In the post-COVID-19, the food industry is rapidly reshaping its market structure toward online distribution. Rapid delivery system driven by large distribution platforms has ushered in an era of online distribution of fresh seafood that was previously limited. This study surveyed 1,000 consumers nationwide to determine their online seafood purchasing behaviors. The research methodology used factor analysis of consumer lifestyle and Heckman’s ordered probit sample-selection model. The main results of the analysis are as follows. First, quality, freshness, selling price, product reviews from other buyers, and convenience are particularly important considerations when consumers purchase seafood from online shopping. Second, online retailers and the government must prepare measures to expand seafood consumption by considering household characteristics and consumer lifestyles. Third, it was analyzed that consumers trust the quality and safety of seafood distributed online platforms. It is not possible to provide purchase incentives to consumers who consider value consumption important, so improvement measures are needed. The results of this study are expected to provide implications on consumer preferences to online platforms, seafood companies, and producers, and can be used to establish future marketing strategies.

Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary’s network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

본 연구는 K연구원의 상향식 R&D과제기획 차원의 신규 연구기획과제 선정 평가를 위한 평가도구 개발에 목적을 두고 진행하였다. 이를 위해 CIPP모형과 연구기획평가를 위한 선정평가 및 평가지표에 관한 선행연구를 중심으로 R&D과제기획 선정평가 항목과 문항을 개발 한 후, 2회에 걸친 델파이 조사를 실시하였다. 개발된 평가도구는 13명의 전문가를 대상으로 설문조사를 실시하여 내용타당도, 합의도 및 수렴도를 검증하였다. 최종 선정된 R&D과제기획 선정평가 도구는 8개 항목에 총 21개 문항으로, 상황평가 5 문항, 투입평가 2문항, 과정평가 8문항, 산출평가 6문항으로 구성되었다. 개발된 평가 도구는 상향식 기획 과정상의 문제점을 해소하고 연구자들의 기획역량을 제고하는 데 기여할 것이다. 또한, 선정 평가 시 평가에 대한 일관성과 효율성 제고에 기여할 것이다.

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an “if-then” rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers’ general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier’s performance and eventually influence buyer’s production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

Ensemble classification involves combining individually trained classifiers to yield more accurate prediction, compared with individual models. Ensemble techniques are very useful for improving the generalization ability of classifiers. The random subspace ensemble technique is a simple but effective method for constructing ensemble classifiers; it involves randomly drawing some of the features from each classifier in the ensemble. The instance selection technique involves selecting critical instances while deleting and removing irrelevant and noisy instances from the original dataset. The instance selection and random subspace methods are both well known in the field of data mining and have proven to be very effective in many applications. However, few studies have focused on integrating the instance selection and random subspace methods. Therefore, this study proposed a new hybrid ensemble model that integrates instance selection and random subspace techniques using genetic algorithms (GAs) to improve the performance of a random subspace ensemble model. GAs are used to select optimal (or near optimal) instances, which are used as input data for the random subspace ensemble model. The proposed model was applied to both Kaggle credit data and corporate credit data, and the results were compared with those of other models to investigate performance in terms of classification accuracy, levels of diversity, and average classification rates of base classifiers in the ensemble. The experimental results demonstrated that the proposed model outperformed other models including the single model, the instance selection model, and the original random subspace ensemble model.

This study intends to propose a non-oriented DEA based game cross-efficiency approach for supplier selection. With a discussion on the choice of DEA models and approaches that are most appropriate for supplier selection, we propose a game cross efficiency model based upon the non-oriented variable returns-to-scale RAM DEA by adapting the existing game cross efficiency model based upon the oriented constant returns-to-scale CCR DEA. We develop the RAM game cross efficiency model and a convergent iterative solution procedure to find the best game cross efficiency scores that constitute a Nash equilibrium. We illustrate the proposed model with two data sets of supplier selection, and demonstrate that significantly different results are obtained when compared with the existing approaches.

