Green Supply Chain Performance Prediction Using a Bayesian Belief Network

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.

[1]  M. N. Qureshi,et al.  Performance measurement systems for green supply chains using modified balanced score card and analytical hierarchical process , 2012 .

[2]  Keah Choon Tan,et al.  Green supply chain management practices and performance , 2013, Ind. Manag. Data Syst..

[3]  Wantao Yu,et al.  An empirical examination of stakeholder pressures, green operations practices and environmental performance , 2015 .

[4]  Qinghua Zhu,et al.  Green supply chain management in China: pressures, practices and performance , 2005 .

[5]  Sarah Shaw,et al.  Developing environmental supply chain performance measures , 2010 .

[6]  Zoltán Lakner,et al.  Analysis and Comparison of Economic and Financial Risk Sources in SMEs of the Visegrad Group and Serbia , 2019, Sustainability.

[7]  Michael Myrvold Jenssen,et al.  Implementing life cycle assessment in green supplier selection: A systematic review and conceptual model , 2019, Journal of Cleaner Production.

[8]  Joseph Sarkis,et al.  Greening the manufacturing function , 1995 .

[9]  Hua Shi,et al.  Green Supplier Evaluation and Selection Using Interval 2-Tuple Linguistic Hybrid Aggregation Operators , 2018, Informatica.

[10]  Angappa Gunasekaran,et al.  Green supply chain performance measures: A review and bibliometric analysis , 2017 .

[11]  Virgilio Cruz-Machado,et al.  A proposal of LARG Supply Chain Management Practices and a Performance Measurement System , 2011 .

[12]  Siba Sankar Mahapatra,et al.  Sustainable supplier selection in intuitionistic fuzzy environment: a decision-making perspective , 2018 .

[13]  D. Gambelli,et al.  A Bayesian network to predict the probability of organic farms' exit from the sector: A case study from Marche, Italy , 2010 .

[14]  Vinay V. Panicker,et al.  Modelling supply chain decision problem with fixed charge - a review , 2011, Int. J. Bus. Perform. Supply Chain Model..

[15]  G. Noci,et al.  Designing "green" vendor rating systems for the assessment of suppliers environmental performance , 1997 .

[16]  F. Testa,et al.  Shadows and lights of GSCM (Green Supply Chain Management): determinants and effects of these practices based on a multi-national study , 2010 .

[17]  Ju'e Guo,et al.  Sustainable Cooperation in the Green Supply Chain under Financial Constraints , 2019, Sustainability.

[18]  Heungshik Oh,et al.  The impact of decision-making sharing between supplier and manufacturer on their collaboration performance , 2005 .

[19]  Kannan Govindan,et al.  Application of fuzzy VIKOR for evaluation of green supply chain management practices , 2015 .

[20]  Natasha Smith,et al.  Bayesian networks for system reliability reassessment , 2001 .

[21]  Prasenjit Chatterjee,et al.  Integrated QFD-MCDM framework for green supplier selection , 2017 .

[22]  R. Kant,et al.  Green purchasing behaviour: A conceptual framework and empirical investigation of Indian consumers , 2018 .

[23]  Luigi Portinale,et al.  Bayesian networks in reliability , 2007, Reliab. Eng. Syst. Saf..

[24]  Ana Maria Cruz,et al.  Earthquake-related Natech risk assessment using a Bayesian belief network model , 2019 .

[25]  Ali H. Diabat,et al.  A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences , 2013 .

[26]  Leon Hirsch,et al.  Design Environment A Global Guide To Designing Greener Goods , 2016 .

[27]  Francisco Rodrigues Lima Junior,et al.  Quantitative models for supply chain performance evaluation: A literature review , 2017, Comput. Ind. Eng..

[28]  Kwok Hung Lau,et al.  Benchmarking green logistics performance with a composite index , 2011 .

[29]  Wenge Zhu,et al.  Green product design in supply chains under competition , 2017, Eur. J. Oper. Res..

[30]  Vipul Jain,et al.  A review on select models for supply chain formation , 2011, Int. J. Bus. Perform. Supply Chain Model..

[31]  Sanjeev Swami,et al.  Channel coordination in green supply chain management , 2013, J. Oper. Res. Soc..

[32]  Jurgita Antucheviciene,et al.  Supplier evaluation and selection in fuzzy environments: a review of MADM approaches , 2017 .

[33]  Richard E. Neapolitan,et al.  Learning Bayesian networks , 2007, KDD '07.

[34]  Pamela J. Zelbst,et al.  Green supply chain management practices: impact on performance , 2012 .

[35]  Bernard Yannou,et al.  Identifying product failure rate based on a conditional Bayesian network classifier , 2011, Expert Syst. Appl..

[36]  Muhamad Zameri Mat Saman,et al.  Green supply chain management: a review and research direction , 2012 .

[37]  M. Helms,et al.  Performance measurement for green supply chain management , 2005 .

[38]  Cory Searcy,et al.  An analysis of metrics used to measure performance in green and sustainable supply chains , 2015 .

[39]  Kuldip Singh Sangwan,et al.  Benchmarking Indian ceramic enterprises based on green supply chain management pressures, practices and performance , 2018, Benchmarking: An International Journal.

[40]  Alvin B. Culaba,et al.  Evaluating Environmental Performance of Pulp and Paper Manufacturing Using the Analytic Hierarchy Process and Life‐Cycle Assessment , 2002 .

[41]  Laijun Zhao,et al.  A Bibliometric Analysis of Green Supply Chain Management Based on the Web of Science (WOS) Platform , 2019, Sustainability.

[42]  A. Gunasekaran,et al.  Performance measures and metrics in a supply chain environment , 2001 .

[43]  Jitesh Thakkar,et al.  Green supply chain management practices and performance , 2017 .

