- E-ISSN2288-7709
- KCI
13권 2호
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Purpose: Entrepreneurship plays a pivotal role in ensuring the success and sustainability of small businesses, particularly in dynamic and highly competitive market environments. This study investigates the influence of entrepreneurship - specifically, innovation, risk-taking, and proactiveness - on differentiation strategies and overall business performance. The objective is to elucidate how these entrepreneurial characteristics facilitate strategic differentiation and, in turn, enhance firm outcomes. Research Design, Data, and Methodology: A quantitative research design was employed, utilizing survey data collected from small business owners operating across diverse industries. Structural equation modeling (SEM) was used to test the hypothesized relationships among entrepreneurship, differentiation strategies, and business performance. Furthermore, the direct effects of the sub-dimensions of entrepreneurship - innovativeness, risk-taking, and proactiveness - on differentiation strategies were analyzed. Results: The empirical findings reveal that entrepreneurship exerts a significant and positive influence on both differentiation strategies and small business performance. Entrepreneurs exhibiting higher levels of innovativeness, risk-taking, and proactiveness are more likely to implement unique differentiation strategies that strengthen their competitive advantage. Conclusions: This study highlights the critical role of entrepreneurship in driving the performance of small businesses. The findings offer valuable implications for entrepreneurs, policymakers, and educators by emphasizing the importance of innovation-oriented strategies and the development of supportive infrastructures. Strengthening entrepreneurial capabilities enables small firms to overcome resource limitations and navigate market uncertainty, thereby securing sustainable competitive advantage and long-term growth.
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Purpose: Urban regeneration has been supported by the Special Act on Revitalization and Support for Urban Regeneration, enacted in 2013, with projects implemented nationwide. However, education focused on simple understanding and business explanation has limited effectiveness in increasing satisfaction. As educational formats have dualized into online and offline before and after COVID-19, offline education has decreased while online education has increased, necessitating discussions on diverse educational methods. Research design, data and methodology : This study investigated the impact of intrinsic and extrinsic factors on learning satisfaction and performance among the digital native generation through descriptive statistics and correlation analysis. Pearson's correlation coefficient was used to analyze relationships between factors to determine how intrinsic and extrinsic factors influence learning satisfaction and performance. Result: This study Results showed strong positive correlations between self-efficacy and learning performance (r=0.71, p<0.01), while system quality significantly impacted satisfaction (r=0.68, p<0.01). The findings provide specific guidelines for designing effective online content-based courses that accommodate digital natives' learning preferences in community regeneration education. Conclusions: Based on these findings, the study draws implications for designing and operating online content-based convergence courses tailored to the characteristics of digital native generation learners.
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Purpose: This study attempts to provide empirical evidences on the effect of buyers' risk propensities on market outcomes under information asymmetry. We have analyzed experimental data to understand how each individual buyer's purchase decision is associated with her risk propensity in order to suggest effective target marketing strategies under information asymmetry. Research design, data and methodology: We have examined 362 subjects through an experimental method with detailed purchase scenarios to estimate buyers' purchase decisions under information asymmetry along with the measurement of each subject's risk propensity through their lottery choices focusing on the level of acceptable risk. Results: Our experimental analysis has shown that the buyers who prefer to purchase products with revealed negative aspects are actually more risk-averse, and the buyers who choose products with concealed negative aspects are more risk-taking. However, we have not found predicted purchase patterns within the buyer groups of similar risk propensities. Conclusions: This study provides meaningful empirical evidences on the theoretical literature about how risk propensities of buyers affect seller’s decision to reveal negative information. The finding from this study is thus expected to suggest how to carefully design targeted marketing communications under information asymmetry based on each individual customer’s risk propensity.
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Purpose: The intersection of information technology and elderly care services has received widespread attention in recent times. This study investigates the influence of privacy protection activities on user satisfaction. Research design, data and methodology: This study identified five independent factors within privacy protection activities: new technologies, assurance, empathy, regulations, and support activities, and developed a theoretical model to present the connections between privacy protection activities, trust, digital literacy, and user satisfaction. Results: The findings of the study show that privacy protection activities significantly impact user satisfaction in intelligent elderly care services. Trust and digital literacy play significant mediating and moderating roles in these relationships. Conclusions: This study bridges the gap between IT, healthcare and older adults by addressing the privacy dimension of intelligent elderly care to promote improved quality of life and ensure that technological solutions are effective and trusted by users with the growing need for privacy protection in intelligent elderly care services in multiple scenarios, directions, and levels.
