Internal benchmarking in retailing with DEA and GIS: the case of a loyalty-oriented supermarket chain
Abstract
Data Envelopment Analysis (DEA) is a relative measure of efficiency applied to a set of decision units and is being used more and more frequently in the supermarket sector. Nonetheless, given how strongly the sector’s financials depend on demand, companies need to combine this measurement with trade area information to best manage corporate efficiency. In this paper, the proposal consists of integrating DEA with a clearly articulated, structural typology so that supermarkets, based on their particular characteristics, can determine which variables are most critical for improving their efficiency. This methodology has been validated in the case of one of Spain’s five largest supermarket chains. A principal component analysis and a classification analysis were carried out on a series of internal management variables from 61 locations for which DEA had been used to calculate efficiency and to which multiple trade area variables were added using GIS. Some of them are related to the loyalty scheme membership programme. These latter variables described the implantation of the loyalty scheme member programme and were revealed as key elements for the efficiency of the supermarket. This methodology provides marketing profiles that are more adapted to local circumstances, thus allowing companies to set better internal benchmarking objectives.
Keyword : efficiency, Data Envelopment Analysis (DEA), Geographical Information Systems (GIS), multivariate analysis, benchmarking, trade area, geomarketing
How to Cite
Baviera-Puig, A., Baviera, T., Buitrago-Vera, J., & Escribá-Pérez, C. (2020). Internal benchmarking in retailing with DEA and GIS: the case of a loyalty-oriented supermarket chain. Journal of Business Economics and Management, 21(4), 1035-1057. https://doi.org/10.3846/jbem.2020.12393
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
Chaudhuri, M., Voorhees, C. M., & Beck, J. M. (2019). The effects of loyalty program introduction and design on short- and long-term sales and gross profits. Journal of the Academy of Marketing Science, 47(4), 640–658. https://doi.org/10.1007/s11747-019-00652-y
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Donthu, N., & Yoo, B. (1998). Retail productivity assessment using data envelopment analysis. Journal of Retailing, 74(1), 89–105. https://doi.org/10.1016/S0022-4359(99)80089-X
Donthu, N., Hershberger, E. K., & Osmonbekov, T. (2005). Benchmarking marketing productivity using data envelopment analysis. Journal of Business Research, 58(11), 1474–1482. https://doi.org/10.1016/j.jbusres.2004.05.007
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Emrouznejad, A., & Yang, G. L. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 61, 4–8. https://doi.org/10.1016/j.seps.2017.01.008
Felício, J. A., & Galindo, M. P. (2015). Family characteristics and governance of small and medium-sized family firms. Journal of Business Economics and Management, 16(6), 1069–1084. https://doi.org/10.3846/16111699.2012.747446
Gandhi, A., & Shankar, R. (2014). Efficiency measurement of Indian retailers using Data Envelopment Analysis. International Journal of Retail and Distribution Management, 42(6), 500–520. https://doi.org/10.1108/IJRDM-10-2012-0094
Goldman, A. (1992). Evaluating the performance of the Japanese distribution system. Journal of Retailing, 68(1), 11–39.
Goss, J. (1995). We know who you are and we know where you live: The instrumental rationality of geodemographic systems. Economic Geography, 71(2), 171–198. https://doi.org/10.2307/144357
Grewal, D., Levy, M., Mehrotra, A., & Sharma, A. (1999). Planning merchandising decisions to account for regional and product assortment differences. Journal of Retailing, 75(3), 405–424. https://doi.org/10.1016/S0022-4359(99)00015-9
Hanousek, J., Kocenda, E., & Shamsur, A. (2015). Corporate efficiency in Europe. Journal of Corporate Finance, 32, 24–40. https://doi.org/10.1016/j.jcorpfin.2015.03.003
Harris, R., Sleight, P., & Webber, R. (2005). Geodemographics, GIS and neighbourhood targeting. John Wiley & Sons.
Herranz, R., Estévez, P., Oliva, M., & Dé, R. (2017). Leveraging financial management performance of the Spanish aerospace manufacturing value chain. Journal of Business Economics and Management, 18(5), 1005–1022. https://doi.org/10.3846/16111699.2017.1357655
Ingene, C. A. (1984). Productivity and functional shifting in spatial retailing: Private and social perspectives. Journal of Retailing, 60, 15–36.
Kang, J., Alejandro, T. B., & Groza, M. D. (2015). Customer-company identification and the effectiveness of loyalty programs. Journal of Business Research, 68(2), 464–471. https://doi.org/10.1016/j.jbusres.2014.06.002
Kato, A. (2015). Productivity and characteristics of firms: An application of a bootstrapped data envelopment analysis to Japanese firm-level data. Journal of Asia-Pacific Studies, 24, 145–159.
