1. Introduction
Emerging markets like India offer significant opportunities for e-commerce due to widespread Internet penetration and rising consumer affluence. India’s e-commerce revenue is expected to surge from USD 30 billion in 2016 to USD 120 billion in 2020, growing at an annual rate of 51%, the highest in the world (ASSOCHAM, 2016). The number of online shoppers in the country is anticipated to swell from 39 million in 2015 to 220 million in 2020 growing at a CAGR of 41% (CII-Deloitte, 2016). Online sales are restricted to few Indian young people who purchase small-value products for their personal use (Gupta, Handa, & Gupta, 2008). There is a significant gap in understanding the Indian online shopping behavior (Beldona, Racherla, & Mundhra, 2011). It mandates understanding the psychological factors influencing the online consumer behavior. Consumer innovativeness or novelty seeking has been considered as a salient psychological variable influencing consumer behavior (Manning, Bearden, & Madden, 1995; Hirschman, 1980). Since online shopping can be viewed as an innovative way of shopping, innovativeness should have abearingon its adoption(Chang, Cheung, & Lai, 2005).
Innovativeness in the context of online buying has been largely under researched. Some studies (Limayem, Khalifa, & Frini, 2000; Donthu & Garcia, 1999) have concluded that innovativeness had a positive relationship with online purchase while others (Khare, Singh, & Khare, 2010; Sin & Tse, 2002; Citrin, Sprott, Silverman, & Stem, 2000) have found the relationship to be insignificant. Innovativeness varies across countries (Tellis, Yin, & Bell, 2009), and it does not affect adoption uniformly across various cultures (Truong, 2013). Similarly, the relationship between online novelty seeking and information search (significant determinant of consumer behavior) has not been empirically much tested in the Indian context. Its relationship with online information-search, shopping attitudes and purchase intentions is still unexplored. It merits understanding the role of innovativeness on online buying in this emerging market. This paper aims at examining the relationship between consumer innovativeness, information search, online purchase attitude and online purchase intentions in the Indian context.
2. Literature Review
2.1. Innovativeness
Innovativeness refers to the extent to which an individual is interested in new ideas (Chang, Cheung, & Lai, 2005). Innovativeness is the inclination to buy new and different products(Roehrich, 2004). It significantly influences new adoption process (Truong, 2013; Manning, Bearden, & Madden, 1995). Since online shopping can be considered as an innovative shopping, innovativeness could have aninfluence on its adoption (Chang, Cheung, & Lai, 2005).
There is a gap in knowledge of Indian online purchase behavior (Beldona, Racherla, & Mundhra, 2011). There is scant research on innovativeness, information search, attitudes and online purchase intentions.
2.2. Information Search
Information search is a deliberate attempt to acquire information to fill gaps in one’s knowledge (Case, 2007). Consumers’ pursuit for information stimulates them to explore the Internet. Information search is an essential motivation for online consumers (Rose & Samouel, 2009; Noble, Griffith, & Adjie, 2006). They spendtime and money in information search that may subsequently lead to purchasing (Maity, Hsu, & Pelton, 2012).
Information search has a positively associated with on line buying (Yulihasri, Islam, & Daud, 2011). Product information search is one of the antecedents of consumer’s purchase intention (Kim & Park, 2005). In offline consumer behavior, innovativeness is positively related to information search (Stella & Adam, 2006).
In the online consumer behavior context, information search has been acknowledged to affect online shopping (Liu & Forsythe, 2010; Rose & Samouel, 2009; To, Liao, & Line, 2007) but its relationship with innovativeness is still under researched. The internet serves as a source of information on product feature, prices, retailer information and store comparison (Khare, Singh, & Khare, 2010). Consumers increasingly assemble online product information or even surf for enjoyment (Demangeot & Broderick, 2007). Information search strongly influences online shopping intentions (Bigne-Alcan~iz, Ruiz-Mafe´, Alda´s-Manzano, & Sanz-Blas, 2008; So, Wong, & Sculli, 2005).
2.3. Attitude
Attitude refers to the affective evaluation of online shopping (Wang, Wang, &Wang, 2006). It is an important predictor of online purchase intentions (Wang, Wang, & Wang, 2006; George, 2004; Hansen, Jensen, & Solgaard, 2004; Monsuwe, Dellaert, & Ruyter, 2004; Vijayasarathy, 2004). Innovativeness is positively related to online purchase intentions (Park, Burns, & Rabolt, 2007). Attitude mediates the relationship between innovativeness and purchasing intention.
2.4. Shopping Intention
Intentions are the forerunners of behavior, and they are the potent predictors of behavior (Ajzen, 1991). The stronger the intentions the greater is the likelihood that an action will be performed (Ajzen, 2001; Azjen, 1991).
Past studies provide strong support for positive effect of innovativeness on attitude and online shopping intentions (Bigne-Alcan~iz, Ruiz-Mafe´,Alda´s-Manzano, & Sanz-Blas, 2008; Goldsmith, 2001; Limayem, Khalifa, & Frini, 2000).Further, innovativeness positively effects online shopping information search(Bigne-Alcan~iz, Ruiz-Mafe´,Alda´s-Manzano, & Sanz-Blas, 2008).
