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    The Factors Affecting the Growth of the Smart Buildings Industry in the Irish Commercial Buildings Sector

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    Padraic Cremins - 10564534 - B9RS102 - Smart Buildings (1).pdf (1.740Mb)
    Author
    Cremins, Padraig
    Date
    2022-05
    Degree
    Master of Business Administration (Cloud Computing)
    URI
    https://esource.dbs.ie/handle/10788/4394
    Publisher
    Dublin Business School
    Rights holder
    http://esource.dbs.ie/copyright
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    Abstract
    Smart Buildings are currently, and will continue to be one of the most important trends in the built environment and construction industries. While such buildings can bring many benefits to society, the environment, owners, occupiers, and developers, they bring with them risks and barriers to adoption. The purpose of this exploratory, qualitative research project is to identify the factors, within the Technology Acceptance Model (TAM), that affect the growth of the Smart Buildings industry in the context of the Irish commercial buildings sector. Semi-structured interviews with some industry-leading experts in the fields of design, engineering, and facility management in Ireland were used as the data gathering tool. The factors that were identified as limiting the growth of the industry were, the usefulness of the technology, generally inadequate knowledge levels amongst most of the key stakeholders, inappropriate procurement models in the Irish construction industry, insufficient market understanding, perceived additional cost and cyber-security. This research project provides valuable insights to many of the stakeholders involved in the Smart Buildings industry in Ireland. Design consultants can gain a deeper understanding of the market need and facility managers’ and occupant’s concerns. System integrators will come to see the areas that they need to address to capitalise on market potential. All stakeholders on the other hand, will identify a need to increase knowledge levels. Finally, the construction industry will see a need to redefine its procurement models and the academic community can benefit from the insights provided to support future research in this ever-growing area.
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