• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.99-103
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• 2017

Productivity improvement is one of the important goals which firms' technology developments aim at. Firms' improved productivity from technology development means that their inputs can produce more outputs through technology development, which makes firms' productivity improvement from technology development more and more important in the age of technology advance and convergence like today. This research empirically analyzes the influence of the external technology collaboration network diversity on the productivity improvement of the small and medium-sized enterprises (SMEs) from technology development and the moderating effect of the chief technology officer (CTO)-driven technology development on this influence. This study constructs the research model reflecting the moderating impact of the CTO-driven technology development and tests it with the ordinary least squares regression through the IBM SPSS version 23 by using the 2,000 data about South Korean SMEs. This research empirically reveals two points. One is that SMEs' external technology collaboration network diversity has a positive influence on their productivity improvement from technology development. The other is that the positive effect of SMEs' external technology collaboration network diversity on their productivity improvement from technology development is moderated by the CTO-driven technology development. The two points revealed in this study present two meaningful implications in not only the practical but also academic point of view. The practical implication is that it is effective for SMEs to use CTOs in increasing their productivity improvement from technology development. The academic implication is that making technology collaboration with more diverse external partners can increase SMEs' productivity improvement from technology development.

• Korean Journal of Construction Engineering and Management
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• v.14 no.5
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• pp.113-121
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• 2013

An expansion into the global market increasingly becomes a buzz world among Construction Management(CM) firms in Korea. The objective of this study is to identify potential obstacles and investigate their nature and implications to CM firms in Korea. The study identified 25 obstacles under 5 categories. Base on a questionnaire survey and interviews with CM experts who have global CM projects experience, the study discusses that while there exist various types of obstacles, a more attention needs to be paid for a small number of major obstacles to minimine risks in overseas CM projects. It also suggests that improving pre-construction management competency through securing CM experts should be listed as a top agenda for Korean CM firms.

• Journal of Convergence for Information Technology
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• v.8 no.2
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• pp.209-218
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• 2018

The purpose of this study is to analyze the influence of information system factors and organizational factors on procedural management performance in small and medium-sized venture companies in the Seoul metropolitan area. In the previous study was conducted mainly on large companies and general SMEs. In this study, the research was conducted considering the characteristics of SMEs. The results showed that system suitability, system quality, and IT assets had a positive effect on procedural management performance, and manager perception and human resource capacity had a positive effect on procedural management performance. But the evaluation and compensation did not have a positive effect on procedural management performance. The results of this study showed almost the same results as those of the previous studies. Venture firms have poor financial ability, technology, and organizational management ability than general SMEs. However, the introduction and diffusion factors of new information systems were not significantly different from those of general SMEs.

• Journal of the Economic Geographical Society of Korea
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• v.4 no.1
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• pp.19-35
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• 2001

This paper is concerned with the relationships between large firms with global reaches in their markets and subcontracting firms, mostly small and medium-sized firms. It then attempts to focus in more detail on the dynamic relational dimensions between the two. In doing so, we draw upon the secondary data and the results of interviewing survey with some senior managers. The empirical study shows that the localisation of subcontracting networks have been increasingly reinforced thanks to the increasing tendency of vertical disintegration by LC. However, it is identified that there is a tendency that local subcontractors are specialised in producing relatively low value-added and low technology-intensive electronic parts/components. Based on these results, the author suggests the implications of regional economic development in the context of innovation and learning.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.1
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• pp.178-199
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• 2014

This study aims to understand regional specificity and its impact on the IT service industry in Fairfax County. Fairfax County primarily specializes in the IT service in the United States, and it has cultivated a resilient and unique industrial environment. Business-related initiatives by the federal government have resulted in the influx and expansion of IT service firms, the formation of new small firms, the abundance of skilled workers, and the growth of the IT services related with the federal procurement market, though the government policies do not explicitly intend to affect the industrial path in Fairfax County. Meanwhile, local institutions have provided various programs and services for both incumbent firms and potential entrants, and have recently focused on the accumulation and leverage of relational assets among economic actors through a variety of networking venues.

