• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.327-341
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• 2021

The knowledge management was considered as the inevitable result of the rule of knowledge in this era, and its importance became clear in being the main source for achieving success, the need to consider and manage knowledge as an independent field that must be addressed with a clear scientific methodology has become intangible - they are very valuable and a strategic asset. On the other hand, the innovation process relates to all parts of the organization, and helps to improve the behavioral patterns of individuals and their attitudes towards adopting modern and innovative ideas, it is a purposeful process adopted by the senior management and works to provide the capabilities and requirements for embodying the innovative behavior in it. In the field of dealing with the market, it is a product of the organization's innovative approach, which aims at advancement, change, and intended and organized renewal. The main objective of this article is to determine the most appropriate ways to integrate knowledge management mechanisms to employ innovation factors within universities based on the role of universities in supporting innovation. This was achieved through reviewing many relevant research and listing the most prominent concepts of knowledge management, its importance, objectives, and processes determining the stages of knowledge management application, the requirements for applying knowledge management, and the obstacles that impede its application; Then the statement "Innovation in universities, through which it addressed the concept of innovation, its importance, stages, and requirements for its application, as well as identifying the most prominent models of innovation, and obstacles to innovation, in addition to that the role of universities in supporting innovation will be identified. From the surveyed study done in this article, we concluded that the relationship among organizational culture, knowledge management and innovation capability can provide useful insights for managers regarding developing a strong culture, promote knowledge management practices effectively and eventually enhance the whole organization's innovation capability. Also, we found that different components of Knowledge Management as Knowledge activities, Knowledge types, transformation of knowledge and technology have a significant positive effect in bringing innovation through transformation of knowledge into knowledge assets in universities.

• Journal of Distribution Science
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• v.10 no.2
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• pp.7-17
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• 2012

The aim of this study is to empirically explore micro and macroeconomic factors affecting the Pakistani sugar industries and searching the energy potential of this industry, through the survey of literature. The empirical part has been explored by employing Vector Autoregression (VAR), Granger Causality tests and simultaneous equation models through quarterly data for the period of 1991q2-2008q4. The study also aims to devise policies for the development of sugar industries and identify its growing importance for the energy sector of Pakistan. Empirical tests applied on the domestic prices of sugar, domestic interest rates, and exchange rate, productive capacities of sugar mills, per capita income, world sugar prices on cultivable area and sugar production reveal very useful results. Results reveal an improvement of productive capacity of the sugar mills of Pakistan on account of increasing crushing capacity of this sector. Negative effect of rising wholesale prices on the harvesting area was also observed. Profit earnings of the sugar mills significantly increase with the rise of sugar prices but the system does not exist for the farming community to share the rising prices of sugar. The models indicate positive and significant effect of local prices of sugar on its volume of import. Another of the findings of this study positively relates the local sugar markets with the international prices of sugar. Additionally, the causality tests results reveal exchange rate, harvesting area and overall output of sugarcane to have significant effects on the local prices of sugar. Similarly, import of sugar, interest rate, per capita consumption of sugar, per capita national income and the international prices of sugar also significantly affect currency exchange rate of Pakistani rupee in terms of US$. The study also finds sugar as an essential and basic necessity of the Pakistani consumers. That is why there are no significant income and price effects on the per capita consumption of sugar in Pakistan. All the empirical methods reiterate the relationship of variables. Economic policy makers are recommended to improve governance and management in the production, stock taking, internal and external trading and distribution of sugar in Pakistan using bumper crop policies. Macroeconomic variables such as interest rate, exchange rate per capita income and consumption are closely connected with the production and distribution of sugar in Pakistan. The cartelized role of the sugar industries should also be examined by further studies. There is need to further explore sugar sector of Pakistan with the perspective of energy generation through this sector; cartelized sugar markets in Pakistan and many more other dimensions of this sector. Exact appraisal of sugar industries for energy generation can be done appropriately by the experts from applied sciences.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.141-152
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• 2018

Although the 1997 Raw Data of the National Wealth Statistical Survey (South Korea) is timely 20-year-old data, it is meaningful as a benchmarking in the capital stock estimations of Korea, which is estimated by PIM (permanent inventory method). In the case of machinery/equipment, it is the data that can analyze in depth the changes in the industrial structure of Korea. In the case of ASL (average service life) which has economic concept, since the change of ASL is not so large, ASL yielded by the Raw Data of the 1997 National Wealth Statistical Survey is meaningful as reference value for the ASL estimated by the Bank of Korea and the National Statistical Office. As you know Japan has changed its service life due to changes in its industrial structure. However, many of its assets are still used for the years indicated in Showa (before 1989). The same trend with other countries such as Japan. However, the United States is constantly devoted to assessing the useful ASL and value of assets by distinguishing between the Hulten-Wykoff models and those not. Korea has also benchmarked the useful ASL of the United States and Japan when it conducted its own survey every 10 years by due diligence until 1997. In this study, the 'constraint' Iowa curve estimation by the Raw Data of the 1997 National Wealth Statistical Survey is based on the age records of the assets and the maximum age of the assets appropriately derived. And then we made modified Iowa curve by smoothing. From this modified one, we suggested ASL by asset. After 1997, the vintage disposal data directly were collected by the National Statistical Office with Oh Hyun Seung, Cho Jin Hyung, in order to estimate the useful ASL. Since then, the B/S team of the Economic and Statistics Bureau of the Bank of Korea has been working on a new concept of content training.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.