• Journal of Venture Innovation
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• v.5 no.2
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• pp.49-66
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• 2022

This study intends to examine how the perception of covid-19 risk affects consumers' consumption behavior based on previous studies in a situation where the spread of covid-19 is prolonged. This study demonstrates how consumers' perception of covid-19 risk affects online and offline consumption behavior through the perceived severity, perceived vulnerability, coping effectiveness, and self-efficacy of the revised protective motivation theory (Rogers, 1983). We want to test it through analysis. In order to achieve the purpose of this study, consumers living in Seoul and Gyeonggi Province who have purchased within the past 3 months were selected as a sample. In addition, variable data such as risk perception of covid-19, perceived severity, perceived vulnerability, coping effectiveness, self-efficacy, online purchase attitude and purchase intention, offline purchase attitude and purchase intention were collected through the questionnaire.A total of 363 copies of valid responses were tested to test the hypothesis of the relationship between variables through the covariance structure model. The analysis results of this study were first, that covid-19 risk perception had a significant positive (+) effect on perceived severity, perceived vulnerability, and coping effectiveness. Second, perceived severity and perceived vulnerability were found to have a significant positive (+) effect on offline purchasing attitude. Third, perceived severity, perceived vulnerability, coping plan effectiveness, and self-efficacy were all found to have significant positive (+) effects on online purchase attitude. Finally, it was found that offline purchase attitude and online purchase attitude had a significant positive (+) effect on offline purchase intention and online purchase intention, respectively. Also, it was found that online purchase attitude had a negative (-) effect on offline purchase intention. The results of this analysis will provide meaningful implications for the establishment of strategies for distribution channels according to the social risk of infectious diseases.

• Journal of Venture Innovation
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• v.7 no.3
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• pp.65-84
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• 2024

This study confirms the relative influence of satisfaction with the government's start-up support project at each growth stage of start-up companies and entrepreneurs' commercialization capabilities on start-up commitment. The start-up growth stage was divided into start-up stage, initial growth stage, stagnation stage, and high growth stage, and the government's start-up support project was divided into eight types(entrepreneurship education, mentoring/consulting, facility space, commercialization support, policy funds, sales channels/marketing/overseas expansion, R&D support, and start-up events/network) and satisfaction was evaluated. The data used was the results of the Daegu Creative Economy Innovation Center's survey on entrepreneurship conditions. As a result of the analysis, it was confirmed that the entrepreneur's commercialization capabilities are more effective in increasing the entrepreneur's commitment to starting a business than the satisfaction with the government's start-up support project. Additionally, it was confirmed that relatively important factors in entrepreneurship immersion differ depending on the start-up stage. During the start-up period, the government's start-up support project was found to be an important factor in increasing entrepreneurs' commitment to starting a business, but it was confirmed that the government's start-up support project had no effect on the start-up commitment after the start-up growth stage. In addition, this study confirmed the relatively important government start-up support projects by start-up growth stage and found that satisfaction with start-up facilities can increase start-up commitment during the start-up stage, and that start-up facilities and commercialization support are important during the early growth stage. And in the Death Valley stage, startup facilities, commercialization support, and policy funds were confirmed to be relatively important factors, and in the high growth stage, mentoring was confirmed to be an important factor in increasing entrepreneurship immersion. The results of this study not only contribute theoretically to building entrepreneurship theory, but also determine the size and effective support plan for the government's entrepreneurship support project for each growth stage of startup companies, and help organizations that operate entrepreneurship policy and institutional support and startup support programs. It will have a significant contribution to management measures.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.33-37
