative research “is anything but standardized, or, more tellingly, impersonal” (p. xi). Design is emergent and is often created as it is being done.

Qualitative research is also complex. This complexity is addressed by providing a framework with three distinct layers of knowledge creation resources that are assembled during qualitative research: the methods layer, the logic layer, and the paradigmatic layer. Research methods are addressed first because “there is no necessary connection between research strategies and methods of data collection and analysis” (Blaikie, 2010 , p. 227). Research methods (e.g., interviews) must be adapted for use with the specific logical strategies and paradigmatic assumptions in mind.

The first, or methods, layer uses qualitative methods to “collect data.” That is, to observe phenomena and record written descriptions of observations, often through field notes. Established methods for description include participant and non-participant observation, ethnography, focus groups, individual interviews, and collection of documentary data. The article explains how established methods have been adapted and used to answer a range of qualitative research questions.

The second, or logic, layer involves selecting a research strategy—a “logic, or set of procedures, for answering research questions” (Blaikie, 2010 , p. 18). Research strategies link research objectives, data collection methods, and logics of analysis. The three logical strategies used in qualitative organizational research are inductive logic, deductive logic and abductive logic (Blaikie, 2010 , p. 79). 1 Each logical strategy makes distinct assumptions about the nature of knowledge (epistemology), the nature of being (ontology), and how logical strategies and assumptions are used in data collection and analysis. The task is to describe important methods suitable for each logical strategy, factors to consider when selecting methods (Blaikie, 2010 ), and illustrates how data collection and analysis methods are adapted to ensure for consistency with specific logics and paradigms.

The third, or paradigms, layer of research design addresses broad frameworks and scholarly traditions for understanding research findings. Commitment to a paradigm or research tradition entails commitments to theories, research strategies, and methods. Three paradigms that do empirical research and seek scientific knowledge are addressed first: positivism, interpretive induction, and interpretive abduction. Then, three scholarly and humanist approaches that critique conventional research and practice to encourage organizational change are discussed: critical theory and research, postmodern perspectives, and organization development (OD). Paradigms or traditions provide broad scholarly contexts that make specific studies comprehensible and meaningful. Lack of grounding in an intellectual tradition limits the ability of research to contribute: contributions always relate to advancing the state of knowledge in specific unfolding research traditions that also set norms for assessing research quality. The six research designs are explained to show how consistency in design levels can be achieved for each of the different paradigms. Further, qualitative research designs must balance the need for a clear plan to achieve goals with the need for adaptability and flexibility to incorporate insights and overcome obstacles that emerge during research.

Our general goal has been to provide a practical guide to inspire and assist readers to better understand, design, implement, and publish qualitative research. We conclude by addressing future challenges and trends in qualitative research.

The Substance of Research Design

A research design is a written text that can be prepared prior to the start of a research project (Blaikie, 2010 , p. 4) and shared or used as “a private working document.” Figure 1 depicts the elements of a qualitative research design and research process. Interest in a topic or problem leads researchers to pose questions and select relevant research methods to fulfill research purposes. Implementation of the methods requires use of logical strategies in conjunction with paradigms of research to specify concepts, theories, and models. The outcomes, depending on decisions made during research, are scientific knowledge, scholarly (non-scientific) knowledge, or applied knowledge useful for practice.

Figure 1. Elements of qualitative research design.

Research designs describe a problem or research question and explain how to use specific qualitative methods to collect and analyze qualitative data that answer a research question. The purposes of design are to describe and justify the decisions made during the research process and to explain how the research outcomes can be produced. Designs are thus future-oriented plans that specify research activities, connect activities to research goals and objectives, and explain how to interpret the research outcomes using paradigms and theories.

In contrast, a research proposal is “a public document that is used to obtain necessary approvals for a research proposal to proceed” (Blaikie, 2010 , p. 4). Research designs are often prepared prior to creating a research proposal, and research proposals often require the inclusion of research designs. Proposals also require greater formality when they are the basis for a legal contract between a researcher and a funding agency. Thus, designs and proposals are mutually relevant and have considerable overlap but are addressed to different audiences. Table 1 provides the specific features of designs and proposals. This discussion focuses on designs.

Table 1. Decisions Necessitated by Research Designs and Proposals

Source: Based on Blaikie ( 2010 ), pp. 12–34.

The “real starting point” for a research design (or proposal) is “the formulation of the research question” (Blaikie, 2010 , p. 17). There are three types of research questions: “what” questions seek descriptions; “why” questions seek answers and understanding; and “how” questions address conditions where certain events occur, underlying mechanisms, and conditions necessary for change interventions (p. 17). It is useful to start with research questions rather than goals, and to explain what the research is intended to achieve (p. 17) in a technical way.

The process of finding a topic and formulating a useful research question requires several considerations (Silverman, 2014 , pp. 31–33, 34–40). Researchers must avoid settings where data collection will be difficult (pp. 31–32); specify an appropriate scope for the topic—neither too wide or too narrow—that can be addressed (pp. 35–36); fit research questions into a relevant theory (p. 39); find the appropriate level of theory to address (p. 42); select appropriate designs and research methods (pp. 42–44); ensure the volume of data can be handled (p. 48); and do an effective literature review (p. 48).

A literature review is an important way to link the proposed research to current knowledge in the field, and to explain what was previously known or what theory suggests to be the case (Blaikie, 2010 , p. 17). Research questions can used to bound and frame the literature review while the literature review often inspires research questions. The review may also provide bases for creating new hypotheses and for answering some of the initial research questions (Blaikie, 2010 , p. 18).

Layers of Research Design

There are three layers of research design. The first layer focuses on research methods for collecting data. The second layer focuses on the logical frameworks used for analyzing data. The third layer focuses on the paradigm used to create a coherent worldview from research methods and logical frameworks.

Layer One: Design as Research Methods

Qualitative research addresses the meanings people have for phenomena. It collects narratives of organizational activity, uses analytical induction to create coherent representations of the truths and meanings in organizational contexts, and then creates explanations of this conduct and its prevalence (Van Maanan, 1998 , pp. xi–xii). Thus qualitative research involves “doing research with words” (Gephart, 2013 , title) in order to describe the linguistic symbols and stories that members use in specific settings.

There are four general methods for collecting qualitative data and creating qualitative descriptions (see Table 2 ). The in-depth case study approach provides a history of an event or phenomenon over time using multiple data sources. Observational strategies use the researcher to observe and describe behavior in actual settings. Interview strategies use a format where a researcher asks questions of an informant. And documentary research collects texts, documents, official records, photographs, and videos as data—formally written or visually recorded evidence that can be replayed and reviewed (Creswell, 2014 , p. 190). These methods are adapted to fit the needs of specific projects.

Table 2. Qualitative Data Collection Methods

The in-depth case study method.

The in-depth case study is a key strategy for qualitative research (Piekkari & Welch, 2012 ). It was the most common qualitative method used during the formative years of the field, from 1956 to 1965 , when 48% of qualitative papers published in the Administrative Science Quarterly used the case study method (Van Maanen, 1998 , p. xix). The case design uses one or more data collection strategies to describe in detail how a single event or phenomenon, selected by a researcher, has changed over time. This provides an understanding of the processes that underlie changes to the phenomenon. In-depth case study methods use observations, documents, records, and interviews that describe the events in the case unfolded and their implications. Case studies contextualize phenomena by studying them in actual situations. They provide rich insights into multiple dimensions of a single phenomenon (Campbell, 1975 ); offer empirical insights into what, how, and why questions related to phenomena; and assist in the creation of robust theory by providing diverse data collected over time (Gephart & Richardson, 2008 , p. 36).

Maniha and Perrow ( 1965 ) provide an example of a case study concerned with organizational goal displacement, an important issue in early organizational theorizing that proposed organizations emerge from rational goals. Organizational rationality was becoming questioned at the time that the authors studied a Youth Commission with nine members in a city of 70,000 persons (Maniha & Perrow, 1965 ). The organization’s activities were reconstructed from interviews with principals and stakeholders of the organization, minutes from Youth Commission meetings, documents, letters, and newspaper accounts (Maniha & Perrow, 1965 ).

The account that emerged from the data analysis is a history of how a “reluctant organization” with “no goals to guide it” was used by other aggressive organizations for their own ends. It ultimately created its own mission (Maniha & Perrow, 1965 ). Thus, an organization that initially lacked rational goals developed a mission through the irrational process of goal slippage or displacement. This finding challenged prevailing thinking at the time.

Observational Strategies

Observational strategies involve a researcher present in a situation who observes and records, the activities and conversations that occur in the setting, usually in written field notes. The three observational strategies in Table 2 —participant observation, ethnography, and systematic self-observation—differ in terms of the role of the researcher and in the data collection approach.

Participant observation . This is one of the earliest qualitative methods (McCall & Simmons, 1969 ). One gains access to a setting and an informant holding an appropriate social role, for example, client, customer, volunteer, or researcher. One then observes and records what occurs in the setting using field notes. Many features or topics in a setting can become a focus for participant observers. And observations can be conducted using continuum of different roles from the complete participant, observer as participant, and participant observer, to the complete observer who observes without participation (Creswell, 2014 , Table 9.2, p. 191).

Ethnography . An ethnography is “a written representation of culture” (Van Maanen, 1988 ) produced after extended participation in a culture. Ethnography is a form of participant observation that focuses on the cultural aspects of the group or organization under study (Van Maanen, 1988 , 2010 ). It involves prolonged and close contact with group members in a role where the observer becomes an apprentice to an informant to learn about a culture (Agar, 1980 ; McCurdy, Spradley, & Shandy, 2005 ; Spradley, 1979 ).

Ethnography produces fine-grained descriptions of a micro-culture, based on in-depth cultural participation (McCurdy et al., 2005 ; Spradley, 1979 , 2016 ). Ethnographic observations seek to capture cultural members’ worldviews (see Perlow, 1997 ; Van Maanen, 1988 ; Watson, 1994 ). Ethnographic techniques for interviewing informants have been refined into an integrated developmental research strategy—“the ethno-semantic method”—for undertaking qualitative research (Spradley, 1979 , 2016 ; Van Maanen, 1981 ). The ethnosemantic method uses a structured approach to uncover and confirm key cultural features, themes, and cultural reasoning processes (McCurdy et al., 2005 , Table 3 ; Spradley, 1979 ).

Systematic Self-Observation . Systematic self-observation (SSO) involves “training informants to observe and record a selected feature of their own everyday experience” (Rodrigues & Ryave, 2002 , p. 2; Rodriguez, Ryave, & Tracewell, 1998 ). Once aware that they are experiencing the target phenomenon, informants “immediately write a field report on their observation” (Rodrigues & Ryave, 2002 , p. 2) describing what was said and done, and providing background information on the context, thoughts, emotions, and relationships of people involved. SSO generates high-quality field notes that provide accurate descriptions of informants’ experiences (pp. 4–5). SSO allows informants to directly provide descriptions of their personal experiences including difficult to capture emotions.

Interview Strategies

Interviews are conversations between researchers and research participants—termed “subjects” in positivist research and informants in “interpretive research.” Interviews can be conducted as individual face-to-face interactions (Creswell, 2014 , p. 190) or by telephone, email, or through computer-based media. Two broad types of interview strategies are (a) the individual interview and (b) the group interview or focus group (Morgan, 1997 ). Interviews elicit informants’ insights into their culture and background information, and obtain answers and opinions. Interviews typically address topics and issues that occur outside the interview setting and at previous times. Interview data are thus reconstructions or undocumented descriptions of action in past settings (Creswell, 2014 , p. 191) that provide descriptions that are less accurate and valid descriptions than direct, real-time observations of settings.

Structured and unstructured interviews. Structured interviews pose a standardized set of fixed, closed-ended questions (Easterby-Smith, Thorpe, & Jackson, 2012 ) to respondents whose responses are recorded as factual information. Responses may be forced choice or open ended. However, most qualitative research uses unstructured or partially structured interviews that pose open-ended questions in a flexible order that can be adapted. Unstructured interviews allow for detailed responses and clarification of statements (Easterby-Smith et al., 2012 ; McLeod, 2014 )and the content and format can be tailored to the needs and assumptions of specific research projects (Gephart & Richardson, 2008 , p. 40).

The informant interview (Spradley, 1979 ) poses questions to informants to elicit and clarify background information about their culture, and to validate ethnographic observations. In interviews, informants teach the researcher their culture (Spradley, 1979 , pp. 24–39). The informant interview is part of a developmental research sequence (McCurdy et al., 2005 ; Spradley, 1979 ) that begins with broad “grand tour” questions that ask an informant to describe an important domain in their culture. The questions later narrow to focus on details of cultural domains and members’ folk concepts. This process uncovers semantic relationships among concepts of members and deeper cultural themes (McCurdy et al., 2005 ; Spradley, 1979 ).

The long interview (McCracken, 1988 ) involves a lengthy, quasi-structured interview sessions with informants to acquire rapid and efficient access to cultural themes and issues in a group. Long interviews differ ethnographic interviews by using a “more efficient and less obtrusive format” (p. 7). This creates a “sharply focused, rapid and highly intense interview process” that avoids indeterminate and redundant questions and pre-empts the need for observation or involvement in a culture. There are four stages in the long interview: (a) review literature to uncover analytical categories and design the interview; (b) review cultural categories to prepare the interview guide; (c) construct the questionnaire; and (d) analyze data to discover analytical categories (p. 30, fig. 1 ).

The active interview is a dynamic process where the researcher and informant co-construct and negotiate interview responses (Holstein & Gubrium, 1995 ). The goal is to uncover the subjective meanings that informants hold for phenomenon, and to understand how meaning is produced through communication. The active approach is common in interpretive, critical, and postmodern research that assumes a negotiated order. For example, Richardson and McKenna ( 2000 ) explored how ex-patriate British faculty members themselves interpreted and explained their expatriate experience. The researchers viewed the interview setting as one where the researchers and informants negotiated meanings between themselves, rather than a setting where prepared questions and answers were shared.

Documentary, Photographic, and Video Records as Data

Documents, records, artifacts, photographs, and video recordings are physically enduring forms of data that are separable from their producers and provide mute evidence with no inherent meaning until they are read, written about, and discussed (Hodder, 1994 , p. 393). Records (e.g., marriage certificate) attest to a formal transaction, are associated with formal governmental institutions, and may have legally restricted access. In contrast, documents are texts prepared for personal reasons with fewer legal restrictions but greater need for contextual interpretation. Several approaches to documentary and textual data analysis have been developed (see Table 3 ). Documents that researchers have found useful to collect include public documents and minutes of meetings; detailed transcripts of public hearings; corporate and government press releases; annual reports and financial documents; private documents such as diaries of informants; and news media reports.

Photographs and videos are useful for capturing “accurate” visual images of physical phenomena (Ray & Smith, 2012 ) that can be repeatedly reexamined and used as evidence to substantiate research claims (LeBaron, Jarzabkowski, Pratt, & Fetzer, 2018 ). Photos taken from different positions in space may also reveal different features of phenomena. Videos show movement and reveal activities as processes unfolding over time and space. Both photos and videos integrate and display the spatiotemporal contexts of action.

Layer Two: Design as Logical Frameworks

The second research design layer links data collection and analysis methods (Tables 2 and 3 ) to three logics of enquiry that answer specific questions: inductive, deductive, and abductive logical strategies (see Table 4 ). Each logical strategy focuses on producing different types of knowledge using distinctive research principles, processes, and types of research questions they can address.

Table 3. Data Analysis and Integrated Data Collection and Analysis Strategies

Table 4. logical strategies for answering qualitative research questions with evidence.

Based in part on Blaikie ( 1993 ), ch. 5 & 6; Blaikie ( 2010 ), p. 84, table 4.1

The Inductive Strategy

Induction is the scientific method for many scholars (Blaikie, 1993 , p. 134), and an essential logic for qualitative management research (Pratt, 2009 , p. 856). Inductive strategies ask “what” questions to explore a domain to discover unknown features of a phenomenon (Blaikie, 2010 , p. 83). There are four stages to the inductive strategy: (a) observe and record all facts without selection or anticipating their importance; (b) analyze, compare, and classify facts without employing hypotheses; (c) develop generalizations inductively based on the analyses; and (d) subject generalizations to further testing (Blaikie, 1993 , p. 137).

Inductive research assumes a real world outside human thought that can be directly sensed and described (Blaikie, 2010 ). Principles of inductive research reflect a realist and objectivist ontology. The selection, definition, and measurement of characteristics to be studied are developed from an objective, scientific point of view. Facts about organizational features need to be obtained using unbiased measurement. Further, the elimination method is used to find “the characteristics present in all the positive cases, which are absent in all the negative cases, and which vary in appropriate degrees” (Blaikie, 1993 , p. 135). This requires data collection methods that provide unbiased evidence of the objective facts without pre-supposing their importance.

Induction can establish limited generalizations about phenomena based solely on the observations collected. Generalizations need to be based on the entire sample of data, not on selected observations from large data sets, to establish their validity. The scope of generalization is limited to the sample of data itself. Induction creates evidence to increase our confidence in a conclusion, but the conclusions do not logically follow from premises (Blaikie, 1993 , p. 164). Indeed, inferences from induction cannot be extended beyond the original set of observations and no logical or formal process exists to establish the universality of inferences.

Key data collection methods for inductive designs include observational strategies that allow the researcher to view behavior without making a priori hypotheses, to describe behavior that occurs “naturally” in settings, and to record non-impressionistic descriptions of behavior. Interviews can also elicit descriptions of settings and behavior for inductive qualitative research. Data analysis methods need to describe actual interactions in real settings including discourse among members. These methods include ethnosemantic analysis to uncover key terms and validate actual meanings used by members; analyses of conversational practices that show how meaning is negotiated through sequential turn taking in discourse; and grounded theory-based concept coding and theory development that use the constant comparative method.

Facts or descriptions of events can be compared to one another and generalizations can be made about the world using induction (Blaikie, 2010 ). Outcomes from inductive analysis include descriptions of features in a limited domain of social action that are inferred to exist in other similar settings. Propositions and broader insights can be developed inductively from these descriptions.

The Deductive Strategy

Deductive logic (Blaikie, 1993 , 2010 ) addresses “why” questions to explain associations between concepts that represent phenomena of interest. Researchers can use induction, abduction, or any means, to develop then test the hypotheses to see if they are valid. Hypotheses that are not rejected are temporarily corroborated. The outcomes from deduction are tested hypotheses. Researchers can thus be very creative in hypothesis construction but they cannot discover new phenomena with deduction that is based only on phenomena known in advance (Blaikie, 2010 ). And there is also no purely logical or mechanical process to establish “the validity of [inductively constructed] universal statements from a set of singular statements” from which deductive hypotheses were formed (Hempel, 1966 , p. 15 cited in Blaikie, 1993 , p. 140).

The deductive strategy uses a realist and objectivist ontology and imitates natural science methods. Useful data collection methods include observation, interviewing, and collection of documents that contain facts. Deduction addresses the assumedly objective features of settings and interactions. Appropriate data analysis methods include content coding to identify different types, features, and frequencies of observed phenomena; grounded theory coding and analytical induction to create categories in data, determine how categories are interrelated, and induce theory from observations; and pattern recognition to compare current data to prior models and samples. Content analysis and non-parametric statistics can be used to quantify qualitative data and make it more amenable to analysis, although quantitative analysis of qualitative data is not, strictly speaking, qualitative research (Gephart, 2004 ).

The Abductive Strategy

Abduction is “the process used to produce social scientific accounts of social life by drawing on the concepts and meanings used by social actors, and the activities in which they engage” (Blaikie, 1993 , p. 176). Abductive reasoning assumes that the socially meaningful world is the world experienced by members. The first abductive task is to discover the insider view that is basic to the actions of social actors (p. 176) by uncovering the subjective meanings held by social actors. Subjective meaning (Schutz, 1973a , 1973b ) refers to the meaning that actions hold for the actors themselves and that they can express verbally. Subjective meaning is not inexpressible ideas locked in one’s mind. Abduction starts with lay descriptions of social life, then moves to technical, scientific descriptions of social life (Blaikie, 1993 , p. 177) (see Table 4 ). Abduction answers “what” questions with induction, why questions with deduction, and “how” questions with hypothesized processes that explain how, and under what conditions, phenomena occur. Abduction involves making a logical leap that infers an explanatory process to explain an outcome in an oscillating logic. Deductive, inductive, and inferential processes move recursively from actors’ accounts to social science accounts and back again in abduction (Gephart, 2018 ). This process enables all theory and second-order scientific concepts to be grounded in actors’ first-order meanings.

