• Journal of Distribution Science
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• v.13 no.4
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• pp.9-19
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• 2015

Purpose - This study focuses on the use of evaluative criteria software for imprecise market information, and product mapping relationships between design parameters and customer requirements. Research design, data, and methodology - This study involved using the product predicted value method, synthesizing design alternatives through a morphological analysis and plan, realizing the synthesis in multi-criteria decision-making (MCDM), and using its searching software capacity to obtain optimal solutions. Results - The establishment of product designs conforms to the customer demand, and promotes the optimization of several designs. In this study, the construction level analytic method and the simple multi attribute comment, or the quantity analytic method are used. Conclusions - This study provides a solution for enterprise products' multi-goals decision-making, because the product design lacks determinism, complexity, risk, conflict, and so on. In addition, the changeable factor renders the entire decision-making process more difficult. It uses Fuzzy deduction and the correlation technology for appraising the feasible method and multi-goals decision-making, to solve situations of the products' multi-goals and limited resources, and assigns resources for the best product design.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.3 s.43
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• pp.271-284
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• 1992

The purpose of this study is to clarify the change of important clothing evaluative criteria according to the clothing buying process and to bulid the flow chart of clothing buying process and clothing evaluative criteria. The study is carried out in two ways, they are, literature study and empirical survey. The results are as following; 1. the change of the important clothing evaluative criteria according to the clothing buying process is found out. 2. The clothing buying process is that problem recognition -1 decision of clothing wearing situation $\rightarrow$ search and evaluation of genaral Clothing information $\rightarrow$ decision of price limit $\rightarrow$ (search and evaluation of brand information 1 narrowing of brand range) $\rightarrow$ search and evaluation of store information $\rightarrow$ decision of store $\rightarrow$ search and evaluation of clothings in the store $\rightarrow$ narrowing of determinant clothing range $\rightarrow$ trial, trial evaluation and decision $\rightarrow$ buy-ing (or reject) $\rightarrow$ result evaluation. 3. The flow chart is built by the clothing buying process and the clothing evaluative criteria

• Journal of the Korean Society for Aviation and Aeronautics
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• v.11 no.2
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• pp.43-58
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• 2003

To decide the type of airplane to purchase in air service agencies is a typical matter of multi-criteria decision making process. The selection of airplane type is very important because it has great impact on the budget and management of air service agency, once the decision has been made. AHP is being recognized as one of many effective methods of multi-criteria decision making processes. In this study, checklist for the selecting optimum type of light airplane to be purchased is developed by the AHP.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.125-142
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• 1999

The increased investment in technological innovations makes the investigation of factors affecting technology adoption more interesting. Several perspectives have been proposed to explain the determinants of information technology adoption. While the traditional innovation diffusion research streams try to explain and predict adoption behavior with the adopter's perceptions about the characteristics of the innovation itself, critical mass theorists argue that adoption behavior as a collective action is based on what their business partners are doing and whether there exists enough critical mass to justify the investment. Drawing on theses two perspectives, this study investigates the decision criteria in the adoption of information technology as innovation and factors affecting the decision criteria. The survey results reveal that the adoption behavior is affected both by innovation characteristics and by critical mass's activity. Correlation analysis, t-test, and stepwise regression models also show that as the environmental uncertainty is getting higher, adoption decision is affected more by what others are doing, and that highly competitive organizations seem to play the role of critical mass.

• IE interfaces
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• v.16 no.spc
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• pp.14-20
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• 2003

This paper presents a multi-criteria decision model and Multi-Criteria Generic Algorithm(MCGA) approach to improve backbone topology by leveraging the Virtual Link(VL) system in an hierarchical Link-State(LS) routing domain. Given that the sound backbone topology structure has a great impact on the overall routing performance in an hierarchical LS domain, the importance of this research is evident. The proposed decision model is to find an optimal configuration of VLs that properly meets two-pronged engineering goals in installing and maintaining VLs: i.e., operational costs and network reliability. The experiment results clearly indicates that it is essential to the effective operations of hierarchical LS routing domain to consider not only engineering aspects but also specific benefits from systematical layout of VLs, thereby presenting the validity of the decision model and MCGA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.649-664
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• 2011

