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Strategic conversations involve one party with an informational advantage and another with an interest in the information. This paper proposes machine learning-based methods to quantify the evasiveness and incoherence of the more -informed party during real-time strategic conversations. To demonstrate the effectiveness of these methods in a real -world setting, we consider the question -and -answer sessions of earnings conference calls, during which managers face scrutinizing questions from analysts. Being reluctant to disclose adverse information, managers may resort to evasive answers and sometimes respond less coherently than they otherwise would. Using data from the earnings calls of S&P 500 companies from 2006 to 2018, we show that the proposed measures predict worse next -quarter earnings. The stock market also perceives incoherence as a negative signal. This paper contributes methodologically to business analytics by developing machine learning methods to extract behavioral cues from real-time strategic conversations. We believe the wide adoption of these tools can increase the efficiency of various markets and institutions where real-time strategic conversations routinely occur, which ultimately benefits business and society.

Online reputation trading is a new phenomenon facilitated by the prosperity of e-commerce and social networks. Whether reputations will be reliable when people can purchase rather than build them originally is a natural concern and also a challenge to online marketplaces. In the present study, we examine a reputation market in an infinitely repeated game setting, where agents sell products and trade their online reputations. Agents exert effort to provide products, and their reputations are updated based on consumer feedback. High-type agents have a lower cost of effort than low types. In addition to reputation system, we consider products that are randomly audited, and agents do not receive payment for products that fail the audit. Our analysis depicts a separating equilibrium: high-type agents can be sorted out from low-type agents by their reputations, which contrasts with the results in Tadelis (2002). In a separating equilibrium, reputations become a perfect indicator of agents’ types, effort levels, and product quality. We demonstrate the key role of auditing in separating different types of agents, and reveal the substitution effect between auditing frequency and harshness of reputation systems. We also study the design of the reputation system and the audit mechanism in order to achieve different equilibria in the reputation market. By proposing online reputations as an asset, our paper generates implications for establishing reliable online environments and promoting effective online interactions.

Online reputation trading is a new phenomenon facilitated by the prosperity of e-commerce and social networks. Whether reputations will be reliable when people can purchase rather than build them originally is a natural concern and also a challenge to online marketplaces. In the present study, we examine a reputation market in an infinitely repeated game setting, where agents sell products and trade their online reputations. Agents exert effort to provide products, and their reputations are updated based on consumer feedback. High-type agents have a lower cost of effort than low types. In addition to reputation system, we consider products that are randomly audited, and agents do not receive payment for products that fail the audit. Our analysis depicts a separating equilibrium: high-type agents can be sorted out from low-type agents by their reputations, which contrasts with the results in Tadelis (2002). In a separating equilibrium, reputations become a perfect indicator of agents’ types, effort levels, and product quality. We demonstrate the key role of auditing in separating different types of agents, and reveal the substitution effect between auditing frequency and harshness of reputation systems. We also study the design of the reputation system and the audit mechanism in order to achieve different equilibria in the reputation market. By proposing online reputations as an asset, our paper generates implications for establishing reliable online environments and promoting effective online interactions.

Online reputation trading is a new phenomenon facilitated by the prosperity of e-commerce and social networks. Whether reputations will be reliable when people can purchase rather than build them originally is a natural concern and also a challenge to online marketplaces. In the present study, we examine a reputation market in an infinitely repeated game setting, where agents sell products and trade their online reputations. Agents exert effort to provide products, and their reputations are updated based on consumer feedback. High-type agents have a lower cost of effort than low types. In addition to reputation system, we consider products that are randomly audited, and agents do not receive payment for products that fail the audit. Our analysis depicts a separating equilibrium: high-type agents can be sorted out from low-type agents by their reputations, which contrasts with the results in Tadelis (2002). In a separating equilibrium, reputations become a perfect indicator of agents’ types, effort levels, and product quality. We demonstrate the key role of auditing in separating different types of agents, and reveal the substitution effect between auditing frequency and harshness of reputation systems. We also study the design of the reputation system and the audit mechanism in order to achieve different equilibria in the reputation market. By proposing online reputations as an asset, our paper generates implications for establishing reliable online environments and promoting effective online interactions.

