• Title/Summary/Keyword: group modeling

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Relationships among Brand Equity Components: An Exploratory Study of the Moderating Role of Product Type (품패자산조성부분간적상호관계(品牌资产组成部分间的相互关系): 관우산품충류조절작용적탐색연구(关于产品种类调节作用的探索研究))

  • Moon, Byeong-Joon;Park, Won-Kyu;Choi, Sang-Chul
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.1
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    • pp.98-109
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    • 2010
  • Research on the construction, measurement, and management of brand equity has been extensive since David A. Aaker(1991) and Kevin Lane Keller(1993) first advanced the concept. Recently, much attention has been devoted to the components of brand equity: brand awareness, perceived quality, brand image, and brand loyalty. This study explores the relationships among these components, focusing particularly on the moderating role of product type (utilitarian vs. hedonic) in their causal relationships. A model to study the relationship among components of brand equity, particularly the moderating role of product type, is featured in Figure 1. The hypotheses of the study are proposed as follows: that consumers' brand awareness has a positive influence on brand loyalty and brand image; that consumers' perceived quality has a positive influence on brand loyalty and brand image; that consumers' brand image influences brand loyalty positively; and that relationships among components of brand equity will be moderated by product type. That is, in the case of utilitarian products, the impact of perceived quality on brand loyalty will be relatively stronger, whereas with hedonic products the impact of brand image on brand loyalty will be relatively stronger. To determine the products for the study, a pre-test of 58 college students in the Seoul metropolitan area was conducted based on the product type scale. As a result, computers were selected as the utilitarian product and blue jeans became the hedonic product. For each product type, two brands were selected: Samsung and HP for computers, and Levis and Nix for blue jeans. In the main study, 237 college students in the metropolitan area were surveyed to measure their brand awareness, perceived quality, brand image, and brand loyalty toward the selected two brands of each product type. The subjects were divided into two groups: one group (121 subjects) for computers, the other (116 subjects) for blue jeans. The survey questionnaires for the study included four parts: five questions on brand awareness and four questions each on perceived quality, brand image, and brand loyalty. All questions were to be answered using 7-point Likert scales. The data collected by the survey were processed to assess reliability and validity, and the causal relationships were analyzed to verify the hypotheses using the AMOS 7 program, a tool for analyzing structural equation modeling. A confirmatory factor analysis assessed the appropriateness of the measurement model, and the fit indices denoted that the model was satisfactory. The relationships among the components of brand equity were also analyzed using AMOS 7. The fit indices of the structural model denoted that it was also satisfactory. The paths in the structural model as will be seen in Figure 2 show that perceived quality affects brand image positively, but that brand awareness does not affect brand image. Moreover, it shows that brand awareness, perceived quality, and brand image are positively related with brand loyalty, and that this relationship is moderated by product type. In the case of utilitarian products, perceived quality has relatively more influence on brand loyalty. Conversely, in the case of hedonic products, brand image has relatively more influence on brand loyalty. The results of this empirical study contribute toward the advancement of our understanding of the relationships among the components of brand equity and expand the theoretical underpinnings for brand equity measurement. It also helps further our understanding of the effect of product type on customer-based brand equity. In a marketing management practice perspective, these results may provide managerial implications for building and maintaining brand equity effectively.

Environmental Health Surveillance of Low Birth Weight in Seoul using Air Monitoring and Birth Data (2002년 서울시 대기오염과 출생 자료를 이용한 저체중아 환경보건감시체계 연구)

