• 제목/요약/키워드: Task-Technology Fit

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감사인의 데이터 분석 기법 채택에 영향을 미치는 요인 연구 (A Study on the Effect of Selection on Data Analytics by Auditor)

  • 정관훈;이정훈;김다솜
    • Journal of Information Technology Applications and Management
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    • 제22권1호
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    • pp.37-60
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    • 2015
  • As the dependence on information systems in enterprises has grown dramatically, the importance of implementing information systems in audit has been increased as well. However, there is a lact of about utilization of information system for audit process. Thus, this study is to investigate the factors that effect auditor's adopting Data Analytics to audit work. Through literature research and focus group interview, we added two factors that affect the behavioral intention to UTAUT model. We have selected performance expectancy, effort expectancy, social influence, facilitating conditions, anxiety, task fit, behavioral intention as variables and verified hypotheses based on survey questionnaires from auditors. As a result, it was found that performance expectations, social influence, task fit influenced the behavior intention. In Addition, we analyzed adding two variables, IT-related work experience and type of auditor as moderate variable. This study has an implication for companies to motivate implementation as well as activation of Data Analytics technique.

기업의 머신러닝 선정에 영향을 미치는 요인 연구: 확장된 알고리즘 선택 문제의 관점으로 (A Study on the Factors Influencing a Company's Selection of Machine Learning: From the Perspective of Expanded Algorithm Selection Problem)

  • 이영수;권민수;권오병
    • 한국전자거래학회지
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    • 제27권2호
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    • pp.37-64
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    • 2022
  • 인공지능의 사회적수용도가 증가하면서 머신러닝 기법을 기업에 적용하는 사례가 증가하고 있다. 머신러닝 기법의 선정에는 주로 정확성이나 해석 가능성 등 기술적 요인이 주로 기준이 되어왔다. 그러나 머신러닝 채택의 성공은 개발부서, 사용부서, 리더십과 조직문화 등 경영관리 요인도 영향을 주기도 한다. 아쉽게도 기술적 요인과 경영관리적 요인이 함께 고려된 머신러닝 선정의 성공 요인을 이해하는 통합 연구가 거의 존재하지 않는다. 이에 본 논문의 목적은 기업 내 머신러닝 선정을 이해하기 위해 John Rice의 algorithm selection process model과 task-technology fit, 그리고 IS Success Model 이론을 결합한 기술-경영관리 통합 모형을제안하고 실증적 분석을 하는 것이다. 머신러닝을 도입한 국내 기업 240곳을 대상으로 설문 분석을 실시한 결과 알고리즘 품질과 데이터 품질이 높을수록 문제-알고리즘 적합성에 높게 영향을 주는 것으로 나타났으며, 문제-알고리즘 적합성은 조직의 생산성과 혁신성에도 유의한 영향을 미치는 것으로 검증되었다. 또한 외주화와 경영진 지원이 머신러닝 시스템 품질에 긍정적인 영향을 미치고, 데이터 중심 경영 및 동기화와 같은 조직문화 요인은 활용성과에 높은 영향을 미치는 것으로 확인되었다.

IT 지원 조직의 조직 적합성에 관한 연구 : 농촌 IT 지원조직의 사례 (A Study on the Organizational Fit of IT Supporting Organizations : A Case of IT Supporting Agricultural Promotion Agencies)

  • 박성희;안경아;김민정;최영찬;문정훈
    • 한국IT서비스학회지
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    • 제12권1호
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    • pp.15-32
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    • 2013
  • The concrete information technology (IT) has affected ways for supporting agricultural products. However, studies relating IT to agriculture in a broader sense have not been prevalent. The objective of this study is to improve agencies' effectiveness and performance in the use and application of IT through understanding the organizational fit and misfit. This research applied a multi-contingency view to Korean IT supporting agricultural promotion agencies and it evaluated the competitiveness of these agencies with reference to the correspondence of factors (Goal, Strategy, Environment, Knowledge Exchange, Task Design, and Information System) affecting their performance with organizational goals. The results reveal that organizations with good performance show better organizational fit with their organizational goal. This study contributes to the ways of efficient IT management in agricultural organizations in Korea.

How User's Participation in Feasibility Study Enhances Use of Business Intelligence Systems

  • Kim, Nam Gyu;Kim, Sung Kun
    • Journal of Information Technology Applications and Management
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    • 제24권3호
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    • pp.1-21
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    • 2017
  • Business Intelligence (BI) system is a strategic tool that presents an analytical perspective about business and external environments. Even though its strategic value was well known, users often avoid using it or adopt it ceremonially. In fact, over 50 per cent of BI projects worldwide are reported to end in failure. Such an unexpectedly lower success rate has been a key issue in BI studies. In order to enhance a proper use of information systems, MIS field provided a number of theoretical constructs. One example is Goodhue & Thompson's Task-Technology Fit (TTF). In addition, internalization, the degree to which people make their own effort to modify behavior, was recently suggested as another important determinant of use. Though in MIS community both TTF and internalization proved to be a key determinant of system use, there has been not much study aiming to discover antecedents influencing these constructs. In this study we assert that user participation should be highlighted in BI projects. Especially, we emphasize user participation at the phase of feasibility study that is mainly conducted to determine whether a BI system is essentially necessary and practicable. Our research model employs participative feasibility study as a major antecedent for TTF and internalization that consequently will lead to user satisfaction and actual use. This model was empirically tested on 121 BI system users. The result shows that user participation in feasibility study is positively associated with TTF and internalization, each being related to user satisfaction and system use. It implies that, if an organization has BI users get involved in strategic feasibility study phase, the BI system would turn out to fit users' tasks and, furthermore, users would put more efforts spontaneously in order to use it properly.

