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This study attempts to understand the factors that influence clinician resistance to the implementation of health information technology in a mandatory setting. A survey study was conducted with 202 clinicians regarding their perceptions of the implementation of electronic medication management systems (eMMS) in an Australian hospital. The data was collected during the initial roll-out of eMMS for model validation and quantitative analysis. The overall results indicated that performance expectancy, switching costs, and facilitating conditions are direct predictors of clinician resistance, whereas effort expectancy and social influence showed indirect effects on clinician resistance through performance expectancy or switching costs. The study is among the first study that investigates passive clinician resistance to the implementation of health information technology in a health organisation. This study also focused on opposition behaviour among under-examined degrees of resistance. This study provides some insights to the hospital management on how to mitigate clinician resistance in the implementation of health information technology. Other types of clinician resistance, such as postponement and rejection, are not examined in this study. Future research on postponement behaviour and rejection behaviour is needed to have a more comprehensive view of clinician resistance. [ABSTRACT FROM AUTHOR]

Purpose: Electronic books (e-books) have been in the market for decades but have been unable to replace paper books. Previous studies on e-books have failed to identify significant factors affecting the adoption and diffusion of e-books. This study develops a theoretical framework to explain the adoption behavior of e-books from the perspective of user resistance. Design/methodology/approach: After a pilot test with 50 e-book users, the research model is validated using a partial least squares structural equation modeling (PLS-SEM) technique. A web-based survey method is used to collect data from a sample of 350 people – selected from Korean e-book users and nonusers – during a week in March 2017. This study tests the reliability and validity of the integrated model of planned behavior and resistance theory and tests the hypotheses with bootstrapping resampling. Findings: The results show that four barriers – usage, value, risk and image – cause resistance to change and users with higher resistance have lower intention to use. The moderating effect of self-efficacy between resistance to change and intention to use is confirmed. Self-efficacy interacts not only with the encouraging factors but also with resistance. Originality/value: This study expands the understanding of users' adoption behavior of e-books by examining inhibiting factors using a novel integrated model. The findings of this research provide insights for digital product providers, especially e-book publishers, to understand why digital products have not been successful in the marketplace. [ABSTRACT FROM AUTHOR]

The study makes use of the photo-hosting site, namely Flickr, for students to upload screenshots to demonstrate computer software problems and troubleshooting software. By creating non-text stickers and text-based annotations above the screenshots, students are able to help one another to diagnose and solve problems with greater certainty. In addition to applying the technology acceptance model, three factors from the user resistance perspective, namely, user resistance, peer opinion, and self-efficacy for change, were chosen as the basis for the research model. Based on data collected from 399 students, the results indicated that students’ resistance had a negative and direct effect on their behavioral intention. Both peer opinions and students’ self-efficacy for change had negative and direct effects on their resistance, which positively and indirectly influenced behavioral intention. User resistance could be significantly improved by promoting positive peer opinions or enhancing students’ self-efficacy for change. [ABSTRACT FROM AUTHOR]

In fact, ERP system has become required for many organizations particularly those organizations that have foundations in different countries. Recently, some organizations in Yemen have adopted ERP system but the usage of this system failed as it faced user resistance. Hence, the prime concern of this study is to investigate the resistance factors of Enterprise Resource planning from user perspective not organization or technical perspective to specify the basic reasons for user resistance to successfully adopting ERP system. Four factors are examined their association with adopting ERP. These factors are user training, resistance to change, user expectation, and system usage. A questionnaire was distributed to 200 of ERP end users. Linear regression analysis program was used to analyze the data and examine the relationship between user’s resistance factors and ERP adoption. The result shows that each of user’s training, resistance to change and system usage has a significant relationship with ERP adoption, However results show no relationship between user expectation and ERP adoption. This paper benefits management in organizations by providing the factors that contribute to adopt ERP system. [ABSTRACT FROM AUTHOR]

