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Privacy in online social networking (OSN) is more complex than in traditional online environments, such as e-commerce. In addition to simply limiting self-disclosure, OSN users can also use privacy settings and manage their network size to ensure privacy. This complexity calls for an enhanced OSN privacy model that more completely explains privacy behaviors. Combining the privacy calculus model with part of the uses and gratifications approach, this paper proposes an OSN privacy model that depicts both antecedents (i.e., privacy concern, trusting beliefs, and personal interest) and outcomes (i.e., gratifications obtained) of perceived privacy and use behaviors. Using an Empanel survey sample collected from U.S. Facebook users, results show that privacy concern influences network size, trust influences privacy setting use and use frequency, and personal interest influences each privacy and use behavior. Findings also show that the privacy behaviors’ influence on gratifications obtained is complex in nature. A three-way interaction influences enjoyment and habit gratifications, and a two-way interaction influences bonding social capital. This paper provides opportunities for future research regarding OSN privacy behaviors, and it discusses practical implications.

Purpose Organizational insiders play a critical role in protecting sensitive information. Prior research finds that moral beliefs influence compliance decisions. Yet, it is less clear what factors influence moral beliefs and the conditions under which those factors have stronger/weaker effects. Using an ethical decision-making model and value congruence theory, this study aims to investigate how moral intensity and organizational criticality influence moral beliefs and intentions to perform information protection behaviors. Design/methodology/approach The hypotheses were tested using a scenario-based survey of 216 organizational insiders. Two of the scenarios depict low criticality information security protection behaviors and two depict high criticality behaviors. Findings A major finding is that users rely more on perceived social consensus and magnitude of consequences when organizational criticality is low and on temporal immediacy and proximity when criticality is high. In addition, the moral intensity dimensions explain more variance in moral beliefs when organizational criticality is low. Research limitations/implications The study is limited by its sample, which is organizational insiders at a mid-size university. It is also limited in that it only examined four of the six moral intensity dimensions. Practical implications The findings can guide management about which moral intensity dimensions are more important to focus on when remediating tone at the top and other leadership weaknesses relating to information security. Originality/value This study adds value by investigating the separate dimensions of moral intensity on information protection behaviors. It also is the first to examine moral intensity under conditions of low and high organizational criticality.

Online privacy management research related to e-commerce mainly focuses on whether or not to disclose information. Online social networking on the other hand, offers a broader set of privacy management behaviors such as using vendor-provided privacy settings, limiting self-disclosures, and managing network size. While much prior research has examined these privacy behaviors individually, we investigate how Facebook users combine these behaviors to form privacy management strategies. Using communications privacy management and impression management theories we first develop four propositions about possible user strategies that combine differing levels of disclosure, network size, and privacy setting use. One strategy is the most public, whereas two others deviate from this public strategy by either limiting disclosures, or using privacy settings to restrict access. The final strategy is the most private. We then survey two samples of Facebook users (college students and the general population) about their privacy management behaviors, privacy perceptions, technology usage perceptions, and demographics. Using cluster analysis we find some support for all four propositions, and for an additional strategy that beginning users may employ. The findings also reveal intriguing differences among the privacy management strategies in terms of perceptions and demographics like privacy concern, usefulness, enjoyment, and age, gender, and experience. Implications for future research are discussed.

Successful business-to-business (B2B) data exchanges can help firms improve inter-organizational cooperation and operational practices, thereby increasing competitive advantage. However, data exchange quality and trust are not assured. Further, although researchers have examined how trust in the exchange partner relates to data exchange system success, both trust and distrust may be important to consider. Using two-factor theory and trust theory, we examine the differential impacts of information quality, system quality, and service outcome quality on trusting and distrusting beliefs. We also study whether trusting and distrusting beliefs have differential influences on relationship commitment and perceived risk. Results from a laboratory experiment show that information quality, a process (i.e., motivating) factor, more strongly influences trusting beliefs than distrusting beliefs, whereas service outcome quality, an outcome (i.e., hygiene) factor, more strongly influences distrusting beliefs. Also, while trusting beliefs has a significantly stronger influence on relationship commitment, trusting and distrusting beliefs have equivalent effects on perceived risk. Implications and ways to expand this research are discussed.

