• 한국의류산업학회지
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• 제22권3호
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• pp.323-334
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• 2020

This study analyzed the effects of consumers' characteristic variables on information search and purchase decisions in a decision-making process that validated the path model in purchasing apparel products. In constructing a structural equation model using AMOS 19.0., the variables including enjoyment pursuit, price pursuit, product involvement and product risk were selected as consumers' characteristic variables affecting the stage of information search. A questionnaire was distributed to consumers over 20 years old who purchased apparel products using offline and online channels within one year; consequently, we were able to analyze 468 effective data. The results were as follows. First, the path model of this research proved to be the appropriate model explaining the effects of consumers' characteristic variables on the stage of purchase decision-making. Second, enjoyment pursuit had a significant positive influence on offline information search; in addition, price pursuit and product risk affected the online information search significantly. Product involvement affected online information search as well as offline information search. Third, the offline information search affected offline purchase and online information search affected online purchase. However, consumer's channel switching behavior between the stage of information search and the stage of purchase decision was not proven. The findings suggest that companies need to develop distribution strategies according to consumers' characteristic factors that effect consumer's purchase decision-making.

• International Journal of Contents
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• 제8권1호
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• pp.100-107
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• 2012

While considerable research suggests that users' uncertainty gradually decreases, as they proceed through the information seeking process, others argue that it can arise at any stage of their information seeking process. Reflecting the latter view, this study examined user perceptions of uncertainty in the final stage of users' information seeking process, the stage of search results evaluation. Considering the significance of Web search engines for academic study, this study investigated the relevance decision stage of scholarly researchers in the field of science, who use Web search engines for their academic study. Based on the analysis of the users' uncertainty, this study provided implications to improve information systems and Web contents design.

• 한국통신학회논문지
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• 제24권9A호
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• pp.1392-1400
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• 1999

본 논문에서는 전역 탐색 알고리듬 (full search algorithm; FSA)과 동일한 성능을 나타내면서도 고속으로 움직임을 추정할 수 있는 블록 움직임 추정을 위한 2단계 고속 전역 탐색 알고리듬을 제안하였다. 제안한 방법에서는 첫 번째 단계에서 9:1로 부표본화된 탐색점에 대하여 블록 정합을 행하여, 여기서 얻어지는 최소 평균 절대치 오차 (mean absolute error, MAE)를 기준 MAE로 설정한다. 두 번째 단계에서는 첫 번째 단계에서 블록 정합을 행하지 않은 탐색점에 대하여 각 탐색점에서 가질 수 있는 MAE의 최소 범위를 구한 뒤, 이 값이 기준 MAE보다 작은 탐색점에 대해여서만 블록 정합을 행하였다. 이때, MAE의 최소 범위는 첫 번째 단계에서 블록 정합을 통하여 얻은 MAE들과 현재 블록 내의 화소들의 이웃 화소간의 화소 값의 차를 이용하여 구하였다. 그러므로, 제안한 방법에서는 MAE의 최소 범위를 이용하여 블록 정합이 필요한 블록에 대하여서만 정합을 행함으로써 FAS와 동일한 움직임 추정 성능을 유지하면서도 움직임 벡터의 추정을 위한 계산량을 줄일 수 있었다.

• 한국의류학회지
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• 제46권4호
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• pp.638-656
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• 2022

This study aimed to identify characteristics of Generation MZ's consumer purchase decision journey to develop the new fashion CDJ model. The initial stage was affected by habit, online community, social media, aesthetics, circumstantial need, and proxy. In the search and consideration stage, mobile channels were used actively. In the active search and evaluation stage, online media, experiential data, and personal information were employed. In the purchase stage, zoomers took plenty of time in search and evaluation before spending, contrary to millennials who made their purchases more quickly. In the post-purchase experience stage, zoomers actively displayed follow-up behaviors depending on their satisfaction, such as retaining or deleting the app. While, millennials did not turn away from the store or brand, but followed up on their purchases even when they had an unsatisfactory experience. Based on the characteristics of CDJ, iterative cycle CDJ models were developed. Zoomers CDJ model was presented as a search loop that consists of the search and evaluation process, in which information accumulates, and a purchase loop in which the actual purchase occurs. The iterative cycle CDJ model was presented connected to the loyalty loop as the main section, which is accelerated in millennials' CDJ model.

• 한국통신학회논문지
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• 제27권1B호
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• pp.24-33
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• 2002

비동기 W-CDMA를 위한 셀 탐색 방법은 슬롯 동기 과정(stage 1), 그룹 확인 및 프레임 동기 과정(stage 2), 긴 코드 동기 과정(stage 3)으로 구성되어있다. 특히 이동국에 전력이 처음 들어왔을 때 수행되는 셀 탐색을 초기 셀 탐색이라 한다. 초기 셀 탐색에서는 이동국의 초기 주파수 오차와 시간 오차에 의해 성능이 저하된다. 본 논문에서는 이러한 동기 오류 중 초기에 클럭 발생기에 의해 유발되는 시간 오차를 보상해주기 위해 시간 동기 블록을 적용한 초기 셀 탐색 방법을 제안한다. 제안된 방식에서는 시간 동기 블록이 슬롯 동기 과정에서 할당된 슬롯 시작점을 기준으로 동기 추적 과정을 수행하므로 stage 2와 stage 3에서의 시간 오차를 보상하게 된다. 제안된 초기 셀 탐색 방법을 사용할 경우, 시스템의 시간 오차가 ${\pm}T_c$/2일 때, 기존 방식보다 최대 1.5dB의 성능 향상을 얻을 수 있었다.