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• 2010

Purpose: In the early stage of using PET/CT, it was used to damper revision but recently shows that CT with MDCT is commonly used and works well for an anatomical diagnosis. This hospital makes the accuracy and convenience more higher in the diagnosis and evaluate of coronary heart disease through concurrently running myocardial perfusion SPECT examination, myocardial PET examination with FDG, and CT coronary artery CT angiography(coronary CTA) used PET/CT with 64-slice. This report shows protocol and image based on results from about 400 coronary heart disease examinations since having 64 channels PET/CT in July 2007. Materials and Methods: An Equipment for this examination is 64-slice CT and Discovery VCT (DVCT) that is consisted of PET with BGO ($Bi_4Ge_3O_{12}$) scintillation crystal by GE health care. First myocardial perfusion SPECT with pharmacologic stress test to reduce waiting time of a patient and get a quick diagnosis and evaluation, and right after it, myocardial FDG PET examination and coronary CTA run without a break. One-stop evaluation protocol of ischemic heart disease is as follows. 1)Myocardial perfusion SPECT with pharmacologic stress: A patient is injected with $^{99m}Tc$-MIBI 10 mCi and does not have any fatty food for myocardial PET examination and drink natural water with ursodeoxcholic acid 100 mg and we get SPECT image in an hour. 2)Myocardial FDG PET: To reduce blood fatty content and to increase uptake of FDG, we used creative oral glucose load using insulin and Acipimox to according to blood acid content. A patient is injected with $^{18}F$-FDG 5 mCi for reduction of his radiation exposure and we get a gated image an hour later and get delay image when we need. 3) Coronary CTA: The most important point is to control heart rate and to get cooperation of patient's breath. In order to reduce a heart rate of him or her below 65 beats, let him or her take beta blocker 50 mg ~ 200 mg after a consultation with a doctor about it and have breath-practices then have the examination. Right before the examination, we spray isosorbide dinitrate 3 to 5 times to lower tension of bessel wall and to extension a blood wall of a patient. It makes to get better the shape of an anatomy. At filming, a patient is injected CT contrast with high pressure and have enough practices before the examination in order to have no problem. For reduction of his radiation exposure, we have to do ECG-triggered X-ray tube modulation exposure. Results: We evaluate coronary artery stenosis through coronary CTA and study correlation (culprit vessel check) of a decline between stenosis and perfusion from the myocardial perfusion SPECT with pharmacologic stress, coronary CTA, and can check viability of infarction or hibernating myocardium by FDG PET. Conclusion: The examination makes us to set up a direction of remedy (drug treatment, PCI, CABG) because we can estimate of effect from remedy, lesion site and severity. In addition, we have an advantage that it takes just 3 hours and one-stop in that all of process of examinations run in succession and at the same time. Therefore it shows that the method is useful in one stop evaluation of ischemic heart disease.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• Journal of Haehwa Medicine
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• v.8 no.2
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• pp.211-243
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• 2000

This study was performed to investigate the cause, symptom, treatment, medicine of Wei symptom through the literature of oriental and western medicine. The results obtained were as follows: 1. Wei symptom is the symptom that reveals muscle relaxation without contraction and muscle relaxation occures in the lower limb or upper limb, in severe case, leads to death. 2. Since the pathology and etiology of Wei symptom was first described as "pe-yeol-yeop-cho"(肺熱葉焦) in Hung Ti Nei Ching(黃帝內經), for generations most doctors had have accepted it. but after Dan Ge(丹溪), it had been classified into seven causes, damp-heat(濕熱), phlegm-damp(濕痰), deficiency of qi(氣虛), deficiency of blood(血虛), deficiency of yin(陰處), stagnant blood(死血), stagnant food(食積). Chang Gyeng Ag(張景岳) added the cause of deficiency of source qi(元氣). 3. The concept of "To treat Yangming, most of all"(獨治陽明) was emphasized in the treatment of Wei symptom and contains nourishment of middle warmer energy(補益中氣), clearance of yangming-damp-heat(淸化陽明濕熱). 4. Since Nei-ching era(內經時代), Wei and Bi symptom(痺症) is differenciated according to the existence of pain. After Ming era(明代) appeared theory of co-existence of Wei symptom and pain or numbness but they were accepted as a sign of Wei symptom caused by the pathological factor phelgm(痰), damp(濕), stagnancy(瘀). 