Drivers of, and Barriers to, the Adoption of Mixed Reality in the Construction Industry of Developing Countries
Auteur(s): |
Ahsen Maqsoom
Muhammad Zulqarnain Muhammad Irfan Fahim Ullah Fahad K. Alqahtani Khurram Iqbal Ahmad Khan |
---|---|
Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 24 mars 2023, n. 4, v. 13 |
Page(s): | 872 |
DOI: | 10.3390/buildings13040872 |
Abstrait: |
Mixed Reality (MR) that combines elements of both augmented reality (AR) and virtual reality (VR) has great potential for use in the construction industry. However, its usage in construction projects in developing countries has not been widely researched. This study aims to examine the major drivers of, and barriers to, the adoption of MR technologies (MRTs) in the construction sector of developing countries. A mixed methodology that included both qualitative and quantitative data analysis was used. The literature review revealed 37 barriers to, and 41 drivers of, MR adoption. A questionnaire was then distributed to 220 randomly selected respondents from the pertinent construction industry, representing all major stakeholders. The relative importance index (RII) was used to rank the barriers and drivers in terms of significance. The results showed that the primary barriers to MR adoption are the high cost of initial investment, public perception of the technology being immature, limited demand, and difficulty accessing relevant experts’ knowledge. The key drivers of MR adoption include improved project knowledge, reduced overall project costs, low-cost and realistic training scenarios, reduced damage and development costs, and enhanced user experience. These findings provide insights into the major barriers and drivers of MR in the construction sector of developing countries and will help pertinent companies to focus their research and development (R&D) efforts on overcoming these barriers and promote their adoption to move towards the much sought-after construction automation and digitalization. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
0.42 MB
- Informations
sur cette fiche - Reference-ID
10728229 - Publié(e) le:
30.05.2023 - Modifié(e) le:
01.06.2023