{"title":"Two's company, platforms make a crowd: Talent identification in tripartite work arrangements in the gig economy","authors":"Jeroen Meijerink , Sandra Fisher , Anthony McDonnell , Sharna Wiblen","doi":"10.1016/j.hrmr.2024.101011","DOIUrl":null,"url":null,"abstract":"<div><p>The gig economy provides a novel setting that challenges many established ways of working. This paper unpacks the nature of talent identification in the gig economy through the role of three central actors; the online labor platform firm, the requester/customer and the gig worker. Talent identification in this context is especially novel as it emerges from tripartite relationships among independent economic actors, in contrast to traditional settings where talent identification is studied from a dyadic perspective (i.e., talented workers and the organization). We decipher the heterogeneity across online labor platforms and their gig workforces through the practice of talent identification. We provide an agenda to guide future research on the inclusive versus exclusive nature of talent identification in the gig economy as well as on online labor platforms as independent, yet powerful players who identify talents themselves alongside shaping talent identification processes between workers and hiring organizations. Accordingly, this paper extends the parameters of talent identification scholarship along with providing a different lens by which we examine work in the gig context.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"34 2","pages":"Article 101011"},"PeriodicalIF":8.2000,"publicationDate":"2024-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1053482224000019/pdfft?md5=49ad18310ab5ae7084b332d184713201&pid=1-s2.0-S1053482224000019-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Resource Management Review","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1053482224000019","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
The gig economy provides a novel setting that challenges many established ways of working. This paper unpacks the nature of talent identification in the gig economy through the role of three central actors; the online labor platform firm, the requester/customer and the gig worker. Talent identification in this context is especially novel as it emerges from tripartite relationships among independent economic actors, in contrast to traditional settings where talent identification is studied from a dyadic perspective (i.e., talented workers and the organization). We decipher the heterogeneity across online labor platforms and their gig workforces through the practice of talent identification. We provide an agenda to guide future research on the inclusive versus exclusive nature of talent identification in the gig economy as well as on online labor platforms as independent, yet powerful players who identify talents themselves alongside shaping talent identification processes between workers and hiring organizations. Accordingly, this paper extends the parameters of talent identification scholarship along with providing a different lens by which we examine work in the gig context.
期刊介绍:
The Human Resource Management Review (HRMR) is a quarterly academic journal dedicated to publishing scholarly conceptual and theoretical articles in the field of human resource management and related disciplines such as industrial/organizational psychology, human capital, labor relations, and organizational behavior. HRMR encourages manuscripts that address micro-, macro-, or multi-level phenomena concerning the function and processes of human resource management. The journal publishes articles that offer fresh insights to inspire future theory development and empirical research. Critical evaluations of existing concepts, theories, models, and frameworks are also encouraged, as well as quantitative meta-analytical reviews that contribute to conceptual and theoretical understanding.
Subject areas appropriate for HRMR include (but are not limited to) Strategic Human Resource Management, International Human Resource Management, the nature and role of the human resource function in organizations, any specific Human Resource function or activity (e.g., Job Analysis, Job Design, Workforce Planning, Recruitment, Selection and Placement, Performance and Talent Management, Reward Systems, Training, Development, Careers, Safety and Health, Diversity, Fairness, Discrimination, Employment Law, Employee Relations, Labor Relations, Workforce Metrics, HR Analytics, HRM and Technology, Social issues and HRM, Separation and Retention), topics that influence or are influenced by human resource management activities (e.g., Climate, Culture, Change, Leadership and Power, Groups and Teams, Employee Attitudes and Behavior, Individual, team, and/or Organizational Performance), and HRM Research Methods.