User resistance has long been acknowledged as a critical issue during information technology implementation. Resistance can be functional when it signals the existence of problems with the IT or with its effects; it will be dysfunctional when it leads to organizational disruption. Notwithstanding the nature of resistance, the implementers--business managers, functional managers, or IT professionals--have to address it. Although the literature recognizes the importance of user resistance, it has paid little attention to implementers' responses--and their effect--when resistance occurs. Our study focuses on this phenomenon, and addresses two questions: What are implementers' responses to user resistance? What are the effects of these responses on user resistance? To answer these questions, we conducted a case survey, which combines the richness of case studies with the benefits of analyzing large quantities of data. Our case database includes 89 cases with a total of 137 episodes of resistance. In response to our first research question, we propose a taxonomy that includes four categories of implementers' responses to user resistance: inaction, acknowledgment, rectification, and dissuasion. To answer our second question, we adopted a set-theoretic analysis approach, which we enriched with content analysis of the cases. Based on these analyses, we offer a theoretical explanation of how implementers' responses may affect the antecedents that earlier research found to be associated with user resistance behaviors. [ABSTRACT FROM AUTHOR]

The article discusses the issue of user resistance in the implementation of enterprise systems (ES) through psychological contract theory. It mentions that ES refer to commercial software packages that integrate business processes and transaction data in an organization. It says that user resistance is an opposition to a system implementation. It cites several determinants that affect psychological contract and level of user resistance including uncertainty, technical problems and training.

User resistance to information systems implementation has been identified as a salient reason for the failure of new systems and hence needs to be understood and managed. While previous research has explored the reasons for user resistance, there are gaps in our understanding of how users evaluate change related to a new information system and decide to resist it. In particular, missing in the explanation of user decision making is the concept of status quo bias, that is, that user resistance can be due to the bias or preference to stay with the current situation. Motivated thus, this study develops a model to explain user resistance prior to a new IS implementation by integrating the technology acceptance and resistance literatures with the status quo bias perspective. The results of testing the model in the context of a new enterprise system implementation indicate the central role of switching costs in increasing user resistance. Further, switching costs also mediate the relationship between other antecedents (colleague opinion and self-efficacy for change) and user resistance. Additionally, perceived value and organizational support for change are found to reduce user resistance. This research advances the theoretical understanding of user acceptance and resistance prior to a new IS implementation and offers organizations suggestions for managing such resistance. [ABSTRACT FROM AUTHOR]

To better explain resistance to information technology implementation, we used a multilevel, longitudinal approach. We first assessed extant models of resistance to IT. Using semantic analysis, we identified five basic components of resistance: behaviors, object, subject, threats, and initial conditions. We further examined extant models to (1) carry out a preliminary specification of the nature of the relationships between these components and (2) refine our understanding of the multilevel nature of the phenomenon. Using analytic induction, we examined data from three case studies of clinical information systems implementations in hospital settings, focusing on physicians' resistance behaviors. The resulting mixed-determinants model suggests that group resistance behaviors vary during implementation. When a system is introduced, users in a group will first assess it in terms of the interplay between its features and individual and/or organizational-level initial conditions. They then make projections about the consequences of its use. If expected consequences are threatening, resistance behaviors will result. During implementation, should some trigger occur to either modify or activate an initial condition involving the balance of power between the group and other user groups, it will also modify the object of resistance, from system to system significance. If the relevant initial conditions pertain to the power of the resisting group vis-à-vis the system advocates, the object of resistance will also be modified, from system significance to system advocates. Resistance behaviors will follow if threats are perceived from the interaction between the object of resistance and initial conditions. We also found that the bottom-up process by which group resistance behaviors emerge from individual behaviors is not the same in early versus late implementation. In early implementation, the emergence process is one of compilation, described as a combination of independent, individual behaviors. In later stages of implementation, if group level initial conditions have become active, the emergence process is one of composition, described as the convergence of individual behaviors. [ABSTRACT FROM AUTHOR]