Adoption of E-Commerce - Research Proposal Example

?Adoption of E-Commerce This paper sought to examine the factors that influence adoption of e-commerce by organisations. The technology adoption model by Rogers has been used as a theoretical framework and five hypotheses developed from the model. A survey of 30 respondents was done using questionnaires. The analysis was performed using descriptive and regression analysis. The results show that all the five factors had a significant influence on e-commerce adoption leading to the conclusion that they influence the adoption of e-commerce technology. Background and problem statement Adoption of electronic commerce has been studied in a number of technology adoption and diffusion studies over the years and the interest in this topic has not stopped yet despite the number of studies. According to Zwass, electronic commerce is defined as “the sharing of business information, maintaining of business relationships, and conducting of business transactions by means of telecommunications networks”. The electronic commerce activities are inter-organisational processes of market-based sell-buy relationships and collaboration, consumer oriented activities, and inter-organisational processes that support them (Zwass). The innovation diffusion theory by Rogers has been widely applied as a theoretical framework to analyse adoption of technology. The framework identified five factors which influence adoption of technology in organisations. These factors are relative advantage, compatibility, complexity, trialability and observability. Relative advantage is defined as “the degree to which an innovation is perceived as being better than the idea it supersedes”. Compatibility is defined as “the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters”. Complexity is defined as “the degree to which an innovation is perceived as relatively difficult to understand and use”. Trialability is defined as “the degree to which an innovation may be experimented with on a limited basis”. Observability is defined as “the degree to which the results of an innovation are visible to others” (Alam et al). While studies have studied these factors in most of technology adoption studies, a lot still remains to be done on how these factors explain adoption of e-commerce in organizations. This study therefore seeks to identify the factors that influence adoption of e-commerce in organisations using Rogers’ model. Research Questions 1. What is the effect of relative advantage on adoption of e-commerce? 2. Does compatibility affect adoption of e-commerce? 3. What is the effect of complexity on adoption of e-commerce? 4. Does trialability affect adoption of e-commerce? 5. What is the effect of observability on adoption of e-commerce? Research Objectives The objectives of this study are: 1. To examine the effect of relative advantage on adoption of e-commerce. 2. To determine the effect of compatibility on adoption of e-commerce. 3. To assess the effect of complexity on adoption of e-commerce. 4. To examine the effect of trialability on adoption of e-commerce. 5. To determine the effect of observability on adoption of e-commerce. Significance of the Study This study is very important to organisations in Saudi Arabia as well as other Arab countries. The results of this study will be very valuable in informing the management of these retail stores on how a number of factors will influence adoption of e-commerce for those who wish to do so. The study is also important to government agencies in charge of policy-making decisions. The study will provide valuable recommendations on how regulation of e-commerce should be carried out based on the results on the adoption factors of e-commerce. The policy recommendations will therefore help come up with solutions that will address the challenges of e-commerce among retailers. Researchers will also find this study valuable source information as a reference material as well as act as a basis for further studies on the subject matter especially in developing countries. Through the suggestions made in this study on what areas need further investigation, researchers will be able to focus on the suggested areas. Literature Review Relative Advantage According to Agarwal and Prasad, relative advantage is the advantage gained by an organisation over previous ways of performing the same task. Firms that see a technology as offering a number of advantages are likely to adopt the technology as opposed to those that do not perceive advantages. Relative advantage is therefore likely to have a positive impact on adoption of electronic commerce. A number of studies have been done in this regard. Limthongchai and Speece in a study on e-commerce adoption in Thailand showed that relative advantage had a positive and significant influence on e-commerce adoption. Alam et al. in their study on factors affecting e-commerce adoption in electronic manufacturing companies in Malaysia found that relative advantage had a positive and significant effect on electronic commerce adoption. Ghobakhloo et al found that perceived relative advantage positively and significantly influenced adoption of e-commerce among SMEs in Iran. Given these results, I hypothesise as follows: H1. There is no relationship between e-commerce adoption and perceived relative advantage. Compatibility Any form of technology will be easier to adopt when it is compatible with the value system, previous ideas, and responsibilities (Tonatzky and Klein). Further, an innovation should be able to meet the needs of the client for it to be adopted. Rogers noted that when an organisation understands the needs of customers, then recommends an innovation that meets those needs and meets them, adoption rate is usually high. A positive effect of compatibility on adoption of electronic commerce is therefore expected. A number of studies have been carried out on this area too. Limthongchai and Speece found a positive and significant impact of compatibility on e-commerce adoption in Thailand. The study by