• Journal of Venture Innovation
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• v.4 no.3
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• pp.17-30
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• 2021

Environmental deterministic perspectives and resource-based perspectives have different perceptions on the factors that determine corporate performance. While the environmental deterministic viewpoint sees the external environment as having a significant impact on corporate performance. On the other hand, the resource-compliant viewpoint believes that it is important to obtain the necessary resources through appropriate decision-making in order to overcome the uncertainty of the environment. Although the external environmental impact on corporate performance is important, the study is in the position that efforts within the company to cope with environmental uncertainty are necessary. This study identified the role that factors within the company play in the process of affecting the external environment of the company's performance. This study looked at whether the CEO's innovation direction plays an mediating role in the market environment favorability affecting sales growth rate. The data was collected using a survey method. We collected data from 138 small and medium-sized manufacturing companies in Gyeongin area. The collected data was analyzed using SPSS 22 packages. According to the analysis, market environment favorability positively affects sales growth rate, and the CEO's innovation direction plays a mediating role between market environment favorability and sales growth rate. The results of this study showed that depending on the market environment, the CEO's interest and willingness to innovate, present a vision for innovation, and institutionalize innovation activities increase management performance through innovation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.39-50
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• 2022

Based on the signaling theory, this study examined whether startups are more likely to attract venture investment when receiving government R&D subsidies. First, we reviewed previous studies of the investment decision-making process of venture capitalists and understood the conditions that influence investment decisions. Based on previous studies on the signal effect of government subsidies, particularly government R&D grants, on inducing private fund investment, this study revealed a mechanism to induce venture investment by startups. In addition, in order to verify whether government R&D subsidies have the effect of inducing venture investment, an empirical analysis was conducted based on data from startups under seven years and certified as a venture companies in 2021. This paper used PSM(Propensity Score Matching) method and DID(Difference In Difference) analysis for an empirical study to analyze the average treatment effect on the treated group(beneficiary startups of government R&D grants). As a result of empirical analysis, companies that receive more government R&D subsidies after starting a business are more likely to attract venture investment. From two to three years after conducting the first government R&D project, startups that received government R&D grants attracted more venture investment than those that did not. The results of this paper demonstrate that government R&D projects can also affect the venture investment ecosystem, giving policy implications to government R&D projects targeting startups. It is also expected to suggest strategic implications to startups that need new funding.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.159-174
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• 2023

In this paper, we proposed a methodology to effectively determine the selection and prioritization of new business and innovation projects using AI technology. AI technology is a technology that can upgrade the business of companies in various industries and increase the added value of the entire industry. However, there are various constraints and difficulties in the decision-making process of selecting and implementing AI projects in the enterprise. In this paper, we propose a new methodology for prioritizing AI projects using Morphology, AHP, and TOPSIS. The proposed methodology helps prioritize AI projects by simultaneously considering the technical feasibility of AI technology and real-world user requirements. In this study, we applied the proposal methodology to a real enterprise that wanted to prioritize multiple AI projects in the HR field and evaluated the results. The results confirm the practical applicability of the methodology and suggest ways to use it to help companies make decisions about AI projects. The significance of the methodology proposed in this study is that it is a framework for prioritizing multiple AI projects considered by a company in the most reasonable way by considering both business and technical factors at the same time.

• Industry Promotion Research
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• v.9 no.1
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• pp.89-101
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• 2024

The purpose of this study is to examine the relationship between parental/parental attachment and career indecision among college students, and to examine the goodness of fit and influence of variables in a model that assumes that socially imposed perfectionism has an influence on the relationship between parental/parental attachment and career indecision. It's about verification. For this purpose, an online survey was conducted by randomly sampling 250 college students attending 4-year institutions across the country, and data analysis was conducted using a three-stage regression method using SPSS Win 25.0. The analysis results are as follows. First, psychological attachment to parents appears to have a negative effect on career indecision, confirming that the more a stable attachment relationship with parents is formed, the less difficulties in career decision-making. Second, the mediating effect of socially imposed perfectionism was confirmed in the relationship between psychological attachment to parents and career indecision. This shows that the more stable the psychological attachment to the father and mother is formed, the lower the level of socially imposed perfectionism and career indecision. Based on these research results, implications for career counseling practice and follow-up research were discussed.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.75-84
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• 2023

Many developing countries face challenges in estimating long-term discharge due to the lack of hydrological data for water supply planning, making it difficult to establish a rational water supply plan for decision-making on water distribution. The study area, the Bandung region in Indonesia, is experiencing rapid urbanization and population concentration, leading to a severe shortage of freshwater. The absence of water reservoir prediction methods has resulted in a water supply rate of approximately 20%. In this study, we aimed to propose an approach for predicting water reservoirs in developing countries by analyzing water safety and potential water supply using the MODSIM (Modified SIMYLD) network model. To assess the suitability of the MODSIM model, we applied the unit hydrograph method to calculate long-term discharge based on 19 years of discharge data (2002-2020) from the Pataruman observation station. The analysis confirmed alignment with the existing monthly optimal operation curve. The analysis of power plant capacity revealed a difference of approximately 0.30% to 0.50%, and the water intake safety at the Pataruman point showed 1.64% for Q95% flow and 0.47% for Q355 flow higher. Operational efficiency, compared to the existing reservoir optimal operation curve, was measured at around 1%, confirming the potential of using the MODSIM network model for water supply evaluation and the need for water supply facilities.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.243-256
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• 2024

