• Journal of the Korean Society of Marine Environment & Safety
• /
• v.23 no.6
• /
• pp.719-730
• /
• 2017

Recently, oceanic research has been carried out investigating global scientific interests and the territorial management of national marine jurisdictional waters, including exclusive economic zones (EEZ) and the open seas. To meet the needs of ocean researchers pursuing these - objectives, acquiring advanced research infrastructure, including research vessels, large facilities, and equipment, is a top priority in ocean science. However, ocean science is a similar to space science, and securing resources and state-of-the-art technology can be expensive. Faced with these challenges, our study focused on establishing a strategy for the efficient operation and management of research vessels, attempting to establish benchmarks from foreign examples that can be adapted to suit the target context. The results of this study provide ways to identify operating systems that could increase the efficiency of joint-use research vessels. The different systems examined in this study included a joint-use committee-based management system (JCMS, Type 1), private enterprise entrusted operating system (PEOS, Type 2), institutional investment operating system (IIOS, Type 3), and commissioned executive operating system (CEOS, Type 4). The efficiencies of JCMS, PEOS, IIOS and CEOS were 9.17, 5.82, 11.2 and -1.72 %, respectively. Given the total costs involved, the most affordable operating system was IIOS. JCMS was the most cost-effective system based on a quantitative cost-benefit analysis, but IIOS also had an acceptable cost-benefit balance. An operational committee would be required and regulations and guidelines shoulde be established to employ, JCMS, while a strategy to yield independent revenue would be needed to utilize an IIOS system.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
• /
• v.27 no.2
• /
• pp.63-70
• /
• 2021

As the government strengthens its policy of separating and discharging packaging materials, consumers are increasingly dissatisfied. In order to increase consumer participation in separate discharge policy of packaging materials, it is necessary to increase the willingness to participate by reducing potential consumer problems such as removal of packaging labels. This study conducted a survey of 300 consumers aged 14 and over who recycle and discharge directly from their homes. Ninety-nine percent of consumers said PET bottles are released separately. However, only 65% of consumers removed labels (attachment labels, shrink labels) and other materials (caps, vinyl coatings, tapes, handles, bases, etc.) during separate discharge process. Nearly 52% of consumers cited 'difficulty of separation' as the main reason for not removing labels and other materials. One-way ANOVA analysis showed that 'strong adhesion', 'removal initiation problem' and 'material strength' had high mean regardless of age, which are major factors impedes label removal. Using shrink labels with perforated lines rather than adhesive labels would be more beneficial to encouraging participation in separate discharge. However, if the shrink labels do not have perforated lines or are difficult to remove, adhesive labels are often easier to remove than shrink labels because of the strong cohesiveness of shrink labels. As a result, how easy it is for consumers to remove the label is more important than technological differences. In order to increase consumer participation in packaging material and label separations, improvements in structural design are needed along with the selection of materials that are easy to separate. This study is meaningful in examining consumer perceptions, deriving problems and suggesting directions for policy improvement.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.5
• /
• pp.75-89
• /
• 2021

Currently, small business owners are facing a situation where it is difficult to run their business in the existing way due to the spread of digital technology and the prolonged COVID-19. As a necessary competency for them, this study focused on digital literacy and examined the relationship between digital literacy and individual and market characteristics, business performance of small business owners. The specific research purpose is to examine the effect of entrepreneurial characteristics, which are individual factors, and market characteristics, which are environmental factors, on business performance and the mediating effect of digital literacy. In previous studies, various factors explaining the business performance of small business owners were reviewed, and innovation and self-determination, which are entrepreneurial characteristics of small business owners, and market competition and growth were derived as independent variables, and financial and non-financial performance were set as dependent variables. The hypothesis was established as digital literacy was expected to play a role in mediating the relationship between independent and dependent variables. For empirical research, a survey was conducted on small business owners across the country, and the analysis results are summarized as follows. It was found that the innovation and self-determination of small business owners had a positive (+) significant effect on financial and non-financial performance. In addition, it was confirmed that the degree of competition in the market had no significant effect on financial and non-financial performance, and that the growth of the market had a significant positive (+) effect on financial and non-financial performance. In the case of the mediating effect of digital literacy, it was confirmed that innovation had a partial mediating effect on non-financial performance, and digital literacy had a complete mediating effect on the effect of market competition on financial and non-financial performance. Finally, it was confirmed that digital literacy has a partial mediating effect on the effect of market growth on non-financial performance. Looking at the results, it can be seen that the entrepreneurial characteristics of small business owners, which correspond to innovation and self-determination, directly act as a factor to increase business performance, and market characteristics indirectly increase digital literacy to achieve results. Based on the above research results, the implications and limitations of the study and future research directions were presented together.

