본 연구는 농촌지역인 자연공간과 시가화공간이 복합적으로 나타나고 있는 중국 호남성 일부 농촌지역 읍·면을 사례지로 선정하여 토지이용 및 개발계획 전해 시에 경관활성화 적용을 위한 기준 제시에 큰 의의가 있다. 이를 위해 우선 토지이용/토지피복도(LU/LC Map)를 기반으로 ArcGIS를 활용하여 연구대상지의 경관다양성 평가를 수행하고 시공간적 변화를 분석하였다. 연구대상지의 경관다양성을 정량적으로 구축하기 위하여 해상도 5x5의 크기로 적절하여 FRAGSTATS를 통하여 경관패턴지수를 분석하였다. 추출된 경관패턴지수 중에 높은 상관도를 나타내는 지수를 제외한 후, PLAND, PD, LSI, AREA-MN, ENN_MN, 그리고 AWMSI 등 6개 지수를 이용하여 최종적으로 3개(44.3%, 33.7%, 8.9%) 주성분(PCA)을 추출하였다. 결과를 보면 본 대상지에 수역, 습지, 산림지역을 경관다양성이 상당히 높게 측정되었으며, 일부 시가화지역이 초지로 전환된다. 또한 시가지역이 확장함에 따라 생태관광지역 일대의 개발제한구역을 중심으로 경관다양성이 증가되었으며, 지속가능한 농촌지역을 재개발하는 데는 자연 공간을 보전 하고 유지하는 것이 가장 바람직하다. 본 연구결과는 중국에서 새롭게 개발될 「국토공간계획(國土空間計劃)」에 경관다양성을 적용하기 위한 다각적인 정책 기준을 뒷받침할 수 있는 중요한 기초자료가 될 수 있을 것이다. 또한 본 연구에서 활용된 연도별 토지이용/토지피복은 자연적인 공간과 인공적인 공간의 분포 현황을 3차원인 시공간적으로 판단하기 때문에 실제 드러나는 경관은 인위적인 영향 등으로 인해 다르게 나타날 수 있을 것이다. 따라서 향후 연구에서는 농촌지역 정주자 생활권의 변화 등과 같은 다양한 요인도 복합적으로 고려해야 할 것으로 판단된다.

Online reviews enable brands to promote their products by means of word-of-mouth communication. In an e-commerce environment, user-generated customer feedback, as a form of electronic word-of-mouth (eWOM), is a crucial source of information in the prepurchase stage as many customers base their purchase decision on feedback from other customers. eWOM is perceived as a reliable source of information and has become especially important in an online environment (Chevalier & Mayzlin, 2006; Li & Zhan, 2011). Existing research has shown that customer feedback positively influences sales (Chevalier & Mayzlin, 2006; Forman, Ghose, & Wiesenfeld, 2008; Ha, Bae, & Son, 2015). Yet, only very limited research on how to communicate customer feedback to maximize a company’s top-line growth has been conducted (Packard & Berger, 2017). In this study, we aim to fill this gap by investigating how numerical customer feedback metrics should be communicated to attract new customers. Using an experiment, we empirically investigate which of the two widely established numerical customer feedback metrics, a customer recommendation rate or a customer satisfaction rate, is better suited to attract new customers and hence stimulate company growth. The impact of the stimulus on the purchase process is measured by means of three different dependent variables to imitate the hierarchy of a purchase decision: consumers’ interest towards the ad, their attitude towards the product shown in the ad as well as their purchase intention. Furthermore, we include several moderating factors, which have proven to be relevant when looking at online reviews, namely product type as well as consumers’ motivation and ability to process persuasive communication (Gupta & Harris, 2010; Klein, 1998; Petty & Cacioppo, 1986).

