• Title/Summary/Keyword: Power Modeling

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Process Design of Carbon Dioxide Storage in the Marine Geological Structure: II. Effect of Thermodynamic Equations of State on Compression and Transport Process (이산화탄소 해양지중저장 처리를 위한 공정 설계: II. 열역학 상태방정식이 압축 및 수송 공정에 미치는 영향 평가)

  • Huh, Cheol;Kang, Seong-Gil
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.11 no.4
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    • pp.191-198
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    • 2008
  • To design a reliable $CO_2$ marine geological storage system, it is necessary to perform numerical process simulation using thermodynamic equation of state. $CO_2$ capture process from the major point sources such as power plants, transport process from the capture sites to storage sites and storage process to inject $CO_2$ into the deep marine geological structure can be simulate with numerical modeling. The purpose of this paper is to compare and analyse the relevant equations of state including ideal, BWRS, PR, PRBM and SRK equation of state. We also studied the effect of thermodynamic equation of state in designing the compression and transport process. As a results of comparison of numerical calculations, all relevant equation of state excluding ideal equation of state showed similar compression behavior in pure $CO_2$. On the other hand, calculation results of BWRS, PR and PRBM showed totally different behavior in compression and transport process of captured $CO_2$ mixture from the oxy-fuel combustion coal-fired plants. It is recommended to use PR or PRBM in designing of compression and transport process of $CO_2$ mixture containing NO, Ar and $O_2$.

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A Study on the Black Box Design using Collective Intelligence Analysis (집단지성 분석법을 활용한 블랙박스 디자인 개발 연구)

  • Lee, Hee young;Hong, Jeong Pyo;Cho, Kwang Soo
    • Science of Emotion and Sensibility
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    • v.21 no.2
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    • pp.101-112
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    • 2018
  • This study was carried out to enhance the competitiveness of blackbox design for domestic and international companies, based on the explosive growth of the blackbox market due to development of blackbox design for vehicle accident prevention and post-treatment. In the past, the blackbox market has produced products indiscriminately to meet the ever-increasing demand of consumers. Therefore, we thought a new design method was necessary to effectively investigate the needs of rapidly changing consumers. In this study, we aimed to identify the best-selling blackbox to understand the design flow, and the optimum area for a blackbox, considering the uniqueness of associated vehicle. Based on discussion with blackbox design experts, we studied the direction of design and the problems with blackbox use, which were reflected in blackbox development. Through this research, two types of design - leading blackbox (A type) and mass production blackbox (B type) - were proposed for compatibility of the blackbox with the car. The leading type of blackbox was positioned so that it was wrapped with the room mirror hinge before the screw was fastened, in order to achieve an integrated design. Therefore, we designed an integrated form and resolved the placement problem of an adhesive blackbox. To blend, the mass production blackbox implemented material and surface processing in the same way with the car, and adopted the slide structure to automatically turn off the main body power when removing the SDcard, reflecting consumer needs. This study considers evolving consumer needs through a case study and collective intelligence and deals with implementation of the whole design process during mass production. In this study, we aimed to strengthen the competitiveness of the blackbox design based on design method and its realization.

An Intelligent Intrusion Detection Model Based on Support Vector Machines and the Classification Threshold Optimization for Considering the Asymmetric Error Cost (비대칭 오류비용을 고려한 분류기준값 최적화와 SVM에 기반한 지능형 침입탐지모형)

  • Lee, Hyeon-Uk;Ahn, Hyun-Chul
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.157-173
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    • 2011
  • As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

Analysis of Modality and Procedures for CCS as CDM Project and Its Countmeasures (CCS 기술의 CDM 사업화 수용에 대한 방식과 절차 분석 및 대응방안 고찰)

