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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Knowledge-Based Systems, Volume 24, Issue 3, April 2011, Pages 355–366
This study examines the factors that influence employees’ adoption and use of e-learning systems and tests the applicability of the technology acceptance model (TAM) in the organizational context. We examined the relationship of employees’ perceptions of their behavioral intention to use e-learning systems in terms of four determinants (individual, organizational, task characteristics, and subjective norm), to further explore the effects of management and organizational support on the subjective norm. Data were 357 valid questionnaires from four industries in Taiwan. The findings indicate that organizational support and management support significantly affected perceived usefulness and intention to use. Individuals’ experience with computers and computer self-efficacy had significantly positive effects on perceived ease of use. Task equivocality significantly influenced perceived usefulness. Organizational and management supports significantly impacted the subjective norm, perceived usefulness, perceived ease of use, and intention to use. Additionally, the results suggest that external variables that affect perceived usefulness, perceived ease of use, and intention to use, need to be considered as important factors in the process of designing, implementing, and operating e-learning systems. The results provided a more comprehensive insight of individual, organizational, and task characteristics in predicting e-learning acceptance behavior in the organizational contexts, rarely tested in previous studies. By considering these identified factors, practitioners can take corresponding measures to predict or promote organizational employees’ e-learning systems acceptance more effectively and efficiently. Furthermore, by explaining employees’ acceptance behavior, the findings of this research help to develop more user-friendly e-learning systems and provide insight into the best way to promote e-learning systems for employees.
Information technology has dramatically altered the way people teach and learn. Electronic learning (e-learning), a new approach in education, highlights learner-oriented and life-long teaching–learning processes (Ong et al., 2003) . E-learning generally refers to the use of computer network technology, primarily over an intranet or through the Internet, to deliver information and instruction to individuals. The characteristics of e-learning fulfill the requirements for learning in a technologically advanced society and have created great demand from businesses for e-learning systems . E-learning allows training to reach diverse and geographically dispersed workforces in a cost-efficient manner, and can take place on-demand and at a lesser cost than on-site training. E-learning systems have become popular tools for facilitating teaching and learning processes that allow flexible learner-centered training. In this case, the e-learning system is defined as an information system that can integrate a wide variety of instructional material (via audio, video, and text mediums) conveyed through e-mail, live chat sessions, online discussions, forums, quizzes and assignments. Additionally, e-learning encompasses Internet, intranet, extranet, satellite broadcasts, interactive TV and CD-ROMs, allowing for synchronous and asynchronous communication and instructional delivery between trainers and learners. Consequently, these e-learning systems may better meet the needs of employees who are geographically dispersed or have conflicting schedules. In order to meet the needs of today’s highly competitive global economy, employees must be up-to-date with the latest knowledge and technologies. To cultivate a highly trained and educated workforce, organizations have invested substantial resources in developing e-learning alternatives to traditional types of training systems . Training is considered to be a key strategic organizational tool and is associated with higher profits and lower employee turnover. Many organizations have adopted e-learning solutions for their corporate training, such as Dell Learning, CISCO E-Learning, and the HP Virtual Classroom . As a result, organizations are increasingly relying on e-learning as a solution to training issues of immediacy, convenience, and consistency . E-learning plays a significant role in training and development within the organizational environment. The benefits of e-learning applications in organizations and educational institutions have been discussed in many studies , , ,  and . Although e-learning systems are increasingly being used and are proving to be beneficial in organizations and educational institutions, the problem of underutilization remains , ,  and . Whereas business and educational institutions have invested substantial resources in e-learning systems  and , the benefits of such systems will not be achieved if learners fail to use the system  and . Therefore, researchers and practitioners alike strive to investigate the decision of whether an individual will adopt those technology systems that appear to promise substantial benefits , , ,  and  (Hu et al., 1999; Venkatesh et al., 2003). Furthermore, the study of user perception (McMahon et al., 1999) and an understanding the factors that promote effective use of those systems (Mun & Hwang, 2003) become increasingly essential to improve understanding and prediction of acceptance and utilization of educational technologies in organizational contexts (Lau & Woods, 2008). Prior empirical studies made efforts to explicate the determinants and mechanisms of users’ adoption decisions on the basis of the technology acceptance model (TAM) , , , ,  and  with the conviction that the adoption process influences successful use of particular technology systems (Grover et al., 1998; Karahanna, Straub, & Chervany, 1999; Liao, Palvia, & Chen, 2009). The TAM, adapted from a theory of reasoned action (TRA)  and , has been used as a theoretical basis for many empirical studies of user technology acceptance ,  and . The TAM has partially contributed to understanding end-users’ acceptance of e-learning systems (Ajzen & Fishbein, 1977) , ,  and . A number of studies have focused on acceptance by students in educational institutions , , ,  and . However, research literature that addresses learner acceptance of e-learning systems in organizational contexts is scarce. Ong et al.  examined perceived credibility and computer self-efficacy to investigate the applicability of the TAM in explaining engineers’ decisions to accept e-learning. In their investigation of workers’ intentions to use e-learning in four international agencies of United Nations, Roca and Gagne (2007) proposed perceived autonomy support, perceived competence and perceived relatedness as determinants of the TAM variables. Although research exists on some specific external variables in an attempt to understand users’ acceptance behavior of e-learning in organizational contexts, existing parameters of the TAM are not sufficient to fully reflect the e-learning system end-users’ acceptance within organizations, and further examination of additional factors is still required . Thus far, it has not been clear as to what additional factors would affect e-learning system usage behavior and intentions in organizational contexts. Studies investigating the determinants related to e-learning systems use have not been empirically tested from the more comprehensive perspectives of individual, organizational, and task characteristics in the organizational context , ,  and . Additionally, researchers have suggested that TAM studies should extend beyond technology-based tools and include a broader range of social factors, such as the subjective norm, to better predict users’ technology use and acceptance ,  and . Subjective norm, a construct from the theory of reasoned action (TRA), was found to be affected by external variables . A substantial body of empirical evidence has been accumulated to provide support for the predictive power of the combined model of TAM and TRA in the context of IT acceptance , , ,  and . However, several researchers (David et al., 1989)  indicated that subjective norm was not a significant construct in TAM. This could be attributed to the use of students as respondents in many TAM studies. As Taylor and Todd  noted, subjective norm is expected to be more important in an organizational setting. In the present study, the participants were those who may experience some social pressure to use the e-learning systems in the organizations. Accordingly, the present study used the TAM as a baseline model and the inclusion of subjective norm (from TRA) to explain the dynamics of user acceptance of an e-learning system. The purpose was to establish a theoretical framework for understanding the conditions under which e-learning systems adoption was practical and beneficial in the organizational context. Specifically, we identified a rich set of antecedents to determine the comprehensive nature of e-learning systems adoption in organizations. To accomplish this aim, structure equation modeling (SEM) was applied to examine and validate the hypothesized relationships of employees’ perceptions of their behavioral intention to use e-learning systems in terms of four aspects of determinants (individual, organizational, task characteristics, and subjective norm), and to further explore the effect of management and organizational support on subjective norms. Hopefully, by examining the impact of these specific antecedents on e-learning systems acceptance in organizations, the knowledge base on important determinants of e-learning system adoption can be expanded. This empirical study could be useful for researchers to develop theories, and practitioners to better understand the strategies for designing and promoting e-learning systems in organizations. In the next section, we establish the theoretical foundation for the research model, and explain our reasons for adopting it as the theoretical framework of this study. This is followed by a description of the survey instruments and data collection methods. We then present the results of testing our hypotheses, and finally, the limitations, conclusions, and implications are discussed.
نتیجه گیری انگلیسی
The study results clearly indicate that the TAM appears to provide researchers with a theoretically sound and parsimonious model that can be used to predict the employees’ behavioral intentions to use the e-learning systems in organizations. In agreement with prior findings ,  and , it was found that both PU and PEU were important factors in determining the acceptance of e-learning systems in organizations. Our findings provide evidence for the power of the TAM in explaining the employees’ intention to use e-learning systems in particular. Specifically, there exists a strong relationship between PEU and PU, as originally proposed by Davis et al. , and they were also significantly associated with behavioral intentions to use e-learning systems. Furthermore, according to Park et al. (2009), the key variables of the TAM (PU and PEU) may function differently depending on the external variables of specific research settings. This study employed seven external variables representing organizational characteristics, individual differences, task features, and social factors. Our findings showed that OS was significantly associated with PU and, in turn, related to the intention to use. Consistent with previous findings , this study found that given assistance and other resources from the organization, employees were likely to believe that e-learning systems were useful. Consistent with previous empirical studies, our results confirm the relationship that organizational support affects information technology implementation. Furthermore, this study found that management support significantly influenced PEU; such results are consistent with Taylor and Todd , Lin and Wu . In terms of organizational contexts, the training and e-learning systems were designed to meet organizational strategic goals; thus, employees perceive the usefulness of the e-learning systems to be an improvement in learning performance. Additionally, in our study, the role of management was perceived by the employees as facilitators and supporters of the use of e-learning systems; because of the mangers’ continuous support for using e-learning systems, employees tended to perceive the e-learning systems as easy to use. Since our results showed insignificant relationships between OS to PEU and MS to PU, and previous studies have yielded mixed results, further investigation should be conducted to individually examine the effects of OS and MS on PEU and PU in various contexts of e-learning systems. This study found that IEC significantly affected PEU, which was consistent with existing research showing that IEC influences users’ intention to use various technology applications (e.g. e-learning)  and . It may be inferred that users employ the knowledge gained from computer experience to perceive the ease of use of the system, which in turn enhances their intentions to use the e-learning systems. Consistent with previous studies  and , it was found that CSE is an important determinant of PEU. Those who were highly confident in their computer skills were more likely to perceive e-learning systems as easy to use, which resulted in higher BI. From a management perspective, our findings suggest that CSE is important, and trainers must overcome