  • Seo, Ju-Hee;Kim, Ok-Jin;Kim, Byung-Mi;Park, Hye-Sook;Leem, Jong-Han;Hong, Yun-Chul;Kim, Young-Ju;Ha, Eun-Hee
    • Journal of Preventive Medicine and Public Health
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    • v.40 no.5
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    • pp.363-370
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    • 2007
  • Objectives: The principal objective of this study was to determine the relationship between maternal exposure to air pollution and low birth weight and to propose a possible environmental health surveillance system for low birth weight. Methods: We acquired air monitoring data for Seoul from the Ministry of Environment, the meteorological data from the Korean Meteorological Administration, the exposure assessments from the National Institute of Environmental Research, and the birth data from the Korean National Statistical Office between January 1, 2002 and December 31, 2003. The final birth data were limited to singletons within $37{\sim}44$ weeks of gestational age. We defined the Low Birth Weight (LBW) group as infants with birth weights of less than 2500g and calculated the annual LBW rate by district. The air monitoring data were measured for $CO,\;SO_2,\;NO_2,\;and\;PM_{10}$ concentrations at 27 monitoring stations in Seoul. We utilized two models to evaluate the effects of air pollution on low birth weight: the first was the relationship between the annual concentration of air pollution and low birth weight (LBW) by individual and district, and the second involved a GIS exposure model constructed by Arc View 3.1. Results: LBW risk (by Gu, or district) was significantly increased to $1.113(95%\;CI=1.111{\sim}1.116)\;for\;CO,\;1.004(95%\;CI=1.003{\sim}1.005)\;for\;NO_2,\;1.202(95%\;CI=1.199{\sim}1.206\;for\;SO_2,\;and\;1.077(95%\;CI=1.075{\sim}1.078)\;\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was significantly increased to $1.081(95%\;CI=1.002{\sim}1.166)\;for\;CO,\;1.145(95%\;CI=1.036{\sim}1.267)\;for\;SO_2,\;and\;1.053(95%\;CI=1.002{\sim}1.108)\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was increased to $1.003(95%\;CI=0.954{\sim}1.055)\;for\;NO_2$, but this was not statistically significant. The air pollution concentrations predicted by GIS positively correlated with the numbers of low birth weights, particularly in highly polluted regions. Conclusions: Environmental health surveillance is a systemic, ongoing collection effort including the analysis of data correlated with environmentally-associated diseases and exposures. In addition. environmental health surveillance allows for a timely dissemination of information to those who require that information in order to take effective action. GIS modeling is crucially important for this purpose, and thus we attempted to develop a GIS-based environmental surveillance system for low birth weight.

A Feasibility Study for Decision-Making Support of a Radioactive Contamination Model in an Urban Environment (METRO-K) (도시환경 방사능오염 평가모델 METRO-K의 대응행위 결정지원을 위한 실용성 연구)

  • Hwang, Won-Tae;Han, Moon-Hee;Jeong, Hyo-Joon;Kim, Eun-Han;Lee, Chang-Woo
    • Journal of Radiation Protection and Research
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    • v.33 no.1
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    • pp.27-34
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    • 2008
  • A Korean urban contamination model METRO-K (${\underline{M}}odel$ for ${\underline{E}}stimates$ the ${\underline{T}}ransient$ Behavior of ${\underline{R}}adi{\underline{O}}active$ Materials in the ${\underline{K}}orean$ Urban Environment, which is capable of calculating the exposure doses resulting from radioactive contamination in an urban environment, is taking part in a model testing program EMRAS (${\underline{E}}nvironmental$ ${\underline{M}}odelling$ for ${\underline{RA}}diation$ ${\underline{S}}afety$) oragnized by the IAEA (${\underline{I}}nternational$ ${\underline{A}}tomic$ ${\underline{E}}nergy$ ${\underline{A}}gency$). For radioactive contamination scenarios of Pripyat districts and a hypothetical RDD (${\underline{R}}adiological$ ${\underline{D}}ispersal$ ${\underline{D}}evice$), the predicted results using METRO-K were submitted to the EMRAS's Urban Contamination Working Group. In this paper, the predicted results for the contamination scenarios of a Pripyat district were shown in case of both without remediation measures and with ones. Comparing with the predictied results of the models that have taken part in EMRAS program, a feasibility for decision-making support of METRO-K was investigated. As a predicted result of METRO-K, to take immediately remediation measures following a radioactive contamination, if possible, might be one of the best ways to reduce exposure dose. It was found that the discrepancies of predicted results among the models are resulted from 1) modeling approaches and applied parameter values, 2) exposure pathways which are considered in models, 3) assumptions of assessor such as contamination surfaces which might affect to an exposure receptor and their sizes, 4) parameter values which are related with remediation measures applied through literature survey. It was indentified that a Korean urban contamination model METRO-K is a useful tool for dicision-making support through the participation of EMRAS program.

