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Digital Advantages for the Construction Industry

Author

Listed:
  • Plamen Yankov

    (University of Economics - Varna, Varna, Bulgaria)

  • Stefka Petrova

    (University of Economics - Varna, Varna, Bulgaria)

  • Svetlana Todorova

    (University of Economics - Varna, Varna, Bulgaria)

Abstract

Currently, the digital transformation is recognized as a source of many potential effects for the business organization from all sectors of the economy. The purpose of this study is to identify and highlight the possible advantages of the application of digital technologies in the construction sector. A scientometric analysis of the existing literature is performed. The scope of the study is given from three perspectives through three search criteria - digitalization, big data, and forecasting. A total of 2371 articles are abstracted. Then, the extracted data is visualized through Vosviewer software tool. The growth of publications increases significantly over the last decade. The results illustrate that the digitalization in the construction sector affect all aspects of construction projects, with the strongest impact on the architecture design and building information modelling. Big data in construction is associated with the data storage, data analytics and information management, during the whole life of the buildings. The third search criterion shows that construction companies most often forecast the total costs using regression analysis, machine learning algorithms, artificial neural networks, etc The research findings could support decision makers and practitioners with-depth understanding for the possible advantages of digital technologies in the construction industry. The current study is part of a larger project called "Digitalization of Economy in a Big Data Environment" BG05M2OP001-1.002-0002-C02.

Suggested Citation

  • Plamen Yankov & Stefka Petrova & Svetlana Todorova, 2021. "Digital Advantages for the Construction Industry," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, vol. 10(3), pages 21-32, December.
    • Handle: RePEc:vra:journl:v:10:y:2021:i:3:p:21-32
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    File URL: http://su-varna.org/journal/IJUSV-ESS/2021.10.3/21-32.pdf
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    References listed on IDEAS

    as
    1. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
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    More about this item

    Keywords

    construction industry; big data; digitalization; forecast; scientometric analysis; Vosviewer;
    All these keywords.

    JEL classification:

    • E02 - Macroeconomics and Monetary Economics - - General - - - Institutions and the Macroeconomy

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