• Journal of Applied Tourism Food and Beverage Management and Research
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• v.8
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• pp.89-121
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• 1997

Many of the measures and policies advocated by supply-siders, such as lower taxation, less government intervention, more freedom from restrictive legislation and regulation, and the need for increased productivity can be found in writing the classical economist. Nor is supply-side economics a complete divorcement from Keynesian analysis. In both camps the objectives are the same-high level employment, stable prices and healthy economic growth, the means or suggestions for attaining the objectives, however, differ. Consequently, recommended economic policies and measures are different. keynesians rely primarily on the manipulation of effective demand to increase output and employment and to combat inflation. They assume ample resources to be available in order that supply will respond to demand. The supply-siders emphasize the need to increase savings, investment, productivity and output as a means of increasing income. Supply-siders assume that the increase in income will lead to an increase in effective demand. Keynesians suggest that savings, particularly those not invested, dampen economic activity. Supply-siders hold that savings, or at least an increase in after-tax income, stimulates work effort and provides funds for investment. Perhaps keynesians are guilty of assuming that most savings are not going to be invested, whereas supply-siders may erroneously assume that almost all savings will flow into investment and/ or stimulate work effort. In reality, a middle ground is possible. The supply-siders stress the need to increase supply, but Keynes did not preclude the possibility of increasing economic activity by working through the supply side. According to Keynes' aggregate demand-aggregate supply framework, a decrease in supply will increase output and employment. It must be remembered, however, that Keynes' aggregate supply is really a price. Lowering the price or cost of supply would there by result in higher profit and/ or higher output. This coincides with the viewpoint of supply-siders who want to lower the cost of production via various means for the purpose of increasing supply. Then, too, some of the means, such as tax cuts, tax credits and accelerated depreciation, recommended by suply-siders to increase productivity and output would be favored by Keynesians also as a means of increasing investment, curbing costs, and increasing effective demand. In fact, these very measures were used in the early 1960s in the United State during the years when nagging unemployment was plaguing the economy. Keynesians disagree with the supply-siders' proposals to reduce transfer payments and slow down the process of income redistribution, except in full employment inflationary periods. Keynesians likewise disagree with tax measures that favored business as opposed to individuals and the notion of shifting the base of personal taxation away from income and toward spending. A frequent criticism levied at supply-side economics is that it lacks adequate models and thus far has not been quantified to any great extent. But, it should be remembered that Keynesian economics originally was lacking in models and based on a number of unproved assumptions, such as, the stability of the consumption function with its declining marginal propensity to consume. Just as the economic catastrophe of the great depression of the 1930s paved the way for the application of Keynesian or demand-side policies, perhaps the frustrating and restless conditions of the 1970s and 1980s is an open invitation for the application of supply-side policies. If so, the 1980s and 1990s may prove to be the testing era for the supply-side theories. By the end of 1990s we should have better supply-side models and know much more about the effectiveness of supply-side policies. By that time, also, supply-side thinking may be more crystallized and we will learn whether it is something temporary that will fade away, be widely accepted as the new economics replacing Keynesian demand analysis, or something to be continued but melded or fused with demand management.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.1-40
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• 2007

We test a model of investment-cashflow-growth opportunities relationship in order to estimate the sensitivities to investments. In this study, we use a new proxy variable for the value of growth opportunities(hereafter "VGO"), which is based on the seminal papers of M&M(1958:1961:1963) and Lee(2006;2007). The empirical findings on the sensitivities of cashflow and growth opportunities are as follows. First, when the traditional proxy variables for the growth opportunities such as Tobin's Q, MBR and sales growth are included with the new proxy VGO in the estimation, their coefficients are turned out to be insignificant. Second, only the new proxy variable VGO shows a statistically significant positive sensitibity to investment, which can be regarded that the growth opportunities hold the positive influences to investments. Third, the Tobin's Q can be decomposed into three factors such as the value of growth opportunities(VGO), the value of asset-in-place and valuation errors. It turns out that only the VGO shows a statistically significant positive relationship with investment among others. This means that the new variable VGO is a good proxy variable for the growth opportunities in the investment-cashflow sensitivity analysis. In sum, thanks to the above findings in this study, we can say that it will not be proper to choose a proxy variable for the growth opportunities from the traditional set of proxies such as Tobin's Q, MBR, or sales growth rate.