Our paper studies the impact of reputation management on executives career using the evidence from their usage of Twitter. This self-promoting behavior has both a direct influence of the barging powers in negotiating compensation and sorting in the hiring process, which helps an executive to increase the chance of finding a job. Our structural model based on a Two-Sided Matching model is able to exploit the characteristics of the other candidates to separately identify influence in barging power and sorting in getting a job. We model the assignment of executives to firms and the pay as endogenously determined. Both effects are found to be significant but in different ways. While self-promotion increases CEO compensation, in the recruiting process, only past very unsatisfactory CEO candidates benefit from reputation management. The results show more salient positive assortative matching of reputation management in Chief Marketing Officer market than the CEO market.

Our paper studies the impact of reputation management (RM) on executives' career using their usage of Twitter. This self-promoting behavior has an influence on the bargaining powers in negotiating compensation and sorting during the hiring process, which increases their job acquisition chances. Our structural model which is based on a two sided matching model, is able to separately identify the two influences. We modeled the matching and the pay as endogenously determined. We find both effects to be significant. While RM only increases the compensations of successful candidates, in the recruiting process of CEO and CMO markets, both outstanding and outperformed applicants benefit from it. Our analysis sheds light upon the pricing scheme of social media for the use of self-promotion.

Our paper studies the impact of reputation management on executives career using the evidence from their usage of Twitter. This self-promoting behavior has both a direct influence of the barging powers in negotiating compensation and sorting in the hiring process, which helps an executive to increase the chance of finding a job. Our structural model based on a Two-Sided Matching model is able to exploit the characteristics of the other candidates to separately identify influence in barging power and sorting in getting a job. We model the assignment of executives to firms and the pay as endogenously determined. Both effects are found to be significant but in different ways. While self-promotion increases CEO compensation, in the recruiting process, only past very unsatisfactory CEO candidates benefit from reputation management. The results show more salient positive assortative matching of reputation management in Chief Marketing Officer market than the CEO market.

Our paper studies the impact of reputation management (RM) on executives' career using their usage of Twitter. This self-promoting behavior has an influence on the bargaining powers in negotiating compensation and sorting during the hiring process, which increases their job acquisition chances. Our structural model which is based on a two sided matching model, is able to separately identify the two influences. We modeled the matching and the pay as endogenously determined. We find both effects to be significant. While RM only increases the compensations of successful candidates, in the recruiting process of CEO and CMO markets, both outstanding and outperformed applicants benefit from it. Our analysis sheds light upon the pricing scheme of social media for the use of self-promotion.

Our paper studies the impact of reputation management (RM) on executives' career using their usage of Twitter. This self-promoting behavior has an influence on the bargaining powers in negotiating compensation and sorting during the hiring process, which increases their job acquisition chances. Our structural model which is based on a two sided matching model, is able to separately identify the two influences. We modeled the matching and the pay as endogenously determined. We find both effects to be significant. While RM only increases the compensations of successful candidates, in the recruiting process of CEO and CMO markets, both outstanding and outperformed applicants benefit from it. Our analysis sheds light upon the pricing scheme of social media for the use of self-promotion.

Our paper studies the impact of reputation management on executives career using the evidence from their usage of Twitter. This self-promoting behavior has both a direct influence of the barging powers in negotiating compensation and sorting in the hiring process, which helps an executive to increase the chance of finding a job. Our structural model based on a Two-Sided Matching model is able to exploit the characteristics of the other candidates to separately identify influence in barging power and sorting in getting a job. We model the assignment of executives to firms and the pay as endogenously determined. Both effects are found to be significant but in different ways. While self-promotion increases CEO compensation, in the recruiting process, only past very unsatisfactory CEO candidates benefit from reputation management. The results show more salient positive assortative matching of reputation management in Chief Marketing Officer market than the CEO market.

