Showing papers in "Management Information Systems Quarterly in 2018"
TL;DR: A unified model, called the unified model of information security policy compliance (UMISPC), is proposed, which integrates elements across these extant theories, and empirically tests the UMISPC in a new study, which provided preliminary empirical support for the model.
Abstract: Information systems security (ISS) behavioral research has produced different models to explain security policy compliance This paper (1) reviews 11 theories that have served the majority of previous information security behavior models, (2) empirically compares these theories (Study 1), (3) proposes a unified model, called the unified model of information security policy compliance (UMISPC), which integrates elements across these extant theories, and (4) empirically tests the UMISPC in a new study (Study 2), which provided preliminary empirical support for the model The 11 theories reviewed are (1) the theory of reasoned action, (2) neutralization techniques, (3) the health belief model, (4) the theory of planned behavior, (5) the theory of interpersonal behavior, (6) the protection motivation theory, (7) the extended protection motivation theory, (8) deterrence theory and rational choice theory, (9) the theory of self-regulation, (10) the extended parallel processing model, and (11) the control balance theory The UMISPC is an initial step toward empirically examining the extent to which the existing models have similar and different constructs Future research is needed to examine to what extent the UMISPC can explain different types of ISS behaviors (or intentions thereof) Such studies will determine the extent to which the UMISPC needs to be revised to account for different types of ISS policy violations and the extent to which the UMISPC is generalizable beyond the three types of ISS violations we examined Finally, the UMISPC is intended to inspire future ISS research to further theorize and empirically demonstrate the important differences between rival theories in the ISS context that are not captured by current measures
263 citations
TL;DR: A needs–affordances–features–features (NAF) perspective on social media use is developed which posits that individuals’ psychological needs motivate their use of social media applications to the extent to which these applications provide affordances that satisfy these needs.
Abstract: The paper develops a needs–affordances–features (NAF) perspective on social media use which posits that individuals’ psychological needs motivate their use of social media applications to the extent to which these applications provide affordances that satisfy these needs Our theoretical development builds upon two psychological theories, namely self-determination and psychological ownership, to identify five psychological needs (needs for autonomy, relatedness, competence, having a place, and self-identity), that we posit are particularly pertinent to social media use According to NAF, these psychological needs will motivate use of those social media applications that provide salient affordances to fulfill these needs We identify such affordances through a comprehensive review of the literature and of social media applications and put forth propositions that map the affordances to the psychological needs that they fulfill Our theory development generates important implications First, it has implications for social media research in that it provides an overarching comprehensive framework for the affordances of social media as a whole and the related psychological needs that motivate their use Future studies can leverage NAF to identify psychological needs motivating the use of specific social media sites based on the affordances the sites provide, and design science research can leverage NAF in the design and bundling of specific social media features to engage users Second, it has implications for technology acceptance research in that NAF can enrich existing models by opening up the mechanisms through which psychological needs influence user perceptions of social media and their use patterns and behaviors Finally, NAF provides a new lens and common vocabulary for future studies, which we hope can stimulate cumulative research endeavors to develop a comprehensive framework of information systems affordances in general and the psychological needs that information systems satisfy
214 citations
TL;DR: In this paper, the authors examined how cross-side network effects on different platform sides (app-side and user-side) are temporally asymmetric, and how these CNEs are influenced by the platform's governance policies.
Abstract: In the context of software platforms, we examine how cross-side network effects (CNEs) on different platform sides (app-side and user-side) are temporally asymmetric, and how these CNEs are influenced by the platform’s governance policies. Informed by a perspective of value creation and capture, we theorize how the app-side and the user-side react to each other with distinct value creation/capture processes, and how these processes are influenced by the platform’s governance policies on app review and platform updates. We use a time-series analysis to empirically investigate the platform ecosystem of a leading web browser. Our findings suggest that while the growth in platform usage results in long-term growth in both the number and variety of apps, the growth in the number of apps and the variety of apps only leads to short-term growth in platform usage. We also find that long app review time weakens the long-term CNE of the user-side on the app-side, but not the short-term CNE of the app-side on the user-side. Moreover, we find that frequent platform updates weaken the CNEs of both the user-side and the app-side on each other. These findings generate important implications regarding how a software platform may better govern its ecosystem with different participants.
142 citations
TL;DR: Evidence is provided of the value of employing bootstrap confidence intervals in conjunction with PLSc, which is a more appropriate alternative than PLS for many of the research scenarios that are of interest to the field.
Abstract: Partial least squares (PLS) is one of the most popular statistical techniques in use in the Information Systems field. When applied to data originating from a common factor model, as is often the case in the discipline, PLS will produce biased estimates. A recent development, consistent PLS (PLSc), has been introduced to correct for this bias. In addition, the common practice in PLS of comparing the ratio of an estimate to its standard error to a t distribution for the purposes of statistical inference has also been challenged. We contribute to the practice of research in the IS discipline by providing evidence of the value of employing bootstrap confidence intervals in conjunction with PLSc, which is a more appropriate alternative than PLS for many of the research scenarios that are of interest to the field. Such evidence is direly needed before a complete approach to the estimation of SEM that relies on both PLSc and bootstrap CIs can be widely adopted. We also provide recommendations for researchers on the use of confidence intervals with PLSc.
