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Electronic Word-of-Mouth in B2C Virtual Communities: An Empirical Study from CTrip.com (B2C허의사구중적전자구비(B2C虚拟社区中的电子口碑): 관우휴정려유망적실증연구(关于携程旅游网的实证研究))

  • Li, Guoxin;Elliot, Statia;Choi, Chris
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.3
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    • pp.262-268
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    • 2010
  • Virtual communities (VCs) have developed rapidly, with more and more people participating in them to exchange information and opinions. A virtual community is a group of people who may or may not meet one another face to face, and who exchange words and ideas through the mediation of computer bulletin boards and networks. A business-to-consumer virtual community (B2CVC) is a commercial group that creates a trustworthy environment intended to motivate consumers to be more willing to buy from an online store. B2CVCs create a social atmosphere through information contribution such as recommendations, reviews, and ratings of buyers and sellers. Although the importance of B2CVCs has been recognized, few studies have been conducted to examine members' word-of-mouth behavior within these communities. This study proposes a model of involvement, statistics, trust, "stickiness," and word-of-mouth in a B2CVC and explores the relationships among these elements based on empirical data. The objectives are threefold: (i) to empirically test a B2CVC model that integrates measures of beliefs, attitudes, and behaviors; (ii) to better understand the nature of these relationships, specifically through word-of-mouth as a measure of revenue generation; and (iii) to better understand the role of stickiness of B2CVC in CRM marketing. The model incorporates three key elements concerning community members: (i) their beliefs, measured in terms of their involvement assessment; (ii) their attitudes, measured in terms of their satisfaction and trust; and, (iii) their behavior, measured in terms of site stickiness and their word-of-mouth. Involvement is considered the motivation for consumers to participate in a virtual community. For B2CVC members, information searching and posting have been proposed as the main purpose for their involvement. Satisfaction has been reviewed as an important indicator of a member's overall community evaluation, and conceptualized by different levels of member interactions with their VC. The formation and expansion of a VC depends on the willingness of members to share information and services. Researchers have found that trust is a core component facilitating the anonymous interaction in VCs and e-commerce, and therefore trust-building in VCs has been a common research topic. It is clear that the success of a B2CVC depends on the stickiness of its members to enhance purchasing potential. Opinions communicated and information exchanged between members may represent a type of written word-of-mouth. Therefore, word-of-mouth is one of the primary factors driving the diffusion of B2CVCs across the Internet. Figure 1 presents the research model and hypotheses. The model was tested through the implementation of an online survey of CTrip Travel VC members. A total of 243 collected questionnaires was reduced to 204 usable questionnaires through an empirical process of data cleaning. The study's hypotheses examined the extent to which involvement, satisfaction, and trust influence B2CVC stickiness and members' word-of-mouth. Structural Equation Modeling tested the hypotheses in the analysis, and the structural model fit indices were within accepted thresholds: ${\chi}^2^$/df was 2.76, NFI was .904, IFI was .931, CFI was .930, and RMSEA was .017. Results indicated that involvement has a significant influence on satisfaction (p<0.001, ${\beta}$=0.809). The proportion of variance in satisfaction explained by members' involvement was over half (adjusted $R^2$=0.654), reflecting a strong association. The effect of involvement on trust was also statistically significant (p<0.001, ${\beta}$=0.751), with 57 percent of the variance in trust explained by involvement (adjusted $R^2$=0.563). When the construct "stickiness" was treated as a dependent variable, the proportion of variance explained by the variables of trust and satisfaction was relatively low (adjusted $R^2$=0.331). Satisfaction did have a significant influence on stickiness, with ${\beta}$=0.514. However, unexpectedly, the influence of trust was not even significant (p=0.231, t=1.197), rejecting that proposed hypothesis. The importance of stickiness in the model was more significant because of its effect on e-WOM with ${\beta}$=0.920 (p<0.001). Here, the measures of Stickiness explain over eighty of the variance in e-WOM (Adjusted $R^2$=0.846). Overall, the results of the study supported the hypothesized relationships between members' involvement in a B2CVC and their satisfaction with and trust of it. However, trust, as a traditional measure in behavioral models, has no significant influence on stickiness in the B2CVC environment. This study contributes to the growing body of literature on B2CVCs, specifically addressing gaps in the academic research by integrating measures of beliefs, attitudes, and behaviors in one model. The results provide additional insights to behavioral factors in a B2CVC environment, helping to sort out relationships between traditional measures and relatively new measures. For practitioners, the identification of factors, such as member involvement, that strongly influence B2CVC member satisfaction can help focus technological resources in key areas. Global e-marketers can develop marketing strategies directly targeting B2CVC members. In the global tourism business, they can target Chinese members of a B2CVC by providing special discounts for active community members or developing early adopter programs to encourage stickiness in the community. Future studies are called for, and more sophisticated modeling, to expand the measurement of B2CVC member behavior and to conduct experiments across industries, communities, and cultures.