IT governance is important to the success of most business enterprises. One form of IT governance is the use of board-level IT committees. This study examines committee charters, which are the basic foundation for an effective committee. Based on prior literature and theory, we develop a framework and six propositions for assessing IT committee charter components including committee characteristics, member characteristics, and roles and responsibilities. We test the propositions by exploring the IT committee charters and information from other sources for 23 Fortune 500 companies. We find that most IT committees have more members and meet more often than required by the charter. All but one committee has at least one member with IT expertise as defined in our study. Also, most roles and responsibilities are focused on the five IT governance focus areas prescribed by the Information Technology Governance Institute. However, the roles are not consistently specified in all charters. Suggestions for future research and guidelines for practice are provided.

Trust in technology is an emerging research domain that examines trust in the technology artifact instead of trust in people. Although previous research finds that trust in technology can predict important outcomes, little research has examined the effect of unmet trust in technology expectations on trusting intentions. Furthermore, both trust and expectation disconfirmation theories suggest that trust disconfirmation effects may be more complex than the linear expectation disconfirmation model depicts. However, this complexity may only exist under certain contextual conditions. The current study contributes to this literature by introducing a nonlinear expectation disconfirmation theory model that extends understanding of trust-in-technology expectations and disconfirmation. Not only does the model include both technology trust expectations and technology trusting intention, it also introduces the concept of expectation maturity as a contextual factor. We collected data from three technology usage contexts that differ in expectation maturity, which we operationalize as length of the introductory period. We find that the situation, in terms of expectation maturity, consistently matters. Using polynomial regression and response surface analyses, we find that in contexts with a longer introductory period (i.e., higher expectation maturity), disconfirmation has a nonlinear relationship with trusting intention. When the introductory period is shorter (i.e., expectation maturity is lower), disconfirmation has a linear relationship with trusting intention. This unique set of empirical findings shows when it is valuable to use nonlinear modeling for understanding technology trust disconfirmation. We conclude with implications for future research.

Continued use of strategic information systems is not always a given. This study proposes that users’ trust in the system may influence their satisfaction and continuance intention. While trust has been found to have strategic implications for understanding consumers’ technology usage, relatively little research has examined how trust’s influence operates over time. To gain insight into trust’s influence on strategic system usage over time and to explain how trust relates to satisfaction and continuance intention, we integrate trust-related constructs with the Complete Expectation Disconfirmation Theory (EDT) Model. Our results demonstrate that trust plays a central role in the EDT process and that the EDT process helps explain trust’s role more completely. The study shows that technology trusting expectations influence trusting intention through performance, disconfirmation, and satisfaction. We also show that technology trusting intention adds predictive power to EDT’s satisfaction construct as together they predict usage continuance intention. For research, our results provide a strong combined EDT and trust theory base for future studies that examine expectation management and system development projects. For practice, our study informs systems implementation strategies for technologies that have fewer human-like characteristics and more technology-like characteristics. Our findings underscore that managers need to adopt an EDT process-based view when seeking to build trust, satisfaction, and continuance intention in strategically important information systems.

While some online social networking (OSN) websites, such as Facebook, have reported sustained growth, others, such as Bebo, have not. This study investigates the factors that influence users' intentions to continue using these websites. We adapt the theory of reasoned action and develop a model depicting how trusting beliefs, habit, attitude, and subjective norm lead to continuance intention. We propose that trusting beliefs and habit will have differential effects depending on the levels of privacy restrictiveness and site experience. An analysis of data collected from Facebook users shows that the effects of trusting beliefs on continuance intention diminish as OSN users become more experienced, yet, do not diminish when users set privacy controls high. The latter finding contradicts theory positing control and trusting beliefs are substitutes. The finding that the trusting belief-continuance intention relationship is not significant when experience is high demonstrates that trusting beliefs and experience interact. We also show that habit is a stronger predictor when users restrict their personal information. However, contrary to predictions, habit shapes intention among users with both high and low experience. These findings explain how habit and trusting beliefs predict continuance intention in the new OSN environment and have both practical and research implications.

