A Different Insight on Retailing and Retailing Research (Article Critique)
- Vanessa Lam
- Mar 31, 2023
- 4 min read
Updated: Apr 22, 2023
Paper Title | Retailing and Retailing Research In the Age of Big Data Analytics |
Author | Marnik G. Dekimpe |
Year | 28 September 2019 |
Journal | International Journal of Research in Marketing 37 (2020) 3-14 |
Journal Homepage | |
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Summary of the Paper
In this article, the author presented that the retail sector has vast and abundance of big data available and often used by analyst to paint a beautiful picture on all the benefits one can envision from the use of the data. The author said that many analysts claimed in industry reports that data analytics from the retail sector are promising and game changing. However, he brought up that data proliferation had already reached near unsustainable levels. The author observed that data collected from the retail sector is at the centre of a storm of big data opportunities and challenges, now is the big data revolution age. He listed down the opportunities and challenges for 5 groups of people in relation to retailing.
Author’s Findings:
Retail Managers
1. Big data offer the retailers numerous new opportunities to create value.
2. Suggest that retailers look beyond the hype for false impression of success frequency.
3. There is a clear need for academic research.
Retail Researchers
1. Big data revolution benefits the retail researchers.
2. However, there might be more difficult balance between technical complexity and
managerial relevance.
3. It is getting more difficult to listen to data and how to remain relevant to practice.
Policy Makers
1. How policy makers regulate consumer privacy issues.
2. Reducing data divide by considering smaller businesses that do not have the means to
invest in big data.
Investors
1. More work needs to be done to assess the business instead of depending on making data
driven decision.
Retail Educators
1. Shortage of training of personnels in many retail organisations.
2. With new retail-specific courses, educators need to balance the topics on algorithms
and data analysis as with domain-specific insights.
His conclusion is that more work needs to be done to achieve more value from big data and reminded all not to be blinded by the one side of the fanciful research report, but to be sensitive to the relevance and the value of the big data.
Comment:
The problem statement was not clearly stated on the title. It has a certain level of agreement that the issues are on the new age of big data analytics, however the article needs to be read a few rounds to catch the essence of the problem statement about big data being at the centre of a storm and the suggestions of opportunities and challenges in the retail sector big data.
Review of Literature
The author cited 4 clear reviews of literature to start the argument in the introduction segment on how analysts like to present the beauty of the retail sector for all the benefits that one can envision from the use of big data. After which, he made a reverse by citing 6 clear reviews of literature supporting the hindsight of the study that despite of heavy investment in big data, the return of investment was not as expected or desired, which is good for the readers to understand the pros and cons.
Comment:
The author whose work focused mostly on retailing-related studies over the decades, provided many supporting reviews of literature in the retail scene from both sides of the coin, allowing the readers to have full understanding on various perspectives to help in making the right decisions in applying big data in each field.
Originality
There was originality in this paper as it can be seen the continuation from the author’s past articles and journals. (Dekimpe & Geyskens, Retailing Research in Rapidly Changing Times: On the Danger of Being Leapfrogged by Practice, 2019 March) and (Dekimpe & Morrison, A Modeling Framework for Analyzing Retail Stores Duration, 1991). The thoughts and perspective on retail sector remain unchanged.
Method
The author did not specify his method of findings, instead claimed that this paper emerged from talks during the occasions of his 2016 European Marketing Academy Distinguished Marketing Scholar Award and his honorary doctorate at the University of Hamburg in 2018. Various discussions throughout the years with the authors of articles and books as referenced in this paper and the co-authors of the author’s previous retail projects have contributed to this paper greatly.
Comment:
The methods used for this paper were clearly explained, and that secondary data analysis and archival study were applied. The author has given more than 90 references to support his argument. However, there was no concrete evidence of the discussions or record of them as claimed by him.
Quality of Presentation
The article was well presented and structured. In this article, the readers were first brought onto a journey of understanding the fascinating and fertile ground of the retailing sector. Then, seamlessly brought the readers on weighing the pros and cons in big data for the various data users such as retail managers, retail researchers, policy makers, investors, and retail educators.
However, in Table 1, the author presented an illustrative research agenda on micro-targeting opportunities that identified 16 big data levers along 5 functional domains. Though it is a detailed table to identify the opportunities, however I do not see the relation to the title of the paper, nor complement to the subject of this article.
Conclusion
Overall, I find this paper genuine and sincere. It gave me a different insight of retailing and retailing research. It has convinced me to see big data differently and beyond what it is on paper. It has taught me to smell for opportunities to create value and challenges to avoid pitfall. I have read two similar articles on big data for the retail sector by (Bradlow, Gangwar, Kopalle, & Voleti, 2017) (1) and (McAfee & Brynjolfsson, 2012) (2), I still find this article comprehensive and educational.
References
Dekimpe, M. G., & Geyskens, I. (2019 March). Retailing Research in Rapidly Changing Times: On the Danger of Being Leapfrogged by Practice. Journal of Retailing, 95 (1), 6-9.
Dekimpe, M. G., & Morrison, D. G. (n.d.).
Dekimpe, M. G., & Morrison, D. G. (1991). A Modeling Framework for Analyzing Retail Stores Duration. Journal of Retailing, 67(1), 68.
McAfee, A., & Brynjolfsson, E. (2012). Big Data: The management revolution . Harvard Business Review (Oct), 1-9.
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