<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T19:49:49Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/107353" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/107353</identifier><datestamp>2022-10-06T12:04:30Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Donna H. Rhodes.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Wei, Wei (Scientist in system design and management)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Engineering Systems Division.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">System Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Engineering Systems Division</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Institute for Data, Systems, and Society</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2017-03-10T15:06:43Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2017-03-10T15:06:43Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/107353</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">973329958</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, System Design and Management Program, 2016.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 97-98).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Motivated by the aspiration to extrapolate optimal combinations of job characteristics that may minimize employee turnover rate, this research investigates impacts of specific workplace policies in autonomy, performance feedback, skill and task variety, identity, and significance. A questionnaire is designed to discover what the most effective talent management strategies are to attract, develop and retain top tier talents in STEM fields. In this thesis, the targeted demographics are professionals who hold at least one bachelor's degree in STEM fields or work in STEM fields. By collecting, organizing, and analyzing the survey data set, the research attempts to identify series of workplace autonomy policies and work task characteristics that are appealing to the targeted demographics. The thesis analyzes the respondent dataset using three approaches. Firstly, chisquared tests suggest that the dataset exhibits similar job characteristic preference patterns within each demographic dimension (i.e. generation, gender, household composition, education and professional backgrounds). Secondly, conditional probability tests indicate respondents' acquisition and retention rates associated with specific policies. Lastly, the cross-tabulated contingency tables summarize the insights for optimizing performance review frequency and methods. After investigating questionnaire participants' responses, this thesis enriches the data set with literature review findings. This thesis proposes practical recommendations to improve existing workplace autonomy policies based on the research insights.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Wei Wei.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Engineering and Management</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">98 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Institute for Data, Systems, and Society.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">System Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Engineering Systems Division.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">An investigation of optimal job characteristics for recruiting and retaining Science, Technology, Engineering, and Mathematics (STEM) professionals</dim:field>
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   	&lt;Title>An investigation of optimal job characteristics for recruiting and retaining Science, Technology, Engineering, and Mathematics (STEM) professionals&lt;/Title>
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   	&lt;PublicationDate>2016&lt;/PublicationDate>
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        	&lt;DisplayName>Wei, Wei (Scientist in system design and management)&lt;/DisplayName>
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    &lt;Keyword>Institute for Data, Systems, and Society.&lt;/Keyword>
    &lt;Keyword>System Design and Management Program.&lt;/Keyword>
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   	&lt;Abstract>Motivated by the aspiration to extrapolate optimal combinations of job characteristics that may minimize employee turnover rate, this research investigates impacts of specific workplace policies in autonomy, performance feedback, skill and task variety, identity, and significance. A questionnaire is designed to discover what the most effective talent management strategies are to attract, develop and retain top tier talents in STEM fields. In this thesis, the targeted demographics are professionals who hold at least one bachelor&amp;apos;s degree in STEM fields or work in STEM fields. By collecting, organizing, and analyzing the survey data set, the research attempts to identify series of workplace autonomy policies and work task characteristics that are appealing to the targeted demographics. The thesis analyzes the respondent dataset using three approaches. Firstly, chisquared tests suggest that the dataset exhibits similar job characteristic preference patterns within each demographic dimension (i.e. generation, gender, household composition, education and professional backgrounds). Secondly, conditional probability tests indicate respondents&amp;apos; acquisition and retention rates associated with specific policies. Lastly, the cross-tabulated contingency tables summarize the insights for optimizing performance review frequency and methods. After investigating questionnaire participants&amp;apos; responses, this thesis enriches the data set with literature review findings. This thesis proposes practical recommendations to improve existing workplace autonomy policies based on the research insights.&lt;/Abstract>
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