142 citations
TL;DR: The empirical analysis suggests that IT infrastructure flexibility affects M&A through two key pathways: (1) a flexible IT infrastructure facilitates the development of business flexibility that provides the responsiveness to seize M &A opportunities and make acquisitions, and (2) a flexibility in IT integration capability provides the control to integrate the IT and business resources of the acquired firm and realize the economic benefits from M& a.
Abstract: Although mergers and acquisitions (M&A) are a common strategy to reduce costs and pursue growth, the variance in returns from M&A is very high. This research examines how information technology (IT) infrastructure flexibility affects M&A. We use a combination of secondary as well as matched-pair survey data from 100 mid-size firms in Spain to investigate this relationship. The empirical analysis suggests that IT infrastructure flexibility affects M&A through two key pathways: (1) a flexible IT infrastructure facilitates the development of business flexibility that provides the responsiveness to seize M&A opportunities and make acquisitions, and (2) a flexible IT infrastructure facilitates the development of post-M&A IT integration capability that provides the control to integrate the IT and business resources of the acquired firm and realize the economic benefits from M&A.
134 citations
TL;DR: It is demonstrated that IT mindfulness differs from important existing concepts such as cognitive absorption, can be manipulated, more closely relates to active system use than automatic system use, and provides more predictive power within the IS context than general trait mindfulness.
Abstract: Mindfulness is an important emerging topic. Individual mindfulness in IT use has not been studied systematically. Through three programmatic empirical studies, this paper develops a scale for IT mindfulness and tests its utility in the post-adoption system use context. Study 1 develops a measure of IT mindfulness and evaluates its validity and reliability. Study 2 employs a laboratory experiment to examine whether IT mindfulness can be manipulated and whether its influence is consistent across technological contexts. Study 3 places IT mindfulness in a nomological network and tests the construct’s utility for predicting more active system use (e.g., trying to innovate and deep structure usage) as well as more automatic system use (e.g., continuance intention). Our primary contribution includes the development and validation of a scale for IT mindfulness. In addition, we demonstrate that IT mindfulness (1) differs from important existing concepts such as cognitive absorption, (2) can be manipulated, (3) more closely relates to active system use than automatic system use, and (4) provides more predictive power within the IS context than general trait mindfulness.
110 citations
TL;DR: This work proposes that the widespread adoption of digital technology in everyday life leads to “everyone’s IT,” which is a new set of shared beliefs among consumers that highlights democratized access and individualized use of IT.
Abstract: IT governance describes the decision rights and accountability framework used to ensure the alignment of IT-related activities with the organization’s strategy and objectives. Conversely, IT consumerization refers to the process whereby the changing practices and expectations of consumers influence the IT-related activities of workers and managers in organizations. We propose that IT consumerization not only challenges the foundations of IT governance but ultimately also transforms it. To explore this research problem, we utilize the punctuated equilibrium theory and a case study of IT consumerization and the transformation of IT governance in a large global bank. Our findings suggest that the widespread adoption of digital technology in everyday life leads to “everyone’s IT,” which is a new set of shared beliefs among consumers that highlights democratized access and individualized use of IT. As everyone’s IT beliefs begin to alter the IT-related activities of workers, the result is IT governance misalignments that ultimately lead to a punctuated transformation of IT governance that dismantles functional IT governance. The establishment of platform-based governance marks a new equilibrium period. Our mid-range theory contributes to the IS domain with the novel concept of everyone’s IT and a grounded explanation of IT governance transformation in the context of IT consumerization. Our theory offers a set of significant research and practical implications.
104 citations
TL;DR: This research proposes contextualizing and extending McKnight et al.
Abstract: The life-like collaborative potential offered by virtual worlds (VWs) has sparked significant interest for companies to experiment with VWs in order to organize convenient, cost-effective virtual global workplaces. Despite the initial hype, recent years have witnessed a rather stagnant use of VWs for collaboration in organizations. Previous research recognizes that the inherent uncertainties within the VW environment are factors limiting their utilization by businesses. Hence, grounding this research in uncertainty reduction theory (URT), we aim to understand the modalities and mechanisms for mitigating the uncertainties and fostering user trust within VWs so that they can be effectively utilized as a workplace collaboration tool. With this end in view, we propose contextualizing and extending McKnight et al.’s (2002) institutional trust framework to the context of VWs by examining the significant role that social presence has in influencing the efficacy of the institution-based trust-building factors of situational normality and structural assurance in VWs. Using a sequential mixed methods approach (Venkatesh et al. 2013; Venkatesh, Brown, and Sullivan 2016), this research integrates results from a quantitative study with findings from a qualitative study to arrive at rich and robust inferences and meta-inferences, with the qualitative method first corroborating the inferences obtained from the quantitative research and then complementing them by identifying boundary conditions that may limit the use of VWs in organizations for workplace collaboration. The results together suggest not only the direct but also the interactional (complementary and substitutive) influences of social presence on the relationships of the two institutional trust-building factors to user trust in VWs.
