Measuring online consumer behavior: scale development & validation

Abstract

The purpose of this paper is to measure online consumer behavior in Saudi Arabian context. The study has identified 7 factors like Web Atmosphere, E-Retailors Image, attitude, Trust, Situational factors, social factors and cultural factors which have a significant influence on the online consumer behavior. These seven factors have been measured using 35 statements. The scale developed has shown strong internal consistency, reliability and has remained consistent across different samples. The findings have revealed that web atmosphere is one of the most dominant factors along with the E-Retailors image and cultural factor have emerged out to be least significant factor. The main contribution of this study lies in validating a divergent scale measuring online consumer behavior. The findings of this study have important implications both for the academia and practitioners. The limitations and directions for future research are also discussed. Corresponding author: Zaid Ahmad Ansari Email address for corresponding author: drzaidansari@gmail.com First submission received: 1st May 2018 Revised submission received: 5th July 2018 Accepted: 12th August 2018 Introduction Saudi Arabia is a country which is unusual in every possible way imaginable. A country where majority of the people like to go out for shopping in humongous and giant air-conditioned malls. People like to pay in cash and therefore postal codes are hardly used. This makes building online retail business presence much more difficult and complicated than any other country in the world. With the entry of American E-commerce giant, ‘Amazon’ and local players like ‘Souq’ and ‘Noon.com’ things are expected to take a U-turn pretty soon because E-commerce gives information and communication not only to businesses but to consumers as well (Maghrabi & Dennis, 2011). According to the recent data from Reuters the online sales in Saudi Arabia is expected to surge to $13.9 billion by 2021 from $8.7 billion in 2017. The research on E-commerce has seen quite a surge over the last decade. The research on online consumer behavior has appeared in some of the prominent journals of management, marketing, information technology and even phycology. A close introspection of the previous research which has appeared in these journals highlights that researchers have drawn theories from classical consumer behavior research like behavioral learning (skinner,1938), personality research (Folkes, 1988), information processing (Bettman, 1979) and attitude models (Fishbein, 1975). Although, I acknowledge that the application is not that straightforward as simply borrowing the theories because significant differences exist between online and offline behaviors of the consumers. Despite the surge in academic and non-academic literature in studying online consumer behavior, there is still dearth of studies which have attempted to integrate research findings across studies from a theoretical marketing and consumer behavior perspective (Darley & Blankson, 2010). Further very rare papers have studied the online consumer behavior with respect to Saudi Arabia. Therefore, there is a need to bride this gap by constructing a valid measuring instrument which will help online businesses Journal of Business and Retail Management Research (JBRMR), Vol. 13 Issue 3 April 2019 www.jbrmr.com A Journal of the Academy of Business and Retail Management (ABRM) 223 understand the major factors which have an influence on the overall consumer behavior. Despite encouraging and high online growth rates researchers argue that many customers who search products on multiple online sites abandon their purchase decisions Talal Al et al., (2010). This is critical because previous research has highlighted that acquiring new customers may be five times costlier than acquiring an old one (Bhattacherjee, 2001; Crego & Schiffrin, 1995; Petrissans, 1999). Therefore, the objective of this paper is to construct, test and validate a scale for measuring online consumer behavior in E-commerce with special emphasis on the Saudi Arabia. Researchers have considered E-commerce as a reference point because there is a paucity of studies in the available literature. Researcher has tried to bridge this gap by constructing a highly valid and reliable scale which measures the consumer behavior in E-commerce. The rest of the paper is organized into 5 main sections. First, a thorough review of literature has been conducted highlighting all the previous measures of ecommerce. Second, highly valid and reliable scale development procedures as per the recommendations of Churchill (1979) and Hinkin (1995) have been discussed. Third, the researcher has discussed the implications of the study along with the limitations and directions for future research. Review of literature Escalation in internet usage pushed the commerce into digital age, affecting almost every aspect of day to day life, from knowledge to