  • Noh, Hyon-Jeong;Huh, Cheol;Kang, Seong-Gil
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.15 no.3
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    • pp.263-272
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    • 2012
  • Carbon dioxide, emitted by human activities since the industrial revolution, is regarded as a major contributor of global warming. There are many efforts to mitigate climate change, and carbon dioxide capture and geological storage (CCS) is recognized as one of key technologies because it can reduce carbon dioxide emissions from large point sources such as a power station or other industrial installation. The inclusion of CCS as clean development mechanism (CDM) project activities has been considered at UNFCCC as financial incentive mechanisms for those developing countries that may wish to deploy the CCS. Although the Conference of the Parties serving as the Meeting of the Parties to the UNFCCC's Kyoto Protocol (CMP), at Cancun in December 2010, decided that CCS is eligible as CDM project activities, the issues identified in decision 2/CMP.5 should be addressed and resolved in a satisfactory manner. Major issues regarding modalities and procedure are 1) Site selection, 2) Monitoring, 3) Modeling, 4) Boundaries, 5) Seepage Measuring and Accounting, 6) Trans-Boundary Effects, 7) Accounting of Associated Project Emissions (Leakage), 8) Risk and Safety Assessment, and 9) Liability Under the CDM Scheme. The CMP, by its decision 7/CMP.6, invited Parties to submit their views to the secretariat of Subsidiary Body for Scientific and Technological Advice (SBSTA), SBSTA prepared a draft modalities and procedure by exchanging views of Parties through workshop held in Abu Dhabi, UAE (September 2011). The 7th CMP (Durban, December 2011) finally adopted the modalities and procedures for CCS as CDM project activities (CMP[2011], Decision-/CMP.7). The inclusion of CCS as CDM project activities means that CCS is officially accredited as one of $CO_2$ reducing technologies in global carbon market. Consequently, it will affect relevant technologies and industry as well as law and policy in Korea and aboard countries. This paper presents a progress made on discussion and challenges regarding the issue, and aims to suggest some considerations to policy makers in Korea in order to demonstrate and deploy the CCS project in the near future. According to the adopted modalities and procedures for CCS as CDM project activities, it is possible to implement relevant CCS projects in Non-Annex I countries, including Korea, as long as legal and regulatory frameworks are established. Though Korea enacted 'Framework Act on Low Carbon, Green Growth', the details are too inadequate to content the requirements of modalities and procedures for CCS as CDM project. Therefore, it is required not only to amend the existing laws related with capture, transport, and storage of $CO_2$ for paving the way of an prompt deployment of CCS CDM activities in Korea as a short-term approach, but also to establish the united framework as a long-term approach.

Geochemical Characteristics of the Gyeongju LILW Repository II. Rock and Mineral (중.저준위 방사성폐기물 처분부지의 지구화학 특성 II. 암석 및 광물)

  • Kim, Geon-Young;Koh, Yong-Kwon;Choi, Byoung-Young;Shin, Seon-Ho;Kim, Doo-Haeng
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.6 no.4
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    • pp.307-327
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    • 2008
  • Geochemical study on the rocks and minerals of the Gyeongju low and intermediate level waste repository was carried out in order to provide geochemical data for the safety assessment and geochemical modeling. Polarized microscopy, X-ray diffraction method, chemical analysis for the major and trace elements, scanning electron microscopy(SEM), and stable isotope analysis were applied. Fracture zones are locally developed with various degrees of alteration in the study area. The study area is mainly composed of granodiorite and diorite and their relation is gradational in the field. However, they could be easily distinguished by their chemical property. The granodiorite showed higher $SiO_2$ content and lower MgO and $Fe_2O_3$ contents than the diorite. Variation trends of the major elements of the granodiorite and diorite were plotted on the same line according to the increase of $SiO_2$ content suggesting that they were differentiated from the same magma. Spatial distribution of the various elements showed that the diorite region had lower $SiO_2,\;Al_2O_3,\;Na_2O\;and\;K_2O$ contents, and higher CaO, $Fe_2O_3$ contents than the granodiorite region. Especially, because the differences in the CaO and $Na_2O$ distribution were most distinct and their trends were reciprocal, the chemical variation of the plagioclase of the granitic rocks was the main parameter of the chemical variation of the host rocks in the study area. Identified fracture-filling minerals from the drill core were montmorillonite, zeolite minerals, chlorite, illite, calcite and pyrite. Especially pyrite and laumontite, which are known as indicating minerals of hydrothermal alteration, were widely distributed in the study area indicating that the study area was affected by mineralization and/or hydrothermal alteration. Sulfur isotope analysis for the pyrite and oxygen-hydrogen stable isotope analysis for the clay minerals indicated that they were originated from the magma. Therefore, it is considered that the fracture-filling minerals from the study area were affected by the hydrothermal solution as well as the simply water-rock interaction.

