• Industry Promotion Research
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• v.8 no.4
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• pp.221-227
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• 2023

This study is a study to analyze Nativity's occupational aptitude by examining the functions and structures of the planets that make up the Nativity birth chart of Classic Astrology. If the occupation that appears in the birth chart is viewed as an individual's natural occupation, it is analyzed through the strength and weakness of the sign and planets, and the aspect (relationship with the planet). In Classic Astrology's nativity birth chart, there are three major planets when judging occupations: Venus (♀). Mars (♂). It was thought to be determined by Mercury (☿). However, in order to meet the diversity of jobs required in today's highly developed knowledge and information society, there are some shortcomings, so Saturn (♄), Jupiter (♃), Sun (☉), Moon (☽) was added to apply the aptitude for the job. Thus, the native's ASC vocational aptitude could be applied more diversely and broadly based on the relationship between planets and their aspects. As a result, Venus (♀. Venus) means enjoying artistic work that people think is beautiful and making it a pleasure in life, while Mars (♂) means work that requires physical strength and strength, such as working days. Mercury (☿) means using knowledge and brains, and the Sun (☉) plays a role in giving authority to jobs and talents. The Moon (☽) helps the native gain people's trust in his or her profession and talents, Jupiter (♃) helps the native to revive his or her profession and talents through faith, sincerity, fairness, and generosity, and Saturn (♄) can appear as an obstacle that blocks career and talent due to greed, sadness, poverty, etc. As a result of the study, it was found that the native's occupations vary depending on the strengths and weaknesses of the planets and their aspect relationships.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korean Society for Library and Information Science
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• v.20
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• pp.65-125
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• 1991

The study has tried to analize and appraise how did public library system under the Japanese imperialism affect the establishment and managemant of Korean public libraries. To achieve the purpose of the above-mentioned study, the contents of $\ulcorner$Japanese library statute$\lrcorner$ under Japanese imperialism and the current $\ulcorner$Korean library law$\lrcorner$ have been mutually compared, at the same time, the vestiage of Japanese imperialism in view of the establishment, personnel administration and reading systems have been concretely investigated, analyzed and compared. The conclusions obtained from the above are as followings. 1. In those days of the Korean Liberation, the situation of Korean public libraries was such as it under the Japanese rule and so, their names were only changed. However, as a part of its independent activities, the national library have once carried out the various programs such as the training of professional librarians, the establishment of the new classification schedule and the chief Librarian and deputy Librarian from the professional librarians in the office regulations, and they were well worth being the good examples for today's Korean library circle. Though the Goverment of the Republic of Korea had been formally established, the situation of the library circle was very dull owing to the Korean war for a long time. In 1963, $\ulcorner$The Korean library law$\lrcorner$ was promulgated, but the establishment of public libraries did not give satisfactory results because of the institutional fragility. In the 1980's the importance of library was embossed from the viewpoint of life-long education and the number of libraries was increased. However, there were still the remaining vestiges of Japanese library system in the practical library services. 2. After the Korean Liberation, the influnces of public library system under the Japanese imperialism showed in the office regulation of national library and the Korea library Law were also in the legal mechanism. In particular, the regulations of $\ulcorner$The staff-member of public library$\lrcorner$ and $\ulcorner$Admission fee of public library$\lrcorner$ including the chief librarian have referred to the library system under the Japanese imperialism since the liberation day to date. 3. At that time of the Korean Liberation, the U.S.Military Government Office had decided that the public library administration should be attached to the administration of local and internal affairs in accordance with the Japanese administative system. As a result, the public libraries had been forced to be indirectly affected by public library system under the Japanese imperialism for twenty years since the Liberation. 4. Since the Liberation, the personnel adminstration of public library has been so far on the steps of model under the Japanese imperialism. As the result of the field survey, the position standards of local chief librarians, non-professional character, the extra post system and the preponderant appointment of non-professional offices have analyzed by the influence of Public library system under the Japanese imperialism. Therefore, the Government authorities-concerned must readjust the standards of qualification and the divided duties corresponding to the position of public library staff members and to stipulate expressly in the revised library law. In addition, the regulation of the admission fee should be also actively detected for the free adminssion of library users. 5. Since the Liberation Day, the reading methods of public library have been so far similar to reading method under the Japaness imperialism. For example, the admission fee levied, the complicated procedures of using books including entrance and exit of a library, no-admission system, the limited lending books, the deposit system of outdoor lending books and the surety liable jointly and severally are originally caused by bureaucracy of under the Japanese imperialism. Therefore, the public libraries should make an offer space and opportunities which can enjoy freedom to the gull in future. The procedures and standards of library users will be simplified, if possible. As the above-mentioned, the actual conditions of Korean public libraries have been examined and analyzed. As the result of it, there are still the remaining vestiges of public library system under the Japanese imperialism in the establishment and management of the nation-wide public libraries. Such the remnants are an obstacle to the democratic development of public libraries and so, the authorities-concerned should take the proper-measures as soon as possible.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.199-230
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• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• 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 Environmental Health Sciences
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• v.18 no.2
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• pp.3-18
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• 1992

