Journal of Management Information Systems

Volume 38 Number 3 2021 pp. 574-578

Special Section: Improving New Digital Market Mechanisms

Kauffman, Robert J and Weber, Thomas A

Robert J. Kauffman ([email protected]; corresponding author) holds the Endowed Chair in Digitalization at the Copenhagen Business School and is Emeritus Professor at Singapore Management University (SMU). His graduate degrees are from Cornell University and Carnegie Mellon. Dr. Kauffman’s research has focused on technology and strategy, the economics of IT, financial services and technology, managerial decision-making, sustainability economics, and e-commerce. He previously served as Associate Dean (Faculty) and Associate Dean (Research), and Chair of the IS and Management Area at SMU’s School of Computing and IS. He also held a chaired appointment at Arizona State University, and was Director of the MIS Research Center at the Carlson School of Management, University of Minnesota, where he chaired the Information and Decision Sciences Department. His work has appeared in Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Management Science, Review of Economics and Statistics, IEEE Transactions on Software Engineering, IEEE Transactions on Engineering Management, and Telecommunication Policy, among many other journals. His research has won numerous awards.

Thomas A. Weber ([email protected]) is Professor of Operations, Economics and Strategy at the Swiss Federal Institute of Technology in Lausanne. Previously, he was a senior consultant with the Boston Consulting Group and a member of the standing faculty at Stanford University. He holds Master’s degrees in Technology and Policy, and Electrical Engineering and Computer Science from MIT, and a Ph.D. in Applied Economics and Managerial Science from the Wharton School of the University of Pennsylvania. He was a visiting faculty in Economics at Cambridge University and in Mathematics at Moscow State University. Dr. Weber’s research interests include dynamic systems, optimization, economics of information and uncertainty, the design of contracts, and strategy. He has published over 100 scholarly papers in journals such as American Economic Journal: Microeconomics, Economics Letters, Information Systems Research, Journal of Management Information Systems, Journal of Mathematical Economics, Management Science, Economic Theory, Operations Research, Physical Review E, Theory and Decision, and many others. He is the author of Optimal Control Theory with Applications in Economics (MIT Press, 2011).

Effective market mechanisms are important for supporting the high performance and profitability of digital commerce firms, just as they have been for traditional buyer-seller exchange networks that maximize overall welfare and optimize the distribution of goods and services so firms can sustain viable businesses [5, 12]. Economic decisions typically are made based on the agents’ informedness about relevant opportunities for exchange, while recognizing the critical importance of incentive-compatibility and individual-rationality constraints that they face [7].1 The latter depend on their preferences as well as on their resource endowments. Thus, market mechanisms, through the agents’ informedness and market-wide awareness they engender, offer a means for price discovery, link formation, transactional contracts, and the eventual (re-)allocation of products and services among market participants [8]. Intermediaries, through their self-interest paired with informational inefficiencies, may well reduce market efficiency on one side [11], while at the same time contributing market innovation and a co-creation of value (jointly with agents and firms) in their respective business circles and social networks [4, 9].

New technologies have emerged in the past decade to create social media-based communication, digital exchanges for shared goods and services, tracing capabilities for supply-chain goods and resources, wearable Internet-of-things devices, and—most recently—new ways to work due to the COVID-19 pandemic. One of the main impacts of information systems (IS) over the years has been to shift the boundaries of firms and support new ways for them to jointly create value within business networks and markets. Technology has exerted power to drive an information-based transformation of organizational strategy and society, yielding new organizational forms. It has also changed the ways in which people interact and dramatically transformed the (endogenous) nature of market linkages [2]. In addition, information asymmetries are no longer so asymmetrical, with the increasing availability of customer-centric data. Second-degree price discrimination (based on self-selection in a world of unobservable characteristics) is moving toward third-degree price discrimination (derived from detailed, consumer-specific information) through personalized “special offers,” mass customization, and personalization, creating “markets-of-one” [10].

This Special Section of Journal of Management Information Systems (JMIS) on Improving New Digital Market Mechanisms deals with theoretical and practical issues that arise with market mechanisms for social media-based customer services in the airline industry and rewards-based crowdfunding in the fintech sector. In these applied contexts, there are economic incentives that prompt air carriers to seek new channels for harvesting passenger complaints about their services. Similar types of incentives encourage crowdfunding intermediaries to promote new ways of achieving successful matches among crowdfunding campaign creators and their funds-donating backers. These mechanisms reflect aspects of the long-term viability of the new market approaches related to the underlying economics at work in the digital economy.