Introduction The concept of brand equity has been receiving considerable interest from academia and practice in the past decades. While mutual understanding exists on the importance of establishing high-equity brands, less agreement among academics and practitioners prevails regarding its conceptualization and operationalization. Many approaches have been proposed to measure brand equity in academic literature and numerous competing companies such as Millward Brown, Interbrand, or Young & Rubicam offer commercial metrics and brand evaluations, which are likely to estimate different values to a specific brand. This study reflects a consumer-based perspective on brand equity, which resides in the heart and mind of the consumer and captures the value a brand endows beyond the attributes and benefits its products imply. Growing calls for the accountability of marketing has resulted in increasing interest in marketing metrics, which includes mind-set metrics to address the “black box” between marketing actions and consumer actions in the market. Theoretical Development One of the most prominent conceptualizations of brand equity is based on the premise that brand equity is “the differential effect of brand knowledge on consumer response to the marketing of the brand” consisting of brand awareness and brand image as the predominant dimensions that shape brand knowledge. In this model, a crucial role is ascribed to consumer’s associations with a brand as a reflection of its image. Accordingly, brand building and differentiation is based on establishing favorable, strong, and unique associations. Human associative network theory is a widely accepted concept to explain the storage and retrieval of information and has been largely applied in the context of brands. Associative network theory suggests that brand information is stored in long-term memory in a network of nodes that are linked to brand associations such as attributes, claims or evaluations. Consumers use brand names as cues to retrieve associations. Once cues activate corresponding nodes and consumers retrieve information from memory, the activation spreads to related nodes. Consequently, a transfer of associations can also occur through associative chains in a process of attitude formation. Consumer response to a brand can be of attitudinal and behavioral character and research on attitudes supports the general notion that both, affective and cognitive structures, explain attitude formation. The predictive properties of attitudes regarding actual behavior have been acknowledged by prior research and the attitude-behavior relationship has been established. Research Design Operationalization of Brand Equity This study distinguishes between attitudinal and behavioral measures of brand equity. The behavioral measures of brand equity should reflect the attitudinal brand equity components in predicting product-market outcomes. High brand equity should lead to a willingness to pay a price premium, purchase intention and willingness to recommend. Survey Brand equity measures are tested with two waves of data collection2 from online surveys conducted in 2015 and 2016. Respondents were recruited from a professional panel provider to ensure that the same respondents participated in wave two after a year from the first wave. Participants were selected according to a quota regarding age and gender to increase representativeness and were then randomly assigned to one of the three industries beer, insurance, and white goods capturing brand equity from different perspectives and allowing for a more holistic view. Sample The sample for the first wave consists of 2.798 respondents. The sample was matched with the response from wave two and only those respondents were selected who participated in both waves. Given the panel mortality rate, the final sample size for longitudinal analysis is 1.292 observations. The respondents’ age ranges from 18 to 74 with 52 percent being male and 48 percent female. Analysis Panel regression is used to estimate models assessing the relative importance of various brand equity metrics regarding the three outcome variables for the three categories included. The results suggest that no universal brand equity metric dominates that can be applied to predict behavioral outcomes across categories. Yet, category-specific brand equity metrics prevail across outcomes. Consumers seem to evaluate a strong brand as an entity they can personally connect to in the insurance category. In the beer category, consumers’ evaluation of strong brands reflects deep affect and the perception of product quality. High equity brands relate to loyal consumers with strong affective evaluations in the category of durable household products. Moreover, the results indicate that brand equity measurement can be simplified to a small subset of metrics without risking loss of model fit and predictive power. Discussion While a plethora of brand equity metrics exists, the results of this study suggest that brand managers can apply a small subset of available metrics to track their brands’ equity and predict behavior without implementing long surveys that require considerable time and effort from increasingly overloaded consumers. Yet, adjustments to the composition of brand equity metrics might be inevitable in light of category-specific effects. Moreover, the results reveal that a consideration of metrics capturing affective components such as brand self-connection and deep feelings such as brand love is indispensable for brand equity measurement. Including emotional measures and extending established brand equity metrics that are deeply rooted in extant research might provide a considerable advantage when it comes to measuring brand value in different product categories. References are available upon request.