• The Korean Journal of Elementary Counseling
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• v.8 no.1
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• pp.33-50
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• 2009

The purpose of this study was to develop a PBL-based career education program and to examine its effectiveness on school children's career maturity. It's specifically meant to prepare a career education program to assist students to get an accurate grip on their aptitude, interest and personality and explore various sorts of occupations in the course of solving authentic and contextual career-related problems. After children's developmental characteristics and needs were analyzed, task analysis was implemented, and the objectives were defined. And then the core of the program, PBL problems were developed, and the validity of the problems were verified Evaluation plans and tools were prepared to assess children's problem-solving process and presentation, and an online learning space was designed. The program that consisted of 10-minute 21 sessions was provided to fifth-grade elementary schoolers for eight weeks. The findings of the study were as follows: The experimental group that participated in the PBL-based career education program showed a more significant improvement than the control group that didn't in career attitude and three career attitude subfactors involving planness, disposition and compromise. And the former made a more significant progress than the latter in career ability and its subfactors including vocational comprehension, self-understanding and decision-making skills as well. As a result of making a content analysis to make up for the survey, the students reported that they were able to get an objective understanding of themselves and acquire diverse and profound knowledge on work and the business world in the middle of solving the given PBL problems related to different areas in group and giving a presentation. In conclusion, a PBL based career education program developed by this researcher encouraged the students to have an objective self-understanding, to have a dynamic interactive discussion with their group members. Therefore the program had a positive impact on boosting the career attitude and career ability of the elementary schoolers. The findings suggested that in the field of elementary career education, autonomous learning attitude and subjecthood are the crucial factors to stimulate school children to explore and create their own future.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.51-67
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• 2009

Developing an agile recommender system for nomadic users has been regarded as a promising application in mobile and ubiquitous settings. To increase the quality of personalized recommendation in terms of accuracy and elapsed time, estimating future context of the user in a correct way is highly crucial. Traditionally, time series analysis and Makovian process have been adopted for such forecasting. However, these methods are not adequate in predicting context data, only because most of context data are represented as nominal scale. To resolve these limitations, the alignment-prediction algorithm has been suggested for context prediction, especially for future context from the low-level context. Recently, an ontological approach has been proposed for guided context prediction without context history. However, due to variety of context information, acquiring sufficient context prediction knowledge a priori is not easy in most of service domains. Hence, the purpose of this paper is to propose a novel context prediction methodology, which does not require a priori knowledge, and to increase accuracy and decrease elapsed time for service response. To do so, we have newly developed pattern-based context prediction approach. First of ail, a set of individual rules is derived from each context attribute using context history. Then a pattern consisted of results from reasoning individual rules, is developed for pattern learning. If at least one context property matches, say R, then regard the pattern as right. If the pattern is new, add right pattern, set the value of mismatched properties = 0, freq = 1 and w(R, 1). Otherwise, increase the frequency of the matched right pattern by 1 and then set w(R,freq). After finishing training, if the frequency is greater than a threshold value, then save the right pattern in knowledge base. On the other hand, if at least one context property matches, say W, then regard the pattern as wrong. If the pattern is new, modify the result into wrong answer, add right pattern, and set frequency to 1 and w(W, 1). Or, increase the matched wrong pattern's frequency by 1 and then set w(W, freq). After finishing training, if the frequency value is greater than a threshold level, then save the wrong pattern on the knowledge basis. Then, context prediction is performed with combinatorial rules as follows: first, identify current context. Second, find matched patterns from right patterns. If there is no pattern matched, then find a matching pattern from wrong patterns. If a matching pattern is not found, then choose one context property whose predictability is higher than that of any other properties. To show the feasibility of the methodology proposed in this paper, we collected actual context history from the travelers who had visited the largest amusement park in Korea. As a result, 400 context records were collected in 2009. Then we randomly selected 70% of the records as training data. The rest were selected as testing data. To examine the performance of the methodology, prediction accuracy and elapsed time were chosen as measures. We compared the performance with case-based reasoning and voting methods. Through a simulation test, we conclude that our methodology is clearly better than CBR and voting methods in terms of accuracy and elapsed time. This shows that the methodology is relatively valid and scalable. As a second round of the experiment, we compared a full model to a partial model. A full model indicates that right and wrong patterns are used for reasoning the future context. On the other hand, a partial model means that the reasoning is performed only with right patterns, which is generally adopted in the legacy alignment-prediction method. It turned out that a full model is better than a partial model in terms of the accuracy while partial model is better when considering elapsed time. As a last experiment, we took into our consideration potential privacy problems that might arise among the users. To mediate such concern, we excluded such context properties as date of tour and user profiles such as gender and age. The outcome shows that preserving privacy is endurable. Contributions of this paper are as follows: First, academically, we have improved sequential matching methods to predict accuracy and service time by considering individual rules of each context property and learning from wrong patterns. Second, the proposed method is found to be quite effective for privacy preserving applications, which are frequently required by B2C context-aware services; the privacy preserving system applying the proposed method successfully can also decrease elapsed time. Hence, the method is very practical in establishing privacy preserving context-aware services. Our future research issues taking into account some limitations in this paper can be summarized as follows. First, user acceptance or usability will be tested with actual users in order to prove the value of the prototype system. Second, we will apply the proposed method to more general application domains as this paper focused on tourism in amusement park.

