Hao Yu , Min Huang , Yang Song , Xingwei Wang , Xiaohang Yue
{"title":"充分利用私人停车位:不失策略的双重拍卖交错共享计划","authors":"Hao Yu , Min Huang , Yang Song , Xingwei Wang , Xiaohang Yue","doi":"10.1016/j.trb.2024.103102","DOIUrl":null,"url":null,"abstract":"<div><div>Platform-intermediated Private Parking Slot Sharing (PPSS) is broadly deemed a viable avenue to alleviate parking problems in metropolises. Despite a captivating future where PPSS will be as convenient as public parking today, tension is mounting in practice concerning how to efficiently match and price self-interested suppliers and demanders with incomplete information. To reconcile this tension, this paper delves into the nuances of PPSS operations and proposes double auction-based solutions that embed staggered sharing to integrate fragmented non-commute-driven demand. Confronting the intertwined difficulties of temporally heterogeneous and incompatible demands imposed by staggered sharing on auction mechanism design, we first propose a Demand Classification-based Trade Reduction (DCTR) auction mechanism that teases apart the conflated demands through the idea of “divide and conquer”. We prove theoretically that the DCTR auction mechanism satisfies Strategy-Proofness (SP), Budget Balance (BB), and Individual Rationality (IR) in general, and Asymptotic Efficiency (AsE) when demand categories are finite. To cut down the welfare loss due to distributed trade reduction in the DCTR auction mechanism when demands are diversified, we propose a family of Group Buying-based Trade Reduction (GBTR) auction mechanisms that unify demands through a preceding grouping process and conduct one unified trade reduction only. We contrive alternative group bid determination and trade reduction rules to accommodate distinct market conditions. To strengthen privacy preservation and relieve the strategy identification burden of cognitively limited bidders, we further design the Double-Clock implementations of the GBTR auction mechanisms (DC-GBTR) that additionally satisfy Unconditional Winner Privacy (UWP) and Obvious Strategy-Proofness (OSP). A hybrid mechanism is further designed to enable the integration of mechanisms that could induce budget deficits and orchestrate different auctions by automatically selecting the proper one depending on market conditions while ensuring BB in expectation. Extensive experimental results highlight the merits of incorporating staggered sharing in auction design, shed light on how to choose among alternative auctions to cater to distinct market conditions, showcase the superiority and potential of hybridization, and deduce managerial insights from the perspectives of different stakeholders to facilitate the navigation of PPSS marketplaces.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"191 ","pages":"Article 103102"},"PeriodicalIF":5.8000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Making the most of your private parking slot: Strategy-proof double auctions-enabled staggered sharing schemes\",\"authors\":\"Hao Yu , Min Huang , Yang Song , Xingwei Wang , Xiaohang Yue\",\"doi\":\"10.1016/j.trb.2024.103102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Platform-intermediated Private Parking Slot Sharing (PPSS) is broadly deemed a viable avenue to alleviate parking problems in metropolises. Despite a captivating future where PPSS will be as convenient as public parking today, tension is mounting in practice concerning how to efficiently match and price self-interested suppliers and demanders with incomplete information. To reconcile this tension, this paper delves into the nuances of PPSS operations and proposes double auction-based solutions that embed staggered sharing to integrate fragmented non-commute-driven demand. Confronting the intertwined difficulties of temporally heterogeneous and incompatible demands imposed by staggered sharing on auction mechanism design, we first propose a Demand Classification-based Trade Reduction (DCTR) auction mechanism that teases apart the conflated demands through the idea of “divide and conquer”. We prove theoretically that the DCTR auction mechanism satisfies Strategy-Proofness (SP), Budget Balance (BB), and Individual Rationality (IR) in general, and Asymptotic Efficiency (AsE) when demand categories are finite. To cut down the welfare loss due to distributed trade reduction in the DCTR auction mechanism when demands are diversified, we propose a family of Group Buying-based Trade Reduction (GBTR) auction mechanisms that unify demands through a preceding grouping process and conduct one unified trade reduction only. We contrive alternative group bid determination and trade reduction rules to accommodate distinct market conditions. To strengthen privacy preservation and relieve the strategy identification burden of cognitively limited bidders, we further design the Double-Clock implementations of the GBTR auction mechanisms (DC-GBTR) that additionally satisfy Unconditional Winner Privacy (UWP) and Obvious Strategy-Proofness (OSP). A hybrid mechanism is further designed to enable the integration of mechanisms that could induce budget deficits and orchestrate different auctions by automatically selecting the proper one depending on market conditions while ensuring BB in expectation. Extensive experimental results highlight the merits of incorporating staggered sharing in auction design, shed light on how to choose among alternative auctions to cater to distinct market conditions, showcase the superiority and potential of hybridization, and deduce managerial insights from the perspectives of different stakeholders to facilitate the navigation of PPSS marketplaces.</div></div>\",\"PeriodicalId\":54418,\"journal\":{\"name\":\"Transportation Research Part B-Methodological\",\"volume\":\"191 \",\"pages\":\"Article 103102\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part B-Methodological\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0191261524002261\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part B-Methodological","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0191261524002261","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Making the most of your private parking slot: Strategy-proof double auctions-enabled staggered sharing schemes
Platform-intermediated Private Parking Slot Sharing (PPSS) is broadly deemed a viable avenue to alleviate parking problems in metropolises. Despite a captivating future where PPSS will be as convenient as public parking today, tension is mounting in practice concerning how to efficiently match and price self-interested suppliers and demanders with incomplete information. To reconcile this tension, this paper delves into the nuances of PPSS operations and proposes double auction-based solutions that embed staggered sharing to integrate fragmented non-commute-driven demand. Confronting the intertwined difficulties of temporally heterogeneous and incompatible demands imposed by staggered sharing on auction mechanism design, we first propose a Demand Classification-based Trade Reduction (DCTR) auction mechanism that teases apart the conflated demands through the idea of “divide and conquer”. We prove theoretically that the DCTR auction mechanism satisfies Strategy-Proofness (SP), Budget Balance (BB), and Individual Rationality (IR) in general, and Asymptotic Efficiency (AsE) when demand categories are finite. To cut down the welfare loss due to distributed trade reduction in the DCTR auction mechanism when demands are diversified, we propose a family of Group Buying-based Trade Reduction (GBTR) auction mechanisms that unify demands through a preceding grouping process and conduct one unified trade reduction only. We contrive alternative group bid determination and trade reduction rules to accommodate distinct market conditions. To strengthen privacy preservation and relieve the strategy identification burden of cognitively limited bidders, we further design the Double-Clock implementations of the GBTR auction mechanisms (DC-GBTR) that additionally satisfy Unconditional Winner Privacy (UWP) and Obvious Strategy-Proofness (OSP). A hybrid mechanism is further designed to enable the integration of mechanisms that could induce budget deficits and orchestrate different auctions by automatically selecting the proper one depending on market conditions while ensuring BB in expectation. Extensive experimental results highlight the merits of incorporating staggered sharing in auction design, shed light on how to choose among alternative auctions to cater to distinct market conditions, showcase the superiority and potential of hybridization, and deduce managerial insights from the perspectives of different stakeholders to facilitate the navigation of PPSS marketplaces.
期刊介绍:
Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.