A group decision model for credit granting in the financial market

As the number of people involved in a decisionmaking problem increases, the complexity of the group decision-making (GDM) process increases accordingly. The size of participants and the heterogeneous information have important effects on the consensus reaching process in GDM. To deal with these two issues, traditional methods divide large groups into smaller ones to reduce the scale of GDM and translate heterogeneous information into a uniform format to handle the heterogeneity problem. These methods face two challenges: 1) how to determine the appropriate group size? and 2) how to avoid or reduce loss of information during the transformation process? To address these two challenges, this article uses fuzzy cluster analysis to integrate heterogeneous information for large-scale GDM problems. First, a large group is divided into smaller ones using fuzzy cluster analysis and the F-statistic is applied to determine the satisfactory number of clusters. The original information is retained based on the similarity degree. Then, a consensus reaching process is conducted within these small groups to form a unified opinion. A feedback mechanism is developed to adjust the small GDM matrix when any group cannot reach a consensus, and the heterogeneous technique for order preference by similarity to an ideal solution (TOPSIS) is used to select the best alternative. To validate the proposed approach, an experiment study is conducted using a practical example of selecting the best rescue plan in an emergency situation. The result shows that the proposed approach helps to choose the best rescue plan faster.

show abstract

“…1 2 . Definition 3 [48]: A matrix R = (r ij ) m×n is defined as a fuzzy matrix, if r ij ∈ [0, 1] (i = 1, 2, .…”

Section: Definitions and Notationsmentioning

confidence: 99%

Heterogeneous Large-Scale Group Decision Making Using Fuzzy Cluster Analysis and Its Application to Emergency Response Plan Selection

Kou

Peng

2022

IEEE Trans. Syst. Man Cybern, Syst.

120

View full text Add to dashboard Cite

show abstract

“…As the number of subsidiaries continues to increase, the parent company faces a more complex and more volatile environment, and the challenges of corporate strategic management, organizational operations, and capital management follow (Gibbons et al 2011;Schotten and Morais 2019). Operations management is a key factor in an enterprise's survival (Rahiminezhad Galankashi et al 2020).…”

Section: Major Financial Managementmentioning

confidence: 99%

Identifying the key factors of subsidiary supervision and management using an innovative hybrid architecture in a big data environment

Hsu

Chen

et al. 2021

Financ Innov

View full text Add to dashboard Cite

In a highly intertwined and connected business environment, globalized layout planning can be an effective way for enterprises to expand their market. Nevertheless, conflicts and contradictions always exist between parent and subsidiary enterprises; if they are in different countries, these conflicts can become especially problematic. Internal control systems for subsidiary supervision and management seem to be particularly important when aiming to align subsidiaries’ decisions with parent enterprises’ strategic intentions, and such systems undoubtedly involve numerous criteria/dimensions. An effective tool is urgently needed to clarify the relevant issues and discern the cause-and-effect relationships among them in these conflicts. Traditional statistical approaches cannot fully explain these situations due to the complexity and invisibility of the criteria/dimensions; thus, the fuzzy rough set theory (FRST), with its superior data exploration ability and impreciseness tolerance, can be considered to adequately address the complexities. Motivated by efficient integrated systems, aggregating multiple dissimilar systems’ outputs and converting them into a consensus result can be useful for realizing outstanding performances. Based on this concept, we insert selected criteria/dimensions via FRST into DEMATEL to identify and analyze the dependency and feedback relations among variables of parent/subsidiary gaps and conflicts. The results present the improvement priorities based on their magnitude of impact, in the following order: organizational control structure, business and financial information system management, major financial management, business strategy management, construction of a management system, and integrated audit management. Managers can consider the potential implications herein when formulating future targeted policies to improve subsidiary supervision and strengthen overall corporate governance.

show abstract

“…(A i )) can be computed (shown in Table 10). Next, using Equations (12) to (14), the inclusion degrees of T 2 C1 are obtained as I δ…”

Section: C1mentioning

confidence: 99%

“…In addition, as the building-material supplier selection is a multi-attribute group decision-making (MAGDM) problem, how to express the judgments of a group and choose an appropriate MAGDM method are critical issues [12,13]. The rough number has proved to be an effective and objective tool in presenting the vagueness of human assessments, while the double normalization-based multiple aggregation (DNMA) method, which considers two types of normalized methods, three aggregation models, and a collective ranking score, is an effective ranking method for massive alternatives.…”

Section: Introductionmentioning

confidence: 99%

Green-Building-Material Supplier Selection with a Rough-Set-Enhanced Quality Function Deployment

et al. 2019

View full text Add to dashboard Cite

Building material supplier evaluation and selection is a significant strategic-decision problem for reducing construction costs and ensuring the quality of a residential product. As people are increasingly concerning about the green level of a residential product and the competition in the housing market is becoming increasingly fierce, it becomes important to select a green customer-oriented material supplier for property developers. Quality function deployment (QFD) has been proven to be an effective quality-control technique to take customer voices into consideration. However, the relationship matrix in the QFD technique, as a key to translate customer requirements into technical attributes, was subjectively given by decision-makers in previous studies, which failed to reflect customer requirements accurately. The aim of this study is to put forward a neighborhood-rough-set-based quality function deployment model for a green-building-material supplier selection. The neighborhood rough set, as a nonparametric and flexible data-mining approach, can effectively and objectively determine the core relationships between a variety of factors. A rough number-based aggregation approach is applied to effectively and objectively aggregate the evaluations given by a group of experts. Then, the classical double normalization-based multiple aggregation method, which considers two types of normalization methods, three aggregation models, and a comprehensive score formula, is extended in rough-number form in order to rank the alternatives. Afterward, an attempt is made to evaluate and rank eleven alternative building-material suppliers for a repute property developer in mainland China, and the corresponding comparative and sensitive analyses verify the effectiveness and robustness of the proposed hybrid model.

show abstract

A group decision model for credit granting in the financial market

Cited by 26 publications

References 30 publications

Heterogeneous Large-Scale Group Decision Making Using Fuzzy Cluster Analysis and Its Application to Emergency Response Plan Selection

Heterogeneous Large-Scale Group Decision Making Using Fuzzy Cluster Analysis and Its Application to Emergency Response Plan Selection

Identifying the key factors of subsidiary supervision and management using an innovative hybrid architecture in a big data environment

Green-Building-Material Supplier Selection with a Rough-Set-Enhanced Quality Function Deployment

Contact Info

Product

Resources

About