96 citations
Journal Article•
TL;DR: The results suggest that after-hours work interruptions do not necessarily benefit work performance and come at the cost of work exhaustion, and the effects of interruptions are dependent on the technology via which these occur.
Abstract: Work interruptions have made significant inroads into the knowledge workers’ nonwork domain, in large part due to the ubiquitous nature of mobile devices that blur the work–nonwork boundaries by enabling work interruptions anywhere and at any time. We examine the effects of such technology-mediated work-related interruptions that occur during one’s time off on both work and nonwork outcomes. Leveraging theoretical perspectives from interruption, work–life interface, and conservation of resources, we conceptualize both positive and negative effects of such interruptions on behavioral and psychological outcomes. We identify three mediating mechanisms via which these effects occur: interruption overload and psychological transition via which negative effects occur and task closure via which positive effects occur. Results reveal significant effects of interruptions on work and nonwork outcomes through the three mediating mechanisms. Although positive effects are observed, the total effects of work-related interruptions are detrimental across both work and nonwork outcomes, with the strongest negative effect on work exhaustion. The results suggest that after-hours work interruptions do not necessarily benefit work performance and come at the cost of work exhaustion. Analyses also reveal that the effects of interruptions are dependent on the technology via which these occur. While phone and messaging generate negative outcomes through interruption overload, e-mail leads to both positive and negative outcomes through task closure and psychological transition respectively. The study concludes with implications for research and practice on how to mitigate negative effects and enhance positive effects.
88 citations
TL;DR: This work proposes a LAP-based text analytics framework to support sense-making in online discourse and rigorously evaluates a system that is developed based on the framework in a series of experiments using a test bed encompassing social media data from multiple channels and industries.
Abstract: Social media and online communities provide organizations with new opportunities to support their business-related functions. Despite their various benefits, social media technologies present two important challenges for sense-making. First, online discourse is plagued by incoherent, intertwined conversations that are often difficult to comprehend. Moreover, organizations are increasingly interested in understanding social media participants’ actions and intentions; however, existing text analytics tools mostly focus on the semantic dimension of language. The language-action perspective (LAP) emphasizes pragmatics; not what people say but, rather, what they do with language. Adopting the design science paradigm, we propose a LAP-based text analytics framework to support sense-making in online discourse. The proposed framework is specifically intended to address the two aforementioned challenges associated with sense-making in online discourse: the need for greater coherence and better understanding of actions. We rigorously evaluate a system that is developed based on the framework in a series of experiments using a test bed encompassing social media data from multiple channels and industries. The results demonstrate the utility of each individual component of the system, and its underlying framework, in comparison with existing benchmark methods. Furthermore, the results of a user experiment involving hundreds of practitioners, and a four-month field experiment in a large organization, underscore the enhanced sense-making capabilities afforded by text analytics grounded in LAP principles. The results have important implications for online sense-making and social media analytics.
86 citations
TL;DR: This paper characterize the dynamics of user contributions using a hidden Markov model with latent motivation states under the public goods framework, and focuses on three motivating mechanisms on transitioning users between the latent states: reciprocity, peer recognition, and self-image.
Abstract: User contribution is critical to online communities but also difficult to sustain given its public goods nature. This paper studies the design of IT artifacts to motivate voluntary contributions in online communities. We propose a dynamic approach, which allows the effect of motivating mechanisms to change across users over time. We characterize the dynamics of user contributions using a hidden Markov model (HMM) with latent motivation states under the public goods framework. We focus on three motivating mechanisms on transitioning users between the latent states: reciprocity, peer recognition, and self-image. Based on Bayesian estimation of the model with user-level panel data, we identify three motivation states (low, medium, and high), and show that the motivating mechanisms, implemented through various IT artifacts, could work differently across states. Specifically, reciprocity is only effective to transition users from low to medium motivation state, whereas peer recognition can boost all users to higher states. And self-image shows no effect when a user is already in high motivation state, although it helps users in low and medium states move to the high state. Design simulations on our structural model provide additional insights into the consequences of changing specific IT artifacts. These findings offer implications for platform designers on how to motivate user contributions and build sustainable online communities.
TL;DR: This paper distinguishes between two types of e-mail interruptions (incongruent and congruent) and draws upon action regulation theory and the computer-mediated communication literature to examine their direct and indirect effects on individual performance.
