Customer Acceptance of Internet Shopping in India: Impact of Shopping Orientations, Knowledge and Security

Abstract

Customer acceptance of innovations necessitates behavioral research aimed at examining and predicting behavior and behavioral intentions. Due to low penetration of internet in India (around 4% according to Business Today, 5.2% according to Nasscom’s projection for 2005 and 7.1% in November 2008 according to internet World Stats’ usage and populations statistics) as compared to other countries (China 22.4%, Taiwan 66.1%), internet shopping can be considered as an innovation for the Indian customer. Customer demand for the internet is a key factor that may ultimately drive widespread acceptance of the internet by retailers. Whether the customer has access and how they use or perceive internet shopping in a way will affect its ultimate acceptance (Shirky, 1997). Therefore, this study examines internet shopping acceptance in developing countries; in this case India. The exponential growth of internet penetration in India and increased e-commerce activity both on consumer side as well as corporate side during last few years provides the impetus to investigate this phenomenon among potential online shoppers. The study tests a comprehensive Technology Acceptance Model incorporating shopping profiles and security and privacy concerns exploring their effects on successful adoption of internet shopping in India. The study is divided into various chapters. Chapter 1 Presents the review of the literature in various sections. The first section presents the literature on Theories relevant to predicting and explaining behavior. The second section presents the analysis of customer research. The last section presents the literature on shopping orientations. The review of the literature is instrumental in identification of the research gaps, which are discussed in Chapter 2. This is followed by the presentation of the model for the study; the research bjectives, and the hypotheses which are also part of Chapter 2 Based on the literature review and research gaps, the proposed model focuses mainly on incorporating Shopping Orientations and Security/Privacy concerns to the original Technology Acceptance Model. Chapter 3 Is the Method section of the study. The operational definitions of the variables in the study are discussed first, followed by discussion of the scales used in the study. This is followed by the data-collection methodology and the details about the sample. The chapter closes by discussing the descriptive characteristics of the sample. Not surprisingly the age-group 25-34 was the most represented age-group. Chapter 4 Describes the results of the study. The student version 12.0 of the Statistical Package for the Social Sciences (SPSS) was used for the statistical computation and the analyses under this section. The categorical variables, for example, age, gender, educational qualification, etc. were coded before data entry. Continuous variables were entered into the excel sheet (MS Office Excel 2003) as they had been responded to onto the questionnaires. The hypotheses were tested using statistical tools like Canonical Correlation Analysis and Simple and Multiple Regression. The results section consists of the presentation of the findings for the study in two major sections, with their sub-sections. The first section describes the results on the validity and reliability of the scale. This section comprises of sub-sections like descriptive statistics of the scale constructs; factor analysis of Shopping orientation scale, intercorrelations and reliability and validity estimates for the sub-scales. The present scale was found to be multi-dimensional. The Shopping orientations scale was tested for its nomological, discriminant and construct validity. The scale displays theoretically supported relationships with other variables, demonstrating nomological validity. It is also distinguishable from the construct of knowledge, thus demonstrating discriminant validity. The construct validity test revealed four shopping orientations as compared to the proposed five shopping orientations structure. The shopping orientations were named Home, Economic, Mall-socializing and Personalizing. The second section describes the results of the study with respect to the model testing. This section comprises sub-sections like descriptive statistics for each variable in the study; results of correlation analysis; results of multivariate analyses and partial correlation coefficients. Two multivariate techniques have been discussed, namely canonical correlation analysis and regression analysis. Canonical correlation analysis has been used to study relationships between the independent and the dependent variate as multiple regression is restrictive in terms of allowing only one criterion variable to be examined at a time. Partial correlation coefficients were examined so as to determine the strength of the relationship between the criterion variable and a single independent variable when the effects of the other independent variables in the model are held constant. Results indicate that a significant amount of variance in the PU and A variables is explained for by the variability in the shopping Orientation variables and vice versa. Contrary to predicted, though Knowledge was found to be significantly positively affecting perceived usefulness of internet shopping, it was not found to be positively affecting perceived ease of use of internet shopping. Chapter 5 Presents the discussion of the analyses reported in the previous chapter. This chapter first discusses the findings on the validation of the shopping orientation scale. Four factors were derived from the results of the factor analysis and labeled as Home, Economic, Mall-Socializing and Personalizing shoppers. With respect to the psychometric properties of the scale, it was found to be scientifically reliable. Further, the scale demonstrated both nomological and discriminant validity. The scale displayed theoretically supported relationships with other variables, demonstrating nomological validity. The chapter next discusses the results of the model testing. Chapter 6 Is the discussion of the implications of the research. This chapter discusses the finding of the research in more details. This discussion is divided in three subsections. First is the theoretical implications, which discusses the robustness of the proposed model and depth of the proposed constructs from empirical and theoretical point of view. Overall, the model of online shopping behavior presented in this study is supported by the empirical results. Second section of the chapter discusses the methodological implications, which shows the method used throughout the research has deep roots in line with sound research methodology. For any research to be meaningful, its contributions to the practical life and industry is most important. Therefore, the last section of this chapter focuses on the practical implications of the research. The most important finding as revealed through the study is that shopping orientations and in that sense personality fit are very important for targeting online shoppers. Chapter 7 Discusses limitations of the study and future research directions. The chapter is divided in two sections. The first section highlights some of the limitations of this research. The second section discusses few suggestions and directions for future research focusing on the subject matter for reducing the effect of the limitations. Mainly, as this study has just initiated methodological exploration of online shopping in India through focusing on shopping orientations and their causal relationships with attributes of online shopping adoption at macro level, future research exploring shopping orientations should also focus on clusters of potential online shoppers within each shopping orientation and the behavioral differences among the four shopping orientations at micro level.