• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.301-314
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• 2013

The existing computer environment, numerous mobile environments and the internet environment make human life easier through the development of IT technology. With the emergence of the mobile and internet environment, data is getting bigger rapidly. From this environment, we can take advantage of using those data as economic assets for organizations which make dreams come true for the emerging Big Data environment and Big Data security services. Nowadays, Big Data services are increasing. However, these Big Data services about Big Data security is insufficient at present. In terms of Big Data security the number of security by Big Data studies are increasing which creates value for Security by Big Data not Security for Big Data. Accordingly in this paper our research will show how security for Big Data can vitalize Big Data service for organizations. In details, this paper derives the priorities of the components of Big Data Information Security Service by AHP.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.89-97
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• 2014

As Big Data's value is perceived and Government 3.0 is announced, there is a growing interest in Big Data. However, it won't be easy for each public institute or local government to apply Big Data systematically and make a successful achievement despite lacking of specific alternative plan or strategy. So, this study tried to suggest strategies to use Big Data after arranging the area which local government utilize it in. As a result, utilization areas of local administration's Big Data are divided into four areas; recognizing and corresponding the abnormal phenomenon, predicting and corresponding the close future, corresponding analyzed situation and developing new policy(administration service), and citizen customized service. In addition, strategies about how to use Big Data are suggested; stepwise approach, user's requirements analysis, critical success factors based implementation, pilot project, result evaluation, performance based incentive, building common infrastructure.

• East Asian Journal of Business Economics (EAJBE)
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• v.4 no.1
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• pp.5-15
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• 2016

With vigorous development of global network community, smart phones and mobile devices, enterprises can rapidly collect various kinds of data from internal and external environments. How to discover valuable information and transform it into new business opportunities from big data which grow rapidly is an extremely important issue for current enterprises. This study treats Company S as the subject and tries to find the factors of big data application in enterprises by a modified Decision Making Trial and Evaluation Laboratory (DEMATEL) and perceived benefits - perceived barriers relation matrix as reference for big data application and management of managers or marketing personnel in other organizations or related industry.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.19-20
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• 2015

Since 2013, Seoul Metropolitan Government (SMG) has introduced big data initiatively in administration and put into practices in transportation, safety, welfare in order to overcome limited resources and conflicting interests. For establishing a new midnight bus service, SMG prepared optimized midnight bus routes by analyzing big data from mobile phone Call Data Record (CDR) through collaboration with a telecommunication company. Despite of limited budget and resources, newly identified routes can cover over 42% of the citizen with 9 routes and less than 1% of buses compare with day time operation. In addition to solve transportation problem, SMG utilizes big data to resolve location selection problem for choosing new facility locations such as life double cropping centers and senior citizen leisure centers. As results, SMG demonstrates big data as a good tool to make policies and to build smarter city by overcome space-time limitation of resources, mediation of conflicts, and maximizes benefit of the citizen.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.103-103
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• 2019

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.131-143
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• 2024

Purpose - The purpose of this study was to analyze cases of big data-driven business in the financial industry, focusing on organizational structure and business processes using big data in banking industry. Design/methodology/approach - This study used a case study approach. To this end, cases of two banks implementing big data-driven business were collected and analyzed. Findings - There are two things in common between the two cases. One is that the central tasks for big data-driven business are performed by a centralized organization. The other is that the role distribution and work collaboration between the headquarters and business departments are well established. On the other hand, there are two differences between the two banks. One marketing campaign is led by the headquarters and the other marketing campaign is led by the business departments. The two banks differ in how they carry out marketing campaigns and how they carry out big data-related tasks. Research implications or Originality - When banks plan and implement big data-driven business, the common aspects of the two banks analyzed through this case study can be fully referenced when creating an organization and process. In addition, it will be necessary to create an organizational structure and work process that best fit the special situation considering the company's environment or capabilities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.84-90
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• 2019

Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. One of the most rapidly growing technologies in this sphere is business intelligence, and associated concepts such as big data and data mining. BI is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, big data has come to mean various things to different people. When comparing big data vs business intelligence, some people use the term big data when referring to the size of data, while others use the term in reference to specific approaches to analytics. As the volume of data grows, businesses will also ask more questions to better understand the data analytics process. As a result, the analysis team will have to keep up with the rising demands on the infrastructure that supports analytics applications brought by these additional requirements. It's also a good way to ascertain if we have built a valuable analysis system. Thus, Business Intelligence and Big Data technology can be adapted to the business' changing requirements, if they prove to be highly valuable to business environment.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.15-27
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• 2023

The purpose of this research is to investigate the impact of Business Intelligence (BI) on the relation between Big Data Analytics (BDA) and Financial Performance (FP), at the beginning we reviewed the academic accounting and finance literature to develop the theoretical framework of business intelligence, big data and financial performance in terms of definition, motivations and theories, then we conduct an empirical analysis based on questionnaire-base survey data collected. The researchers identified the study population in the joint-stock companies listed on the Egyptian Stock Exchange and operating in the sectors and activities related to modern technologies in information systems, big data analytics, and business intelligence, in addition to the auditing offices that review the financial reports of these companies, and The sector closest to the research objective is the communications, media, and information technology sector, where the survey list was distributed among the sample companies with (15) lists for each company, and (15) lists for each audit office, so that the total sample becomes (120) individuals (with a response rate 83.3%), The results show, First, Big data analytics significantly affect organizations' financial performance, second, Business intelligence mediates (partial) the relationship between big data analytics and financial performance.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.17-22
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• 2019

As the value of big data is recognized as important, it is possible to advance decision making by effectively introducing and improving the development and utilization of JAVA and R programs that can analyze vast amounts of existing and unstructured data to governments, public institutions and private businesses. In this study, news data was collated and analyzed through text mining techniques in order to establish marketing strategies based on consumers' airline preferences. This research is meaningful in establishing marketing strategies based on analysis results by analyzing consumers' airline preferences using high-level big data utilization program techniques for data that were difficult to obtain in the past.

• Knowledge Management Research
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• v.21 no.4
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• pp.243-263
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• 2020

The purpose of this study is to propose the performance measurement model for open big data platform. In order to develop the performance measurement model, we have integrated big data reference architecture(NIST 2018) with performance prism model(Neely et al. 2001) in the platform perspective of open big data. Our proposed model consists of five key building blocks for measuring performance of open data platform as follows: stakeholder contribution, big data governance capabilities, big data service capabilities, big data IT capabilities, and stakeholder satisfaction. In addition, our proposed model have twenty four evaluation indices and seventy five measurement items. We believe that our model could offer both research and practical implications for relevant research.