• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Management & Information Systems Review
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• v.35 no.3
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• pp.57-79
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• 2016

It is required to derive various conclusions by identifying the type of power and the relationship between SCMs and presenting practical implications. Thus, we can identify the differential effects of each type of power on SCM performance. We can contribute to develop the practical implications at more sophisticated multi-dimension by comparing results of this study with various SCM theories. Through previous studies, the source of power is largely divided into binding power and non-binding power. Binding power is classified into behavior coercion, binding reward and relationship legitimacy. Non-binding power is classified into work expertise, information superiority and value compliance. Enterprises should fully understand and recognize partners within supply chains including understanding of the source of power, imbalance and results. Thus, we look into types of power and effects on trust and commitment, and identify a causal relationship leading to collaboration and SCM performance. Specific research results are as follows. First, the binding power did not give a significant effect to the trust. However, the binding power gave a positively(+) significant effect to the commitment. Second, non-binding power showed a significant effect on both trust and commitment. As a result of analysis on total effects, it was shown that non-binding power gave indirect effects to collaboration and SCM performance. Third, it was shown that both trust and commitment significantly affected collaboration. From the perspectives of social exchange theory and trading cost theory among inter-organizational relationship theory, it may lead to SCM performance of trust, commitment and collaboration. Moreover, it was found that association of each attribute of power led to the significant result. Fourth, it was shown that trust and collaboration significantly affected SCM performance. However, commitment did not directly affect SCM performance, but it indirectly significantly affected SCM performance through collaboration. Proper use of this power can firmly build partnerships between members of the supply chain and induce the improvement on supply chain performance and satisfaction of members.

• Journal of Bio-Environment Control
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• v.15 no.4
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• pp.306-316
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• 2006

In this study, the effect of the shade level, water flow rate applied to the shades and the temperature of water on the greenhouse cooling was investigated depending on the shade level of 0, 35, 55, 75%, and water flow rate and water temperature by the test on the small wooden frames to find out the low cost cooling method. With increasing of the dry bulb temperature of outside air, the dry bulb temperature in the wooden frames increased. For the frames with the shade and water, inside temperatures of the frames were lower of -0.2$\sim$-1.2$^{\circ}C$ than the temperature of the outside air and higher than the water temperature. For the frames without water, inside temperatures of the frames were higher of 1.7$\sim$4$^{\circ}C$ than the outside and not affected by the shade level very much. The water flow rate and the temperature of the water were not the important factors to decrease the inside temperatures in the frames. The black globe temperature became lower with increasing of shade level. The shade frames with water curtain showed the best cooling effect because of reducing thermal radiation and cooling the plastic film cover. The surface temperatures of the plastic film cover for the water supplied modules became lower with increasing of the shade level. The relative humidity was decreased with the dry bulb temperature in the frame increasing and not affected by the dry bulb temperature of the outside air for the frames with the shade and water.

• Korea Journal of Hospital Management
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• v.12 no.1
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• pp.1-30
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• 2007

