The purpose of this study is to examine what are the important variables for information security compliance and whether the information security investment by the industry is different. To comply with the information security policies, the organization must establish measures to prevent or resolve information security incidents. This research process consists of four stages, and the analysis method was conducted with the categorical regression analysis and the correspondence analysis. The first analysis analyzed the independent variables that affect security regulations compliance. The rest of the analysis was conducted by industry in the order of security compliance regulations, manpower investment, and budget investment. As a result of the first analysis, this had positive effects on an organization and personal information protection awareness, joint operation organization of information protection, manpower and budget investment, corporate size, and industry. The correspondence analysis was conducted from the second analysis to the fourth analysis and it analyzed the differences in information security investment by industry. The second analysis showed that the construction industry, science and technology industry, and finance industry have higher compliance with security regulations than other industries. The third analysis showed that the financial industry and the science and technology industry were higher than other industries. The last analysis showed that the financial industry was higher than other industries. The theoretical contribution of this study provided the basis for updating the information security theory. The practical contribution of this study requires government support to reduce information security deviations by industry.
This study, in order to complement instability of analysis result stemming from the choice between reference point and comparison point which is pointed out as the defect of shift-share analysis, conducted shift-share analysis using Gross Regional Domestic Product (GRDP) trend of Geumgang area, Chungcheongnam-do for the period from 2000 to 2011. As a result of the analysis, (1) industries that had both the positive Regional Share Effect (RSE) and Industrial Mixed Effect (IME) were service industries such as manufacturing industry, electricity gas, transportation industry, art, etc., which are positively influencing the regional industry. (2) industries that had both the negative RSE and IME were other service industries such as wholesale and retail businesses, lodging industry, food industry, real estate business and leasing service, business service industry, public administration, etc., which provide basic livelihood services for the residents. (3) industries that had the positive RSE and negative IME were agriculture, forestry and fishery industry, mining industry, construction industry, and educational service industry. (4) industries that had the negative RSE and positive IME were info-communications industry, financial and insurance businesses, health industry, etc.
The fisheries industry has led the Korean economy, and has been achieving high-level position in the world. However, this industry meets aging, low growth and profit. In order to overcome this critical situation, it is needed to understand the overall status of industry. In industry level, most of previous researches focused on ocean industry rather than fisheries. In addition, scholars have been getting a lot of attention about fisheries cooperatives, fishing-ports, methods of fishery, and manufacturing process in fisheries sector. The aim of this research is analysis of domestic fisheries industry's managerial performance using data envelopment analysis(DEA) considering operating and scale view. Furthermore, the comparative analysis is performed by firm size, and industry type. In results, fisheries industry's managerial performance is not high, overall. In more detail, most of big size firms are under decreasing returns to scale(DRS) status. Fishery processing industry's performance is low, and fishery distribution industry has the best performance. This paper suggests that transferring operating capability from big firms to small firms, and policy supports and firm's activities should be accompanied for high-value added in fisher, and fishery processing industries.
Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.
The forging industry is composed of those plants that make parts to order for customers; or make parts for their own company's internal use; or make standard parts for resale. Also, the forging industry is closely related with automobile industry and ship building industry - Korea's major export industry. But, it is hard to find the Korea's forging industry's statistical analysis because it is not revealed with final product. In this paper, we perform statistical analysis using the micro data service provided by the Statistics Korea. We focus on the analysis of production costs as well as the status of forging company and their employee.
Although concerns about overheating of the franchise industry's market structure continue to be raised, there are few studies that analyze the market structure of the franchise industry and suggest practical use. Most existing studies mainly analyze the market structure of other industries using industrial concentration(HHI) as an indicator of market competition intensity from the perspective of industrial organization theory. This study seeks to present a market structure analysis method that is different from existing methods. Considering practical application, this study presented a method to analyze the market structure that combines industry concentration(HHI) analysis and matrix analysis of the franchise industry. First, the industry concentration(HHI) and operating profit ratio(SMR) of 15 major industries in the franchise industry were analyzed in a time series manner (2014-2019). Second, using industrial concentration and operating profit ratio(SMR) as two variables on the x-axis and y-axis, a two-stage matrix analysis was used to understand the market structure characteristics of 15 industries at a glance. Third, a method of utilizing the matrix analysis results for practical decision-making was presented.
