Developing a Neuro-Fuzzy Inference System to Assess the Appropriateness of Retail Types with Product Features

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Marketing, Faculty of Management, University of Tehran, Farabi College, Qom, Iran.

2 Assistant Prof., Faculty of Management, University of Tehran, Farabi College, Qom, Iran.

Abstract

Objective: Retailers are one of the most fundamental parts of the supply and distribution chains. They have different explicit and implicit distinguishing features. These features can be considered as marketing or competitive tools that provide managers with useful information so that they can select their marketing combination accordingly. Understanding of their features and purchasing behaviors can significantly affect the companies’ sales. Regarding the retailers’ different intentions to buy a product, producers should inspect the appropriateness of the product features in different retail formats. This research aimed to evaluate the appropriateness of retail format with different product features in Iran.
 
Methodology: At first, a theoretical foundation of different product features and retail format was reviewed, and the factors affecting the choice of the product by the retail format were extracted. Then, in-depth interviews were conducted with 12 experts and store managers, and the collected data were analyzed using the content analysis method. At the interview stage, the expert and the individuals were selected for the interview if they had at least one of the criteria influencing the accurate answers. Finally, an adaptive neuro-fuzzy inference system was developed by MATLAB software to assess the appropriateness of the retail format with product features.
 
Findings: The findings of the qualitative content analysis stage showed the four characteristics of appearance, intrinsic, competitive, and price as the system inputs; in the inference stage, the findings showed the difference in the appropriateness of each type of retail with these characteristics. The results also showed that product characteristics play an important role in determining and deciding on the retail format and hence, each format will need to be aligned with the characteristics of its own appropriate product.
 
Conclusion: The results showed that the appearance is appropriate for convenience retailers, the competitive and intrinsic feature for supermarkets, the intrinsic and price feature for the flea market format, the competitive and price for hypermarkets, wholesale, as well as discount retailers, the appearance and intrinsic feature for specialty retailers, and finally the appearance and price features are appropriate for sales machine to increase the probability of sales. Producers can start producing the goods after they considered the features of the products which are accepted by the desired stores and paid attention to the products criteria which are suggested by the retail format and ultimately sell the product. This might make it easier for the products to enter a store and be placed on the shelves; in addition, because the store managers are regarded as one of our desired groups that are responsible to choose the product features and besides these managers choose the features based on the target customers’ opinions, ultimately the product circulation in the store shelves will increase.

