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https://hdl.handle.net/20.500.14365/6590Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ayranci, Gonul | - |
| dc.contributor.author | Ozbiltekin-Pala, Melisa | - |
| dc.contributor.author | Mangla, Sachin Kumar | - |
| dc.contributor.author | Kazancoglu, Yigit | - |
| dc.date.accessioned | 2025-11-25T15:25:05Z | - |
| dc.date.available | 2025-11-25T15:25:05Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.issn | 0953-7287 | - |
| dc.identifier.issn | 1366-5871 | - |
| dc.identifier.uri | https://doi.org/10.1080/09537287.2025.2574089 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/6590 | - |
| dc.description.abstract | Supply chains, involving multiple stakeholders and complex operations, are vulnerable to disruptions; therefore, ensuring their resilience is crucial. Recently, the concept of an energy-efficient supply chain has gained attention, because it reduces costs and supports social and environmental development. However, many risks arise while improving energy efficiency in supply chains, and it is important to identify these risks, particularly in emerging economies. This study identifies these risks and their interrelations through literature review and expert opinions. By integrating Bayesian Belief Network and Monte Carlo Simulation, scenario analyses are conducted to explore the possible consequences of these risks, and the study finds that natural events are the most critical risks to energy efficiency in supply chain resilience. It contributes to the small body of literature on risks to energy efficiency in supply chain resilience, and innovatively applies scenario analysis to these risks, providing managers and practitioners with valuable insights. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor & Francis Ltd | en_US |
| dc.relation.ispartof | Production Planning & Control | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Risk Management | en_US |
| dc.subject | Supply Chain Management | en_US |
| dc.subject | Energy Efficiency | en_US |
| dc.subject | Bayesian Belief Networks | en_US |
| dc.subject | Monte Carlo Simulation | en_US |
| dc.title | Risks to Energy Efficiency in Supply Chain Resilience: From an Emerging Economy Context | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | 10.1080/09537287.2025.2574089 | - |
| dc.identifier.scopus | 2-s2.0-105019200816 | - |
| dc.department | İzmir Ekonomi Üniversitesi | en_US |
| dc.authorwosid | Ozbiltekin-Pala, Melisa/Aaa-2580-2019 | - |
| dc.authorwosid | Ayranci, Gonul/Mzr-6427-2025 | - |
| dc.authorwosid | Kazancoglu, Yigit/E-7705-2015 | - |
| dc.authorwosid | Mangla, Sachin/B-7605-2017 | - |
| dc.authorscopusid | 60147917200 | - |
| dc.authorscopusid | 57222809402 | - |
| dc.authorscopusid | 55735821600 | - |
| dc.authorscopusid | 15848066400 | - |
| dc.identifier.wos | WOS:001595552700001 | - |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.identifier.scopusquality | Q1 | - |
| dc.identifier.wosquality | Q1 | - |
| dc.description.woscitationindex | Science Citation Index Expanded | - |
| item.cerifentitytype | Publications | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
| item.fulltext | With Fulltext | - |
| item.openairetype | Article | - |
| item.grantfulltext | reserved | - |
| item.languageiso639-1 | en | - |
| crisitem.author.dept | 17.15. Banking and Insurance | - |
| crisitem.author.dept | 03.02. Business Administration | - |
| Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection | |
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