• Journal of Venture Innovation
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• v.7 no.3
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• pp.1-23
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• 2024

This study empirically analyzed the factors affecting acceptance intention when introducing digital transformation in the passenger vehicle transportation business, and examined the moderating effect of corporate agility. Based on the technology acceptance model (TAM) and the technology-organization-environment (TOE) model, the study set introduction usability, ease of introduction, digital transformation capability, CEO support, customer demand, and competitive pressure as independent variables, and 316 effective samples were analyzed by setting corporate agility as a modulating variable. As a result of the analysis, ease of introduction, digital transformation capability, CEO support, customer demand, and competitive pressure all had a significant influence on the intention to accept digital transformation, and in particular, digital transformation capability had the greatest influence. This suggests that the ability of companies to effectively utilize digital technology is an essential factor in the success of digital transformation. On the other hand, the usefulness of introduction did not significantly affect the intention to accept, which means that concerns about costs and risks can have a greater impact on the introduction of digital transformation. In addition, corporate agility showed a positive moderating effect in the relationship between acceptance intention and independent variables, and it was shown that the more agile the company can effectively solve the challenges that arise in the process of introducing digital transformation. In particular, when corporate agility is high, the effect of usefulness of introduction changes positively. This study is the first attempt to systematically analyze digital transformation in the passenger vehicle transportation business, and in practice, it has great academic significance and confirmed the importance of digital transformation capabilities and CEO support. However, since the scope of the study is limited to the passenger vehicle transportation business, there is a limit to generalization, research expanded to various industries and fields is needed in the future.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

• Journal of Distribution Research
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• v.16 no.1
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• pp.141-177
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• 2011

I. Research Objectives: Most of the previous studies on diffusion have concentrated on efficacy of WOM communication with the use of variables at individual level (Iacobucci 1996; Midgley et al. 1992). However, there is a paucity of studies which investigated network's structural properties as antecedents of WOM from the perspective of consumers' sociocultural propensities. Against this research backbone, this study attempted to link the network's structural properties and consumer' WOM behavior on cross-national basis. The major research objective of this study was to examine the relationship between network properties and WOM by comparing Korean and Chinese consumers. Specific objectives of this research are threefold; firstly, it sought to examine whether network properties (i.e., tie strength, centrality, range) affect WOM (WOM intention and quality of WOM). Secondly, it aimed to explore the moderating effects of cutural orientation (uncertainty avoidance and individuality) on the relationship between network properties and WOM. Thirdly, it substantiates the role of innovativeness as antecedents to both network properties and WOM. II. Research Hypotheses: Based on the above research objectives, the study put forth the following research hypotheses to validate. ${\cdot}$ H 1-1 : The Strength of tie between two counterparts within network will positively influence WOM effectivenes ${\cdot}$ H 1-2 : The network centrality will positively influence the WOM effectiveness ${\cdot}$ H 1-3 : The network range will positively influence the WOM effectiveness ${\cdot}$ H 2-1 : The consumer's uncertainty avoidance tendency will moderate the relationship between network properties and WOM effectiveness ${\cdot}$ H 2-2 : The consumer's individualism tendency will moderate the relationship between network properties and WOM effectiveness ${\cdot}$ H 3-1 : The consumer's innovativeness will positively influence the social network properties ${\cdot}$ H 3-2 : The consumer's innovativeness will positively influence WOM effectiveness III. Methodology: Through a pilot study and back-translation, two versions of questionnaire were prepared, one in Korean and the other in Chinese. The chinese data were collected from the chinese students enrolled in language schools in Suwon city in Korea, while Korean data were collected from students taking classes in a major university in Seoul. A total of 277 questionnaire were used for analysis of Korean data and 212 for Chinese data. The reason why Chinese students living in Korea rather than in China were selected was based on two factors: one was to neutralize the differences (ie, retail channel availability) that may arise from living in separate countries and the second was to minimize the difference in communication venues such as internet accessibility and cell phone usability. SPSS 12.0 and AMOS 7.0 were used for analysis. IV. Results: Prior to hypothesis verification, mean differences between the two countries in terms of major constructs were performed with the following result; As for network properties (tie strength, centrality and range), Koreans showed higher scores in all three constructs. For cultural orientation traits, Koreans scored higher only on uncertainty avoidance trait than Chinese. As a result of verifying the first research objective, confirming the relationship between network properties and WOM effectiveness, on Korean side, tie strength(Beta=.116; t=1.785) and centrality (Beta=.499; t=6.776) significantly influenced on WOM intention, and similar finding was obtained for Chinese side, with tie strength (Beta=.246; t=3.544) and centrality (Beta=.247; t=3.538) being significant. However, with regard to WOM argument quality, Korean data yielded only centrality (Beta=.82; t=7.600) having a significant impact on WOM, whereas China showed both tie strength(Beat=.142; t=2.052) and centrality(Beta=.348; t=5.031) being influential. To answer for the second research objective addressing the moderating role of cultural orientation, moderated regression anaylsis was performed and the result showed that uncertainty avoidance moderated between network range and WOM intention for both Korea and China, But for Korea, the uncertainty avoidance moderated between tie strength and WOM quality, while for China it moderated between network range and WOM intention. And innovativeness moderated between tie strength and WOM intention for Korea but it moderated between network range and WOM intention for China. As a result of analysing for third research objective, we found that for Korea, innovativeness positively influenced centrality only (Beta=.546; t=10.808), while for China it influenced both tie strength (Beta=.203; t=2.998) and centrality(Beta=.518; t=8.782). But for both countries alike, the innovativeness influenced positively on WOM (WOM intention and WOM quality). V. Implications: The study yields the two practical implications. Firstly, the result suggests that companies targeting multinational customers need to identify segments which are susceptible to the positive WOM and WOM information based on individual traits such as uncertainty avoidance and individualism and based on that, develop marketing communication strategy. Secondly, the companies need to divide the market on Roger's five innovation stages and based on this information, enforce marketing strategy which utilizes social networking tools such as public media and WOM. For instance, innovator and early adopters, if provided with new product information, will be able to capitalize upon the network advantages and thus add informational value to network operations using SNS or corporate blog.

