Despite the publicity regarding big data and analytics (BDA), the success rate of these projects and strategic value created from them are unclear. Most literature on BDA focuses on how it can be used to enhance tactical organizational capabilities, but very few studies examine its impact on organizational value. Further, we see limited framing of how BDA can create strategic value for the organization. After all, the ultimate success of any BDA project lies in realizing strategic business value, which gives firms a competitive advantage. In this study, we describe the value proposition of BDA by delineating its components. We offer a framing of BDA value by extending existing frameworks of information technology value, then illustrate the framework through BDA applications in practice. The framework is then discussed in terms of its ability to study constructs and relationships that focus on BDA value creation and realization. We also present a problem-oriented view of the framework—where problems in BDA components can give rise to targeted research questions and areas for future study. The framing in this study could help develop a significant research agenda for BDA that can better target research and practice based on effective use of data resources.

The value and credibility of online consumer reviews are compromised by significantly increasing yet difficult-to-identify fake reviews. Extant models for automated online fake review detection rely heavily on verbal behaviors of reviewers while largely ignoring their nonverbal behaviors. This research identifies a variety of nonverbal behavioral features of online reviewers and examines their relative importance for the detection of fake reviews in comparison to that of verbal behavioral features. The results of an empirical evaluation using real-world online reviews reveal that incorporating nonverbal features of reviewers can significantly improve the performance of online fake review detection models. Moreover, compared with verbal features, nonverbal features of reviewers are shown to be more important for fake review detection. Furthermore, model pruning based on a sensitivity analysis improves the parsimony of the developed fake review detection model without sacrificing its performance.

The use of mobile and wireless technologies and wearable devices for improving health care processes and outcomes (mHealth) is promising for health p

This study examines trust in technology‐supported groups from the perspectives of culture, social presence and group composition. Our results demonstrate that, in culturally homogeneous groups, individualism has a negative impact on the level of interpersonal trust; however, in culturally heterogeneous groups consisting of Chinese and U.S. participants, individualism has a positive impact on interpersonal trust among members. There were also significant differences in the level of trust between homogeneous Chinese groups and heterogeneous groups consisting of Chinese and U.S. participants. In addition, the mediating role of communication quality was identified to explain the effect for trust‐of social presence on trust. These findings have important implications on building and communication in global technology‐supported decision‐making groups.

(2018). Special Issue: Strategic Value of Big Data and Business Analytics. Journal of Management Information Systems: Vol. 35, No. 2, pp. 383-387.