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Purpose: This study examines the relationship between key service characteristics and customer use intention in peer-to-peer(P2P) platforms, explicitly modeling the mediating role of perceived risks. Research design, data and methodology: Five independent factors assurance, intermediation, security, trustworthiness, and technological maturity were identified as key service characteristics that influence user perceptions and intentions. Conclusions: Among the service characteristics, assurance and security influenced customer use intention through the mediation of perceived risks, while intermediation and trustworthiness had a direct impact on customer use intention. However, technological maturity did not significantly affect customer use intention and did not serve as a mediator for perceived risks. Conclusions: The results of this empirical analysis underscore the necessity of strategically prioritizing the reduction of perceived risks and the enhancement of trust, rather than relying solely on technology, within the rapidly evolving digital financial ecosystem.
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Purpose: This study aims to redefine the housing welfare beneficiaries by considering the diversity and particularity in Seoul, and to propose the improved direction of Seoul's housing welfare policy without blind spots. A survey method subject to experts was conducted. The survey questionnaire included expanded meaning of the housing-vulnerable people, the necessity levels and effective ways of each housing welfare policy, and the practical needs for a housing welfare program. Results Results from the survey for experts are as follows; first, expanded definition for the housing-vulnerable people was highly demanded. In detail, at-risk adolescents (teenage parents, young care givers, reclusive youth), marginalized persons from a welfare facility (those discharged from residential welfare facilities for the elderly, medical facilities), marriage immigrants, and foreign irregular workers should be included to the housing-vulnerable people. Second, the most necessary policy for housing welfare was the housing welfare programs followed by housing improvement, housing expense support, and public rental housing supply. Third, the most demanded need for detailed policies for each housing welfare field was the housing welfare delivery system. Then the support for housing upward mobility was next followed by expansion of housing welfare governance, housing improvement of old and defective houses, housing improvement within households, employment of housing welfare professionals, housing service programs, and demand-tailored policies for rental housing. Fourth, the suggested direction of each housing welfare policy in Seoul were that the current public rental housing policy should be maintained, financial and housing expense support should be expanded, housing improvement should be expanded or maintained, and housing welfare service programs should be expanded.
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Purpose: This study aims to predict monthly prepayment rates of Mortgage-Backed Securities (MBS) issued by the Korea Housing Finance Corporation, focusing on the effects of external shocks such as the financial crisis and COVID-19. Research design: The research compares traditional fixed-effects regression models with machine learning techniques (ElasticNet, LASSO, Ridge) to determine which model best predicts MBS prepayment rates before and after external shocks. Data and methodology: The study uses monthly data from June 2004 to December 2020, analyzing MBS prepayment rates alongside various macroeconomic variables. The performance of each model is assessed using cross-validation and blocked cross-validation methods to evaluate stability under different economic conditions. Results: Machine learning models, particularly ElasticNet, consistently outperform traditional regression models. ElasticNet showed the highest predictive accuracy, with a stable performance even after the financial crisis and COVID-19, unlike traditional models that struggled to adapt to the shocks. Conclusions: The study concludes that machine learning models, especially ElasticNet, offer superior predictive performance in forecasting MBS prepayment rates, especially in volatile market conditions, and should be considered over traditional models for financial predictions.
