• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.107-120
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• 2022

The purpose of this study is to analyze the net effect and the combined effect of the determinants of the likelihood of start-up success of researchers at public research institutes. Based on the existing literature, the determinants of the researcher's likelihood of start-up success were reviewed, and a conceptual relationship between the determinants of the likelihood of start-up success was established. Data collection was conducted through a survey targeting researchers at public research institutes, and a total of 114 data were collected. The partial least squares (PLS) analysis method was used to analyze the net effect of the likelihood of start-up success determinant, and the fuzzy-set qualitative comparative analysis (fsQCA) was used to analyze the combined effect of the likelihood of start-up success determinant. In the PLS analysis results, it was found that technology commercialization probability and creative self-efficacy had a significant positive effect independently on the likelihood of start-up success. In the fsQCA results, we found a combined effect of increasing the likelihood of start-up success when the technology commercialization probability, technology commercialization capability, and creative self-efficacy were high. These research results provide academic implications for understanding the determinants of the likelihood of start-up success of researchers in public research institutes.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.31-47
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• 2022

The TIPS, a representative public-private cooperative project to revitalize the start-up ecosystem, is a government supported policy that promotes successful commercialization through various start-up support for technology-based startups. The purpose of this study is to analyze the investment decision factors of the TIPS program and to derive priorities. In order to achieve the research purpose, first, the investment decision factors were derived through literature analysis, a Delphi surveys were conducted on investors and experts participating in the evaluation of the TIPS program, and an AHP analysis was conducted on 20 VCs to empirically analyze the priority of factors on investment decisions. As a result of the analysis, the importance of critical factors was confirmed in the order of entrepreneurs(team) > market > product/service > finance > network. The importance of detailed factors was found in the order of entrepreneur's reliability and authenticity > market growth and scalability > team members' expertise and capabilities > adequacy of current market size > new market creation. This study presented the capabilities of technology-based startups preparing to participate in the TIPS program by deriving factors that influence investment decisions from an investor's perspective and comparing and analyzing the importance. It is also meaningful that basic data on determinants of private-led investment decision-making were presented to stake-holders such as venture capital, accelerator, and start-up support institutions.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.437-447
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• 2023

By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.

• Information Systems Review
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• v.22 no.4
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• pp.75-92
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• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• Information Systems Review
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• v.22 no.4
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• pp.185-203
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• 2020

With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.

• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• Convergence Security Journal
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• v.24 no.1
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• pp.51-57
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• 2024

Although industrial control systems (ICSs) recently keep evolving with the introduction of Industrial IoT converging information technology (IT) and operational technology (OT), it also leads to a variety of threats and vulnerabilities, which was not experienced in the past ICS with no connection to the external network. Since various control command messages are sent to field devices of the ICS for the purpose of monitoring and controlling the operational processes, it is required to guarantee the message integrity as well as control center authentication. In case of the conventional message integrity codes and signature schemes based on symmetric keys and public keys, respectively, they are not suitable considering the asymmetry between the control center and field devices. Especially, compromised node attacks can be mounted against the symmetric-key-based schemes. In this paper, we propose message authentication scheme based on double hash chains constructed from cryptographic hash function without introducing other primitives, and then propose extension scheme using Merkle tree for multiple uses of the double hash chains. It is shown that the proposed scheme is much more efficient in computational complexity than other conventional schemes.

• Journal of Korean Neurosurgical Society
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• v.67 no.1
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• pp.94-102
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• 2024

Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.

• Animal Bioscience
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• v.37 no.1
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• pp.28-38
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• 2024

Objective: Tibetan chickens, which have unique adaptations to extreme high-altitude environments, exhibit phenotypic and physiological characteristics that are distinct from those of lowland chickens. However, the mechanisms underlying hypoxic adaptation in the liver of chickens remain unknown. Methods: RNA-sequencing (RNA-Seq) technology was used to assess the differentially expressed genes (DEGs) involved in hypoxia adaptation in highland chickens (native Tibetan chicken [HT]) and lowland chickens (Langshan chicken [LS], Beijing You chicken [BJ], Qingyuan Partridge chicken [QY], and Chahua chicken [CH]). Results: A total of 352 co-DEGs were specifically screened between HT and four native lowland chicken breeds. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses indicated that these co-DEGs were widely involved in lipid metabolism processes, such as the peroxisome proliferator-activated receptors (PPAR) signaling pathway, fatty acid degradation, fatty acid metabolism and fatty acid biosynthesis. To further determine the relationship from the 352 co-DEGs, protein-protein interaction network was carried out and identified eight genes (ACSL1, CPT1A, ACOX1, PPARC1A, SCD, ACSBG2, ACACA, and FASN) as the potential regulating genes that are responsible for the altitude difference between the HT and other four lowland chicken breeds. Conclusion: This study provides novel insights into the molecular mechanisms regulating hypoxia adaptation via lipid metabolism in Tibetan chickens and other highland animals.