Search results

The purpose of this paper is to construct a structural definition-based terminology ontology system that defines the meanings of academic terms on the basis of properties and links terms with properties that are structured by conceptual categories (classes). This study also aims to test the possibility of semantic searches by generating inference rules and setting very complicated search scenarios.

For the study, 55,236 keywords from the articles of the “Korea Citation Index” were structurally defined and relationships among terms and properties were built. Then, the authors converted the RDB data into RDF and designed ontologies using the ontology developing tool Protégé. The authors also tested the designed ontology with the inference engine of the Protégé editor. The generated reference rules were tested by TBox and SPARQL queries.

The authors generated inference control rules targeting high-input-ratio data in the properties of classes by calculating the input ratio of real input data in the system, and then the authors executed a semantic search by SPARQL query by setting very complicated search scenarios, for which it would be difficult to deduce results via a simple keyword search. As a result, it was confirmed that the search results show the logical combination of semantically related term data.

The proposed terminology ontology system was constructed with the author keywords from research papers, it will be useful in searching the research papers which include the keywords as search results by the complex combination of semantic relation. And the Structural Terminology Net database could be utilized as an index database in retrieval services and the mining of informal big data through the application of well-defined semantic concepts to each term.

This paper presented a methodology for supporting IR using expanded queries based on a novel model of structural terminology-based ontology. The user who wants to access the specific topic can create query that brings the semantically relevant information. The search results show the logical combination of semantically related term data, which would be difficult to deduce results via traditional IR systems.

As social media platforms become increasingly popular among service firms, many US hospitals have been using social media as a means to improve their patients’ experiences. However, little research has explored the implications of social media use within a hospital context. The purpose of this paper is to investigate a hospital’s customer engagement through social media and its association with customers’ experiential quality. Also, this study examines the role of a hospital’s service characteristics, which could shape the nature of the interactions between patients and the hospital.

Data from 669 hospitals with complete experiential quality and demographic data were collected from multiple sources of secondary data, including the rankings of social media friendly hospitals, the Hospital Compare database, the Center for Medicare and Medicaid (CMS) cost report, the CMS impact file, the Healthcare Information and Management Systems Society Analytics database and the Dartmouth Atlas of Health Care. Specifically, the authors designed the instrumental variable estimate to address the endogeneity issue.

The empirical results suggest a positive association between a hospital’s social media engagement and experiential quality. For hospitals with a high level of service sophistication, the association between online engagement and experiential quality becomes more salient. For hospitals offering various services, offline engagement is a critical predictor of experiential quality.

A hospital with more complex services should make efforts to engage customers through social media for better patient experiences. The sample is selected from databases in the US, and the databases are cross-sectional in nature.

Not all hospitals may be better off improving the patient experience by engaging customers through social media. Therefore, practitioners should exercise caution in applying the study’s results to other contexts and in making causal inferences.

The current study delineates customer engagement through social media into online and offline customer engagement. This study is based on the theory of customer engagement and reflects the development of mobile technology. Moreover, this research may be considered as pioneering in that it considers the key characteristics of a hospital’s service operations (i.e., service complexity) when discovering the link between customers’ engagement through a hospital’s social media and experiential quality.

This study aims to develop metadata of conceptual elements based on the text structure of research articles on Korean studies, to propose a search algorithm that reflects the combination of semantically relevant data in accordance with the search intention of research paper and to examine the algorithm whether there is a difference in the intention-based search results.

This study constructed a metadata database of 5,007 research articles on Korean studies arranged by conceptual elements of text structure and developed F1(w)-score weighted to conceptual elements based on the F1-score and the number of data points from each element. This study evaluated the algorithm by comparing search results of the F1(w)-score algorithm with those of the Term Frequency- Inverse Document Frequency (TF-IDF) algorithm and simple keyword search.

The authors find that the higher the F1(w)-score, the closer the semantic relevance of search intention. Furthermore, F1(w)-score generated search results were more closely related to the search intention than those of TF-IDF and simple keyword search.

Even though the F1(w)-score was developed in this study to evaluate the search results of metadata database structured by conceptual elements of text structure of Korean studies, the algorithm can be used as a tool for searching the database which is a tuning process of weighting required.

A metadata database based on text structure and a search method based on weights of metadata elements – F1(w)-score – can be useful for interdisciplinary studies, especially for semantic search in regional studies.

This paper presents a methodology for supporting IR using F1(w)-score—a novel model for weighting metadata elements based on text structure. The F1(w)-score-based search results show the combination of semantically relevant data, which are otherwise difficult to search for using similarity of search words.

