{"title":"不对称服务提供商竞争下的服务设计:人工智能服务的应用","authors":"Shiqiang Yu, Chunxiang Guo","doi":"10.1016/j.tre.2024.103424","DOIUrl":null,"url":null,"abstract":"<div><p>Recently, with the advancement of artificial intelligence (AI) technology (e.g. ChatGPT), more enterprises are incorporating AI into their customer service to reduce costs. However, the excessive use of AI technology will also reduce consumers’ satisfaction with services, and finding a balance between high-quality human service and cost-effective AI service is crucial for enterprises. To answer this question, this paper establishes a service competition model in which a service integrator (SI) procures services from an AI service provider (ASP) and a human service provider (HSP), and then combines them to offer integrated services to consumers. The findings reveal that, under certain conditions, the introduction of low-cost AI service by SI may result in increased product price. This occurs because ASP tends to set higher price for AI service to ensure its profitability per unit. When the consumer service sensitivity is moderate, SI can generate greater profits by skillfully designing blended service instead of relying on a single service. HSP encourages SI to adopt some of its competitors’ AI service when the consumer service sensitivity is low, while ASP does the opposite. Interestingly, a win–win scenario emerges, where all competing service providers earn higher profits compared to offering exclusive services, and SI profits and consumer welfare are also higher. In addition, service integration is essential to increase revenue for all parties involved, but the revenue increase is the same regardless of which party performs the service integration.</p></div>","PeriodicalId":8,"journal":{"name":"ACS Biomaterials Science & Engineering","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Service design under asymmetric service provider competition: Applications of AI services\",\"authors\":\"Shiqiang Yu, Chunxiang Guo\",\"doi\":\"10.1016/j.tre.2024.103424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Recently, with the advancement of artificial intelligence (AI) technology (e.g. ChatGPT), more enterprises are incorporating AI into their customer service to reduce costs. However, the excessive use of AI technology will also reduce consumers’ satisfaction with services, and finding a balance between high-quality human service and cost-effective AI service is crucial for enterprises. To answer this question, this paper establishes a service competition model in which a service integrator (SI) procures services from an AI service provider (ASP) and a human service provider (HSP), and then combines them to offer integrated services to consumers. The findings reveal that, under certain conditions, the introduction of low-cost AI service by SI may result in increased product price. This occurs because ASP tends to set higher price for AI service to ensure its profitability per unit. When the consumer service sensitivity is moderate, SI can generate greater profits by skillfully designing blended service instead of relying on a single service. HSP encourages SI to adopt some of its competitors’ AI service when the consumer service sensitivity is low, while ASP does the opposite. Interestingly, a win–win scenario emerges, where all competing service providers earn higher profits compared to offering exclusive services, and SI profits and consumer welfare are also higher. In addition, service integration is essential to increase revenue for all parties involved, but the revenue increase is the same regardless of which party performs the service integration.</p></div>\",\"PeriodicalId\":8,\"journal\":{\"name\":\"ACS Biomaterials Science & Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-01-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Biomaterials Science & Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554524000140\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Biomaterials Science & Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554524000140","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
摘要
近来,随着人工智能(AI)技术(如 ChatGPT)的发展,越来越多的企业将人工智能融入到客户服务中,以降低成本。然而,过度使用人工智能技术也会降低消费者对服务的满意度,如何在高质量的人工服务和低成本的人工智能服务之间找到平衡点对企业来说至关重要。为了回答这个问题,本文建立了一个服务竞争模型,即服务集成商(SI)从人工智能服务提供商(ASP)和人工服务提供商(HSP)采购服务,然后将两者结合起来向消费者提供综合服务。研究结果表明,在某些条件下,服务集成商引入低成本人工智能服务可能会导致产品价格上涨。这是因为 ASP 倾向于为人工智能服务设定更高的价格,以确保其单位利润率。当消费者对服务的敏感度较低时,SI 可以通过巧妙地设计混合服务而不是依赖单一服务来获得更大的利润。当消费者对服务的敏感度较低时,HSP 鼓励 SI 采用竞争对手的部分人工智能服务,而 ASP 则相反。有趣的是,双赢局面出现了,与提供独家服务相比,所有参与竞争的服务提供商都获得了更高的利润,SI 的利润和消费者福利也更高。此外,服务整合对增加参与各方的收入至关重要,但无论哪一方进行服务整合,收入的增加都是一样的。
Service design under asymmetric service provider competition: Applications of AI services
Recently, with the advancement of artificial intelligence (AI) technology (e.g. ChatGPT), more enterprises are incorporating AI into their customer service to reduce costs. However, the excessive use of AI technology will also reduce consumers’ satisfaction with services, and finding a balance between high-quality human service and cost-effective AI service is crucial for enterprises. To answer this question, this paper establishes a service competition model in which a service integrator (SI) procures services from an AI service provider (ASP) and a human service provider (HSP), and then combines them to offer integrated services to consumers. The findings reveal that, under certain conditions, the introduction of low-cost AI service by SI may result in increased product price. This occurs because ASP tends to set higher price for AI service to ensure its profitability per unit. When the consumer service sensitivity is moderate, SI can generate greater profits by skillfully designing blended service instead of relying on a single service. HSP encourages SI to adopt some of its competitors’ AI service when the consumer service sensitivity is low, while ASP does the opposite. Interestingly, a win–win scenario emerges, where all competing service providers earn higher profits compared to offering exclusive services, and SI profits and consumer welfare are also higher. In addition, service integration is essential to increase revenue for all parties involved, but the revenue increase is the same regardless of which party performs the service integration.
期刊介绍:
ACS Biomaterials Science & Engineering is the leading journal in the field of biomaterials, serving as an international forum for publishing cutting-edge research and innovative ideas on a broad range of topics:
Applications and Health – implantable tissues and devices, prosthesis, health risks, toxicology
Bio-interactions and Bio-compatibility – material-biology interactions, chemical/morphological/structural communication, mechanobiology, signaling and biological responses, immuno-engineering, calcification, coatings, corrosion and degradation of biomaterials and devices, biophysical regulation of cell functions
Characterization, Synthesis, and Modification – new biomaterials, bioinspired and biomimetic approaches to biomaterials, exploiting structural hierarchy and architectural control, combinatorial strategies for biomaterials discovery, genetic biomaterials design, synthetic biology, new composite systems, bionics, polymer synthesis
Controlled Release and Delivery Systems – biomaterial-based drug and gene delivery, bio-responsive delivery of regulatory molecules, pharmaceutical engineering
Healthcare Advances – clinical translation, regulatory issues, patient safety, emerging trends
Imaging and Diagnostics – imaging agents and probes, theranostics, biosensors, monitoring
Manufacturing and Technology – 3D printing, inks, organ-on-a-chip, bioreactor/perfusion systems, microdevices, BioMEMS, optics and electronics interfaces with biomaterials, systems integration
Modeling and Informatics Tools – scaling methods to guide biomaterial design, predictive algorithms for structure-function, biomechanics, integrating bioinformatics with biomaterials discovery, metabolomics in the context of biomaterials
Tissue Engineering and Regenerative Medicine – basic and applied studies, cell therapies, scaffolds, vascularization, bioartificial organs, transplantation and functionality, cellular agriculture