Abstract: Interruption of work by e-mail and other communication technologies has become widespread and ubiquitous. However, our understanding of how such interruptions influence individual performance is limited. This paper distinguishes between two types of e-mail interruptions (incongruent and congruent) and draws upon action regulation theory and the computer-mediated communication literature to examine their direct and indirect effects on individual performance. Two empirical studies of sales professionals were conducted spanning different time frames: a survey study with 365 respondents and a diary study with 212 respondents. The results were consistent across the two studies, showing a negative indirect effect of exposure to incongruent interruptions (interruptions containing information that is not relevant to primary activities) through subjective workload, and a positive indirect effect of exposure to congruent interruptions (interruptions containing information that is relevant to primary activities) through mindfulness. The results differed across the two studies in terms of whether the effects were fully or partially mediated, and we discuss these differences using meta-inferences. Technology capabilities used during interruption episodes also had significant effects: rehearsing (fine-tuning responses to incoming messages) and reprocessing (reexamining received messages) were positively related to mindfulness, parallel communication (engaging in multiple e-mail conversations simultaneously) and leaving messages in the inbox were positively related to subjective workload, and deleting messages was negatively related to subjective workload. This study contributes to research by providing insights on the different paths that link e-mail interruptions to individual performance and by examining the effects of using capabilities of the interrupting technology (IT artifact) during interruption episodes. It also complements the experimental tradition that focuses on isolated interruptions. By shifting the level of analysis from specific interruption events to overall exposure to interruptions over time and from the laboratory to the workplace, our study provides realism and ecological validity.
TL;DR: It is found that paying for premium leads to an increase in both content-related and community-related social engagement, and premium subscribers create value not only for themselves by consuming more content, but also for the community and site by organizing more content and adding more friends.
Abstract: Making sustainable profits from a baseline zero price and motivating free consumers to convert to premium subscribers is a continuing challenge for all freemium communities. Prior research has causally established that social engagement (Oestreicher-Singer and Zalmanson 2013) and peer influence (Bapna and Umyarov 2015) are two important drivers of users converting to premium subscribers in such communities. In this paper, we flip the perspective of prior research and ask whether the decision to pay for a premium subscription causes users to become more socially engaged. In the context of the Last.fm music listening freemium social community, we establish, using a novel 41-month-long panel dataset, a look-ahead propensity score matching (LA-PSM) procedure coupled with a difference-in-difference estimator of the treatment effect, that payment for premium leads to more social engagement. Specifically, we find that paying for premium leads to an increase in both content-related and community-related social engagement. Free users who convert to premium listen to 287.2% more songs, create 1.92% more playlists, exhibit a 2.01% increase in the number of forum posts made, and gain 15.77% more friends. Thus, premium subscribers create value not only for themselves by consuming more content, but also for the community and site by organizing more content and adding more friends, who are subsequently engaged by the social diffusion emerging from the focal user’s activities.
TL;DR: A model that builds on user innovation theory and the work design literature to explain the influences of lead userness, design autonomy, toolkit support, and their interactions on user’s innovation outcomes (innovation quantity) on mobile phone platforms is proposed.
Abstract: User participation is increasingly being seen as a way to mitigate the challenges that firms face in innovation, such as high costs and uncertainty of customer acceptance of their innovations. Thus, firms are establishing online platforms to support users in innovating services, such as iOS and Android platforms for mobile data service (MDS) innovation. Mobile phone platforms are characterized by technology (toolkits) and policy (rules) components that could influence user’s innovation. Additionally, attributes of user innovators (lead userness) are expected to drive their innovation behavior. Yet it is unclear how these characteristics jointly impact users’ service innovation outcomes. To address this knowledge gap, we propose a model that builds on user innovation theory and the work design literature to explain the influences of lead userness, design autonomy, toolkit support, and their interactions on user’s innovation outcomes (innovation quantity) on these platforms. We conceptualize toolkit support in terms of two constructs (i.e., ease of effort and exploration), and design autonomy in terms of three constructs (i.e., decision-making autonomy, scheduling autonomy, and work-method autonomy). The model was tested using survey and archival data from two dominant mobile phone platforms (i.e., iOS and Android). As hypothesized, lead userness, exploration through toolkits, and ease of effort through toolkits positively affect users’ innovation quantity. Additionally, decision-making autonomy and work-method autonomy influence innovation quantity, but scheduling autonomy does not. Further, the proposed three-way interactions between lead userness, toolkit support, and design autonomy constructs on users’ quantity of MDS innovation are largely supported. The findings enhance our understanding of user innovation on mobile phone platforms.
TL;DR: It is shown that the platform sponsor’s investments in knowledge seeding have a positive, significant association with user knowledge contribution, and returns decrease with the age of the community, consistent with the observation that the most active contributors are lead users who tend to join the community early.
