Revisiting the Impact of System Use on Task Performance: An Exploitative-Explorative System Use Framework
Heshan Sun, Ryan Wright, Jason Thatcher
How information systems (IS) impact task performance has attracted a significant amount of attention from information systems researchers and generated high interest among practitioners. A commonly accepted view is that the potential of information systems must be realized through system use. Nevertheless, existing findings regarding the impact of system use on task performance are not yet conclusive. We attributed this to the various conceptualizations of system use and the unclear mechanisms through which system use influences task performance. Thus, this research attempts to create a better understanding of how system use influences task performance. To this end, we developed an exploitative-explorative system use framework in order to reconcile the various conceptualizations of system use and to depict how both exploitative and explorative system use influences task performance through impacting task innovation, management control, and task productivity. We created an instantiation of the framework using USAGE (exploitative system use) and adaptive system use (ASU, explorative system use). We conducted two empirical studies involving two different populations and using two different technologies. The first study consisted of 212 experienced users of MS Office, whereas the second study employed 372 new users of a video-editing tool. Our findings offer insight into how exploitative system use and explorative system use independently and jointly influence task performance constructs and also have implications for research and practices.
Theorizing the Multilevel Effects of Interruptions and the Role of Communication Technology
Shamel Addas, Alian Pinsonneault
Our understanding of how interrupting the work of an individual affects group outcomes and the role of communication technologies (CT) in shaping these effects is limited. Drawing upon coordination theory and the literatures on computer-mediated communication and interruptions, this paper develops a multilevel theory of work interruptions. It suggests that interruptions that target individuals can also affect other group members through various ripple effects and a cross-level direct effect. We also discuss how the usage of five CT capabilities during interruption episodes can moderate the impact of interruptions at the individual and group levels. Our theoretical model draws attention to the importance of examining the individual-to-group processes to better understand the impact of interruptions in group environments. Additionally, by accounting for the role of the use of CT capabilities during interruption episodes, our work contributes to both the interruptions literature, which dedicates scant attention to the interrupting media, and to IS research on media use and media effects.
Editorial: Data-Driven Meets Theory-Driven Research in the Era of Big Data: Opportunities and Challenges for Information Systems Research
Wolfgang Maass, Jeffrey Parsons, Sandeep Purao, Veda C. Storey, Carson Woo
The era of big data provides many opportunities for conducting impactful research from both data-driven and theory-driven perspectives. However, data-driven and theory-driven research have progressed somewhat independently. In this paper, we develop a framework that articulates important differences between these two perspectives and proposes a role for information systems research at their intersection. The framework presents a set of pathways that combine the data-driven and theory-driven perspectives. From these pathways, we derive a set of challenges, and show how they can be addressed by research in information systems. By doing so, we identify an important role that information systems research can play in advancing both data-driven and theory-driven research in the era of big data.
Designing Social Nudges for Enterprise Recommendation Agents: An Investigation in the Business Intelligence Systems Context
Martin Kretzer, Alexander Maedche
According to behavioral economists, a "nudge" is an attempt to steer individuals toward making desirable choices without affecting their range of choices. We draw on this concept. We design and examine nudges that exploit social influence's effects to control individuals' choices. Although recommendation agent research provides numerous insights into extending information systems and assisting end-consumers, it lacks insights into extending enterprise information systems to assist organizations' internal employees. We address this gap by demonstrating how enterprise recommendation agents (ERAs) and social nudges can be used to tackle a common challenge that enterprise information systems face. That is, we are using an ERA to facilitate information (i.e., reports) retrieval in a business intelligence system. In addition, we are using social nudges to steer users toward reusing specific recommended reports rather than choosing between recommended reports randomly. To test the effects of the ERA and the four social nudges, we conduct a within-subjects lab experiment with 187 participants. We also conduct gaze analysis ('eye tracking') to examine the impact of participants' elaboration. The results of our logistic mixed-effects model show that the ERA and the proposed social nudges steer individuals toward certain choices. Specifically, the ERA steers users toward reusing certain reports. These theoretical findings also have high practical relevance and applicability: In an enterprise setting, the ERA allows employees to reuse existing resources (such as existing reports) more effectively across their organizations because employees can easier find the reports they actually need. This in turn prevents the development of duplicate reports.
A Tale of Two Deterrents: Considering the Role of Absolute and Restrictive Deterrence to Inspire New Directions in Behavioral and Organizational Security Research
Robert Willison, Paul Benjamin Lowry, Raymond Paternoster
This research-perspective article reviews and contributes to the literature that explains how to deter internal computer abuse (ICA), which is criminal computer behavior committed by organizational insiders. ICA accounts for a large portion of insider trading, fraud, embezzlement, the selling of trade secrets, customer privacy violations, and other criminal behaviors, all of which are highly damaging to organizations. Although ICA represents a momentous threat for organizations, and despite numerous calls to examine this behavior, the academic response has been lukewarm. However, a few security researchers have examined ICAís influence in an organizational context and the potential means of deterring it. However, the results of the studies have been mixed, leading to a debate on the applicability of deterrence theory (DT) to ICA. We argue that more compelling opportunities will arise in DT research if security researchers more deeply study its assumptions and more carefully recontextualize it. The purpose of this article is to advance a deterrence research agenda that is grounded in the pivotal criminological deterrence literature. Drawing on the distinction between absolute and restrictive deterrence and aligning them with rational choice theory (RCT), this paper shows how deterrence can be used to mitigate the participation in and frequency of ICA. We thus propose that future research on the deterrent effects of ICA should be anchored in a more general RCT, rather than in examinations of deterrence as an isolated construct. We then explain how adopting RCT with DT opens up new avenues of research. Consequently, we propose three areas for future research, which cover not only the implications for the study of ICA deterrence, but also the potential motivations for this type of offence and the skills required to undertake them.
