Technological, organisational and environmental determinants of smart contracts adoption: UK construction sector viewpoint. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Badi, Sulafa; Ochieng, Edward; Nasaj, Mohamed; Papadaki, Maria
• Is Part Of: Construction management and economics. Volume 39:Issue 1(2021)
• Page Start: 36
• Page End: 54
• Publication Date: 2021-01-02
• Subjects: Smart contract -- use intention -- technological -- organisational -- environmental -- the construction industry; Construction industry -- Management -- Periodicals; Construction industry -- Finance -- Periodicals; 338.47624
• DOI: 10.1080/01446193.2020.1819549
• Languages: English
• ISSNs: 0144-6193

Abstract

Abstract: This study aims to identify the factors that influence the adoption of smart contracts in the UK construction sector. A deductive questionnaire-based approach informed by the technology-organisation-environment (TOE) model is adopted. The framework is comprised of twelve independent variables and one dependent variable of smart contracts use intention. Ten hypotheses are developed to statistically test the causal relationships between the eleven variables of the research model. The study adopts a convenience sampling approach, with the population of interest being primarily drawn from among UK construction practitioners. The results generated from linear regression analysis suggest that the following four factors have a significant influence on the adoption of smart contracts: supply chain pressure, competitive pressure, top management support, and observability. The descriptive statistics obtained also offer a greater understanding of the perceptions and attitudes towards smart contracts across the UK construction sector. The results demonstrate the usefulness of a perception-based model that utilises the TOE framework to assess facets that influence the adoption of smart contracts. The study contributes to innovation diffusion studies in construction project management and supports "early adopters" at the footfall of the technology's diffusion curve.