Abstract

Increasing rivalry for-profit or non-profit is pushing companies to devote more and more attention to pleasing consumers with excellent quality customer services. This study aims to develop a model to analyse customer behaviour in a retail store and provide accurate inference for decision making. Another critical objective for this research work is the adaptation of the faceted form of neuro-response, which is substituted by the Adaptive Fuzzy Logistic Regression Model (AFLRM). AFLRM has resulting benefits over Neuro-surface and Mean Demand Heuristic methods. A sample of 100 customers who visited or walked in the retails was used as a sample. Other than neuro-response surfaces (NRSM) and The Mean Demand Heuristic models (MDSM), the present study has accustomed a generalized form known as Adaptive Fuzzy Linear Regression Model (AFLRM) to deliver the benchmark for former models and give the highest level of accuracy for future behaviour of a customer. LINGO based Markovian analysis has also been used with the above model to understand the behaviour of the system under study. The significance of service and product attributes is implicitly derived via the fuzzy regression model for customer satisfaction measurement. It is observed that the critical gap between the quality of product and services and Customer Satisfaction is Product/Service Satisfaction, Motivation and Buying Experience, and Credibility and Security. The authors’ finding indicates that the effort of listening to the customer’s voice should be more critical. Result analysis based on computational results concerning the questionnaire for measuring the customer behaviour and the system validates the model under study. Appropriate, useful with reliable action plans for every critical product and service aspect can be developed by applying the adaptive regression methodology to control the quality of service or managing the customer satisfaction, thereby providing executives with a competitive gain. Also explored the behaviour of the system, i.e., whether the customer will move to the new retail outlets or they will remain in the same state by using the LINGO based software program model.

Keywords: heuristic, fuzzy, Markov process, retail customer, customer behaviour, LINGO, ISM.

JEL Classification: D2, Q33, M31.

Cite as: Rizwanullah, M., Abounar, S., & Qazi, S. (2020). Customer satisfaction and behaviour at retail outlets: an Adaptive Fuzzy Regression Model with LINGO based analysis. Marketing and Management of Innovations, 2, 275-285. https://doi.org/10.21272/mmi.2020.2-20

This work is licensed under a Creative Commons Attribution 4.0 International License

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