• Journal of Information Technology Applications and Management
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• v.28 no.1
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• pp.13-31
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• 2021

The purpose of this study is to find the factors that influence big data characteristics on decision satisfaction and utilization behavior, analyze the extent of their influence, and derive differences from existing studies. To summarize the results of this study, First, the study found that among the three categories that classify the characteristics of big data, qualitative attributes such as representation, purpose, interpretability, and innovation in the value innovation category greatly enhance decision confidence and decision effectiveness of decision makers who make decisions using big data. Second, the study found that, among the three categories that classify the characteristics of big data, the individuality properties belonging to the social impact category improve decision confidence and decision effectiveness of decision makers who use big data to make decisions. However, collectivity and bias characteristics have been shown to increase decision confidence, but not the effectiveness of decision making. Third, the study found that among the three categories that classify the characteristics of big data, the attributes of inclusiveness, realism, etc. in the integrity category greatly improve decision confidence and decision effectiveness of decision makers who make decisions using big data. Fourth, it was analyzed that using big data in organizational decision making has a positive impact on the behavior of big data users when the decision-making confidence and finally, decision-making effect of decision-makers increases.

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

• The Research Journal of the Costume Culture
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• v.12 no.3
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• pp.468-484
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• 2004

The purposes of this study were (1) to segment female college students' apparel shoppers into unique apparel buying decision-making style groups; and (2) to profile for each segment in terms of personal characteristics (material values, change seeking tendency and prestige sensitivity) and fashion information sources. Data were collected through questionnaires from convenient sample of 290 female college students. As a result of cluster analysis and univariate analysis of variance, distinctive consumer decision-making style groups of consumers were identified; Value-maximizing Recreational Shoppers, Brand-Maximizing Emotional Shoppers, and Apathetic Shoppers. These three groups were compared as to the effect of personal characteristics variables and fashion information sources through univariate analysis of variance and chi-square statistics. The result showed that personal characteristics (material values, change seeking tendency and prestige sensitivity) and fashion-information sources do influence the consumer decision-making styles and that these three groups were unique in their decision-making characteristics showing that consumer decision-making styles can be a good segmentation base for apparel market.

• Asia pacific journal of information systems
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• v.10 no.1
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• pp.1-18
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• 2000

One stream of the GDSS(Group Decision Support System) research is to investigate how GDSS affects decision performances of small groups according to task types, support features, meeting facilitation modes and meeting environments. But little study has investigated the effects of group member characteristics on group decision processes and outcomes depending upon whether GDSS is provided or not. To date, most GDSS studies have not controlled group member characteristics(e,g. personality, sex, decision style) in laboratory experiments. However, this study included the decision styles of group members as an independent variable. Therefore, this study investigated how differently members of two different decision styles perceive the use of GDSS in small group meetings through lab experiments. The two decision styles are feeling(F) style and thinking(T) style. We found that the effect of GDSS is a function of individual's decision style only in the communication thoroughness variable. The decision style is a statistically significant factor that can mediate the effects of the group support technology on the perceived communication thoroughness. Specifically, the GDSS is positively related to participants' perception about satisfaction on decision process, goal achievement, communication thoroughness, degree of influence-outward and effort for achieving meeting goals.

• Journal of Korean Academy of Nursing
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• v.29 no.4
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• pp.880-891
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• 1999

The purpose of this study was to describe nursing decision tasks, their characteristics, and problems associated with decision making. The subjects were 32 nurses who had at least one-year nursing experience and worked on medical-surgical units or intensive care units(ICU). They were asked to describe their decision making experiences in patient care situations and to identify the characteristics of each decisions. They were also asked to describe perceived problems associated with decision making in nursing. The responses on nursing decision tasks and problems were analyzed with content analysis and the decision characteristics were identified by statistical analysis of variance. It was found that there were 16 nursing decisions which are as follows : decisions related to interpreting and selecting appropriate strategies for pain management(6.6%) ; decisions related to providing emotional support (0.7%) ; decisions related to explaining the patient's condition and rationale for procedures(1.1%) ; decisions related to assisting patients to integrate the implications of illness and recovering into their lifestyles(2.9%) ; decisions related to detecting significant changes In patients and selecting appropriate intervention strategies (17.2%) ; decisions related to anticipating problems and selecting preventive measures(4.2%) ; decisions related to identifying emergency situations(0.4%) ; decisions related to effective management of patient crisis until physician assistance becomes available(2.8%) ; decisions related to starting and maintaining intravenous therapy(2.6%) ; decisions related to administering medications(8.1%) ; decisions related to combating the hazards of immobility(7.3%) : decisions related to treating wound management strategies(5.5%) ; decisions related to relieving patient discomfort(13.9) ; decisions related to selecting appropriate strategy according to the changing situation of the patient(18.2%) ; decisions related to selecting the best strategy for patient management(5.3%) ; and decisions related to coordinating, ordering, and meeting the various needs of the patient (3.1%). The nurses reported the fellowing problems in decision making : difficulties due to lack of knowledge and experience (18.6%) ; uncertainty and complexity of decision tasks(15.2%) ; lack of time to make decisions(2.9%) ; personal values which conflict with other staff(15.7%) ; lack of selection autonomy(30.0%) ; and organizational barriers(7.6%). Continuing education programs and decision support systems for frequent nursing decision tasks can be established on the basis of these results. Then decision ability in nurses will increase through the education programs and decision support systems, and then quality of nursing service will be better.

