• Journal of Environmental Impact Assessment
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• v.25 no.1
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• pp.63-76
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• 2016

In 2015, Summits of State and Government at United Nations General Assembly agreed to set the world on a path towards Sustainable Development(SD) through the adoption of the 2030 Agenda. 2030 Agenda adopts 17 Sustainable Development Gooals(SDG) to achieve 3 pillars of social security, economic efficiency and environmental integrity. Sustainable Development Indicators(SDI) which are suggested by UN SDSN(United Nations Sustainable Development Solutions Network), have been developed for measuring SDG implementation, by which Sustainability Assessment(SA) can be accomplished to check through more holistic approaches to poverty alleviation, social inclusion and environmental management. In Korea, Strategic Environmental Impact Assessment(SEIA) has been applied to PPP(policy, plan, program) by 'Ministry of Environment', whereas 'National Land Planning Assessment(NLPA) which is one sort of SEA has been implemented to evaluate PPP of Ministry of Land, Infrastructure and Transport'. Although SEIA and NLPA have been utilized as decision-making support tools for stakeholders including high authorities, the reference criteria of these institutions are not considered as convincible and communicable. Evaluation criteria of alternatives which are core principles for SEIA and NLPA seem so ambiguous and unscientific. Through incorporation of SDI into SEIA, a convenient, quick and credible diagnosis of the key dimensions of SD comprising social equity, economic development and environmental management, can help develop a shared understanding of priorities of implementation of SDG.

• Korean Journal of Construction Engineering and Management
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• v.2 no.2 s.6
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• pp.68-80
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• 2001

While opportunities for international construction firms have been growing with globalization, the risk of international construction projects is significantly increasing in severity and complexity. However, the traditional risk management approach in the construction industry has maintained a profit focus. In addition, this approach has not considered the overall risk at the corporate level, but rather has focused only on the risk of individuals at the project level. Corporate risk management should be implemented from the initial stages of new project selection. This paper suggests the Multi-criteria Integrated Systematic Analysis as a strategic decision-making tool for international construction contractors. The model integrates the multi-criteria of risk, return, and efficiency to choose the optimal set of new portfolios at the corporate level. This model also introduces the Value at Risk (VaR) concept to the international construction industry to present the total risk at the corporate level. To validate this model, this paper tested an experimental case study using the historical data of a global general contractor.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.89-100
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• 2011

As an impactive factor on industries and national economy, The Social Overhead Capital(SOC) is major factor to determine the national competitiveness and the investment of SOC is essential for its economic growth. Accordingly, introduction of the preliminary feasibility study and establishment of legal institutionalization and evaluation system has been carried out and reviewed since 1999. Nevertheless of these efforts, basic problems such as lack of scientific method for investment evaluation and loss of effectiveness on feasibility studies are continuously being brought up. Moreover, as the preliminary study to improve the mentioned problems is mainly focused on the economic and estimated demand analysis, the study of policy analysis, the most important phase during a feasibility study, is still insufficient. Therefore, in this paper, a quantitative decision-making model, to which the performance assessment method of Value Engineering(VE) is applied, is developed and proposed to improve the policy analysis of (preliminary) feasibility study that requires combining with relative studies, to induce quantitative analysis method, and to contribute the improvement of value on the political aspect for SOC investment goals and use as a strategic decision-making method by systematic analysis.

• Journal of Service Research and Studies
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• v.14 no.3
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• pp.188-205
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• 2024

The food truck business, which involves selling various types of food from mobile vehicles, has gained significant popularity in urban centers and at events. These food trucks have rapidly expanded due to their relatively low initial investment and high flexibility, attracting customers with unique menus and personalized services. However, as competition increases, the need to manage service quality to boost customer satisfaction and encourage repeat visits has become more critical. Despite this growing importance, there has been limited empirical research on the topic. This study aims to analyze customer experiences with food truck services to gain strategic insights for improving service quality. By applying structural topic modeling to customer review data, the study identified 50 key topics. The process included a comprehensive evaluation of model diagnostics and interpretability to determine the optimal number of topics, ultimately selecting the most relevant ones related to service experiences. The impact of these identified topics on overall customer satisfaction was empirically tested using regression analysis. The results showed that aspects such as "Food Taste," "Friendly Staff," and "Positive Emotion" had a positive influence on customer satisfaction, whereas "Delayed Service," "Negative Emotion," and "Beverage Service" had a negative impact. Based on this analysis, the study proposes concrete methods for food truck operators to systematically analyze customer feedback and use it to drive service improvements and innovation. This research highlights the importance of data-driven decision-making in small business environments like food trucks and contributes to expanding the application of topic modeling in the service industry.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.103-115
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• 2005

For today's enterprises to survive in the current rapidly changing business environments, it is imperative to make quick and successful decisions to various challenges. In making important business decisions, if enterprises utilize business rules and knowledge, properly and promptly, they may effectively reduce the chance of failures. However, in most of today's information systems, these rules and knowledge are not managed in centralized and systemic manner. They disperse over entire enterprises' information systems, and sometimes reside in the heads or memos of enterprises' employees. BRE (Business Rule Engines) is a solution that systematically and centrally manages these business knowledge and rules of an enterprise. With BREs, any business user is able to store, edit, retrieve and utilize business rules and knowledge in centralized repository, without IT development skills. And with BRE, enterprises could improve business intelligence and attain strategic advantages over other enterprises. However, since there is no clear criteria for BRE introductions, it is not easy to decide whether or not to introduce the expensive BRE solution to an enterprise. In this research we propose a decision model for BRE introduction. Using this model, business analysts considering BRE introduction, readily make decisions on BRE introduction.