This study explores how internal and external factors influence the design and use of marketing performance measurement (MPM) practices in Chinese firms. The results show that a firm’s MPM practice is subject to its characteristics (e.g., marketing dashboard, market orientation, marketing complexity) and its external condition (i.e., market turbulence).

Products are successfully designed only when they are in accord with the users’ emotional needs. A systematic research approach is aimed to propose that physiological metrics can be effectively used to assess user emotion and behavior intention based on an eye tracker and neurophysiological approach. Forty participants (20 males and 20 females, mean age=35.6, SD=6.38, range 21-48 years), were recruited from college campuses and communities to conduct an eye tracker and electroencephalography (EEG) experiment with the presented stimuli (images of SUVs). The study uses partial least squares structural equation modeling (PLS-SEM) to test the model hypotheses. The results show a strong and significant relationship between eye tracker metrics, neurophysiological metrics, user affective responses, and behavior intention. These findings could enable industrial counselors, professional product designers, and academics to categorize users’ emotional needs that can be subsequently incorporated into final product design.

다양한 이미지 샘플의 Eye test를 바탕으로 기술적인 화질 지표 조절을 통하여 감성 화질을 최적화 시키는 방법이 소개된다. 여러 가지 이미지 콘텐츠의 다양한 이미지에 대하여, 콘트라스트, 명도, 채도 화질 지표 톤 커브를 사용하여 평가가 수행 되었다. 이미지 화질 향상에 기여하는 우선순위는 명암, 채도 및 밝기 순으로 분석 되었다. 이미지 감성 화질 측정치의 기술적인 화질 지표 변화에 따른 기울기의 공통점을 살펴본 결과, 거의 0, 중간 그리고 최대 기울기의 영역으로 구성된 함수 형태로 모델링을 할 경우, 기존의 역 U 형태의 성질 뿐 아니라 log 또는 포화 형태의 감성 화질 변화까지 분석 가능함을 알 수 있었다. 단일 및 복수의 화질 지표의 경우에 대하여도 화질 개선 방안이 모색 되었으며, 기존 및 본 논문에서 분석된 결과를 위한 새로운 함수가 소개 되었다. 복수의 통합적 이미지 화질 지표를 통하여 향상 시킬 경우 오직 몇몇 한정된 지표 제어의 경우에만 실현 가능하다는 것을 알 수 있었다. 또한, 화질 향상 방법은 영상 콘텐츠에 따라 크게 차이가 없음을 알 수 있었다.

최근 조직공학 기술의 발달로 재해와 질병으로 인한 손상된 조직과 장기의 대체연구들 이 진행되고 있다. 장기 대체 연구의 핵심 요소 중 하나는 재건된 조직이나 장기가 혈관 망을 형성하여 host tissue로부터 양분과 산소의 전달이다. 본 연구는 조직공학 기법을 이용하여 장기 재건에 필수적인 혈관 재건을 위해 혈관을 구성하는 주세포인 endothelial cell을 체외에서 배양하는 것이다. Endothelial cell(EC)배양을 위해서는 세포지지체인 세 포외 기질(External cellular metrics, ECM)을 필요로 하기 때문에 ECM중에 대표적인 collagen과 gelatin을 사용하여 지지체에 따른 체외배양능을 비교하였다. 실험 동물로는 돼지 대동맥을 채취하여, 대동맥 속에 collagenase type I을 주입하고, 혈관의 입·출구를 봉합한 상태로 10분 간 37℃에서 처리하였다. 관류된 용액은 10% FBS가 함유된 기본배 양액(EGM-2 media)을 사용하여 2번 수세한 후 회수된 세포를 각각의 ECM이 처리된 dish위에서 배양 하였다. EC세포인지를 확인하기 위해서 EC표지 인자인 CD31과 vWF 항체의 발현을 flow cytometry로 확인 하였고, 회수된 세포에서 두 단백질이 모두 발현 되었다. ECM에 따른 EC의 세포 형태를 비교하였을 때 형태학적 차이는 없었다. Basement Membrane Extract위에서 calcein-AM으로 염색된 EC는 ECM의 종류와 상관 없이 2-6시간 사이에 Tube Formation을 보였다. 또한 endothelial cell의 표지 마크인 CD31, Flk1, vWF의 mRNA 발현양과 IHC에 의한 단백질 발현을 조사한 결과 collagen 지지체 위에서 배양된 endothelial cells에서 발현양이 더 높았다. 결론적으로 두 가지 ECM에서 모두 성공적으로 endothelial cell의 배양이 가능하지만 collagen위에서 배양된 endothelial cell이 더 우수한 maintenance능력을 가짐을 확인 할 수 있었다.