'Computing' Requirements for Open Source Software: A Distributed Cognitive Approach
Xuan Xiao, Aron Lindberg, Sean Hansen, Kalle Lyytinen
Most requirements engineering (RE) research has been conducted in the context of structured and agile software development. Software, however, is increasingly developed in open source software (OSS) forms which have several unique characteristics. In this study, we approach OSS RE as a sociotechnical, distributed cognitive process where distributed actors 'compute' requirements ñ i.e., transform requirements-related knowledge into forms that foster a shared understanding of what the software is going to do and how it can be implemented. Such computation takes place through social sharing of knowledge and the use of heterogeneous artifacts. To illustrate the value of this approach, we conduct a case study of a popular OSS project, Rubinius - a runtime environment for the Ruby programming language - and identify ways in which cognitive workload associated with RE becomes distributed socially, structurally, and temporally across actors and artifacts. We generalize our observations into an analytic framework of OSS RE, which delineates three stages of requirements computation: excavation, instantiation, and testing-in-the-wild. We show how the distributed, dynamic, and heterogeneous computational structure underlying OSS development builds an effective mechanism for managing requirements. Our study contributes to sorely needed theorizing of appropriate RE processes within highly-distributed environments as it identifies and articulates several novel mechanisms that undergird cognitive processes associated with distributed forms of RE.
Sleight of Hand: Identifying Concealed Information by Monitoring Mouse-Cursor Movements
Jeffrey Jenkins, Jeff Proudfoot, Joe Valacich, G. Mark Grimes, Jay Nunamaker
Organizational members who conceal information about adverse behaviors, such as insider threat or noncompliance activities, present a substantial risk to that organization. Yet the task of identifying who is concealing information is extremely difficult, expensive, error-prone, and time-consuming. We propose a unique methodology for identifying concealed information: measuring people's mouse-cursor movements in online screening questionnaires. We present a specialized screening questionnaire based on the concealed information test. We then theoretically explain how mouse-cursor movements captured during this test differ between people concealing information and truth tellers. We empirically evaluate our hypotheses using an experiment during which people conceal information about a questionable act. While people completed the screening questionnaire, we simultaneously collected mouse-cursor movements and electrodermal activity the primary sensor used for polygraph examinations as an additional validation of our methodology. We found that mouse-cursor movements can significantly differentiate between people concealing information and people telling the truth. Mouse-cursor movements also can differentiate between people concealing information and truth tellers on a broader set of comparisons relative to electrodermal activity. Both mouse-cursor movements and electrodermal activity have the potential to identify concealed information, yet mouse-cursor movements yielded significantly fewer false positives. Our results demonstrate that analyzing mouse-cursor movements has promise for identifying concealed information. This methodology can be automated and deployed online for mass screening of individuals in a natural setting without the need for human facilitators, who can introduce bias into the results. Our approach further demonstrates that mouse-cursor movements can provide insight into the cognitive state of computer users.
An Activity Theory Approach to Modeling Dispatch-Mediated Emergency Response
Rohit Valecha, Raj Sharman, H. Raghav Rao, Shambhu J. Upadhyaya
Emergency response involves multiple local, state and federal communities of responders. These communities are supported by emergency dispatch agencies that share digital traces of task-critical information. However, the communities of responders are often an informal network of people, and lack structured mechanisms of information sharing. To standardize the exchange of task-critical information in communities of responders we develop a conceptual modeling grammar. We base the grammar on an Activity Theory perspective, and ground it in an analysis of emergency dispatch incident reports. The paper contributes to research in dispatch-mediated emergency response literature by (1) developing a framework of elements and relationships to support critical information flow within emergency communities of responders, (2) developing a conceptual modeling grammar for modeling emergency tasks in dispatch-mediated emergency response, and (3) implementing a prototype system to demonstrate the utility of the conceptual modeling grammar.
Never, Never Together Again: How Post-Purchase Affect Drives Consumer Outcomes within the Context of Online Consumer Support Communities
Eun Hee Park, Ghiyoung Im, Veda C. Storey, Richard L. Baskerville
Online support communities are popular for consumers of information technology products who might need help identifying or resolving a problem. Information technology products, in general, have their own needs and requirements. Prior research has focused on the intermediate benefits of online support communities to companies, such as knowledge contribution and community participation. This study, in contrast, investigates the less explored issue of value creation by online support communities with respect to consumer post-purchase outcomes. To do so, an affect (emotional) process model is developed to understand how customers' post-purchase outcomes of information technology products are influenced through cognitive and affective processes after a product failure. Special attention is paid to the roles of affect during the recovery process. An empirical assessment of the model uses two online support communities, with a netnography methodology employed for data collection. The results suggest that consumers' post-purchase outcomes are influenced by affect and regulation, not just cognition. Key influences emerge as the consumers' own problem appraisals and affective experiences, the consumers' social group, and regulation provided by company technicians and/or community experts.
A Multi-Appeal Model of Persuasion for Online Petition Success: A Linguistic Cue-Based Approach
Yan Chen, Shuyuan Deng, Dong-Heon Kwak, Ahmed El Noshokaty, Jiao Wu
Online petitions have become a powerful tool for the public to use to affect society. Despite the increasing popularity of these petitions, it remains unclear how the public consumes and interprets their content and how this public consumption and interpretation help the creators of online petitions achieve their goals. This study investigates how linguistic factors in the texts of online petitions influence their success. Specifically, drawing upon the dual-process theory of persuasion and the moral persuasion literature, this study examines cognitive, emotional, and moral linguistic factors in the texts of petitions and identifies their role in the success of online petitions. The results, which are based on an analysis of 45,377 petitions from Change.org, show that petitions containing positive emotions and enlightening information are more likely to succeed. Contrary to popular belief, petitions containing heavy cognitive reasoning and emphasizing moral judgment are less likely to succeed. This study exemplifies use of an analytical approach to examining crowd-sourced content involving online political phenomena related to policy making, governance, political campaigns, and large societal causes.
Appraisal of Email Use as a Source of Workplace Stress: A Person-Environment Fit Approach
Jean-Francois Stich, Monideepa Tarafdar, Patrick Stacey, Sir Cary Cooper
The paper develops and tests theory that explains under what conditions the extent of email use is appraised as a stressor. Integrating concepts from information acquisition and person environment fit theories, we theorize that individuals appraise their extent of email use as stressful based on the mismatch between their current and desired extents of email use. We define such match as email fit and mismatch as email misfit. We develop a conceptual framework and hypotheses that associates email misfit with the individual’s experience of three key workplace stressors – work relationship stressor, job control stressor and job conditions stressor. We test our hypotheses by applying quadratic polynomial regressions and surface-response analysis, to survey data obtained from 118 working individuals. The paper makes three theoretical contributions. Firstly, in reporting a theoretical and empirical construction of email fit and misfit and their relationship to workplace stressors, it shows that, email misfit is appraised as stress-creating. That is, both too much and too little email compared to what the individual desires, are associated with stressors. In doing so and secondly, it shows that IT use (in this case, email) is appraised as stressful both when it exceeds (i.e., associated with overload) and fails to meet (i.e., associated with underload), the user’s expectation and preference. Thirdly, it suggests the person environment approach as a theoretically novel way to conceptualize the cognitive appraisal and judgement associated with information under - and over – acquisition, and shows workplace stressors as potentially new effects associated with them.