Abstract: How should digital platforms engage with and invest in their online communities to shape innovation and knowledge contributions from members in their platform ecosystems? This is an important question because user contributions are important drivers of technological progress and business value. We examine the effect of platform sponsors’ investments in online communities on user knowledge contributions, using fine-grained longitudinal data from a leading enterprise software vendor’s community network. We focus on the sponsor practice of knowledge seeding, in which its employees provide free technical support by answering questions posted in discussion forums. We define user knowledge contribution as peer-evaluated, quality-weighted solutions that community members provide to help resolve the questions their peers raise. We show that the platform sponsor’s investments in knowledge seeding have a positive, significant association with user knowledge contribution. We also find temporal and geographical variations in returns on the sponsor’s knowledge investments. Specifically, returns (i.e., amount of user contribution that is stimulated) decrease with the age of the community, consistent with the observation that the most active contributors are lead users who tend to join the community early. In addition, returns vary across different countries, such that greater returns are realized when the investment is made in countries with higher levels of information technology (IT) infrastructure, partly because country-level IT infrastructure may be associated with greater absorptive capacity of these countries. We discuss the implications for research and practice.
TL;DR: This is the first paper in the literature to study the existence and drivers of differential treatment when customer service is delivered on social media, and it is found that the airlines are more likely to respond to complaints from customers withMore followers, and customers with more followers are morelikely to receive faster responses, thus confirming the existence of a concealed social media influence effect.
Abstract: Companies increasingly are providing customer service through social media, helping customers on a real-time basis. Although some traditional call centers might prioritize customers based on their expected business values, the grounds for differential customer service on social media are unclear, since there has been little theoretical or empirical investigation of this new phenomenon. Building on the literature of social psychology and complaint management, we hypothesize two main drivers of differential treatment: the social media influence effect, which refers to the impact of the customer’s relative standing on social media, and the bystander effect, which refers to the impact of the presence of other social media users. To test these effects, we analyzed more than three million tweets to seven major U.S. airlines on Twitter from September 2014 to May 2015. The evidence is clear that airlines respond to less than half of the tweets directed at them by complaining customers—in contrast with traditional call centers, which are expected to address all callers. Interestingly, we find that the airlines are more likely to respond to complaints from customers with more followers, and customers with more followers are more likely to receive faster responses, thus confirming the existence of a concealed (or at least unpublicized) social media influence effect. We also find that airlines are less likely to respond to complaints with multiple parties mentioned, confirming the existence of the bystander effect. To the best of our knowledge, this is the first paper in the literature to study the existence and drivers of differential treatment when customer service is delivered on social media, and we expect our findings will have important implications for companies, customers, and regulators.
TL;DR: The results show that the influence of microblog sentiment on stock returns is both statistically and economically significant at the hour level, and stock returns have a stronger influence on negative sentiment than on positive sentiment.
Abstract: Opinion mining of microblog messages has become a popular application of business analytics in recent times. Opinions reflected in microblogs have provided businesses with great opportunities to acquire insights into their operating environments in real time. In particular, the relationship between microblog sentiment and stock returns is of great interest to investment professionals and academic researchers across multiple disciplines. We empirically test this complex relationship in a comprehensive study. We perform vector autoregression on a data set containing close to 18 million microblog messages spanning 4 years at the market and the individual stock levels, and at the daily and the hourly frequencies. The results show that the influence of microblog sentiment on stock returns is both statistically and economically significant at the hour level. Microblog sentiment is also largely driven by movements in the market. Moreover, stock returns have a stronger influence on negative sentiment than on positive sentiment. These findings have important implications for both research and practice.
TL;DR: This article found that the average account posts links to more politically moderate news sources than the ones they receive in their own feed, which could explain the widespread perception of polarization on social media.
Abstract: Social media have great potential to support diverse information sharing, but there is widespread concern that platforms like Twitter do not result in communication between those who hold contradictory viewpoints. Because users can choose whom to follow, prior research suggests that social media users exist in echo chambers or become polarized. We seek evidence of this in a complete cross section of hyperlinks posted on Twitter, using previously validated measures of the political slant of news sources to study information diversity. Contrary to prediction, we find that the average account posts links to more politically moderate news sources than the ones they receive in their own feed. However, members of a tiny network core do exhibit cross-sectional evidence of polarization and are responsible for the majority of tweets received overall due to their popularity and activity, which could explain the widespread perception of polarization on social media.
TL;DR: Results show not only a general decline of participants’ attention to warnings over time but also that attention recovers at least partially between workdays without exposure to the warnings, and demonstrate that polymorphic warnings can substantially improve adherence.
Abstract: Research in the fields of information systems and human-computer interaction has shown that habituation— decreased response to repeated stimulation—is a serious threat to the effectiveness of security warnings. Although habituation is a neurobiological phenomenon that develops over time, past studies have only examined this problem cross-sectionally. Further, past studies have not examined how habituation influences actual security warning adherence in the field. For these reasons, the full extent of the problem of habituation is unknown.