5. In the western medical point of view, Wei symptom is like paraplegia, or tetraplegia. and according to the causative disease, it is accompanied by dysesthesia, paresthsia, pain. thus it is more recommended to use hwal-hyel-hwa-ae(活血化瘀) method considering damp-heat(濕熱), qi deficiency of spleen and stornach(脾胃氣虛) as pathological basis than to simply differenciate Wei and Bi symptom according to the existence of pain. 6. The cause of Gullian-Barre syndrome(GBS) is consist of two factors, internal and external. Internal factors include asthenia of spleen and stomach, and of liver and kidney. External factors include summur-damp(暑濕), damp-heat(濕熱), cold-damp(寒濕) and on the basis of "classification and treatment according to the symptom of Zang-Fu"(臟腑辨證論治), the cause of GBS is classified into injury of body fluid by lung heat(肺熱傷津), infiltration of damp-heat(濕熱浸淫), asthenia of spleen and kidney(脾腎兩虛), asthenia of spleen and stomach(脾胃虛弱), asthenia of liver and kidney (肝腎兩虛). 7. The cause of GBS is divided by according to the disease developing stage: Early stage include dryness-heat(燥熱), damp(濕邪), phlegm(痰濁), stagnant blood(瘀血), and major treatment is reducing of excess(瀉實). Late stage include deficiency of essence(精虛), deficiency with excess(虛中挾實), and essencial deficiency of liver and kidney(肝腎精不足) is major point of treatment. 8. Following is the herbal medicine of GBS according to the stage. In case of summur-damp(暑濕), chung-seu-iki-tang(淸暑益氣湯) is used which helps cooling and drainage of summer-damp(淸利暑濕), reinforcement of qi and passage of collateral channels(補氣通絡). In case of damp-heat, used kun-bo-hwan(健步丸), In case of cool-damp(寒濕), used 'Mahwang-buja-sesin-tang with sam-chul-tang'(麻黃附子細辛湯合蓼朮湯). In case of asthenia of spleen and kidney, used 'Sam-lyeng-baik-chul san'(蔘笭白朮散), In case of asthenia of liver and kidney, used 'Hojam-hwan'(虎潛丸). 9. Following is the herbal medicine of GBS according to the "classification and treatment according to the symptom of Zang-Fu"(臟腑辨證論治). In the case of injury of body fluid by lung heat(肺熱傷津), 'Chung-jo-gu-pae-tang'(淸燥救肺湯) is used. In case of 'infiltration of damp-heat'(濕熱浸淫), us-ed 'Yi-myo-hwan'(二妙丸), In case of 'infiltration of cool-damp'(寒濕浸淫), us-ed 'Yui-lyung-tang', In case of asthenia of spleen, used 'Sam-lyung-bak-chul-san'. In case of yin-deficiency of liver and kidney(肝腎陰虛), used 'Ji-bak-ji-hwang-hwan'(知柏地黃丸), or 'Ho-jam-hwan'(虎潛丸). 10. Cervical spondylosis with myelopathy is occuered by compression or ischemia of spinal cord. 11. The cause of cervical spondylosis with myelopathy consist of 'flow disturbance of the channel points of tai-yang'(太陽經兪不利), 'stagnancy of cool-damp'(寒濕凝聚), 'congestion of phlegm-damp stagnant substances'(痰濕膠阻), 'impairment of liver and kidney'(肝腎虛損). 12. In treatment of cervical spondylosis with myelopathy, are used 'Ge-ji-ga-gal-geun-tang-gagam'(桂枝加葛根湯加減), 'So-hwal-lack-dan-hap-do-hong-eum-gagam(小活絡丹合桃紅飮加減), 'Sin-tong-chuck-ue-tang-gagam(身痛逐瘀湯加減), 'Do-dam-tang-hap-sa-mul-tang-gagam'(導痰湯合四物湯加減), 'Ik-sin-yang-hyel-guen-bo-tang'(益腎養血健步湯加減), 'Nok-gakyo-hwan-gagam'(鹿角膠丸加減). 13. The cause of muscle dystropy is related with 'the impairement of vital qi'(元氣損傷), and 'impairement of five Zang organ'(五臟敗傷). Symptoms and signs are classified into asthenia of spleen and stomach, deficiency with excess, 'deficiency of liver and kidney'(肝腎不足) infiltration of damp-heat, 'deficiency of qi and blood'(氣血兩虛), 'yang deficiency of spleen and kidney'(脾腎陽虛). 14. 'Bo-jung-ik-gi-tang'(補中益氣湯), 'Gum-gang-hwan'(金剛丸), 'Yi-gong-san-hap-sam-myo-hwan'(異功散合三妙丸), 'Ja-hyel-yang-gun-tang'(滋血養筋湯), 'Ho-jam-hwan'(虎潛丸) are used for muscle dystropy. 15. The causes of myasthenia gravis are classified into 'insufficiency of middle warmer energy'(中氣不足), 'deficiency of qi and yin of spleen and kidney'(脾腎兩處), 'asthenia of qi of spleen'(脾氣虛弱), 'deficiency of qi and blood'(氣血兩虛), 'yang deficiency of spleen and kidney'(脾腎陽虛). 16. 'Bo-jung-ik-gi-tang-gagam'(補中益氣湯加減), 'Sa-gun-ja-tang-hap-gi-guk-yang-hyel-tang'(四君子湯合杞菊地黃湯), 'Sa-gun-ja-tang-hap-u-gyi-eum-gagam'(四君子湯合右歸飮加減), 'Pal-jin-tang'(八珍湯), 'U-gyi-eum'(右歸飮) are used for myasthenia gravis.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.141-173
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• 2007

