• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.4 s.54
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• pp.289-293
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• 2005

Nowadays there are many sun protection cosmetics including organic or inorganic UV filter as an active ingredient. Chemically stable inorganic sunsEreen agents, usually metal oxides, we widely employed in high SPF products. Titanium dioxide is one of the most frequently used inorganic UV filters. It has been used as pigments for a long period of cosmetic history. With the development of micronization techniques, it becomes possible to incorporate titanium dioxide in sunscreen formulations without whitening effect and it becomes an important research topic. However, there are very few works related to quantitations of titanium dioxide in sunscreen products. In this research, we analyzed amounts of titanium dioxide in sunscreen cosmetics by adapting redof titration, reduction of Ti(IV) to Ti(III) and reoxidation to Ti(IV). After calcification of other organic ingredients of cosmetics, titanium dioxide is dissolved by hot sulfuric acid. The dissolved Ti(IV) is reduced to the Ti(III) by adding aluminum metals. The reduced Ti(III) is titrated against a standard oxidizing agent, Fe(III) (ammonium iron(III) sulfate), with potassium thiocyanate as an indicator In order to test accuracy and applicability of the proposed method, we analyzed the amounts of titanium dioxide in four types of sunscreen cosmetics, such as cream, make-up base, foundation and powder, after adding known amounts of titanium dioxide $(1{\sim}25w/w%)$. The percent recoveries of the titanium dioxide in four types of formulations were in the range between 96 and 105%. We also analyzed 7 commercial cosmetic products labeled titanium dioxide as an ingredient and compared the results with those of obtained from ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry), one of the most powerful atomic analysis techniques. The results showed that the titrated amounts were well coincided with the analyzed amounts of titanium dioxide by ICP-AES. Although instrumental analytical methods, ICP-MS (Inductively Coupled Plasma-Mass Spectrometry) and ICP-AES, are the best for the analysis of titanium, it is hard to adopt because of their high prices for small cosmetic companies. It was found that the volumetric method presented here gat e quantitative and reliable results with routine lab-wares and chemicals.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.148-169
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• 2023

Hayeob pigment is known as one of the traditional dark green pigments, but the color, raw material, and manufacturing method have not been clearly identified. However, comparing the analysis results of the particle shape and constituent minerals of Hayeob pigments revealed through pigment analysis studies of colored cultural properties such as Dancheong, Gwaebul, and paintings, Hayeob pigments appear to be the same as Dongrok pigments produced by salt corrosion. Therefore, in order to restore Hayeob pigment, the manufacturing method of Dongrok pigment was studied based on the records of old literature. The Dongrok pigment manufacturing method confirmed in the old literature records is a natural corrosion method in which copper powder and a caustic are mixed and then left in a humid condition to corrode. Based on this, artificial corrosion using a corrosion tester was adopted to corrode the copper powder more efficiently, and an appropriate mixing ratio was selected by analyzing the state of corrosion products according to the mixing ratio of the caustic agent. In addition, the manufacturing method of Dongrok pigment was established by adding a salt removal process to remove residual caustic agents and a purification process to increase chroma during pigment coloring. The prepared Dongrok pigments have a bluish green or green color, show an elliptical particle shape and a form in which small particles are aggregated, and a porous surface is observed. The main constituent elements are copper(Cu) and chlorine(Cl), and the main constituent mineral is identified as atacamite [Cu₂Cl(OH)₃]. As a result of an accelerated weathering test to evaluate the stability of the prepared Dongrok pigments, it was found that the greenness partially decreased and the yellowness significantly increased as deterioration progressed. Before deterioration, the Dongrok pigments had lower yellowness compared to the Hayeob pigments of the old Dancheong, but after deterioration, yellowness increased significantly, and it was found to have a similar chromaticity range as Dancheong's Hayeob pigments. As a result, the prepared Dongrok pigments were confirmed to be similar to Dancheong's Hayeob pigments in terms of color as well as particle shape and constituent minerals.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.201-214
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• 2022