• Journal of Bio-Environment Control
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• v.16 no.4
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• pp.314-321
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• 2007

This study was conducted to select leaf vegetables suitable for cultivation in apartment verandas and simple and easy fertigation method for home gardening. In order to develop the convenient fertigation method, hydroponics, wick irrigation, and overhead irrigation methods were compared. For the wick irrigation, two types of nutrient sources were used; one was slow release fertilizers mixed with medium and the other one was nutrient solution filled in container located under pots. The growth of leafy lettuce, leaf mustard, and leaf beet was better in both of the wick irrigation methods rather than in overhead irrigation and hydroponics. The wick irrigation method is very easy, so that it is expected to bring a good result from the cultivating and managing point of view, if it brings with commercialized system along with slow release fertilizer. As a result of investigation of environment such as temperature, relative humidity, and irradiance level in apartment verandas in autumn the highest irradiance level during a day was just 48% and 35% in verandas facing south and feeing southeast, respectively, comparing to that in greenhouse. The light environment was investigated as a limiting factor for vegetable growing in verandas. Therefore, to select the vegetables showing good growth under low irradiance environment, nine leaf vegetables such as romaine lettuce, lent lettuce, head lettuce, endive, pak-choi, leaf mustard, garland chrysanthemum, leaf beet, and Chinese chive were grown under 0%, 50%, 70%, 90% shading. Among them, Chinese chive showed the best growth under low irradiance levels. Endive showed line growth reduction according to shading degree, however, even under 90% shading condition, it showed good growth. And then leafy lettuce, garland chrysanthemum, and pak-choi followed. Therefore, these results will be of help in selecting vegetables for veranda gardening with different light levels.

