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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">109</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:3dc5f44e-8666-58db-bc76-a455210e8891</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">JUCS - Journal of Universal Computer Science</journal-title>
        <abbrev-journal-title xml:lang="en">jucs</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0948-695X</issn>
      <issn pub-type="epub">0948-6968</issn>
      <publisher>
        <publisher-name>Journal of Universal Computer Science</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.3217/jucs-017-10-1367</article-id>
      <article-id pub-id-type="publisher-id">29993</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>A.0 - GENERAL</subject>
          <subject>A.1 - INTRODUCTORY AND SURVEY</subject>
          <subject>A.m - MISCELLANEOUS</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>What is Productivity in Knowledge Work? - A Cross-Industrial View -</article-title>
      </title-group>
      <contrib-group content-type="authors">
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Erne</surname>
            <given-names>Rainer</given-names>
          </name>
          <email xlink:type="simple">rainer.erne@idp-lab.org</email>
          <xref ref-type="aff" rid="A1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>1</label>
        <addr-line content-type="verbatim">Leeds Metropolitan University, Leeds, United Kingdom</addr-line>
        <institution>Leeds Metropolitan University</institution>
        <addr-line content-type="city">Leeds</addr-line>
        <country>United Kingdom</country>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p>Corresponding author: Rainer Erne (<email xlink:type="simple">rainer.erne@idp-lab.org</email>).</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Academic editor: </p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2011</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>01</day>
        <month>06</month>
        <year>2011</year>
      </pub-date>
      <volume>17</volume>
      <issue>10</issue>
      <fpage>1367</fpage>
      <lpage>1389</lpage>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/1183025A-9043-5C27-BC73-A6EE3DBD0C38">1183025A-9043-5C27-BC73-A6EE3DBD0C38</uri>
      <uri content-type="zenodo_dep_id" xlink:href="https://zenodo.org/record/7001715">7001715</uri>
      <permissions>
        <copyright-statement>Rainer Erne</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="" xlink:type="simple">
          <license-p>This article is freely available under the J.UCS Open Content License.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p>Experts in specific professional domains form the fastest increasing workforce in OECD countries. Since this fact has been realised by management researchers, they have focussed on the question of how to measure and enhance the productivity of said workforce. According to the author's cross-industrial research undertaken in five different knowledge-intensive organisations, it is, however, not productivity in the traditional meaning of the term which is to be regarded as the crucial performance indicator in expert work. There rather exist multiple performance indicators, each of which is, moreover, differently graded as to its importance by different stakeholders. These findings, firstly, indicate the need for an alternative definition and way of measurement of productivity when the term is applied to knowledge work, and, secondly, they indicate the need for alternative management strategies in order to generate an increase in the productivity of knowledge workers. This paper describes and summarises the key performance indicators for expert work as well as the major 'managing forces' and their general strategies in assessing knowledge workers' performance across five different business segments. It further delineates consequences for the management of knowledge workers - consequences affecting various 'knowledge-intensive' industries.</p>
      </abstract>
    </article-meta>
  </front>
</article>
