Computer-Related Task Performance: A new perspective

The existing information system (IS) literature has acknowledged computer self-efficacy (CSE) as an important factor contributing to enhancements in computer-related task performance. However, the empirical results of CSE on performance have not always been consistent, and increasing an individual's CSE is often a cumbersome process. Thus, we introduce the theoretical concept of self-prophecy (SP) and examine how this social influence strategy can be used to improve computer-related task performance. Two experiments are conducted to examine the influence of SP on task performance. Results show that SP and CSE interact to influence performance. Implications are then discussed in terms of organizations’ ability to increase performance.     

Cognitive engagement with a multimedia ERP training tool: Assessing computer self-efficacy and technology acceptance

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.     

How and why trust matters in post-adoptive usage: The mediating roles of internal and external self-efficacy

Since the underutilization of technology often prevents organizations from reaping expected benefits from IT investments, an increasing body of literature studies how to elicit value-added, post-adoptive IT use behaviors. Such behaviors include extended and innovative feature use, both of which are exploratory in nature and can lead to improved work performance. Since these exploratory behaviors can be risky, research has directed attention to trust in technology as an antecedent to post-adoptive IT use. In parallel, research has examined how computer self-efficacy relates to post-adoptive IT use. While such research has found that both trust and efficacy can lead to value-added IT use and that they might do so interdependently, scant research has examined the interplay between these antecedents to post-adoptive IT use. Drawing on the Model of Proactive Work Behavior with a focus on its predictions about trust and efficacy, we develop a research model that integrates trust in technology and computer self-efficacy in the post-adoption context. Our model suggests that the two concepts are interdependent such that trust-related impacts on post-adoptive use behaviors unfold via computer-related self-efficacy beliefs. Contemporary tests of mediation on data from more than 350 respondents provided support for our model. Hence, our findings begin to open the black box by which trust-related impacts on post-adoptive behaviors unfold, revealing computer self-efficacy as an important mediating factor. In doing so, this study furthers understanding of how, and why, trust matters in post-adoptive usage, enabling strategic change management by elucidating the “fit” between technological characteristics and post-adoptive usage.     

Computer skills instruction for pre-service teachers: A comparison of three instructional approaches

The computer self-efficacy of teachers contributes positively to their technology integration self-efficacy. Many studies have examined instructional strategies that foster computer self-efficacy but not their corresponding impact on teachers’ technology integration self-efficacy. This study investigated the instructional strategies used for pre-service teacher computer skills instruction and their corresponding impact on teacher computer self-efficacy and technology integration self-efficacy. Using a multiple case-study approach, video recordings were made of the class sessions of three participating instructors throughout a semester. Content analysis of these video recordings found the instructors using three approaches of computer skills instruction: Extensive behavioral modeling, targeted behavioral modeling, and independent problem-solving. Analysis of pre and post-study student survey responses also found that the three instructional approaches raised their perceived computer self-efficacy. However, the effect sizes were largest when the independent problem-solving approach was used. This approach was also found to have had better motivational effects on students than the extensive behavioral modeling approach. On the other hand, computer skills instruction increased students’ technology integration self-efficacy only when instructors modeled teaching-related examples and provided students with multiple mastery experiences of technology integration practices. The applications of the three computer skills instructional approaches for teacher education are discussed.     

Understanding the continuance use of social network sites: a computer self-efficacy perspective

Based on social cognitive theory and the balanced thinking–feelings model, this study proposes a research model to examine the different roles of general computer self-efficacy (CSE) and specific CSE. The research model was tested with a survey of university students in Singapore in the Facebook context. It is found that while general CSE affects continuance intention through both cognition and affection, specific CSE mainly affects continuance intention through cognition. It is also found that general computer experience affects general CSE only and specific computer experience affects specific CSE only.     

Effects of computer self-efficacy and system reliability on user interaction with decision support systems

Computer self-efficacy (CSE) has been identified as a major determinant of computer-related ability and usage in organizational contexts. However, there has been little research on the impact of CSE on the use of high level computerized systems such as decision support systems. In order to examine this relationship, participants completed a visual search task with the assistance of an automated decision support system which varied in reliability from moderately reliable (70%) to highly reliable (90%). After completion of the task, a median split was performed on participants’ CSE scores to divide participants into high-CSE and low-CSE groups. We examined the relationship between CSE and trust and utilization of the system. High-CSE participants trusted the system more, complied with it more and generated significantly more hits than low-CSE participants, particularly on trials in which the aid was highly reliable. This indicated that high-CSE levels led to a better ability to gauge the true capabilities of the system. However, all participants uniformly underestimated the true reliability of the system at both levels of CSE. This study provides insight into the potential significance of personality factors in shaping human–technology interaction and has implications for designers of automated systems.     

