| Author: | Oluleye, Ifeoluwa Benjamin |
| Title: | Assessment model and decision support system for the adoption and implementation of circular economy in the building construction industry of Nigeria |
| Advisors: | Chan, W. M. Daniel (BRE) |
| Degree: | Ph.D. |
| Year: | 2024 |
| Subject: | Construction industry -- Nigeria -- Management Construction industry -- Environmental aspects Commercial buildings -- Nigeria Sustainable construction Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Building and Real Estate |
| Pages: | xxvii, 391 pages : color illustrations |
| Language: | English |
| Abstract: | The building construction industry (BCI) significantly impacts environmental sustainability, contributing 33% of greenhouse gas emissions, 40% of waste generation, and 50% of the carbon footprint. To mitigate these effects, the circular economy (CE) concepts have been proposed, focusing on sustainable production and consumption through restorative and regenerative eco-design principles. Despite the potential positive influence of CE, its adoption and implementation in construction projects remains scarce, especially in developing regions like Africa. For example, Nigeria, a typical country in West Africa whose BCI contributes 35 million tonnes of solid waste and has the highest population of 250 million people in Africa, is still struggling with CE adoption. Notable reasons include the unfamiliarity of construction professionals with CE concepts, lack of information about the barriers and actionable factors to guide resource allocation for CE, lack of assessment methods and models for circularity performance, lack of diffusion of CE, and lack of an integrated system to guide actions and decision making. This research aims to develop an assessment model and a decision support system for CE adoption in Nigeria's BCI, with applications for similarly positioned countries. The objectives are: (1) To identify and assess the major barriers and critical success factors (CSFs) for CE adoption in the BCI from an international perspective; (2) To determine and evaluate the major barriers and critical success factors (CSFs) for CE adoption in the BCI of Nigeria; (3) To develop a data-driven hybrid model towards predicting CE diffusion in the BCI of Nigeria; (4) To determine the circularity level and impact potential through a case study of a conventional commercial building in Nigeria; and (5) To develop an automated knowledge-based decision support system (KBDSS) for CE adoption in building projects. To achieve Objective #1, international insights from 140 construction professionals across 39 countries revealed that organization, information technology, infrastructure and logistics barriers militate the widespread adoption of CE. The Mann-Whitney U test highlighted differences in regulatory, information technology, and economic barriers between developing and developed economies. Regarding the CSFs, exploratory factor analysis (EFA) identified 4 clustered principal success factors (PSFs): data-driven digital tools and circularity plans, capacity building and pre-demolition auditing, systemic circularity guidelines and commitment, and circular metric and secondary market development. According to the results of fuzzy synthetic evaluation (FSE) method, the top two PSFs in developed economies are systemic circularity guidelines and commitment, and circular metric and secondary market development, whereas data-driven digital tools and circularity plans, and capacity building and demolition monitoring are the top two PSFs in developing economies. The rank agreement analysis (RAA) unveiled a mixed consensus between developed and developing economies regarding the PSFs. The overall research findings accentuated the contextual nature of the barriers to CE integration in BCI, emphasizing the need for both generic and specific policy development. Also, findings of the PSFs emphasize the importance of considering specific context when applying them in practice. Based on the Objective #1 findings, Objective #2 examined the major barriers and CSFs for CE adoption in the BCI of Nigeria. The analysis pinpointed regulatory barriers as the foremost impediment to adopting CE, followed by infrastructure and logistics, and economic and market challenges. The study further revealed that establishing systemic circularity guidelines and a strong commitment are pivotal for successful CE adoption, alongside the development of circular metrics and a secondary market. Evaluation models were developed to aid policymakers and stakeholders in grasping the CE concepts and strategizing its application within the BCI. These valuable insights are expected to assist in formulating a robust plan for CE execution. The proposed models will guide resource allocation to overcome the potential barriers and reinforce the CSFs for CE initiatives development and implementation. Objective #3 delved deeper into developing a data-driven hybrid model for predicting CE diffusion in the BCI of Nigeria using the Technology, Organization and Environment (TOE) framework. Based on the partial least squares structural equation modelling (PLS-SEM) method, the results indicated that technological compatibility, relative technological advantages, top management support, and organizational readiness significantly influence CE diffusion in the BCI. Based on the machine learning (ML) algorithm evaluation metrics results, the random forest (RF) classifier was the optimal model for predicting CE diffusion in the BCI. Using the SHapley Additive exPlanation (SHAP) experiment, organizational readiness, top management support, and relative technological advantages are the most contributing features to predicting CE diffusion in the BCI. These findings necessitate understanding the level of circularity and impact potential of a case building in Nigeria for better CE decision-making. Objective #4 integrated life cycle assessment (LCA) from cradle to cradle (C2C) with a predictive building systemic circularity indicator (PBSCI) to assess the circularity level and environmental impact of a commercial building in Nigeria. The PBSCI results showed a base scenario circularity of 50.6%, while six other various scenarios ranged from 0% to 90%. The base scenario's environmental impact included 51,159.23 kg CO2/m2 global warming potential and 158.81 kg CFC-11eq ozone depletion. Scenario 2, with the highest circularity (90%) and lowest environmental impact, was recommended. This aids decision-makers in prioritizing CE adoption based on environmental impacts and end-of-life recyclability. Objective #5 involved developing an automated Knowledge-Based Decision Support System (KBDSS) for CE adoption in the BCI. This system integrates a decision support system (DSS) and an expert system (ES). Decision-Making Factors (DMFs) were identified from literature and expert reviews and categorized into six clustered groups comprising 32 individual DMFs. These were evaluated by experienced Nigerian construction experts using a two-round Delphi survey and analysed with the fuzzy synthetic evaluation (FSE) method to calculate the circularity index. Based on this index, the KBDSS was developed, incorporating action plans from literature and expert interviews. Built with an interactive Python-based app using the Streamlit framework, the KBDSS was validated by senior industry professionals through a case study. The KBDSS provides a robust empirical tool for evaluating various construction projects for CE adoption and offers action plans for effective implementation. The study highlights the necessity for generic and specific policies tailored to the barriers in different economies. The developed models will guide resource allocation, reinforce CSFs, aid strategic planning for CE adoption, and promote the prediction of CE diffusion levels in the BCI. Additionally, the study provides effective guidelines for product designers to evaluate the circularity level and impact potential of a product system at the beginning of life (BoL). The KBDSS offers a practical useful tool for industry professionals by enhancing decision-making processes in CE adoption. Although the study focused on Nigeria, its findings and policy implications are applicable to other developing countries facing similar challenges. The processes, actionable factors, guidelines, determinants, and decision-making factors identified in this study can serve as a comprehensive checklist for other developing countries aiming to adopt CE practices. The study has contributed to the existing body of knowledge particularly regarding CE adoption in developing economies and the research deliverables will benefit various CE project stakeholders and researchers in both professional and academic contexts. |
| Rights: | All rights reserved |
| Access: | open access |
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