Cross-Level Moderation of Team Cohesion in Individuals’ Utilitarian and Hedonic Information Processing: Evidence in the Context of Team-Based Gamified Training
Dong-Heon Kwak, Xiao Ma, Greta Polites, Mark Srite, Ross T. Hightower, William Dave Haseman
Today firms use teams extensively to accomplish organizational objectives. In addition, gamification has recently received much attention as a means of persuading employees and customers to engage in desired behaviors. Despite the importance of teams and the growing interest in gamification as a persuasion tool, past researchers have paid little attention to team-based gamification from a multilevel perspective. Based on motivational consistency theories, we propose that at the team level, team performance has a positive effect on team cohesion. Drawing upon the elaboration likelihood model (ELM), we further propose two cross-level effects in the context of team-based gamified training: first, that team cohesion will positively moderate the relationship between utilitarian perceptions (i.e., perceived quality of learning) and attitude; and second, that team cohesion will negatively moderate the relationship between hedonic perceptions (i.e., perceived enjoyment of learning) and attitude. We tested our research model using an enterprise resource planning (ERP) simulation game involving 232 participants in 78 teams. The results of Ordinary Least Squares and Hierarchical Linear Modeling analysis support our hypotheses. This study makes three substantive contributions to the team literature and to the ELM in the context of team-based gamified training. First, it theorizes and empirically tests the effect of team performance on team cohesion at the team level. Second, it extends the ELM by examining the cross-level moderation of team cohesion in human information processing. Third, it demonstrates that the utilitarian and hedonic aspects of information technology do not influence user attitudes equally.
It Takes a Village: Understanding the Collective Security Efficacy of Employee Groups
Allen C. Johnston, Paul M. Di Gangi, Jack Howard, Jame Worrell
An organization’s ability to successfully manage information security incidents is determined by the actions of its employees, as well as the actions of various groups of employees within its organizational boundary. To date, information security research has primarily focused on individual-level phenomena, not yet exploring group-level phenomena such as how employee groups recognize and respond to security incidents in a way that is consistent with the organization’s security goals and objectives. The current study addresses this gap, thereby answering the call for group-level security research perspectives. The present study explores how employee groups formulate their collective security efficacy, which influences how group members recognize and respond to information security incidents. Using a case study of a large healthcare research organization (HRO), we analyze two security incidents, a malware attack and a physical security breach, to identify a unique set of ecological and social properties of employee groups that are salient to their collective security efficacy.
Privacy in the Sharing Economy
Timm Teubner, Michael Christoph Flath
Contemporary C2C platforms, such as Airbnb, have exhibited considerable growth in recent years and are projected to continue doing so in the future. These novel consumer-to-consumer marketplaces have started to obliterate the boundaries between private and economic spheres. Marketing personal resources online is inherently associated with the disclosure of personal and sometimes intimate information. This raises unprecedented questions of privacy. Yet, there is so far little research on the role of privacy considerations in the sharing economy literature. Leveraging the theoretical perspective of privacy calculus, we address this gap by investigating how privacy concerns and economic prospects shape a potential provider’s intentions to share via different communication channels. We relate privacy concerns back to the provider’s perceptions of the audience. We evaluate our research model by means of a scenario-based online survey, providing broad support for our reasoning.
Sublating Tensions in the IT Project Risk Management Literature: A Model of the Relative Performance of Intuition and Deliberate Analysis for Risk Assessment
Mohammad Moeini, Suzanne Rivard
The information technology (IT) project risk management literature comprises two dominant but diverging bodies of knowledge: the normative and the experiential. We conducted a three-step dialectical review of this literature with the aim of creating a bridging body of knowledge. In the first step, delineation, we synthesize the overarching variance and process explanations in each body of knowledge and motivate the examination of their divergences. In the second step, contrastation, we perform a dialectical interrogation of these bodies to articulate their key assumption-level tensions. We elaborate on the most prominent tension between the two bodies, namely, the relative performance of intuition and deliberate analysis for project risk assessment. In the third step, sublation, we propose a theoretical model that resolves this tension. Anchored in both bodies of knowledge and drawing from managerial decision-making research, the model proposes that the relative performance of intuition depends on characteristics of the IT project manager (project-specific expertise), the project (risks’ temporal complexity and risks’ structural complexity), and the project’s organizational environment (e.g., stakeholders’ involvement in risk management, methods-using pressures). Moreover, the model posits that project-specific expertise moderates all the other effects. Building on the bridging knowledge insights from this model, we discuss how researchers can design interventions to increase project managers’ use of deliberate analysis when it is expected to outperform intuition or to encourage reliance on intuition when it is likely to outperform deliberate analysis.
An Economic Analysis of Consumer Learning on Entertainment Shopping Websites
Jin Li, Zhiling Guo, Geoffrey Tso
Online entertainment shopping, normally supported by the pay-to-bid auction mechanism, represents an innovative business model in e-commerce. Because the unique selling mechanism combines features of shopping and online auction, consumers expect both monetary return and entertainment value from their participation. We propose a dynamic structural model to analyze consumer behaviors on entertainment shopping websites. The model captures a consumer’s learning process both from her own participation experiences and from the observational learning of historical auction information. We estimate the model using a large data set from an online entertainment shopping website. Results show that consumers’ initial participation incentives mainly come from a significant overestimation of the entertainment value and an obvious underestimation of the auction competition. Both types of learning contribute to a general decreasing participation trend among consumers over time. Our model provides both a theoretical explanation and empirical evidences of the consumer churn issue. It further identifies two groups of consumers with different risk characteristics: One group is risk-averse and quits the website before effective learning takes place, while the other group exhibits risk-seeking behavior and overly commits to the auction games. Based on the estimated parameters of the model, we perform counterfactual analyses to evaluate the effects of policy changes on consumers’ participation behaviors. We discuss several important design implications and recommend strategies for building a sustainable business model in the entertainment shopping industry.
