• Journal of Distribution Science
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• v.22 no.7
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• pp.13-22
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• 2024

Purpose: This research is a quantitative study aimed at determining the influence of brand experience and brand image on brand equity through brand loyalty in the distribution in Coworking Space industry. Research design, data and methodology: The analytical method employed in this research is Partial Least Squares Structural Equation Modeling (PLS-SEM). The study utilizes a quantitative approach, with data collected through online questionnaires distributed via Google Forms among Coworking Space users. A total of 68 respondents represent the research population.. The data was analyzed using PLS-SEM to examine the relationships between the variables under investigation. Results: The research findings indicate that brand experience significantly affects both brand loyalty and brand equity. Similarly, brand image significantly influences both brand loyalty and brand equity. Additionally, brand loyalty has a significant impact on brand equity Conclusions: The research findings indicate that brand experience has a significant effect on brand loyalty and brand equity. Brand image significantly affects both brand loyalty and brand equity.Additionally, brand loyalty significantly influences brand equity.

• Analytical Science and Technology
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• v.17 no.6
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• pp.496-513
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• 2004

This study was carried out to evaluate the performance of sampling and analytical methodology used for the measurement of toxic volatile organic compounds (VOCs) in the ambient air. VOCs were determined by the adsorbent tube sampling and automatic thermal desorption coupled with GC/MSD analysis. Target analytes were 33 compounds including major aromatic compounds such as BTEX, and halogenated compounds. The methodology was investigated with a wide range of different adsorbents which are commercially available and have been frequently adopted for the VOC measurement. A total of 10 adsorbents were tested in this study: 6 carbon-based adsorbents such as Carbotrap, Carbopack B, Carbosieve S-III, Carboxen 1000, Carbotrap C, Activated Charcoal; and 4 polymer-based adsorbents including Tenax, Porapak Q, Chromosorb 102, and Chromosorb 106. The sampling performance was evaluated with respect to the sampling capacity of VOCs with single-adsorbent and multiple-adsorbents methods for standard samples and field samples. As a result, the best adsorbents for single-adsorbent method in the sampling of toxic organic compounds (including benzene, toluene, xylenes etc.) appeared to be Carbotrap, Carbopack B and Tenax TA. On the other hand, Chromosorb 102, Chromosorb 106 and Porapak Q were found to be unsuitable adsorbents for VOC measurement based on thermal desorption method. Multi-adsorbent packings were evaluated with 4 carbon-based adsorbents, which classified by 3 combination sets of double adsorbents and 2 combination sets of triple adsorbents. The results indicated that the most suitable combination for toixc VOC measurements is Carbotrap C with Carbotrap. Multi-sorbents tubes packed with a strong adsorbent such as Carbosieve S-III or Carboxen 1000 were found to be relatively unsuitable for several compounds, not only owing to the effect of migration of adsorbed compounds from weaker adsorbent to stronger adsorbent, but to hydrophobic nature of the adsorbents. Therefore, it should be addressed that selection of a proper adsorbent (or combination of multi sorbents) is extremely important to obtain reliable data for the concentrations of toxic VOCs in indoor and outdoor environments.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.149-153
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• 2008

The pollutant capacity occurred before and after the development of a watershed should be quantitatively estimated and controlled for the minimization of water contamination. The Ministry of Environment suggested a guideline for the legal management of nonpoint source from 2006. However, the rational method for the determination of treatment capacity from nonpoint source proposed in the guideline has the problem in the field application because it does not reflect the project based cases and overestimates the pollutant load to be reduced. So, we perform the standard rainfall analysis by analytical probabilistic method for the estimation of an additional pollutant load occurred by a project and suggest a methodology for the estimation of contaminant capacity instead of a simple rational method. The suggested methodology in this study could determine the reasonable capacity and efficiency of a treatment facility through the estimation of pollutant load from nonpoint source and from this we can manage the watershed appropriately. We applied a suggested methodology to the projects of housing land development and a dam construction in the watersheds. When we determine the treatment capacity by a rational method without consideration of the types of projects we should treat the 90% of pollutant capacity occurred by the development and to do so, about 30% of the total cost for the development should be invested for the treatment facility. This requires too big cost and is not realistic. If we use the suggested method the target pollutant capacity to be reduced will be 10 to 30% of the capacity occurred by the development and about 5 to 10% of the total cost can be used. The control of nonpoint source must be performed for the water resources management. However it is not possible to treat the 90% of pollutant load occurred by the development. The proper pollutant capacity from nonpoint source should be estimated and controlled based on various project types and in reality, this is very important for the watershed management. Therefore the results of this study might be more reasonable than the rational method proposed in the Ministry of Environment.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.233-243
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• 2008

