Tag Archive | Article

Supply Chain Coordination with Contracts

Today I would like to talk about Supply Chain Coordination with Contracts, a chapter written by Cachon (2003). It has become the standard reference when it comes to teaching some key supply chain models. Coordination between the members of a supply chain is certainly very relevant but also challenging. Because the members of a supply chain are typically concerned with optimizing their own objectives, their actions might not lead to optimal supply chain performance. Therefore, contracts need to be carefully designed. The author “reviews and extends the supply chain literature on the management of incentive conflicts with contracts”. For example, Cachon presents key supply chain models, hereby extending the newsvendor model “by allowing the retailer to choose the retail price in addition to the stocking quantity” and “by allowing the retailer to exert costly effort to increase demand”. Teaching such models can help students to gain the required problem-solving competencies and abstraction capabilities that are needed in today’s business world.

Cachon, G.P. (2003). Supply Chain Coordination with Contracts. Handbooks in Operations Research and Management Science, 11 (Supply Chain Management: Design, Coordination and Operation), 227-339 https://doi.org/10.1016/S0927-0507(03)11006-7

The Constitution of Trust

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

Three Types of SCM Definitions

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

Five Ways to Fix Statistics in Supply Chain Research

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

Four Types of Case Study Research Designs

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

How to Do a Systematic Literature Review

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

Fisher’s Supply Chain–Product Match/Mismatch Framework

I have used 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.

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