Computer Self-Efficacy: Finding the Right Construct, for the Right Job, using the Right Measurement

Computer self-efficacy is a commonly used construct to explore user behavior and adoption of IS systems. However, there has been limited and somewhat conflicting empirical evidence to support the theorizing about the construct. After conducting a multi-discipline literature review of self-efficacy and analyzing the IS field’s usage of computer self-efficacy, we offer a discussion about the challenges and opportunities we see for the construct’s use in IS research. We state 6 propositions in this article that are structured around: (1) the nomological network of computer self-efficacy and the opportunities to refocus theorizing around generative capability as a source of performance mechanisms and (2) the appropriate task context in which to consider computer self-efficacy as a predictor. Next, we offer a discussion and set of recommendations around the challenges and considerations associated with current computer self-efficacy scales

Understanding Primary Appraisal in User Adoption: an Exploration case study of a Telehealth Project

Implementation of a new system typically results in significant change for users’ work processes who engage in adaptation processes to cope with the change. Coping theory explains how people choose adaptation behaviors after a series of appraisal processes. Primary appraisal results in the categorization of the IT artifact as a threat or an opportunity. Understanding these primary appraisals, specifically what antecedents produce various appraisal results, allows better prediction of user behaviors and ultimately of implementation success. Drawing on observations during a case study of a telehealth pilot project in six sites, we offer a theoretical model to better understand the antecedents of primary appraisal

The Eureka Effect: Exploring the Benefits of Struggling with Technology

This research in progress piece adds two interesting theoretical insights to traditional models of adoption. First, it introduces the Eureka effect, which suggests that some types of usage challenges can actually increase satisfaction with the system--even if they decrease the user\u27s perceived ease of use. Second, it expands on expectation-disconfirmation adoption models to carefully problematize when a user\u27s expectations of a system are confirmed or disconfirmed and builds theory in the various liminal states in between preadoption and postadoption. Specifically, this paper builds the foundational base of theory and grounds initial hypotheses to support its two contributions to IS theory

Greenway Medical Technologies: The Pace-Setting David of Electronic Health Records

This teaching case updates a previous study of Greenway Medical Technologies, a software company delivering electronic healthcare record (EHR) solutions to physicians. The current EHR marketplace is considered, including global trends as well as the impact of U.S. government funded monetary incentives. Greenway continues to build on its best-in-class software application and find ways to provide new enticements to medical practices and improvements to the broader medical community. The case also describes the EHR systems industry and explores the reasons for Greenway’s continued success and growth that surpasses its competitors

Self-Reliant and Deferred Privacy Stances: A Natural Quasi-Experiment of iOS Users’ Acceptance of Privacy Offerings

We often assume that technology users are concerned about their privacy and will readily take steps to protect it. But while there is clear evidence that users harbor serious privacy concerns, it is increasingly unclear whether users actually accept offers to improve their privacy. This study brings to light two strategies—a self-reliant privacy stance and a deferred privacy stance—that many users take to cope with their increasing loss of control over privacy. We argue that the two privacy stances help users envision positive future outcomes regarding their privacy but can paradoxically cause users to hesitate in accepting new privacy offerings from technology firms. We conduct a natural quasi- experiment studying how iPhone users under some mixture of the two privacy stances respond to a major privacy offering from Apple, in the form of an iOS update to that helps users control the tracking behavior of mobile apps like Facebook. We find that users taking a deferred privacy stance are less likely to accept the privacy offering than users with less staunch privacy stances. This hesitance on part of technology users is an underexamined challenge to privacy measures. By modeling privacy stances, information systems researchers can gain a more nuanced understanding of how people deal with the complex mix of threats to their privacy and the offers to manage their privacy. And by understanding privacy stances, firms might better calibrate their messaging to users holding out from technology offerings that genuinely seek to address privacy or security threats

Understanding the Role of Technology in Coordination: An Affordance Perspective

Supporting and enabling coordination is a critical function of information technology in organizations. Previous studies have considered technology as a passive medium over which coordination activities occur. We complement these studies by considering t

A Randomized Field Experiment to Explore the Impact of Herding Cues as Catalysts for Adoption

A herding cue is a lean information signal that an individual receives about the aggregate number of others who have engaged in a behavior that may result in herd behavior. Given the ease with which they can be leveraged as implementation interventions or design features on online sites, herding cues hold the promise to provide a means to influence adoption behaviors. Yet, little attention has been devoted in the IS adoption literature to understanding the effects of herding cues. Given that herding cues are just one of several forms of social influence on adoption behaviors and are relatively lean in nature, understanding their viability as an implementation intervention necessitates understanding their effects in the presence of (1) other forms of social influence, which also serve to reduce uncertainty and signal the appropriateness of technology adoption, and (2) an individual’s own beliefs about adopting. In this vein, we conducted a randomized field experiment to examine the use of a herding cue as an implementation intervention to hasten adoption behaviors. The research model was evaluated using survival analysis by combining the data from the field experiment with two waves of surveys, and archival logs of adoption. Our results show that a herding cue (1) directly impacts the time it takes an individual to adopt a technology, (2) amplifies the effects of peer behaviors (another type of informative social influence), but has no impact on the effect of subjective norm (a form of normative social influence), and (3) dampens the effects of an individual’s private beliefs about the usefulness of a technology. Our paper disentangles herding information signals to define a herding cue as distinct from other herd behavior triggers, explores how it may interact with other forms of social influences and private beliefs to influence adoption behaviors, and, on a practical level, provides evidence of how a herding cue can be a tangible intervention to accelerate technology adoption