The abductive strategy contains four layers: (a) everyday concepts and meanings of actors, used for (b) social interaction, from which (c) actors provide accounts, from which (d) social scientific descriptions are made, or theories are generated and applied, to interpret phenomena (Blaikie, 1993 , p. 177). The multifaceted research process, described in Table 4 , requires locating and comprehending members’ important everyday concepts and theories before observing or creating disruptions that force members to explain the unstated knowledge behind their action. The researcher then integrates members’ first-order concepts into a general, second-order scientific theory that makes first-order understandings recoverable.

Abduction emerged from Weber’s interpretive sociology ( 1978 ) and Peirce’s ( 1936 ) philosophy. But Alfred Schutz ( 1973a , 1973b ) is the contemporary scholar who did the most to extend our understanding of abduction, although he never used the term “abduction” (Blaikie, 1993 , 2010 ; Gephart, 2018 ). Schutz conceived abduction as an approach to verifiable interpretive knowledge that is scientific and rigorous (Blaikie, 1993 ; Gephart, 2018 ). Abduction is appropriate for research that seeks to go beyond description to explanation and prediction (Blaikie, 1993 , p. 163) and discovery (Gephart, 2018 ). It employs an interpretive ontology (Schutz, 1973a , 1973b ) and social constructionist epistemology (Berger & Luckmann, 1966 ), using qualitative methods to discover “why people do what they do” (Blaikie, 1993 ).

Dynamic data collection methods are needed for abductive research to capture descriptions of interactions in actual settings and their meanings to members. Observational and interview approaches that elicit members’ concepts and theories are particularly relevant to abductive understanding (see Table 2 ). Data analysis methods must analyze situated, first-order (common sense) discourse as it unfolds in real settings and then systematically develop second-order concepts or theories from data. Relevant approaches to produce and validate findings include ethnography, ethnomethodology, and grounded theorizing (see Table 3 ). The combination of what, why, and how questions used in abduction produces a broader understanding of phenomena than do what and why deductive and inductive questions.

Layer Three: Paradigms of Research

Scholarly paradigms integrate methods, logics, and intellectual worldviews into coherent theoretical perspectives and form the most abstract level of research design. Six paradigms are widely used in management research (Burrell & Morgan, 1979 ; Cunliffe, 2011 ; Gephart, 2004 , 2013 ; Gephart & Richardson, 2008 ; Hassard, 1993 ). The first three perspectives—positivism, interpretive induction, and interpretive abduction—build on logics of design and seek to produce rigorous empirical research that constitutes evidence (see Table 5 ). Three additional perspectives pursue philosophical, critical, and practical knowledge: critical theory, postmodernism, and organization development (see Table 6 ). Tables 5 and 6 describe important features of each research design to show similarities and differences in the processes through which theoretical meaning is bestowed on research results in management and organization studies.

Table 5. Paradigms, Logical Strategies, and Methodologies for Empirical Research

Sources: Based on and adapted and extended from Blaikie ( 1993 , pp. 137, 145, & 152); Blaikie ( 2010 , Table 4.1, p. 84); Gephart ( 2013 , Table 9.1, p. 291) and Gephart ( 2018 , Table 3.1, pp. 38–39).

Table 6. Alternative Paradigms, Logical Strategies, and Methodologies

Based in part on Gephart ( 2004 , 2013 , 2018 ).

The Positivist Approach

The qualitative positivist approach makes assumptions equivalent to those of quantitative research (Gephart, 2004 , 2018 ). It assumes the world is objectively describable and comprehensible using inductive and deductive logics. And rigor is important and achieved by reliability, validity, and generalizability of findings (Kirk & Miller, 1986 ; Malterud, 2001 ). Qualitative positivism mimics natural science logics and methods using data recorded as words and talk rather than numerals.

Positivist research (Bitektine, 2008 ; Su, 2018 ) starts with a hypothesis. This can, but need not, be based in data or inductive theory. The research process, aimed at publication in peer-reviewed journals, requires researchers to (a) identify variables to measure, (b) develop operational definitions of the variables, (c) measure (describe) the variables and their inter-relationships, (d) pose hypotheses to test relationships among variables, then (e) compare observations to hypotheses for testing (Blaikie, 2010 ). When data are consistent with theory, theory passes the test. Otherwise the theory fails. This theory is also assessed for its logical correctness and value for knowledge. The positivist approach can assess deductive and inductive generalizations and provide evidence concerning why something occurs—if proposed hypotheses are not rejected.

Positivists view qualitative research as highly subject to biases that must be prevented to ensure rigor, and 23 methodological steps are recommended to enhance rigor and prevent bias (Gibbert & Ruigrok, 2010 , p. 720). Replicability is another concern because methodology descriptions in qualitative publications “insufficiently describe” how methods are used (Lee, Mitchell, & Sablynski, 1999 , p. 182) and thereby prevent replication. To ensure replicability, a qualitative “article’s description of the method must be sufficiently detailed to allow a reader . . . to replicate that reported study either in a hypothetical or actual manner.”

Qualitative research allows positivists to observe naturally unfolding behavior in real settings and allow “the real world” of work to inform research and theory (Locke & Golden-Biddle, 2004 ). Encounters with the actual world provide insights into meaning construction by members that cannot be captured with outsider (etic) approaches. For example, past quantitative research provided inconsistent findings on the importance of pre- and post-recruitment screening interviews for job choices of recruits. A deeper investigation was thus designed to examine how recruitment impacts job selection (Rynes, Bretz, & Gerhart, 1991 ). To do so, students undergoing recruitment were asked to “tell us in their own words” how their recruiting and decision processes unfolded (Rynes et al., 1991 , p. 399). Using qualitative evidence, the researchers found that, in contrast to quantitative findings, “people do make choices based on how they are treated” (p. 509), and the choices impact recruitment outcomes. Rich descriptions of actual behavior can disconfirm quantitative findings and produce new findings that move the field forward.

An important limitation of positivism is its common emphasis on outsiders’ or scientific observers’ objective conceptions of the world. This limits the attention positivist research gives to members’ knowledge and allows positivist research to impose outsiders’ meanings on members’ everyday behavior, leading to a lack of understanding of what the behavior means to members. Another limitation is that no formal, logical, or proven techniques exist to assess the strength of “relationships” among qualitative variables, although such assessments can be formally done using well-formed quantitative data and techniques. Thus, qualitative positivists often provide ambiguous or inexplicit quantitative depictions of variable relations (e.g., “strong relationship”). Alternatively, the analysts quantify qualitative data by assigning numeric codes to categories (Greckhamer, Misngyi, Elms, & Lacey, 2008 ), using non-parametric statistics, or quantitative content analysis (Sonpar & Golden-Biddle, 2008 ) to create numerals that depict associations among variables.

An illustrative example of positivist research . Cole ( 1985 ) studied why and how organizations change their working structures from bureaucratic forms to small, self-supervised work teams that allow for worker participation in shop floor activities. Cole found that existing research on workplace change focused on the micropolitical level of organizations. He hypothesized that knowledge could be advanced differently, by examining the macropolitical change in industries or nations. Next, a testable conclusion was deduced: a macro analysis of the politics of change can better predict the success of work team implementation, measured as the spread of small group work structures, than an examination of the micropolitics of small groups ( 1985 ). Three settings were selected for the research: Japan, Sweden, and the United States. Japanese data were collected from company visits and interviews with employment officials and union leaders. Swedish documentary data on semiautonomous work groups were used and supplemented by interviews at Volvo and Saab, and prior field research in Sweden. U.S. data were collected through direct observations and a survey of early quality circle adopters.

Extensive change was observed in Sweden and Japan but changes to small work groups were limited in the United States (Cole, 1985 ). This conclusion was verified using records of the experiences of the three nations in work reform, compared across four dimensions: timing and scope of changes, managerial incentives to innovate, characteristics of mobilization, and political dimensions of change. Data revealed the United States had piecemeal experimentation and resistance to reform through the 1970s; diffusion emerged in Japan in the early 1960s and became extensive; and Swedish workplace reform started in the 1960s and was widely and rapidly diffused.

Cole then answered the questions of “why” and “how” the change occurred in some countries but not others. Regarding why Japanese and Swedish managers were motivated to introduce workplace change due to perceived managerial problems and the changing national labor market. Differences in the political processes also influenced change. Management, labor, and government interest in workplace change was evident in Japan and Sweden but not in the United States where widespread resistance occurred. As to how, the change occurred through macropolitical processes (Cole, 1985 , p. 120), specifically, the commitment of the national business leadership to the change and whether or not the change was contested or uncontested by labor impacted the adoption of change. Organizational change usually occurs through broad macropolitical processes, hence “the importance of macro-political variables in explaining these outcomes” (p. 122).

Interpretive Induction

Two streams of qualitative research claim the label of “interpretive research” in management and organization studies. The first stream, interpretive induction, emphasizes induction as its primary logical strategy (e.g., Locke, 2001 , 2002 ; Pratt, 2009 ). It assumes a “real world” that is inherently objective but interpreted through subjective lenses, hence different people can perceive or report different things. This research is interpretive because it addresses the meanings and interpretations people give to organizational phenomena, and how this meaning is provided and used. Interpretive induction contributes to scientific knowledge by providing empirical descriptions, generalizations, and low-level theories about specific contexts based on thick descriptions of members’ settings and interactions (first-order understandings) as data.

The interpretive induction paradigm addresses “what” questions that describe and explain the existence and features of phenomena. It seeks to uncover the subjective, personal knowledge that subjects have of the objective world and does so by creating descriptive accounts of the activities of organizational members. Interpretive induction creates inductive theories based on limited samples that provide low-scope, abstract theory. Limitations (Table 5 ) include the fact that inductive generalizations are limited to the sample used for induction and need to be subjected to additional tests and comparisons for substantiation. Second, research reports often fail to provide details to allow replication of the research. Third, formal methods for assessing the accuracy and validity of results and findings are limited. Fourth, while many features of scientific research are evident in interpretive induction research, the research moves closer to humanistic knowledge than to science when the basic assumptions of inductive analysis are relaxed—a common occurrence.

An illustrative example of interpretive induction research . Adler and Adler ( 1988 , 1998 ) undertook a five-year participant-observation study of a college basketball program (Adler, 1998 , p. 32). They sought to “examine the development of intense loyalty in one organization.” Intense loyalty evokes “devotional commitment of . . . (organizational) members through a subordination that sometime borders on subservience” (p. 32). The goal was to “describe and analyze the structural factors that emerged as most related” to intense loyalty (p. 32).

The researchers divided their roles. Peter Adler was the active observer and “expert” who undertook direct observations while providing counsel to players (p. 33). Patricia Adler took the peripheral role of “wife” and debriefed the observer. Two research questions were posed: (a) “what” kinds of organizational characteristics foster intense loyalty? (b) “how” do organizations with intense loyalty differ structurally from those that lack intense loyalty?

The first design stage (Table 5 ) recorded unbiased observations in extensive field notes. Detailed “life history” accounts were obtained from 38 team members interviewed (Adler & Adler, 1998 , p. 33). Then analytical induction and the constant comparative method (Glaser & Strauss, 1967 ) were used to classify and compare observations (p. 33). Once patterns emerged, informants were questioned about variations in patterns (p. 34) to develop “total patterns” (p. 34) reflecting the collective belief system of the group. This process required a “careful and rigorous means of data collection and analysis” that was “designed to maximize both the reliability and validity of our findings” (p. 34). The study found five conceptual elements were essential to the development of intense loyalty: domination, identification, commitment, integration, and goal alignment (p. 35).

The “what” question was answered by inducing a generalization (stage 3): paternalistic organizations with charismatic leadership seek people who “fit” the organization’s style and these people require extensive socialization to foster intense loyalty. This description contrasts with rational bureaucratic organizations that seek people who fit specific, generally known job descriptions and require limited socialization (p. 46). The “how” question is answered by inductive creation of another generalization: organizations that control the extra-organizational activities of members are more likely to evoke intense loyalty by forcing members to subordinate all other interests to those of the organization (p. 46).

The Interpretive Abduction Approach

The second stream of interpretive research—interpretive abduction—produces scientific knowledge using qualitative methods (Gephart, 2018 ). The approach assumes that commonsense knowledge is foundational to how actors know the world. Abductive theory is scientifically built from, and refers to, everyday life meanings, in contrast to positivist and interpretive induction research that omits concern with the worldview of members. Further, interpretive abduction produces second-order or scientific theory and concepts from members’ first-order commonsense concepts and meanings (Gephart, 2018 , p. 34; Schutz, 1973a , 1973b ).

The research process, detailed in Table 5 (process and stages), focuses on collecting thick descriptive data on organizations, identifying and interpreting first-order lay concepts, and creating abstract second-order technical constructs of science. The second-order concepts describe the first-order principles and terms social actors use to organize their experience. They compose scientific concepts that form a theoretical system to objectively describe, predict, and explain social organization (Gephart, 2018 , p. 35). This requires researchers to understand the subjective view of the social actors they study, and to develop second-order theory based on actors’ subjective meanings. Subjective meaning can be shared with others through language use and communication and is not private knowledge.

A central analytical task for interpretive abduction is creating second-order, ideal-type models of social roles, motives, and interactions that describe the behavioral trajectories of typical actors. Ideal-type models can be objectively compared to one another and are the special devices that social science requires to address differences between social phenomena and natural phenomena (Schutz, 1973a , 1973b ). The models, once built, are refined to preserve actors’ subjective meanings, to be logically consistent, and to present human action from the actor’s point of view. Researchers can then vary and compare the models to observe the different outcomes that emerge. Scientific descriptions can then be produced, and theories can be created. Interpretive abduction (Gephart, 2018 , p. 35) allows one to addresses what, why, and how questions in a holistic manner, to describe relationships among scientific constructs, and to produce “empirically ascertainable” and verifiable relations among concepts (Schutz, 1973b , p. 65) that are logical, hold practical meaning to lay actors, and provide abstract, objective meaning to interpretive scientists (Gephart, 2018 , p. 35). Abduction produces knowledge about socially shared realities by observing interactions, uncovering members’ first-order meanings, and then developing technical second-order or scientific accounts from lay accounts.

Interpretive abduction (Gephart, 2018 ) uses well-developed methods to create, refine, test, and verify second-order models, and it provides well-developed tools to support technical, second-level analyses. Research using the interpretive abduction approach includes a study of how technology change impacts sales automobile practices (Barley, 2015 ) and an investigation study of how abduction was used to develop new prescription drugs (Dunne & Dougherty, 2016 ).

An illustrative example of the interpretive abduction approach . Perlow ( 1997 ) studied time management among software engineers facing a product launch deadline. Past research verified the widespread belief that long working hours for staff are necessary for organizational success. This belief has adversely impacted work life and led to the concept of a “time bind” faced by professionals (Hochschild, 1997 ). One research question that subsequently emerged was, “what underlies ‘the time bind’ experienced by engineers who face constant deadlines and work interruptions?” (Perlow, 1997 , p. xvii). This is an inductive question about the causes and consequences of long working hours not answered in prior research that is hard to address using induction or deduction. Perlow then explored assumption underlying the hypothesis, supported by lay knowledge and management literature, that even if long working hours cause professionals to destroy their life style, long work hours “further the goals of our organizations” and “maximize the corporation’s bottom line” (Perlow, 1997 , p. 2).

The research commenced (Table 5 , step 1) when Perlow gained access to “Ditto,” a leader in implementing flexible work policies (Perlow, 1997 , p. 141) and spent nine months doing participant observation four days a week. Perlow collected descriptive data by walking around to observe and converse with people, attended meetings and social events, interviewed engineers at work and home and spouses at home, asked participants to record activities they undertook on selected working days (Perlow, 1997 , p. 143), and made “thousands of pages of field notes” (p. 146) to uncover trade-offs between work and home life.

Perlow ( 1997 , pp. 146–147) analyzed first-order concepts uncovered through his observations and interviews from 17 stories he wrote for each individual he had studied. The stories described workstyles, family lives, and traits of individuals; provided objective accounts of subjective meanings each held for work and home; offered background information; and highlighted first-order concepts. Similarities and differences in informant accounts were explored with an empirically grounded scheme for coding observations into categories using grounded theory processes (Gioia, Corley, & Hamilton, 2012 ). The process allowed Perlow to find key themes in stories that show work patterns and perceptions of the requirements of work success, and to create ideal-type models of workers (step 3). Five stories were selected for detailed analysis because they reveal important themes Perlow ( 1997 , p. 147). For example, second-order, ideal-type models of different “roles” were constructed in step 3 including the “organizational superstar” (pp. 15–21) and “ideal female employee” (pp. 22–32) based on first-order accounts of members. The second-order ideal-type scientific models were refined to include typical motives. The models were compared to one another (step 4) to describe and understand how the actions of these employee types differed from other employee types and how these variations produced different outcomes for each trajectory of action (steps 4 and 5).

Perlow ( 1997 ) found that constant help-seeking led engineers to interrupt other engineers to get solutions to problems. This observation led to the abductively developed hypothesis that interruptions create a time crisis atmosphere for engineers. Perlow ( 1997 ) then created a testable, second-order ideal-type (scientific) model of “the vicious working cycle” (p. 96), developed from first-order data, that explains the productivity problems that the firm (and other research and development firms)—commonly face. Specifically, time pressure → crisis mentality → individual heroics → constant interruptions of others’ work to get help → negative consequences for individual → negative consequences for the organization.

Perlow ( 1997 ) then tested the abductive hypothesis that the vicious work cycle caused productivity problems (stage 5). To do so, the vicious work cycle was transformed into a virtuous cycle using scheduling quiet times to prevent work interruptions: relaxed work atmosphere → individuals focus on own work completion → few interruptions → positive consequences for individual and organization. To test the hypothesis, an experiment was conducted (research process 2 in Table 5 ) with engineers given scheduled quiet times each morning with no interruptions. The experiment was successful: the project deadline was met. The hypothesis about work interruptions and the false belief that long hours are needed for success were supported (design stage 6). Unfortunately, the change was not sustained and engineers reverted to work interruptions when the experiment ended.

There are three additional qualitative approaches used in management research that pursue objectives other than producing empirical findings and developing or testing theories. These include critical theory and research, postmodernism, and change intervention research (see Table 6 ).

The Critical Theory and Research Approach

The term “critical” has many meanings including (a) critiques oriented to uncovering ideological manifestations in social relations (Gephart, 2013 , p. 284); (b) critiques of underlying assumptions of theories; and (c) critique as self-reflection that reflexively encapsulates the investigator (Morrow, 1994 , p. 9). Critical theory and critical management studies bring these conceptions of critical to bear on organizations and employees.

Critical theory and research extend the theories Karl Marx, and the Frankfurt School in Germany (Gephart & Kulicki, 2008 ; Gephart & Pitter, 1995 ; Habermas, 1973 , 1979 ; Morrow, 1994 ; Offe, 1984 , 1985 ). Critical theory and research assume that social science research differs from natural science research because social facts are human creations and social phenomena cannot be controlled as readily as natural phenomena (Gephart, 2013 , p. 284; Morrow, 1994 , p. 9). As a result, critical theory often uses a historical approach to explore issues that arise from the fundamental contradictions of capitalism. Critical research explores ongoing changes within capitalist societies and organizations, and analyzes the objective structures that constrain human imagination and action (Morrow, 1994 ). It seeks to uncover the contradictions of advanced capitalism that emerge from the fundamental contradiction of capitalism: owners of capital have the right to appropriate the surplus value created by workers. This basic contradiction produces further contradictions that become sources of workplace oppression and resistance that create labor issues. Thus contradictions reveal how power creates consciousness (Poutanen & Kovalainen, 2010 ). Critical reflection is used to de-reify taken-for-granted structures that create power inequities and to motivate resistance and critique and escape from dominant structures (see Table 6 ).

Critical management studies build on critical theory in sociology. It seeks to transform management and provide alternatives to mainstream theory (Adler, Forbes, & Willmott, 2007 ). The focus is “the social injustice and environmental destruction of the broader social and economic systems” served by conventional, capitalist managers (Adler et al., 2007 , p. 118). Critical management research examines “the systemic corrosion of moral responsibility when any concern for people or for the environment . . . requires justification in terms of its contribution to profitable growth” (p. 4). Critical management studies goes beyond scientific skepticism to undertake a radical critique of socially divisive and environmentally destructive patterns and structures (Adler et al., 2007 , p. 119). These studies use critical reflexivity to uncover reified capitalist structures that allow certain groups to dominate others. Critical reflection is used to de-reify and challenge the facts of social life that are seen as immutable and inevitable (Gephart & Richardson, 2008 , p. 34). The combination of dialogical inquiry, critical reflection, and a combination of qualitative and quantitative methods and data are common in this research (Gephart, 2013 , p. 285). Some researchers use deductive logics to build falsifiable theories while other researchers do grounded theory building (Blaikie, 2010 ). Validity of critical research is assessed as the capability the research has to produce critical reflexivity that comprehends dominant ideologies and transforms repressive structures into democratic processes and institutions (Gephart & Richardson, 2008 ).