Performance Estimation of Large-scale High-sensitive Compton Camera for Pyroprocessing Facility Monitoring (파이로 공정 모니터링용 대면적 고효율 콤프턴 카메라 성능 예측)

  • Kim, Young-Su;Park, Jin Hyung;Cho, Hwa Youn;Kim, Jae Hyeon;Kwon, Heungrok;Seo, Hee;Park, Se-Hwan;Kim, Chan Hyeong
    • Journal of Radiation Protection and Research
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    • v.40 no.1
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    • pp.1-9
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    • 2015
  • Compton cameras overcome several limitations of conventional mechanical collimation based gamma imaging devices, such as pin-hole imaging devices, due to its electronic collimation based on coincidence logic. Especially large-scale Compton camera has wide field of view and high imaging sensitivity. Those merits suggest that a large-scale Compton camera might be applicable to monitoring nuclear materials in large facilities without necessity of portability. To that end, our research group have made an effort to design a large-scale Compton camera for safeguard application. Energy resolution or position resolution of large-area detectors vary with configuration style of the detectors. Those performances directly affect the image quality of the large-scale Compton camera. In the present study, a series of Geant4 Monte Carlo simulations were performed in order to examine the effect of those detector parameters. Performance of the designed large-scale Compton camera was also estimated for various monitoring condition with realistic modeling. The conclusion of the present study indicates that the energy resolution of the component detector is the limiting factor of imaging resolution rather than the position resolution. Also, the designed large-scale Compton camera provides the 16.3 cm image resolution in full width at half maximum (angular resolution: $9.26^{\circ}$) for the depleted uranium source considered in this study located at the 1 m from the system when the component detectors have 10% energy resolution and 7 mm position resolution.

Predicting the Performance of Recommender Systems through Social Network Analysis and Artificial Neural Network (사회연결망분석과 인공신경망을 이용한 추천시스템 성능 예측)

  • Cho, Yoon-Ho;Kim, In-Hwan
    • Journal of Intelligence and Information Systems
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    • v.16 no.4
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    • pp.159-172
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    • 2010
  • The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

Validation of the Proximity of Clothing to Self Scale for Older Persons (의복의 자아 근접성 척도 검증 - 노년층을 대상으로 -)

  • Lee, Young-A;Sontag, M. Suzanne
    • Journal of the Korean Society of Clothing and Textiles
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    • v.31 no.6 s.165
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    • pp.848-858
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    • 2007
  • Sontag and Lee (2004) recently developed an objectively measurable instrument, the Proximity of Clothing to Self(PCS) Scale, which measured the psychological closeness of clothing to self. They validated a 4-factor, 24-item PCS Scale for use with adolescents and identified the need for confirmation of the factor structure with other age groups. This paper extends the work of Sontag and Lee by employing the PCS Scale with older persons, age 65 and over, and reports the validation of a 3-factor, 19-item PCS Scale for older persons. A mail survey was sent to a national random sample of 1,700 older Persons by means of a list purchased from a U.S. survey sampling company in late November 2004. Total usuable number of respondents was 250 with an adjusted response rate of 15.6 percent. Three analytical rounds of confirmatory factor analysis(CFA) to test the construct validity of the PCS Scale were conducted by using AMOS 5.0(Analysis of Moment Structures), one of several structural equation modeling(SEM) programs. Completion of three rounds of the CFA resulted in a 3-factor, 19-item PCS Scale with demonstrated construct validity and reliability for older persons. The three PCS dimensions are clothing in relation to 1) self as structure-process(PCS Dimension 1-2-3 combined), 2) self-esteem-evaluative and affective processes(PCS Dimension 4-5 combined), and 3) body image and body cathexis(PCS Dimension 6). The initially hypothesized 6-factor scale(Sontag & Lee, 2004) was not confirmed for adolescents in their study nor with older persons in this study. In addition, the 4-factor solution for the adolescent group did not hold for older persons. It appears that the self-system of older persons is more integrated than may be true for younger individuals. Recommendations for future testing of construct validity of the PCS Scale are made.

Development of A Material Flow Model for Predicting Nano-TiO2 Particles Removal Efficiency in a WWTP (하수처리장 내 나노 TiO2 입자 제거효율 예측을 위한 물질흐름모델 개발)

  • Ban, Min Jeong;Lee, Dong Hoon;Shin, Sangwook;Lee, Byung-Tae;Hwang, Yu Sik;Kim, Keugtae;Kang, Joo-Hyon
    • Journal of Wetlands Research
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    • v.24 no.4
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    • pp.345-353
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    • 2022
  • A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO2, (nano-TiO2) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO2 to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO2 was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO2 removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO2 particles in a WWTP.

