International Journal of Applied Decision Sciences (13 papers in press)
A Hierarchical SBM-Tobit Approach for Examining the Influencing Factors of Industrial CO2 Emission Efficiency in the Yangtze River Delta
by Jie Zhang, Mei Yang, Zhencheng Xing*
Abstract: As the most developed region, the Yangtze River Delta (YRD) has been one of the largest CO2 emitter in China. Chinese government has proposed the concept of YRD urban agglomeration to improve its competitiveness. To this end, we evaluate industrial CO2 emission efficiency (ICEE) of 26 cities in YRD and its space-time distribution during 2006-2015 by applying SBM-Undesirable model and the method of GIS visualization respectively. Moreover, we used Tobit model to study factors influencing ICEE. The results are as follows: (1) ICEE of YRD increases in fluctuation during our study period; (2) There is a spatial cluster in the distribution of ICEE; (3) The proportion of industrial research and development funds to regional GDP (R&D), population size (PS) and the degree of opening up to the outside world (OPEN) positively influence the ICEE, while industrial energy structure (IES) and the actual use of foreign direct investment (FDI) negatively do.
Keywords: Yangtze River Delta; industrial CO2 emission efficiency; influencing factors; SBM-Undesirable model; Tobit regression.
Price Coordination in Closed-loop Data Supply Chain
by Xinming Li, Huaqing Wang, Lei Wen, Yu Nie
Abstract: By focusing on new features of data products and, based on game theoretical models, we study three pricing mechanisms' performance and their effects on the participants in the data industry from the data supply chain perspective. A win-win pricing strategy for the players in the data supply chain is proposed. We obtain analytical solutions in each pricing mechanism, including the decentralised and centralised pricing, Nash bargaining pricing, and revenue sharing mechanism. Our findings show that: 1) the decentralised pricing has the lowest performance; 2) although Nash bargaining pricing can achieve the centralised channel performance, the upstream data provider and downstream application provider can only equally divide the total channel profit; 3) revenue sharing mechanism, in which the data provider subsidises the application provider, can achieve the first best performance and divide the maximum profit arbitrarily. Accordingly, end-users benefit mostly from the bargaining pricing and revenue sharing.
Keywords: price coordination; data pricing; Nash Bargaining; revenue sharing; channel coordination.
Game theory in supply chain management: Current trends and applications
by Neelesh N. Vasnani, Felixter Leone S. Chua, Lanndon Ocampo, Lance Brandon M. Pacio
Abstract: As game theory continues to be a relevant approach in evaluating supply chain coordination and competition, this paper explores the various applications and current trends of game theory to supply chain management through an exhaustive review on the literature. This work reviews more than 200 papers which cover several supply chain formations, structures, environments, and decisions together with different game theoretic concepts and applications. First, the paper elaborates on the basic concepts of Nash and Stackelberg games to allow further understanding of their applications in supply chain analysis. The review is then presented and divided into three segments: 1) the development of game theory; 2) the use of Nash and Stackelberg solution concepts in analysing supply chain management; 3) the integration of game theory to different supply chain structures, decisions, and present conditions. Moreover, descriptive analytics are also provided to highlight the distribution of trending topics in the domain field. Finally, the paper provides a summary of the review and recommendation for future works in line with using game theory for supply chain analysis.
Keywords: game theory; supply chain management; current trends; applications; literature review.
Measuring the Productivity of the Bank Branches using Data Envelopment Analysis and Malmquist Index
by Kaveh Khalili-Damghani, Batoul Rahmani, Melfi Alrasheedi
Abstract: Productivity measurement is assumed as one of the main guideline to assess the effectiveness and efficiency of organisations. Productivity of the bank branches as main players of financial systems should be measured periodically. In this paper, the productivity and its components (i.e., technical efficiency change and technological frontier change) in 42 profit-making branches of a private bank in Tehran province, Iran, are analysed during the period 2014-2016. Inefficient bank branches are determined. The projection of inefficient bank branches toward efficient frontier is also discussed. Productivity and technical efficiency of production elements of branches of a private bank are investigated by Malmquist productivity index (MPI) and an input-oriented data envelopment analysis (DEA) in constant returns to scale (CRS) and variable returns to scale (VRS) conditions. Based on results, scale inefficiency had the greatest impact on technical efficiency in the case study.
Keywords: Bank performance; Malmquist productivity index; Data envelopment analysis; Technical efficiency; Technological Frontier.
