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.

In order to support start-ups effectively with limited resources, it is necessary to provide support tailored to start-up companies. Businesses that are operating in local incubation centers may have different demands for the support depending on the region characteristics. This study was worked on companies that have entered into the incubation center 'Youth Cube', which is operated by Ansan City. We investigated the perception of importance in the field of support to identify support policy priorities, and the satisfaction level of each field of support currently supported. Then We conducted an IPA analysis to derive the direction of support. The Ansan area has regional characteristics that it is located in the metropolitan area with well-equipped start-up infrastructure and many innovative institutions, As a result of the importance survey, technology commercialization was recognized as the most important, and education/mentoring was recognized as the least important. Satisfaction with the space and facilities that can be used free of charge was the highest, and the satisfaction was the lowest for entrepreneurship education/mentoring, as was the degree of importance. In addition, according to each quadrant, we derived support that should be maintained, support that should be intensively improved, support that should be given a low policy priority, and support directions that should be kept in mind to avoid excessive support.

NDF (No Defect Found) is a phenomenon in which defects have been found in the manufacturing, operation and use of a product or facility, but phenomenon of defects is not reproduced in the subsequent investigation system or the cause of the defects cannot be identified. Recently, with the development of the fourth industrial revolution, convergence of hardware and software technologies in various fields is spreading to products such as aircraft, home appliances, and mobile devices, and the number of parts is increasing due to functional convergence. The application of such convergence technologies and the increase in the number of parts are major factors that lead to an increase in NDF phenomena. NDF phenomena have a significant negative impact on cost, reliability, and reliability for both manufacturers, service providers and operators. On the other hand, due to the nature of NDF phenomena such as difficult and intermittent cause identification and ambiguity in judgment, it is common to underestimate the cost of NDF or fail to take appropriate countermeasures in corporate management. Therefore, in this paper, we propose a methodology for estimating NDF costs by the PAF model which is a quality cost analysis model and ABC (Activity Based Costing) technique. The methodology of this study suggests a detailed procedure and the concept to accurately estimate the NDF costs, using ABC analysis, accounting system information, and IT system data. In addition case studies have validated the methodology. We think this could be a valid methodology to refer to when estimating the cost of other parts. And, it is meaningful to provide important judgment information in the decision-making process based on quality management and ultimately reduce NDF costs by visualizing them separately by major variable factors.

Recently, with the development of technologies for the fourth industrial revolution, convergence and complex technology are being applied to aircraft, electronic home appliances and mobile devices, and the number of parts used is increasing. Increasing the number of parts and the application of convergence technologies such as HW (hardware) and SW (software) are increasing the No Defect Found (NDF) phenomenon in which the defect is not reproduced or the cause of the defect cannot be identified in the subsequent investigation systems after the discovery of the defect in the product. The NDF phenomenon is a major problem when dealing with complex technical systems, and its consequences may be manifested in decreased safety and dependability and increased life cycle costs. Until now, NDF-related prior studies have been mainly focused on the NDF cost estimation, the cause and impact analysis of NDF in qualitative terms. And there have been no specific methodologies or examples of a working-level perspective to reduce NDF. The purpose of this study is to present a practical methodology for reducing NDF phenomena through data mining methods using quantitative data accumulated in the enterprise. In this study, we performed a cluster analysis using market defects and design-related variables of mobile devices. And then, by analyzing the characteristics of groups with high NDF ratios, we presented improvement directions in terms of design and after service policies. This is significant in solving NDF problems from a practical perspective in the company.

The dynamic capabilities of sensing market signals, creating new opportunities and reconfiguring resources and capabilities to new opportunities in a rapidly changing economic environment determines the competitiveness of the enterprise to create added value and survival. This study conceptualized a two-stage performance measurement framework based on the casual model of resource (input)-process-performance (output). We have developed a ‘Process capability index’ that reflect the dynamic capabilities factors as a key intermediary product linking resource inputs and performance outputs in enterprise performance measurement. The process capability index consists of four elements : manpower (level of human resource), operation productivity, structure and risk management. The DEA (Data Envelopment Analysis) model was applied to the developed performance indicators to analyze the branch office performance of a telecom company. Process capability efficiency (stage 1) uses resource inputs to reach a certain level of process capabilities. In performance result efficiency (stage 2), the process capabilities are used to generate sales revenues and subscribers. The two-stage DEA model derives intermediate output values that optimize the individual stages simultaneously. Some branch offices in the telecom company have focused on process capability efficiency or some other branch offices focused on performance result efficiency. Positioning map using two-stage efficiency decomposition and benchmarking can help identify the sources of inefficiencies and visualize strategic directions for performance optimization. Applications of two-stage DEA in conjunction with the case study that are meaningfully used in performance measurement areas have been scarce. In particular, this paper has the contribution to present a new performance measurement model considering the organization theory, the dynamic capabilities.

Recently, with the increase in demand for big data analysis, related techniques and tools are being developed, which makes it possible to utilize data that was difficult to analyze by traditional methods. Topic modeling is a useful technique for deriving topics from a vast amount of text, and is often used in research on trends and predictions of academic research or science and technology. However, the topic derived from the topic modeling is a combination of words presented on the basis of the frequency and probability of simultaneous occurrence, and cannot describe the importance or priority of each word. Therefore, in this study, we applied AHP (Analytic Hierarchy Process) technique to evaluate the priority of the result derived from topic modeling (Topic). In this study, bibliographic data (total of 15,888 articles) of academic researches related to consulting were collected and used in the analysis of this study in order to suggest prioritization method using Topic-Modeling and AHP.

‘Consulting’, which is the main research topic of the knowledge service industry, is a field of study that is essential for the growth and development of companies and proliferation to specialized fields. However, it is difficult to grasp the current status of international research related to consulting, mainly on which topics are being studied, and what are the latest research topics. The purpose of this study is to analyze the research trends of academic research related to ‘consulting’ by applying quantitative analysis such as topic modeling and statistic analysis. In this study, we collected statistical data related to consulting in the Scopus DB of Elsevier, which is a representative academic database, and conducted a quantitative analysis on 15,888 documents. We scientifically analyzed the research trends related to consulting based on the bibliographic data of academic research published all over the world. Specifically, the trends of the number of articles published in the major countries including Korea, the author key word trend, and the research topic trend were compared by country and year. This study is significant in that it presents the result of quantitative analysis based on bibliographic data in the academic DB in order to scientifically analyze the trend of academic research related to consulting. Especially, it is meaningful that the traditional frequency-based quantitative bibliographic analysis method and the text mining (topic modeling) technique are used together and analyzed. The results of this study can be used as a tool to guide the direction of research in consulting field. It is expected that it will help to predict the promising field, changes and trends of consulting industry related research through the trend analysis.

Improving efficiency of the telecommunication is crucial to the development and growth of Korean economy. Recently, it has become important with the huge development of information technology and its greater potential for extensive impact on the rest of the economy. Hence, it is useful to determine the factors that help enhance efficiency in telecommunication and consider them in improving the evaluation model. This study applies DEA (data envelopment analysis) to evaluate the relative efficiency of 51 branches of a Korean telecommunication company. Using the super-efficiency approach, we tested outliers which may affect the results and ranked the efficient branches. A method of deriving key variables applied to business operation is proposed to identify the key performance indicators for evaluation that takes environmental (non-discretionary) factors into account. We used the extended CCR model proposed by Banker and Morey to investigate the influence of non-discretionary factor. The information provided by the model (slacks, weights) and the sensitivity analysis shows that the most important indicator that affects the branch performance is operating cost. The results of sensitivity analysis show that average efficient score decreases from 0.972 (base case) to 0.863 for CASE2-COST. The average score of the data proves the priority of operating cost over other indicators. The effect of environmental (non-discretionary) variable was found to be significant. The population effect was positive and improved overall efficiency by 0.91% on average. Non-discretionary factor plays a meaningful role explaining the performance of branches. The performance optimization report can help a manager of an inefficient branch to develop branch strategies. Managers can identify the top-performing units, study best practices and adopt the strategy to the organization.

