• Journal of Technology Innovation
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• v.22 no.3
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• pp.37-63
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• 2014

This study is intended to demonstrate how different factors induce the Korean government's direct investment in research and development according to the type of business enterprise in Korea. We analyzed that what factors made the government directly invest in research and development by using a total of 18,272 company panel data, which are not limited to specific industries or government-led research and development (R&D) programs. The results showed that the direct investment for R&D by the government led to the increase in the number of researchers in SMEs. For major companies, the direct investment resulted in the increase of sales and company's own R&D expenses. Moreover, this study found that government's direct support for R&D even led to the decrease of SMEs' own R&D expenses; however, this result was not statistically significant. In addition, the most significant factor to increase both SMEs' and major company's own R&D expenses was the sales amount of the company, rather than government's direct investment for R&D. The factor that increases sales was the company's own R&D expenses, rather than government's direct investment for R&D. Through the analysis using Mixed Effects Model, this study suggested the policy should be changed to make SMEs invest in its own R&D expenses, rather than to secure researchers of SMEs by government's direct investment for R&D.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.123-130
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• 2012

The automobile industry has been rapidly developing and the manufacturers in Korea as well as auto makers in other advanced countries are putting every ounce of their energies in securing their competitive edges in technology and in marketing. To that purpose, each company focuses on (i) reducing costs and (ii) improving productivity. We believe that the improved productivity can be capitalized by a set of various factors including improved organization-internal environment and employees' job satisfaction. The present research aims to identify how the internal elements contribute and lead to improved productivity. The present paper is a report of an empirical survey performed to 161 employees working in small and medium-sized firms in the automobile industry. After testing reliability and validity of the collected data, we have performed structural equation analysis using Amos of SPSS and tested a set of research hypotheses and models. The reported results will clarify the factors that influence productivity and job satisfaction and also shed light on the directions for strategic polices to keep up with the ever changing climate of the industry.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.427-436
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• 2013

Social media is drawing attention among companies for its potential as a marketing tool. There are many types of social media and their characteristics are varied, and thus choosing the appropriate social media considering the purpose of the company is important. In this paper, we conduct comparative analysis on the popular social media such as Facebook, Twitter, Naver blog, Youtube, Cyworld and Me2day using multidimensional scaling method. The result shows that there are differences in the effectiveness of enhancing diverse dimensions of corporate image among social media. This result can be used in developing social media based marketing strategy.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.147-153
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• 2017

This research empirically analyzes not only the direct impact of the external technological information network diversity of small and medium-sized enterprises (SMEs) on the sales growth from their technology development but also the mediating impact of their productivity improvement and the moderating effect of the technology development driven by CEO on this direct impact in order to deepen the research stream on SMEs' external technological information network. Based on the ordinary least squares regression by using 2,200 data of South Korean SMEs, this study reveals the three findings. First, SMEs' external technological information network diversity positively influences their sales growth from technology development. Second, SMEs' productivity improvement partially mediates this positive influence of the external technological information network diversity. Third, SMEs' technology development driven by CEO moderates the positive influence.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.388-408
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• 2021

Recently, the importance of B2B CSR is being highlighted. Meanwhile, in B2B marketing, salesperson is widely recognized as a key resource influencing supplier firm performance. Therefore, the author paid attention to the role of supplier CSR reputation in customer-salesperson interaction process. So, this study collected dyadic data from 161 B2B purchasing managers and salespersons interacting with them. For customers, a supplier CSR reputation increased customer citizenship behavior and customer long-term orientation. With salespersons, they experienced less burnout due to interacting with customers having higher customer citizenship behavior and long-term orientation. Moreover, the results confirmed that a supplier CSR reputation lowered salespersons' emotional exhaustion through two serial-multiple mediation paths. This research verified that customers' perception and responses to supplier's CSR significantly influence B2B salesperson burnout.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.369-379
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• 2022

