This study examines the demand system of shrimp imported from top four countries and domestically produced by using AIDS (Almost Ideal Demand System) model. Top four import countries are Vietnam, Ecuador, China, and Malaysia based on the value of imports in 2021. As results of the analysis, the demand system of shrimp turn out to be below. First, the relationship of domestic shrimp and imported shrimp (Ecuadorian and Vietnamese) is identified as complements or substitutes depending on whether the income effect is considered. This result implies that imported shrimp supplements domestic supply against excess demand while homogeneous shrimp products competes with domestic shrimp in fish market. Second, the relationship among imported shrimps turned out to be both substitutes and complements. Especially, the Vietnamese shrimp is complementary with Chinese and Malaysian shrimp, but substitutes of Ecuadorian. It is assumed that adjoining Asian countries shares similar shrimp species and processing system which differentiates from Ecuadorian. Finally, the study included quarter as dummy variable and GDP as instrumental variable of expenditure in the model. The result confirmed that domestic shrimp is highly on demand during the main production season while imported shrimp is mainly demanded during the rest of the season.

PURPOSES : The primary purpose of this study is to develop a framework for predicting the demand and distribution of pedestrians when an open space zone is built at the top through the undergroundization of the Gyeongin Expressway. METHODS : After analyzing the current status through a survey on the number of people, students, surrounding traffic volume, and future socioeconomic indicators, the rate of change in the floating population and the rate of increase and decrease in the traffic volume of pedestrians were calculated to evaluate the effect. In addition, microscopic analysis results were derived by setting a pedestrian analysis zone (PAZ). A walking environment index (WEI) was developed that can quantitatively evaluate the degree of walking activation by indicating walking-related surrounding environmental factors. Based on this, a walking demand prediction model was developed. In addition, the results were validated by calculating the walking volume through a micro-simulation in/around the open space zone. RESULTS : The number of crosswalks and schools, transit development indicators, and pedestrian volume increased as the WEI value increased. However, the log form of the distance was observed to be a factor that reduced walking. CONCLUSIONS : This study attempted to reliably predict the demand for walking on the Gyeongin Expressway by calculating the amount of induced walking and the amount of passing walking. The pedestrian demand can be boosted by improving walking environments.

본 연구는 전주시에 위치한 기린봉, 완산칠봉, 황방산 등 3개의 산지형 근린공원을 대상으로 이용행태, 이용권의 인구 통계학적 특성, 근린공원까지의 도달거리를 사용하여 유효이용수요를 예측한 것이다. 조사대상 3개 근린공원의 이용자는 주로 40대~60대 이상이었으며, 이용방법은 주로 도보로 근린공원에 도달하였다. 방문횟수는 주간 1~2회 정도로 나타났다. 조사대상 근린공원의 유효 이용권을 1,000m로 설정하여 변형 중력모델에 의해 이용수요를 예측한 결과 기린봉 근린공원은 4,500명/일, 완산칠봉 근린공원은 3,159명/일, 황방산 근린공원은 2,961명/일이었다. 전체 유효 이용수요는 기린봉 근린공원이 가장 많이 나타났으나, 면적대비 유효이용수요는 완산칠봉 근린공원이 가장 높게 나타났다.

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

국내산 과일 및 과채류의 소비가 정체 내지는 감소하는 반면 수입과일의 소비는 지속적으로 증가하고 있는 상황에서, 본 연구는 소매단계에서 가구들의 계절별 주요 과일 및 과채류 수요를 분석하였다. 이 를 위해, 2010∼2017년 동안 농촌진흥청의 불균형 소비자 패널 자료를 이용하여 일반적인 준이상수요 체계(AIDS) 모형을 확장한 이차형 준이상수요체계(QUAIDS) 모형을 추정하여 계절별로 품목들의 가격 및 지출탄력성을 계측하였다. 분석 결과, 일반적으로 계절별, 품목별로 자체가격 탄력성과 교차가격 탄 력성의 절대값이 차이를 보였다. 봄철에는 사과와 완숙토마토, 오렌지와 바나나 등이, 여름철은 바나나 와 방울토마토, 사과, 참외와 완숙토마토 수박과 완숙토마토가, 가을철은 바나나와 방울토마토, 사과와 완숙토마토, 겨울에는 사과와 단감, 감귤과 완숙토마토, 포도, 오렌지 등이 강한 대체관계를 가지는 것 으로 분석되었다. 방울토마토는 가을과 겨울에, 포도는 봄과 겨울에 자체가격 탄력성이 매우 큰 것으로 나타난 반면, 방울토마토는 봄, 포도는 여름과 가을에 비탄력적인 것으로 분석되었다. 또한 여름철 제 철 품목인 수박, 복숭아, 포도는 자기가격탄력성이 비탄력적인 것으로 확인되었다.

