ERIC K. CLEMONS is a professor of operations and information management at the Wharton School of the University of Pennsylvania. His education includes an S.B. in physics from MIT, and an M.S. and a Ph.D. in operations research from Cornell University. His research for the past 30 years has involved the systematic study of the transformational effects of information on the strategy and practice of business. He was among the first scholars to study online global securities trading, business process outsourcing, channel conflict and e-commerce, and the effect of information on product proliferation and the transformation of consumer behavior in these new marketplaces. More recently, he has begun studying privacy and the challenges of applying current antitrust law to online business models. He is the founder and project director for the Wharton School’s Sponsored Research Project on Information: Strategy and Economics within the Program for Global Strategy and Knowledge Intensive Organizations. He has also held appointments at the Harvard Business School, the Johnson School of Management at Cornell, the Engineering College at Cornell, Hong Kong University of Science and Technology, Peking University Law School, and the Desautels Centre at the Rotman School of the University of Toronto. He has published over 100 scholarly papers and regularly publishes online in Huffington Post, Business Insider, and Tech Crunch.
RAJIV M. DEWAN is the Xerox Professor of Business and a professor of computers and information systems at the Simon Business School of the University of Rochester. His teaching and research interests include business analytics, organizational issues in management of information systems, the information technology industry, and financial information systems. He has won three Best Paper Awards for research, done in collaboration with colleagues at the Simon School, on the use of information systems standards in organizations, redesign of business processes, and management of websites. His papers have appeared in the Journal of Computing, Management Science, Decision Support Systems, and IEEE Transactions on Computers, among other journals.
ROBERT J. KAUFFMAN is a professor of information systems at the School of Information Systems, Singapore Management University. He also serves as associate dean (research) and deputy director of the Living Analytics Research Centre. He holds an M.S. (systems science) and a Ph.D. (industrial administration) from the Tepper School of Business, Carnegie Mellon University, as well as an M.A. (East Asian studies) from Cornell University. Recently, he was a Distinguished Visiting Fellow at the Center for Digital Strategies of the Tuck School of Business at Dartmouth. His research focuses on technology and strategy, the economics of IT, technology in financial services and e-business, managerial decision making, and innovations in research methods. His work has appeared in Information Systems Research (ISR), Journal of Management Information Systems, MIS Quarterly, Telecommunications Policy, IEEE Transactions on Engineering Management, Management Science, Review of Economics and Statistics, Operations Research Letters, and elsewhere. His 2014 ISR paper was recently nominated as European Research Paper of the Year by CIONET Europe, a group of 4,600 chief information officers.
THOMAS A. WEBER holds the Chair of Operations, Economics and Strategy at the Management of Technology and Entrepreneurship Institute at the Swiss Federal Institute of Technology in Lausanne (EPFL). Earlier he was a faculty member at Stanford University. He is an Ingénieur des Arts et Manufactures (Ecole Centrale Paris) and a Diplom-Ingenieur in Electrical Engineering (Technical University Aachen). He has Master’s degrees in technology and policy and electrical engineering and computer science from MIT, and a Ph.D. from the Wharton School. He was visiting faculty in economics at Cambridge University and in mathematics at Moscow State University. Between 1998 and 2002, he was a senior consultant with the Boston Consulting Group. His current research interests include the economics of information and uncertainty, the design of contracts, and strategy. His articles have appeared in American Economic Journal: Microeconomics, Information Systems Research, Journal of Management Information Systems, Management Science, Economics Letters, Economic Theory, Journal of Mathematical Economics, Journal of Regulatory Economics, and other journals. He is the author of Optimal Control Theory with Applications in Economics (MIT Press, 2011).
The rapid adoption of social networks in industrialized countries affects the organization of activities, the allocation of resources, and the way individuals interact with each other and with institutions. The results can be powerfully positive, such as in crowdsourcing, where a task that might be too expensive to carry out alone becomes suddenly feasible by distributing it to an online user base. They can also be more problematic, when companies use their newfound proximity to their users to extract larger rents: especially with the most unsuspecting of the online population, the young and vulnerable. The two papers in this Special Section explore the complex and contradictory effects of online connectivity by presenting advancing hypotheses and empirical observations about the good, the bad, and the ugly in online interactions. The authors also suggest paths for regulators to improve social welfare by requiring widespread access to a common information infrastructure.
