• Title/Summary/Keyword: Offline quality

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Research on Policy Measures to Activate Sports Welfare

  • KIM, Young Chul;KIM, Jun Su
    • Journal of Sport and Applied Science
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    • v.5 no.1
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    • pp.17-26
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    • 2021
  • Purpose: The purpose of this study is to suggest the policy and scope of the concept of sports welfare and to present a systematic model enhancing sport welfare of the society. Research design, data, and methodology: In order to induce idea for welfare policy and conceptual sport welfare model, this study reviewed a literature discussing the functions and mechanism of sport in enhancing a sense of life quality and thus rebuilding welfare of community. Results: The study suggests these. First, sports welfare ensures the rights of sports of all citizens and has the main purpose of providing social services, creating environments against inequality, improving the quality of life and happiness for everyone to enjoy, and the range should be continued from the right to live, environments against inequality, to the improvement of life and happiness. Second, since the integrated perspective was first suggested, sports integration development will be researched as well as the direction of the development of policies of the integrated model. Basic research of indicator development will need to be proceeded to execute and evaluate the integrated model. Third, the improvement of treatment of sports welfare instructors is urgent. Namely, compared to sports-related budget and the enhancement of facilities, the poor environment of sports welfare instructors needs to be improved. Instead of only testing physical fitness and prescription, the business needs to be continued by connecting to the participants' continuous participation in sports. Conclusions: Whether sports welfare succeeds depends on the need for an active beneficiary, identification of demand, a beneficiary that can discover potential to join offline and online into one, the establishment of sports policies to promote competency development, and a direct progression is needed.

Knowledge Sharing Model in Virtual Communities Considering Personal and Social Factors (개인적·사회적 요인을 고려한 가상 공동체에서의 지식 공유 모형)

  • Choi, Kyungsun;Ahn, Hyunchul
    • The Journal of Information Systems
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    • v.28 no.1
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    • pp.41-72
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    • 2019
  • Purpose Virtual communities (VCs) are becoming ever more important in these days, sometimes more than offline communities. Notably, they have become significant sources of knowledge sharing. Therefore, in order to foster a VC, it is very important to understand why people share their knowledge in the VC. Under this background, this paper aims at proposing the behavioral model best explains knowledge sharing activities in VCs. Design/methodology/approach We basically design our behavioral model for knowledge sharing in VCs based on theory of reasoned action (TRA). However, to understand knowledge sharing in VCs better, we specify knowledge sharing by dividing it into knowledge contribution and knowledge use. Also, instead of 'subjective norm', we adopt 'sense of virtual community (SOVC)' as a main social factor, which has been found to be important in the literature. We also include the antecedents such as 'quality of the shared knowledge', 'trust in community members', 'passion of the community leader', 'reciprocity', and 'self efficacy', which affect VC users' attitude towards knowledge sharing and SOVC. To test the hypotheses in our proposed model, we collected 253 valid surveys from the VC users. Structural equation modeling (SEM) using AMOS 23 is employed to assess the relationships proposed as the hypotheses. Findings Major findings are as follows. SOVC positively affects both intention to contribute knowledge and intention to use knowledge. And, trust in community members positively affects the attitude towards knowledge use and SOVC. The attitude towards knowledge use is also affected by the quality of the shared knowledge. Reciprocity is found to strongly positively affect the attitude towards knowledge contribution. However, passion of the community leader and self efficacy are found to have insignificant effect on SOVC and the attitude towards knowledge contribution respectively. Our study sheds a light on how to foster VCs from the perspective of knowledge management.

A Study on the Intention of Financial Consumers to Accept AI Services Using UTAUT Model (통합기술수용이론을 이용한 금융소비자들의 인공지능 서비스 수용의도 연구)

  • Kim, Sun Mi;Son, Young Doo
    • Journal of Korean Society for Quality Management
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    • v.50 no.1
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    • pp.43-61
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    • 2022
  • Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI understanding as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the intention to use AI. It was also found that AI knowledge of users differently influence the intention to use through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness have positive causation to the intention to use in AI financial service. On the facilitating conditions, unlike other variables, it was found that the user's intention to use was different by the level of AI understanding. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the intention to use AI.