This research was carried out on 1,017 production workers for four months from May to August, 1991, to search more effective management method of their health by grasping their knowledge and attitude on industrial health. The results of this study can be summarized as follows: 1. As for general characteristics, 74.2% were male and 25.8% were female among the 1,017 workers. The two largest age groups were 30~39, 38.7%. As for education level, graduation from high school was 58.6%, 61.2% were married, 35.9% owned their house, and workers who worked more than 1 year less than 5 years was 52.9%, workers who worked 8 hours a day was 46.7%, the largest group income level was 60~69 thousand won 21.2%, and the degree of satisfaction with work was ordinary, 45.6%. 2. The degree of recognition concerning occupational diseases was 92.5% at a very high rate. Causes of occupational diseases under the present work field were in order of noise, dust, heavy metal. The largest group of the counterplan for prevention was an improvement of working environment, 62.0%. 3. The major cause that threatens worker's health was poor working environment, 31.4%. As the best method for workers' health management, working environment management was pointed. 4. As for health examination result, the response that it is of use to health management was 53.8%. As for examination method and result, 42.7% responded that they are formal. The practice period was more than once every six months as the largest group, and the highest desire for improvement was that they wants an exact information of the result. 5. 49.3% of the respondents know about the measurement of working environment an the response that the measurement is necessary to improve working environment was 57.9%, and that the results from the measurement were reflected on improvement an management 57.5%. Appropriate period to take a measurement was more than once per six months, 40.2% and per three months, 29.1%. 6. As for safety and halth instruction, 34.5% were educated for both, 38.2% for only safety education and just 4.6% for only health education. 51.9% responded that they had never been educated out of work place. The period of its practice was more than once a month, 39.5% and every three months, 21.3%. 7. The importance of safety and health showed that the one is equal to the other, 59.8%, that the one is more important, 29.6%, and that other is more important, 7.6%. 67.7% said the necessity of a safety and health manager. 8. In spite of more or less health obstacle of work environment, 14.9% of the respondents wanted to overwork to gain an allowance for over-time work, 39.9% didn't, and 40.2% according to condition and state. 9. As the most important cause of industrial accident, 40.2% indicated unsafe behavior. As for the individual protective instrument, 66.1% of all the respondents said they have worn it to protect industrial diseases. 10. As for the degree of understanding of the contents in Industrial Safety and Health Law and Industrial Law of Accident Insurance, an affirmative response was respectively 49.3% and 50.8% and the sources of safety-health information were televisions and radios, 28.0%. Therefore, it is necessary that we do positive working environmental improvement, continuous management and health education's inforcement to increase their health and prevent occupational diseases.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.93-99
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• 2010

Purpose: Currently, PET/CT scan has been known to provide useful information to both preoperative and postoperative examination of cancer patients. Contracted stomach by the long fasting could cause difficulties of interpretation because of its size on reconstructed image data. To solve this problem, after the whole body PET/CT scan, patients were administrated in drinking 300 mL of water to expand stomach and performed additional scan on stomach region. Not only PET/CT scan but also CT performs this water-administration, and patients were take oral solution to make stomach expand for stomach cancer. When this scan performed, patients lay supine position. In this study, we evaluated the capacity of stomach through PET/CT scan with drinking water performed in supine and prone position so that we can distinguish exact location of cancer around pylorus and inferior wall of stomach. Furthermore, image data from supine and prone positions were analyzed the difference of volume of stomach through the change of standardized uptake values. Materials and Methods: From July 2009 to January 2010 in severance hospital, 30 patients who were diagnosed as early gastric cancer or advanced gastric cancer were chosen. All patients had PET/CT scan before the operation and have had follow-up PET/CT. The patients fast for at least 8 hours, and had an injection intravenously with $^{18}F$-FDG, 7.4 MBq (0.2 mCi/kg) per kilogram. They were rested for 60 minutes. Before the examination, all patients were administrated to drink water for 300 mL Patients had PET/CT scan with supine position around the region of stomach, whole body, and around the region of stomach with prone position after drinking another 300 mL of water respectively. Results: As a results of comparison between stomach capacity of 30 patients in supine and prone position, the study draw results that average capacity of stomach body was 460.29 $mm^2$ in supine position, and 641.39 $mm^2$ in prone position for 30 patients. The change of capacity shows 41.3% expanded in prone position. And there was no noticeable difference at maximum standardized uptake values in supine position and prone position. Conclusion: As results, stomach would have more expanded capacity in prone position than supine position. For patients who have physical disabilities to move freely, additional scan in prone position will be obstacle to perform. However, if additional scan in supine position add with the scan in prone position, it will be easier to diagnose stomach cancer. Moreover, we believe that this study will help the research for inventing support tools for patients who have physical disabilities in prone position.

• 한국벤처창업학회:학술대회논문집
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• 2006.04a
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• pp.45-75
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• 2006

How much influence does a business plan have on a corporate performance? Whilst previous studies and literatures all assert a strong correlation between the two, very few have actually conducted practical analyses to support that. This study takes an empirical approach in its analysis of Korea' s small and medium-sized enterprises (SME) with the view to finding an answer to the question. A business plan' s components, which have to date been suggested only in theory and in concept, have been selected through the study of literatures and preliminary examination. The selected components were then narrowed down into five factors of productivity, implementation, operational direction, product/service and customer accessibility by applying factor analysis. With which items to measure corporate performance is also an important question as results differ depending on which measurement items were used. For the purpose of this study, corporate performance was classified into effectiveness, adaptability and efficiency to measure how greatly each is influenced by the components of a business plan. Results show that effectiveness and adaptability have a positive (+) influence on corporate performance. The regression model seems to explain effectiveness particularly well. However, different directions of influences were showed in explain power of the research model were not high. And it can be interpreted that implementation of the plan is as important as the establishment of it. Thus a good corporate performance is to be had only under an excellent plan and following an excellent implementation. In most of the companies surveyed, business plans were established regularly led by the intense involvement of the CEO. Such plans were then used in internal operations, such as guiding operational direction and measuring corporate performance. Unlike general expectations, relatively few companies used them in financing from external sources such as banks or venture capitals. These findings are different from previous studies conducted in this field. Also, as market uncertainty was pointed out as the biggest obstacle to business planning. a manager must pay more attention to acquiring external information and knowledge so as to minimize it.