An illustrative example of critical research . Barker ( 1998 , p. 130) studied “concertive control” in self-managed work teams in a small manufacturing firm. Concertive control refers to how workers collaborate to engage in self-control. Barker sought to understand how control practices in the self-managed team setting, established to allow workers greater control over their work, differed from previous bureaucratic processes. Interviews, observations, and documents were used as data sources. The resultant description of work activities and control shows that rather than allowing workers greater control, the control process enacted by workers themselves became stronger: “The iron cage becomes stronger” and almost invisible “to the workers it incarcerates” (Barker, 1998 , p. 155). This study shows how traditional participant observation methods can be used to uncover and contest reified structures and taken-for-granted truths, and to reveal the hidden managerial interests served.

Postmodern Perspectives

The postmodern perspective (Boje, Gephart, & Thatchenkery, 1996 ) is based in philosophy, the humanities, and literary criticism. Postmodernism, as an era, refers to the historical stage following modernity that evidences a new cultural worldview and style of intellectual production (Boje et al., 1996 ; Jameson, 1991 ; Rosenau, 1992 ). Postmodernism offers a humanistic approach to reconceptualize our experience of the social world in an era where it is impossible to establish any foundational underpinnings for knowledge. The postmodern perspective assumes that realities are contradictory in nature and value-laden (Gephart & Richardson, 2008 ; Rosenau, 1992 , p. 6). It addresses the values and contradictions of contemporary settings, how hidden power operates, and how people are categorized (Gephart, 2013 ). Postmodernism also challenges the idea that scientific research is value free, and asks “whose values are served by research?”

Postmodern essays depart from concerns with systematic, replicable research methods and designs (Calas, 1987 ). They seek instead to explore the values and contradictions of contemporary organizational life (Gephart, 2013 , p. 289). Research reports have the character of essays that seek to reconceptualize how people experience the world (Martin, 1990 ; Rosenau, 1992 ) and to disrupt this experience by producing “reading effects” that unsettle a community (Calas & Smircich, 1991 ).

Postmodernism examines intertextual relations—how texts become embedded in other texts—rather than causal relations. It assumes there are no singular realities or truths, only multiple realities and multiple truths, none of which are superior to other truths (Gephart, 2013 ). Truth is conceived as the outcome of language use in a context where power relations and multiple realities exist.

From a methodological view, postmodern research tends to focus on discourse: texts and talk. Data collection (in so far as it occurs) focuses on records of discourse—texts of spoken and written verbal communication (Fairclough, 1992 ). Use of formal or official records including recordings, texts and transcripts is common. Analytically, scholars tend to use critical discourse analysis (Fairclough, 1992 ), narrative analysis (Czarniawska, 1998 ; Ganzin, Gephart, & Suddaby, 2014 ), rhetorical analysis (Culler, 1982 ; Gephart, 1988 ; McCloskey, 1984 ) and deconstruction (Calais & Smircich, 1991 ; Gephart, 1988 ; Kilduff, 1993 ; Martin, 1990 ) to understand how categories are shaped through language use and come to privilege or subordinate individuals.

Postmodernism challenges models of knowledge production by showing how political discourses produce totalizing categories, showing how categorization is a tool for social control, and attempting to create opportunities for alternative representations of the world. It thus provides a means to uncover and expose discursive features of domination, subordination, and resistance in society (Locke & Golden-Biddle, 2004 ).

An illustrative example of postmodern research . Martin ( 1990 ) deconstructed a conference speech by a company president. The president was so “deeply concerned” about employee well-being and involvement at work that he encouraged a woman manager “to have her Caesarian yesterday” so she could participate in an upcoming product launch. Martin deconstructs the story to reveal the suppression of gender conflict in the dialogue and how this allows gender conflict and subjugation to continue. This research established the existence of important domains of organizational life, such as tacit gender conflict, that have not been adequately addressed and explored the power dynamics therein.

The Organization Development Approach

OD involves a planned and systematic diagnosis and intervention into an organizational system, supported by top management, with the intent of improving the organization’s effectiveness (Beckhard, 1969 ; Palmer, Dunford, & Buchanan, 2017 , p. 282). OD research (termed “clinical research” by Schein, 1987 ) is concerned with changing attitudes and behaviors to instantiate fundamental values in organizations. OD research often follows the general process of action research (Lalonde, 2019 ) that involves working with actors in an organization to help improve the organization. OD research involves a set of stages the OD practitioner (the leader of the intervention) uses: (a) problem identification; (b) consultation between OD practitioner and client; (c) data collection and problem diagnosis; (d) feedback; (e) joint problem diagnosis; (f) joint action planning; (g) change actions; and (h) further data gathering to move recursively to a refined step 1.

An illustrative example of the organization development approach . Numerous OD techniques exist to help organizations change (Palmer et al., 2017 ). The OD approach is illustrated here by the socioeconomic approach to management (SEAM) (Buono & Savall, 2007 ; Savall, 2007 ). SEAM provides a scientific approach to organizational intervention consulting that integrates qualitative information on work practices and employee and customer needs (socio) with quantitative and financial performance measures (economics). The socioeconomic intervention process commences by uncovering dysfunctions that require attention in an organization. SEAM assumes that organizations produce both (a) explicit benefits and costs and (b) hidden benefits and costs. Hidden costs refer to economic implications of organizational dysfunctions (Worley, Zardet, Bonnet, & Savall, 2015 , pp. 28–29). These include problems in working conditions; work organization; communication, co-ordination, and co-operation; time management; integrated training; and strategy implementation (Savall, Zardet, & Bonnet, 2008 , p. 33). Explicit costs are emphasized in management decision-making but hidden costs are ignored. Yet hidden costs from dysfunctions often greatly outstrip explicit costs.

For example, a fishing company sought to protect its market share by reducing the price and quality of products, leading to the purchase of poor-quality fish (Savall et al., 2008 , pp. 31–32). This reduced visible costs by €500,000. However, some customers stopped purchasing because of the lower-quality product, producing a loss of sales of €4,000,000 in revenue or an overall drop in economic performance of €3,500,000. The managers then changed their strategy to focus on health and quality. They implemented the SEAM approach, assessed the negative impact of the hidden costs on value added and revenue received, and purchased higher-quality fish. Visible costs (expenses) increased by €1,000,000 due to the higher cost for a better-quality product, but the improved quality (performance) cut the hidden costs by increasing loyalty and increased sales by €5,000,000 leaving an increased profit of €4,000,000.

SEAM allows organizations to uncover hidden costs in their operations and to convert these costs into value-added human potential through a process termed “qualimetrics.” Qualimetrics assesses the nature of hidden costs and organizational dysfunctions, develops estimates of the frequencies and amounts of hidden costs in specific organizational domains, and develops actions to reduce the hidden costs and thereby release additional value added for the organization (Savall & Zardet, 2011 ). The qualimetric process is participative and involves researchers who use observations, interviews and focus groups of employees to (a) describe, qualitatively, the dysfunctions experienced at work (qualitative data); (b) estimate the frequencies with which dysfunctions occur (quantitative data); and (c) estimate the costs of each dysfunction (financial data). Then, strategic change actions are developed to (a) identify ways to reduce or overcome the dysfunction, (b) estimate how frequently the dysfunction can be remedied, and (c) estimate the overall net costs of removing the hidden costs to enhance value added. The economic balance is then assessed for changes to transform the hidden costs into value added.

OD research creates actionable knowledge from practice (Lalonde, 2019 ). OD intervention consultants use multistep processes to change organizations that are flexible practices not fixed research designs. OD plays an important role in developing evidence-based practices to improve organizational functioning and performance. Worley et al. ( 2015 ) provide a detailed example of the large-scale implementation of the SEAM OD approach in a large, international firm.

Here we discuss implication of qualitative research designs for covert research, reporting qualitative work and novel integrations of qualitative and quantitative work.

Covert Research

University ethics boards require researchers who undertake research with human participants to obtain informed consent from the participants. Consent requires that all participants must be informed of details of the research procedure in which they will be involved and any risks of participation. Researchers must protect subjects’ identities, offer safeguards to limit risks, and insure informant anonymity. This consent must be obtained in the form of a signed agreement from the participant, obtained prior to the commencement of research observations (McCurdy et al., 2005 , pp. 29–32).

Covert research that fails to fully disclose research purposes or practices to participants, or that is otherwise deceptive by design or tacit practice, has long been considered “suspect” in the field (Graham, 1995 ; Roulet, Gill, Stenger, & Gill, 2017 ). This is changing. Research methodologists have shown that the over/covert dimension is a continuum, not a dichotomy, and that unintended covert elements occur in many situations (Roulet et al., 2017 ). Thus all qualitative observation involves some degree of deception due practical constraints on doing observations since it is difficult to do fully overt research, particularly in observational contexts with many people, and to gain advance consent from everyone in the organization one might encounter.

There are compelling benefits to covert research. It can provide insights not possible if subjects are fully informed of the nature or existence of the research. For example, the year-long, covert observational study of an asylum as a “total institution” (Goffman, 1961 ) showed how ineffective the treatment of mental illness was at the time. This opened the field of mental health to social science research (Roulet et al., 2017 , p. 493). Covert research can also provide access to institutions that researchers would otherwise be excluded from, including secretive and secret organizations (p. 492). This could allow researchers to collect data as an insider and to better see and experience the world from members’ perspective. It could also reduce “researcher demand effects” that occur when informants obscure their normal behavior to conform to research expectations. Thus, the inclusion of covert research data collection in research designs and proposals is an emerging trend and realistic possibility. Ethics applications can be developed that allow for aspects of covert research, and observations in many public settings do not require informed consent.

The Appropriate Style for Reporting Qualitative Work

The appropriate style for reporting qualitative research has become an issue of concern. For example, editors of the influential Academy of Management Journal have noted the emergence of an “AMJ style” for qualitative work (Bansal & Corley, 2011 , p. 234). They suggest that all qualitative work should use this style so that qualitative research can “benefit” from: “decades of refinement in the style of quantitative work.” The argument is that most scholars can assess the empirical and theoretical contributions of quantitative work but find it difficult to do so for qualitative research. It is easier for quantitatively trained editors and scholars “to spot the contribution of qualitative work that mimics the style of quantitative research.” Further, “the majority of papers submitted to . . . AMJ tend to subscribe to the paradigm of normal science that aims to find relationships among valid constructs that can be replicated by anyone” (Bansal, Smith, & Vaara, 2018 , p. 1193). These recommendations appear to explicitly encourage the reporting of qualitative results as if they were quantitatively produced and interpreted and highlights the advantage of conformity to the prevailing positivist perspective to gain publication in AMJ.

Yet AMJ editors have also called for researchers to “ensure that the research questions, data, and analysis are internally consistent ” (Bansal et al., 2018 , p. 1193) and to “Be authentic , detailed and clear in argumentation” (emphasis added) (Bansal et al., 2018 , p. 1193). These calls for consistency appear to be inconsistent with suggestions to present all qualitative research using a style that mimics quantitative, positivist research. Adopting the quantitative or positivist style for all qualitative reports may also confuse scholars, limit research quality, and hamper efforts to produce innovative, non-positivist research. This article provides six qualitative research designs to ensure a range of qualitative research publications are internally consistent in methods, logics, paradigmatic commitments, and writing styles. These designs provide alternatives to positivist mimicry in non-positivist scholarly texts.

Integrating Qualitative and Quantitative Research in New Ways

Qualitative research often omits consideration of the naturally occurring uses of numbers and statistics in everyday discourse. And quantitative researchers tend to ignore qualitative evidence such as stories and discourse. Yet knowledge production processes in society “rely on experts and laypeople and, in so doing, make use of both statistics and stories in their attempt to represent and understand social reality” (Ainsworth & Hardy, 2012 , p. 1649). Numbers and statistics are often used in stories to create legitimacy, and stories provide meaning to numbers (Gephart, 1988 ). Hence stories and statistics cannot be separated in processes of knowledge production (Ainsworth & Hardy, 2012 , p. 1697). The lack of attention to the role of quantification in everyday life means a huge domain of organizational discourse—all talk that uses numbers, quantities, and statistics—is largely unexplored in organizational research.

Qualitative research has, however, begun to study how words and numbers are mutually used for organizational storytelling (Ainsworth & Hardy, 2012 ; Gephart, 2016 ). This focus offers the opportunity to develop research designs to explore qualitative features and processes involved in quantitative phenomena such as financial crises (Gephart, 2016 ), to address how stories and numbers need to work together to create legitimate knowledge (Ainsworth & Hardy, 2012 ), and to show how statistics are used rhetorically to convince others of truths in organizational research (Gephart, 1988 ).

Ethnostatistics (Gephart, 1988 ; Gephart & Saylors, 2019 ) provides one example of how to integrate qualitative and quantitative research. Ethnostatistics examines how statistics are constructed and used by professionals. It explores how statistics are constructed in real settings, how violations of technical assumptions impact statistical outcomes, and how statistics are used rhetorically to convince others of the truth of research outcomes. Ethnostatistics has been used to reinterpret data from four celebrated network studies that themselves were reanalyzed (Kilduff & Oh, 2006 ). The ethnostatistical reanalyses revealed how ad hoc practices, including judgment calls and the imputation of new data into old data set for reanalysis, transformed the focus of network research from diffusion models to structural equivalence models.

Another innovative study uses a Bayesian ethnostatistical approach to understand how the pressure to produce sophisticated and increasingly complex theoretical narratives for causal models has impacted the quantitative knowledge generated in top journals (Saylors & Trafimow, 2020 ). The use of complex causal models has increased substantially over time due to a qualitative and untested belief that complex models are true. Yet statistically speaking, as the number of variables in a model increase, the likelihood the model is true rapidly decreases (Saylors & Trafimow, 2020 , p. 3).

The authors test the previously untested (qualitative) belief that complex causal models can be true. They found that “the joint probability of a six variable model is about 3.5%” (Saylors & Trafimow, 2020 , p. 1). They conclude that “much of the knowledge generated in top journals is likely false” hence “not reporting a (prior) belief in a complex model” should be relegated to the set of questionable research practices. This study shows how qualitative research that explores the lay theories and beliefs of statisticians and quantitative researchers can challenge and disrupt conventions in quantitative research, improve quantitative practices, and contribute qualitative foundations to quantitative research. Ethnostatistics thus opens the qualitative foundations of quantitative research to critical qualitative analyses.

The six qualitative research design processes discussed in this article are evident in scholarly research on organizations and management and provide distinct qualitative research designs and approaches to use. Qualitative research can provide research insights from several theoretical perspectives, using well-developed methods to produce scientific and scholarly insights into management and organizations. These approaches and designs can also inform management practice by creating actionable knowledge. The intended contribution of this article is to describe these well-developed methods, articulate key practices, and display core research designs. The hope is both to better equip researchers to do qualitative research, and to inspire them to do so.

Acknowledgments

The authors wish to acknowledge the assistance of Karen Lund at The University of Alberta for carefully preparing Figure 1 . Thanks also to Beverly Zubot for close reading of the manuscript and helpful suggestions.

