Coordinating Dual-Channel Supply Chain Under Price Mechanism With Production Cost Disruption

This paper studies a two-stage dual-channel supply chain consisting of one manufacturer and one traditional retailer. The manufacturer has its own online channel when he sells the product to the offline retailer. There exists a Stackelberg game between the manufacturer and the offline retailer, in which the manufacturer is the leader and the retailer is the follower. The manufacturer abandons the pricing right in the online channel and adopts the marketing strategy which the online retail price is equal to the offline one. When the supply chain is in a static (undisrupted) condition, it can obtain Pareto improvement and eventually be coordinated by a two-part-tariff contract with a one-time transfer payment. When disruptions make the manufacturer’s unit production cost change, we can obtain the retail price, the production quantity and the total supply chain profit under different disruption levels in the centralized supply chain. Then, we find that there are some certain robustness both in the manufacturer’s production quantity and in the offline retail price. When the supply chain is decentralized, we can coordinate the supply chain by changing the wholesale price according to different disruption levels. Finally, some numerical examples are presented to illustrate the results

Examining price and service competition among retailers in a supply chain under potential demand disruption

© 2017 Elsevier Ltd Supply chain disruptions management has attracted significant attention among researchers and practitioners. The paper aims to examine the effect of potential market demand disruptions on price and service level for competing retailers. To investigate the effect of potential demand disruptions, we consider both a centralized and a decentralized supply chain structure. To analyze the decentralized supply chain, the Manufacturing Stackelberg (MS) game theoretical approach was undertaken. The analytical results were tested using several numerical analyses. It was shown that price and service level investment decisions are significantly influenced by demand disruptions to retail markets. For example, decentralized decision makers tend to lower wholesale and retail prices under potential demand disruptions, whereas a proactive retailer needs to increase service level with an increased level of possible disruptions. This research may aid managers to analyze disruptions prone market and to make appropriate decision for price and service level. The manufacturer or the retailers will also be able to better determine when to close a market based on the proposed analysis by considering anticipated disruptions. The benefits and usefulness of the proposed approach are explained through a real-life case adopted from a toy supply chain in Bangladesh

Strategy choice in tourism supply chains for package holidays: a game-theoretic approach

Enterprises in a tourism supply chain usually adopt and operate two business strategies: maximizing their profits or their revenues. This paper investigates the conditions on which these strategies allow enterprises to achieve the maximum benefits in the context of entire supply chain. Several managerial implications have been derived from this theoretical research. Firstly, theme park operator, tour operators and hotel & accommodation providers obtain larger market shares and profits if they select the revenue maximization (R) strategy. Secondly, the profit maximization (P) strategy is a better strategy for both sectors when all the tour operators and all hotel & accommodation providers choose the same strategy. Finally, if both sectors could freely choose their strategies, there is market equilibrium where P-strategy and R-strategy could coexist.published_or_final_versio

STRATEGY CHOICE IN TOURISM SUPPLY CHAINS FOR PACKAGE HOLIDAYS: A GAME-THEORETIC APPROACH

Enterprises in a tourism supply chain usually adopt and operate two business strategies: maximizing their profits or their revenues. This paper investigates the conditions on which these strategies allow enterprises to achieve the maximum benefits in the context of entire supply chain. Several managerial implications have been derived from this theoretical research. Firstly, theme park operator, tour operators and hotel & accommodation providers obtain larger market shares and profits if they select the revenue maximization (R) strategy. Secondly, the profit maximization (P) strategy is a better strategy for both sectors when all the tour operators and all hotel & accommodation providers choose the same strategy. Finally, if both sectors could freely choose their strategies, there is market equilibrium where P-strategy and R-strategy could coexist

Developing an Agent Based Heuristic Optimisation System for Complex Flow Shops with Customer-Imposed Production Disruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies.

Game-Theoretic Approach to Competition Dynamics in Tourism Supply Chains

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A Game-theoretic Approach to Choice of Profit and Revenue Maximization Strategies in Tourism Supply Chains for Package Holidays

2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Developing agent based heuristic optimisation system for complex flow shops with customer-imposed production distruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies

Developing Agent Based Heuristic Optimisation System for Complex Flow Shops with Customer-Imposed Production Disruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturers decision-making policies

Developing agent based heuristic optimization system for complex flow shop with customer-imposed production disruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems.However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes.In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system.The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies