• Management & Information Systems Review
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• v.37 no.4
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• pp.175-193
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• 2018

As a new type of business model in the market competition situation of tour companies, this study has developed to the online form of the travel industry to the business form which is the combination of the electronic commerce function and the mobile service process in the provision of the simple web-site, This study explores the difficulties of change for the development of the travel industry from the point of view that recognition is not a simple marketing strategy diversification means but a change of recognition as a business model for expanding new markets or creating new markets. The factors affecting the choice of online travel agent (OTA) and the factors that influence the choice of online travel agency were analyzed. Were used for the empirical survey. The purpose of this study is to investigate the factors influencing the choice of online travel agents who have experience with or experience using online travel agency (OTA), what factors are important to them, and how they differ in importance when visiting again. The results of this study are as follows: First, there was a significant difference between the first and second visitors of online travel agencies. The results of this study were as follows: Attitude toward resolving complaints, convenience of change and cancellation, delivery of tickets and documents, convenience of complaints, The emphasis should be on establishing and strengthening service environments such as the speed of updating the latest information, the simplicity of the booking procedure, the degree of satisfaction of the past, the ability of employees to handle their work, the safety of various payment methods and settlement, The results of this study are as follows: First, the satisfaction of the online travel agency is influenced by the selection factors of the selected online tour agency, and the A/S such as the convenience of prompt delivery, Environmental factors contributed to satisfaction. It is suggested that the systematic service structure such as customer satisfaction and ease of use is a necessary marketing strategy for survival and development of online travel agencies. It is suggested that the marketing concentration strategy with the first visitors as the target market is effective and this is a part of the marketing strategy for the survival of online travel agencies.

• (The)Study of the Eastern Classic
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• no.73
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• pp.249-279
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• 2018

This paper analyzes the 'strategy' of Sunzi's art of war and verifies the modern application value of it by combining the 'strategy' of the art of war with modern enterprise management. The army adopts 'war strategy' with the aim of minimizing the loss and sacrifice caused by the war and winning in the shortest time. Enterprise aims to maximize profits at the lowest cost and adopt 'business strategy'. Three factors of art of war's strategic, the 'power', 'adaptation', 'trickery', are similar to the 'internal resources analysis', 'external environment analysis' and 'information management' of the modern enterprise's management. In the process of establishing strategic plan, the art of war emphasizes 'strategy of winning' including 'prophet', 'estimates' and 'maneuvering', in the modern enterprise management, 'prophet' is shown as 'competitor analysis' of the '3C analysis' and 'benchmarking learning'. 'Estimates' is shown as 'SWOT analysis' and '4P's analysis'. 'Maneuvering' is shown as 'market positioning strategy' and 'market preemption strategy'. In the stage of implementing the strategy, 'surprise attack strategy', 'strategy of void and actuality' and 'dividing and integrating strategy' of the art of war are shown as follows in modern enterprises ; 'Surprise attack strategy' is shown as 'differentiation strategy' and 'concentration strategy', 'Strategy of void and actuality' is shown as 'information management' and 'rational market positioning strategy'. 'Dividing and integrating strategy' is shown 'diversification strategy', 'concentration strategy', 'change management', 'basic competition strategy', 'synergy effect' and etc. In terms of strategic results, the 'victory of war' of the art or war is shown as 'competitive advantage' and 'maximization of profits' in modern enterprise management strategy. In a word, although there are different names and expressions between the strategy of Sunzi's art of war and modern enterprise, but their connotation is the same. We can see that the art of war which was written in about B.C.500, has left a high utilization value for modern enterprise in rapid environmental change and intense competition.

• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.139-148
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• 2021

This study aimed to verify how a multisensory storytelling-based activity-based intervention affects social interaction in children with cerebral palsy. As a quasi-experimental investigation, this study used a single-blind, two-group pre-post test design. This study comprised 24 children aged 7 to 8 y who had been diagnosed with spastic cerebral palsy and were classified as having GMFCS stages I to III. Twelve children were randomly assigned to experimental and control groups, with neither the children nor their guardians knowing which group they were placed in. The group program comprised 16 sessions of 60 min each, twice a week for eight weeks. The experimental group engaged in an activity-centered intervention centered on multisensory storytelling, whereas the control group engaged in structured physical activity. The activities were assessed using the peer relations skills scale to determine the extent to which social interaction had changed prior to and during the child's intervention. The SPSS 25.0 for Windows (IBM Corp, USA) application was used to analyze the data, and the significance level (α) for statistical verification was set to 0.05. Furthermore, the Wilcoxon Signed-Rank and Mann-Whitney U tests were used to assess the differences in social interaction between the experimental and control groups. Significant differences were observed in the total of the peer relationship skill scale and cooperation and empathy areas of the subtest in the intragroup change of the peer relationship skill scale between the experimental and control groups. However, the experimental group demonstrated a significant difference in the initiative area, whereas the control group demonstrated no significant difference. A significant difference was observed in the amount of change between the two groups in the initiative area and total of the subtest of peer relationship skills but no significant difference in the collaboration and empathy areas. We gave a multisensory storytelling-based activity-based intervention based on multisensory storytelling to children with cerebral palsy and saw a significant improvement in peer relationship skills. It may be proposed as an effective intervention strategy for children with cerebral palsy who struggle with social contact.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 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 Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.53-65
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• 2022

