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Online crowdsourcing markets (OCM) are becoming more popular as a source for data collection. In this paper, we examine the consistency of survey results across student samples, consumer panels, and online crowdsourcing markets (specifically Amazon’s Mechanical Turk) both within the United States and outside. We conduct two studies examining the technology acceptance model (TAM) and the expectation–disconfirmation theory (EDT) to explore potential differences in demographics, psychometrics, structural model estimates, and measurement invariances. Our findings indicate that (1) U.S.-based OCM samples provide demographics much more similar to our student and consumer panel samples than the non-U.S.-based OCM samples; (2) both U.S. and non-U.S. OCM samples provide initial psychometric properties (reliability, convergent, and divergent validity) that are similar to those of both student and consumer panels; (3) non-U.S. OCM samples generally provide differences in scale means compared to those of our students, consumer panels, and U.S. OCM samples; and (4) one of the non-U.S. OCM samples refuted the highly replicated and validated TAM model in the relationship of perceived usefulness to behavioral intentions. Although our post hoc analyses isolated some cultural and demographic effects with regard to the non-U.S. samples in Study 1, they did not address the model differences found in Study 2. Specifically, the inclusion of non-U.S. OCM respondents led to statistically significant differences in parameter estimates, and hence to different statistical conclusions. Due to these unexplained differences that exist within the non-U.S. OCM samples, we caution that the inclusion of non-U.S. OCM participants may lead to different conclusions than studies with only U.S. OCM participants. We are unable to conclude whether this is due to of cultural differences, differences in the demographic profiles of non-U.S. OCM participants, or some unexplored factors within the models. Therefore, until further research is conducted to explore these differences in detail, we urge researchers utilizing OCMs with the intention to generalize to U.S. populations focus on U.S.-based participants and exercise caution in using non-U.S. participants. We further recommend that researchers should clearly describe their OCM usage and design (e.g., demographics, participant filters, etc.) procedures. Overall, we find that U.S. OCM samples produced models that lead to similar statistical conclusions as both U.S. students and U.S. consumer panels at a considerably reduced cost.

As a social construct, privacy is at the heart of relationships and drives the sharing of information. Previous research on privacy has taken for granted the relationship involved in information sharing. Our research theorizes that the nature of the relationship itself plays a key role in influencing privacy concerns and trust. Using network theory, we posit that privacy concerns, trust, and information sharing occur at two levels: the relational as interpersonal (i.e., dyadic) and the individual as intrapersonal. Relationships characterized as multiplex, or multidimensional, are richer and experience greater trust while reducing privacy concerns. Utilizing data collected from work groups that use digital communication platforms, we analyze our data using a covariance-based SEM multilevel model approach. Our results indicate that greater multiplex relationships lead to increases in trust, which in turn leads to greater information sharing. Multiplexity does not impact privacy concerns. Surprisingly, privacy concerns have a positive relationship with information sharing, counter to previous research. Our findings suggest that privacy mechanisms are more complex than previously modeled because they depend on the quality and type of interpersonal relationship.

Previous research investigating information disclosure with online merchants has extended social contract theory using psychological contracts to explain the nature of the relationship between the consumer and merchant. This research extends the role of psychological contracts to social media platforms (SMP) by investigating how institutional psychological contract violations (PCV) influence trust in the SMP through institutional arrangements. Using a sample from MTurk, we presented two hypothetical scenarios manipulating the degree of PCV. Our findings suggest institutional PCVs act differently on institutional arrangements. Institutional PCVs impact attitudes toward institutional arrangements and trust in the SMP.

Hedonic-motivation systems (HMS) -- systems used primarily to fulfill users' intrinsic motivations -- are the elephant in the room for IS research. Growth in HMS sales has outperformed utilitarian-motivation systems (UMS) sales for more than a decade, generating billions in revenue annually; yet IS research focuses mostly on UMS. In this study, researchers explain the role of intrinsic motivations in systems use and propose the HMS adoption model (HMSAM) to improve the understanding of HMS adoption. The HMSAM extends van der Heijden's (2004) model of hedonic system adoption by including cognitive absorption (CA) as a key mediator of perceived ease of use (PEOU) and of behavioral intentions to use (BIU) HMS. Results from experiments involving 665 participants confirm that, in a hedonic context, CA is a more powerful and appropriate predictor of BIU than PEOU or joy, and that the effect of PEOU on BIU is fully mediated by CA sub-constructs.

Previous research on gamification and virtual laboratories has suggested that both produce successful educational outcomes, but few studies have looked at both gamification and virtual labs in tandem. Drawing on social cognitive theory, we investigate gamification in the virtual labs’ context to examine whether learners’ educational performance is enhanced. In particular, we employ leaderboards as a motivational gamification mechanism for more engagement and participation that can result in higher learning outcomes. Using a student sample, our results show that using gamification within a virtual lab environment results in higher student performance; specifically, it helps them complete more-complex tasks and increases their self-efficacy. Our findings show promising evidence that gamification in virtual lab learning environments positively influences learning.

