• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.492-492
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• 2018

'물발자국(Water Footprint)' 개념은 가상수의 개념이 확장된 것으로 제품 생산과 서비스 전 과정에서 사용된 물의 양을 나타낸다. 따라서 한 국가내의 수자원 총량의 산출 시에 국제 무역을 통해 수출-수입되는 가상수의 양까지 고려하여 국가 물 총합(Water Budget)을 계산한다. 본 연구는 가상수의 수자원 활용에 관한 산업적 차원의 비교를 위하여 산업별 물발자국 산정모델을 구축하고자 하였다. 산업별 물발자국을 산정하기 위하여 첫째, 산업별 용수사용량에 기초하여 물발자국을 산정하였고, 둘째, 단위 물발자국에 기초하여 산업별 물발자국을 산정하였다. 먼저 산업별 용수사용량에 기초한 물발자국 산정은 하향식 접근법을 적용하였다. 국가 산업별 물발자국을 산정한 결과, 산업 전체 물발자국은 약 330억$m^3$이며 그 중 농업계가 연간 118.8억$m^3$으로 전체 물발자국의 36%를 차지하였다. 그 다음은 생활계로 전체의 34%인 111억 4천만$m^3$이다. 축산계의 물 사용량은 연간 2억 6천 7백만$m^3$ 정도이지만, 오염물질을 정화하는데 필요한 물인 회색수의 양이 많아 물발자국이 73억 $m^3$으로 비교적 높게 산정되었다. 공업계의 가상수량은 연간 26억$m^3$으로 타 산업에 비하여 오염부하량이 높지 않아 회색수량이 작게 나타났다. 다음으로 단위 물발자국에 기초하여 산업별 물발자국을 산정하였다. 단위 물발자국과 생산량을 활용하여 산정하는 상향식 접근법을 활용하였다. 1980년대부터 2014년까지 쌀 외 18개 품목에 대한 농산물 생산의 물발자국을 산정한 결과, 전체 물발자국은 평균 90억$m^3$으로 추정되었다. 한편, 2차 산업의 물발자국은 산업연관분석을 활용하여 산정하였다. 산업연관분석을 위하여 한국은행의 산업연관표와 경제총조사의 용수비 항목을 활용하였다. 2차 산업의 총 물발자국을 산정한 결과, 60억 $m^3$으로 추정되었다. 3차 산업의 물발자국도 이와 동일한 방식으로 산업연관표를 활용하여 산정하였다. 산업연관분석을 활용한 3차 산업의 물발자국 산정한 결과, 숙박 및 음식점업에서의 물발자국이 가장 큰 것으로 산정되었다. 이에 따라 Case Study로서 국내 워터파크 대상으로 물발자국을 산정하였다. 자료가 없는 부분을 제외하고 연간 총 840만 $m^3$의 물발자국을 가지는 것으로 나타났으며, 이 중 직접수는 70만 $m^3$, 간접수는 770만 $m^3$으로 간접수의 비율이 92%를 차지하였다.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.3
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• pp.281-298
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• 2022

The COVID-19 pandemic has so far given the world a great shock and fear that cannot be compared to other infectious diseases, and local economies are experiencing a serious economic crisis accordingly. This paper examines the regional characteristics of economic recession and resilience due to the COVID-19 pandemic, focusing on the employment fluctuations in 85 cities nationwide. Although the overall trend is in line with national employment indicators, there are some differences in the shock response and the recovery of employment in individual cities. The difference between cities is somewhat greater in the resilience of the recovery stage than the resistance, which is the shock-response stage. In terms of resilience, cities in the capital area have relatively good condition compared to cities in the non-capital area. The weak resilience of large cities such as Seoul, which has a high population density, can be explained to be the effect of the COVID-19 pandemic of infectious diseases. Regarding the economic structure of the city, the ratio of service and sales workers, wholesalers and retailers, and food and lodging businesses are analyzed as valid explanatory variables for the resilience of cities.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.385-396
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• 2009

