• Title/Summary/Keyword: collective intelligence

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Collective Intelligence and Human Decision Bias (집단지성(Collective Intelligence)과 의사결정의 편향성)

  • Han, Joo-Hee;Shin, Kyung-shik;Chai, Sangmi
    • 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.

A Study on the User Acceptance Model of Mass Collective Intelligence (대중 집단지성의 사용자 수용 모형에 관한 연구)

  • Lee, Hyoung-Yong;Ahn, Hyun-Chul
    • Journal of Information Technology Applications and Management
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    • v.17 no.4
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    • pp.1-17
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    • 2010
  • As web technologies evolve and so-called Web 2.0 technologies appear, collective intelligence is being applied in widespread areas. In general, mass collective intelligence like Wikipedia is created, revised, and managed by anonymous participants in an uncontrolled system. Thus, the knowledge provided by mass collective intelligence may be distorted, and may not be true, which may affect the user acceptance behavior. However, there have been few academic studies that analyzed the factors that affect user acceptance of mass collective intelligence, and their relationships. Under this academic background, we develop a model to examine how mass collective intelligence is accepted by users. The theoretical model is validated through an online survey of the Wikipedia users from three universities in Korea. The results reveal that the users will have positive attitude towards adopting mass collective knowledge when they perceive that the knowledge from mass collective intelligence is useful. We also find that the perceived usefulness of the knowledge is affected by perceived knowledge quality and trust in knowledge contributors. The results also suggest that perceived knowledge quality is determined by perceived level of collaboration, perceived objectivity, and recipient expertise, whereas trust in knowledge contributors is determined by natural propensity to trust and perceived objectivity. Theoretical and practical implications about mass collective knowledge are discussed.

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An Integrative Framework for Creating Collective Intelligence and Enhancing Performance (집단지성과 성과창출을 위한 통합적 개념틀 검토)

  • Chu, Cheol Ho;Ryu, Su Young
    • 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.

A Study on Measurement of Collective Intelligence using Business Management Game (소셜네트워크를 이용한 집단지성 측정연구)

  • Yun, Ho-Seong;Lee, Ki-Dong
    • Journal of Digital Convergence
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    • v.9 no.2
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    • pp.53-63
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    • 2011
  • In connection with each other through social networks, individuals share valuable knowledge and information. Furthermore the knowledge and information based on the collective intelligence is growing. Collective intelligence with more peoples will grow by gathering intelligence to enhance the collective intelligence. This study investigates the collective intelligence using business management game, and observes forming process of collective intelligence. To achieve the objective to observe the forming process of collective intelligence, only the test subjects available were exposed to the Corporate Management Game with SNS space. During the experimentation, the interaction and feedback were observed. The results of the study show that different performance, feedback and interaction for each group.

The Effects of Confirmation in Collective Intelligence Quality on Continuance Intention through Trust (지식검색 서비스에서 집단지성 품질이 지속사용 의도에 미치는 영향: 기대일치이론과 신뢰를 중심으로)

  • Kim, Jin-Wan;Hong, Tae-Ho
    • The Journal of Information Systems
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    • v.20 no.4
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    • pp.1-22
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    • 2011
  • This study addressed trust to collective intelligence for explaining the affecting factors to the intention to use of collective intelligence by dividing the object of trust into a Web site and an information source group. We explored the factors affecting user's continuance intention toward collective intelligence in the view off trust building. We made a well-structured survey of our proposed model and gained 205 cases. We analyzed the proposed research model empirically using partial least square method. The findings are summarized as follows. First, all key factors (relevance, timeless, completeness, understandability) composing of collective intelligence quality have a positive and significant impact on confirmation. Second, confirmation has a significant impact on trust toward a Web site, as well as toward an information source group. The last is that trust toward a Web site influences on continuance intention, whereas trust toward an information source group doesn't.

The Structural Relationship among Individual Creativity, Team Trust, Team Efficacy and Collective Intelligence in Collaborative Learning at Universities (대학 협력학습에서 개인창의성, 팀신뢰, 팀효능감 및 집단지성의 구조적 관계)

  • Song, Yun-Hee
    • Journal of Convergence for Information Technology
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    • v.10 no.9
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    • pp.173-182
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    • 2020
  • In recent years, collaborative learning in university courses has been emphasized in order to improve collective intelligence. Based on literature reviews, individual creativity was used as a variable of personal characteristic, team trust and collective efficacy were used as variables of teams to see the relationship with collective intelligence as a variable of learning outcome. Data were collected from 770 students from A University in Gyeonggi-do, H University in the Daejeon, and K University in Chungcheong-do, and analyzed by using structural equations modeling. As results, individual creativity had significant influence on collective efficacy and collective intelligence. Team trust also had significant influence on collective efficacy and collective intelligence. In addition, collective efficacy had a positive effect on collective intelligence. This study will be able to utilize basic data for establishing instructional design and strategies of collaborative learning in the universities.

Social Media as a Platform of Collective Intelligence : An Exploratory Analysis Based on Communication Types (집단지성 플랫폼으로서의 소셜미디어 : 커뮤니케이션 유형별 실험 분석)

  • Kim, Tae-Won;Kim, Sang-Wook
    • Journal of Information Technology Services
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    • v.12 no.3
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    • pp.127-149
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    • 2013
  • Is the social web environment in which production, distribution and consumption of information occurs from users an environment where manifestation of collective intelligence is easily made? Or is the social web environment a condition that incites people to depend on the groupthink due to biased information? It is important to conduct empirical studies on the possibility of social media as a tool of collective intelligence under the situation where conflicting opinions prevail. However, most of the existing studies related to this were limited to an exploratory research rather than an empirical research. In this regard, this study attempted to examine if the social media can perform a part as a platform of the collective intelligence empirically. Based on the experimental results, it can be safely said that the communication methods of social media showed its usefulness in both 'intellectual capacity of the group' and 'problem-solving skill of the group.'

