• Title/Summary/Keyword: Value Activity Network

Search Result 86, Processing Time 0.024 seconds

Estimation of Unit Cost by Handling Cargo in Busan New Port DistriPark (부산항 신항 배후단지 취급화물별 비용 원단위 추정)

  • Kim, Yun-Hoe;Choung, Sang-Won;Kim, Yul-Seong
    • Journal of Navigation and Port Research
    • /
    • v.44 no.6
    • /
    • pp.550-556
    • /
    • 2020
  • Over the past years, the role of ports in the global network of supply chains has becoming increasingly important, not merely as a physical location for loading and unloading goods, but also as an essential center of economic activity where additional value is added to cargo. Due to the overall growing importance of ports, each country has chosen to adopt hub growth as a primary economic strategy. Northeast Asia in particular, due to its high population density, experiences intense competition between its ports. Busan's port, as a result, has used the establishment of Distripark in order to attract high and stable trade volume, and compete more effectively with other ports in the region. This study estimates the unit cost of the logistic process for the all principal cargos handled at Busan New Port, with the findings revealing that unit cost increases gradually starting with chemical products, LME bulk goods, automobile parts, LME containers, general cargoes, and LME inland transportation goods coming in last. Future research will look more closely at all all categories of cargo handled in the Distrpark of Busan New Port, thereby enabling us to better understand the value created by the port, and how to best implement effective trade volume-attraction strategy.

A Study on the Revitalization of Tourism Industry through Big Data Analysis (한국관광 실태조사 빅 데이터 분석을 통한 관광산업 활성화 방안 연구)

  • Lee, Jungmi;Liu, Meina;Lim, Gyoo Gun
    • Journal of Intelligence and Information Systems
    • /
    • v.24 no.2
    • /
    • pp.149-169
    • /
    • 2018
  • Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

Big Five Personality in Discriminating the Groups by the Level of Social Sims (심리학적 도구 '5요인 성격 특성'에 의한 소셜 게임 연구: <심즈 소셜> 게임의 분석사례를 중심으로)

  • Lee, Dong-Yeop
    • Cartoon and Animation Studies
    • /
    • s.29
    • /
    • pp.129-149
    • /
    • 2012
  • The purpose of this study was to investigate the clustering and Big Five Personality domains in discriminating groups by level of school-related adjustment, as experienced by Social Sims game users. Social Games are based on web that has simple rules to play in fictional time and space background. This paper is to analyze the relationships between social networks and user behaviors through the social games . In general, characteristics of social games are simple, fun and easy to play, popular to the public, and based on personal connections in reality. These features of social games make themselves different from video games with one player or MMORPG with many unspecific players. Especially Social Game show a noticeable characteristic related to social learning. The object of this research is to provide a possibility that game that its social perspective can be strengthened in social game environment and analyze whether it actually influences on problem solving of real life problems, therefore suggesting its direction of alternative play means and positive simulation game. Data was collected by administering 4 questionnaires (the short version of BFI, Satisfaction with life, Career Decision-.Making Self-.Efficacy, Depression) to the participants who were 20 people in Seoul and Daejeon. For the purposes of the data analysis, both Stepwise Discriminant analysis and Cluster analysis was employed. Neuroticism, Openness, Conscientiousness within the Big Five Personality domains were seen to be significant variables when it came to discriminating the groups. These findings indicated that the short version of the BFI may be useful in understanding for game user behaviors When it comes to cultural research, digital game takes up a significant role. We can see that from the fact that game, which has only been considered as a leisure activity or commercial means, is being actively research for its methodological, social role and function. Among digital game's several meanings, one of the most noticeable ones is the research on its critical, social participating function. According to Jame Paul gee, the most important merit of game is 'projected identity'. This means that experiences from various perspectives is possible.[1] In his recent autobiography , he described gamer as an active problem solver. In addition, Gonzalo Francesca also suggested an alternative game developing method through 'game that conveys critical messages by strengthening critical reasons'. [2] They all provided evidences showing game can be a strong academic tool. Not only does a genre called social game exist in the field of media and Social Network Game, but there are also some efforts to positively evaluate its value Through these kinds of researches, we can study how game can give positive influence along with the change in its general perception, which would eventually lead to spreading healthy game culture and enabling fresh life experience. This would better bring out the educative side of the game and become a social communicative tool. The object of this game is to provide a possibility that the social aspect can be strengthened within the game environment and analyze whether it actually influences the problem solving of real life problems. Therefore suggesting it's direction of alternative play means positive game simulation.

