• Title/Summary/Keyword: Cloud Service Satisfaction

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A Study on the Importance Analysis of Reliability, Security, Economic Efficiency Factors that Companies Should Determine When Adopting Cloud Computing Services (클라우드 컴퓨팅 서비스 채택 시 기업이 판단해야 하는 신뢰성, 보안성, 경제성 요인의 중요도 분석)

  • Kang, Da-Yeon
    • Journal of Digital Convergence
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    • v.19 no.9
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    • pp.75-81
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    • 2021
  • The purpose of this research is to derive and evaluate priorities for critical factors that must be determined before an enterprise adopts a cloud computing service. AHP analysis techniques were used to reflect decisions made by experts as research methods. AHP is a decision-making technique that expresses complex decision-making problems hierarchically and derives the best alternatives through pairwise comparison between the items of the hierarchy. Compared to the existing statistical decision making techniques, the decision making process is systematic and simple, making it easy to understand. In addition, the procedure is also reasonable by providing an indicator to determine the consistency of the decision maker in the analysis process. The analysis results of this research showed that security was the first priority, reliability was the second priority, and economic efficiency was the third priority. Among the factors in the first-priority security items, the access control rights and the safety factors of external threats are the most important factors. Research results can be used as a guideline in future practice, and it is necessary to evaluate, compare and analyze the satisfaction of companies that have adopted cloud computing services in the future.

A Genetic Algorithm Based Task Scheduling for Cloud Computing with Fuzzy logic

  • Singh, Avtar;Dutta, Kamlesh
    • IEIE Transactions on Smart Processing and Computing
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    • v.2 no.6
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    • pp.367-372
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    • 2013
  • Cloud computing technology has been developing at an increasing expansion rate. Today most of firms are using this technology, making improving the quality of service one of the most important issues. To achieve this, the system must operate efficiently with less idle time and without deteriorating the customer satisfaction. This paper focuses on enhancing the efficiency of a conventional Genetic Algorithm (GA) for task scheduling in cloud computing using Fuzzy Logic (FL). This study collected a group of task schedules and assessed the quality of each task schedule with the user expectation. The work iterates the best scheduling order genetic operations to make the optimal task schedule. General GA takes considerable time to find the correct scheduling order when all the fitness function parameters are the same. GA is an intuitive approach for solving problems because it covers all possible aspects of the problem. When this approach is combined with fuzzy logic (FL), it behaves like a human brain as a problem solver from an existing database (Memory). The present scheme compares GA with and without FL. Using FL, the proposed system at a 100, 400 and 1000 sample size*5 gave 70%, 57% and 47% better improvement in the task time compared to GA.

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The Impact of Multi-dimensional Trust for Customer Satisfaction

  • Choi, Jae-Won;Sohn, Chang-Soo;Lee, Hong-Joo
    • Management Science and Financial Engineering
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    • v.16 no.2
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    • pp.81-97
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    • 2010
  • Trust is one of the most important aspects of the relationship between retailers and consumers in e-commerce. Users may have concerns about transaction security or personal information leakage when they engage in transactions over the Internet. It can be difficult to attract customers if the retailers or service providers cannot establish trust with their customers. There have been many studies of trust-building mechanisms between customers and e-storefronts. However, little work has been done on identifying the relationships between customer satisfaction, purchase intention, and trust. In addition, trust building occurs in the pre- and post-purchase phases of an e-commerce transaction, as well as gradually over repeated transactions. Thus we distinguish between cue-based trust and experience-based trust. The objective of this study was to explain the impact of trust on customer satisfaction and purchase intention in relation to e-commerce sites from the perspective of a multi-dimensional concept of trust. We surveyed 350 undergraduate students and obtained 331 responses for analysis. The result of our analysis showed that cue-based trust has a positive relationship with trust based on experience. Although the two concepts of trust have positive relationships with satisfaction, the path coefficient of trust based on experience was higher than that of cue-based trust. In addition, the purchase intention mediates the relationship between cue-based trust and experience-based trust.

