Boutros, M. B. F.; El Hajj, C.; Martínez Montes, G. and Jawad, D. (2026) Managerial perceptions of emerging technology adoption in construction: Evidence from developing countries. Journal of Engineering, Design and Technology, 24(4), pp. 1057-1075. ISSN 1726-0531
Abstract
Purpose – This study aims to address the limited understanding of how emerging digital technologies reshape managerial functions and create adoption challenges in developing countries. It investigates the impact of four emerging technologies: artificial intelligence (AI), data analytics, cloud computing and robotic process automation (RPA) on managers' roles and the construction industry in developing countries. It captures the perspectives of managers from the construction and related sectors and examines the factors influencing their intentions to adopt these technologies. Design/methodology/approach – A structured questionnaire was designed based on the technology–organization–environment framework and distributed to managers across 15 developing countries. The study is based on data obtained from 325 managerial respondents operating in construction and related fields. Data were analyzed using structural equation modeling (SEM) with SmartPLS, following a two-step approach to assessing measurement and structural models. Findings – Findings are collected from managers in the construction and related industry across 15 countries in the Middle East and Africa. Data analytics (68%) and AI (63%) are perceived as having the greatest impact on managerial roles, followed by cloud computing (53%) and RPA (46%). SEM analysis shows ease of use (ß = 0.331, p < 0.05) and perceived improvement in management practices (ß = 0.501, p < 0.05) as the strongest predictors of adoption intentions. Regulatory constraints have a statistically significant but moderate effect (ß = 0.298, p < 0.05), while relative advantages, financial incentives and competitive pressure are non-significant. Research limitations/implications – These findings underscore the need for managers to develop competencies in AI, data analytics and cloud-based systems, and for the construction sector to invest in these technologies to remain competitive. Originality/value – Given that emerging technologies are new and rapidly evolving, and considering the additional challenges faced in developing countries, investigating the current adoption status is important. Its added value lies in capturing managerial perceptions from diverse developing regions, providing cross-country insights rarely addressed in Construction 4.0 research, which has predominantly centered on technical outcomes within isolated national settings.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | adoption; construction 4.0; developing countries; emerging technologies; impact; technology–organization–environment |
| Index terms: | Africa, relative advantage, construction 4.0, added value, artificial intelligence, construction industry, emerging technology, structural equation modelling, cloud computing, manager, Middle East, financial incentive, developing country, construction sector, robotic process automation, digital technology, questionnaire, evidence, management practice, methodology |
| Subjects: | computing systems, data collection methods, artificial intelligence, regions and continents, management, industry analysis, digital infrastructure, statistical analysis, innovation studies, practitioner, evaluation and assessment methods, digital engineering, innovation and technology management, economic analysis, automation and robotics, development economics, physical geography and landforms, research methods |
| Topics: | Geographical Context, Digital Applications, International Construction, Business Strategy, Research Practice, Roles and Professions |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here