Time Series Analysis of Park Use Behavior Utilizing Big Data - Targeting Olympic Park - (빅데이터를 활용한 공원 이용행태의 시계열분석 - 올림픽공원을 대상으로 -)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.46 no.2
    • /
    • pp.27-36
    • /
    • 2018
  • This study suggests the necessity of behavior analysis as changes to a park environment to reflect user desires can be implemented only by grasping the needs of park users. Online data (blog) were defined as the basic data of the study. After collecting data by 5 - year units, data mining was used to derive the characteristics of the time series behavior while the significance of the online data was verified through social network analysis. The results of the text mining analysis are as follows. First, primary results included 'walking', 'photography', 'riding bicycles'(inline, kickboard, etc.), and 'eating'. Second, in the early days of the collected data, active physical activity such as exercise was the main factor, but recent passive behavior such as eating, using a mobile phone, games, food and drinking coffee also appeared as a new behavior characteristic in parks. Third, the factors affecting the behavior of park users are the changes of various conditions of society such as internet development and a culture of expressing unique personalities and styles. Fourth, the special behaviors appearing at Olympic Park were derived from educational activities such as cultural activities including watching performances and history lessons. In conclusion, it has been shown that people's lifestyle changes and the behavior of a park are influenced by the changes of the various times rather than the original purpose that was intended during park planning and design. Therefore, it is necessary to create an environment tailored to users by considering the main behaviors and influencing factors of Olympic Park. Text mining used as an analytical method has the merit that past data can be collected. Therefore, it is possible to form analysis from a long-term viewpoint of behavior analysis as well as to measure new behavior and value with derived keywords. In addition, the validity of online data was verified through social network analysis to increase the legitimacy of research results. Research on more comprehensive behavior analysis should be carried out by diversifying the types of data collected later, and various methods for verifying the accuracy and reliability of large-volume data will be needed.

A Deep Learning Based Approach to Recognizing Accompanying Status of Smartphone Users Using Multimodal Data (스마트폰 다종 데이터를 활용한 딥러닝 기반의 사용자 동행 상태 인식)

  • Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
    • Journal of Intelligence and Information Systems
    • /
    • v.25 no.1
    • /
    • pp.163-177
    • /
    • 2019
  • As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

An Exploratory Study for the Adoption and Use of Telepresence: Focusing on Supporting Trade Business Activity of SME (텔레프레즌스 도입 및 사용에 관한 탐색적 연구: 국내 중소기업의 무역활동 지원을 중심으로)

  • Kim, Kil-Lae;Jeong, So-Yeon
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.11 no.9
    • /
    • pp.3538-3547
    • /
    • 2010
  • As Telepresence has emerged as a key collaboration tool for supporting trade business, the need for using Telepresence has also been increased in the foreign countries. In this context, we has studied an exploratory research to analyze how staffs-in-charges of trade support authority, exhibition & convention center and SME(Small and Medium-Size Enterprise) perceive the general concept of Telepresence, the necessity, feasibility, business values and expected problems of Telepresence's adoption and use. The finding indicated that there seemed to be significant differences between the necessity and the feasibility of Telepresence adoption and use. In addition, they were anticipating some problems when building Telepresence. Major reasons are incompatibility between Telepresence systems, lack of usability and difficulties of fixing a rental fee. The results of the perception analysis also showed that Telepresence would positively influence on creating business value. The analysis revealed that the core factors of the successful adoption and use of Telepresence are stable network environment, awareness and accessability, and education and promotion. Through the perception analysis, I came up with the core factors to implement Telepresence successfully and use it properly. And the fact that I presented the guideline to build Telepresence for SME makes this study meaningful.

