by Yany Grégoire, HEC Montréal. He received in 2018 the Journal of Service Research “Best Reviewer” Award.
First, I would like to thank Werner for inviting me to write this short essay on reviewing in Service Marketing. I have been a professor for almost 15 years now, and I realized early in my career that Service Marketing was MY community, MY academic family. Sharing some insights about reviewing with you is an immense pleasure. I hope these few tips will be helpful to some of you, especially the younger researchers.
I’m almost mid-career now, which means that I review about 30-40 manuscripts a year. I do this for various reasons. First, I believe it is part of our duty as scholars to review the research of others; it just seems fair if we want others to review our own work. It is also a good way to serve and be part of my favorite academic community. In addition, it is an excellent way to learn and to stay up-to-date on recent research and the fast-evolving game of publishing. At the end of the day, it is a privilege to sit on the board of quality journals—such as JSR, JAMS, and JBR—which have at heart the wellbeing of the service community. It is very rewarding to be part of this knowledge creation process.
Over time, I have realized that experienced reviewers share similar heuristics that create a kind of “secret” language and set of “unspoken” criteria to evaluate research. Such reviewers quickly realize—often in the first 2 or 3 pages—if the authors speak the same “language” they do. My objective here is to try to communicate such tacit criteria and heuristics for new authors so that they can become more fluent in the “reviewing language.” Specifically, I discuss three unspoken “acid tests” used to measure the quality of the positioning, theory, and method.
- The positioning (or the introduction) is a critical part. Its length typically varies between 2 and 4 pages. A quality manuscript regularly starts by discussing a “sexy” topic or current event (e.g., social media crises, big data challenges, liquid possession, etc.) and by highlighting a large gap for managers or researchers. Then, the authors present between two and four concrete solutions—often called contributions—to address this large gap. The way these contributions are framed is crucial. They need to relate directly to the model or the hypotheses. The positioning can almost be viewed as a form of executive summary in which the authors present upfront their key findings and recommendations. The authors need to be assertive, clear, and precise about their specific contributions. This is not a place for generalities and empty sentences; each word should be carefully selected and weighed. As an author, I always spend an unreasonable number of hours writing (and rewriting) this part. As a reviewer, I expect to see the same concern for quality and precision. It is probably the first “acid test” of a manuscript.
- Then comes the theory section. Here, I would recommend avoiding the expression “literature review” and replacing it by “research background.” A sign that the authors do not speak the “language” is when they discuss in detail various tangential notions that are not directly related to the positioning. For instance, if you’re interested in the outcomes related to online complaining, there is no point in having a lengthy discussion about its antecedents. Try to write the background section economically, using a linear and concise style. The background section should focus on defining new core concepts (e.g., engagement, brand hate, etc.), or foundational theories that are essential to the formulation of the hypotheses (e.g., resource-based view, broaden-and-build theory, etc.). It is difficult to make a substantial contribution in this section; it should be written clearly, effectively, and should be to the point.It is my sense that tightly written articles move quickly to the conceptual model or the hypotheses (maybe after 5 or 6 pages in total, including the positioning). If you have a figure—which is common in marketing strategy and service marketing—present it early and use it as a “roadmap” to expose your logic. If you conduct behavioral research (i.e., field studies, experiments, etc.), you should probably avoid predicting main effects as your core hypotheses. Main effects in behavioral research are like the “kiss of the death”; these are likely to be viewed as too simplistic and intuitive. Try to emphasize “cool” interaction or moderation effects, which present strong reversal effects or interesting counterintuitive patterns. Reviewers will also expect to see hypotheses about the process—this is almost mandatory for experimental work—and some discussion about ruling out rival explanations. It is by presenting counterintuitive interaction effects and rich mediation effects that the reviewers will conclude that you are making a sufficient theoretical contribution. A word of caution here: a lack of theoretical contribution is probably the most common reason for rejection, as well as the easiest way for a reviewer to dismiss your manuscript. The aspects related to the richness of your model compose the second “acid test” of your manuscript.
- The third and final “acid test” is not the least. There is a growing expectation for multi-methods research (including at least one special data collection), and for the use of sophisticated analytical approaches. In managerial and behavioral research, the combination of different methods is becoming a best practice. However, it is probably not sufficient to combine a basic cross-sectional survey with a few basic scenario-based experiments in order to get published in a top journal. In my opinion, the authors need to go the extra mile to conduct at least one special data collection. The harder it is to collect data, the more the data will be considered by the review team. For instance, it is now common to see dyadic or triadic data, longitudinal design, multilevel design, neurophysiological measures, textual data, voice data, financial data, etc. In addition, along with the collection of “newer” data, it is expected that enhanced statistical analyses, going beyond ANOVAS, SEM, and PROCESS, will be used. There is certainly a growing demand for mixed models, multilevel models, event studies, and sophisticated econometric models accounting for endogeneity, to name a few.
I hope these three “acid tests” do not look too stringent for new researchers. They should not be. They are merely part of doing good and fun research. New researchers should give it some time and enjoy the process of knowledge creation. By doing research one day at a time, you will see that this academic language will become yours in no time.
I look forward to seeing you, my dear service friends, at a conference this summer.
Yany Grégoire
Chair Omer DeSerres in Retailing at HEC Montréal
HEC Montreal, Canada
Photo: https://www.britannica.com/science/acid
I rarely comment, but i did some searching and wound up here Three “Acid Tests” to
Evaluate Youur Research – SERVSIG. And I actually do have 2 questions for you if
you tend not too mind. Is it simply me oor does it look as if
like some of the responses look as if they are left byy braqin deadd
folks? 😛 And, if you are posting at other places, I would like to keep
up with anything fresh you have to post. Could you lis of every one
of all your community pages like your linkedin profile,
Facebook page or twitter feed?
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