• Tuberculosis and Respiratory Diseases
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• v.58 no.6
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• pp.562-569
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• 2005

Background : The severity scoring system is useful for predicting the outcome of critically ill patients. However, the system is quite complicated and cost-ineffective. Simple serologic markers have been proposed to predict the outcome, which include troponin-I, lactate and C-reactive protein(CRP). The aim of this study was to evaluate the prognostic values of troponin-I, lactate and CRP in critically ill non-cardiac patients. Methods : From September 2003 to June 2004, 139 patients(Age: $63.3{\pm}14.7$, M:F = 88:51), who were admitted to the MICU with non-cardiac critical illness at Gyeongsang National University Hospital, were enrolled in this study. This study evaluated the severity of the illness and the multi-organ failure score (Acute Physiologic and Chronic Health EvaluationII, Simplified Acute Physiologic ScoreII and Sequential Organ Failure Assessment) and measured the troponin-I, lactate and CRP within 24 hours after admission in the MICU. Each value in the survivors and non-survivors was compared at the 10th and 30th day after ICU admission. The mortality rate was compared at 10th and 30th day in normal and abnormal group. In addition, the correlations between each value and the severity score were assessed. Results : There were significantly higher troponin-I and CRP levels, not lactate, in the non-survivors than in the survivors at 10th day($1.018{\pm}2.58ng/ml$, $98.48{\pm}69.24mg/L$ vs. $4.208{\pm}10.23ng/ml$, $137.69{\pm}70.18mg/L$) (p<0.05). There were significantly higher troponin-I, lactate and CRP levels in the non-survivors than in the survivors on the 30th day ($0.99{\pm}2.66ng/ml$, $8.02{\pm}9.54ng/dl$, $96.87{\pm}68.83mg/L$ vs. $3.36{\pm}8.74ng/ml$, $15.42{\pm}20.57ng/dl$, $131.28{\pm}71.23mg/L$) (p<0.05). The mortality rate was significantly higher in the abnormal group of troponin-I, lactate and CRP than in the normal group of troponin-I, lactate and CRP at 10th day(28.1%, 31.6%, 18.9% vs. 11.0%, 15.8 %, 0%) and 30th day(38.6%, 47.4%, 25.8% vs. 15.9%, 21.7%, 14.3%) (p<0.05). Troponin-I and lactate were significantly correlated with the SAPS II score($r^2=0.254$, 0.365, p<0.05). Conclusion : Measuring the troponin-I, lactate and CRP levels upon admission may be useful for predicting the outcome of critically ill non-cardiac patients.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.3
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• pp.316-338
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• 1988

To identify the physiological phenomena on the sudden wilting of japonica/indica crossed varieties, Pot experiment was carried out under the heavy N application with various levels of potassium in Japan. The results obtained are as follows. 1. Sudden wilting was occurred in both varieties used, Yushin and Milyang 23. The former showed a higher degree than the latter. 2. Sudden wilting was occurred into two types, one at early ripening stage and the other at late ripening stage. The former type was found in the field with low potassium supply and the latter was seemed to be related to varietal wilting tolerence. 3. By the investigation of concerning the effective tillering rate and the change of dry weight of each organ at the heading stage, it was inferred that the growth status from young panicle formation stage to heading stage were related to sudden wilting tolerence. 4. Manganese content at heading stage, ratio of Fe/Mn and Fe. Fe/Mn in stern at late ripening stage and $K_2$ O/N ratio of stem at harvesting stage were recognized as the specific factors in connection with sudden wilting. Mn content in the sudden wilting rice plant was already in creased remarkably at heading stage. In relation to root age and absoption characteristics of Mn, the senility of root before heading stage was inferred as the cause of increase the value of Fe/Mn or Fe. Fe/Mn. 5. The $K_2$ O/N ratio of culm at harvesting stage was lower in upper node than lower node in relation to sudden wilting. And it was well accordance with the fact that the symptoms of sudden wilting proceeded from upper leaf to lower leaf. These phenomenon was different from the usual one that the effect of potassium deficiency was more remarkable in lower node than upper node. 6. All varieties which have a condition of potassium deficiency have a high degree of nitrogen content of leaves at heading stage and the $K_2$ O/N ratio of each organ was low, Especialy, $K_2$ O/N ratio is much lower in sheath and culm than leaves.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.141-153
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• 1986