The first paper, “Task Division for Team Success in Crowdsourcing Contests: Resource Allocation and Alignment Effects,” by Indika Dissanayake, Jie Zhang, and Bin Gu, studies how the allocation of human capital on a crowdsourcing platform affects team performance. Based on a large data set from Kaggle.com, the work highlights the importance of different capabilities, here represented by “social capital” and “intellectual capital,” for different roles in a virtual team effort. In particular, the authors observe that team performance is positively related with the team leader’s social capital and with any team expert’s intellectual capital, while an increase of the other capability for the leader or an expert has no positive effect on team performance. The authors also argue that the aggregation of capabilities across the members of a team is non-uniform, in the sense that a simple average or direct sum of the values for the individuals is not the best indicator for team performance. This is because an individual’s role in the team moderates the impact of his or her capabilities.
These observations are significant because the observed incentives in the data set are strong, with a median reward of about $8,000 (and an average reward of about $15,000) for more than 700 teams participating in Kaggle’s crowdsourcing competitions. Interestingly, with an increase of the competitiveness in a given task, as measured by a decrease of the Herfindahl–Hirschman Index (HHI), the importance of the social-intellectual alignment for team performance diminishes. Thus, when exposed to greater competitive pressure, teams with a similar level of capabilities do better both socially and intellectually. While this might seem intuitive, it is empirically surprising that the converse holds when competitive pressures are low, that is, teams with less well-aligned capabilities do better. This study is the first to focus on the effects of team members’ heterogeneity on the team’s performance in crowdsourcing tasks.
The second paper, “Family Preferences Concerning Online Privacy, Data Mining, and Targeted Ads: Regulatory Implications,” by Eric K. Clemons and Joshua S. Wilson, analyzes international survey data about the online activities of teenagers as well as parental awareness and preferences about data-mining practices related to their children. The authors note that combining user-specific information from a variety of sources enables companies such as Google and organizations purchasing this type of data to estimate consumer preferences very well. They can now do this to a resolution that allows a high degree of price discrimination in order to extract greater rents overall, revealing each individual’s entire willingness to pay. The implications of data mining for privacy are worse because the adverse consequences are potentially longer-lived, especially with respect to vulnerable user groups.
Using survey data from the United States, Germany, Japan, and several South American countries, the authors argue that there is a wide gap between the online behavior of teens and parental awareness, and preferences about privacy. By penetrating the institutional safety of schools, once-trusted companies are able to collect private data about unsuspecting users, which can only be the tip of the iceberg for the information aggregates, collected and sold as “big data” to third parties. The authors explore the real costs associated with targeted ads and data mining, and then lay the groundwork for a structured discussion about regulatory intervention, which so far has barely begun. A case in point is the recent intervention of the European Union into Google’s potential abuse of its market power by exploiting control over data aggregates to serve its own interest . This paper is one of the first systematic empirical investigations to link potential corporate malpractice in extracting consumer data and public policy. Thus, it is a pioneering piece in opening up a new line of inquiry into regulatory intervention for the protection of privacy and the limitation of corporate data use.
Broadly speaking, both papers tackle new types of incentives that matter because of online social connections. Individuals can form virtual teams and try to perform well together by assigning roles to different members. A higher degree of connectedness therefore results, all else equal, in more teams and thus a higher degree of competitiveness (measured in the HHI of “brain share” concentration), changing the returns to diversity in teams. On the other hand, corporations are embracing their users’ online presence by tracking behavior and finding ways to mine the data so as to improve predictive accuracy, with the goal of using this one-sided intimacy to their advantage. This is a form of collusion against consumers. Here one can also expect an excess return for those who perform best at extracting information rents. This is ultimately likely to reduce variety, and is a counterintuitive outcome for the diverse beginnings of social connections.
1.Barker, A.; Oliver, C.; Chassany, A.-S. Europe to accuse Google of illegally abusing its dominance. Financial Times, April 15, 2015. http://www.ft.com/cms/s/0/643f49ec-e285-11e4-aa1d-00144feab7de.html#axzz3gZg8xBKJ (accessed July 21, 2015).