Logistics companies are worrying about securing of differential competitiveness so as to be competitive companies in keen logistics market. The ground is how users are satisfied by sell-established service system to respond not only economic feasibility of logistics costs but also diversity and advancement of logistics needs. The competitiveness of logistics companies is also caused by customer satisfaction of service and only companies finding and satisfying customer needs continuously may be more competitive. For the competitiveness, it’s the most important to analyze demands of current and potential customers and their pursuing value properly. Therefore, this researcher grasped PSL for online logistics service users with 5-point Likert-scale and quality-level decision method that consider the weighted value based on Kano model, measured customer’s potential Demand for service through PCDI, and suggested methodology for deciding the priority of the improvement with loss function of Taguchi.

Recently, service quality must reflect several demands of customers who show rapid and various changes so as to be compared with the past. So, objective and rapid measuring methods for service quality are necessary. For them, first of all, service company must calculate their standard of service quality accurately by measuring service quality exactly. Kano classified the degree of influence that is the degree of correspondence of the quality attributes of products and services to the subjective satisfaction of customers. As a result, the types of qualities are classified as attractive, must be, one dimensional, and indifference attributes. They have been widely used quality attributes in various industrial fields up to now. However, Kano model has a limit that it ignores the characters of the next frequent numbers even though there are not much gap comparing to the most frequent number in the questionnaire answers. The limit is attributed to the character of Kano model that the most frequent number is accepted as the only quality character. Timko calculated the customer satisfaction coefficient by using Kano’s method and studied the differences in quality character by classifying the quality characteristics in a graphical way through the relationship between the satisfaction and the dissatisfaction coefficient. In this study, we used the quality level determination method of the 7-point Likert scale, which takes the weight into account, to complement the deficiencies of the existing Kano model. We also developed and applied a Potential Satisfaction Level (P) and Potential Customer Demand Improvement (PCDI) Index to present a new approach to the determination of service quality attributes. To measure the level of potential service satisfaction and to understand the degree of improvement, we collected specimens of 51 participants who has been trained in the National Strategy Business Training Program, which has been managed by government agent, and analyzed the results.1)

본 연구는 공급자(supplier), 중간공급자(distributor) 그리고 고객(customer)으로 구성된 2 단계 공급사슬에서 퇴화성 제품(deteriorating products)에 대한 중간공급자의 재고모형을 분석하였다. 문제 분석을 위해 공급자는 중간공급자의 수요 증대를 목적으로 중간공급자의 주문 크기에 따라 차별적으로 외상 기간을 허용하고, 최종 고객의 수요는 중간공급자의 재고 수준에 따라 선형적(linearly)으로 증가한다는 가정 하에 모형을 분석하였다. 중간공급자의 이익을 최대화하는 경제적 주문량 결정 방법을 제시하였고, 예제를 통하여 그 해법의 타당성을 보였으며, 민감도 분석을 통하여 퇴화율이 재고정책에 미치는 영향을 분석하였다.