Building Error-Reflected Models for Collaborative Filtering Recommender System (협업적 여과 추천 시스템을 위한 에러반영 모델 구축)

  • Kim, Heung-Nam;Jo, Geun-Sik
    • The KIPS Transactions:PartD
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    • v.16D no.3
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    • pp.451-462
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    • 2009
  • Collaborative Filtering (CF), one of the most successful technologies among recommender systems, is a system assisting users in easily finding the useful information. However, despite its success and popularity, CF encounters a serious limitation with quality evaluation, called cold start problems. To alleviate this limitation, in this paper, we propose a unique method of building models derived from explicit ratings and applying the models to CF recommender systems. The proposed method is divided into two phases, an offline phase and an online phase. First, the offline phase is a building pre-computed model phase in which most of tasks can be conducted. Second, the online phase is either a prediction or recommendation phase in which the models are used. In a model building phase, we first determine a priori predicted rating and subsequently identify prediction errors for each user. From this error information, an error-reflected model is constructed. The error-reflected model, which is reflected average prior prediction errors of user neighbors and item neighbors, can make accurate predictions in the situation where users or items have few opinions; this is known as the cold start problems. In addition, in order to reduce the re-building tasks, the error-reflected model is designed such that the model is updated effectively and users'new opinions are reflected incrementally, even when users present a new rating feedback.

The Effect of Service Qualities' Characteristics on Customer Satisfaction and Revisit Intention in Chinese Mid/Low-Priced Hotel

  • HAN, Sun;JUNG, Jin-Sup
    • The Journal of Industrial Distribution & Business
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    • v.12 no.6
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    • pp.57-74
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    • 2021
  • Purpose: Before COVID-19 pandemic, Chinese mid/low-priced hotel industry has been steadily growing in recent years, and internal and external competition has been intensifying. Under these circumstances, this study started with a strategic objective to increase the quality of service, thus enabling customer satisfaction and revisit intention. For enhancing the competitiveness of Chinese mid/low-priced hotel business, we plan to establish a model using SERVQUAL, O2O platform, and identify their relationship through empirical analyses. Research design, data and methodology: Through the consideration of the existing literature, this study intended to identify the characteristics of service quality in Chinese mid/low-priced hotels and to consider their impact on customer satisfaction and revisit intention. We also wanted to examine the moderating effect of the O2O platform between the characteristics of service quality and customer satisfaction. A survey was carried out on customers using mid/low-priced hotels in China and empirical analyses were conducted using regression analyses. Results: First, in the hypothesis of service qualities' effects on customer satisfaction were identified with significant positive effects. Second, in the hypothesis of service qualities' effects on revisit intention, "tangibles, reliability, and empathy" have shown significant positive. Third, in the verification of the moderating effect of the O2O platform, there were "positive partial moderating effects" between service qualities and customer satisfaction. Finally, the effect of customer satisfaction on revisit intention was positive significant. Conclusions: In order to satisfy their customers, improvements in service quality should be made first. In addition, customer satisfaction had a positive impact on revisit intention. In order to revitalize Chinese mid/low-priced hotels, differentiation strategy is also needed for specialized customers such as college students, and basically, efforts should be made to optimize the O2O platform. O2O platforms should establish optimal platform construction strategies based on the customer's perspective. After all, in the case of Chinese mid/low-priced hotels, it is necessary to strengthen the construction of the latest hardware infrastructure and O2O platform of software infrastructure, and to improve customers' advanced online and offline experiences. Finally, regarding the hypothesis that was rejected among service qualities' characteristics, we tried to discuss the reason and find the implications of these.

Effect of E-Service Quality of Fashion Mobile Applications on Flow, User Satisfaction, and Service Loyalty (패션 모바일 애플리케이션의 e-서비스 품질이 몰입 및 사용자 만족과 서비스 충성도에 미치는 영향)

  • Jhee, SeonYoung;Han, Sang-Lin
    • Journal of Service Research and Studies
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    • v.13 no.3
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    • pp.39-56
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    • 2023
  • Due to restrictions on offline activities caused by COVID-19, the use of mobile applications is increasing along with interest in online shopping, which are non-face-to-face commerce. Accordingly, mobile applications and various industries are combined, and the number of cases of using mobile applications in the fashion industry is increasing. In this study, the effect of e-service quality of fashion mobile applications on user's flow, user satisfaction, and service loyalty was examined. To conduct this study, a survey of 274 people who experienced the 'ABLY' fashion mobile application was used for analysis to verify the hypothesis. As a result of the analysis, it was found that informativity and responsiveness among the e-service quality of fashion mobile applications had a positive (+) effect on flow. And it has been confirmed that informativity, reliability, and responsiveness affect user satisfaction. In addition, flow has a positive (+) (+) effect on user satisfaction, and user satisfaction has a positive (+) effect on service loyalty. However, among the e-service quality of fashion mobile applications, reliability did not have a positive (+) effect on flow. And ease of use did not have a positive (+) effect on both flow and user satisfaction. Finally, it was confirmed that flow did not directly affect service loyalty. Through this study, we intend to contribute to the establishment of marketing strategies for fashion mobile application users, who are increasing with the development of mobile technology, and provide practical implications for the post-COVID-19 era.