Alam et al in Malaysia revealed that compatibility had a positive and significant influence on electronic commerce adoption among manufacturing firms surveyed. A study by Garcia et al found that perceived compatibility was a significant factor to foster non-buyers’ adoption of electronic business-to-consumer e-commerce. In Iran, Ghobakhloo et al also revealed that perceived compatibility had a positive and significant impact on adoption of e-commerce among SMEs. Given these results, I hypothesise as follows: H2. The adoption of e-commerce is not related to the perceived compatibility of using e-commerce. Complexity With the adoption of any technology or innovation, one needs to acquire complex equipment, possess adequate resources, and technical competencies (Chong). Therefore, when e-commerce is perceived as being complex, adoption rate will be slow and vice versa. A negative relationship is therefore expected. A number of studies have also examined the effect of complexity on electronic commerce adoption. Limthongchai and Speece noted that perceived complexity had a negative but insignificant influence on e-commerce adoption among SMEs in Thailand. Alam et al found that complexity had a negative and significant influence on electronic commerce adoption in Malaysia. Given these results, I hypothesise as follows: H3. The adoption of e-commerce by organisations is not related to the perceived complexity of using e-commerce. Trialability Potential adopters should be able to experiment with an innovation prior to adoption to reduce the uncertainties that are normally associated with new or unfamiliar technologies or products (Rogers). If an innovation can offer trialability, then the potential adopters are more comfortable with it and therefore more likely to recommend it for adoption (Agarwal and Prasad). A positive relationship is therefore expected. The results of Alam et al. showed that trialability had negative but insignificant influence on electronic commerce in Malaysia. Limthongchai and Speece found that trialability was negatively but insignificantly correlated with e-commerce adoption among SMEs in Thailand. Given these results, I hypothesise as follows: H4. The adoption of e-commerce by organisations is not related to the perceived trialability of using e-commerce. Observability Observability is defined as “the degree to which the results of an innovation are visible to others” (Alam et al.). Potential adopters need to easily observe the results of an innovation. When the results can be easily observed, adoption is faster while when it cannot be easily observed the adoption is slow. According to Rogers, this is an important factor especially in the early adoption of innovation. It is expected that observability will have a positive effect on electronic commerce adoption. Studies have also tested the effect of this factor on electronic commerce adoption. Limthongchai and Speece found a positive and significant influence of observability on e-commerce adoption among SMEs in Thailand. Alam et al found that observability had a positive and significant effect on electronic commerce adoption among manufacturing firms in Malaysia. Given these results, I hypothesise as follows: H4. The adoption of e-commerce by organisations is not related to the perceived observability of using e-commerce. Gap in the research literature The studies above have shown that indeed a number of factors influence e-commerce adoption in organisations. However, most of these studies were done in different environments and organisations and not in retail firms. Studies on e-commerce adoption in Saudi Arabia specifically are scarce. Further, studies on e-commerce adoption that have applied the Rogers model in retail firms are very scarce. In the studies above, some of the factors were found to be insignificant. There is therefore a gap in literature which the present study seeks to bridge by focusing on the factors which influence e-commerce adoption in retail firms in Saudi Arabia. The study is therefore based on the following theoretical framework: Source: Author (2013) Methodology The present study uses survey method to gather data from retailers in Saudi Arabia. Specifically, the study targets 30 organisations. These 30 stores were randomly selected. A questionnaire was developed based on the five factors (independent variables) and e-commerce adoption (dependent variable). Demographic variables were also included in the questionnaire. Analysis is done using descriptive analysis and multiple regression analysis. The hypotheses are tested at 5% level of significance. Therefore, results of regression analysis for the independent variables with p-values beyond 5% will lead to acceptance of null hypotheses and any results with p-values less than 5% will lead to the rejection of null hypotheses. Result The results in Table 1 show that most of the firms (53%) had an experience of over 6 years in using the internet while 80% had at least 4 years of existence in the retail business. Most of the stores (60%) were also large with over 50 employees. The results of regression analysis (Table 2) show that relative advantage had a positive and significant impact on e-commerce adoption, p < .01. Hypothesis 1 is therefore rejected because the level of significance is less than 5%. This therefore means that relative advantage of using e-commerce influences the adoption of e-commerce in organisations. The results also show that compatibility positively and significantly influenced e-commerce adoption, p < .01. Since the p-value is less than 5%, H2 is rejected. This therefore means that perceived compatibility of e-commerce application with the organisation influences the adoption of e-commerce in organisations. Further, complexity had negative and significant effect on e-commerce adoption, p < .05. Hypothesis 3 is therefore rejected because the p-value does not exceed 5%. This therefore means that perceived complexity of using e-commerce influences the adoption of e-commerce in organisations. Trialability was found to