Knowledge that Transforms

Understanding information technology (IT) use is vital for the information systems (IS) discipline due to its substantial positive and negative consequences. In recent years, IT use for personal purposes has grown rapidly. Although personal use is voluntary and can often reflect fun, technostress is a common negative consequence of such use. When left unaddressed, technostress can cause serious harm to IT users. However, prior research has not explained how technostress forms over time or how its mitigation takes place in a personal—rather than organizational—environment. To address these research gaps, we conducted a qualitative study with narrative interviews of IT users who had experienced technostress. This study contributes to (1) the technostress literature by unpacking states in which technostress forms and can be mitigated and (2) the IT affordance literature by explaining the role of affordances and their actualizations in technostress as well as introducing the new concept of actualization cost. In terms of practice, our findings help individuals and societies identify the development of technostress, understand the activities required for its mitigation, and recognize mitigation barriers.

With today’s technological advancements, mobile phones and wearable devices have become extensions of an increasingly diffused and smart digital infrastructure. In this paper, we examine mobile health (mHealth) platforms and their health and economic impacts on the outcomes of chronic disease patients. To do so, we partnered with a major mHealth firm that provides one of the largest mobile health app platforms in Asia specializing in diabetes care. We designed and implemented a randomized field experiment based on detailed patient health activities (e.g., steps, exercises, sleep, food intake) and blood glucose values from 1,070 diabetes patients over several months. Our main findings show that the adoption of the mHealth app leads to an improvement in health behavior, which in turn leads to both short term metrics (such as reduction in patients’ blood glucose and glycated hemoglobin levels) and longer-term metrics (such as hospital visits and medical expenses). Patients who adopted the mHealth app undertook higher levels of exercise, consumed healthier food with lower calories, walked more steps and slept for longer times on a daily basis. They also were more likely to substitute offline visits with telehealth. A comparison of mobile versus PC-enabled versions of the same app demonstrates that the mobile version has a stronger effect than PC version in helping patients make these behavioral modifications with respect to diet, exercise, and lifestyle, which ultimately leads to an improvement in their healthcare outcomes. We also compared outcomes when the platform facilitates personalized health reminders to patients vis-à-vis generic (non-personalized) reminders. Surprisingly, we found that personalized mobile messages with patient-specific guidance can have an inadvertent (smaller) effect on patient app engagement and lifestyle changes, leading to a lower health improvement. However, they are more like to encourage a substitution of offline visits by telehealth. Overall, our findings indicate the massive potential of mHealth technologies and platform design in achieving better healthcare outcomes.

This paper explores the structure and design of digital strategic initiatives (DSI): identifiable competitive moves that depend on digital resources to create and appropriate economic value. We use the term digital deliberately, in line with the recent push for discerning the so-called IT “x” and Digital “x” phenomena. The paper contributes to basic science by precisely defining the digital strategic initiative concept and its essential elements: digital resources. It clarifies the difference between digital resources and established constructs such as IT resources and IT-enabled resources. We posit that the defining characteristics of digital resources are their modular design, encapsulation of value, and programmatic interface. This work also shows how the design and development of digital strategic initiatives thrive in an infrastructural, combinatorial, and servitized environment. Using illustrative cases, we demonstrate applications of the concepts by introducing two value creation pathways for DSI: (1) orchestration of digital resources and (2) creation of novel digital resources. The paper concludes by presenting open research questions and offering extensions for future inquiry.

Evidence shows that older users have lower performance levels for IT-enabled tasks than younger users. This is alarming at a time when the workforce is rapidly aging and organizational technologies are proliferating. Since the explanation for these lower performance levels remains unclear, managers are not sure how to help older users realize their full potential as contributors to organizational success. The research model presented here identifies the declining information-processing speed of older workers as the cause of their reduced capacity to perform IT-enabled tasks. According to the model, IT experience and IT self-efficacy reduce the negative impacts of this decline, whereas IT overload and the effort cost of IT use aggravate them. To test the model, data were collected using three complementary studies. The results supported the model and indicated five ways that organizations can help older users improve their capacity to perform IT-enabled tasks. Additional data collected in interviews with human resources directors confirmed the relevance of these solutions.

