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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    Design and application of Internet of Things based Warehouse Management System for Smart Logistics
    Lee, CKM ; Lv, Y ; Ng, KKH ; Ho, W ; Choy, KL (Taylor & Francis, 2018)
    Warehouse operations need to change due to the increasing complexity and variety of customer orders. The demand for real-time data and contextual information is requried because of the highly customised orders, which tend to be of small batch size but with high variety. Since the orders frequently change according to customer requirements, the synchronisation of purchase orders to support production to ensure on-time order fulfilment is of high importance. However, the inefficient and inaccurate order picking process has adverse effects on the order fulfilment. The objective of this paper is to propose an Internet of things (IoT)-based warehouse management system with an advanced data analytical approach using computational intelligence techniques to enable smart logistics for Industry 4.0. Based on the data collected from a case company, the proposed IoT-based WMS shows that the warehouse productivity, picking accuracy and efficiency can be improved and it is robust to order variability.
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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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    The state-of-the-art integrations and applications of the analytic hierarchy process
    Ho, W ; Ma, X (Elsevier, 2018)
    Because of its great flexibility and wide applicability, integrated analytic hierarchy process (AHP) approaches have been studied extensively for the last 20 years. This paper, as a follow-up study to Ho (2008), reviews the literature on the integrated AHP approaches and applications published between 2007 and 2016 and compares those studies with papers published during the previous decade, i.e., 1997-2006. Based on the 88 journal articles, five questions can be answered: (1) which type of integrated AHP approaches was paid most attention to? (2) Which application areas were integrated AHP approaches primarily applied to? (3) Which specific problems were integrated AHP approaches most commonly applied to? (4) What is the trend in publications regarding integrated AHP approaches? and (5) Which international journals were integrated AHP approaches most widely published in? Finally, some new applications of new AHP integrations are proposed to assist scholars in filling the literature research gaps.
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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, 2018-02-01)
    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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    A genetic algorithm for the generalised transportation problem
    Ho, W ; Ji, P (Inderscience, 2005-07-11)
    The generalised transportation problem (GTP) is an extension of the linear Hitchcock transportation problem. However, it does not have the unimodularity property, which means the linear programming solution (like the simplex method) cannot guarantee to be integer. This is a major difference between the GTP and the Hitchcock transportation problem. Although some special algorithms, such as the generalised stepping-stone method, have been developed, but they are based on the linear programming model and the integer solution requirement of the GTP is relaxed. This paper proposes a genetic algorithm (GA) to solve the GTP and a numerical example is presented to show the algorithm and its efficiency. Copyright © 2005 Inderscience Enterprises Ltd.
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    A multi-depot travelling salesman problem and its iterative and integrated approaches
    Ho, W ; Ji, P ; Dey, PK (Inderscience, 2006)
    Resource allocation is one of the major decision problems arising in higher education. Resources This paper formulates a logistics distribution problem as the multi-depot travelling salesman problem (MDTSP). The decision makers not only have to determine the travelling sequence of the salesman for delivering finished products from a warehouse or depot to a customer, but also need to determine which depot stores which type of products so that the total travelling distance is minimised. The MDTSP is similar to the combination of the travelling salesman and quadratic assignment problems. In this paper, the two individual hard problems or models are formulated first. Then, the problems are integrated together, that is, the MDTSP. The MDTSP is constructed as both integer nonlinear and linear programming models. After formulating the models, we verify the integrated models using commercial packages, and most importantly, investigate whether an iterative approach, that is, solving the individual models repeatedly, can generate an optimal solution to the MDTSP.
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    An integrated multiple criteria decision making approach for resource allocation in higher education
    Ho, W ; Higson, HE ; Dey, PK (Inderscience, 2007)
    Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the Analytic Hierarchy Process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the Goal Programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include 'hardware' (tangible university's infrastructures), and 'software' (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model
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    Component scheduling for chip shooter machines: a hybrid genetic algorithm approach
    Ho, W ; Ji, P (PERGAMON-ELSEVIER SCIENCE LTD, 2003-12-01)
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