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Purpose: Gyeonggi-do’s Green Belt serves as a critical environmental buffer, mitigating urban sprawl and contributing to urban sustainability. However, increasing damage to these areas threatens their ecological functions and long-term viability. To address this issue, this study proposes a sustainable maintenance plan for Damaged Green Belt Areas (DGBA) by identifying key factors influencing degradation and suggesting appropriate management strategies. Research design, data and methodology: To systematically classify DGBA, ANOVA was conducted to determine significant factors related to land damage, followed by cluster analysis to categorize these areas into three groups. Results: Group 1, characterized by low damage levels and a low building ratio, is suitable for Green Belt restoration and green space preservation. Group 2, with moderate damage and a high proportion of residential buildings, is appropriate for urban park development and small-scale housing renewal projects. Group 3, which exhibits high levels of damage and a high concentration of production and commercial facilities, is best suited for redevelopment into logistics centers and small industrial complexes. Conclusions: To ensure the sustainable management of these areas, this study suggests three key policy recommendations. First, stronger government regulations should be enforced to prevent further damage to Green Belt areas. Second, eco-friendly restoration strategies should be prioritized to rehabilitate degraded land while maintaining ecological balance. Third, a differentiated and targeted approach should be adopted by subdividing DGBA and implementing customized maintenance plans based on each area’s characteristics
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Purpose: This study aims to examine the impact of social capital cultivated through entrepreneurial education on university students' entrepreneurial activities. It explores how social capital influences perceived feasibility and desirability of entrepreneurship and their effects on entrepreneurial intention. By focusing on nascent entrepreneurs and general university students, this study seeks to provide new insights into the role of social capital in entrepreneurship. Research design, data and methodology: This study conducts an empirical analysis involving university students who have participated in entrepreneurial education programs. A partial least square modeling approach is used to examine the relationships between social capital, perceived feasibility, perceived desirability, and entrepreneurial intention. Survey data collected from students are analyzed to test the proposed hypotheses. Results: The results indicate that social capital positively influences both perceived feasibility and desirability of entrepreneurship. These factors, in turn, significantly enhance entrepreneurial intention among university students. The findings highlight the crucial role of social capital in shaping entrepreneurial mindsets and motivation. Conclusions: This study underscores the importance of social capital in fostering entrepreneurial intention among university students. By enhancing perceived feasibility and desirability, social capital plays a vital role in shaping entrepreneurial motivation. These findings offer theoretical and practical implications for improving entrepreneurial education and support programs.
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Central Luzon, Philippines, boasts a wealth of cultural experiences and natural attractions, yet its tourism industry faces several significant challenges. Issues such as inadequate infrastructure, environmental degradation, and socio-political instability hinder the region's ability to sustain tourism demand. Poor transportation, environmental damage, and safety concerns further exacerbate these challenges. Additionally, political factors can skew resource allocation, favoring more developed areas over marginalized communities. Emerging trends like digitalization and shifting consumer preferences necessitate innovative marketing strategies. To revitalize and sustain the region's tourism industry, it is crucial to address these challenges and understand the impact of socio-economic demographics and PESTLE (Political, Economic, Social, Technological, Legal, and Environmental) factors
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Purpose: This study examines the effects of government subsidies on small and medium-sized enterprises (SMEs), focusing on their economic, technological, and social impacts. By assessing pre- and post-subsidy performance, we aim to determine whether government R&D funding effectively enhances firm growth and innovation. Research design, data, and methodology: Using a panel dataset of 552 SMEs that participated in the 2019 Start-up Growth Technology Development Program, we employ a two-way fixed effects model to evaluate the impact of government R&D subsidies. Our empirical approach controls for firm-specific heterogeneity and time effects, and we further analyze time-lagged effects to capture the long-term influence of subsidies. Results: The analysis demonstrates that government R&D subsidies exert a statistically significant positive impact on patent applications, whereas no significant effects were observed on sales, exports, internal R&D investment, or employment. The time-lagged analysis revealed that sales, exports, and internal R&D exhibited the largest positive coefficients in the year immediately following subsidy disbursement, though these effects lacked statistical significance. These findings suggest that while government R&D subsidies effectively enhance firms' innovation capabilities, the translation of these innovations into financial performance requires additional time and complementary processes, highlighting the temporal complexity of innovation-driven growth dynamics. Conclusions: While government subsidies may not yield immediate returns, their long-term effects on exports suggest their role in fostering firm competitiveness and technological advancement. Given that SMEs and startups are the backbone of South Korea’s economy, continuous support is essential to promote innovation and sustainable growth.