Non-household unit water use for each type of business are estimated in this study. The business types are subdivided into forty based on nine categories by the national industrial standard classification, such as office, commerce, public bathing, public water use etc. Correlation analysis and analysis of variance (ANOVA) are applied to obtain statistical characteristics between industrial water use data, surveyed in six cities including Nonsan, Seosan and the National Statistical Bureau and site area, employees number etc. for each detailed business area. As the proposed non-household unit water uses are compared with five surveyed data in USA, it is shown that almost of water uses per unit area are less than those in USA. Non-household unit water uses of 25% cumulative probability water use recommended as efficiency benchmarks among surveyed data in Korea are also less than those in USA. Especially, in the case of water use in school, the average and the range are similar results showing water use range between 0.4 and 6.2 ($l/m^2/day$) as liter per capita day per an unit area, also water use range between 11.9 to 64.0 (l/student/day) as liter per capita day per a person. From the result of correlation analysis with internal and exogenous affecting factors on non-household water use, it can be concluded that a unit area is most appropriate factor as a standard of non-household unit water use. In case of water use in educational business, the number of students including staffs is more correlated than site ares with water use for the settled water consumption tendency. Although the increase and decrease of educational institutes, retail/wholesale store and restaurants are shown remarkable by the temperature as a representative factor, low correlations are shown in water use fluctuation in lodging house and hospital.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• Korean Security Journal
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• no.36
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• pp.387-416
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• 2013

This study's purpose is to present the improvement of effectiveness of security activity for international conference which can be held hereafter. On the basis of security activity problems originating in G20 summit meeding that had been held in Seoul in 2010. I made up questions three times to on the members of the police, military, fire figher and national intelligence service who had experienced in Seoul G20 summit meeding and recognition of possible problem and possibility of improvement on each item of questions was analyzed by Delphi Method. Also interviews with 4 security experts selected from each security agency were conducted to present improvement in each part of problem. The results obtained from the face to face interview with four experts of security-enforcement agency about the role of event site activity stage for international conference are as followings; First, 'security protocol section' protocol and security are needed mutual win-win enough to be compared with adaptative relationship, thereby being demanded the closer cooperation and information exchange. Second, 'situation management section' there is a need of reinforcing the cooperative system between situation rooms of each agency in order to possibly operate all of the security manpower integrally, which are dispersed by function and by event site, in addition to the swift and organic information exchange between wide-area local government and all the security agencies focusing on a preparation planning group. Third, 'security manpower resource management section' there is a need of encouragement and interest in the leadership in order to devise system that all of the security manpower can concentrate on event and to be possibly satisfied the given conditions. Fourth, 'local government cooperative support section' the wide-area local government of a hosting city as international city operates several kinds of the facilities for international conference, supports operation of conference, achieves a ripple effect of event such as tourism, maximizes service of accomodations, and performs the primary responsibility for the maintenance of the traffic facilities, thereby needing to execute special inspection under the responsibility of Si-Do governors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.4
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• pp.71-102
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• 2007

There were many comprehensive analyses conducted within the existing research activities wherein factors affecting technology progress including investment in R&D vis-${\Box}$-vis their influences act as the determinants of TFP. Note, however, that there were few comprehensive analysis in the industrial research performed regarding the impact of the economy of scale as it affects TFP; most of these research studies dealt with the analysis of the non -parametric Malmquist productivity index or used the stochastic frontier production function models. No comprehensive analysis on the impacts of individual independent variables affecting TFP was performed. Therefore, this study obtained the TFP increase rate of each industry by analyzing the factors of the existing growth accounting equation and comprehensively analyzed the TFP determinants by constructing a comprehensive analysis model considering the investment in R&D and economy of scale (smallness by industry) as the influencers of TFP by industry. First, for the TFP increase rate of the 15 industries as a whole, the annual average increase rate for 1993${\sim}$ 1997 was approximately 3.8% only; during 1999${\sim}$ 2000 following the foreign exchange crisis, however, the annual increase rate rose to approximately 7.8%. By industry, the annual average increase rate of TFP between 1993 and 2000 stood at 11.6%, the highest in the electrical and electronic equipment manufacturing business and IT manufacturing sector. In contrast, a -0.4% increase rate was recorded in the furniture and other product manufacturing sectors. In the case of the service industry, the TFP increase rate was 7.3% in the transportation, warehousing, and communication sectors. This is much higher than the 2.9% posted in the electricity, water, and gas sectors and -3.7% recorded in the wholesale, food, and hotel businesses. The results of the comprehensive analysis conducted on the determinants of TFP showed that the correlations between R&D and TFP in general were positive (+) correlations whose significance has yet to be validated; in the model where the self-employed and unpaid family workers were used as proxy variables indicating the smallness of industry out of the total number of workers, however, significant negative (-) correlations were noted. On the other hand, the estimation factors of variables surrogating the smallness of scale in each industry showed that a consistently high "smallness of scale" in an industry means a decrease in the increase rate of TFP in the same industry.