Application of Support Vector Regression for Improving the Performance of the Emotion Prediction Model (감정예측모형의 성과개선을 위한 Support Vector Regression 응용)

  • Kim, Seongjin;Ryoo, Eunchung;Jung, Min Kyu;Kim, Jae Kyeong;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.185-202
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    • 2012
  • .Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

A Study on the Regional Characteristics of Broadband Internet Termination by Coupling Type using Spatial Information based Clustering (공간정보기반 클러스터링을 이용한 초고속인터넷 결합유형별 해지의 지역별 특성연구)

  • Park, Janghyuk;Park, Sangun;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.45-67
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    • 2017
  • According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

An Investigation of Local Naming Issue of Tamarix aphylla (에셀나무(Tamarix aphylla)의 명칭문제에 대한 고찰)

  • Kim, Young-Sook
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.37 no.1
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    • pp.56-67
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    • 2019
  • In order to investigate the issue with the proper name of eshel(Tamarix aphylla) mentioned in the Bible, analysis of morphological taxonomy features of plants, studies on the symbolism of the Tamarix genus, analysis of examples in Korean classics and Chinese classics, and studies on the problems found in translations of Korean, Chinese and Japanese Bibles. The results are as follows. According to plant taxonomy, similar species of the Tamarix genus are differentiated by the leaf and flower, and because the size is very small about 2-4mm, it is difficult to differentiate by the naked eye. However, T. aphylla found in the plains of Israel and T. chinensis of China and Korea have distinctive differences in terms of the shape of the branch that droops and its blooming period. The Tamarix genus is a very precious tree that was planted in royal courtyards of ancient Mesopotamia and the Han(漢) Dynasty of China, and in ancient Egypt, it was said to be a tree that gave life to the dead. In the Bible, it was used as a sign of the covenant that God was with Abraham, and it also symbolized the prophet Samuel and the court of Samuel. When examining the example in Korean classics, the Tamarix genus was used as a common term in the Joseon Dynasty and it was often used as the medical term '$Ch{\bar{e}}ngli{\check{u}}$(檉柳)'. Meanwhile, the term 'wiseonglyu(渭城柳)' was used as a literary term. Upon researching the period and name of literature related to $Ch{\bar{e}}ngli{\check{u}}$(檉柳) among Chinese medicinal herb books, a total of 16 terms were used and among these terms, the term Chuísīliǔ(垂絲柳) used in the Chinese Bible cannot be found. There was no word called 'wiseonglyu(渭城柳)' that originated from the poem by Wang Wei(699-759) of Tang(唐) Dynasty and in fact, the word 'halyu(河柳)' that was related to Zhou(周) China. But when investigating the academic terms of China currently used, the words Chuísīliǔ(垂絲柳) and $Ch{\bar{e}}ngli{\check{u}}$(檉柳) are used equally, and therefore, it appears that the translation of eshel in the Chinese Bible as either Chuísīliǔ (垂絲柳) or $Ch{\bar{e}}ngli{\check{u}}$(檉柳) both appear to be of no issue. There were errors translating tamarix into 'やなぎ(willow)' in the Meiji Testaments(舊新約全書 1887), and translated correctly 'ぎょりゅう(檉柳)' since the Colloquial Japanese Bible(口語譯 聖書 1955). However, there are claims that 'gyoryu(ぎょりゅう 檉柳)' is not an indigenous species but an exotics species in the Edo Period, so it is necessary to reconsider the terminology. As apparent in the Korean classics examples analysis, there is high possibility that Korea's T. chinensis were grown in the Korean Peninsula for medicinal and gardening purposes. Therefore, the use of the medicinal term $Ch{\bar{e}}ngli{\check{u}}$(檉柳) or literary term 'wiseonglyu' in the Korean Bible may not be a big issue. However, the term 'wiseonglyu' is used very rarely even in China and as this may be connected to the admiration of China and Chinese things by literary persons of the Joseon Dynasty, so the use of this term should be reviewed carefully. Therefore, rather than using terms that may be of issue in the Bible, it is more feasible to transliterate the Hebrew word and call it eshel.

