Social Conflict and the Evolution of Unequal Conventions
( Hwang, Sung-Ha | Naidu, Suresh | Bowles, Samuel )Journal of the European Economic Association2024-10
Abstract
We propose a theory of social norms (or conventions) that implement substantial levels of inequality between men and women, ethnic groups, and classes and that persist over long periods of time despite being inefficient and not supported by formal institutions. Consistent with historical cases, we extend the standard asymmetric stochastic evolutionary game model to allow subpopulation sizes to differ and idiosyncratic rejection of a status quo convention to be intentional to some degree (rather than purely random as in the standard evolutionary models). In this setting, if idiosyncratic play is sufficiently intentional and the subordinate class is sufficiently large relative to the elite, then risk-dominated conventions that are both more unequal and inefficient relative to alternative conventions will be stochastically stable and may persist for long periods. We show that the same is true in a general bipartite network of the population if most of the subordinate groups interactions are local, while the elite is more "cosmopolitan". We apply the model to the evolution of wage conventions on the bipartite network of workers and employers, and find that an unequal monopsonistic wage convention is robust to the idiosyncratic play of workers that otherwise might displace it.
Physical Frictions and Digital Banking Adoption
( Choi, Hyun-Soo | Loh, Roger K. )MANAGEMENT SCIENCE2024-10
Abstract
The behavioral literature suggests that minor frictions can elicit desirable behavior without obvious coercion. Using closures of ATMs in a densely populated city as an instrument for small frictions to physical banking access, we find that customers affected by ATM closures increase their usage of the bank's digital platform. Other spillover effects of this adoption of financial technology include increases in point-of-sale transactions, electronic funds transfers, automatic bill payments, and savings, and a reduction in cash usage. Our results show that minor frictions can help overcome the status quo bias and facilitate significant behavior change.
Optimal influence design in networks
( Jeong, Daeyoung | Shin, Euncheol )JOURNAL OF ECONOMIC THEORY2024-09
Abstract
We examine an influence designer's optimal intervention in the presence of social learning in a network. Before learning begins, the designer alters initial opinions of agents within the network to shift their ultimate opinions to be as close as possible to the target opinions. By decomposing the influence matrix, which summarizes the learning structure, we transform the designer's problem into one with an orthogonal basis. This transformation allows us to characterize optimal interventions under complete information. We also demonstrate that even in cases where the designer has incomplete information about the network structure, the designer can still design an asymptotically optimal intervention in a large network. Finally, we provide examples and extensions, including repeated social learning and competition.
On Crafting Effective Theoretical Contributions for Empirical Papers in Economics of Information Systems: Some Editorial Reflections
( Gopal, Anandasivam | Chen, Pei-yu | Oh, Wonseok | Xu, Sean Xin | Sarker, Suprateek )INFORMATION SYSTEMS RESEARCH2024-09
Abstract
The terms theory and theoretical contributions evoke mixed reactions in the information systems discipline, especially among empirical researchers in the economics of information systems (Econ-IS) area. Although some see such contributions as the raison d'etre for academic scholars engaged in research, others feel that the discipline has developed a fetish for theory, with reviewers and editors often demanding an unreasonable level of theoretical contributions for empirical manuscripts to succeed in the review process. Moreover, there exists a great deal of diversity in the conception of what constitutes a reasonable theoretical contribution, especially within empirical work, across editors and reviewers, leading to frustration with the review process and disappointment with editorial decisions. Given the different types of theoretical contributions that may be suitable for a given manuscript and recognizing the changing nature of empirical work within Econ-IS, we attempt to shed some light on theoretical contributions within empirical Econ-IS research, paying attention to their nature, types, and impact. Specifically, we start by reflecting on the typical theory-related comments we have seen in review packets that we generalize to a set of critiques often related to empirical papers. Subsequently, we provide a working definition of a theoretical contribution and the components that make up such a contribution. We then propose a taxonomy of theoretical contributions typically observed in Information Systems Research (ISR). ISR ). Based on this taxonomy of contributions, the typical critiques observed in empirical Econ-IS papers, and a set of published papers, we provide some broad guidelines for how authors may craft an effective theoretical contribution for submission to ISR. . We also discuss a pathway for manuscripts that do not (seek to) offer significant theoretical contributions. Such manuscripts are welcome, but we believe that a very high bar of practical impact must be met for them to succeed in the review process. Based on the guidelines and suggestions made here, our hope is that authors and evaluators will participate in the review process with a shared understanding of the elusive notion of theoretical contributions.
Disinformation Spillover: Uncovering the Ripple Effect of Bot-assisted Fake Social Engagement on Public Attention
( Lee, Sanghak | Shin, Donghyuk | Kwon, K. Hazel | Han, Sang Pil | Lee, Seok Kee )MIS Quarterly2024-09
Abstract
Disinformation activities that aim to manipulate public opinion pose serious challenges to managing online platforms. One of the most widely used disinformation techniques is bot-assisted fake social engagement, which is used to falsely and quickly amplify the salience of information at scale. Based on agenda-setting theory, we hypothesize that bot-assisted fake social engagement boosts public attention in the manner intended by the manipulator. Leveraging a proven case of bot-assisted fake social engagement operation in a highly trafficked news portal, this study examines the impact of fake social engagement on the digital public's news consumption, search activities, and political sentiment. For that purpose, we used ground-truth labels of the manipulator's bot accounts, as well as real-time clickstream logs generated by ordinary public users. Results show that bot-assisted fake social engagement operations disproportionately increase the digital public's attention to not only the topical domain of the manipulator's interest (i.e., political news) but also to specific attributes of the topic (i.e., political keywords and sentiment) that align with the manipulator's intention. We discuss managerial and policy implications for increasingly cluttered online platforms.
