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The sociotechnical perspective is often seen as one of the foundational viewpoints—or an “axis of cohesion”—for the Information Systems (IS) discipline, contributing to both its distinctiveness and its ability to coherently expand its boundaries. However, our review of papers in the two leading IS journals from 2000 to 2016 suggests that IS research has lost sight of the discipline’s sociotechnical character—a character that was widely acknowledged at the discipline’s inception. This is a problem because an axis of cohesion can be fundamental to a discipline’s long-term vitality. In order to address this issue, we offer ways to renew the sociotechnical perspective so that it can continue to serve as a distinctive and coherent foundation for the discipline. Our hope is that the renewed sociotechnical frame for the IS discipline discussed in the paper holds potential to contribute to the enduring strength of our diverse, distinctive, yet unified discipline. It also prompts members of the discipline to think more deeply about what it means to be an IS scholar.

Gamification, an emerging idea for using game design elements and principles to make everyday tasks more engaging, is permeating many different types of information systems. Excitement surrounding gamification results from its many potential organizational benefits. However, few research and design guidelines exist regarding gamified information systems. We therefore write this commentary to call upon information systems scholars to investigate the design and use of gamified information systems from a variety of disciplinary perspectives and theories, including behavioral economics, psychology, social psychology, information systems, etc. We first explicate the idea of gamified information systems, provide real-world examples of successful and unsuccessful systems, and, based on a synthesis of the available literature, present a taxonomy of gamification design elements. We then develop a framework for research and design: its main theme is to create meaningful engagement for users; that is, gamified information systems should be designed to address the dual goals of instrumental and experiential outcomes. Using this framework, we develop a set of design principles and research questions, using a running case to illustrate some of our ideas. We conclude with a summary of opportunities for IS researchers to extend our knowledge of gamified information systems, and, at the same time, advance existing theories.

Managerial responses to online customer reviews not only affect customers who receive the responses but may also influence subsequent customers who observe the responses. This externality arises because of the public nature of online interactions. However, prior studies were mainly in offline settings where such externality rarely exists. In this study, we assess the magnitude of such externality. Using a difference-in-difference-in-differences framework and matched hotels across two large travel agencies, we find that managerial responses indeed have a significant and positive impact on the volume of subsequent customer reviews. The impact on the review valence is not evident, which can be attributed to the unique design of identity disclosure in our research context. Furthermore, our results suggest nuances that were not known in the prior literature. For example, responding to positive and negative reviews may have different effects on future reviews, and managers should provide detailed responses to negative reviews but brief ones to positive reviews. Our results offer managerial implications to service providers on how to improve customer engagement in the interconnected online environment. The online appendix is available at https://doi.org/10.1287/isre.2018.0781 .

Despite the fact that validating the measures of constructs is critical to building cumulative knowledge in MIS and the behavioral sciences, the process of scale development and validation continues to be a challenging activity. Undoubtedly, part of the problem is that many of the scale development procedures advocated in the literature are limited by the fact that they (1) fail to adequately discuss how to develop appropriate conceptual definitions of the focal construct, (2) often fail to properly specify the measurement model that relates the latent construct to its indicators, and (3) underutilize techniques that provide evidence that the set of items used to represent the focal construct actually measures what it purports to measure. Therefore, the purpose of the present paper is to integrate new and existing techniques into a comprehensive set of recommendations that can be used to give researchers in MIS and the behavioral sciences a framework for developing valid measures. First, we briefly elaborate upon some of the limitations of current scale development practices. Following this, we discuss each of the steps in the scale development process while paying particular attention to the differences that are required when one is attempting to develop scales for constructs with formative indicators as opposed to constructs with reflective indicators. Finally, we discuss several things that should be done after the initial development of a scale to examine its generalizability and to enhance its usefulness.

Electronic health records (EHR) facilitate integration of patient health history for planning safe and proper treatment. Combined with data analytics, aggregate-level EHR enable examination and development of effective medicines and therapies for chronic diseases. Although promising efforts to implement EHRs are underway, social and organizational challenges plague EHR development and widespread use. These challenges are due to lingering issues such as privacy, interoperability, and security among key stakeholders (patients, providers, and purveyors). Based upon stakeholders’ needs and the issues, we identify two primary thematic areas—integration and analytics—in which the information systems (IS) discipline can contribute to EHRs. Through the accumulated body of knowledge, IS researchers are well positioned and have the expertise to design, develop, and facilitate the use of EHR in the delivery of healthcare. We identify potential research opportunities in each of the two thematic areas that have the potential to transform the delivery of healthcare. We conclude with a recommendation for IS scholars to collaborate with allied healthcare disciplines in order to advance the use of EHR to improve patient care.

Increasingly abundant trace data provide an opportunity for information systems researchers to generate new theory. In this research commentary, we draw on the largely “manual” tradition of the grounded theory methodology and the highly “automated” process of computational theory discovery in the sciences to develop a general approach to computationally intensive theory development from trace data. This approach involves the iterative application of four general processes: sampling, synchronic analysis, lexical framing, and diachronic analysis. We provide examples from recent research in information systems.

