JUSTIN SCOTT GIBONEY ([email protected]; corresponding author) is an assistant professor of information technology at Brigham Young University. He received his Ph.D. in management information systems from the University of Arizona. His research focuses on behavioral information security, deception detection, and knowledge-based systems. He has published numerous papers related to information security, deception detection, and decision support.
ROBERT O. BRIGGS ([email protected]) is a professor of information systems at San Diego State University. He earned his doctorate in management information systems at the University of Arizona. He researches the cognitive foundations of collaboration and uses his findings to design new collaborative work practices and technologies. He is a cofounder of the collaboration engineering field and coinventor of the ThinkLets design pattern language for collaborative work processes. He has designed collaboration systems and collaborative workspaces for industry, academia, government, and the military. He has published more than 200 scholarly works on collaboration systems and technology, addressing issues of team productivity, technology-supported learning, creativity, satisfaction, and technology transition.
JAY F. NUNAMAKER JR. ([email protected]) is Regents and Soldwedel Professor of MIS, Computer Science and Communication and director of the Center for the Management of Information and the National Center for Border Security and Immigration at the University of Arizona. He received his Ph.D. in operations research and systems engineering from Case Institute of Technology. He has held a professional engineer’s license since 1965. He was inducted into the Design Science Hall of Fame and received the LEO Award for Lifetime Achievement from the Association for Information Systems. He was featured in the July 1997 issue of Forbes Magazine on technology as one of eight key innovators in information technology. His specialization is in the fields of system analysis and design, collaboration technology, and deception detection. The commercial product GroupSystems ThinkTank, based on his research, is often referred to as the gold standard for structured collaboration systems. He founded the MIS Department at the University of Arizona in 1974 and served as department head for 18 years.
An information system is, by definition, “A way to create value with information” [1, p. 2]. It is common in business to equate value with money—revenue, expenses, and the bottom line. Monetary value, however, is but one of several kinds of value we can create with information. Among the others are:
Social value—relationships among individuals to one another and to society
Political value—power, influence, and the ability to prevail in a conflict
Cognitive value— time- and attention-constrained mental resources in the knowledge economy
Emotional value—positive/negative affect, for example, satisfaction, entertainment, therapy
Physical value—safety, health, comfort, and well-being.
A given information system (IS) may create more than one kind of value. A search engine creates cognitive value for users by granting instant access to information, and monetary value to the advertisers who fund it. Health-care informatics create physical value for patients and cognitive value to health-care professionals by facilitating their interactions. Theaters and theme parks use information systems to create emotional and physical value for their patrons. People will sacrifice monetary value to gain value in the other categories, so many information systems create monetary value as well. As we create information systems, then, we can ask not only “What kind of value should we create with this information system?” but also “What other kinds of value could we create with the same information?”
Because IS can create value beyond the monetary, all six categories of value should be of central concern to IS research and practice. It would therefore be useful to single out each of the nonmonetary categories for focused consideration. Toward that end, this special issue focuses on a single nonmonetary category: social value.
Two of the articles in this issue address using information to create social value pertaining to relationships among individuals, such as mutual understanding, credibility, and trust. In their article, “Beyond Brainstorming: Exploring Convergence in Teams,” Isabella Seeber, Ronald Maier, Gert-Jan de Vreede, and Barbara Weber, examine the ways teams converge. Convergence comprises two elements: (a) how individuals on a team move from less to more shared understanding of the concepts with which they work; and (b) how they move from having many concepts to a focus on fewer ideas they deem worthy of further attention. The article proposes an approach to measuring the quality of a convergence process, which is a valuable contribution upon which many other researchers may build. It then reports a detailed investigation of how variations in the structure of the convergence process relate to convergence quality of an idea set, and group-member satisfaction with the converged idea set.
