• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.9 no.4
• /
• pp.249-254
• /
• 2009

The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.

• Korean Journal of Mathematics
• /
• v.29 no.1
• /
• pp.137-167
• /
• 2021

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws (ST L) for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers (SFNs). Then, we presented a group decision- making (DM) strategy to address the multi-attribute group decision making (MAGDM) problem using the developed aggregation operators. In order to verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of laptop. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2005.11a
• /
• pp.183-192
• /
• 2005

Recently, community computing has been proposed for group formation and group decision-making. However, legacy community computing systems do not support group need identification for ad hoc group formation, which would be one of key features of ubiquitous decision support systems and services. Hence, this paper aims to provide a multi-agent based methodology to enable nomadic community computing which supports ad hoc need identification and group formation. Focusing on supporting group decision-making of relatively small sized multiple individual in a community, the methodology copes with the following three characteristics: (1) ad hoc group formation, (2) context-aware group need identification, and (3) using mobile devices working in- and out-doors. NAMA-US, an RFID-based prototype system, has been developed to show the feasibility of the idea proposed in this paper.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.3
• /
• pp.109-122
• /
• 2023

As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users' abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.

• Journal of Korean Home Economics Education Association
• /
• v.25 no.1
• /
• pp.1-14
• /
• 2013

The purpose of the study was investigated on that whether there was any statistical difference or not in terms of the career decision making according to the growth environment of High school students. The researcher surveyed 600 questionnaires for high school students and was using 539 questionnaires in the final analysis. They were analyzed by cluster analyses according to the growth environment scale and it classified into two cluster groups. The cluster group A and B had a significant difference on scores of the growth environment scale. The group A had more interested in activities such as political, social, intellectual, and cultural ones and participated at social and leisure activities. Moreover, the group was emphasis on moral and religious values. The group B got the higher score than group A about the score of the rational type of the career decision making: the group A got the higher score than the group B to the score of the dependent type. On the matter of the job information collection sub-scale, the group A got the higher score than the group B: the group A scored higher points than group B about the goal establishment and the self-estimate sub-scales. Therefore, in order to do the career-guidance of youths, each family had to provide positive growth environment which required various stimuli and affluent in experience settings for them to mature.

• International Journal of Human Ecology
• /
• v.7 no.1
• /
• pp.53-65
• /
• 2006

The purpose of this study was to examine the differences in the decision making styles of Korean and American consumers. Focus group interviews were used as the median to collect information related to their methods of approach to a market to buy a universal need such as clothing for personal use. Findings suggest that within each construct, there may be different factors that should be used to measure the decision making styles of Korean and American consumers. It also implies that the previously established Consumer Decision making styles instrument may not be a reliable measure cross-culturally. Recommendations for future research are suggested.

• Journal of Fisheries and Marine Sciences Education
• /
• v.20 no.2
• /
• pp.286-296
• /
• 2008

This study aims to examine the relationship between teachers' parcitipation levels in the decision making process and the organizational effectiveness in the middle schools. To achieve this objectives, 559 teachers of 18 middle schools in Busan were involved through a questionaire. The results are as follows: First, teachers consider their participation in decision-making to be low. Second, teachers view the effectiveness of school systems higher than average. Third, the correlation between teachers' participation and the system effectiveness (including job satisfaction, organization adaptability and job achievement) was positively high. When teachers' participation levels were divided into 3 groups - low, middle, and high-, the system effectiveness appeared highest with the high- level participation group. These results suggest the need for teacher participation in decision making to enhance the effectiveness of school systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.7
• /
• pp.3128-3149
• /
• 2018

A number of effective methods for multiple-attribute group decision making (MAGDM) with interval-valued intuitionistic fuzzy numbers (IVIFNs) have been proposed in recent years. However, the different methods frequently yield different, even sometimes contradictory, results for the same problem. In this paper a novel criterion to determine the advantages and disadvantages of different methods is proposed. First, the decision-making process is divided into three parts: translation of experts' preferences, aggregation of experts' opinions, and comparison of the alternatives. Experts' preferences aggregation is considered the core step, and the quality of the collective matrix is considered the most important evaluation index for the aggregation methods. Then, methods to calculate the similarity measure, correlation, correlation coefficient, and energy of the intuitionistic fuzzy matrices are proposed, which are employed to evaluate the collective matrix. Thus, the optimal method can be selected by comparing the collective matrices when all the methods yield different results. Finally, a novel approach for aggregating experts' preferences with IVIFN is presented. In this approach, experts' preferences are mapped as points into two-dimensional planes, with the plant growth simulation algorithm (PGSA) being employed to calculate the optimal rally points, which are inversely mapped to IVIFNs to establish the collective matrix. In the study, four different methods are used to address one example problem to illustrate the feasibility and effectiveness of the proposed approach.

• Human Ecology Research
• /
• v.54 no.2
• /
• pp.207-225
• /
• 2016

This study investigated a conceptual framework of fashion consumers' purchase decision-making styles related to behavioral typology of personality. In response to critiques on fragmented and varied use of personality measurements, this study selectively tested and verified an alternative typological model of Enneagram value systems and self-construal levels that could explain the fashion consumers' typological propensities in purchase decision-making. One hundred-item measurement scale for the fashion consumers' purchase decision-making styles was developed based on the extensive literature. Three groups of fashion major students, a total of 107 participants, who respectively participated in 2-hour-long Enneagrams seminars from spring 2013 to fall 2014, were asked to re-sentence the question items to clearly reflect their Enneagram personality to make purchase decisions. Participants described their propensities in their own words about the most comfortable state during the 5-step processes of the purchase decision making process. The revised scale was distributed to 423 participants in January 2016, and the results verified the group differences in various styles in the process of purchase decision-making corresponding to the typological variables discussed in Enneagram. The correlation between Enneagram core values embodied by fashion consumers during the stages of purchase decision-making in extensive levels of self-construal were verified in the context of their fashion decision making. This study found the possibility of the typological approach toward Enneagram types of personality to be applicable to explain and predict peculiar facets of fashion consumers' purchase decision-making styles.

• Communications of Mathematical Education
• /
• v.26 no.2
• /
• pp.221-249
• /
• 2012

The purpose of this study is to investigate students decision-making progress through ill-structured problem solving process. For this study, 25 fifth graders in an elementary school were observed by applying ABCDE model (Analyze - Browse - Create - Decision making - Evaluate), and analyzed their decision-making progress analyzing framework which follows 3 steps - making their own decision, discussing/revising with peers, and lastly decision making/solving problem. Upper two groups with better performance in ill-structured problem solving model among 6 groups showed active discussion in group and decision making process with 3 steps (making their own decision, discussing/revising with peers). Even though their decisions are not good-fit to mathematical reasoning result, development and application of ill-structured problems would bring better ability of high level thinking and problem solving to students.