Anna Dello Russo has worked with H&M, the Sartorialist's Scott Schuman has written his second book and home-grown Susie Bubble has consulted for Gap, Armani and Selfridges to name a few. There is no doubt that these figures are key influencers in the world of fashion and they are turning their efforts and knowledge into fiscal benefits. Fashion blogs have become not only a form of user-generated content, a medium for communicating to the masses without any prior training or knowledge, but have also evolved to become a new marketing communications channel in their own right. Fashion writers are not only dictating content to esteemed fashion titles that were once only contributed to by the fashion journalist elite, but they are engaged as brand consultants with the aim of shaping the future direction of brands in terms of content, style and scope. When did all this power and influence happen and how can we measure it? This is the central question inherent to this study’s focus. The dynamic nature of digital, online and social media activities means that most research is out of date or getting closer to ‘expiry’ even as the ink dries on the page. To exemplify: research dated just three years ago still includes MySpace in a comprehensive list of online networks and social media sites (e.g. Mir and Zaheer, 2012) and ‘second life’ as an innovation [albeit this has been experiencing somewhat of a renaissance within certain consumer sectors in recent times]. This aside, the point is thus: academic scholarship cannot keep up with the rapid rate of digital change in the landscape, but it continues to try, as does this humble study. A volume of research has recently contributed to the understanding of the influence of social media in the fashion sphere, predominately from an electronic word-of-mouth (e-wom) perspective, for example (Bronner and Hoog, 2013; Fang, 2014; Hennig-Thurau, 2004; Kulmala et al., 2013; Liu, 2006; Trusov et al., 2009) engagement with social media (e.g. Campbell et al, 2012; Dhaoui, 2014). This body of literature has supplied a solid foundation for understanding why user-generated content may be shared and under what circumstances and to whom. However, a limitation of these significant contributions are reasons for propensity to influence, that is, once it has been shared, distributed and circulated, how do we measure the impact of this influence? Yes we can use analytics to quickly demonstrate quantitative and numerical impact in terms of followers, traffic, interaction, sales and (not so quickly) the wider reach of blogs on PR for brands, brand-metrics and customer engagement. But what about the wider influential impact of key social media writers and opinion leaders, or those that follow and listen to them: how can we evaluate this impact of influence? How does it work? Why does it work with some over others? We seek to find answers around this notion of social influence and ask: why do people listen to bloggers? Do consumers of this information distinguish between platforms: do they prefer blogs? Twitter? Picture-content through Instagram or Pinterest? Is there a gender difference? Considering also the rise in ‘erasable’ social media in the form of SnapChat, which lasts ten seconds before ‘self destructing’: what impact are these having in terms of influence in particular sectors like fashion, how can brands harness this power and use it to build equity, target new consumers, increase sales and revenue? In other geographical domains, such as China, where social media constraints and censorship are notable, emerging applications like WeChat are increasing in popularity, first with consumers, but retail and fashion brands are also beginning to endorse them to facilitate a meaningful conversation with their customers through these innovations. We also aim to explore the current state of play regarding terminology for social media contributors – are they still bloggers even though they create content across-platform? (It would be unusual for example, for a popular and credible blogger to only have a blog and no twitter or Instagram activity). Is the term blogger naturally all-encompassing or is it a misnomer that we need to create new terminology to explain these phenomena? Cullen (2014) the fashion magazine editor of Elle Australia created a blogger award ceremony to honour the contribution of these fashion influencers and comments that: “We picked the ones that we felt have the most traction with our readers. It is very clear we are in a blogger boom right now and everyone wants to jump on the bandwagon and [the nominees] gave fashion this new relevance. They took fashion and democratized it, so rather than have to see what the designer wanted you to see [on the catwalk], they took the runway fashion and put it together in their own ways. They