Developing an analytical model to predict customer churn for customer satisfaction (cs) and customer loyalty (cl) with respect to automobile after sales service centres (aassc)

By: Contributor(s): Material type: BookBookLanguage: en. Publication details: Bangalore : Indian institute of science , 2022 .Description: xvi, 193p. e-Thesis col. ill. ; 29.1 cm * 20. 5 cm 4.330MbDissertation: PhD; 2022; Management studiesSubject(s): DDC classification:
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Online resources: Dissertation note: PhD; 2022; Management studies Summary: Customer Satisfaction has always been a key to success for any automobile after sales service centre (AASSC). To retain customer satisfaction (CS) and customer loyalty (CL), it is crucial for any AASSC to track the important factors and its measurement variables that influence CS and CL. From the literature, it was identified that many research studies considered only Service Quality as the factor influencing CS and CL. Further, a few studies have considered different combinations of the other factors: Belief, Brand Awareness, Product Quality, Economic Service, Convenient service, Service Capability, and Warranty Handling for understating its influence on CS and CL at AASSC. However, it appears from the analysis of the literature that there is no study considers all the unique factors mentioned in the literature together to understand its influence on CS and CL at AASSC. Moreover, every AASSC has been striving hard in identifying and prioritising the factors that have been given importance by the customers during and after services are provided. Overall, it appears from the analysis of the literature that (a) identifying all the unique factors and its measurement variables, which are expected to strongly influence CS and CL, (b) constructing a structural / conceptual model, considering the identified factors and its measurement variable to predict the customer churning from AASSC, and (c) prioritizing the identified factors are not dealt in the literature in general, and particularly for Indian AASSC. Accordingly, this study addresses 4 research objectives : (i) To identify the factors and its measurement variables which are influencing CS and CL for AASSC and to develop a conceptual framework for CS-CL-AASSC using a rational approach : Total Interpretive Structural Modelling (TISM); (ii) To validate and finalize the proposed conceptual framework for CS-CL-AASSC; (iii) To prioritize and rank the factors involved in the proposed conceptual framework for CS-CL-AASSC, from the customer perspective, using MCDM methods : Analytical Hierarchy Process (AHP) and Best Worst Method (BWM); (iv) To develop an analytical model using the identified factors to predict the customer churn for AASSC. From the analysis of the literature, 10 unique factors are identified, and 2 new factors are proposed from the researcher’s perspective considering their importance. For measuring these factors, 53 measurement variables are identified from the literature review, researcher's perspective and from the adaption of Caselet approach. Considering the identified factors and its measurement variables, a structural / conceptual model is developed for CS-CL-AASSC following the TISM approach. For validating the proposed conceptual framework, a descriptive research method, particularly the survey method is carried out to collect the opinion from the customers regarding the services provided by AASSC. The questionnaire developed is circulated among 226 and 228 Hyundai car owners/customers in Bangalore and Chennai based Hyundai AASSC respectively and collected the required data (called as BSC-data and CSC-data respectively). Each of the BSC-data and CSC-data is appropriately given as input to simple hypothesis testing through Structural Equation Modelling (SEM) approach and validated each of the conceptual model constructed for Bangalore and Chennai based Hyundai AASSC. Based on the validation processes, a few insignificant measurement variables for a few factors associated with each of the conceptual model constructed for Bangalore and Chennai based Hyundai AASSC are removed, and a final conceptual model are derived. Further, by applying two MCDM methods: AHP and BWM, independently, the 10 factors considered in each of the proposed conceptual models are prioritized. Based on the processes of prioritizing the factors it is observed that the 3 factors: Product Quality, Service Quality, and Belief are found to be the most important factors for CS-CL-AASSC. Considering these 3 factors as a key input, this study developed an analytical model for predicting customer churn for each of the Bangalore and Chennai based Hyundai AASSC. This analytical model would provide insight for the service advisor to identify the profile of the customers who would be satisfied at AASSC. In addition, an advisor at AASSC can identify the important factors for AASSC from the customer's perspective. Although the research has accomplished its planned objectives, there are certain limitations such as (i) The survey conducted in this study considers only passenger vehicles and not commercial vehicles, (ii) The required data are collected only from respondents in tier 1 cities and not from the tier 2 and tier 3 cities, and (iii) For demonstrating the workability of the MCDM methods for prioritizing the factors, the required data is collected only from six customers. In addition to addressing each of these limitations as immediate future research in this area, one can think of either modifying the proposed conceptual model or proposing a new conceptual model for CS-CL-AASSC focusing on (a) Battery Cars, and (b) two-wheelers as further research issues in this area of research.
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PhD; 2022; Management studies

