A structural equation model for assessing determinants of contractors' digital technology adoption in renovation waste management based on the theory of planned behaviour

Yu, Shiwang (2023) A structural equation model for assessing determinants of contractors' digital technology adoption in renovation waste management based on the theory of planned behaviour. PhD thesis, University of Liverpool.

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Abstract

China's rapid urbanisation has generated a huge amount of renovation waste, with over 200 million tonnes of it generated in 2022. Contractors face difficulties in renovation waste management (RWM) due to intricate components and low waste output per project. Digital technology (DT) is perceived as effective for providing efficient solutions for RWM by helping to reduce waste and implement recycling. Most previous studies regarding the use of DT for RWM have focused on the technical application aspects, with little attention given to the determinants affecting contractors’ adoption of DT for RWM. Therefore, using a framework based on the theory of planned behaviour, this study develops a structural equation model (SEM) to assess the determinants of contractors’ adoption of DT for RWM. To develop the model, thirteen DT adoption determinants for RWM were initially identified and grouped into four categories of determinants: individual, technological, social, and managerial. A conceptual framework and research hypotheses were then proposed, and a survey of renovation contractors was conducted to collect data for statistical analysis and hypothesis validation. Descriptive analysis of means, standard deviations, skewness, and kurtosis confirmed normality of the data. Construct reliability and validity were analysed using Cronbach's alpha, composite reliability and average variance extracted values, and discriminant validity was evaluated with the Fornell-Larcker criterion and the Heterotrait-Monotrait ratio. With the hypothesis validated, a SEM model was developed and tested, with a goodness-of-fit value of 0.76. Scenario analysis was completed using fuzzy cognitive maps to examine the determinants' effectiveness on DT adoption in varying scenarios. The results of descriptive analysis show that moral norm and environmental awareness have the highest mean value of 4.080 and 4.090 respectively, while DT adoption behaviour has the lowest mean value of 3.435. The results of partial least squares structural equation modelling analysis indicate that: (1) DT adoption for RWM is impacted by individual determinants, including behavioural intention and perceived behavioural control; (2) behavioural intention is impacted by individual, social, and managerial determinants, namely attitude, subjective norm, moral norm, and government support; (3) attitude is impacted by technological and managerial determinants, namely perceived cost, perceived risk, perceived usefulness, perceived ease of use, and government support; (4) subjective norm is impacted by social determinants, including moral norm and environmental awareness; and (5) perceived behavioural control is impacted by managerial determinants, including facilitating condition, knowledge of DT, and government support. The results of scenario analysis show that individual determinates have the greatest effect on DT adoption with an output value of 0.667, followed by managerial determinants with an output value of 0.465. Technological determinants have the least effect on DT adoption with an output value of 0.014. The results of this research demonstrate the significance of individual determinants in influencing the adoption of DT by contractors for RWM. These insights can aid policymakers in the development of educational and training programs aimed at enhancing the attitudes, subjective norms, and behavioural intentions of contractors towards DT adoption. The study also confirms the importance of government support and facilitating conditions for the adoption of DT by contractors for RWM, thereby underscoring the need for government to develop effective supportive strategies and provide appropriate conditions at RWM sites. Finally, the study demonstrates DT’s usefulness and ease of use, which can inform policy decisions and encourage contractors to use DT for improving the performance and efficiency of RWM.

Item Type:	Thesis (PhD)
Uncontrolled Keywords:	Renovation waste management; Digital technology adoption behaviour; Theory of planned behaviour; Structural equation model; Renovation contractors; Circular economy; Fuzzy cognitive mapping; Scenario analysis.
Divisions:	Faculty of Science and Engineering > School of Engineering
Depositing User:	Symplectic Admin
Date Deposited:	02 Feb 2024 15:58
Last Modified:	02 Feb 2024 15:58
DOI:	10.17638/03176776
Supervisors:	Hao, Jianli Tang, Xiaonan Guo, Fangyu Di Sarno, Luigi
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3176776