As the penalized vortex-in-cell (pVIC) method is based on the vorticity-velocity form of the Navier–Stokes equation, the pressure variable is not incorporated in its solution procedure. This is one of the advantages of vorticity-based methods such as pVIC. However, dynamic pressure is an essential flow property in engineering problems. In pVIC, the pressure field can be explicitly evaluated by a pressure Poisson equation (PPE) from the velocity and vorticity solutions. How to specify far-field boundary conditions is then an important numerical issue. Therefore, this paper aims to robustly and accurately determine the boundary conditions for solving the PPE.

This paper introduces a novel non-iterative method for specifying Dirichlet far-field boundary conditions to solve the PPE in a bounded domain. The pressure field is computed using the velocity and vorticity fields obtained from pVIC, and the solid boundary conditions for pressure are also imposed by a penalization term within the framework of pVIC. The basic idea of our approach is that the pressure at any position can be evaluated from its gradient field in a closed contour because the contour integration for conservative vector fields is path-independent. The proposed approach is validated and assessed by a comparative study.

This non-iterative method is successfully implemented to the pressure calculation of the benchmark problems in both 2D and 3D. The method is much faster than all the other methods tested without compromising accuracy and enables one to obtain reasonable pressure field even for small computation domains that are used regardless of a source distribution (the right-hand side in the Poisson equation).

The strategy introduced in this paper provides an effective means of specifying Dirichlet boundary conditions at the exterior domain boundaries for the pressure Poisson problems. It is very efficient and robust compared with the conventional methods. The proposed idea can also be adopted in other fields dealing with infinite-domain Poisson problems.

As the wave of liberalization and deregulation have accelerated to relieve rigid controls over airline routes, capacity, and fare setting regimes, Low Cost Carriers (LCCs) have emerged especially in local aviation markets since the 1970s.

This paper has studied the effects of LCC's entry into the domestic aviation market which was pre-occupied by two major carriers, Korean Air (KAL) and Asiana Airlines. Through a simple model describing two situations, prior and post to LCC's entry, we analyzed changes and trends of each airline's output and profit based on the Cournot and two-stage Stackelberg game equilibrium.

In summary, our conclusion consists of five points: (1) Even though JIN Air's entry reduced KAL's respective output and profit, the more JIN Air produces, the higher the joint-profit of KAL and JIN Air is, (2) From the joint-profit aspect, increasing KAL's output to a level than JIN Air's is more profitable on the Gimpo-Jeju route, on the other hand, increasing JIN Air's output higher than KAL's is more profitable on the Jeju-Busan route, (3) Even though JIN Air's entry increase Asiana Airline's output, the more JIN Air produces, the less Asiana Airlines's profit is, (4) Total output in markets as well as total profits of firms will increase under certain conditions, (5) KAL and JIN Air tend to get caught in an unresolved conflict on level of LCC cost.

Online web searches have played crucial roles in influencing consumers’ purchasing decisions. Web search traffic information enables researchers and practitioners to better understand consumers in terms of their preferences and interests, among other things. The purpose of this paper is to use web search traffic information provided by Google Trends to derive relationships among product brands as well as those between product brands and product attributes to propose a method to enhance the visibility of consumer brand positioning.

This study builds upon the interesting observation that consumers’ behavior in performing simultaneous searches, or searches including two or more keywords, can be converted into data indicating relationships among brands as well as those between brands and their attributes. The study focuses on the cases of hybrid cars and tablet PCs, and applies a social network analysis method to identify these relationships. Time series information on web search traffic is used because it can track these two product groups from the early stages to the present. This step is completed to verify the changes in the status of each brand and in their relationships that occurred in consumers’ minds over time.

Results show that consumers’ web search behaviors reveal the brand positioning and brand-attribute associations in their minds. Specifically, using consumers’ simultaneous search data, the authors derived relationships among brands (brand-brand network) from consumers’ behaviors of searching simultaneously for two brands and the relationships between brands and attributes (brand-product attributes network) from consumers’ behavior of searching simultaneously for a specific brand and certain product attributes.

Theoretically, this study verifies that consumers’ web search traffic information can be used to microscopically identify the positions of individual brands and their relationships in the minds of consumers. Regarding practical applications, this study proposes a method that can be used by companies to track how consumers perceive their brands by performing a simple and cost-effective analysis using the free search traffic information provided by Google.

This study aims to provide nuanced insights into the effectiveness of digital outdoor advertising in redefining urban tourism appeal. Amidst a transformative era for urban tourism and city branding strategies, this study evaluates Tecoration’s influence on city branding and tourism promotion frameworks. Using the “Wave” digital outdoor advertising campaign in Seoul as a focal point, this analysis explores how such innovative marketing efforts reshape potential tourists’ perceptions and intentions toward visiting Seoul.

