A Brief Introduction to Grammarly and Deepl Write
As the recent debate about ChatGPT has shown, artificial intelligence tools are advancing rapidly. Today, I would like to introduce two AI tools that can be used to improve the language of academic texts. The first tool, Grammarly, can be integrated into programs like Word and suggests improvements, both in terms of errors and style. Grammarly has already found a large following among academic writers. The second tool is called Deepl Write and is currently in beta. It allows users to type text into an input field and get an improved text back. I tested this tool today by using it to improve the text of this blog post. While such tools may not be perfect, I believe they can help increase participation in SCM research by non-native speakers and those who cannot afford expensive proofreading services. The development is moving fast and I am excited to see what comes next.
Gap-Spotting or Problematization
How should researchers construct research questions for their academic work? One intuitive answer is by spotting a gap in the existing academic literature. This is certainly an effective approach that follows the Popperian scientific method. In addition to gap-spotting, there is a second approach that deserves a little more attention: problematization. Alvesson and Sandberg (2011) describe this approach in their famous article Generating Research Questions Through Problematization (a must read!). They write that “[t]he dominance of gap-spotting is surprising, given it is increasingly recognized that theory is made interesting and influential when it challenges assumptions that underlie existing literature.” This is what problematization does: it is about identifying and challenging assumptions that underlie existing theories and generating research questions that lead to the development of more interesting and influential theories. Of course, we will still need gap-spotting in the future. But I do believe that SCM research could benefit from more problematization.
Alvesson, M., & Sandberg, J. (2011). Generating Research Questions Through Problematization. Academy of Management Review, 36(2), 247–271. https://doi.org/10.5465/amr.2009.0188
Using Supply Chain Databases in Academic Research
In recent years, academic articles that use supply chain databases have become more and more common in SCM-related journals. Such databases (e.g., Bloomberg SPLC, FactSet Supply Chain Relationships, and Mergent Supply Chain) were originally not developed for use in academic research, but for use in business practice. However, they offer great potential for a better understanding of supply chains (or more precisely supply networks) and supply chain management and are therefore also very interesting for researchers. A recent article by Culot and her coauthors (2023) discusses these potentials and points out pitfalls for using supply chain databases in SCM research. The article is entitled Using Supply Chain Databases in Academic Research: A Methodological Critique and based on a review of previous studies using such databases, publicly available materials, interviews with information service providers, and the direct experience of the authors. I am sure this long-awaited article will serve as a reference for quantitative research relying on such databases for years to come.
Culot, G., Podrecca, M., Nassimbeni, G., Orzes, G., & Sartor, M. (2023). Using Supply Chain Databases in Academic Research: A Methodological Critique. Journal of Supply Chain Management, 59(1), 3–25. https://doi.org/10.1111/jscm.12294
Sensemaking in Supply Chains
Something that is long-established in other management disciplines but sadly almost completely neglected in the SCM discipline is research related to sensemaking. In short, sensemaking “involves turning circumstances into a situation that is comprehended explicitly in words and that serves as a springboard into action” (Weick et al., p. 409). Such research is concerned with subjective interpretations rather than objective truth and is therefore better suited to the study of social science phenomena than much of the positivist research we see in contemporary SCM research. Sensemaking is closely associated with the name of Karl E. Weick and his way of analyzing phenomena. Among Weick’s most famous studies is The Collapse of Sensemaking in Organizations: The Mann Gulch Disaster (1993). It could serve as a blueprint for analyzing SCM phenomena. Anyone considering a sensemaking study should read the book Sensemaking in Organizations (Weick, 1995). The article Organizing and the Process of Sensemaking (Weick et al., 2005) gives a very good overview of sensemaking.