Recommender systems appear all across the internet. For e-retailers, this represents an opportunity to get more and niche products before customers’ eyes. However, we find that while implementing recommender systems does increase overall sales figures, it does not generally improve the relative sales for niche items, leading to a rich-get-richer situation. We find, across a wide range of product categories, that the use of traditional collaborative filters (CFs) is associated with a decrease in sales diversity relative to a world without product recommendations. The decrease in aggregate sales diversity may not always be accompanied by a corresponding decrease in individual-level consumption diversity. In fact, it is even possible for individual consumption diversity to increase as aggregate sales diversity decreases. CFs help individuals explore new products, but similar users still end up exploring the same kinds of products, resulting in concentration bias at the aggregate level. There is one insight for management: Traditional collaborative filters carry the unintended consequence of increasing concentration bias. A firm interested in exposing consumers to a broader assortment of products may prefer a different design from another simply interested in maximizing sales. We investigate the impact of collaborative filtering recommender algorithms (e.g., Amazon’s “Customers who bought this item also bought”) commonly used in e-commerce on sales diversity. We use data from a randomized field experiment run on the website of a top retailer in North America across 82,290 products and 1,138,238 users. We report four main findings. First, we demonstrate and quantify across a wide range of product categories that the use of traditional collaborative filters (CFs) is associated with a decrease in sales diversity relative to a world without product recommendations. Furthermore, the design of the CF matters. CFs based on purchase data are associated with a greater effect size than those based on product views. Second, the decrease in aggregate sales diversity may not always be accompanied by a corresponding decrease in individual-level consumption diversity. In fact, it is even possible for individual consumption diversity to increase while aggregate sales diversity decreases. Third, copurchase network analyses show that while recommenders can help individuals explore new products, similar users still end up exploring the same kinds of products, resulting in concentration bias at the aggregate level. Fourth and finally, there is a difference between absolute and relative impact on niche items. Specifically, absolute sales and views for niche items in fact increase, but their gains are smaller compared with the gains in views and sales for popular items. Thus, whereas niche items gain in absolute terms, they lose out in terms of market share. We discuss economic impacts and managerial implications. The online appendices are available at https://doi.org/10.1287/isre.2018.0800 .

Recent academic investigations of computer security policy violations have largely focused on non-malicious noncompliance due to poor training, low employee motivation, weak affective commitment, or individual oversight. Established theoretical foundations applied to this domain have related to protection motivation, deterrence, planned behavior, self-efficacy, individual adoption factors, organizational commitment, and other individual cognitive factors. But another class of violation demands greater research emphasis: the intentional commission of computer security policy violation, or insider computer abuse. Whether motivated by greed, disgruntlement, or other psychological processes, this act has the greatest potential for loss and damage to the employer. We argue the focus must include not only the act and its immediate antecedents of intention (to commit computer abuse) and deterrence (of the crime), but also phenomena which temporally precede these areas. Specifically, we assert the need to consider the thought processes of the potential offender and how these are influenced by the organizational context, prior to deterrence. We believe the interplay between thought processes and this context may significantly impact the efficacy of IS security controls, specifically deterrence safeguards. Through this focus, we extend the Sträub and Welke (1998) security action cycle framework and propose three areas worthy of empirical investigation—techniques of neutralization (rationalization), expressive/instrumental criminal motivations, and disgruntlement as a result of perceptions of organizational injustice—and propose questions for future research in these areas.

Traditional retailers are closing down their brick and mortar stores and increasing investments in their online channels. This may not be a beneficial strategy for retailers selling nondigital products, such as apparel, which customers prefer to physically evaluate to make the purchase decision. In such product categories, retailers’ physical stores could influence the sales on its online channel. We utilize the event of store opening by a large apparel retailer and use customer-level data to examine the effect of store presence on the online purchase behavior of its existing customers. We find that the retailer’s store openings resulted in an increase in online purchases from such customers for two reasons. First, higher store interactions engaged customers with the retailer’s brand, which resulted in their higher online purchases. Second, customers could freely purchase apparel from the retailer’s online channel, because they had the option to return it at a nearby store if it did not fit their expectations. Multichannel retailers should organize store events to engage customers and design lenient return policies to reduce the risk of purchase from online channel. We utilize the event of store opening by a large apparel retailer and use customer-level data to estimate the effect of store presence on the online purchase behavior of its existing customers. We find that the retailer’s store openings resulted in an increase in online purchases from such customers. Drawing on the theory of planned behavior and prospect theory, we propose two mechanisms to explain this complementary effect of store presence on online purchases by existing customers. These mechanisms are the store engagement effect —customers making higher online purchases because of higher engagement from store interactions—and the store return effect —reduced risk of online purchase because of the option of store returns. We provide direct empirical evidence of these mechanisms on customer-level data. We further show that these effects increase as customers’ distances from the retailer’s store reduce because of the store openings. Our findings have significant implications for multichannel retailers. The online appendices are available at https://doi.org/10.1287/isre.2018.0814 .

Despite renewed interest and many advances in methodology in recent years, information systems and organizational researchers face confusing and inconsistent guidance on how to choose amongst, implement, and interpret findings from the use of different measurement procedures. In this article, the related topics of measurement and construct validity are summarized and discussed, with particular focus on formative and reflective indicators and common method bias, and, where relevant, a number of allied issues are considered. The perspective taken is an eclectic and holistic one and attempts to address conceptual and philosophical essentials, raise salient questions, and pose plausible solutions to critical measurement dilemmas occurring in the managerial, behavioral, and social sciences.