Fashion is primarily based on adoption of trends by consumers in textiles, clothing, footwear, jewelry and art, inter alia. As fashion is based on human preferences, it is characterized by dynamic changes throughout seasons and years, short life cycles, low predictability and high volatility of demand and impulse purchases. In the dynamic environment of apparel markets, fashion firms aim at successfully forecasting both the desirability of new collections and the volumes of each item produced and released to the market under terms of substantial levels of uncertainty. When demand for an item exceeds its supply, the firm is likely to lose additional profits that could have been collected had a sufficient volume of this item been present in the market. Alternatively, if the supply of an item surpassed its demand, it would remain unsold, thereby generating loss equal to its marginal production and distribution costs. The paper proposes a forecasting model that enhances the accuracy of fashion trend forecasting in the context of multiple variants of colour clothing. The model aims at maximizing profits of the firms, while minimizing the forecasting error and reducing the costs that result from excess capacity of production or, alternatively, from loss of potential revenues due to low demand.

Spare part management is very important to products that have large number of parts and long lifecycle such as automobile and aircraft. Supply chain must support immediate procurement for repair. However, it is not easy to handle spare parts efficiently due to huge stock keeping units. Qualified forecasting is the basis for the supply chain to achieve the goal. In this paper, we propose an agent based modeling approach that can deal with various factors simultaneously without mathematical modeling. Simulation results show that the proposed method is reasonable to describe demand generation process, and consequently, to forecast demand of spare parts in long-term perspective.

In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and this has led to various studies regarding energy saving and improvement of water supply reliability. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The concepts was demonstrated through application to observed from water plant (A) in the South Korea. Various statistics (e.g. the efficiency coefficient, the correlation coefficient, the root mean square error, and a maximum error rate) were evaluated to investigate model efficiency. The ensemble based model with an cross-validate prediction procedure showed better predictability for water demand forecasting at different temporal resolutions. In particular, the performance of the ensemble model on hourly water demand data showed promising results against other individual prediction schemes.

The annual energy demand of the standard rural house models Nongrim-10-26 -ga was analyzed using the DesignBuilder. Size of window and type of window were selected as simulation parameters. As a result, heating energy demand was 8.3 times higher than cooling energy demand and reducing heating energy demand is important factor in reducing total building energy. When increasing window glazing size, internal heat gain and loss was changed depending on the outdoor weather conditions. Cooling energy demand increases in summer and heating energy demand increases in winter. When the type of window was changed, cooling energy demand was decreased as the SHGC value was decreased. However, heating energy demand was changed depending on both of the SHGC value and U-value of the selected window type.

수요대응형 교통수단(Demand Responsive Transit)은 변화하는 이동수요에 대응하는 탄력적인 교통수단으로 단순히 노약자와 장애인을 위한 복지교통 서비스의 영역이 아니라, 무선통신과 위치정보서비스(Location Based Service: LBS)의 발달로 인하여 도심형 수단으로 보다 효율적인 교통수단으로 자리매김하고 있다. 그러나 문전서비스(Door-to-Door)를 제공하는 수요대응형 교통수단 시뮬레이션에 적합한 상용툴의 부재로 인하여 알고리즘이나 차량 운행 요소를 면밀하게 분석하기 힘든 어려움이 있었다. 본 연구는 수요대응형 교통수단에 연관된 다양한 차량 운영계획과 알고리즘을 구현, 평가할 수 있는 시뮬레이션 환경을 제안한다. 문전서비스(Door-to-Door) 기반의 차량 운행 모형을 적용하기 위하여 확보되어야 하는 시뮬레이션 입력 데이터를 정의하고 있으며, 수요대응형 교통수단의 대표적인 범주에 속하는 실시간 합승 택시(Shared-Taxi) 서비스를 서울시 교통망과 택시 수요를 이용하여 적용하였다. 합승 택시 운행 계획을 위하여 Nearest Vehicle Dispatch(NVD)와 Insertion Heuristic(IH), 두 종류의 알고리즘을 제안하였으며, 제안된 시뮬레이션을 통하여 성능을 비교하였다. 또한, 합승(Ride-sharing)을 허용하지 않는 일반적인 택시와의 비교를 통하여 시스템 효율 향상과 서비스 품질 변화를 분석하였다.