• Adler, P. A. , & Adler, P. (1988). Intense loyalty in organizations: A case study of college athletics. Administrative Science Quarterly , 401–417.
• Adler, P. A. , & Adler, P. (1998). Intense loyalty in organizations: A case study of college athletics. In J. Van Maanen (Ed.), Qualitative studies of organizations (pp. 31–50). Thousand Oaks, CA: SAGE.
• Adler, P. S. , Forbes, L. C. , & Willmott, H. (2007). Critical management studies. Academy of Management Annals , 1 (1), 119–180.
• Agar, M. H. (1980). The professional stranger: An informal introduction to ethnography . New York, NY: Academic Press.
• Ainsworth, S. , & Hardy, C. (2012). Subjects of inquiry: Statistics, stories, and the production of knowledge. Organization Studies , 33 (12), 1693–1714.
• Akeson, C. (2005). Getting the truth: The police detective and the art of interviewing. In D. W. McCurdy , J. P. Spradley , & D. J. Shandy (Eds.), The cultural experience: Ethnography in complex society (2nd ed., pp. 103–111). Long Grove, IL: Waveland Press.
• Avenier, M.-J. , & Thomas, C. (2015). Finding one’s way around various methodological guidelines for doing rigorous case studies: A comparison of four epistemological frameworks. Systèmes d’information & Management , 20 (1), 61–98.
• Bansal, P. , & Corley, K. (2011). From the editors—The coming of age for qualitative research: Embracing the diversity of qualitative methods. Academy of Management Journal , 54 (2), 233–237.
• Bansal, P. , Smith, W. K. , & Vaara, E. (2018). From the editors: New ways of seeing through qualitative research. Academy of Management Journal , 61 (4), 1189–1195.
• Barker, J. R. (1993). Tightening the iron cage: Concertive control in self-managing teams. Administrative Science Quarterly , 38 (3), 408–437.
• Barker, J. (1998). Tightening the iron cage: Concertive control in self-managing teams. In J. Van Maanen (Ed.), Qualitative studies of organizations (pp. 126–158). Thousand Oaks, CA: SAGE.
• Barley, S. R. (2015). Why the internet makes buying a car less loathsome: How technologies change role relations. Academy of Management Discoveries , 1 (1), 31–60.
• Beckhard, R. (1969). Organization development: Strategies and models . Boston, MA: Addison-Wesley.
• Berger, P. L. , & Luckmann, T. (1966). The social construction of reality: A treatise in the sociology of knowledge . New York, NY: Doubleday.
• Bhaskar, R. (1978). A realist theory of science . Sussex: Harvester Press; Atlantic Highlands, NJ: Humanities Press.
• Bitektine, A. (2008). Prospective case study design: Qualitative method for deductive theory testing. Organizational Research Methods , 11 (1), 160–180.
• Blaikie, N. (1993). Approaches to social enquiry (1st ed.). Cambridge, UK: Polity Press.
• Blaikie, N. (2010). Designing social research: The logic of anticipation (2nd ed.). Cambridge, UK: Polity Press.
• Boje, D. M. (2001). Narrative methods for organizational and communication research . Thousand Oaks, CA: SAGE.
• Boje, D. M. (2008). Storytelling organizations . Thousand Oaks, CA: SAGE.
• Boje, D. M. , Gephart, R. P., Jr. , & Thatchenkery, T. J. (Eds.). (1996). Postmodern management and organization theory . Thousand Oaks, CA: SAGE.
• Boje, D. M. , & Saylors, R. (2014). Quantum storytelling: An ontological perspective on process. In F. Cooren , E. Vaara , A. Langley , & H. Tsoukas (Eds.), Language and communication at work: Discourse, narrativity, and organizing (pp. 197–217). Oxford, UK: Oxford University Press.
• Buono, A. F. , & Savall, H. (Eds.). (2007). Socio-economic intervention in organizations: The intervener-researcher and the SEAM approach to organizational analysis . Charlotte, NC: Information Age.
• Burrell, G. , & Morgan, G. (1979). Sociological paradigms and organisational analysis: Elements of the sociology of corporate life . London, UK: Heinemann.
• Calás, M. B. (1987). Organizational science/fiction: The postmodern in the management disciplines (Unpublished doctoral dissertation). University of Massachusetts, Amherst.
• Calás, M. B. , & Smircich, L. (1991). Voicing seduction to silence leadership. Organization Studies , 12 (4), 567–601.
• Campbell, D. T. (1975). Degrees of freedom and the case study. Comparative Political Studies , 8 (2), 178–193.
• Cicourel, A. V. (1980). Three models of discourse analysis: The role of social structure. Discourse Processes , 3 (2), 101–132.
• Cole, R. E. (1985). The macropolitics of organizational change: A comparative analysis of the spread of small-group activities. Administrative Science Quarterly , 30 (4), 560–585.
• Coulon, A. (1995). Ethnomethodology . Thousand Oaks, CA: SAGE.
• Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks, CA: SAGE.
• Culler, J. (1982). On deconstruction: Theory and criticism after structuralism . Ithaca, NY: Cornell University Press.
• Cummings, T. G. , & Worley, C. G. (2015). Organization development and change (10th ed.). Stamford, CT: Cengage Learning.
• Cunliffe, A. L. (2010). Retelling tales of the field: In search of organizational ethnography 20 years on. Organizational Research Methods , 13 (2), 224–239.
• Cunliffe, A. L. (2011). Crafting qualitative research: Morgan and Smircich 30 years on. Organizational Research Methods , 14 (4), 647–673.
• Czarniawska, B. (1998). A narrative approach to organization studies . Thousand Oaks, CA: SAGE.
• de Rond, M. , & Tuncalp, D. (2017). Where the wild things are: How dreams can help identify countertransference in organizational research. Organizational Research Methods , 20 (3), 413–437.
• Denzin, N. K. , & Lincoln, Y. S. (1994). Introduction: Entering the field of qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (1st ed., pp. 1–7). Thousand Oaks, CA: SAGE.
• Dunne, D. D. , & Dougherty, D. (2016). Abductive reasoning: How innovators navigate in the labyrinth of complex innovation. Organization Studies , 37 (2), 131–159.
• Duriau, V. J. , Reger, R. K. , & Pfarrer, M. D. (2007). A content analysis of the content analysis literature in organization studies: Research themes, data sources, and methodological refinements. Organizational Research Methods , 10 (1), 5–34.
• Dutton, J. E. , Workman, K. M. , & Hardin, A. E. (2014). Compassion at work. Annual Review of Organizational Psychology and Organizational Behavior , 1 (1), 277–304.
• Easterby-Smith, M. , Thorpe, R. , & Jackson, P. (2012). Management research (4th ed.). Thousand Oaks, CA: SAGE.
• Fairclough, N. (1992). Discourse and social change . Cambridge, UK: Polity Press.
• Ganzin, M. , Gephart, R. P., Jr. , & Suddaby, R. (2014). Narrative and the construction of myths in organizations. In F. Cooren , E. Vaara , A. Langley , & H. Tsoukas (Eds.), Language and communication at work: Discourse, narrativity, and organizing (pp. 219–260). Oxford, UK: Oxford University Press.
• Garfinkel, H. (1964). Studies of the routine grounds of everyday activities. Social Problems , 11 (3), 225–250.
• Garfinkel, H. (1967). Studies in ethnomethodology . Englewood Cliffs, NJ: Prentice-Hall.
• Gephart, R. P., Jr. (1978). Status degradation and organizational succession: An ethnomethodological approach. Administrative Science Quarterly , 23 (4), 553–581.
• Gephart, R. P. (1986). Deconstructing the defense for quantification in social science: A content analysis of journal articles on the parametric strategy. Qualitative Sociology , 9 (2), 126–144.
• Gephart, R. P., Jr. (1988). Ethnostatistics: Qualitative foundations for quantitative research . Thousand Oaks, CA: SAGE.
• Gephart, R. P., Jr. (1993). The textual approach: Risk and blame in disaster sensemaking. Academy of Management Journal , 36 (6), 1465–1514.
• Gephart, R. P., Jr. (1997). Hazardous measures: An interpretive textual analysis of quantitative sensemaking during crises. Journal of Organizational Behavior , 18 (S1), 583–622.
• Gephart, R. P., Jr. (2004). From the editors: Qualitative research and the Academy of Management Journal . Academy of Management Journal , 47 (4), 454–462.
• Gephart, R. P., Jr. (2013). Doing research with words: Qualitative methodologies and industrial/organizational psychology. In J. M. Cortina & R. S. Landis (Eds.), Modern research methods for the study of behavior in organizations (pp. 265–317). New York, NY: Routledge.
• Gephart, R. P., Jr. (2016). Counter-narration with numbers: Understanding the interplay of words and numerals in fiscal storytelling. European Journal of Cross-Cultural Competence and Management , 4 (1), 21–40.
• Gephart, R. P., Jr. (2018). Qualitative research as interpretive social science. In C. Cassell , A. L. Cunliffe , & G. Grandy (Eds.), The SAGE handbook of qualitative business and management research methods: History and traditions (pp. 33–53). Thousand Oaks, CA: SAGE.
• Gephart, R. P., Jr. , & Kulicki, M. (2008). Environmental ethics and business: Toward a Habermasian perspective. In D. M. Boje (Ed.), Critical theory ethics for business and public administration (pp. 373–393). Charlotte, NC: Information Age.
• Gephart, R. P., Jr. , & Pitter, R. (1995). Textual analysis in technology research: An investigation of the management of technology risk. Technology Studies , 2 (2), 325–354.
• Gephart, R. P., Jr. , & Richardson, J. (2008). Qualitative research methodologies and international human resource management. In M. M. Harris (Ed.), Handbook of research in international human resource management (pp. 29–52). New York, NY: Erlbaum.
• Gephart, R. P., Jr. , & Saylors, R. (2019). Ethnostatistics . In P. Atkinson , S. Delamont , A. Cernat , J. W. Sakshaug , & R. A. Williams (Eds.), SAGE research methods foundations . Thousand Oaks, CA: SAGE.
• Gephart, R. P., Jr. , Topal, C. , & Zhang, Z. (2010). Future-oriented sensemaking: Temporalities and institutional legitimation. In T. Hernes & S. Maitlis (Eds.), Process, sensemaking, & organizing (pp. 275–311). Oxford, UK: Oxford University Press.
• Gibbert, M. , & Ruigrok, W. (2010). The “what” and “how” of case study rigor: Three strategies based on published work. Organizational Research Methods , 13 (4), 710–737.
• Gill, G. J. (2017). Dynamics of democratization: Elites, civil society and the transition process . New York, NY: Macmillan International Higher Education.
• Gioia, D. A. , Corley, K. G. , & Hamilton, A. L. (2012). Seeking qualitative rigor in inductive research: Notes on the Gioia methodology. Organizational Research Methods , 16 (1), 15–31.
• Glaser, B. G. , & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research . Chicago, IL: Aldine.
• Goffman, E. (1961). Asylums: Essays on the social situation of mental patients and other inmates . New York, NY: Anchor Books.
• Graham, L. (1995). On the line at Subaru-Isuzu: The Japanese model and the American worker . Ithaca, NY: Cornell University Press.
• Greckhamer, T. , Misangyi, V. F. , Elms, H. , & Lacey, R. (2008). Using qualitative comparative analysis in strategic management research: An examination of combinations of industry, corporate, and business-unit effects. Organizational Research Methods , 11 (4), 695–726.
• Greenwood, M. , Jack, G. , & Haylock, B. (2019). Toward a methodology for analyzing visual rhetoric in corporate reports. Organizational Research Methods , 22 (3), 798–827.
• Habermas, J. (1973). Legitimation crisis ( T. McCarthy , Trans.). Frankfurt, Germany: Suhrkamp Verlag.
• Habermas, J. (1979). Communication and the evolution of society ( T. McCarthy , Trans.). Boston, MA: Beacon Press.
• Hansen, H. , & Trank, C. Q. (2016). This is going to hurt: Compassionate research methods. Organizational Research Methods , 19 (3), 352–375.
• Hassard, J. (1993). Sociology and organization theory: Positivism, paradigms and postmodernity . Cambridge, UK: Cambridge University Press.
• Hempel, C. (1966). Philosophy of natural science . Upper Saddle River, NJ: Prentice-Hall.
• Hochschild, A. R. (1997). The time bind: When work becomes home and home becomes work . New York, NY: Metropolitan Books.
• Hodder, I. (1994). The interpretation of documents and material culture. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (1st ed., pp. 393–402). Thousand Oaks, CA: SAGE.
• Holstein, J. A. , & Gubrium, J. F. (1995). The active interview . Thousand Oaks, CA: SAGE.
• Jameson, F. (1991). Postmodernism, or, the cultural logic of late capitalism . Durham, NC: Duke University Press.
• Kelle, U. (Ed.). (1995). Computer-aided qualitative data analysis: Theory, methods and practice . London, UK: SAGE.
• Kilduff, M. (1993). Deconstructing organizations. Academy of Management Review , 18 (1), 13–31.
• Kilduff, M. , & Oh, H. (2006). Deconstructing diffusion: An ethnostatistical examination of Medical Innovation network data reanalyses. Organizational Research Methods , 9 (4), 432–455.
• Kirk, J. , & Miller, M. L. (1986). Reliability and validity in qualitative research . Beverly Hills, CA: SAGE.
• Lalonde, C. (2019). The development of actionable knowledge in crisis management. In R. P. Gephart, Jr. , C. C. Miller , & K. Svedberg Helgesson (Eds.), The Routledge companion to risk, crisis and emergency management (pp. 431–446). New York, NY: Routledge.
• LeBaron, C. , Jarzabkowski, P. , Pratt, M. G. , & Fetzer, G. (2018). An introduction to video methods in organizational research. Organizational Research Methods , 21 (2), 239–260.
• Lee, T. W. , & Mitchell, T. R. (1994). An alternative approach: The unfolding model of voluntary employee turnover. Academy of Management Review , 19 (1), 51–89.
• Lee, T. W. , Mitchell, T. R. , & Sablynski, C. J. (1999). Qualitative research in organizational and vocational psychology, 1979–1999. Journal of Vocational Behavior , 55 (2), 161–187.
• Lee, T. W. , Mitchell, T. R. , Wise, L. , & Fireman, S. (1996). An unfolding model of voluntary employee turnover. Academy of Management Journal , 39 (1), 5–36.
• Locke, K. (2001). Grounded theory in management research . Thousand Oaks, CA: SAGE.
• Locke, K. (2002). The grounded theory approach to qualitative research. In F. Drasgow & N. Schmitt (Eds.), Measuring and analyzing behavior in organizations: Advances in measurement and data analysis (pp. 17–43). San Francisco, CA: Jossey-Bass.
• Locke, K. , & Golden-Biddle, K. (2004). An introduction to qualitative research: Its potential for industrial and organizational psychology. In S. G. Rogelberg (Ed.), Handbook of research methods in industrial and organizational psychology (pp. 99–118). Oxford, UK: Blackwell.
• Malterud, K. (2001). Qualitative research: Standards, challenges, and guidelines. The Lancet , 358 (9280), 483–488.
• Maniha, J. , & Perrow, C. (1965). The reluctant organization and the aggressive environment. Administrative Science Quarterly , 10 (2), 238–257.
• Martin, J. (1990). Deconstructing organizational taboos: The suppression of gender conflict in organizations. Organization Science , 1 (4), 339–359.
• McCall, G. J. , & Simmons, J. L. (1969). (Eds.). Issues in participant observation: A text and reader . Reading, MA: Addison-Wesley.
• McCloskey, H. J. (1984). Ecological ethics and politics .Lanham, MD: Rowman and Littlefield
• McCloskey, D. N. (1985). The rhetoric of economics (1st ed.). Madison: University of Wisconsin Press.
• McCracken, G. (1988). The long interview . Thousand Oaks, CA: SAGE.
• McCurdy, D. , Spradley, J. , & Shandy, D. (2005). The cultural experience: Ethnography in complex society (2nd ed.). Long Grove, IL: Waveland Press.
• McLeod, S. A. (2014, February 5). The interview research method . Simply Psychology.
• Mills, A. J. , Durepos, G. , & Wiebe, E. (Eds.). (2010). Encyclopedia of case study research (Vol. 1). Thousand Oaks, CA: SAGE.
• Morgan, D. L. (1997). Focus groups as qualitative research (2nd ed.). Thousand Oaks, CA: SAGE.
• Morrow, R. A. (with Brown, D. D. ). (1994). Critical theory and methodology (1st ed.). Thousand Oaks, CA: SAGE.
• Offe, C. (1984). Das Wachstum der Dienstleistungsarbeit: Vier soziologische Erklärungsansätze. In C. Offe (Ed.), Arbeitsgeselleschaft. Strukturprobleme und Zukunftsperspektiven (pp. 291–319). Frankfurt am Main, Germany: Campus Verlag.
• Offe, C. (1985). New social movements: Challenging the boundaries of institutional politics. Social Research , 52 (4), 817–868.
• Palmer, I. , Dunford, R. , & Buchanan, D. A. (2017). Managing organizational change: A multiple perspectives approach (3rd ed.). New York, NY: McGraw-Hill Education.
• Perlow, L. A. (1997). Finding time: How corporations, individuals, and families can benefit from new work practices . Ithaca, NY: Cornell University Press.
• Piekkari, R. , & Welch, C. (2012). Pluralism in international business and international management research: Making the case. In R. Piekkari & C. Welch (Eds.), Rethinking the case study in international business and management research (pp. 3–23). Cheltenham, UK: Edward Elgar.
• Peirce, C. S. (1936). The Collected Papers . Eds. Charles Hartshorne and Paul Weiss . Cambridge M.A.: Harvard University Press.
• Pollach, I. (2012). Taming textual data: The contribution of corpus linguistics to computer-aided text analysis. Organizational Research Methods , 15 (2), 263–287.
• Poutanen, S. , & Kovalainen, A. (2010). Critical theory. In A. J. Mills , G. Durepos , & E. Wiebe (Eds.), Encyclopedia of case study research (Vol. 1, pp. 260–264). Thousand Oaks, CA: SAGE.
• Pratt, M. G. (2009). For the lack of a boilerplate: Tips on writing up (and reviewing) qualitative research. Academy of Management Journal , 52 (5), 856–862.
• Ray, J. L. , & Smith, A. D. (2012). Using photographs to research organizations: Evidence, considerations, and application in a field study. Organizational Research Methods , 15 (2), 288–315.
• Richardson, J. , & McKenna, S. (2000). Metaphorical “types” and human resource management: Self-selecting expatriates. Industrial and Commercial Training , 32 (6), 209–218.
• Rodriguez, N. , & Ryave, A. (2002). Systematic self-observation . Thousand Oaks, CA: SAGE.
• Rodriguez, N. , Ryave, A. , & Tracewell, J. (1998). Withholding compliments in everyday life and the covert management of disaffiliation. Journal of Contemporary Ethnography , 27 (3), 323–345.
• Rosenau, P. M. (1992). Post-modernism and the social sciences: Insights, inroads, and intrusions . Princeton, NJ: Princeton University Press.
• Rosile, G. A. , Boje, D. M. , Carlon, D. M. , Downs, A. , & Saylors, R. (2013). Storytelling diamond: An antenarrative integration of the six facets of storytelling in organization research design. Organizational Research Methods , 16 (4), 557–580.
• Roulet, T. J. , Gill, M. J. , Stenger, S. , & Gill, D. J. (2017). Reconsidering the value of covert research: The role of ambiguous consent in participant observation. Organizational Research Methods , 20 (3), 487–517.
• Rynes, S. L. , Bretz, R. D. , & Gerhart, B. (1991). The importance of recruitment in job choice: A different way of looking. Personnel Psychology , 44 (3), 487–521.
• Savall, H. (2007). ISEOR’s socio-economic method: A case of scientific consultancy. In A. F. Buono & H. Savall (Eds.), Socio-economic intervention in organizations: The intervener-researcher and the SEAM approach to organizational analysis (pp. 1–31). Charlotte, NC: Information Age.
• Savall, H. , & Zardet, V. (2011). The qualimetrics approach: Observing the complex object . Charlotte, NC: Information Age.
• Savall, H. , Zardet, V. , & Bonnet, M. (2008). Releasing the untapped potential of enterprises through socio-economic management . Geneva, Switzerland: International Labour Organization.
• Saylors, R. , & Trafimow, D. (2020). Why the increasing use of complex causal models is a problem: On the danger sophisticated theoretical narratives pose to truth . Organizational Research Methods , 1094428119893452.
• Schein, E. H. (1987). The clinical perspective in fieldwork . Thousand Oaks, CA: SAGE.
• Schutz, A. (1973a). Common-sense and scientific interpretation of human action. In M. Natanson (Ed.), Collected papers, volume I: The problem of social reality (pp. 3–47). The Hague, The Netherlands: Martinus Nijhoff.
• Schutz, A. (1973b). Concept and theory formation in the social sciences. In M. Natanson (Ed.), Collected papers, volume I: The problem of social reality (pp. 48–66). The Hague, The Netherlands: Martinus Nijhoff.
• Silverman, D. (2014). Interpreting qualitative data (5th ed.). Thousand Oaks, CA: SAGE.
• Smith, A. (2015). What grounded theory is . . . Organizational Research Methods , 18 (4), 578–580.
• Sonpar, K. , & Golden-Biddle, K. (2008). Using content analysis to elaborate adolescent theories of organization. Organizational Research Methods , 11 (4), 795–814.
• Spradley, J. P. (1979). The ethnographic interview . Belmont, CA: Wadsworth.
• Spradley, J. P. (2016). Participant observation . Long Grove, IL: Waveland Press.
• Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin & Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). Thousand Oaks, CA: SAGE.
• Su, N. (2018). Positivist qualitative methods. In C. Cassell , A. L. Cunliffe , & G. Grandy (Eds.), The SAGE handbook of qualitative business and management research methods: History and traditions (pp. 17–32). Thousand Oaks, CA: SAGE.
• Van Maanen, J. (1973). Observations on the making of policemen. Human Organization , 32 (4), 407–418.
• Van Maanen, J. (1981, March). Fieldwork on the beat: An informal introduction to organizational ethnography . Paper presented at the workshop on Innovations in Methodology for Organizational Research, Center for Creative Leadership, Greensboro, NC.
• Van Maanen, J. (1988). Tales of the field: On writing ethnography . Chicago, IL: University of Chicago Press.
• Van Maanen, J. (1998). Different strokes: Qualitative research on the Administrative Science Quarterly from 1956 to 1996. In J. Van Maanen (Ed.), Qualitative studies of organizations (pp. ix–xxxii). Thousand Oaks, CA: SAGE.
• Van Maanen, J. (2010). A song for my supper: More tales of the field. Organizational Research Methods , 13 (2), 240–255.
• Walsh, I. , Holton, J. A. , Bailyn, L. , Fernandez, W. , Levina, N. , & Glaser, B. (2015). What grounded theory is . . . A critically reflective conversation among scholars. Organizational Research Methods , 18 (4), 581–599.
• Watson, T. J. (1994) . In search of management: Culture, chaos, and control in managerial work . London, UK: Routledge.
• Weber, M. (1978). Economy and society: An outline of interpretive sociology . Berkeley: University of California Press.
• Whittle, A. (2018). Ethnomethodology. In C. Cassell , A. L. Cunliffe , & G. Grandy (Eds.), The SAGE handbook of qualitative business and management research methods: History and traditions (pp. 217–232). Thousand Oaks, CA: SAGE.
• Worley, C. G. , Zardet, V. , Bonnet, M. , & Savall, A. (2015). Becoming agile: How the SEAM approach to management builds adaptability . Hoboken, NJ: Jossey-Bass.
• Yan, A. , & Gray, B. (1994). Bargaining power, management control, and performance in United States-China joint ventures: A comparative case study. Academy of Management Journal , 37 (6), 1478–1517.
• Ybema, S. , Yanow, D. , Wels, H. , & Kamsteeg, F. (2009). Organizational ethnography: Studying the complexity of everyday life . Thousand Oaks, CA: SAGE.

1. The fourth logic is retroduction. This refers to the process of building hypothetical models of structures and mechanisms that are assumed to produce empirical phenomena. It is the primary logic used in the critical realist approach to scientific research (Avenier & Thomas, 2015 ; Bhaskar, 1978 ). Retroduction requires the use of inductive or abductive strategies to discover the mechanisms that explain regularities (Blaikie, 2010 , p. 87). There is no evident logic for discovering mechanisms and this requires disciplined scientific thinking aided by creative imagination, intuition, and guesswork (Blaikie, 2010 ). Retroduction is likr deduction in asking “what” questions and differs from abduction because it produces explanations rather than understanding, causes rather than reasons, and hypothetical conceptual mechanisms rather than descriptions of behavioral processes as outcomes. Retroduction is becoming important in the field but has not as yet been extensively used in management and organization studies (for examples of uses, see Avenier & Thomas, 2015 ); hence, we do not address it at length in this article.

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Which are the best business research methods.

12 min read Business research is a well-established way to get an edge in your market. In this article, we’ll cover some of the most valuable business research methods.

Business research is a well-established way to gain an edge in your target market . But less than 40% of US marketers use consumer research to make decisions, according to data from Google. Could the huge range of methodologies and techniques be preventing business research takeup?

In this article, we’ll lay out some of the most popular and valuable business research methods, from general approaches to industry-specific techniques, to help you decide which business research process is the best fit for you and your company.

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What do we mean by business research?

There are two primary areas of business research – understanding the market in which you’re operating, including the target consumers out there who don’t yet buy from you, and understanding your existing customers.

Market research

Market research is an umbrella term covering a wide variety of business research techniques which are used to help a business understand its target customer’s preferences.

This arm of business research often involves techniques like the focus group, where a moderated discussion helps companies understand their target audience, and survey research, including online surveys.

Customer feedback is an important part of any business intelligence process. This might come in the form of direct feedback, where a customer provides their opinion to a business either spontaneously or in response to a survey invitation or feedback form, or through indirect methods like social media listening.

As well as being able to assess customer satisfaction , this allows businesses to discover the unmet needs of their current customers. This kind of business research helps seed new product development, among other improvements.

Qualitative research methods for business

Qualitative business research techniques are all about the ‘why’ of what’s happening in your business. Rather than relying on data and statistics, they use description and human interpretation to investigate situations and events.

