There are different types of case-based research methods that differ considerably in their basic assumptions and objectives. An example of such a method is the multi-case theory-building approach, which is based on the work of Kathleen M. Eisenhardt. Her 1989 article, which laid the foundation for this method, has been cited tens of thousands of times to date. Unfortunately, there are countless misconceptions about the method in terms of types of data, number of cases, and performance emphasis. The method is also often overinterpreted as a rigid template, although it was never intended to be such a template. In a new article entitled What Is the Eisenhardt Method, Really?, Eisenhardt now puts her method in a new light and argues that the method’s relatively few defining features enable a wide variety of research possibilities. It should be clear that this new article is important reading for anyone who wants to do research with Eisenhardt’s method and for anyone whose work aims at theory building.
Eisenhardt, K.M. (2021). What Is the Eisenhardt Method, Really? Strategic Organization, 19(1), 147–160. https://doi.org/10.1177/1476127020982866
Academics and students often have very different ideas in mind when they talk about case study research. Indeed, case studies in SCM research are not alike and several different case study research designs can be distinguished. A recent article by Ridder (2017), titled The Theory Contribution of Case Study Research Designs, provides an overview of four common approaches. First, there is the “no theory first” type of case study design, which is closely connected to Eisenhardt’s methodological work. The second type of research design is about “gaps and holes”, following Yin’s guidelines. This type of case study design is what can be seen in SCM journals maybe most often. A third design deals with a “social construction of reality”, which is represented by Stake. Finally, the reason for case study research can also be to identify “anomalies”. A representative scholar of this approach is Burawoy. Each of these four approaches has its areas of application, but it is important to understand their unique ontological and epistomological assumptions. A very similar overview is provided by Welch et al. (2011).
Ridder, H.G. (2017). The Theory Contribution of Case Study Research Designs. Business Research, 10 (2), 281-305. https://doi.org/10.1007/s40685-017-0045-z
You should all read this interesting article: Approaching the Conceptual Leap in Qualitative Research by Klag & Langley (2013), which is useful for researchers who build theory from qualitative data. Its central message is “that the abductive process is constructed through the synthesis of opposites that [the authors] suggest will be manifested over time in a form of ‘bricolage’.” The authors use four dialectic tensions: deliberation—serendipity, engagement—detachment, knowing—not knowing, social connection—self-expression. One of the poles of each dialectic has a disciplining character, the other pole has a liberating influence: On the one hand, overemphasizing the disciplining poles “may result in becoming ‘bogged down’ in contrived frameworks (deliberation), obsessive coding (engagement), cognitive inertia (knowing) or collective orthodoxy (social connection)”. On the other hand, overemphasizing the liberating poles “can also be unproductive as researchers wait for lightning to strike (serendipity), forget the richness and nuances of their data (detachment), reinvent the wheel (not knowing) or drift off into groundless personal reflection (self-expression)”.
Klag, M., & Langley, A. (2013). Approaching the Conceptual Leap in Qualitative Research. International Journal of Management Reviews, 15 (2), 149-166 DOI: 10.1111/j.1468-2370.2012.00349.x
Like it or not: Our discipline is very much dominated by positivism and the application of the scientific method, which assumes that new knowledge can be created by developing and testing theory or, in other words, by induction or deduction. Another type of inference is abduction. Spens & Kovács (2006) present an overview of the deductive, inductive and abductive research processes.
Spens, K., & Kovács, G. (2006). A Content Analysis of Research Approaches in Logistics Research. International Journal of Physical Distribution & Logistics Management, 36 (5), 374-390 https://doi.org/10.1108/09600030610676259
Many theory-testing efforts in our field are made by borrowing theories from other fields (e.g., transaction cost economics or resource-based theory), adapting them to a supply chain context and deriving hypotheses that are eventually tested statistically. By doing so, we have reached a lot! But we also need our own theories. For example, several years ago, Lambert & Cooper (2000) noted: “One of the most significant paradigm shifts of modern business management is that individual businesses no longer compete as solely autonomous entities, but rather as supply chains”. So, part of our theoretical toolkit could be a theory of supply chain vs. supply chain competition which could explain how the supply chains of Apple and Samsung interact. However, surprisingly few attempts have been made towards such a theory. This includes a thought piece by Rice & Hoppe (2001) and, more recently, a case study by Antai & Olson (2013). We need to continue this theory-building process.