Internet tools used as knowledge retrieval mechanisms can be beneficial for knowledge acquisition (KA). This study applies the concepts of decisional guidance and restrictiveness to three commonly used tools to predict perceived information overload, task quality, and task speed for tasks that differ in complexity. In an experimental setting we find that less restrictive pull systems (i.e., web directories and Google search) increased quality in high-complexity tasks over more restrictive push systems (i.e., listservs) and lowered perceived information overload in both low- and high-complexity tasks. In low-complexity tasks, subjects using predefined guidance (i.e., listservs and web directories) performed better and faster than those using participative guidance (i.e., Google search). In high-complexity tasks, participative guidance provided lower perceived information overload and higher task quality. Implications for research and practice are discussed. Highlights? In high-complexity tasks, less restrictive pull systems (i.e., web directories and Google search) increased quality and lowered perceived information overload over more restrictive push systems (i.e., listservs). ? In low-complexity tasks less restrictive pull systems lowered perceived information overload. ? In low-complexity tasks, predefined guidance (i.e., listservs and web directories) performed better and faster than those using participative guidance (i.e., Google search). ? In high-complexity tasks, participative guidance provided lower perceived information overload and higher task quality than predefined guidance.

Researchers have recently studied technology trust in terms of the technological artifact itself. Two different kinds of trusting beliefs could apply to a website artifact. First, the trusting beliefs may relate to the interpersonal characteristics--competence, integrity, and benevolence. Second, they may relate to corresponding technology characteristics--functionality, reliability, and helpfulness. Since social networking websites like Facebook may demonstrate either interpersonal or technology trust characteristics, researchers may need to carefully choose the beliefs to model. Thus it is important to understand not only the conceptual meaning of these beliefs, but also whether human and technology trust beliefs are distinct. Using data collected from 362 university-student Facebook users, we test two second-order factor structures that represent alternative ways to model the three interpersonal and three technology trust beliefs. We find that the best-fitting measurement model depicts the three conceptually-related pairs of trust beliefs (competence-functionality, integrity-reliability, and benevolence-helpfulness) as three distinct second-order factors. This model outperformed the model splitting trusting beliefs into separate interpersonal and technology second-order factors. The results show people distinguish among three types of conceptually-related trust attributes, and that they trust Facebook as both a technology and a quasi-person. These second-order trust factors can be used in future research to better understand social networking trust and usage continuance intentions

IT researchers have recently distinguished habits from prior behavior frequency. We expanded this research by examining habit's antecedents and investigating the simultaneous effect of habit and prior IT use on continued IT use. We found that the research model was relatively robust over four specific use activities of one software application. Indeed, prior IT use, satisfaction, and importance significantly influenced IT habits. Also, while prior IT use predicted continued IT use in the combined data set, habit only predicted continued IT use for activities with higher habit levels. Practical implications are discussed.

Objective: Health care providers are beginning to deliver a range of Internet-based services to patients; however, it is not clear which of these e-health services patients need or desire. The authors propose that patients' acceptance of provider-delivered e-health can be modeled in advance of application development by measuring the effects of several key antecedents to e-health use and applying models of acceptance developed in the information technology (IT) field. Design: This study tested three theoretical models of IT acceptance among patients who had recently registered for access to provider-delivered e-health. Measurements: An online questionnaire administered items measuring perceptual constructs from the IT acceptance models (intrinsic motivation, perceived ease of use, perceived usefulness/extrinsic motivation, and behavioral intention to use e-health) and five hypothesized antecedents (satisfaction with medical care, health care knowledge, Internet dependence, information-seeking preference, and health care need). Responses were collected and stored in a central database. Results: All tested IT acceptance models performed well in predicting patients' behavioral intention to use e-health. Antecedent factors of satisfaction with provider, information-seeking preference, and Internet dependence uniquely predicted constructs in the models. Conclusion: Information technology acceptance models provide a means to understand which aspects of e-health are valued by patients and how this may affect future use. In addition, antecedents to the models can be used to predict e-health acceptance in advance of system development.

