• Korean Journal of Legislative Studies
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• v.15 no.1
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• pp.93-118
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• 2009

Why the National Assembly of Korea shows the serious disagreements or arguments in its operation? Regarding the question, this study pays attention to the perceptual differences among the parties for the structure of collective decision-making in the National Assembly of Korea. In addition, this study asserts that deepens the conflicts and the distrust in it. To be more specific, this study discusses about the optimal model for collective decision-making in legislative politics based on Buchanan and Tullock's opinion about it. And then, the trust in legislature forms the basis that makes it possible to respect the will of majority and protect the right of minority. The main reason that can't make the collective decision-making optimally in the National Assembly of Korea is to fight each other without the consensus about it. In this vein, making the collective decision-making optimally and recovering the trust among the parties are necessary to adopt a more consensual system. It will be helpful to prevent the use of noninstitutional means like the outside struggles or physical resistances in the National Assembly of Korea.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.113-122
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• 2015

Collective intelligence can be an influential factor of decision-making based on collaboration and information exchange between individuals. Our study explores whether collective intelligence can mitigate the loss aversion effect, bias and error in human judgment, and collective intelligence in online communities can reduce the loss aversion effect. Our community settings display both individual-level and group-level loss aversion effect, investigate effective collective intelligence characteristics like investment commitment, participant experience. Using a multi-method approach our research comprises a web-based experiment with 100 participants investing 3 situations from a real-world community, data from a survey measuring loss aversion behavior of participants. The results suggest the loss aversion effect mitigates under the online-circumstance. Overall, our results suggest that, while collective intelligence mitigates the loss aversion effect, participants do not transfer these results to other settings.

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

• Journal of Korean Philosophical Society
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• v.144
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• pp.257-283
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• 2017

The purpose of this paper is primarily to examine models of collective decision-formation and decision-making. The goal is to propose a model of decision-formation and decision-making that is appropriate for a democratic society. Habermas distinguishes these models of decision-formation and decision-making by liberal, republican, and deliberative political models according to their justification types. Axel Honneth, on the other hand, is divided into three models of liberalism, proceduralism, and republicanism. I want to divide the model of possible decision-making in democratic society into three, that is, the model based on force, the model based on procedure, and the republican model. This distinction will identify the characteristics of each decision-making model and this confirmation will help us find the best decision-making model for a democratic society. In the end, I will combine the republican model with the procedural model. For this synthesis, I will also propose three conditions in modern society. I will argue that the three conditions of collective intelligence, active freedom, and horizontal networks are necessary.

• Asia pacific journal of information systems
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• v.14 no.2
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• pp.37-59
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• 2004

Team decision making is a collective behavior that needs to be understood by considering properties belonging to team and individual member domains together. This paper introduces a conceptual model called "Dual-Level(DL)" model that describes a team decision-making process in terms of team level, member level, and the relationship between them. The team-level view explains the decision-making process by considering the team as a wholeand divides the process into three stages: Problem Conceptualization, Alternative Generation, and Selection. The member-level view describes what happens to individual members when they go through the group process and splits it into the five phases: Individual Cognitive Mapping, Problem Decomposition, Subproblem Session, Subproblem Integration, and Team Decision. The DL model works as a theoretical framework to explore team decision making by using a set of computational models of team design and team members. In practice, the conceptual framework is used to build a computational model of decision making team, called "Team-Soar."

• Journal of Digital Convergence
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• v.7 no.4
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• pp.169-180
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• 2009

IT governance implies a system in which all stakeholders with a given organization, including the board, internal customers, and related areas such as finance provide the necessary input into their decision-making process. However, the concepts of IT governance are broad and ambiguous, so IT governance is eventually needed multi-criteria decision making. This paper presents a hierarchical structure to better understand the relationship between control structure and the complexity of collective behavior with respect to IT governance and proposes a corresponding fuzzy model for analyzing IT governance complexity based on an extensive literature review. The results of this study are expected to provide a clearer understanding of how the concerns of IT governance behave and how they interact and form the collective behavior of the entire system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.237-246
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• 2016

Recently various types of cyber attacks have occurred. The strategic goals & tactical means of these have evolved. Especially KHNP cyber attack was the type of hacktivism combined hack and psychological warfare. The cyber attackers have forecd the nation to participate in the cyber warfare and the government to make strategic decisions to the releases of confidential information and the threats of stopping KHNP. In this paper, we would like to study the effective strategic decision-making model utilizing the game theory and including an attack intelligence on open policy Decision framework.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.533-538
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• 2015

Collective intelligence is related to several areas such as sociology, business administration, political science, and computer science. This paper can be classified as a product of social engineering of the era of liberal arts and science convergence, fusion, consilience. Members today have higher need for self-actualization and contribution. As the business is changing fast and getting more complicated, a mechanism of natural science is necessary in social organization. The mechanisms of collective intelligence are composed of divergence process and convergence process. And the seven steps were designed that the first letter of each steps leads to 'PROCESS'. When implemented by applying the procedures that reflect the opinions of members throughout this paper, there are members who participated in the decision-making process will contribute to actively participate in the decision when to run, and specific tools and techniques in online communities are for future studies.

• Knowledge Management Research
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• v.19 no.3
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• pp.173-187
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• 2018

This study was aimed at suggesting an integrative framework for creating collective intelligence and enhancing group performance after reviewing previous studies including those related to learning organizations, organizational learning, knowledge management, and collective intelligence. In the first, we examined that the similarities and differences between collective intelligence and other similar concepts, such as learning organizations, organizational learning, and knowledge management. Next, an integrative framework for creating collective intelligence and channeling it into strong group performance were suggested. In this process, we reviewed conditions for creating collective intelligence and segmented the major variables as expectancy, valence, and instrumentality, according to Vroom's (1964) expectancy theory. Characteristics of problems and the roles of leaders were respectively considered as valence for inducing collaboration and expectancy for managing probability to achieve goals. Instrumental factors were also adopted from conditions for creating group intelligence suggested from several researchers, such as creativity, openness, willingness for working together, horizontal communication, centralization in decision making, and building effective information and communication technology system and active usage of it. We discussed two potentially disputable matters about the scope and level of collective intelligence and group performance and suggest several theoretical and practical implications in the Discussion.