본 연구는 공급자(supplier), 중간분배자(retailer/distributor) 그리고 고객(customer)으로 구성된 2 단계 공급사슬을 대상으로 공급자가 수요 증대를 목적으로 중간분배자에게 일정기간 동안 제품대금에 대한 지불 연기를 허용한다는 가정 하에 중간분배자의 최적 재고정책 결정을 위한 재고 모형을 다루었다. 소비성 상품의 경우, 고객의 수요는 일반적으로 상품 진열대에 진열되어있는 상품의 재고량에 많은 영향을 받는 것으로 알려져 있다.

내진설계기준이 반영되지 않은 기존 구조물의 경우 내진보강에 의하여 구조물의 내진성능을 향상시킬 수 있다. 내진보강의 수준을 합리적으로 결정하기 위해서는 구조물의 사용기간 동안에 예상되는 지진피해 관련 손실이 최소화되도록 하여야 하는데, 이를 위해서는 구조물이 위치한 지역에 대한 지진의 강도별 발생빈도, 지진에 의한 구조물의 기능상실 및 직접/간접 피해를 복합적으로 고려하여 구조물의 예상 손실비용을 산정하여야 하며 이는 구조물 손상에 대한 지진위험도 해석을 통해서 그 해석을 수행할 수 있다. 본 연구에서는 확률적 지진요구모델을 이용한 위험도 평가를 통하여 구조물의 지진에 대한 피해 손실을 정량적으로 산정하고 이를 바탕으로 초기비용과 예상손실비용을 포함한 총 손실비용을 최소화시킬 수 있도록 내진보강 수준을 최적화하는 절차를 제시하였다. 구조물과 관련된 지진피해 산정에 있어서 지진하중의 강도별 발생확률 및 구조물의 손상확률을 동시에 고려하여 구조물 생애주기에 대한 구조물의 지진손상 확률밀도함수 및 누적분포함수를 수식화하였으며 수식의 유효성을 유지하기 위한 확률변수의 유효범위를 정의하였다. 또한 여기에 사회적, 경제적 손실을 정량화하기 위한 손실함수를 결부시켜 구조물과 관련된 지진 피해 손실의 기댓값을 정량적으로 산정할 수 있도록 하였다. 제시된 해석기법은 기존의 시뮬레이션에 의한 손실산정법과 비교하여 해석의 정확도는 잃지 않으면서 구조해석의 반복횟수를 대폭 줄일 수 있다는 장점이 있으며 빌딩과 교량을 비롯한 구조물의 내진성능 평가 및 개선을 위한 의사결정 시에 효율적으로 적용될 수 있을 것으로 판단된다.

ETCS는 1990년대 초부터 선진국에서 유료도로 톨게이트에서의 교통체증 및 지체문제를 해결하기 위하여 적용되기 시작하였다. ETCS의 성공적인 운영을 위해서는 ETCS 이용률을 정확히 예측하는 것이 중요하다. 본 연구에서는 창원시의 신뢰성 있는 ETCS 이용수요예측 모형 개발이 시도되었다. 총 11개의 설명변수들을 고려하면서 이항로짓 및 신경망 모형들이 검토되었다. 신경망모형에서 가장 좋은 결과를 얻었다. 그러나 ETCS 이용률 추정을 위해 설명변수 11개를 추정하기에는 어려움이 있으므로 차내장치 임대보증금, 절약시간, 할인률의 중요 3개 정책변수만을 고려한 신경망 및 로짓 모형들을 ETCS 이용률 추정모형으로 분석하였다. 모형의 예측력 평가와 적합도 분석에 있어서 신경망모형이 로짓모형보다 우수한 모형으로 판단되어지나 학습에 사용된 9가지 이외의 시나리오에서 신뢰성이 떨어지는 것으로 나타나, ETCS 이용률 추정 모형으로 3개의 중요한 정책변수를 고려한 이항로짓모형이 제안된다. 이 모형은 평균제곱오차 0.14, σ20.31, x2488.9로 신뢰성이 높은 모형으로 평가되며 창원시와 규모가 유사한 도시에 적용이 가능할 것으로 기대된다.