• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.131-145
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• 2010

The framework for making a coordinated decision for large-scale facilities has become an important issue in supply chain(SC) management research. The competitive business environment requires companies to continuously search for the ways to achieve high efficiency and lower operational costs. In the areas of production/distribution planning, many researchers and practitioners have developedand evaluated the deterministic models to coordinate important and interrelated logistic decisions such as capacity management, inventory allocation, and vehicle routing. They initially have investigated the various process of SC separately and later become more interested in such problems encompassing the whole SC system. The accurate quotation of ATP(Available-To-Promise) plays a very important role in enhancing customer satisfaction and fill rate maximization. The complexity for intelligent manufacturing system, which includes all the linkages among procurement, production, and distribution, makes the accurate quotation of ATP be a quite difficult job. In addition to, many researchers assumed ATP model with integer time. However, in industry practices, integer times are very rare and the model developed using integer times is therefore approximating the real system. Various alternative models for an ATP system with time lags have been developed and evaluated. In most cases, these models have assumed that the time lags are integer multiples of a unit time grid. However, integer time lags are very rare in practices, and therefore models developed using integer time lags only approximate real systems. The differences occurring by this approximation frequently result in significant accuracy degradations. To introduce the ATP model with time lags, we first introduce the dynamic production function. Hackman and Leachman's dynamic production function in initiated research directly related to the topic of this paper. They propose a modeling framework for a system with non-integer time lags and show how to apply the framework to a variety of systems including continues time series, manufacturing resource planning and critical path method. Their formulation requires no additional variables or constraints and is capable of representing real world systems more accurately. Previously, to cope with non-integer time lags, they usually model a concerned system either by rounding lags to the nearest integers or by subdividing the time grid to make the lags become integer multiples of the grid. But each approach has a critical weakness: the first approach underestimates, potentially leading to infeasibilities or overestimates lead times, potentially resulting in excessive work-inprocesses. The second approach drastically inflates the problem size. We consider an optimized ATP system with non-integer time lag in supply chain management. We focus on a worldwide headquarter, distribution centers, and manufacturing facilities are globally networked. We develop a mixed integer programming(MIP) model for ATP process, which has the definition of required data flow. The illustrative ATP module shows the proposed system is largely affected inSCM. The system we are concerned is composed of a multiple production facility with multiple products, multiple distribution centers and multiple customers. For the system, we consider an ATP scheduling and capacity allocationproblem. In this study, we proposed the model for the ATP system in SCM using the dynamic production function considering the non-integer time lags. The model is developed under the framework suitable for the non-integer lags and, therefore, is more accurate than the models we usually encounter. We developed intelligent ATP System for this model using genetic algorithm. We focus on a capacitated production planning and capacity allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using an evolutionary system to solve it efficiently. This method makes it possible for the population to reach the approximate solution easily. Moreover, we designed and utilized a representation scheme that allows the proposed models to represent real variables. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solutions converge to the optimum quickly.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Korean Journal of Culture and Social Issue
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• v.19 no.2
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• pp.285-318
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• 2013

The purpose of this research is to examine the self-concept in the cyberspace, self-efficacy, relationship with friends, subjective well-being and academic grade among adolescents who are addicted to Internet and those who are not addicted to Internet. A total of 1,057 adolescents (male=545, female=512), 326 from middle school, 361 from high school, and 370 from special education school, participated in the study. The results are as follows. First, qualitative analysis of the conception of self in the cyberspace indicates that those adolescents addicted to Internet reported that in the cyberspace they have fun, followed by they are the same as in real life, they spend time in cyberspace and they can become an imaginary person. Those adolescents not addicted to Internet reported that in the cyberspace they are the same as in real life, followed by they spend time in cyberspace and they can become an imaginary person. When they play Internet games, majority of adolescents in both groups reported that it is fun, followed by they become engrossed and they become aggressive. Second, those adolescents who are not addicted to Internet had higher scores on self-efficacy than those adolescents who are addicted to Internet, including self-regulatory efficacy for learning, relational efficacy, and resiliency of efficacy. Third, the number of friends and close friends that adolescents who are not addicted to Internet were not significantly different from those adolescents who are addicted to Internet. However, those adolescents who are not addicted to Internet were more likely receive social support from friends and were less likely to be social excluded than those adolescents who are addicted to Internet. Fourth, those adolescents who are not addicted to Internet had significantly higher scores on subjective well-being than those adolescents who are addicted to Internet. Fifth, those adolescents who are not addicted to Internet had significantly higher scores on both subjective and objective academic grade than those adolescents who are addicted to Internet.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Journal of Korean Academy of Nursing
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• v.26 no.2
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• pp.387-398
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• 1996