Cloud Task Scheduling Based on Proximal Policy Optimization Algorithm for Lowering Energy Consumption of Data Center

  • Yang, Yongquan;He, Cuihua;Yin, Bo;Wei, Zhiqiang;Hong, Bowei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권6호
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    • pp.1877-1891
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    • 2022
  • As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

한국형전투기(KF-X)의 최적정비를 위한 PBL 적용방안에 관한 연구 (A study on the PBL Application Scheme for Optimal Maintenance of the KF-X Project)

  • 박근석;윤용현
    • 한국항공운항학회지
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    • 제24권3호
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    • pp.10-18
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    • 2016
  • This paper deals with the Performance Based Logistics(PBL) application scheme pertaining to optimal maintenance program for logistics of Korean Fighter Experimental(KF-X) Project. For enhancement of the performance based logistics system application to KF-X program the selection of appropriate standards fit to maximize cost-cutting, a set of performance metrics fit for the purpose of the contract, foreign technology dependence of core equipments and parts were considered. Thus, selecting appropriate standards fit for Korean logistics environment, domestic maintenance enterprise for stable rate of operation of KF-X, a systematic reliability task that is able to measure quantitative combat capability are suggested.

Managing Deadline-constrained Bag-of-Tasks Jobs on Hybrid Clouds with Closest Deadline First Scheduling

  • Wang, Bo;Song, Ying;Sun, Yuzhong;Liu, Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권7호
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    • pp.2952-2971
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    • 2016
  • Outsourcing jobs to a public cloud is a cost-effective way to address the problem of satisfying the peak resource demand when the local cloud has insufficient resources. In this paper, we studied the management of deadline-constrained bag-of-tasks jobs on hybrid clouds. We presented a binary nonlinear programming (BNP) problem to model the hybrid cloud management which minimizes rent cost from the public cloud while completes the jobs within their respective deadlines. To solve this BNP problem in polynomial time, we proposed a heuristic algorithm. The main idea is assigning the task closest to its deadline to current core until the core cannot finish any task within its deadline. When there is no available core, the algorithm adds an available physical machine (PM) with most capacity or rents a new virtual machine (VM) with highest cost-performance ratio. As there may be a workload imbalance between/among cores on a PM/VM after task assigning, we propose a task reassigning algorithm to balance them. Extensive experimental results show that our heuristic algorithm saves 16.2%-76% rent cost and improves 47.3%-182.8% resource utilizations satisfying deadline constraints, compared with first fit decreasing algorithm, and that our task reassigning algorithm improves the makespan of tasks up to 47.6%.

IS Acceptance in the Perspective of the Extended TTF Theory: An Exploratory Study on Employment Insurance Systems in Korea

  • Kwahk, Kee-Young
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2003년도 추계학술대회 및 정기총회
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    • pp.99-102
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    • 2003
  • While information technology has been advanced impressively, the issue of system underutilization has continued. Although TAM provides a theoretical and empirical model for explaining information technology acceptance, there exist some issues: lack of focusing task and organization. The present study examines the motivational factors influencing the beliefs about the system, in terms or the extended TTF (task-technology fit) model, to address the issues. For this purpose, an exploratory case study was conducted based on the data gathered from a Web-based survey. The present research proposes five propositions, based on the results of the case study and prior study findings, which can be used as a starting point fur future research.

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An Exploration of a Performer's Organic Action

  • BongHee, Son
    • International Journal of Advanced Culture Technology
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    • 제10권4호
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    • pp.383-388
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    • 2022
  • This thesis explores the principle of a performer's organic action by means of his/her bodily responses on stage. This research has been developed to define the nature of a performer's central task in order to constitute empirical understanding of acting and the purpose of training in addressing the question of what sort of qualitative bodily training is necessary to be in a state of the full body involvement. This study investigates to articulate a performer's fundamental task at the most rudimentary level by utilizing those theatre artists' concepts with practical assumptions. In particular, the key terms, happen and change signifies the quality of a performer's body that has to fit into the given environment in which the performer's body can be subordinated through the moment on stage. Here, we argue that a performer's essential task parallel to make the following moment to happen and change by means of progressing a set of the next moment. In this manner, we also argue that a moment of displaying the performer's conscious effort, forceful and externalizing the visible elements under the use of erroneous language leads his/her body not to function on stage, a state of disengagement from his/her body. Finally, we provide a way to facilitate a performer's organic action by focused on his/her lived experience to create the functional moment which is opposite to the predominance of a representation, maintaining the performer's intellectual sense.

실버산업의 ICT 융합 유형과 ICT 기여 가치 탐색 (Exploring Silver ICT Convergent Typology and ICT Contribution Value)

  • 한현수;강태욱
    • 경영과학
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    • 제34권1호
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    • pp.57-70
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    • 2017
  • The phenomenon of increasing aging population is one of the crucial social and economic issues in these day. In this paper, drawn from the industrial application cases and relevant literatures, we present the typology of ICT convergent applications targeted for silver generation, referred as silver ICT. Subsequently, the contributional value of ICT as the enabling technology is estimated. We firstly conduct keyword search to collect currently used silver ICT applications. Secondly, drawn from the social welfare literature, we organize distinctive needs of the silver generations. Then, on the basis of task technology fit framework, typology of ICT enabled silver applications is organized through the fit of ICT in the sense of fulfilling those silver needs. Finally, using the industry input-output table figures, potential ICT contributions for silver ICT are estimated. The proposed silver ICT typology and ICT contributions provides useful insights for further research in the area of ICT convergence and silver market research.