• Tuberculosis and Respiratory Diseases
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• v.43 no.2
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• pp.190-200
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• 1996

Background : Mechanical ventilation constitutes the last therapeutic method for acute respiratory failure when oxygen therapy and medical treatment fail to improve the respiratory status of the patient. This invasive ventilation, classically administered by endotracheal intubation or by tracheostomy, is associated with significant mortality and morbidity. Consequently, any less invasive method able to avoid the use of endotracheal ventilation would appear to be useful in high risk patient. Over recent years, the efficacy of nasal mask ventilation has been demonstrated in the treatment of chronic restrictive respiratory failure, particularly in patients with neuromuscular diseases. More recently, this method has been successfully used in the treatment of acute respiratory failure due to parenchymal disease. Method : We assessed the efficacy of Bilevel positive airway pressure(BiPAP) in the treatment of acute exacerbation of chronic obstructive pulmonary disease(COPD). This study prospectively evaluated the clinical effectiveness of a treatment schedule with positive pressure ventilation via nasal mask(Respironics BiPAP device) in 22 patients with acute exacerbations of COPD. Eleven patients with acute exacerbations of COPD were treated with nasal pressure support ventilation delivered via a nasal ventilatory support system plus standard treatment for 3 consecutive days. An additional 11 control patients were treated only with standard treatment. The standard treatment consisted of medical and oxygen therapy. The nasal BiPAP was delivered by a pressure support ventilator in spontaneous timed mode and at an inspiratory positive airway pressure $6-8cmH_2O$ and an expiratory positive airway pressure $3-4cmH_2O$. Patients were evaluated with physical examination(respiratory rate), modified Borg scale and arterial blood gas before and after the acute therapeutic intervention. Results : Pretreatment and after 3 days of treatment, mean $PaO_2$ was 56.3mmHg and 79.1mmHg (p<0.05) in BiPAP group and 56.9mmHg and 70.2mmHg (p<0.05) in conventional treatment (CT) group and $PaCO_2$ was 63.9mmHg and 56.9mmHg (p<0.05) in BiPAP group and 53mmHg and 52.8mmHg in CT group respectively. pH was 7.36 and 7.41 (p<0.05) in BiPAP group and 7.37 and 7.38 in cr group respectively. Pretreatment and after treatment, mean respiratory rate was 28 and 23 beats/min in BiPAP group and 25 and 20 beats/min in CT group respectively. Borg scale was 7.6 and 4.7 in BiPAP group and 6.4 and 3.8 in CT group respectively. There were significant differences between the two groups in changes of mean $PaO_2$, $PaCO_2$ and pH respectively. Conclusion: We conclude that short-term nasal pressure-support ventilation delivered via nasal BiPAP in the treatment of acute exacerbation of COPD, is an efficient mode of assisted ventilation for improving blood gas values and dyspnea sensation and may reduce the need for endotracheal intubation with mechanical ventilation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Korean Journal of Organic Agriculture
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• v.22 no.4
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• pp.731-742
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• 2014

In the current study, we investigated effects of a combination of earthworm casting, environment-friendly by-product fertilizer, and cultivation soil of Gymnocalycium mihanovichii in a heavy fertilizing culture on diameter, height, numbers of tubercles, and chemical properties of soil thereby elucidating optimal mixture ratio for securing production as well as providing nutrients throughout cultivation period. The Gymnocalycium mihanovichii var 'Ihong', one of grafted cactus for export (Rootstock: 9 cm, Scion: $1.5{\times}1.3cm$ grafted cactus) was cultured in plastic houses of Agricultural Technology Center located in Naegok-dong, Seocho-gu, Seoul from June, 2013 through December, 2013. For the control group, a mixture of sand and fertilizer (50:50) was used as this ratio is widely utilized in farmhouses. In contrast, a variety mixtures of sand and earthworm casting that was produced with food wastes was compared; the mixture ratios were 80:20, 60:40, 40:60, 20:80, and 0:100 and pH for these mixtures were found to be similar each other (ranging between 7.1 and 7.4) which is in an appropriate range (pH 6.5-7.5) for cultivation of G. mihanovichii. The organic content was increasing along with increasing contents of earthworm casting ratio while it was lower than the treatment practice group (32-43 mg/kg vs. 55 mg/kg). The content of exchangeable cation was also increasing as the ratio of earthworm casting was elevated; although levels of $K^+$, $Na^+$, and $Mg^{2+}$ were lower than the treatment practice group, the level of $Ca^{2+}$ was higher ($9.1cmol^+/kg$ and $11.5-33.7cmol^+/kg$ in the treatment practice group and the earthworm casting group, respectively). Three months after grafting, diameters of G. mihanovichii were compared with the control group; consequently, there was a significant difference noted in between the earthworm casting group and the control group (31.39 mm vs. 32.46-37.59 mm). After 5 months, growth characteristics of G. mihanovichii were evaluated. Similarly, the diameter of G. mihanovichii was significantly increasing in the group with higher ratio of earthworm casting treatment (32.63 mm vs. 32.49-37.59 mm). The height of tubercles was 2.63 mm in the control group while it was significantly elevating along with the ratio of earthworm casting mixture. The more numbers of tubercles, the more incomes for farm-houses; as results, higher mixture ration of earthworm casting resulted more numbers of tubercles compared to the control group (2.7 vs. 3.2-8.3 ea). In particular, in the earthworm casting groups with 80% and 100% ratios, the numbers of tubercles were 6.2 and 8.3 ea, respectively, which is 2.5 times more than those of the control group. These results indicate that earthworm casting treatment may be utilized in G. mihanovichii farming houses for short term production of tubercles. In the group with 40% and 60% of earthworm casting mixture, the numbers of tubercles were found to be 4.5 and 4.8 ea, respectively which is higher than the control group as well; in these groups, there were no issues with soil drainage as well as moss formation. Given the analysis results of growth characteristics of G. mihanovichii, it was concluded that 40% and 60% of earthworm casting mixture might be the optimal ratios.

