International Journal of Business Performance and Supply Chain Modelling
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International Journal of Business Performance and Supply Chain Modelling (2 papers in press)
Developing a multi-method simulation model of a green closed-loop supply chain and determining pricing and advertising policy against a competitor by Samira Parsaiyan, Maghsoud Amiri, Parham Azimi, Mohammad Taghi Taqhavi Fard Abstract: The environmental impact of supply chains has motivated many studies in this area. This research proposes a novel multi-method simulation approach which combines agent-based and discrete event modelling approaches to model a green closed-loop supply chain and optimize it through an Optimization Via Simulation technique. A closed-loop supply chain is developed under the demand uncertainty to minimize total cost and total greenhouse gases (GHG) emissions and maximize management preference of the supply chain in the presence of a competitor. Taguchi design of experiments method is used to generate scenarios, then total cost and total GHG emissions are recorded through simulating the scenarios. Management preference is determined based on decision makers opinion. Scenarios are ranked against three attributes with the proposed panel-group TOPSIS method. Inventory replenishment parameters, pricing and advertising policies, and transportation type are determined via solving the model. An automotive industry case is provided to demonstrate the models capabilities. Keywords: green closed-loop supply chain; agent-based modelling; multi-method simulation; pricing policy; advertising policy; TOPSIS.
Effect of Internal Supply Chain Drivers on Green Supply Chain Management (GSCM) Attributes by Ganesh Kumar Ramesh, Murali R, Anand S Abstract: With a call for cleaner and efficient processes every-where around, green supply chain management attributes came to the fore. This calls for their study in a systematic manner. In an attempt to fulfil this requirement, this study puts forth several ideas. It studies the impact of the variables anticipation of benefits and customer orientation on green supply chain management (GSCM) attributes. These variables have impacts on the GSCM attributes to a varying degree. Partial Least Squares Structural Equations Modelling was used for the study and the open-source statistical tool R was used for the analysis. Partial Least Squares Structural Equations Modelling is an apt tool when the data size is small and there are no assumptions about the characteristics of the data. Keywords: Internal Supply Chain drivers; Anticipation of benefits; Customer Orientation of benefits; GSCM Attributes; Partial Least Squares Structural Equations Modelling.