• Asia pacific journal of information systems
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• v.21 no.1
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.193-202
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• 2005

Due to the importance of SCM(Supply Chain management) in business logistics. many studies related to the SCM performance measurement have been conducted. However, previous SCM performance measurement models have not reflected both ways, operational efficiency and response for market shift. The aim of this research is to suggest a dynamic model to measure SCM performance both with operational efficiency and response for market shift, based on previous SCOR model. To achieve this aim, we developed a cognitive map-based model described eleven KPIs (Key Performance Indicators) with different weight values. And, to measure response level for market shift, we used the concept of entropy-elasticities. Finally, through some actual cases, merits that have no previous models were shown.

• Journal of Korea Trade
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• v.26 no.5
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• pp.106-124
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• 2022

Purpose - The increasing share of Korean private label products (PLPs) in the domestic market helped generate lucrative revenue. In recent years, major South Korean retailers have begun to cast their sights on overseas markets and actively export their PLPs. In China, the proportion of private label fresh food (PLFF) is gradually expanding amid the development of the new retailing model. A profound understanding of the relationship between private label fresh produce and purchase intention may be the answer to helping Chinese retailer private labels expand supply chains in Korea. This study, taking Chinese retailers as an example, examines the impacts of selection factors of private label fresh food and perceived value on purchase intention. Apart from that, the relationship between the selection factors and purchase intention will be analyzed with perceived value as a mediator. Design/methodology - This work aims to empirically analyze the purchase intention of private label fresh food using statistical analysis. In this study, a hypothetical causal model consisting of 6 latent variables and 24 measured variables is developed based on the literature review. To validate the research hypotheses and the research model, SPSS23.0/AMOS23.0 is used to analyze factors such as validity and reliability, as well as structural equation modeling. Findings - The hypothetical model established in this study is of general applicability. In respect to PLFF, perceived value, while significantly influencing purchase intention in combination with four selection factors (perceived quality, perceived price, brand trust, and store image), mediates partially between the first three factors and purchase intention, which rules out the impact and mediating effect of store image on purchase intention. Originality/value - These research results, as helpful insights into the present circumstances of Chinese PLFF in the domestic market, provide useful information and guidance for Korean retailers and service providers to innovate production and service, as well as develop marketing and promotion strategies, so that they can shift private label goods with advantages from domestic demand to export, thus increasing overseas profitability. Further, this work will also contribute to relevant research.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.67-80
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• 2020

This study has been conducted at a time when Korean government continues to extend support for youth startups as part of its policy to create jobs and the focus moves from career and employment to youth startups with a growing interest in the field of youth startups. Against this background, this study aims to identify difficulty factors of youth startups in areas besides the Seoul Metropolitan Area, seek ways to overcome difficulty factors, and propose policy implications. To this end, this study set five criteria and 25 sub-criteria to evaluate the difficulties of youth startups by reviewing previous studies and conducting literature review, and performing brainstorming method. The empirical analysis of the evaluation criteria was performed, using the analytic hierarchy process (AHP) method, on youths aged 19 to 39 in Gunsan area. The analysis results showed that the largest difficulty factors facing local youths include business model establishment, business administration and management, and startup funding in the criteria. As for sub-criteria, the largest difficulty factors are market information acquisition, technology commercialization, project feasibility, technology development, and new market pioneering in descending order. Local youths have much difficulty about the process of turning a business item into a product and commercializing it. According to a comparative analysis by gender, men were a relatively high difficulty in commercializing business models than women. men were a relatively high difficulty in commercializing business models than women. On the other hand, women were higher than men in all factors (management management, entrepreneurship, improvement of entrepreneurship system, and improvement of entrepreneurship awareness) except for factors affecting business model. In addition, the factors of entrepreneurship were found to be relatively different among young people (college students, prospective entrepreneurs, entrepreneurs). In conclusion, it was suggested that in order to revitalize youth entrepreneurship in the region, it is necessary to actively resolve the difficulties of business model commercialization rather than entrepreneurship funds. In addition, it is necessary to strategically support customized entrepreneurship support and situational administrative services because gender and hierarchical difficulties are different than general solutions. This study presented practical priorities and derivation methods for the entrepreneurship difficulties faced by local youth, and suggested measures and improvements for vitalizing local youth entrepreneurship in the future.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.13-35
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• 2011

The advancement of the information technology provides a wide range of corporate to cope with new business environments that are different in size, life and operation conditions. The Research methodology used in this study is Technology Acceptance Model. The Study Method are mainly survey and questionnaire. The major result of article can be summarized. Its are as the follows: This paper ware investigated the determinants of 'port service quality', 'perceived usefulness', 'perceived ease of use', 'utilization intention', 'practice use'. There are 400 sended samples and 150 returns, 173 of them are analyzed on a port utilization using TAM model. 1. The Port service quality are found to have a positive effect to 'perceived usefulness', 'perceived ease of use', 'utilization intention' 2. The perceived ease of use are found to have a positive effect to 'perceived usefulness', 'utilization intention' 3. The perceived usefulness is found to be positively related to 'utilization intention' 4. The utilization intention is found to have a positive effect to ''practice use' we hove to provide useful contribution to increase the Korea ports' competitiveness in introduction of port information system. In addition, in order to port development offer some insight in further research.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.5
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• pp.87-102
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• 2018