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A Study on the DC Resistivity Method to Image the Underground Structure Beneath River or Lake Bottom (하저 지반특성 규명을 위한 수상 전기비저항 탐사에 관한 연구)

  • Kim Jung-Ho;Yi Myeong-Jong;Song Yoonho;Choi Seong-Jun;Lee Seoung Kon;Son Jeong-Sul;Chung Seung-Hwan
    • Geophysics and Geophysical Exploration
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    • v.5 no.4
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    • pp.223-235
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    • 2002
  • Since weak Bones or geological lineaments are likely to be eroded, there may develop weak Bones beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. DC resistivity method, however, has seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of a case history, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing them at the water bottom, because the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the DC resistivity method can provide fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio (S/N ratio) data as well as the high resolving power. Some of the modified electrode arrays can provide the data having reasonably high S/N ratio and need not to install remote electrode(s), and thus, they may be suitable to the resistivity survey at the water-covered area.

A Meta Analysis of Using Structural Equation Model on the Korean MIS Research (국내 MIS 연구에서 구조방정식모형 활용에 관한 메타분석)

  • Kim, Jong-Ki;Jeon, Jin-Hwan
    • Asia pacific journal of information systems
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    • v.19 no.4
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    • pp.47-75
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    • 2009
  • Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

Analyzing Different Contexts for Energy Terms through Text Mining of Online Science News Articles (온라인 과학 기사 텍스트 마이닝을 통해 분석한 에너지 용어 사용의 맥락)

  • Oh, Chi Yeong;Kang, Nam-Hwa
    • Journal of Science Education
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    • v.45 no.3
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    • pp.292-303
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    • 2021
  • This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

An Exploratory Study on the Components of Visual Merchandising of Internet Shopping Mall (인터넷쇼핑몰의 VMD 구성요인에 대한 탐색적 연구)

