SATISFACTION OF CUSTOMERS IN USING CUSTOMER SERVICES PROVIDED BY PUBLIC AND PRIVATE SECTOR BANKS IN THANJAVUR DISTRICT – A COMPARATIVE STUDY
Keywords:
Customer Satisfaction, Public Sector Banks, Private Sector Banks, Thanjavur DistrictSynopsis
The primary objective of this study is to assess customers' satisfaction in using customer services provided by public and private sector banks in Thanjavur district. The explorative research method was used. Both qualitative and quantitative data were collected and used to assess customer satisfaction. Related information was collected and tested to test the hypothesis. The multi-stage sampling technique was used to select the sample public and private sector banks and sample customers. There are 8 public sector banks with 161 branches and 7 private sector banks with 83 branches functioning in rural and urban areas of Thanjavur district. From this, only 30 branches i.e., every two branches from sample public and private sector banks (one from rural and another from urban), were determined as sample branches. The simple random sampling technique was used to select the branches of banks. Bank officials did not provide a list of customers due to the banks' policy. Thus, the population of the study was considered unknown. Therefore, using simple random sampling techniques, every 10 customers from sample branches were determined as sample respondents. Hence, 160 customers from sample public sector banks and 140 customers from sample private sector banks were used as sample customers. The analysis result reveals that irrespective of the banks' the majority of the sample customers have a moderate and low level of satisfaction with the various customer services provided by public and private sector banks. However, most of the public sector banks' sample customers are highly satisfied with the service cost charged by banks. At the same time, most of the private sector banks' sample customers are dissatisfied with the service cost charged by banks. Further, the result reveals that the customers' satisfaction level is based on bank officials' approaches and service costs charged by banks.
References
[1] Manidayanand & Neelamegam (2021), “Customer perception towards services provided by public sector and private sector banks: a comparative study”, Ilkogretim Online - Elementary Education Online, Year; Vol 20 (Issue 5): pp. 2005-2013 http://ilkogretim-online.org doi: 10.17051/ilkonline.2021.05.220.
[2] Biju & Philip, Anu (2020), “Customer Perception on Banking Services -A Study Among Public Sector and Private Sector Banks” Studies in Indian Place Names, ISSN: 2394-3114, Vol-40-Issue-50-March.
[3] Devanathan (2019),”A study on customer perception in e-banking services in public and private sector bank in Chennai”, Think India Journal, Vlo.22, Issue 4, December.
[4] Kannaghi and shanmugam (2019), “A study on customer satisfaction of e-banking services in public sector banks with special reference to cuddalore district”, Think India Journal, Vlo.22, Issue 4, December.
[5] Therasha (2019), “A study on customer satisfaction of banking services offered by Canara Bank with special reference to Tahadur Branch Tiruttani”, Think India Journal, Vlo.22, Issue 4, December.
[6] Ahmed, E.M & Phin, G.S (2016), “Customer Perception towards Internet Banking in an Emer ging Economy like Malaysia”, Journal of Internet Banking and Commerce,18(3).
[7] Asad, M. M., Mohajerani, N., & Nourseresh, M. (2016), “Prioritising Factors Affecting Customer Satisfaction in the Internet Banking System Based on Cause and Effect Relationships”, Procedia Economics and Finance, 36(16), 210–219.
[8] Mukhtar,M (2015), “Perceptions of UK Based Customer toward Internet Banking in the United Kingdom”, Journal of Internet Banking and Commerce, 20(1) :1-4.
[9] Dharmalingam and Kannan (2011), “Customer Perception on Service Quality of New Private Sector Banks in Tamilnadu”, JBFSIR Volume 1, Issue 5.
[10] Kavitha (2011), “Influence of Demographic Variables on Customer Satisfaction Regarding E-Banking”, Issues in Information Systems, Volume XII.
[11] RAJKUMAR, R., & SUDHA, G. (2013). FIBROMYALGIA–AN OUTCOME OF WORK LIFE IMBALANCE.
[12] Senthilkumar, K., & Rajkumar, R. (2019). A study on women entrepreneurship in Tanjore region. International Conference on Management Research, 2(2), 9-13.
[13] Senthilkumar, K., & Rajkumar, R. (2018). Analysis of consumer behaviour towards various cement brands grades with special reference to Thanjavur district. International Conference on Management Research, 1(1), 4-8.
[14] Sudha, G., & Rajkumar, R. (2014). Influence of gender on better balance. Journal of Business Studies, 1(SPL), 47-54. University of Jaffna.
[15] Sudha, G., & Rajkumar, R. (2012). Work life balance for working women - Is it so tough. Sankhya - International Journal of Management and Technology, 3(2), 100-103. SIMS Publication.
[16] Senthilkumar, K., K. Iyyappan, and S. Subramaniam. "Customer awareness on electronic banking in Thanjavur town—An empirical study." 2012-International Conference on Management Issues in Emerging Economies (ICMIEE). IEEE, 2012.
[17] Senthilkumar, K. (2014). Medical tourism: Changing scenario in health care sector. Holy Grace Management Review, 6(1), 118-122.
[18] Senthilkumar, K. (2014). Analysis of consumer behavior towards various cement brands & grades with special reference to Thanjavur district. Emerging Paradigms in Management Research, 3(2), 4-9.
[19] Senthilkumar, K. (2012). A comparative study on innovation management of health care services in rural India with other developing countries of Asia. In Conference Proceedings of Strategic Trends on Innovations & Creativity in Management Practices, 2(1), 31.