• Journal of The Korean Society of Grassland and Forage Science
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• v.18 no.2
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• pp.95-106
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• 1998

A study was made to estimate the economic level(Necon.) of mineral nitrogen and a cutting frequency for the dry matter production of reed canarygrass(Phalaris arundinacea L.) in uncultivated rice paddy during the harvested years in 1993~1995. Annual mineral nitrogen was applied at the levels of 0, 90, 180, 270 and 360 kg $ha^{-1}$ in 3 cuttings, 0, 120, 240, 360 and 480 kg $ha^{-1}$ in 4 cuttings, and 0, 150, 300, 450 and 600 kg $ha^{-1}$ in 5 cuttings, respectively. The results were summarized as follows; 1. The dry matter yields of all cutting frequencies in 1993 were significantly higher than in the other hay years. Mean dry matter yield were 14.40, 13.88 and 15.98 tons $ha^{-1}$ in 3, 4 and 5 cuttings, respectively. 2. Significantly higher matter yields were obtained as 15.37 and 15.80 tons $ha^{-1}$ at the level of 120 kg $ha^{-1}\;cut^{-1}$ in 3 and 4 cuttings, and 14.02~14.08 tons $ha^{-1}$ levels of 90~120 kg $ha^{-1}$ in 5 cuttings, respectively. 3. Higher efficiencies of dry matter production in response to mineral nitrogen application were recorded as 29.7 kg at level of 90 kg $ha^{-1}\;yr^{-1}$ in 3 cuttings, 19.6 kg at level of 240 kg $ha^{-1}\;yr^{-1}$ in 4 cuttings, and 20.1 kg at level of 150 kg $ha^{-1}\;yr^{-1}$ in 5 cuttings, respectively. 4. Significantly higher matter yields appeared as 5.02 tons $ha^{-1}$ at 2nd cut in 3 cuttings, 3.94~4.37 tons $ha^{-1}$ at 2nd and 3rd cut in 4 cuttings, and 3.81~3.58 tons $ha^{-1}$ at 2nd and 3rd cut in 5 cuttings, respectively. 5. The highest values of relative dry matter yield were 40.4% for 2nd cut in 3 cuttings, 34.9% for 3rd cut in 4 cuttings, and 31.5% for 2nd cut in 5 cuttings, respectively. 6. The estimated marginal dry matter yields(Ymar.) were 13.8~14.7 tons $ha^{-1}$ at ranges of economic N level of 228.5~291.9 kg $ha^{-1}\;yr^{-1}$ in 3 cuttings, 13.8~14.2 tons $ha^{-1}$ at ranges of 293.5~335.7 kg $ha^{-1}\;yr^{-1}$ in 4 cuttings, and 12.2~12.8 tons $ha^{-1}$ at ranges of 237.5~302.5 kg $ha^{-1}\;yr^{-1}$ in 5 cuttings, respectively. 7. Maximun dry matter yields(Ymax.) were 17.0 tons at the level of limiting N(Nmax.) of 558.9 kg $ha^{-1}\;yr^{-1}$ in 3 cuttings, 16.1 ton at level of limiting N of 531.4 kg $ha^{-1}\;yr^{-1}$ in 4 cuttings, and 13.9 ton at level of limiting N of 546.3 kg $ha^{-1}\;yr^{-1}$ in 5 cuttings, respectively. 8. Economic N level in all cuts were in the ranges of 42.6~123.8 kg $ha^{-1}$ in 3 cuttings, 27.3~144.1 kg $ha^{-1}$ in 4 cuttings, and 9.3~159.4 kg $ha^{-1}$ in 5 cuttings, respectively. 9. The proper cutting frequency for matter production of reed canarygrass was 3 cuttings during the h harvested years in 1993~1995, due mainly to the higher efficiency of N for the dry matter production.

• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.579-588
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• 2018

Purpose : To analyze the eyeglasses supply system for ametropic soldiers in ROK military. Methods : We investigated and analyzed the supply system of eyeglasses for the ametropic soldiers provided by the Korean military. The refractive powers and corrected visual acuity were measured for 37 ametropic soldiers who wear insert glasses for ballistic protective and gas-masks supplied by the military based on their habitual prescriptions. Full correction of refractive error was prescribed for subjects having less than 1.0 of distance visual acuity, and comparison was held for inspecting the changes in corrected visual acuity. Suggestions were provided for solving the issues regarding current supplying system, and this study investigated the applicabilities for utilizing professional optometric manpower. Results : The new glasses supplied by army for ametropic soldiers were duplicated from the glasses they worn when entering the army. The spherical equivalent refractive powers of the conventional, ballistic protective and gas-mask insert glasses supplied for 37 ametropic soldiers were $-3.47{\pm}1.69D$, $-3.52{\pm}1.66D$ and $-3.55{\pm}1.63D$, respectively, and the spherical equivalent refractive power of full corrected glasses was $-3.79{\pm}1.66D$, which showed a significant difference(p<0.05). The distant corrected visual acuity measured at high and low contrast(logMAR) of conventional, ballistic protective and gas-mask insert glasses were $0.06{\pm}0.80$, $0.21{\pm}0.82$, $0.15{\pm}0.74$, $0.34{\pm}0.89$, $0.10{\pm}0.70$ and $0.22{\pm}0.27$, respectively, while the corrected visual acuity by full corrected glasses were increased to $0.02{\pm}1.05$, $0.10{\pm}0.07$, $0.09{\pm}0.92$, $0.26{\pm}0.10$, $0.04{\pm}1.00$ and $0.19{\pm}1.00$, respectively. There was a significant difference(p<0.05) except for the case of the low contrast corrected visual acuity of the conventional and gas-mask insert glasses. The procedure for ordering, dispensing, and supplying military glasses consists of 5 steps, and it was found that approximately two weeks or more are required to supply from the initial examination. Conclusion : The procedure of supplying the military glasses showed three issues: 1) a lack of refraction for prescription system, 2) relatively long length of time required for supplying the glasses, 3) an inaccurate power of supplied glasses. In order to solve those issues, in the short term, education is necessarily required for soldiers on the measurement of the refractive powers, and in the near future, further standard procedures for prescription of glasses as well as the securement of optometric manpower are expected.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.219-240
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• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.

• Asia Marketing Journal
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• v.12 no.2
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• pp.111-133
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• 2010