• Korean Journal of Social Welfare
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• v.53
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• pp.285-310
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• 2003

As National Pension Scheme for all nation complete in 1999 through expanding application in cities, the public pension including Public Occupational Pension became main axis of old-age income maintenance. After 4years since then, now, it is only half of total National Pension insured persons who have been qualified to receive pension through participate and contribution. The other half of National Pension insured is left the excluded from public pension. This paper is intended to identify scale and characteristics of the excluded from public pension and to analysis its cause, and to explore policy measures for solving the excluded's problem. for current recipients over 60 years old generation, the its excluded's scale is no less than 86% of the old over 60 years. The probability of getting in the excluded is high in case of old elderly and female for current elderly generation. For future recipients 18-59 years working generation, the its excluded's scale is no less than 61% of the 18-59 years total population. The probability of getting in the excluded is high in case of 18-29 years and female for current working generation. As logistic regression analysis determinant factor of paying or not pension contribution for future recipients, it appear that probability of getting in the excluded for current working generation is high in case of younger old, lower education attainment, irregular employee, working at agriculture forestry fishery sector, construction sector, wholesale retail trade restaurants hotels sector, financial institution and insurance real estate renting and leasing sector in comparison with manufacturing sector, occpaying at elementary occupation, professionals technicians and associate professionals, sale and service workers, plant machine operators and assemblers, legislators senior officials and managers in comparison with clerks. The Policy measures for the current recipient old generation have need to reinforce supplemental role of Senior's pension(non-contribution pension) until maturing of public pension, because of no having chance of public pension participants for them. And the Policy measures for the future recipient working generation have need to restructure social security fundamentally corresponding with social-economic change as labour market and family structure etc. The pension system has need to change from one earner one pension to one citizen one pension with citizenship rights. At this point, public pension have need to manage with combining insurance's contribution principle and citizenship principle financing by taxes. Then public pension will become substantially universal social network for old-age income maintenance and we can find real solution for the excluded from.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.43-50
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• 2016

Urbanization in Korea has increased significantly and subsequently, various facilities have been concentrated in urban areas at high speed in accordance with a growing urban population. Accordingly, damages have occurred due to a variety of disasters. In particular, fire damage among the social disasters caused the most severe damage in urban areas along with traffic accidents. 44,432 cases of fire occurred in 2015 in Korea. Due to these accidents, 253 were killed and property damage of 4,50 billion won was generated. However, despite the efforts to reduce a variety of damage, fire danger still remains high. In this regard, this study collected fire data, generated from 2007 to 2014 through the Jinju Fire Department and the National Fire Data System(NFDS) and calculated fire risk by analyzing the clustering of fire cases and facilities in Jinju-si based on the current DB of facilities, offered by the Ministry of Government Administration and Home Affairs. As a result, the risk ratings of fire occurrence were classified as four stages under the standards of the US Society of Fire Protection Engineers(SEPE). Business facilities, entertainment facilities, and automobile facilities were classified as the highest A grade, detached houses, Apartment houses, education facilities, sales facilities, accommodation, set of facilities, medical facilities, industrial facilities, and life service facilities were classified as U grade, and other facilities were classified as EU grade. Finally, hazardous production facilities were classified as BEU grade, the lowest grade. In addition, in the case of setting the standard with loss of life, the highest risk facility was the hazardous production facilities, while in the case of setting the standard with property damage, a set of facilities and industrial facilities showed the highest risk. In this regard, this study is expected to be effectively utilized to establish the fire reduction measures against facilities, distributed in urban space by calculating risk grades regarding the generation frequency, casualties, and property damage, through the classification of fire, occurred in the city, according to the facilities.

