Management and Marketing - Research Publications
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ItemEvaluating sustainably resilient supply chains: a stochastic double frontier analytic model considering Netzero(Springer Science and Business Media LLC, 2022-01-01)Abstract In era of reglobalization, sustainably resilient supply chains (SCs) are imperative in corporations to improve performance and meet stockholders’ expectations. However, sustainably resilient SCs could not be effective if are not assessed by using advanced frameworks, systems, and models. As such, developing a novel network data envelopment model (DEA) to appraise sustainably resilient SCs is our purpose in this article. To do so, we present a new double-frontier methodology to provide optimistic and pessimistic efficiency measures in network structures. Moreover, ideas of outputs weak disposability, chance-constrained programming, and discrete dominance are incorporated in a unified framework of modelling efficient and inefficient production technologies. The new network DEA model also can address dissimilar types of data, including undesirable and integer-valued and ratio outputs, stochastic intermediate products, and integer-valued inputs in a unified framework. Furthermore, an aggregated Farrell type efficiency measure is developed which allows to provide the complete ranking of units so that each decision-making unit (DMU) has its own rank in both overall and divisional point of view. We show the unique features of our developed model using a real case study in paint industry to evaluate the efficiency and reducing carbon dioxide (CO2) emissions. The results show that how well the proposed models can evaluate the sustainability and resilience of supply chains in the presence of uncertainty and with dissimilar types of data.
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ItemCoordinated pricing analysis with the carbon tax scheme in a supply chain(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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ItemDesign and application of Internet of Things based Warehouse Management System for Smart Logistics(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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ItemModels for supplier selection and risk mitigation: A holistic approach(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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ItemThe state-of-the-art integrations and applications of the analytic hierarchy process(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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ItemContract Design with Information Asymmetry in a Supply Chain under an Emissions Trading Mechanism(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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ItemStrategic sourcing in the UK bioenergy industry(ELSEVIER, 2013-12)
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ItemMulti-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop(Elsevier BV, 2013)The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem.
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ItemDesign and development of a hybrid artificial bee colony algorithm for the environmental vehicle routing problem(Elsevier BV, 2014-08)The vehicle routing problem (VRP) is a critical and vital problem in logistics for the design of an effective and efficient transportation network, within which the capacitated vehicle routing problem (CVRP) has been widely studied for several decades due to the practical relevance of logistics operation. However, CVRP with the objectives of minimizing the overall traveling distance or the traveling time cannot meet the latest requirements of green logistics, which concern more about the influence on the environment. This paper studies CVRP from an environmental perspective and introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles. In this research, the environmental influence is measured through the amount of the emission carbon dioxide, which is a widely acknowledged criteria and accounts for the major influence on environment. A hybrid artificial bee colony algorithm (ABC) is designed to solve the EVRP model, and the performance of the hybrid algorithm is evaluated through comparing with well-known CVRP instances. The computational results from numerical experiments suggest that the hybrid ABC algorithm outperforms the original ABC algorithm by 5% on average. The transformation from CVRP to EVRP can be recognized through the differentiation of their corresponding optimal solutions, which provides practical insights for operation management in green logistics.
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ItemStrategic supplier selection using multi-stakeholder and multi-perspective approaches(ELSEVIER SCIENCE BV, 2015-08)