Proceedings of the Sixteenth ACM Conference on Economics and Computation最新文献

{"title":"Customer Referral Incentives and Social Media","authors":"I. Lobel, E. Sadler, L. Varshney","doi":"10.2139/ssrn.2520615","DOIUrl":"https://doi.org/10.2139/ssrn.2520615","url":null,"abstract":"We study how to optimally attract new customers using a referral program. Whenever a consumer makes a purchase, the firm gives her a link to share with friends, and every purchase coming through that link generates a referral payment. The firm chooses the referral payment function and consumers play an equilibrium in response. The optimal payment function is nonlinear and not necessarily monotonic in the number of successful referrals. If we approximate the optimal policy using a linear payment function, the approximation loss scales with the square root of the average consumer degree. Using a threshold payment, the approximation loss scales proportionally to the average consumer degree. Combining the two, using a linear payment function with a threshold bonus, we can achieve a constant bound on the approximation loss.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128587807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust Dynamic Pricing With Strategic Customers","authors":"Yiwei Chen, V. Farias","doi":"10.1145/2764468.2764530","DOIUrl":"https://doi.org/10.1145/2764468.2764530","url":null,"abstract":"We consider the canonical problem of revenue management (RM) wherein a seller must sell an inventory of some product over a finite horizon via an anonymous, posted price mechanism. Unlike typical models in RM, we assume that customers are forward looking. In particular, customers arrive randomly over time, and strategize about their time of purchase. The private valuations of these customers decay over time and the customers incur monitoring costs; both the rate of decay and these monitoring costs are private information. Moreover, customer valuations and monitoring costs are potentially correlated. This setting has proven to be a difficult one for the design of optimal dynamic mechanisms heretofore. Optimal pricing schemes -- an almost necessary mechanism format for practical RM considerations -- have been similarly elusive. We propose a class of pricing policies, and a simple to compute policy within this class, that is guaranteed to achieve expected revenues that are at least within 29% of those under an optimal (not necessarily posted price) dynamic mechanism. Moreover, the seller can compute this pricing policy without any knowledge of the distribution of customer discount factors and monitoring costs. Our scheme can be interpreted as solving a dynamic pricing problem for myopic customers with the additional requirement of a novel --restricted submartingale constraint on prices. Numerical experiments suggest that the policy is, for all intents, near optimal.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114728665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Markets with Production: A Polynomial Time Algorithm and a Reduction to Pure Exchange","authors":"J. Garg, R. Kannan","doi":"10.1145/2764468.2764517","DOIUrl":"https://doi.org/10.1145/2764468.2764517","url":null,"abstract":"The classic Arrow-Debreu market model captures both production and consumption, two equally important blocks of an economy, however most of the work in theoretical computer science has so far concentrated on markets without production, i.e., the exchange economy. In this paper we show two new results on markets with production. Our first result gives a polynomial time algorithm for Arrow-Debreu markets under piecewise linear concave (PLC) utilities and polyhedral production sets provided the number of goods is constant. This is the first polynomial time result for the most general case of Arrow-Debreu markets. Our second result gives a novel reduction from an Arrow-Debreu market M (with production firms) to an equivalent exchange market M' such that the equilibria of M are in one-to-one correspondence with the equilibria of M'. Unlike the previous reduction by Rader where M' is artificially constructed, our reduction gives an explicit market M' and we also get: (i) when M has concave utilities and convex production sets (standard assumption in Arrow-Debreu markets), then M' has concave utilities, (ii) when M has PLC utilities and polyhedral production sets, then M' has PLC utilities, and (iii) when M has nested CES-Leontief utilities and nested CES-Leontief production, then M' has nested CES-Leontief utilities.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132733407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pricing in Ride-Sharing Platforms: A Queueing-Theoretic Approach","authors":"Siddhartha Banerjee, Ramesh Johari, C. Riquelme","doi":"10.1145/2764468.2764527","DOIUrl":"https://doi.org/10.1145/2764468.2764527","url":null,"abstract":"We study optimal pricing strategies for ride-sharing platforms, using a queueing-theoretic economic model. Analysis of pricing in such settings is complex: On one hand these platforms are two-sided - this requires economic models that capture the incentives of both drivers and passengers. On the other hand, these platforms support very high temporal-resolution for data collection and pricing - this requires stochastic models that capture the dynamics of drivers and passengers in the system. We focus our attention on the value of dynamic pricing: where prices can react to instantaneous imbalances between available supply and incoming demand. We find two main results: We first show that profit under any dynamic pricing strategy cannot exceed profit under the optimal static pricing policy (i.e., one which is agnostic of stochastic fluctuations in the system load). This result belies the prevalence of dynamic pricing in practice. Our second result explains the apparent paradox: we show that dynamic pricing is much more robust to fluctuations in system parameters compared to static pricing. Moreover, these results hold even if the monopolist maximizes welfare or throughput. Thus dynamic pricing does not necessarily yield higher performance than static pricing - however, it lets platforms realize the benefits of optimal static pricing, even with imperfect knowledge of system parameters.