Qualitative research can be quite time-consuming and historically it has been harder to automate than quantitative methods, although nowadays tools are available to scale up qualitative data collection.

Even without these tools, qualitative research can be done with smaller sample sizes and still provides rich information that can offer lasting value.

Focus groups

Focus groups are a business research mainstay. They can help companies understand their current customers or target customers in a deep and authentic way using the power of conversation and connection. Focus groups can be valuable for nuanced topics, as well as controversial ones, since you can use the format to bring in multiple points of view from within your target audience.

As a form of qualitative research, focus groups are well-established with plenty of best practice advice and techniques available. They are also relatively familiar to the general public, which means low effort is required to on-board your participants.

At the height of COVID-19, Jittrapirom et al. (2021) used remote focus groups to study perceptions of car-sharing services in Bangkok, Thailand as a way of improving transport planning. They found that the ‘mental models’ of different stakeholder groups were significantly different depending on their understanding of the car-sharing concept. Working with the focus group, the researchers were able to collaboratively build a diagrammatic representation of how car-sharing works, which could then be used to help roll it out as a more sustainable means of transport in developing countries.

Ethnographic research

In ethnographic research, you study people in a naturally occurring setting. Rather than bringing them into your offices or restricting your data collection to a survey, you’re looking at the person and their environment as a whole.

In this sense, ethnographic research is all about understanding the context. You might be observing customers in a store, or interviewing them as they interact with your products and services. Ethnographic research in contexts like shopping malls, online discussion boards or social media can help you understand your target consumer too. Business research of this kind can be especially valuable in consultancy and B2B settings, where one business is looking to gain a deep understanding of another in order to help them improve.

Autmaring et al. (2018) studied SMEs working in B2B to investigate the potential for ethnographic research to improve product development. They found that although SME-level businesses had good access to their customers, their uptake of ethnographic research was low because of a lack of familiarity and concerns about expense. The B2B SMEs studied had low awareness of the benefits of ethnographic research and did not recognize that they were in a strong position to carry it out. This suggests that ethnographic research is an underused technique in business, and one that could offer significant advantages for SMEs especially.

Quantitative research methods for business

Like qualitative research methods, quantitative research methods help you understand your customer and your market better. Quantitative research can also be used to make forecasts and predictions about what might happen in the future. You can develop an in depth knowledge of your customers using existing data, or you can carry out business research to find out more about a specific research question.

Experimental research

In experimental research, you start out with a hypothesis about something happening in your business, and test it by manipulating an independent variable – or multiple independent variables – to find out the effect on a dependent variable. Strictly speaking, experimental research should follow rigorous scientific principles, but in business it’s more likely you will adopt a quasi-experimental approach with less emphasis on method and more on results.

One of the most popular applications of experimental research in business is A/B testing. A/B testing pits two or more variations of something against one another to find out which is more successful. It’s commonly used in marketing management when developing ads or marketing campaigns. In A/B testing, the hypothesis you’re testing is that both or all variations are equally successful. You’ll disprove this if one of the variants gets better results.

One of the benefits of A/B testing is that you can test multiple variants simultaneously by segmenting your audience.

For example, Kornitzer et. al (2020) used A/B testing in a healthcare setting to compare 9 patient messaging options to see which were more effective at preventing hospital appointment no-shows. The options each used a behavioral ‘nudge’ to encourage patients not to skip their appointments. By randomly assigning patients with upcoming appointments into groups, the researchers were able to test all 9 messaging approaches simultaneously. They determined that the most successful messages were those reminding people that skipping their appointment negatively impacted other patients who needed care.

Correlational research

Unlike causal research and experimental research, which look at relationships between a dependent variable and the independent variables acting on it, correlational research doesn’t deal with cause and effect. Instead it looks at phenomena that occur in proportion to one another, without one necessarily having to act on the other.

This kind of business research is helpful because it acts as a starting-point for further research. It can provide promising hypotheses that are worth investing in, as opposed to just guessing which variables might be related causally. Correlational research can also be used to bust myths and remove unhelpful assumptions.

For example, a correlational study by Stanley (2011) explored the relationship between corporate social responsibility and financial performance, using quantitative data to challenge assumptions that socially responsible behavior is negatively associated with financial success in business.

Combined qualitative and quantitative research methods

Mixed mode research.

Mixed mode is a form of business research that combines quantitative and qualitative research methods in a single research project. Qualitative business research can be used in an exploratory way to uncover the questions that should be addressed more deeply. Quantitative research is used to investigate specific research questions arising from the qualitative study. Then, a second round of qualitative research might be used to add depth and nuance to the quantitative verdict, bringing the insights to life.

Survey research

Surveys are a staple among business research methods, as well as being to collect data in other forms of research such as academic studies. A survey can generate both qualitative and quantitative data, depending on the question formats used. It’s a familiar format for most people, and can be taken in a variety of formats from online surveys to telephone surveys. This makes it a very inclusive method, giving you maximum access to your target audience. Survey business research can be used for everything from customer satisfaction to concept testing.

Today’s technology means that surveys can be integrated right into the experiences they’re measuring. This helps offset some of the weaknesses of the survey method, such as participants misremembering or generalizing their experiences, or forgetting details because of the time lag between the events being studied and the participant taking the survey.

For example, Virgin Media used on page surveys to gather user feedback from website customers who had abandoned their carts. These in-the-moment insights helped them not only to understand the customer pain points , but to put them right quickly and efficiently.

Case study research

In case study research, the emphasis is on depth rather than breadth. Researchers explore a particular phenomenon in situ, looking at how a group or organization behaved in a specific time and place, and what happened as a result. It is both a quantitative research method and a qualitative research method, as the research involves both types of data.

Case study research can be very helpful in business, as it offers an opportunity to learn how other companies approached a challenge you might be facing, and to learn from the solutions they devised and the obstacles they faced. However, this research method does require care and attention on the part of the researcher to make sure the research involves relevant cases. They must fully understand the similarities and differences between their own business goals and the situation being explored, in order to avoid incorrectly assuming equivalence and coming to faulty conclusions.

Case study research really comes into its own in emerging areas where best practice approaches are not yet firmly established.

For example, Urbaniti et al. (2020) conducted case study research on circular economy practices in multiple European manufacturing businesses. They noted different managers’ peculiar and innovative approaches to achieving the circular economy business model, taking into account environmental factors like legislation which helped shape the approaches.

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Business Research: Types, Methods, Examples

• Updated on  
• Jan 29, 2024

Ever wondered what it takes to build a flourishing business ? Aiming to provide maximum sales and profit, business research helps you to gather comprehensive information about your business and accordingly make relevant changes if required. So, in this process of being successful, we gather all types of data to better define our strategies and understand what products or services customers want. And in case, you’re planning to expand your business, research can help you determine your odds of positive results. In this blog, we’ll help you understand the basics of research and analysis .

“Whoever gets closer to the customer, wins.” – Bernadette Jiwa

This Blog Includes:

What is business research, business research example, importance of business research, types & methods, focus groups , case study research , ethnographic research, survey , correlation research , experimental research , advantages and disadvantages of business research, scope of business research, role of business research, business research books, business research report, top 10 tools for business research, business research partners, top 10 business research topics, career prospects , [bonus] best mba colleges in the world.

Business Research can be simply defined as a process of gathering comprehensive data and information on all the areas of business and incorporating this information for sales and profit maximization. If you are wondering what is Business Research, it is a systematic management activity helping companies to determine which product will be most profitable for companies to produce. Also, there are multiple steps in conducting research, with each thoroughly reviewed to ensure that the best decision is made for the company as a whole.

Also Read: Scope of MBA in International Business

Let’s say there’s an automobile company that is planning to launch a car that runs on CNG. To promote cleaner fuel, the company will be involved in developing different plans and strategies to identify the demand for the car they intend to launch. Other than this, the company will also look for competitors, and the target audience, keeping in mind the distribution of CNG in India. Hence the research is conducted on various ideas to formulate a sustainable and more efficient design. 

When it comes to the question of why Business Research is important, it has an essential role to play in varied areas of business. Here are some of the reasons describing the importance of Business Research:

• It helps businesses gain better insights into their target customer’s preferences, buying patterns, pain points, as well as demographics.
• Business Research also provides businesses with a detailed overview of their target markets, what’s in trend, as well as market demand.
• By studying consumers’ buying patterns and preferences as well as market trends and demands with the help of business research, businesses can effectively and efficiently curate the best possible plans and strategies accordingly.
• The importance of business research also lies in highlighting the areas where unnecessary costs can be minimized and those areas in a business which need more attention and can bring in more customers and hence boost profits.
• Businesses can constantly innovate as per their customers’ preferences and interests and keep their attention on the brand.
• Business Research also plays the role of a catalyst as it helps businesses thrive in their markets by capturing all the available opportunities and also meeting the needs and preferences of their customers.

Also Read: Business Analyst vs Data Analyst

Business research plays an important role in the business intelligence process. This is usually conducted to determine if a company can succeed in a new region through competitive analyses and a better marketing approach. Due to this, this broad field has been distinguished into two types namely, Qualitative Research and Quantitative Research Method.

Here are the most important types of Business Research :

Qualitative Research Methods 

It involves putting open-ended questions to the audience through different channels of communication to understand why researchers think in a particular manner. Stress is laid on understanding the intent, attitude, and beliefs to figure out the behaviour and response of the customers. Moreover, the goal of Qualitative Business Research is to get in-depth knowledge about the subjects of the research. Moreover, qualitative research enables us to put the perspective of the consumer in front of the researcher so that we can understand and see the alignment of the ideas between the market and the business. 

The data collected in this type of business research is by the following methods:  

• Interviews 
• Case Study 
• Ethnographic Research 
• Website Visitor Profiling 
• Content Analysis 

Also Read: Study MBA in Music Business at Berklee College of Music!

Let us take a detailed look at some of the ways-

Interviews and surveys are similar. The only difference lies in the fact that the responder can put a question in an interview whilst it is not possible during a survey. Through interviews, it is easier to understand the detailed perspective of the person concerning the subject of research. A mobile brand researched to understand why certain colours are preferred by male and female customers. The research revealed that since red is assumed to be a feminine colour, it is more preferred by females than males. 

Focus groups are a type of business research that involves only a set of individuals. Each selected individual represents a particular category of the target market. The major difference between interviews and focus groups is the number of people that it involves. To launch a new product for a particular group of society, focus groups prove to be the best way to understand the needs of the local audience. 

For example, Tesla decides to launch their latest car model in India. The company, therefore, will require feedback from the Indian audience only.

Did you know? Amazon, the internet giant changed its payment strategy to enter the Indian market. Since the Indian economy was not entirely ready for online modes of payment, amazon introduced a new payment method and came up with ‘ cash on delivery ’ to gain consumers’ trust.

One of the most effective ways for business research is conducting case studies. With the motive to understand customer satisfaction, challenges that usually the customers face while using the product and hence, providing them with the right solution can be achieved by analysing data secured through data secured by case studies. Case study researchers are conducted in many fields of business that ultimately aid organisations in improving their products or services. 

Ethnographic Research refers to understanding people as a whole. One must be able to grok their consumers or target audience which will help identify patterns, flaws, etc. Ethnography is a branch of anthropology that is the study of what elements or features make us humans. How did people live? What aspect made us so dependent on smartphones and technology? Why would people buy one product over the other? It refers to asking questions about lifestyle, communities, etc., and trying to gain insight into consumer behaviour and buying patterns.

For example, consider a random product. Are people looking for that product? Do they need it? Is it a necessity or a luxury? Which class of people are most likely to buy it? People often cannot comprehend what they are looking for. Gaining different perceptions can help us tailor our products accordingly to the consumers. Who would have thought that the majority of humans will need face masks for survival?

Also Read: How to Become a Research Analyst?

Quantitative Research Methods 

With the employment of mathematical, statistical and computational techniques, quantitative research is carried out to deal with numbers. This systematical empirical investigation starts with the acquisition of the data and then moves on to analyzing it with the help of different tools. The goal is to identify clientele and then meet the targets of the audience. As the method of business research employs a questionnaire to determine the audience’s response, the questions are built around the idea that the audience knows about the product or the services that the firm offers. Some of the key questions answered in quantitative research methods include, who is connected with your network, how they qualify for the ‘product’ or how regularly they visit your website.

The data is collected based on the following research:

• Correlational
• Online 
• Casual Comparative 
• Experimental 

It is the most common method under quantitative research via which a huge amount of data can be collected concerning a product or service. A common set of questions are asked to the people and they are asked to provide their inputs. To understand the nature of the market in-depth, this method is massively used by leading organisations all across the globe. Analysing data recorded through service helps organisations make suitable decisions.

Under this research, usually two entities are put together to examine the impact they create on each other. As suggested by the name it is the best process to understand patterns, relationships and trends. the data grasped through correlation research is generally combined with other tools as one cannot achieve a firm conclusion using this type of business research.  

Experimental research is purely based on proving a particular theory that is pre-assumed. True experimental research companies can understand varied behavioural traits of the customers that further assist them in generating more revenue. Exposing a set of audience to common parameters, their behaviour is recorded and hence analysed. This can be understood as the main basis of the experimental research. 

Also Read: Scope of Operation Research

There are certain pros and cons of business research that you must know about. Here are the advantages and disadvantages of Business Research.

Advantages of Business Research

• Business Research plays the role of a catalyst in identifying potential threats, issues as well as opportunities .
• It provides a detailed analysis of customers and the target audience , thus helping in building better relationships with one’s audience and capturing the areas which we might be missing out on.
• It also anticipates future problems thus the enterprise is able to tackle those uncertainties and prepare for them beforehand.
• It keeps a continuous track of competition in the market and gives businesses the scope to come up with better strategies to tackle their competitors.
• Business Research also conducts a thorough cost analysis thus helping the company efficiently manage resources and allocate them in an optimal manner.
• It keeps you updated with the latest trends and competitor analysis .

Disadvantages of Business Research

• Business Research can be expensive and time-consuming .
• It also has the danger of being assumptive and imprecise at times , because the focus groups might be small or can be highly based on assumptions.
• The market is ever-changing and ever-evolving and capturing the right trends or anticipating them can constitute a complicated process for business research.

Also Read: Types of Research Design

The process of business research can be as comprehensive and as detailed as a business wants it to be. Generally, a company takes up research with a certain aim or hypothesis in order to figure out the issues, opportunities and trends and how they can be leveraged in the best way.

Here is the step-by-step process of Business Research:

• Identifying the Opportunity or Problem – To begin with the research, we first need to know what is the problem or the opportunity we would be leveraging on. It can be a popular trend or a common problem that a business is facing and can potentially become the headstart for the research process. Once you know the problem or the opportunity, go ahead with giving an understandable statement of what it’s about, what the hypothesis of the research will be as well as its objectives.
• Decide and Plan the Research Design – The next step in the business research process to find the right research design which suits the objectives and overall plan of the research. The most popular research designs are Quantitative and Qualitative Research.
• Determining the Research Method – The research design is closely connected to the research method since both qualitative and quantitative research designs have different methods for data collection, analysis, amongst others. So, once you have put a finger on what the right research design will be, go ahead with finding the right research method as per the plan, types of data collection, objective, costs involved, and other determining factors.
• Collect Data – Utilizing the research method and design, the next step in the business research process is to collect data and assimilate it.
• Data Analysis and Evaluation – After assimilating the data required, the data analysis will take place to gather all the observations and findings.
• Communicate Results – The presentation of the business research report is the concluding step of this procedure after which the higher management works upon the best techniques and strategies to leverage the opportunity or tackle the issue.

Also Read: MBA in Business Analytics

The scope of Business Research is multifarious and reaches out to many specialisations and areas. Let’s take a look the scope of business research across various specialisations:

• Marketing Management When it comes to business research, becomes an important part of marketing management that analyses consumer behaviour, target audiences, competition, price policy, promotional plans and much more.
• Financial Management It also plays an essential role in budgeting, financial planning, cost allocation, capital raising, tackling fluctuations with international currency as well as taking finance-related decisions.
• Production Management Production Management also includes business research as it helps in product development, planning out for a newer one, finalizing the right technologies for production, and so on.
• Materials Management Business Research is an important aspect of checking the best materials and carrying out its production, supply chain management , logistics , as well as shortlisting negotiation strategies.

There is an incremental role of business research as its importance is across every aspect of the business. Let’s take a look at the role of business research in an enterprise:

• The most primary role of business research is that it helps across every decision in the business, from product innovation to marketing and promotional planning.
• Business Research also helps in forecasting a business, whether in terms of competition or any other types of problems it will be facing.
• Another key area where this plays a bigger role is ensuring consumer satisfaction as through research, we can carry out research and highlight areas where we can efficiently serve our target audience.
• Business research also helps in implementing cost-effectiveness in a business as it can assist in cutting costs wherever needed and investing more in those areas, where profit is coming from.

Want to understand and learn more about business research? Here are some of the books that will make you a pro in this field. Check out the list of business research books:

Also Read: Is It Possible to Study MBA in Europe Without GMAT?

The purpose of a report is to inform the other members, junior and subordinates of the team to provide information on the specific topic. There is a specific format of a business report which makes it look more professional and presentable. There should be a title with the date and nature. The second section includes the introduction, body, and then conclusion. Reports help to identify the issues and helps in resolving them at earlier stages. It can include graphs, surveys, interviews, flow, and piecharts also.

Are you wondering why is there a need to do business research? Business is not stable and it is vital to stay up to date with all the data and developments. It is also important to make business-related decisions, and keep track of competitors, customer feedback, and market changes. The basic objective of business research is to identify the issues and evaluate a plan to resolve them for better managerial functioning.

Now that you are familiar with the objective, importance, and advantages the next important step is to know how to conduct research. There are numerous tools available for free while for some advanced tools there is a membership. Check out the list of top 10 tools:

• Google Keyword Tools
• Google Analytics
• Google Trends

The one thing constant in a business is market changes. A new trend or change comes every time you blink an eye. To keep track of everything externally and internally a research partner comes helpful. There are a few things to keep in mind that will help you in choosing the right business partner. The first thing to keep in mind is that the person should have relevant work experience and expertise in that particular field. An experienced partner can help businesses reach new heights. Look for a partner that can provide well-curated solutions and not the generic ideas that every enterprise follows. Last but not least is that your business research partner should have knowledge of the latest tools and techniques.

Also Read: MBA in Sustainable Development: Courses & Universities

Is your big presentation coming up or your report is due on Monday but you still haven’t finalized your business research topic? Here are some of the trendiest research topics for you:

• How advertisements influence consumer behaviour?
• Does incentive motivation increase employee productivity?
• How to handle crises in the business?
• How to create a work-life balance in the organization?
• What are the things a small business owner has to face?
• How to expand the company globally?
• How is digital marketing helping every business type?
• How to maintain the quality and quantity of products?
• What are the struggles entrepreneurs of a start-up face?
• How to create a budget and maintain company finances?

In order to build a career in Research , you can simply grab a degree in the field of Management , Business or Administration. So, students with an understanding of the core concepts of business and an inclination for research can consider it as a go-to option. Other suitable programs can be Master in Management , MBA Business Analytics , and MBA Data Analytics , to name a few.

To know more, check out Qualitative Research Methods !

It can simply mean researching every area of a business and using the provided information and data to ensure profit maximization.

There are different types of business research such as interviews, surveys, focus groups, correlational research, ethnographic research, case study research, and quantitative research methods, amongst others.

It is essentially important for various aspects of a business such as profit maximization, cost-cutting, financial management , personnel management, consumer behaviour, etc.

The process of research depends upon the type of research design you are opting for. To start with, we first need to determine the aim or objective of the research, then plan out the whole process which includes the types of methods we will be using, then the actual research that takes place followed by the data found that helps in understanding the key observations and how they can be implemented to actualize research hypothesis.

If you’re thinking to start a product line in your existing business or planning a startup, business research is a fundamental process that helps you to navigate the opportunities and obstacles in the marketplace. Knowing your strengths and weaknesses can help you come up with advanced and powerful research techniques that will make it easier to manage. Are you planning to take your higher education abroad? Then, you can quickly book a counselling session with the experts at Leverage Edu and we can help you build the right platform for you to grow in the corporate world.

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Home » Research Methods – Types, Examples and Guide

Research Methods – Types, Examples and Guide

Table of Contents

Research Methods

Definition:

Research Methods refer to the techniques, procedures, and processes used by researchers to collect , analyze, and interpret data in order to answer research questions or test hypotheses. The methods used in research can vary depending on the research questions, the type of data that is being collected, and the research design.

Types of Research Methods

Types of Research Methods are as follows:

Qualitative research Method

Qualitative research methods are used to collect and analyze non-numerical data. This type of research is useful when the objective is to explore the meaning of phenomena, understand the experiences of individuals, or gain insights into complex social processes. Qualitative research methods include interviews, focus groups, ethnography, and content analysis.