have a positive and significant impact on e-commerce adoption, p < .05. Hypothesis 4 is therefore rejected as the level of significance is less than 5%. This therefore means that trialability of e-commerce influences the adoption of e-commerce in organisations. The results also revealed that observability had a positive and significant influence on e-commerce adoption, p < .01. Hypothesis 5 is therefore rejected because the p-value is less than 5%. This means that observability of e-commerce influences the adoption of e-commerce in organisations. Discussion The results have clearly shown that all the five factors from Rogers’ technology adoption model as significant predictors of e-commerce adoption among organisations. These results are consistent with a number of studies on e-commerce adoption specifically those of Limthongchai and Speece in Thailand. E-commerce adoption in organisations in Saudi Arabia is influenced by the same factors that have been found to influence technology adoption in other parts of the world and in other unrelated industries. Conclusion The study concludes that e-commerce adoption in organisations is influenced by the relative advantage offered by e-commerce, perceived complexity, perceived compatibility, trialability, and observability. All the effects are positive except for complexity which is negative and significant. Retailers should therefore take keen note on these factors as they influence the adoption of e-commerce. Reference Agarwal, R., Prasad, J. "The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies." Decision Sciences, 28.3 (1997): 557-82. Alam, S.S., Khatibi, A., Ahmad, M.I.S., and Ismail, H.B. "Factors affecting e-commerce adoption in the electronic manufacturing companies in Malaysia." International Journal of Commerce and Management, 17.1/2 (2007): 125 – 139. Chong, S. "Electronic commerce adoption by small- and medium-sized enterprises in Australia: an empirical study of influencing factors." Proceedings for the European Conference of Information Systems (ECIS), 14-16 June 2004. Turku: Finland, 2004. Print. Garcia, A.H., Pradas, S.I., Pelaez, J.C., and Miguel, F.P. “Perceived Compatibility and the Adoption of B2C E-Commerce by Non-buyers”, Organizational, Business, and Technological Aspects of the Knowledge Society Communications in Computer and Information Science, 112 (2010): 186 – 192. Print. Ghobakhloo, M., Aranda, D.A., and Amado, J.B. “Adoption of e-commerce applications in SMEs", Industrial Management & Data Systems,” 111.8 (2011): 1238-1269. Print. Limthongchai, P., and Speece, M.W. "The effect of perceived characteristics of innovation on e-commerce adoption by SMEs in Thailand." Paper presented at The Seventh International Conference on Global Business and Economic Development, 8-11 January, 2003. 1573-85. Print. Rogers, E.M. (1995), The Diffusion of Innovations, New York: Free Press, 1995. Tornatzky, L.G., Klein, K.J. "Innovation characteristics and innovation adoption-implementation: a meta-analysis of findings." IEEE Transactions on Engineering Management, 29.1 (1982): 28-45. Zwass, V. “Electronic Commerce and Organizational Innovation: Aspects and Opportunities.” International Journal of Electronic Commerce, 7.3 (2003): 7-37. Print. Appendices Research Questionnaire Part 1: Demographic Information 1. How long has the store been using the internet? 1 – 3 years [ ] 4 – 6 years [ ] Over 6 years [ ] 2. How long has this store existed? 1 – 3 years [ ] 4 – 6 years [ ] Over 6 years [ ] 3. How many employees does the store currently have? Less than 20 [ ] 20 – 50 [ ] 51 – 100 [ ] Over 100 [ ] Part 2: Electronic Commerce Adoption 4. How often does your retail store use the following e-commerce applications? Mark appropriately with a?. E-commerce features Frequent use Seldom use Never use Web page Selling products Buying supplies 5. To what extent do you agree that the following factors influence adoption of e-commerce in your store? Factor Strongly Disagree Disagree Neutral Agree Strongly agree Relative advantage: Electronic commerce should help … Reduce cost of business operations Improve customer service Improve distribution channels Reap operational benefits Increase ability to compete Perceived Compatibility: Electronic commerce fits well our Organisational beliefs and practices Existing technology infrastructure Communication is very open in our organisation Our organisation has strong relationship with suppliers and customers Our organisation has a positive attitude towards electronic commerce Perceived Complexity Learning to operate electronic commerce is easy Interacting with electronic commerce is flexible My interaction with electronic commerce is clear and understandable It would be easy for me to become skilful at using electronic commerce Trialability We had access to free trial before purchase Firm has opportunity to try a number of e-commerce applications before making a decision We are allowed to use e-commerce on a trial basis long enough to see its true capabilities It was easy to get out after testing e-commerce package Start-up cost for using e-commerce is low Observability There are many computers in the firm which can be used to access internet and e-commerce Competitors and business partners use e-commerce e-commerce helps the company to connect with domestic and international business partners anytime e-commerce use has shown improved results over doing business the traditional way The end Tables Table 1: Demographic Variables No. Demographic variables N % Cumulative % 1 Years of internet experience 1 – 3 years 5 17 17 4 – 6 years 9 30 47 Over 6 years 16 53 100 2 Years of retailing experience 1 – 3 years 6 20 20 4 – 6 years 12 40 60 Over 6 years 12 40 100 3 Size of firms Less than 20 3 10 10 20 – 50 years 9 30 40 51 – 100 years 7 23 63 Over 100 years 11 37 100 Table 2: Regression Results Variable Estimate Standard error p-value Relative advantage 0.641 0.012 0.000 Compatibility 0.341 0.141 0.000 Complexity - 0.214 0.114 0.021 Trialability 0.314 0.074 0.014 Observability 0.354 0.061 0.007 Read More