Weick, K.E. (1993). The Collapse of Sensemaking in Organizations: The Mann Gulch Disaster. Administrative Science Quarterly, 38(4), 628–652. https://doi.org/10.2307/2393339
Weick, K.E. (1995). Sensemaking in Organizations. SAGE. ISBN 080397177X
Weick, K.E., Sutcliffe, K.M., & Obstfeld, D. (2005). Organizing and the Process of Sensemaking. Organization Science, 16(4), 409–421. https://doi.org/10.1287/orsc.1050.0133
Experiments in Supply Chain Management Research
Experiments have exerted a growing methodological influence on the SCM discipline in recent years. In their recently published article on this subject, entitled Experiments in Strategy Research: A Critical Review and Future Research Opportunities, Bolinger et al. (2021) examine and categorize experiments by “[identifying] topic areas in which experiments have been effectively deployed as well as several literature streams that have a limited amount of prior experimental research.” The authors also discuss challenges in using experiments, thereby addressing the level of analysis. SCM researchers should pay particular attention to this aspect, as many of the phenomena they study are not located at the firm level, as in strategy research, but at the supply chain level. The authors argue that their work “documents experimental research and provides a methodological practicum, thereby offering a platform for future experiment-based research in strategic management”. Although the authors review extant experimental work in strategic management, their results are certainly also very useful for SCM researchers.
Bolinger, M. T., Josefy, M. A., Stevenson, R., & Hitt, M. A. (2022). Experiments in Strategy Research: A Critical Review and Future Research Opportunities. Journal of Management, 48(1), 77–113. https://doi.org/10.1177/01492063211044416
Writing Skills: The Paragraph
The paragraph is probably the most important unit of a well-written academic text. It has a specific structure and standards that make it effective and enjoyable to read. This video demonstrates how to construct good paragraphs and improve writing with better clarity and flow.
What Is the Eisenhardt Method, Really?
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
How To Improve Your Writing Skills
What distinguishes a good paper? The idea should be creative, the methodological approach should be flawless, and there should be a theoretical contribution. Sure. However, good communication with the reader is at least as important as all of the rest. Unfortunately, very often I have reviewed manuscripts that contain interesting theories, data, and results, but are simply not well-written. As academics we are often busy, but there is one thing we all should do: read a book about academic writing. The reading time is well invested. I have two book recommendations. The first is Natalie Reid (2018), Getting Published in International Journals: Writing Strategies for European Social Scientists. An academic friend of mine once wrote on LinkedIn that this was the best book he had ever read. And it is really good. My favorite chapters deal with “paragraphing” and “constructing and argument, sentence by sentence”. My second recommendation is aimed at German-speaking academics: Gerlinde Mautner (2019), Wissenschaftliches Englisch: Stilsicher Schreiben in Studium und Wissenschaft. This is one of the best books I have ever read.
Reid, N. (2018): Getting Published in International Journals: Writing Strategies for European Social Scientists. Revised Edition. ISBN 0692929959
Mautner, G. (2019): Wissenschaftliches Englisch: Stilsicher Schreiben in Studium und Wissenschaft. 3rd Edition. ISBN 3825252191
Connected Papers
The following tool was brought to my attention the other day: Connected Papers, “a visual tool to help researchers and applied scientists find and explore papers relevant to their field of work”. It analyzes thousands of papers, selects the ones with the strongest connections to an entered paper, and generates a graph. In this graph, the tool arranges papers according to their similarity in terms of co-citation and bibliographic coupling. Unlike in a citation tree (e.g., Web of Science), “even papers that do not directly cite each other can be strongly connected and very closely positioned”, which I believe is a very useful alternative to other search strategies. “According to this measure, two papers that have highly overlapping citations and references are presumed to have a higher chance of treating a related subject matter.” With the help of the tool, I was able to identify very exciting papers that I would certainly not have found with other search engines. Connected Papers is self-funded and free.
Interpretive Supply Chain Management Research
Our discipline is still almost exclusively shaped by positivism. This is very surprising in view of the very complex social phenomena with which the discipline deals. However, recently I have noticed a (slowly) growing trend toward interpretivism. For example, Darby and her coauthors (2019) have discussed the set of questions interpretive research can address in SCM. Many SCM researchers may still be unsure of how best to conduct an interpretive study. Used to the structured approaches of positivist studies (e.g., Yin), we often would like to have a template in hand that shows us how to conduct an interpretive study. A new article by Mees-Buss and her coauthors (2021) argues that the inductive route to theory that templates (e.g., Gioia) offer do not address the challenges of interpretation. They argue that “a return to a hermeneutic orientation opens the way to more plausible and insightful theories based on interpretive rather than procedural rigor” and they offer “a set of heuristics to guide both researchers and reviewers along this path”.
Mees-Buss, J., Welch, C., & Piekkari, R. (2021), From Templates to Heuristics: How and Why to Move Beyond the Gioia Methodology. Organizational Research Methods, in print. https://doi.org/10.1177/1094428120967716