본 연구는 일반영재성 이론을 기반으로 하여 무용영재 선발모형을 개발하고자 한다. 이를 위 하여 국내·외 예술영재기관에서의 무용영재 선발과정을 비교/분석하고, 선발단계에서 투입되는 검사도구와 평가방법들을 조사하였다. 우선 국외의 무용영재 선발기관은 러시아 바가노바, 영국 로얄발레, 프랑스 파리오페라극장 발레단 등으로 분류하였고, 국내기관은 한국예술영재교육원, 안양예고/계원예고 무용영재학급 등으로 분류하였다. 각 나라별, 기관별 무용영재 선발과정을 분석한 결과, 공통된 선발내용은 2단계 이상 분류하여 다단계 선발방법으로 추진되고 있다는 점 과 무용동작을 얼마나 잘 수행할 수 있는지에 대한 수행능력을 평가한다는 점이다. 국외기관은 무용영재로서의 잠재된 능력을 중시하는데 특히 체격조건과 체력, 동작수행을 위한 선천적인 재 능(리듬, 음악성, 창의성 등)을 고려하여 선발하였다. 반면 국내기관은 다양한 추천(학교장, 교사 등)에 의해 1차 판별되었고, 2차는 무용수행 결과에 초점을 두고 선발하였다. 국·내외 기관의 선발은 선발목표에 따라 선발내용이 상이한 차이를 보였으나, 무용영재 선발의 타당한 결과를 도출해내기 위한 방안이 강구되고 있음을 알 수 있다. 이에 본 연구는 일반 영재성 이론과 분석 된 자료를 바탕으로 첫째, 다단계 선발방법, 둘째 검증된 판별도구 사용 셋째, 다양한 추천제(관 찰도구)를 적용함으로써 무용영재 선발모형을 개발하였다. 무용영재 선발은 총 4단계로써 1단계 는 다면정보 수집단계이며, 다양한 추천경로와 무용영재성 검사, 그리고 관찰평가 등으로 구성하 였다. 2단계는 무용재능 검사 단계이며, 체격검사, 체력검사, 실기검사, 창의성 검사 등의 수업관 찰을 통해 평가하도록 하였다. 3단계는 심층면담으로서 부모면담과 학생면담으로 구분하여 1, 2 단계에서 관찰되지 않은 내용을 심층적으로 확인할 수 있도록 하였다. 마지막 4단계는 무용영재 전문가들로 구성된 무용영재선정심사위원회를 소집하여 최종 무용영재를 선발하도록 하였다.

As environmental protection is becoming more and more important, green production has become a key issue for almost every manufacturer and will determine a manufacturer can be sustainable in the long term. Therefore a performance evaluation system for green suppliers is necessary to determine the suitability of suppliers to cooperate with the company. While the works on the evaluation and/or selection of suppliers are abundant, those that concern environmental issues are rather limited. The objective of this study is to construct a combined model based on fuzzy analytic hierarchy process (FAHP) and balanced scorecard (ESC) for evaluating green suppliers in the manufacturing industry. The ESC concept is applied to define the hierarchy with four major perspectives (i.e. financial, customer, internal business process, and learning and growth), and performance indicators are selected for each perspective. FAHP is then proposed in order to tolerate vagueness and ambiguity of information. Finally, FAHP is finally constructed to facilitate the solving process. With the proposed model, manufacturers can have a better understanding of the capabilities that a green supplier must possess and can evaluate and select the most suitable green supplier for cooperation.

With the trends of massiveness and complexity of construction, the main agents of construction have considered the various types of risk management strategies to minimize the loss caused by the risk factors from the nature of construction project, regional characteristics, and scale of construction. The risk management has been conducted, because the risk factors have exacerbated the condition of construction in terms of the level of productivity, quality of construction, atmosphere, and budget. Based on thε interests regarding risk factor management, the current study suggests the work breakdown structure-based process. Additionally, based on the work breakdown structure, the risk factors on constructions are identified and stratified depending on the level of salience of each risk factor. The purpose of result is to lead Korean Land Corporation understand and control the risk factors properly for the advanced construction process of Korean Land Corporation. Ultimately the current study contribute to advance of efficient risk management strategies by using ANP method, which identify and control the primary risk factos depending on the impact of the interaction and subordinate relationship between risk factors.

  Supply Chain Management (SCM) system is a critical investment that can affect the competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper presents the characteristic factors of SCM system a

  기술집약적인 경제성장의 중요성이 강조되고 있는 가운데 이공계 진학과 과학기술직종선택의 감소는 성장잠재력에 가장 근본적인 위협이 된다. 이를 유지하려는 여러 가지 정책이 교육학적이나 사회학적 근거에서 제시되고 있으나 이를 분석하는 이론적 경험적 틀이 상대적으로 부족한 상태이다. 직업선택모델은 사회학적인 접근법이 활발하게 진행되었으나, 경제적 동인에 대한 분석이 부족하다. 본 논문에서는 2000년 미국 센서스 데이터에 나타난 가장 국제화된 미국의 과학기

Supply Chain Management(SCM) system is a critical investment that can affect future competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper provides the characteristic factors of SCM system selection and the SCM system evaluation and selection model based on Analytic Hierarchy Process(AHP). The proposed model can systematically construct the objectives of SCM system selection to support the business goals. A empirical example demonstrates the feasibility of the proposed model and the model can help a company to make better decision-making in selecting SCM system.

The problem of system reliability is very important issue in the digitalized nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and fatal damage of human. Therefore the purpose of this s