A Study of Establishing a Web Model of Historical and Geographical Information for Youths through 'Collective Intelligence' -Junior Maphistory e-encyclopedia

  • BANG, Mi-Hyang
    • Educational Technology International
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    • v.9 no.1
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    • pp.49-77
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    • 2008
  • As clearly suggested in the case of Wikipedia, collective intelligence is predicted to develop into the most important platform of knowledge and information in the future society. But it just remains at the level of activities for group projects in the present frame of education and so it doesn't lead to creating collective intelligence. This study looks into an 'information repository model of collective intelligence' that makes it possible to deliver an education process a priori of Shared Knowledge Reservoir to "Junior Digital Nomad", who is definitely and will be in existence, and that further enables them to be active there in reality. Based on this storage model, it suggests a practicable web system model; Junior Maphistory e-encyclopedia, which is appropriately consistent with the features of Web 2.0 and can grow into a general historical and geographical information service.

The Effect of Smart Work Quality on Collective Intelligence and Job Satisfaction (스마트워크 품질이 집단지성 및 직무만족에 미치는 영향)

  • Kim, Hyun-Chul;Kim, Oh-Woo
    • Journal of Distribution Science
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    • v.13 no.5
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    • pp.113-120
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    • 2015
  • Purpose - As the rapid development of ICT has been made recently, many domestic companies are trying to introduce smart work infrastructure. The purpose of institution of smart work is to enhance their performance. To this end, it is necessary to advance the way of working. Developing employees' collective intelligence should be regarded as a prerequisite for advancing the way of working. Job satisfaction of the employees is another important factor to enhance organizational performance. So this study aims to provide the theoretical background of systematic approach to smart work quality by empirically analyzing the effect of smart work quality on collective intelligence and job satisfaction. Research design, data, and methodology - A structural equation model was designed to examine cause-and-effect relationships among three latent variables(smart work quality, collective intelligence, job satisfaction). Three hypotheses were formulated. The first hypothesis is that the effect of smart work quality on collective intelligence will be positively and statistically significant. Likewise, the second hypothesis is that the effect of smart work quality on job satisfaction will be positively and statistically significant. Finally, the third hypothesis is that the effect of collective intelligence on job satisfaction will be positively and statistically significant. Based on the previous researches, 34 questionnaire items were developed to measure the effect of the three variables. The survey was conducted on 162 employees who are working under smart work environment. The number of the effective questionnaires for the analysis was 154. PASW Statistics 18 and AMOS 18 were used for the statistical analysis. Results - The validity and reliability test for questionnaire items have been carried out. From the factor analysis, 1 out of 34 items was eliminated. As a result, 33 out of 34 items were used for analyzing. The values of Cronbach's α ranged from 0.701 to 0.910, indicating the acceptable reliability of the questionnaire items. The values of χ2, df, CFI, TLI, RMSEA of the model are 102.838, 51, 0.949, 0.935, 0.082, respectively. So the structural equation model was statistically significant. The first and third hypotheses were supported. But the second hypothesis was rejected. Conclusions - An analysis using structural equation model showed meaningful implications about the effect of smart work quality on collective intelligence and job satisfaction. First, as the five quality elements of the smart work improved, the level of collective intelligence increased. Second, the statistical analysis showed smart work didn't have a direct effect on job satisfaction, which is inconsistent with the prior findings. The main purpose of smart work is to help achieve greater performance. The companies also need to make efforts to improve job satisfaction of their employees along with achieving greater performance. Third, an organization with higher level of collective intelligence showed greater job satisfaction. The companies under smart work environment need to develop functions to encourage participation, sharing, openness, and collaboration. This research will provide useful information for the companies which want to introduce smart work, distribution information system, management information system, etc.

The Structural Relationships among Emotional Intelligence, Communication Ability, Collective Intelligence, Learning Satisfaction and Persistence in Collaborative Learning of the College Classroom (대학생의 협력학습에서 감성지능, 의사소통능력, 집단지성, 학습만족도 및 학습지속의향 간의 구조적 관계)

  • Song, Yun-Hee
    • Journal of Convergence for Information Technology
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    • v.10 no.1
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    • pp.120-127
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    • 2020
  • The purpose of this study was to examine related variables that improve learning outcomes in collaborative learning. Based on literature reviews, emotional intelligence was used as a variable of personal character, communication ability and collective intelligence were used as variables in learning process, and learning satisfaction, and persistence were used as variables of learning outcomes. Data were collected from 3,475 students at A university, and were analyzed using structural equation modeling. The results of this study are as follows: First, it turned out that emotional intelligence had a significant and positive impact on communication ability, collective intelligence, learning satisfaction, and persistence. Second, communication ability influenced collective intelligence and persistence positively. Third, collective intelligence influenced learning satisfaction and persistence positively. Fourth, learning satisfaction had a significant and positive impact on persistence. These findings offer basic data for collaborative learning by revealing the structural relationships among related variables that improve learning outcomes in collaborative learning of college students.