The study uses a bifurcated methodological framework. The initial phase undertakes a granular topical analysis, decoding keyword patterns from YouTube video commentaries, offering an unmediated insight into viewer sentiment. This is juxtaposed with a structural equation modeling technique in the subsequent phase, which serves to validate and triangulate the findings of the primary analysis.

The study reveals that viewer reactions, imbued with a sense of surprise attributable to both the content’s novelty and the technological innovation, exhibit a strong correlation with increased media engagement. This enhanced engagement significantly influences the viewers’ overall perception of the city, culminating in a marked increase in their intentions to visit Seoul.

The findings have transformative implications for city branding strategies, accentuating the potential of digital outdoor mediums. The study advocates for a paradigm shift that underscores the indispensability of Tecoration in elevating urban brand imagery and catalyzing the broader objectives of smart city metamorphosis, urban tourism rejuvenation and commercial growth trajectories.

The results of this research highlight the transformative potential of digital outdoor media in city branding. The findings suggest a shift in strategy, emphasizing the critical role of Tecoration in enhancing urban brand imagery, driving smart city development, revitalizing urban tourism and fostering commercial growth. This study underscores the strategic importance of integrating Tecoration into the urban branding framework, showcasing its vital contribution to the growth and dynamism of modern cities.

The findings of this study highlight the social implications of integrating Tecoration media in urban environments. By enhancing city branding and tourism through innovative digital signage, cities can foster a more vibrant and attractive urban atmosphere, promoting community pride and engagement. Additionally, the increased visitor traffic can boost local economies and support cultural exchange, contributing to the overall social and economic well-being of urban areas. Strategic use of digital outdoor advertising can also bridge the gap between technological advancements and public spaces, creating more interactive and inclusive urban experiences for residents and tourists alike.

This study embraces a viewer-centric perspective, delving into the relatively uncharted realms of surprise and media engagement within the digital consumption landscape. By adopting this innovative angle, the research significantly deepens the comprehension of viewer experiences and broadens the academic boundaries concerning city branding and media effect frameworks in management literature.

After the COVID-19 outbreak began, travel demand dropped sharply and the potential impact of COVID-19 on sharing accommodations appears to be significant. Thus, it would be meaningful to investigate how travelers have changed their perceptions of staying at sharing accommodations in the wake of the coronavirus pandemic. The purpose of this research was to compare consumers' perceived risks of using sharing accommodations, such as Airbnb, before and during the coronavirus pandemic.

Paired sample t-tests were applied, using two surveys collected in 2017 (pre-pandemic) and 2020 (peri-pandemic). The effects of stress levels from COVID-19 and previous experience with sharing lodging services on risk perception changes were also examined.

Consumers showed higher social, physical, performance and convenience risk perceptions during the pandemic. Not surprisingly, those respondents who were more conscious of the pandemic in terms of concern and anxiety had higher changes in their risk perceptions. In addition, changes in risk perception differed by consumers' usage experience.

The results of this study add to the body of knowledge about consumers' risk perceptions of the sharing economy, particularly in connection with a huge disruption such as the COVID-19 pandemic.

The maritime freight transportation industry has played an important role in the Korean economy. The Korean maritime freight transportation industry is faced with a period of transforming it competitively and efficiently in this global age. This paper, therefore, aims to identify the impact of the maritime freight transportation industry in the Korean national economy. Hence, this paper provides policy-makers with accessible and reliable information regarding the role of the Korean maritime freight transportation industry. This study employs input-output (I-O) analysis to examine the role of the maritime freight transportation industry in the national economy for the period 1995-2003, with specific application to Korea. This study pays particular attention to the maritime freight transportation industry by taking the industry as exogenous variable and then investigates its economic impacts. We identify inter-industry linkage effects in 20 sectors, production-inducing effects, added value-inducing effects, and supply-shortage effects of the maritime freight transportation industry.

The purpose of this paper is to develop an integrated model for manpower forecasting for the information security (IS) industry, one of the fastest growing IT‐related industries. The proposed model incorporates three critical factors (feedback structure, time lags, and a flexible saturation point) in a system dynamics (SD) simulation frame.

A simulation model using SD is developed for a dynamic manpower forecasting by decomposing complex processes of manpower planning into a set of feedback loops with a causal‐loop diagram. Data gathered from a Korean Government agency were utilized in the simulation for forecasting the manpower demand and supply in the context of the IS industry.

The simulation results showed an overall IS manpower shortage in the IS industry. Policy alternatives were proposed based on the simulation results. The simulation model was rerun to reflect the various alternatives to achieve a stable manpower balance between demand and supply.

The research provides insights into the development of effective manpower planning at the industry level (macro level), and policies to increase its efficiency and effectiveness. The research model was developed and verified using SD.