| 1. |
- Chen, Lujie, 1983-
(author)
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Sustainability and company performance : Evidence from the manufacturing industry
- 2015
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Doctoral thesis (other academic/artistic)abstract
- This dissertation approaches the question of sustainability and its influence on company performance, with special focus on the manufacturing industry. In the contemporary production environment, manufacturing operations must take into account not only profit, but also environmental and social performance, in order to ensure the long-term development of the company. Companies have to decide whether they should allocate resources to environmental and social practices in order to improve their competitive advantage. Consequently, in decision-making processes concerning operations, it is important for companies to understand how to coordinate profit, people, and planet.The objective of this dissertation was to investigate the current situation regarding manufacturers’ sustainable initiatives, and to explore the relationship between these sustainable practices and companies’ performance, including financial performance, operational performance, innovation performance, environmental performance, and social performance. First of all, a structured literature review was conducted to identify sustainable factors considered to be important in the decision making of manufacturing operations. The findings were synthesized into a conceptual model, which was then adopted as the basis for designing the survey instrument used in this dissertation. Drawing on Global Reporting Initiative (GRI) reports, empirical research was performed to explore the relationship between environmental management practices and company performance. Interestingly, the findings showed that many environmental management practices had a strong positive impact on innovation performance. Sustainability disclosures and financial performance were further analyzed using extended data from the GRI reports. The results also showed that several sustainability performance indicators, such as product responsibility, human rights, and society, displayed a significant and positive correlation with return on equity in the sample companies.In order to further explore the research area and to verify these findings, a triangulation approach was adopted and new data were collected via a survey conducted among middle and large sample companies in the Swedish manufacturing industry. The results indicated that the sustainable improvement practices had a positive impact on company performance. Some environmental and social improvement practices had a direct and positive correlation with product and process innovation. Furthermore, findings suggested that better cooperation with suppliers on environmental work could help to strengthen the organizational green capabilities of the focal companies.When considering the company’s general approach to implementing sustainable practices, some interesting findings emerged. There were limited significant differences in sustainable practices when comparing different manufacturing sectors, and different countries and regions. However, the results showed that Swedish manufacturing companies often place higher priority on implementing economic and environmental sustainability practices than on social ones.This dissertation contributes to the literature on manufacturing sustainability. The study expands the understanding of how environmental, social, or economic perspectives as a triple bottom line can influence company performance and to a certain extent the supply chain. Identifying and understanding such relationships gives companies the opportunity to integrate sustainability into their manufacturing operations strategy in order to sustain their manufacturing operations over the long term.
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| 2. |
- Gandhi, Kanika, et al.
(author)
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Three Echelon Supply Chain Design with Supplier Evaluation
- 2014
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In: Proceedings of the Third International Conference on Soft Computing for Problem Solving. - Berlin : Springer-Verlag GmbH. - 9788132217671 - 9788132217688 ; , s. 867-881
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Conference paper (peer-reviewed)abstract
- Effective supply chain management (SCM), which facilitates companies to react to changing demand by swiftly communicating those needs to their supplier, is at the root of successful manufacturing. Optimizing a supply chain (SC) performance is a key factor for success in long term SC relationships. Much information like price, delivery time percentage and acceptance percentage are discussed in the process. A factor as imprecise demand is added in the same process that fuzzifies coordination between buyer and supplier. The paper considers nondeterministic conditions in the environment of business, coordination in procurement and distribution in a supplier selection problem that was proposed and a fuzzy model with two objectives was defined. The proposed model is a “fuzzy bi-objective mixed integer nonlinear” problem. A “fuzzy solution and fuzzy goal programming method” is used to convert the model into crisp form and solved using differential evolution
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| 3. |
- Govindan, Kannan, et al.
