Management and Marketing - Research Publications

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    Coordinated pricing analysis with the carbon tax scheme in a supply chain
    Ma, X ; Ho, W ; Ji, P ; Talluri, S (Wiley, 2018-10)
    The carbon tax is a cost-efficient scheme to curb emissions, and it has been implemented in Australia, British Columbia, and other places worldwide. We aim to analyze its effect on dynamic pricing in a supply chain with multiple suppliers and one manufacturer. The profit-maximizing manufacturer makes final products using raw materials from suppliers with heterogeneous prices and emission rates. A two-stage game model is built over an infinite time horizon for this issue. In the first stage, suppliers face price-dependent demand to set their prices and production rates under the constraint of inventory capacity. Then, in response to the carbon tax scheme, the manufacturer evaluates the procurement prices and emission rates of suppliers to control its emission volumes and sets the sales price of its product. This paper predominately focuses on the optimal pricing strategies in a decentralized supply chain. The open-loop equilibrium and Markovian Nash equilibrium for the dynamic pricing game models of both suppliers and the manufacturer are derived, respectively. The equilibrium prices of suppliers and the manufacturer can be solved based on both irreversible actions and real-time states. These two types of equilibria can be regarded as the solutions of two different models in specific situations. To analyze the effect of sourcing diversity on pricing strategies and emissions control for the manufacturer, the more general equilibrium price for the manufacturer in an n-suppliers oligopoly is studied. Numerical examples are presented to illustrate the equilibrium and its monotonicity with various parameter settings.
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    Models for supplier selection and risk mitigation: A holistic approach
    Yoon, J ; Talluri, S ; Yildiz, H ; Ho, W (Taylor & Francis, 2018)
    According to a study conducted by PwC and the Business Continuity Institute in 2013, 75% of companies experience at least one major supply chain disruption a year and majority of the disruptions were caused by supply-related problems. With an increasing emphasis on upstream risk, risk management in supplier selection has become a critical issue faced by companies. Although previous studies proposed different methods and tools for effective and efficient supplier selection, only few approaches have attempted to incorporate risk mitigation strategies in supplier selection decisions. Our study aims to fill this gap by considering a wide range of quantitative and qualitative risk factors in supplier selection and evaluates the efficacy of alternative risk mitigation strategies in this context. Moreover, we suggest that both upstream and downstream strategies should be utilised simultaneously rather than relying on a single type of strategy. We further suggest that it is critical to align upstream and downstream risk mitigation strategies to reduce risk. We employ multi-objective optimization-based simulation in developing a decision model and consider data from an automotive parts manufacturer to demonstrate the application of our approach.
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    Contract Design with Information Asymmetry in a Supply Chain under an Emissions Trading Mechanism
    Ma, X ; Ho, W ; Ji, P ; Talluri, S (WILEY, 2018-02)
    ABSTRACT We aim to design an appropriate sourcing mechanism with information asymmetry in a supply chain with one manufacturer and multiple suppliers subject to an emissions trading scheme. The manufacturer purchases raw materials from suppliers, who hold private information regarding the green degree—that is, the unit emission rates—of their raw materials. An appropriate strategy must be adopted by the manufacturer for the contract design, including a series of payments and the order quantities; the suppliers are subsequently invited to bid for the contracts. The basic model is formulated to assist the manufacturer in designing a reasonable contract for a single supplier. The characteristics of the optimal order quantity and payoff functions of both the manufacturer and supplier are analyzed. A competitive procurement scenario with multiple suppliers is also discussed. With respect to the diversity of auctions, three different auction types are analyzed, including a green degree auction, a price auction with emissions targets, and a performance‐based auction. In addition, an efficient emissions trading policy is established to guide manufacturers regarding how to balance their emission allowances based on the optimal order quantities. Our approach provides an effective decision support system for both the manufacturer and suppliers.
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    Supply chain risk management: a literature review
    Ho, W ; Zheng, T ; Yildiz, H ; Talluri, S (Taylor & Francis, 2015)
    Risk management plays a vital role in effectively operating supply chains in the presence of a variety of uncertainties. Over the years, many researchers have focused on supply chain risk management (SCRM) by contributing in the areas of defining, operationalising and mitigating risks. In this paper, we review and synthesise the extant literature in SCRM in the past decade in a comprehensive manner. The purpose of this paper is threefold. First, we present and categorise SCRM research appearing between 2003 and 2013. Second, we undertake a detailed review associated with research developments in supply chain risk definitions, risk types, risk factors and risk management/mitigation strategies. Third, we analyse the SCRM literature in exploring potential gaps.
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    A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments
    Scott, J ; HO, W ; Dey, PK ; Talluri, S (Elsevier, 2015-06-01)
    Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors׳ knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process–Quality Function Deployment (AHP–QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.
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    Reliable Supply Chain Network Design
    Yildiz, H ; Yoon, J ; Talluri, S ; Ho, W (Wiley Blackwell, 2016)
    Decision Sciences Institute.Risk management in supply chains has been receiving increased attention in the past few years. In this article, we present formulations for the strategic supply chain network design problem with dual objectives, which usually conflict with each other: minimizing cost and maximizing reliability. Quantifying the total reliability of a network design is not as straightforward as total cost calculation. We use reliability indices and develop analytical formulations that model the impact of upstream supply chain on individual entities' reliability to quantify the total reliability of a network. The resulting multiobjective nonlinear model is solved using a novel hybrid algorithm that utilizes a genetic algorithm for network design and linear programming for network flow optimization. We demonstrate the application of our approach through illustrative examples in establishing tradeoffs between cost and reliability in network design and present managerial implications.