The study aims at quantifying the effect of nano technology in the fields of economics and social aspects by using the methodology of system dynamics. A case study which using selenium oxide nanoparticles as additive agent in order to enhance fuel efficiency was selected as an example of nano technology in economic and societal benefits. Additionally, models for exhaust gas from combustion of fuel (diesel) and related issues are developed to evaluate real-time assessment of the effect of nano technology. It was found that the selenium oxide nanoparticles increase fuel efficiency, and it also affects on the amount of exhaust gas and the respiratory disease related issues. The results of this study which give quantitative value for the effect of nano technology can be used as objective references in development of national policy.

It is difficult to make an accurate estimate of the economic value and effects on societal economy of Nano-technologies. This research measures an economic value of Nano-technologies quantitatively and analyzes its influences on societal economy. This paper chooses some major industries as analysis targets and adapts the DEFRA comparative methodology model which has been developed in the UK and recommended by OECD. For this reason, some industries which are in range of economic value assessment were investigated and related data were collected. Also, the economic value and societal influences of Nano-technologies were calculated, through the procedure of the model. In addition, this study conducts a questionnaire to experts for the validity of measurement results and procedures. This paper suggests a guideline for economic value and effects on societal economy of Nano-technologies assessments through quantitative Defra comparative methodologies.

Rutin is one of the major flavonoids found in buckwheat (Fagopyrum esculentum Moench). While rutin is already known to exhibit anti-oxidative, anti-inflammatory, and anti-carcinogenic activities. However, the health beneficial function of rutin metabolites is not well understood. In DPPH radical scavenging assays, the present study found that 3,4-dihydroxyphenyl acetic acid had the highest total anti-oxidant activity, followed by 3,4-dihydroxyphenylacetic acid, rutin, homovanillic acid, and 3-hydroxyphenyl acetic acid. Further, 3,4-dihydroxyphenylacetic acid strongly reduced LPS-induced IL-6 production in RAW 264.7 cells, compared with other metabolites. Therefore, these results suggest that rutin metabolites have potential to be utilized as food ingredients with anti-oxidant and anti-inflammatory activities.

In the manufacturing industry, fostering talented workers has become a core activity as well as an important resource leading to manufacturing enterprises’ innovative activities, which has come to the fore as one of the biggest success factors for innovat

The aim of the study was to confirm whether the coriander seeds ethanol extract (CSEE) exhibited effective antioxidant activity and oxidative stability in corn oil. The results showed that the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) cation radical scavenging activity were 24.4, 55.0, and 81.0, and 8.9, 16.8, and 34.3% at the concentrations of 0.25, 0.5, and 1.0 mg/mL, respectively. The ferric reducing antioxidant power (FRAP) reduction power was 284.1 μM ascorbic acid equivalent/g extract, and the total phenol content (TPC) was 31.9 μM tannic acid equivalent/g extract. Furthermore, the TPC showed positive correlations with the DPPH radical scavenging activity, ABTS cation radical scavenging, and FRAP value (p<0.01). oxygen radical absorbance by fluorescein (ORAC) analysis showed that the antioxidant activities of trolox 50 μM and CSEE 100 μg/mL were 3.1 and 4.4 times higher than those of blank AUC, respectively. In addition, CSEE reduced the amounts of conjugated diene and ρ-anisidine by 8.3 and 40.8%, respectively, in the oxidized corn oil. Thus, the coriander seeds ethanol extract is confirmed to have effective antioxidant activity and oxidative stability in corn oil, and it can be used as a natural antioxidant for preservation in food processing.