• Journal of Digital Convergence
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• v.13 no.5
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• pp.237-244
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• 2015

Export-led policies, FTA signed and economics of scale through a variety of market-oriented policies, such as regulations to improve market grew constantly. Accordingly, the correct decision making accurately analyze the economics market for decision, a problem has been an important issue in predicting. For accurate analysis and decision-making of the most common indicators of the stock market by proposing a number of indicators of economic transformation techniques were applied to the convergence model combining estimation and forecasts problem confirmed its effectiveness. Experimental result, gave the model estimation method to apply a transform to show the valid combinations proposed model state estimation result was confirmed in a very similar exercise aspect of the physical problem and the KOSPI index prediction.

• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.907-937
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• 2018

This study analyzed the policy decision process of the International Science Business Belt (ISBB) applying multiple stream model combining Kingdon (2013) and Howlett et al. (2014) models. We looked at what socio-political factors influenced the process and sought to find ways to promote the project of ISBB and the policy of basic science in the future. As a concrete analysis, the policy decision process was divided into policy, policy formation, and implementation policy, and the streams of problem, process, policy and politics, policy window, and policy participant were used as variables. As a result of the analysis, the stream of politics and the role of the policy-entrepreneur played an important role in the policy decision process. Politicians and government officials were more involved than the scientists.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.63-70
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• 2013

A judgment on the redevelopment projects' predicted profitability is an essential decision-making element for the success of the redevelopment projects. It is necessary to review the literature on profitability of redevelopment project and draw risk factors that could affect profitability through the risk analysis based on surveys. It is also necessary to judge profitability prediction toward the business value of the redevelopment project in the planning phase according to the risk analysis results which can affect the profitability prediction. In order to prevent the growing difficulties in executing the projects, a profitability prediction model is proposed using the method of management and disposal based on a proportional calculation that can estimate the share of expenses in order to judge profitability in the planning phase. With the improvement of profitability prediction models, it is possible to appropriately judge profitability in the planning phase in order to allow the prevention of suspension, reduction of project term, reduction of cost, and making of rational decisions.

• Journal of the Korean Geographical Society
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• v.36 no.3
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• pp.278-291
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• 2001

This paper is to build a spatial decision support system designed to solve problems relevant to the decision-making for retail center locations. For construction of the system this paper discusses the primary procedures of spatial modeling and issues of data, which are required for integrating spatial interaction models to GIS having capability of managing, analyzing and visualizing spatial data sets. Lexington, Kentucky, is selected as a case study to implement the spatial decision support system based on the spatial modeling module. This system for retail center locations is useful of estimating the catchment areas more accurately and analyzing resultant flow patterns. And this system can make spatial analysis efficiently for what-if scenarios such as an intended retail center or changing demand. The benefits of adopting this system allow the decision makers to plan the investment strategies and search for stable market structure.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.207-222
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• 2005

A prerequisite for making R&D more productive is to able to measure its productivity. Most of the previous studies on this topic have attempted to measure R&D productivity at the firm or industry levels. In this study, however, R&D productivity is measured at the national level to provide R&D policy implications, particularly for Asian countries. Contrary to the previous studies where total factor productivity was adopted, this study employs the data envelopment analysis (DEA) approach to measure R&D productivity. DEA is a multi-factor productivity analysis model for measuring the relative efficiency of each Decision Making Unit (DMU). In addition to the basic DEA model that includes all inputs and outputs, five additional models are constructed by combining single input with all outputs and single output with all inputs in order to measure specialized R&D efficiency. In this study, the twenty-seven countries are classified into four clusters based on the output-specialized R&D efficiency: inventors, merchandisers, academicians, and duds. Then, the characteristics of the Asian countries with respect to R&D efficiency are identified. It is found that Singapore ranks high in total efficiency, and Japan in patent-oriented efficiency. Meanwhile, China, Korea, and Taiwan are found to be relatively inefficient in R&D. We expect that the findings from this study will be able to provide directions for R&D policy-making of the Asian countries.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.158-169
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• 2012

Sabah has experienced a rapid decline in the extent of forest cover. The precise impact of habitat loss on the conservation status of the plants of Sabah is uncertain. In this study we use the niche modelling algorithm MAXENT to construct preliminary, revised and final ecological niche models for Dipterocarpus lamellatus and Dipterocarpus ochraceus and combined these models with data on current land-use to derive conservation assessments for each species. Preliminary models were based on herbarium data alone. Ground surveys were conducted to evaluate the performance of these preliminary models, and a revised niche model was generated from the combined herbarium and ground survey data. The final model was obtained by constraining the predictions of the revised models by filters. The range overlap between the preliminary and revised models was 0.47 for D. lamellatus and 0.39 for D. ochraceus, suggesting poor agreement between them. There was substantial variation in estimates of habitat loss for D. ochraceus, among the preliminary, revised and constrained models, and this has the potential to lead to incorrect threat assessments. From these estimates of habitat loss, the historic distribution and estimates of population size we determine that both species should be classified as Critically Endangered under IUCN Red List guidelines. Our results suggest that ground-truthing of ecological niche models is essential, especially if the models are being used for conservation decision making.

• Journal of Climate Change Research
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• v.5 no.1
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• pp.21-36
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• 2014

Forest ecosystem provides variety goods and services for human being. Unlike goods, forest ecosystem services could not be easily priced by market mechanism. This uncertainty has been caused to conflict in decision-making related forest ecosystem services. Quantification of forest ecosystem services is required to understand the importance of ecosystem services and their contribution to decision-making. As a growing concern of climate change, it is necessary to quantify and calculate carbon storage and sequestration in forest. In this study, for quantifying carbon storage and sequestration, we compared scale, output, input data availability of the models and analyzed the applicability of the models to Korea. The results of this study show that most models are applicable for quantifying carbon storage and sequestration. However, relatively few models are applicable for other regulating services (air quality regulation, flood mitigation, erosion control, water quality, etc.) of forest. This study would be helpful for quantifying regulating services of forest ecosystem research.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.260-277
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• 2015

The object of this study was the climate change sensitivity assessment of Korean Fir and Khinghan Fir as a representative subalpine plant in South Korea. Using species distribution models, we predicted the probability of current and future species distribution. According to this study, potential distribution that have been predicted based on the threshold (MTSS) is, Khinghan Fir was higher loss rate than Korean Fir. And in the climate change sensitivity assessment using the scalar sensitivity weight ($W_{is}$), $W_{is}$ of Korean Fir was higher relatively than the sensitivity of Khinghan Fir. When using the species distribution models as shown in this study may vary depending on the probability of presence data and spatial variables. Therefore should be prior decision studies on the ecological environment of the study species. Based on this study, if it is domestic applicable climate change sensitivity assessment method is developed. it would be important decision-making to climate change and biological diversity of adaptation policy.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.77-86
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• 2010

The study developed physical distribution channel choice models reflecting decision making of the firms and studied how choice decision factors influence selection of distribution channel. The distribution channel survey data in Korea was used to do empirical study. As a choice set, distribution channels were classified into two main choice channels: direct and indirect channels. In addition, indirect channels were classified into other three channels according to the type of intermediate point: distribution center, wholesale store, and agency. This study developed choice models by applying both binary and multinomial logit model with various set of factors. The results showed that the developed logit models seemingly reflect distribution channel choice behaviors. The hypothesis tests on how each factor influences choice of distribution channel were performed and discussed as well.