scholarly journals Green Procurement Relationships Development under Carbon Emissions Regulations: A Bi-Level Programming Approach

2018 ◽  
Vol 15 (10) ◽  
pp. 2183 ◽  
Author(s):  
Xiao-Ying Bao ◽  
Lei Zhang
Keyword(s):  
Supply Chain ◽  
Carbon Emissions ◽  
Stackelberg Game ◽  
Programming Model ◽  
Carbon Tax ◽  
Raw Materials ◽  
Programming Approach ◽  
Green Procurement ◽  
Multiple Sourcing ◽  
Upper Level

A multi-period Stackelberg game is adopted to study a green procurement relationship between manufacturers and suppliers in a supply chain. The manufacturers are considered as leaders, while the suppliers are modelled as followers in this Stackelberg game. Accordingly, a mixed binary linear bi-level programming model is developed to elaborate the game in consideration of carbon tax scheme. The upper level (the leader) aims at selecting a proper number of suitable suppliers to provide heterogeneous raw materials at the lowest operational cost. The objective of the lower level (the follower) is to find optimal purchasing quantities of raw materials. In addition, two lemmas are introduced to transform the mixed linear bi-level programming model into a single level linear programming model. The numerical example illustrates that: (1) the manufacturer prefers to adopt the multiple sourcing strategy due to the flexibility; (2) keeping stable supplies and large order volumes could effectively reduce carbon emissions for the suppliers and make the supply chain greener.

scholarly journals The Farmers’ Channel Selection and Sustainable Analysis under Carbon Tax Policy

2019 ◽  
Vol 11 (10) ◽  
pp. 2765 ◽  
Author(s):  
Cong Zheng ◽  
Quangui Pang ◽  
Tianpei Li ◽  
Guizheng Wang ◽  
Yiji Cai ◽  
...  
Keyword(s):  
Supply Chain ◽  
Carbon Emissions ◽  
Stackelberg Game ◽  
Carbon Tax ◽  
Product Yield ◽  
Channel Selection ◽  
Low Carbon ◽  
Deterioration Rate ◽  
Dual Channels ◽  
The Government

This paper examines a farmer’s channel selection in a supply chain led by a retailer, considering carbon emissions and products’ deterioration. Three channels—online channels, retail channels, and dual channels—are proposed. The inventory model of perishable products and the two-stage Stackelberg game model are used to illustrate the operational process. To compare performances of the three channel structures, we further determine the critical points consisting of the profits and the carbon emissions among these channels. The results provide useful insights for supply chain members and the government. Farmers can choose a channel to optimize profit with respect to deterioration rate and product yield, but it might conflict with the aim of least carbon emissions. When the deterioration rate is high, the online channel is not a suitable choice. For the government, the carbon tax contributes to the reduction of carbon emissions, but it also leads to the loss of the farmer’s profit. Additionally, numerical results further illustrate that, from the perspective of the government, transporting and inventory processes are two major sources of emissions, and it is essential to implement carbon tax and exploit low-carbon transportation.

scholarly journals A Multistage Sustainable Production–Inventory Model with Carbon Emission Reduction and Price-Dependent Demand under Stackelberg Game

2020 ◽  
Vol 10 (14) ◽  
pp. 4878
Author(s):  
Chi-Jie Lu ◽  
Tian-Shyug Lee ◽  
Ming Gu ◽  
Chih-Te Yang
Keyword(s):  
Supply Chain ◽  
Carbon Emissions ◽  
Stackelberg Game ◽  
Carbon Tax ◽  
Inventory Model ◽  
Sustainable Production ◽  
Equilibrium Solutions ◽  
Production Inventory ◽  
Dependent Demand ◽  
Tax Regulation

This paper investigated a multistage sustainable production–inventory model for deteriorating items (i.e., raw materials and finished goods) with price-dependent demand and collaborative carbon reduction technology investment under carbon tax regulation. The model was developed by first defining the total profit of the supply chain members under carbon tax regulation and, second, considering a manufacturer (leader)–retailer (follower) Stackelberg game. The optimal equilibrium solutions that maximize the manufacturer’s and retailer’s total profits were determined through the method analysis. An algorithm complemented the model to determine the optimal equilibrium solutions, which were then treated with sensitivity analyses for the major parameters. Based on the numerical analysis, (a) carbon tax policies help reduce carbon emissions for both the manufacturer and retailer; (b) most carbon emissions from supply chain operations negatively impact the total profits of both members; (c) the retailer may increase the optimal equilibrium selling price to respond to an increase in carbon emissions from supply chain operations or carbon tax; and (d) autonomous consumption positively affects both members’ optimal equilibrium policies and total profits, whereas induced consumption does the opposite. These findings are very managerial and instructive for companies seeking profits and fulfilling environmental responsibility and governments.

scholarly journals Single-Manufacturer Multi-Retailer Supply Chain Models with Discrete Stochastic Demand