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133580245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incentive-Compatible Experimental Design","authors":"Panos Toulis, D. Parkes, Elery Pfeffer, James Y. Zou","doi":"10.1145/2764468.2764525","DOIUrl":"https://doi.org/10.1145/2764468.2764525","url":null,"abstract":"We consider the design of experiments to evaluate treatments that are administered by self-interested agents, each seeking to achieve the highest evaluation and win the experiment. For example, in an advertising experiment, a company wishes to evaluate two marketing agents in terms of their efficacy in viral marketing, and assign a contract to the winner agent. Contrary to traditional experimental design, this problem has two new implications. First, the experiment induces a game among agents, where each agent can select from multiple versions of the treatment it administers. Second, the action of one agent -- selection of treatment version -- may affect the actions of another agent, with the resulting strategic interference complicating the evaluation of agents. An incentive-compatible experiment design is one with an equilibrium where each agent selects its natural action, which is the action that maximizes the performance of the agent without competition (e.g., expected number of conversions if agent is assigned the advertising contract). Under a general formulation of block experiment designs, we identify sufficient conditions that guarantee incentive-compatible experiments.These conditions rely on the existence of statistics that can estimate how agents would perform without competition,and their use in constructing score functions to evaluate the agents. In the setting with no strategic interference, we also study the power of the design, i.e., the probability that the best agent wins, and show how to improve the power of incentive-compatible designs.From the technical side, our theory uses a range of statistical methods such as hypothesis testing, variance-stabilizing transformations and the Delta method, all of which rely on asymptotics.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128907225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leximin Allocations in the Real World","authors":"David Kurokawa, A. Procaccia, Nisarg Shah","doi":"10.1145/2764468.2764490","DOIUrl":"https://doi.org/10.1145/2764468.2764490","url":null,"abstract":"As part of a collaboration with a major California school district, we study the problem of fairly allocating unused classrooms in public schools to charter schools. Our approach revolves around the randomized leximin mechanism. We extend previous work to the classroom allocation setting, showing that the leximin mechanism is proportional, envy-free, efficient, and group strategyproof. We also prove that the leximin mechanism provides a (worst-case) 4-approximation to the maximum number of classrooms that can possibly be allocated. Our experiments, which are based on real data, show that a nontrivial implementation of the leximin mechanism scales gracefully in terms of running time (even though the problem is intractable in theory), and performs extremely well with respect to a number of efficiency objectives. We take great pains to establish the practicability of our approach, and discuss issues related to its deployment.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","authors":"T. Roughgarden, M. Feldman, M. Schwarz","doi":"10.1145/2764468","DOIUrl":"https://doi.org/10.1145/2764468","url":null,"abstract":"The papers in these Proceedings were presented at the Sixteenth ACM Conference on Economics and Computation (EC'15), held June 15-19, 2015 in Portland, Oregon, United States. Since 1999 the ACM Special Interest Group on Electronic Commerce (SIGecom) has sponsored EC, the leading scientific conference on advances in theory, systems, and applications at the interface of economics and computation, including applications to electronic commerce. The papers were selected by the program committee from among 220 submissions that were received by February 11, 2015. Paper submissions were invited in the following three non-exclusive focus areas: \u0000TF: Theory and Foundations \u0000AI: Artificial Intelligence and Applied Game Theory \u0000EA: Experimental, Empirical, and Applications \u0000 \u0000 \u0000 \u0000The call for papers attracted 220 distinct submissions that were deemed to satisfy the formatting requirements. Each paper was reviewed by at least three program committee members and two senior program committee members on the basis of significance, scientific novelty, technical quality, readability, and relevance to the conference. Following the tradition of recent iterations of the conference, the authors were asked to align their submission with one or two of the tracks. \u0000 \u0000Of the total of 220 submissions, 131 indicated TF track of them 48 were accepted, 25 indicated AI track, of these 8 were accepted, 23 indicated EA track of these 7 were accepted, 41 papers indicated two tracks, of these 9 papers were accepted. \u0000 \u000045 of the accepted papers are published in these Proceedings. For the remaining 27, at the authors' request, only abstracts are included along with pointers to full working papers that the authors guarantee to be reliable for at least two years. This option accommodates the practices of fields outside of