Profiling Customers Based on Their Social Risk Perception: A Cluster Analysis Approach

Author:

Ghuman Mandeep Kaur1,Mann Bikram Jit Singh1

Affiliation:

1. University Business School, Guru Nanak Dev University, Amritsar, India.

Abstract

Past research asserts that social risk is an important determinant of consumer purchase behaviour; however, the characteristics of consumers who perceive high/low social risk in a purchase decision have been largely neglected. This study examines consumer social risk perception from a sample of Indian consumers of automobiles. The study segments the consumers using a cluster analysis, and explores differences between clusters based on consumers’ social risk perception and their psychological, cultural, and socio-demographic variables. Need for cognition (NFC) and risk-taking tendency are the two psychological variables focused in the study. The three cultural dimensions considered include collectivism, power distance, and masculinity. The cluster analysis yielded three clusters: high social risk perceivers, medium social risk perceivers, and low social risk perceivers. High social risk perceivers are found to be the individuals with high NFC, low risk-taking tendency, high collectivism, low power distance, and high masculinity. Medium social risk perceivers are the individuals with medium level of NFC, risk taking tendency and collectivism, and are low on power distance and masculinity. Low social risk perceivers are the consumers low in NFC, high in risk-taking tendency, low on collectivism, high on power distance, and low on masculinity. Further, each cluster was cross tabulated with consumer demographics.

Publisher

SAGE Publications

Subject

General Earth and Planetary Sciences,General Environmental Science

Cited by 4 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. Leveraging Unsupervised Machine Learning to Optimize Customer Segmentation and Product Recommendations for Increased Retail Profits;Advances in Computational Intelligence and Robotics;2024-08-30

2. Exploring the effectiveness of fashion recommendations made by social media influencers in the centennial generation;Textile Research Journal;2023-02-16

3. Modeling of Social Risks in the Labor Sphere;Journal of Risk and Financial Management;2021-10-14

4. Decision Tree and MCDA Under Fuzziness to Support E-Customer Satisfaction Survey;Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018);2019-04-10

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