• Korean Journal of Construction Engineering and Management
• /
• v.20 no.4
• /
• pp.114-125
• /
• 2019

Off-Site Construction (OSC) is a new construction method based on factory production. OSC (Off-Site Construction) is a new construction method based on factory production. Researches such as OSC-related design and production standardization, transport methods are actively conducted in the U.S., UK and other parts of the world as this new method has an edge over existing methods in terms of productivity, economy and quality. As the emergence of this new area requires reasonable management, an analysis of the scope of construction project management is required accordingly. Therefore, this research analyzed the study trends and relationships at the CM/PM range's "Operation level" to identify areas of study, relationship between studies and deficiencies in current research. This study carried out a comprehensive literature review of the OSC (CM/PM) research by analyzing 94 papers in Operation level as of September 3, 2018, and the analysis results are as follows. (1) Working stage level researches have been increasing rapidly since 2006. (2) Non-volumetric type is contributing most significantly at work stage level. In the building sector, it has been identified that problems such as residential: living, quality issues, non-residential: economic difficulties, factory: productivity problems have been addressed. (4) The Non-volumetric pre-assembly type dealt with the economic feasibility of residential and non-residential buildings, whereas the modular type was studied in regards to assembly quality. (5) From 2006, project management areas (e.g., quality, human resources, risks) have been expanded. It is expected that this research will help find new areas of research for OSC. If the analysis is carried out to the level of the industrial, corporate and project phases in the future, it is deemed that the overall research flow and area of the OSC industry can be identified.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.4
• /
• pp.199-209
• /
• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.4
• /
• pp.63-73
• /
• 2019

Recently, as young and senior entrepreneurs are getting interested in starting a business, the domestic startup rate is gradually increasing. However, the survival rate of start-ups is so low. In this regard, this study empirically examines how the entrepreneurial intention affects both financial and non-financial start-up performances through the intermediation effects of experiential competence, financing competency, marketing competence and differentiated competitive advantage. In doing so, the purpose of this study is to find out the key elements to successful start-ups. To this end, the survey results of 200 start-ups in Pohang from January 21 to February 1, 2019 were used to test the research hypotheses. The results of the study are summarized as follows. First, it is shown that the entrepreneurial intention have a positive effect on the experiential competence, financing competence and marketing competence. Second, it is found that both experiential competence and marketing competence have significant positive effects on the differentiated competitive advantage. On the other hand, the financing competence has not been shown to have a significant effect on the differentiated competitive advantage, which might result from the characteristic of the data that most of the respondents are from new businesses. Third, it is shown that the differentiated competitive advantage has a positive effect on both financial and non-financial performances. In conclusion, the results of this study suggest a theoretical basis for the successful start-up performance. Namely, it is necessary for the founders of start-ups to secure differentiated competitive advantage through the entrepreneurial intention and the entrepreneurial competences such as financing competence and marketing competence because the differentiated competitive advantage leads to the successful financial and non-financial start-up performances. In addition, the results of this study suggest to both entrepreneurs and managers that for the successful business performance, it is important for them to make continuous efforts to come up with new ideas and to reinforce financing and marketing activities in order to achieve the differentiated competitive advantage.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.179-200
• /
• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• KIPS Transactions on Computer and Communication Systems
• /
• v.10 no.10
• /
• pp.261-268
• /
• 2021

Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.

• Journal of Intelligence and Information Systems
• /
• v.28 no.2
• /
• pp.237-262
• /
• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of Korea Port Economic Association
• /
• v.37 no.4
• /
• pp.127-144
• /
• 2021

The purpose of this study is to derive service factors based on the "Rail Statistical Yearbook" data of railroad service providers from 1990 to 2019, and to analyze the effect of the service factors on the operating profit ratio(OPR), a representative management performance variable of railroad transport service providers. In particular, it has academic significance in terms of empirical research to evaluate whether the management innovation of the KoRail has changed in line with the purpose of establishing the corporation by dividing the research period into the first period (1990-2003) and the latter (2004-2019). The contents of this study investigated previous studies on the quality of railway passenger transportation service and analyzed the contents of government presentation data related to the management performance evaluation of the KoRail. As an empirical analysis model, a research model was constructed using OPR as a dependent variable and service factor variables of infrastructure, economy, safety, connectivity, and business diversity as explanatory variables based on the operation and management activity information during the analysis period 30 years. On the results of research analysis, OPR is that the infrastructure factor is improved by structural reform or efficiency improvement. And economic factors are the fact that operating profit ratio improves by reducing costs. The safety factor did not reveal the significant explanatory power of the regression coefficient, but the sign of influence was the same as the prediction. Connectivity factor reveals a influence on differences between first period and latter, but OPR impact direction is changed from negative in before to positive in late. This is an evironment in which connectivity is actually realized in later period. On diversity factor, there is no effect of investment share in subsidiaries and government subsidies on OPR.