computer science in which conference publishing can preclude journal publishing. We expect that many of the papers in these Proceedings will appear in a more polished and complete form in scientific journals in the future. \u0000 \u0000Papers were presented in parallel sessions with the exception of a plenary session with the following papers that received best paper and best student paper awards: \u0000 \u0000Best paper: Econometrics for Learning Agents, by Denis Nekipelov, Vasilis Syrgkanis, and Eva Tardos \u0000 \u0000Best student paper: Why Prices Need Algorithms, by Tim Roughgarden and Inbal Talgam-Cohen \u0000 \u0000To emphasize commonalities among the problems studied at EC, and to facilitate interchange at the conference, sessions were organized by topic rather than by focus area, and no indication of a paper's focus area(s) was given at the conference or appears in these proceedings. \u0000 \u0000In addition to the main technical program, EC'15 featured the following plenary sessions: \u0000ACM SIGecom Doctoral Dissertation Award talk, by Balasubramanian Sivan \u0000ACM SIGecom Test of Time Award talk, by Eric J. Friedman and Paul Resnick \u0000 \u0000 \u0000 \u0000Finally, EC also featured a poster session that included 19 papers. \u0000 \u0000W","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"506 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124504468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"At What Quality and What Price?: Eliciting Buyer Preferences as a Market Design Problem","authors":"J. Horton, Ramesh Johari","doi":"10.1145/2764468.2764516","DOIUrl":"https://doi.org/10.1145/2764468.2764516","url":null,"abstract":"Buyers and sellers in markets often signal to inform the other side about their preferences. Both have a mutual incentive to reveal information with respect to horizontal differentiation, but the case of vertical differentiation is more complex: a buyer claiming they place a high value on quality may attract more sellers of the right ``type'' increasing efficiency, but they might also simply pay a higher price. Although an efficiency-minded social planner may not care about higher prices, if this fear prevents a buyer from stating his of her true preferences, then desirable sorting caused by information-revelation may be unattainable. In this paper, we consider the buyer's vertical differentiation disclosure problem through the lens of a large field experiment conducted in an online labor market. A new signaling mechanism was introduced into the market that allowed buyers to state their relative preferences over price and quality. We find that the buyer signal improved seller-side sorting, with more sellers going to buyers of the right ``type''; the total number of applications also fell. However, sellers also clearly tailored their wages bid to the type of buyer they faced. Despite this markup, buyers chose to honestly disclose their preferences, suggesting they found the sorting effect to dominate the bargaining power effect.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115694075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assigning More Students to their Top Choices: A Tiebreaking Rule Comparison","authors":"I. Ashlagi, Afshin Nikzad, Assaf Romm","doi":"10.1145/2764468.2764540","DOIUrl":"https://doi.org/10.1145/2764468.2764540","url":null,"abstract":"School choice districts that implement stable matchings face various design issues that impact students' assignments to schools. We study properties of the rank distribution of students with random preferences, when schools use different tiebreaking rules to rank equivalent students. We find that under a multiple tiebreaking rule a vanishing fraction of students match to one of their top choices, in contrast to a single tiebreaking rule under which a constant fraction of students are assigned to one of their top choices. We find that when students can submit only a relatively short preference list, the multiple tiebreaking rule allows a constant fraction of students to match to one of their top choices, with only a \"small\" fraction of students remaining unmatched.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115638622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generalized Decision Scoring Rules: Statistical, Computational, and Axiomatic Properties","authors":"Lirong Xia","doi":"10.1145/2764468.2764518","DOIUrl":"https://doi.org/10.1145/2764468.2764518","url":null,"abstract":"We pursue a design by social choice, evaluation by statistics and computer science paradigm to build a principled framework for discovering new social choice mechanisms with desirable statistical, computational, and social choice axiomatic properties. Our new framework is called generalized decision scoring rules (GDSRs), which naturally extend generalized scoring rules [Xia and Conitzer 2008] to arbitrary preference space and decision space, including sets of alternatives with fixed or unfixed size, rankings, and sets of rankings. We show that GDSRs cover a wide range of existing mechanisms including MLEs, Chamberlin and Courant rule, and resolute, irresolute, and preference function versions of many commonly studied voting rules. We provide a characterization of statistical consistency for any GDSR w.r.t. any statistical model and asymptotically tight bounds on the convergence rate. We investigate the complexity of winner determination and a wide range of strategic behavior called vote operations for all GDSRs, and prove a general phase transition theorem on the minimum number of vote operations for the strategic entity to succeed. We also characterize GDSRs by two social choice normative properties: anonymity and finite local consistency.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116829855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}