This study intends to document the existing cyclical fluctuations of garic and onion price at farm gate level during the period of 1966-1986 in Korea. The existing patterns of such cyclical fluctuations were estimated systematically by removing the seasonal fluctuation and irregular movement as well as secular trend from the original price through the moving average method. It was found that the cyclical fluctuations of garic and onion prices repeated six and seven times respectively during the same period, also the amplitude coefficient of cyclical fluctuations showed speed up in recent years. It was noticed that the cyclical fluctuations of price in onion was higher than that of in garic.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.83-95
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• 2018

Purpose : After planning the Respiratory Gated Radiotherapy for Lung cancer, the movement and volume change of sparing normal structures nearby target are not often considered during dose evaluation. This study carried out 4-D dose evaluation which reflects the movement of normal structures at certain phase of Respiratory Gated Radiotherapy, by using Deformable Image Registration that is well used for Adaptive Radiotherapy. Moreover, the study discussed the need of analysis and established some recommendations, regarding the normal structures's movement and volume change due to Patient's breathing pattern during evaluation of treatment plans. Materials and methods : The subjects were taken from 10 lung cancer patients who received Respiratory Gated Radiotherapy. Using Eclipse(Ver 13.6 Varian, USA), the structures seen in the top phase of CT image was equally set via Propagation or Segmentation Wizard menu, and the structure's movement and volume were analyzed by Center-to Center method. Also, image from each phase and the dose distribution were deformed into top phase CT image, for 4-dimensional dose evaluation, via VELOCITY Program. Also, Using $QUASAR^{TM}$ Phantom(Modus Medical Devices) and $GAFCHROMIC^{TM}$ EBT3 Film(Ashland, USA), verification carried out 4-D dose distribution for 4-D gamma pass rate. Result : The movement of the Inspiration and expiration phase was the most significant in axial direction of right lung, as $0.989{\pm}0.34cm$, and was the least significant in lateral direction of spinal cord, as -0.001 cm. The volume of right lung showed the greatest rate of change as 33.5 %. The maximal and minimal difference in PTV Conformity Index and Homogeneity Index between 3-dimensional dose evaluation and 4-dimensional dose evaluation, was 0.076, 0.021 and 0.011, 0.0 respectfully. The difference of 0.0045~2.76 % was determined in normal structures, using 4-D dose evaluation. 4-D gamma pass rate of every patients passed reference of 95 % gamma pass rate. Conclusion : PTV Conformity Index was more significant in all patients using 4-D dose evaluation, but no significant difference was observed between two dose evaluations for Homogeneity Index. 4-D dose distribution was shown more homogeneous dose compared to 3D dose distribution, by considering the movement from breathing which helps to fill out the PTV margin area. There was difference of 0.004~2.76 % in 4D evaluation of normal structure, and there was significant difference between two evaluation methods in all normal structures, except spinal cord. This study shows that normal structures could be underestimated by 3-D dose evaluation. Therefore, 4-D dose evaluation with Deformable Image Registration will be considered when the dose change is expected in normal structures due to patient's breathing pattern. 4-D dose evaluation with Deformable Image Registration is considered to be a more realistic dose evaluation method by reflecting the movement of normal structures from patient's breathing pattern.

• (The) Research of the performance art and culture
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• no.36
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• pp.441-471
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• 2018

