Zhang, Y; Wang, Z; Lin, W; Minchin, R E and Xue, X (2022) Understanding the slow diffusion of alternative delivery systems using interpretive structural modelling. Construction Management and Economics, 40(6), pp. 459-476. ISSN 01446193
Abstract
The slow uptake of the alternative delivery systems (ADSs) can potentially waste an astronomical amount of precious public funds that can be used to meet other critical needs (e.g. education and healthcare). The existing literature mainly focussed on performance evaluation of the ADSs and few provided decision support to select ADSs matching a particular project’s characteristics or external environment. Nonetheless, there lacks of research exploring the slow diffusion of ADSs, especially a deep understanding of the interaction mechanisms of the influencing factors. This research aims to increase the use of ADSs in practice. To achieve the objective, based on the data retrieved from literature, case study and interviews, this study, therefore, aims to: identify the internal and external influencing factors; reveal the interplays of these factors using interpretive structural modelling (ISM) and analyse the driving and dependence power of the factors based on Matrice d’Impacts Croisés-Multiplication Appliquée á un Classement analysis (MICMAC). Based on the 25 identified factors, the ISM built a hierarchical structural model, which reveals the interaction mechanism of the factors and the fundamental factors. The MICMAC analysis discovered the high driving, high dependent, transitive/linkage and independent factors on the diffusion of ADSs. The findings contribute to the body of knowledge about what and how the factors influencing the slow diffusion of ADSs and help contractor administrators formulate effective strategies to improve the usage of ADSs.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | hierarchy model; highway construction; innovative delivery system; interpretive structure modelling |
| Index terms: | strategy, influencing factor, interview, performance evaluation, interpretive structural modelling, linkage, modelling, interaction, highway construction, decision support, body of knowledge, case study |
| Subjects: | knowledge management, civil engineering, decision analysis, behavioral psychology, data collection methods, performance measurement, data analysis and analytics, management, analytical methods, business, risk assessment |
| Topics: | Research Practice, Quality Management, Information Management, Business Strategy, Risk Management, Engineering Principles |
| Descriptive scope: | 4 PCEA |
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