This study examines the relationship of the industry-specific factors that effect innovation of manufacturing technology and the market share within the defense industry. Since the establishment of the basic defense industry framework in 1973, there were numerous interactions of the industry-specific factors of the defense industry structure with the technological innovation and market organization of the defense industry. During last three decades, the domestic defense industry has achieved the considerable level but the framework of the basic system has not developed much in areas of the military science and the defense manufacturing technology. Industry-specific factors were formed in the process and appeared in a variety of behavioral characteristics as subsystems. Currently, there IS a growing trend where the management of defense industry is gradually deteriorating due to limitation of the domestic industry-specific factor (e.g. defense technologies, amount of demand, etc.). If there is a prominent imbalance of the industry-specific factors. it can trigger the potential problem of conflict, lack of cooperation and control, slowing the growth of the manufacturing technology thereby diminishing the market and deteriorating the defense supply/demand relationship. In a research conducted by Joe S. Bain, Bain analyzed the relationship of the traditional industrial organization where industry-specific factor(S) not only impacts the conductor(C). And, conductor(C) influences the shaping of the performance(P) of relationship of the traditional industrial organization. Consequently, the researcher has identified the demand monopoly, barriers to entry, and market competition with comparison of defense industry issues. These defense issues were three industry-specific factors identified, which are 1) The demand monopoly and The entry barriers to new market competition, 2) the industrial technical factor to a production technical competitiveness and a market sharing competitiveness, 3) the probability factor to revolution for military affairs(RMA) and a R&D production. According to baseline with these factors, the following research model is established from the special companies group(Group A), the systematization companies group(Group B), and the general companies group(Group 0. The hypothesis is that if there are more industry-specific factors, then there will be more relationships of defense industry relation statutes. This research is an empirical study on the relationship that the industry specific factors effects the innovation of manufacturing technology and the shaping of the market in the defense industry. Moreover, the existing models to evaluate the industry specific factors of the defense industry IS much to be desired with the controlled statistical analysis of the result. It is vital to study on current situation with suggesting alternative strategy to the efficient strategy. The descriptive analysis approach analysis is conducted with SPSSWIN to conduct reliability test, factor analysis, correlation analysis, cross-tabulation analysis, one-way ANOVA, and multiple regression analysis. However, there were some limitations of the survey such as the rigidity of concept about the technical factors and various market management factors. The wishes is that the decision-maker could be utilized these defence industrial factors to formulate efficient defence policy and strategy in the future.
This study attempts to analyze the economic impact of the service robot industry using Input-Output analysis, which is conducted based on Demand-driven model, the Leontief price model, the Backward and Forward Linkage Effects, and the Exogenous Methods. In a Demand-driven model analysis, we can conclude that the service robot industry contains characteristics of both the manufacturing industry and the service industry, which causes a positive impact on the overall industry by compensating for the weaknesses of the two industries. The Leontief price analysis indicates when wages in the service robot industry increase, prices related to robot manufacturing also increase. Also, when profits in the service robot industry increase, prices related to service provision increase, too. The Backward and Forward Linkage Effects analysis shows that the service robot industry is highly sensitive to the current economic condition and has a great influence on the service industry. The service robot industry can highlight the aspect of service characteristics when the manufacturing industry is in recession and vice versa. In addition, the service robot industry can be regarded as a value-adding and domestic economy promoting industry which utilizes knowledge of information and communication technologies. It is important to foster the service robot industry in South Korea, which is in economic recession to provide an opportunity to stimulate the growth of both service and robot industries.
The objective of this study is to investigate patent trends of Daegu city which tries to introduce environment friendly energy and to develop new technology or new industry sprung from technology convergence on smart decentralized energy technology and other technologies. After applying network analysis to corresponding groups of technology or industry convergence, strategy for future energy convergence industry is provided. Patent data applied in Daegu city area are used to obtain research goal. The technology which contains several IPC codes (IPC Co-occurrence) is considered as a convergence technology. Path finder network analysis is used for visualizing and grouping by using IPC codes. The analysis results categorized 13 groups in energy convergence industry and reclassified them into 3 cluster groups (Smart Energy Product Production Technology Group, Smart Energy Convergence Supply Technology Group, Smart Energy Indirect Application Technology Group) considering the technical characteristics and policy direction. Also, energy industry has evolved rapidly by technological convergence with other industries. Especially, it has been converged with IT industry, and there is a trend that energy industry will be converged with service industry and manufacturing industry such as textile, automobile parts, mechanics, and logistics by employing infrastructure as well as network. Based on the research results on core patent technology, convergence technology and inter-industry analysis, the direction of core technology research and development as well as evolution on decentralized energy industry is identified. By using research design and methodology in this study, the trend of convergence technology is investigated based on objective data (patent data). Above all, we can easily confirm the core technology in the local industry by analyzing the industrial competitiveness in the macro level. Based on this, we can identify convergence industry and technology by performing the technological convergence analysis in the micro level.
In these days, the interest on medical industry is increasing around the world. This paper attempts to estimate the economic effects of the medical and measuring instrument industry through the Input-Output Analysis. Especially, 78*78 Sector Tables were used as the first analysis tool. So then, 79*79 Sector Tables adjusted were used for that industry. The main analysis tools of this study are comparing and analyzing backward and forward linkage effect, the induced effect of the self industry and other industries and the induced coefficients such as products, value-added, employee's pay, sales surplus, employment. According to the result of analysis, the medical and measuring instrument industry has great economic impacts which affects the major macroeconomic factors such as production and backward linkage effect. And the induced effects of the self medical and measuring instrument industry are significant compared to other industries in aspects of production, employee's pay and sales surplus.
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