made it wearable, as they mixed it with other labels and all those things that make an outfit work for real life.” This quote serves to illuminate an example of the commercial impact of fashion bloggers in the fashion sector and the relevance that influential opinion leaders believe they can have on their readership. Thus, we seek, through our research, to interrogate existing literature on social media, marketing, consumption and consumer psychological theories in the context of fashion influence with the aim of contributing to understanding in this fast-evolving transformative sector. Social media has been defined as: ‘A group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content. (Kaplan and Haenlein, 2010, .61). Within this context, social media applications exist to facilitate user interaction, and include blogs, content communities, discussion boards and chat rooms, product and/or service review sites, virtual worlds, and social networking sites (Kaplan and Haenlein, 2010; Mangold and Faulds, 2009). In this paper we focus on social networking, which refers to applications, such as Facebook and Twitter, Instagram/Pinterest and more disposable aps like Snapchat. Essentially, we take an all-embracing approach to understanding social media, as this is simply how it is used by consumers, in the virtual landscape (for example, users do not distinguish between platforms, they simply use the most appropriate means to communicate their content at that time). We aim to contribute a perspective that is original by investigating existing literature in two territories: social media influence and Social Impact Theory, which we will use as a theoretical perspective to explore the influence of social media on fashion. A Theoretical Lens: Social Influence Theory (SIT) After dismissing other theoretical frameworks for our study’s focus including: Uses and Gratifications theory; Involvement and Motivation, the choice to focus on Social Impact Theory (SIT) (Latane, 1981) was rationalized by the centrality of influence as a construct, to the characteristics of the theory. SIT (Latane, 1981) maintains, “as the number of people increases the impact on the target individual’s attitude and behavior enhances”. As influence is inherent to our aim, this theory, albeit being created almost two decades before the concept of social media, may have transferable qualities that may aid comprehension of understanding into the complexities associated with understanding the influence of social media in the fashion sector. This seemingly large leap from a traditional application of the theory to the virtual world is made more plausible by at least one previous study, that has started to also recognize the value of this framework for understanding online activity for example, Mir and Zaheer (2012) who use SIT in the contexts of social media and banking. The theory has not however, been used thus far in the realm of fashion and social media, thus, a study of this kind aims to contribute to knowledge in this field. Social impact has been defined by the founding father of the theory as: ‘Any of the great variety of changes in physiological states and subjective feelings, motives and emotions, cognitions and beliefs, values and behavior, that occur in an individual, human, or animal, as a result of the real, implied or imagined presence or actions of other individuals’. (Latané, 1981, p. 343) Latané (1981) created social impact theory to validate his hypothesis about how influence works, which led to the identification of three factors that make up social impact theory: 1) Strength: How important is the influencing group to the target of the influence; 2) Immediacy: How close in proximity and in time is the influencing group to the target of the influence; 3) Number: How many people are in the influencing group. Taking each one of these in turn, the leverage of these variables to a social media context seems obvious. Social media by its very nature encourages a ‘pull’ approach to groups or communities (hence the ‘strength’ variable); the ‘immediacy’ of social media in the sense that messages can be communicated and responded to in real time, have been facilitated by social media capabilities. Finally, the third variable of SIT is ‘number’; in a virtual world, there is a real sense that there is no limit to the amount of people you can communicate with. To exemplify, we refer to Facebook with its 9 Billion plus users as an example of this reach, or Lady GaGa with her 44 Million plus followers on Twitter. This succinct insight into SIT theory provides a short rationale as to its applicability to a social media context, specifically the fashion sector. A more in-depth analysis of its use and application to this study will be developed for the final paper following data collection.