• Journal of Distribution Science
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• v.9 no.2
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• pp.111-122
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• 2011

The purpose of this study is to survey the successful cases of small and medium Business Systematization Cognition by examining their entrepreneurial characteristics and analysing the factors affecting their success. To that end, previous studies on the association types of small businesses were studied. A research model was developed, and research hypotheses for an empirical analysis were established upon it. Suh et al. (2010) insist on the importance of Small Business Systematization in Korea but also show that small business performance is suffering: they are too small to stand alone. That is why association is so crucial for them: they must stand together. Unfortunately, association is difficult, as they have few specific links and little motivation. Even in franchising networks, association tends to be initiated by big franchisers, not small ones. In that sense, association among small businesses is crucial for their long-term survival. With this in mind, this study examines how they think and feel about the issue of 'Industrial Classification', how important Industrial Classification is to their business success, and what kinds of problems it raises in the markets. This study seeks the different cognitions among the association types of small businesses from the perspectives of participation motivation, systematization expectation, policy demand level, and management performance. We assume that different industrial classification types of small businesses will have different cognitions concerning these factors. There are four basic industrial classification types of small businesses: retail sales, restaurant, service, and manufacturing. To date, most of the studies in this area have focused on collecting data on the external environments of small businesses or performing statistical analyses on their status. In this study, we surveyed 4 market areas in Busan, Masan, and Changwon in Korea, where business associations consist of merchants, shop owners, and traders. We surveyed 330 shops and merchants by sending a questionnaire or visiting. Finally, 268 questionnaires were collected and used for the analysis. An ANOVA, T-test, and regression analyses were conducted to test the research hypotheses. The results demonstrate that there are differences in cognition depending upon the industrial classification type. Restaurants generally have a higher cognition concerning job offer problems and a lower cognition concerning their competitiveness. Restaurants also depend more on systematization expectation than do the other industrial classification types. On the policy demand level, restaurants have a higher cognition. This study identifies several factors that are contributing to management performance through differences in cognition that depend upon association type: systematization expectation and policy demand level have positive effects on management performance; participation motivation has a negative effect on management performance. We confirm also that the image factors of different cognitions are linked to an awareness of the value of systematization and that these factors show sequential and continual patterns in the course of generating performances. In conclusion, this study carries significant implications in its classifying of small businesses into the four different associational types (retail sales, restaurant, services, and manufacturing). We believe our study to be the first one to conduct an empirical survey in this subject area. More studies in this area will likely use our research frameworks. The data show that regionally based industrial classification associations such as those in rural cities or less developed areas tend to suffer more problems than those in urban areas. Moreover, restaurants suffer more problems than the norm. Most of the problems raised in this study concern the act of 'associating itself'. Most associations have serious difficulties in associating. On the other hand, the area where they have the least policy demand is that of service types. This study contributes to the argument that associating, rather than financial assistance or management consulting, promotes the start-up and managerial performance of small businesses. This study also has some limitations. The main limitation is the number of questionnaires. We could not survey all the industrial classification types across the country because of budget and time limitations. If we had, we could have produced many more useful results and enhanced the precision of our analysis. The history of systemization is very short and the number of industrial classification associations is relatively low in Korea. We should keep in mind, though, that this is very crucial to systemization entrepreneurs starting their businesses, as it can heavily affect their chances of success. Being strongly associated with each other might be critical to the business success of industrial classification members. Thus, the government needs to put more effort and resources into supporting the drive of industrial classification members to become more strongly associated.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.