• Journal of Service Research and Studies
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• v.4 no.1
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• pp.21-35
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• 2014

Many people have a social network service (SNS) by utilizing a variety of community activities, information sharing, and the creation of social networking. In terms of marketing academics view social networks between businesses and consumers in the new communication strategy, a new way to make them in terms of marketing a new business opportunity. That is, they are actively engaged in the various marketing activities targeting customers using SNS. According to H. A. Simon's needle theory, it is efficient to make a decision within the bounded rationality due to the difficulty of collecting data in decision-making as well as the inability to collect all information because of limited time and money. If the information or the informant can be trusted, the customers would be able to make a quick decision and get higher satisfaction from it. Therefore, this study examines and thereby empirically demonstrates what role customers' trust plays in a company's marketing using SNS by exploring how trust condition works in the mediated model and, theoretically, intends to introduce an empirical methodology on more strictly mediated moderating effects and, in practice, revisit the role of trust on direct and indirect effect the SNS's Information quality has on the performance variables such as customer satisfaction and loyalty. This study thereby aims to provide a strategic tool for the companies that plan to use the SNS in developing marketing strategies.

• Journal of Service Research and Studies
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• v.3 no.1
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• pp.17-31
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• 2013

With the advent of smart phones, there are increasing demands from customers to connect to the social media services at any time and at any place without restraint. As a result, many foreign companies have lately been able to pursue two-way communication with customers through social media which has enabled them to see the reaction and the needs of customers immediately and respond timely. That is, they are actively engaged in the various marketing activities targeting customers using SNS. According to H. A. Simon's needle theory, it is efficient to make a decision within the bounded rationality due to the difficulty of collecting data in decision-making as well as the inability to collect all information because of limited time and money. If the information or the informant can be trusted, the customers would be able to make a quick decision and get higher satisfaction from it. Therefore, this study examines and thereby empirically demonstrates what role customers' trust plays in a company's marketing using SNS by exploring how trust condition works in the mediated model and, theoretically, intends to introduce an empirical methodology on more strictly mediated moderating effects and, in practice, revisit the role of trust on direct and indirect effect the SNS's quality has on the performance variables such as customer satisfaction and loyalty. This study thereby aims to provide a strategic tool for the companies that plan to use the SNS in developing marketing strategies.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• The Journal of Fisheries Business Administration
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• v.37 no.3 s.72
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• pp.1-24
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• 2006

In terms of the size of aquaculture farms and production volume, inland freshwater aquaculture is much smaller than marine aquaculture in Korea. However, freshwater aquaculture provides fish which is not produced in the sea. Freshwater aquaculture plays an important role in the efficient use of resources, development of local areas and economy vitalization in under - developed areas. freshwater aquaculture also helps ecosystem recovery by stocking farmed fry. As addressed above, inland freshwater aquaculture plays various roles and can not be ignored. However, freshwater aquaculture has been off the interest of fisheries authority. Considering a series of changes in the circumstances such as the government's disapproval of pen - raised aquaculture, higher standard for discharged water from aquaculture farms and a rapid increase in import of low price fish from other countries, it is difficult to expect the quantitative expansion of the freshwater aquaculture any more. Furthermore, freshwater aquaculture lost the trust of people because of the use of Malachite green, and the consumption of farmed product plummeted last year. Even though it would be difficult to expect the quantitative expansion, we could expect qualitative growth and let the inland freshwater aquaculture keep playing the own roles. In order to achieve competitive advantage and regain the trust by providing safer farmed product, the government's support and freshwater aquaculture industry's active and voluntary efforts are very important. This paper suggests several points for the future oriented inland freshwater aquaculture in Korea such as strategic intensive development of selected species, the technical improvement and its diffusion, increased cooperation among the government authority, industry and scientists.

• Journal of the military operations research society of Korea
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• v.34 no.3
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• pp.1-12
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• 2008

Design of supply chain network (SCN) is required to optimize every factor in SCN and to provide a long-term and strategic decision-making. A mathematical model can not reflect the real world because design of SCN contains variables and stochastic factors according to status of its system. This paper presents the designing methodology of military SCN using the mathematical model and the simulation model. It constructs SCN to minimize its total costs using the Mixed Integer Programming (MIP) model. And we solve problems of a vehicle assignment and routing through adaptation of experiment parameters repeatedly in the simulation model based on the results from the MIP model. We implement each model with CPLEX and AutoMod, and experiment to reconstruct SCN when the Logistic Support Unit is restricted to support military units. The results from these experiments show that the proposed method can be used for a design of military SCN.