The amount of data in companies today in terms of volume, velocity and variety is unique in the history of business. Despite on-going calls for more accountability of the marketing function, there is a lack of studies that examine the role of metrics in order to interpret this data. This study focuses on how marketing metrics and financial metrics are used within organizations to both quantify and to explore data relevant for marketing mix decision-making. An analysis of primary data from six case studies and 29 marketing mix decisions promises to provide a rich understanding of the activities and metrics that are used to trigger and inform managerial decision-making. The aim is to contribute to the body of knowledge on metrics use with the aim of improving managerial decision-making, marketing mix performance and the standing of the marketing function in the firm.

This research discusses the characteristics and the implementation strategies for two types of quality metrics to analyze innovation effects in six sigma projects: fixed specification type and moving specification type. Zst, Ppk are quality metrics of fixed specification type that are influenced by predetermined specification. In contrast, the quality metrics of moving specification type such as Strictly Standardized Mean Difference(SSMD), Z-Score, F-Statistic and t-Statistic are independent from predetermined specification. Zst sigma level obtains defective rates of Parts Per Million(PPM) and Defects Per Million Opportunities(DPMO). However, the defective rates between different industrial sectors are incomparable due to their own technological inherence. In order to explore relative method to compare defective rates between different industrial sectors, the ratio of specification and natural tolerance called, Ppk, is used. The drawback of this Ppk metric is that it is highly dependent on the specification. The metrics of F-Statistic and t-Statistic identify innovation effect by comparing before-and-after of accuracy and precision. These statistics are not affected by specification, but affected by type of statistical distribution models and sample size. Hence, statistical significance determined by above two statistics cannot give a same conclusion as practical significance. In conclusion, SSMD and Z-Score are the best quality metrics that are uninfluenced by fixed specification, theoretical distribution model and arbitrary sample size. Those metrics also identify the innovation effects for before-and-after of accuracy and precision. It is beneficial to use SSMD and Z-Score methods along with popular methods of Zst sigma level and Ppk that are commonly employed in six sigma projects. The case studies from national six sigma contest from 2011 to 2012 are proposed and analyzed to provide the guidelines for the usage of quality metrics for quality practitioners.

This paper proposes a strategic model of linkage between productivity metrics and financial accounting metrics to properly evaluate the financial effect of TPM activities and the business performance. This linkage strategy provides a connection tool for clear communication between factory-level and headquarters that the metrics proposed by this paper ultimately improves a quality of support from the management by receiving the factors required for productivity activities in the practical field. This factor includes such as equipment, raw materials and labors. Here, we propose that chain reaction models using break down structure of productivity metrics and financial metrics enhance the knowledge sharing of KPI (Key Performance Indicator) which generally tend to create oversimplified communication between management in headquarters and employees in the practical fields. The productivity metrics include OEE(Overall Equipment Effectiveness) of TPM (Total Productive Maintenance), OLE (Overall Labor Effectiveness) of PAC(Performance and Analysis and Control) activities, and OYE (Overall Yield Effectiveness) of TMM(Total Material Management) activities. The financial accounting metrics include ROE(Return on Equity), ROA(Return on Asset), and AVR(Added-Value Rate). The suggested chain reaction model selects the financial metrics as initial stage and branch down until final stage of productivity metrics. When demand exceeds supply, an ideal speed rate, the lean OEE strategy can be initially applied to reduce the gap between the demand and supply, then apply variable costing to estimate correct amount of operating profit. In addition, the paper presents a new type of model for linkage between financial accounting metrics including CAPEX(Capital Expenditure), OPEX(Operating Expenditure), EVA(Economic Added Value), DCL(Degree of Combined Leverage), and TPM productivity activities including AM(Autonomous Maintenance), PM(Preventive Maintenance), MP(Maintenance Prevention) and QM(Quality Maintenance). In order to support the evidence of proposed linkage strategy, a case analysis on 52 projects from national TPM contest from 2011 to 2012 is analyzed. The case presents the classification of CAPEX and OPEX activities from TPM, and proposes the correct implementation of financial effect for TPM projects.

