• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.4
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• pp.75-90
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• 2022

Purpose - This study aims to study the activation pattern of declining industries by applying the Gompertz growth model using available resources based on the theory of industrial life cycle, classifying declining industries among Korean manufacturing industries, and identifying resource input characteristics. Research design and methodology - This study was conducted by combining the Gompertz growth model that predicts the limit of output based on available resources under the industrial life cycle theory. Using Gompertz model, this study analyzed the life cycle of 39 Korean manufacturing industries from the perspective of domestic production, number of employees, and fixed assets Results - According to a life cycle analysis of 39 manufacturing industries in Korea, the computer, textile, and shoe industries were classified as declining industries. Among them, research on resource input characteristics on the shoe industry showed that domestic production and the number of employees decreased, while the proportion of domestic R&D personnel and the number of research departments gradually increased. Conclusion - Among the declining industries in Korea, the shoe industry is considered to revitalize the industry, that is, to extend the life of the declining industry by offshoring its production site and improving constitution with a "R&D center for global" support.

• Environmental and Resource Economics Review
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• v.29 no.2
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• pp.171-194
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• 2020

We revisit the impact of oil shocks on the Korean economy and examine how this impact varies depending on a business cycle. First, we estimate the probability of a recession through a logistic probability distribution, and correct the probability to match business cycles announced by the Korea National Statistical Office. We set up a STVAR model to analyze the response of macroeconomic variables to oil shocks according to business cycles. We find that oil shocks during the recession have a negative effect on GDP in the mid- and long-term, but during the expansion, GDP does not show a statistically significant response to oil shocks. We presume that this finding is associated with the factors of both the increase in demand for consumption and the increase in current account during the economic boom. Also, we find that the impact of oil shocks on the price level was also observed differently in terms of the persistence of inflation by business cycle. These results highlight the importance of an application of a regime switching model, which has been widely used in energy economics in recent years.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.5
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• pp.805-826
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• 2022

This study explored the process by which consumers purchase products from small fashion business owners via online and mobile channels. In addition, group types were classified given that the purchasing process depends on the consumers' life cycle. The consumer focus group interview (FGI) was conducted on 18 participants that were divided into six groups by age, work, and children. Results revealed that first, consumer journey comprised four stages. Factors influencing need recognition were "attention to information of social media influencer," "attention to information of affiliated groups," and "repeated advertising of SME products/brands." For information searching, "exploring purchase reviews," "environment for mobile shopping information exploration," and "continuous product tracking" were important factors. Purchasing and shopping stages were affected by "price-free, improvised purchase decision" and "convenient mobile payment system and point benefits." After the purchase, "active sharing and repeated purchase when satisfied" and "blocking relationships when dissatisfied" occurred. Second, six consumer groups based on the fashion life cycle are the "Platform lover," "Influencer follower," "Trust builder," "Novelty seeker," "Convenience seeker," and "New designer supporter." Ultimately, small business owners can develop the process of planning and selling fashion products more efficiently.

• Economic Analysis
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• v.26 no.2
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• pp.43-71
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• 2020

This paper aims to derive macroeconomic implications by analyzing the business cycle characteristics of the youth unemployment. The results of empirical analysis seem to show that youth unemployment appears to be relatively less correlated with business cycle compared to other age groups, and thus it is difficult to explain the recent steady increase in the potential labor force as a result of the business cycle fluctuation alone. Moreover, the alternative unemployment measures of the youth group showing upward trend were estimated to be co-integrated with output measures. This co-integrated trend increase suggests that unlike other age groups, youth may be influenced by structural factors inherent in Korea's economic growth path. The fact that the wage difference based on firm size has widened steadily since the Asian financial crisis and that the proportion of large companies that provide relatively high-quality jobs compared to major industrialized countries is significantly lower may be the evidence of the structural changes in Korean youth labor market. The results of above analysis may explain why the job search periods for youth has lengthened amid these structural changes.

