scholarly journals Green Supply Chain Performance Prediction Using a Bayesian Belief Network

2020 ◽  
Vol 12 (3) ◽  
pp. 1101 ◽  
Author(s):  
Md. Rabbi ◽  
Syed Mithun Ali ◽  
Golam Kabir ◽  
Zuhayer Mahtab ◽  
Sanjoy Kumar Paul
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Performance Measures ◽  
Performance Indicators ◽  
Bayesian Belief Network ◽  
Sustainable Growth ◽  
Green Supply Chain ◽  
Supply Chain Performance ◽  
Belief Network ◽  
The Impact

Green supply chain management (GSCM) has emerged as an important issue to lessen the impact of supply chain activities on the natural environment, as well as reduce waste and achieve sustainable growth of a company. To understand the effectiveness of GSCM, performance measurement of GSCM is a must. Monitoring and predicting green supply chain performance can result in improved decision-making capability for managers and decision-makers to achieve sustainable competitive advantage. This paper identifies and analyzes various green supply chain performance measures and indicators. A probabilistic model is proposed based on a Bayesian belief network (BBN) for predicting green supply chain performance. Eleven green supply chain performance indicators and two green supply chain performance measures are identified through an extensive literature review. Using a real-world case study of a manufacturing industry, the methodology of this model is illustrated. Sensitivity analysis is also performed to examine the relative sensitivity of green supply chain performance to each of the performance indicators. The outcome of this research is expected to help managers and practitioners of GSCM improve their decision-making capability, which ultimately results in improved overall organizational performance.

scholarly journals Integrating Green Practices into Operational Performance: Evidence from Brazilian Manufacturers

2019 ◽  
Vol 11 (10) ◽  
pp. 2956 ◽  
Author(s):  
Hannah Santos ◽  
Gustavo Lannelongue ◽  
Javier Gonzalez-Benito
Keyword(s):  
Supply Chain ◽  
Management Practices ◽  
Empirical Support ◽  
Sustainable Growth ◽  
Operational Performance ◽  
Green Supply Chain ◽  
Environmental Practices ◽  
Market Society ◽  
Green Practices ◽  
The Impact

The pressures exerted by the market, society, regulators and/or clients on organisational environmental responsibility have required companies to adopt environmental management practices. Within this process, integration with suppliers and customers is important to enable companies to meet these demands, and at the same time achieve their organisational goals. Using empirical results from 117 respondents on Green Supply Chain Management (GSCM) practices among Brazilian manufacturers, we examined the impact of the adoption of green practices on operational performance. To do so, we developed a questionnaire to collect the variables on environmental practices and operational performance in manufacturing firms in Brazil, an emerging economy in which this sector accounts for 25% of its Gross Domestic Product (GDP). The results show that the adoption of GSCM between suppliers and/or customers has a positive effect on operational performance. This means companies can benefit from a green supply chain by cooperating with upstream suppliers of environmentally responsible production technology and by exchanging environmental information with them, as well as considering the views of customers and green consumers in their production processes. This study provides empirical support for managers promoting environmental practices that may lead to operational performance and sustainable growth.

scholarly journals Analysis of the Value of Information and Coordination in a Dyadic Closed Loop Supply Chain

2020 ◽  
Vol 12 (20) ◽  
pp. 8398
Author(s):  
Juan Pedro Sepúlveda-Rojas ◽  
Rodrigo Ternero
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Value Of Information ◽  
Closed Loop ◽  
Local Optimization ◽  
Supply Chain Performance ◽  
Optimization Approach ◽  
Closed Loop Supply Chain ◽  
Definition Of ◽  
The Impact

Purpose: This article analyzes the value of information and coordination in a closed loop supply chain (CLSC) and discusses the benefits of a global or local optimization approach and the impact of uncertainty. Methodology: A theoretical dyadic closed loop supply chain is analyzed where the manufacturer re-manufactures products returned by customers, producing “as good as new products” for the retailer. Twelve coordination scenarios were analyzed. For the definition of these scenarios, a framework based on two criteria was proposed: value of information and perimeter of decision making. Findings: Information on returns leads to lower costs than information on demand. In the presence of complete or partial coordination between the actors in the supply chain, it is preferable to have low product return rates. However, if we are in the complete absence of coordination, high rates of return are more convenient as they function as a buffer against uncertainties. The perimeter of decision making (global or local optimization) does not significantly improve the supply chain performance in relation to its costs. Only the exchange of information improves its performance. Therefore, companies should make efforts to exchange information, first, on their lot sizes, then on their returns and finally, on the customer demand. Originality: The novelty of our work relies on an analysis of the closed loop supply chain performance with the simultaneous presence of information, coordination, and uncertainty.