Quantitative Research Method

Quantitative research methods are used to collect and analyze numerical data. This type of research is useful when the objective is to test a hypothesis, determine cause-and-effect relationships, and measure the prevalence of certain phenomena. Quantitative research methods include surveys, experiments, and secondary data analysis.

Mixed Method Research

Mixed Method Research refers to the combination of both qualitative and quantitative research methods in a single study. This approach aims to overcome the limitations of each individual method and to provide a more comprehensive understanding of the research topic. This approach allows researchers to gather both quantitative data, which is often used to test hypotheses and make generalizations about a population, and qualitative data, which provides a more in-depth understanding of the experiences and perspectives of individuals.

Key Differences Between Research Methods

The following Table shows the key differences between Quantitative, Qualitative and Mixed Research Methods

Examples of Research Methods

Examples of Research Methods are as follows:

Qualitative Research Example:

A researcher wants to study the experience of cancer patients during their treatment. They conduct in-depth interviews with patients to gather data on their emotional state, coping mechanisms, and support systems.

Quantitative Research Example:

A company wants to determine the effectiveness of a new advertisement campaign. They survey a large group of people, asking them to rate their awareness of the product and their likelihood of purchasing it.

Mixed Research Example:

A university wants to evaluate the effectiveness of a new teaching method in improving student performance. They collect both quantitative data (such as test scores) and qualitative data (such as feedback from students and teachers) to get a complete picture of the impact of the new method.

Applications of Research Methods

Research methods are used in various fields to investigate, analyze, and answer research questions. Here are some examples of how research methods are applied in different fields:

• Psychology : Research methods are widely used in psychology to study human behavior, emotions, and mental processes. For example, researchers may use experiments, surveys, and observational studies to understand how people behave in different situations, how they respond to different stimuli, and how their brains process information.
• Sociology : Sociologists use research methods to study social phenomena, such as social inequality, social change, and social relationships. Researchers may use surveys, interviews, and observational studies to collect data on social attitudes, beliefs, and behaviors.
• Medicine : Research methods are essential in medical research to study diseases, test new treatments, and evaluate their effectiveness. Researchers may use clinical trials, case studies, and laboratory experiments to collect data on the efficacy and safety of different medical treatments.
• Education : Research methods are used in education to understand how students learn, how teachers teach, and how educational policies affect student outcomes. Researchers may use surveys, experiments, and observational studies to collect data on student performance, teacher effectiveness, and educational programs.
• Business : Research methods are used in business to understand consumer behavior, market trends, and business strategies. Researchers may use surveys, focus groups, and observational studies to collect data on consumer preferences, market trends, and industry competition.
• Environmental science : Research methods are used in environmental science to study the natural world and its ecosystems. Researchers may use field studies, laboratory experiments, and observational studies to collect data on environmental factors, such as air and water quality, and the impact of human activities on the environment.
• Political science : Research methods are used in political science to study political systems, institutions, and behavior. Researchers may use surveys, experiments, and observational studies to collect data on political attitudes, voting behavior, and the impact of policies on society.

Purpose of Research Methods

Research methods serve several purposes, including:

• Identify research problems: Research methods are used to identify research problems or questions that need to be addressed through empirical investigation.
• Develop hypotheses: Research methods help researchers develop hypotheses, which are tentative explanations for the observed phenomenon or relationship.
• Collect data: Research methods enable researchers to collect data in a systematic and objective way, which is necessary to test hypotheses and draw meaningful conclusions.
• Analyze data: Research methods provide tools and techniques for analyzing data, such as statistical analysis, content analysis, and discourse analysis.
• Test hypotheses: Research methods allow researchers to test hypotheses by examining the relationships between variables in a systematic and controlled manner.
• Draw conclusions : Research methods facilitate the drawing of conclusions based on empirical evidence and help researchers make generalizations about a population based on their sample data.
• Enhance understanding: Research methods contribute to the development of knowledge and enhance our understanding of various phenomena and relationships, which can inform policy, practice, and theory.

When to Use Research Methods

Research methods are used when you need to gather information or data to answer a question or to gain insights into a particular phenomenon.

Here are some situations when research methods may be appropriate:

• To investigate a problem : Research methods can be used to investigate a problem or a research question in a particular field. This can help in identifying the root cause of the problem and developing solutions.
• To gather data: Research methods can be used to collect data on a particular subject. This can be done through surveys, interviews, observations, experiments, and more.
• To evaluate programs : Research methods can be used to evaluate the effectiveness of a program, intervention, or policy. This can help in determining whether the program is meeting its goals and objectives.
• To explore new areas : Research methods can be used to explore new areas of inquiry or to test new hypotheses. This can help in advancing knowledge in a particular field.
• To make informed decisions : Research methods can be used to gather information and data to support informed decision-making. This can be useful in various fields such as healthcare, business, and education.

Advantages of Research Methods

Research methods provide several advantages, including:

• Objectivity : Research methods enable researchers to gather data in a systematic and objective manner, minimizing personal biases and subjectivity. This leads to more reliable and valid results.
• Replicability : A key advantage of research methods is that they allow for replication of studies by other researchers. This helps to confirm the validity of the findings and ensures that the results are not specific to the particular research team.
• Generalizability : Research methods enable researchers to gather data from a representative sample of the population, allowing for generalizability of the findings to a larger population. This increases the external validity of the research.
• Precision : Research methods enable researchers to gather data using standardized procedures, ensuring that the data is accurate and precise. This allows researchers to make accurate predictions and draw meaningful conclusions.
• Efficiency : Research methods enable researchers to gather data efficiently, saving time and resources. This is especially important when studying large populations or complex phenomena.
• Innovation : Research methods enable researchers to develop new techniques and tools for data collection and analysis, leading to innovation and advancement in the field.

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Toward a framework for selecting indicators of measuring sustainability and circular economy in the agri-food sector: a systematic literature review

• LIFE CYCLE SUSTAINABILITY ASSESSMENT
• Published: 02 March 2022

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• Cecilia Silvestri   ORCID: orcid.org/0000-0003-2528-601X 1 ,
• Luca Silvestri   ORCID: orcid.org/0000-0002-6754-899X 2 ,
• Michela Piccarozzi   ORCID: orcid.org/0000-0001-9717-9462 1 &
• Alessandro Ruggieri 1  

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A Correction to this article was published on 24 March 2022

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The implementation of sustainability and circular economy (CE) models in agri-food production can promote resource efficiency, reduce environmental burdens, and ensure improved and socially responsible systems. In this context, indicators for the measurement of sustainability play a crucial role. Indicators can measure CE strategies aimed to preserve functions, products, components, materials, or embodied energy. Although there is broad literature describing sustainability and CE indicators, no study offers such a comprehensive framework of indicators for measuring sustainability and CE in the agri-food sector.

Starting from this central research gap, a systematic literature review has been developed to measure the sustainability in the agri-food sector and, based on these findings, to understand how indicators are used and for which specific purposes.

The analysis of the results allowed us to classify the sample of articles in three main clusters (“Assessment-LCA,” “Best practice,” and “Decision-making”) and has shown increasing attention to the three pillars of sustainability (triple bottom line). In this context, an integrated approach of indicators (environmental, social, and economic) offers the best solution to ensure an easier transition to sustainability.

Conclusions

The sample analysis facilitated the identification of new categories of impact that deserve attention, such as the cooperation among stakeholders in the supply chain and eco-innovation.

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Source: Authors’ elaboration. Notes: The graph shows the temporal distribution of the articles under analysis

Source: Authors’ elaborations. Notes: The graph shows the time distribution of articles from the three major journals

Source: Authors’ elaboration. Notes: The graph shows the composition of the sample according to the three clusters identified by the analysis

Source: Authors’ elaboration. Notes: The graph shows the distribution of articles over time by cluster

Source: Authors’ elaboration. Notes: The graph shows the network visualization

Source: Authors’ elaboration. Notes: The graph shows the overlay visualization

Source: Authors’ elaboration. Notes: The graph shows the classification of articles by scientific field

Source: Authors’ elaboration. Notes: Article classification based on their cluster to which they belong and scientific field

Source: Authors’ elaboration

Source: Authors’ elaboration. Notes: The graph shows the distribution of items over time based on TBL

Source: Authors’ elaboration. Notes: The graph shows the Pareto diagram highlighting the most used indicators in literature for measuring sustainability in the agri-food sector

Source: Authors’ elaboration. Notes: The graph shows the distribution over time of articles divided into conceptual and empirical

Source: Authors’ elaboration. Notes: The graph shows the classification of articles, divided into conceptual and empirical, in-depth analysis

Source: Authors’ elaboration. Notes: The graph shows the geographical distribution of the authors

Source: Authors’ elaboration. Notes: The graph shows the distribution of authors according to the continent from which they originate

Source: Authors’ elaboration. Notes: The graph shows the time distribution of publication of authors according to the continent from which they originate

Source: Authors’ elaboration. Notes: Sustainability measurement indicators and impact categories of LCA, S-LCA, and LCC tools should be integrated in order to provide stakeholders with best practices as guidelines and tools to support both decision-making and measurement, according to the circular economy approach

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A Correction to this paper has been published: https://doi.org/10.1007/s11367-022-02038-9

Acero AP, Rodriguez C, Ciroth A (2017) LCIA methods: impact assessment methods in life cycle assessment and their impact categories. Version 1.5.6. Green Delta 1–23

Accorsi R, Versari L, Manzini R (2015) Glass vs. plastic: Life cycle assessment of extra-virgin olive oil bottles across global supply chains. Sustain 7:2818–2840. https://doi.org/10.3390/su7032818

Adjei-Bamfo P, Maloreh-Nyamekye T, Ahenkan A (2019) The role of e-government in sustainable public procurement in developing countries: a systematic literature review. Resour Conserv Recycl 142:189–203. https://doi.org/10.1016/j.resconrec.2018.12.001

Article   Google Scholar  

Aivazidou E, Tsolakis N, Vlachos D, Iakovou E (2015) Water footprint management policies for agrifood supply chains: a critical taxonomy and a system dynamics modelling approach. Chem Eng Trans 43:115–120. https://doi.org/10.3303/CET1543020

Alhaddi H (2015) Triple bottom line and sustainability: a literature review. Bus Manag Stud 1:6–10

Allaoui H, Guo Y, Sarkis J (2019) Decision support for collaboration planning in sustainable supply chains. J Clean Prod 229:761–774. https://doi.org/10.1016/j.jclepro.2019.04.367

Alshqaqeeq F, Amin Esmaeili M, Overcash M, Twomey J (2020) Quantifying hospital services by carbon footprint: a systematic literature review of patient care alternatives. Resour Conserv Recycl 154:104560. https://doi.org/10.1016/j.resconrec.2019.104560

Anwar F, Chaudhry FN, Nazeer S et al (2016) Causes of ozone layer depletion and its effects on human: review. Atmos Clim Sci 06:129–134. https://doi.org/10.4236/acs.2016.61011

Aquilani B, Silvestri C, Ruggieri A (2016). A Systematic Literature Review on Total Quality Management Critical Success Factors and the Identification of New Avenues of Research. https://doi.org/10.1108/TQM-01-2016-0003

Aramyan L, Hoste R, Van Den Broek W et al (2011) Towards sustainable food production: a scenario study of the European pork sector. J Chain Netw Sci 11:177–189. https://doi.org/10.3920/JCNS2011.Qpork8

Arfini F, Antonioli F, Cozzi E et al (2019) Sustainability, innovation and rural development: the case of Parmigiano-Reggiano PDO. Sustain 11:1–17. https://doi.org/10.3390/su11184978

Assembly UG (2005) Resolution adopted by the general assembly. New York, NY

Avilés-Palacios C, Rodríguez-Olalla A (2021) The sustainability of waste management models in circular economies. Sustain 13:1–19. https://doi.org/10.3390/su13137105

Azevedo SG, Silva ME, Matias JCO, Dias GP (2018) The influence of collaboration initiatives on the sustainability of the cashew supply chain. Sustain 10:1–29. https://doi.org/10.3390/su10062075

Bajaj S, Garg R, Sethi M (2016) Total quality management: a critical literature review using Pareto analysis. Int J Product Perform Manag 67:128–154

Banasik A, Kanellopoulos A, Bloemhof-Ruwaard JM, Claassen GDH (2019) Accounting for uncertainty in eco-efficient agri-food supply chains: a case study for mushroom production planning. J Clean Prod 216:249–256. https://doi.org/10.1016/j.jclepro.2019.01.153

Barth H, Ulvenblad PO, Ulvenblad P (2017) Towards a conceptual framework of sustainable business model innovation in the agri-food sector: a systematic literature review. Sustain 9. https://doi.org/10.3390/su9091620

Bastas A, Liyanage K (2018) Sustainable supply chain quality management: a systematic review

Beckerman W (1992) Economic growth and the environment: whose growth? Whose environment? World Dev 20:481–496. https://doi.org/10.1016/0305-750X(92)90038-W

Belaud JP, Prioux N, Vialle C, Sablayrolles C (2019) Big data for agri-food 4.0: application to sustainability management for by-products supply chain. Comput Ind 111:41–50. https://doi.org/10.1016/j.compind.2019.06.006

Bele B, Norderhaug A, Sickel H (2018) Localized agri-food systems and biodiversity. Agric 8. https://doi.org/10.3390/agriculture8020022

Bilali H El, Calabrese G, Iannetta M et al (2020) Environmental sustainability of typical agro-food products: a scientifically sound and user friendly approach. New Medit 19:69–83. https://doi.org/10.30682/nm2002e

Blanc S, Massaglia S, Brun F et al (2019) Use of bio-based plastics in the fruit supply chain: an integrated approach to assess environmental, economic, and social sustainability. Sustain 11. https://doi.org/10.3390/su11092475

Bloemhof JM, van der Vorst JGAJ, Bastl M, Allaoui H (2015) Sustainability assessment of food chain logistics. Int J Logist Res Appl 18:101–117. https://doi.org/10.1080/13675567.2015.1015508

Bonisoli L, Galdeano-Gómez E, Piedra-Muñoz L (2018) Deconstructing criteria and assessment tools to build agri-sustainability indicators and support farmers’ decision-making process. J Clean Prod 182:1080–1094. https://doi.org/10.1016/j.jclepro.2018.02.055

Bonisoli L, Galdeano-Gómez E, Piedra-Muñoz L, Pérez-Mesa JC (2019) Benchmarking agri-food sustainability certifications: evidences from applying SAFA in the Ecuadorian banana agri-system. J Clean Prod 236. https://doi.org/10.1016/j.jclepro.2019.07.054

Bornmann L, Haunschild R, Hug SE (2018) Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis. Scientometrics 114:427–437. https://doi.org/10.1007/s11192-017-2591-8

Boulding KE (1966) The economics of the coming spaceship earth. New York, 1-17

Bracquené E, Dewulf W, Duflou JR (2020) Measuring the performance of more circular complex product supply chains. Resour Conserv Recycl 154:104608. https://doi.org/10.1016/j.resconrec.2019.104608

Burck J, Hagen U, Bals C et al (2021) Climate Change Performance Index

Calisto Friant M, Vermeulen WJV, Salomone R (2020) A typology of circular economy discourses: navigating the diverse visions of a contested paradigm. Resour Conserv Recycl 161:104917. https://doi.org/10.1016/j.resconrec.2020.104917

Campbell BM, Beare DJ, Bennett EM et al (2017) Agriculture production as a major driver of the earth system exceeding planetary boundaries. Ecol Soc 22. https://doi.org/10.5751/ES-09595-220408

Capitanio F, Coppola A, Pascucci S (2010) Product and process innovation in the Italian food industry. Agribusiness 26:503–518. https://doi.org/10.1002/agr.20239

Caputo P, Zagarella F, Cusenza MA et al (2020) Energy-environmental assessment of the UIA-OpenAgri case study as urban regeneration project through agriculture. Sci Total Environ 729:138819. https://doi.org/10.1016/j.scitotenv.2020.138819

Article   CAS   Google Scholar  

Chabowski BR, Mena JA, Gonzalez-Padron TL (2011) The structure of sustainability research in marketing, 1958–2008: a basis for future research opportunities. J Acad Mark Sci 39:55–70. https://doi.org/10.1007/s11747-010-0212-7

Chadegani AA, Salehi H, Yunus M et al (2017) A comparison between two main academic literature collections : Web of Science and Scopus databases. Asian Soc Sci 9:18–26. https://doi.org/10.5539/ass.v9n5p18

Chams N, Guesmi B, Gil JM (2020) Beyond scientific contribution: assessment of the societal impact of research and innovation to build a sustainable agri-food sector. J Environ Manage 264. https://doi.org/10.1016/j.jenvman.2020.110455

Chandrakumar C, McLaren SJ, Jayamaha NP, Ramilan T (2019) Absolute sustainability-based life cycle assessment (ASLCA): a benchmarking approach to operate agri-food systems within the 2°C global carbon budget. J Ind Ecol 23:906–917. https://doi.org/10.1111/jiec.12830

Chaparro-Africano AM (2019) Toward generating sustainability indicators for agroecological markets. Agroecol Sustain Food Syst 43:40–66. https://doi.org/10.1080/21683565.2019.1566192

Colicchia C, Strozzi F (2012) Supply chain risk management: a new methodology for a systematic literature review

Conca L, Manta F, Morrone D, Toma P (2021) The impact of direct environmental, social, and governance reporting: empirical evidence in European-listed companies in the agri-food sector. Bus Strateg Environ 30:1080–1093. https://doi.org/10.1002/bse.2672

Coppola A, Ianuario S, Romano S, Viccaro M (2020) Corporate social responsibility in agri-food firms: the relationship between CSR actions and firm’s performance. AIMS Environ Sci 7:542–558. https://doi.org/10.3934/environsci.2020034

Corona B, Shen L, Reike D et al (2019) Towards sustainable development through the circular economy—a review and critical assessment on current circularity metrics. Resour Conserv Recycl 151:104498. https://doi.org/10.1016/j.resconrec.2019.104498

Correia MS (2019) Sustainability: An overview of the triple bottom line and sustainability implementation. Int J Strateg Eng 2:29–38.  https://doi.org/10.4018/IJoSE.2019010103

Coteur I, Marchand F, Debruyne L, Lauwers L (2019) Structuring the myriad of sustainability assessments in agri-food systems: a case in Flanders. J Clean Prod 209:472–480. https://doi.org/10.1016/j.jclepro.2018.10.066

CREA (2020) L’agricoltura italiana conta 2019

Crenna E, Sala S, Polce C, Collina E (2017) Pollinators in life cycle assessment: towards a framework for impact assessment. J Clean Prod 140:525–536. https://doi.org/10.1016/j.jclepro.2016.02.058

D’Eusanio M, Serreli M, Zamagni A, Petti L (2018) Assessment of social dimension of a jar of honey: a methodological outline. J Clean Prod 199:503–517. https://doi.org/10.1016/j.jclepro.2018.07.157

Dania WAP, Xing K, Amer Y (2018) Collaboration behavioural factors for sustainable agri-food supply chains: a systematic review. J Clean Prod 186:851–864

De Pascale A, Arbolino R, Szopik-Depczyńska K et al (2021) A systematic review for measuring circular economy: the 61 indicators. J Clean Prod 281. https://doi.org/10.1016/j.jclepro.2020.124942

De Schoenmakere M, Gillabel J (2017) Circular by design: products in the circular economy

Del Borghi A, Gallo M, Strazza C, Del Borghi M (2014) An evaluation of environmental sustainability in the food industry through life cycle assessment: the case study of tomato products supply chain. J Clean Prod 78:121–130. https://doi.org/10.1016/j.jclepro.2014.04.083

Del Borghi A, Strazza C, Magrassi F et al (2018) Life cycle assessment for eco-design of product–package systems in the food industry—the case of legumes. Sustain Prod Consum 13:24–36. https://doi.org/10.1016/j.spc.2017.11.001

Denyer D, Tranfield D (2009) Producing a systematic review. In: Buchanan B (ed) The sage handbook of organization research methods. Sage Publications Ltd, Cornwall, pp 671–689

Google Scholar  

Dietz T, Grabs J, Chong AE (2019) Mainstreamed voluntary sustainability standards and their effectiveness: evidence from the Honduran coffee sector. Regul Gov. https://doi.org/10.1111/rego.12239