Kim, H-Y., Lee, J. Y., Choi, D., Wu, J., & Johnson, K. K. (2013). Perceived benefits of retail loyalty programs: Their effects on program loyalty and customer loyalty. Journal of Relationship Marketing, 12(2), 95–113. https://doi.org/10.1080/15332667.2013.794100
Kumar, V., & Petersen, J. A. (2005). Using a customer-level marketing strategy to enhance firm performance: A review of theoretical and empirical evidence. Journal of the Academy of Marketing Science, 33(4), 504–519. https://doi.org/10.1177/0092070305275857
Kumar, V., & Shah, D. (2004). Building and sustaining profitable customer loyalty for the 21st century. Journal of Retailing, 80(4), 317–329. https://doi.org/10.1016/j.jretai.2004.10.007
Lao, Y., & Liu, L. (2009). Performance evaluation of bus lines with data envelopment analysis and geographic information systems. Computers, Environment and Urban Systems, 33(4), 247–255. https://doi.org/10.1016/j.compenvurbsys.2009.01.005
Leenheer, J., Van Heerde, H. J., Bijmolt, T. H., & Smidts, A. (2007). Do loyalty programs really enhance behavioral loyalty? An empirical analysis accounting for self-selecting members. International Journal of Research in Marketing, 24(1), 31–47. https://doi.org/10.1016/j.ijresmar.2006.10.005
Lewis, H. F., & Sexton, T. R. (2004). Data envelopment analysis with reverse inputs and outputs. Journal of Productivity Analysis, 21, 113–132. https://doi.org/10.1023/B:PROD.0000016868.69586.b4
Li, Y., & Liu, L. (2012). Assessing the impact of retail location on store performance: A comparison of Wal-Mart and Kmart stores in Cincinnati. Applied Geography, 32(2), 591–600. https://doi.org/10.1016/j.apgeog.2011.07.006
López-Roldán, P. (1996). La construcción de tipologías: Metodologías de análisis. Papers, 48, 9–29. https://doi.org/10.5565/rev/papers.1811
López-Roldán, P., & Fachelli, S. (2015). Análisis de clasificación. In P. López-Roldán & S. Fachelli (Eds.), Metodología de la Investigación Social Cuantitativa (1a edición, versión 2). Bellaterra: Dipòsit Digital de Documents, Universitat Autónoma de Barcelona. http://ddd.uab.cat/record/142929
López-Roldán, P., & Fachelli, S. (2016). Análisis factorial. In P. López-Roldán & S. Fachelli (Eds.), Metodología de la Investigación Social Cuantitativa (1a edición, versión 3). Bellaterra: Dipòsit Digital de Documents, Universitat Autónoma de Barcelona. http://ddd.uab.cat/record/142928
Meyer-Waarden, L. (2007). The effects of loyalty programs on customer lifetime duration and share of wallet. Journal of Retailing, 83(2), 223–236. https://doi.org/10.1016/j.jretai.2007.01.002
Meyer-Waarden, L. (2008). The influence of loyalty programme membership on customer purchase behavior. European Journal of Marketing, 42(1/2), 87–114. https://doi.org/10.1108/03090560810840925
Meyer-Waarden, L., & Benavent, C. (2006). The impact of loyalty programmes on repeat purchase behaviour. Journal of Marketing Management, 22(1), 61–88. https://doi.org/10.1362/026725706776022308
Mimouni-Chaabane, A., & Volle, P. (2010). Perceived benefits of loyalty programs: Scale development and implications for relational strategies. Journal of Business Research, 63(1), 32–37. https://doi.org/10.1016/j.jbusres.2009.01.008
Moreno, J. (2010). Productivity growth of European retailers: A benchmarking approach. Journal of Economic Studies, 37(3), 288–313. https://doi.org/10.1108/01443581011061285
Mostafa, M. (2009). Benchmarking the US specialty retailers and food consumer store using data envelopment analysis. International Journal of Retail and Distribution Management, 37(8), 661–679. https://doi.org/10.1108/09590550910966178
Neves Bezerra de Melo, F. L., Sampaio, R. M. B., & Sampaio, L. M. B. (2018). Efficiency, productivity gains, and the size of Brazilian supermarkets. International Journal of Production Economics, 197, 99–111. https://doi.org/10.1016/j.ijpe.2017.12.016
Nielsen. (2018). Retailers database. Nielsen Company.
Nitkiewicz, T., Pachura, P., & Reid, N. (2014). An appraisal of regional intellectual capital performance using Data Envelopment Analysis. Applied Geography, 53, 246–257. https://doi.org/10.1016/j.apgeog.2014.06.011
Noordhoff, C., Pauwels, P., & Odekerken-Schröder, G. (2004). The effect of customer card programmes: A comparative study in Singapore and The Netherlands. International Journal of Service Industry Management, 15(4), 351–364. https://doi.org/10.1108/09564230410552040
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