  • Kim, Kwang-Seok;Shin, Jong-Kuk;Koo, Dong-Mo
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.2
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    • pp.19-45
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    • 2008
  • This study is to empirically examine the primary dimensions of visual merchandising (VMD) of internet shopping mall, namely store design, merchandise, and merchandising cues, to be a attractive virtual store to the shoppers. The authors reviewed the literature related to the major components of VMD from the perspective of the AIDA model, which has been mainly applied to the offline store settings. The major purposes of the study are as follows; first, tries to derive the variables related with the components of visual merchandising through reviewing the existing literatures, establish the hypotheses, and test it empirically. Second, examines the relationships between the components of VMD and the attitude toward the VMD, however, putting more emphasis on finding out the component structure of the VMD. VMD needs to be examined with the perspective that an online shopping mall is a virtual self-service or clerkless store, which could reduce the number of employees, help the shoppers search, evaluate and purchase for themselves, and to be explored in terms of the in-store persuasion processes of customers. This study reviewed the literatures related to store design, merchandise, and merchandising cues which might be relevant to the store, product, and promotion respectively. VMD is a total communication tool, and AIDA model could explain the in-store consumer behavior of online shopping. Store design has to do with triggering a consumer attention to the online mall, merchandise with a product related interest, and merchandising cues with promotions such as recommendation and links that induce the desire to pruchase. These three steps might be seen as the processes for purchase actions. The theoretical rationale for the relationship between VMD and AIDA could be found in Tyagi(2005) that the three steps of consumer-oriented merchandising are a store, a product assortment, and placement, in Omar(1999) that three types of interior display are a architectural design display, commodity display, and point-of-sales(POS) display, and in Davies and Ward(2005) that the retail store interior image is related to an atmosphere, merchandise, and in-store promotion. Lee et al(2000) suggested as the web merchandising components a merchandising cues, a shopping metaphor which is an assistant tool for search, a store design, a layout(web design), and a product assortment. The store design which includes differentiation, simplicity and navigation is supposed to be related to the attention to the virtual store. Second, the merchandise dimensions comprising product assortments, visual information and product reputation have to do with the interest in the product offerings. Finally, the merchandising cues that refer to merchandiser(MD)'s recommendation of products and providing the hyperlinks to relevant goods for the shopper is concerned with attempt to induce the desire to purchase. The questionnaire survey was carried out to collect the data about the consumers who would shop at internet shopping malls frequently. To select the subject malls, the mall ranking data announced by a mall rating agency was used to differentiate the most popular and least popular five mall each. The subjects was instructed to answer the questions after navigating the designated mall for five minutes. The 300 questionnaire was distributed to the consumers, 166 samples were used in the final analysis. The empirical testing focused on identifying and confirming the dimensionality of VMD and its subdimensions using a structural equation modeling method. The confirmatory factor analysis for the endogeneous and exogeneous variables was carried out in four parts. The second-order factor analysis was done for a store design, a merchandise, and a merchandising cues, and first-order confirmatory factor analysis for the attitude toward the VMD. The model test results shows that the chi-square value of structural equation is 144.39(d.f 49), significant at 0.01 level which means the proposed model was rejected. But, judging from the ratio of chi-square value vs. degree of freedom, the ratio was 2.94 which smaller than an acceptable level of 3.0, RMR is 0.087 which is higher than a generally acceptable level of 0.08. GFI and AGFI is turned out to be 0.90 and 0.84 respectively. Both NFI and NNFI is 0.94, and CFI 0.95. The major test results are as follows; first, the second-order factor analysis and structural equational modeling reveals that the differentiation, simplicity and ease of identifying current status of the transaction are confirmed to be subdimensions of store design and to be a significant predictors of the dependent variable. This result implies that when designing an online shopping mall, it is necessary to differentiate visually from other malls to improve the effectiveness of the communications of store design. That is, the differentiated store design raise the contrast stimulus to sensory organs to promote the memory of the store and to have a favorable attitude toward the VMD of a store. The results that navigation which means the easiness of identifying current status of shopping affects the attitude to VMD could be interpreted that the navigating processes via the hyperlinks which is characteristics of an internet shopping is a complex and cognitive process and shoppers are likely to lack the sense of overall structure of the store. Consequently, shoppers are likely to be alost amid shopping not knowing where to go. The orientation tool enhance the accessibility of information to raise the perceptive power about the store environment.(Titus & Everett 1995) Second, the primary dimension of merchandise and its subdimensions was confirmed to be unidimensional respectively, have a construct validity, and nomological validity which the VMD dimensions supposed to have a positive correlation with the dependent variable. The subdimensions of product assortment, brand fame and information provision proved to have a positive effect on the attitude toward the VMD. It could be interpreted that the more plentiful the product and brand assortment of the mall is, the more likely the shoppers to favor it. Brand fame and information provision as well affect the VMD attitude, which means that the more famous the brand, the more likely the shoppers would trust and feel familiar with the mall, and the plentifully and visually presented information could have the shopper have a favorable attitude toward the store VMD. Third, it turned out to be that merchandising cue of product recommendation and hyperlinks affect the VMD attitude. This could be interpreted that recommended products could reduce the uncertainty related with the purchase decision, and the hyperlinks to relevant products would help the shopper save the cognitive effort exerted into the information search and gathering, which could lead to a favorable attitude to the VMD. This study tried to sheds some new light on the VMD of online store by reviewing the variables mentioned to be relevant with offline VMD in the existing literatures, and tried to link the VMD components from the perspective of AIDA model. The effect size of the VMD dimensions on the attitude was in the order of the merchandise, the store design and the merchandising cues.It is said that an internet has an unlimited place for display, however, the virtual store is not unlimited since the consumer has a limited amount of cognitive ability to process the external information and internal memory. Particularly, the shoppers are likely to face some difficulties in decision making on account of too many alternative and information overloads. Therefore, the internet shopping mall manager should take into consideration the cost of information search on the part of the consumer, to establish the optimal product placements and search routes. An efficient store composition would be possible by reducing the psychological burdens and cognitive efforts exerted to information search and alternatives evaluation. The store image is in most part determined by the product category and its brand it deals in. The results of this study support this proposition that the merchandise is most important to the VMD attitude than other components, the manager is required to take a strategic approach to VMD. The internet users are getting more accustomed and more knowledgeable about the internet media and more likely to accept the internet as a shopping channel as the period of time during which they use the internet to shop become longer. The web merchandiser should be aware that the product introduction using a moving pictures and a bulletin board become more important in order to present the interactive product information visually and communicate with customers more actively, therefore leading to making the quantity and quality of product information more rich.

