A fuzzy integral-based model for supplier evaluation and improvement
Introduction
Supplier evaluation and improvement processes are the most significant variables in the effective management of globalization, as they improve organizations through the channels of high-quality products and customer satisfaction. The traditional approach has been to rank and select suppliers solely on the basis of price. However, moving from ranking/selection to selection/improvement decisions in the contemporary supply-chain network is complicated, as potential options for selection/improvement decisions are evaluated using multiple criteria. Therefore, supplier selection/improvement has become an MCDM problem that includes several tangible and intangible factors [3], [54]. Recently, these criteria have become increasingly complex, interdependent, and dynamic as environmental, social, political, and customer satisfaction concerns have been added to the traditional factors of quality, delivery, cost, and service. Additionally, traditional MCDM methods have generally only employed an additive model to evaluate, rank, and/or select the alternatives. More important, and from a practical standpoint, solving the problem of criteria gaps (gaps between actual performance and aspiration levels) while incorporating a non-additive (or super-additive) framework to address interdependence and feedback problems is a current trend within the MCDM field. Kahneman and Tversky [23] developed the basic concept of non-additive (or super-additive) value-function aggregation in multi-criteria problems. This concept has led researchers to an important question on how these two concepts (non-additive value functions and aspiration levels) can be applied to real world inter-relationship (dependence and feedback) problems. This article contributes a novel, hybrid, fuzzy integral-based DANP (DEMATEL-based ANP) model for reducing the gaps between each dimension and criterion to reach a given aspiration level in real world inter-relationship problems.
Effective supplier selection/improvement demands robust analytical methods and tools that are applicable to the supplier decision and able to analyze multiple subjective and objective criteria [2]. A series of literature reviews has summarized the criteria and decision methods that have appeared in papers since the mid-1960s. For example, in an exhaustive review of 76 articles, Weber et al. [53] found that 47 articles address the involvement of more than one criterion. Two journal articles [10], [59] reviewed the literature regarding supplier evaluation and improvement/selection models. Ho et al. [16] extended these reviews by surveying multi-criteria supplier evaluation and improvement/selection approaches through a literature review and a classification of international journal articles from 2000 to 2008. They concluded that only extensive, multi-criteria decision-making approaches have been proposed for supplier selection. The approaches include the analytic hierarchy process (AHP), analytic network process (ANP), data envelopment analysis (DEA), fuzzy set theory, genetic algorithms (GA), mathematical programming, the multi-attribute rating technique (i.e., gray relation, VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), technique for order preference by similarity to an ideal solution (TOPSIS), and their hybrids.
Prior studies have made significant contributions to supplier selection; however, they have assumed the criteria to be independent when modeling the supplier selection problem. In the real world, the criteria are seldom independent. In fact, the relationships between the criteria are all, to some extent, interactive and occasionally include dependence and feedback effects [20], [36], [46]. Others [19], [27], [30], [18], [29], [12] have accounted for this interdependence (i.e., by using the ANP) but nonetheless employed additive models (i.e., VIKOR, gray relation or TOPSIS) to aggregate performances and weights. However, these methods are inconsistent with the assumption that the criteria are interdependent. A means of avoiding this inconsistency is to apply non-additive fuzzy integrals to integrate the interdependent performance values. In this study, we improve on prior research in three ways. First, the interdependent relationships between, and weights of, the criteria are constructed and calculated using DEMATEL and a fundamental concept of the ANP called DANP. This method can derive weights directly from the DEMATEL results and accommodate the different degrees of influence across dimensions. It also avoids the time-consuming process of performing pair-wise comparisons between criteria required in the original ANP analysis. Second, based on the concepts of VIKOR, the traditional relative good solution from the existing alternatives is replaced by the aspiration levels to avoid the “Choose the best among inferior choices/options/alternatives”, i.e., avoid “Pick the best apple among a barrel of rotten apples” option. Third, a non-additive fuzzy integral is used to obtain influence weighted gaps that enable managers to better measure and understand the gaps between aspiration levels and actual levels and establish improvement priorities. Using this hybrid model, we can remedy the inconsistency in our prior studies [18], [29] that assume interdependent criteria but apply additive models. This study may present the first model that integrates the concepts of a non-additive value function and interdependence with feedback effects in the supplier selection problems. Moreover, the emphasis in the MCDM field has shifted from ranking and selection when determining the most preferable approaches to performance improvement. Our model provides a systematic approach to identify the source of problems rather than addressing the systems of the problems. We used data from a Taiwanese company to demonstrate this model. This generic model can be easily extended to other industries to aid other types of firms in selecting their optimal suppliers.
Section snippets
A brief review of the existing literature
Over the last two decades, various decision-making methods have been proposed to address supplier evaluation and selection problems. Critical reviews have summarized the criteria and decision methods employed in the supplier selection process, for example, Ho et al. [16], De Boer et al. [9], Degraeve et al. [10] Wu et al. [55] and Weber et al. [54]. Based on prior studies, we categorize the methodologies used to analyze the supplier selection problem as follows: (1) multi-attribute
Proposed fuzzy integral-based integrated approach
In this section, we introduce the analytical processes of the hybrid model as illustrated in Fig. 1. As shown in the figure, a DEMATEL-based ANP is used to establish the structural relationship model and determine the criteria weights with dependence and feedback. In a complex system, all system criteria are either directly or indirectly mutually related. In such intricate systems, it is very difficult for a decision maker to obtain a specific objective/aspect and avoid interference from the
Empirical example using a real case
An empirical study on the selection and improvement of service suppliers in the airline industry is used in this section to illustrate the feasibility of the proposed methodology.
Discussion
According to the global weights (Table 7) of the improvement/selection criteria, the relationship (11.2%) is the most important criterion in supplier improvement/selection, followed by cost savings (10.3%) and billing flexibility (10.1%). However, based on the INRM (Fig. 3) and the influential degree analysis (Table 4), cost has the lowest (ri − si) value. These interesting results indicate that managers do not believe that cost influences the other criteria; however, they nonetheless consider
Conclusion and remarks
This paper analyzes supplier evaluation using a fuzzy integral-based model. We improve on previous models in several ways. First, the traditional models assume that the criteria are independently and hierarchically structured; however, in reality, decision problems are frequently characterized by interdependent criteria and dimensions and may even exhibit feedback-like effects. We applied the DEMATEL method to construct the network relationship. The DEMATEL-based ANP method is then used to
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2020, Expert Systems with ApplicationsCitation Excerpt :During the last years, the research and development efforts made in the field of materials science have motivated the materials cost reduction for solar cells manufacturing, improving the total upfront costs and allowing for the adoption of PV energy (Ramírez et al., 2017). In the SC assessment the sourcing costs are directly related to the supplier selection (Ageron et al., 2012; Freeman & Chen, 2015; Lima-Junior & Carpinetti, 2016; Liou, Chuang, & Tzeng, 2014; Zhang, Shah, Wassick, Helling, & van Egerschot, 2014). In this research, sourcing costs is an indicator to minimise and the values, in € /Wp, have been obtained from the literature (IEA, 2015b; 2016; IRENA, 2012; Ossenbrink et al., 2013; Wirth, 2016) for the selected countries, Table 3.