acquisition of the products and services (Kim & Lennon, 2008). Recently internet prevalence intensified the study of consumer based electronic commerce (Cheung, Chan, & Limayem, 2005). The significant growth in the literature of online consumer behavior is highly acknowledged over the last decade (Darley, Blankson, & Luethge, 2010) and consequently it has become an emerging area of research (Cheung et al., 2005). According to Cheung at al. (2005) online consumer behavior became one of the emerging areas of research since 2000, due to dramatic increase in the number of publications per year. The literature reveals that, most of the discussion related to consumer behavior confines to its factors or components. Researchers have different opinions when defining the components of the consumer behavior. The literature also revealed that consumer behavior is measured through diverse factors. One of the major and most important component discussed in the literature is related to web atmosphere which includes a number of web specific aspects like, experience with internet and internet self-efficacy (Aljukhadar & Senecal 2011); online risk (Bianchi & Andrews 2012); online technology enjoyment, familiarity with online transactions, and online purchase intension (Chen & Barnes 2007); navigation (Childers, Carr, Peck, & Carson, 2001); screen clarity, content relevance, and link relevance (Demangeot & Broderick 2007); characteristics and evaluation of websites (Kim, Yang, & Yong Kim, 2013); Navigation (Liang & Lai 2002); web experience and site quality (McKnight, Choudhury, & Kacmar, 2002); interface (Schoenbachler & Gordon 2002) are frequently studied in consumer behavior studies. Second widely discussed component or factor of consumer behavior is e-retailers image which covers company size and reputation (Chen & Barnes 2007); retailer image and reputation (Constantinides, 2004; Dennis, Merrilees, Jayawardhena, & Tiu Wright, 2009; Eurofood, 2000); retailer reputation (Kim, Yang, and Yong Kim, 2013; Korgaonkar, Silverblatt, & Girard, 2006). Highlighting the importance image in e-commerce Boulding (1956) reported “image” signifies comprehensive evaluation or rating of something in such a way that guide the actions of consumers. Similarly, Constantinides, (2004) suggested that retailer image and reputation help in reduction of customer anxiety by lowering transaction risks and by enhances virtual interactions. Third important component discussed in the literature of consumer behavior is consumer’s attitude (Bhattacherjee, 2000; Bianchi & Andrews 2012; Chan, Cheung, Kwong, Limayem, & Zhu, 2003; Childers, Carr, Peck, & Carson, 2001; Goldsmith & Bridges 2000; Hansen 2008; Kang, Hahn, Fortin, Hyun, & Eom, 2006; Koernig, 2003; Lim, & Dubinsky, 2005; Menon, & Kahn, 2002; Schiffman, Sherman, & Long, 2003; Shim, Eastlick, Lotz, & Warrington, 2001; Song, & Zahedi, 2005; Sorce, Perotti, & Widrick, 2005) Fourth subsequent factor of consumer behavior is trust which includes disposition to trust, institution-based trust, trusting beliefs, and trusting intentions (McKnight, Choudhury, & Kacmar, 2002), propensity to trust (Bianchi & Andrews 2012; Aljukhadar & Senecal 2011; Chen & Barnes 2007; Cheung, & Journal of Business and Retail Management Research (JBRMR), Vol. 13 Issue 3 April 2019 www.jbrmr.com A Journal of the Academy of Business and Retail Management (ABRM) 224 Lee, 2001; Fung, & Lee, 1999), benevolence trust (Cho, 2006), interpersonal trust (Das, Echambadi, McCardle, & Luckett, 2003), trust (Dash, & Saji, 2008; Falk, Schepers, Hammerschmidt, & Bauer, 2007; Jarvenpaa, Tractinsky, & Vitale, 2000; Lee, & Turban, 2001; Jiang, Jones, & Javie, 2008; Lee, Kim, & Moon, 2000). One of the other widely discussed components include situational factors of e-consumer (Darley, Blankson, & Luethge, 2010; Dennis et al., 2009; Rohm & Swaminathan 2004). Various researchers’ e.g Evanschitzky, Iyer, Hesse, & Ahlert, (2004); Szymanski, & Hise, (2000), argue that perception of convenience acts as one of the important situational component in online shopping, and also significantly influences e-satisfaction of consumers (Kim, Kim, & Kandampully, 2009), in this issue Dennis et al. (2009) suggested convenience in online shopping eliminates costs (travel and psychological) and enhances efficiency of e-consumers. The next subsequent component highlighted in literature of consumer behavior is social factors (Ajzen & Fishbein, 1980; Dennis et al., 2009; Darley, et al., 2010; Engel, Blackwell, & Miniard, 2001; Lim, & Dubinsky, 2005). In context of social factors, the theory of reasoned action (TRA) argues that even wishes of our best friends on purchase of particular items effects our intention (Dennis et al., 2009). Likewise, Rohm & Swaminathan (2004) found that social influence of e-consumers acts as a significant motivator for online shopping. On similar lines Parson (2002) reported that social factors like outside experiences, communication with people of similar interest, peer group membershi