Measuring and Controlling Social Desirability Bias: Applications in Information Systems Research
Dong-Heon Kwak, Philipp Holtkamp, Sung S. Kim
Despite the potential risks that social desirability (SD) bias poses to the validity of information systems (IS) research, little is known about the extent of such bias. This study examines the extent of SD bias in the IS domain and compares alternative techniques for measuring it. Our findings suggest that despite the popularity of the Marlowe-Crowne scale in IS research, the Impression Management scale functions better in assessing the extent of SD bias. We also found that under certain circumstances, SD bias can threaten the validity of IS research. This study contributes to the IS literature by showing the difference in SD bias across IS contexts and suggesting an effective way to test for the presence of SD bias.
PLS-Based Model Selection: The Role of Alternative Explanations in Information Systems Research
Pratyush Nidhi Sharma, Marko Sarstedt, Galit Shmueli, Kevin H. Kim, Kai Oliver Thiele
Exploring theoretically plausible alternative models for explaining the phenomenon under study is a crucial step in advancing scientific knowledge. This paper advocates model selection in MIS studies that use partial least squares path modeling (PLS) and suggests the use of model selection criteria derived from Information Theory for this purpose. These criteria allow researchers to compare alternative models and select a parsimonious yet well-fitting model. However, as our review of prior MIS research practice shows, their use—while common in the econometrics field and in factor-based SEM—has not found its way into studies using PLS. Using a Monte Carlo study, we compare the performance of several model selection criteria in selecting the best model from a set of competing models under different model set-ups and various conditions of sample size, effect size, and loading patterns. Our results suggest that appropriate model selection cannot be achieved by relying on the PLS criteria (i.e., R2, Adjusted R2, GoF, and Q2), as is the current practice in academic research. Instead, model selection criteria, in particular the Bayesian information criterion (BIC) and the Geweke-Meese criterion (GM), should be used due to their high model selection accuracy and ease of use. To support researchers in the adoption of these criteria, we introduce a five-step procedure that delineates the roles of model selection and statistical inference, and discuss misconceptions that may arise in their use.
Designing Process Guidance Systems
Stefan Morana, Julia Kroenung, Alexander Maedche, Silvia Schacht
Process knowledge is a vital prerequisite for employees to execute organizational processes successfully in the course of their daily work. However, the lack of process knowledge, especially of novice users, and the need for support pose a challenge to employers. Inspired by research on spatial knowledge and navigation, we conceptualize three process knowledge types addressing the needs of employees during their process execution. On the basis of these process knowledge types, we derive three theoretically grounded design principles for process guidance systems to support employees’ process execution. We instantiate the design principles and evaluate the resulting artifacts in a laboratory experiment and in a subsequent field study. The results demonstrate the positive effects of process guidance systems on users’ process knowledge and process execution performance. Our study contributes to research and practice by proposing a new conceptualization of process knowledge and a nascent design theory for process guidance systems that builds on theories of spatial knowledge and navigation, as well as decision support research.
On the Optimal Fixed-Up-To Pricing for Information Services
Shinyi Wu, Paul Pavlou
Fixed-Up-To (FUT) pricing allows consumers to purchase a fixed usage amount of an information service for a certain fixed price chosen from a menu of plans. In this study, we first derive an optimal analytical solution for FUT menu pricing without imposing the strong single-crossing assumption. Second, we illustrate the analytical solution by leveraging mixed integer nonlinear programming to derive an optimal FUT pricing scheme for information services. Third, we investigate when, and by how much, FUT pricing improves upon the commonly-used “flat rate” pricing. Our numerical results show that FUT pricing improves the service provider’s profits while enhancing social welfare when consumers face different maximum consumption level bounds. Notably, in terms of optimal pricing, our numerical results show that the consumers’ maximum consumption level bounds are more important than their utility functions. Most importantly, our results show that FUT pricing performs better than flat rate pricing under incomplete information. Finally, we empirically show that it is not necessary to treat over limit rates as a decision variable in terms of optimal FUT pricing since both FUT pricing and three-part tariffs are reasonable approximations of non-linear pricing in terms of both firm profits and social welfare. Theoretical and practical implications for the design of optimal FUT pricing toward enhancing firm profits, consumer surplus, and social welfare are discussed.
Effects of Symbol Sets and Needs Gratifications on Audience Engagement: Contextualizing Police Social Media Communication
Jennifer Xu, Jane Fedorowicz, Christine B. Williams
We propose a research model based on Media Synchronicity Theory (MST) and examine how the use of different symbol sets (e.g., images and text) is related to audience engagement on social media. We include Uses and Gratifications Theory (UGT) in the model to identify task characteristics that are relevant to message recipients in the specific context of community policing. Based on our analyses of Facebook posts by five police departments we find first that, consistent with MST, posts conveying information garner more responses when accompanied by more natural symbol sets, and more textual content is preferred to less, but responses differ depending on the type of engagement: intimacy (likes), interaction (comments), or influence (shares). Second, posts intended for meaning convergence gratify the audience’s socialization and assistance needs and are positively related to intimacy and interaction. Finally, the fit between symbol sets and task characteristics impacts different dimensions of audience engagement. These findings provide empirical support for relying on MST when studying social media and for integrating with UGT to capture contextual task characteristics. We conclude the paper with a discussion of the implications of its findings for theory and offer recommendations for practice.
Deconstructing Information Sharing
Paul Beynon-Davies, Yingli Wang
Information sharing between actors, working in different institutions, is proposed by much literature to improve aspects of both intra and inter-institutional performance. However, it is unclear from the literature what exactly information sharing is and why it is important to institutional performance. This paper seeks to deconstruct the concept of information sharing, particularly within aspects of the supply chain. We shall argue that the central problem with the concept of information sharing is that it relies on a notion of information as stuff that can be manipulated, transmitted, and used relatively unproblematically between organizations. We wish to question conventional notions of this construct by examining and analyzing a case of information sharing, applicable within an international supply chain as well as several problems experienced with such sharing. Through deconstructing this case we demonstrate how certain perceived problems in information sharing are better conceptualized as breakdowns in the inter-institutional scaffolding of data structures.