The objective of this study was to clarify whether there are any differences between normal and over-weight middle-aged(40∼59yrs)women in their perceived weight, health status, health conception and health behavior choices. The sample consisted of 39 normal weight and 55 over-weight (11％ above on the Body Index Scale) women who live in Juan, Inchon. The Participants were randomly selected in each weight group considering socio-demographic factors. The findings from this study are summarized below. 1) Among the 55 overweight middle-aged women, 16 were above 20％ on the Body Index Scale and 14 were above 30％. Twenty-five(45.5％) of the overweight group and 12(30.8％) of the normal weight group had one disease, and there were 12(21.8％) in the overweight group and 8(20.5％) in the normal weight group where one of the family members had a disease, but these differences were not statistically significant. The average monthly family income for the overweight group was ￦l,880,000 compared to ￦2,140, 000 for the normal weight group, but this difference was also not significant. The age range for the whole group was between 40 and 59(mean＝46.8 for total, 48.6 for overweight and 45.7 for normal weight group). Again no significant difference found. Occupations were housemaker 53(56.4％), private business(13.8％), salarywoman(9.6％), and teacher (2.1％). Thirty housemaker(54.5％) from the overweight group and 23(59％) from the normal group did not constitute a statistically significant different. For the educational status, 34(61.8％) of the overweight women and 33(84.6％)of the normal weight group finished high school or more educational courses, but there was no significant statistical difference. Eleven(20.0％) of the overweight women and 5(12. 8％) of the normal weight group were single, but again no significant statistical difference was found. 2) A test for difference in health characteristics between two weight groups indicated that two groups do not show statistical differences in their perceived health status, health conception or health behavior choice. That is, the overweight group, also perceive their health status as good as the normal group, and regard ‘Health’ as a state that enables them to carry out social roles and functions rather than as the traditional concept of health as no disease or no symptoms. Moreover. the overweight group selected their health behaviors not for the prevention of diseases or maintenance of health but for promotion of health. To determine if no statistical difference might be related to the overweight group's failure of perceive themselves as overweight, the perceived and objective overweight status were compared by the chi-square analysis, and no difference was found（X/sup²＝49.37, df＝1, p＝.000）. However, 7(17.9％) of the normal group perceived themselves as being overweighted and 7(12.7％) of the overweight group thought they were of normal weight. Even though the overweight group employed in this study perceived themselves as being overweight, they regarded themselves as healthy as those in the normal weight group. It was shown that there was no statistical difference between two groups in health conception, and that they chose health behaviors to promote health status. 3) Perceived health conception was shown to be significantly related to health behavior choice （r＝ .28, p＝.006 for whole group : r＝.33, p＝.014 for overweight group : and r＝.12. p＝.463 for normal group） .There was an indication that the more complicated the perceived health conception was, the more the trend of health behavior choice to promote health. This was especially true for the overweight group. But, the perceived health status did not related to health behavior choice statistically（r＝.13, p＝.202）, and it was thought that reasons for selecting health behaviors were not related to their health status. That is, the overweight group perceive themselves as healthy as the normal weight group or thought that overweight itself does not incur any risk on their health. Data from two groups were combined and analyzed with multiple regression methodology, because the relationship pattern of the two groups was similar. The analysis showed that health behavior has a significant relationship with age and the perceived health conception（r/sup²＝.1517, p=.05, F＝8.133）. It means they come to health behavior along with their health conception and their age rather than their weights, perceived weight, health status or other social characteristics. This study was intended to understand how overweight middle-aged women perceive ‘weight’ and ‘health’, and how they meet their health related needs in comparison with normal weight middle-aged women. Other factors related to the health behavior in overweight middle-aged woman need to be determined through further descriptive studies outlined in the following recommendations. a) Reseach with the study area expanded. b) Reseach with grouping more detailed : much more overweight and underweight group c) Reseach on restricted relationship between overweight and age or profession. d) Reseach on what overweight middle-aged women do to reduce their weight and what factors motivate them to do it

• The Korean Journal of Air & Space Law and Policy
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• v.35 no.2
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• pp.113-136
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• 2020