Objective: We aimed to investigate whether 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[¹⁸F]FDG PET/CT) can aid in evaluating the risk of malignancy in ampullary tumors detected by endoscopy. Materials and Methods: This single-center retrospective cohort study analyzed 155 patients (79 male, 76 female; mean age, 65.7 ± 12.7 years) receiving 2-[¹⁸F]FDG PET/CT for endoscopy-detected ampullary tumors 5-87 days (median, 7 days) after the diagnostic endoscopy between June 2007 and December 2020. The final diagnosis was made based on histopathological findings. The PET imaging parameters were compared with clinical data and endoscopic features. A model to predict the risk of malignancy, based on PET, endoscopy, and clinical findings, was generated and validated using multivariable logistic regression analysis and an additional bootstrapping method. The final model was compared with standard endoscopy for the diagnosis of ampullary cancer using the DeLong test. Results: The mean tumor size was 17.1 ± 7.7 mm. Sixty-four (41.3%) tumors were benign, and 91 (58.7%) were malignant. Univariable analysis found that ampullary neoplasms with a blood-pool corrected peak standardized uptake value in earlyphase scan (SUVe) ≥ 1.7 were more likely to be malignant (odds ratio [OR], 16.06; 95% confidence interval [CI], 7.13-36.18; P < 0.001). Multivariable analysis identified the presence of jaundice (adjusted OR [aOR], 4.89; 95% CI, 1.80-13.33; P = 0.002), malignant traits in endoscopy (aOR, 6.80; 95% CI, 2.41-19.20; P < 0.001), SUVe ≥ 1.7 in PET (aOR, 5.43; 95% CI, 2.00-14.72; P < 0.001), and PET-detected nodal disease (aOR, 5.03; 95% CI, 1.16-21.86; P = 0.041) as independent predictors of malignancy. The model combining these four factors predicted ampullary cancers better than endoscopic diagnosis alone (area under the curve [AUC] and 95% CI: 0.925 [0.874-0.956] vs. 0.815 [0.732-0.873], P < 0.001). The model demonstrated an AUC of 0.921 (95% CI, 0.816-0.967) in candidates for endoscopic papillectomy. Conclusion: Adding 2-[¹⁸F]FDG PET/CT to endoscopy can improve the diagnosis of ampullary cancer and may help refine therapeutic decision-making, particularly when contemplating endoscopic papillectomy.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.37-63
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• 2023

In medical litigation, there are various cases where a doctor's 'explanation' of a patient becomes problematic. Medical explanations and guidance are required from the doctor, starting from the beginning of diagnosis, through treatment processes such as surgery, when hospitalization is necessary for treatment, during hospitalization, upon discharge, and after discharge. Furthermore, notification from the doctor or medical institution may be requested regarding the economic costs that will be incurred due to medical treatment. South Korea's judiciary has been developing legal principles regarding such doctor's explanations by distinguishing between explanations for obtaining consent for medical treatment and medical explanations related to guidance on patient treatment methods, taking into account related laws such as the stage of treatment and the Medical Service Act. Additionally, the Constitutional Court recently ruled on the non-benefit cost notification system linked to the explanation of economic costs. However, holding a doctor accountable solely because the doctor's explanation was insufficient has aspects that do not correspond to the actual situation in clinical reality, and may have a reflexive disadvantage that results in a decline in legal rights. Therefore, the doctor's explanation needs to be examined from both perspectives: guaranteeing the patient's right to self-determination and protecting his or her right to decision.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.71-81
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• 2024

In response to the COVID-19 pandemic, the global airport industry is actively introducing 4th Industrial Revolution technology-based systems for quarantine and passenger safety, and test bed construction and prior verification using airport infrastructure and resources are actively being conducted. Analysis of recent cases shows that despite the changing travel patterns of airport users and the diversification of airport service demands, most testbeds construction studies are still focused on suppliers, and task prioritization is also determined by decision makers. There is a tendency to rely on subjective judgment. In order to find practical ways to become a first mover that leads innovation in the aviation industry, this study selected tasks and derived priorities to build testbeds from a service perspective that reflects various customer service needs and changes. Research results using the AHP analysis method resulted in priorities in the order of access transportation and parking services (29.2%), security screening services (23.4%), and departure services (21.8%), and these analysis results were tested in the airport industry. It shows that innovation in testbeds construction is an important factor. In particular, the establishment of smart parking and UAM transportation testbeds not only helps strengthen airports as centers of technological innovation, but also promotes cooperation with companies, research institutes, and governments, and provides an environment for testing and developing new technologies and services. It can be a foundation for what can be done. The results and implications produced through this study can serve as useful guidelines for domestic and foreign airport practitioners to build testbeds and establish strategies.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.484-499
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• 2024

Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.