• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.73-77
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• 2000

It is necessary to express and evaluate annoyances, caused by noises, as a comparable quantity for establishing an efficient, economic and user-oriented noise control plan. In particular, cares should be taken for impact noises, since their dynamic properties are different from those of steady-state noises. A series of preliminary experiments were carried out to quantify the annoyances caused by floor impact noises. Results suggests that the characteristics of an impact source was more important factor than the properties of a floor structure for determining loudness and noisiness of subjects. Also, the heavy impact source was found to be felt louder and noisier by 5-6dB than the light impact source.

• The Journal of Information Systems
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• v.27 no.2
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• pp.135-155
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• 2018

Purpose Recently, with the enhancement of mobile technologies, people have formed various relationships and spreaded networks on social network service(SNS). In addition, although people make a decision based on the thoughts and emotions about self, there is little empirical research on social relations and self-construal of users in social network game (SNG). Design/methodology/approach This study was designed to examine the structural relationships among SNG users' social capital, self-construal, behavioral adaptation, SNG reuse intention and charged item purchasing intention. Findings The results from this study are as follow. First of all, the bonding social capital did not have a significant impact on behavioral adaptation to SNG, but bridging social capital had a positive impact on behavioral adaptation. Second, independent self-construal did not have a significant impact on behavioral adaptation to SNG, but interdependent self-construal had a positive impact on behavioral adaptation. Lastly, the behavioral adaptation to SNG had a positive impact reuse intention and charged item purchasing intention. Also, SNG reuse intention had a positive impact on charged item purchasing intention.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.159-166
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• 2019

In this paper, we propose takes network marketing as a starting point for analysis, uses the theory of purchasing behavior and enterprise performance to analyze the network marketing strategy of artistic products, incorporates the practical problems encountered by some artistic products enterprises in Zhejiang Province in network marketing into theoretical research. The theoretical model of network marketing strategy acting on enterprise performance through the intermediary effect of purchasing behavior is constructed. This paper conducted an in-depth survey of three representative core domestic companies engaged in Internet marketing of artistic products, and analyzed the questionnaires of 357 respondents. The initial model was verified by statistical tools such as SPSS and AMOS, and three conclusions were drawn: Firstly, network marketing strategies of different dimensions have different effects on purchasing behavior: pricing strategy and product strategy have significant positive effects on impulse purchasing behavior, but channel strategy has no significant impact on impulse purchasing behavior; Channel strategy and product strategy have a significant positive impact on repeated purchasing behavior, but pricing strategy has no significant impact on repeated purchasing behavior. Second, user purchasing behavior has a significant positive impact on enterprise performance. Third, network marketing strategies of different dimensions have significant direct and positive impact on enterprise performance.

• KIEAE Journal
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• v.16 no.3
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• pp.5-12
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• 2016

Purpose: In case of existing building, A lot of attempts are being made like changing thermal system or using high efficiency products to decrease energy load and increase energy efficiency. However, (1) Absence of systemed database of green-remodeling technology and products. (2) Absence of comparative analysis system and qualitative/quantitative evaluation method of energy performance and energy reduction cost. (3) Existing remodeling was very hard to access for non-experts. So, in this paper, the authors developed data base for green-remodeling(Impact Table A, Impact Table B) and optimum combination dedication tool for user convenience. Accordingly, purpose of this paper validate usefulness of Impact Table and optimum alternative dedication tool. Method: For validate the usefulness of Impact Table and optimum combination dedication tool, the authors selected five test model office buildings. Next, through research investigation, the authors diagnosed the present state of buildings. In base of diagnosis results, select technologies for remodeling by qualitative comparison (Impact Table A). Next, evaluate quantitative price and performance technologies that selected in Impact Table A (Impact Table B). Lastly, through final evaluation of Impact Taba A and Impact Table B, determine the direction of the green-remodeling. Result: Impact Table and optimum combination dedication tool can use relative indicator for green-remodeling, especially through ROI by detail field.

• Journal of Korea Artificial Intelligence Association
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• v.2 no.1
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• pp.1-6
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• 2024

In this paper, we develop an AI-based recommendation system that matches the specifications of smartphones from company 'S'. The system aims to simplify the complex decision-making process of consumers and guide them to choose the smartphone that best suits their daily needs. The recommendation system analyzes five specifications of smartphones (price, battery capacity, weight, camera quality, capacity) to help users make informed decisions without searching for extensive information. This approach not only saves time but also improves user satisfaction by ensuring that the selected smartphone closely matches the user's lifestyle and needs. The system utilizes unsupervised learning, i.e. clustering (K-MEANS, DBSCAN, Hierarchical Clustering), and provides personalized recommendations by evaluating them with silhouette scores, ensuring accurate and reliable grouping of similar smartphone models. By leveraging advanced data analysis techniques, the system can identify subtle patterns and preferences that might not be immediately apparent to consumers, enhancing the overall user experience. The ultimate goal of this AI recommendation system is to simplify the smartphone selection process, making it more accessible and user-friendly for all consumers. This paper discusses the data collection, preprocessing, development, implementation, and potential impact of the system using Pandas, crawling, scikit-learn, etc., and highlights the benefits of helping consumers explore the various options available and confidently choose the smartphone that best suits their daily lives.