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Antecedents of Manufacturer's Private Label Program Engagement : A Focus on Strategic Market Management Perspective (제조업체 Private Labels 도입의 선행요인 : 전략적 시장관리 관점을 중심으로)

  • Lim, Chae-Un;Yi, Ho-Taek
    • Journal of Distribution Research
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    • v.17 no.1
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    • pp.65-86
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    • 2012
  • The $20^{th}$ century was the era of manufacturer brands which built higher brand equity for consumers. Consumers moved from generic products of inconsistent quality produced by local factories in the $19^{th}$ century to branded products from global manufacturers and manufacturer brands reached consumers through distributors and retailers. Retailers were relatively small compared to their largest suppliers. However, sometime in the 1970s, things began to slowly change as retailers started to develop their own national chains and began international expansion, and consolidation of the retail industry from mom-and-pop stores to global players was well under way (Kumar and Steenkamp 2007, p.2) In South Korea, since the middle of the 1990s, the bulking up of retailers that started then has changed the balance of power between manufacturers and retailers. Retailer private labels, generally referred to as own labels, store brands, distributors own private-label, home brand or own label brand have also been performing strongly in every single local market (Bushman 1993; De Wulf et al. 2005). Private labels now account for one out of every five items sold every day in U.S. supermarkets, drug chains, and mass merchandisers (Kumar and Steenkamp 2007), and the market share in Western Europe is even larger (Euromonitor 2007). In the UK, grocery market share of private labels grew from 39% of sales in 2008 to 41% in 2010 (Marian 2010). Planet Retail (2007, p.1) recently concluded that "[PLs] are set for accelerated growth, with the majority of the world's leading grocers increasing their own label penetration." Private labels have gained wide attention both in the academic literature and popular business press and there is a glowing academic research to the perspective of manufacturers and retailers. Empirical research on private labels has mainly studies the factors explaining private labels market shares across product categories and/or retail chains (Dahr and Hoch 1997; Hoch and Banerji, 1993), factors influencing the private labels proneness of consumers (Baltas and Doyle 1998; Burton et al. 1998; Richardson et al. 1996) and factors how to react brand manufacturers towards PLs (Dunne and Narasimhan 1999; Hoch 1996; Quelch and Harding 1996; Verhoef et al. 2000). Nevertheless, empirical research on factors influencing the production in terms of a manufacturer-retailer is rather anecdotal than theory-based. The objective of this paper is to bridge the gap in these two types of research and explore the factors which influence on manufacturer's private label production based on two competing theories: S-C-P (Structure - Conduct - Performance) paradigm and resource-based theory. In order to do so, the authors used in-depth interview with marketing managers, reviewed retail press and research and presents the conceptual framework that integrates the major determinants of private labels production. From a manufacturer's perspective, supplying private labels often starts on a strategic basis. When a manufacturer engages in private labels, the manufacturer does not have to spend on advertising, retailer promotions or maintain a dedicated sales force. Moreover, if a manufacturer has weak marketing capabilities, the manufacturer can make use of retailer's marketing capability to produce private labels and lessen its marketing cost and increases its profit margin. Figure 1. is the theoretical framework based on a strategic market management perspective, integrated concept of both S-C-P paradigm and resource-based theory. The model includes one mediate variable, marketing capabilities, and the other moderate variable, competitive intensity. Manufacturer's national brand reputation, firm's marketing investment, and product portfolio, which are hypothesized to positively affected manufacturer's marketing capabilities. Then, marketing capabilities has negatively effected on private label production. Moderating effects of competitive intensity are hypothesized on the relationship between marketing capabilities and private label production. To verify the proposed research model and hypotheses, data were collected from 192 manufacturers (212 responses) who are producing private labels in South Korea. Cronbach's alpha test, explanatory / comfirmatory factor analysis, and correlation analysis were employed to validate hypotheses. The following results were drawing using structural equation modeling and all hypotheses are supported. Findings indicate that manufacturer's private label production is strongly related to its marketing capabilities. Consumer marketing capabilities, in turn, is directly connected with the 3 strategic factors (e.g., marketing investment, manufacturer's national brand reputation, and product portfolio). It is moderated by competitive intensity between marketing capabilities and private label production. In conclusion, this research may be the first study to investigate the reasons manufacturers engage in private labels based on two competing theoretic views, S-C-P paradigm and resource-based theory. The private label phenomenon has received growing attention by marketing scholars. In many industries, private labels represent formidable competition to manufacturer brands and manufacturers have a dilemma with selling to as well as competing with their retailers. The current study suggests key factors when manufacturers consider engaging in private label production.

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