We address these gaps by conducting two complementary longitudinal experiments. First, we performed an experiment collecting fMRI and eye-tracking data simultaneously to directly measure habituation to security warnings as it develops in the brain over a five-day workweek. Our results show not only a general decline of participants’ attention to warnings over time but also that attention recovers at least partially between workdays without exposure to the warnings. Further, we found that updating the appearance of a warning— that is, a polymorphic design—substantially reduced habituation of attention.
Second, we performed a three-week field experiment in which users were naturally exposed to privacy permission warnings as they installed apps on their mobile devices. Consistent with our fMRI results, users’ warning adherence substantially decreased over the three weeks. However, for users who received polymorphic permission warnings, adherence dropped at a substantially lower rate and remained high after three weeks, compared to users who received standard warnings. Together, these findings provide the most complete view yet of the problem of habituation to security warnings and demonstrate that polymorphic warnings can substantially improve adherence.
TL;DR: A framework of causal structure, warranted by philosophy and social theory, specialized for the needs of Information Systems scholars is proposed, which aims to offer useful insights into the nature of IS theory and the conundrum of theoretical contribution.
Abstract: Whatever answer one gives to the question “Is information technology changing the world?,” the answer contains reasoning about causality. Causal reasoning is central to IS theorizing. This paper focuses on the concept of causal structure, defined by Markus and Robey (1988) as a theorist’s assumptions about causal influences in IS phenomena, and proposes a framework of causal structure, warranted by philosophy and social theory, specialized for the needs of Information Systems scholars. The three dimensions of the framework concern the theorist’s views about the reality and meaning of causation (causal ontology), about that which is changed in causation (causal trajectory), and about the role of humans and/or technology in bringing about the change (causal autonomy). On each dimension, mutually exclusive alternative positions are described, backed by authoritative warrants, and illustrated with IS examples. The framework aims to offer useful insights into the nature of IS theory and the conundrum of theoretical contribution.
TL;DR: In this article, the authors compare the predictive power of privacy decision making from a behavioral perspective and a rational perspective by evaluating the impact of changes in the objective risk of disclosure and the change in the relative perceptions of risk on both hypothetical and actual consumer privacy choices.
Abstract: Privacy decision making has been examined in the literature from alternative perspectives A dominant “normative” perspective has focused on rational processes by which consumers with stable preferences for privacy weigh the expected benefits of privacy choices against their potential costs More recently, a behavioral perspective has leveraged theories from decision research to construe privacy decision making as a process in which cognitive heuristics and biases predictably occur In a series of experiments, we compare the predictive power of these two perspectives by evaluating the impact of changes in the objective risk of disclosure and the impact of changes in the relative perceptions of risk of disclosure on both hypothetical and actual consumer privacy choices We find that both relative and objective risks can, in fact, influence consumer privacy decisions However, and surprisingly, the impact of objective changes in risk diminishes between hypothetical and actual choice settings Vice versa, the impact of relative risk becomes more pronounced going from hypothetical to actual choice settings Our results suggest a way to integrate diverse streams of the information systems literature on privacy decision making: in hypothetical choice contexts, relative to actual choice contexts, consumers may both overestimate their response to normative factors and underestimate their response to behavioral factors
TL;DR: This work compares bias in these two models in the context of contested knowledge, which involves subjective, unverifiable, or controversial information, and finds that Wikipedia articles are more slanted toward Democratic views than are Britannica articles, as well as more biased.
Abstract: Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective, unverifiable, or controversial information. Using data from Encyclopedia Britannica, authored by experts, and Wikipedia, an encyclopedia produced by an online community, we compare the slant and bias of pairs of articles on identical topics of U.S. politics. Our slant measure is less (more) than zero when an article leans toward Democratic (Republican) viewpoints, while bias is the absolute value of the slant. We find that Wikipedia articles are more slanted toward Democratic views than are Britannica articles, as well as more biased. The difference in bias between a pair of articles decreases with more revisions. The bias on a per word basis hardly differs between the sources because Wikipedia articles tend to be longer than Britannica articles. These results highlight the pros and cons of each knowledge production model, help identify the scope of the empirical generalization of prior studies comparing the information quality of the two production models, and offer implications for organizations managing crowd-based knowledge production.
TL;DR: Results suggest that users evaluate ESNS information differently depending on the type of processing (heuristic or systematic) and that these social capital perceptions influence preferences for different team members.
Abstract: Social media has changed the way many team members “meet” for the first time. Due to the increased use of virtual environments, it is now common for team members to examine each other’s profile on a firm’s enterprise social networking site (ESNS) in lieu of an initial face-to-face meeting. This study examines how the information provided in an ESNS impacts impression formation at the initial formation of a virtual team, specifically perceptions of social capital (i.e., relational, structural, and cognitive). To examine social capital perceptions, the elaboration likelihood model (ELM) is utilized to understand how not only information impacts these perceptions but the way in which the user processes information to form the perceptions. Toulmin’s model of argumentation is used in conjunction with ELM to understand the strength of the argument presented. Results suggest that users evaluate ESNS information differently depending on the type of processing (heuristic or systematic) and that these social capital perceptions influence preferences for different team members.
