• Journal of Venture Innovation
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• v.6 no.3
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• pp.43-60
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• 2023

Although the importance of starting a business is being emphasized, it is not easy for a start-up to survive. Therefore, it is necessary to come up with a plan to strengthen startup satisfaction and improve the survival rate of startup companies. In this study, we examined the impact of start-up motivation, start-up capabilities, and start-up passion of start-up companies on start-up satisfaction, as well as the moderating effect according to the founding type of general start-up companies and startups. Entrepreneurship motivation was divided into self-actualization motivation and pro-social motivation. Entrepreneurship capabilities were divided into marketing capabilities and experience capabilities. Entrepreneurship passion was divided into harmonious passion and obsessive passion. Empirical analysis was conducted by receiving surveys from 361 managers of general and startup companies within 7 years of founding their businesses online and offline. As a result, self-actualization motivation, pro-social motivation, marketing competency, experiential competency, and harmonious passion had a significant positive (+) effect on startup satisfaction. However, obsessive passion did not have a significant effect. In addition, the magnitude of influence on startup satisfaction appeared in the following order: harmonious passion, marketing competency, self-actualization motivation, pro-social motivation, and experiential competency. The moderating effect according to the type of founding of general start-ups and startups was found in pro-social motivation, experience competency, and passion for harmony. However, there was no significant moderating effect between self-actualization motivation, marketing competency, obsessive passion, and entrepreneurship satisfaction. This study presented academic implications that harmonious passion and marketing capabilities are important factors in improving startup satisfaction. In addition, practical and policy implications were presented, including the need for programs to support the psychological stability of startup business owners, strengthening startup capabilities through experts, and strengthening startup education programs that can foster self-actualization motivation and pro-social motivation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.173-188
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• 2023

This paper analyzed the Earnings management of firms selected as preliminary Unicorn. If a manager is selected as a preliminary unicorn firm, he can receive financial support of up to 20 billion won, creating a factor in managing the manager's earnings. The motive for management's earnings management is related to the capital market. Accounting information is used by investors and financial analysts, and corporate profits affect corporate value. Therefore, if the accounting earning is adjusted upward, the corporate value will be raised and investment conditions will be favorable. In this paper, earnings quality was measured by the modified Jones model of Dechow et al.(1995) by the ROA control model of Kothari et al.(2005) among the discretionary accruals estimated using an alternative accrual prediction model. Competing similar companies in the same market as the selected companies were formed, and the discretionary accruals were mutually compared to verify the research hypotheses, and only the selected companies were analyzed for the audit year and after the audit year. As a result of the analysis, it was found that the companies selected as preliminary unicorns had higher earnings management compared to the corresponding companies in question, which had a negative impact on the quality of accounting profits. It was found that the companies selected as preliminary unicorns continued to receive incentives for management's earnings management even after being selected. These results indicate that the companies selected as prospective unicorns are recognized for their value in the market through external growth rather than internal growth, and thus, incentives for management's earnings management to attract investment from external investors under favorable conditions are continuing. In the future preliminary unicorn selection evaluation, it was possible to present what needs to be reviewed on the quality of accounting earning. The implication of this paper is that the factors of management's earnings management eventually hinder investors and creditors from judging the reliability of accounting information. It was suggested that a policy alternative for the K-Unicorn Project, which enhances reliability were presented by reflecting the evaluation of earnings quality through discretionary accruals.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.201-219
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• 2023

ESG (Environment, Social, Governance) is becoming the core of the interest of today's entrepreneurs concerning about the earth crisis. Numerous studies are going on these days about the importance of ESG, but most of them seem confined to the introductory level. This study concentrates on "ESG education" that will teach the learners how to put various ESG ideas into practice, knowing that the earth crisis would not be overcome without actual practice of those ideas. First, elementary and junior·senior high school, professors in university and educational consultants in the field designed educational programs and related content materials under "ESG entrepreneurship education" integrated with ESG and Entrepreneurship education, which have been implemented previously. Participatory learning methods are converged with the program. The researcher analyzed the learning effects in depth after implementing the programs in the education field. Thus, this study first examined the effects of key variables of ESG educational program i.e., ESG entrepreneurship education, student participatory learning, and team-based learning on creative problem-solving and social value recognition with an essential variant of ESG educational programs and identified the relations to creative problem-solving and social value recognition. Besides, this study investigated the moderating effects of school atmosphere, and teachers' enthusiasm, regarding traits of educational programs and social value recognition. Findings indicate that sub variants of the traits of educational programs i.e., ESG entrepreneurship education, student participatory learning, and team-based learning significantly affect creative problem-solving skills and social value recognition and that creative problem-solving impacts social value recognition. In addition, teachers' enthusiasm has moderating effects between traits of educational programs and social value recognition. This study provides content-program learning methods that can be practically applied in education, emphasizing practice in ESG in elementary and junior·senior high school education. Implications suggest that ESG entrepreneurship education and active participatory learning affect social value recognition and that teachers' enthusiasm plays a significant role in education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.157-175
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• 2022