• 한국유통학회지:유통연구
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• 제12권3호
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• pp.69-90
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• 2007

본 연구는 소비자의 구매과정을 정보탐색 및 구매결정 단계로 나누어 각각의 단계에서 소비자가 온라인 또는 오프라인 채널을 선택하는 행동에 영향을 주는 요인을 분석하였으며 어떤 요인이 채널 전환(온라인 탐색$\rightarrow$오프라인 구매, 오프라인 탐색$\rightarrow$온라인 구매)을 가져오는지 검증하였다. 영향 요인으로는 소비자 개인 특성, 제품 특성, 구매 상황과 관련된 10개 변수를 고려하였으며, 순차적 로짓(sequential legit) 기법을 사용하여 실증 분석한 결과를 요약하면 다음과 같다. 정보탐색 단계에서는 소비자의 채널에 대한 지식이 채널 선택에 영향을 미쳤으며 쇼핑에서 재미를 추구하거나 제품에 대한 관여도가 높은 경우 오프라인 채널을 선택할 가능성이 높게 나타났다. 반면에 온라인으로 쇼핑한 경험이 많은 소비자들은 온라인에서 정보를 탐색하는 경향이 높았다. 구매 단계의 검증결과는 탐색 채널에 따라 다르게 나타났다. 소비자가 온라인에서 정보를 탐색한 경우, 온라인 쇼핑경험이 많거나 가격추구의 쇼핑 가치를 크게 느끼거나 시간적 여유가 없는 소비자일수록 온라인에서 구매하는 경향이 높았던 반면에, 필요한 정보의 양이 많거나 제품에 대한 관여도와 인지된 위험이 높은 소비자는 구매 단계에서 오프라인 채널로 전환하였다. 한편 소비자가 오프라인에서 정보를 탐색한 경우, 쇼핑에서 편의나 재미를 추구하는 소비자와 시간적 여유가 없는 소비자일수록 오프라인에서 구매할 가능성이 높았고, 온라인 쇼핑경험이 많은 소비자는 구매 채널을 온라인으로 전환하는 경향이 높았다. 본 연구의 분석결과는 정보탐색 및 구매 단계에서 채널 선택에 영향을 주는 요인이 서로 다름을 보여주었으며 두 개의 채널을 모두 제공하는 유통 업자에게 매우 유용한 실무적 시사점을 제공한다.

• 한국정보시스템학회지:정보시스템연구
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• 제26권3호
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• KIEE International Transactions on Power Engineering
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• 제5A권2호
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• pp.177-185
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• 2005

This paper proposes an expert system that can enhance the accuracy of real-time bus reconfiguration strategy by adopting the local minimum tree search method and that can minimize the spreading effect of the fault by considering the operating condition when a main transformer fault occurs in an automated substation. The local minimum tree search method is used to expand the best-first search method. This method has the advantage that it can improve the solution performance within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. The second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules from the obtained switching candidate set. Also, this paper proposes generalized distribution substation modeling using graph theory, and a substation database based on the study results is designed.

• 한국통신학회논문지
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• 제25권1B호
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• pp.128-140
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• 2000

본 논문에서는 이웃 탐색점에서의 평균 절대치 오차 (mean absoulte error, MAE) 및 탐색여역 줄임을 이용한 고속 블록 정합 알고리듬 제안하였다. 이 알고리듬은 두 단계로 구성되어있다. 첫 번째 단계에서는 탐색영역을 3$\times$3 크기의 영역으로 겹치지 않게 나눈 뒤, 각 영역의 중심 탐색점에 대하여 블록 정합을 행하여 MAE를 구하고, 이들 중 가장 작은 MAE를 기준 MAE로 정한다. 그리고, 두 번째 단계에서는 각 영역의 중심 탐색점에서의 MAE를 이용하여 각 3$\times$3 영역의 나머지 탐색점에서의 MAE의 최소 범위를 구한 뒤, 최소 범위가 기준 MAE로 결정된 탐색점 근처에 존재할 가능성이 매우 큼을 이용하여 기준 MAE로 결정된 탐색점을 중심으로 탐색영역의 크기를 줄인 뒤, 블록 정합이 필요한 탐색점에 대하여서만 블록 정합을 행함으로써 고속으로 움직임을 추정하였다. 모의 실험을 통하여 본 제안한 방법이 우수한 움직임 추정 성능을 유지하면서도 많은 계산량의 감소를 얻을 수 있음을 확인하였다.

• 한국의류산업학회지
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• 제11권4호
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• pp.537-548
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• 2009

Consumers' price related response in the clothing purchase decision-making process includes their expectation of price, price perception, attitude toward price and consequent behaviors. The purposes of this research are to systematically organize consumers' price related responses in the clothing purchase decision-making process, and to explain the effect of price on their purchasing. The qualitative research including shopping observation and in-depth interview was conducted. The result identified stages that showed different price related responses in clothing purchase decision-making process, and clarified each stage's characteristics. In the internal search stage, consumers recalled price information from memory and had a specific expectation about the price. This set a direction for the external search. In the external search stage, consumers selected brands or stores by a non-compensatory evaluating with an expectation of the price, and narrowed these down to several determinant alternatives by actively evaluating the products. In case a sufficient amount of price information was not recalled, the consumer established reference price through the external search. Finally, in the purchasing stage, consumers evaluated the determinant alternatives based on their compensatory evaluation. When perception of price was negative, consumers evaluate price combined with the higher criteria of clothing benefits, such as symbolic value and usability. The research is expected to contribute to predicting consumers' responses to price, and to establishing an effective pricing strategy.