The purpose of this study is to determine the impact of food service franchise's support system on franchisee's trust, financial performance and intention of multi-store operation. For this purpose, the results of the survey were collected for 111 small and mid-sized food service franchisees in Korea with less than 100 brand franchises, referring to article 9 of the act on Fair Trade. Structural equation model analysis was used for hypothesis testing. The results of the study are as follows; First, a support for store development, education, logistics, and supervisors among franchise's support system were found to have a significant impact on the franchisee's trust, but public relations support was not significantly affected. Second, a support for store development had significant influence on the financial performance, but the support for education, logistics, supervisors and public relations did not significantly affect the financial performance. Third, franchisee's trust has been shown to have a significant impact on financial performance and intention of multi-store operation. Fourth, financial performance was shown to have a significant impact on the intention of multi-store operation. Finally, confirming the mediated effects of financial performance on the effect of franchisee's trust and intention of multi-store operations also proved to have indirect effects. This study identified the impact relationship between the small and medium-sized food service franchise support system, franchisee's trust, financial performance and intention of multi-store operation. In particular, it is deemed meaningful that the performance of Korea's small and medium-sized food service franchises and the relationship of influence that can grow together through the qualitative growth of the franchise's system.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.204-209
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• 2012

본 논문은 전국적인 소매업체의 각 지점별 고객 수요가 불확실한 상황에서 고객 서비스 목표 수준을 충족하는 최적재고 수준을 결정하는 문제에 대해 연구하였다. 이를 위해 전국에 분포한 지점에서 물품을 판매하는 베스트바이, 월마트, 혹은 시어스와 같은 전국적인 소매업체 관점에서 사용할 수 있는 핵심 관리 지표(KPI)로서 ISR(In-Stock Ratio)를 정의하였으며, 전국적인 소매업체가 평균 ISR로 정의되는 고객 서비스 목표 수준을 충족하면서 각 지점 보유 재고의 총합을 최소화할 수 있는 최적화 모델을 수립하였다. 본 논문은 해당 모델에 항상 최적해가 존재함을 증명하고 해당 최적해를 Karush-Kuhn-Tucker 조건을 사용하여 고객 수요의 확률분포의 형태에 상관없이 일반화된 형태로 표현하였다. 또한 본 논문은 고객 수요가 정규분포와 같은 특정 확률분포를 따르는 경우에 대해 연구하였으며, 이 경우에 대한 최적 재고수준을 나타내는 식을 도출하였다. 마지막으로 본 논문에서는 상기 기술된 상황에 대한 수리적인 예제를 통하여 최적재고 수준과 확률분포 파라미터들간의 관계를 분석하였다.

• IE interfaces
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• v.22 no.2
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• pp.153-164
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• 2009

An effective management for reverse flows of products such as reuse, repair and disposal, has become an important issue for every aspect of business. In this paper, we study the Location-Routing Problem (LRP) in the multi-stage closed-loop supply chain network. The closed-loop supply chain in this study integrated both forward and reverse flows. In forward flow, a factory, Distribution Center (DC) and retailer are considered as usual. Additionally in reverse flow, we consider the Central Returns collection Center (CRC) and disposal facility. We propose a mixed integer programming model for the design of closed-loop supply chain integrating both forward and reverse flows. Since the LRP belongs to an NP-hard problem, we suggest a heuristic algorithm based on genetic algorithm. For some test problems, we found the optimal locations and routes by changing the numbers of retailers and facility candidates. Furthermore, we compare the efficiencies between open-loop and closed-loop supply chain networks. The results show that the closed-loop design is better than the open one in respect to the total routing distance and cost. This phenomenon enlarges the cut down effect on cost as an experimental space become larger.

• Journal of Distribution Science
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• v.21 no.5
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• pp.31-41
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• 2023

Purpose: Electric vehicle (EV) technology started in 2015 in Thailand. The Thai Government has indicated that 30% of all cars produced in Thailand by 2025 will be EVs. Using EVs in Thailand will reduce road pollution and increase energy efficiency, especially in major cities. Hence, the adoption of EVs in the country has been promoted. This study pointed out that social influence, facilitating conditions, perceived enjoyment, environmental concern, attitude, and perceived behavioral control are key factors affecting the behavioral intention to adopt EVs among logistic and distribution firms in Thailand. Research design, data, and methodology: 500 top management, middle management and purchasing managers of logistic and distribution firms in Thailand are surveyed. The study employed judgmental, convenience, and snowball sampling. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) are the main statistical tools for data analysis. Results: The results show that all determinants impact customers' willingness to adopt EVs, except perceived enjoyment and environmental control. Conclusions: The study proposes to promote the incentives by decreasing electricity prices and endorsing EVs purchase to accelerate the adoption of EVs in Thailand. Therefore, future policies should focus on behavioral intention toward EVs amongst logistic and distribution firms for enhancing the future of mobility in Thailand.