TL;DR: By using CPOE in a comprehensive manner, patient care team members are better able to coordinate patient care and are able to better inform the patient about their care, ultimately leading to improved patient satisfaction.
Abstract: In the United States, the Centers for Medicare & Medicaid Services (CMS) has begun instituting pay-for-performance incentives that reward hospitals based on patient-centric outcomes such as patient satisfaction Further, to promote the “meaningful use” of health information technology (HIT), CMS has been prompting hospitals to adopt and use HITs Computerized provider order entry (CPOE) is one such HIT and is designed to improve coordination in patient care teams and consequently patient outcomes We explore the impact of CPOE-enabled coordination on patient satisfaction with the care team In a departure from prior research that has tended to treat the team as all clinicians within a hospital unit/clinic, we conceptualize (and operationalize) patient care teams as ad hoc and patient-specific and thus comprised of those clinicians having direct contact with the patient In a further departure from prior research that has employed lean measures of IS use (eg, use intentions, duration, or frequency of use), we respond to the call for rich measures of IS use by conceptualizing deep structure use (DSU) of CPOE as patient care team-level usage of CPOE features
We draw upon adaptive structuration theory (AST) to identify faithfulness of appropriation (FOA) and consensus on appropriation (COA) as two related, but distinct, aspects of CPOE appropriation by patient care teams that affect DSU We also draw on relational coordination theory to conceptualize communicative coordination (CC) as team communication for coordination purposes and theorize that DSU affects patient satisfaction through CC and informating the patient differentially across high/low patient mortality risk conditions
Based on data from 224 patient care teams caring for both low and high patient mortality risk conditions, our results indicate that FOA and COA are salient predictors of DSU, and that the effect of COA on DSU is mediated by FOA We also observed a significant indirect effect of DSU on patient satisfaction (as mediated by communicative coordination and patient informating), but only for high patient mortality risk conditions Our findings are important because they show that by using CPOE in a comprehensive manner, patient care team members are better able to coordinate patient care and are able to better inform the patient about their care, ultimately leading to improved patient satisfaction Additional implications for HIT research and practice are discussed
TL;DR: It is theorized that the effect of imperfect recommendation on consumers’ unplanned purchases depends on their mood, and that consumers in positive moods are more likely to form an urge to buy than those in negative moods.
Abstract: By tracking consumers’ browsing and purchase history, web personalization generates taste-matched recommendations for each consumer to stimulate purchases In addition to taste-matching, mobile personalization matches recommendations to a consumer’s physiological need and current location These two additional features, referred to as need-matching and location-matching, are believed to be enablers of unplanned purchases However, mobile advertisers may not be able to generate recommendations that meet all personalization criteria Hence, mobile recommendations may be imperfect We examine two questions in relation to imperfect recommendations First, how do we use a descriptor to promote such recommendations? Second, what personalization criterion should be downplayed to induce unplanned purchases? Drawing upon the theory of mood congruence, we theorize that the effect of imperfect recommendation on consumers’ unplanned purchases depends on their mood We conducted three field experiments to test our hypotheses Our findings indicate that (1) consumers in positive moods are more likely to form an urge to buy than those in negative moods, and this difference is larger when the descriptor is partial than when it is complete (Experiment 1); (2) need-matching is more influential on urge to buy for consumers in negative moods than for those in positive moods (Experiment 2); and (3) for taste-and-need-matched recommendations, location-matching exerts a stronger effect on the urge to buy for consumers in negative moods than for those in positive moods (Experiment 3) We validated the relevance of our research findings to practice through interviews with senior executives in personalization solution providers Pathways for enhancing practical impacts of this line of research are recommended
TL;DR: A framework to recommend tasks to solvers who wish to participate in crowdsourcing contests and it is shown that deploying such a system should benefit not only the solvers, but also the seekers and the platform itself.
Abstract: Crowdsourcing contests have emerged as an innovative way for firms to solve business problems by acquiring ideas from participants external to the firm As the number of participants on crowdsourcing contest platforms has increased, so has the number of tasks that are open at any time This has made it difficult for solvers to identify tasks in which to participate We present a framework to recommend tasks to solvers who wish to participate in crowdsourcing contests The existence of competition among solvers is an important and unique aspect of this environment, and our framework considers the competition a solver would face in each open task As winning a task depends on performance, we identify a theory of performance and reinforce it with theories from learning, motivation, and tournaments This augmented theory of performance guides us to variables specific to crowdsourcing contests that could impact a solver’s winning probability We use these variables as input into various probability prediction models adapted to our context, and make recommendations based on the probability or the expected payoff of the solver winning an open task We validate our framework using data from a real crowdsourcing platform The recommender system is shown to have the potential of improving the success rates of solvers across all abilities Recommendations have to be made for open tasks and we find that the relative rankings of tasks at similar stages of their time lines remain remarkably consistent when the tasks close Further, we show that deploying such a system should benefit not only the solvers, but also the seekers and the platform itself
TL;DR: An analytical model is developed to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor and finds that vendor competition does not always result in higher consumer surplus, and it might lead to a socially inefficient outcome under certain conditions.
