JOURNAL ARTICLE
Motivational Factors Influencing Bancassurance Customers: An Analysis.
Published In: IUP Journal of Accounting Research & Audit Practices, 2024, v. 23, n. 4. P. 515 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Pranavi, E.; Mamatha, J. 3 of 3
Abstract
This study explores the key motivational factors influencing customers to purchase insurance products through bancassurance channels in India. Employing a descriptive research design, the primary data were collected through a structured and pilot-tested questionnaire from a representative sample of 400 respondents across public and private sector banks. Seven motivational factors were examined: convenience, low service charges, high-paying features of insurance policies, service quality and variety, reputation and brand image, bank employee advice, and influence of well-wishers. The study integrates secondary data to contextualize the findings, and employs appropriate statistical controls to ensure validity. The results indicate that high-paying features and service quality are the most influential factors, with notable differences observed between public and private sector banks. The study contributes to the existing literature by identifying specific drivers of customer motivation in the Indian bancassurance sector and provides actionable recommendations for banks to enhance their service strategies, including leveraging digital platforms and improving customer engagement practices. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:IUP Journal of Accounting Research & Audit Practices. 2024/10, Vol. 23, Issue 4, p515
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2024
- ISSN:2583-5211
- Accession Number:182396238
- Copyright Statement:Copyright of IUP Journal of Accounting Research & Audit Practices is the property of IUP Publications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.