Non-Obvious Manipulability for Single-Parameter Agents and Bilateral Trade

Mechanism design for one-sided markets is an area of extensive research in economics and, since more than a decade, in computer science as well. Two-sided markets, on the other hand, have not received the same attention despite the numerous applications to web advertisement, stock exchange, and frequency spectrum allocation. This work studies double auctions, in which unit-demand buyers and unit-supply sellers act strategically.An ideal goal in double auction design is to maximize the social welfare of buyers and sellers with individually rational (IR), incentive compatible (IC) and strongly budget-balanced (SBB) mechanisms. The first two properties are standard. SBB requires that the payments charged to the buyers are entirely handed to the sellers. This property is crucial in all the contexts that do not allow the auctioneer retaining a share of buyers' payments or subsidizing the market.Unfortunately, this goal is known to be unachievable even for the special case of bilateral trade, where there is only one buyer and one seller. Therefore, in subsequent papers, meaningful trade-offs between these requirements have been investigated.Our main contribution is the first IR, IC and SBB mechanism that provides an O(1)-approximation to the optimal social welfare. This result holds for any number of buyers and sellers with arbitrary, independent distributions. Moreover, our result continues to hold when there is an additional matroid constraint on the sets of buyers who may get allocated an item. To prove our main result, we devise an extension of sequential posted price mechanisms to two-sided markets. In addition to this, we improve the best-known approximation bounds for the bilateral trade problem.

Mechanism design for one-sided markets is an area of extensive research in economics and, since more than a decade, in computer science as well. Two-sided markets, on the other hand, have not received the same attention despite the numerous applications to web advertisement, stock exchange, and frequency spectrum allocation. This work studies double auctions, in which unit-demand buyers and unit-supply sellers act strategically.An ideal goal in double auction design is to maximize the social welfare of buyers and sellers with individually rational (IR), incentive compatible (IC) and strongly budget-balanced (SBB) mechanisms. The first two properties are standard. SBB requires that the payments charged to the buyers are entirely handed to the sellers. This property is crucial in all the contexts that do not allow the auctioneer retaining a share of buyers' payments or subsidizing the market.Unfortunately, this goal is known to be unachievable even for the special case of bilateral trade, where there is only one buyer and one seller. Therefore, in subsequent papers, meaningful trade-offs between these requirements have been investigated.Our main contribution is the first IR, IC and SBB mechanism that provides an O(1)-approximation to the optimal social welfare. This result holds for any number of buyers and sellers with arbitrary, independent distributions. Moreover, our result continues to hold when there is an additional matroid constraint on the sets of buyers who may get allocated an item. To prove our main result, we devise an extension of sequential posted price mechanisms to two-sided markets. In addition to this, we improve the best-known approximation bounds for the bilateral trade problem.

This paper will review important topics on the subject of auction theory and mechanism design, these include: efficiency first and foremost, also revenue comparison between different types of auctions and the issue of incentive compatibility, individual rationality with the general idea and proof that bilateral trade is inefficient. Mechanism design theory tells us that if buyers and sellers both have private information full efficiency is impossible, however Vickrey auction (single unit auction) will be efficient i.e. will put the goods in the hands of the buyers that value them most. However, the conclusion from this paper is that because of overvaluation of bidders the main result is inefficient, i.e. bids are too high. When weak and strong bidders are compared the main conclusion is that strong bidders’ expected payoff is higher in second price auction (SPA), while weak bidder prefers first price auction (FPA) bid.

The goal of this paper is to develop a strategy-proof (SP) mechanism for the k-winner selection problem, which finds a set of (at most) k winners among participants. Here, we assume the winners can have positive/negative externalities with each other; the gross utility of a winner not only depends on whether she wins, but also on the other winners. If the types of agents, i.e., the gross utilities of agents, are known, we can obtain a Pareto efficient (PE) allocation that maximizes the sum of the gross utilities of winners in polynomial time, assuming k is a constant. On the other hand, when the types of agents are private information, we need a mechanism that can elicit the true types of agents; it must satisfy SP. We first show that there exists no SP mechanism that is PE, individual rational (IR), and non-deficit (ND) in a general setting where we put no restrictions on possible agent types. Thus, we need to give up at least one of these desirable properties.Next, we examine how a family of Vickrey-Clarke-Groves (VCG) based mechanisms works for this problem. We consider two alternative VCG-based mechanisms in this setting, both of which are SP and PE. We show that one alternative, called VCG-ND, is ND but not IR, and the other alternative, called VCG-IR, is IR but not ND. Also, we show special cases where VCG-ND satisfies IR, or VCG-IR satisfies ND. Moreover, we propose mechanisms called VCG-ND+ and VCG-IR+, which can be applied to a general setting, where a mechanism designer has partial knowledge about the possible interactions among agents. Both VCG-ND+ and VCG-IR+ are SP, IR, and ND, but they are not PE. Finally, we present a concise graphical representation scheme of agant types.KeywordsMechanism DesignerIndividually RationalCombinatorial AuctionSocial SurplusTrue TypeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