Privacy needs on today’s internet differ from the information privacy needs in traditional e-commerce settings due to their focus on interactions among online peers rather than merely transactions with an online vendor. Peer-oriented online interactions have critical implications for an individual’s virtual presence and self-cognition. Yet existing conceptualizations of internet privacy concerns have solely focused on the control of personal information release and on online interactions with online vendors. Drawing on the theory of personal boundaries, this study revisits the theoretical foundation of online privacy and proposes a multidimensional peer-related privacy concern construct, that focuses on privacy violations from online peers. We term this new construct “Peer Privacy Concern” (PrPC) and define it as the general feeling of being unable to maintain functional personal boundaries in online activities as a result of the behavior of online peers. This construct consists of four dimensions comprised of a reconceptualization of information privacy concerns to also reflect privacy concerns with respect to peers’ handling of self-shared information and with respect to peer-shared information about one’s self, and three new dimensions that tap into the arising privacy needs from virtual interactions (i.e., virtual territory privacy concern and communication privacy concern) as well as from the need to maintain psychological independence (i.e., psychological privacy concern). These new dimensions, which are rooted in the theory of personal boundaries, are prominent privacy needs in online social interactions with peers. However, they are absent from previous privacy concern conceptualizations. Scales for measuring this new construct are developed and empirically validated.

Although individual adoption and use of a single system has been examined extensively, little is known about how people evaluate and compare competing systems. In this paper, we discuss and test three alternative models underlying user comparison of competing systems: separate, crossover effect, and relative comparison processes. The separate comparison process proposes that users develop separate cognitive, affective, and conative evaluations toward each system, and the between-system comparison only occurs at the point of choosing a preferred system. The crossover effect comparison process posits that users not only perform separate evaluations for each system, but also consider the competitive effects when proceeding across cognitive, affective, and conative evaluation stages. In contrast, the relative comparison process postulates that users directly compare competing systems within each of the cognitive, affective, and conative evaluation stages. Based on the IS continuance model, we tested each of these three models using data collected from 315 users of two competing instant messaging systems. Our results showed that the relative comparison process is the most parsimonious and the best model in terms of explaining the mechanisms underlying the comparison of system use by individuals. Theoretical and practical implications are discussed.

Medication nonadherence (MNA) can lead to serious health ramifications and costs U.S. healthcare systems $290 billion annually. Understanding the reasons underlying patients’ MNA is thus an urgent goal for researchers, practitioners, and the pharmaceutical industry in order to mitigate negative health and economic consequences. In recent years, patient engagement on social media sites has soared, making it a cost-efficient and rich information source that can complement prior survey studies and deepen the understanding of MNA. Yet these data remain untapped in existing MNA studies because of technical challenges such as long texts, decision-making based on negative sentiment, varied patient vocabulary, and the scarcity of relevant information. For this study, we developed a sentiment-enriched deep learning method (SEDEL) to address these challenges and extract reasons for MNA. We evaluated SEDEL using 53,180 reviews concerning 180 drugs and achieved a precision of 89.25%, a recall of 88.48%, and an F1 score of 88.86%. SEDEL significantly outperformed state-of-the-art baseline models. We identified nine categories of MNA reasons, which were verified by domain experts. This study contributes to IS research by devising a novel deep-learning-based approach for reason mining and by providing direct implications for the health industry and for practitioners regarding the design of interventions.

By empowering customers to make fitting purchases, user reviews play an important role in reducing inefficiencies in the provisioning of product information. Because of the abundance of reviews and the signals they provide, this information may become confusing and risks overloading customers. Consequently, review hosting platforms have adjusted their designs to feature a signal “distilled” from a selective set of “top reviews” and their valences. The expected ease with which customers process this signal is intended to increase their satisfaction, thus reducing dispersion in their subsequent review ratings. In this study, we analyze the influential role that top reviews and their valence play under various scenarios: when customers are overloaded by a large number of reviews, when top reviews themselves are not parsimonious in number, and when the signals from top reviews are not in concordance with that from all the other reviews. We find that the valence of top reviews plays a central role in mitigating information overload. However, the influence of those top reviews diminishes when they too pose an overload risk but is strengthened when their signal is reaffirmed by signals from all other reviews. Finally, the impact of top reviews is weaker for less popular products.