A Study of the Removal of the Seated Medicine Buddha from the Samneung Valley at Namsan, Gyeongju during the Japanese Colonial Era (일제강점기 경주 남산 삼릉계 약사여래좌상 반출 경위에 대한 고찰)

  • Jun, Araki
    • Korean Journal of Heritage: History & Science
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    • v.53 no.4
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    • pp.150-169
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    • 2020
  • Surveys of Buddhist ruins at Namsan in Gyeongju began in earnest during the Japanese colonial era, undertaken by Japanese scholars. These surveys of Buddhist remains in Namsan made during the colonial period should be seen as previous research which cannot be ignored in any in-depth study of Buddhist ruins in Gyeongju. Full-scale surveys of Buddhist ruins at Namsan began in the 1920s. Previous surveys conducted around the time of the Japanese annexation of Korea in 1910 are generally viewed as only representing preliminary investigations and, thus, have not received much attention. However, these early surveys are significant in that they led to the Buddhist ruins on Namsan becoming widely known in the 1910s and served as the foundations for later studies. The removal of the Seated Medicine Buddha from Samneung Valley in Gyeongju in 1915 and its subsequent exhibition at the Joseon Local Products Expo, which marked the fifth anniversary of the Japanese administration of Korea, was especially important in garnering attention for Namsan's wealth of Buddhist artifacts, as the statue was placed in the main hall of the art museum and attracted a great deal of interest from visitors. It is typically thought that this Seated Medicine Buddha was exhibited in 1915 because it was the most beautiful and well-preserved statue from Namsan. However, the removal of this statue was closely related to the proposed move of the Seokguram statue to Seoul around the time of Korea's annexation. The plan to move Seokguram to Seoul was primarily devised by Terauchi Masatake, and the plan, based on Ilseontongjo-ron ('日鮮同祖論'), a historical theory that prehistoric Korean and Japanese people were of the same blood, and Joseon Jeongcheasoeng-ron ('朝鮮停滯性論'), a historical theory arguing that development had stagnated in Korea, was intended to be a visual demonstration of a new era for Korea. This new era was to proceed under the rule of the Japanese Empire through the dissolution of Gyeongbokgung, the symbol of the Joseon Dynasty, which would be replaced with past glories as symbolized by the statue of Buddha. However, as the plan floundered, the replacement for Seokguram in Seoul ended up being none other than the Seated Medicine Buddha of Samneung Valley. Surveys of the Seated Medicine Buddha began in 1911, administered by Sekino Tadashi, but he likely learned of the statue's location from Moroga Hideo or Kodaira Ryozo, Japanese residents of Gyeongju. It is also probable that these Japanese residents received a request from the Japanese Government General of Korea to find a Buddha statue that was worthy of being displayed at exhibitions. In this way, we can say that the transfer of the Seated Medicine Buddha to Seoul was the result of close cooperation between the Government General, Sekino Tadashi, and Japanese residents of Gyeongju. This also had the effect of removing the magical veil which had shrouded the Buddhist ruins of Namsan. In other words, while the early surveys of Buddhist ruins on Namsan are significant, it is difficult to argue that the surveys were undertaken for purely academic purposes, as they were deeply related to the imperial ambitions of Governor-General Terauchi which encompassed the plans to move Seokguram to Seoul and the successful hosting of the 1915 Expo. It should also be pointed out that the failure of the plan to move Seokguram to Seoul and the preservation of the Seated Stone Buddha of Mireuggok at Namsan was in no small part due to resistance from Korean residents in Gyeongju. Although it is not described in detail in the paper, research is needed which shows that the Korean residents of Gyeongju were not simple bystanders, but agents of history.

Aspect-Based Sentiment Analysis Using BERT: Developing Aspect Category Sentiment Classification Models (BERT를 활용한 속성기반 감성분석: 속성카테고리 감성분류 모델 개발)

  • Park, Hyun-jung;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.1-25
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    • 2020
  • Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

The Effect of Price Promotional Information about Brand on Consumer's Quality Perception: Conditioning on Pretrial Brand (품패개격촉소신식대소비자질량인지적영향(品牌价格促销信息对消费者质量认知的影响))

