Predicting Customer’s Satisfaction (Dissatisfaction) Using Logistic Regression

Author:

Anand Adarsh1,Bansal Gunjan1

Affiliation:

1. Department of Operational Research University of Delhi, Delhi 110007, India

Abstract

Customer satisfaction is a metric of how products and services offered by companies meet customer expectations. This performance indicator assists companies in managing and monitoring their business effectively. Firms thus need reliable and representative measure to know the customer satisfaction. In the present work, we provide a predictive model to identify customer’s satisfaction (dissatisfaction) with the firm’s offerings. For the analysis, “mobile phone” has been used as a product and 11 related decision making variables have been taken as independent variables. Due to the dichotomous (i.e. satisfaction/ dissatisfaction) nature of the dependent variable, a powerful tool among multivariate techniques i.e. Logistic Regression has been applied for the validation. Further, Receiver Operating Characteristic (ROC) curve has been plotted which displays the degree to which the prediction agrees with the data graphically. The analysis has been done on data collected from students of University of Delhi, Delhi.

Publisher

International Journal of Mathematical, Engineering and Management Sciences plus Mangey Ram

Subject

General Engineering,General Business, Management and Accounting,General Mathematics,General Computer Science

Reference21 articles.

1. Allen, D. R., Allen, D. R., & Rao, T. R. (2000). Analysis of customer satisfaction data: A comprehensive guide to multivariate statistical analysis in customer satisfaction, loyalty, and service quality research. Asq Press.

2. Alleyne, R. (2011). The young generation are 'addicted' to mobile phones, The Telegraph, http://www.telegraph.co.uk/technology/8458786/The-young-generation-are-addicted-to-mobile-phones.html, Accessed Date- 17-Apirl-2016.

3. Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. The Journal of Marketing, 53-66.

4. Brown, S. P., & Beltramini, R. F. (1989). Consumer complaining and word of mouth activities: field evidence. NA-Advances in Consumer Research Volume 16.

5. Cowles, D. L., (1996), To trust or Not to Trust, background paper, 1st Internet onference on Relationship Marketing, http://www.mcb.co.uk/services/conference_relation.mar./new_phil/backgnd2.htm, April 18th

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Quantification of number of adopters: a study to showcase products-sold and products-in-use;International Journal of System Assurance Engineering and Management;2023-10-24

2. Successive generation introduction time for high technological products: an analysis based on different multi-attribute utility functions;Environment, Development and Sustainability;2022-04-28

3. Modeling multi-generational diffusion for competitive brands: an analysis for telecommunication industries;Journal of Management Analytics;2021-02-08

4. Modelling Popularity Dynamics Based on YouTube Viewers and Subscribers;International Journal of Mathematical, Engineering and Management Sciences;2019-12-01

5. A study on the effect of imbalanced data in tourism recommendation models;International Journal of Quality and Service Sciences;2019-09-13

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3