• Journal of Digital Convergence
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• v.19 no.10
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• pp.143-149
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• 2021

As the need to establish a big data system for rapid provision of big data and efficient management of resources has emerged due to rapid entry into the hyper-connected intelligence information society, public institutions are pushing to establish a big data system. Therefore, this study analyzed and combined the success factors of big data-related studies and the specific aspects of big data in public institutions based on the measurement of environmental factors for establishing an integrated information system for higher education institutions. In addition, 19 measurement items reflecting big data characteristics were derived from big data experts using brainstorming and Delphi methods, and a plan to successfully apply them to public institutions that want to build big data systems was proposed. We hope that this research results will be used as a foundation for the successful establishment of big data systems in public institutions.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.237-253
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• 2018

In a rapidly changing environment, dynamic resources have become important factors for companies, the use of Big Data come into focus new core value of business but researches on the major resources and capabilities of companies are insufficient. In this study, the effect of dynamic capability and entrepreneurial orientation in the SMEs on the intention of Big Data utilization are explored. For the purpose of empirical analysis, the survey condusted of 364 domestic SMEs to analyze the effect of dynamic capability on the intention of Big Data utilization through entrepreneurial orientation, performed a parallel multi-parameter analysis of using SPSS Win Ver.22.0 and PROCESS macro v3.0. The results of hypothesis testing showing that dynamic resources and entrepreneurial orientation had positive influence intention of big data utilization. For the determinants of Big Data utilization related to AI it provide suggestions thereby improving the understanding of dynamic capabilities and entrepreneurial orientation and helping to improve the management of SMEs.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.377-389
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• 2021

This study aims at investigating the effects of big accounting data on the sustainable business growth of listed firms in Thailand. In addition, it examines the mediating effects of accounting information quality and decision-making effectiveness and the moderating effects of digital innovation on the research relationships. The study's useful samples are the 289 listed Thai companies. To examine the research relationships, the structural equation model and multiple regression analysis are used in this study. According to the results of this study, big accounting data has a significant effect on accounting information quality, decision-making effectiveness, and sustainable business growth. Next, accounting information quality significantly affects decision-making effectiveness and sustainable business growth. Similarly, decision-making effectiveness significantly affects sustainable business growth. Both accounting information quality and decision-making effectiveness mediate the big accounting data-sustainable business growth relationships. Lastly, digital innovation moderates the effects of accounting information quality and decision-making effectiveness on sustainable business growth. Accordingly, In conclusion, big accounting data has emerged as a key source of sustainable competitive advantage. As a result, to succeed in competitive environments, businesses must have a thorough understanding of big accounting data.

• The Journal of Information Systems
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• v.24 no.4
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• pp.139-152
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• 2015

With the advancement of the Internet/IT technologies and the increased computation power, massive data can be collected, stored, and processed these days. The availability of large databases has brought forth a new era in which companies are hard pressed to find innovative ways to utilize immense amounts of data at their disposal. Indeed, data has opened a new age of business operations and management. There are already many cases of innovative businesses reaping success thanks to scientific decisions based on data analysis and mathematical algorithms. Big Data is a new paradigm in itself. In this article, Big Data is viewed as a new perspective rather than a new technology. This value centric definition of Big Data provides a new insight and opportunities. Moreover, the Business Analytics, which is the framework of creating tangible results in management, is introduced. Then the Internet of Things (IoT), another innovative concept of data collection and networking, is presented and how this new concept can be interpreted with Big Data in terms of the value centric perspective. The challenges and opportunities with these new concepts are also discussed.

• Journal of Information Technology Applications and Management
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• v.28 no.1
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• pp.13-31
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• 2021

The purpose of this study is to find the factors that influence big data characteristics on decision satisfaction and utilization behavior, analyze the extent of their influence, and derive differences from existing studies. To summarize the results of this study, First, the study found that among the three categories that classify the characteristics of big data, qualitative attributes such as representation, purpose, interpretability, and innovation in the value innovation category greatly enhance decision confidence and decision effectiveness of decision makers who make decisions using big data. Second, the study found that, among the three categories that classify the characteristics of big data, the individuality properties belonging to the social impact category improve decision confidence and decision effectiveness of decision makers who use big data to make decisions. However, collectivity and bias characteristics have been shown to increase decision confidence, but not the effectiveness of decision making. Third, the study found that among the three categories that classify the characteristics of big data, the attributes of inclusiveness, realism, etc. in the integrity category greatly improve decision confidence and decision effectiveness of decision makers who make decisions using big data. Fourth, it was analyzed that using big data in organizational decision making has a positive impact on the behavior of big data users when the decision-making confidence and finally, decision-making effect of decision-makers increases.

• Journal of Distribution Science
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• v.13 no.9
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• pp.5-11
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• 2015

Purpose - The purpose of this research is to provide insights that can be used for deliberate decision making around challenging big data investments by measuring the economic value of such big data implementations. Research design, data, and methodology - We perform empirical research through an event study. To this end, we measure actual abnormal returns of companies that are triggered by their investment announcements in big data, or firm size information, during the three-year research period. The research period targets a timeframe after the introduction of big data at Korean firms listed on the Korea stock markets. Results - Our empirical findings discover that on the event day and the day after, the abnormal returns are significantly positive. In addition, our further examination of firm size impacts on the abnormal returns does not show any evidence of an effect. Conclusions - Our research suggests that an event study can be useful as an alternative means to measure the return on investment (ROI) for big data in order to lessen the difficulties or decision making around big data investments.

• Knowledge Management Research
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• v.18 no.3
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• pp.63-80
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• 2017

Big Data environment is established by accumulating vast amounts of data as users continuously share and provide personal information in online environment. Accordingly, the more data is accumulated in online environment, the more data is accessible easily by third parties without users' permissions compared to the past. By utilizing strategies based on data-driven, firms recently make it possible to predict customers' preferences and consuming propensity relatively exactly. This Big Data environment, on the other hand, establishes 'Dataveillance' which means anybody can watch or control users' behaviors by using data itself which is stored online. Main objective of this study is to identify the relationship between Dataveillance and users' online privacy protection behaviors. To achieve it, we first investigate perceived online service efficiency; loss of control on privacy; offline surveillance; necessity of regulation influences on users' perceived threats which is generated by Dataveillance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.433-434
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• 2014

Big Data services is composed of Big Data user, Big Data service provider, and Big Data application provider. And it is possible to extend the service to interplay-reciprocal actions among three subjects such as providing, being provided, connecting, being connected, and so on. In this paper, we propose an ecosystems of Big Data and a framework of its service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1562-1565
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• 2020

With the development of digital technology, the industrial structure is becoming digitalize. The government selected big data as the key technology of the 4th industrial revolution. Among them, big data is widely used to create new values and services by utilizing vast amounts of information. In order to cultivate professional manpower for the use of big data, various education programs are provided at universities. We intend to develop a curriculum for systematic training of talented people who can acquire knowledge about the three stages of collection, analysis, and application of big data. To this end, subjects are classified into basic competency, technical competency, analysis competency, and business competency based on the big data competency model proposed by the Korea Internet & Security Agency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.728-731
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• 2014

Today, the quality of medical service has become a major concern because that sustainable development of IT technology and extending people's life expectancy. This paper, it is used as a tool for the medical information quality management that analyze tweets big data form generated by individual's daily. The result of the analyze big data offers improvement medical information based evidence based medicine. Also it has been possible for a trace observation of chronic disease and can reduce additional other complications of patients. Therefore, effective treatment of disease and prevention is possible.