scholarly journals Dual-Channel Green Supply Chain Decision-Making and Coordination considering CSR and Consumer Green Preferences

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Xiaochun Chen ◽  
Rui Zhang ◽  
Bo Lv
Keyword(s):  
Supply Chain ◽  
Social Welfare ◽  
Rapid Development ◽  
Consumer Surplus ◽  
Green Supply Chain ◽  
Supply Chain Performance ◽  
Dual Channel ◽  
Green Preferences ◽  
Corporate Social ◽  
The Impact

With the rapid development of the Internet and changes in consumer buying habits, many manufacturers are increasingly relying on online channels to sell their products as opposed to traditional retail channels. In this study, we innovatively investigate the impact of corporate social responsibility (CSR) and consumer green preferences (CGP) on supply chain performance and product green level in the dual-channel green supply chain (DCGSC). Specifically, four models of DCGSC (centralized, independent CSR, cooperative CSR, and collaboration contract) are investigated. Next, we use game theory to investigate the optimal product green level, online and offline selling prices, social welfare, profits of supply chain enterprises, and the whole supply chain under the four models. We give numerical examples to demonstrate the effectiveness and viability of the four models. We find several interesting conclusions. First, increasing the attention to both CSR and CGP by supply chain enterprises is conducive to stimulating innovation and improving product green level. Second, when supply chain enterprises actively execute their CSR, they can reasonably control online and offline selling prices and increase consumer surplus and the profits of whole supply chain and social welfare are increased. Third, it is beneficial to increase the value of supply chain enterprises to enhance CSR within a certain threshold, but when CSR is higher than the threshold, the profitability of supply chain enterprises is weakened. Finally, collaboration contracts are capable of coordinating DCGSC and guaranteeing the profitability of supply chain enterprises.

scholarly journals Impact of Green Supply Chain on Supply Chain Performance

2022 ◽  
Vol 19 ◽  
pp. 442-452
Author(s):  
Ghufran Saed Hijjawi
Keyword(s):  
Supply Chain ◽  
Literature Review ◽  
Green Design ◽  
Green Supply Chain ◽  
Supply Chain Performance ◽  
Proposed Model ◽  
Green Production ◽  
The Impact

The purpose of this paper is empirically assessment of the impact of the green supply chain on supply chain performance in terms of social, operational, and environmental, for Jordanian chemical industries. In this paper, the proposed model was developed based on literature review and previous exploratory studies related to GSC and different kinds of SC performance. Tested on sample equal 150 managers of Jordanian detergent manufacturing factories and the returned ones that applicable for analysis were 120 questionnaires, which analyzed using AMOS 27. The results were as follows: there is no impact of green purchase, green production, and green distribution on supply chain performance. While there is an impact of green supply and green design on SC performance, taking into consideration the community and region of study.

scholarly journals Analysis of Variance Amplification and Service Level in a Supply Chain with Correlated Demand

2020 ◽  
Vol 12 (16) ◽  
pp. 6470 ◽  
Author(s):  
Ahmed Shaban ◽  
Mohamed A. Shalaby ◽  
Giulio Di Gravio ◽  
Riccardo Patriarca
Keyword(s):  
Supply Chain ◽  
Performance Measures ◽  
Bullwhip Effect ◽  
Service Level ◽  
Operating Conditions ◽  
Supply Chain Performance ◽  
Chain Model ◽  
Ordering Policy ◽  
Smoothing Parameters ◽  
The Impact