East Coast Gut, Korean shamanism ritual on its east coastal area, is a Gut held in fishing villages alongside Korean east coastal area from Goseong area in Gangwon-Do to Busan area. East Coast Gut is performed in a series mainly by a successor shaman, Korean shaman, who hasn't received any spiritual power from a God, and the implications of this thesis lie in that we look over the learning aspects of Seokchool Kim shaman group among other East Coast Gut successor shaman groups after dividing it into 2 categories, successor shaman and learner shaman and based upon this, we reveal the meaning of the learning aspects of East Coast Gut. For successor shamans, home means the field of education. Since they are little, they chased Gut events performing dance in a series to accumulate onsite experiences. However, in the families of successor shamans that have passed their shaman work down from generation to generation, their descendents didn't inherit shaman work any longer, which changed the way of succession and learning of shaman work. Since 1980's, Gut has been officially acknowledged as a kind of general art embracing songs, dance and music and designated as a cultural asset of the state and each city and province, and at art universities, it was adopted as a required course for its related major, which caused new learner shamans who majored in shamanism to emerge. These learner shamans are taking systematical succession lessons on the performance skills of East Coast Byeolshin Gut at universities, East Coast Byeolshin Gut preservation community, any places where Guts are held and etc.. As changes along time, the successor shamans accepted the learner shamans to pass shaman work down and changes appeared in the notion of towners who accept the performer groups of Gut and Gut itself. Unlike the past, as Gut has been acknowledged as the origin of Korean traditional arts and as the product of compresensive learning on songs, dance and music and it was designated as a national intangible cultural asset, shaman's social status and personal pride and dignity has become very high. As shaman has become positioned as the traditional artist getting both national and international recognition unlike its past image of getting despised, at the site of Gut event or even in the relation with towners, their status and the treatment they get became far different. Even towners, along with shift in shaman groups' generation, take position to acknowledge and accept the addition of new learning elements unlike the past. Even in every town, rather than just insisting on the type or the event purpose of traditional Gut, they think over on the type of festival and the main direction of a variety of Guts with which all of towners can mingle with each other. They are trying to find new meanings in the trend of changing Gut and the adaptation of new generation to this. In our reality of Gut events getting minimalized along with rapid change of times, East Coast Gut is still very actively performed in a series until now compared to Guts in other regions. This is because following the successor shamans who have struggled to preserve the East Coast Gut, the learner shamans are actively inflowing and the series performance groups preserve the origin of Gut and try hard to use Gut as art contents. Besides, the learner shamans systematically organize what they learned on shamanism from the successor shamans and get prepared and try to hand it down to descendents in the closest possible way to preserve its origin. In the future, East Coast Gut will be succeeded by the learner shamans from the last successor shamans to inherit its tradition and develop it to adapt to the times.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• The Korean Journal of Archival Studies
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• no.29
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• pp.175-223
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• 2011

A university is an organization charged with publicity and has accountability to the community for the operating process. Students account for a majority of members in a university. In universities, numerous creatures are pouring out every year and university students are major producers of these records. However, roles and functions of university students producing enormous amount of records as main agents of universities and focused concentration on produced records have not been made yet. It is reality that from the archival point of view, the importance of produced records of which main agents are university students has been relatively underestimated. In this background, this study attempted approach in archival point of view on records produced by university students, main agents. There are various types of records that university students produce such as records produced in the process of research and teaching as well as records produced in the process of various autonomy activities like clubs, students' associations. This study especially focused on university student autonomy activity process and placed emphasis on accountability securing measures on autonomy activity process of university students. To secure accountability of activities, records management should be based. Therefore, as a way to ensure accountability of unversity students autonomy activity, we tried to present records management systematization and records utilization measures. For this, a student body, a university student autonomy organization was analyzed and a student body of Myongji University Humanities Campus was selected as a specific target. First, to identify records management status, activities and organization and functions of the student body, we conducted an interview with the president of the student body. Through this, we analyzed the activities of the university student body and examined the necessity of accountability accordingly. Also, we derived the types and characteristics of records to be produced at each stage by analyzing the organization and functions of the student body of Myongji University. Like this, after deriving the types of production records according to the necessity, organization and functions of accountability and activities of the student body, we analyzed records management status of the present student body. First, to identify the general process status of activities of the student body, we analyzed activity process by stage of the student body of Myongji University. And we analyzed records management method of the student body and responsibility principal and conducted real condition analysis. Through this analysis, we presented the measures to ensure accountability of a university student body in three categories such as systematization of records management process, establishment of records management infrastructure, accountability guarantee measures. This study discussed accountability on society by analyzing activities and functions of a student body, targeting a student body, an autonomy organization of university students. And as a measure to secure accountability of a student body, we proposed a model for records management environment settlement. But in terms that a student body is an organization operated in one year basis, there is a limit that records management environment is hard to settle. This study pointed out this limit and was to provide clues when more active researches were carried out in the field of student records management in the future through presentation of student body records management model. Also, it is expected that the analysis results derived from this research will have significance in terms of school history arrangement and conservation.

• Trans-
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• v.12
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• pp.51-79
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• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.

• 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.