Evaluations of participant samples for experiments in information systems research often appear to be informal and intuitive. Appropriate participant choice becomes a more salient issue as the population of information technology professionals and users grows increasingly diverse, and the distribution of relevant characteristics in participant samples such as age, gender, nationality, and experience can often be unrepresentative of the characteristics’ distribution in target populations. In this paper, we present a framework based on widely accepted standards for evaluating participant choice and providing rationale that the choice is appropriate. Using a step-by-step approach, we compare current practice in experimental studies from top information systems journals to this framework. Based on this comparison, we recommend how to improve the treatment of participant choice when evaluating the validity of study inferences and how to discuss the tradeoffs involved in choosing participant samples.

This chapter presents a new rational-objective (R-O) model of e-health use that accounts for effects of facilitating conditions as well as patients’ behavioral intention. An online questionnaire measured patients’ behavioral intention to use a new e-health application as well as proxy measures of facilitating conditions that assess prior use of and structural need for health services. A second questionnaire administered three months later collected patients’ self-reported use of e-health during the intervening period. The new model increased predictions of patients’ e-health use (measured in R2) by more than 300% over predictions based upon behavioral intention alone, and all measured factors contributed significantly to prediction of use during the three-month assessment period.

While information and communication technologies can increase the health care provided to underserved populations, research concerning these technologies often involves only those patients who possess access to technology or who are otherwise willing and able to use it. This issue is important for both researchers and practitioners because non-users’ beliefs may not only be different from users’ beliefs, they may become more important to understand as access to technology increases. To address this problem: 1. We develop a model of the antecedents to perceived usefulness of an interactive health communication (IHC) system. While our research model combines health-related beliefs with technology perceptions, the antecedents can all be measured before an individual has contact with a particular IHC system. Thus, in the current (and in future) work, they can be used to assess the beliefs of individuals who may not currently be willing or able to use technology. 2. We test this model using paper-based scenarios that depict hypothetical interactions with an IHC system. These paper-based scenarios are more flexible and easier to use than a working system, thus we are able to obtain data from many sources, resulting in a perceptually diverse sample. Results of our hypothesis testing show that patients with higher knowledge and discipline are less likely than those with less knowledge and/or discipline to find an IHC system useful. In addition we learned several lessons from our research process including how to increase participation rates and what reactions to expect from participants.

Healthcare is a large and growing industry that is experiencing major transformation in its information technology base. IS confronted similar transformations in other industries and developed theories and methods that should prove useful in healthcare applications. In turn, IS may benefit from incorporating knowledge from health informatics, a discipline that studies IT within medical and healthcare contexts. Despite the benefits, it is often a struggle for interdisciplinary researchers in IS and healthcare to publish their work, especially in journals directed toward IS audiences. In this paper, we outline strategies and resources to help ease this publication bottleneck. As a part of our discussion, we identify and categorize journal outlets for interdisciplinary research in IS and healthcare.

Researchers find customer satisfaction with service-oriented Web sites (e-services) can be modeled effectively based on the match between customers’ initial expectations and subsequent perceptions of performance. However, little is known about the factors leading to expectations or the ability of such factors to provide early predictions of satisfaction. We use social cognitive theory as a basis to propose that self-efficacy, past experiences (participation, knowledge, and Internet experience), and affective factors (prior satisfaction and enjoyment) will influence expectations of an e-health service. We test these factors in conjunction with the direct-effects model of satisfaction among patients registered for an e-health service. We find that these antecedents explain 57% of the variance (R 2 ) in expectations. Further, early predictions made from antecedents during initial use of the e-health service explain 39% of the variance in satisfaction. Our findings suggest that the antecedents are important contributors to patients’ expectations and can provide early guidance to development of successful e-health services.

Asynchronous online communication technologies are likely to cause major changes in the way patients and their healthcare providers communicate. Initially, these technologies will be applied to undemanding communication uses, such as requesting prescription refills. In the longer term, however, the technologies may provide strategic benefits to healthcare innovators. In this paper, we project changes that we expect to accompany the advent of asynchronous healthcare communication and propose several strategic opportunities that these changes will create.