“Applying the theory of Perceived Risk and Technology Acceptance Model in Online Shopping”
Research proposal submitted to: Prof. Dilipchandra Marketing department, CUIM Bangalore
Submitted by: Bhagesh Kumar 1221208 MBA Marketing 2012-2014 Page 1 of 8
1. WORKING TITLE OF THE PROJECT: A study on the applying the theory of perceived risk and technology acceptance model (TAM) in online shopping. 2. INTRODUCTION: Internet in recent years has been perceived as extra ordinary event. One of the continuing issues in the management of information technologies is identifying significant factors that influence consumers to accept and make use of systems developed and implemented by others. Over 875 million consumers have shopped online. The number of online shoppers has also increased upto 40% in last two years. The total value of e-commerce activities in India has crossed Rs 5.7 billion during 2004-05 and Rs. 23 billion by the year 2006-07. With approximately 8 million Indians shopping online in 2012, the online shopping industry is growing rapidly and will continue to see an exponential growth. Due to the favourable conditions which has encouraged many companies and enterprises to join in order to stay competitive and spend considerable amount of resources to expand and retain its customer base.
Online shopping is witnessing a whopping 200% growth in the sale of electronic items every year. Electronic gadgets such as mobile phones, iPods and MP3 players are in huge demand not only from urban but also from rural and small cities. The total estimated value of E-commerce in India has crossed Rs. 5.7 billion during 2004-05 and Rs. 23 billion by the year 2006-07. Approximately 8 million Indians shopping online in 2012, the online shopping industry in India is growing rapidly. Due to the expansion of online shopping trend, many companies and enterprises have jointly participated in retaining as well as expanding the customer base.
Although this dramatic development of commerce through internet has also opened new avenues, newer challenges are evolving. In reality, many of the consumers use this medium to obtain information and not actually purchasing a product. Customers are still reluctant to shop online due to not user friendly online technologies, infrastructure and interface which often cause confusion to the online shoppers which finally results in loss in online retail sale. Page 2 of 8
Retrospectively, many theories and models have been suggested by researchers across the globe to address this problem. In 1989, Davis proposed the theory of Technology Acceptance Model (TAM) to explain online user’s behavioural intention to use a technological innovation. TAM is based on the theory of reasoned action and involves two important predictors- perceived ease of use (PEOU) and perceived usefulness (PU) and the dependent variable behavioural intention (BI). R.A. Bauer contributed towards theory of perceived risk and his observations shall be used as foundation principal in this study. Perceived risk primarily takes the centre stage while doing prior information search to actual buying. The difference between the information search (purchase goal) and the actual shopping determines the extent of perceived risk.
The main purpose of this study is to integrate the perceived risk theory and technology acceptance model and apply on the online shopping.
3. OBJECTIVES: The objective of the research is to find the relationship between perceived risk, perceived ease of use, perceived usefulness and actual purchase behavior.
4. SCOPE: The study is applicable to online shoppers in Bangalore using the underlying principles of technology acceptance model and perceived risk.
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5. LITERATURE REVIEW: Technology Acceptance Model, proposed by Davis in 1989, is one of the most influential research models in studies of the determinants of information systems and information technology acceptance to predict intention to use and acceptance of information systems and information technology by individuals. Technology Acceptance Model has received considerable attention of researchers in the information system field over the past decade (Chuttur, 2009). In the Technology Acceptance Model, there are two determinants including perceived ease of use and perceived usefulness. Perceived usefulness is the degree to which an individual believes that using a particular information system or information technology would enhance his or her job or life performance. Perceived ease of use is the degree to which a person believes that using a particular information system or information technology would be free of effort. Perceived ease of use and perceived usefulness positively affect the attitudes toward an information system; and further, positively affect the individuals’ intentions to use and the acceptance of the information system. In addition, perceived ease of use positively affects the perceived usefulness, and both of perceived ease of use and perceived usefulness are influenced by external variable (Yong-Hui Li, 2009). The measurement items of technology acceptance model are proposed as follows. Perceived ease of use was usually at least measured including three items; a sample item: It is easy for me to use the [Name of information technology]. Perceived usefulness was usually at least measured including three items; a sample item: Using [Name of information technology] would enhance my effectiveness for my study. Attitude was usually at least measured including three items; a sample item: Using [Name of the information technology] is a wise idea. Behavioural intention was usually at least measured including three items; a sample item: I intend to use [Name of information technology] as often as needed (Harridge, 2006). While Theory of Reasoned Action and Theory of Planned Behaviour have the capability to explore the system usage by incorporating subjective norms and perceived behavioural controls with attitudes toward using technology, Technology Acceptance Model is more appropriate to be applied in online contexts for several advantages. First, Technology Acceptance Model is specific on information system usage for applying the concepts of ease of use and usefulness.