• Asia pacific journal of information systems
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• v.4 no.1
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• pp.74-114
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• 1994

In spite of the importance of group decision making in corporations and recent active research efforts in group decision support systems in the US., few studies have been done in the area of group decision making in Korea. There is an urgent need to understand the behavior and peculiar characteristics of group decision making in Korea before we initiate any research in developing computer systems to help group decision making. This study proposes a model for group decision making based on the literature survey and empirical studies have been conducted using the model Although this study is exploratory in nature, tentative hypotheses are given for future research in group decision making.

• The Research Journal of the Costume Culture
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• v.6 no.4
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• pp.120-135
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• 1998

The purpose of this study were to develop the taxonomy of apparel buying decision approaches and to identify the relationships between the apparel buying decision approaches and the situational characteristics. Data were collected via a questionnaire developed on the previous studies and the focus interview from 425 female college students living at Pusan, and analyzed by Factor Analysis, Cluster Analysis, Analysis of Variance, and Discriminant Analysis. Results indicated that apparel buying decision approaches consisted of eight dimensions and situational characteristics of affecting a particular apparel buying decision approaches were composed of three or five factors. The four types of apparel buying decision approaches were derived by Cluster Analysis and ANOVA: Recreational Shoppers, Brand Conscious Shoppers, Quality Conscious Shoppers, and Apathetic Shoppers. The findings revealed some patterns that were similar to previous studies and was useful to marketing managers who can view their customer segments in terms of the types in the taxonomy. Further, it provided a tool by which sales representatives can develop adaptive selling approaches based on a small set of buying situation and corresponding apparel buying decision approaches.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.171-186
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• 1998

While one main stream of research in GDSS (Group Decision Support System) is to investigate how GDSS affects decision-making performances of groups according to task types, support features, meeting facilitation modes and meeting environments. little study h3s been done about how group characteristics affect group decision processes and outcomes depending upon GDSS is provided or not. So far, most GDSS research has considered group characteristics (e.g. personality homogeneity) as given and did not include it as control variables in experiments. Therefore, the objective of this study is to investigate how members of two different groups perceive the use of GDSS in group meetings through lab experiments. The two groups are homogeneous and heterogeneous groups in terms of members' personality mix. This research found that the effect of GDSS is a function of groups' personality homogeneity in regards of the satisfaction on decision process and the communication thoroughness. The support of GDSS and the group homogeneity are proved to influence participant's perception about some dependent variables such as satisfaction on decision process.

• Journal of the Korean housing association
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• v.17 no.1
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• pp.107-115
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• 2006

It is the purpose of this study that propose method to estimate weights of decision-making for design concepts considering characteristics of places. In order to acquire these weights of concepts, the investigation with questionnaire by AHP(Analytic Hierarchy Process) is employed as a mean. Targets of this investigation was 63 respondents which were graduate students(21) and experts of design field(42). As a result, we could find differences between these weights of the relative concepts and know the differences in the weights of design concepts as characteristics of places were reflected. These weights of concepts will be take opinions about concept from design-related members into consideration. Therefore, In design process, the weights of design concepts will help for designer to verify the concepts in design initially, and finally be used by a criteria in decision-making. The Weights of decision-making for design concepts as a result of this study will be used as a guideline for the systematical and conceptual approach in design practice.

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.1-5
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• 2003

We purpose a decision model to select the optimal facilities for the Decision Making problems with multiple characteristics(nominal-is-best characteristics, larger-is -better characteristics, smaller- is -better characteristics). Using this model, concept of the loss function is used in this comprehensive method of for select the optimal preferred facilities. To solve the issue on the optimal preferred facilities for multiple characteristics, this study propose the loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms.