The Special Issue on “Strategic Value of Big Data and Business Analytics” presents research that aims to go beyond the highly publicized notions about big data and to discover how the accumulations of very large longitudinal collections of structured and unstructured data can be deployed to create value that can furnish organizations with strategic benefits. The potential strategic value may include enhanced customer relationships, evidence-based decision making, action-oriented knowledge management, fielding of service-extended products with continuing revenue flows, and more flexible or efficient supply-web management. Ultimately, and particularly in the case of several major online companies, the exclusive possession of vast data can lead to lasting competitive advantage. The guest editors of the Special Issue, Roger H.L. Chiang, Varun Grover, Ting-Peng Liang, and Dongsong Zhang, introduce to you the problematic of the analytics grounded in the big data and offer a framework of research within which our field can contribute.
It must be recognized that these are still early days and it was not long ago that we passed the end of the beginning of the big data movement in information systems (IS). We are far better at assembling data aggregates and conditioning them for use than at actually deploying them for organizational results. Nevertheless, as the examples of the leading companies show, such results can be gained with well-targeted and sustained organizational actions. And such results can be devastating to competitors that do not measure up, as well as presenting tall barriers to entry. A firm that has been collecting data that surround its activities for a decade—and deploys the data with appropriate IS—has an inherent and lasting advantage over a competitor that has not collected its longitudinal data. The Big Five online companies in the United States and several companies that are rapidly gaining similar scope in China are already in a position to command their marketplaces.
Like any other major asset, big data attracts risks. These include the distortion of marketplace functioning by firms with massive captive data aggregates, further erosion of privacy, inappropriate purely algorithmic decision making, and data breaches. These exposures will need to be paid attention to on the societal and international levels. As noted above, we are only past the end of the beginning. The studies in the Special Issue point to several paths forward. The guest editors present an encompassing framework within which our research can help derive organizational value from big data.
The first article in the general section contributes to our understanding of the economy of intangibles, more specifically, of information goods. Sampling of such goods is almost costless to the provider. In the context of video on demand, Ai-Phuong Hoang and Robert J. Kauffman empirically study the effectiveness of such sampling and its influence on consumer purchasing decisions. The researchers find an intricate dependence of consumer buying decisions and willingness to pay for the complete entertainment product on preference match during sampling. Indeed, it is found beneficial to the provider to offer free sampling rather than limit access to the customers with paid samples. A number of strategies to expand the viewing by sampling entertainment content emerge from the work. This work bears generalization to other content products.
Two subsequent studies address enterprise social media (ESM), which aim to harness the advantages of online communities within an organization. While in some respects resembling general social media activities, the organizational nature of the communities that emerge on these media conditions the specificities. In the first of the articles, Burcu Bulgurcu, Wietske van Osch, and Gerald C. Kane study the operations of such a community in a global firm to determine these special features. The researchers find that the majority of users, whom the authors call promoters, use the platform for self-promotion, without reference to posts by others. Further, self-promoters contribute to groups of a different scope than that in open social media. The findings surface a phenomenon deleterious to organizational knowledge sharing and elaboration. Attention must be paid to this, and the culture of ESM use in some organizations calls for change. In the second of the two articles, Wietske van Osch and Charles W. Steinfield investigate the boundary-spanning role of ESM use by groups within an organization. The visibility affordance of ESM allows all the group members (rather than just the team gatekeepers) to modulate the information flow across the group boundary. The differential characteristics of the networks constituted by the employee groups lead to more or less effective boundary-spanning activities. Taken together, the two studies offer novel insights into organizational information and knowledge sharing occasioned by ESM. The intersection of social media and organizational cultures offers a fruitful domain of study with a view toward harvesting ESM benefits in a firm.
In the concluding article of the issue, Kholekile L. Gwebu, Jing Wang, and Li Wang present a study of organizational management in the aftermath of a data breach. Specifically, the researchers investigate the efficacy of various responses to a breach in relation to the firm’s reputation. The authors’ findings draw on an established theoretical background, accumulated knowledge about crisis management, and an extensive data-breach database. They find that the firm’s reputation is highly salient in protecting the firm’s value consequent to a breach. They also discover differential effects of various response strategies. The evidence-based findings will help firms in reacting to this, unfortunately, all too frequent occurrence. This is, of course, a complement to the strategies that prevent data breaches in the first place.