This research paper introduces the application and implementation of medical decision metrics that classifies medical decision-making into four different metrics using statistical diagnostic tools, such as confusion matrix, normal distribution, Bayesian prediction and Receiver Operating Curve(ROC). In this study, the metrics are developed based on cross-section study, cohort study and case-control study done by systematic literature review and reformulated the structure of type I error, type II error, confidence level and power of detection. The study proposed implementation strategies for 10 quality improvement activities via 14 medical decision metrics which consider specificity and sensitivity in terms of α and β. Examples of ROC implication are depicted in this paper with a useful guidelines to implement a continuous quality improvement, not only in a variable acceptance sampling in Quality Control(QC) but also in a supplier grading score chart in Supplier Chain Management(SCM) quality. This research paper is the first to apply and implement medical decision-making tools as quality improvement activities. These proposed models will help quality practitioners to enhance the process and product quality level.

In this paper, we provide application strategies of representative finance and investment metrics using breakdown properties of Return On Equity(ROE). The research discusses the relationship of ROE for finance and investment metrics such as Return On Asset(ROA), Return On Invested Capital(ROIC), Price Book Ratio(PBR), and Price Earning Ratio(PER). Furthermore, we provide three different perspectives of its purpose and utility of Residual Income(RI) Models, Market Value(MV) Models and Enterprise Value(EV) Models.

This paper aims to develop a new chain metrics for obtaining lean Overall Equipment Effectiveness(OEE) and present implementation strategy which considers the properties for Total Productive Maintenance(TPM) to reduce machine losses, Performance Analysis and Control(PAC) to reduce labor losses, Lean Production System(LPS) to reduce floor wastes, and Theory of Constraints(TOC) to minimize the problem of Capacity Constrained Resource(CCR). The study reviews the related literatures and reformulates the structure of machine losses, labor losses and field wastes. The research also develops the integrated productivity metrics according to time, units, reliability and maintainability. It is found that the study develops the actual productivity measure in terms of efficiency, effectiveness and standard productivity. In addition to that, it outlines and develops by using the integrated LPS and TPM, lean OEE measures such as Time Based Productivity(TBP), Unit Based Productivity(UBP), and Reliability & Maintainability Based Availability(RMBA). Implication examples are proposed to make it easier and available for practioners to understand the implementation strategies about TPM OEE, lean OEE and TOC OEE. Futhermore related to other studies, the research contributes to create a new chain productivity measures to clear the interrelationship concepts of productivity, efficiency and effectiveness. Moreover the paper develops the enhanced OEE measures by integration of TPM, PAC, LPS and TOC with the perspective of schedule, throughput, reliability, maintainability and availability.

Performance management is very popular in business area and seems to be an exciting topic. Despite significant research efforts and myriads of performance metrics, performance management today as a rigorous approach is still in an immature state and metri

데이터의 폭발적 증가와 동시다발적인 인터넷 사용, 급속도로 발전하는 미디어 환경 변화에 따라 이미지의 상대적 파급력이 높아지고 있다. 이에, 지식과 정보의 시각적 표현과 함께 시각언어를 생산하고 구축하는 시각디자이너 역량강화에도 필요성이 대두된다. 본 연구에서는 지식 정보의 홍수 속에서 커뮤니케이션 환경과 시대에 맞는 소통방법이 시각언어임을 밝히고 창의적이며 유연한 사고확산의 인재를 양성하기 위한 VCD(Visual Communication Design)교육 방법론을 콘셉트 매트릭스 활용으로 논의하였다. VCD교육과 시각언어, 콘셉트 매트릭스의 이론적 고찰을 토대로 그 의미와 가치를 탐색하고 콘셉트 매트릭스를 활용한 해외 사례를 분석하여 시사점을 도출하였다. 분석결과 정신교육, 문제해결기반교육, 협업교육, 실무중심형 교육으로 확산되는 양상을 보여줌을 알 수 있었으며 다음과 같이 제언한다. 첫째, 시각언어를 기반으로 둔 VCD교육은 일반교육이 아닌 전문인력양성을 위한 교육에 초점을 맞추어 교육철학의 콘셉트를 정확히 설계하여야 한다. 둘째, 양적인 교육 성과만을 지표로 삼는 것보다 질적인 면에서 전문교육이 진행되어야 함으로써 관련 전문가와 교육자로서의 역량 강화도 필요하다. 셋째, 체계적인 단계의 장기 계획을 세우고, 기초부터 심화까지 실무중심형 단계별 학습으로 이루어져야 한다. 또한 급속도로 발전하는 미디어 환경에 맞추어 기술이 결합한 시각언어의 디지털 콘텐츠 교육시스템을 구축하여야 한다. 본 연구는 시각언어를 기반으로 둔 VCD교육에 있어 콘셉트 매트릭스가 활용되어 지속가능형의 실질적인 디자인교육 실체화가 이루어지길 기대한다.