• Journal of Oral Medicine and Pain
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• v.36 no.1
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• pp.39-51
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• 2011

The aims of this study were to investigate whether the facial skeletal patterns previously reported to be related to temporomandibular disorder (TMD) in other studies could be consistently observed in the TMD patients diagnosed according to Research Diagnostic Criteria for Temporomandibular Disorder (RDC/TMD) Axis I and evaluate its usability in the orthodontic clinics to examine the patients with TMD related symptoms. The clinical records and radiographs of female patients who visited the TMD and Orofacial Pain Clinic of Seoul National University Dental Hospital and were diagnosed as TMD were consecutively filed for this study. Patients were clinically examined and diagnosed according to the revised diagnostic algorithms of RDC/TMD Axis I and the lateral cephalogram, panoramic orthopantomogram, temporomandibular joint (TMJ) orthopantomogram, and transcranial radiograph of each patient were taken and digitalized. The data of patients who were under 18 years of age or had any systemic disease, trauma history involving the TMJ, or skeletal deformity at the time of the first examination were excluded. The remaining data of 96 female patients were finally analyzed. The obtained results were as follows: 1. There are no significant differences of cephalometric measurements between RDC I (muscle disorders) diagnostic groups. 2. Only the articular angle of the RDC group IIc (disk displacement without reduction without limited opening) patients was larger than patients of the no diagnosis of RDC II group (disk displacement). 3. Larger articular angle and smaller facial height ratio were observed in RDC IIIc group (osteoarthrosis) compared to IIIa group (arthralgia). Larger articular angle, larger Bjork sum, smaller posterior facial height, and smaller facial height ratio were observed in RDC group IIIc compared to no diagnosis of RDC III group (arthralgia, arthritis, and arthrosis). 4. According to the results of cephalometric analysis in simplified RDC groups, smaller overjet was observed in muscle disorders (MD) group. Facial height ratio and IMPA were smaller and articular angle was larger in disk displacements (DD) group than in no diagnosis of DD group. In arthrosis (AR) group, posterior facial height, and facial height ratio were smaller, and articular angle, gonial angle, facial convexity, FMA, Bjork sum, and ANB were larger than in no diagnosis of AR group. In joint pain (JP) group, only posterior facial height was smaller than no diagnosis of JP group. In conclusion, Facial morphologic patterns showing posterior-rotated mandible and lower posterior facial height is related to RDC group II and III diagnosis of the TMJ in female TMD patients. RDC/TMD Axis I diagnosis can provide a good clinical diagnostic tool for the standardized examination of the TMJ in orthodontic clinics.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.