• Information Systems Review
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• v.14 no.3
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• pp.25-51
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• 2012

The purpose of this study is to analyze the key factors affecting satisfaction of the visually impaired SNS users so that they may use SNS more effectively in the future. This study has used three factors such as the information factor, the relationship factor and the speed factor and the usability as independent variables. The social presence factor was used as a parameter and the SNS user satisfaction as a dependent variable. For the research, 195 visually impaired SNS users have participated in this survey. The major findings of this study are that the relationship factor has strong effects on the self-identification factor, the social presence factor and the SNS usage satisfaction among the factors affecting the visually impaired users to be satisfied with SNS. On the other hand, the information factor and usage factor have no effects on the self-identification factor and the social presence factor. However, they have effects on the SNS usage satisfaction. Additionally, the self-identification factor has no effect on the SNS usage satisfaction, but the social presence factor has effect. Based on the above study results, this paper proposed for the government to enhance the educational program on the use of SNS for the visually impaired and to increase its financial and political support on this subject. Additionally, technical supports on SNS service accessibility and usage by the government are vital for the visually impaired. Academically, this study provides a concrete groundwork for the research on the use of SNS by the visually impaired by providing a solid research direction for further study on this subject. Socially, this study helps the visually impaired use SNS more effectively by increasing the general public awareness of the importance of SNS usages by the visually impaired so that the information gap of the society may be diminished in the future.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.115-137
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• 2010

Information technology (IT) outsourcing, the use of a third-party vendor to provide IT services, started in the late 1980s and early 1990s in Korea, and has increased rapidly since 2000. Recently, firms have increased their efforts to capture greater value from IT outsourcing. To date, there have been a large number of studies on IT outsourcing. Most prior studies on IT outsourcing have focused on outsourcing practices and decisions, and little attention has been paid to objectively measuring the value of IT outsourcing. In addition, studies that examined the performance of IT outsourcing have mainly relied on anecdotal evidence or practitioners' perceptions. Our study examines the contribution of IT outsourcing to economic growth in Korean industries over the 1990 to 2007 period, using a production function framework and a panel data set for 54 industries constructed from input-output tables, fixed-capital formation tables, and employment tables. Based on the framework and estimation procedures that Han, Kauffman and Nault (2010) used to examine the economic impact of IT outsourcing in U.S. industries, we evaluate the impact of IT outsourcing on output and productivity in Korean industries. Because IT outsourcing started to grow at a significantly more rapid pace in 2000, we compare the impact of IT outsourcing in pre- and post-2000 periods. Our industry-level panel data cover a large proportion of Korean economy-54 out of 58 Korean industries. This allows us greater opportunity to assess the impacts of IT outsourcing on objective performance measures, such as output and productivity. Using IT outsourcing and IT capital as our primary independent variables, we employ an extended Cobb-Douglas production function in which both variables are treated as factor inputs. We also derive and estimate a labor productivity equation to assess the impact of our IT variables on labor productivity. We use data from seven years (1990, 1993, 2000, 2003, 2005, 2006, and 2007) for which both input-output tables and fixed-capital formation tables are available. Combining the input-output tables and fixed-capital formation tables resulted in 54 industries. IT outsourcing is measured as the value of computer-related services purchased by each industry in a given year. All the variables have been converted to 2000 Korean Won using GDP deflators. To calculate labor hours, we use the average work hours for each sector provided by the OECD. To effectively control for heteroskedasticity and autocorrelation present in our dataset, we use the feasible generalized least squares (FGLS) procedures. Because the AR1 process may be industry-specific (i.e., panel-specific), we consider both common AR1 and panel-specific AR1 (PSAR1) processes in our estimations. We also include year dummies to control for year-specific effects common across industries, and sector dummies (as defined in the GDP deflator) to control for time-invariant sector-specific effects. Based on the full sample of 378 observations, we find that a 1% increase in IT outsourcing is associated with a 0.012~0.014% increase in gross output and a 1% increase in IT capital is associated with a 0.024~0.027% increase in gross output. To compare the contribution of IT outsourcing relative to that of IT capital, we examined gross marginal product (GMP). The average GMP of IT outsourcing was 6.423, which is substantially greater than that of IT capital at 2.093. This indicates that on average if an industry invests KRW 1 millon, it can increase its output by KRW 6.4 million. In terms of the contribution to labor productivity, we find that a 1% increase in IT outsourcing is associated with a 0.009~0.01% increase in labor productivity while a 1% increase in IT capital is associated with a 0.024~0.025% increase in labor productivity. Overall, our results indicate that IT outsourcing has made positive and economically meaningful contributions to output and productivity in Korean industries over the 1990 to 2007 period. The average GMP of IT outsourcing we report about Korean industries is 1.44 times greater than that in U.S. industries reported in Han et al. (2010). Further, we find that the contribution of IT outsourcing has been significantly greater in the 2000~2007 period during which the growth of IT outsourcing accelerated. Our study provides implication for policymakers and managers. First, our results suggest that Korean industries can capture further benefits by increasing investments in IT outsourcing. Second, our analyses and results provide a basis for managers to assess the impact of investments in IT outsourcing and IT capital in an objective and quantitative manner. Building on our study, future research should examine the impact of IT outsourcing at a more detailed industry level and the firm level.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.113-145
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• 2009

