Previous literature in IT adoption has proposed more and more factors, and their correlations have been used to
give us formulas, e.g. - a cross-country study of e-business adoption by Zhu et al. [2002]. In some respects, those
researches have provided insightful views for analysis in future study. However, their research findings have limited
practical relevance for real situations in different levels of IT adoption. For example, one of Zhu et al.’s [2002]
hypotheses is ‘Larger firms are more likely to adopt eBusiness’. If people surf on the Internet, they will find out all
types of eBusiness activities which have been created by small firms. A clever idea can make small enterprises
successful with little investments of IT infrastructure, such as the inaugurator of search engine ‘Yahoo.com!’, and
the famous Taiwanese cosmetic online retailer ‘eBeauty’. They both started with very few resources and capital. As
a matter of fact, regardless of what IT adoption level a firms has, it can adopt eCommerce and be Internet ready.
Without carefully differentiating the levels of IT adoption so as to map those factors, models might be hardly
practical. Therefore, we suggest that the internal and external factors identified in the previous literature should be
integrated into those practical levels as portrayed in figure 1. It is also expected to examine those factors with
adjustable scales to compare samples or static scales for a set of similar firms as cluster analyses.
Previous literature in IT adoption has proposed more and more factors, and their correlations have been used to
give us formulas, e.g. - a cross-country study of e-business adoption by Zhu et al. [2002]. In some respects, those
researches have provided insightful views for analysis in future study. However, their research findings have limited
practical relevance for real situations in different levels of IT adoption. For example, one of Zhu et al.’s [2002]
hypotheses is ‘Larger firms are more likely to adopt eBusiness’. If people surf on the Internet, they will find out all
types of eBusiness activities which have been created by small firms. A clever idea can make small enterprises
successful with little investments of IT infrastructure, such as the inaugurator of search engine ‘Yahoo.com!’, and
the famous Taiwanese cosmetic online retailer ‘eBeauty’. They both started with very few resources and capital. As
a matter of fact, regardless of what IT adoption level a firms has, it can adopt eCommerce and be Internet ready.
Without carefully differentiating the levels of IT adoption so as to map those factors, models might be hardly
practical. Therefore, we suggest that the internal and external factors identified in the previous literature should be
integrated into those practical levels as portrayed in figure 1. It is also expected to examine those factors with
adjustable scales to compare samples or static scales for a set of similar firms as cluster analyses.
การแปล กรุณารอสักครู่..