Influential Factors of Social Relation on the Change in the Depression Level of Elderly -Longitudinal Analysis using a Latent Growth Model (노인의 사회적관계 요인이 우울 궤적에 미치는 영향 -잠재성장모형을 이용한 종단연구)

  • Kim, Jin-hun
    • The Journal of the Korea Contents Association
    • /
    • v.19 no.7
    • /
    • pp.138-148
    • /
    • 2019
  • Although social relation factors are confirmed to be closely associated with the depression level of the elderly through the preceding studies, there has been no specific study on subfactors of social relation that influence the trajectory of depression level. Considering such limitation, this study aims to analyze influencing subfactors of social relation on the trajectory of depression of the elderly. The 3rd, 4th, 5th, and 6th-year data of the Korean Longitudinal Survey of Ageing (KLoSA), which were provided by the Korea Employment Information Service (KEIS), were used in this study and 2,484 people aged 65 and over who responded to all the four-session surveys were used as final analysis subjects. In the result of the longitudinal study on depression level of the elderly aged 65 and over, the individual depression level was confirmed become lowered over time, showing a positive change. Also, the conditional model of Latent Growth Modeling (LGM) was applied to identify specific social network factors that influence the longitudinal change of depression level of the elderly. In the result of the analysis, it was found that initial value of depression of the elderly was influenced by whether they have a spouse or not, number of household member, meeting with close people, whether they do economic activity or not, whether they have a religion or not, etc. and the rate of change in depression of the elderly was influenced by number of household member, meeting with close people, expectation about life, etc. Through above results, this study suggests a need for specific programs and supports to continuously lower the depression level of the elderly.

The Study on the key Factors for Communitiy -Based Rural Landscape Conservation- (커뮤니티 기반 농촌경관 보전을 위한 주요 요인 고찰 -경상남도 함안군 여항면을 대상으로-)

  • Lee, Da-Young;Jeong, Jae-Hyeon;Park, Jin-Wook
    • Journal of Korean Society of Rural Planning
    • /
    • v.30 no.3
    • /
    • pp.19-28
    • /
    • 2024
  • This study investigated and analyzed the landscape conservation activity promotion process targeting the 'Alassiasdeuli Community Farming Association Corporation', which is carrying out continuous rural landscape conservation activities led by local residents in the area of Yeohang Mountain, Yeohang-myeon, Haman-gun, Gyeongsangnam-do. Through this, the factors necessary to promote rural landscape conservation activities led by residents were identified, and implications necessary for rural landscape conservation activities led by residents were derived. The first factor that allowed Alassiasdeuli to pursue resident-led rural landscape conservation activities was the fact that an economically stable foundation was established before pursuing conservation activities. Rural landscape conservation activities are carried out based on continuous agricultural activities, and agriculture is closely related to the economic aspect. Accordingly, Alassiasdeuli had a small but regular income from the package business, and was able to carry out various rural landscape conservation activities based on this. Second, within the community, a sense of purpose for rural landscape conservation was shared as a common value. It started with common values that were in line with rural landscape conservation, such as an economic community based on agriculture, indigenous seed conservation, and eco-friendly agriculture, and later, awareness of traditional agriculture and rural landscape conservation was gradually established through members' continued empowerment and related experiences. It has been done. Third, various connections and cooperative relationships were established with residents, related organizations, and administration. We established cooperative relationships by recruiting local organizations and residents as active participants beyond program participation, and exchanged information and expanded the scope of activities by establishing networks with organizations such as the 'Gyeongnam Darang-Non Network'. In addition, through connection with administration, we experienced various projects and ensured the sustainability of activities through support. Fourth, there was a keyman who could organize activities and control the scale of support projects, taking into account the awareness and capabilities of members. In particular, it is thought that this was possible because the Secretary General was based on building a relationship of trust with residents before Alassiasdeuli was formed. Therefore, in order for resident-led rural landscape conservation activities to be continuously carried out, an organization must be formed centered on farmers, and the economic sustainability of the organization, sharing of common values, and trust relationships among members are the basis, and the Sustainable activities can be promoted through various cooperative relationships between residents, organizations, and administration.