Dixon-Woods M (2011) Using framework-based synthesis for conducting reviews of qualitative studies. BMC Med 9:9–10. https://doi.org/10.1186/1741-7015-9-39

do Canto NR, Bossle MB, Marques L, Dutra M, (2020) Supply chain collaboration for sustainability: a qualitative investigation of food supply chains in Brazil. Manag Environ Qual an Int J. https://doi.org/10.1108/MEQ-12-2019-0275

dos Santos RR, Guarnieri P (2020) Social gains for artisanal agroindustrial producers induced by cooperation and collaboration in agri-food supply chain. Soc Responsib J. https://doi.org/10.1108/SRJ-09-2019-0323

Doukidis GI, Matopoulos A, Vlachopoulou M, Manthou V, Manos B (2007) A conceptual framework for supply chain collaboration: empirical evidence from the agri‐food industry. Supply Chain Manag an Int Journal 12:177–186. https://doi.org/10.1108/13598540710742491

Durach CF, Kembro J, Wieland A (2017) A new paradigm for systematic literature reviews in supply chain management. J Supply Chain Manag 53:67–85. https://doi.org/10.1111/jscm.12145

Durán-Sánchez A, Álvarez-García J, Río-Rama D, De la Cruz M (2018) Sustainable water resources management: a bibliometric overview. Water 10:1–19. https://doi.org/10.3390/w10091191

Duru M, Therond O (2015) Livestock system sustainability and resilience in intensive production zones: which form of ecological modernization? Reg Environ Chang 15:1651–1665. https://doi.org/10.1007/s10113-014-0722-9

Edison Fondazione (2019) Le eccellenze agricole italiane. I primati europei e mondiali dell’Italia nei prodotti vegetali. Milan (IT)

Ehrenfeld JR (2005) The roots of sustainability. MIT Sloan Manag Rev 46(2)46:23–25

Elia V, Gnoni MG, Tornese F (2017) Measuring circular economy strategies through index methods: a critical analysis. J Clean Prod 142:2741–2751. https://doi.org/10.1016/j.jclepro.2016.10.196

Elkington J (1997) Cannibals with forks : the triple bottom line of 21st century business. Capstone, Oxford

Esposito B, Sessa MR, Sica D, Malandrino O (2020) Towards circular economy in the agri-food sector. A systematic literature review. Sustain 12. https://doi.org/10.3390/SU12187401

European Commission (2018) Agri-food trade in 2018

European Commission (2019) Monitoring EU agri-food trade: development until September 2019

Eurostat (2018) Small and large farms in the EU - statistics from the farm structure survey

FAO (2011) Biodiversity for food and agriculture. Italy, Rome

FAO (2012) Energy-smart food at FAO: an overview. Italy, Rome

FAO (2014) Food wastage footprint: fool cost-accounting

FAO (2016) The state of food and agriculture climate change, agriculture and food security. Italy, Rome

FAO (2017) The future of food and agriculture: trends and challenges. Italy, Rome

FAO (2020) The state of food security and nutrition in the world. Transforming Food Systems for Affordable Healthy Diets. Rome, Italy

Fassio F, Tecco N (2019) Circular economy for food: a systemic interpretation of 40 case histories in the food system in their relationships with SDGs. Systems 7:43. https://doi.org/10.3390/systems7030043

Fathollahi A, Coupe SJ (2021) Life cycle assessment (LCA) and life cycle costing (LCC) of road drainage systems for sustainability evaluation: quantifying the contribution of different life cycle phases. Sci Total Environ 776:145937. https://doi.org/10.1016/j.scitotenv.2021.145937

Ferreira VJ, Arnal ÁJ, Royo P et al (2019) Energy and resource efficiency of electroporation-assisted extraction as an emerging technology towards a sustainable bio-economy in the agri-food sector. J Clean Prod 233:1123–1132. https://doi.org/10.1016/j.jclepro.2019.06.030

Fiksel J (2006) A framework for sustainable remediation. JOM 8:15–22. https://doi.org/10.1021/es202595w

Flick U (2014) An introduction to qualitative research

Franciosi C, Voisin A, Miranda S et al (2020) Measuring maintenance impacts on sustainability of manufacturing industries : from a systematic literature review to a framework proposal. J Clean Prod 260:1–19. https://doi.org/10.1016/j.jclepro.2020.121065

Gaitán-Cremaschi D, Meuwissen MPM, Oude AGJML (2017) Total factor productivity: a framework for measuring agri-food supply chain performance towards sustainability. Appl Econ Perspect Policy 39:259–285. https://doi.org/10.1093/aepp/ppw008

Galdeano-Gómez E, Zepeda-Zepeda JA, Piedra-Muñoz L, Vega-López LL (2017) Family farm’s features influencing socio-economic sustainability: an analysis of the agri-food sector in southeast Spain. New Medit 16:50–61

Gallopín G, Herrero LMJ, Rocuts A (2014) Conceptual frameworks and visual interpretations of sustainability. Int J Sustain Dev 17:298–326. https://doi.org/10.1504/IJSD.2014.064183

Gallopín GC (2003) Sostenibilidad y desarrollo sostenible: un enfoque sistémico. Cepal, LATIN AMERICA

Garnett T (2013) Food sustainability: problems, perspectives and solutions. Proc Nutr Soc 72:29–39. https://doi.org/10.1017/S0029665112002947

Garofalo P, D’Andrea L, Tomaiuolo M et al (2017) Environmental sustainability of agri-food supply chains in Italy: the case of the whole-peeled tomato production under life cycle assessment methodology. J Food Eng 200:1–12. https://doi.org/10.1016/j.jfoodeng.2016.12.007

Gava O, Bartolini F, Venturi F et al (2018) A reflection of the use of the life cycle assessment tool for agri-food sustainability. Sustain 11. https://doi.org/10.3390/su11010071

Gazzola P, Querci E (2017) The connection between the quality of life and sustainable ecological development. Eur Sci J 7881:1857–7431

Geissdoerfer M, Savaget P, Bocken N, Hultink EJ (2017) The circular economy – a new sustainability paradigm ? The circular economy – a new sustainability paradigm ? J Clean Prod 143:757–768. https://doi.org/10.1016/j.jclepro.2016.12.048

Georgescu-Roegen N (1971) The entropy low and the economic process. Harward University Press, Cambridge Mass

Book   Google Scholar  

Gerbens-Leenes PW, Moll HC, Schoot Uiterkamp AJM (2003) Design and development of a measuring method for environmental sustainability in food production systems. Ecol Econ 46:231–248. https://doi.org/10.1016/S0921-8009(03)00140-X

Gésan-Guiziou G, Alaphilippe A, Aubin J et al (2020) Diversity and potentiality of multi-criteria decision analysis methods for agri-food research. Agron Sustain Dev 40. https://doi.org/10.1007/s13593-020-00650-3

Ghisellini P, Cialani C, Ulgiati S (2016) A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. J Clean Prod 114:11–32. https://doi.org/10.1016/j.jclepro.2015.09.007

Godoy-Durán Á, Galdeano- Gómez E, Pérez-Mesa JC, Piedra-Muñoz L (2017) Assessing eco-efficiency and the determinants of horticultural family-farming in southeast Spain. J Environ Manage 204:594–604. https://doi.org/10.1016/j.jenvman.2017.09.037

Gold S, Kunz N, Reiner G (2017) Sustainable global agrifood supply chains: exploring the barriers. J Ind Ecol 21:249–260. https://doi.org/10.1111/jiec.12440

Goucher L, Bruce R, Cameron DD et al (2017) The environmental impact of fertilizer embodied in a wheat-to-bread supply chain. Nat Plants 3:1–5. https://doi.org/10.1038/nplants.2017.12

Green A, Nemecek T, Chaudhary A, Mathys A (2020) Assessing nutritional, health, and environmental sustainability dimensions of agri-food production. Glob Food Sec 26:100406. https://doi.org/10.1016/j.gfs.2020.100406

Guinée JB, Heijungs R, Huppes G et al (2011) Life cycle assessment: past, present, and future †. Environ Sci Technol 45:90–96. https://doi.org/10.1021/es101316v

Guiomar N, Godinho S, Pinto-Correia T et al (2018) Typology and distribution of small farms in Europe: towards a better picture. Land Use Policy 75:784–798. https://doi.org/10.1016/j.landusepol.2018.04.012

Gunasekaran A, Patel C, McGaughey RE (2004) A framework for supply chain performance measurement. Int J Prod Econ 87:333–347. https://doi.org/10.1016/j.ijpe.2003.08.003

Gunasekaran A, Patel C, Tirtiroglu E (2001) Performance measures and metrics in a supply chain environment. Int J Oper Prod Manag 21:71–87. https://doi.org/10.1108/01443570110358468

Hamam M, Chinnici G, Di Vita G et al (2021) Circular economy models in agro-food systems: a review. Sustain 13

Harun SN, Hanafiah MM, Aziz NIHA (2021) An LCA-based environmental performance of rice production for developing a sustainable agri-food system in Malaysia. Environ Manage 67:146–161. https://doi.org/10.1007/s00267-020-01365-7

Harvey M, Pilgrim S (2011) The new competition for land: food, energy, and climate change. Food Policy 36:S40–S51. https://doi.org/10.1016/j.foodpol.2010.11.009

Hawkes C, Ruel MT (2006) Understanding the links between agriculture and health. DC: International Food Policy Research Institute. Washington, USA

Hellweg S, Milà i Canals L (2014) Emerging approaches, challenges and opportunities in life cycle assessment. Science (80)344:1109LP–1113. https://doi.org/10.1126/science.1248361

Higgins V, Dibden J, Cocklin C (2015) Private agri-food governance and greenhouse gas abatement: constructing a corporate carbon economy. Geoforum 66:75–84. https://doi.org/10.1016/j.geoforum.2015.09.012

Hill T (1995) Manufacturing strategy: text and cases., Macmillan

Hjeresen DD, Gonzales R (2020) Green chemistry promote sustainable agriculture?The rewards are higher yields and less environmental contamination. Environemental Sci Techonology 103–107

Horne R, Grant T, Verghese K (2009) Life cycle assessment: principles, practice, and prospects. Csiro Publishing, Collingwood, Australia

Horton P, Koh L, Guang VS (2016) An integrated theoretical framework to enhance resource efficiency, sustainability and human health in agri-food systems. J Clean Prod 120:164–169. https://doi.org/10.1016/j.jclepro.2015.08.092

Hospido A, Davis J, Berlin J, Sonesson U (2010) A review of methodological issues affecting LCA of novel food products. Int J Life Cycle Assess 15:44–52. https://doi.org/10.1007/s11367-009-0130-4

Huffman T, Liu J, Green M et al (2015) Improving and evaluating the soil cover indicator for agricultural land in Canada. Ecol Indic 48:272–281. https://doi.org/10.1016/j.ecolind.2014.07.008

Ilbery B, Maye D (2005) Food supply chains and sustainability: evidence from specialist food producers in the Scottish/English borders. Land Use Policy 22:331–344. https://doi.org/10.1016/j.landusepol.2004.06.002

Ingrao C, Faccilongo N, Valenti F et al (2019) Tomato puree in the Mediterranean region: an environmental life cycle assessment, based upon data surveyed at the supply chain level. J Clean Prod 233:292–313. https://doi.org/10.1016/j.jclepro.2019.06.056

Iocola I, Angevin F, Bockstaller C et al (2020) An actor-oriented multi-criteria assessment framework to support a transition towards sustainable agricultural systems based on crop diversification. Sustain 12. https://doi.org/10.3390/su12135434

Irabien A, Darton RC (2016) Energy–water–food nexus in the Spanish greenhouse tomato production. Clean Technol Environ Policy 18:1307–1316. https://doi.org/10.1007/s10098-015-1076-9

ISO 14040:2006 (2006) Environmental management — life cycle assessment — principles and framework

ISO 14044:2006 (2006) Environmental management — life cycle assessment — requirements and guidelines

ISO 15392:2008 (2008) Sustainability in building construction–general principles

Istat (2019) Andamento dell’economia agricola

Jaakkola E (2020) Designing conceptual articles : four approaches. AMS Rev 1–9. https://doi.org/10.1007/s13162-020-00161-0

Jin R, Yuan H, Chen Q (2019) Science mapping approach to assisting the review of construction and demolition waste management research published between 2009 and 2018. Resour Conserv Recycl 140:175–188. https://doi.org/10.1016/j.resconrec.2018.09.029

Johnston P, Everard M, Santillo D, Robèrt KH (2007) Reclaiming the definition of sustainability. Environ Sci Pollut Res Int 14:60–66. https://doi.org/10.1065/espr2007.01.375

Jorgensen SE, Burkhard B, Müller F (2013) Twenty volumes of ecological indicators-an accounting short review. Ecol Indic 28:4–9. https://doi.org/10.1016/j.ecolind.2012.12.018

Joshi S, Sharma M, Kler R (2020) Modeling circular economy dimensions in agri-tourism clusters: sustainable performance and future research directions. Int J Math Eng Manag Sci 5:1046–1061. https://doi.org/10.33889/IJMEMS.2020.5.6.080

Kamilaris A, Gao F, Prenafeta-Boldu FX, Ali MI (2017) Agri-IoT: a semantic framework for Internet of Things-enabled smart farming applications. In: 2016 IEEE 3rd World Forum on Internet of Things, WF-IoT 2016. pp 442–447

Karuppusami G, Gandhinathan R (2006) Pareto analysis of critical success factors of total quality management: a literature review and analysis. TQM Mag 18:372–385. https://doi.org/10.1108/09544780610671048

Kates RW, Parris TM, Leiserowitz AA (2005) What is sustainable development? Goals, indicators, values, and practice. Environ Sci Policy Sustain Dev 47:8–21. https://doi.org/10.1080/00139157.2005.10524444

Khounani Z, Hosseinzadeh-Bandbafha H, Moustakas K et al (2021) Environmental life cycle assessment of different biorefinery platforms valorizing olive wastes to biofuel, phosphate salts, natural antioxidant, and an oxygenated fuel additive (triacetin). J Clean Prod 278:123916. https://doi.org/10.1016/j.jclepro.2020.123916

Kitchenham B, Charters S (2007) Guidelines for performing systematic literature reviews in software engineering version 2.3. Engineering 45. https://doi.org/10.1145/1134285.1134500

Korhonen J, Nuur C, Feldmann A, Birkie SE (2018) Circular economy as an essentially contested concept. J Clean Prod 175:544–552. https://doi.org/10.1016/j.jclepro.2017.12.111

Kuisma M, Kahiluoto H (2017) Biotic resource loss beyond food waste: agriculture leaks worst. Resour Conserv Recycl 124:129–140. https://doi.org/10.1016/j.resconrec.2017.04.008

Laso J, Hoehn D, Margallo M et al (2018) Assessing energy and environmental efficiency of the Spanish agri-food system using the LCA/DEA methodology. Energies 11. https://doi.org/10.3390/en11123395

Lee KM (2007) So What is the “triple bottom line”? Int J Divers Organ Communities Nations Annu Rev 6:67–72. https://doi.org/10.18848/1447-9532/cgp/v06i06/39283

Lehmann RJ, Hermansen JE, Fritz M et al (2011) Information services for European pork chains - closing gaps in information infrastructures. Comput Electron Agric 79:125–136. https://doi.org/10.1016/j.compag.2011.09.002

León-Bravo V, Caniato F, Caridi M, Johnsen T (2017) Collaboration for sustainability in the food supply chain: a multi-stage study in Italy. Sustainability 9:1253

Lepage A (2009) The quality of life as attribute of sustainability. TQM J 21:105–115. https://doi.org/10.1108/17542730910938119

Li CZ, Zhao Y, Xiao B et al (2020) Research trend of the application of information technologies in construction and demolition waste management. J Clean Prod 263. https://doi.org/10.1016/j.jclepro.2020.121458

Lo Giudice A, Mbohwa C, Clasadonte MT, Ingrao C (2014) Life cycle assessment interpretation and improvement of the Sicilian artichokes production. Int J Environ Res 8:305–316. https://doi.org/10.22059/ijer.2014.721

Lueddeckens S, Saling P, Guenther E (2020) Temporal issues in life cycle assessment—a systematic review. Int J Life Cycle Assess 25:1385–1401. https://doi.org/10.1007/s11367-020-01757-1

Luo J, Ji C, Qiu C, Jia F (2018) Agri-food supply chain management: bibliometric and content analyses. Sustain 10. https://doi.org/10.3390/su10051573

Lynch J, Donnellan T, Finn JA et al (2019) Potential development of Irish agricultural sustainability indicators for current and future policy evaluation needs. J Environ Manage 230:434–445. https://doi.org/10.1016/j.jenvman.2018.09.070

MacArthur E (2013) Towards the circular economy. J Ind Ecol 2:23–44

MacArthur E (2017) Delivering the circular economy a toolkit for policymakers, The Ellen MacArthur Foundation

MacInnis DJ (2011) A framework for conceptual. J Mark 75:136–154. https://doi.org/10.1509/jmkg.75.4.136

Mangla SK, Luthra S, Rich N et al (2018) Enablers to implement sustainable initiatives in agri-food supply chains. Int J Prod Econ 203:379–393. https://doi.org/10.1016/j.ijpe.2018.07.012

Marotta G, Nazzaro C, Stanco M (2017) How the social responsibility creates value: models of innovation in Italian pasta industry. Int J Glob Small Bus 9:144–167. https://doi.org/10.1504/IJGSB.2017.088923

Martucci O, Arcese G, Montauti C, Acampora A (2019) Social aspects in the wine sector: comparison between social life cycle assessment and VIVA sustainable wine project indicators. Resources 8. https://doi.org/10.3390/resources8020069

Mayring P (2004) Forum : Qualitative social research Sozialforschung 2. History of content analysis. A Companion to Qual Res 1:159–176

McKelvey B (2002) Managing coevolutionary dynamics. In: 18th EGOS Conference. Barcelona, Spain, pp 1–21

McMichael AJ, Butler CD, Folke C (2003) New visions for addressing sustainability. Science (80- ) 302:1191–1920

Mehmood A, Ahmed S, Viza E et al (2021) Drivers and barriers towards circular economy in agri-food supply chain: a review. Bus Strateg Dev 1–17. https://doi.org/10.1002/bsd2.171

Mella P, Gazzola P (2011) Sustainability and quality of life: the development model. In: Kapounek S (ed) Enterprise and competitive environment. Mendel University: Brno, Czechia. 542–551

Merli R, Preziosi M, Acampora A (2018) How do scholars approach the circular economy ? A systematic literature review. J Clean Prod 178:703–722. https://doi.org/10.1016/j.jclepro.2017.12.112

Merli R, Preziosi M, Acampora A et al (2020) Recycled fibers in reinforced concrete: a systematic literature review. J Clean Prod 248:119207. https://doi.org/10.1016/j.jclepro.2019.119207

Miglietta PP, Morrone D (2018) Managing water sustainability: virtual water flows and economic water productivity assessment of the wine trade between Italy and the Balkans. Sustain 10. https://doi.org/10.3390/su10020543

Mitchell MGE, Chan KMA, Newlands NK, Ramankutty N (2020) Spatial correlations don’t predict changes in agricultural ecosystem services: a Canada-wide case study. Front Sustain Food Syst 4:1–17. https://doi.org/10.3389/fsufs.2020.539892

Moraga G, Huysveld S, Mathieux F et al (2019) Circular economy indicators: what do they measure?. Resour Conserv Recycl 146:452–461. https://doi.org/10.1016/j.resconrec.2019.03.045

Morrissey JE, Dunphy NP (2015) Towards sustainable agri-food systems: the role of integrated sustainability and value assessment across the supply-chain. Int J Soc Ecol Sustain Dev 6:41–58. https://doi.org/10.4018/IJSESD.2015070104

Moser G (2009) Quality of life and sustainability: toward person-environment congruity. J Environ Psychol 29:351–357. https://doi.org/10.1016/j.jenvp.2009.02.002

Muijs D (2010) Doing quantitative research in education with SPSS. London

Muller MF, Esmanioto F, Huber N, Loures ER (2019) A systematic literature review of interoperability in the green Building Information Modeling lifecycle. J Clean Prod 223:397–412. https://doi.org/10.1016/j.jclepro.2019.03.114

Muradin M, Joachimiak-Lechman K, Foltynowicz Z (2018) Evaluation of eco-efficiency of two alternative agricultural biogas plants. Appl Sci 8. https://doi.org/10.3390/app8112083

Naseer MA, ur R, Ashfaq M, Hassan S, et al (2019) Critical issues at the upstream level in sustainable supply chain management of agri-food industries: evidence from Pakistan’s citrus industry. Sustain 11:1–19. https://doi.org/10.3390/su11051326

Nattassha R, Handayati Y, Simatupang TM, Siallagan M (2020) Understanding circular economy implementation in the agri-food supply chain: the case of an Indonesian organic fertiliser producer. Agric Food Secur 9:1–16. https://doi.org/10.1186/s40066-020-00264-8

