• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Distribution Science
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• v.9 no.2
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• pp.49-59
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• 2011

A franchise can be said to be the main method of distribution and marketing. It appears to be the future of the retail industry and is one of the world's fastest growing businesses sectors, as many policy reports and research results have acknowledged. Korea's franchise industry began in the 1970s, spread out into many areas (including food services, retail, and the service industry), and has grown by over 10% each year ever since. The industry's influence on the national economy becomes ever greater. Although the size of the franchise industry is expected to grow as it spreads and as the government expands its support, it has not yet attracted much academic interest. Research has so far been very fragmented. The main interest has been the relationship and conflicts between the head offices and the affiliates. No study has yet occurred on whether the concepts of satisfaction and intent to conclude a contract directly affect the success or failure of the affiliates. Few studies have empirically inquired into the demographic characteristics and abilities of the affiliates that significantly affect their results. Domestic franchise industries must prepare to leap from quantitative to qualitative growth. Most important is the need for affiliate headquarters and affiliates to build confidence between them. A friendly and reliable relationship between affiliate headquarters and affiliates will eliminate distrust from the franchise and maintain a healthy franchise system. This study suggests that current and prospective heads of affiliation should concentrate not on attracting affiliates but on investment and techniques of affiliate support. They should work on the reinforcement of brand power, the appropriate affiliate business environment, systematic education/training, taking burdens off the affiliate business persons, consolidating the relationship with the affiliate business persons, marketing mix factors (e.g. products, price conditions, logistics and shipping services, promotion, supervising and supervisor, operation procedures/processes, and material evidence); these all greatly affect the success or failure of the affiliate business. Supporting the affiliates is an important factor that enhances their results and satisfaction and consequently increases the positive recommendations to others and the ratio of recurrent conclusions of contracts, which ultimately generate the growth of the franchises. In addition, it is suggested that prospective franchise founders should make every effort to choose a good head office since the characteristics of the head office greatly influence the success of the affiliates. This study is significant in that it grasps the characteristics of the head office of affiliation and of the affiliates that influence affiliate results in ways not yet academically attempted.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.19-36
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• 2020

The bidding phase for logistics outsourcing services is critical for both shippers and logistics companies. According to the logistics bidding phase, the shipper should provide logistics operation information to logistics companies to resolve uncertainty. In addition, the logistics company can win the contract volume that was placed in the bid by expressing their experience and know-how, and proposing to share the risks and benefits of the shipper's logistics operation. Therefore, it is necessary to examine the factors that can be identified during the bidding phase for logistics outsourcing and how these factors affect the satisfaction of logistics outsourcing services. Based on the factors identified in the preceding studies on logistics outsourcing partnership factors and those on logistics outsourcing determinants, a survey was conducted on experts engaged in logistics companies, performing logistics for domestic shippers and analyzed using Smart-PLS. This study presents the following implications. First, in the logistics bidding phase, the shipper should provide its logistics operation information to logistics firms to resolve uncertainties. Details An in-depth explanation of the operation details will be presented via the bidding presentation, and on-site tours of manufacturing plants and logistics centers should also be carried out if necessary. Second, in the bidding phase, logistics companies should appeal through proposals to their competitiveness, such as experience and knowledge of the logistics of the shipper, and also consider alliances with other logistics companies to supplement their insufficient logistics services. Third, logistics companies should make proposals to share profits and risks through logistics outsourcing during the bidding phase, propose accepting risks from environmental uncertainties of the shipper within its capacity to an acceptable extent, and share the benefits of carrying out the shipper's logistics.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1379-1385
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• 2007

In domestic transitional zone design, there is regulation to prevent generation of irregular substructure behaviors that negatively influence in prevention of plasticity settlement on approach section and contact section as well as relieve overall track rigidity by reducing sectional foundation and track stiffness difference, but design guideline that considers dynamic behavior of transitional track in actual service line is very insignificant. Therefore in this study, characteristics of transitional track dynamic behaviors by substructure stiffness are researched and measured dynamic response of transitional track by substructure stiffness in order to prove correlation between substructure and track and calculate elasticity(stiffness) and track load of transitional track by using measurement and formula to provide basic information for developing design guideline considering dynamic behavior of service line transitional track.

• Journal of the Korean Society for Library and Information Science
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• v.12
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• pp.39-86
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• 1985