Customer Satisfaction has always been a key to success for any automobile after sales service centre (AASSC). To retain customer satisfaction (CS) and customer loyalty (CL), it is crucial for any AASSC to track the important factors and its measurement variables that influence CS and CL. From the literature, it was identified that many research studies considered only Service Quality as the factor influencing CS and CL. Further, a few studies have considered different combinations of the other factors: Belief, Brand Awareness, Product Quality, Economic Service, Convenient service, Service Capability, and Warranty Handling for understating its influence on CS and CL at AASSC. However, it appears from the analysis of the literature that there is no study considers all the unique factors mentioned in the literature together to understand its influence on CS and CL at AASSC. Moreover, every AASSC has been striving hard in identifying and prioritising the factors that have been given importance by the customers during and after services are provided. Overall, it appears from the analysis of the literature that (a) identifying all the unique factors and its measurement variables, which are expected to strongly influence CS and CL, (b) constructing a structural / conceptual model, considering the identified factors and its measurement variable to predict the customer churning from AASSC, and (c) prioritizing the identified factors are not dealt in the literature in general, and particularly for Indian AASSC. Accordingly, this study addresses 4 research objectives : (i) To identify the factors and its measurement variables which are influencing CS and CL for AASSC and to develop a conceptual framework for CS-CL-AASSC using a rational approach : Total Interpretive Structural Modelling (TISM); (ii) To validate and finalize the proposed conceptual framework for CS-CL-AASSC; (iii) To prioritize and rank the factors involved in the proposed conceptual framework for CS-CL-AASSC, from the customer perspective, using MCDM methods : Analytical Hierarchy Process (AHP) and Best Worst Method (BWM); (iv) To develop an analytical model using the identified factors to predict the customer churn for AASSC. From the analysis of the literature, 10 unique factors are identified, and 2 new factors are proposed from the researcher’s perspective considering their importance. For measuring these factors, 53 measurement variables are identified from the literature review, researcher's perspective and from the adaption of Caselet approach. Considering the identified factors and its measurement variables, a structural / conceptual model is developed for CS-CL-AASSC following the TISM approach. For validating the proposed conceptual framework, a descriptive research method, particularly the survey method is carried out to collect the opinion from the customers regarding the services provided by AASSC. The questionnaire developed is circulated among 226 and 228 Hyundai car owners/customers in Bangalore and Chennai based Hyundai AASSC respectively and collected the required data (called as BSC-data and CSC-data respectively). Each of the BSC-data and CSC-data is appropriately given as input to simple hypothesis testing through Structural Equation Modelling (SEM) approach and validated each of the conceptual model constructed for Bangalore and Chennai based Hyundai AASSC. Based on the validation processes, a few insignificant measurement variables for a few factors associated with each of the conceptual model constructed for Bangalore and Chennai based Hyundai AASSC are removed, and a final conceptual model are derived. Further, by applying two MCDM methods: AHP and BWM, independently, the 10 factors considered in each of the proposed conceptual models are prioritized. Based on the processes of prioritizing the factors it is observed that the 3 factors: Product Quality, Service Quality, and Belief are found to be the most important factors for CS-CL-AASSC. Considering these 3 factors as a key input, this study developed an analytical model for predicting customer churn for each of the Bangalore and Chennai based Hyundai AASSC. This analytical model would provide insight for the service advisor to identify the profile of the customers who would be satisfied at AASSC. In addition, an advisor at AASSC can identify the important factors for AASSC from the customer's perspective. Although the research has accomplished its planned objectives, there are certain limitations such as (i) The survey conducted in this study considers only passenger vehicles and not commercial vehicles, (ii) The required data are collected only from respondents in tier 1 cities and not from the tier 2 and tier 3 cities, and (iii) For demonstrating the workability of the MCDM methods for prioritizing the factors, the required data is collected only from six customers. In addition to addressing each of these limitations as immediate future research in this area, one can think of either modifying the proposed conceptual model or proposing a new conceptual model for CS-CL-AASSC focusing on (a) Battery Cars, and (b) two-wheelers as further research issues in this area of research.

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