• Journal of Contemporary Eastern Asia
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• v.19 no.1
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• pp.97-122
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• 2020

This paper examines the existence of herd behaviour in fifteen (15) global stock markets, which consist of Developed Markets (Canada, Hong Kong, Japan, Singapore and the United Kingdom), Advanced Emerging Markets (Brazil, Malaysia, Mexico, Poland and South Africa) and Secondary Emerging Markets (Chile, China, Indonesia, the Philippines and Russia) by using Cross Sectional Absolute Deviation (CSAD) method of Chiang and Zheng (2010). It also seeks to explore the impact of social factors such as prosperity, education, ageing society, industry orientation and gender on the existence of market-wide herding. The findings of this paper indicate that herd behaviour exists in Singapore (Developed Market), Mexico, Poland and South Africa (Advanced Emerging Markets) and China and the Philippines (Secondary Emerging Markets). No evidence of herding is observed for Canada, Hong Kong, Japan, United Kingdom, Brazil, Malaysia, Chile, Indonesia and Russia. Ageing society is also found to have significant impact on the existence of herd behaviour. Nonetheless, prosperity, education, industry orientation and gender are found to be insignificant to herding. This study sheds some light on whether social factors determine herding behaviour in the 15 selected stock markets.

• Asia-Pacific Journal of Business
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• v.10 no.3
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• pp.143-151
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• 2019

Whether export-market prioritization is effective on financial performance is a controversial issue. Nevertheless, few studies have addressed this issue. The present study attempted to explicate the effects of exporters' market prioritization on their superior financial performance. Based prominently on the market-segmentation theory and the relationship-marketing theory, the current study developed propositions of whether export-market prioritization is economically reasonable. It is posited that export-market prioritization postively influences buyer satisfaction in a primary market; that export-market prioritization negatively affects on buyer satisfaction in a secondary market; that export market prioritization reduces costs in relation to export marketing and sales; that buyer satisfaction positively influences buyer loyalty for both buyers in primary markets and ones in secondary markets; that buyer loyalty positively influences share of wallet for both buyers in primary markets and ones in secondary markets; and that share of wallet positively influences sales per buyer for both buyers in primary markets and ones in secondary markets. Thus, exporters should identify suitable export-market segments and prioritize export markets. The present study suggested that exporters monitor market profitability, assess the quality of buyer information, and conduct selective organizational alignment in order to develop a prioritization strategy.

• Journal of Distribution Science
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• v.12 no.10
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• pp.5-9
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• 2014

Purpose - This paper aims to critically examine capital market developments in India before and after liberalization. Research design, data, and methodology - The paper examines the Indian capital market from its inception to the latest developments related to both primary and secondary markets, and also discusses recent initiatives of capital markets to enhance the expected level of services to the investor community. It also sheds light on the regulatory framework for investor protection. Results - The study further highlights the future roadmap for the radical development of the Indian capital market. The paper identifies the various initial obstacles and intricacies that affect the smooth functioning of the Indian capital markets. Hence, the paper articulates that these concerns should be addressed by the regulatory authorities and at the policy level at the earliest for further strengthening the capital markets in the interests of the economy in general and retail investors in particular. Conclusion - This is a topic of utmost contemporary importance to worldwide national economies, and calls for novel methods and techniques in dealing effectively with the menace facing capital markets.

• 한국균학회소식:학술대회논문집
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• 2018.05a
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• pp.51-51
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• 2018

The application of recombinant DNA technology has been remarkable and nearly replaced commonly used traditional methods. Traditional industrial microbiology long depended on the discovery of valuable strains and mutagenesis of such strains to improve its secretion capacity of enzymes and secondary metabolites on the industrial scale. Commodities included industrial enzymes and biopharmaceuticals. The purpose of genome manipulation by the crossing of different strains or genetic recombination of naked DNA to the genome is of increased production of valuable metabolites. We optimized a transformation method to either for removal of innate genes, introduction of heterologous genes, or combination of both. We have been used selected whole or partial genes to manipulate target fungi toward the development of strains overproducing invaluable proteins. We have also used the whole genome sequence information of fungal genomes in public databases and functional genomics approach to select genes to manipulate and eventually contributing greatly to the development of overproducing industrial strains overproducing proteins or secondary metabolites. I will briefly review 1) filamentous fungi as a host for production of recombinant proteins and secondary metabolites, 2) markets of industrial metabolites, 3) a new approach to manipulate up to five genes at the same time in the system that ProxEnrem uses.