This study theoretically and empirically examined whether organizational communication mediates the effect of organizational learning culture perceived by members in the organization on task performance and contextual performance. Organizational learning culture is defined as a culture that is good at creating, acquiring, transferring, and modifying behavior to reflect new knowledge and insights. The hypothesis of this study is that the perceived organizational learning culture can increase performance through organizational communication between members. In particular, we measured communication within the organization into three types: upward, horizontal, and downward. These communications were set as mediating variables. In empirical studies, independent variables were perceived organizational learning culture, mediation variables were upward, horizontal and downward communication, and dependent variables were task performance and contextual performance. Hypothesis 1 is that the organizational learning culture will have a positive effect on employees' tasks and contextual performance. Hypothesis 2 is about the mediating effect of communication on the relationship between Hypothesis 1. In the empirical study, after verifying the validity and reliability of the research variables, correlation analysis and hypothesis verification were conducted. Hypothesis 1 was verified through regression analysis, and all detailed hypotheses were supported. To verify Hypothesis 2, we conducted a bootstrap test using process macro to separate the total, direct, and indirect effects and examine the significance of the indirect effects. As a result, Hypothesis 2 was partially supported. Downward communication mediated organizational learning culture and task and contextual performance, and horizontal communication mediated organizational learning culture and contextual performance. The mediating effect of upward communication was not significant. The results of this study contributed to the suggestion of implications, research limitations, and research directions. Organizational learning culture is the direction and intention of the organization to achieve its goals through the learning and growth of its members. By strengthening internal motivation, organizational members can take voluntary desirable actions that help groups and organizations as well as essential tasks given. since this relationship appears as a medium of downward communication, organizations can strengthen the relationship between organizational learning culture and performance through leadership education.

• Information Systems Review
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• v.20 no.4
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• pp.1-23
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• 2018

A smart phone has been widely spread around world and makes people enjoy online shopping in any time and any place. Recently it also changes the distribution environment. O2O (Online-to-Offline) service becomes new normal due to its convenience of ease shopping of product and services. O2O service market shows steady and steep growth, It is reported that, however, 80% of the businesses has been discontinued within the first year because of unstable business models, customer dissatisfaction and distrust of service. Therefore, it is very important research issue to find out influential factors promoting continuous usage intention of O2O service. Previous study shows that it only considers online characteristics and lack of analysis about offline characteristics and social impact factors. The purpose of this paper is to find out continuous usage intention factors of O2O services by literature review, case analysis, and empirical test. A comprehensive research model and related hypothesis are developed and tested by using a structural equation, Survey was carried out among users who have used O2O service including payment service for at least once. Finally 611 samples are selected out of total 813 surveys. The result shows that the model is theoretically proved and 12 out of 17 hypotheses are accepted. The contribution of this paper is that it provides a new theoretical research model about continuous usage intention factors as well as practical guidelines about promoting continuous usage and growth strategies of O2O service.

• Magazine of the Korean Society of Agricultural Engineers
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• v.16 no.1
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• pp.3225-3262
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• 1974