Online reputation trading is a new phenomenon facilitated by the prosperity of e-commerce and social networks. Whether reputations will be reliable when people can purchase rather than build their reputations is a natural concern and also a challenge to online marketplaces. In the present study, we examine a reputation market in an infinitely repeated game setting, where agents sell products and trade their online reputations. Agents exert effort to provide products, and their reputations are updated based on consumer feedback. High type agents have a lower cost of effort than low types. In addition to reputation system, we consider products that are randomly audited, and agents do not receive payment for products that fail the audit. Our analysis depicts a separating equilibrium: high-type agents can be sorted out from low-type agents by their reputations, which contrasts with the results in Tadelis (2002). In a separating equilibrium, reputations become a perfect indicator of agents' types, effort levels, and quality of the products. We demonstrate the key role of auditing in separating different types of agents, and reveal the substitution effect between auditing frequency and harshness of reputation systems. We also study the design of the reputation system and the audit mechanism in order to achieve different equilibria in the reputation market. By proposing online reputations as an asset, our paper generates implications for establishing reliable online environments and promoting effective online interactions.

Online reputation trading is a new phenomenon facilitated by the prosperity of e-commerce and social networks. Whether reputations will be reliable when people can purchase rather than build their reputations is a natural concern and also a challenge to online marketplaces. In the present study, we examine a reputation market in an infinitely repeated game setting, where agents sell products and trade their online reputations. Agents exert effort to provide products, and their reputations are updated based on consumer feedback. High type agents have a lower cost of effort than low types. In addition to reputation system, we consider products that are randomly audited, and agents do not receive payment for products that fail the audit. Our analysis depicts a separating equilibrium: high-type agents can be sorted out from low-type agents by their reputations, which contrasts with the results in Tadelis (2002). In a separating equilibrium, reputations become a perfect indicator of agents' types, effort levels, and quality of the products. We demonstrate the key role of auditing in separating different types of agents, and reveal the substitution effect between auditing frequency and harshness of reputation systems. We also study the design of the reputation system and the audit mechanism in order to achieve different equilibria in the reputation market. By proposing online reputations as an asset, our paper generates implications for establishing reliable online environments and promoting effective online interactions.

Online reputation trading is a new phenomenon facilitated by the prosperity of e-commerce and social networks. Whether reputations will be reliable when people can purchase rather than build their reputations is a natural concern and also a challenge to online marketplaces. In the present study, we examine a reputation market in an infinitely repeated game setting, where agents sell products and trade their online reputations. Agents exert effort to provide products, and their reputations are updated based on consumer feedback. High type agents have a lower cost of effort than low types. In addition to reputation system, we consider products that are randomly audited, and agents do not receive payment for products that fail the audit. Our analysis depicts a separating equilibrium: high-type agents can be sorted out from low-type agents by their reputations, which contrasts with the results in Tadelis (2002). In a separating equilibrium, reputations become a perfect indicator of agents' types, effort levels, and quality of the products. We demonstrate the key role of auditing in separating different types of agents, and reveal the substitution effect between auditing frequency and harshness of reputation systems. We also study the design of the reputation system and the audit mechanism in order to achieve different equilibria in the reputation market. By proposing online reputations as an asset, our paper generates implications for establishing reliable online environments and promoting effective online interactions.

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content remains a challenge because of the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly affects strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. We find that when being moderated with different probabilities based on their reputations, commentators might display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from high-reputation commentators can be inferior to that from low-reputation commentators (reverse reputation). We then investigate the optimal moderation resource allocation and conclude that the seemingly abnormal reverse reputation could arise as an optimal result. Our study underscores the importance of moderation and highlights that the frequency of moderation should be properly chosen for better performance of online communities. © 2011 M.E. Sharpe, Inc.

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content remains a challenge because of the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly affects strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. We find that when being moderated with different probabilities based on their reputations, commentators might display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from high-reputation commentators can be inferior to that from low-reputation commentators (reverse reputation). We then investigate the optimal moderation resource allocation and conclude that the seemingly abnormal reverse reputation could arise as an optimal result. Our study underscores the importance of moderation and highlights that the frequency of moderation should be properly chosen for better performance of online communities. © 2011 M.E. Sharpe, Inc.