Today, people spend many hours each day on social networking sites where they share a great deal of information with others. Prior research has shown that, unlike many other online contexts (e.g., e-commerce), individuals who use social networking sites (SNS) tend to share their personal information almost completely irrespective of their concerns for information privacy (CFIP). Thus, researchers have asked whether people really care about their privacy in SNS. In this study, by developing a new conceptual model based on privacy calculus theory and testing it using a scenario-based survey (N = 180), we argue that the inconsistencies in the literature (i.e., information sharing in SNS in the presence of CFIP) have emerged because researchers have not explicitly conceptualized and properly operationalized models. Our results show that prior research widely lacks parallelism between the operationalization levels of CFIP and willingness to share information. Moreover, we show that situational factors such as sensitivity of information and perceived control over privacy play a critical role in explaining the decision-making mechanism for information disclosure in SNS.

With increasing usage of social networking sites like Facebook there is a need to study privacy. Previous research has placed more emphasis on outcome-oriented contexts, such as e-commerce sites. In process-oriented contexts, like Facebook, privacy has become a source of conflict for users. The majority of architectural privacy (e.g. privacy policies, website mechanisms) enables the relationship between a user and business, focusing on the institutional privacy concern and trust; however, architectural privacy mechanisms that enables relationships between and among users is lacking. This leaves users the responsibility to manage privacy for their interpersonal relationships. This research focuses on the following question: \"How does privacy influence the sharing of personal information in interpersonal relationships on social networking sites?\" The management of the sharing of personal information is explained using the Need to Belong theory, psychological contract, and approach-avoidance motivation theory. Individuals' desire to interact socially and engage in relationships where respect for personal information is implied leads to overcoming concerns over privacy. Three essays address the question of interest. Essay 1 explains that this drive is motivated by a fear of social exclusion from social transactions and interpersonal relationships and does not rely on the institutional relationship between a user and the social media website. Essay 2 uses a social network analysis lens to describe how the multiplexity of relationships and social influences (both of the network and the self) influence social interaction and the sharing of personal information. Essay 3 focuses on explaining how individuals' disposition toward subconscious processes of approach or avoidance motivation influence decisions to share and not share personal information. The implication of these studies is that privacy in a process-oriented context—like Facebook—involves different attitudes and beliefs centered on interpersonal relationships rather than institutional ones.

Online crowdsourcing markets (OCM) are becoming more popular as a source for data collection. In this paper, we examine the consistency of survey results across student samples, consumer panels, and online crowdsourcing markets (specifically Amazon’s Mechanical Turk) both within the United States and outside. We conduct two studies examining the technology acceptance model (TAM) and the expectation– disconfirmation theory (EDT) to explore potential differences in demographics, psychometrics, structural model estimates, and measurement invariances. Our findings indicate that (1) U.S.-based OCM samples provide demographics much more similar to our student and consumer panel samples than the non-U.S.-based OCM samples; (2) both U.S. and non-U.S. OCM samples provide initial psychometric properties (reliability, convergent, and divergent validity) that are similar to those of both student and consumer panels; (3) non-U.S. OCM samples generally provide differences in scale means compared to those of our students, consumer panels, and U.S. OCM samples; and (4) one of the non-U.S. OCM samples refuted the highly replicated and validated TAM model in the relationship of perceived usefulness to behavioral intentions. Although our post hoc analyses isolated some cultural and demographic effects with regard to the non-U.S. samples in Study 1, they did not address the model differences found in Study 2. Specifically, the inclusion of non-U.S. OCM respondents led to statistically significant differences in parameter estimates, and hence to different statistical conclusions. Due to these unexplained differences that exist within the non-U.S. OCM samples, we caution that the inclusion of non-U.S. OCM participants may lead to different conclusions than studies with only U.S. OCM participants. We are unable to conclude whether this is due to of cultural differences, differences in the demographic profiles of non-U.S. OCM participants, or some unexplored factors within the models. Therefore, until further research is conducted to explore these differences in detail, we urge researchers utilizing OCMs with the intention to generalize to U.S. populations focus on U.S.-based participants and exercise caution in using non-U.S. participants. We further recommend that researchers should clearly describe their OCM usage and design (e.g., demographics, participant filters, etc.) procedures. Overall, we find that U.S. OCM samples produced models that lead to similar statistical conclusions as both U.S. students and U.S. consumer panels at a considerably reduced cost.

HVTN 505 is a preventative vaccine efficacy trial testing DNA followed by recombinant adenovirus serotype 5 (rAd5) in circumcised, Ad5-seronegative men and transgendered persons who have sex with men in the United States. Identified immune correlates of lower HIV-1 risk and a virus sieve analysis revealed that, despite lacking overall efficacy, vaccine-elicited responses exerted pressure on infecting HIV-1 viruses. To interrogate the mechanism of the antibody correlate of HIV-1 risk, we examined antigen-specific antibody recruitment of Fcγ receptors (FcγRs), antibody-dependent cellular phagocytosis (ADCP), and the role of anti-envelope (anti-Env) IgG3. In a prespecified immune correlates analysis, antibody-dependent monocyte phagocytosis and antibody binding to FcγRIIa correlated with decreased HIV-1 risk. Follow-up analyses revealed that anti-Env IgG3 breadth correlated with reduced HIV-1 risk, anti-Env IgA negatively modified infection risk by Fc effector functions, and that vaccine recipients with a specific FcγRIIa single-nucleotide polymorphism locus had a stronger correlation with decreased HIV-1 risk when ADCP, Env-FcγRIIa, and IgG3 binding were high. Additionally, FcγRIIa engagement correlated with decreased viral load setpoint in vaccine recipients who acquired HIV-1. These data support a role for vaccine-elicited anti-HIV-1 Env IgG3, antibody engagement of FcRs, and phagocytosis as potential mechanisms for HIV-1 prevention.