• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.31-34
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• 2018

We live in the digital era, and the characteristics of our customers in the digital era are constantly changing. That's why understanding business requirements and converting them to technical requirements is essential, and you have to understand the data model behind the business layout. Moreover, BI(Business Intelligence) is at the crux of revolutionizing enterprise to minimize losses and maximize profits. In this paper, we have described a leading study about the situation of desk-top BI(software product & programming language) in aspect of front-end side and the Data Lake platform based on Big Data by data modeling in aspect of back-end side to support the business intelligence.

• Journal of Smart Tourism
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• v.2 no.1
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• pp.21-31
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• 2022

This review paper aims at providing a systematic analysis of articles published in various journals and related to the uses and business applications of big data. The goal is to provide a holistic picture of the place of big data in the tourism industry. The reviewed articles have been selected for the period 2013-2020 and have been classified into 8 broad categories namely business strategy and firm performance; banking and finance; healthcare; hospitality; networks and telecommunications; urbanism and infrastructures; law and legal regulations; and government. While the categories are reflective of components of tourism industries and infrastructures, the meta-analysis is organized around 3 broad themes: preferred research contexts, conceptual developments, and methods used to research big data business applications. Main findings revealed that firm performance and healthcare remain popular contexts of research in the big data realm, but also demonstrated a prominence of qualitative methods over mixed and quantitative methods for the period 2013-2020. Scholars have also investigated topics involving the notions of competitive advantage, supply chain management, smart cities, but also ethics and privacy issues as related to the use of big data.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.1-9
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• 2014

This research describes strategies to promote the growth of the Big Data industry and the companies within the ecosystem. In doing so, we identify the roles and responsibilities of various objects of this ecosystem and Big Data concepts. We describe the five components of the Big Data ecosystem: governance, data holders, service users, service providers and infrastructure providers. Related to the Big Data industry, the paper discusses 13 business strategies between the five components in the ecosystem. These strategies directly respond to areas of research by the Big Data industry leading experts on its early development. These strategies focus on how companies can gain competitive advantages in a growing new business environment of Big Data. The strategy topics are as follows: 1) the government's long term policy, 2) building Big Data support centers, 3) policy support and improving the legal system, 4) improving the Privacy Act, 5) increasing the understanding of Big Data, 6) Big Data support excavation projects, 7) professional manpower education, 8) infrastructure system support, 9) data distribution and leverage support, 10) data quality management, 11) business support services development, 12) technology research and excavation, 13) strengthening the foundation of Big Data technology. Of the proposed strategies, establishing supportive government policies is essential to the successful growth of thee Big Data industry. This study fosters a better understanding of the Big Data ecosystem and its potential to increases the competitive advantage of companies.

• 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.

• Industry Promotion Research
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• v.5 no.4
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• pp.91-100
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• 2020

In the U.S.A. from the late 19th to the early 20th century, the big business system emerged surpassing the British Empire economy. Such growth resulted from the realization of the "American-productive mode' being derived from the continuous immigrants inflow, renovative development of transportation, national markets formation and R&D of the science·technology. During 10 years after 1895, American economy was prevalent with the combination trends by the vertical or horizontal integration and these both mixed systems. As such big business was recognized, the American domestic citizens expressed the strong doubt to the revolutionary change and its public benefits and inaugurated the anti-big business campaign with deep concern that the American traditional symbol 'land of the wealth and opportunity' would be threatened. Although the governmental organizations controlling big business were established and the control laws were enforced, the American society accepted the new economic order. This situation resulted from the American economic prosperity, material affluence and managerialism of the big business.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.507-517
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• 2020

The present research intends to examine the relationship between the Big Five personality traits and leadership initiations among the marketing executives in Delhi NCR (INDIA), and seeks to uncover the predictors of leadership initiations within personality traits. The data are collected through online survey method using different social media platforms. A sample of 233 (male =136 and female =97) marketing executive's responses were included. The data collected with the help of self-reported Big Five model inventory and leadership initiation test. The collected data were analyzed statistically by using descriptive statistics, correlation. and stepwise multiple regression analysis. The results revealed that the age of respondents inversely correlated with leadership initiation. Neuroticism revealed significant inverse correlation with leadership initiation, whereas significant positive correlations were found between extraversion, conscientiousness, agreeableness, and leadership initiations, while openness to experience revealed insignificant positive correlation with leadership initiation. Extraversion and conscientiousness appeared as the most dominant personality traits among marketing executives, irrespective of gender, that positively influenced leadership initiation and appeared as the predictor of leadership initiation. In male executives extraversion and age emerged as the predictors of leadership behavior, while in female executives extraversion and openness to experience personality traits appeared as the predictors of leadership initiation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.209-220
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• 2020

This study aimed to analyze characteristics of banker's personality who were engaged in five commercial banks (KB Kookmin Bank, Shinhan Bank, Woori Bank, KEB Hana Bank and NH Nonghyup Bank) with Big5 personality traits and also, investigate the influence of personality traits on entrepreneurial intention and digital media utilization capability, especially based on preceding research. Also, it analyzed mediated effect of digital media capability between Big5 personality traits and entrepreneurial intention. First, the analysis results of the influence of Big5 personality traits on the entrepreneurial intention showed that extroversion, openness had positive impact on the entrepreneurial intention but sincerity had negative impact on the entrepreneurial intention. Second, the friendliness, sincerity, openness had positive impact on contents utilization capability while openness had positive impact on the communication utilization capability. Third, the influence of communication utilization capability on the entrepreneurial intention was positive. Fourth, the mediated effect of digital media capability between Big5 personality traits and entrepreneurial intention discovered that the communication utilization capability mediated the openness and entrepreneurial intention. It's required to look for the bankers with extroversion, openness that positively influenced entrepreneurial intention and carry out systematic, practical entrepreneurship education to help set up actual business after retirement. This study successfully derive conclusion that it's in urgent need to improve entrepreneurship education program so that the bankers could strengthen their communication utilization capability and improve their capability to gather various information through entrepreneurship education and furthermore, create new value followed by starting their own business.

• The Journal of Bigdata
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• v.1 no.1
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• pp.23-32
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• 2016

With the rapid development of information technology, we can manage not only structured data but also unstructured data. Big data environments drive new business values. This study examines the effect of analytic resources to business performance under big data environments. Recent worldwide reports showed empirical performance results of big data applications. Compared to these reports, we attempt to analyze resources of big data applications to companies in Korea. This study results in current status of big data use in Korea. and will help to develop a maturity model of big data applications.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.109-121
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• 2023

This study aims to address the literature gap by examining the direct relationship between big data analytics capability, marketing innovation, and organizational innovations. Additionally, this study would examine big data analytics capability as the antecedent for both innovation types and how these relationships influence firm performance. The research model is developed based on the integration of resource-based view and knowledge-based view theories. The quantitative method is used as the research methodology for this study. Based on a purposive sampling method, a total of 115 questionnaires were obtained from managers in star-rated hotels located in Malaysia. Partial least square structural equation modeling (PLS-SEM) is utilized for the data analysis. The result shows that big data analytics capability positively affects marketing and organizational innovations. The findings show that big data analytics capability and organizational innovation positively influence firm performance. Nonetheless, the result revealed that marketing innovation is not positively related to firm performance. The findings also indicate to hotel managers the importance of big data analytic capability and the resources required to build and develop this capability. The contributions from this study enrich the literature on big data and innovation, which is particularly limited in the hospitality and tourism context.

• 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.