• Journal of Labour Economics
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• v.19 no.2
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• pp.161-174
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• 1996

Much of the dual labor markets literature is devoted to exploring the reasons as th why the markets are segmented along the lines where the observed wage differentials are not a result of underlying skill differentials . ; and why otherwise comparable workers different the duration of their job tenure and incidence of unemployment. the logic of competitive economics denies the possibility of equally skilled workers being treated differently in labor markets. The model presented in this paper shows that workers could be segregated quite simply due to the structure of information and job-match quality, even though they are the same in terms of productivity. In general, the model predicts that observability of a worker's productivity and the extent of match specificity are key features of labor market segmentation. An important implication is that the negative from the past labor market experienes, sometimes called as hysteresis effect, helps to restrict mobility of workers among different sectors and results in perpetuation of unemployment in the secondary sector. The model also provides an explanation of the efficient wage scheme in the primary sector.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.2
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• pp.18-26
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• 1992

The purpose of this study is to suggest a method for identifying target markets of potential urban park users by their sociodemographic variables. Data was classified into(ⅰ) users vs. nonusers ; (ⅱ) of chosen three urban parks ; or(ⅲ) users of each urban park then analyzed by discriminant analysis. The results showed that linear combination of selected sociodemographic variables could be used for identifying target markets in some cases. In general, season and sex were the most powerful discriminant variables. But the other cases were not satisfactory. The weak points of this study due to adapting secondary data for analysis were discussed.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.173-183
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• 2022

The objective of this research is to examine the influence of the COVID-19 pandemic on stock markets in a few developing and developed countries. This study uses daily data from January 2020 to May 2021 and obtained from World Health Organization and Thomson Reuters. The secondary data was evaluated through panel econometric methodology that includes different unit root tests, and to analyze the long-run relationship between variables, panel cointegration techniques were applied. The long-run causality among variables was examined through Panel Vector Error Correction Model. The overall findings of this study suggest a long-run association exists between several cases and death with the stock returns of the GCC and other stock markets. Furthermore, the VECM model also identified a long-run causality running from COVID cases and death towards the stock rerun of both sets of stock markets. However, a subsequent Wald test yielded mixed results, indicating no short-run causality between cases and deaths and stock returns in both groups; however, in the case of GCC, several COVID-19 cases are having a causal impact on stock markets, which is notable in light of the fact that the death rate in GCC is significantly lower than in many developed and developing countries.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.171-179
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• 2021

In the international markets, financial variables can be volatile and may affect each other, especially in the crisis times. COVID-19, which began in China in 2019 and spread to many countries of the world, created a crisis not only in the global health system but also in the international financial markets and economy. The purpose of this study is to analyze the contagious effect of the COVID-19 pandemic on the volatility of selected financial variables such as Bitcoin, gold, oil price, and exchange rates and the connections between the volatilities of these variables during the pandemic. For this aim, we use the ARMA-EGARCH model to measure the impact of volatility and shocks. In other words, it is aimed to measure whether the impact of the shock on the financial variables of the contagiousness of the epidemic is also transmitted to the markets. The data was collected from secondary and daily data from September 2th 2019 to December 20th, 2020. It can be said that the findings obtained have statistically significant effects on the conditional variability of the variables. Therefore, there are findings that the shocks in the market are contaminated with each other.

• The Journal of Economics, Marketing and Management
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• v.11 no.5
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• pp.15-27
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• 2023

Purpose: Taking Tesla Motors as a case study object, this research aims to summarize the management strategy of Tesla Motors through an evaluation of its business models in Korea and China then helps other new energy automobile enterprises in formulating strategic directions in a targeted manner. Research design, data and methodology: Using the case study method, this study conducts in-depth research on the business model of Tesla, a representative enterprise of the new energy automobile industry. This study mainly uses secondary data obtained from the official websites to support our research. Results: With its top-level innovative technology, distinctive marketing model, and extensive strategic model, Tesla holds the largest share of the new energy vehicle market. Local market brands such as BYD and Hyundai-Kia still have a considerable competitive advantage, and there is a need to learn from each other for further development. Conclusions: To adapt to the needs of economic transformation and environmental development, implementing business strategies related to new energy automobile enterprises is a topic worthy of study. Enterprises such as BYD and Hyundai-Kia have unique advantages in their home markets. However, as sustainable development progresses, these advantages will gradually weaken, and further measures are necessary to maintain their competitive advantage.