Worldwide, so-called 'over-booking' of Air Carriers is established in practice. Although not invalid, despite their current contracts, passengers can be refused boarding, which can hinder travel planning. The Korean Supreme Court ruled that an airline carrier who refused to board a passenger due to over-booking was liable for compensation under the "Nonperformance of obligation". But what the court should be thinking about is when the benefit(transport) have been disabled. Thereforeit may be considered that the impossibility of benefit (Transport) due to the rejection of boarding caused by 'Over-booking' may be not the 'subsequent impossibility', but not the 'initialimpossibility '. The legal relationship due to initial impossibility is nullity (imposibilium nulla est obligation). When benefits are initial impossibile, our civil code recognizes liability for damages in accordance with the law of "Culpa in Contrahendo", not "nonperformance of obligation". On this reason, the conclusion that the consumer will be compensated for the loss of boarding due to overbooking by the Air Carrier is the same, but there is a need to review the legal basis for the responsibility from the other side. However, it doesn't matter whether it is non-performance or Culpa in Contrahendo. Rather, the recognition of this compensation is likely to cause confusion due to unstable contractual relationships between both parties. Even for practices permitted by Air Carriers, modifications to current customary overbooking that consumers must accept unconditionally are necessary. At the same time, if Air Carriers continue to be held liable for non-performance of obligations due to overselling tickets, it can be fatal to the airline business environment that requires overbooking for stable profit margins. Therefore, it would be an appropriate measure for both Air Carriers and passengers if the Air Carrier were to be given a clearer obligation to explain (to the consumer) and, at the same time, if the explanation obligation is fulfilled, the Air Carrier would no longer be forced to take responsibility for overbooking.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.101-123
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• 2010

Recently, firms are operating a number of teams to accomplish organizational performance. Especially, ad hoc teams like proposal preparation team are quite different from permanent teams like R&D team in the sense of how the team forms network structure and deals with organizational learning culture and knowledge management participation efforts. Moreover, depending on the team characteristics, individual creativity will differ from each other, which will lead to organizational performance eventually. Previous studies in the field of creativity are lacking in this issue. So main objectives of this study are organized as follows. First, the issue of how to improve individual creativity and organizational performance will be analyzed empirically. This issue will be performed depending on team characteristics such as ad hoc team and permanent team. Antecedents adopted for this research objective are cultural and knowledge factors such as organizational learning culture, and knowledge management participation. Second, the network structure such as degree centrality, and structural hole is used to analyze its influence on individual creativity and organizational performance. SI (System Integration) companies are facing severely tough requirements from clients to submit very creative proposals. Also, R&D teams are widely accepted as relatively creative teams because their responsibilities are focused on suggesting innovative techniques to make their companies remain competitive in the market. SI teams are usually ad hoc, while R&D teams are permanent on an average. By taking advantage of these characteristics of the two kinds of teams, we will prove the validity of the proposed research questions. To obtain the survey data, we accessed 7 SI teams (74 members), and 6 R&D teams (63 members), collecting 137 valid questionnaires. PLS technique was applied to analyze the survey data. Results are as follows. First, in case of SI teams, organizational learning culture affects individual creativity significantly. Meanwhile, knowledge management participation has a significant influence on Individual creativity for the permanent teams. Second, degree centrality Influences individual creativity significantly in case of SI teams. This is comparable with the fact that structural hole has a significant impact on individual creativity for the R&D teams. Practical implications can be summarized as follows: First, network structure of ad hoc team should be designed differently from one of permanent team. Ad hoc team is supposed to show a high creativity in a rather short period, implying that network density among team members should be improved, and those members with high degree centrality should be encouraged to show their Individual creativity and take a leading role by allowing them to get heavily engaged in knowledge sharing and diffusion. In contrast, permanent team should be designed to take advantage of structural hole instead of focusing on network density. Since structural hole can be utilized very effectively in the permanent team, strong arbitrators' merits in the permanent team will increase and therefore helps increase both network efficiency and effectiveness too. In this way, individual creativity in the permanent team is likely to lead to organizational creativity in a seamless way. Second, way of Increasing individual creativity should be sought from the perspective of organizational culture and knowledge management. Organization is supposed to provide a cultural atmosphere in which Innovative idea suggestions and active discussion among team members are encouraged. In this way, trust builds up among team members, facilitating the formation of organizational learning culture. Third, in the ad hoc team, organizational looming culture should be built such a way that individual creativity can grow up fast in a rather short period. Since time is tight, reasonable compensation policy, leader's Initiatives, and learning culture formation should be done In a short period so that mutual trust is built among members quickly, and necessary knowledge and information can be learnt rapidly. Fourth, in the permanent team, it should be kept in mind that the degree of participation in knowledge management determines level of Individual creativity. Therefore, the team ought to facilitate knowledge circulation process such as knowledge creation, storage, sharing, utilization, and learning among team members, which will lead to team performance. In this way, firms must control knowledge networks in permanent team and ad hoc team in a way mentioned above so that individual creativity as well as team performance can be maximized.

• 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.