Recognition for the importance and roles of public transportation is increasing because of traffic problems in many cities. In spite of this paradigm change, previous researches related with public transportation trip assignment have limits in some aspects. Especially, in case of multimodal public transportation networks, many characters should be considered such as transfers. operational time schedules, waiting time and travel cost. After metropolitan integrated transfer discount system was carried out, transfer trips are increasing among traffic modes and this takes the variation of users' route choices. Moreover, the advent of high-technology public transportation card called smart card, public transportation users' travel information can be recorded automatically and this gives many researchers new analytical methodology for multimodal public transportation networks. In this paper, it is suggested that the methodology for establishment of brand new multimodal public transportation networks based on computer programming methods using transportation card data. First, we propose the building method of integrated transportation networks based on bus and urban railroad stations in order to make full use of travel information from transportation card data. Second, it is offered how to connect the broken transfer links by computer-based programming techniques. This is very helpful to solve the transfer problems that existing transportation networks have. Lastly, we give the methodology for users' paths finding and network establishment among multi-modes in multimodal public transportation networks. By using proposed methodology in this research, it becomes easy to build multimodal public transportation networks with existing bus and urban railroad station coordinates. Also, without extra works including transfer links connection, it is possible to make large-scaled multimodal public transportation networks. In the end, this study can contribute to solve users' paths finding problem among multi-modes which is regarded as an unsolved issue in existing transportation networks.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.57-66
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• 2015

Considerable research efforts are being directed towards analyzing unstructured data such as text files and log files using commercial and noncommercial analytical tools. In particular, researchers are trying to extract meaningful knowledge through text mining in not only business but also many other areas such as politics, economics, and cultural studies. For instance, several studies have examined national pending issues by analyzing large volumes of text on various social issues. However, it is difficult to provide successful information services that can identify R&D documents on specific national pending issues. While users may specify certain keywords relating to national pending issues, they usually fail to retrieve appropriate R&D information primarily due to discrepancies between these terms and the corresponding terms actually used in the R&D documents. Thus, we need an intermediate logic to overcome these discrepancies, also to identify and package appropriate R&D information on specific national pending issues. To address this requirement, three methodologies are proposed in this study-a hybrid methodology for extracting and integrating keywords pertaining to national pending issues, a methodology for packaging R&D information that corresponds to national pending issues, and a methodology for constructing an associative issue network based on relevant R&D information. Data analysis techniques such as text mining, social network analysis, and association rules mining are utilized for establishing these methodologies. As the experiment result, the keyword enhancement rate by the proposed integration methodology reveals to be about 42.8%. For the second objective, three key analyses were conducted and a number of association rules between national pending issue keywords and R&D keywords were derived. The experiment regarding to the third objective, which is issue clustering based on R&D keywords is still in progress and expected to give tangible results in the future.