We examine the benefits and limitations of mechanism design as it applies to multi-agent meeting scheduling. We look at the problem of scheduling multiple meetings between various groups of agents that arise over time. Each of the agents has private information regarding their tune preferences for meetings. Our aim is to extract this information and assign the meetings to times in a way that maximises social welfare. We discuss problems with previous attempts to design incentive compatible (IC) and individually rational (IR) mechanisms for the task. We focus on the problem of determining when agents are available. In particular, we show that when agents with general valuation functions are asked to supply their availability for meeting times, there is no IC and IR mechanism. Given this impossibility result, we show how the likelihood of violating IR can be reduced through agents expressing their value for the presence of others at meetings. We also show how requesting agent preferences for entire schedules helps to eliminate IC problems.

Crowdsourcing is an emerging paradigm where users can pay for the services they need or receive rewards for providing services. One example in wireless networking is mobile crowdsourcing, which leverages a cloud computing platform for recruiting mobile users to collect data (such as photos, videos, mobile user activities, etc) for applications in various domains, such as environmental monitoring, social networking, healthcare, transportation, etc. However, a critical problem arises as how to ensure that users pay or receive what they deserve. Free-riding and false-reporting may make the system vulnerable to dishonest users. In this paper, we aim to design schemes to tackle these problems, so that each individual in the system is better off being honest. We first design a mechanism EFF which eliminates dishonest behavior with the help from a trusted third party for arbitration. We then design another mechanism DFF which, without the help from any third party, discourages free-riding and false-reporting. We prove that EFF eliminates the existence of free-riding and false-reporting, while guaranteeing truthfulness, individual rationality, budget-balance, and computational efficiency. We also prove that DFF is semi-truthful, which discourages dishonest behavior such as free-riding and false-reporting when the rest of the individuals are honest, while guaranteeing budget-balance and computational efficiency. Performance evaluation shows that within our mechanisms, no dishonest behavior could bring extra benefit for each individual.

The paper considers the specifics of research in the field of academic integrity in the works of researchers in the United States of America. The main purpose of the paper is to describe the peculiarities of the interpretation of the concept of honesty as a component of the value basis of academic integrity in the papers of US researchers. The main sources of information on the issue of integrity in the research of scientists in the United States in the context of academic integrity are both scientific papers and case studies and various informational resources and manuals for students on the issue of integrity and ethics. In the works of scholars the research question is considered in philosophical and educational contexts. One of the key issues is also the opposition of the concepts of "honesty" - "dishonesty", which allows us to offer a convenient in terms of practical application of the definition, and take into account the main aspects of the problem. Along with the study of the concept of honesty, there is also the concept of "honest behavior" and the opposite "dishonest behavior". Teachers in higher education institutions in the United States receive significant resource and methodological support, which helps to involve them in the process of forming values of the academic environment, in particular, taking into account the priority of academic integrity. An important source of information about academic dishonesty for students is special manuals and codes of conduct for students, which are mostly posted on the websites of educational institutions. The information provided in such sources highlights the rights and responsibilities of students and educators, and serves as a guide. Quite interesting is the approach of American scientists to the prevention of academic dishonesty, which is based on modeling the profiles of "academically honest student" and "academically dishonest student." The scientific understanding of the issue is mostly based on the activity approach. Taking into account the specifics of educational activities, theoretical models of honest and dishonest behavior are formed, in accordance with these models, recommendations are created for participants in the educational process. As the prospects for further studies we can mention the research aimed at adapting the scientific achievements of US researchers for implementation in the system of educational work in educational institutions of Ukraine.

Studied impressions of personality when descriptions of honest (H) or dishonest (D) behavior, based on Hartshorne and May's (1928) situational tests of deceit, were used instead of or in addition to descriptions of extrovert (E) or introvert (I) behavior. Experiments with 100 college or high school students showed very different responses to the H and D descriptions, even for questions not bearing on honest or dishonest behavior. When the H and D descriptions were combined without paragraph indentations as HD or DH descriptions, subjects expressed more awareness of inconsistencies than they did when the E and I blocks were combined. Primacy effects prevailed but were weaker for the DH and HD communications than for the EI or IE communications. The D block exerted a stronger primacy effect than did the H block, as did the I block, as compared to the E block. When a questionnaire was given after the D or H information and again after the E or I information, responses to the D block were strikingly ...