Keywords


Afshari, H., & Benam, F. H. (2011). Retail logistics. Logistics operations and management. Concepts and models, 267-289.
Andreti, J., Zhafira, N. H., Akmal, S. S., & Kumar, S. (2013). The analysis of product, price, place, promotion and service quality on customers’ buying decision of convenience store: A survey of young adult in Bekasi, West Java, Indonesia. International Journal of Advances in Management and Economics2(6), 72-78.
Ataman, B., & Ülengin, B. (2003). A note on the effect of brand image on sales. Journal of Product & Brand Management, 12(4), 237-250.
Azizi, SH., & Ghasemi Naghibdehi, A. (2020). The Analysis of Factors Affecting New Product Categorization (Case Study: Lactivia Drinking-Yogurt). Journal of Business Management, 12(1), 243- 259. (in Persian)
Behmanesh, M., & Mohammadi, M. (2016). Trained self-feedback Adaptive neural-fuzzy inference system with colonial competition algorithm to predict turbulent time series. Computational Intelligence in Electrical Engineering (Intelligent Systems in Electrical Engineering), 7(4), 13-30. (in Persian)
Bishop Gagliano, K., & Hathcote, J. (1994). Customer expectations and perceptions of service quality in retail apparel specialty stores. Journal of Services Marketing, 8(1), 60-69.
Botchkarev, A. (2018). Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology. arXiv preprint arXiv:1809.03006.
Carpenter, J. M., & Brosdahl, D. J. (2011). Exploring retail format choice among US males. International Journal of Retail & Distribution Management, 39(12), 886-898.
Cascio, W. F. (2006). Decency means more than “always low prices”: A comparison of Costco to Wal-Mart's Sam's club. Academy of Management perspectives, 20(3), 26-37.
Denstadli, J. M., Lines, R., & Grønhaug, K. (2005). First mover advantages in the discount grocery industry. European Journal of Marketing, 39(7/8), 872-884.
Ellickson, P. B. (2016). The evolution of the supermarket industry: from A & P to Walmart. In Handbook on the Economics of Retailing and Distribution. Edward Elgar Publishing.
Gable, M., Topol, M. T., Lala, V., & Fiorito, S. S. (2008). Differing perceptions of category killers and discount stores. International Journal of Retail & Distribution Management, 36(10), 780-811.
Godey, B., & Lai, C. (2011). Construction of international brand portfolios: impact on local brands. Journal of Product & Brand Management, 20(5), 402-407.
Hamidizadeh, M.R., Akhavan, M., & Kazemi, A. (2019). Identifying All the Types of Consumption Experiences and Their Impact on Perceptions of Prices. Journal of Business Management, 11(3), 585-608. (in Persian)
Han, S., Gupta, S., & Lehmann, D. R. (2001). Consumer price sensitivity and price thresholds. Journal of Retailing, 77(4), 435-456.
Hassan, H., Bakar Sade, A., & Sabbir Rahman, M. (2013). Malaysian hypermarket retailing development and expansion. International Journal of Retail & Distribution Management, 41(8), 584-595.
Hill, A. V. (2012). The encyclopedia of operations management: a field manual and glossary of operations management terms and concepts. FT Press.
Hökelekli, G., Lamey, L., & Verboven, F. (2017). The battle of traditional retailers versus discounters: The role of PL tiers. Journal of Retailing and Consumer Services, 39, 11-22.
Huddleston, P., Whipple, J., Nye Mattick, R., & Jung Lee, S. (2009). Customer satisfaction in food retailing: comparing specialty and conventional grocery stores. International Journal of Retail & Distribution Management, 37(1), 63-80.
Jang, J. S. (1993). ANFIS: adaptive-network-based fuzzy inference system. IEEE transactions on systems, man, and cybernetics23(3), 665-685.
Kauppinen-Räisänen, H., & Luomala, H. T. (2010). Exploring consumers' product-specific colour meanings. Qualitative Market Research: An International Journal, 13(3), 287-308.
Kearney, A. T. (2004). How many Supply Chain do you need? –Matching Supply Chain Strategies to products and customers. AT Kearney.
Kim, S. H., & Choi, S. C. (2007). The role of warehouse club membership fee in retail competition. Journal of Retailing, 83(2), 171-181.
Kişi, Ö. (2010). River suspended sediment concentration modeling using a neural differential evolution approach. Journal of Hydrology389(1-2), 227-235.
Krueger, E., Prior, S. A., Kurtener, D., Rogers, H. H., & Runion, G. B. (2011). Characterizing root distribution with adaptive neuro-fuzzy analysis. International Agrophysics25(1), 93-96.
Langenberg, K. U., Seifert, R. W., & Tancrez, J. S. (2012). Aligning supply chain portfolios with product portfolios. International Journal of Production Economics, 135(1), 500-513.
Mason, L. P. I., & Sprankle, D. A. (2011). U.S. Patent No. 7,988,015. Washington, DC: U.S. Patent and Trademark Office.
McBratney, A. B., & Odeh, I. O. (1997). Application of fuzzy sets in soil science: fuzzy logic, fuzzy measurements and fuzzy decisions. Geoderma77(2-4), 85-113.
Miller, N. J., Campbell, J. R., Littrell, M. A., & Travnicek, D. (2005). Instrument development and evaluation for measuring USA apparel product design attributes. Journal of Fashion Marketing and Management: An International Journal, 9(1), 54-70.
Mishra, M. S. (2007). The consumption pattern of Indian Consumers: choice between traditional and organized Retail. Available at SSRN 994238.
Mizuno, T., Toriyama, M., Terano, T., & Takayasu, M. (2008). Pareto law of the expenditure of a person in convenience stores. Physica A: Statistical mechanics and its applications, 387(15), 3931-3935.
O’Regan, N. (2002). Market share: the conduit to future success?. European Business Review, 14(4), 287-293.
Petrescu, M., & Bhatli, D. (2013). Consumer behavior in flea markets and marketing to the Bottom of the Pyramid. Journal of Management Research13(1), 55-63.
Rastgar, A., & Shahriari, M. (2018). From Shopping Centers’ Image to Purchase Intention with Perceived Value, Customer Satisfaction and Customer Preference (Case Study: Shopping Centers in Semnan). Journal of Business Management, 10(3), 643-658. (in Persian)
Saeida Ardakani, S., Saneian, Z.S., & Menati, N. (2019). Measurement of the Factors Affecting the Tendency of Iranian Consumers to Buy and Consume Iranian Goods. Journal of Business Management, 11(2), 241-258. (in Persian)
Shamser, R. (2012). The Importance of product attributes influencing purchase decision: a comparative study between FMCG laundry soaps. DU Journal of Marketing15(2), 55-63.
Sharkey, J. R., Dean, W. R., & Nalty, C. (2012). Convenience stores and the marketing of foods and beverages through product assortment. American journal of preventive medicine43(3), S109-S115.
Sherman, E., McCrohan, K., & Smith, J. D. (1985). Informal retailing: an analysis of products, attitudes, and expectations. ACR North American Advances.
Tripathi, A., & Pandey, N. (2018). Does impact of price endings differ for the non-green and green products? Role of product categories and price levels. Journal of Consumer Marketing, 35(2), 143-156.
Ullman, J. B. (2006). Structural equation modeling: Reviewing the basics and moving forward. Journal of personality assessment, 87(1), 35-50.
Wadhwa, S., & Fuloria, M. C. (2004). A practitioner's approach to responsive supply planning. Studies in Informatics and Control, 13(3), 191-198.
Zhao, X., Niu, R. H., & Castillo, I. (2010). Selecting distribution channel strategies for non-profit organizations. European Journal of Marketing, 44(7/8), 972-996.