감지추구자적매체습관(感知追求者的媒体习惯) (Media Habits of Sensation Seekers)
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- 마케팅과학연구
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- 제20권2호
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- pp.179-187
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- 2010
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对营销和广告经理来说, 理解消费者的偏好和使用的媒体类型是非常有必要的, 尤其是在如今市场细分的情况下. 清晰的理解能帮助经理更有效的选择合适的媒体. 而且由于性格特征的不同, 个人对媒体类型的选择和使用都不相同. 本文测试了一个性格特征, 即感知追求. 这是在测试 "新" 媒体偏好和使用的文献中尚未出现的. 感知追求是被定义为 "一种对变化, 新颖和复杂的感觉的需要和经历. 以及为承担这些经历愿意承受生理的和社会的风险" (Zuckerman 1979). 根据文献回顾, 我们提出了6个假设. 我们尤其关注使用与满足理论(Katz 1959), 这个理论解释了为什么人们选择媒体类型和他们使用不同媒体类型的动机的原因. 目前的理论表明高感知追求者(HSS), 由于他们对新颖, 激励和非传统的内容和想象的需要, 他们会更多的使用新媒体. 因此, 我们假设高感知追求者比低感知追求者(LSS)(H2a)或中等感知追求者(MSS)(H2b)会更多的使用网络而不是广播(H1a)或印刷媒体(H1b). 另外, 高感知追求者有更多的社交活动及朋友, 因此他们会比低感知追求者(a) 和中等感知追求者(b)更多的使用社交网络网页例如Facebook/MySpace(H3) 以及聊天室(H4). 感知追求者可以显示出一系列的行为包括抑制解除. 我们认为具有高水平去抑制的人们比低水平或中等水平的人们会更多的使用社交网络如Facebook/MySpace (H5) 和聊天室(H6). 我们的数据来源于对参加极限运动的参与者的网上调查. 为得到这个群组的信息, 我们使用雪球样本技术的提高版, 即连锁推荐方法来选择应答者. 这种方法被认为是对隐藏人群进行有效估算的方法(Heckathorn, 1997). 最终的有效样本包括1108名应答者. 主要是年轻人(56.36%在34岁以下), 男性(86.1%)和中产阶级(58.7%的家庭收入超过50,000美元). 我们用这个样本来进行感知追求的研究. 我们用简要感知追求量表来测试感知追求(Hoyle et al. 2007). 我们用自我报告使用过的不同媒体类型来测量媒体使用. 结果并不支持H1a和b. 高感知追求者并没有更多的使用网络这样的媒体. 事实上, 同其他的媒体类型相比, 这个平均水平是较低的. 高感知追求者使用最多的媒体类型时印刷媒体, 这说明了一种对主流的反抗. 结果支持H2a和b. 高感知追求者比低感知或中等感知追求者更多的使用网络. 进一步的分析揭示了在高感知和低感知追求者之间在使用印刷媒体方面有显著不同. 高感知追求者在他们感兴趣的极限运动方面会追求更专业的印刷出版物. 假设3a和b 揭示了高感知追求者比低感知或中等感知追求者更多的使用Facebook/MySpace. 在使用聊天室方面低感知和高感知追求者之间没有显著差距. 所以结果也不支持假设H4a, 但是H4b的结果是显著的. 不同抑制解除水平的应答者被认为使用Facebook/MySpace 和聊天室的水平也不同. 去抑制水平高比低水平或中等水平的使用Facebook/MySpace的水平高. 所以H5a和b 被支持. 类似的, H6b也被支持. 去抑制水平高的人们使用聊天室的概率显著多于中等水平的但并不多于低水平的人们(H6a). 这些结果为管理者提供了一些有趣的见解. 第一, 尽管高感知追求者比低感知或中等感知追求者更多的使用在线媒体, 但他们使用在线媒体仍然少于印刷或广播媒体. 广告执行者们不应该对这个重要的客户群过分的强调在线媒体. 第二, 社交媒体, 例如Facebook/MySpace和聊天室会是接近这个群体的有潜力的方法. 最后, 对去抑制水平高的群体, 有公共关系方面的启示. 这些个体更倾向于一些社会风险的行为. 这些直接的启示包括因特网捕食者和未来的雇主. 本研究的一个不足是受访者都是参与极限运动的. 这本身就是一个高感知追求者活动. 更大范围的人群需要被测试.
