Abstract

The small and medium-sized enterprises (SMEs) which are the backbone of any economy are often on the disadvantaged side of the digital divide in the construction industry. With the advent of building information modelling (BIM), the SMEs are facing challenges and are slow with its uptake. Hitherto, extant research studies on BIM have focused primarily on the large firms and there is an observed trend of underrepresentation of the SMEs in BIM studies. Thus, this paper aims to investigate the major drivers of sustainable adoption of Building Information Modelling in SMEs and the dynamics of these drivers in developing countries using interpretive structural modelling approach and Matrice d’Impacts croises-multipication applique a classement (MICMAC) analysis. The findings reveal that organizational readiness is of utmost importance for the proliferation of BIM in SMEs. Also, the independent drivers which are the most important drivers consist of BIM characteristics, internal and external environment drivers and thus portray the BIM adoption as a complex socio-technical system. This study categorizes the drivers for easy intervention of SMEs’ managers and policymakers. It contributes to the nascent studies of BIM adoption in SMEs of developing countries.

Highlights

  • The Construction Industry is complex, and this can be related to the inefficiency of the operation, uncertainties, and interdependence making way for an increase in complexity of the industry as opined by Dubois and Gadde [1]

  • The need for sustainable adoption of building information modelling (BIM) in the small and medium-sized enterprises (SMEs) of developing countries cannot be overemphasized because they have innate potentials and represent the backbone of the economy

  • Sustainable adoption of BIM in the Nigerian SMEs is necessary in order to bridge the digital divide between the SMEs and the large firms that are BIM compliant

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Summary

Introduction

The Construction Industry is complex, and this can be related to the inefficiency of the operation, uncertainties, and interdependence making way for an increase in complexity of the industry as opined by Dubois and Gadde [1]. The culture of the industry, increase in population, increase in stakeholders, increase in demand, lack of information reuse and management, and poor cross-disciplinary communications contributed to this complexity. This has been having a tremendous effect on the productivity and the performance of the industry which has been a subject of criticisms. A more integrated approach has been recommended as one of the ways to curb the ineffectiveness of the industry

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