The main purpose of the present study is to survey the major iudexing bulletins of national nature in Korea, to define such problem areas as lacunae, duplicates and limitation in coverage in the indexing services currently available in Korea, and to make some suggestions for action for improving the existing indexing services in the light of general principles and the tradition and constraints unique to Korea. The major findings and conclusions reached at this study are summarised as follows: (A) A new indexing bulletin of general nature covering the entire field needs to be created in each of the following fields without an established indexing service available for the outcome of research and development activities in Korea. (1) Philosophy (2) Religion (3) Pure sciences (4) Art (5) Language (6) Literature (7) History (B) A new specialised indexing bulletin needs to be created in each of the following fields where indexing services are heavily utilised but no, or only partial, indexing service is available. (1) Social sciences (a) Statistics (b) Sociology (c) Folklore (d) Military science (2) Pure sciences (a) Mathematics (b) Physics (c) Chemistry (d) Astronomy (e) Geology (f) Mineralogy (g) Life sciences (h) Botany (i) Zoology (3) Applied sciences (a) Medicine (b) Agriculture (c) Civil engineering (d) Architectural engineering (e) Mechanical engineering (f) Electrical engineering (g) Chemical engineering (h) Domestic science (C) Publication of the indexing bulletins suggested in A and B above may be ideally carried on by a qualified and dependable learned society established in the respective fields and designated by the Minister of Education, and should be financially supported from the public fund under the provisions of Art. 27 of the Scientific Research Promotion Act of 1979. (D) The coverage and contents of the four indexing bulletins in the field of banking and financing published by the Library of the Bank of Korea are similar and considerably duplicated. It is, therefore, suggested that the four indexing bulletins are combined in one to form a more comprehensive and efficient bibliographical tool in the field and it is further developed into a general guide to the literature produced in the entire field of economics in Korea by gradually expanding its subject coverage. (E) For the similar reasons stated in D, the Index to the Articles on North Korea and the Catalogue of Theses on North Korea, both publisheds by the Ministry of Unification Library, are suggested to make into one. The Index to the Articles of the Selected North Korean Journals and the Index to the Articles of the North Korean Journals in Microfilm Housed in the Ministry of Unification Library, both published by the same Library, are also suggested to be combined in one. (F) The contents of the Catalogue of the Reports Submitted by Government Officials Who Have Travelled Abroad, published by the National Archives are included in the Index to the Information Materials Related to Government Administration, published by the National Archives. The publication of the former is hardly justified. (G) The contents of the Index to Legal Literature published by the Seoul National University Libraries and those of the Law Section of the Index to Scholastic Works published by the National Central Library are nearly identical. One of the two indexes should cease to be published. (H) Though five indexes are being published in the field of political science and four in the field of public administration, their subject coverage is limited. Naturally, these indexes are little usable to many other researchers in the two fields. A comprehensive index covering all the specialised areas in each field needs to be developed on one or all the existing indexes. (I) It is suggested that the Catalogue of the Scholastic Works on Curricula published by the National Central Library expands its subject coverage to become a more usable and effective index to all the researchers in the field of education. (J) The bimonthly Index to Periodical Articles and the specialised index by subject series published by the National Assembly Library, and the Index to Scholastic Works published by the National Central Library are expected to increase their coverage and frequency of publication to be used more effectively and more efficiently by all users in all fields till the indexing bulletins suggested in this study will fully be available in Korea.

• Korean Journal of Food Science and Technology
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• v.35 no.5
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• pp.818-824
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• 2003

Capillary electrophoresis (CE) and near-infrared spectroscopy (NIRS) were performed to discriminate astragalus roots (Astragalus membranaceus) according to geographical origin (domestic or foreign). Two-hundred-and-four astragalus roots were extracted with 30% methanol in 0.1 M phosphate buffer (pH 2.5) and separated in a uncoated fused-silica $(50\;{\mu}m{\times}27\;cm)$ capillary. Conditions for optimal analysis included: temperature $-45^{\circ}C$, voltage -14 kV, and pressure injection time -8 sec. The optimal separation buffer was 0.1 M phosphate buffer (pH 2.5) containing 40 mM hexane sulfonic acid with 20% 2-methoxy ethanol. Raw NIR spectra were obtained using NIRS, and modified partial least square regression was used to develop the prediction model. The correlation coefficient and standard error of prediction were 0.915 and 14.3%, respectively. Under the optimal conditions established for CE and NIRS, the geographical origins of the astragalus roots were correctly identified in 80 and 97%, respectively. Astragalus roots that were not discriminated by NIRS were correctly discriminated by CE. Hence, CE and NIRS are potential methods for discriminating the geographical origins of astragalus roots that complement one another.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.25-42
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• 2019

The purpose of this study is to analyze the effect of internal competence of small business on the competitive advantage and start-up intention. Through this, which key competence of small business can be proposed for market growth against of large companies that have a great capital power. Also, implications for development direction can be suggested. For this purpose, technology capability, financing capability, marketing capability, and product/service differentiation capability factors were set as independent variables, as well as competitive advantage as a mediating factor, and startup intention to be franchiser as a dependent variable. For the analysis, a structured questionnaires survey was conducted to 276 domestic small business in capital area. The main results are as follows. First, in relation to the internal competency and the competitive advantage of small businesses, it was found that technological capabilities, financing capabilities and product (service) differentiation have a positive effect on competitive advantage. Second, the relationship between the internal capacity of a small entity and startup intention to commercialize a franchiser business indicates that its financing capacity and marketing capabilities have a positive effect on startup intention to commercialize the business, and that competitive advantage has a significant effect on startup intention to commercialize the franchise. Third, competitive advantage was found to mediate the relationship between internal competency and startup intention. Finally, it was shown that the internal capacity of a small business has a regulating effect in relation to its financing capacity, marketing capabilities and startup intention to commercialize the franchise, and that it also had a regulating effect in relation to its relationship with its competitive advantage and franchise suitability. Based on the above results, if small business can take competitive advantage in the market, they also consider startup intention to commercialize a franchiser, in addition, it is expected that one suggestion can be made from an internal capacity perspective required more emphasis on operations and management as an alternative to expanding small businesses' business, including market access measures that can be linked to internal capacity factors of small businesses.