The study carried out a survey with employees of hospitals located in Daejeon, Chungnam, and Chungbuk from Sep. 12 to Sep. 30, 2005 in order to derive primary elements that affect the improvement of hospital's competitiveness. The study investigated and analyzed the employees' recognition on the change of competitive environment caused by the change of medical environment. The study also analyzed the elements that affect the hospital's competitiveness and the competitive strategies of the hospitals. The conclusion of this study can be summarized as follows. 1. Summary 1) Most of the employees responded that there is a rival in the competitive environment and the competitive is intense. Especially when the employees are married, live in urban areas, have an education level of university graduate or are managers, they tend to think the competitive is very intense. Also, they said that the competitive is based upon the quality of medical service. They mentioned the element that has the biggest effect on the competitiveness is the element of medical consumer and they recognized that the medical services in university and general hospitals have more competitiveness than the one-department hospitals. 2) It was investigated that the medical technique service has the most effect on the hospital's competitiveness. Also, the external service of medical techniques also has a large effect on the hospital's competitiveness. 3) When they were asked for the factors that affect the patients' decision on selecting a hospital, most of them responded "capability and technique of the medical staffs." Also, they said that "sufficient explanation from doctors" and "special center and clinic" are the factors that have big effects on the patients' decision. 4) In the SWOT analysis, most of them responded that the strength is the hospital's characteristics and the weakness is insufficient and obsolete equipment. They said the opportunity is the demands for professional medical service and the risk is the intense competitive among the hospitals. 5) In the SWOT strategy, they emphasized the strategy that uses the opportunity and the strength and the strategy that uses the opportunity while overcoming the weakness. 6) As for the basic competition strategy, most of them thought of the strategy of professionalizing the medical service most importantly. Next, they focused on the strategy of distinct service and the strategy of lower prime cost. 2. Conclusion 1) Because service competition between hospitals is happening seriously, need competitiveness security through right awareness transfer and satisfaction upgrade about medical consumer. 2) For medical technique service upgrade that equip Hospital's competitiveness but affects most, must solidify the countermeasure because professionalizing the medical service and newest medical technique induction should be achieved first, and compose task force for the external service of medical techniques improvement. 3) To improve SWOT of hospital, opportunity and the strength strategy choice that rescue hospital's characteristics heightening professionalizing the medical service level is fancied. 4) As for the basic competition strategy, will have to try in phase triangular position of hospital which is trusted medical level upgrade and excellent manpower security and finance independence through upgrade. The study was only done with hospitals in Daejeon, Chungnam and Chungbuk. Also, it is a study from the side of suppliers of medical service so there are limitations. However, the significance of the study is to present the basic data for improvement of hospital's competitiveness by examining the importance of medical techniques and external service of medical techniques that are the main effects on the improvement of hospital's competitiveness.

• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.99-128
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• 2008

Nearly all Koreans are insured through National Health Insurance(NHI). While NHI coverage is nearly universal, it is not complete. Coverage is largely limited to minimal level of hospital and physician expenses, and copayments are required in each case. As a result, Korea's public insurance system covers roughly 50% of overall individual health expenditures, and the remaining 50% consists of copayments for basic services, spending on services that are either not covered or poorly covered by the public system. In response to these gaps in the public system, 64% of the Korean population has supplemental private health insurance. Expansion of private health insurance raises negative externality issue. Like public financing schemes in other countries, the Korean system imposes cost-sharing on patients as a strategy for controlling utilization. Because most insurance policies reimburse patients for their out-of-pocket payments, supplemental insurance is likely to negate the impact of the policy, raising both total and public sector health spending. So far, most empirical analysis of supplemental health insurance to date has focused on the US Medigap programme. It is found that those with supplements apparently consume more health care. Two reasons for higher health care consumption by those with supplements suggest themselves. One is the moral hazard effect: by eliminating copayments and deductibles, supplements reduce the marginal price of care and induce additional consumption. The other explanation is that supplements are purchased by those who anticipate high health expenditures - adverse effect. The main issue addressed has been the separation of the moral hazard effect from the adverse selection one. The general conclusion is that the evidence on adverse selection based on observable variables is mixed. This article investigates the extent to which private supplementary insurance affect use of health care services by public health insurance enrollees, using Korean administrative data and private supplements related data collected through all relevant private insurance companies. I applied a multivariate two-part model to analyze the effects of various types of supplements on the likelihood and level of public health insurance spending and estimated marginal effects of supplements. Separate models were estimated for inpatients and outpatients in public insurance spending. The first part of the model estimated the likelihood of positive spending using probit regression, and the second part estimated the log of spending for those with positive spending. Use of a detailed information of individuals' public health insurance from administration data and of private insurance status from insurance companies made it possible to control for health status, the types of supplemental insurance owned by theses individuals, and other factors that explain spending variations across supplemental insurance categories in isolating the effects of supplemental insurance. Data from 2004 to 2006 were used, and this study found that private insurance increased the probability of a physician visit by less than 1 percent and a hospital admission by about 1 percent. However, supplemental insurance was not found to be associated with a bigger health care service utilization. Two-part models of health care utilization and expenditures showed that those without supplemental insurance had higher inpatient and outpatient expenditures than those with supplements, even after controlling for observable differences.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.81-93
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• 2022

