CONSMERS PERCEPTION AND INTENTION TO ADOPT MOBILE COMMERCE IN INDIA

Abstract

A splurge in the information and communication technology during the recent years and rapid proliferation of internet enabled mobile phones has resulted in the electronic as well as mobile commerce opportunities to shoot up. Users are switching over to wireless network from wired one, i.e. to mobile commerce or m-commerce from the traditional electronic commerce (Bushell, 2002). The various value chain partners involved in mobile commerce are consumers, service providers, network operators, technology vendors, application developers and content providers. The prospect of mobile commerce industry relies on the efficiency and performance of all these partners. Consumer being the most important element of the mobile commerce eco-system plays a significant role in its success or failure. The study of factors influencing consumers’ decision to adopt mobile commerce can provide useful insights to other partners in the value chain in creating and developing better suited technologies or applications. With this backdrop, the present study aims at identifying major areas of mobile commerce applications in India and the variables which influence consumers’ intentions to adopt mobile commerce. It further analyses their relationship with consumers’ behavioural intention and studies the impact of consumers’ Age, Gender and Household Income on the proposed relationships. Finally it attempts to identify and analyse the strategies followed by Indian mobile commerce firms for consumer adoption. The study utilised both primary as well as secondary data collection techniques to meet its objectives. A thorough literature review was conducted to identify major areas of mobile commerce applications in India, to study and compare various existing technology adoption frameworks and for identifying key factors influencing mobile commerce adoption. Further, a balanced approach was adopted where in, along with the primary data collected to develop and validate the research framework for mobile commerce adoption, cases of successful vi mobile commerce companies were also analysed to understand the role of identified parameters in the adoption of services offered by mobile-commerce entities. The research design of the study was descriptive in nature. The absence of a formal sampling frame in such kind of studies justified the use of non-random sampling techniques to collect data, which have been utilised for this research. The data was collected through a self administered questionnaire. A Likert scale of five points, ranging from 1 representing high disagreement to the statement and 5 representing high agreement with the statement was utilised to measure the items which were further used to determine the identified independent and dependent variables. A multi-staged analysis was conducted on the primary data collected including Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) of the measurement model created in SPSS AMOS, testing of proposed relationships through Structural Equation Modelling (SEM), followed by Artificial Neural Networks (ANN) analysis to re-confirm complex linear relationships between the variables. For analysing the strategies implemented by different existing e-commerce companies as well as emerging mobile commerce companies for consumer adoption, cases from the industry were analysed. Exploratory Factor Analysis (EFA) resulted in the establishment of 12 independent and 2 dependent factors explaining mobile commerce adoption. In the second phase of data analysis, the model’s reliability and validity was established in SPSS and AMOS and further, measures of model fit were found to confirm the factor analysis. Also the relation of independent variables with the dependent variable were tested and variables such as Facilitating Conditions, Variety of Services, Perceived Usefulness, Personal Innovativeness, Perceived Critical Mass, Perceived ease of Use, Perceived Regulatory Support, Perceived Trust, Perceived Risk, and Promotional Benefits were observed affecting the Behavioural vii Intention of consumers towards adoption of mobile commerce in a significant manner, Perceived Regulatory Support being the most significant factor. Behavioural Intention was also observed to significantly affect the mobile commerce Actual Usage by the consumers. The demographic factors namely the respondent’s gender, annual household income and age were found to moderate the proposed relationships. Finally, the results of the third phase of analysis through ANN model, established Perceived Ease of Use to predict Behaviour Intention of consumers towards adoption of mobile commerce in a most significant way. The findings of the research have important implications from the managerial, practical, and research point of view. It provides meaningful insights to various partners in the mobile commerce value-chain including marketers, app developers, service providers, and regulatory authorities enabling them to ensure a steady growth in the acceptance of mobile commerce by potential consumers. By integrating Artificial Neural Network Model with Structural Equation Modelling, the study provides a relatively new dimension to the analysis useful for the future researchers working in the domain of mobile commerce.