• Analytical Science and Technology
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• v.22 no.6
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• pp.488-497
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• 2009

In this study, analytical methodology for several organic fatty acids (OFA: propionic acid (PA), butyric acid (BA), isovaleric acid (IA), and valeric acid (VA)) designated as new offensive odorants in Korea (as of year 2010) was investigated along with some odorous VOCs (styrene, toluene, xylene, methyl ethyl ketone, methyl isobutyl ketone, butyl acetate, and isobutyl alcohol). For this purpose, working standards (WS) containing all of these 13 compounds were loaded into adsorption tube filled with Tenax TA, and analyzed by gas chromatography (GC) system thermal desorber interfaced with. The analytical sensitivities of organic fatty acids expressed in terms of detection limit (both in absolute mass (ng) and concentration (ppb)) were lower by 1.5-2 times than other compounds (PA: 0.24 ng (0.16 ppb), BA: 0.19 ng (0.11 ppb), IA: 0.15 ng (0.07 ppb), and VA: 0.28 ng (0.13 ppb)). The precision of BA, IA, and VA, if assessed in terms of relative standard error (RSE), maintained above 5%, while the precison of other compounds were below 5%. The reproducibility of analysis improved with the aid of internal standard calibration (PA: $1.1{\pm}0.4%$, BA: $10{\pm}0.46$, IA; $12{\pm}0.3%$, VA: $4{\pm}0.1%$), respectively. The results of this study showed that organic fatty acid can be analyzed using adsorption tube and thermal desorber in a more reliable way to replace alkali absorption method introduced in the odor prevention law of the Korea Ministry of Environment (KMOE).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.56-62
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• 2009

In this paper we investigate an analytical approach for noise properties and geometric structure in Computed Radiography(CR) images of industrial steel-tubes. Over thirty diverse radiographic images are sampled from industrial radiography measurements according to radiation intensity. Each image consists of three regions; background, thickness and inner-tube. Among these the region of inner-tube is selected for the object of analysis. Geometric structure which includes the noise generation is analyzed by the statistical and functional methodology. The analysis is carried on spacially and line by line. It verifies the geometrical transfigure from the circle configuration of steel-tube and noise variation. The estimation of fitting function and its error are the geometric factors. The statistics such as standard deviation, mean and signal-to-noise ratio are noise parameters for discrimination. These factors are considered under the intensity variation which is the penetrative strength of radiation. The analysing results show that the original geometry of circle is preserved in the form of elliptic or short/long diameter circle, and the noise deviation has increased inverse proportional to the radiation intensity.

• Analytical Science and Technology
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• v.7 no.1
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• pp.53-64
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• 1994

After establishment of methodology for the separation and quantitation of optical isomer existed in food or biomaterial, the relationship between isomer and nutrient or biological sample was investigated. The optical isomers of standard amino acids and free amino acids were quantitized and the protein was assayed from the Korean bean, pasted bean, soy sauce, gochujang, powderd milk and cataract followed by hydrolysis and dervatization with TFA-IPA for GLC analysis with chirasil val column. Amino acids showing the racemization were alanine, aspartic acid, glutamic acid and phenyl alanine. The most convenient amino acid deducing age and biological activity was aspartic acid. Glutamic acid and phenyl alanine have shown poor resolution with less racemization. The ratio of d-form amino acids was 3~6% for home made pasted bean, about 3% for commerical pasted bean, 2~4% for soy sauce, about 1% for bean, 1~2% for cataract, 1.0~1.5% for powdered milk. The racemization during fermentation process was significant.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.12-28
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• 2017

The core of the transportation service, so-called Mobility 4.0 is the flexibility of the entire mobility and its implementation. By doing so, the most essential element is to build a platform to link a supply and a demand simultaneously. In other word, a comprehensive analytical framework is to be set with a data repository which can be periodically updated. With such circumstances, the entire trip chain including pedestrian movements is required to be thoroughly investigated and constructed at the viewpoint of the intermodal transit station. A few studies, however, have been attempted. In this study, the comprehensive analytical framework with the integrated mobility at intermodal transit station was proposed, which consisted of the three modules; 1) Data Repository Extracting from Smart Card DB, 2) Framework of Analyzing Integrated Mobility, and 3) Interpretation of the Integrated Mobility with GIS information and the other factors. A case study with the seven railway stations (Sadang, Sindorom, Samseong, Gwanghwanoon, Gangnam, Jamsil, Seoul Nat'l Univ. of Education) was conducted. The stations of the case study were clustered by the three groups with the statistical ground, and it is most likely to understand the effect of a variety of factors and a comprehensive data-driven analyses with the entire trip stages.