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content remains a challenge because of the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly affects strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. We find that when being moderated with different probabilities based on their reputations, commentators might display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from high-reputation commentators can be inferior to that from low-reputation commentators (reverse reputation). We then investigate the optimal moderation resource allocation and conclude that the seemingly abnormal reverse reputation could arise as an optimal result. Our study underscores the importance of moderation and highlights that the frequency of moderation should be properly chosen for better performance of online communities. © 2011 M.E. Sharpe, Inc.

The online world has developed from a source of information to a complex economic and social environment. However, many online environments fail to function effciently due to the lack of reliable reputation and anonymity of users. We propose a tradable reputation mechanism and conduct a virtual field experiment, using Second Life as an experimental platform, to investigate the role of reputation trading, based on our game theory analysis of the economic in uence of tradable reputation. We introduce an avatar market that allows users to buy and sell avatars in terms of the reputation. Our main theoretical results show that reliable reputation is induced in a separating equilibrium where users are separated based on their ability in fulfilling tasks or transactions. We generate five hypotheses to test in the field experiment. We also describe a computer system that realizes the proposed mechanism as a basis for the field experiment.

The online world has developed from a source of information to a complex economic and social environment. However, many online environments fail to function effciently due to the lack of reliable reputation and anonymity of users. We propose a tradable reputation mechanism and conduct a virtual field experiment, using Second Life as an experimental platform, to investigate the role of reputation trading, based on our game theory analysis of the economic in uence of tradable reputation. We introduce an avatar market that allows users to buy and sell avatars in terms of the reputation. Our main theoretical results show that reliable reputation is induced in a separating equilibrium where users are separated based on their ability in fulfilling tasks or transactions. We generate five hypotheses to test in the field experiment. We also describe a computer system that realizes the proposed mechanism as a basis for the field experiment.

The online world has developed from a source of information to a complex economic and social environment. However, many online environments fail to function effciently due to the lack of reliable reputation and anonymity of users. We propose a tradable reputation mechanism and conduct a virtual field experiment, using Second Life as an experimental platform, to investigate the role of reputation trading, based on our game theory analysis of the economic in uence of tradable reputation. We introduce an avatar market that allows users to buy and sell avatars in terms of the reputation. Our main theoretical results show that reliable reputation is induced in a separating equilibrium where users are separated based on their ability in fulfilling tasks or transactions. We generate five hypotheses to test in the field experiment. We also describe a computer system that realizes the proposed mechanism as a basis for the field experiment.

The online world has developed from a source of information to a complex economic and social environment. However, many online environments fail to function effciently due to the lack of reliable reputation and anonymity of users. We propose a tradable reputation mechanism and conduct a virtual field experiment, using Second Life as an experimental platform, to investigate the role of reputation trading, based on our game theory analysis of the economic in uence of tradable reputation. We introduce an avatar market that allows users to buy and sell avatars in terms of the reputation. Our main theoretical results show that reliable reputation is induced in a separating equilibrium where users are separated based on their ability in fulfilling tasks or transactions. We generate five hypotheses to test in the field experiment. We also describe a computer system that realizes the proposed mechanism as a basis for the field experiment.

The online world has developed from a source of information to a complex economic and social environment. However, many online environments fail to function effciently due to the lack of reliable reputation and anonymity of users. We propose a tradable reputation mechanism and conduct a virtual field experiment, using Second Life as an experimental platform, to investigate the role of reputation trading, based on our game theory analysis of the economic in uence of tradable reputation. We introduce an avatar market that allows users to buy and sell avatars in terms of the reputation. Our main theoretical results show that reliable reputation is induced in a separating equilibrium where users are separated based on their ability in fulfilling tasks or transactions. We generate five hypotheses to test in the field experiment. We also describe a computer system that realizes the proposed mechanism as a basis for the field experiment.

The online world has developed from a source of information to a complex economic and social environment. However, many online environments fail to function effciently due to the lack of reliable reputation and anonymity of users. We propose a tradable reputation mechanism and conduct a virtual field experiment, using Second Life as an experimental platform, to investigate the role of reputation trading, based on our game theory analysis of the economic in uence of tradable reputation. We introduce an avatar market that allows users to buy and sell avatars in terms of the reputation. Our main theoretical results show that reliable reputation is induced in a separating equilibrium where users are separated based on their ability in fulfilling tasks or transactions. We generate five hypotheses to test in the field experiment. We also describe a computer system that realizes the proposed mechanism as a basis for the field experiment.