Computer training, frequency of usage and burnout: the moderating role of computer self-efficacy

The main aim of this paper is to test the moderating role of computer self-efficacy in the relationship among computer training, frequency of usage and burnout (i.e. exhaustion and cynicism). The sample was made up of 140 workers using computer-aided technology in their jobs. Hierarchical multiple regression analyses were carried out. Results show that frequency of usage and computer training are positively associated with computer self-efficacy. Futhermore, we found interaction effects between computer training×computer self-efficacy on both indicators of burnout as outcomes. Computer self-efficacy moderated the relationship between computer training and burnout. Limitations of the study and practical implications of these findings are discussed.     

Initial Empirical Testing of Potential Factors Contributing to Patient Use of Secure Medical Teleconferencing

Providing timely and cost-effective healthcare appears to be significantly desired. Factors such as computer skills and comprehension of instructions impact people’s perception of the accessibility of such alternatives, especially for medical professionals. There are limited studies examining the aforementioned factors in information systems (IS) literature in the context of medical teleconferencing (ehealth) from the patients’ perspective. Thus, the purpose of this research study was to examine the underlying structure of four factors, namely IS usage (ISU), computer self-efficacy (CSE), ethical severity of misusing IS (ESMIS), and the resistance to use IS (RESUIS). Based on data gathered from 140 participants, confirmatory factor analysis (CFA) was conducted, using the partial least squares (PLS) technique. Results indicated a very strong validity and reliability of the constructs, however, with a relatively low overall model predictability. Furthermore, the constructs of CSE and RESUIS appear to demonstrate significant contribution toward ISU.     

Toward IT support for coordination in network organizations

A critical issue facing managers of information technology (IT) today is how to respond to the emergence and growth of the network organization that is virtually formed by separate firms, each retaining its own authority in major budgeting and pricing matters, to function as integral parts of a greater organization. What can and should be done from an IT standpoint to support and exploit this new organization form? What needs and opportunities exist for new kinds of computer-based systems devised specifically to facilitate management and coordination in network organizations? A prerequisite for answering these questions in a systematic, definitive way is clear understanding of the variables and constructs involved in coordinating such organizations. An empirically supported model of coordination in network organizations is introduced. Our model development takes a ‘reputation’-oriented framework of coordination within network organizations as a starting point. The model posits that participating firms' reputation strongly influence coordination decisions in networks, affecting each firms' initiation into the organization, selection for task execution, and termination from the network.     

Factors affecting e-training adoption: an examination of perceived cost,computer self-efficacy and the technology acceptance model

The objective of this paper is to highlight the role that perceived cost, computer self-efficacy and the technology acceptance model (TAM) constructs have in e-training adoption in the Nigerian civil service. With the use of the SmartPLS 2.0 M3 software, a framework that included perceived cost, computer self-efficacy and TAM constructs (perceived usefulness (PU) and perceived ease of use (PEOU)) was tested on 450 heads of departments. Scales on perceived cost, computer self-efficacy, PU and PEOU developed by previous studies were modified accordingly and used. This paper found perceived cost to have a significant effect on e-training adoption. Computer self-efficacy was statistically insignificant through PEOU. In addition, PEOU had an indirect effect through PU. Therefore, only PU of the TAM constructs indicated strong predictive strength in e-training adoption. This paper showed that with e-training adoption, facilities such as computers can be put in place, which can improve the outlook of the civil service. In addition, the cost that is usually associated with traditional training can be reduced, increasing the opportunity to invest in other aspects of the civil service which can help in adding to the overall performance. Relationships were examined in this paper, which were shown to be favourable to e-training adoption in the Nigerian civil service.     

Teacher self-efficacy,academic self-efficacy,and computer self-efficacy as predictors of attitude toward applying computer-supported education

There is a large body of research regarding teacher self-efficacy, academic self-efficacy, computer self-efficacy, and attitude toward applying computer-supported education of teachers and prospective teachers. However, no study has been conducted on the correlation among the effects of teacher self-efficacy, academic self-efficacy, computer self-efficacy, and attitude toward applying computer-supported education and which additionally explains their relationships to one other. This research is conducted in order to test the effect levels among the latent variables of teacher self-efficacy, academic self-efficacy, computer self-efficacy, and attitude toward applying computer-supported education and these latent variables' ratios to each other. For this, eight hypotheses were developed in light of theoretical information by reviewing the literature. This research is done by using Academic Self-Efficacy Scale, Teacher Self-Efficacy Scale, Computer Self-Efficacy Scale, and The Attitude Scale Toward Applying Computer-Supported Education. The participant group of the research consists of 323 prospective teachers. Exploratory factor analyses of scales were analyzed via SPSS 16.0 software. For the confirmatory factor analyses of scales and the structural equation modeling, AMOS 20.0 software was used. The most significant finding of this study is that teacher self-efficacy, academic self-efficacy, and computer self-efficacy are important predictors of prospective teachers' attitude toward applying computer-supported education.     