Recently, due to the globalization of the IT(Information Technology) market, devices and systems designed in one country are used in other countries as well. This phenomenon is becoming the key factor for increased interest on cross-cultural, or cross-national, research within the IT area. However, as the IT market is becoming bigger and more globalized, a great number of IT practitioners are having difficulty in designing and developing devices or systems which can provide optimal experience. This is because not only tangible factors such as language and a country's economic or industrial power affect the user experience of a certain device or system but also invisible and intangible factors as well. Among such invisible and intangible factors, the cultural characteristics of users from different countries may affect the user experience of certain devices or systems because cultural characteristics affect how they understand and interpret the devices or systems. In other words, when users evaluate the quality of overall user experience, the cultural characteristics of each user act as a perceptual lens that leads the user to focus on a certain elements of experience. Therefore, there is a need within the IT field to consider cultural characteristics when designing or developing certain devices or systems and plan a strategy for localization. In such an environment, existing IS studies identify the culture with the country, emphasize the importance of culture in a national level perspective, and hypothesize that users within the same country have same cultural characteristics. Under such assumptions, these studies focus on the moderating effects of cultural characteristics on a national level within a certain theoretical framework. This has already been suggested by cross-cultural studies conducted by scholars such as Hofstede(1980) in providing numerical research results and measurement items for cultural characteristics and using such results or items as they increase the efficiency of studies. However, such national level culture has its limitations in forecasting and explaining individual-level behaviors such as voluntary device or system usage. This is because individual cultural characteristics are the outcome of not only the national culture but also the culture of a race, company, local area, family, and other groups that are formulated through interaction within the group. Therefore, national or nationally dominant cultural characteristics may have its limitations in forecasting and explaining the cultural characteristics of an individual. Moreover, past studies in psychology suggest a possibility that there exist different cultural characteristics within a single individual depending on the subject being measured or its context. For example, in relation to individual vs. collective characteristics, which is one of the major cultural characteristics, an individual may show collectivistic characteristics when he or she is with family or friends but show individualistic characteristics in his or her workplace. Therefore, this study acknowledged such limitations of past studies and conducted a research within the framework of 'theoretically integrated model of user satisfaction and emotional attachment', which was developed through a former study, on how the effects of different experience elements on emotional attachment or user satisfaction are differentiated depending on the individual cultural characteristics related to a system or device usage. In order to do this, this study hypothesized the moderating effects of four cultural dimensions (uncertainty avoidance, individualism vs, collectivism, masculinity vs. femininity, and power distance) as suggested by Hofstede(1980) within the theoretically integrated model of emotional attachment and user satisfaction. Statistical tests were then implemented on these moderating effects through conducting surveys with users of four digital devices (mobile phone, MP3 player, LCD TV, and refrigerator) in three countries (US, Germany, and Russia). In order to explain and forecast the behavior of personal device or system users, individual cultural characteristics must be measured, and depending on the target device or system, measurements must be measured independently. Through this suggestion, this study hopes to provide new and useful perspectives for future IS research.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.