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        <title type="main" level="a">A Systematic Literature Review to Identify a Methodological Approach for Use in the Modelling and Forecasting of Capital Expenditure of Hyperscale Data Centres</title>
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          <persName n="1" ref="https://orcid.org/0000-0002-8026-3796" type="ORCID">
            <forename>David</forename>
            <surname>King</surname>
            <placeName type="affiliation">Anglia Ruskin University, United Kingdom</placeName>
          </persName>
          <persName n="2" ref="https://orcid.org/0000-0001-8889-8019" type="ORCID">
            <forename>Nadeeshani</forename>
            <surname>Wanigarathna</surname>
            <placeName type="affiliation">Anglia Ruskin University, United Kingdom</placeName>
          </persName>
          <persName n="3" ref="https://orcid.org/0000-0002-8883-9673" type="ORCID">
            <forename>Keith</forename>
            <surname>Jones</surname>
            <placeName type="affiliation">Anglia Ruskin University, United Kingdom</placeName>
          </persName>
          <persName n="4" ref="https://orcid.org/0000-0003-2872-9437" type="ORCID">
            <forename>Joseph</forename>
            <surname>Ofori-Kuragu</surname>
            <placeName type="affiliation">Anglia Ruskin University, United Kingdom</placeName>
          </persName>
        </author>
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          <resp>This is a section of <title>CONVR 2023 - Proceedings of the 23rd International Conference on  Construction Applications of Virtual Reality </title>(DOI: <idno type="DOI">10.36253/979-12-215-0289-3</idno>) by </resp>
          <name>Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi</name>
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      <publicationStmt>
        <publisher>Firenze University Press</publisher>
        <pubPlace>Florence</pubPlace>
        <date when="2023">2023</date>
        <idno type="DOI">https://doi.org/10.36253/10.36253/979-12-215-0289-3.37</idno>
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          <p>Available for academic research purposes</p>
          <p>Open Access</p>
          <p>Copyright Author(s)</p>
          <licence source="text" target="https://creativecommons.org/licenses/by-nc/4.0/legalcode">
            <p>Content licence CC BY-NC 4.0</p>
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        <p>This is original content, published for academic research purposes</p>
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      <abstract xml:lang="en">
        <p>The theme of ‘Managing the digital transformation of the construction industry’ emphasises the importance of considering various dimensions of digitalisation and optimising the built environment. This review aims to present methodological approaches from existing literature that elucidate location-related factors impacting the capital cost of data centres. These findings facilitate adjustments to historical cost data when estimating total costs for new data centres. A systematic literature review method was employed to ensure an objective and comprehensive synthesis. In conjunction with Bayes's theory, this review identifies that a Delphi methodology is the most suitable methodological approach for forecasting and modelling capital expenditure for hyper-scale data centres. The methodology enables collective decision-making and consensus building, recognising the stakeholder's pivotal role in shaping the future of data centres. These findings offer valuable insights for researchers and practitioners in forming a methodological approach for further investigations into the location-related factors impacting the capital cost of data centres. Embracing this knowledge allows us to align research and practice, ensuring that these practices become integral to shaping the future of data centres and the digitalisation and optimisation of the built environment</p>
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        <keywords>
          <list>
            <item>cost; decision analysis; forecasting</item>
            <item>data centres</item>
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      <p>It is available online at https://doi.org/10.36253/10.36253/979-12-215-0289-3.37<ref target="https://doi.org/10.36253/10.36253/979-12-215-0289-3.37" /></p>
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