Healthcare Technology Self-Efficacy (HTSE) and its influence on individual attitude: An empirical study

Previous research on technology acceptance and adoption has established perceived self-efficacy as an important factor influencing user acceptance of information technologies. However, research on self-efficacy perceptions and its effect on user attitude in the context of health technologies is limited. This study identifies three self-efficacy factors that may be important for shaping individual attitude toward healthcare technologies. This research proposes a new context-specific self-efficacy factor, Healthcare Technology Self-Efficacy (HTSE) and a conceptual model incorporating HTSE and two existing self-efficacy factors, General Self-Efficacy (GSE) and Computer Self-Efficacy (CSE). The conceptual model is validated using a survey of 314 participants. We found that HTSE has a positive influence on attitude toward the use of health technologies. We also found that two existing self-efficacy constructs (GSE and CSE) have positive relationships with HTSE. However these two factors did not have any significant influence on attitude toward health technology use, contrary to our expectations. Rather, HTSE mediates the relationships between GSE and attitude and the relationship between CSE and attitude in the context of health technology use behavior. The results of this study have important implications for both research and practice in the healthcare technology domain.     

New technology in personnel selection: How recruiter characteristics affect the adoption of new selection technology

The aim of the present field study is to expand the understanding of how characteristics of recruiters relate to their adoption of new selection technology. In two studies, among 198 recruiters, we used the Technology Acceptance Model (TAM), together with two measures of personality (i.e., openness to experience and neuroticism), two information technology specific individual differences (i.e., personal innovativeness in information technology and computer self-efficacy), and reactions to and actual usage of new technology. Both studies showed that all recruiter characteristics (except openness to experience) relate to perceptions of usefulness and ease of use, and that these perceptions relate to intentions to use new selection technologies. Study 2 showed that recruiter characteristics predict perceptions of usefulness and ease of use over and above established predictors of the TAM. Perceptions of usefulness and ease of use were better predictors of intentions to use new technology than perceptions of face validity, predictive validity, and fairness. Thus, when it comes to the adoption of new selection technology, recruiter characteristics, and perceptions of usefulness and ease of use play an important role.     

Effect of personal factors to use ICTs on e-learning adoption: comparison between learner and instructor in developing countries

This research investigated some key factors influencing an individual’s behavior to use e-learning in developing countries through social cognitive theory for examining the adoption of e-learning by instructors and learners, who are the key e-learning users. This paper focused on the personal capacity of Information and Communications Technologies and also investigated the mediating effects of computer self-efficacy (CSE) and performance expectation on intention to use e-learning. The results indicate that performance expectation and CSE were crucial factors influencing behavior intention to use e-learning systems for both instructors and learners. This study also found that computer experience and personal innovativeness in the domain of information technology were prominent factors for instructors. In addition, some differences and similarities were identified in the results for instructors and learners. This study used structure equation model, partial least squares, for data analysis, and data were collected from universities in Indonesia.     

Computer use and the gender gap: The issue of access, use, motivation, and performance

Since the beginning of computerization, it has been of interest whether there are differential effects on computer behavior, in particular in terms of computer access, computer use, and motivational variables, such as computer self-efficacy. The current research addresses the questions if the gender-related differences in this respect persist to the present day and if there is also a difference in actual performance characteristics. A sample of 48 university students (23 male) was administered a technology self-efficacy questionnaire, a survey on computer access, recorded a user diary, and turned in a computer task. Results show that the gender gap is closing as far as computer access and self-efficacy are concerned. Also, female and male students report comparable amounts of computer usage for their studies. User behavior appears to be gender-specific as males spend more time at the computer for personal purposes. There is also some evidence that male students outperform female students at a computer task (remastering of Power-Point slides). Conclusions for creating computer-based learning environments are discussed.     