The purposes of this thesis are to clarify experimentally the variation of ground water temperature in tube wells during the irrigation period of paddy rice, and the effect of ground water irrigation on the growth, grain yield and yield components of the rice plant, and, furthermore, when and why the plant is most liable to be damaged by ground water, and also to find out the effective ground water irrigation methods. The results obtained in this experiment are as follows; 1. The temperature of ground water in tube wells varies according to the location, year, and the depth of the well. The average temperatures of ground water in a tubewells, 6.3m, 8.0m deep are $14.5^{\circ}C$ and $13.1^{\circ}C$, respercively, during the irrigation period of paddy rice (From the middle of June to the end of September). In the former the temperature rises continuously from $12.3^{\circ}C$ to 16.4$^{\circ}C$ and in the latter from $12.4^{\circ}C$ to $13.8^{\circ}C$ during the same period. These temperatures are approximately the same value as the estimated temperatures. The temperature difference between the ground water and the surface water is approximately $11^{\circ}C$. 2. The results obtained from the analysis of the water quality of the "Seoho" reservoir and that of water from the tube well show that the pH values of the ground water and the surface water are 6.35 and 6.00, respectively, and inorganic components such as N, PO4, Na, Cl, SiO2 and Ca are contained more in the ground water than in the surface water while K, SO4, Fe and Mg are contained less in the ground water. 3. The response of growth, yield and yield components of paddy rice to ground water irrigation are as follows; (l) Using ground water irrigation during the watered rice nursery period(seeding date: 30 April, 1970), the chracteristics of a young rice plant, such as plant height, number of leaves, and number of tillers are inferior to those of young rice plants irrigated with surface water during the same period. (2) In cases where ground water and surface water are supplied separately by the gravity flow method, it is found that ground water irrigation to the rice plant delays the stage at which there is a maximum increase in the number of tillers by 6 days. (3) At the tillering stage of rice plant just after transplanting, the effect of ground water irrigation on the increase in the number of tillers is better, compared with the method of supplying surface water throughout the whole irrigation period. Conversely, the number of tillers is decreased by ground water irrigation at the reproductive stage. Plant height is extremely restrained by ground water irrigation. (4) Heading date is clearly delayed by the ground water irrigation when it is practised during the growth stages or at the reproductive stage only. (5) The heading date of rice plants is slightly delayed by irrigation with the gravity flow method as compared with the standing water method. (6) The response of yield and of yield components of rice to ground water irrigation are as follows: \circled1 When ground water irrigation is practised during the growth stages and the reproductive stage, the culm length of the rice plant is reduced by 11 percent and 8 percent, respectively, when compared with the surface water irrigation used throughout all the growth stages. \circled2 Panicle length is found to be the longest on the test plot in which ground water irrigation is practised at the tillering stage. A similar tendency as that seen in the culm length is observed on other test plots. \circled3 The number of panicles is found to be the least on the plot in which ground water irrigation is practised by the gravity flow method throughout all the growth stages of the rice plant. No significant difference is found between the other plots. \circled4 The number of spikelets per panicle at the various stages of rice growth at which_ surface or ground water is supplied by gravity flow method are as follows; surface water at all growth stages‥‥‥‥‥ 98.5. Ground water at all growth stages‥‥‥‥‥‥62.2 Ground water at the tillering stage‥‥‥‥‥ 82.6. Ground water at the reproductive stage ‥‥‥‥‥ 74.1. \circled5 Ripening percentage is about 70 percent on the test plot in which ground water irrigation is practised during all the growth stages and at the tillering stage only. However, when ground water irrigation is practised, at the reproductive stage, the ripening percentage is reduced to 50 percent. This means that 20 percent reduction in the ripening percentage by using ground water irrigation at the reproductive stage. \circled6 The weight