The study examines how the environmental factors of store influence service brand personality and repurchase intention in the service environment. The service industry has been experiencing the intensified competition with the industry's continuous growth and the influence from rapid technological advancement. Under the circumstances, it has become ever more important for the brand competitiveness to be distinctively recognized against competition. A brand needs to be distinguished and differentiated from competing companies because they are all engaged in the similar environment of the service industry. The differentiation of brand achievement has become increasingly important to highlight certain brand functions to include emotional, self-expressive, and symbolic functions since the importance of such functions has been further emphasized in promoting consumption activities. That is the recent role of brand personality that has been emphasized in the service industry. In other words, customers now freely and actively express their personalities or egos in consumption activities, taking an important role in construction of a brand asset. Hence, the study suggests that it is necessary to disperse the recognition and acknowledgement that the maintenance of the existing customers contributes more to boost repurchase intention when it is compared to the efforts to create new customers, particularly in the service industry. Meanwhile, the store itself can offer a unique environment that may influence the consumer's purchase decision. Consumers interact with store environments in the process of,virtually, all household purchase they make (Sarel 1981). Thus, store environments may encourage customers to purchase. The roles that store environments play are to provide informational cues to customers about the store and goods and communicate messages to stimulate consumers' emotions. The store environments differentiate the store from competing stores and build a unique service brand personality. However, the existing studies related to brand in the service industry mostly concentrated on the relationship between the quality of service and customer satisfaction, and they are mostly generalized while the connective studies focused on brand personality. Such approaches show limitations and are insufficient to investigate on the relationship between store environment and brand personality in the service industry. Accordingly, the study intends to identify the level of contribution to the establishment of brand personality made by the store's physical environments that influence on the specific brand characteristics depending on the type of service. The study also intends to identify what kind of relationships with brand personality exists with brand personality while being influenced by store environments. In addition, the study intends to make meaningful suggestions to better direct marketing efforts by identifying whether a brand personality makes a positive influence to induce an intention for repurchase. For this study, the service industry is classified into four categories based on to the characteristics of service: experimental-emotional service, emotional -credible service, credible-functional service, and functional-experimental service. The type of business with the most frequent customer contact is determined for each service type and the enterprise with the highest brand value in each service sector based on the report made by the Korea Management Association. They are designated as the representative of each category. The selected representatives are a fast-food store (experimental-emotional service), a cinema house (emotional-credible service), a bank (credible-functional service), and discount store (functional-experimental service). The survey was conducted for the four selected brands to represent each service category among consumers who are experienced users of the designated stores in Seoul Metropolitan City and Gyeonggi province via written questionnaires in order to verify the suggested assumptions in the study. In particular, the survey adopted 15 scales, which represent each characteristic factor, among the 42 unique characteristics developed by Jennifer Aaker(1997) to assess the brand personality of each service brand. SPSS for Windows Release 12.0 and LISREL were used in the analysis of data verification. The methodology of the structural equation model was used for the study and the pivotal findings are as follows. 1) The environmental factors ware classified as design factors, ambient factors, and social factors. Therefore, the validity of measurement scale of Baker et al. (1994) was proved. 2) The service brand personalities were subdivided as sincerity, excitement, competence, sophistication, and ruggedness, which makes the use of the brand personality scales by Jennifer Aaker(1997) appropriate in the service industry as well. 3) One-way ANOVA analysis on the scales of store environment and service brand personality showed that there exist statistically significant differences in each service category. For example, the social factors were highest in discount stores, while the ambient factors and design factors were highest in fast-food stores. The discount stores were highest in the sincerity and excitement, while the highest point for banks was in the competence and ruggedness, and the highest point for fast-food stores was in the sophistication, The consumers will make a different respond to the physical environment of stores and service brand personality that are inherent to the corresponding service interface. Hence, the customers will make a different decision-making when dealing with different service categories. In this aspect, the relationships of variables in the proposed hypothesis appear to work in a different way depending on the exposed service category. 