اضافه کردن ویژگی های متنی به مدل قبول واقعیت فناوری
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|38523||2006||21 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers in Human Behavior, Volume 22, Issue 3, May 2006, Pages 427–447
Abstract This paper examines the influence of contextual specificity when describing technology acceptance. Social cognitive theory provides the basis for adding several independent variables (computer anxiety, prior experience, other’s use, organizational support, task structure, and system quality) and one intervening variable (computer-efficacy) to the technology acceptance model (TAM). This extended model was tested using a mail survey and the results are tabulated using partial least squares. The results show that system usage is strongly influenced by computer anxiety, prior experience, other’s use, organizational support, task structure, system quality, and perceived usefulness. In addition, perceived usefulness is the strongest mediator in determining system usage.
. Introduction Researchers and practitioners alike strive to understand individuals’ unwillingness to accept systems that appear to promise substantial benefits. Davis, Bagozzi, and Warshaw (1989, p. 587) conclude that, “understanding why people accept or reject computers has proven to be one of the most challenging issues in IS research.” This lack of understanding continues despite recent improvements in application usability and ease of use (Hasan, 2003). With employees seemingly accepting and rejecting systems unsystematically, many organizations are failing to achieve the benefits promised to them by software manufacturers. The technology acceptance model (TAM) is one of the most widely used models for describing IT usage behaviors (Igbaria, Guimaraes, & Davis, 1995). The TAM asserts that IT behaviors are based largely on users’ perceptions of a system’s ease of use and usefulness. While the model “has been empirically proven to have high validity” (Chau, 1996, p.187), it “only supplies general information on users’ opinions about a system” (Mathieson, 1991, p. 173). Similarly, user evaluation measures, such as perceived ease of use and perceived usefulness, encompass many different user meanings and theoretical constructs (Chau, 1996, Moore and Benbasat, 1991 and Segars and Grover, 1994). Goodhue (1995, p. 1828) concludes that “there are so many different underlying constructs, it is probably not possible to develop a single general theoretical basis for user evaluations.” Cognitive psychologists support arguments opposing the mental averaging of an activity domain. “Combining diverse attributes into a single index creates confusions about what is actually being measured and how much weight is given to particular attributes in the forced summary judgment” (Bandura, 1997, p. 11).