Steven J. Pentland, Nathan W. Twyman, Judee K. Burgoon, Jay F. Nunamaker Jr., and Christopher B.R. Diller build and test an automated system for interviewing crime suspects and assessing their credibility in their article, “A Video-Based Screening System for Automated Risk Assessment Using Nuanced Facial Features.” The study provides evidence that, under the conditions of the automated interviews, guilty subjects tend to freeze their expressions and hold them unchanged when they lie, but allow their expressions to vary more when they tell the truth. Innocent people tend not to freeze their expressions. It may be possible to generalize the technology to other settings where it is essential to assess a person’s credibility.
Three other articles in the special issue touch on using information to create social value at the societal level, focusing variously on renewable energy, cyber security, and risk factors in safety management systems.
Jan-Hendrik Piel, Julian F.H. Hamann, André Koukal, and Michael H. Breitner, in their article, “Promoting the System Integration of Renewable Energies: Toward a Decision Support System for Incentivizing Spatially Diversified Deployment,” tackle the society-level challenge of deciding where to locate renewable energy power plants. Renewable energy sources, such as solar and wind generation, tend to be intermittent; they are affected by the weather and can drop off line suddenly. If sources are concentrated in one geographic area, changes in local weather conditions can cause this sudden drop off line, potentially impairing the stability of the entire electricity grid. Following a design-science research approach, the study develops a model for optimizing the geographic placement of renewable sources and evaluates the model with a simulation. The article contributes a nascent design theory for identifying favorable special distributions of renewable energy capacity.
In their article, “Exploring Emerging Hacker Assets and Key Hackers for Proactive Cyber Threat Intelligence,” Sagar Samtani, Ryan Chinn, Hsinchun Chen, and Jay F. Nunamaker Jr. propose a step toward reducing the $445 billion global loss per year due to cyber attacks. Many cyber security initiatives focus on analyzing attacks after they happen to derive advice for the future. This work develops a proactive approach to better understanding the present threats, and mitigating them in anticipation of an attack. It uses an automated approach to collect and analyze vast amounts of malicious hacker tools from underground hacker communities. The study shows that it is possible to discover numerous malicious assets such as crypters, keyloggers, web exploits, and database exploits, which makes it possible to develop defenses against them before they are used in attacks.
Donghui Shi, Jian Guan, Jozef Zurada, and Andrew Manikas seek to improve public safety, for example, in aviation, in their article, “A Data-Mining Approach to Identification of Risk Factors in Safety Management Systems.” The study uses a machine-learning algorithm to analyze the unstructured text of daily incident reports to identify and analyze 170,000 incident reports from the U.S. Federal Aviation Safety Board. The approach reduces the need for extensive manual identification of risk factors, and addresses the challenge of incomplete data. They compared three different algorithms and report their relative strengths and limitations with respect to these tasks. The approach also demonstrates a more general capability—that a topic mining algorithm can produce useful inputs for a machine-learning classification model.
The final study addresses an issue of IS for social value with implications for individuals and for society. “Information Security Control Theory: Achieving a Sustainable Reconciliation between Sharing and Protecting the Privacy of Information,” by Chad Anderson, Richard L. Baskerville, and Mala Kaul examines the trade-off between the expected benefits and the potential security risks of having immediate and complete information shared within and between organizations, for example, in health care, law enforcement, or commerce. The article reports a study of four iterations to develop and test a theory of information security control based on a balance between exposure controls (e.g., to prevent hacking) and ethical controls (e.g., policies and laws with consequences for violations). The findings suggest that practitioners may be able to use the theory to find a balance between openness and protection that aligns with their specific, local information goals.
Each of the articles in this special issue originated in a presentation nominated for a best-paper award at the Hawaii International Conference on System Sciences. Each reveals a different facet of creating social value with information systems. We commend them to your reading.
1.Nunamaker, J.F., Jr., and Briggs, R.O. Toward a broader vision for information systems. ACM Transactions on Management Information Systems, 2, 4 (2011), 20:1-20:12.