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Abstract

In economics, the principal-agent problem is the difficulty in motivating one party (the agent), to act in the best interests of another (the principal) rather than in his own interests. We consider the example of a journal editor (the principal) wondering whether his or her reviewer (the agent) is recommending rejection of a manuscript because it does not have enough quality to be published or because the reviewer dislikes effort and he/she must work to acquire in-depth knowledge of the content of the manuscript. The reviewer's effort provides him or her with superior information about a manuscript's quality. If this information is not correctly communicated, the reviewer has more information when compared with the journal editor. This inherently leads to an encouragement of moral hazard, where the editor will not know whether the reviewer has done his or her job in accordance to the editor's interest. Prescriptions need to be given as to how the journal editor should control the reviewers to curb self-interest. Besides the associate editors monitoring the peer-review process, incentives can be employed to limit moral hazard on the part of the reviewer. Drawing on agency theory, we examine the incentives motivating the reviewers to expend effort to generate information about the quality of submissions. This model predicts that for reviewers early in their careers, promotion-based incentives may mean there is no need for within-job incentives, but also that within-job rewards for a referee's performance should depend on individual differences in ability and promotion opportunities.

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Abstract

The intent of this article is to use cooperative game theory to predict the level of social impact of scholarly papers created by citation networks. Social impact of papers can be defined as the net effect of citations on a network. A publication exerts direct and indirect influence on others (e.g., by citing articles) and is itself influenced directly and indirectly (e.g., by cited articles). This network leads to an influence structure of citing and cited publications. Drawing on cooperative game theory, our research problem is to translate into mathematical equations the rules that govern the social impact of a paper in a citation network. In this article, we show that when citation relationships between academic papers function within a citation structure, the result is social impact instead of the (individual) citation impact of each paper. Mathematical equations explain the interaction between papers in such a citation structure. The equations show that the social impact of a paper is affected by the (individual) citation impact of citing publications, immediacy of citing articles, and number of both citing and cited papers. Examples are provided for several academic papers.

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Abstract

Adverse selection occurs when a firm signs a contract with a potential worker but his/her key skills are still not known at that time, which leads the employer to make a wrong decision. In this article, we study the example of adverse selection of reviewers when a potential referee whose ability is his private information faces a finite sequence of review processes for several scholarly journals, one after the other. Our editor's problem is to design a system that guarantees that each manuscript is reviewed by a referee if and only if the reviewer's ability matches the review's complexity. As is typically the case in solving problems of adverse selection in agency theory, the journal editor offers a menu of contracts to the potential referee, from which the reviewer chooses the contract that is best for him given his ability. The optimal contract will be the one that provides the right incentives to match the complexity of the review and the ability of the reviewer. The payment of contracts is made through a proportional increment of the reviewer factor, which measures the importance of reviewers to their field.