Skip to content
Research Article Open access CC BY 4.0

Diffusion of Innovations: The Status of Building Information Modelling Uptake in Nigeria

Mansur Hamma-adama, Huda Salman, Tahar Kouider

Journal of Scientific Research and Reports · pp. 1–12 · Published 23 Jan 2018

10.9734/JSRR/2017/38711

Abstract

Aim: This study evaluated Building Information Modelling (BIM) awareness and adoption in Nigeria through the line of enquiry known as the ‘diffusion of innovations’ and its possible uptake.   Study Design: The study is quantitative in nature and the primary data fetched through questionnaire survey within Nigerian construction industry. Place and Duration of the Study: Conducted within North-west, North-central and Lagos, Nigeria for a period of 4 months. Methodology: A quantitative approach was adopted to x-ray the Nigerian construction industry; a structured questionnaire was used across the Architecture, Engineering and Construction (AEC). The generated data were analysed through descriptive statistics (in percentages) and presented in charts and graphs. Results: The result revealed that 59.5% are aware of BIM technology; 22.8% are aware and currently using BIM and the remaining 17.7% neither aware nor using BIM; consequently, the industry was evaluated just within the Late Majority in terms of awareness and just entered the Early Majority in terms of BIM technology adoption. Conclusion: Nigeria is at least five years behind US, UK and South Africa. In addition to lagging behind by at least five years, it is also behind by about 10% and 50% for UK and US respectively. The study also discovers the most significant barriers to BIM adoption as lack of BIM experts and lack of collaboration by its team stakeholders. The industry is likely to take the UK pattern in adopting the BIM and Recommendations are made based on the findings of the research.

Adoption BIM collaboration diffusion of innovations integration

References (17)

  1. 1 Addressing individual perceptions: An application of the unified theory of acceptance and use of technology to building information modelling [DOI]
  2. 2 Contractors' Perception of the Factors Affecting Building Information Modelling (BIM) Adoption in the Nigerian Construction Industry [DOI]
  3. 3 Barriers of Implementing BIM in Construction Industry from the Designers' Perspective: A Hong Kong Experience
  4. 4 Analysis of the Adoption Rate of Building Information Modeling [BIM] and its Return on Investment [ROI] [DOI]
  5. 5 BIM in Malaysian Construction Industry: Status, Advantages, Barriers and Strategies to Enhance the Implementation Level [DOI]
  6. 6 Computing in Civil and Building Engineering
  7. 7 The Status Of Bim Adoption On Six Continents [DOI]
  8. 8 Project procurement systems in the attainment of sustainable construction [DOI]
  9. 9 Construction Project Administration in Practice [DOI]
  10. 10 Integrated project teams’ performance in managing unexpected change events [DOI]
  11. 11 A proposed approach to comparing the BIM maturity of countries [DOI]
  12. 12 BUILDING INFORMATION MODELLING AS A CONSTRUCTION MANAGEMENT TOOL IN NIGERIA [DOI]
  13. 13 Building Information Modelling and Collaboration in the Nigerian Construction Industry [DOI]
  14. 14 Assessment of BIM Implementation among MEP Firms in Nigeria [DOI]
  15. 15 Assessing the capacity of construction consultants to adopt building information modeling in Ghana
  16. 16 Journal of Civil Engineering and Management [DOI]
  17. 17 International Journal of Advances in Applied Sciences [DOI]

Cited by 30

Barriers to BIM implementation and ways forward to improve its adoption in the Nigerian AEC firms

S. Babatunde, Chika Udeaja, A. Adekunle · International Journal of Building Pathology and Adaptation · 2020

Macro-BIM Adoption Study: Establishing Nigeria’s BIM Maturity

Mansur Hamma-adama, T. Kouider · The Construction Industry in the Fourth Industrial Revolution · 2019

Research on BIM technology diffusion barrier - based on innovation diffusion theory

Tao Chen, Y. Ni · IOP Conference Series: Earth and Environment · 2019

Showing 26 of 30 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

77

Page views

0

PDF downloads

10

Outbound clicks

30

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.