Cooperative spectrum sensing (CSS) with decision fusion is considered as a key technology for tackling the challenges caused by fading/shadowing effects and noise uncertainty in spectrum sensing in cognitive radio. However, most existing solutions assume an error-free decision transmission, which is obviously not the case in realistic scenarios. This paper extends the general decision-fusion-based CSS scheme by considering the fading/shadowing effects and noise corruption in the common control channels. With this more practical model, the fusion centre first estimates the local decisions using a binary minimum error probability detector, and then combines them to get the final result. Theoretical analysis and simulation of this CSS scheme are performed over typical channels, which suggest some performance deterioration compared with the pure case that assumes an error-free decision transmission. Furthermore, the fusion strategy optimization in the proposed cooperation model is also investigated using the Bayesian criteria. The numerical results show that the total error rate of noisy CSS is higher than that of the pure case, and the optimal values of fusion parameter in the counting rule under both cases decrease as the local detection threshold increases.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.15-23
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• 2021

Most of the open-source decision tree algorithms are based on three splitting criteria (Entropy, Gini Index, and Gain Ratio). Therefore, the advantages and disadvantages of these three popular algorithms need to be studied more thoroughly. Comparisons of the three algorithms were mainly performed with respect to the predictive performance. In this work, we conducted a comparative experiment on the splitting criteria of three decision trees, focusing on their interpretability. Depth, homogeneity, coverage, lift, and stability were used as indicators for measuring interpretability. To measure the stability of decision trees, we present a measure of the stability of the root node and the stability of the dominating rules based on a measure of the similarity of trees. Based on 10 data collected from UCI and Kaggle, we compare the interpretability of DT (Decision Tree) algorithms based on three splitting criteria. The results show that the GR (Gain Ratio) branch-based DT algorithm performs well in terms of lift and homogeneity, while the GINI (Gini Index) and ENT (Entropy) branch-based DT algorithms performs well in terms of coverage. With respect to stability, considering both the similarity of the dominating rule or the similarity of the root node, the DT algorithm according to the ENT splitting criterion shows the best results.

• Journal of applied mathematics & informatics
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• v.42 no.2
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• pp.257-281
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• 2024

In real life, a decision-maker can assign multiple values for pairwise comparison with a certain confidence level. Studies incorporating multi-choice parameters in multi-criteria decision-making methods are lacking in the literature. So, In this work, an extension of the Best-Worst Method (BWM) with multi-choice pairwise comparisons and multi-choice confidence parameters has been proposed. This work incorporates an extension to the original BWM with multi-choice uncertainty and confidence level. The BWM presumes the Decision-Maker to be fully confident about preference criteria vectors best to others & others to worst. In the proposed work, we consider uncertainty by giving decision-makers freedom to have multiple choices for preference comparison and having a corresponding confidence degree for each choice. This adds one more parameter corresponding to the degree of confidence of each choice to the already existing MCDM, i.e. multi-choice BWM and yields acceptable results similar to other studies. Also, the consistency ratio remained low within the acceptable range. Two real-life case studies are presented to validate our study on proposed models.

• The Research Journal of the Costume Culture
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• v.23 no.2
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• pp.213-227
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• 2015

This study understood what effect was produced on the purchasing decision making of outdoor wear by a shopping orientation, fashion involvement and demographic characteristics offered practical suggestions as to what effect was produced on the store selection criteria, product selection criteria for purchasing decision making in purchasing outdoor wear. This research was conducted through a questionnaire survey, and 397 males in were collected for analysis. The results were as follows. First, shopping orientation group was classified into hedonic shopping orientation group and utilitarian shopping orientation group. And it was classified into high fashion involvement group and low fashion involvement group according to fashion involvement. Product selection criteria were classified into 2 factors such as intrinsic attributes and extrinsic attributes. And store selection criteria were classified into 4 factors such as store atmosphere, store environment, promotion and salesmen. Second, there was partly significant difference in product selection criteria, and store selection criteria between utilitarian shopping group and hedonic shopping group. Third, there was significant difference in product selection criteria and store selection criteria between high fashion involvement group and low fashion involvement group. Finally, there was significant difference in the and according to age, job, and income among demographic characteristics.