Circular supply chain practices and sustainable development goals : a moderator of machine learning analytics / Nik Athirah Nik Mahdi
Material type:
TextPublisher: Kuantan, Pahang : UMP, 2024Copyright date: 2024Description: xvi, 205 pages : illustration ; 1 CD-ROMContent type: - text
- unmediated
- volume
- THE0009908 (Local)
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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Thesis
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UMPLIB GAMBANG | Reference | FIM .A84 2024 r Thesis (Browse shelf(Opens below)) | 1 | Not for loan | T000003261 | ||
Thesis
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UMPLIB GAMBANG | CD13633 (Browse shelf(Opens below)) | 1 | In Transit | T000003262 |
Faculty of Industrial Management
Thesis (Master of Science) -- Universiti Malaysia Pahang – 2024
Includes bibliographical references
Sustainable development goals (SDG) are a universal call for action to eradicate poverty, protect the planet, and ensure that all people enjoy peace and prosperity by 2030. However, the current Malaysian SDG index portrayed that a significant portion of the SDG goals are on track, with a notable percentage showing limited progress, while the remainder is worsening. Malaysia is a developing country with manufacturing as the core sector, which has led to concerns about sustainability issues. Thus, this study aims to investigate the relationship between circular supply chain practices (CSCP) and SDG. Additionally, SDG is known as widely defined, ambiguous, incoherent, and difficult to measure, execute, and observe, which adds to uncertainty about practice and SDG reporting. This led to less information to report of the SDG status among practitioners. Thus, as a mediating role, green growth (GG) can provide adaptable practical recommendations for practitioners to implement CSCP by reducing carbon emission and pollution, energy and resources efficiency, and biodiversity and ecosystem services. The addition of machine learning analytics (MLA) as a moderator role exhibited a significant relationship in analysing the GG criteria to achieve SDG. This study adopted a quantitative method. 700 questionnaires were distributed to manufacturing firms registered in Federation of Manufacturing Malaysia (FMM), and 180 completed questionnaires were collected and analysed. The IBM SPSS version 27 and partial least squared (PLS-SEM) are utilised to analyse data. CSCP has been investigated under a few domains, including management initiative, government, cleaner production, economybased, social and cultural practices, product design and infrastructure and technology, which were bound to be significant, with the long-term benefits contributing to pollution reduction and improved sustainability outcomes. Thus, implementing CSCP within manufacturing can help achieve the SDG targets by 2030. However, this study found that cleaner production practice and social and cultural practices of circular supply chain has significant affect toward SDG achievement. Implementing all circular practices can pose significant challenges within manufacturing companies. Limited knowledge, awareness, high-cost initial investment and absence of accessible policies and guidelines have added more problems resulting in the low implementation of CSCP. The novel findings affirm that the GG, and MLA significantly affected the SDG target. This finding extended the framework of CSCP and the natural resources-based view (NRBV) theory literature, especially towards social and cultural practices.