Rice, J.B. & Hoppe, R.M. (2001). Supply Chain vs. Supply Chain: The Hype & the Reality. Supply Chain Management Review, 5 (5) http: web.mit.edu/supplychain/repository/scvssc.pdf
Antai, I. & Olson, H. (2013). Interaction: A New Focus for Supply Chain vs Supply Chain Competition. International Journal of Physical Distribution & Logistics Management, 43 (7), 511-528 https://doi.org/10.1108/IJPDLM-06-2012-0195
In their very insightful essay, Toward the Theory of the Supply Chain, Carter, Rogers & Choi (2015) argue that “before we continue to build theories of supply chain management, we must first develop a theory of the supply chain – the phenomenon that we purport to manage”. I could not agree more with their argument. Indeed, without focusing on the supply chain before focusing on how to manage it, SCM research would not be more than fishing in murky waters. The authors present six foundational premises to characterize a supply chain. These provide “a holistic conceptualization of the supply chain – what it is and how it behaves”. Moreover, the authors present several future avenues for further developing their conceptualization of the supply chain. I can only recommend reading this important new paper and I am convinced that it will have a major influence on how future SCM research is being conducted.
Carter, C.R., Rogers, D.S., & Choi, T.Y. (2015). Toward the Theory of the Supply Chain. Journal of Supply Chain Management, 51 (2), 89–97 DOI: 10.1111/jscm.12073
Are you currently conducting conceptual, qualitative, or survey research? Are you also aiming to publish the results in a top journal? Then I have some tips for you that could bring you one step closer to your goal. These tips can be found in a recent JBL editorial: A Trail Guide to Publishing Success: Tips on Writing Influential Conceptual, Qualitative, and Survey Research. Herein, the authors identify and describe agreed-upon basics that can help to “(1) increase consistency in the review process, (2) reduce publication cycles, and (3) begin to roll back the length of articles”. For three types of research (conceptual, qualitative, and survey research), best practices are presented for crafting articles. I especially like a table with warning signs “that authors are wandering down a perilous path”, which can be used as a check list for your own research. These warning signs might also help reviewers to evaluate the quality of a manuscript.
Fawcett, S., Waller, M., Miller, J., Schwieterman, M., Hazen, B., & Overstreet, R. (2014). A Trail Guide to Publishing Success: Tips on Writing Influential Conceptual, Qualitative, and Survey Research. Journal of Business Logistics, 35 (1), 1-16 https://doi.org/10.1111/jbl.12039
Theory-building empirical research needs formal conceptual definitions. Particularly, such definitions are necessary conditions for construct validity. But what is a “good” formal conceptual definition? In his seminal JOM paper, A Theory of Formal Conceptual Definitions: Developing Theory-building Measurement Instruments, Wacker (2004) presents eight rules for formal conceptual definitions: (1) “Definitions should be formally defined using primitive and derived terms.” (2) “Each concept should be uniquely defined.” (3) “Definitions should include only unambiguous and clear terms.” (4) “Definitions should have as few as possible terms in the conceptual definition to avoid violating the parsimony virtue of ‘good’ theory.” (5) “Definitions should be consistent within the [general academic] field.” (6) “Definitions should not make any term broader.” (7) “New hypotheses cannot be introduced in the definitions.” (8) “Statistical tests for content validity must be performed after the terms are formally defined.” These rules are explained in detail in Wacker’s article. I am convinced that Wacker’s rules lead to better measurement instruments.
Wacker, J.G. (2004). A Theory of Formal Conceptual Definitions: Developing Theory-building Measurement Instruments. Journal of Operations Management, 22 (6), 629-650 https://doi.org/10.1016/j.jom.2004.08.002
Research revolves around theory. Hereby, the role of researchers is twofold: Researchers can either start with real-life observations and produce a set of propositions that summarize a new theory (inductive theory building), e.g., using grounded theory research, or start with an existing theory for formulating hypotheses and use data to test them (deductive theory testing), e.g., using structural equation modeling.
For an extensive investigation of this dual role see Colquitt and Zapata-Phelan (2007).
Colquitt, J. & Zapata-Phelan, C. (2007). Trends in theory building and theory testing: A five-decade study of the Adademy of Management Journal. Academy of Management Journal, 50 (6), 1281-1303 DOI: 10.5465/AMJ.2007.28165855
The Journal of Operations Management has now published two interesting articles about the science of operations and supply chain management. These two articles are intertwined and they were written by Singhal and Singhal (2012). The first article is titled Imperatives of the science of operations and supply-chain management and discusses two opportunities for pursuing radical innovations. The first opportunity is the pursuit of all phases of science (including theory development and theory testing). The second opportunity is the pursuit of multiple perspectives (e.g., based on different methods and different parts of a system). The second article is titled Opportunities for developing the science of operations and supply-chain management and proposes and analyzes ways to seize these two opportunities. It is found that networks of research teams, outliers, and meta-analyses can help to obtain multiple perspectives and to discover radical innovation. In conclusion, both articles will help our community to further develop SCM research.