There seems to be a lot of confusion about what theory is. At least this is a recurring question I get from students. Let us first discuss what theory is not: Sutton & Staw (1995) show that “references, data, variables, diagrams, and hypotheses are not theory” and they “explain how each of these five elements can be confused with theory” (p. 371). But we should also be aware of the difference between facts and theory! In his essay, which is part of a collection of six essays, Pagell (in: Boer et al., 2015) paints the picture of an ideal research world where “most research will be building or testing facts, not theory”, while “theory building and testing [will be left] to a much smaller group of papers, where the theoretical argument would be critical” (p. 1244). So, what is theory? A definition I like comes from Suddaby (2015): “[T]heory is simply a way of imposing conceptual order on the empirical complexity of the phenomenal world” (p. 1).
“Scale purification” – the process of eliminating items from multi-item scales – is widespread in empirical research, but studies that critically examine the implications of this process are scarce. In our new article, titled Statistical and Judgmental Criteria for Scale Purification, we (1) discuss the methodological underpinning of scale purification, (2) critically analyze the current state of scale purification in supply chain management (SCM) research, and (3) provide suggestions for advancing the scale purification process. Our research highlights the need for rigorous scale purification decisions based on both statistical and judgmental criteria. We suggest several methodological improvements. Particularly, we present a framework to demonstrate that the justification for scale purification needs to be driven by reliability, validity and parsimony considerations, and that this justification needs to be based on both statistical and judgmental criteria. We believe that our framework and additional suggestions will help to advance the knowledge about scale purification in SCM and adjacent disciplines.
Wieland, A., Durach, C.F., Kembro, J. & Treiblmaier, H. (2017). Statistical and Judgmental Criteria for Scale Purification. Supply Chain Management: An International Journal, 22 (4). DOI: 10.1108/SCM-07-2016-0230
My guest post today comes from Alan McKinnon who for several years has been raising concerns about the academic obsession with journal rankings and low rating of logistics/SCM journals. He has just published a new paper updating his earlier arguments.
In a paper that I wrote five years ago I argued that the development of logistics/supply chain management (SCM) as a discipline was being impaired by the relatively low ranking of specialist journals in this field. I was surprised and heartened by the favourable response I received both from logistics/SCM researchers and academics in other disciplines experiencing a similar problem. I have now returned to the journal ranking debate with a sequel to my original article which reviews recent literature on the subject, analyses new data on the validity of the journal ranking as an indicator of research quality and discusses the recalibration of logistics/SCM journals since 2010/11. The literature challenging the principle, practice and application of journal ranking has been steadily expanding and becoming more critical. Regrettably this is not deterring university managers from basing many recruitment, promotional and resource allocation decisions on the rating of journals. Data generated by the UK government’s assessment of university research (REF) has confirmed that, in the field of business and management, the journal ranking is an unreliable predictor of the quality and impact of an individual journal paper. In this analysis, papers published in lower ranked journals tended to be under-valued, a finding of particular relevance to logistics/SCM journals as they tend to be on the 2nd or 3rd tiers of the major journal lists. Since 2010/11, there has been some overall improvement in the relative standing of these journals, though a couple have been downgraded in the widely-used ABS list. Fortunately the backlash against journal rank “fetishism” has begun with bottom-up campaigns such as DORA and top-down, government-led initiatives in countries such as the UK and Australia aiming to make research assessment fairer, more transparent and more rigorous.
Alan McKinnon is Professor of Logistics in Kühne Logistics University, Hamburg and Professor Emeritus at Heriot-Watt University, Edinburgh. You can find out more about his research and publications at www.alanmckinnon.co.uk and follow him on Twitter @alancmckinnon.
McKinnon, A.C. (2017). Starry-eyed II: The Logistics Journal Ranking Debate Revisited. International Journal of Physical Distribution & Logistics Management, 47 (6). DOI: 10.1108/IJPDLM-02-2017-0097
It is among the common research practices in our field to build a statistical model with a limited set of variables in order to take the lens of a theory – often being alien to our field – on a supply chain phenomenon, and to test this model based on maybe 200 datasets. Other researchers collect data from three or four case companies to build or extend a research model that comprises a small set of propositions. So far so good. “So far so outdated”, I should say if I were to be malicious. Why? Researchers in fields like supply chain management might soon (or already?) be competing with “companies like Google, which have grown up in an era of massively abundant data, [that] don’t have to settle for wrong models”, as the editor in chief of Wired put it already back in 2008, proclaiming The End of Theory. So, is the data deluge about to make our research obsolete? If so, how should our community adapt to this new reality?
I am pleased to announce that our new article, The Human Factor in SCM: Introducing a Meta-theory of Behavioral Supply Chain Management, which I co-authored with Timm Schorsch and Carl Marcus Wallenburg, has now been published by the International Journal of Physical Distribution & Logistics Management. Our article provides a comprehensive overview of the behavioral supply chain management (BSCM) research landscape. In addition, we present a meta-theory of BSCM that encompasses all central elements of the research field. We also formulate five promising future research opportunities: Research being conducted in this area could (1) integrate cognitive and social psychological research, (2) apply a holistic view to decision-making and problem solving, (3) strengthen the concept of emergence and apply meso-level theory approaches, (4) complement our meta-theory, and (5) broaden the scope of inventory and capacity decision-making. We are confident that the critical discussions in our article and the formulated research opportunities will help scholars in positioning their own research to enhance its contribution.
A copy of our article can be requested via ResearchGate.
Schorsch, T., Wallenburg, C.M., & Wieland, A. (2017). The Human Factor in SCM: Introducing a Meta-theory of Behavioral Supply Chain Management. International Journal of Physical Distribution & Logistics Management, 47 (4), 238-262 DOI: 10.1108/IJPDLM-10-2015-0268
We certainly all agree: Trust between supply chain partners has a lot of benefits. However, in their forthcoming study of trust in the buyer–supplier relationship, Villena and her co-authors argue that there is a “duality of trust”: Trust has benefits but it can also become dysfunctional if it is excessive. The results of their study show “that trust follows an inverted-U shape with performance”, i.e., at a certain point the negative effects offset the benefits of trust and performance declines. The authors also show that “[t]rust’s negative effects are more severe for those buyers that are highly dependent and operate in stable markets”. But why could trust ever be harmful? Well, trust might create “blind faith” into a supplier when the buyer is too optimistic. Another explanation could be that buyers might avoid tensions with suppliers that they otherwise trust – even if they observe declining performance. Trust can also increase reliance and unnecessary obligations that constrain the buyer.
Villena, V.H., Choi, T.Y., & Revilla, E. (in press). Revisiting Interorganizational Trust: Is More Always Better or Could More Be Worse? Journal of Management