{"title":"服务动态供应与匹配的平台生态系统演化模型","authors":"Xinyue Zhou;Jianmao Xiao;Xiao Xue;Shizhan Chen;Zhiyong Feng","doi":"10.1109/TCSS.2023.3332064","DOIUrl":null,"url":null,"abstract":"Governance strategies related to platform ecosystems have become a vital issue for developing a smart society, attracting governments’ and practitioners’ attention. Under the consensus of “service as a commodity” and “platform as market,” service providers, platforms, services, and various supply demand matching methods form new supply processes. These elements are continuously and uncertainly changing during supply demand matching, which makes platform ecosystems constantly evolving. However, when multiple supply demand matching methods coexist such as service composition and crossover fusion, dynamic service supply and matching cause dilemmas in the platform ecosystem governance. To this end, this article proposes a model for platform ecosystem evolution with four dynamics: 1) dynamics between ISPs (services) and platforms; 2) dynamics between users and platforms; 3) dynamics among services; and 4) dynamics between services and demands. The model considers multiple supply demand matching methods and considers both fully online services and incompletely online services. Then, according to the market operation law, we design six evaluation indexes such as demand matching rate, service diversity, and market concentration to evaluate the efficiency of the platform market. Finally, a computational experiment system is established to simulate the dynamic supply and matching processes. The experimental results show that reducing the cost of service release can increase the amount of demand and the diversity of services, and the monopoly of digital platforms is a natural trend to improve the efficiency of supply and demand. The model provides a reference for the governance of platform ecosystems and lays a foundation for further research on the value cocreation mechanism of platform ecosystems.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Platform Ecosystem Evolution Model With Service Dynamic Supply and Matching\",\"authors\":\"Xinyue Zhou;Jianmao Xiao;Xiao Xue;Shizhan Chen;Zhiyong Feng\",\"doi\":\"10.1109/TCSS.2023.3332064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Governance strategies related to platform ecosystems have become a vital issue for developing a smart society, attracting governments’ and practitioners’ attention. Under the consensus of “service as a commodity” and “platform as market,” service providers, platforms, services, and various supply demand matching methods form new supply processes. These elements are continuously and uncertainly changing during supply demand matching, which makes platform ecosystems constantly evolving. However, when multiple supply demand matching methods coexist such as service composition and crossover fusion, dynamic service supply and matching cause dilemmas in the platform ecosystem governance. To this end, this article proposes a model for platform ecosystem evolution with four dynamics: 1) dynamics between ISPs (services) and platforms; 2) dynamics between users and platforms; 3) dynamics among services; and 4) dynamics between services and demands. The model considers multiple supply demand matching methods and considers both fully online services and incompletely online services. Then, according to the market operation law, we design six evaluation indexes such as demand matching rate, service diversity, and market concentration to evaluate the efficiency of the platform market. Finally, a computational experiment system is established to simulate the dynamic supply and matching processes. The experimental results show that reducing the cost of service release can increase the amount of demand and the diversity of services, and the monopoly of digital platforms is a natural trend to improve the efficiency of supply and demand. The model provides a reference for the governance of platform ecosystems and lays a foundation for further research on the value cocreation mechanism of platform ecosystems.\",\"PeriodicalId\":13044,\"journal\":{\"name\":\"IEEE Transactions on Computational Social Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computational Social Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10391267/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10391267/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
A Platform Ecosystem Evolution Model With Service Dynamic Supply and Matching
Governance strategies related to platform ecosystems have become a vital issue for developing a smart society, attracting governments’ and practitioners’ attention. Under the consensus of “service as a commodity” and “platform as market,” service providers, platforms, services, and various supply demand matching methods form new supply processes. These elements are continuously and uncertainly changing during supply demand matching, which makes platform ecosystems constantly evolving. However, when multiple supply demand matching methods coexist such as service composition and crossover fusion, dynamic service supply and matching cause dilemmas in the platform ecosystem governance. To this end, this article proposes a model for platform ecosystem evolution with four dynamics: 1) dynamics between ISPs (services) and platforms; 2) dynamics between users and platforms; 3) dynamics among services; and 4) dynamics between services and demands. The model considers multiple supply demand matching methods and considers both fully online services and incompletely online services. Then, according to the market operation law, we design six evaluation indexes such as demand matching rate, service diversity, and market concentration to evaluate the efficiency of the platform market. Finally, a computational experiment system is established to simulate the dynamic supply and matching processes. The experimental results show that reducing the cost of service release can increase the amount of demand and the diversity of services, and the monopoly of digital platforms is a natural trend to improve the efficiency of supply and demand. The model provides a reference for the governance of platform ecosystems and lays a foundation for further research on the value cocreation mechanism of platform ecosystems.
期刊介绍:
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.