A Uniqueness-Driven Similarity Measure for Automated Competitor Identification
by Adam Fleischhacker, Xin Ji, Yi-Lin Tsai
Abstract: Uniqueness is an important source of competitive advantage and a salient aspect for firms identifying competitors and market structure. While marketing research often includes uniqueness as an important aspect of product positioning and product strategy, the existing literature has offered little guidance on operationalizing this notion for use in the competitor identification process. This paper proposes a probabilistic similarity measure to quantify a competitive landscape where uniqueness is a key driver of competition. The proposed measure, when used with readily available data and combined with existing clustering algorithms, enables automation of the competitor identification process. Empirical experiments are used to validate the proposed measure. These experiments show that marketers can use readily available data, including social media tags and geographical proximity data, to reveal the same insight as is gathered when using the more laborious and time-consuming approach of traditional consumer surveys.
Keywords: Uniqueness; Similarity; Competitor Identification; Related Social Tags.
Consistency Formation of Fuzzy Multi-Attribute Group Decision Making Based on Alternative Adjustment
by Bingjiang Zhang
Abstract: Analytic hierarchy process (AHP) is a method usually used in group decision making. The process of group decision making using AHP is essentially an individual preference of the decision maker incorporating process. In this process, it becomes one of the cores for studying theory and method of group decision making, how we incorporate effectively different forms of preference information. Therefore, in this paper, we propose a solution which makes consistency preference of decision maker group form finally by decision alternative adjustment. We can make clear the deference of decision preference of each division on basis of group division by means of decision information of the decision maker and put forward to employ flexibly AHP for consistency formation of fuzzy multi-attribute group decision making. Thus, an effective dynamic group decision making process is formed. A group decision making example of market approves of new tissue product shows the feasibility of the proposed method.
Keywords: Operations research; Fuzzy multi-attribute group decision making; AHP; Judge matrix; Clustering analysis.
A Goal Programming Embedded Genetic Algorithm for Multi-objective Manufacturing Cell Design
by Barnali Chaudhuri, R.K. Jana, Dinesh K. Sharma, P.K. Dan
Abstract: In this paper, a multi-objective manufacturing cell design problem is studied. A goal programming (GP) embedded real-coded genetic algorithm (GA) is designed for solving this problem. Initially, the GA is used to obtain the individual minimum of each objective. Thereafter, utilising the concepts of GP, an equivalent problem is derived, and the sum of deviation variables associated with the objectives are minimised. The GA is used further to obtain the optimal cell design. A software toolkit is developed based on the proposed technique using C Sharp.net to ensure its use in a larger scale. The effectiveness of the technique is judged based on a set of test problems of different sizes. The proposed technique is found to be better in terms of the performance measure over the existing ones.
Keywords: Manufacturing Cell Design; Multi-objective Optimization; Goal Programming; Genetic Algorithm.
Lights on the shadows: exploring the need for regulation in shadow banking
by Valentina Lagasio, Marina Brogi
Abstract: Since the outbreak of the economic and financial crisis of 2007-2008, the shadow banking system gained attention and caused concerns among standard setters, policy makers, and academics. This research is aimed at analysing the growth of the shadow banking system and assessing whether and how shadow banking entities should be further regulated. Using an instrument-based definition we infer the need for regulation in the shadow banking system by directly investigating the time series of asset backed commercial paper (ABCP) and securitised real estate loans (SREL). By means of several advanced and refined econometric tests, we explore time series data and find a non-stationary trend. This provides support for the need to regulate shadow banking. Further policy implications are discussed in detail.
Keywords: shadow banking system; financial intermediation; Asset Backed Commercial Paper; Securitized Real Estate Loan; time series analysis.
A production capacity optimisation model for a global supply chain coordinator
by Snehamay Banerjee, Damodar Golhar, Ram Gopalan
Abstract: A supply chain coordinator (SCC) serves as an intermediary between raw material suppliers, contract manufacturers, and end customers who are typically large retailers. The SCC may not actually own a physical manufacturing plant or supply raw material, but performs a crucial coordinating role in a supply chain by orchestrating the purchase of raw material and contract manufacturing of customised products for distribution to globally dispersed retailers. In this intermediary role, the SCC exploits global differences in manufacturing costs at various candidate facilities, but also bears operational risks if the demand at end retailers is significantly different from projected forecasts. This research addresses a facility choice, capacity selection, productions and transportation decisions faced by a SCC who tries to fulfil a multi-period, counter-seasonal demand at a guaranteed service level. A mathematical programming model is developed that integrates the various decision variables. The use of the model as a contract negotiation tool is also illustrated.