• The Journal of Information Systems
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• v.16 no.1
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• pp.179-200
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• 2007

In this research, we study how task and KMS fit influences on KMS performance in large corporations during its practical use. Based on the task-technology fit theory and information system success model, we developed a research model by considering the characteristics of KMS for supporting tasks. We try to verify how individual traits, task traits, and KMS Units affect task-KMS fit and how task KMS fit influences on KMS performance. We surveyed 212 employees who were using KMS and working for the large-sized manufacturing firms. We analyzed the collected data from LISREL 8.54 for Windows, and found the following significant results. First user satisfaction is increased when KMS provides knowledge to help to perform task rather than KMS' functionality. Second, user satisfaction is increased when KMS is suitable for performing task Hence, we verified task-KMS fit is an antecedent of user satisfaction. Third, task-KMS fit and user satisfaction have significant impacts on KMS performance. And user satisfaction affected more heavily on KMS performance than task-KMS fit did. As a result, we realized an individual performance can be improved when task KMS fit is high and, consequently, user satisfaction is increased. Forth while the usefulness of task-KMS fit is demonstrated, causal factors such as individual traits, task traits, and KMS traits significantly affect task-KMS fit. Formalization and knowledge trait we significant in enhancing user satisfaction, but KMS self-efficacy, autonomy, md system trait are not. These results indicate that task-KMS fit variable is useful as a measure of KMS performance as well as that of user satisfaction. Based on these results, we conclude that when KMS supports task activity, performance can be significantly improved by coordinating the task with KMS.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.856-874
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• 2019

The performance of recommender systems (RS) has been measured mainly in terms of accuracy. However, there are other aspects of performance that are difficult to understand in terms of accuracy, such as coverage, serendipity, and satisfaction with recommended results. Moreover, particularly with RSs that suggest multiple items at a time, such as YouTube, user satisfaction with recommended results may vary not only depending on their accuracy, but also on their configuration, content, and design displayed to the user. This is true when classifying an RS as a single RS with one recommended result and as a multiple RS with diverse results. No empirical analysis has been conducted on the influence of the content and distribution of recommendation items on user satisfaction. In this study, we propose a research model representing the content and distribution of recommended items and how they affect user satisfaction with the RS. We focus on RSs that recommend multiple items. We performed an empirical analysis involving 149 YouTube users. The results suggest that user satisfaction with recommended results is significantly affected according to the HHI (Herfindahl-Hirschman Index). In addition, satisfaction significantly increased when the recommended item on the top of the list was the same category in terms of content that users were currently watching. Particularly when the purpose of using RS is hedonic, not utilitarian, the results showed greater satisfaction when the number of views of the recommended items was evenly distributed. However, other characteristics of selected content, such as view count and playback time, had relatively less impact on satisfaction with recommended items. To the best of our knowledge, this study is the first to show that the category concentration of items impacts user satisfaction on websites recommending diverse items in different categories using a content-based filtering system, such as YouTube. In addition, our use of the HHI index, which has been extensively used in economics research, to show the distributional characteristics of recommended items, is also unique. The HHI for categories of recommended items was useful in explaining user satisfaction.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.189-203
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• 2021

Environmental changes, which are strongly requiring technological cooperation, such as technological development and strategic alliances according to industrial ecosystem change, have a significant impact on not only product quality but also services. Thus, there is a need for 'servitization' that can satisfy the needs of customers and the ecosystem of businesses through the convergence of manufacturing companies and services. This study uses the Expectation-Confirmation Model to examine the impact on user satisfaction and Continuance Usage Intention. Research(Study) was conducted on users who are using high-tech-based cars. For this, we used Expectation Confirmation(match expections for the user's pre-and post-use relationships), Perceived Ease, Perceived Usefulness, User Satisfaction and Habitual Use and using Continuance Usage Intention as a dependent variable. Their causation was examined with the spss 26.0 and smartpls 2.0 statistical programs. As implications of this study, Expectation Confirmation has been shown to have significant positive effects on Perceived Ease, Perceived Usefulness, User Satisfaction and Habitual Use. For this results, the expectations before and after the use of high-tech cars lead to improved daily lives convenience and(or) work efficiency, leading to user satisfaction and further Continuance Usage Intention. Motors consider it important to pursue the work improvements that consumers want and use it useful in daily lives in the production and sale of high-tech cars. It is expected that it will create natural habits for services that users are satisfied with, and that these habits will affect the continuous growth and understanding of the trend of change.

• IE interfaces
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• v.17 no.3
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• pp.314-329
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• 2004

The rapid growth of investments in mobile service to reach a large and growing body of customers, coupled with low communication costs, has made user acceptance an increasingly critical management issue. The study draws upon the task-technology fit (TTF) model as its theoretical basis and its empirical findings to pragmatically explain the key factors that affect the performance and user acceptance of mobile service in medical field. A total of 110 usable responses were obtained. The findings indicate that the task, technology, and individual user characteristics positively affect task-technology fit and mobile service usage. The task-technology fit and mobile service usage are the dominant factors that affect mobile service performance. The result points out the importance of the fit between technologies and users' tasks in achieving individual performance impact from mobile service in medical arena.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.49-58
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• 2020

Non-orthogonal multiple access (NOMA) has been recognized as a significant technology in the fifth generation (5G) and beyond mobile communication, which encompasses the advanced smart convergence of the artificial intelligence (AI) and the internet of things (IoT). In NOMA, since the channel resources are shared by many users, it is essential to establish the user fairness. Such fairness is achieved by the power allocation among the users, and in turn, the less power is allocated to the stronger channel users. Especially, the first and second strong channel users have to share the extremely small amount of power. In this paper, we consider the power optimization for the two users with the small power. First, the closed-form expression for the power allocation is derived and then the results are validated by the numerical results. Furthermore, with the derived analytical expression, for the various channel environments, the optimal power allocation is investigated and the impact of the channel gain difference on the power allocation is analyzed.