• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.4
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• pp.459-468
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• 2013

In the application of the ecosystem-based fisheries assessment Jeonnam marine ranching ecosystem, two fisheries, funnel fishery and trap fishery, were selected as target fisheries. Black seabream, Acanthopagru schlegelii, rock bream, Sebastes inermis, gray mullet, Mugil cephalus, were selected as target species for the funnel fishery, and conger eel, Conger myriaster, was target species for the trap fishery. For assessing indicators of four management objectives, that is the maintenance of sustainability, biodiversity, habitat quality and socio-economic benefits, indicators were selected considering the availability of data, which were 5 indicators for sustainability, 3 indicators for biodiversity, 4 indicators for habitat, 2 indicators for socio-economic benefit. The Objective risk indices for sustainability and biodiversity of two fisheries were estimated at yellow zone, medium risk level. The objective risk indices for habitat and socio-economic benefit were estimated at green zone, safe level. The species risk indices (SRI) were estimated at yellow zone. The fishery risk indices (FRIs) were estimated at 1.143 and 1.400 for funnel net fishery and trap fishery, respectively. Finally the ecosystem risk index estimated at 1.184.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.15-22
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• 2020

Economic indicators are a factor that affects air cargo volume. This study analyzes the different factors affecting air cargo volume by each Chinese cities according to the main characteristics. The purpose of this study is to help companies related to China, airlines, and other stakeholders predict and prepare for the fluctuations in air cargo volume and make optimal decisions. To this end, 20 economic data were used, and the entire data was reduced to 5 dimensions through factor analysis to build a dataset necessary and evaluated the influencing factors by multi regression. The result shows that Macro-Economic Indicators, Production/Service indicators are significant for every cities and Chinese manufacture/Customer indicators, Korean manufacture/Oil Price indicators, Trade/Current indicators are significant for each other city. All adjusted R2 values are high enough to explain our model and the result showed excellent performance in terms of analyzing the different factors which affects air cargo volume. If companies that are currently doing business with China can identify factors affecting China's cargo volume, they can be flexible in response to changes in plans such as plans to enter China, production plans and inventory management, and marketing strategies, which can be of great help in terms of corporate operations.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.125-135
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• 2022

This study aims to explore variables using machine learning and provide analysis techniques suitable for predicting pharmacy sales whether government statistical indicators built to create an industrial ecosystem based on data, network, and artificial intelligence affect pharmacy sales. Therefore, this study explored predictive variables and performance through machine learning techniques such as Random Forest, XGBoost, LightGBM, and CatBoost using analysis data from January 2016 to December 2021 for 28 government statistical indicators and pharmacies in the retail sector. As a result of the analysis, economic sentiment index, economic accompanying index circulation change, and consumer sentiment index, which are economic indicators, were found to be important variables affecting pharmacy sales. As a result of examining the indicators MAE, MSE, and RMSE for regression performance, random forests showed the best performance than XGBoost, LightGBM, and CatBoost. Therefore, this study presented variables and optimal machine learning techniques that affect pharmacy sales based on machine learning results, and proposed several implications and follow-up studies.

• Journal of People, Plants, and Environment
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• v.24 no.3
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• pp.245-256
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• 2021

Background and objective: The vitalization of urban agriculture has increased various forms of experience-based education using school gardens, which raised the importance of school gardens in terms of value as well as the need to develop an implementation system for education-based agricultural experience service using school gardens. Thus, we reset the evaluation indicators from the previous study to establish objective evaluation indicators that enable quantitative comparison of school garden education services. Methods: Analytic hierarchy process (AHP) and direct question (DQ) surveys were conducted on 20 experts from October 12 to 19, 2020 after establishing the purpose and subjects of evaluation, and then the weights were calculated using the Expert Choice 2010 program. Results: First, we analyzed the problems of the previous indicators by categorizing the performance indicators and comparing and verifying them with six requirements of valuation. Then, we added 'welfare values' and established sub-indicators accordingly. The importance of value indicator in AHP was in the order of education values (0.544), health values (0.182), welfare values (0.164), environmental values (0.062), and economic values (0.049). The importance of environmental and economic values was relatively low, less than 0.1. The importance of sub-indicators was highest in cultivating character (0.144), followed by enhancing ecological sensitivity (0.141) > promoting mental health (0.134) > cultivating agricultural literacy (0.120) > improving social skills (0.104). And mitigating climate change in environmental values was lowest (0.009). Increase in income was the lowest (0.036). This can be regarded as the expression of change to increase the educational effect based on collective life and the connotative meaning of 'school'. In the case of DQ, the AHP weight and order were the same, but the environmental and economic values were relatively low, and the result was different from AHP weight. For sub-indicators, the importance in DQ was highest in promoting mental health (0.136), followed by promoting physical health (0.085), ]cultivating character (0.082), social integration (0.072), and enhancing ecological sensitivity (0.071). After reviewing related experts, we came up with 5 evaluation indicators and 16 sub-indicators for school garden education service, which are objective evaluation indicators that enable quantitative comparison. Conclusion: In the future, we will validate the socioeconomic values of school garden education services and contribute to revitalizing school gardens by establishing policy alternatives for effective operation and management of school gardens.