A Meta-Design Theory for Tailorable Decision Support
Shah Jahan Miah, John Gammack, Judy McKay
Despite years of Decision Support Systems (DSS) research, DSS artefacts are frequently criticized for lacking practitioner relevance, and for neglecting configurability and contextual dynamism. Tailoring in end-user contexts can produce relevant emergent DSS artefacts, but design theory for this is lacking. Design Science Research (DSR) has important implications for improving DSS uptake, but generally this has not been promoted in the form of meta-designs with design principles applicable to other DSS developments. This paper describes a meta-design theory for tailorable DSS, generated through action design research studies in different primary industries. Design knowledge from a DSS developed in an agricultural domain was distilled and generalized into a design theory comprising: 1) a general solution concept (meta-design) and 2) five hypothesized design principles. These were then instantiated via a second development in which the meta-design and design principles were applied in a different domain (forestry) to produce a successful DSS, thus testing the meta-design and validating the design principles. In addition to contributing to DSR and illustrating innovation in tailorable technology the paper demonstrates the utility of action design research to support theory development in DSS design.
The Role of Morality in Digital Piracy: Understanding the Deterrent and Motivational Effects of Moral Reasoning in Different Piracy Contexts
Kar Yan Tam, Yue Katherine Feng, Samuel Kwan
Digital piracy has been a chronic issue in intellectual property protection. With the prevalence of online technologies, digital piracy has become even more rampant as digital resources can now be accessed and disseminated easily through the Internet. While the antecedents of piracy behaviors have been studied for years, previous studies often focus on a specific type of behavior or pirated content and the findings are far from conclusive. They do not paint a coherent picture of the impacts of antecedents. In this study, we focus on the role of morality by revealing the different levels of moral reasoning that can both deter and motivate users’ piracy intention. Furthermore, we differentiate between two types of piracy behaviors (unauthorized copying/downloading vs. unauthorized sharing) and two categories of digital products (application software vs. music/movies) so that the differential impacts of the various antecedents can be assessed and articulated more clearly. Models are empirically evaluated in the four piracy contexts using a sample of 3,426 survey participants from a sizable IT-literate society. The findings indicate the conflicting roles of morality in piracy intention and demonstrate its differential impacts across the two types of piracy behaviors yet can be generalized across the two categories of digital products. Our study sheds new light on end-users’ considerations in accessing and disseminating unauthorized digital content. It also informs the design of copyright protection policies and sanction measures with different levels of specificity.
Beyond Information: The Role of Territory in Privacy Management Behavior in Social Networking Sites
Shuai-Fu Lin, Deb Armstrong
This study draws on communication privacy management theory to explore aspects of social networking sites (SNSs) that may influence individual privacy management behaviors and conceptualizes two behaviors for managing privacy in SNSs: private disclosure (for managing information privacy) and territory coordination (for managing territory privacy). Evidence from two studies of SNS members indicates that perceptions of trespassing over agreed upon virtual boundaries within SNSs affects risk beliefs regarding information privacy and territory privacy differently. These distinct privacy risk beliefs, in turn, influence two privacy management behaviors. Theoretically, this study demonstrates that a more complete conceptualization of individual privacy management in SNSs should consider both information privacy and territory privacy; and that territory coordination is a more significant indicator of privacy management behaviors in SNSs than private disclosure. From a practical standpoint, this study provides guidance to SNS platform organizations on how to reduce individuals’ privacy risk beliefs, encourage users to share private information, and potentially build larger online communities.
Understanding Ambidexterity: Managing Contradictory Tensions between Exploration and Exploitation in the Evolution of Digital Infrastructure
Ramiro Montealegre, Kishen Iyengar, Jeffrey Sweeney
Prior research on the evolution of digital infrastructure has paid considerable attention to effective strategies for resolving contradictory tensions, yet what we still do not understand is the role of higher-level organizational capabilities that help balance the contradictory tensions that emerge during this evolution. In addressing this gap, two related questions guided our investigation: 1) how do organizations experience and resolve contradictory tensions throughout the evolution of digital infrastructure? and 2) what can we learn about the organizational capabilities that drive strategic actions in resolving these contradictory tensions? We approach these questions using an in-depth case study at RE/MAX LLC, a global real estate franchise. Based on our findings, we propose a theoretical model of digital infrastructure ambidexterity. The model recognizes three pairs of capabilities (identifying and germinating, expanding and legitimizing, as well as augmenting and implanting) and two supporting factors (leadership and structure) that are key to resolving contradictory tensions during this evolution. This study responds to a recent research call for dynamic process perspectives at multiple levels of analysis. The implications of this model for research and practice are discussed and observations for future research are offered.
Designing for ICT-Enabled Openness in Bureaucratic Organizations: Problematizing, Shifting and Augmenting Boundary Work
Isam Faik, Mark Thompson, Geoff Walsham
There is a growing focus on achieving ‘openness’ in the design and transformation of organizations, in which the enabling role of ICTs is considered increasingly central. However, bureaucratic organizations with rigid structures continue to face significant challenges in moving towards more open forms of organizing. In this paper, we contribute to our understanding of these challenges by building on existing conceptualizations of openness as a form of boundary work that transforms by challenging both internal and external organizational boundaries. In particular, we draw on a performative view derived from actor-network theory to analyze a case study of ICT-based administrative reforms in a judicial system. Building on our case analysis, we develop a typology of the various roles that ICTs can play in both enabling and constraining ongoing boundary work within the context of their implementation. We thus present a view of ICT-enabled open organizing as a process where ICTs contribute to problematizing, shifting, and augmenting ongoing boundary work. This view highlights the inherently equivocal nature of the role of ICTs in transformations towards higher levels of openness.
