It has been said, not infrequently, that our field has a tendency to overlook the real issues facing our society, our organizations, and all of us as individuals and social actors, while focusing on topics that lend themselves more readily to academic research. The special issue on Creating Social Value with Information that you will read here gainsays that. Guest-edited by Justin Scott Giboney, Robert O. Briggs, and Jay F. Nunamaker Jr., the special issue demonstrates how our research methodologies and our research tradition can produce actionable results—and cumulate knowledge while doing so. Automated risk assessment based on the nuances of facial expressions, automatic approaches to the prevention (rather than postmortems of occurrences) of cyber attacks, data mining to identify risk factors in safety management systems, collaborative brainstorming, the improved deployment of renewable energy resources, and privacy protection while sharing information—all these are the subjects of research work presented in the special issue. The guest editors will further introduce the articles.
In the first work in the general section, Chaitanya Sambhara, Arun Rai, Mark Keil, and Vijay Kasi investigate the risks attendant on the reverse auctions used most commonly in B2B procurement. Reverse auctions are an important complement to the relationship-based maintenance of steady supply chains. They can also damage buyer–supplier relationships, if not used judiciously, with appropriate management and risk controls. What these appropriate controls are is surfaced in the article via a Delphi study combining the perspectives of buyers (prone to overuse such auctions) and suppliers (prone to resist their use). Grounding themselves in several theoretical perspectives, the authors classify the risks and identify the effective controls.
As computer-based guidance expands in scope and depth, the partitioning of work among people and machines moves to the center of policymaking attention. Much research has been devoted to the computer-based systems that help to overcome human information-processing limitations and cognitive biases, and to the humans compensating for the narrowness and brittleness of computer-based systems. In the next article, Andrew Hardin, Clayton A. Looney, and Gregory D. Moody investigate the effects of suggestive guidance by decision support systems, the guidance that proposes a solution, rather than simply informing users. This guidance is often combined with credibility indicators for the suggested course of action. The authors show how more or less aggressive guidance combines with the credibility indicators to push users toward more or less risky decisions.
Online reviews have been a subject of extensive research, insofar as in many cases they are able to sway the public toward a product or away from it. In the case examined in the next article, early success and continuing receipts from of a theater-based movie release can be significantly affected by online opinions—but the authors show that these effects will differ depending on the type of online review platform. The authors, Jianxiong Huang, Wai Fong Boh, and Kim Huat Goh, offer highly nuanced results. These results are based on a very comprehensive data set and grounded in information-processing theory. They provide guidance for future researchers—and those offering all experience goods.
Philip Menard, Gregory J. Bott, and Robert E. Crossler study user motivation in engaging in secure behaviors in the information systems (IS) context. The authors empirically compare the effectiveness of two motivation theories that serve to elicit these secure behaviors. When stripped to the core, it is fear versus an intrinsic desire to behave in a secure manner. The authors show that the effects of the two approaches differ significantly. Based on their analysis and the empirics, the authors offer and demonstrate the effectiveness of an approach that integrates both theories of secure user behavior. Considering the key importance of the human element in IS security, the work is very much of the moment.