Drivers and effects of post-implementation learning on ERP usage

Many organizations adopting enterprise resource planning (ERP) systems are failing to achieve their anticipated business goals, the major reason being system under-utilization. It is imperative to understand the way users learn to use ERP systems effectively. This is especially important given the integrated and complex nature of the ERP system, which forces users to continually learn new skills after implementation. This study aims to explore the role played by post-implementation learning in ERP usage. Moreover, we identify social capital and post-training self-efficacy as antecedents to post-implementation learning. A survey method was employed to collect data from 659 ERP users. This study finds that post-implementation learning contributes to ERP usage, and that social capital and post-training self-efficacy are important antecedents to post-implementation learning. Our findings provide academics and practitioners with an understanding of how post-implementation learning can be manipulated to improve ERP usage.     

An empirical investigation of sources of application-specific computer-self-efficacy and mediators of the efficacy—performance relationship

Integrating theory from research on training, computer self-efficacy (CSE), and motivation, this research validated a model of four factors that contribute to application-specific computer self-efficacy (AS-CSE) formation (previous experience, personality, learning goal orientation and computer anxiety) and three factors that mediate the relationship between AS-CSE and performance (goal level, goal commitment and performance goal orientation (PGO)). Using data from 313 individuals in an introductory computer skills course, the model was validated for database software. Results indicate that previous database software experience, trainee personality and learning goal orientation were positively related to AS-CSE, whereas computer anxiety was negatively related to AS-CSE. Additionally, goal level, goal commitment and PGOs were related to database test performance, and the relationship between AS-CSE and database test performance was also partially mediated by goal level and goal commitment. Implications for research and practice are discussed.     

The impact of general and specific performance and self-efficacy on learning with computer-based concept mapping

When students learn a new and challenging task, for which they have very limited corresponding personal or vicarious experiences to refer, it is important to understand how their self-efficacy beliefs evolve during the course of sequential lessons; how they differ in the way their general learning performance and self-efficacy influence their ratings of task-specific self-efficacy and performance; and, how such differences may result in different learning outcomes and motivations for learning. By examining a group of 66 students engaged in learning to construct good concept maps with computer software, this study revealed several important findings on these questions. Students generally tended to initially overestimate their ability to successfully carry out the required task. They also varied in the way their general self-efficacy and performance were associated with their task-specific self-efficacy and performance. And, these differences did appear to be associated with different learning outcomes and motivations for learning. These results indicate that investigating individual differences in students’ patterns of association between general and specific performance and their self-efficacy may lead to a better understanding of how students differ in their levels of motivation and outcomes when learning a new and challenging task.     

Are we talking about the task or the computer? An examination of the associated domains of task-specific and computer self-efficacies

Much research has investigated computer self-efficacy. Despite these efforts, the relation between efficacy beliefs concerning the task being performed on the computer and beliefs dealing with the computer application remains overlooked. In this study, we apply associationism to show how task-specific self-efficacy beliefs (TSE) positively influence computer-specific self-efficacy (CSE) judgments. We also show that this relation might be more complex than first thought: the degree of match between the novelty of the task and the novelty the application moderates this relation. That is, when both the task and the application are novel (or not), the influence of TSE on CSE is greater than when one is novel and the other is not. Furthermore, we show that CSE positively influences perceptions of usefulness, and as such, CSE represents one of the building blocks of the formation of beliefs about computer applications. Finally, several implications for practice and future research are discussed.     

The mediating effect of anti-phishing self-efficacy between college students’ internet self-efficacy and anti-phishing behavior and gender difference

This study investigates the mediating effect of college students' anti-phishing self-efficacy between Internet self-efficacy and anti-phishing behavior. Also the gender effect on the researched variables are concerned. The participants in the study were 434 university students who had experience using the Internet. The Internet self-efficacy scale (translated and modified based on Kim & Glassman scale, 2013), the self-designed anti-phishing self-efficacy scale, and the self-designed anti-phishing behavior scale were used in this study. This study used convenience sampling to conduct the survey, which resulted in 411 valid responses. Confirmatory factor analysis and structural equation modeling are adopted to test the mediation effect. The results showed statistically significant differences in anti-phishing behavior and anti-phishing self-efficacy between female and male university students. The SEM analysis showed that Internet self-efficacy is a positive precedent to anti-phishing behavior, and anti-phishing self-efficacy significantly mediated the relation between Internet self-efficacy and anti-phishing behavior. This study suggests that educators could use strategies to improve Internet self-efficacy and anti-phishing self-efficacy in order to enhance learners’ motivation and experience with anti-phishing. The Internet self-efficacy scale and the anti-phishing self-efficacy scale may be used as a reference for adaptive teaching materials.