Knowledge Management Strategy of a Franchise Business : The Case of a Paris Baguette Bakery (프랜차이즈 기업의 지식경영 전략 : 파리바게뜨 사례를 중심으로)

  • Cho, Joon-Sang;Kim, Bo-Yong
    • Journal of Distribution Science
    • /
    • v.10 no.6
    • /
    • pp.39-53
    • /
    • 2012
  • It is widely known that knowledge management plays a facilitating role that contributes to upgrading organizational performance. Knowledge management systems (KMS), especially, support the knowledge management process including the sharing, creating, and using of knowledge within a company, and maximize the value of knowledge resources within an organization. Despite this widely held belief, there are few studies that describe how companies actually develop, share, and practice their knowledge. Companies in the domestic small franchise sector, which are in the early stages in terms of knowledge management, need to improve their KMS to manage their franchisees effectively. From this perspective, this study uses a qualitative approach to explore the actual process of knowledge management implementation. This article presents a case study of PB (Paris Baguette) company, which is the first to build a KMS in the franchise industry. The study was able to confirm the following facts through the analysis of target companies. First, the chief executive's support is a critical success factor and this support can increase the participation of organization members. Second, it is important to build a process and culture that actively creates and leverages information in knowledge management activities. The organizational learning culture should be one where the creation, learning, and sharing of new knowledge is developed continuously. Third, a horizontal network organization is needed in order to make relationships within the organization more close-knit. Fourth, in order to connect the diverse processes such as knowledge acquisition, storage, and utilization of knowledge management activities, information technology (IT) capabilities are essential. Indeed, IT can be a powerful tool for improving the quality of work and maximizing the spread and use of knowledge. However, during the construction of an intranet based KMS, research is required to ensure that the most efficient system is implemented. Finally, proper evaluation and compensation are important success factors. In order to develop knowledge workers, an appropriate program of promotion and compensation should be established. Also, building members' confidence in the benefits of knowledge management should be an ongoing activity. The company developed its original KMS to achieve a flexible and proactive organization, and a new KMS to improve organizational and personal capabilities. The PB case shows that there are differences between participants perceptions and actual performance in managing knowledge; that knowledge management is not a matter of formality but a paradigm that assures the sharing of knowledge; and that IT boosts communication skills, thus creating a mutual relationship to enhance the flow of knowledge and information between people. Knowledge management for building organizational capabilities can be successful when considering its focus and ways to increase its acceptance. This study suggests guidelines for major factors that corporate executives of domestic franchises should consider to improve knowledge management and the higher operating activities that can be used.

  • PDF

A Study on the Types of Jazz Performance Audiences Using Q Methodology (Q 방법론을 적용한 재즈공연 관객의 유형에 관한 연구)

  • Jeong, Woo Sik
    • Korean Association of Arts Management
    • /
    • no.53
    • /
    • pp.5-45
    • /
    • 2020
  • This study aims to deeply analyze the subjective attitude of jazz performance audiences in Korea using Q methodology. In order to establish a population for the research, we decided 'People's mind about jazz performances' as the main topic and finally selected a Q model consist of 38 statements after having a depth interview with corresponding experts. Additionally, from January to February 2019, we implemented a Q-sorting and individual interview to total of 27 people including people majored in music, jazz club members and other citizens. The result were the following. First of all, a musical-interest oriented type. People of this type understood watching jazz performance as a daily leisure activity and went to watch a show more than once a month on overage. Those people obtained information of performances and actors before attending a show using social network such as SNS and jazz clubs. They also had a big desire to have an emotional interaction with jazz musicians while having a fan signing event or performance. Secondly, a general-interest oriented type. This type of people had a tendency of considering watching a jazz performance as a especial experience and not a daily life event. Attending a jazz performance was a novel experience which could be done with their close friends in a special day. Thirdly, people with self-value oriented type. This people were majored in jazz and classic in their universities. As they had a concrete perspective, professional knowledge and experiences, they were more sensitive on the general quality of the performances such as show's sound, light, video, sound system of the theater, player's ability, level of facilities, accessibility, etc. rather than the reputation of an artist. This research did not only revealed jazz audience's subjective tendency using Q methodology but also demonstrated the types of jazz audiences and their characteristics. Therefore, this could be a meaningful study for suggesting a significant implication for the marketing mix of performance planning on each jazz audience type.