certain baseline learning curves beyond which technology acceptance can be facilitated by training on more sophisticated technologies . When employees did not have sufficient knowledge of information technology or they had very limited computer literacy, their PEU of information technology was greatly diminished . Our results indicate a lack of association between CSE and PU. Therefore, it was suggested that trainers should include lessons that promote the employees’ computer self-efficacy to help them obtain the computer literacy necessary to find training relevant to their job performance. Similar to the findings of previous studies , this study found that task interdependence (TI) significantly affected employees’ PEU of the e-learning systems. Thus, the level of task autonomy may impact the users’ perception of ease of use. Since e-learning systems are a relatively novel technology, employees must learn them in the workplace rather than school, and they are likely to look for help from their personal network when encountering difficulties using the system. For individuals whose job required a high level of interaction with others, consulting and interacting with social referents is not unusual. Thus, when they encounter difficulties in using IT systems, they may tend to search for social support. Thus, the level of task interdependence would be an important factor affecting employees’ perception of the e-learning systems ease of use. As for the influence of TI on PU, previous studies showed scant empirical evidence to examine the role of TI in the extended TAM model. This issue is worth pursuing in future research. On the other hand, our results indicated that task equivocality (TE) did not significantly influence PEU and PU. Employees’ PEU was primarily determined by whether the e-learning system was easy to use; therefore, task equivocality was not a major factor influencing the employees’ perceived ease of use of an e-learning system, which is consistent with the results by Kim et al. (2008). Moreover, when employees encounter a high level of task uncertainty, they may tend to rely on organizational predetermined procedures to perform their work, instead of depending on the use of e-learning systems, and may not perceive the e-learning systems useful to them. From a management perspective, in order to foster e-learning systems acceptance, administrators and trainers must stress, demonstrate, and communicate convincing evidence that convey the e-learning systems’ relevance to employees’ tasks. Given these conflicting results, more research remains to be done to explore the precise roles of task characteristics in this area. Our findings showed that the SN, a new construct incorporated into the TAM, played a significant role on PU and PEU as congruent with previous studies ,  and . This meant that whether the employees perceived the e-learning system easy to use was influenced by the SN. It may imply that whether people decide to use e-learning systems could be partly attributed to their motivation of being attached to significant others. The above findings suggest that employees might subconsciously align their perceptions and initial acceptance decisions with colleagues’ or significant social referents’ opinions or suggestions. In our case, the employees might have exhibited an intention to accept e-learning systems at the beginning of the training partially because of the perceived assessments of colleagues or significant social referents. In addition, with a higher level of the SN, people tend to build interpersonal relationships with others, and they are more likely to use the e-learning systems with the influence of significant social referents. Managers should consider means for developing a positive community norm as this forms and reinforces initial technology acceptance. Meanwhile, they should leverage such norms by assisting employees to acquire more expertise and experience in using the technology  and . SN has been a special interest in this study since Taiwanese people tend to be sensitive to other people’s opinions and expectations . This study confirmed previous studies ,  and  and found significant influences of MS and OS on the SN, which affected the individuals’ PU and PEU. Consequently, the employees could be encouraged to use e-learning systems through various approaches: (1) attending compulsory training in using e-learning systems for organizations; (2) providing the necessary support and resources in using e-learning systems; (3) role modeling by managers, and (4) being exposed to organizational policies on the use of the e-learning systems. With regard to the variables measuring task characteristics, it was found that TE and TI did not significantly affect the SN, contrary to expectation. Such findings were consistent with Kim et al. , showing that TE did not have an impact on SN. However, Kim et al.  indicated that TI significantly affected the SN given the use of Internet in the nation of Korea. Our findings could be attributed to the fact that different national settings and IT utilization could lead to specific task characteristics, which may influence the interpersonal relationships with others in the workplace. Given the conflicting results, more research remains to be done to explore the precise relationship between the SN and task characteristics in this area. Given the amount of attention on the aforementioned factors, this study points out a path for future research that would be valuable for both researchers and practitioners. Although this research was quantitative in design to better establish the nature of the relationships, our understanding of these constructs could be enhanced by future studies that use qualitative as well as quantitative methodologies. In summary, the findings of this study suggest that both the key variables (PU, PEU) and external variables (OS, MS, CSE, IEC, TI, and SN) should be considered as important factors in the process of designing, implementing, and operating e-learning systems in organizations. In particular, the individual characteristics that motivate users to adopt e-learning systems (CSE and IEC), the task features that influence the employee’s perceived ease of use of the e-learning systems (TI), the organizational characteristics that support e-learning activities (OS and MS), and the social factors (SN) that influence an individual’s decision to use IT were critical to increasing an employee’s behavioral intention to use e-learning systems. Overall, the results of this study emphasize the importance of employees’ surrounding environments over and beyond the implementation of an e-learning system itself. Thus, it is suggested that the concepts of organizational factors and employee-centered design are key aspects of e-learning systems development.