According to the advancement of the GNSS satellite positioning system, the module of hardware and operation software reflecting accuracy and economical efficiency is implemented in the user sector including the multi-channel GNSS receiver, the multi-frequency external antenna and the mobile app (App) base public positioning analysis software etc., and the multichannel GNSS RTK positioning of the active configuration method (DIY, Do it yourself) is possible according to the purpose of user. Especially, as the infrastructure of multi-GNSS satellite is expanded and the potential of expansion of utilization according to various modules is highlighted, interest in the utilization of multi-channel low-cost GNSS receiver module is gradually increasing. The purpose of this study is to review the multi-channel low-cost GNSS receivers that are appearing in the mass market in various forms and to analyze the utilization plan of the "address information facility investigation project" of the Ministry of Public Administration and Security by constructing the multi-channel low-cost GNSS positioning module based RTK survey system (hereinafter referred to as "multi-channel GNSS RTK module positioning system"). For this purpose, we constructed a low-cost "multi-channel GNSS RTK module positioning system" by combining related modules such as U-blox's F9P chipset, antenna, Ntrip transmission of GNSS observation data and RTK positioning analysis app through smartphone. Kinematic positioning was performed for circular trajectories, and static positioning was performed for address information facilities. The results of comparative analysis with the Static positioning performance of the geodetic receivers were obtained with 5 fixed points in the experimental site, and the good static surveying performance was obtained with the standard deviation of average ±1.2cm. In addition, the results of the test point for the outline of the circular structure in the orthogonal image composed of the drone image analysis and the Kinematic positioning trajectory of the low cost RTK GNSS receiver showed that the trajectory was very close to the standard deviation of average ±2.5cm. Especially, as a result of applying it to address information facilities, it was possible to verify the utility of spatial information construction at low cost compared to expensive commercial geodetic receivers, so it is expected that various utilization of "multi-channel GNSS RTK module positioning system"

• Journal of Communication Design
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• v.68
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• pp.278-288
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• 2019

The purpose of this study is to analyze the effects of risk and convenience on purchase intention in the IOT market, and I want to analyze the moderating effect of emotional consumption value. In this study, two products were selected from three product groups. There are three major methods of research. First, theoretical considerations. Second, survey analysis. Reliability analysis and factor analysis were performed using descriptive statistics using SPSS. Third, we measured changes of EEG according to in - depth interview and indirect experience. As a result of the hypothesis of this study, it was confirmed that convenience of use of IoT product influences purchase intention. Risk was predicted to have a negative effect on purchase intentions, but not significant in this study. This implies that IoT products tend to be neglected in terms of monetary loss such as cost of purchase, cost of use, and disposal cost when purchasing. In-depth interviews and EEG analysis revealed that there is a desire to purchase and try out the IoT product due to the nature of the product, the novelty of new technology, and the vague idea that it will benefit my life. The aesthetic, symbolic, and pleasure factors, which are sub - elements of emotional consumption value, were found to have a great influence. This is consistent with previous research showing that emotional consumption value has a positive effect on purchase intention. In-depth interviews and EEG analyzes also yielded the same results. This study has revealed that emotional consumption value affects the intention to purchase IoT products. It seems that companies producing IoT products need to concentrate on marketing with more emotional consumption value.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.59-73
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• 2022

Untact marketing is being activated due to COVID-19. As a result, live commerce, an untact seller, is also active in the e-commerce market. Therefore, in this study, we tried to find out what factors influence consumers when they purchase through live commerce. In particular, since consumers' trust and flow in live commerce platforms and products is important, their mediating effects were analyzed. The research model was established by deriving common variables among the characteristics of live commerce based on previous studies. An online survey was conducted for empirical analysis. 200 users who made at least one purchase in live commerce were analyzed. The study results are as follows. Among the characteristics of live commerce, entertainment, economics, professionality were found to have a positive (+) effect on purchase intention. On the other hand, ease of use did not significantly affect purchase intention. The influence was shown in the order of entertainment, professionality and economics. The mediating effect of trust was found to play a mediating role in that entertainment, economics, and professionality affect purchase intention. On the other hand, a significant mediating effect was not tested between ease of use and purchase intention. As for the mediating effect of flow, it was found that flow plays a mediating role in that entertainment and economics affect purchase intention. On the other hand, the mediating effect of flow in terms of ease of use and economics affecting purchase intention was not tested. As for the multiple mediating effect of flow and trust, the mediating effect of flow was stronger than the mediating effect of trust when entertainment had an effect on purchase intention. In terms of professionality affecting purchase intention, the mediating effect of flow was also stronger than the mediating effect of trust. On the other hand, it was analyzed that only trust had a mediating effect when economics had an effect on purchase intention. The results of this study empirically tested that entertainment, which is a fun and interesting factor of live commerce content, is the most important factor when consumers use live commerce. In addition, various results were derived, such as cases where trust and flow act as mediators at the same time or not at all. Practical implications can be found in that it provided a clue about what to prioritize in order to reach consumers for live commerce platform.