Keywords: supply chain coordinator; SCC; contract manufacturing; counter seasonal demand.
A risk-based emergency group decision method for haze disaster weather based on cumulative prospect theory
by Haitao Li
Abstract: The frequent occurrence of extreme haze episodes currently in China has caused widespread public concern. The Chinese Government has developed and implemented a series of long-term measures to mitigate the serious situation. Nevertheless, some emergency response measures are also needed in the short-term. Hence, a risk-based emergency group decision method for haze disaster weather based on cumulative prospect theory (CPT) with linguistic evaluation information is proposed. This method obtains and expresses group decision-makers' (DMs') evaluation information based on additional linguistic evaluation scale and its extended scale, calculates the comprehensive prospect value matrix of each haze emergency response alternative based on CPT, after that, calculates the final decision results with DMs' weights. On these bases, the best haze disaster emergency response alternative can be selected. Finally, an application case of HD city in North China is presented to illustrate the usefulness and effectiveness of the proposed method.
Keywords: haze disaster weather; risk-based emergency group decision-making; cumulative prospect theory; CPT; linguistic evaluation information.
A heuristic algorithm enhanced with probability-based incremental learning and local search for dynamic facility layout problems
by T.G. Pradeepmon, Vinay V. Panicker, R. Sridharan
Abstract: The dynamic facility layout problem (DFLP) involves finding an arrangement of facilities that minimises the sum of material handling cost and rearrangement cost over multiple periods. In this paper, the DFLP is modelled as a multiple quadratic assignment problem (QAP), one for each period. Probability-based incremental learning algorithm with a pair-wise exchange local search (PBILA-PWX) is proposed for solving the QAP for each period. The proposed heuristic and 16 algorithms available in the literature are applied for solving a set of 48 benchmark instances of the DFLP. For most of the problem instances, the proposed heuristic provides better results in comparison with an existing robust algorithm. The deviations of the solutions for the proposed heuristic are found to be within 5% of the best known solutions. A case study conducted for determining the machine shop layout of firm manufacturing printing machines is also presented.
Keywords: quadratic assignment problem; QAP; dynamic facility layout problem; DFLP; estimation of distribution algorithm; probability-based incremental learning; pair-wise exchange local search; PBILA-PWX.
Time-cost trade-off resource-constrained project scheduling problem with stochastic duration and time crashing
by Zhe Zhang, Xuejuan Zhong
Abstract: In this paper, time crashing is implemented to solve the limitation of buffer insertion when consider the high variability of activities and resources in resource constrained project scheduling problem (RCPSP). The activity duration and resource are considered to be beta and exponential distributed, respectively. To settle the discrete time-cost trade off problem, a nonlinear combinatorial optimisation model is developed to pursuing the time, cost and robustness of the project. Six improvement principles are proposed and three balance points are discovered according to the different situations in the time-cost trade-off process, in which the earliness bonus, tardiness penalty, instability cost and time crashing cost are involved. To minimise total budget of the project, tabu search and starting time criticality heuristic is designed as the solution method. Finally, a numerical example is presented to highlight the efficiency of proposed model and solution method.
Keywords: resource constrained project scheduling problem; RCPSP; time crashing; time-cost trade-off; uncertainty.
3D model for optimising the communication topologies of iterated N-players prisoners' dilemma
by Sally Almanasra, Khaled Suwais
Abstract: The evolution of cooperative behaviour in iterated N-players prisoners' dilemma (INPPD) is studied over several communication topologies. Existing models presented several solution models for evolving the cooperative behaviour among INPPD players. The researches revealed that none of the existing models pay attention to the pivot role of the best players in evolving the cooperative behaviour. In this paper, we present a 3D model for optimising communication topologies of INPPD to increase the cooperative rate between players. The 3D model aims to transfer well-known topologies to new 3D topologies that give the best players major roles in the game. This is important as exchanging experiences between players is essential for evolving effective cooperation. Concerning the evolutionary algorithm, this model was designed with the support of a genetic algorithm with synchronous updating to evolve the players' strategies. The results showed that the 3D model could increase the cooperative rate dramatically when compared to the original communication topologies.
Keywords: communication topology; prisoners' dilemma; game theory; iterated N-players prisoners' dilemma; INPPD.