(author)
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A Bi-objective location-routing model for the healthcare waste management in the era of logistics 4.0 under uncertainty
- 2024
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In: INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS. - 0925-5273 .- 1873-7579. ; 276
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Journal article (peer-reviewed)abstract
- The purpose of this study is to apply Industry 4.0-based technologies to improve the management of infectious healthcare waste considering location-routing problem and population risk under uncertainty. To achieve this, a decision support system is developed and implemented utilizing a bi-objective mixed-integer linear programming (MILP) model. The bi-objective MILP model improves the performance of the healthcare waste management by applying Industry 4.0 technologies, including electric autonomous vehicles, information sharing system, internet of things (IoT), Global Navigation Satellite System (GNSS), and RFID-tagged waste bags. We develop a multiobjective solution approach by integrating the lexicographic and TH methods. The validity of the model has been established through its implementation in seven hospitals in the city of Karaj, Iran. The results denoted significant improvements in waste collection efficiency, route optimization, and the reduction of contamination risks.
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| 4. |
- Govindan, Kannan, et al.
(author)
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Designing a resilient reverse network to manage the infectious healthcare waste under uncertainty: A stochastic optimization approach
- 2024
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In: COMPUTERS & INDUSTRIAL ENGINEERING. - 0360-8352 .- 1879-0550. ; 194
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Journal article (peer-reviewed)abstract
- The global expansion of healthcare facilities has resulted in increased levels of infectious-hazardous waste, posing serious threats to the environment and public health. Existing waste management systems can become overwhelmed during health crises, such as epidemics or natural disasters, exacerbating the problem. This study formulates a mixed-integer linear programming model for developing a resilient infectious waste management reverse network during the outbreak of the COVID-19 pandemic. Health crisis are unpredictable in nature and it is almost impossible to predict their exact behavior. Therefore, in this paper, the uncertainty of ambiguous parameters is considered using a scenario-oriented approach. To make the proposed model resilient, three strategies, including establishing new collection centers, overtime, and cooperation with third-party logistics, are introduced. The results derived from running the developed model in GAMS software using the case study data showed that the active collection center cannot serve the network alone, and to make the network more resilient, the strategy of establishing a new collection center should be selected. The findings validate the model's utility in designing a resilient waste management network during a health crisis, emphasizing the importance of resilience in infectious healthcare waste management networks.
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| 5. |
- Shahparvari, Shahrooz, et al.
(author)
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Closing the Loop : Redesigning Sustainable Reverse Logistics Network in Uncertain Supply Chains
- 2021
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In: Computers & industrial engineering. - : Elsevier. - 0360-8352 .- 1879-0550. ; 157
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Journal article (peer-reviewed)abstract
- This paper develops a robust stochastic optimization model for reverse logistics in closed-loop supply chains. By determining the optimal flow of products using a Chance Constrained Robust Stochastic Programming (CCRSP), it is highlighted how the number of plant openings is influenced by the changes in carbon credit price. To assess the model performance, a set of numerical experiments in different sizes are developed and conducted. The effectiveness of the results are then compared to a proposed Heuristic Hybrid Taguchi PSO (HTPSO) solution algorithm, which underlines the effectiveness of the model. A sensitivity analysis on the carbon emission rate is carried out which underlines the role of Carbon Tax Policy. Finally, a real-lifecase study within the automotive manufacturing industry is carried out by applying the developed robust stochastic model. From a practical standpoint, the model can potentially be employed to meet the carbon credits that are used for handling the different carbon prices and trade scenarios. Also, it provides insights on how tobetter manage uncertainties, as well as to reduce the overall emissions in supply chains.
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| 6. |
- Soleimani, Hamed, et al.
(author)
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Fuzzy Multi-Objective Sustainable and Green Closed-Loop Supply Chain Network Design
- 2017
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In: Computers & industrial engineering. - : Elsevier. - 0360-8352 .- 1879-0550. ; 109, s. 191-203
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Journal article (peer-reviewed)abstract
- This article addresses a design problem of a closed loop supply chain, including suppliers, manufacturers, distribution centers, customers, warehouse centers, return centers, and recycling centers. The problem entails three choices regarding recycling, namely, product recycling, and components recycling raw material recycling. Modeling this chain is carried out by accounting for environmental considerations, total profit optimization, and reduction of lost working days due to occupational accidents, we well as maximizing responsiveness to customer demand. In order to solve the model, genetic algorithm has been used and multiple scenarios with different aspects have been studied. Solving this model provides decisions regarding opening or closing of each of the components of the network and the optimal product flow among them. The results prove the feasibility of the presented model and the applicability of the developed solution methodology.
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