تعامل شناختی با یک ابزار چندرسانه ای آموزش ERP: برر سیخوداثربخشی کامپیوتر و پذیرش فن آوری
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|26276||2009||12 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Information & Management, Volume 46, Issue 4, May 2009, Pages 221–232
Computer self-efficacy (CSE) is a person's judgment of his or her ability to use a computer system. We investigated cognitive engagement, prior experience, computer anxiety, and organizational support as determinants of CSE in the use of a multimedia ERP system's training tool. We also examined the impact of CSE on its acceptance. We determined the benefits of a sequential multi-method approach using structural equation modeling and neural network analysis. High reliability predictions of individual CSE were achieved with a sequential multi-method approach. Specifically, we obtained almost 68% perfect CSE group prediction overall, with almost 85% perfect CSE group prediction using fuzzy sets and over 94% accuracy within one group classification. The resulting CSE assessment and classification enables management interventions, such as allocating users to appropriate instruction for more effective training.
ERP systems are deployed in over 70% of all U.S. medium to large corporations; they spent about $51 billion on formal training in 2004 and 38.4% of that was for end-users. End-user training normally accounts for 30% of ERP project costs, but organizations that spend less than 15% are likely to have inadequately trained users resulting in implementation delays and escalating costs. However, very little research has focused on the use of multimedia technology for training. Given this gap, we decided to investigate user engagement and acceptance of a multimedia ERP training tool. We built on past research by incorporating user engagement in TAM. In fact, perceived ease of use (PEOU) is strongly anchored to general beliefs about computers, such as CSE, an individual self-assessment of ability to use a computer. Low CSE may hinder computer learning. Consequently, assessing CSE and its determinants could help an organization understand the role of PEOU on acceptance of a multimedia ERP training tool. The training tool we tested was professionally produced for an ERP vendor; it included movie clips, audio enhanced presentations and screen cams. Prior research had suggested that experience, computer anxiety (CA), and organizational support were important antecedents to CSE, though empirical results had shown inconsistency. We analyzed this and proposed cognitive engagement as a critical determinant of CSE in the use of a multimedia-training tool. Therefore, our goal was to improve understanding of the role of multimedia technology in user engagement during ERP training and to assess CSE as potential inhibitors or enablers of the use and acceptance of a training tool. Our research questions were: (1) “Does engagement influence CSE?,” (2) “What other factors affect CSE?,” (3) “Does CSE in a multimedia ERP training context affect system acceptance?” and (4) “How can CSE classification be derived from engagement and support measures?”. To examine these questions, we employed two analytic methods, with the results from the first, SEM, feeding into a neural network analysis, NN. This was therefore a sequential multi-method research design. SEMs strength in path analysis was used to help answer the first three research questions while NNs strength in classification was needed to answer the last question. Since different analytic methods focus on different aspects of reality, a richer understanding of the topic could be gained by combining methods. Mingers advocated that research situations were inherently complex and multidimensional and would benefit from a range of methods . By combining methodologies we can develop a method where “the advantages of one analysis technique offset the disadvantages of another”