At this moment, a paradigm shift is taking place across all sectors of society for the transition movements to the digital economy. Various movements are taking place in the global agricultural industry to achieve innovative growth using big data which is a key resource of the 4th industrial revolution. Although the government is making various attempts to promote the use of big data, the movement of the agricultural industry as a key player in the use of big data, is still insufficient. Therefore, in this study, effects of performance expectations, effort expectations, social impact, facilitation conditions, based on the Unified Theory of Acceptance and Use of Technology(UTAUT), and innovation tendencies on the acceptance intention of big data were analyzed using the economic and practical benefits that can be obtained from the use of big data for agricultural-related companies as moderating variables. 333 questionnaires collected from agricultural-related companies were used for empirical analysis. The analysis results using SPSS v22.0 and Process macro v3.4 were found to have a significant positive (+) effect on the intention to accept big data by effort expectations, social impact, facilitation conditions, and innovation tendencies. However, it was found that the effect of performance expectations on acceptance intention was insignificant, with social impact having the greatest influence on acceptance intention and innovation tendency the least. Moderating effects of economic benefit and practical benefit between effort expectation and acceptance intention, moderating effect of practical benefit between social impact and acceptance intention, and moderating effect of economic benefit and practical benefit between facilitation condition and acceptance intention were found to be significant. On the other hand, it was found that economic benefits and practical benefits did not moderate the magnitude of the influence of performance expectations and innovation tendency on acceptance intention. These results suggest the following implications. First, in order to promote the use of big data by companies, the government needs to establish a policy to support the use of big data tailored to companies. Significant results can only be achieved when corporate members form a correct understanding and consensus on the use of big data. Second, it is necessary to establish and implement a platform specialized for agricultural data which can support standardized linkage between diverse agricultural big data, and support for a unified path for data access. Building such a platform will be able to advance the industry by forming an independent cooperative relationship between companies. Finally, the limitations of this study and follow-up tasks are presented.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.147-163
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• 2022

The relocation policy of public Institutions throughout provincial areas that implemented for the purpose of "balanced national development" finished in 2019 with the last relocation of the Korea Institute of Science & Technology Evaluation and Planning, which moved to Chungbuk Innovation City. Electric power public corporations also completed relocation program over eight regions across the nation. This study was conducted empirically to identify the structural relationship between the public service motivation and job attitude. In this, the relationship of organizational change, particularly occurred by the regional relocation, with the psychological state of these organization members (experienced direct changes and got substantial impacts in various aspects such as psychological, economic and living environment, etc.,) was studied. This study aims to seek early organizational stabilization ideas for electric power public corporations after relocation, and to present some implications that can contribute to the secondary relocation of public institutions to local areas. This study shows the statistically significant relationship between the psychological state occurred by relocation and organizational commitment. The result shows that the higher the expectation levels, the higher the degree of organizational commitment, while anxious psychological state has no relation with that. Additionally, expectation level has no significant functional relation with turnover intention. Followings are the major conclusions revealed in this study; The stronger the anxious psychological state, the higher the turnover inducement goes up. The higher the expectation levels, the higher the public service motivation grows, and the higher the anxiety psychological state, the public service motivation lowers. The organizational commitment grows according to the public service motivation proportionally, but the turnover inducement intention is weak. The moderating effect of public service motivation between the expectation of organizational change and turnover intention was not significant, but it was analyzed that the moderating effect of public service motivation formed a significant relationship with other anxiety psychology. The expectation levels of employees of electric power public corporations has grown up after moving to provincial areas. Relationship between the expectation mind and the turnover inducement has decreased after local relocation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.63-79
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• 2024

