Factors Influencing E-Commerce Adoption: Evaluation Using Structural Equation Modelling (SEM)
DOI:
https://doi.org/10.33736/ijbs.3334.2020Keywords:
E-commerce, CEO’s technology knowledge, relative advantage, competitive pressure, Small and Medium Enterprises (SMEs), Structural Equation Modelling (SEM)Abstract
Electronic commerce (e-commerce) has become a rapidly growing phenomenon to date. A peep into the exponential growth of the main players in this industry reveals a large reservoir of market potential for ecommerce. Nevertheless, the prevalence of e-commerce adoption has attracted attention from the government, retailers, and academicians to place specific focus on this area. As such, this study determined the correlation between Chief Executive Officer’s (CEO’s) technology knowledge, relative advantages, and competitive pressure through the lens of Tornatzky and Fleischer’s (1990) Organisational, Technological, and Environmental (OTE) model in order to probe into the adoption of e-commerce. CEOs and managers of Small and Medium Enterprises (SMEs) established in the Northern states of Malaysia were selected as the subject of analysis. A total of 283 out of 364 questionnaires distributed were valid for analysing and testing the hypotheses. Next, the gathered data were analysed using Statistical Package for the Social Sciences (SPSS) version 18.0 and Analysis of a Moment Structures (AMOS) version 16.0. The Structural Equation Modelling (SEM) was employed to assess model fit and to test hypotheses. As a conclusion, CEO’s technology knowledge and relative advantage displayed significantly positive influence upon adoption of ecommerce, whereas competitive pressure exhibited insignificant impact upon adoption of e-commerce. In precise, the insignificant influence of competitive pressure on e-commerce implementation appeared to be driven by other unseen variables worthy to be discovered. For future research, a comparison study can be conducted by selecting samples both from employers and employees, as well as other multiple variables associated with e-commerce adoption, so as to keep sampling bias at a minimum level.
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