Marketing financial services used to be easier. Today, the competition in financial services is fierce. Not only has the competition become more intense, financial services have also changed structurally. In an environment with various customer needs and severe competitions, the marketing in financial services industry is getting more difficult and more important than before. However, there are still not enough studies on financial services marketing in Korea whereas lots of research papers have been published frequently in some international journals. The purpose of this paper is (1)to review the literature on financial services marketing, (2)to investigate current marketing activities based on in-depth interview with financial marketing managers in Korea, and (3)to suggest some implications for future research on the financial services marketing. Financial products are not consumer products. In fact, they are not products at all in the way product marketing is usually described. Nor are they altogether like services. The financial industry operates in a unique way, and its marketing tasks are correspondingly complex. However, the literature review shows that there has been a lack of basic studies which dealt with inherent characteristics of financial services marketing compared to the research on marketing in other industries. Many studies in domestic marketing journals have so far focused only on the general customer behaviors and the special issues in some financial industries. However, for more effective financial services marketing, we have to answer following questions. Is there any difference between financial service marketing and consumer packaged goods marketing? What are the differences between the financial services marketing and other services marketing such as education and health services? Are there different ways of marketing among banks, securities firms, insurance firms, and credit card companies? In other words, we need more detailed research as well as basic studies about the financial services marketing. For example, we need concrete definitions of financial services marketing, bank marketing, securities firm marketing, and etc. It is also required to compare the characteristics of each marketing within the financial services industry. The products sold in each market have different characteristics such as duration and degree of risk-taking. It means that there are sub-categories in financial services marketing. We have to consider them in the future research on the financial services marketing. It is also necessary to study customer decision making process in the financial markets. There have been little research on how customers search and process information, compare alternatives, make final decision, and repeat their choices. Because financial services have some unique characteristics, we need different understandings in the customer behaviors compared to the behaviors in other service markets. And also considering the rapid growth in financial markets and upcoming severe competition between domestic and global financial companies, it is time to start more systematic and detailed research on financial services marketing in Korea. In the second part of this paper, I analyzed the results of in-depth interview with 20 marketing managers of financial services companies in Korea. As a result, I found that the role of marketing departments in Korean financial companies are mainly focused on the short-term activities such as sales support, promotion, and CRM data analysis although the size and history of marketing departments to some extent show a sign of maturity. Most companies established official marketing departments before 2001. Average number of employees in a marketing department is about 58. However, marketing managers in eight companies(40% of the sample) still think that the purpose of marketing is only to support and manage general sales activities. It shows that some companies have sales-oriented concept rather than marketing-oriented concept. I also found three key words which marketing managers think importantly in financial services markets. They are (1)Trust in customer relationship, (2)Brand differentiation, and (3)Rapid response to customer needs. 50% of the sample support that "Trust" is the most important key word in the financial services marketing. It is interesting that 80% of banks and securities companies think that "Trust" is the most important thing, whereas managers in credit card companies consider "Rapid response to customer needs" as the most important key word in their market. In addition, there are different problems recognition of marketing managers depending on the types of financial industries they belong to. For example, in the case of banks and insurance companies, marketing managers consider "a lack of communication with other departments" as the most serious problem. On the other hand, in the case of securities firms, "a lack of utilization of customer data" is the most serious problem. These results imply that there are different important factors for the customer satisfaction depending on the types of financial industries, and managers have to consider them when marketing financial products in more effective ways. For example, It will be necessary for marketing managers to study different important factors which affect customer satisfaction, repeat purchase, degree of risk-taking, and possibility of cross-selling according to the types of financial industries. I also suggested six hypothetical propositions for the future research.

• Asia Marketing Journal
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• v.12 no.4
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• pp.55-78
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• 2011

Recently strategic alliance between business firms has become prevalent to overcome increasing competitive threats and to supplement resource limitation of individual firms. As one of allianced sales promotion activities, a new type of discount program, so called "Alliance Card Discount", is introduced with the partnership of credit cards and loyalty cards. The program mainly pursues short-term sales growth by larger discount scheme while spends less through cost share among alliance partners. Thus this program can be regarded as cost efficient discount promotion. But because there is no solid evidence that it can really deliver profitable sales growth, an empirical study for its effects on sales and profit should be conducted. This study has two basic research questions concerning the effects of allianced discount program ; 1)the possibility of sales increase 2) the profitability of the discount driven sales. In F&B industry, sales increase mainly comes from increased guest count. Especially in family restaurants, to increase the number of guests we need to enlarge the size of visitor group (number of visitors for one group) because customers visit by group in a special occasion. And because they pay the bill by group(table), the increase of sales per table is a key measure for sales improvement. The past researches for price & discount sensitivity and reference discount rate explain that price sensitive consumers have narrow reference discount zone and make rational purchase decision. Differently from all time discount scheme of regular sales promotions, the alliance card discount program only provides the right to get discount like discount coupon. And because it is usually once a month opportunity given by the past month usage level, customers tend to perceive alliance card discount as a rare chance to get. So that we can expect customers try to maximize the discount effect when they use the limited discount opportunity. Considering group visiting practice and low visit frequency of family restaurants, the way to maximize discount effect should be the increase the size of visit group. And their sensitivity to discount and rational consumption behavior defer the additional spending for ordering high price menu, even though they get considerable amount of savings from the discount. From the analysis of sales data paid by alliance discount cards for four months, we found the below. 1) The relation between discount rate and number of guest per table is positive : 25% discount results one additional guest 2) The relation between discount rate and the spending per guest is negative. 3) However, total profit amount per table is increased when discount rate is increased. 4) Reward point accumulation & redemption did not show any significant relationship with the increase of number of guests. These results suggest that the allianced discount program substantially contributes to sales increase and profit improvement by increasing the number of guests per table. Though the spending per guest is decreased by discount rate increase, the total amount of profit per table is improved. It seems the incremental profit by increased guest count offsets the profit decrease. Additional intriguing finding is the point reward system does not have any significant impact on the increase of number of guest, even if the point accumulation & redemption of loyalty program are usually regarded as another saving offers by customers. In sum, because it is proved that allianced discount program with credit cards and loyalty cards is effective to both sales drive and profit increase, the alliance card program could be recommended as strategically buyable program.