Clustering E-Shoppers on the Basis of Shopping Values and Web Characteristics

Clustering E-Shoppers on the Basis of Shopping Values and Web Characteristics

Sanjeev Prashar, Sai Vijay Tata, Chandan Parsad, Abhishek Banerjee, Nikhil Sahakari, Subham Chatterjee
DOI: 10.4018/978-1-7998-8957-1.ch048
OnDemand:
(Individual Chapters)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

This article describes how the exponential growth of e-commerce in India and the presence of many national and multinational e-retailers has set the trend for the major overhaul of the online industry. Most of the e-retailers have failed to differentiate themselves from the competitors. This has resulted in their failure to attract and retain the right set of consumers for their respective businesses. The present paper is aimed at identifying and developing the typology of online shoppers based on importance given by them to shopping values and web portal features. The data collected was analysed using factor, cluster and correspondence analyses. The article identifies four types of online shoppers – ‘Information Seekers,' ‘Utility Seekers,' ‘Value Seekers' and ‘Core Shoppers.' Each of these four segments display significant differences and this information can be strategically used by web retailers in targeting their markets effectively.
Chapter Preview
Top

Introduction

An online market place is an entity where information regarding product or service is provided by a third-party seller followed by the execution by the operator of the market place. Commonly known as electronic commerce websites, these provide a convenient option for vendors to sell products or services without having a physical store. Electronic commerce (or e-commerce) has been defined as commercial transactions that occur between buyer and sellers over the internet while enabling new economic and business practices. The rapid emergence and acceptance of e-commerce has changed the structure and environment of businesses conducted in today’s world. With the current GDP of India constituting at over US $2.48 trillion, and growing steadily at 7.49%, the Indian economy is pegged to be the fastest growing economy in the world (Economy Watch, 2017). With such high growth, online market places are expected to increase in number. Online retailing in India is estimated to grow from US $30 billion in 2016 to reach US $100 billion by the end of 2020 (IBEF, 2017). Positing several reasons for the rapid emergence of online market places in India, Gehrt (2012) attributed the rise of the Indian economy, purchasing power parity, large number of college students, and growth in telecom sector coupled with higher internet penetration in the country as major influencers. Ravichandran (2009) observed that the economic crisis of 2008 forced more people to compare prices with different retailers giving prominence to the online market places. In India, there exists a plethora of online market places, like Flipkart, Amazon, Snapdeal, Paytm, etc. Flipkart leads the pack with 44% market share, followed by Amazon at approximately 31% and Snapdeal 14% (Economic Times, 2017).

The exponential growth of e-commerce in India, coupled with vastness of the market, motivated the researchers to identify various online shoppers’ segments on the basis of pertinent shopping values and web characteristics that have influence on the website selection. It has been anticipated that India would be in the top 10 e-commerce destinations in the world, but the online firms are posed with plenty of challenges (Vyas & Gupta, 2017). Despite the exponential growth of online retailing in India, not much research has been undertaken to understand and identify the online shopper segments in India (Gehrt et al., 2012). In the preliminary study, Gehrt et al. (2012) observed the presence of three segments: ‘value singularity,’ ‘quality at any price’ and ‘reputation/recreation’ on the basis of key shopping orientation themes and web site dimensions. A study by Pandey et al. (2015) on online shopping lifestyles in India identified three shopping segments, ‘mature traditionalists,’ ‘offer enthusiasts’ and ‘technology mavericks,’ and it concluded that internet self-inefficacy impacts mature buyers. It also observed that the offer-seeking shoppers, comprising mostly of students from lower age group, do not enjoy the convenience of online shopping. The major limitation of this study was the usage of parameters defined for American lifestyles in Indian context.

Studies have also been undertaken to identify consumers and firms’ preferences in using internet marketing channels (e.g. Khatwani & Srivastava, 2015; Khatwani & Srivastava, 2017). A study in the Indian context by Prashar et al. (2017a) has noted that nearly sixty-four percent of variance in web satisfaction is explained by motivations based on shopping values and website characteristics. These motivations form an important dimension for online shoppers and can be used as basis for segmenting the shoppers. However, the earlier studies have not segmented shoppers on the basis of these motivations. Hence, the present paper is pioneer in classifying online shoppers as per their attitude towards shopping values and site features. It further explored the association, if any, between income groups and the identified segments using correspondence analysis. The paper is sequenced in the following manner. The next section details the research background and incorporates extensive review of literature. This is followed by discussion on research methodology that includes the process of data collection. Data analyses using factor, cluster and correspondence analysis is available thereafter. The final section contains discussion of findings, implications and limitations of the study.

Complete Chapter List

Search this Book:
Reset