• Economic Analysis
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• v.26 no.4
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• pp.39-64
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• 2020

Typical business cycle models have difficulties in explaining key macroeconomic labor market variables, such as employment and unemployment, as they usually consider labor hour choices only. In this paper, we introduce labor market search and matching frictions into a New Keynesian nominal rigidity model and estimate it by Bayesian methods to examine the dynamics of the key labor market variables and business cycles in Korea. The results show that unemployment rates are largely explained by technology shocks, which affect the labor demand side, as well as labor supply shocks. In addition, wage bargaining shocks originating from the bargaining process between firms and workers have non-negligible negative effects on output and employment growth, and careful measures need to be taken to limit their adverse effects.

• Korean Business Review
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• v.11
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• pp.149-171
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• 1998

The most important thing in the Tourist Market Segmentation is to find descriptive variables which can describe the changes of tourist demand properly. There are many descriptive variables. Among them, vital statistical variables were proved to be effective. The strongest variable but which was studied much less is the Family Life Cycle. This study will focus on the relation between Family Life Cycle and Travel Behavior of Destination Choice. In this study, I will verify the validity of Family Life Cycle as a descriptive variable of Tourist Market Segmentation, and try to find the meaningful variable at each steps. Therefore, The purpose of this study is to explain the relation between Family Life Cycle and Travel Behavior of Destination Choice, to verify the validity of Family Life Cycle as descriptive variable and to find the strategy to respond to the increase in quantity and diversity of quality of Tourist Market. The studies on the Family Life Cycle should be updated continuously according to the change of family structure and it should be understood as standard for Tourist Market Segmentation in the public and private sphere.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.863-867
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• 2020

This study was conducted on financial data of 38 economic groups listed on Vietnam's stock market for the period 2009 - 2019 and it aims to provide an empirical evidence on the impact of working capital management policy on performance in all phases of the economic cycle of Vietnamese economic groups. The study uses FGLS estimation method with 2 dependent variables ROA, GOP, independent variables including INV, AR, AP, CCC, dummy variable representing different phases of the economic cycle, variables Control includes CAT, CR, LEV, SZ, GR. Research shows that the greater the level of investment by companies in liquid assets corresponding to a certain level of activity (shown by average days of inventory (INV), average days of collection. (AR), cash flow cycle (CCC)) the lower the rate of return on assets. The study also provides additional evidence of the negative effects of economic crisis on the performance of economic groups. The study also shows that the number of short-term asset cycles has a positive impact on operational efficiency, and the level of debt use has a negative impact on operational efficiency. This result implies that the managers of economic groups can increase the efficiency of businesses through a reasonable working capital policy.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.3-19
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• 2017

The purpose of this paper is to analyze the impacts of regional industrial diversity on regional business cycle response to national volatility. We employed mean group and pooled mean group estimators of panel vector error-correction models in order to control unobserved heterogeneity of the port cities, such as Pusan, Ulsan and Incheon. The results show that in various industrial regions, short-term fluctuations in the unemployment rate are small compared to other regions. On the contrary, long-term volatility of manufacturing production index is low in those regions.

• Journal of Labour Economics
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• v.41 no.2
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• pp.31-59
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• 2018

This study examines how the rate of transition between employment and non-employment changes with the business cycle using monthly panel data constructed from 2000-2013 Korea Labor and Income Panel Study(KLIPS). In particular, we investigate whether the transition rates are different across demographic groups when the labor market is depressed. We find that, as the labor market weakens, the transition rate into non-employment significantly increases. The rates of transition into non-employment are substantially higher for female, older and less educated groups than those for male, prime-aged and more educated groups.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.291-298
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• 2014

Demand forecasting plays a key role in overall business activities such as production planning, distribution management, and inventory management. Especially, for a fast-changing environment of the clothing industry, logical forecasting techniques are required. In this study, we propose a procedure to predict product life cycle using data mining algorithms. The proposed procedure involves three steps : extracting key variables from profiles, clustering, and classification. The effectiveness and applicability of the proposed procedure were demonstrated through a real data from a leading clothing company in Korea.