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Bridging the digital divide gap in BIM technology adoption

Author(s):

Medium: journal article
Language(s): English
Published in: Engineering, Construction and Architectural Management, , n. 10, v. 25
Page(s): 1398-1416
DOI: 10.1108/ecam-05-2017-0091
Abstract:

Purpose

In the architecture, engineering and construction (AEC) industry, a “digital divide” exists in technology adoption because SMEs (who often form the bulk of AEC organisations in most countries) are thought to be “Late Majority” and “Laggards” in the adoption of Building information modelling (BIM) technology. Larger organisations not saddled with financial and socio-technical constraints might be considered as being among the “Early Majority” or “Innovators”. It is crucial to understand how these organisations differ in their speed of BIM technology adoption and the rationale for this difference. The purpose of this paper is to investigate the potential causes of the digital divide and suggest solutions for bridging the gap.

Design/methodology/approach

Using mixed research method, data were collected through online questionnaire survey of over 240 global respondents as well as a semi-structured interview with nine experts for which statistical and thematic analyses were used, respectively.

Findings

Organisations can be zoned into “layers” and “levels” of BIM technology adoption and their size is not always significant in terms of the speed at which they adopt BIM. The digital divide is unequal across layers/levels and large organisations utilise technologies across the BIM maturity levels depending on project circumstances. A conceptual model for BIM technology was developed to aid identification of the “Laggards” and “Late Majority” from the “Innovators” through which change agents can customise adoption strategies for each group.

Originality/value

The developed model could serve as a tool for engagement and policy making and it contributes to the body of knowledge in the field of BIM technology adoption.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1108/ecam-05-2017-0091.
  • About this
    data sheet
  • Reference-ID
    10576682
  • Published on:
    26/02/2021
  • Last updated on:
    26/02/2021