Designing a satisfaction model for service re-creation with an emphasis on brand loyalty in the banking industry; A case study of the Bank of Agriculture

The current research was carried out with the aim of identifying the components of satisfaction from service re-creation with an emphasis on brand loyalty in the banking industry and is in the scope of developmental research. A mixed method was used in this research. The statistical population in the qualitative section is the experts and managers of Iran's banking industry, of which ۱۵ people were selected in a non-random way. The statistical population in the quantitative part includes all customers of the Agricultural Bank in Tehran (unlimited population). Based on this, a sample of ۳۸۴ people is selected using Morgan's table. The main tool for data collection is a semi-structured in-depth interview and a researcher-made questionnaire. Qualitative data analysis was done with the method of data base theory using MAXQDA software and in the quantitative part with partial least squares method. Based on the paradigm model obtained in this research, the components related to service recovery satisfaction in six categories of causal factors (customer-oriented, brand image, communication, evaluation of correct performance and growth and development of services), background conditions (brand culture), central phenomenon (satisfaction with re-creation), strategies (organization strategy, marketing, and advertising), intervening conditions (customer anger and environmental factors) and consequences (brand loyalty, brand trust, customer satisfaction and profit increase) were identified. The results of the quantitative part of the research showed that the model proposed in this research is valid. Based on the obtained results, it can be concluded that the level of satisfaction and loyalty of banking customers can be improved by focusing on the components identified in relation to service regeneration.

Keywords:

service re-creation , brand loyalty , Banking Industry , nonlinear analysis , PLS