The present study explores the relationship between online novelty seeking and purchase intentions. Further, it extends the relationship by inclusion of two important variables namely information search and attitude. The study seeks to understand the association between online innovativeness, information search, attitude and shopping intentions. Based on extant literature we propose the following hypotheses:
[H1] There is a positive relationship between consumer innovativeness and information search.
[H2] There is a positive relationship between consumer innovativeness and consumer attitude
[H3] There is a positive relationship between consumer innovativeness and intention to shop online.
[H4] There is a positive relationship between consumer attitude and intention to shop online.
[H5] There is a positive relationship between information search and intention to shop online.
3. Research Methodology
The study adopted the consumer intercept method of survey. Four hundred respondents were intercepted across the various shopping centers and malls of the Chandigarh City, in northern India. The country’s census (2011) ranks the city highest on the Internet density in the country. Data was collected using a self-completion questionnaire administered to the respondents. The study used published scales to operationalize the variables under study. The construct‘ innovativeness’ was operationalized with scale of Manning, Bearden & Madden(1995). To measure information search, attitude and online purchase intentions scales of Khare & Rakesh (2011) were adopted. The items related to the constructs were measured on a 5-point Likert scale, ranging from ‘strongly disagree’ to ‘strongly agree. The research employed factor analysis to verify correct loading of items on corresponding factors and to confirm the applicability of constructs in the Indian context. The relationships between the various variables were tested employing regression analysis.
Four hundred respondents were intercepted across the numerous shopping places of Chandigarh city and asked to complete the questionnaire. The effective sample size constituted of 326 respondents. The sample is comprised of 72.4 per cent males and 27.6 per cent females. The sample varied in age from below 18 years to 70 years of age.
4. Results
The exploratory factor analysis was conducted employing varimax rotation. Four factors were extracted (Eigen values>1) and the items loaded correctly on the corresponding factors as in earlier studies. The results established the measurement scales’ convergent and discriminant validities. The regression results [Table 1]show that the variable ‘innovativeness’is a significant predictor of information search (R²= 0.414, p< .001). The R² shows that ‘innovativeness’ independently accounts for 41.2 % of variance in the online information search.
[Table 1] Regression Results-Innovativeness
**Significant at .001 level
The ß value (0.643) shows innovativeness as a salient contributor for online information search. The ANOVA test shows that the predicted regression by variety seeking is significant in the model (F=228.179, p<0.001). It indicates that innovativeness is an important stimulator for online information search.
The regression results show the variable innovativeness as a significant predictor of attitude towards online shopping (R²= 0.223, p<0.001). The R² shows that ‘innovativeness’ independently accounts for 22.3 % of variance in the attitude towards online shopping.
[Table 2] Regression results- Online shopping intentions
**Significant at .001 level
The ß value (0.475) elucidates that innovativeness significantly predicts attitude towards online purchase. The ANOVA test shows that the predicted regression by ‘innovativeness’ is significant in the model (F=94.315, p< .001). It indicates that ‘innovativeness’ is an important predictor of attitude towards online purchase. The results prove that hypotheses [H1] and [H2] are true.
The stepwise regression results showed that ‘‘innovativeness’; ‘information search’ and ‘attitude’ significantly affected online purchase intentions. The above variables were responsible for total 55.5% of the variance in the online purchase intention.
Variable ‘innovativeness’ was the main predictor of online purchase intention (R²= 0.524; F=355.92; ß=0.724; p< .001). The addition of ‘attitude’ along with ‘novelty seeking’ saw a further increase in predictability of the regression model (R²= 0.554; F=199.96, p< .001). The predictor variables namely ‘novelty seeking’, ‘attitude’ and ‘information search’ together accounted for 55.9% of the variance in model (R²= 0.559; F=135.87; p< .001). Results of regression results prove the H3, H4 and H5 to be true.
5. Discussion
The study is successful to the extent of explaining the relationships between online innovativeness, information search, attitude and shopping intentions. Online innovativeness behavior has surfaced to be a significant predictor of online ‘information search’, attitude and purchase intentions.
This has major implications for online retail companies. Novelty seeking positively influences adoption of innovations (Truong, 2013; Manning, Bearden, & Madden, 1995). This mandates that companies incorporate innovative website design so as to attract consumers to their sites. Websites should promote their offerings in terms of the level of novelty they provide in goods and services. Innovators are early adaptors and could be the opinion leaders of their groups (Ho & Wu, 2011). Innovators should be made to try novel products so that they become advocators of the products. Since innovators are early adopters, price-skimming strategy should be adopted (Bigne-Alcan~iz, Ruiz-Mafe´, Alda´s-Manzano, & Sanz-Blas, 2008). Companies could adopt social media tools to highlight the innovative products.
Information search positively influences the online purchase. The websites may provide sufficient information as it would increase the time spent by the consumers on browsing, and alleviate consumers’ perceived risk (Smith & Sivakumar, 2004). Information search can be amplified with adequate website speed and pleasant website background. Featuring novel products would result in more information search and further facilitate the online purchase.
Attitude is the fundamental antecedent of purchase intentions. Attitude may be influenced by promotions by emphasizing that the products offered by the company are novel, genuine and competitively priced. It is necessitated that the companies ensure novelty in their websites and entice consumers for more information search so as to have a positive attitude and intentions for online shopping.
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