• Knowledge Management Research
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• v.22 no.2
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• pp.33-53
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• 2021

Use of mobile apps being extended, privacy concern on the side of the users is increased while they are willing to provide the private information to use the apps. In this study, we tried to identify the motivating elements that influence the users' intention to use the apps, based on the tendency towards regulatory focus and the privacy calculus theory. To verify the study model, we collected data from 151 adults who use health apps throughout the country, and analyzed the data using the PLS-SEM method. According to the result of the study, it was turned out that tendency towards promotion focus had negative impact on privacy concern and privacy danger, and tendency towards prevention focus had positive impact on privacy concern. Privacy concern had negative impact on the intention to use the mobile apps, and privacy benefit and privacy knowledge had positive impact on the intention to use the mobile apps. Finally, the intention to use the mobile apps had positive impact on the intention to continue to use the mobile apps. In this study, we identified different impacts of two types of tendency towards regulatory focus on privacy concern, and identified different influences on the intention to use the mobile apps accordingly.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.1-12
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• 2021

In this paper, we study empirically examined the adventurous investments in corporate venture capital (CVC) firms' investment in the U.S. based corporate venture capital industry. Unlike existing studies focusing CVC firm's characteristics related to parent corporates and regarding CVC firm as a vehicle of corporate venturing, we identified CVC firm as an independent learning agent to adapt to dynamic environment and investigate their exploration and exploitation in investments based on organizational learning theory. Specifically, we investigate the market-environmental factors affecting CVC's adventurous investment in different sector rather than previously done. First, we examined competition intensity in CVC industry might be related to CVC firm's explorative investments. Second, CVC firm's investment experiences might affect as an inertia to invest on unexperienced sector. Finally, we investigated risk preference effect on CVC firm's venturing investments. The empirical data analyzed in the study contained a total of 85 U.S. based CVC firms and their 2,306 investments from 1996 until 2017. After conducting a GEE regression analysis and a Logit regression analysis, we found the significance and direction of our independent and moderating variables strongly supported all of our four hypotheses in a highly robust manner.

• Korean small business review
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• v.43 no.3
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• pp.91-117
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• 2021

The purpose of this study is to study the effect of internatioanl entrepreneurial orientation of small and medium-sized Chinese manufacturing companies on export performance. A total of 183 corporate data were used for empirical analysis for Chinese manufacturing export companies. In summary, first, international entrepreneurial orientation was shown to have a significant positive effect on export performance, second, international etrprenurial orientation was shown to have a significant positive effect on absorption capacity, and third, the stronger environmental dynamics and network capacity, the stronger international business orientation and export ability. The implications of this study are summarized as follows. It suggests that the more innovative, enterprising and risk-taking Chinese SMEs are, the better their export performance and the better their ability to absorb foreign knowledge. It also suggests that small business managers must continue to strengthen their network capabilities to improve export performance through international entrepreneurial orientation, and this relationship is further strengthened in a dynamic environment. It also suggests that the impact of firm's absorption capacity on export performance will weaken over time.

• Korean small business review
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• v.43 no.1
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• pp.1-33
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• 2021

This study explores differential value implications of R&D expenditure across firms, especially in terms of growth potential of small businesses. Analyzing Korean listed firms for the period from 1982 to 2014, we document the followings. First, large firms, defined as the top quintile group based on market capitalization, have spent higher R&D expenditure compared to small (bottom quintile group) and medium (middle quintile groups) firms and the difference between groups has enlarged over time. Relatedly, the persistence of R&D spending, measured by the association between current R&D expenditure and cumulative future R&D expenditure over the next five years, is lowest in small firms. Second, R&D of large (small) firms are more (less) likely to generate operating profits over the next five years. Additional analyses suggest that the relation between R&D and gross margin is strongest in large firms, suggesting that R&D underlies their competitiveness in the product market. Third, small firms have borne the highest uncertainty related to R&D investment proxied by the association between current R&D and volatility of future earnings. As a result, the likelihood of R&D leading to future patents is also lowest in small firms. Fourth, the probability of moving up to the next size group within the next five years is significantly lower in small firms than others. Finally, we find that the divergence in R&D expenditure between large and small firms is positively associated with product market concentration. Overall, our findings confirm the small business growth trap in relation to R&D investment.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.1-23
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• 2011

The Freedom of Information System has been introduced into the society based on the Fair Trade Transactions Act, which was established by Fair Trade Commission (FTC) on May, 2002. However, the system itself has showed limitations in guaranteeing a reliability and transparency of the disclosure document. Thus, since February, 2008, FTC not only made franchisors to register disclosure documents but also adopted the Disclosure Document Registration System, which forced them to provide registered disclosure documents to franchise applicants and franchisee. Franchisors consider the newly adopted Disclosure Document Registration System a restrictive system. However, considering the recent trend of fast growing franchising industry and the importance of being competitive, franchisors need to utilize the disclosure documents to promote their business and to gain trusts from franchise applicants by providing truthful information. In that way, franchisors will be able to establish a foundation that franchising industry might be successful and reduce the agency fee by cutting out conflicts with franchisees. Thus, this study aims to study the ways of effective preparation of disclosure document and its utilization from a franchisor viewpoint.