Analyzing Topic Trends and the Relationship between Changes in Public Opinion and Stock Price based on Sentiment of Discourse in Different Industry Fields using Comments of Naver News (네이버 뉴스 댓글을 이용한 산업 분야별 담론의 감성에 기반한 주제 트렌드 및 여론의 변화와 주가 흐름의 연관성 분석)

  • Oh, Chanhee;Kim, Kyuli;Zhu, Yongjun
    • Journal of the Korean Society for information Management
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    • v.39 no.1
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    • pp.257-280
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    • 2022
  • In this study, we analyzed comments on news articles of representative companies of the three industries (i.e., semiconductor, secondary battery, and bio industries) that had been listed as national strategic technology projects of South Korea to identify public opinions towards them. In addition, we analyzed the relationship between changes in public opinion and stock price. 'Samsung Electronics' and 'SK Hynix' in the semiconductor industry, 'Samsung SDI' and 'LG Chem' in the secondary battery industry, and 'Samsung Biologics' and 'Celltrion' in the bio-industry were selected as the representative companies and 47,452 comments of news articles about the companies that had been published from January 1, 2020, to December 31, 2020, were collected from Naver News. The comments were grouped into positive, neutral, and negative emotions, and the dynamic topics of comments over time in each group were analyzed to identify the trends of public opinion in each industry. As a result, in the case of the semiconductor industry, investment, COVID-19 related issues, trust in large companies such as Samsung Electronics, and mention of the damage caused by changes in government policy were the topics. In the case of secondary battery industries, references to investment, battery, and corporate issues were the topics. In the case of bio-industries, references to investment, COVID-19 related issues, and corporate issues were the topics. Next, to understand whether the sentiment of the comments is related to the actual stock price, for each company, the changes in the stock price and the sentiment values of the comments were compared and analyzed using visual analytics. As a result, we found a clear relationship between the changes in the sentiment value of public opinion and the stock price through the similar patterns shown in the change graphs. This study analyzed comments on news articles that are highly related to stock price, identified changes in public opinion trends in the COVID-19 era, and provided objective feedback to government agencies' policymaking.

Violations of Information Security Policy in a Financial Firm: The Difference between the Own Employees and Outsourced Contractors (금융회사의 정보보안정책 위반요인에 관한 연구: 내부직원과 외주직원의 차이)

  • Jeong-Ha Lee;Sang-Yong Tom Lee
    • Information Systems Review
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    • v.18 no.4
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    • pp.17-42
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    • 2016
  • Information security incidents caused by authorized insiders are increasing in financial firms, and this increase is particularly increased by outsourced contractors. With the increase in outsourcing in financial firms, outsourced contractors having authorized right has become a threat and could violate an organization's information security policy. This study aims to analyze the differences between own employees and outsourced contractors and to determine the factors affecting the violation of information security policy to mitigate information security incidents. This study examines the factors driving employees to violate information security policy in financial firms based on the theory of planned behavior, general deterrence theory, and information security awareness, and the moderating effects of employee type between own employees and outsourced contractors. We used 363 samples that were collected through both online and offline surveys and conducted partial least square-structural equation modeling and multiple group analysis to determine the differences between own employees (246 samples, 68%) and outsourced contractors (117 samples, 32%). We found that the perceived sanction and information security awareness support the information security policy violation attitude and subjective norm, and the perceived sanction does not support the information security policy behavior control. The moderating effects of employee type in the research model were also supported. According to the t-test result between own employees and outsourced contractors, outsourced contractors' behavior control supported information security violation intention but not subject norms. The academic implications of this study is expected to be the basis for future research on outsourced contractors' violation of information security policy and a guide to develop information security awareness programs for outsourced contractors to control these incidents. Financial firms need to develop an information security awareness program for outsourced contractors to increase the knowledge and understanding of information security policy. Moreover, this program is effective for outsourced contractors.

