본 연구실은 생산전략과 경영과학을 기반으로 재고관리, 공급사슬 최적화, 지속가능성 투자, 탄소배출 저감, 에너지 공급망 설계 등 기업과 사회의 복합적 운영 문제를 정량적으로 분석하며, 불확실한 환경에서 효율성과 지속가능성을 동시에 높일 수 있는 데이터 기반 의사결정 모형과 정책적 시사점을 제시하는 연구를 수행하고 있다.
A data-driven viable supply network for energy security and economic prosperity
Kwon Gi Mun, Wenbo Cai, Mark D. Rodgers, Sungyong Choi
IF 7.3
International Journal of Production Research
Developing countries face significant challenges in achieving energy stability due to disruptions in their energy supply chains, which jeopardise their sustainability and survivability. Addressing these issues requires careful consideration of public funding in the energy sector and the design of a robust electricity infrastructure. This study aims to identify long-term infrastructure investment strategies that can strengthen the viability of the energy supply network in developing countries, even with limited public funds. The research is underpinned by an empirical study that shows the successful development of energy infrastructure through the effective implementation of viable energy strategies in developing countries. By adopting these strategies, energy supply networks in developing countries can mitigate supply disruptions and avert economic losses. Further, this study evaluates the effectiveness of the viable energy supply network by incorporating a mix of energy resources based on actual data from Pakistan. The contributions of the study are as follows. We develop a viable energy supply network model that considers crucial elements, such as extraction, transportation, generation, transmission, and supply and facilities decision-making. Additionally, we show that the performance of the energy network is not only driven by electricity supply but also influenced by the overall economic growth of the country.
Supply chain investment and contracting for carbon emissions reduction: A social planner's perspective
Jun-Yeon Lee, Sungyong Choi
IF 10
International Journal of Production Economics
We consider a supply chain consisting of a supplier and a buyer whose efforts jointly influence carbon emissions per unit of the product. The product demand is affected by the effort levels. The carbon footprint is allocated to the supply chain members by a social planner, and they pay carbon penalties for their allocated emissions. We first examine the social first-best solution and then analyze a no-collaboration scenario, where the supply chain members simultaneously make their own effort decisions under an allocation rule, and two supply chain contracting scenarios: credible buyer and double moral hazard, where the buyer designs and offers a contract to the supplier that specifies an order quantity and a payment scheme contingent on the realized carbon footprint. We find that the social planner may need to over- or under-allocate the emissions to the firms to induce the social first-best effort levels in the no-collaboration scenario. However, the social first-best effort levels can be attained with a simple allocation rule without over- or under-allocation in the credible buyer scenario. For the double moral hazard scenario, where the buyer is not credible to the supplier, the social first-best may not be attainable and there may be a significant loss in the social value of the supply chain.
본 과제는 재고관리에서 널리 쓰이는 뉴스벤더 (newsvendor) 모형을 수요가 아니라 이항수율 (Binomial distribution) 형태의 확률적 수율이 결정하는 생산 프로세스에 적용한 연구임.
연구 목표는 이항수율 생산 프로세스를 수리 최적화 모형 (mathematical optimization model)으로 모형 화 (modeling)하여 기대 순 이익의 최적 생산 로트 (production lot) 크기와 분석적 결과를 도출하는 데 있음. 핵심 연구 내용은 single production run single stage에서 과다·과소 수율의 상충관계를 포함한 비 제약 최대화 문제 (unconstrained maximization problem)를 정규 근사로 미분 가능한 근사 모형으로 확장하고, 가능 시 폐쇄형 (closed-form) 최적 해를 확보하는 절차임. 기대 효과는 stylized하고 analytically tractable한 이항수율 모형을 제공하여 산업 적용 가능성을 높이는 학문적 공헌임.