• Convergence Security Journal
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• v.23 no.2
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• pp.27-36
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• 2023

In recent years, ransomware attacks have become more organized and specialized, with the sophistication of attacks targeting specific individuals or organizations using tactics such as social engineering, spear phishing, and even machine learning, some operating as business models. In order to effectively respond to this, various researches and solutions are being developed and operated to detect and prevent attacks before they cause serious damage. In particular, honeypots can be used to minimize the risk of attack on IT systems and networks, as well as act as an early warning and advanced security monitoring tool, but in cases where ransomware does not have priority access to the decoy file, or bypasses it completely. has a disadvantage that effective ransomware response is limited. In this paper, this honeypot is optimized for the user environment to create a reliable real-time dynamic honeypot file, minimizing the possibility of an attacker bypassing the honeypot, and increasing the detection rate by preventing the attacker from recognizing that it is a honeypot file. To this end, four models, including a basic data collection model for dynamic honeypot generation, were designed (basic data collection model / user-defined model / sample statistical model / experience accumulation model), and their validity was verified.

• Asia Marketing Journal
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• v.13 no.1
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• pp.27-50
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• 2011

In today's market scenario, consumers are bombarded with similar promotional messages. It means that managers have to pay attention to promotion strategy to create strong effect as well as to break through the monotony. In this context, although there are strong needs concerning tie-in promotion, research investigating tie-in promotion is limited. Therefore, we extracted tie-in promotion tools and defined the concept of each tie-in promotion tool by analyzing various tie-in promotion cases which are executed in current market. In addition, consumer's recognition of tie-in promotion was investigated through the in-depth interview. The results of case analysis of tie-in promotion and in-depth interview are summarized as follows. First, 9 tie-in promotion tools were extracted: tie-in price reductions, tie-in coupons, tie-in membership, tie-in contests, tie-in premiums (tangibility, intangibility), tie-in payment terms, tie-in sample, tie-in event(culture event, charity event, experience event) and tie-in fund·rebate. Second, 3 categories of the recognition of the consumer for tie-in promotion were extracted: features of preferred tie-in promotion, expectation benefit of tie-in promotion, and risk factors of tie-in promotion. Especially, at the aspect of features of preferred tie-in promotion, fit between consumer pursuit benefit and tie-in promotion was found to be interesting. Moreover, the recognition of the consumer for tie-in promotion were divided with positive(preferred tie-in promotion features, expectation benefit of tie-in promotion) and negative(risk factors of tie-in promotion) factors. In conclusion, the company's effort will be necessary to lower the perceived risk level occurring from the process of accomplishing the tie-in promotion strategy since consumers recognize both positive and negative effects of tie-in promotion.

• Information Systems Review
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• v.25 no.4
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• pp.233-248
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• 2023

The increasing integration of intelligent information technologies within organizational systems has amplified the risk to personal information security. This escalation, in turn, has fueled growing apprehension about an organization's capabilities in safeguarding user data. While Internet users adopt a multifaceted approach in assessing a company's information security, existing research on the multiple dimensions of information security is decidedly sparse. Moreover, there is a conspicuous gap in investigations exploring whether users' evaluations of organizational information security differ across industry types. With an aim to bridge these gaps, our study strives to identify which information security attributes users perceive as most critical and to delve deeper into potential variations in these attributes across different industry sectors. To this end, we conducted a structured survey involving 498 users and utilized the analytic hierarchy process (AHP) to determine the relative significance of various information security attributes. Our results indicate that users place the greatest importance on the technological dimension of information security, followed closely by transparency. In the technological arena, banks and domestic portal providers earned high ratings, while for transparency, banks and governmental agencies stood out. Contrarily, social media providers received the lowest evaluations in both domains. By introducing a multidimensional model of information security attributes and highlighting the relative importance of each in the realm of information security research, this study provides a significant theoretical contribution. Moreover, the practical implications are noteworthy: our findings serve as a foundational resource for Internet service companies to discern the security attributes that demand their attention, thereby facilitating an enhancement of their information security measures.

• Information Systems Review
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• v.25 no.4
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• pp.265-290
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• 2023

Even though crowdfunding has become popular as a novel means of raising capital for early-stage ventures and startups through an Internet-based platform, it is unclear how a funder's characteristics, such as motivation and ability, influence their information processing and pledging decision. This study aims to propose and test a research model for determining the relationships between a funder's personal attributes, information processing style, and funding intention. To test the research model, we collected data from 139 Amazon Mechanical Turk participants through an online questionnaire survey. The findings indicate that a funder's self-efficacy has a positive effect on heuristic processing but has no significant effect on systematic processing. By contrast, a funder's personal relevance positively influences both systematic and heuristic processing. Furthermore, heuristic processing, as well as perceived value and perceived risk, influence pledging intentions positively. Our findings potentially contribute to improving the design of crowdfunding platforms to better support a funder's information needs. Based on our findings, we discuss the implications of our study as well as the directions for future research.