Green logistics operations and its impact on supply chain sustainability: An empirical study

Roy, Supriyo; Mohanty, R. P.

doi:10.1002/bse.3531

Cited by 4 publications

(3 citation statements)

References 125 publications

(257 reference statements)

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“…This can reduce transportation costs and the number of empty vehicles, reducing carbon emissions and traffic congestion. Work with green suppliers to select raw materials and products that meet environmental standards and build a sustainable supply chain [14]. Through the evaluation and monitoring of suppliers to ensure that they are using energy saving and emission reduction technologies and processes in the production process.…”

Section: Methodsmentioning

confidence: 99%

Research and practice of energy saving and emission reduction technology in green logistics engineering

2024

ssge

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The development of green logistics engineering has become an important trend in the field of supply chain management. Based on the supply chain model, this paper reduces the distance and frequency of cargo transportation by optimizing the design and layout of logistics network, thus reducing energy consumption and carbon emissions. At the same time, select the appropriate location of warehousing and distribution centers, optimize transportation routes, and establish multimodal transportation systems. Realize real-time monitoring and scheduling of transport vehicles, reasonably arrange the departure time and route of vehicles, improve transport efficiency and reduce energy consumption. It also reduces waste disposal costs and environmental impact by optimizing product recovery, reuse and recycling processes. The analysis found that optimizing transport routes could reduce energy consumption by 20%, while reducing carbon emissions by 100kg. The implementation of green logistics project is not only conducive to environmental protection, but also can bring economic benefits to enterprises.

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Section: Methodsmentioning

confidence: 99%

Research and practice of energy saving and emission reduction technology in green logistics engineering

2024

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“…Industrial structure (IS): measured using the ratio of the value added of the tertiary industry to the value added of the secondary industry (Liu et al, 2018). Average worker wage (AW): measured using the logarithm of the average wage of urban workers (Roy and Mohanty, 2023).…”

Section: Control Variablesmentioning

confidence: 99%

Nonlinear spatial impacts of the digital economy on urban ecological welfare performance: evidence from China

Wang,

2024

Front. Ecol. Evol.

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IntroductionWith the rapid development of digital technology and its deep integration with environmental and ecological fields, the digital economy has become an effective way to guide the transition of cities to an eco-friendly model. However, empirical studies on the nonlinear spatial effects between digital economy and ecological welfare performance are still insufficient.MethodsBased on the panel data of 270 prefecture-level cities in China from 2011 to 2020, this paper empirically examines the impact of the digital economy on the ecological welfare performance of cities and its mechanism of action using spatial econometric modeling.ResultsThe promotion effect of digital economy development on the ecological welfare performance of cities is characterized by the “J” shape of increasing marginal effect, and the spatial spillover effect on the ecological welfare performance of neighboring cities is the inverted “U” shape of inhibiting first and then promoting later. The mechanism test shows that the development of digital economy can enhance the ecological welfare performance of cities through the marginal incremental promotion of green technological innovation in local and neighboring cities and has a positive spatial spillover effect. The development of digital economy can have a direct U shape effect on local ecological welfare performance by influencing factor allocation efficiency and energy utilization efficiency. It also has an inverted U-shaped spatial spillover effect. Environmental regulation has an inverted U-shaped moderating effect on the local eco-welfare performance affected by the digital economy. As the level of rural revitalization increases, it produces a U-shaped moderating effect of inhibiting. Heterogeneity analysis reveals that digital economy development has a more significant facilitating effect and a positive spatial spillover effect on the ecological welfare performance of cities in central China.DiscussionThis paper will provide a reference for the synergistic optimization of digital economy development and ecological welfare performance among regions. The findings of the study will promote the development of digital economy and accelerate the realization of the goal of “Beautiful China”.

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“…A meta-structure is an intermediary between a single firm (microstructure) and the global economy (macrostructure). The physical microstructure consists of three interdependent value-adding operations subsystems, namely, procurement, production and distribution, enlivened through the most pervasive material and goods flow activities, usually termed a supply chain network (Roy and Mohanty, 2023). Planning and operations are carried out through this physical supply chain network.…”

Section: Introductionmentioning

confidence: 99%

Supply chain risk prioritization: a multi-criteria based Intuitionistic Fuzzy TOPSIS approach

Mukherjee,

De,

Roy

2024

IJQRM

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Purpose Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.Design/methodology/approach The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.Findings The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.Research limitations/implications In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.Practical implications The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).Originality/value This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

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Green logistics operations and its impact on supply chain sustainability: An empirical study

Cited by 4 publications

References 125 publications

Research and practice of energy saving and emission reduction technology in green logistics engineering

Research and practice of energy saving and emission reduction technology in green logistics engineering

Nonlinear spatial impacts of the digital economy on urban ecological welfare performance: evidence from China

Supply chain risk prioritization: a multi-criteria based Intuitionistic Fuzzy TOPSIS approach

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