Social media-based customer services and rewards-based crowdfunding are intermediated by digital platforms with large installed bases. They are subject to beneficial (e.g., public information and passengers’ awareness) and detrimental externalities (e.g., informational congestion and campaign-backers’ uncertainty) [1]. Their participants are also affected by the awareness social-media communication delivers, as well as by herd effects that arise for those who do not grasp how asset values, product prices, and sentiments change over time.

Our Special Section opens with an article entitled “Does Active Service Intervention Drive More Complaints on Social Media? The Roles of Service Quality and Awareness,” coauthored by Shujing Sun, Gao Yang, and Huaxia Rui. During the 2010s, air carriers began to use Twitter as a new and open channel for passenger complaints. It serves as an inexpensive means to support customer-service call-center operations and offers a hitherto unheard-of level of transparency into passengers’ problems and their resolution by the various carriers.

The authors tracked social media-based customer service tweets and discussion threads on Twitter across more than 40 international air carriers from 2014 to 2019. Their focus is on the airlines’ use of active service interventions via social media, by customer service representatives (CSRs)—in direct online interactions with disgruntled travelers. The authors ask whether social-media presence encourages complaints due to the mere availability of CSRs and their real-time interactive capacity, or if they may simply have a calming effect on passengers.

They set out to understand how service volume and service quality affect the demand for service, when airlines use social media as a problem-resolution channel for customer complaints. First, they hypothesize a service-volume effect, in that more customer service interventions may lead to more customer complaints. Second, to assess the demand effect of service quality, the authors recognize the possibility of two countervailing tendencies: a snowball effect of service quality where higher social-media service quality leads to an increase in the volume of customer complaints, versus a neutralizing effect of service quality that leads to fewer complaints. While the former would indicate positive feedback generated by increased service accessibility, the latter would corroborate negative feedback due to the durability of solutions to current issues (while forestalling future issues) and a community inoculation effect due to the semi-public nature of the problem-treatment.

The authors’ tests of the various demand effects of brand-service intervention on future customer complaints yield interesting results. Indeed, the service-volume effect finds support in the collected data. Furthermore, service quality was associated with a positive marginal effect on response delay time and a negative marginal effect on the ratio of resolutions achieved. Thus, delayed responses seem to have led to more future complaints, while a better service-request-resolution ratio reduced them. The neutralizing effect of service quality hypothesis was also corroborated, whereas the countervailing snowball effect of service quality hypothesis could not be confirmed.

Overall, the results suggest that using a social-media channel to address customer complaints tends to increase the volume of such complaints. This is not primarily driven by endogenously created chronic complainers, but rather because the ease and visibility of the online service creates additional demand for speedy resolution. This short-term increase of complaint volume can be viewed as an investment in customer retention, as it allows users to vent frustration immediately with a good chance of quasi-instant gratification. By paying attention to how the issues are resolved, however, a company can decrease complaint volume in the medium- to long-term. The question of whether to maintain an online complaint-resolution platform is not really up for debate, being one of competitive necessity. However, when deciding about the seriousness with which this channel is pursued, airlines should keep in mind the interconnectedness of the social-media user base and view it as a critical piece of omnichannel after-sales strategy.

The second article’s research question ties together aspects of theoretical interest, causal empirical research design, and applied issues in the digital economy: “Sustainability of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis of Funding Targets and Backer Satisfaction,” by Michael Wessel, Rob Gleasure, and Robert J. Kauffman. Rewards-based crowdfunding—and its all-or-nothing (AON) funding market microstructure—responds to the need for aligning creators’ incentives and backers’ charitable motives for donating their investable funds. Although campaigns are designed to be launched in an incentive-compatible way for the “principals” (as backers) and the “agent” (as creator), the reality may turn out to be quite different. Incentives that may have been compatible at campaign launch may drift apart, as the funded project adjusts over time to changing market conditions. Meanwhile, backers are locked into early expectations for the project’s outcomes that may be difficult for the creator to deliver on.

This causal empirical case study’s original goal was to assess how campaign creators set targets for crowd-based fundraising, and how well the market microstructure delivered satisfaction with the rewards to campaign-funding backers. Along the way though, some other surprising findings turned up, suggesting possible platform-mechanism problems that could make the crowdfunding-market leader, Kickstarter, become vulnerable to the diminishing viability of its essential business model in the future.

Based on an extensive dataset from a leading crowdfunding platform, the authors first identify the rationale that campaign creators use to set their targets for crowdfunding in the market, given beliefs about the resources needed to carry the respective projects to fruition. A potential “fear of failure” among creators who set their funding goals too high is noted. The authors trace the logic of building success into their campaigns from the start, by setting achievable funding goals. Second, startups tend to want to satisfy their backers by identifying rewards at the outset of their campaigns that would be incentive-compatible with their taking risks and dealing with the uncertain outcomes of the projects. The authors view this process as problematic in the context of agency theory, highlighting a likely divergence of incentives when assessments about the project’s success by principals (backers) and the agent (creator) drift apart over time.

