• 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.

• 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.

• 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.

• Journal of Information Technology Services
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• v.21 no.1
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• pp.103-125
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• 2022

This study empirically examines the correlation between the data, system, service quality, collective intelligence, innovation activity, and work performance of the KMS for employees of state-run enterprises. This study also confirmed that collective intelligence and innovation activity have a mediating effect on the relationship between KMS system quality and work performance. For this study, employees of state-run enterprises completed a 5-point Likert scale survey, and the data obtained were analyzed with descriptive statistics. The reliability and validity of variables were also verified through a measurement model analysis. Structural equation modeling of IBM SPSS 26 and AMOS 26 were used to prove the hypothesis. Through this study, For the improvement of sustainable work performance of state-run enterprises, which is a difficult issue to solve, not only should the quality of the KMS utilized in the enterprises be improved and managed, but also the design for various incentive schemes tailored to the enterprises' job characteristics, such as rewards, HR bonus, work incentives, job allowance, and encouragement from the head of the enterprise, should be reviewed and continuously developed in reflection of the active collective intelligence of the employees and the effect of innovation activities. Then, the work performance of public institutions will increase.

• Informatization Policy
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• v.17 no.4
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• pp.61-79
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• 2010

This study focuses on the emergence of collective intelligence and its impact on the democracy in the information era. Scholars have posed very different-optimistic and pessimistic-views on the possibility of collective knowledge produced by the public. Focusing on the cases of a free online encylopedia known as wikipedia and 2008 Candlelight Demonstration against the imports of US beef in Korea, this paper analyzes the mechanism of collective intelligence and its political implications on the democracy. Specifically, this article approaches changes in new knowledge paradigm with two different variables: the degree of connectivity and the quality of deliberation. Applying two different sets of variables helps us to distinguish the possibilities of collective intelligence and anti-intelligence, which would suggest social and political implications for the democracy in a country. This study finds a critical difference in terms of the quality of deliberation, measured by the indicators such as diversity, independence, and integration mechanism for online deliberation.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.75-99
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• 2012

Innovation can come from inside or outside organizations. Recently, organizations have begun turning to external knowledge more often, through various forms of collective intelligence (CI) as collaborative platform to solve complex problems. Several factors facilitate this CI utilization phenomenon. First, with the rapid development of Internet and social media, numerous web applications have become available to millions of the Internet users over the past few decades. Web 2.0 and social media have become innovative web applications that provide an environment for human social interaction and collaboration. Second, the diffusion of simple and easy-to-use technologies that enable users to interact and design web applications without programming skills have led to vast, previously unknown amounts of user-generated content. Finally, the Internet has enabled communities to connect and collaborate, creating a virtual world of CI. In this study, web enabled CI is defined as a composed ability of individuals who are acting as a single cognitive unit to achieve common goals, think reasonably, solve problems, make decisions, carry out complex tasks, and develop creative ideas collectively through participation and collaboration on the web. Although CI plays a critical role in organizational innovation and collaboration, the dubious quality of CI is still problem that is difficult to solve. In general, the quality level of content collected from the crowd is lower than that from professionals. Thus, it is important to identify determinants of CI quality and to analyze the relationship between CI quality and its usefulness. However, there is a lack of empirical study on the quality factors of web-enabled CI. There exist a variety of web enabled CI sites such as Threadless, iStockphoto or InnoCentive, Wikipedia, and Youtube. One of the most successful forms of web-enabled CI is the Wikipedia online encyclopedia, accessible all over the world. Another one example is Naver KnowledgeiN, a typical and popular CI site offering question and answer (Q&A) services. It is necessary to study whether or not different types of CI have a different effect on CI quality and its usefulness. Thus, the purpose of this paper is to answer to following research questions: ${\bullet}$ What determinants are important to CI quality? ${\bullet}$ What is the relationship between CI quality factors and the usefulness of web-enabled CI? ${\bullet}$ Does CI type have a moderating effect on the relationship between CI quality, its determinants, and CI usefulness? Online survey using Google Docs with email and Kakao Talk was conducted for collecting data from Wikipedia and Naver KnowledgeiN users. A totoal of 490 valid responses were collected, where users of Wikipedia were 220 while users of Naver KnowledgeiN were 270. Expertise of contributors, community size, and diversity of contributors were identified as core determinants of perceived CI quality. Perceived CI quality has significantly influenced perceived CI usefulness from a user's perspective. For improving CI quality, it is believed that organizations should ensure proper crowd size, facilitate CI contributors' diversity and attract as many expert contributors as possible. Hypotheses that CI type plays a role of moderator were partially supported. First, the relationship between expertise of contributors and perceived CI quality was different according to CI type. The expertise of contributors played a more important role in CI quality in the case of Q&A services such as Knowledge iN compared to wiki services such as Wikipedia. This implies that Q&A service requires more expertise and experiences in particular areas rather than the case of Wiki service to improve service quality. Second, the relationship between community size and perceived CI quality was different according to CI type. The community size has a greater effect on CI quality in case of Wiki service than that of Q&A service. The number of contributors in Wikipeda is important because Wiki is an encyclopedia service which is edited and revised repeatedly from many contributors while the answer given in Naver Knowledge iN can not be corrected by others. Finally, CI quality has a greater effect on its usefulness in case of Wiki service rather than Q&A service. In this paper, we suggested implications for practitioners and theorists. Organizations offering services based on collective intelligence try to improve expertise of contributeros, to increase the number of contributors, and to facilitate participation of various contributors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.45-53
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• 2020