Understanding IT-enabled Social Features in Online Peer-to-Peer Business for Cultural Goods
Ermira Zifla, Sunil Wattal
Although the use of IT-enabled social features is gaining prominence in online peer-to-peer platforms, the use of these features is not well understood in the context of ecom-merce marketplaces. In this study, we explain the effects of using IT-enabled social fea-tures for sellers by using data from Etsy.com, which is a peer-to-peer marketplace for cultural goods and also provides social features to its participants. Using the theory of fields of cultural production, we propose hypotheses regarding the direct and indirect im-pact of IT-enabled social features on sales. We find that sellers’ use of IT-enabled social features for community participation (e.g., following members) and content curation (e.g., sharing favorite items) is positively associated with their online status, which in turn is positively associated with their sales. However, sellers’ use of IT-enabled social features is directly negatively associated with sales. Overall, we find that the indirect positive association is large enough to offset the negative direct association. These results have important implications for sellers in peer-to-peer platforms and platform design.
They’re All the Same!' Stereotypical Thinking and Systematic Errors in Users' Privacy-Related Judgments about Online Services
Jin P. Gerlach, Peter Buxmann, Tamara Dinev
Given the ever-increasing volume of online services, it has become impractical for Internet users to study every company’s handling of information privacy separately and in detail. This challenges a central assumption held by most information privacy research to date—that users engage in deliberate information processing when forming their privacy-related beliefs about online services. In this research, we complement previous studies that emphasize the role of mental shortcuts when individuals assess how a service will handle their personal information. We investigate how a particular mental shortcut—users’ stereotypical thinking about providers’ handling of user information—can cause systematic judgment errors when individuals form their beliefs about an online service. In addition, we explore the effectiveness of counter-stereotypic privacy statements in preventing such judgment errors. Drawing on data collected at two points in time from a representative sample of smartphone users, we studied systematic errors caused by stereotypical thinking in the context of a mobile news app. We found evidence for stereotype-induced errors in users’ judgments regarding this provider, despite the presence of counter-stereotypic privacy statements. Our results further suggest that the tone of these statements makes a significant difference in mitigating the judgment errors caused by stereotypical thinking. Our findings contribute to emerging knowledge about the role of cognitive biases and systematic errors in the context of information privacy.
Information Systems as Representations: A Review of the Theory and Evidence
Jan Recker, Marta Indulska, Peter Green, Andrew Burton-Jones, Ron Weber
Representation Theory proposes that the basic purpose of an information system (IS) is to faithfully represent certain real-world phenomena, allowing users to reason about these phenomena more cost-effectively than if they were observed directly. Over the past three decades, the theory has underpinned much research on conceptual modeling in IS analysis and design and increasingly research on other IS phenomena such as data quality, system alignment, IS security, and system use. The original theory has also inspired further development of its core premises and advances in methodological guidelines to improve its use and evaluation. Nonetheless, the theory has attracted repeated criticisms regarding its validity, relevance, usefulness, and robustness. Given the burgeoning literature on the theory over time, both positive and negative, the time is ripe for a narrative, developmental review. We review Representation Theory, examine how it has been used, and critically evaluate its contributions and limitations. Based on our findings, we articulate a set of recommendations for improving its application, development, testing, and evaluation.
Understanding the Elephant: The Discourse Approach to Boundary Identification and Corpus Construction for Theory Review Articles
Kai R. Larsen, Dirk S. Hovorka, Alan R. Dennis, Jevin West
The goal of a review article is to present the current state of knowledge in a research area. Two important initial steps in writing a review article are boundary identification (identifying a body of potentially relevant past research) and corpus construction (selecting research manuscripts to include in the review). We present a theory-as-discourse approach which a) creates a theory ecosystem of potentially relevant prior research using a citation-network approach to boundary identification; and b) identifies manuscripts for consideration using machine learning or random selection. We demonstrate an instantiation of the theory as discourse approach through a proof-of-concept, which we call the Automated Detection of Implicit Theory (ADIT) technique. ADIT improves performance over the conventional approach as practiced in past Technology Acceptance Model reviews (i.e., keyword search, sometimes manual citation chaining); it identifies a set of research manuscripts that is more comprehensive and at least as precise. Our analysis shows that the conventional approach failed to identify a majority of past research. Like the three blind men examining the elephant, the conventional approach distorts the totality of the phenomenon. ADIT also enables researchers to statistically estimate the number of relevant manuscripts which were excluded from the resulting review article, thus enabling an assessment of the review article’s representativeness.
Pricing or Advertising? A Game Theoretic Analysis of Online Retailing
Zhong Wen, Lihui Lin
How should online retailers attract customers? Should they advertise intensively to direct online traffic, or should they simply price lower than their competitors? In this paper, we attempt to study these decisions firms face and how market characteristics affect the firms’ decisions and the market outcome. We develop a game-theoretic model of two firms choosing advertising levels and prices strategically. We find that only asymmetric equilibria exist, or etailers choose different strategies along both advertising and pricing dimensions. When the market mobility is low (i.e., the majority of buyers have high search cost), firms engage in fierce competition in advertising, and the firm choosing a higher advertising level also charges a higher price and earns higher profits. When the market mobility is high (i.e., the majority of buyers have zero search cost) or medium, one firm chooses to advertise intensely while the other may choose to charge a lower price and not to advertise at all; and in such cases either firm may make higher profits. We also compare the market outcome in our model with the case where firms do not have the option to advertise. We find that the option to advertise leads to higher expected prices for any given market composition, and that when the market mobility is high both etailers can make higher profits than without the option, even for the firm that advertises intensively and bears the extra cost. We further extend the model to consider etailers choosing advertising levels sequentially.
Doctor's Orders or Patient’s Preferences? Examining the Role of Physicians in Patients’ Privacy Decisions on Health Information Exchange Platforms
Niam Yaraghi, Ram Gopal, Ram Ramesh
Health Information Exchange (HIE) platforms could increase the efficiency of health care services by enabling providers to instantly access the medical records of their patients. These benefits will not be realized unless patients disclose their information on HIE platforms. We examine actual privacy decisions made by patients on an HIE platform and study the influence of physicians’ recommendations on patients’ decisions and explore the process through which this effect takes place. By analyzing a unique data set consisting of the privacy decisions of 12,444 patients, we show that contrary to the common belief, patients do not merely follow the recommendation of physicians but rather carefully consider the risks and benefits of providing consent. We show that competition among medical providers do not hinder their participation in HIE efforts, but instead providers’ decision to ask for consent is primarily driven by the potential benefits of HIE for themselves and their patients.
