CUSTOMER SATISFACTION AND BEHAVIOUR AT RETAIL OUTLETS: AN ADAPTIVE FUZZY REGRESSION MODEL WITH LINGO BASED ANALYSIS

被引:0
作者
Rizwanullah, Mohd [1 ]
Abunar, Salah [2 ]
Qazi, Sayeeduzzafar [2 ]
机构
[1] Manipal Univ, Jaipur, Rajasthan, India
[2] Univ Business & Technol, Jeddah, Saudi Arabia
来源
MARKETING AND MANAGEMENT OF INNOVATIONS | 2020年 / 02期
关键词
heuristic; fuzzy; Markov process; retail customer; customer behaviour; LINGO; ISM; NEURAL-NETWORK; PERFORMANCE;
D O I
10.21272/mmi.2020.2-20
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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 understudy. 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.
引用
收藏
页码:275 / 285
页数:11
相关论文
共 23 条
[1]  
Albinsson M., 2004, MANAGING SERVICE QUA, V1
[2]  
[Anonymous], 2004, INT J CONT HOSPITALI
[3]   Investigating Key Attributes in Experience and Satisfaction of Hotel Customer Using Online Review Data [J].
Ban, Hyun-Jeong ;
Choi, Hayeon ;
Choi, Eun-Kyong ;
Lee, Sanghyeop ;
Kim, Hak-Seon .
SUSTAINABILITY, 2019, 11 (23)
[4]  
BerleIs K., 1999, QUALITATIVE CO PERFO
[5]   NEURAL NETWORKS AND THEIR APPLICATIONS [J].
BISHOP, CM .
REVIEW OF SCIENTIFIC INSTRUMENTS, 1994, 65 (06) :1803-1832
[6]   Back-propagation neural network based importance-performance analysis for determining critical service attributes [J].
Deng, Wei-Jaw ;
Chen, Wen-Chin ;
Pei, Wen .
EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (02) :1115-1125
[7]  
Foster D.C., 1997, MARKETING NEWS, V31, P17
[8]   A sales forecasting system based on fuzzy neural network with initial weights generated by genetic algorithm [J].
Kuo, RJ .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2001, 129 (03) :496-517
[9]   A methodology of generating customer satisfaction models for new product development using a neuro-fuzzy approach [J].
Kwong, C. K. ;
Wong, T. C. ;
Chan, K. Y. .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (08) :11262-11270
[10]   Logistic regression analysis of customer satisfaction data [J].
Lawson, Cathy ;
Montgomery, Douglas C. .
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2006, 22 (08) :971-984