ارزیابی تجربی از پایان تجدید نظر مدل قبول واقعیت محاسبات کاربران
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|38527||2007||13 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers in Human Behavior, Volume 23, Issue 1, January 2007, Pages 162–174
Abstract This paper proposed a revised technology acceptance model for measuring end user computing (EUC) acceptance. An empirical study was conducted to collect data. This data was empirically used to test the proposed research model. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to examine the reliability and validity of the measurement model. The results demonstrate that the model explains 56% of the variance. This finding contributes to an expanded understanding of the factors that promote EUC acceptance. The implication of this work to both researchers and practitioners is discussed.
. Introduction With the recent growth of practical information technology in such areas as engineering and business, the topics of end user computing (EUC) deserve careful attention. Today, knowledge workers are increasingly using sophisticated tools to develop their own information systems to help them efficiently manage work. EUC acceptance has been established as one of the critical success factors in achieving business success. It is becoming a fundamental part of the organizational plan. End user computing acceptance is one of the most widely researched topics in the information field. The definition of the EUC is not consistent in the literature. Here, the EUC is defined as the adoption and use of information technology by personnel outside the information systems department to develop software applications in support of organizational tasks (Brancheau & Brown, 1993). The reasoned action theory (TRA) is a well-established model and has been broadly used to predict and explain human behavior in various domains. Davis proposed the technology acceptance model (TAM) derived from TRA that has been tested and extended by numerous empirical researches (Davis, 1989, Henderson and Divett, 2003, Igbaria et al., 1997, Legris et al., 2003 and Venkatesh and Davis, 2000). As Davis (1989) pointed out, the original TAM model consists of perceived ease of use (PEOU), perceived usefulness (PU), attitude toward using (AT), behavioral intention to use (BI), and actual system use (AU). PU and PEOU are the primary determinates of system use while prior researches have indicated that attitude towards the technology is not a significant mediating variable. TAM has been proven for its validity and ability to satisfactorily explain end user system usage (SU). Igbaria et al. (1997) assumed that the antecedents of the end user’s perception are intra-organizational and extra-organizational factors. However, Igbaria et al. pointed out that the model variables in their study only explained 25% of the variance in system usage and suggested that further research should incorporate other variables into the model. In addition, some other EUC acceptance researches using TAM are summarized in Table 1. Table 1 shows that none of the explained variance for the model is above 30%. Comprehending the essentials of what determines EUC acceptance can provide great management insights for promoting EUC success. Therefore, this research adopts the TAM, from Igbaria et al. (1997), and integrates it with the task-technology fit theory (TTF), network externality, subject norm, computer self-efficacy and computer enjoyment variables to investigate what determines EUC acceptance. The proposed model is then evaluated. Table 1. Prior TAM for EUC Reference Model The explained variance of the model (%) Adams et al. (1992) Perceived ease of use → Usage 30 Perceived usefulness → Usage Igbaria, Parasuraman, and Baroudi (1996) Organizational support → Usage 28 Complexity → Usage Usefulness → Usage Enjoyment → Usage Social pressure → Usage Igbaria et al. (1997) Internal computing support → Usage 28 Internal computing training → Usage Management support → Usage Internal computing support → Usage External computing support → Usage Perceived ease of use → Usage Perceived usefulness → Usage Table options The rest of the paper is organized as follows. Section 2 reviews the related works and describes the research model and hypotheses. Section 3 presents the research method used in this study. Section 4 analyzes the data and tests the model. Section 5 discusses the results. The last section summarizes and concludes this paper.
نتیجه گیری انگلیسی
7. Conclusion This study proposed a revised TAM that adopted the TAM, from Igbaria et al. (1997), and integrated it with the task-technology fit theory, network externality, subject norm, computer self-efficacy and computer enjoyment variables to investigate what determines EUC acceptance. The results showed that perceived usefulness, perceived ease of use, and computer enjoyment all directly influence actual usage. The essential determinant for actual use is computer enjoyment. If users enjoy using the EUC, they may tend to underestimate the difficulty or process involved in using a new system because they simply enjoy the process and do not perceive it as being effortful (Venkatesh, 2000). Network externality has a direct effect on perceived ease of use. When EUC become more conventional, users can easily obtain information and they become easy to use EUC. The results also indicated that task-technology fit has a direct influence on the perceived ease of use. This is consistent with prior research (Dishaw & Strong, 1999). When the degree of fitness between the task and the tool becomes higher, users perceive the tool to be easier to use for that task. The above findings provide an expanded understanding of the factors that promote EUC acceptance. There were some limitations in our study. First, the number of the returned questionnaires was not broad enough. Because the subjects were limited to employee outside the MIS department, many respondents did not actually know what EUC is. This might have decreased their willing to complete the questionnaires. This study proposed an integrated model and increased the explained variance for EUC acceptance. As information technology diffuses throughout companies, EUC develops a more important role helping workers to complete their work efficiently. In a further study, we could select one company and use our model to help them introduce EUC. The effects from EUC use could be examined. We will leave this issue for further research. The combination of information obtained in this study and from future studies would be valuable to educators, researchers and managers.