With the deepening integration of technology and cultural industries, China's digital cultural industry has begun to rise. The digital culture industry has met new demands for cultural consumption and brought new experiences to consumers in the digital economy era. This paper uses the public data of 36 Chinese A-share listed companies in digital culture from 2018 to 2019 to construct a technical innovation efficiency evaluation index system for listed companies in China's digital cultural industry. Through the use of data envelopment analysis (DEA) method, the technical innovation efficiency of 36 listed companies in China's digital cultural industry was evaluated. The research results show that: (1) China's 36 listed companies have low technological innovation efficiency; (2) the allocation of R&D resources of listed companies is unreasonable; (3) there is a large difference in technological innovation efficiency among listed companies. Therefore, it is necessary to increase the efficiency of technology innovation of listed companies in China's digital culture industry by investing more R&D funds, distributing R&D resources, establishing effective dynamic incentive mechanism, promoting government-industrial-academic research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.141-156
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• 2020

Differential privacy, which used to collect and analysis data and preserve data privacy, has been applied widely in data privacy preserving data application. Local differential privacy algorithm which is the local model of differential privacy is used to user who add noise to his data himself with randomized response by self and release his own data. So, user can be preserved his data privacy and data analyst can make a statistical useful data by collected many data. Local differential privacy method has been used by global companies which are Google, Apple and Microsoft to collect and analyze data from users. In this paper, we compare and analyze the local differential privacy methods which used in practically. And then, we study applicability that applying the local differential privacy method in survey or opinion poll scenario in practically.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.737-751
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• 2023

The importance of digital forensics in the cloud environment is increasing as businesses and individuals move their data from On-premise to the cloud. Cloud data can be stored on various devices, including mobile devices and desktops, and encompasses a variety of user behavior artifacts, such as information generated from linked accounts and cloud services. However, there are limitations in securing and analyzing digital evidence due to environmental constraints of the cloud, such as distributed storage of data and lack of artifact linkage. One solution to address this is archiving services, and Google's Takeout is prime example. In this paper, user behavior data is analyzed for cloud forensics based on archiving data and necessary items are selected from an investigation perspective. Additionally, we propose the process of analyzing selectively collected data based on time information and utilizing web-based visualization to meaningfully assess artifact associations and multi-behaviors. Through this, we aim to demonstrate the value of utilizing archiving data in response to the increasing significance of evidence collection for cloud data.

• Cartoon and Animation Studies
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• s.36
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• pp.553-572
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• 2014

In this paper, for the evaluation of the ease of a particular Web site (www.appbelt.net), insert the log tracking code for Google Analytics in a page of the Web site to collect behavioral data of visitor and has studied the improvement measures for the problems of the Web site, after the evaluation of the overall quality of the Web site through the evaluation of Coolcheck. These findings set the target value of the company's priority (importance) companies want to influence the direction of the business judgment are set up correctly, and the user's needs and behavior will be appropriate for the service seems to help improvement.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.45-48
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• 2016

오늘날의 고객은 다양한 정보를 통해 넓은 선택의 기회를 가진다. 이러한 상황에서 기업들은 고객과의 지속적인 관계를 유지하기 어려워짐에 따라 고객 유지와 신규 고객 유치를 위한 마케팅 비용을 천문학적으로 지출하고 있다. 기업들이 이탈하는 고객의 속성을 분석하고 이탈 시점을 예측할 수 있다면 마케팅에 사용되는 비용과 노력을 최소화할 수 있을 것으로 예측된다. 이를 위해 본 논문에서는 효과적인 고객 이탈 예측을 위한 딥러닝 기반의 이탈 예측 모델을 제안한다. 이 모델은 모바일 RPG 게임 고객의 시계열적인 행동 패턴을 이용하여 이탈을 예측하는 모델로, 예측을 위한 학습을 할 때 모델링된 고객 데이터를 분석하여 이탈 고객의 특성을 파악할 수 있게 한다. 실험을 통해 이탈 고객과 미 이탈 고객의 모델링된 값이 각각 특정 속성에 치중되어 있는 것을 확인하였고, 제안 모델이 합리적으로 고객의 이탈을 예측하는 것을 보였다.