{"title":"Knowledge collaboration and online medical teams’ performance: a multiple participation perspective","authors":"Siqi Wang","doi":"10.1108/ijppm-01-2024-0054","DOIUrl":null,"url":null,"abstract":"PurposeOnline medical teams (OMTs) have emerged as an innovative healthcare service mode that relies on the collaboration of doctors to produce comprehensive medical recommendations. This study delves into the relationship between knowledge collaboration and team performance in OMTs and examines the complex effects of participation patterns.Design/methodology/approachThe analysis uses a dataset that consists of 2,180 OMTs involving 8,689 doctors. Ordinary least squares regression with robust standard error is adopted for data analysis.FindingsOur findings demonstrate a positive influence of knowledge collaboration on OMT performance. Leader participation weakens the relationship between knowledge collaboration and team performance, whereas multidisciplinary participation strengthens it. Passive participation and chief doctor participation have no significant effect on the association between knowledge collaboration and OMT performance.Originality/valueThis study provides valuable insights into how knowledge collaboration shapes OMTs' performance and reveals how the participation of different types of members affects outcomes. Our findings offer important practical implications for the optimization of online health platforms and for enhancing the effectiveness of collaborative healthcare delivery.","PeriodicalId":47944,"journal":{"name":"International Journal of Productivity and Performance Management","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Productivity and Performance Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijppm-01-2024-0054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
PurposeOnline medical teams (OMTs) have emerged as an innovative healthcare service mode that relies on the collaboration of doctors to produce comprehensive medical recommendations. This study delves into the relationship between knowledge collaboration and team performance in OMTs and examines the complex effects of participation patterns.Design/methodology/approachThe analysis uses a dataset that consists of 2,180 OMTs involving 8,689 doctors. Ordinary least squares regression with robust standard error is adopted for data analysis.FindingsOur findings demonstrate a positive influence of knowledge collaboration on OMT performance. Leader participation weakens the relationship between knowledge collaboration and team performance, whereas multidisciplinary participation strengthens it. Passive participation and chief doctor participation have no significant effect on the association between knowledge collaboration and OMT performance.Originality/valueThis study provides valuable insights into how knowledge collaboration shapes OMTs' performance and reveals how the participation of different types of members affects outcomes. Our findings offer important practical implications for the optimization of online health platforms and for enhancing the effectiveness of collaborative healthcare delivery.
期刊介绍:
■Organisational design and methods ■Performance management ■Performance measurement tools and techniques ■Process analysis, engineering and re-engineering ■Quality and business excellence management Articles can address these topics theoretically or empirically through either a descriptive or critical approach. The co-Editors support articles that significantly bring new knowledge to the area both for academics and practitioners. The material for publication in IJPPM should be written in a manner which makes it accessible to its entire wide-ranging readership. Submissions of highly technical or mathematically-oriented papers are discouraged.