• Journal of Korean Society of Rural Planning
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• v.18 no.4
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• pp.69-78
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• 2012

Korean population has been rapidly aging. Most of people regard the aging population as future crisis due to the rate of change and agree to prepare for a soft-landing on aging society in South Korea. Particularly, the aging population growth in rural areas is much faster than urban areas. Also rural areas relatively have poorer social and economic conditions so the countermeasures for population aging considering related social and economic indices are required. Moreover, each rural region has the different preparedness level for rural aging based on regional socio-economic characteristics. In this study, we analyzed correlations of the rural aging rate and local characteristics and developed an evaluation index to show the regional preparedness status for rural aging. To test the applicability of developed indicators, we applied them to 161 rural regions and assessed regional preparedness level for rural aging. This study would provide basic data for establishing policies for rural aging.

• Safety and Health at Work
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• v.11 no.3
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• pp.314-321
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• 2020

Background: Occupational accidents occur for a variety of reasons, such as unsafe behaviors of workers and insufficient safety equipment at the workplace, but there are also various economic and social factors that can impact working conditions and working environment. This study analyzed the relationship between changes in economic factors and the occurrence of occupational accidents in Korea. Methods: Multilinear regression analysis was used as the analysis model. The general to specific method was also used, which consecutively removes statistically insignificant variables from a general model that includes dependent variables and lagged variables of dependent variables. Results: The frequency of occupational accidents was found to have a statistically significant relationship to economic indicators. The monthly number of cases of occupational injury and disease and fatal occupational injuries were found to be closely related to manufacturing capacity utilization, differences in the production index in the services sector, and commencements of building construction. The increase in equipment investment indicators was found to reduce fatal occupational injuries. Conclusion: The results of this study may be used to develop occupational accident trends or leading indicators, which in turn can be used by organizations that manage and monitor occupational accidents toward taking administrative action designed to reduce occupational accidents. The results also imply that short-term and mid- to long-term economic and social changes that can impact workers, workplaces and working conditions, and workplace organizations must be taken into account if more effective government policies are to be established and implemented toward further prevention of occupational accidents.

• KDI Journal of Economic Policy
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• v.45 no.1
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• pp.69-86
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• 2023

Regulatory sentiment refers to the market's subjective evaluation of regulatory reform and is one of the most widely adopted indicators to those charged with implementing and diagnosing regulatory policies. The use of regulatory sentiment in advanced analysis has become universal, albeit it is often limited due to difficulties in articulating consistent and objective quantitative indicators that can meticulously reflect market sentiment overall. Thus, despite ample effort by scholars to read the economic impact of regulatory sentiment in the real economy, causal links are difficult to spot. To fill this gap in the literature, this study analyzes a regulatory sentiment index and economic performance indicators through a text analysis approach and by inspecting diverse tones in media articles. Using different stages of tests, the paper identifies a causal relationship between regulatory sentiment and actual economic activities as measured by private consumption, facility investment, construction investment, gross domestic investment, and employment. Additionally, as a result of analyzing one-unit impulse of regulatory perception, the initial impact on economic growth and private investment was found to be negligible; this was followed by a positive (+) response, after which it converged to zero. Construction investment showed a positive (+) response initially, which then rapidly changed to a negative (-) response and then converged to zero. Gross domestic investment as the initial effect was negligible after showing a positive (+) reaction. Unfortunately, the facility investment outcome was found to be insignificant in the impulse response test. Nevertheless, it can be concluded that it is necessary and important to increase the sensitivity to regulations to promote the economic effectiveness of regulatory reforms. Thus, instead of dealing with policies with the vague goal of merely improving regulatory sentiment, using regulatory sentiment as an indicator of major policies could be an effective approach.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.319-322
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• 2003

Integrated coastal management (ICM) requires robust indicators that gauge the 'health' of the coast in relation to environmental, social and economic activities. Biological indicators(bio-indicators) offer a signal of the biological condition in an ecosystem. Using bio-indicators as an early warning of pollution or degradation in an ecosystem can help sustain critical resources. This review examines the rationale and value of selecting species as bio-indicators of human induced changes within estuaries, using examples from both the western and southern coast. It include a range of biological parameters relating to particular species, groups of species and biological processes. The use of these indicators is critically reviewed and the presence or absence of a relevant framework for their use in Korean ICM programs is discussed.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.3 no.3
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• pp.29-36
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• 2000

The purpose of this study is to develop and adapt indicators for the rural community assessment. Bearing in mind, indicators are derived from the various theoretical literature review and the efficiency of the indicators has been tested through comparing and evaluating 3 different rural communities which was selected based on their distance from Seoul. In order to assess a rural development project, the assessment indicators should include at least 5 domains of natural environment, socio-economic, quality of living environment, community characteristics, public participation, which are the basic formation of indicators of this study. Furthermore, this approach could be a ground for the environmentally friendly rural development planning.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.