회사채 신용등급은 투자자의 입장에서는 수익률 결정의 중요한 요소이며 기업의 입장에서는 자본비용 및 기업 가치와 관련된 중요한 재무의사결정사항으로 정교한 신용등급 예측 모형의 개발은 재무 및 회계 분야에서 오랫동안 전통적인 연구 주제가 되어왔다. 그러나, 회사채 신용등급 예측 모형의 성과와 관련된 가장 중요한 문제는 등급별 데이터의 불균형 문제이다. 예측 문제에 있어서 데이터 불균형(Data imbalance) 은 사용되는 표본이 특정 범주에 편중되었을 때 나타난다. 데이터 불균형이 심화됨에 따라 범주 사이의 분류경계영역이 왜곡되므로 분류자의 학습성과가 저하되게 된다. 본 연구에서는 데이터 불균형 문제가 존재하는 다분류 문제를 효과적으로 해결하기 위한 다분류 기하평균 부스팅 기법 (Multiclass Geometric Mean-based Boosting MGM-Boost)을 제안하고자 한다. MGM-Boost 알고리즘은 부스팅 알고리즘에 기하평균 개념을 도입한 것으로 오분류된 표본에 대한 학습을 강화할 수 있으며 불균형 분포를 보이는 각 범주의 예측정확도를 동시에 고려한 학습이 가능하다는 장점이 있다. 회사채 신용등급 예측문제를 활용하여 MGM-Boost의 성과를 검증한 결과 SVM 및 AdaBoost 기법과 비교하여 통계적으로 유의적인 성과개선 효과를 보여주었으며 데이터 불균형 하에서도 벤치마킹 모형과 비교하여 견고한 학습성과를 나타냈다.
많은 정보통신기술 기업들은 자체적으로 개발한 인공지능 기술을 오픈소스로 공개하였다. 예를 들어, 구글의 TensorFlow, 페이스북의 PyTorch, 마이크로소프트의 CNTK 등 여러 기업들은 자신들의 인공지능 기술들을 공개하고 있다. 이처럼 대중에게 딥러닝 오픈소스 소프트웨어를 공개함으로써 개발자 커뮤니티와의 관계와 인공지능 생태계를 강화하고, 사용자들의 실험, 적용, 개선을 얻을 수 있다. 이에 따라 머신러닝 분야는 급속히 성장하고 있고, 개발자들 또한 여러가지 학습 알고리즘을 재생산하여 각 영역에 활용하고 있다. 하지만 오픈소스 소프트웨어에 대한 다양한 분석들이 이루어진 데 반해, 실제 산업현장에서 딥러닝 오픈소스 소프트웨어를 개발하거나 활용하는데 유용한 연구 결과는 미흡한 실정이다. 따라서 본 연구에서는 딥러닝 프레임워크 사례연구를 통해 해당 프레임워크의 도입 전략을 도출하고자 한다. 기술-조직-환경 프레임워크를 기반으로 기존의 오픈 소스 소프트웨어 도입과 관련된 연구들을 리뷰하고, 이를 바탕으로 두 기업의 성공 사례와 한 기업의 실패 사례를 포함한 총 3 가지 기업의 도입 사례 분석을 통해 딥러닝 프레임워크 도입을 위한 중요한 5가지 성공 요인을 도출하였다: 팀 내 개발자의 지식과 전문성, 하드웨어(GPU) 환경, 데이터 전사 협력 체계, 딥러닝 프레임워크 플랫폼, 딥러닝 프레임워크 도구 서비스. 그리고 도출한 성공 요인을 실현하기 위한 딥러닝 프레임워크의 단계적 도입 전략을 제안하였다: 프로젝트 문제 정의, 딥러닝 방법론이 적합한 기법인지 확인, 딥러닝 프레임워크가 적합한 도구인지 확인, 기업의 딥러닝 프레임워크 사용, 기업의 딥러닝 프레임워크 확산. 본 연구를 통해 각 산업과 사업의 니즈에 따라, 딥러닝 프레임워크를 개발하거나 활용하고자 하는 기업에게 전략적인 시사점을 제공할 수 있을 것이라 기대된다.
본 연구의 목적은 가정교과에서의 안전교육 관련 연구 동향을 파악하여 이 분야에서의 다양하고 균형 있는 연구개발을 위한 기초자료를 제시하는데 목적이 있다. 이를 위하여 2001년부터 2015년까지 한국연구재단 등재지에 게재된 가정교과 관련 15개 학회지의 논문 중 '안전'을 직접적으로 언급한 경우와 안전교육 영역과 관련된 내용을 다룬 논문(244편)과 '안전'을 키워드로 제시하여 검색한 석 박사학위 논문(179편)을 대상으로전집 표집하였다. 분석 내용은 안전교육 관련 논문의 연도별 주제별 연구동향과 안전교육의 영역별 연구방법별 연구동향이다. 본 연구의 결과는 다음과 같다. 첫째, 가정과 교육에서 안전 교육에 관한 연도별 연구논문의 편수는 증가와 감소를 반복하여 매년 14-52편으로 연간 평균 28.2편 정도 지속적인 안전교육에 관련된 연구가 이어져온 것으로 나타났다. 반면, 2015년에는 논문 연구수가 2014년의 26편의 2배인 52편으로 가장 많은 연구가이루어졌는데 이는 정부의 안전종합대책 발표와 교육부의 2015개정 교육과정에서의 안전내용 강조 때문으로 생각된다. 둘째, 연구 주제의 동향을 살펴보면 안전교육관련 논문은 137(29%)편, 안전실태 관련 논문은 336편(71%)으로 2009년 이전에는 사고 실태나 인식 조사가 많은 비율을 차지(74.4%)하였고 반면, 2009년 이후에는 안전교육 프로그램 개발이나 효과 검증, 교육자료 개발, 교육방법 개발 등에 대한 연구가 증가(21편
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.
In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.