유방암을 진단받고 수술 전 확산텐서영상에서 도출된 정량적 확산 지표인 비등방성 확산의 크기(FA)와 현성 확산계수(ADC) 값을 비교하고, 상관관계를 분석하여 보기로 하였다. 확산 그레디언트는 20방향(b-value, 0 및 1,000s/mm2)을 사용하여 정량적 확산 지표를 도출하였다. 정량적 분석은 피어슨의 상관분석, 정성적 분석은 급내 상관계수를 적용하여 분석하였다. 연구 결과는 FAmin, FAmean, FAmax 평균값은 0.098 ± 0.065, 0.302 ± 0.142, 0.634 ± 0.236이고 ADCmin, ADCmean, ADCmax은 0.741 ± 0.403, 1.095 ± 0.394, 1.530 ± 0.447로 나타났다(p > 0.05). 병변 평가에서 Category 6이면서 시간대 신호 강도 그래프가 유실형(Pattern Ⅲ)의 경우는 FAmin, FAmean, FAmax 평균값은 0.132 ± 0.050, 0.418 ± 0.094, 0.770 ± 0.164이고 ADCmin, ADCmean, ADCmax는 0.753 ± 0.189, 1.120 ± 0.236, 1.615 ± 0.372로 나타났다. 정량적 분석 결과 ADCmean – FAmean, ADCmaximal – FAmax 는 음의 상관관계가 나타났다(p = 0.001, 0.003). 정성적 분석 결과 내부 평가자의 경우 ADC 0.628(p = 0.001), FA 0.620(p = 0.001)이고, 외부 평가자의 경우 ADC 0.677(p = 0.001), FA 0.695(p = 0.001)로 나타났다. 결론적으로 형태학적 조직 검사를 바탕으로 동적 조영 검사에서 시간대 신호 강도 그래프는 유실(pattern Ⅲ: wash out) 형태이며, ADCmean 1.120 ± 0.236, FAmean값이 0.032 ± 0.142로 피어슨 상관분석의 결과 음의 상관관계(Y=1.44-1.12X)로 나타났다. 따라서, 시간대 신호강도 그래프의 형태와 ADC와 FA의 상호관계를 파악한다면 유방암에서 악성 질환을 구분하는 기준이 되리라 생각된다.

Statistical rhythmic metrics are applied on a Buckeye corpus of spontaneous interview speech in order to investigate the extent of inter-speaker rhythm variability. Tests are made on speech produced by speakers who share the same regional dialect in North America. The choice is made due to the unique characteristic of the Buckeye corpus in that the speech dataset is obtained from the speakers who have been raised in the same region and hence who share the same dialect with each other. Statistical measures of rhythm metrics are obtained from the subset of the corpus. The results of clustering analysis show that the rhythmic measures that capture the least dialectal variance is the normalized pair-wise variability indices calculated based on the respective adjacent consonantal and vocalic durations. The finding implies that these statistical measures of rhythm can be used in capturing the dialectal similarities on spontaneous speech.