Nazari-Sharabian M, Ahmad S, Karakouzian M (2018) Climate change and eutrophication: a short review. Eng Technol Appl Sci Res 8:3668–3672. https://doi.org/10.5281/zenodo.2532694

Nazir N (2017) Understanding life cycle thinking and its practical application to agri-food system. Int J Adv Sci Eng Inf Technol 7:1861–1870. https://doi.org/10.18517/ijaseit.7.5.3578

Negra C, Remans R, Attwood S et al (2020) Sustainable agri-food investments require multi-sector co-development of decision tools. Ecol Indic 110:105851. https://doi.org/10.1016/j.ecolind.2019.105851

Newsham KK, Robinson SA (2009) Responses of plants in polar regions to UVB exposure: a meta-analysis. Glob Chang Biol 15:2574–2589. https://doi.org/10.1111/j.1365-2486.2009.01944.x

Niemeijer D, de Groot RS (2008) A conceptual framework for selecting environmental indicator sets. Ecol Indic 8:14–25. https://doi.org/10.1016/j.ecolind.2006.11.012

Niero M, Kalbar PP (2019) Coupling material circularity indicators and life cycle based indicators: a proposal to advance the assessment of circular economy strategies at the product level. Resour Conserv Recycl 140:305–312. https://doi.org/10.1016/j.resconrec.2018.10.002

Nikolaou IE, Tsagarakis KP (2021) An introduction to circular economy and sustainability: some existing lessons and future directions. Sustain Prod Consum 28:600–609. https://doi.org/10.1016/j.spc.2021.06.017

Notarnicola B, Hayashi K, Curran MA, Huisingh D (2012) Progress in working towards a more sustainable agri-food industry. J Clean Prod 28:1–8. https://doi.org/10.1016/j.jclepro.2012.02.007

Notarnicola B, Tassielli G, Renzulli PA, Monforti F (2017) Energy flows and greenhouses gases of EU (European Union) national breads using an LCA (life cycle assessment) approach. J Clean Prod 140:455–469. https://doi.org/10.1016/j.jclepro.2016.05.150

Opferkuch K, Caeiro S, Salomone R, Ramos TB (2021) Circular economy in corporate sustainability reporting: a review of organisational approaches. Bus Strateg Environ 1–22. https://doi.org/10.1002/bse.2854

Padilla-Rivera A, do Carmo BBT, Arcese G, Merveille N, (2021) Social circular economy indicators: selection through fuzzy delphi method. Sustain Prod Consum 26:101–110. https://doi.org/10.1016/j.spc.2020.09.015

Pagotto M, Halog A (2016) Towards a circular economy in Australian agri-food industry: an application of input-output oriented approaches for analyzing resource efficiency and competitiveness potential. J Ind Ecol 20:1176–1186. https://doi.org/10.1111/jiec.12373

Parent G, Lavallée S (2011) LCA potentials and limits within a sustainable agri-food statutory framework. Global food insecurity. Springer, Netherlands, Dordrecht, pp 161–171

Chapter   Google Scholar  

Pattey E, Qiu G (2012) Trends in primary particulate matter emissions from Canadian agriculture. J Air Waste Manag Assoc 62:737–747. https://doi.org/10.1080/10962247.2012.672058

Pauliuk S (2018) Critical appraisal of the circular economy standard BS 8001:2017 and a dashboard of quantitative system indicators for its implementation in organizations. Resour Conserv Recycl 129:81–92. https://doi.org/10.1016/j.resconrec.2017.10.019

Peano C, Migliorini P, Sottile F (2014) A methodology for the sustainability assessment of agri-food systems: an application to the slow food presidia project. Ecol Soc 19. https://doi.org/10.5751/ES-06972-190424

Peano C, Tecco N, Dansero E et al (2015) Evaluating the sustainability in complex agri-food systems: the SAEMETH framework. Sustain 7:6721–6741. https://doi.org/10.3390/su7066721

Pearce DW, Turner RK (1990) Economics of natural resources and the environment. Harvester Wheatsheaf, Hemel Hempstead, Herts

Pelletier N (2018) Social sustainability assessment of Canadian egg production facilities: methods, analysis, and recommendations. Sustain 10:1–17. https://doi.org/10.3390/su10051601

Peña C, Civit B, Gallego-Schmid A et al (2021) Using life cycle assessment to achieve a circular economy. Int J Life Cycle Assess 26:215–220. https://doi.org/10.1007/s11367-020-01856-z

Perez Neira D (2016) Energy sustainability of Ecuadorian cacao export and its contribution to climate change. A case study through product life cycle assessment. J Clean Prod 112:2560–2568. https://doi.org/10.1016/j.jclepro.2015.11.003

Pérez-Neira D, Grollmus-Venegas A (2018) Life-cycle energy assessment and carbon footprint of peri-urban horticulture. A comparative case study of local food systems in Spain. Landsc Urban Plan 172:60–68. https://doi.org/10.1016/j.landurbplan.2018.01.001

Pérez-Pons ME, Plaza-Hernández M, Alonso RS et al (2021) Increasing profitability and monitoring environmental performance: a case study in the agri-food industry through an edge-iot platform. Sustain 13:1–16. https://doi.org/10.3390/su13010283

Petti L, Serreli M, Di Cesare S (2018) Systematic literature review in social life cycle assessment. Int J Life Cycle Assess 23:422–431. https://doi.org/10.1007/s11367-016-1135-4

Pieroni MPP, McAloone TC, Pigosso DCA (2019) Business model innovation for circular economy and sustainability: a review of approaches. J Clean Prod 215:198–216. https://doi.org/10.1016/j.jclepro.2019.01.036

Polit DF, Beck CT (2004) Nursing research: principles and methods. Lippincott Williams & Wilkins, Philadelphia, PA

Porkka M, Gerten D, Schaphoff S et al (2016) Causes and trends of water scarcity in food production. Environ Res Lett 11:015001. https://doi.org/10.1088/1748-9326/11/1/015001

Prajapati H, Kant R, Shankar R (2019) Bequeath life to death: state-of-art review on reverse logistics. J Clean Prod 211:503–520. https://doi.org/10.1016/j.jclepro.2018.11.187

Priyadarshini P, Abhilash PC (2020) Policy recommendations for enabling transition towards sustainable agriculture in India. Land Use Policy 96:104718. https://doi.org/10.1016/j.landusepol.2020.104718

Pronti A, Coccia M (2020) Multicriteria analysis of the sustainability performance between agroecological and conventional coffee farms in the East Region of Minas Gerais (Brazil). Renew Agric Food Syst. https://doi.org/10.1017/S1742170520000332

Rabadán A, González-Moreno A, Sáez-Martínez FJ (2019) Improving firms’ performance and sustainability: the case of eco-innovation in the agri-food industry. Sustain 11. https://doi.org/10.3390/su11205590

Raut RD, Luthra S, Narkhede BE et al (2019) Examining the performance oriented indicators for implementing green management practices in the Indian agro sector. J Clean Prod 215:926–943. https://doi.org/10.1016/j.jclepro.2019.01.139

Recanati F, Marveggio D, Dotelli G (2018) From beans to bar: a life cycle assessment towards sustainable chocolate supply chain. Sci Total Environ 613–614:1013–1023. https://doi.org/10.1016/j.scitotenv.2017.09.187

Redclift M (2005) Sustainable development (1987–2005): an oxymoron comes of age. Sustain Dev 13:212–227. https://doi.org/10.1002/sd.281

Rezaei M, Soheilifard F, Keshvari A (2021) Impact of agrochemical emission models on the environmental assessment of paddy rice production using life cycle assessment approach. Energy Sources. Part A Recover Util Environ Eff 1–16

Rigamonti L, Mancini E (2021) Life cycle assessment and circularity indicators. Int J Life Cycle Assess. https://doi.org/10.1007/s11367-021-01966-2

Risku-Norja H, Mäenpää I (2007) MFA model to assess economic and environmental consequences of food production and consumption. Ecol Econ 60:700–711. https://doi.org/10.1016/j.ecolecon.2006.05.001

Ritzén S, Sandström GÖ (2017) Barriers to the circular economy – integration of perspectives and domains. Procedia CIRP 64:7–12. https://doi.org/10.1016/j.procir.2017.03.005

Rockström J, Steffen W, Noone K et al (2009) A safe operating space for humanity. Nature 461:472–475. https://doi.org/10.1038/461472a

Roos Lindgreen E, Mondello G, Salomone R et al (2021) Exploring the effectiveness of grey literature indicators and life cycle assessment in assessing circular economy at the micro level: a comparative analysis. Int J Life Cycle Assess. https://doi.org/10.1007/s11367-021-01972-4

Roselli L, Casieri A, De Gennaro BC et al (2020) Environmental and economic sustainability of table grape production in Italy. Sustain 12.  https://doi.org/10.3390/su12093670

Ross RB, Pandey V, Ross KL (2015) Sustainability and strategy in U.S. agri-food firms: an assessment of current practices. Int Food Agribus Manag Rev 18:17–48

Royo P, Ferreira VJ, López-Sabirón AM, Ferreira G. (2016) Hybrid diagnosis to characterise the energy and environmental enhancement of photovoltaic modules using smart materials. Energy 101:174–189. https://doi.org/10.1016/j.energy.2016.01.101

Ruggerio CA (2021) Sustainability and sustainable development: a review of principles and definitions. Sci Total Environ 786:147481. https://doi.org/10.1016/j.scitotenv.2021.147481

Ruiz-Almeida A, Rivera-Ferre MG (2019) Internationally-based indicators to measure agri-food systems sustainability using food sovereignty as a conceptual framework. Food Secur 11:1321–1337. https://doi.org/10.1007/s12571-019-00964-5

Ryan M, Hennessy T, Buckley C et al (2016) Developing farm-level sustainability indicators for Ireland using the Teagasc National Farm Survey. Irish J Agric Food Res 55:112–125. https://doi.org/10.1515/ijafr-2016-0011

Saade MRM, Yahia A, Amor B (2020) How has LCA been applied to 3D printing ? A systematic literature review and recommendations for future studies. J Clean Prod 244:118803. https://doi.org/10.1016/j.jclepro.2019.118803

Saitone TL, Sexton RJ (2017) Agri-food supply chain: evolution and performance with conflicting consumer and societal demands. Eur Rev Agric Econ 44:634–657. https://doi.org/10.1093/erae/jbx003

Salim N, Ab Rahman MN, Abd Wahab D (2019) A systematic literature review of internal capabilities for enhancing eco-innovation performance of manufacturing firms. J Clean Prod 209:1445–1460. https://doi.org/10.1016/j.jclepro.2018.11.105

Salimi N (2021) Circular economy in agri-food systems BT - strategic decision making for sustainable management of industrial networks. In: International S (ed) Rezaei J. Publishing, Cham, pp 57–70

Salomone R, Ioppolo G (2012) Environmental impacts of olive oil production: a life cycle assessment case study in the province of Messina (Sicily). J Clean Prod 28:88–100. https://doi.org/10.1016/j.jclepro.2011.10.004

Sánchez AD, Río DMDLC, García JÁ (2017) Bibliometric analysis of publications on wine tourism in the databases Scopus and WoS. Eur Res Manag Bus Econ 23:8–15. https://doi.org/10.1016/j.iedeen.2016.02.001

Saputri VHL, Sutopo W, Hisjam M, Ma’aram A (2019) Sustainable agri-food supply chain performance measurement model for GMO and non-GMO using data envelopment analysis method. Appl Sci 9. https://doi.org/10.3390/app9061199

Sassanelli C, Rosa P, Rocca R, Terzi S (2019) Circular economy performance assessment methods : a systematic literature review. J Clean Prod 229:440–453. https://doi.org/10.1016/j.jclepro.2019.05.019

Schiefer S, Gonzalez C, Flanigan S (2015) More than just a factor in transition processes? The role of collaboration in agriculture. In: Sutherland LA, Darnhofer I, Wilson GA, Zagata L (eds) Transition pathways towards sustainability in agriculture: case studies from Europe, CPI Group. Croydon, UK, pp. 83

Seuring S, Muller M (2008) From a literature review to a conceptual framework for sustainable supply chain management. J Clean Prod 16:1699–1710. https://doi.org/10.1016/j.jclepro.2008.04.020

Silvestri C, Silvestri L, Forcina A, et al (2021) Green chemistry contribution towards more equitable global sustainability and greater circular economy: A systematic literature review. J Clean Prod 294. https://doi.org/10.1016/j.jclepro.2021.126137

Smetana S, Schmitt E, Mathys A (2019) Sustainable use of Hermetia illucens insect biomass for feed and food: attributional and consequential life cycle assessment. Resour Conserv Recycl 144:285–296. https://doi.org/10.1016/j.resconrec.2019.01.042

Sonesson U, Berlin J, Ziegler F (2010) Environmental assessment and management in the food industry: life cycle assessment and related approaches. Woodhead Publishing, Cambridge

Soussana JF (2014) Research priorities for sustainable agri-food systems and life cycle assessment. J Clean Prod 73:19–23. https://doi.org/10.1016/j.jclepro.2014.02.061

Soylu A, Oruç C, Turkay M et al (2006) Synergy analysis of collaborative supply chain management in energy systems using multi-period MILP. Eur J Oper Res 174:387–403. https://doi.org/10.1016/j.ejor.2005.02.042

Spaiser V, Ranganathan S, Swain RB, Sumpter DJ (2017) The sustainable development oxymoron: quantifying and modelling the incompatibility of sustainable development goals. Int J Sustain Dev World Ecol 24:457–470. https://doi.org/10.1080/13504509.2016.1235624

Stewart R, Niero M (2018) Circular economy in corporate sustainability strategies: a review of corporate sustainability reports in the fast-moving consumer goods sector. Bus Strateg Environ 27:1005–1022. https://doi.org/10.1002/bse.2048

Stillitano T, Spada E, Iofrida N et al (2021) Sustainable agri-food processes and circular economy pathways in a life cycle perspective: state of the art of applicative research. Sustain 13:1–29. https://doi.org/10.3390/su13052472

Stone J, Rahimifard S (2018) Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework. Supply Chain Manag 23:207–238. https://doi.org/10.1108/SCM-06-2017-0201

Strazza C, Del Borghi A, Gallo M, Del Borghi M (2011) Resource productivity enhancement as means for promoting cleaner production: analysis of co-incineration in cement plants through a life cycle approach. J Clean Prod 19:1615–1621. https://doi.org/10.1016/j.jclepro.2011.05.014

Su B, Heshmati A, Geng Y, Yu X (2013) A review of the circular economy in China: moving from rhetoric to implementation. J Clean Prod 42:215–227. https://doi.org/10.1016/j.jclepro.2012.11.020

Suárez-Eiroa B, Fernández E, Méndez-Martínez G, Soto-Oñate D (2019) Operational principles of circular economy for sustainable development: linking theory and practice. J Clean Prod 214:952–961. https://doi.org/10.1016/j.jclepro.2018.12.271

Svensson G, Wagner B (2015) Implementing and managing economic, social and environmental efforts of business sustainability. Manag Environ Qual an Int Journal 26:195–213. https://doi.org/10.1108/MEQ-09-2013-0099

Tasca AL, Nessi S, Rigamonti L (2017) Environmental sustainability of agri-food supply chains: an LCA comparison between two alternative forms of production and distribution of endive in northern Italy. J Clean Prod 140:725–741. https://doi.org/10.1016/j.jclepro.2016.06.170

Tassielli G, Notarnicola B, Renzulli PA, Arcese G (2018) Environmental life cycle assessment of fresh and processed sweet cherries in southern Italy. J Clean Prod 171:184–197. https://doi.org/10.1016/j.jclepro.2017.09.227

Teixeira R, Pax S (2011) A survey of life cycle assessment practitioners with a focus on the agri-food sector. J Ind Ecol 15:817–820. https://doi.org/10.1111/j.1530-9290.2011.00421.x

Tobergte DR, Curtis S (2013) ILCD Handbook. J Chem Info Model. https://doi.org/10.278/33030

Tortorella MM, Di Leo S, Cosmi C et al (2020) A methodological integrated approach to analyse climate change effects in agri-food sector: the TIMES water-energy-food module. Int J Environ Res Public Health 17:1–21. https://doi.org/10.3390/ijerph17217703

Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidenceinformed management knowledge by means of systematic review. Br J Manag 14:207–222

Trivellas P, Malindretos G, Reklitis P (2020) Implications of green logistics management on sustainable business and supply chain performance: evidence from a survey in the greek agri-food sector. Sustain 12:1–29. https://doi.org/10.3390/su122410515

Tsangas M, Gavriel I, Doula M et al (2020) Life cycle analysis in the framework of agricultural strategic development planning in the Balkan region. Sustain 12:1–15. https://doi.org/10.3390/su12051813

Ülgen VS, Björklund M, Simm N (2019) Inter-organizational supply chain interaction for sustainability : a systematic literature review.

UNEP S (2020) Guidelines for social life cycle assessment of products and organizations 2020.

UNEP/SETAC (2009) United Nations Environment Programme-society of Environmental Toxicology and Chemistry. Guidelines for social life cycle assessment of products. France

United Nations (2011) Guiding principles on business and human rights. Implementing the United Nations “protect, respect and remedy” framework

United Nations (2015) Transforming our world: the 2030 agenda for sustainable development. sustainabledevelopment.un.org

Van Asselt ED, Van Bussel LGJ, Van Der Voet H et al (2014) A protocol for evaluating the sustainability of agri-food production systems - a case study on potato production in peri-urban agriculture in the Netherlands. Ecol Indic 43:315–321. https://doi.org/10.1016/j.ecolind.2014.02.027

Van der Ploeg JD (2014) Peasant-driven agricultural growth and food sovereignty. J Peasant Stud 41:999–1030. https://doi.org/10.1080/03066150.2013.876997

van Eck NJ, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84:523–538. https://doi.org/10.1007/s11192-009-0146-3

Van Eck NJ, Waltman L (2019) Manual for VOSviwer version 1.6.10. CWTS Meaningful metrics 1–53

Vasa L, Angeloska A, Trendov NM (2017) Comparative analysis of circular agriculture development in selected Western Balkan countries based on sustainable performance indicators. Econ Ann 168:44–47. https://doi.org/10.21003/ea.V168-09

Verdecho MJ, Alarcón-Valero F, Pérez-Perales D et al (2020) A methodology to select suppliers to increase sustainability within supply chains. Cent Eur J Oper Res. https://doi.org/10.1007/s10100-019-00668-3

Vergine P, Salerno C, Libutti A et al (2017) Closing the water cycle in the agro-industrial sector by reusing treated wastewater for irrigation. J Clean Prod 164:587–596. https://doi.org/10.1016/j.jclepro.2017.06.239

WCED (1987) Our common future - call for action

Webster K (2013) What might we say about a circular economy? Some temptations to avoid if possible. World Futures 69:542–554

Wheaton E, Kulshreshtha S (2013) Agriculture and climate change: implications for environmental sustainability indicators. WIT Trans Ecol Environ 175:99–110. https://doi.org/10.2495/ECO130091

Wijewickrama MKCS, Chileshe N, Rameezdeen R, Ochoa JJ (2021) Information sharing in reverse logistics supply chain of demolition waste: a systematic literature review. J Clean Prod 280:124359. https://doi.org/10.1016/j.jclepro.2020.124359

Woodhouse A, Davis J, Pénicaud C, Östergren K (2018) Sustainability checklist in support of the design of food processing. Sustain Prod Consum 16:110–120. https://doi.org/10.1016/j.spc.2018.06.008

Wu R, Yang D, Chen J (2014) Social Life Cycle Assessment Revisited Sustain 6:4200–4226. https://doi.org/10.3390/su6074200

Yadav S, Luthra S, Garg D (2021) Modelling Internet of things (IoT)-driven global sustainability in multi-tier agri-food supply chain under natural epidemic outbreaks. Environ Sci Pollut Res 16633–16654. https://doi.org/10.1007/s11356-020-11676-1

Yee FM, Shaharudin MR, Ma G et al (2021) Green purchasing capabilities and practices towards Firm’s triple bottom line in Malaysia. J Clean Prod 307:127268. https://doi.org/10.1016/j.jclepro.2021.127268

Yigitcanlar T (2010) Rethinking sustainable development: urban management, engineering, and design. IGI Global

Zamagni A, Amerighi O, Buttol P (2011) Strengths or bias in social LCA? Int J Life Cycle Assess 16:596–598. https://doi.org/10.1007/s11367-011-0309-3

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Silvestri, C., Silvestri, L., Piccarozzi, M. et al. Toward a framework for selecting indicators of measuring sustainability and circular economy in the agri-food sector: a systematic literature review. Int J Life Cycle Assess (2022). https://doi.org/10.1007/s11367-022-02032-1

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DOI : https://doi.org/10.1007/s11367-022-02032-1

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