2021 ◽  
Vol 13 (15) ◽  
pp. 8271
Author(s):  
Yaqing Xu ◽  
Jiang Zhang ◽  
Zihao Chen ◽  
Yihua Wei
Keyword(s):  
Dynamic Programming ◽  
Supply Chain ◽  
Computational Complexity ◽  
Stackelberg Game ◽  
Programming Model ◽  
Dynamic Programming Method ◽  
Game Model ◽  
Chain Model ◽  
Stochastic Demands ◽  
Demand Models

Although there are highly discrete stochastic demands in practical supply chain problems, they are seldom considered in the research on supply chain systems, especially the single-manufacturer multi-retailer supply chain systems. There are no significant differences between continuous and discrete demand supply chain models, but the solutions for discrete random demand models are more challenging and difficult. This paper studies a supply chain system of a single manufacturer and multiple retailers with discrete stochastic demands. Each retailer faces a random discrete demand, and the manufacturer utilizes different wholesale prices to influence each retailer’s ordering decision. Both Make-To-Order and Make-To-Stock scenarios are considered. For each scenario, the corresponding Stackelberg game model is constructed respectively. By proving a series of theorems, we transfer the solution of the game model into non-linear integer programming model, which can be easily solved by a dynamic programming method. However, with the increase in the number of retailers and the production capacity of manufacturers, the computational complexity of dynamic programming drastically increases due to the Dimension Barrier. Therefore, the Fast Fourier Transform (FFT) approach is introduced, which significantly reduces the computational complexity of solving the supply chain model.

Park-and-Ride Network Design: A Goal Programming Approach

2014 ◽  
Vol 1030-1032 ◽  
pp. 2065-2068
Author(s):  
Xin Yuan Chen ◽  
Zhi Yuan Liu ◽  
Wei Deng
Keyword(s):  
Network Design ◽  
Goal Programming ◽  
Design Problem ◽  
Programming Model ◽  
Search Algorithm ◽  
Network Design Problem ◽  
Programming Approach ◽  
Multi Objective ◽  
Park And Ride ◽  
Upper Level

The paper addresses a park and ride network design problem in a bi-model transport network in a multi-objective decision making framework. A goal programming approach is adopted to solve the multi-objective park and ride network design problem. The goal programming approach considers the user-defined goals and priority structure, which are (i) traffic-efficient goal, (ii) total transit usage goal, (iii) spatial equity goal. This problem is formulated as a bi-level programming model. The upper level programming leads to minimize the deviation from stated goals in the context of a given priority ranking. While the lower level programming model is a modal split/traffic assignment model which is used to assess any given park and ride scheme. A heuristic tabu search algorithm is then adopted to solve this model.

scholarly journals Qualitative Insights into Supply Chain Management of Herbal Medicine in Ghana

2019 ◽  
pp. 1-11
Author(s):  
Charles Adusei ◽  
Ramatu Agambire
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Herbal Medicine ◽  
Raw Materials ◽  
Qualitative Interviews ◽  
Case Study Research ◽  
Structured Interview ◽  
Research Strategy ◽  
Chain Management ◽  
Multiple Sourcing

A qualitative exploratory study was conducted on supply chain and the related risk management at Adutwumwaa Herbal Industries Limited (AHL) in Ghana. The study employed a case study research strategy using semi-structured interview guide as data collection tool. Thematic analysis was used to analyse the qualitative interviews involving five senior officers from the company. They served as Key Informants for the study. Major Themes that were derived from supply chain management were supply chain approach, management of risk to avoid supply chain break down and supply chain management pitfalls facing organisations. The supply chain approach involved sourcing of raw materials, route to market and distribution of products. Management of safety stock for its flagship brands, using multiple sourcing and technological innovations were adopted in managing risk to avoid supply chain breakdown. Unreliable supply of packaging and labeling materials from suppliers and disruption from Food and Drug Authority were the key supply chain management pitfalls facing the company. The study suggests that if herbal medicine companies want to retain competitive edge then they must pursue supply chain operational excellence by reassessing and adjusting its distribution capabilities periodically to improve responsiveness.

Pricing supply chain option contracts: a bilevel programming approach

2020 ◽  
Vol 15 (4) ◽  
pp. 1567-1589
Author(s):  
Abir Trabelsi ◽  
Hiroaki Matsukawa
Keyword(s):  
Supply Chain ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Wholesale Price ◽  
Optimal Order ◽  
Programming Approach ◽  
Market Demand ◽  
Content Type ◽  
Option Contract ◽  
Optimal Pricing Strategy

Purpose This paper considers an option contract in a two-stage supplier-retailer supply chain (SC) when market demand is stochastic. The problem is a Stackelberg game with the supplier as a leader. This research assumes demand information sharing. The purpose of this study is to determine the optimal pricing strategy of the supplier along with the optimal order strategy of the retailer in three option contract cases. Design/methodology/approach The paper model the option contract pricing problem as a bilevel problem. The problem is then solved using bilevel programing methods. After computing, the generated outcomes are compared to a benchmark (wholesale price contract) to evaluate the contract. Findings The results reveal that only one of the contract cases can arbitrarily allocate the SC profit. In both other cases, the Stackelberg supplier manages to earn the total SC profit. Further analysis of the first contract, show that from the supplier’s perspective, the first stage forecast inaccuracy is beneficial, whereas the demand uncertainty in the second stage is detrimental. This contracting strategy guarantees both players better outcomes compared to the wholesale price contract. Originality/value To the best of the authors’ knowledge, this research is the first that links the option contract literature to the bilevel programing literature. It also the first to solve the pricing problem of the commitment option contract with demand update where the retailer exercises the option before knowing the exact demand.