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Furthermore, Technology Acceptance Model is more robust in various information system applications.
Perceived Usefulness
External variables
Attitude towards using
Behavioral intention to use
Actual system use
Perceived ease of use Figure 1: Technology Acceptance model Many studies have validated TAM in the context of the World Wide Web. The contribution is facilitated by applying TAM to lay the groundwork for finding antecedents to ease of use and usefulness. Such antecedents might impact the usage of World Wide Web. An understanding of concepts could guide Web site R&D (Albert L. Lederer, 2000). 6. HYPOTHESIS: Hypothesis 1(H1): Perceived risk is negatively related to perceived usefulness and perceived ease of use in the online shopping. Hypothesis 2(H2): Perceived usefulness and perceived ease of use is positively related to behavioural intention in the online shopping. Hypothesis 3(H3): Behavioral intention is positively related to actual purchase behavior in the online shopping. Page 5 of 8
7. RESEARCH METHODOLOGY Empirical study conducted requires a questionnaire approach designed to collect data for testing the reliability and validity of the model and research hypotheses. The questionnaire includes variables such as perceived risk, perceived usefulness, perceived ease of use, behavioral intention, actual purchase behavior, and other basic information such as Age, Gender, Education, Income, Occupation etc. Likert scale shall be used to capture the response of the respondents. 8. SAMPLING PROCESS
8.1 TARGET POPULATION: The target population used in the study are those who have done online shopping at least once as well as individuals who are involved in frequent online purchase.
8.2 SAMPLING METHOD: In this study, Quota sampling shall be employed which includes selecting representative sample from a population having a common characteristic which is online shoppers in this case. 8.3 SAMPLE SIZE: The expected sample size for the study is 250 respondents. 8.4 ADMINISTRATION: The data will be collected through direct interviews, online interviews with the sampling element.
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REFERENCES:
Albert L. Lederer, D. J. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems 29 , 269-282. Alsajjan, B. (2010). INTERNET BANKING ACCEPTANCE MODEL: CROSSMARKET EXAMINATION. Journal of Business Research, Vol. 63, 0148-2963. , 1-19. Amer Al- Adwan, A. A.-A. (2013). Exploring students acceptance of e-learning using Technology Acceptance Model in Jordanian universities. International Journal of Education and Development using Information and Communication Technology , 4-18. Chuttur, M. (2009). Overview of the Technology Acceptance Model: Origins,Developments and Future Directions. Working Papers on Information Systems , 9-37. Forseegame and Microsec research. (2013). Shooping mode of India. Bangalore: Forsee. gefen, D. (2003). TRUST AND TAM IN ONLINE SHOPPING:INTERGRATED MODEL. MIS Quaterly , 51-90. Harridge, S. (2006). Can the building of trust overcome consumer perceived risk online? Emerald , 746-761. Kenny Phan, T. D. (Journal of Industrial engineering and management). Exploring technology acceptance for mobile services. 339-360. Lina Zhou, L. D. (2007). ONLINE SHOPPING ACCEPTANCE MODEL. Journal of Electronic Commerce Research , VOL 8, NO.1. Mohamed Gamal Aboelmaged, T. R. (2013). Mobile Banking Adoption: An Examination of Technology Acceptance Model and Theory of Planned Behavior. International Journal of Business Research and Development , 35-50. Nor, A. S.-A. (2013). Internet Banking Adoption: Integrating Technology Acceptance model and trust. European Journal of Business and Management , Vol.5, No.3. Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students’ Behavioral Intention to Use e-Learning. Educational Technology & Society , 150–162. Shih Chih Chen, S.-H. L. (2011). RECENT RELATED RESEARCH IN TECHNOLOGY ACCEPTANCE MODEL: A LITERATURE REVIEW. Australian Journal of Business and Management Research , 124-127. Page 7 of 8
Weng Marc Lim, D. H. (2012). E-shopping: an Analysis of the Technology Acceptance Model. Modern Applied Science , Vol. 6, No. 4. Yayla, H. Q. (2008). USER ACCEPTANCE OF E-COMMERCE TECHNOLOGY:A META-ANALYTIC COMPARISON OF COMPETING MODELS. Florida: Florida Atlantic University. Yong-Hui Li, J.-W. H. (2009). Applying Theory of Perceived Risk and Technology Acceptance Model in the Online Shopping Channel. World Academy of Science, Engineering and Technology , 29.
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