[20] Senthilkumar, K. (2012). Challenges and opportunities with special reference to Indian cement industry. Sankhya International Journal of Management and Technology, 3(1), 252-255.
[21] Senthilkumar, K. (2011). Evolution and evaluation of Indian cement industry. International Journal of Applied Management Research (IJAMR), 3(1), 779-784. IJAMR.
[22] Kasthuri, S., and A. Nisha Jebaseeli. "An artificial bee colony and pigeon inspired optimization hybrid feature selection algorithm for twitter sentiment analysis." Journal of Computational and Theoretical Nanoscience 17.12 (2020): 5378-5385.
[23] Kasthuri, S., and A. Nisha Jebaseeli. "Study on social network analysis in data mining." International Journal of Analytical and Experimental Modal Analysis (IJAEMA),(UGC CARE-A Journal), Impact Factor 6.3 11.VIII (2019): 111-116.
[24] Kasthuri, S., and A. Nisha Jebaseeli. "Review analysis of Twitter sentimental data." Bioscience Biotechnology Research Communications (BBRC),(UGC CARE Journal-Web of Science), Special Issue 13.6 (2020): 209-214.
[25] Kasthuri, S., and A. Nisha Jebaseeli. "Social network analysis in data processing." Adalya Journal,(UGC CARE-B Journal–Web of Science), Impact Factor 5 (2020): 260-263
[26] Kasthuri, S., and A. Jebaseeli Nisha. "Review on social network analysis in data mining." Infokara Res 8.12 (2019): 1168-1172.
[27] Ambika, G., and D. P. Srivaramangai. "A study on security in the Internet of Things." Int. J. Sci. Res. Comput. Sci. Eng. Inform. Technol 5.2 (2017): 12-21.
[28] Ambika, G., and P. Srivaramangai. "Encrypted Query Data Processing in Internet Of Things (IoTs): CryptDB and Trusted DB." (2018).
[29] Ambika, G. "Advanced Human Activity Recognition: Leveraging Adaptive Neural Networks and Diverse Machine Learning Algorithms on IoT Data." Fuzzy Systems and Soft Computing, vol. 19, no. 02(V), 2024, pp. 11–17.
[30] G. Ambika, “IoTCryptDB: Encrypted query data processing in Internet of Things,” International Journal of Scientific Research in Computer Science Applications and Management Studies, vol. 7, no. 4, p. 18, Jul. 2018.
[31] Ambika, G. "Processing Over Encrypted Query Data in Internet of Things (IoTs): CryptDBs, MONOMI and SDB." International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, Issue-8, 2018, p. 8.
[32] Shanti, M. A., and K. Saravanan. "Knowledge data map—A framework for the field of data mining and knowledge discovery." International Journal of Computer Engineering & Technology 8.5 (2017): 67-77.
[33] Shanti, M. A., and K. Saravanan. "An Effect of Data Mining Techniques in Public Healthcare-A Case Study." International Journal of Civil Engineering and Technology 9.9 (2018): 115-122.
[34] Shanti, M. A. "A Study to Analyse the Quality of Work Life with Special Reference to Private Sector Bank Employees in Kumbakonam Town of Thanjavur District." Our Heritage, vol. 68, 2020.
[35] Shanti, M. A. "Earthquake Prediction Using SVM Based Time Predictable Technique." International Journal of Computer Sciences and Engineering (IJCSE), vol. 7, no. 4, 2019, pp. 2347–2693.
[36] Shanti, M. A., and K. Saravanan. "Wartortle—A Data Mining and Knowledge Discovery Suite for Data Analysis and Reporting." International Journal of Applied Engineering Research, vol. 13, no. 10, 2018, pp. 7835–7841.
[37] Amalarethinam, George. "DI, Vaaheedha Kfatheen. S,“Max-min Average Algorithm for Scheduling Tasks in Grid Computing Systems”." International Journal of Computer Science and Information Technologies 3.2 (2012): 3659-3663.
[38] Amalarethinam, G. D. I., and V. S. Kfatheen. "Max-Min average algorithm for scheduling tasks in grid computing systems." International Journal of Computer Science and Information Technologies 3.2 (2014): 3659-62.
[39] Sumathy, P., and Ahilan Chandrasekaran. "An Optimized Image Pre-Processing Technique for Face Emotion Recognition System." Annals of the Romanian Society for Cell Biology 25.6 (2021): 6247-6261.
[40] Agilan, C. "A Comprehensive Survey on Emotion Recognition Techniques Using Image Processing." Indian Journal of Natural Sciences, vol. 16, no. 90, 2025, pp. 96569-96579. Indian Journal of Natural Sciences.
[41] Agilan, C. "Enhancing Human Emotion Detection through Optimization-Driven CNN Models." Indian Journal of Natural Sciences, vol. 16, no. 90, 2025, pp. 96422-96433. Indian Journal of Natural Sciences.
[42] Agilan, C. "Energy Efficient Clustering and Dynamic Slot Allocation for Wireless Sensor Networks." IEEE Explore, vol. 1109, ACOIT62457, 2024, https://ieeexplore.ieee.org/xpl/conhome/10939027/proceeding.
[43] Agilan, C. "Optimization-Based Clustering Feature Extraction Approach for Human Emotion Recognition." The Scientific Temper, vol. 15, no. spl.04, 2024, pp. 24-31. Web of Science.
Published
Series
Categories
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.