• KDI Journal of Economic Policy
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• v.39 no.1
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• pp.1-18
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• 2017

This paper empirically studies the effect of public procurement on small and medium-sized enterprises (SMEs) in the Republic of Korea using firm-level data. Public procurement, the purchase of goods and services from private firms by the public sector, is regarded as an important policy measure for providing support to firms, particularly SMEs. This study uses establishment-level panel data of the mining and manufacturing sectors from the Korean National Bureau of Statistics (Statistics Korea) and procurement history from the Korean Public Procurement Service to empirically estimate the effects of public procurement on firms' productivity (total factor productivity) and survivability. Using a propensity score matching estimation method, we find that participating firms showed higher productivity than non-participating ones in the control group only for the year of participation, that is, 2009. After two years, in 2011, they exhibited significantly lower productivity. In contrast, establishments that participated in public procurement for SMEs in 2009 were more likely to survive than those that did not do so in 2011. These results can be interpreted as the negative consequences of government intervention. The market's efficiency enhancement is hindered if underserving companies survive owing to government intervention but fail to improve efficiency.

• The Journal of Economics, Marketing and Management
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• v.10 no.3
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• pp.21-36
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• 2022

Purpose: The purpose of this study is to compare and analyze the enterprise's score index calculated from atypical data and corrected data. Research design, data, and methodology: In this study, news articles which are non-financial information but qualitative data were collected from 2,432 SMEs that has been extracted "square proportional stratification" out of 18,910 enterprises with fixed data and compared/analyzed each enterprise's score index through text mining analysis methodology. Result: The analysis showed that qualitative data can be quantitatively evaluated by region, industry and period by collecting news from SMEs, and that there are concerns that it could be an element of alternative credit evaluation. Conclusion: News data cannot be collected even if one of the small businesses is self-employed or small businesses has little or no news coverage. Data normalization or standardization should be considered to overcome the difference in scores due to the amount of reference. Furthermore, since keyword sentiment analysis may have different results depending on the researcher's point of view, it is also necessary to consider deep learning sentiment analysis, which is conducted by sentence.

• Journal of KIISE
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• v.42 no.4
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• pp.512-521
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• 2015

Internet users purchase goods on the Internet and express their positive or negative emotions of the goods in product reviews. Analysis of the product reviews become critical data to both potential consumers and to the decision making of enterprises. Therefore, the importance of opinion mining techniques which derive opinions by analyzing meaningful data from large numbers of Internet reviews. Existing studies were mostly based on comments written in English, yet analysis in Korean has not actively been done. Unlike English, Korean has characteristics of complex adjectives and suffixes. Existing studies did not consider the characteristics of the Internet language. This study proposes an emotional classification method which increases the accuracy of emotional classification by analyzing the characteristics of the Internet language connoting feelings. We can classify positive and negative comments about products automatically using the Internet emoticon. Also we can check the validity of the proposed algorithm through the result of high precision, recall and coverage for the evaluation of this method.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.221-233
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• 2017

To survive in the ever-changing environment, organizations need to improve or innovate their business processes. As a result, to attain this objective, BPM (Business Process Management) concept is widely adopted in modern enterprises. BPM life cycle consists of diagnosis, design, implementation and enactment. Conventionally, diagnosis of business process within the BPM life cycle is usually conducted by manual methods such as interviews, questionnaires and direct observations of process. And (re)designing business processes is also usually done manually under supervision of business experts from scratch. It is time-consuming and error-prone tasks. The objective of this research is to integrate the diagnosis and (re)design phase of BPM life cycle by sharing automatically generated process model and basic statistics in the diagnosis phase based on the process mining method. Eventually, this approach will lead to automate the tasks of diagnosis and design of business process. To implement and to show the usefulness of the proposed framework, two case studies were conducted in this research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.687-699
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• 2020

The government-led top-down development approach for weapons system faces the problem of technological obsolescence now that technology has rapidly grown. As a result, the government has gradually expanded the corporate-led bottom-up project implementation method to the defense industry. The key success factor of the bottom-up project implementation is the ability of defense companies to plan their technologies. This paper presented a method of analyzing patent data through data mining technique so that domestic defense companies can utilize it for technology planning activities. The main content is to propose corporate selection techniques corresponding to the defense communication-electronics sectors and conduct principal component analysis and cluster analysis for the International Patent Classification. Through this, the technology was classified into four groups based on the patents of nine companies and the representative enterprises of each group were derived.

• Korean small business review
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• v.42 no.4
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• pp.235-250
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• 2020

This study surveyed the perception of university students about employment in Small and Medium-sized Enterprises(SME) in the Chungbuk area to prepare improvement measures. In particular, the data were collected in descriptive questions along with the existing survey methods, and the perception of SME and decent work was identified using text-mining. As a result of the analysis, there are positive perceptions of jobs at SME such as various work experiences and low job competition rates, while there are generally many negative perceptions in pay, work and welfare. However, as a result of co-occurrence network analysis of responses to decent jobs, 'Information' was derived as a keyword. Currently, college students' negative perception of SME is affected by the lack of sufficient information, which needs to be improved first. To solve this problem, it was proposed to establish and operate a platform that can provide information on employment of SME and select necessary personnel.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.77-84
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• 2014

The purpose of this research is to identify and develop technology protection plans for small and medium-sized enterprises (SMEs) by analyzing past technology leakage patterns which were experienced by SMEs. We identified factors which affect the technology leakage, and analyzed patterns of the influences using a data mining algorithms. A decision tree analysis showed several significant factors which lead to technology leakage, so we conclude that preemptive actions must be put in place for prevention. We expect that this research will contribute to determining the priority of activities necessary to prevent technology leakage accidents in Korean SMEs. We expect that this research will help SMEs to determine the priority of preemptive actions necessary to prevent technology leakage accidents within their respective companies.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.424-429
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• 2007

The purpose of this study is to propose types of joint venturesthat can increase the competitivenessof a company in the marketplace. We examine the characteristics of individual venture enterprises based on technology. We considered 16 TEA in order to categorize companies into four groups. Next, we used a multinomial logistic regression model to identify the significant characteristics of a venture company that successfully predicts group membership. Based on this information, we propose various forms of joint venture which complement each other and produce higher overall competence. Our study can provide important feedback information to academics, Policy-makers.

• Asia pacific journal of information systems
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• v.10 no.2
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• pp.213-236
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• 2000

Many enterprises continue to have an interest in the usage of new information technologies to gain a competitive advantage. In particular, their interest in the data warehouse and the data mining reveals the aspect of such a trend. Although lots of vendors announce a variety of tools for data warehousing, many a enterprise have a difficulty in building a robust data warehouse due to the lack of the ability of selecting an appropriate data warehouse technology options. Therefore, this study presents some evaluation factors, evaluation methods, and evaluation results about ETT tools, mainly in terms of a comparative test for the current available data warehousing ETT tools, Also, this paper suggests some guides about choosing the right ETT tools.

• The Journal of Information Systems
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• v.27 no.1
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).