[44]  Stephan Vachon,et al.  Green supply chain practices and the selection of environmental technologies , 2007 .

[45]  María M. Abad-Grau,et al.  Operations strategy and flexibility: modeling with Bayesian classifiers , 2006, Ind. Manag. Data Syst..

[46]  Adam C. Faruk,et al.  Analyzing, Mapping, and Managing Environmental Impacts along Supply Chains , 2001 .

[47]  R. J. Kuo,et al.  Integration of artificial neural network and MADA methods for green supplier selection , 2010 .

[48]  G. Kabir,et al.  Green supply chain management in the chemical industry: structural framework of drivers , 2019, International Journal of Sustainable Development & World Ecology.

[49]  Lima-JuniorFrancisco Rodrigues,et al.  Quantitative models for supply chain performance evaluation , 2017 .

[50]  Jiafu Su,et al.  A Multi-Objective Optimization Model for Green Supply Chain Considering Environmental Benefits , 2019, Sustainability.

[51]  R. L. Shrivastava,et al.  Impact of green manufacturing practices on organisational performance in Indian context: An empirical study , 2016 .

[52]  Federica Cucchiella,et al.  Issue on supply chain of renewable energy , 2013 .

[53]  Ru-Jen Lin,et al.  Green supply chain management performance in automobile manufacturing industry under uncertainty , 2011 .

[54]  Angappa Gunasekaran,et al.  Green supply chain collaboration and incentives: Current trends and future directions , 2015 .

[55]  Joseph Sarkis.  Manufacturing’s role in corporate environmental sustainability ‐ Concerns for the new millennium , 2001 .

[56]  Yan Li,et al.  Research on the Performance Measurement of Green Supply Chain Management in China , 2011 .

[57]  M. Banerjee,et al.  Retail supply chain management practices in India: A business intelligence perspective , 2017 .

[58]  G. Kabir,et al.  An AHP-ELECTRE framework to evaluate barriers to green supply chain management in the leather industry , 2019, International Journal of Sustainable Development & World Ecology.

[59]  M. McAleer.  Assessing the Importance of Market Risk and its Sources in SMEs of the Visegrad Group and Serbia* , 2018 .

[60]  Reza Tavakkoli-Moghaddam,et al.  A new enhanced support vector model based on general variable neighborhood search algorithm for supplier performance evaluation: A case study , 2017, Int. J. Comput. Intell. Syst..

[61]  Davide Luzzini,et al.  Supply chain performance measurement systems: A systematic review and research agenda , 2017 .

[62]  Bart Baesens,et al.  Faculteit Economie En Bedrijfskunde Hoveniersberg 24 B-9000 Gent Bayesian Network Classifiers for Identifying the Slope of the Customer Lifecycle of Long-life Customers Bayesian Network Classifiers for Identifying the Slope of the Customer Lifecycle of Long-life Customers , 2022 .

[63]  Stephen Laison Sondoh,et al.  Examining green consumerism motivational drivers: does premium price and demographics matter to green purchasing? , 2016 .

[64]  M. Tseng,et al.  A literature review on green supply chain management: Trends and future challenges , 2019, Resources, Conservation and Recycling.

[65]  Manoj Kumar Tiwari,et al.  Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach , 2014 .

[66]  Sebastian Kummer,et al.  A review of green supply chain management: From bibliometric analysis to a conceptual framework and future research directions , 2018, Resources, Conservation and Recycling.

[67]  J. Tenenbaum,et al.  Bayesian Networks, Bayesian Learning and Cognitive Development , 2022 .

[68]  Francisco Rodrigues Lima-Junior,et al.  Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks , 2019, International Journal of Production Economics.

[69]  Samir K. Srivastava,et al.  Green Supply-Chain Management: A State-of-the-Art Literature Review , 2007 .

[70]  R. Klassen,et al.  The impact of environmental management on firm performance , 1996 .

[71]  Rick Hoole,et al.  Five ways to simplify your supply chain , 2005 .

[72]  J. Popp,et al.  The Assessment of Non-Financial Risk Sources of SMES in the V4 Countries and Serbia , 2019, Sustainability.

[73]  Steven A. Melnyk,et al.  Applying environmental criteria to supplier assessment: A study in the application of the Analytical Hierarchy Process , 2002, Eur. J. Oper. Res..

[74]  Solomon Tesfamariam,et al.  Consequence-based framework for buried infrastructure systems: A Bayesian belief network model , 2018, Reliab. Eng. Syst. Saf..

[75]  Brian S. Fugate,et al.  Investigating green supply chain management practices and performance , 2019, International Journal of Operations & Production Management.

[76]  Ali Bozorgi-Amiri,et al.  A game theoretical for coordination of pricing, recycling, and green product decisions in the supply chain , 2019, Journal of Cleaner Production.

[77]  Hui Gao,et al.  Models for Multiple Attribute Decision Making with Interval-Valued Pythagorean Fuzzy Muirhead Mean Operators and Their Application to Green Suppliers Selection , 2019, Informatica.

[78]  Meysam Maleki,et al.  Supply chain performance monitoring using Bayesian network , 2013, Int. J. Bus. Perform. Supply Chain Model..

[79]  Patrick Addai,et al.  Measuring Supply Chain Performance , 2017 .

[80]  Elizabeth Chang,et al.  Smart Buyer: A Bayesian Network modelling approach for measuring and improving procurement performance in organisations , 2017, Knowl. Based Syst..

[81]  Michael J. Lenox,et al.  LEAN AND GREEN? AN EMPIRICAL EXAMINATION OF THE RELATIONSHIP BETWEEN LEAN PRODUCTION AND ENVIRONMENTAL PERFORMANCE , 2001 .