The circular economy is gathering momentum: In the future this model could, for example, mean that smartphones will not be sold and consumed anymore, but companies like Apple and Samsung will then keep scarce resources and sell a smartphone service to users instead of a product to consumers. These users will then be required to bring back the phone after a specified amount of time. California Management Review has now published a special issue on the circular economy. Several of the articles of that special issue refer to supply chains and supply chain management; and several of the authors have published in SCM journals before. This indicates that “supply chain thinking” and “circular thinking” are increasingly stimulating each other. I would even go so far to say that the 21st century’s supply chain management has to shift from linear to circular. This also has implications for our research. What we might need to re-think is whether the “chain” in “supply chain management” is still the right expression.
Trust plays an important role in supply chain management research (see some of my previous posts, e.g. The More Trust the Better! Really?, The Evolution of Trust). An article by Free (2008), titled Walking the Talk? Supply Chain Accounting and Trust among UK Supermarkets and Suppliers, asks: “How are calculative practices implicated in the constitution of trust in the UK retail sector?” This leads to two principal findings: First, “existing definitions of trust need to be more tightly and coherently elaborated to be applicable in the inter-organizational context”. The author proposes “a set of trust constructs that reflects both institutional phenomena (system trust) and personal and interpersonal forms of trust (trust, trusting behaviours, trustworthiness and trusting disposition)”. Second, “trust can be invoked in both ritualistic and instrumental ways”. Here, the author suggests “that the simple dichotomy of trust and distrust […] should be expanded to embrace manipulation and the use of trust as a discursive resource”.
Free, C. (2008). Walking the Talk? Supply Chain Accounting and Trust among UK Supermarkets and Suppliers. Accounting, Organizations and Society, 33 (6), 629–662. https://doi.org/10.1016/j.aos.2007.09.001
Today, I present Mentzer et al.’s (2001) must-read article, Defining Supply Chain Management. The authors demonstrate that, “although definitions of SCM differ across authors […], they can be classified into three categories”: (1) SCM as a management philosophy (= supply chain orientation), which involves a systems approach to viewing the supply chain as a whole, a strategic orientation toward cooperative efforts, and a customer focus; (2) SCM as an implementation of a management philosophy, which involves seven activities such as “mutually sharing information”; and (3) SCM as a set of management processes, which includes processes such as “customer relationship management” and “order fulfillment”. The article also contains a useful definition of SCM as “the systemic, strategic coordination of the traditional business functions and the tactics across these business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole”.
Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D. & Zacharia, Z.G. (2001). Defining Supply Chain Management. Journal of Business Logistics, 22 (2), 1–25. https://doi.org/10.1002/j.2158-1592.2001.tb00001.x
The P value debate has revealed that hypothesis testing is in crisis – also in our discipline! But what should we do now? Nature recently asked influential statisticians to recommend one change to improve science. Here are five answers: (1) Adjust for human cognition: Data analysis is not purely computational – it is a human behavior. So, we need to prevent cognitive mistakes. (2) Abandon statistical significance: Academia seems to like “statistical significance”, but P value thresholds are too often abused to decide between “effect” (favored hypothesis) and “no effect” (null hypothesis). (3) State false-positive risk, too: What matters is the probability that a significant result turns out to be a false positive. (4) Share analysis plans and results: Techniques to avoid false positives are to pre-register analysis plans, and to share all data and results of all analyses as well as any relevant syntax or code. (5) Change norms from within: Funders, journal editors and leading researchers need to act. Otherwise, researchers will continue to re-use outdated methods, and reviewers will demand what has been demanded of them.
Leek, J., McShane, B.B., Gelman, A., Colquhoun, D., Nuijten, M.B. & Goodman, S.N. (2017). Five Ways to Fix Statistics. Nature, 551 (2), 557-559. DOI: 10.1038/d41586-017-07522-z
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. DOI: 10.1007/s40685-017-0045-z
There has been a recent trend in several management disciplines, including supply chain management, to create knowledge by systematically reviewing available literature. So far, however, our discipline lacked a “gold standard” that guides researchers in this endeavor. The Journal of Supply Chain Management has now published our new article, Durach, Kembro & Wieland (2017): A New Paradigm for Systematic Literature Reviews in Supply Chain Management. Our systematic literature review process follows six steps: (1) develop an initial theoretical framework; (2) develop criteria for determining whether a publication can provide information regarding this framework; (3) identify literature through structured and rigorous searches; (4) conduct theoretically driven selection of literature and a relevance test; (5) develop two data extraction structures, integrate data to refine the theoretical framework, and develop narrative propositions; and (6) explain the refined framework and compare it to the initial assumptions. We believe that these best-practice guidelines, although developed for the SCM discipline, can be used as a blueprint also for adjacent management disciplines.
Durach, C.F., Kembro, J. & Wieland, A. (2017). A New Paradigm for Systematic Literature Reviews in Supply Chain Management. Journal of Supply Chain Management, 53 (4), 67-85. DOI: 10.1111/jscm.12145
I have been using Fisher’s (1997) supply chain–product match/mismatch framework (What Is the Right Supply Chain for Your Product?) in my teaching for years! Herein, the author argues that functional products require a physically efficient supply chain strategy, whereas innovative products require a market-responsive supply chain strategy. Fisher’s framework finds empirical support: Wagner et al. (2012) demonstrate that “the higher the supply chain fit, the higher the Return on Assets (ROA) of the firm”. Interestingly, a majority of the firms from their sample achieve a negative misfit, i.e. they target high responsiveness for their supply chain although their products are functional. Extensions of the framework exist, for example by Lee (2002), who adds a “supply” dimension, and more recently Gligor (2017), who argues that “benefits generated by perfect supply chain fit might be offset by the resources deployed to achieve that fit”. Research presented by Perez-Franco et al. (2016) helps to “capture, evaluate and re-formulate the supply chain strategy of a business unit”.
Fisher, M.L. (1997). What Is the Right Supply Chain for Your Product? Harvard Business Review, 75 (2), 105-116.
A colleague recently recommended the following article to me: Mansfield (2003): Spatializing Globalization: A “Geography of Quality” in the Seafood Industry. Herein, the author takes a look at the quality of products in that industry. She challenges “recent perspectives that define quality as an alternative to global, industrial forms of production” and “finds that quality is also important for industrial food production and for the global geography of the surimi [a fish paste] seafood industry”. In general, the author takes an interpretive approach – an approach that is almost absent in SCM research, and that might be inspirational for our otherwise empiricist discipline. Particularly, she employs actor–network theory, which proposes that reality does not exist by nature but is rather constructed through socio-material networks. SCM researchers could learn from such a type of research that (1) theory could be mobilized in many different creative ways; (2) technical supply chain issues are embedded in larger social-political arrangements; (3) geography might inform SCM (theoretically as well as materially); and (4) “quality”, or other concepts, do not exist by nature but are stabilized through networks.