of 1,000 kernels is found to show a similar tendency as in the case of ripening percentage i. e. the ground water irrigation during all the growth stages and at the reproductive stage results in a decreased weight of the 1,000 kernels. \circled7 The yield of brown rice from the various treatments are as follows; Gravity flow; Surface water at all growth stages‥‥‥‥‥‥514kg/10a. Ground water at all growth stages‥‥‥‥‥‥428kg/10a. Ground water at the reproductive stage‥‥‥‥‥‥430kg/10a. Standing water; Surface water at all growh stages‥‥‥‥‥‥556kg/10a. Ground water at all growth stages‥‥‥‥‥‥441kg/10a. Ground water at the reproductive stage‥‥‥‥‥‥450kg/10a. The above figures show that ground water irrigation by the gravity flow and by the standing water method during all the growth stages resulted in an 18 percent and a 21 percent decrease in the yield of brown rice, respectively, when compared with surface water irrigation. Also ground water irrigation by gravity flow and by standing water resulted in respective decreases in yield of 16 percent and 19 percent, compared with the surface irrigation method. 4. Results obtained from the experiments on the improvement of ground water irrigation efficiency to paddy rice are as follows; (1) When the standing water irrigation with surface water is practised, the daily average water temperature in a paddy field is 25.2$^{\circ}C$, but, when the gravity flow method is practised with the same irrigation water, the daily average water temperature is 24.5$^{\circ}C$. This means that the former is 0.7$^{\circ}C$ higher than the latter. On the other hand, when ground water is used, the daily water temperatures in a paddy field are respectively 21.$0^{\circ}C$ and 19.3$^{\circ}C$ by practising standing water and the gravity flow method. It can be seen that the former is approximately 1.$0^{\circ}C$ higher than the latter. (2) When the non-water-logged cultivation is practised, the yield of brown rice is 516.3kg/10a, while the yield of brown rice from ground water irrigation plot throughout the whole irrigation period and surface water irrigation plot are 446.3kg/10a and 556.4kg/10a, respectivelely. This means that there is no significant difference in yields between surface water irrigation practice and non-water-logged cultivation, and also means that non-water-logged cultivation results in a 12.6 percent increase in yield compared with the yield from the ground water irrigation plot. (3) The black and white coloring on the inside surface of the water warming ponds has no substantial effect on the temperature of the water. The average daily water temperatures of the various water warming ponds, having different depths, are expressed as Y=aX+b, while the daily average water temperatures at various depths in a water warming pond are expressed as Y=a(b)x (where Y: the daily average water temperature, a,b: constants depending on the type of water warming pond, X; water depth). As the depth of water warning pond is increased, the diurnal difference of the highest and the lowest water temperature is decreased, and also, the time at which the highest water temperature occurs, is delayed. (4) The degree of warming by using a polyethylene tube, 100m in length and 10cm in diameter, is 4~9$^{\circ}C$. Heat exchange rate of a polyethylene tube is 1.5 times higher than that or a water warming channel. The following equation expresses the water warming mechanism of a polyethylene tube where distance from the tube inlet, time in day and several climatic factors are given: {{{{ theta omega (dwt)= { a}_{0 } (1-e- { x} over { PHI v })+ { 2} atop { SUM from { { n}=1} { { a}_{n } } over { SQRT { 1+ {( n omega PHI) }^{2 } } } } LEFT { sin(n omega t+ { b}_{n }+ { tan}^{-1 }n omega PHI )-e- { x} over { PHI v }sin(n omega LEFT ( t- { x} over {v } RIGHT ) + { b}_{n }+ { tan}^{-1 }n omega PHI ) RIGHT } +e- { x} over { PHI v } theta i}}}}{{{{ { theta }_{$\infty$ }(t)= { { alpha theta }_{a }+ { theta }_{ w'} +(S- { B}_{s } ) { U}_{w } } over { beta } , PHI = { { cpDU}_{ omega } } over {4 beta } }}}} where $\theta$$\omega$; discharged water temperature($^{\circ}C$) $\theta$a; air temperature ($^{\circ}C$) $\theta$$\omega$';ponded water temperature($^{\circ}C$) s ; net solar radiation(ly/min) t ; time(tadian) x; tube length(cm) D; diameter(cm) ao,an,bn;constants determined from $\theta$$\omega$(t) varitation. cp; heat capacity of water(cal/$^{\circ}C$ ㎥) U,Ua; overall heat transfer coefficient(cal/$^{\circ}C$ $\textrm{cm}^2$ min-1) $\omega$;1 velocity of water in a polyethylene tube(cm/min) Bs ; heat exchange rate between water and soil(ly/min)

