Abstract
We examine when and how task division improves performance for inventory planning. Specifically, we consider a decentralized inventory management context with two interdependent subtasks: preparing a forecast and setting a service level. Using a behavioral experiment, we reveal that the task challenge moderates the relationship between task division and performance. Our findings indicate that task division improves performance when the task becomes more challenging, such as under high demand uncertainty. It facilitates counteracting behavior, where individuals adjust their decisions to counterbalance their partner's errors, leading to more stabilized final decisions. We identify this counteracting behavior as a critical mechanism driving the benefits of task division, mainly when subtasks are interdependent. We demonstrate the robustness of our findings by examining an egalitarian system, where decision-making authority is shared among team members, and a hierarchical system, where decision control resides entirely with one team member.
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.
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.
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.
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.