An Empirical Study on Motivation Factors and Reward Structure for User's Createve Contents Generation: Focusing on the Mediating Effect of Commitment (창의적인 UCC 제작에 영향을 미치는 동기 및 보상 체계에 대한 연구: 몰입에 매개 효과를 중심으로)

  • Kim, Jin-Woo;Yang, Seung-Hwa;Lim, Seong-Taek;Lee, In-Seong
    • Asia pacific journal of information systems
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    • v.20 no.1
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    • pp.141-170
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    • 2010
  • User created content (UCC) is created and shared by common users on line. From the user's perspective, the increase of UCCs has led to an expansion of alternative means of communications, while from the business perspective UCCs have formed an environment in which an abundant amount of new contents can be produced. Despite outward quantitative growth, however, many aspects of UCCs do not meet the expectations of general users in terms of quality, and this can be observed through pirated contents and user-copied contents. The purpose of this research is to investigate effective methods for fostering production of creative user-generated content. This study proposes two core elements, namely, reward and motivation, which are believed to enhance content creativity as well as the mediating factor and users' committement, which will be effective for bridging the increasing motivation and content creativity. Based on this perspective, this research takes an in-depth look at issues related to constructing the dimensions of reward and motivation in UCC services for creative content product, which are identified in three phases. First, three dimensions of rewards have been proposed: task dimension, social dimension, and organizational dimention. The task dimension rewards are related to the inherent characteristics of a task such as writing blog articles and pasting photos. Four concrete ways of providing task-related rewards in UCC environments are suggested in this study, which include skill variety, task significance, task identity, and autonomy. The social dimensioni rewards are related to the connected relationships among users. The organizational dimension consists of monetary payoff and recognition from others. Second, the two types of motivations are suggested to be affected by the diverse rewards schemes: intrinsic motivation and extrinsic motivation. Intrinsic motivation occurs when people create new UCC contents for its' own sake, whereas extrinsic motivation occurs when people create new contents for other purposes such as fame and money. Third, commitments are suggested to work as important mediating variables between motivation and content creativity. We believe commitments are especially important in online environments because they have been found to exert stronger impacts on the Internet users than other relevant factors do. Two types of commitments are suggested in this study: emotional commitment and continuity commitment. Finally, content creativity is proposed as the final dependent variable in this study. We provide a systematic method to measure the creativity of UCC content based on the prior studies in creativity measurement. The method includes expert evaluation of blog pages posted by the Internet users. In order to test the theoretical model of our study, 133 active blog users were recruited to participate in a group discussion as well as a survey. They were asked to fill out a questionnaire on their commitment, motivation and rewards of creating UCC contents. At the same time, their creativity was measured by independent experts using Torrance Tests of Creative Thinking. Finally, two independent users visited the study participants' blog pages and evaluated their content creativity using the Creative Products Semantic Scale. All the data were compiled and analyzed through structural equation modeling. We first conducted a confirmatory factor analysis to validate the measurement model of our research. It was found that measures used in our study satisfied the requirement of reliability, convergent validity as well as discriminant validity. Given the fact that our measurement model is valid and reliable, we proceeded to conduct a structural model analysis. The results indicated that all the variables in our model had higher than necessary explanatory powers in terms of R-square values. The study results identified several important reward shemes. First of all, skill variety, task importance, task identity, and automony were all found to have significant influences on the intrinsic motivation of creating UCC contents. Also, the relationship with other users was found to have strong influences upon both intrinsic and extrinsic motivation. Finally, the opportunity to get recognition for their UCC work was found to have a significant impact on the extrinsic motivation of UCC users. However, different from our expectation, monetary compensation was found not to have a significant impact on the extrinsic motivation. It was also found that commitment was an important mediating factor in UCC environment between motivation and content creativity. A more fully mediating model was found to have the highest explanation power compared to no-mediation or partially mediated models. This paper ends with implications of the study results. First, from the theoretical perspective this study proposes and empirically validates the commitment as an important mediating factor between motivation and content creativity. This result reflects the characteristics of online environment in which the UCC creation activities occur voluntarily. Second, from the practical perspective this study proposes several concrete reward factors that are germane to the UCC environment, and their effectiveness to the content creativity is estimated. In addition to the quantitive results of relative importance of the reward factrs, this study also proposes concrete ways to provide the rewards in the UCC environment based on the FGI data that are collected after our participants finish asnwering survey questions. Finally, from the methodological perspective, this study suggests and implements a way to measure the UCC content creativity independently from the content generators' creativity, which can be used later by future research on UCC creativity. In sum, this study proposes and validates important reward features and their relations to the motivation, commitment, and the content creativity in UCC environment, which is believed to be one of the most important factors for the success of UCC and Web 2.0. As such, this study can provide significant theoretical as well as practical bases for fostering creativity in UCC contents.