• Journal of Information Technology Applications and Management
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• v.22 no.1
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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.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.37-64
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• 2022

As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.

• Journal of Information Technology Services
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• v.12 no.1
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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.

• Journal of Information Technology Applications and Management
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• v.24 no.3
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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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%.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.3
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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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%.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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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.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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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.

• Korean Management Science Review
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• v.34 no.1
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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.