Abstract: Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the perpetual software vendor adopts one of three different strategies: (1) an entry deterrence strategy, (2) a market segmentation strategy, or (3) a sequential dominance strategy. Surprisingly, we find that vendor competition does not always result in higher consumer surplus, and it might lead to a socially inefficient outcome under certain conditions. We further show insights into how the incumbent perpetual software vendor can defend its market position by providing incremental quality improvement through patching and/or by releasing consecutive versions with major quality upgrades. Finally, we extend our model to include the vendor’s quality improvement cost and users’ switching cost. These additional analyses help to identify the effect of different quality and cost factors on the market competitive equilibrium.
TL;DR: Evidence was found that different combinations of cultural and media effects affected the accuracy of deception detection, especially where the deceptive communication occurs across different media.
Abstract: As the world “gets smaller” and more people engage in cross-cultural communications, their ability to successfully separate truth from deception can be critically important. Yet it is challenging. While deceptive communication has been studied for decades, some areas are not well understood. In particular, two areas that could benefit from further research concern the effects of cultural differences and communication media on deception and its detection. Building on developments in theories of deception and its detection, we examine the question: How do differences in culture between senders and receivers affect deception detection, especially where the deceptive communication occurs across different media? To address this question, stimulus materials from recorded interviews were created featuring participants from the United States, Spain, and India. Three stimulus sets were created, one each in American English, Spanish, and Indian English, and each consisting of 32 interview snippets. Half of the snippets were honest and half were dishonest. Each snippet represented one of four media: full audio-visual, video only, audio only, and text only. Veracity judges were also recruited from the same three countries as the interview participants, to independently observe and evaluate the communication both within their culture and across other cultures. Evidence was found that different combinations of cultural and media effects affected the accuracy of deception detection.
TL;DR: The theory illuminates how polycentric governance principles, as manifested in system rules and infrastructure features, counterbalance various sustainability threats arising from unrestricted participation and can enhance the likelihood of sustained participation across diverse, decentralized online information systems.
Abstract: Research on various distributed online information systems—including blogging, crowdsourcing, media sharing, online communities, online reviews, open source software development, social media, wikis, peer-to-peer file sharing, and two-sided electronic markets—shows that the level of user engagement and overall activity in most systems eventually decline substantially. Here, we draw on Hardin’s theory of the tragedy of the commons and Ostrom’s theory of polycentric governance to introduce a unifying theory of polycentric information commons that explains these phenomena. Further, our theory illuminates how polycentric governance principles, as manifested in system rules and infrastructure features, counterbalance various sustainability threats arising from unrestricted participation. By integrating previous research findings and offering new insights into information and governance practices, the theory, practically applied, can enhance the likelihood of sustained participation across diverse, decentralized online information systems. We conclude by discussing how researchers can use the theory in empirical investigations and how they can engage in theoretical elaborations.
TL;DR: This study investigates the competition between a newEntrant and an incumbent in a SaaS market, and derives the optimal market entry strategy for the new entrant.
Abstract: As a new software licensing model, software-as-a-service (SaaS) is gaining tremendous popularity across the globe. In this study, we investigate the competition between a new entrant and an incumbent in an SaaS market, and derive the optimal market entry strategy for the new entrant. One interesting finding is that, when its product quality is significantly lower than that of the incumbent, the new entrant should adopt an instant-release strategy (i.e., releasing its product at the start of the planning horizon). If the initial quality gap of the two products is small, the new entrant is better off adopting a late-release strategy (i.e., deferring the release of the new product until its quality surpasses that of the existing product). We also find that instant-release and late-release are essentially low-quality/low-price and high-quality/high-price strategies, respectively. In addition, we explore the scenario where the two competing products are partially compatible, and characterize the impact of asymmetric incompatibility on the two vendors’ market strategies at equilibrium. We find that the new entrant’s zero-profit region expands as the level of incompatibility between the two competing products increases. Moreover, if the new entrant adopts the instant-release strategy, its profit decreases with the level of incompatibility. When the level of incompatibility is sufficiently high, the instant-release strategy may not be viable for the new entrant. On the other hand, if the new entrant adopts the late-release strategy, its profit increases with the level of incompatibility from its product to the incumbent’s, but decreases with the level of incompatibility in the other direction.