A Customization Method for Mobile App.'s Performance Improvement (모바일 앱의 성능향상을 위한 커스터마이제이션 방안)

  • Cho, Eun-Sook;Kim, Chul-Jin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.11
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    • pp.208-213
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    • 2016
  • In the fourth industrial revolution, customization is becoming a conversation topic in various domains. Industry 4.0 applies cyber-physical systems (CPS), the Internet of Things (IoT), and cloud computing to manufacturing businesses. One of the main phrases in Industry 4.0 is mass customization. Optimized products or services are developed and provided through customization. Therefore, the competitiveness of a product can be enhanced, and satisfaction is improved. In particular, as IoT technology spreads, customization is an essential aspect of smooth service connections between various devices or things. Customized services in mobile applications are assembled and operate in various mobile devices in the mobile environment. Therefore, this paper proposes a method for improving customized cloud server-based mobile architectures, processes, and metrics, and for measuring the performance improvement of the customized architectures operating in various mobile devices based on the Android or IOS platforms. We reduce the total time required for customization in half as a result of applying the proposed customized architectures, processes, and metrics in various devices.

Text Mining-Based Analysis of Hyundai Automobile Consumer Satisfaction and Dissatisfaction Factors in the Chinese Market: A Comparison with Other Brands (텍스트 마이닝을 이용한 현대 자동차 중국시장 소비자의 만족 및 불만족 요인 분석 연구: 다른 브랜드와의 비교)

  • Cui Ran;Inyong Nam
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.539-549
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    • 2024
  • This study employed text mining techniques like frequency analysis, word clouds, and LDA topic modeling to assess consumer satisfaction and dissatisfaction with Hyundai Motor Company in the Chinese market, compared to brands such as Toyota, Volkswagen, Buick, and Geely. Focusing on compact vehicles from these brands between 2021 and 2023, this study analyzed customer reviews. The results indicated Hyundai Avante's positive factors, including a long wheelbase. However, it also highlighted dissatisfaction aspects like Manipulate, engine performance, trunk space, chassis and suspension, safety features, quantity and brand of audio speakers, music membership service, separation band, screen reflection, CarLife, and map services. Addressing these issues could significantly enhance Hyundai's competitiveness in the Chinese market. Previous studies mainly focused on literature research and surveys, which only revealed consumer perceptions limited to the variables set by the researchers. This study, through text mining and comparing various car brands, aims to gain a deeper understanding of market trends and consumer preferences, providing useful information for marketing strategies of Hyundai and other brands in the Chinese market.

A Study on Establishment of Mid- to Long-Term Comprehensive Development Plan for the Bank of Korea Library (시대적 변화에 따른 경제·금융전문도서관 발전 방향 모색에 관한 연구 - 한국은행 도서관을 중심으로 -)

  • Noh, Younghee;Ko, Jae-Min;Chang, Inho;Ro, Ji-Yoon
    • Journal of Korean Library and Information Science Society
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    • v.52 no.2
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    • pp.65-84
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    • 2021
  • This study aimed to analyze the overall operation status of the Bank of Korea library representing the economic library in Korea, investigate user satisfaction and demand, and to propose a direction for the development of the economic library in the future. To this end, a case study was conducted on changes in the external environment of major libraries at home and abroad, and a user survey was conducted. As a result, the future tasks include introducing smart systems, robotics some library services, non-face-to-face service response spaces that reflect the times, introducing big data analysis services, strengthening user-tailored systems, and activating SNS communication. It proposed developing specialized libraries, online reference and research support services, and providing original DBs for publications to strengthen expertise, maintaining and expanding cloud services, maintaining and expanding cooperative projects, and collecting national knowledge and information.

A Study of An Efficient Clustering Processing Scheme of Patient Disease Information for Cloud Computing Environment (클라우드 컴퓨팅 환경을 위한 환자 질병 정보의 효율적인 클러스터링 처리 방안에 대한 연구)

  • Jeong, Yoon-Su
    • Journal of Convergence Society for SMB
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    • v.6 no.1
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    • pp.33-38
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    • 2016
  • Disease of patient who visited the hospital can cause different symptoms of the disease, depending on the environment and lifestyle. Recent medical services offered in patients has changed in the environment that can be selected for treatment by analyzing the patient according to the disease symptoms. In this paper, we propose an efficient method to manage disease control because the treatment method may change at any patients suffering from the disease according to the patient conditions by grouping the different treatments to patients for disease information. The proposed scheme has a feature that can be ingested by the patient big disease information, as well as to improve the treatment efficiency of the medical treatment the increase patient satisfaction. The proposed sheme can handle big data by clustering of disease information for patients suffering from diseases such as patient consent small groups. In addition, the proposed scheme has the advantage that can be conveniently accessed via a particular keyword, the treatment method according to patient disease information. The experimental results, the proposed method has been improved by 23% in terms of efficiency compared to conventional techniques, disease management time is gained 11.3% improved results. Medical service user satisfaction seen from the survey is to obtain a high 31.5% results.