In this paper, we propose the collective intelligence-based image shared market platform to provide a high quality of image saring services compared to that of the conventional image shared market platforms. The main contribution of this paper can be summarized as follows. First, the proposed platform provides the image sharing services with much more lower price than that of the conventional platforms since the price can be decided based on the buyers themself. Second, since the proposed platform provides very efficient web accessibility, the various buyer can access and evaluate the image efficiently. The results of performance evaluation show that the proposed image shared market platform can support the efficient image shared services efficiently.

• Journal of The Korean Association For Science Education
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• v.34 no.6
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• pp.523-534
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• 2014

This study aimed to develop collective intelligence (CI) based instructional models for teaching socioscientific issues on the basis of intimate collaboration with science teachers, and to investigate the participating teachers' perceptions on the effectiveness of the instructional models. Adapting the ADDIE model, we suggested three types of SSI instructional models (i.e. generative model, exploratory model, and decision-making model). Generative models emphasized the process of brainstorming ideas or possible solutions for SSI. Exploratory models focused on providing students opportunities to explore various SSI cases and diverse perspectives to understand its controversial nature and complexity. Decision-making models encouraged students to negotiate or develop a group-consensus on SSI through the dialogical process. After implementing the instructional models in the science classroom, the teachers reported that CI-based SSI instructional models contributed to encouraging students' active participation and collaboration as well as to improving the quality of their argument or discourses on SSI. They also supported the importance of developing collective consciousness on the issues in the beginning of the SSI class, providing independent time and space for reflecting on their personal values and opinions with scientific evidence, and formulating an atmosphere where they freely exchanged opinions and feedback for constructing better collective ideas.

• Journal of the Korea Institute of Building Construction
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• v.12 no.6
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• pp.664-673
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• 2012

Determining the layout of temporary facilities that support construction activities at a site is an important planning activity, as layout can significantly affect cost, quality of work, safety, and other aspects of the project. The construction site layout problem involves difficult combinatorial optimization. Recently, various artificial intelligence(AI)-based algorithms have been applied to solving many complex optimization problems, including neural networks(NN), genetic algorithms(GA), and swarm intelligence(SI) which relates to the collective behavior of social systems such as honey bees and birds. This study proposes a site facility layout optimization algorithm based on self-organizing maps(SOM). Computational experiments are carried out to justify the efficiency of the proposed method and compare it with particle swarm optimization(PSO). The results show that the proposed algorithm can be efficiently employed to solve the problem of site layout.

• Information Systems Review
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• v.13 no.1
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• pp.75-96
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• 2011

This research uses coolhunting to predict the future trend of e-Commerce industry. Coolhunting is a method to take Cool Trends which are the future trend through social network analysis for discovering the trendsetter and its collective intelligence. Coolhunting is generally carried out by social network analysis while this research uses NodeXL of social network analysis tools. We designed industrial network research model for relation among e-Commerce corporation, product, the types of customer service and customer service employee to discover the Cool Trends of e-Commerce industry. According to the result of this research, e-Commerce industrial network was being changed from chaos to collective intelligence form. As a analysis result for network influences, we found that Cool Trends of e-Commerce industry invigorate social commerce industry through the collective intelligence focusing intelligence VIP, Excellence, grade of Administrating for women customers(trendsetter) and it promotes semantic consumption from customers and purchasing power will be concentrated on cosmetic, beauty, perfume product categories in social commerce. We propose the strategic direction for e-Commerce corporation and hope that domestic e-Commerce corporation continues to grow and high-quality services are provided for customers.