Impact of service quality on customer loyalty: A multi-analytic approach using neural network
The purpose of this study is twofold, first to explore the relationships among service quality dimensions and customer loyalty in the life insurance sector. The second aim is to find the sequence of significant service dimensions in predicting customer loyalty. A total sample of 431 customers from t...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Ramanujan College, University of Delhi, Delhi, India
2022-12-01
|
| Series: | Ramanujan International Journal of Business and Research |
| Subjects: | |
| Online Access: | https://rijbr.in/1/article/view/811/244 |
| _version_ | 1797627547777761280 |
|---|---|
| author | Ms. Monika Agarwal Ms. Samridhi Tanwar Mr. Chandan Parsad Mr. Sanjeev Prashar |
| author_facet | Ms. Monika Agarwal Ms. Samridhi Tanwar Mr. Chandan Parsad Mr. Sanjeev Prashar |
| author_sort | Ms. Monika Agarwal |
| collection | DOAJ |
| description | The purpose of this study is twofold, first to explore the relationships among service quality dimensions and customer loyalty in the life insurance sector. The second aim is to find the sequence of significant service dimensions in predicting customer loyalty. A total sample of 431 customers from the top five private life insurance companies were surveyed. The multi-analytic approach: a combination of structural equation modeling and neural network model was used for the analytical process. The results from structural equation modeling revealed a significant and positive association of six service dimensions namely responsiveness, service availability, tangibility, reliability, assurance, and empathy with loyalty intentions of customers. The result of the neural network model showed that reliability is the best predictor of customer loyalty followed by responsiveness, assurance, tangibility, empathy, and service availability. The application of a multi-analytic approach (a combination of structural equation modeling and neural network) for understanding service quality-customer loyalty relationship can be of great help to private life insurance companies who are devising service strategies to influence loyalty intentions of customers to gain a competitive advantage in the market. |
| first_indexed | 2024-03-11T10:25:51Z |
| format | Article |
| id | doaj.art-8c29357d904149e3be9d51d817acd246 |
| institution | Directory Open Access Journal |
| issn | 2455-5959 2583-0171 |
| language | English |
| last_indexed | 2024-03-11T10:25:51Z |
| publishDate | 2022-12-01 |
| publisher | Ramanujan College, University of Delhi, Delhi, India |
| record_format | Article |
| series | Ramanujan International Journal of Business and Research |
| spelling | doaj.art-8c29357d904149e3be9d51d817acd2462023-11-15T14:13:35ZengRamanujan College, University of Delhi, Delhi, IndiaRamanujan International Journal of Business and Research2455-59592583-01712022-12-0172115https://doi.org/10.51245/rijbr.v7i2.2022.811Impact of service quality on customer loyalty: A multi-analytic approach using neural networkMs. Monika Agarwal0https://orcid.org/0000-0002-0085-0799Ms. Samridhi Tanwar1https://orcid.org/0000-0002-0809-4625Mr. Chandan Parsad2Mr. Sanjeev Prashar3https://orcid.org/0000-0001-9865-3840Jagan Institute of Management Studies, Rohini and IMSAR, Maharshi Dayanand University, Rohtak The Technological Institute of Textile & Sciences, BhiwaniIIM, BodhgayaIIM, RaipurThe purpose of this study is twofold, first to explore the relationships among service quality dimensions and customer loyalty in the life insurance sector. The second aim is to find the sequence of significant service dimensions in predicting customer loyalty. A total sample of 431 customers from the top five private life insurance companies were surveyed. The multi-analytic approach: a combination of structural equation modeling and neural network model was used for the analytical process. The results from structural equation modeling revealed a significant and positive association of six service dimensions namely responsiveness, service availability, tangibility, reliability, assurance, and empathy with loyalty intentions of customers. The result of the neural network model showed that reliability is the best predictor of customer loyalty followed by responsiveness, assurance, tangibility, empathy, and service availability. The application of a multi-analytic approach (a combination of structural equation modeling and neural network) for understanding service quality-customer loyalty relationship can be of great help to private life insurance companies who are devising service strategies to influence loyalty intentions of customers to gain a competitive advantage in the market.https://rijbr.in/1/article/view/811/244service qualitycustomer loyaltylife insurance sectorstructural equation modelling (sem)neural network (nn) |
| spellingShingle | Ms. Monika Agarwal Ms. Samridhi Tanwar Mr. Chandan Parsad Mr. Sanjeev Prashar Impact of service quality on customer loyalty: A multi-analytic approach using neural network Ramanujan International Journal of Business and Research service quality customer loyalty life insurance sector structural equation modelling (sem) neural network (nn) |
| title | Impact of service quality on customer loyalty: A multi-analytic approach using neural network |
| title_full | Impact of service quality on customer loyalty: A multi-analytic approach using neural network |
| title_fullStr | Impact of service quality on customer loyalty: A multi-analytic approach using neural network |
| title_full_unstemmed | Impact of service quality on customer loyalty: A multi-analytic approach using neural network |
| title_short | Impact of service quality on customer loyalty: A multi-analytic approach using neural network |
| title_sort | impact of service quality on customer loyalty a multi analytic approach using neural network |
| topic | service quality customer loyalty life insurance sector structural equation modelling (sem) neural network (nn) |
| url | https://rijbr.in/1/article/view/811/244 |
| work_keys_str_mv | AT msmonikaagarwal impactofservicequalityoncustomerloyaltyamultianalyticapproachusingneuralnetwork AT mssamridhitanwar impactofservicequalityoncustomerloyaltyamultianalyticapproachusingneuralnetwork AT mrchandanparsad impactofservicequalityoncustomerloyaltyamultianalyticapproachusingneuralnetwork AT mrsanjeevprashar impactofservicequalityoncustomerloyaltyamultianalyticapproachusingneuralnetwork |