A Study on The Effect of Service Quality on Service Failure and Loyalty: Focusing on Live Commerce Platform Providers and Companies Using the Platform (서비스품질이 서비스실패와 충성도에 미치는 영향에 관한 연구: 라이브커머스 플랫폼업체와 플랫폼 이용업체를 중심으로)

  • Dae-Hong Yun
    • Journal of Industrial Convergence
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    • v.22 no.1
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    • pp.33-40
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    • 2024
  • This study was intended to examine the effect of service quality on service failure and loyalty, and a survey was conducted online and offline with a focus on those in their 20s and 30s in Busan region. Specific details were as follows: First, service quality was found to have a statistically significant effect on live commerce loyalty(Hypothesis 1), live commerce service failure(Hypothesis 2), service failure of companies using the live commerce platform(Hypothesis 3), and repurchase intention of companies using the live commerce platform(Hypothesis 4). Second, service failure of live commerce companies had a significant effect on service failure of companies using the live commerce platform(Hypothesis 5), but did not have a significant effect on live commerce loyalty(Hypothesis 6) and repurchase intention of companies using the live commerce platform(Hypothesis 7). The service failure of companies using the live commerce platform did not have a statistically significant effect on loyalty of live commerce companies(Hypothesis 8), but had a statistically significant effect on repurchase intention of companies using the live commerce platform(Hypothesis 9). Finally, the repurchase intention of companies using the live commerce platform was found to have a statistically significant effect on live commerce loyalty(Hypothesis 10).

The Impact of Perceived Risks Upon Consumer Trust and Purchase Intentions (인지된 위험의 유형이 소비자 신뢰 및 온라인 구매의도에 미치는 영향)

  • Hong, Il-Yoo B.;Kim, Woo-Sung;Lim, Byung-Ha
    • Asia pacific journal of information systems
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    • v.21 no.4
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    • pp.1-25
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    • 2011
  • Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

Object Tracking Based on Exactly Reweighted Online Total-Error-Rate Minimization (정확히 재가중되는 온라인 전체 에러율 최소화 기반의 객체 추적)

  • JANG, Se-In;PARK, Choong-Shik
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.53-65
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    • 2019
  • Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

Effects of Initiation and Perceived Similarity on the Evaluation of Online Communities (온라인 커뮤니티 속 가입절차 및 지각된 유사성에 따른 평가의 차이)

  • Yoo, Jihyun;Kang, Hyunmin;Han, Kwanghee
    • Science of Emotion and Sensibility
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    • v.21 no.4
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    • pp.25-36
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    • 2018
  • Nowadays, it is hard to imagine one's life without smart phones or the internet. Furthermore, not only do people form groups offline, but also online. Based on the cognitive dissonance theory, there have been many studies about how an offline group's initiation affects attitudes toward the group. However, there has not been a study about how an online group's initiation can affect attitudes toward the group. Therefore, this study aims to find out how cognitive dissonance aroused by initiation affects the attitudes toward the online community, which represents groups that are formed online. In addition, this study examined how perceived similarity affects changes in attitude aroused by cognitive dissonance. Participants were assigned to a group in three ways as follows: without a registration process, with a simple registration process, and/or with a complex registration process. Perceived similarity was calculated by the difference between the current body mass index (BMI) and the target BMI of the participant. Attitudes toward the online group were measured by perceived source credibility, perceived information quality, satisfaction, information usefulness, and continuance intention. Contrary to the cognitive dissonance theory, the results showed that when applied to offline social groups, there were conflicting results. There were cases where there was no difference in the evaluation between initiation conditions. However, other cases showed that groups with the most complex registration process were found to have the worst evaluation. People were more favorable toward the group when the perceived similarity was larger. Interestingly, people who had higher perceived similarity had more positive attitudes toward the groups that had been assigned with a registration process compared to the group formed without a registration process. Conversely, people with lower perceived similarity had more positive attitudes toward the group when there was no initiation process. Online communities may use the results of this study to design more suitable registration processes for their communities.