Measuring the Impacts of Consumers’ Demographics on Spending Propensity and Expenses on Firms Profitability using Market Basket Optimization Model

Zahidul Karim, Sumaya Fatema Binte Shahid, Shahpar Shams

Abstract


Market Basket Analysis (MBA) and its importance in selecting the right basket of goods have obtained considerable interest among the managers and executives of many retail stores. The present study has explored the literature gap in measuring the determinants for managing the optimum market basket of goods for consumers. The study found that some customer demographic and firm specific expense variables provide important prediction power to measure the customer spending propensity and firms’ profitability respectively.  We have used two different market basket optimization models to measure and analyze the results. The results show significant influence of age and advertising expenses on consumers’ propensity to expense and firms’ profitability respectively. The study has used two regression models to analyze the market basket using WarpPLS and R Software. Finally, the study suggests for future study to measure the impacts of consumer behavioral and psychological aspects and industry types on the spending propensity and firms’ profitability through market basket analysis.

Keywords: Market Basket, Consumer Demographics, Spending Propensity, Firms’ Profitability.


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References


Aiello, L. M., Quercia, D., Schifanella, R., & Del Prete, L. (2020). Tesco Grocery 1.0, a large-scale dataset of grocery purchases in London. Scientific data, 7(1), 1-11.

Aguinis, H., Forcum, L. E., & Joo, H. (2013). Using market basket analysis in management research. Journal of Management, 39(7), 1799-1824.

Boztuğ, Y., & Reutterer, T. (2008). A combined approach for segment-specific market basket analysis. European Journal of Operational Research, 187(1), 294-312.

Brin, S., Motwani, R., Ullman, J. D., & Tsur, S. (1997, June). Dynamic itemset counting and implication rules for market basket data. In Proceedings of the 1997 ACM SIGMOD international conference on Management of data (pp. 255-264).

Cavique, L. (2007). A scalable algorithm for the market basket analysis. Journal of Retailing and Consumer Services, 14(6), 400-407.

Griva, A., Bardaki, C., Pramatari, K., & Papakiriakopoulos, D. (2018). Retail business analytics: Customer visit segmentation using market basket data. Expert Systems with Applications, 100, 1-16.

Hwang, W. Y. (2020). Variable selection for collaborative filtering with market basket data. International Transactions in Operational Research, 27(6), 3167-3177.

Kamakura, W. A. (2012). Sequential market basket analysis. Marketing Letters, 23(3), 505-516.

Kaggle (2022). U.S. Supermarket Data. A United States supermarket dataset for marketing analysis purposes. Retrieve from https://www.kaggle.com/datasets/sindraanthony9985/marketing-data-for-a-supermarket-in-united-states

Kim, H. K., Kim, J. K., & Chen, Q. Y. (2012). A product network analysis for extending the market basket analysis. Expert Systems with Applications, 39(8), 7403-7410.

Kock, N. (2021). WarpPLS User Manual: Version 7.0. Laredo, TX: ScriptWarp Systems.

Mamiya, H., Moodie, E. E., & Buckeridge, D. L. (2017). A novel application of point-of-sales grocery transaction data to enhance community nutrition monitoring. In AMIA Annual Symposium Proceedings (Vol. 2017, p. 1253). American Medical Informatics Association.

Mild, A., & Reutterer, T. (2003). An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data. Journal of Retailing and consumer Services, 10(3), 123-133.

Rahman, M., Rodríguez-Serrano, M. Á., & Lambkin, M. (2020). Advertising efficiency and profitability: evidence from the pharmaceutical industry. Industrial Marketing Management, 89, 619-629.

Russell, G. J., & Petersen, A. (2000). Analysis of cross category dependence in market basket selection. Journal of Retailing, 76(3), 367-392.

Walters, R. G., & Jamil, M. (2003). Exploring the relationships between shopping trip type, purchases of products on promotion, and shopping basket profit. Journal of Business Research, 56(1), 17-29.


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