People feel committed to other individuals, groups, organizations, or moral norms in many contexts of everyday life. Such social commitment can lead to positive outcomes, such as increased job satisfaction or relationship longevity; yet, there can also be detrimental effects to feeling committed. Recent high-profile cases of fraud or corruption in companies like Enron or Volkswagen are likely influenced by strong commitment to the organization or coworkers. Although social commitment might increase dishonest behavior, there is little systematic knowledge about when and how this may occur. In the present project, we reviewed 20,988 articles, focusing on studies that experimentally manipulated social commitment and measured dishonest behavior. We retained 445 effect sizes from 121 articles featuring a total of 91,683 participants across 33 countries. We found no evidence that social commitment increases or reduces dishonest behavior in general. Nonetheless, we did find evidence that the effect strongly depends on the target of the commitment. Feeling committed to other individuals or groups reduces honest behavior (g = -0.17 [-0.24, -0.11]), whereas feeling committed to honesty norms through honesty oaths or pledges increases honest behavior (g = 0.27 [0.19, 0.36]). The analysis identified several moderating variables and detected some degree of publication bias across effects. Our findings highlight the diverging effects of different forms of social commitment on dishonest behavior and suggest a combination of the different forms of commitment could be a possible means to combat corruption and dishonest behavior in the organizational context. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mechanism design for first-mile ridesharing based on personalized requirements part II: Solution algorithm for large-scale problems

Honest and dishonest behaviors may both diffuse among the members of an organization. Knowing which of the two spreads faster is important because it impacts the extent to which managers will need to resort to other, potentially more costly solutions to curb dishonest behavior. Assessing empirically which of honest behavior or dishonest behavior spreads faster is challenging because this requires field measurements of social relationships and dishonest behavior of individual members, which poses both measurement and inference problems. We examine an original fine-grained data set from a large company that allows for identifying agents likely to be dishonest and interactions among employees while offering a natural experiment that circumvents the inference problems associated with identifying peer-to-peer diffusion. We find (1) that dishonest behavior diffuses, whereas honest behavior does not; (2) that diffusion likely operates through spreading information about opportunities for collusion; and (3) that policies that screen on dishonesty at hiring may be efficient to curb dishonest behavior in environments with high turnover. This paper was accepted by Lamar Pierce, organizations. Funding: R. Ferrali acknowledges support from the Mamdouha S. Bobst Center for Peace and Justice [Grant 2016-12-Bobst], the French National Research Agency [Grant ANR-17-EURE-0020], and Aix-Marseille University—A*MIDEX [Excellence Initiative]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01981 .

Over the past decade, a large and growing body of experimental research has analyzed dishonest behavior. Yet the findings as to when people engage in (dis)honest behavior are to some extent unclear and even contradictory. A systematic analysis of the factors associated with dishonest behavior thus seems desirable. This meta-analysis reviews four of the most widely used experimental paradigms: sender-receiver games, die-roll tasks, coin-flip tasks, and matrix tasks. We integrate data from 565 experiments (totaling N = 44,050 choices) to address many of the ongoing debates on who behaves dishonestly and under what circumstances. Our findings show that dishonest behavior depends on both situational factors, such as reward magnitude and externalities, and personal factors, such as the participant's gender and age. Further, laboratory studies are associated with more dishonesty than field studies, and the use of deception in experiments is associated with less dishonesty. To some extent, the different experimental paradigms come to different conclusions. For example, a comparable percentage of people lie in die-roll and matrix tasks, but in die-roll tasks liars lie to a considerably greater degree. We also find substantial evidence for publication bias in almost all measures of dishonest behavior. Future research on dishonesty would benefit from more representative participant pools and from clarifying why the different experimental paradigms yield different conclusions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Robust mechanism design and social preferences

With the emergence of big data computing and analysis, cloud computing services become more and more popular, which has recently drawn researchers’ great attentions to develop various new applications and mechanisms. In this paper, we consider the on-demand mechanism design in the infrastructure as a service (IaaS), including resource allocation and pricing issues under dynamic scenarios. Most of existing works on mechanism design assumed static and independent individual utility, while the cloud computing services are provided in a dynamic environment. To solve such problems, we start with analyzing the Google cluster-usage dataset to draw the statistical and stochastic characteristics of the IaaS consumers and providers. Based on the characteristics mined from real data, we propose a stochastic matching algorithm with Markov Decision Process (MDP), which aims at optimizing the long-term system efficiency, with its online version using Q-learning method to address the imperfect model estimation problem. We further design an efficient (EF), incentive compatible (IC), individual rational (IR) auction mechanism, which is an extension of traditional Vickrey-Clarke-Groves (VCG) mechanism. The proposed mechanism is studied under two application scenario: quality sensitive services, where unilateral MDP-VCG auction is implemented; and quality insensitive services, where MDP-VCG double auction is implemented. To verify the performance of our proposed mechanism, we conduct experiment using the Google dataset and show that the proposed MDP-based VCG auction mechanism can achieve EF, IC and IR properties simultaneously.

The application opportunities of mechanism design theory has been analyzed in the scope of company management, particularly in the scope of individual-company negotiations process. The negotiation process has been analyzed using the mechanism design methodology. Besides the individual rationality and incentive compatibility constraints two more efficiency indicators such as net utility of agent and company has been defined to evaluate the mechanisms. During the analysis it became evident, that the widespread mechanisms in the market do not meet the defined efficiency indicators and at the same time are not considered incentive compatible. Adjusted Vickrey-Clarke-Groves mechanism has been designed by the authors, which may be applicable in the negotiation process. The designed mechanism corresponds to the defined efficiency indicators, the individual rationality and incentive compatibility constraints and can be fully implemented in the process of individual-company negotiations.