Platform Leadership: Managing Boundaries for the Network Growth of Digital Platform
Carmen Leong, Shan L. Pan, Dorothy Leidner, Jinsong Huang
This study aims to generate a systematic understanding of how digital platform firms can attain platform leadership. We explore the question by casting a boundary management lens over the complex network of interactions on a digital platform. Firms are faced with various boundaries – boundaries of efficiency, competence, power, identity and ties – and must carefully address tensions within diverse groups of actors with their own interests. An in-depth case study is conducted on China’s largest online ticketing firm, and two contributions for attaining platform leadership are established. First, we conceptualize the development of a digital platform as a set of technology-based boundary management mechanisms (functional multiplexing, scope expansion, community curation, actor empowerment and positional escalation) that includes a combination of boundary spanning, erecting and reinforcing. Second, we uncover the network dynamics of a digital platform by explicating the synergies and tensions of boundary management. Considering our novel findings, this study offers managerial and design guidelines for a digital platform by advocating an integrative view of boundary management. A multidimensional framework that includes five boundaries and four types of networks (dyadic, interconnected, intraconnected and external) is presented for future analysis of networks built on digital platforms.
I am your Fan. Bookmarked! Identification Building in Founder-led Online Communities
Niki Panteli, Anu Sivunen
In this study, we present the findings from an inductive and interpretive case study of a founder-led online community (OC), exploring how members’ identification develops within the community over time. Using a longitudinal study of an OC that was founded by a reputable individual, it is shown that members were first attracted to the OC through their affective and cognitive identification with the founder; however, over time, they developed identification through social interactions with other members. The findings show that this transformation was enabled by the founder’s communication behavior, which not only led to inspired and engaged members but also to the emergence of new leaders who supported the identification process. The study contributes to the fields of founder-led OCs, identification and emergent leadership in the OC context.
The Impact of Goal-Congruent Feature Additions on Core IS Feature Use: When More is Less, Less is More
Felix Wortmann, Frederic Thiesse, Elgar Fleisch
This research investigates the impact of feature additions on the use of an information system’s (IS) existing core features. Based on prior work in marketing and IS, we hypothesize conflicting effects on the usage of the system as a whole and the IS core due to the goal congruence of the two feature sets. In three consecutive empirical studies, we consider the example of a utilitarian consumer IS in the form of a mobile insurance app with additional weather-related functionality. The statistical results indicate that the goal-congruent feature addition exerts a positive influence on system use, whereas the impact on core IS use is negative. More specifically, we show that the latter effect can be explained by changes in the users’ perceptions of the usefulness and ease of use of the core features. From a theoretical perspective, our work goes beyond the predominant system view of technology acceptance and use by employing a more fine-grained, feature-oriented level of investigation, which opens several avenues for further research regarding the relationships between information systems and the features of which they consist. From a managerial perspective, the results help to characterize the detrimental effects that feature additions may have on IS usage. These consequences become particularly relevant when revenue, cost savings, or other benefits on the part of IS operators are linked only to a subset of the entire IS functionality, as in the case of several web portals or mobile apps.
Constraining Opportunism in Information Systems Consulting: A Three Nation Examination
Richard T. Watson, Gregory Dawson, Marie-Claude Boudreau, Yan Li, Ibrahim Al-Jabri, Hongyun Zhang, Wayne Huang
Opportunism is often present in professional services, such as IS consulting, and organizations adopt various mechanisms to constrain it. Opportunism is prevalent in many societies, if not all, yet, researchers have generally ignored (1) the efficacy of constraint mechanisms for different circumstances and (2) the impact of national differences. This study examines the relative effectiveness of different constraint mechanisms for IS consultants in China, Saudi Arabia, and the United States, based on different levels of information asymmetry, tacit, and explicit knowledge. While there is support in all countries for the salience of these dimensions, there are distinctions in the effectiveness of different constraints between the countries. Generally, consulting clients in the United States believe that social constraints are more effective, while those in China and Saudi Arabia favor legal constraints. The findings suggest that these distinctions are a result of differences in the legal systems and the religious foundations for social norm formation.
How do Individuals Interpret Multiple Conceptual Models? A Theory of Combined Ontological Completeness and Overlap
Jan Recker, Peter Green
When analyzing or designing information systems, users often work with multiple conceptual models because each model articulates a different, partial aspect of a real-world domain. However, the available research in this area has largely studied the use of single modeling artefacts only. We develop new theory about interpreting multiple conceptual models that details propositions for evaluation of individuals’ selection, understanding, and perceived usefulness of multiple conceptual models. We detail several implications of our theory development for empirical research on conceptual modeling. We also outline practical contributions for the design of conceptual models and for choosing models for systems analysis and design tasks. Finally, to stimulate research that builds on our theory, we illustrate procedures for enacting our theory and discuss a range of empirically relevant boundary conditions.
Integrating Cognition with an Affective Lens to Better Understand Information Security Policy Compliance
Dustin Ormond, Merrill Warkentin, Robert E. Crossler
Information systems security behavioral research has primarily focused on individual cognitive processes and their impact on information security policy noncompliance. However, affective processes (operationalized by affective absorption and affective flow) may also significantly contribute to misuse or information security policy noncompliance. Our research study evaluated the impact of affective absorption (i.e. the trait or disposition to have one’s emotions drive decision making) and affective flow (i.e. a state of immersion with one’s emotions) on cognitive processes in the context of attitude toward and compliance with information security policies. Our conceptual model was evaluated using a laboratory research design. We found that individuals who were frustrated by work-related tasks experienced negative affective flow and violated information security policies. Furthermore, perceptions of organizational injustice increased negative affective flow. Our findings underscore the need for understanding affective processes as well as cognitive processes which may lead to a more holistic understanding regarding information security policy compliance.