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of Distribution Science
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• v.10 no.3
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• pp.51-61
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• 2012

This study seeks to understand how the choice of a coffee shop is related to a customer's loyalty and which characteristics of a shop influence this choice. It considers large-sized coffee shops brands whose market scale has gradually grown. The users' choice of shop is determined by price, employee service, shop location, and shop atmosphere. The study investigated the effects of these four properties on the brand attitudes of coffee shops. The effects were found to vary depending on users' characteristics. The properties with the largest influence were shop atmosphere and shop location Therefore, the purpose of the study was to examine the properties that could help coffee shops get loyal customers, and the choice properties that could satisfy consumers' desires The study examined consumers' perceptions of shop properties at selection of coffee shop and the difference between perceptual difference and coffee brand in order to investigate customers' desires and needs and to suggest ways that could supply products and service. The research methodology consisted of two parts: normative and empirical research, which includes empirical analysis and statistical analysis. In this study, a statistical analysis of the empirical research was carried out. The study theoretically confirmed the shop choice properties by reviewing previous studies and performed an empirical analysis including cross tabulation based on secondary material. The findings were as follows: First, coffee shop choice properties varied by gender. Price advantage influenced the choice of both men and women; men preferred nearer coffee shops where they could buy coffee easily and more conveniently than women did. The atmosphere of the coffee shop had the greatest influence on both men and women, and shop atmosphere was thought to be the most important for age analysis. In the past, customers selected coffee shops solely to drink coffee. Now, they select the coffee shop according to its interior, menu variety, and atmosphere owing to improved quality and service of coffee shop brands. Second, the prices of the brands did not vary much because the coffee shops were similarly priced. The service was thought to be more important and to elevate service quality so that price and employee service and other properties did not have a great influence on shop choice. However, those working in the farming, forestry, fishery, and livestock industries were more concerned with the price than the shop atmosphere. College and graduate school students were also affected by inexpensive price. Third, shop choice properties varied depending on income. The shop location and shop atmosphere had a greater influence on shop choice. The customers in an income bracket of less than 2 million won selected low-price coffee shops more than those earning 6 million won or more. Therefore, price advantage had no relation with difference in income. The higher income group was not affected by employee service. Fourth, shop choice properties varied depending on place. For instance, customers at Ulsan were the most affected by the price, and the ones at Busan were the least affected. The shop location had the greatest influence among all of the properties. Among the places surveyed, Gwangju had the least influence. The alternate use of space in a coffee shop was thought to be important in all the cities under consideration. The customers at Ulsan were not affected by employee service, and they selected coffee shops according to quality and preference of shop atmosphere. Lastly, the price factor was found to be a little higher than other factors when customers frequently selected brands according to shop properties. Customers at Gwangju reacted to discounts more than those in other cities did, and the former gave less priority to the quality and taste of coffee. Brand preference varied depending on coffee shop location. Customers at Busan selected brands according to the coffee shop location, and those at Ulsan were not influenced by employee kindness and specialty. The implications of this study are that franchise coffee shop businesses should focus on customers rather than aggressive marketing strategies that increase the number of coffee shops. Thus, they should create an environment with a good atmosphere and set up coffee shops in places that customers have good access to. This study has some limitations. First, the respondents were concentrated in metropolitan areas. Secondary data showed that the number of respondents at Seoul was much more than that at Gyeonggi-do. Furthermore, the number of respondents at Gyeonggi-do was much more than those at the six major cities in the nation. Thus, the regional sample was not representative enough of the population. Second, respondents' ratio was used as a measurement scale to test the perception of shop choice properties and brand preference. The difficulties arose when examining the relation between these properties and brand preference, as well as when understanding the difference between groups. Therefore, future research should seek to address some of the shortcomings of this study: If the coffee shops are being expanded to local areas, then a questionnaire survey of consumers at small cities in local areas shall be conducted to collect primary material. In particular, variables of the questionnaire survey shall be measured using Likert scales in order to include perception on shop choice properties, brand preference, and repurchase. Therefore, correlation analysis, multi-regression, and ANOVA shall be used for empirical analysis and to investigate consumers' attitudes and behavior in detail.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.