  • Lee, Min-Hoon;Lim, Hang-Seop
    • Journal of Global Scholars of Marketing Science
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    • v.19 no.3
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    • pp.17-27
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    • 2009
  • Price promotion typically reduces the price for a given quantity or increases the quantity available at the same price, thereby enhancing value and creating an economic incentive to purchase. It often is used to encourage product or service trial among nonusers of products or services. Thus, it is important to understand the effects of price promotions on quality perception made by consumer who do not have prior experience with the promoted brand. However, if consumers associate a price promotion itself with inferior brand quality, the promotion may not achieve the sales increase the economic incentives otherwise might have produced. More specifically, low qualitative perception through price promotion will undercut the economic and psychological incentives and reduce the likelihood of purchase. Thus, it is important for marketers to understand how price promotional informations about a brand have impact on consumer's unfavorable quality perception of the brand. Previous literatures on the effects of price promotions on quality perception reveal inconsistent explanations. Some focused on the unfavorable effect of price promotion on consumer's perception. But others showed that price promotions didn't raise unfavorable perception on the brand. Prior researches found these inconsistent results related to the timing of the price promotion's exposure and quality evaluation relative to trial. And, whether the consumer has been experienced with the product promotions in the past or not may moderate the effects. A few studies considered differences among product categories as fundamental factors. The purpose of this research is to investigate the effect of price promotional informations on consumer's unfavorable quality perception under the different conditions. The author controlled the timing of the promotional exposure and varied past promotional patterns and information presenting patterns. Unlike previous researches, the author examined the effects of price promotions setting limit to pretrial situation by controlling potentially moderating effects of prior personal experience with the brand. This manipulations enable to resolve possible controversies in relation to this issue. And this manipulation is meaningful for the work sector. Price promotion is not only used to target existing consumers but also to encourage product or service trial among nonusers of products or services. Thus, it is important for marketers to understand how price promotional informations about a brand have impact on consumer's unfavorable quality perception of the brand. If consumers associate a price promotion itself with inferior quality about unused brand, the promotion may not achieve the sales increase the economic incentives otherwise might have produced. In addition, if the price promotion ends, the consumer that have purchased that certain brand will likely to display sharply decreased repurchasing behavior. Through a literature review, hypothesis 1 was set as follows to investigate the adjustive effect of past price promotion on quality perception made by consumers; The influence that price promotion of unused brand have on quality perception made by consumers will be adjusted by past price promotion activity of the brand. In other words, a price promotion of an unused brand that have not done a price promotion in the past will have a unfavorable effect on quality perception made by consumer. Hypothesis 2-1 was set as follows : When an unused brand undertakes price promotion for the first time, the information presenting pattern of price promotion will have an effect on the consumer's attribution for the cause of the price promotion. Hypothesis 2-2 was set as follows : The more consumer dispositionally attribute the cause of price promotion, the more unfavorable the quality perception made by consumer will be. Through test 1, the subjects were given a brief explanation of the product and the brand before they were provided with a $2{\times}2$ factorial design that has 4 patterns of price promotion (presence or absence of past price promotion * presence or absence of current price promotion) and the explanation describing the price promotion pattern of each cell. Then the perceived quality of imaginary brand WAVEX was evaluated in the scale of 7. The reason tennis racket was chosen is because the selected product group must have had almost no past price promotions to eliminate the influence of average frequency of promotion on the value of price promotional information as Raghubir and Corfman (1999) pointed out. Test 2 was also carried out on students of the same management faculty of test 1 with tennis racket as the product group. As with test 1, subjects with average familiarity for the product group and low familiarity for the brand was selected. Each subjects were assigned to one of the two cells representing two different information presenting patterns of price promotion of WAVEX (case where the reason behind price promotion was provided/case where the reason behind price promotion was not provided). Subjects looked at each promotional information before evaluating the perceived quality of the brand WAVEX in the scale of 7. The effect of price promotion for unfamiliar pretrial brand on consumer's perceived quality was proved to be moderated with the presence or absence of past price promotion. The consistency with past promotional behavior is important variable that makes unfavorable effect on brand evaluations get worse. If the price promotion for the brand has never been carried out before, price promotion activity may have more unfavorable effects on consumer's quality perception. Second, when the price promotion of unfamiliar pretrial brand was executed for the first time, presenting method of informations has impact on consumer's attribution for the cause of firm's promotion. And the unfavorable effect of quality perception is higher when the consumer does dispositional attribution comparing with situational attribution. Unlike the previous studies where the main focus was the absence or presence of favorable or unfavorable motivation from situational/dispositional attribution, the focus of this study was exaus ing the fact that a situational attribution can be inferred even if the consumer employs a dispositional attribution on the price promotional behavior, if the company provides a persuasive reason. Such approach, in academic perspectih sis a large significance in that it explained the anchoring and adjng ch approcedures by applying it to a non-mathematical problem unlike the previous studies where it wis ionaly explained by applying it to a mathematical problem. In other wordn, there is a highrspedency tmatispositionally attribute other's behaviors according to the fuedach aal attribution errors and when this is applied to the situation of price promotions, we can infer that consumers are likely tmatispositionally attribute the company's price promotion behaviors. Ha ever, even ueder these circumstances, the company can adjng the consumer's anchoring tmareduce the po wibiliute thdispositional attribution. Furthermore, unlike majority of previous researches on short/long-term effects of price promotion that only considered the effect of price promotions on consumer's purchasing behaviors, this research measured the effect on perceived quality, one of man elements that affects the purchasing behavior of consumers. These results carry useful implications for the work sector. A guideline of effectively providing promotional informations for a new brand can be suggested through the outcomes of this research. If the brand is to avoid false implications such as inferior quality while implementing a price promotion strategy, it must provide a clear and acceptable reasons behind the promotion. Especially it is more important for the company with no past price promotion to provide a clear reason. An inconsistent behavior can be the cause of consumer's distrust and anxiety. This is also one of the most important factor of risk of endless price wars. Price promotions without prior notice can buy doubt from consumers not market share.

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