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Cross-functional Team Formation In The Perspective Of Team Performance

Posted on:2014-04-03Degree:DoctorType:Dissertation
Country:ChinaCandidate:X ZhangFull Text:PDF
GTID:1269330422468943Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
In the face of modern competitive market environment, the enterprises ororganizations have to rely on project management to realize their strategic goals forthe purpose of encouraging innovative management and handling complexity.However, no successful project management can do without an effectivecross-functional team (CFT) and collaborative team members. And in practice, theenterprises or organizations execute internal development strategy or externalacquisition strategy to obtain team staff by considering their uniqueness and strategicvalue. To achieve optimal team effectiveness and project outcome, it is still a bigchallenge to form an effective CFT in different staffing strategies.To address the CFT staffing by using internal development strategy that requiresmultiple competence of members, a multi-objective team formation model is proposedthat considers the comprehensive capabilities and interpersonal relationships of allmembers. The Myers-Briggs Type Indicator and Kolbe conative index are employedto model team member relationship and team cooperation, which are traditionallyhard to be quantified, and the fuzzy rating methods are applied to evaluate membercapabilities. Additionally, the proposed model is applied to different team formationscenarios in new product development, software development, and integrated projectdelivery, and the Multi-objective Particle Swarm Optimization algorithm isimplemented to search for Pareto solutions that represent the alternatives for optimalteam composition.Although the CFT formation that develops members from the organizationinternals has examined the issue of individual selection, the selection of functionalclusters in the external acquisition strategy still need to be handled. Therefore, anAnalytic Network Process (ANP) model is established for the selection of functionalcluster compositions that sets different and highly interactive assessment criteria inthe context of the external acquisition. And sensitivity analysis is implemented tocheck the robust of the ANP raking, thus the optimal team formation scheme could beprepared.Furthermore, to check the effectiveness of the CFT formation, a teamperformance prediction model is proposed by using team trust formation factors as input variables. The regression between team trust and performance is built byadopting empirical study and the Support Vector Machine regression (SVR), whichovercomes the weakness of traditional regression methods in addressing multiplevariables. In addition, the model considers both team structural&contextual factorsand project process factors of team trust, and the measures for each trust factor andperformance are developed from the existing literature and empirical study. Theperformance prediction model is then established by using significant factors thatobtain from the regression analysis as the inputs.The proposed methods for the CFT formation and team performance prediction indifferent staffing strategies could provide theoretical references for the CFT memberor functional cluster selection and performance prediction. And the research could notonly help enterprises or organizations obtain optimal team compositions and improvethe quality of combined members, but also give support to the predition andmonitoring of team performance in work.
Keywords/Search Tags:Cross-functional team formation, Team performance, Teamtrust, Multi-objective Particle Swarm Optimization, Analytic Network Process, Support Vector Machine
PDF Full Text Request
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