• International Area Studies Review
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• v.13 no.3
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• pp.213-238
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• 2009

This paper empirically examines effects of exporting on employment over the period 2000-2007 for Korean listed and non-listed manufacturing firms. The paper employs the dynamic panel model of labor demand and controls for simultaneity of the exports and real wages using a two step random effect Tobit-DPD (Dynamic Panel Data) procedure. Our empirical results suggest that surprisingly, there is no robust evidence for employment effects of exporting of Korea's large firms and small-medium sized firms during the sample period after Korean financial crisis. This implies that Korean exporting patterns have been changed in a way that exporting highly capital intensive goods leads to importing more intermediate goods and thus to countervailing the employment effects of exporting. This suggests that expansion of exporting by lowering exporting prices through the bilateral FTA might not be helpful to enhancing employment in Korea.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.123-136
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• 2019

This study is to provide a method to increase the credit rating of the company by examining and managing the executive competency of the CEO of SMEs and Venture Firms. We analyzed the importance and priority of AHP by surveying bank loan staff and CEOs. According to the analysis results, ethics management, strategic thinking, and expertise level were the highest in the relative importance of bank loan staff. The relative importance of CEOs was higher in order of marketing, bank transaction reliability, and financing. Result of this study is similar to the relative importance of the previous research. This study suggests to disclosing credit rating system and reflect the opinions of the CEO in order to protect financial consumers. The significance of this study is to present the factors and the importance that can help to develop advanced models.

• Asia-Pacific Journal of Business
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• v.11 no.2
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• pp.173-188
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• 2020

Purpose - This study examines the determinants of offer price and short-term and long-term performance of small and medium-sized enterprise(SME) IPO stocks listed on the KOSDAQ during the period from July 2007 to December 2016. Design/methodology/approach - The SME IPO samples are classified into three categories of regular listing, technology-based special listing, and listing by merger with special purpose acquisition company(SPAC), whose results are compared each other and compared to the result for the KOSDAQ listing of large firms. Findings - From the point of SME management which attempts to list its company on the KOSDAQ, the listing by merger with SPAC is the most unfavorable, and the underpricing phenomenon of the technology-based special listing is severe in the second place. By contrast, IPO stock investors can earn the largest abnormal return by purchasing the SPAC which succeeds the merger with unlisted firm, and the next abnormal returns are obtained in the order of the IPO stocks of technology-based special listing, regular listing of SMEs, and regular listing of large firms. However, it is interesting to observe that the net buying ratio of individual investors is relatively large for the IPO stocks of regular listing of SMEs and large firms, which exhibit the long-term under-performance. Research implications or Originality - This result implies that the exceptional listing system such as the technology-based special listing or the listing by merger with SPAC cost the SMEs which bypass the complicated procedure of the regular listing.

• Korea Trade Review
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• v.47 no.6
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• pp.335-353
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• 2022

There are two aspects of digital trade: the digitalisation of goods/services being traded and the digitalisation of the transactional act. Digital data (i.e. machine-readable industrial data and transactional data) is the major driving force for both aspects of digital trade. Digital data is a non-rivalrous input, whether for production or marketing activities, and is thus able to be used by many firms or government agencies without limiting the use of others. Digital platforms provide online infrastructure for the interactions between groups, for instance, consumers and producers. The externality effect refers to the situation in which prosperity in one group on a given platform will improve the returns of other groups on the same platform. In the era of the data-driven economy, strategic trade policy can involve data-related policies. The major objective of these policies is to improve the competitiveness of domestic firms. For instance, firms may be subsidised if they use cloud services provided by specific platforms. This strand of strategic trade policies might be useful for increasing the competitiveness of small-and medium-sized enterprises (SMEs) via the digitalisation of production/marketing processes. Alternatively, strategic trade policy may also exploit the externality effect via platform economy-related policies. Further, some countries may form data coalitions to facilitate cross-border data flow. This paper uses cases in Asian countries to illustrate which role these strategic trade policies can play in the digital economy.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.