Greenhouse gas penalty and incentive policies for a joint economic lot size model with industrial and transport emissions

Wangsa, Ivan Darma

doi:10.5267/j.ijiec.2017.3.003

Cited by 29 publications

(16 citation statements)

References 40 publications

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“…A summary of the literature review is presented in Table 1. Yes Bazan et al [26] Yes Yes Zanoni et al [21] Yes Yes Zanoni et al [34] Yes Lee and Kim [25] Yes Yes Sarkar et al [37] Yes Sarkar et al [27] Yes Chan et al [31] Yes Wangsa [38] Yes Tiwari et al [10] Yes Yes Daryanto et al [11] Yes Yes Daryanto et al [41] Yes Marchi et al [46] Yes Yes Yes Bai et al [12] Yes Yes Yes Kumar and Uthayakumar [15] Yes Yes Wee and Daryanto [42] Yes Hasan et al [45] Yes Turken et al [16] Yes Yes Daryanto and Wee [44] Yes Yes This study Yes Yes Yes Yes…”

Section: Low-carbon Supply Chain Managementmentioning

confidence: 99%

“…Sarkar et al [37] use both fixed and variable transportation costs and emissions in a three-level supply chain. Wangsa [38] considers carbon emissions from production, transportation, and material handling activities. Focusing on the supply chain for cold products, Hariga et al [9] studied the cost savings and emissions reductions of an integrated supply chain model.…”

Section: Low-carbon Supply Chain Managementmentioning

confidence: 99%

See 1 more Smart Citation

Low-Carbon Supply Chain Model under a Vendor-Managed Inventory Partnership and Carbon Cap-and-Trade Policy

Astanti

Daryanto

Dewa

2022

Journal of Open Innovation: Technology, Market, and Complexity

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Nowadays, companies are collaborating and forming supply chain partnerships under a certain scheme, such as a vendor-managed inventory scheme. The collaboration increases the supply chain’s visibility, which leads to cost efficiency. It may also contribute to enhancing the supply chain’s green performance. This paper presents a supply chain inventory model to guide managers in making optimal inventory decisions considering the logistics cost and carbon emissions. A vendor supplies products under a vendor-managed inventory; hence, it is responsible for the logistics activities. The effect of product deterioration and quality problems are also considered, in which the vendor performs a 100% quality inspection. A carbon price is imposed on total emissions from production and logistics activities under a cap-and-trade regulation. The result is inventory decisions regarding the optimal delivery quantity as well as the delivery frequencies that minimize the total costs. The reduction in total carbon emissions from the decisions was also studied.

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Section: Low-carbon Supply Chain Managementmentioning

confidence: 99%

Section: Low-carbon Supply Chain Managementmentioning

confidence: 99%

Low-Carbon Supply Chain Model under a Vendor-Managed Inventory Partnership and Carbon Cap-and-Trade Policy

Astanti

Daryanto

Dewa

2022

Journal of Open Innovation: Technology, Market, and Complexity

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“…(2020) also investigated the impact of different carbon policies, namely carbon cap-and-trade, limited CEs and carbon tax, on inventory decisions (Wangsa, 2017). Saga et al (2019) incorporated penalty and incentive policies to cut down the emissions from a supply chain system made of a vendor and a buyer.…”

Section: Carbon Policiesmentioning

confidence: 99%

“…Huang et al. (2020) also investigated the impact of different carbon policies, namely carbon cap-and-trade, limited CEs and carbon tax, on inventory decisions (Wangsa, 2017). Saga et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainability enablers with price-based preservation technology and carbon reduction investment in an inventory system to regulate emissions

Yadav,

Borkar,

Khanna

2023

MEQ

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PurposeWith the pressing need for environmental conservation, regulatory authorities are actively looking for measures to prevent global warming. In the proposed inventory model for deteriorating items, demand is dependent on the selling price and green technology investment (or carbon reduction investment) for the green product (GP), as well as an investment in price-based preservation technology to slow down the pace of deterioration. Furthermore, emission reduction measures are put in place to reduce carbon emissions (CEs).Design/methodology/approachThe current study executed a thorough literature review to determine how to improve supply chain management performance. Furthermore, assumptions are made to fill research gaps, and a mathematical model is created to address the problem mentioned above. To collect the data, the available inventory literature was reviewed. Additionally, numerical illustrations and sensitivity analyses are presented to emphasize the model's robustness.FindingsThe research indicates that it is more prudent to invest in preservation technology based on its selling price in order to control the rate of deterioration. In addition, the proposed model facilitates the management of deteriorated waste through salvage trading and emission reduction investment. The findings validate sustainable practices with a 20.86% increase in profit and a 21.4% decrease in CEs, thereby signifying environmental and economic benefits.Originality/valueThe proposed model enhances understanding of the impact of investments in price-based preservation technology and carbon reduction efforts on consumer perceptions of their intention to purchase GPs. Moreover, the study provides valuable insights by identifying important recommendations for policymakers regarding areas that require further investigation. This guideline can help identify both current and unexplored gaps, enabling researchers to direct future research efforts toward producing new products.

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“…Others also attempted to combine two indicators such as fuel consumption and emissions in developing a new model (Wangsa, 2017;Wangsa et al, 2020). It was discovered that only Jauhari (2022) considered fuel, emissions, and electricity costs simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Sustainable Production-Inventory Model with Multi-Material, Quality Degradation, and Probabilistic Demand: From Bibliometric Analysis to A Robust Model

Utama

Santoso

Hendrawan

et al. 2022

Indonesian J. Sci. Technol

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An adequate sustainable production inventory model is expected to represent complex real-life cases involving fuel, emissions, and electricity costs as well as multi-materials, quality degradation, and probabilistic demand. Therefore, this study was conducted to develop this kind of model to determine the number of raw material shipments (), production cycle time (), and the number of finished goods delivered (n) to maximize the Expected Total Profit (ETP). The proposed model is based on a bibliometric literature analysis of the sustainable production-inventory problem which is visualized using the VOSviewer. Moreover, a sophisticated Harris-Hawks Optimization (HHO) algorithm was proposed to solve the problems identified in the sustainable production inventory model optimization. It is also important to note that three numerical cases were provided to evaluate the performance of the algorithm. The findings showed that the suggested HHO method outperforms the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in maximizing ETP and this means it is better for ETP optimization. It was also discovered from the sensitivity analysis that an increase in the rate of quality degradation (k) led to a reduction in both the ETP and T.

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Greenhouse gas penalty and incentive policies for a joint economic lot size model with industrial and transport emissions

Cited by 29 publications

References 40 publications

Low-Carbon Supply Chain Model under a Vendor-Managed Inventory Partnership and Carbon Cap-and-Trade Policy

Low-Carbon Supply Chain Model under a Vendor-Managed Inventory Partnership and Carbon Cap-and-Trade Policy

Sustainability enablers with price-based preservation technology and carbon reduction investment in an inventory system to regulate emissions

Sustainable Production-Inventory Model with Multi-Material, Quality Degradation, and Probabilistic Demand: From Bibliometric Analysis to A Robust Model

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