The startup ecosystem is experiencing a paradigm shift in founding due to the acceleration of digital transformation, online platform companies have grown significantly into unicorns, but the lack of differentiated approaches and strategic support for deep tech startups has led to the inactivity of the startup ecosystem. is lacking. Therefore, in this study, we proposed ways to develop domestic startup development policies, focusing on the US system, which is an advanced example overseas. Focusing on the definition and characteristics of deep tech startups, current investment status, success stories, support policies, etc., we comprehensively analyzed domestic and international literature and derived suggestions. In particular, he proposed specific ways to improve support policies for domestic deep tech startups and presented milestones for their development. Currently, the United States is significantly strengthening the role of the government in supporting deep tech startups. The US government provides direct financial support to deep tech startups, including detergent support and infrastructure support. It has also established policies to foster deep tech startups, established related institutions, and systematized support. It is worth noting that US universities play a core role in nurturing deep tech startups. Leading universities in the United States operate deep tech startup discovery and development programs, providing research and development infrastructure and technology. It also works with companies to provide co-investment and commercialization support for deep tech startups. As a result, the growth of domestic deep tech startups requires the cooperation of diverse entities such as the government, universities, companies, and private investors. The government should strengthen policy support, and universities and businesses should work together to support R&D and commercialization capabilities. Furthermore, private investors must stimulate investment in deep tech startups. Through such efforts, deep tech startups are expected to grow and Korea's innovation ecosystem will be revitalized.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.71-103
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• 2009

Considering the expenditure size of public institutions centering on public enterprises, about 28% of Korea's GDP in 2007, public institutions have significant influence on the Korean economy. However, still in the new government, there are voices of criticism about the need of constant reform on public enterprises due to their irresponsible management impeding national competitiveness. Especially, political controversy over appointment of executives such as CEOs of public enterprises has caused the distrust of the people. As one of various reform measures for public enterprises, this study analyzes the effect of internal governance structure of public enterprises on their managerial performance, since, regardless of privatization of public enterprises, improving the governance structure of public enterprises is a matter of great importance. There are only a few prior researches focusing on the governance structure and managerial performance of public enterprises compared to those of private enterprises. Most of prior researches studied the relationship between parachuting employment of CEO and managerial performance, and concluded that parachuting produces negative effect on managerial performance. However, different from the results of such researches, recent studies suggest that there is no relationship between employment type of CEOs and managerial performance in public enterprises. This study is distinguished from prior researches in view of following. First, prior researches focused on the relationship between employment type of public enterprises' CEOs and managerial performance. However, in addition to this, this study analyzes the relationship of internal auditors and managerial performance. Second, unlike prior researches studying the relationship between employment type of public corporations' CEOs and managerial performance with an emphasis on parachuting employment, this study researches impact of employment type as well as expertise of CEOs and internal auditors on managerial performance. Third, prior researchers mainly used non-financial indicators from various samples. However, this study eliminated subjectivity of researchers by analyzing public enterprises designated by the government and their financial statements, which were externally audited and inspected. In this study, regression analysis is applied in analyzing the relationship of independence and expertise of public enterprises' CEOs and internal auditors and managerial performance in the same year. Financial information from 2003 to 2007 of 24 public enterprises, which are designated by the government, and their personnel information from the board of directors are used as samples. Independence of CEOs is identified by dividing CEOs into persons from the same public enterprise and persons from other organization, and independence of internal auditors is determined by classifying them into two groups, people from academic field, economic world, and civic groups, and people from political community, government ministries, and military. Also, expertise of CEOs and internal auditors is divided into business expertise and financial expertise. As control variables, this study applied foundation year, asset size, government subsidies as a proportion to corporate earnings, and dummy variables by year. Analysis showed that there is significantly positive relationship between independence and financial expertise of internal auditors and managerial performance. In addition, although business expertise and financial expertise of CEOs were not statistically significant, they have positive relationship with managerial performance. However, unlike a general idea, independence of CEOs is not statistically significant, but it is negatively related to managerial performance. Contrary to general concerns, it seems that the impact of independence of public enterprises' CEOs on managerial performance has slightly decreased. Instead, it explains that expertise of public enterprises' CEOs and internal auditors plays more important role in managerial performance rather than their independence. Meanwhile, there are limitations in this study as follows. First, in contrast to private enterprises, public enterprises simultaneously pursue publicness and entrepreneurship. However, this study focuses on entrepreneurship, excluding considerations on publicness of public enterprises. Second, public enterprises in this study are limited to those in the central government. Accordingly, it should be carefully considered when the result of this study is applied to public enterprises in local governments. Finally, this study excludes factors related to transparency and democracy issues which are raised in appointment process of executives of public enterprises, as it may cause the issue of subjectivity of researchers.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.