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content, however, remains a challenge due to the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly impacts strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. Interestingly, we find that when being moderated with different probabilities based on their reputations, commentators may display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from highreputation commentators can be inferior to that from low-reputation ones (reversed reputation). We finally investigate the optimal moderation resource allocation, and conclude that the seemingly abnormal reversed reputation could arise as an optimal result.

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content, however, remains a challenge due to the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly impacts strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. Interestingly, we find that when being moderated with different probabilities based on their reputations, commentators may display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from highreputation commentators can be inferior to that from low-reputation ones (reversed reputation). We finally investigate the optimal moderation resource allocation, and conclude that the seemingly abnormal reversed reputation could arise as an optimal result.

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content, however, remains a challenge due to the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly impacts strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. Interestingly, we find that when being moderated with different probabilities based on their reputations, commentators may display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from highreputation commentators can be inferior to that from low-reputation ones (reversed reputation). We finally investigate the optimal moderation resource allocation, and conclude that the seemingly abnormal reversed reputation could arise as an optimal result.

This report consists of abstracts of a number of papers in the areas of data base design theory, office automation theory, decision support system theory, and problem solving.

A formal development of planning systems is constructed in this paper. The problem solving system is developed in the framework of a modal logic and the concept of weakest precondition is introduced to guide the solution procedure. The procedure is a generalization of several well-known problem solving algorithms. Moreover, there may be some gains in practicality of the algorithm resulting from this extension, which is illustrated by an example. (Author)

In view of the growing prominence of corporate modeling, an important area of research concerns techniques for facilitating the design and utilization of models. In this paper we show how first-order predicate calcuclus can be used as a language for formally stating modeling knowledge. Furthermore, knowledge stated in this manner can be subjected to the resolution principle. The result is that application specific modeling knowledge need not be embedded in a computer program. Rather, it can be stored in a data base and utilized as needed by a problem processing system employing resolution techniques. Advantages of a decision support system taking an approach of this sort are considerable modeling flexibility, capacity for automating the model formulation and execution processes, and compatibility with a high-level user interface language. (Author)

A formal, generic description of decision support systems is introduced. This description views a decision support system as having three principal components: a language system, a knowledge system and a problem processing system. Several systems are described which fit the generic DSS idea, but which are (for the most part) not the customary kinds of systems encountered in business applications. Nevertheless, the concepts and techniques employed in these systems can make important contributions to the emergence of more powerful business-oriented decision support systems. (Author), Prepared in cooperation with Illinois Univ.

This paper proposes a new approach to energy policy analysis. After a brief review of energy models, a novel decision support system based upon a modal data base, and a collection of programs which operate upon the data base. The paper concludes with an illustrative example. (Author)

Development and application of optimization techniques to water pollution, social choice, and game theory. (Author)

Conditions are demonstrated under which a violation of one Pareto condition means that it is socially desirable that certain other of the Paretian conditions be violated. The commonly held interpretation of the Lipsey-Lancasterassified report DESCRIPTORS: *Economics, Theory, Mathematical analysis, Functions, Partial differential equations, Decision making. Identifiers: Pareto condition (Economics), Theory of second best, Welfare economics. Conditions are demonstrated under which a violation of one Pareto condition means that it is socially desirable that certain other of the Paretian conditions be violated. The commonly held interpretation of the Lipsey-Lancaster theorem - that a violation of one Pareto condition means that none of the remaining Pareto conditions is desirable - is dispelled. The approach is somewhat similar to that used by Lipsey and Lancaster in that the method of maximinization subject to constraints is used. It is demonstrated that the Lipsey-Lancaster formulation of the second-best problem introduces extraneous considerations, does not provide adequate 'guidelines' for policy applications, and leads, at the very best, to misinterpretations of the meaning of their theorem. (Author)