4) The store environment factors influenced on service brand personalities differently by category of service. The factors of store's physical environment are transferred to a brand and were verified to strengthen service brand personalities. In particular, the level of influence on the service brand personality by physical environment differs depending on service category or dimension, which indicates that there is a need to apply a different style of management to a different service category or dimension. It signifies that there needs to be a brand strategy established in order to positively influence the relationship with consumers by utilizing an appropriate brand personality factor depending on different characteristics by service category or dimension. 5) The service brand personalities influenced on the repurchase intention. Especially, the largest influence was made in the sophistication dimension of service brand personality scale; the unique and characteristically appropriate arrangement of physical environment will make customers stay in the service environment for a long time and will lead to give a positive influence on the repurchase intention. 6) The store environment factors influenced on the repurchase intention. Particularly, the largest influence was made on the social factors of store environment. The most intriguing finding is that the service factor among all other environment factors gives the biggest influence to the repurchase intention in most of all service types except fast-food stores. Such result indicates that the customers pay attention to how much the employees try to provide a quality service when they make an evaluation on the service brand. At the same time, it also indicates that the personal factor is directly transmitted to the construction of brand personality. The employees' attitude and behavior are the determinants to establish a service brand personality in the process of enhancing service interface. Hence, there should be a reinforced search for a method to efficiently manage the service staff who has a direct contact with customers in order to make an affirmative improvement of the customers' brand evaluation at the service interface. The findings suggest several managerial implications. 1) Results from the empirical study indicated that store environment factors have a strong positive impact on a service brand personality. To increase customers' repurchase intention of a service brand, the management is required to effectively manage store environment factors and create a friendly brand personality based on the corresponding service environment. 2) Mangers and researchers must understand and recognize that the store environment elements are important marketing tools, and that brand personality influences on consumers' repurchase intention. Based on such result of the study, a service brand could be utilized as an efficient measure to achieve a differentiation by enforcing the elements that are most influential among all other store environments for each service category. Therefore, brand personality established involving various store environments will further reinforce the relationship with customers through the elevated brand identification of which utilization to induce repurchase decision can be used as an entry barrier. 3) The study identified the store environment as a component of service brand personality for the store's effective communication with consumers. For this, all communication channels should be maintained with consistency and an integrated marketing communication should be executed to efficiently approach to a larger number of customers. Mangers and researchers must find strategies for aligning decisions about store environment elements with the retailers' marketing and store personality objectives. All ambient, design, and social factors need to be orchestrated so that consumers can take an appropriate store personality. In this study, the induced results from the previous studies were extended to the service industry so as to identify the customers' decision making process that leads to repurchase intention and a result similar to those of the previous studies. The findings suggested several theoretical and managerial implications. However, the situation that only one service brand served as the subject of analysis for each service category, and the situation that correlations among store environment elements were not identified, as well as the problem of representation in selection of samples should be considered and supplemented in the future when further studies are conducted. In addition, various antecedents and consequences of brand personality must be looked at in the aspect of the service environment for further research.