Since 2008, China's shipping industry has been in a slump, with shipbuilding orders falling sharply, and high-growth excess capacity has become increasingly apparent, leaving many firms with sharply reduced orders at risk of bankruptcy and shutdown. To ensure the development of the shipbuilding industry and enhance the international competitiveness of the shipbuilding industry, it is necessary to analyze the present situation of the shipbuilding industry and the financial situation of the shipbuilding enterprises. And analyzing the problems faced by enterprises from the perspective of capital structure is very meaningful to the shipbuilders with high capital operation. We are trying to analyze the determinants of capital structure of China's shipbuilding listed companies. 30 listed Chinese shipbuilding and listed companies have been designated as sample companies that can obtain financial statements for 13 consecutive years. They also divided 30 sample companies into shipbuilding, shipbuilding-related manufacturing, and shipbuilding-related transportation. Dependent variable is the debt level of the year, independent variable includes the debt level of the previous year, fixed asset ratio, profitability ratio, depreciation cost ratio and asset size. The regression model of the panel used to analyze determinants is capital structure. The results of the empirical analysis are as follows. First, a fixed-effect model for the entire entity showed that the debt-to-equity ratio and the size of the asset in the previous period had a positive effect on the debt-to-equity ratio in the current period. Second, the impact of the profitability ratio on the debt level in the prior term also supports the capital procurement ranking theory rather than the static counter-conflict theory. Third, it was shown that the ratio of the depreciation of the prior term, which replaces the non-liability tax effect, affects the debt-to-equity ratio in the current period.

• 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.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Distribution Research
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• v.17 no.5
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• pp.59-83
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• 2012

Agriculture is a primary industry that influenced by the weather or meterological factors more than other industry. Global warming and worldwide climate changes, and unusual weather phenomena are fatal in agricultural industry and human life. Therefore, many previous studies have been made to find the relationship between weather and the productivity of agriculture. Meterological factors also influence on the distribution of agricultural product. For example, price of agricultural product is determined in the market, and also influenced by the weather of the market. However, there is only a few study was made to find this link. The objective of this study is to investigate the effects of meterological factors on the distribution of agricultural products, focusing on the distribution of chinese cabbages. Chinese cabbage is a main ingredient of Kimchi, and basic essential vegetable in Korean dinner table. However, the production of chinese cabbages is influenced by weather and very fluctuating so that the variation of its price is so unstable. Therefore, both consumers and farmers do not feel comfortable at the unstable price of chinese cabbages. In this study, we analyze the real transaction data of chinese cabbage in wholesale markets and meterological factors depending on the variety and geography. We collect and analyze data of meterological factors such as temperatures, humidity, cloudiness, rainfall, snowfall, wind speed, insolation, sunshine duration in producing and consuming region of chinese cabbages. The result of this study shows that the meterological factors such as temperature and humidity significantly influence on the volume and price of chinese cabbage transaction in wholesale market. Especially, the weather of consuming region has greater correlation effects on transaction than that of producing region in all types of chinese cabbages. Among the whole agricultural lifecycle of chinese cabbages, 'seeding - harvest - shipment - wholesale', meterological factors such as temperature and rainfall in shipment and wholesale period are significantly correlated with transaction volume and price of crops. Based on the result of correlation analysis, we make a regression analysis to verify the meterological factors' effects on the volume and price of chines cabbage transaction in wholesale market. The results of stepwise regression analysis are shown in