흡연은 만성 폐쇄성 폐질환의 가장 흔하고 중요한 원인이며 발생기전으로 단백분해효소 및 그 억제제의 불균형에 의한 폐조직 파괴가 중요한 역할을 한다고 알려져 있다. 생체내의 여러 단백분해효소 중 matrix metalloproteases (MMPs) 의 역할에 대한 연구가 최근 활발한데, 이들의 다수는 젤라틴 분해능을 보인다. 연구자들은 흡연에 의한 MMPs의 발현 및 폐기종 발생과의 관련성을 규명하기 위한 첫 단계로 기니픽에서 흡연에 의한 젤라틴 분해 단백분해효소의 발현 양상을 알아보고자 하였다. 방 법 : 500gm 가량의 건강한 기니핀 15마리를 대조군 5마리, 6주 흡연군 5마리, 12주 흡연군 5마리 씩 배정한 후, 하루에 5시간 씩, 담배 20개피를 간접 흡연시키는 과정을 일주일에 5회 반복하였다. 흡연력의 정도에 따른 폐조직 내 세포 침윤의 증가를 알아보기 위해, 폐조직을 H&E 염색한 후 400배 확대 시야에서 보이는 폐포벽의 세포 수를 계산하여 일반선형모델을 이용한 통계 분석법으로 처리하였다. 흡연에 의한 젤라틴 분해 단백분해효소의 발현 양상을 알아보기 위해 기관지폐포세척술을 시행하여 폐포내 세포를 얻은 다음 이를 배양접시에
이 글은 2000년대 일본의 대북제재가 북한의 대외거래에 미친 효과를 측정한다. 이를 위해 우리는 대북제재의 경제적 효과를 개념화하는 것으로부터 시작하여, 현존하는 북한무역통계를 토대로 일본 대북제재의 효과가 존재하는지 유무를 검증하고, 마지막으로는 현존하는 통계를 합리적으로 재구성함으로써 일본의 제재 효과를 계량적으로 측정한다. 이러한 과정을 통해 우리가 도달한 결론을 요약하면 다음과 같다. 첫째, 국제사회의 경제제재는 북한의 무역에 당사국 효과와 제3국 효과라는 두 가지의 영향을 미친다. 전자는 제재 당사국과 북한의 무역이 줄어드는 것을 의미하며, 후자는 이에 따라 북한과 여타 국가 사이의 무역도 영향을 받는 것을 말한다. 둘째, 이러한 제재의 효과를 분석하기 위해서는 북한무역에 대한 정밀한 통계자료의 입수가 필수적이지만, 현존하는 북한의 무역통계는 모두 특정 국가와 북한의 거래를 잘못 보고하거나, 또는 북한의 실제 거래 국가를 누락하는 등 일정한 결함을 내포하고 있다. 셋째, 이러한 통계의 결함을 감안한 상태에서 이를 우회하는 방식으로 분석을 진행해보면, 일본의 대북제재는 뚜렷한 당사국 효과와 제3국 효과를 동시에 갖는 것으로 나타난다. 일본의 제재로 북일무역은 줄어들지만, 북한은 이를 여타 국가와의 거래확대로 중화시킨다는 뜻이다. 다만, 이러한 제3국 효과는 북한의 수출과 수입에 있어 다르게 나타난다. 수출의 경우에는 한국과 중국, 태국 등 북한의 주요 거래상대국들에서 모두 정(+)의 제3국 효과가 존재하지만, 북한의 수입에 있어서는 한국이나 심지어 중국에 있어서도 제3국 효과의 통계적 유의미성이 부정되는 것이다. 넷째, 일본의 제재 효과를 계수적으로 측정하기 위해서는 현존하는 북한무역통계를 보다 정밀하게 재구성해야만 하는데, 이러한 재구성은 북한의 수입에 있어서는 불가능하지만 수출에 있어서는 가능하다. 이렇게 재구성된 데이터를 토대로 추정하면, 2004~06년 북한의 대일 수출은 일본의 대북제재로 연간 0.8억~1.2억달러의 피해를 입은 것으로 나타난다(당사국 효과). 이는 2003년 북한의 대일 수출액의 60%에 해당한다. 그런데 같은 기간 동안 북한은 일본의 제재에 맞서 다른 나라로의 수출선 전환을 추진하였고, 그 결과 연간 0.8~0.9억달러에 달하는 여타 국가로의 수출증대 효과를 보았다(제3국 효과). 여섯째, 이러한 북한 거래선 이전의 60~70%는 한국(남북교역)에 의해 가능해진 것으로 나타난다. 반면, 중국으로의 거래선 이전은 미미하거나 유의미하지 않은 것으로 나타난다. 일곱째, 북한의 수입에 관해서는 이처럼 계수적으로 제재의 효과를 추정하는 일이 불가능하다. 그러나 비록 결함이 있지만 현존하는 북한무역통계는 일본의 제재가 북한의 수출보다는 수입에 더 큰 영향을 미친다고 말한다. 따라서 일본의 제재가 북한의 수출에 있어 별다른 영향을 미치지 못한다고 해서, 곧바로 제재의 효력 자체가 없다고 단정하는 것은 현명하지 못하다.