The bullwhip effect reflects the variance amplification of demand as they are moving upstream in a supply chain, and leading to the distortion of demand information that hinders supply chain performance sustainability. Extensive research has been undertaken to model, measure, and analyze the bullwhip effect while assuming stationary independent and identically distributed (i.i.d) demand, employing the classical order-up-to (OUT) policy and allowing return orders. On the contrary, correlated demand where a period’s demand is related to previous periods’ demands is evident in several real-life situations, such as demand patterns that exhibit trends or seasonality. This paper assumes correlated demand and aims to investigate the order variance ratio (OVR), net stock amplification ratio (NSA), and average fill rate/service level (AFR). Moreover, the impact of correlated demand on the supply chain performance under various operational parameters, such as lead-time, forecasting parameter, and ordering policy parameters, is analyzed. A simulation modeling approach is adopted to analyze the response of a single-echelon supply chain model that restricts return orders and faces a first order autoregressive demand process AR(1). A generalized order-up-to policy that allows order smoothing through the proper tuning of its smoothing parameters is applied. The characterization results confirm that the correlated demand affects the three performance measures and interacts with the operating conditions. The results also indicate that the generalized OUT inventory policy should be adopted with the correlated demand, as its smoothing parameters can be adapted to utilize the demand characteristics such that OVR and NSA can be reduced without affecting the service level (AFR), implying sustainable supply chain operations. Furthermore, the results of a factorial design have confirmed that the ordering policy parameters and their interactions have the largest impact on the three performance measures. Based on the above characterization, the paper provides management with means to sustain good performance of a supply chain whenever a correlated demand pattern is realized through selecting the control parameters that decrease the bullwhip effect.

Understanding big data-driven supply chain and performance measures for customer satisfaction

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramadas Thekkoote
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Customer Satisfaction ◽  
Performance Measures ◽  
Data Driven ◽  
Equation Modeling ◽  
Supply Chain Performance ◽  
Content Type ◽  
Different Dimensions ◽  
The Impact

PurposeSupply chain analytics with big data capability are now growing to the next frontier in transforming the supply chain. However, very few studies have identified its different dimensions and overall effects on supply chain performance measures and customer satisfaction. The aim of this paper to design the data-driven supply chain model to evaluate the impact on supply chain performance and customer satisfaction.Design/methodology/approachThis research uses the resource-based view, emerging literature on big data, supply chain performance measures and customer satisfaction theory to develop the big data-driven supply chain (BDDSC) model. The model tested using questionnaire data collected from supply chain managers and supply chain analysts. To prove the research model, the study uses the structural equation modeling technique.FindingsThe results of the study identify the supply chain performance measures (integration, innovation, flexibility, efficiency, quality and market performance) and customer satisfaction (cost, flexibility, quality and delivery) positively associated with the BDDSC model.Originality/valueThis paper fills the significant gap in the BDDSC on the different dimensions of supply chain performance measures and their impacts on customer satisfaction.

scholarly journals Green supply chain performance measures: A review and bibliometric analysis

2017 ◽  
Vol 10 ◽  
pp. 85-99 ◽  
Author(s):  
Deepa Mishra ◽  
Angappa Gunasekaran ◽  
Thanos Papadopoulos ◽  
Benjamin Hazen
Keyword(s):  
Supply Chain ◽  
Bibliometric Analysis ◽  
Performance Measures ◽  
Green Supply Chain ◽  
Supply Chain Performance

scholarly journals DECISION SUPPORT MODEL FOR SUPPLY CHAIN MANAGEMENT

TEME ◽  
2021 ◽  
pp. 1457
Author(s):  
Dragana Rejman Petrović ◽  
Predrag Mimović ◽  
Zora Arsovski
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Decision Support ◽  
Supply Chains ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Strategic Decision ◽  
Supply Chain Performance ◽  
Different Types ◽  
Chain Type

The purpose of this paper is the creation of a model for supply chain performance optimization and the development of a prototype of the decision support system.The study covered an efficient and agile supply chain type. The Analytic Hierarchy Process was used (AHP) for the evaluation and ranking of supply chains.The research on this topic have dealt with the evaluation and ranking of suppliers within supply chains not considering the characteristics of different types of supply chains. The contribution of this work is in the development of a new model that enables the evaluation and ranking of supply chains considering the priorities of key performance indicators in different types of supply chains, providing management with the support in decision making through simulation and the finding of optimum solutions for the specific supply chain type, as well as the possibility of evaluation and ranking of different supply chain types on the basis of weighted overall performance of each supply chain.Developed and suggested models provide company management with monitoring and control of individual key performance indicators and total supply chain performance, and in this way, become the support to the management in strategic decision making.

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