Omicron will slow but not weaken German recovery

2021 ◽  
Keyword(s):  
Economic Growth ◽  
Supply Chain ◽  
Carbon Emissions ◽  
Raw Materials ◽  
Electricity Prices ◽  
Short Term ◽  
Content Type ◽  
Legal Immigration ◽  
The Impact

Significance Bundesbank president Jens Weidmann stated that the “recovery has been somewhat pushed back” by the impact of supply chain restrictions, the rising costs of raw materials and energy and the spread of the more transmissible Omicron COVID-19 variant. Impacts Higher taxes on carbon emissions and elevated electricity prices will slow economic growth in the short term. Opening more paths for legal immigration will become a crucial policy for tackling labour shortages over the coming years. Education and infrastructures will be the main recipients of new investment under Chancellor Olaf Scholz’s government.

Supply chain network optimization with consideration of raw material and final product substitutions driven by price and carbon emissions

Kybernetes ◽  
2018 ◽  
Vol 47 (8) ◽  
pp. 1585-1603 ◽  
Author(s):  
Chuanxu Wang ◽  
Yanbing Li ◽  
Zhengcai Wang
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Carbon Emissions ◽  
Network Optimization ◽  
Raw Materials ◽  
Raw Material ◽  
Maximization Problem ◽  
Supply Chain Network ◽  
Product Substitution ◽  
Content Type

Purpose This paper aims to develop a bi-objective mixed integer non-linear programing model to optimize the supply chain networks consisting of raw material providers, final product manufacturers and distribution centers. Raw material substitution caused by varying raw material supply amounts, prices and carbon emissions and final product substitution due to different product prices and carbon emissions are considered. Design/methodology/approach The proposed model aims to achieve total profit maximization and total carbon emission minimization. The objective function of carbon emissions is converted into a maximization problem by changing minimum to maximum. The composite objective function is the weighted sum of the bias value of each objective function. The model is then solved using software Lingo12. Findings Numerical analysis results show that an increase in the number of alternate raw materials for original raw material helps improve supply chain network performance, and variation in that number causes detectable but not significant changes in downstream final product substitution results. Originality/value The major differences between this work and existing research are as follows: first, although previous research considered carbon emissions in supply chain network optimization, it has not considered the substitution effects of products or raw materials. This paper considers the substitution of both raw material and productions. Second, the item substitution considered by previous research is derived from inventory shortage or price difference of original items. However, the substitution considered in the present paper is a response to differences in purchase price, production cost and carbon emissions for items.

Game Models of Green Supply Chain Involved the Third Party Logistics

2014 ◽  
Vol 700 ◽  
pp. 727-733
Author(s):  
Shi Ying Jiang ◽  
Chun Yan Ma
Keyword(s):  
Supply Chain ◽  
Stackelberg Game ◽  
Carbon Tax ◽  
Third Party ◽  
Green Supply Chain ◽  
Third Party Logistics ◽  
Product Price ◽  
The Third Party Logistics ◽  
The Third ◽  
The Third Party

The green supply chain consisting of the third party logistics and retailer is as the background.Some factors are considered such as product green degree, carbon tax and consumer preferences. Two kinds of green supply chain game models are set up: Stackelberg game model dominated by the third party logistics,Stackelberg game model dominated by retailer. The game models are compared, and finally the numerical simulation has been carried on.Study shows that in the game models, with the improvement of product green degree, product price, logistics price, profit of the third party logistics, the profits of retailer and the supply chain will increase;With the increase of carbon tax, product price and logistics price also unceasingly increase.

Emergency Policy for Perishable Products Supply Chain when Nodes Fail

2011 ◽  
Vol 317-319 ◽  
pp. 2097-2102
Author(s):  
Kai Fei Liu ◽  
Xiao Liu
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Emergency Management ◽  
Programming Model ◽  
Raw Materials ◽  
Global Supply Chain ◽  
Mixed Integer ◽  
Perishable Products ◽  
Effective Policy ◽  
Simulation Results

Emergency management is becoming more and more important with the vulnerability increasing in global supply chain. An effective policy which is emergency strategy stock based for perishable supply chain emergency scheduling with a failed produce node has been proposed. Mixed integer programming model was build under the inventory policy of perishable products which include both of raw materials and finished products. The simulation results show that our policy of the model is effective, and could solve these problems completely.

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