An Analysis of the Evolving Intellectual Structure of Health Information Systems Research within the Information Systems (IS) Discipline
Langtao Chen, Aaron Baird, Detmar W. Straub
The rapid evolution of health information systems (Health IS) research has led to many significant contributions. However, while the Health IS subset of information systems (IS) scholarship has considerably grown over the past two decades, this growth has led to questions regarding the current intellectual structure of this area of inquiry. In an effort to more fully understand how Health IS has contributed to the IS discipline, and what this may mean for future Health IS research in the IS domain, we conduct an in-depth evaluation of Health IS research published in mainstream IS journals. We apply citation analysis, latent semantic analysis (LSA), and social network analysis (SNA) to our dataset of Health IS articles in order to: (1) identify Health IS research themes and thematic shifts, (2) determine which Health IS research themes are cohesive (versus disparate), (3) identify which Health IS research themes are central (versus peripheral), (4) clarify networks of researchers (i.e., thought leaders) contributing to these research themes, and (5) provide insights into the connection of Health IS to its reference disciplines. Overall, we contribute a systematic description and explanation of the intellectual structure of the Health IS and highlight how the existing intellectual structure of Health IS provides opportunities for future research.
The Role of Evaluability Bias and the Fairness Effect in Escalation of Commitment to a Troubled Software Product Development Project
Jong Seok Lee, Mark Keil, Sangcheol Park
New software product development entails considerable risks. One significant risk is that decision makers can become overly committed to a troubled software product development project (i.e., escalation of commitment). While prior research has identified factors that promote escalation in information technology projects, there has been little attempt to leverage the context of software product development which can include evaluating attributes of a software product under development and weighing a personal financial reward tied to a successful product launch. In this study, we conducted two experiments to investigate how evaluability bias concerning software attributes, and the fairness effect that arises from the relative amount of a personal financial reward, influence escalation of commitment to a troubled software product development project. Our findings suggest that escalation of commitment to a troubled software product development project is influenced by both evaluability bias, which affects the perceived attractiveness of a software product under development, and the fairness effect, which influences the perceived attractiveness of a personal financial reward tied to a successful product launch. This study contributes to both the information systems (IS) literature and the escalation literature by providing novel theoretical explanations as to why escalation occurs in the context of new software product development.
Brute Force Sentence Pattern Extortion from Harmful Messages for Cyberbullying Detection
Michal Ptaszynski, Fumito Masui, Pawei Lempa, Yasutomo Kimura, Rafal Rzepka, Kenji Araki
Cyberbullying, or humiliating people through the Internet, existed almost since the beginning of Internet communication. Recent introduction of smartphones and tablet computers caused cyberbullying to evolve into a serious social problem. In Japan, to deal with the problem, members of Parent-Teacher Association (PTA) read through the Web to spot cyberbullying entries. To help PTA members in their uphill task we propose a novel method for automatic detection of malicious Internet contents. The method is based on a combinatorial approach resembling brute force search algorithms with application to language classification. The method extracts sophisticated patterns from sentences and uses them in classification. The experiments performed on actual cyberbullying data showed advantage of our method to previous methods. Next, we implemented the method into an application for Android smartphones to automatically detect possible harmful content in messages. The method performed well under the Android environment, although it needs to be optimized for time efficiency to be used in practice.
Scientific Knowledge Communication in Professional Q&A Communities: Linguistic Devices as a Tool to Increase the Popularity and Perceived Professionality of Knowledge Contributions
Yicheng Zhang, Tian Lu, Chee Wei Phang, Chenghong Zhang
With the emergence of professional question-and-answer (Q&A) communities, widespread dissemination of scientific knowledge has become more viable than ever before. However, contributors of scientific knowledge are confronted with the challenge of making their professional knowledge contributions popular, as non-expert readers may not appreciate their contributions given the massive and chaotic information on the Internet. In this study, we first show that, although nonexpert readers are similar to experts in their ability to evaluate the professionality of content contributed in such communities, a salient discrepancy exists between the content they favor and the content they perceive as professional. In line with studies that have suggested writing techniques play an important role in how expert content is received by laypersons, we investigated the effect of the use of linguistic devices on the perceived professionality and popularity of content contributions in Q&A communities. Based on both secondary data and a scenario-based survey, we uncovered specific linguistic devices that can increase content popularity without reducing perceived professionality. Additionally, we revealed linguistic devices that increase popularity at the expense of perceived professionality in this context. A laboratory experiment was conducted to more firmly establish the causal effects of the linguistic device use. The triangulated findings have important implications for both research and practice on communicating scientific knowledge in professional Q&A communities.
Specialized Information Systems for the Digitally Disadvantaged
Florian Pethig, Julia Kroenung
A number of specialized information systems for the digitally disadvantaged (SISD) have been developed to offset the limitations of people unable to participate in the information society. However, contributions from social identity theory and social markedness theory indicate that SISD can activate a stigmatized identity and thus be perceived unfavorably by their addressees. We identify two mechanisms by which functional limitations affect a digitally disadvantaged person’s adoption decision: (1) adoption decision as shaped through technology perceptions (i.e., perceived usefulness, perceived ease of use, and perceived access barriers) and (2) adoption decision as shaped through marked status awareness (i.e., stigma consciousness). We test our contextualized research model on digitally disadvantaged users with physical and/or sensory disabilities. Results of our mediation analysis show that individuals who have most to gain from SISD use (i.e., those with high functional limitations) are doubly disadvantaged. They find it more challenging to use SISD and are also more sensitive to the fear of being marked as disadvantaged or vulnerable.
Game of Platforms: Strategic Expansion into Rival (Online) Territory
Online platforms, such as Google, Facebook, or Amazon, are constantly expanding their activities, while increasing the overlap in their service offering. This paper asks: Is expansion into rival platforms’ services profit-maximizing when users’ platform choices endogenously change with expansion? We model an expansion game between two online platforms, both incumbents in distinct service markets, providing their services for free to users, and earning ad-based revenues. Platforms decide whether or not to expand by adding the service already offered by the rival. Expansion is costly, and impacts users’ platform choice, namely, their choice of single- vs. multi-homing, which, in turn, affects platform prices and profits derived from the advertisers’ side of the market. We demonstrate that, in equilibrium, platforms may choose not to expand. Strategic "no expansion" decisions are due to the quantity and price effects of changes in the user partition due to expansion. We analyze the effects of expansion-driven changes in inter-platform compatibility, expansion costs, users’ probability of ad-engagement, switching costs, and intra-platform service complementarity and quality on the optimal expansion strategy. We derive an optimal expansion rule, incorporating these considerations, to guide managerial decision making regarding expansion into a rival’s “territory.”