The authors test several hypotheses, two of which relate to whether setting targets with low levels of funding are more likely to meet the AON goals for funding success, and whether such funding increases the likelihood that backers would express more dissatisfaction about the rewards they receive at project completion, respectively. The remaining hypotheses address alternative explanations and moderating influences which may question the logic behind the main findings, thus adding to the weight of evidence from new knowledge about how rewards-based crowdfunding works in practice. For example, they sought to assess whether more creator-backer interaction, after a campaign finishes but before its rewards are distributed, would weaken the relationship between a relatively low funding goal and backer satisfaction. They also hypothesized that the link between the initial low funding goal and backer satisfaction may weaken when fundraising targets are exceeded, and—similarly—that backers’ repeated participation in a campaign with a creator may also create negative feedback related to backer satisfaction.

The data consist of variables associated with 390,000 Kickstarter fundraising campaigns, between 2010 and 2020, including about 20 million textual Twitter posts related to campaigns, creators, and backers—as evidence of backer satisfaction on completed projects. The authors’ quasi-experimental research design takes advantage of Kickstarter’s data structure and includes propensity-score matching. The approach supports model-wide causal inference in lieu of adjusting some of the modeling variables for endogeneity and performing separate estimates for robustness against biases. They also test alternative variable and model specifications.

Their results indicate that the freedom creators had to set their own campaign funding targets plays a role in causing lower backer satisfaction with their campaign rewards. They also find that campaigns which achieved excess funding (above their respective AON targets) were no better at improving backer satisfaction than those with relatively low funding targets. Interestingly however, there is no evidence that more post-campaign comments (suggesting ongoing creator-backer alignment) led to higher backer satisfaction, nor were experienced campaign creators likely to moderate the effects of low funding targets on backer satisfaction. Perhaps the most interesting observation pertains to the long-term viability of Kickstarter’s market mechanism, namely the dynamically increasing divergence from 2010 to 2020 between campaign funding success (mostly rising) and backer satisfaction (mostly falling)—especially in recent years. Such diverging expectations among creators and backers may well limit Kickstarter’s market value over time.



For more details on the theory of informedness in the IS discipline, see [3, 6], for example.


[1]Anderson, S.P.; and de Palma, A. Information congestion. RAND Journal of Economics, 40, 4 (Winter 2009), 688–709.

[2]Clemons, E.K.; Dewan, R.M.; Kauffman, R.J.; and Weber, T.A. Understanding the information-based transformation of strategy and society. Journal of Management Information Systems, 34, 2 (Fall 2017), 425–456.

[3]Clemons, E.K.; and Gao, G.G. Consumer informedness and diverse consumer purchasing behaviors: Traditional mass-market, trading down, and trading out into the long tail. Electronic Commerce Research and Applications, 7, 1 (Spring 2008), 3–17.

[4]Kauffman, R.J.; Li, T.; and van Heck, E. Business network-based value creation in electronic commerce. International Journal of Electronic Commerce, 15, 1 (Fall 2010), 111–142.

[5]Kranton, R.E.; and Minehart, D.F. A theory of buyer-seller networks. American Economic Review, 91, 3 (June 2001), 485–508.

[6]Li, T.; Kauffman, R.J.; van Heck, E.; Vervest, P.; and Dellaert, B. Consumer informedness and firm information strategy. Information Systems Research, 25, 2 (June 2014), 345–363.

[7]Myerson, R.B. Mechanism design. In J. Eatwell, M. Milgate, and P. Newman (eds.), Allocation, Information, and Markets, London, UK: Palgrave MacMillan, 1989, pp. 191–206.

[8]Oh, W.; and Lucas, H.C., Jr. Information technology and pricing decisions: Price adjustments in online computer markets. MIS Quarterly, 30, 3 (September 2006), 755–775.

[9]Spulber, D.F. The intermediation theory of the firm: Integrating economic and management approaches to strategy. Managerial Decision and Economics, 24, 4 (June-July 2003), 253–266.

[10]Varian, H.R.; Farrell, J.; and Shapiro, C. The Economics of Information Technology: An Introduction. Cambridge, UK: Cambridge University Press, 2004.

[11]Weber, T.A.; and Zheng, E. A model of search intermediaries and paid referrals. Information Systems Research, 18, 4 (December 2007), 414–436.

[12]Wilson, R.B. Game-theoretic analyses of trading processes. In T.F. Bewley (ed.), Advances in Economic Theory: Fifth World Congress (Econometric Society Monographs), Cambridge, UK: Cambridge University Press, 1987, pp. 227–279.