Robert O. Briggs ([email protected]) is a Professor of Information Systems at San Diego State University. He earned his Ph.D. in Information Systems from University of Arizona. Dr. Briggs researches the cognitive foundations of collaboration and uses his findings to design and deploy new collaboration systems and new collaborative work practices. He is co-founder of Collaboration Engineering as a scholarly discipline, co-inventor of the thinkLets design pattern language, and the inventor of Collaboration Systems, comprising Computer Assisted Collaboration Engineering and Process Support Applications. Dr. Briggs has published more than 250 peer-reviewed manuscripts related to economic, social, political, cognitive, emotional, and technological aspects of collaboration. He lectures around the world on the logic of scientific inquiry.
Jay F. Nunamaker, Jr.([email protected]; corresponding author) 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 of Excellence for Border Security and Immigration, Emeritus at the University of Arizona. He received his Ph.D. in operations research and systems engineering from Case Institute of Technology. Dr. Nunamaker has held a professional engineer’s license since 1965. His specialization is in the fields of system analysis and design, collaboration technology, and deception detection. The commercial product Group Systems ThinkTank, based on his research, is often referred to as the gold standard for structured collaboration systems. He was inducted into the Design Science Hall of Fame and received the LEO Award for Lifetime Achievement from the Association for Information Systems. Dr. Nunamaker was featured in the July 1997 issue of Forbes Magazine on technology as one of eight key innovators in information technology. He founded the MIS Department at the University of Arizona in 1974 and served as department head for 18 years.
IntroductionIn the 1960s, software development centered on single-purpose applications to run on stand-alone computers. The intervening decades have seen exponential growth in system complexity with, for example, integrated enterprise-wide suites of integrated capabilities serving users across the globe. Enterprise system infrastructure includes multiple levels of security, collaboration capabilities for the people working as teams, fraud detection, and data fusion, to name but a few. These aspects add to the complexity of the application. Also, software can do more as a result of processing speed and data storage. This special issue presents three papers, each of which considers the complexity of current systems from a different perspective.
The first paper, “Decision Problems in Blockchain Governance: Old Wine in New Bottles or Walking in Someone Else’s Shoes? ” by Rafael Ziolkowski, Gianluca Miscione, and Gerhard Schwabe, addresses the complex question of managing software capabilities built on blockchain technology. Current research presents a wide array of novel potentially disruptive blockchain application domains, but a recent Gartner survey of CEO’s found that few companies have current plans to implement such applications. A primary impediment appears to be that managers still do not understand how it works or what they can do with it. This paper focuses on complex issues pertaining to the governance of blockchain systems derived from examination of 14 such systems in four application domains. Based on academic literature, semi-structured interviews with representatives from those organizations, and content analysis of grey literature, common problems in blockchain governance have been singled out and contextualized. The identification of these problems enriches the scarce body of knowledge on the governance of blockchain systems, resulting in a better understanding of how blockchain governance links to existing concepts and how it is enacted in practice.
The next paper, “Idea Convergence Quality in Open Innovation Crowdsourcing: A Cognitive Load Perspective” by Xusen Chen, Shizuan Fu, Triparna de Vreede, Gert-Jan de Vreede, Isabella Seeber, Ronald Maier, and Barbara Weber, examines another complexity challenge. Today’s systems can support large-scale collaboration involving hundreds or thousands of people who are using vast stores of semi-structured and unstructured data: how can participants converge on and build shared understanding of the ideas that will be useful for attaining their goals in a short amount of time? This paper prototypes and tests a solution. The exemplar domain for this study is an open innovation crowdsourcing application for online crowds that can quickly converge from massive numbers of candidate ideas of varying quality to a small set of clear, non-redundant ideas that are worthy of further consideration. Drawing on Cognitive Load Theory, they executed a laboratory experiment to test three types of cognitive load manipulations for large-scale convergence. Findings show that germane cognitive load has a positive correlation with a) the quality of converged ideas, b) satisfaction with process, and c) satisfaction with outcome. By contrast, intrinsic cognitive load had a negative association with satisfaction-with-process and satisfaction with outcome. Extraneous cognitive load had only a negative with satisfaction-with-outcome. The study identified positive moderating relationships of knowledge self-efficacy, perceived goal clarity, and need for cognition on the relationship between germane cognitive load and idea convergence quality.
The third paper, “Too Busy to Be Manipulated: How Multitasking with Technology Improves Deception Detection in Collaborative Teamwork” by Nathan W. Twyman, Jeffrey G. Proudfoot, Ann-Frances Cameron, Eric Case, Judee K. Burgoon, and Douglas P. Twitchell, deals with the complexity of assessing the credibility of collaboration partners in the digital workplace. Deception is an unfortunate staple in collaborative work. Guarding against team members’ deceptive tactics and hidden agendas can be difficult and may seem even more difficult in technology-driven business environments that have made multitasking during teamwork increasingly commonplace. This research develops a foundation for a nuanced theoretical understanding of these conditions. This paper reports a laboratory study involving a collaborative game that manipulated deception and multitasking behaviors in a real-time virtual-team environment. Under the conditions of this study, some amount of information multitasking can actually improve a participant’s ability to detect deception detection. The paper conjectures that this may happen because multitaskers engage less in the team conversation, which makes them less susceptible to deceptive manipulations.
These three papers were drawn from the best papers nominees and winners at the Hawaii International Conference on Systems Sciences. We commend them to your reading.