Zhongsheng Hua

On the extent analysis method for fuzzy AHP and its applications

Abstract In a paper by Chang [D.Y. Chang, Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research 95 (1996) 649–655], an extent analysis method on fuzzy AHP was proposed to obtain a crisp priority vector from a triangular fuzzy comparison matrix. It is found that the extent analysis method cannot estimate the true weights from a fuzzy comparison matrix and has led to quite a number of misapplications in the literature. In this paper, we show by examples that the priority vectors determined by the extent analysis method do not represent the relative importance of decision criteria or alternatives and that the misapplication of the extent analysis method to fuzzy AHP problems may lead to a wrong decision to be made and some useful decision information such as decision criteria and fuzzy comparison matrices not to be considered. We show these problems to avoid any possible misapplications in the future.

The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility

Researchers and practitioners regard information technology (IT) as a competitive tool. However, current knowledge on IT capability mechanisms that affect firm performance remains unclear. Based on the dynamic capabilities perspective and the view of a hierarchy of capabilities, this article proposes a model to examine how IT capabilities (i.e., flexible IT infrastructure and IT assimilation) affect firm performance through absorptive capacity and supply chain agility in the supply chain context. Survey data show that absorptive capacity and supply chain agility fully mediate the influences of IT capabilities on firm performance. In addition to the direct effects, absorptive capacity also has indirect effects on firm performance by shaping supply chain agility. We conclude with implications and suggestions for future research.

Predicting corporate financial distress based on integration of support vector machine and logistic regression

The support vector machine (SVM) has been applied to the problem of bankruptcy prediction, and proved to be superior to competing methods such as the neural network, the linear multiple discriminant approaches and logistic regression. However, the conventional SVM employs the structural risk minimization principle, thus empirical risk of misclassification may be high, especially when a point to be classified is close to the hyperplane. This paper develops an integrated binary discriminant rule (IBDR) for corporate financial distress prediction. The described approach decreases the empirical risk of SVM outputs by interpreting and modifying the outputs of the SVM classifiers according to the result of logistic regression analysis. That is, depending on the vectors relative distance from the hyperplane, if result of logistic regression supports the output of the SVM classifier with a high probability, then IBDR will accept the output of the SVM classifier; otherwise, IBDR will modify the output of the SVM classifier. Our experimentation results demonstrate that IBDR outperforms the conventional SVM.

A DS-AHP approach for multi-attribute decision making problem with incomplete information

In this paper, a DS-AHP method is proposed for MADM problems with incomplete information. Different from most of current methods, the DS-AHP method solves a problem directly based on its incomplete decision matrix. On the base of Dempster-Shafer theory of evidence, our approach first identifies all possible focal elements from the incomplete decision matrix, and then it calculates the basic probability assignment of each focal element and the belief interval of each decision alternative. Preference relations among all decision alternatives are determined by comparing their belief intervals. A numerical example is studied to illustrate the detailed implementation process of the DS-AHP approach and demonstrate its potential applications in MADM problems with incomplete information.

Integration TRIZ with problem-solving tools: a literature review from 1995 to 2006

This paper surveys Theory of Inventive Problem Solving (TRIZ) integration into other creativity tools, methods and philosophies using a literature review of publications from 1995 to 2006. After explaining the motivation of the integrations, a categorical analysis is carried out on how TRIZ has been integrated with these tools based on publications of combining TRIZ with design problem-solving tools. The applications of the integrations in different industries are summarised, and possible future directions are presented. This paper can satisfy the needs of researchers and practitioners for easy reference of TRIZ and problem-solving tools, and hence promote the future development of TRIZ.

Allocating the fixed cost as a complement of other cost inputs: A DEA approach

In cost allocation problem, traditional DEA approaches allocate the fixed cost among a group of decision making units (DMUs), and treat the allocated cost as an extra input of each DMU. If costs except for the fixed cost are regarded as inputs in the cost allocation problem, then it is obvious that the fixed cost is a complement of other inputs rather than an extra independent input. Therefore it is necessary to combine the allocated cost with other cost measures in cost allocation problem. Based on this observation, this paper investigates the relationship between the allocated cost and the DEA efficiency score and develops a DEA-based approach to allocate the fixed cost among various DMUs. An example of allocating advertising expenditure between a car manufacturer and its dealers is presented to illustrate the method proposed in this paper.

A chi-square method for obtaining a priority vector from multiplicative and fuzzy preference relations

Abstract Decision makers (DMs)’ preferences on decision alternatives are often characterized by multiplicative or fuzzy preference relations. This paper proposes a chi-square method (CSM) for obtaining a priority vector from multiplicative and fuzzy preference relations. The proposed CSM can be used to obtain a priority vector from either a multiplicative preference relation (i.e. a pairwise comparison matrix) or a fuzzy preference relation or a group of multiplicative preference relations or a group of fuzzy preference relations or their mixtures. Theorems and algorithm about the CSM are developed. Three numerical examples are examined to illustrate the applications of the CSM and its advantages.

Effects of supply chain integration and market orientation on firm performance: Evidence from China

Purpose – The present paper aims to investigate the impact of two different dimensions of supply chain integration on two aspects of firm performance in the emerging economy of China. In addition, the moderating effects of market orientation on the relationship between supply chain integration and firm performance are explored.Design/methodology/approach – Data were obtained from a survey administered to 246 firms in the manufacturing and services industry in China. Hierarchical regression analysis was used to test the hypotheses.Findings – Operational coordination is positively associated with operational performance and business performance. Information sharing affects only operational performance; it has no impact on business performance. Furthermore, the results provide empirical support for the moderating effects of market orientation on the association of supply chain integration and firm performance.Originality/value – The current paper contributes knowledge on the value‐realizing mechanism of supp...

A note on channel performance under consignment contract with revenue sharing

Abstract Wang et al. [Y. Wang, L. Jiang, Z.J. Shen, Channel performance under consignment contract with revenue sharing. Management Science 50 (2004), 34–47] indicate that a decentralized supply chain cannot be perfectly coordinated. This note provides a cooperative game model that implements profit sharing between the manufacturer and the retailer to achieve their cooperation. When the manufacturer and the retailer are assumed to be risk-neutral, under a very mild restriction on the demand distribution function, the cooperative game model can achieve its unique equilibrium solution in iso-price-elastic or linear demand case. Under the revenue sharing agreement attached with the equilibrium payment scheme, the decentralized supply chain can be perfectly coordinated.

Semi-supervised learning based on nearest neighbor rule and cut edges

In this paper, we propose a novel semi-supervised learning approach based on nearest neighbor rule and cut edges. In the first step of our approach, a relative neighborhood graph based on all training samples is constructed for each unlabeled sample, and the unlabeled samples whose edges are all connected to training samples from the same class are labeled. These newly labeled samples are then added into the training samples. In the second step, standard self-training algorithm using nearest neighbor rule is applied for classification until a predetermined stopping criterion is met. In the third step, a statistical test is applied for label modification, and in the last step, the remaining unlabeled samples are classified using standard nearest neighbor rule. The main advantages of the proposed method are: (1) it reduces the error reinforcement by using relative neighborhood graph for classification in the initial stages of semi-supervised learning; (2) it introduces a label modification mechanism for better classification performance. Experimental results show the effectiveness of the proposed approach.