• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.220-234
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• 2002

This study examined the impact of preventive environmental management practices on sales growth, manufacturing and environmental performance of the US chemical manufacturing companies. In order to investigate the impact, this study examined the relationship between the degree of preventive environmental programs and sales growth, manufacturing and environmental performances. Using a cross-sectional research design to test three hypotheses. a survey questionnaire was mailed to chemical companies in the USA. To investigate the relationship between the degree of Preventive environmental programs and sales growth, manufacturing and environmental performances. t-tests were used. According to the results of t-tests the higher preventive implementation programs achieved better manufacturing and environmental performances than lower preventive or reactive strategies. But there was no difference in sales growth between tow groups.

• Fashion & Textile Research Journal
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• v.19 no.3
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• pp.289-295
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• 2017

This study aims to develop clothing sales forecast system using weather information. As the annual temperature variation affects changes in daily sales of seasonal clothes, sales period can be predicted growth, peak and decline period by changes of temperature. From this perspective, we analyzed the correlation between temperature and sales. Moving average method was applied in order to indicate long-term trend of temperature and sales changes. 7-day moving average temperature at the start/end points of the growth, peak, and decline period of S/S clothing sales was calculated as a reference temperature for sales forecast. According to the 2013 data analysis results, when 7-day moving average temperature value becomes $4^{\circ}C$ or higher, the growth period of S/S clothing sales starts. The peak period of S/S clothing sales starts at $17^{\circ}C$, up to the highest temperature. When temperature drops below $21^{\circ}C$ after the peak temperature, the decline period of S/S clothing sales is over. The reference temperature was applied to 2014 temperature data to forecast sales period. Through comparing the forecasted sales periods with the actual sales data, validity of the sales forecast system has been verified. Finally this study proposes 'clothing sales forecast system using weather information' as the method of clothing sales forecast.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.35-42
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• 2022

The paper aims to examine the impact of exports on the growth of Vietnamese manufacturing small and medium-sized enterprises (SMEs) by exploring the information of 36,053 enterprises across 24 manufacturing sectors from the Vietnam Annual Enterprise Survey (VAES) in the period 2014-2019. To deal with the problem of variable variance, autocorrelation, and endogeneity of the model, the paper uses the OLS regression method with a strong standard error method and system GMM. Export participation by SMEs is positively associated with business growth in terms of sales and total assets, according to the findings. The GMM estimate shows that the rate of sales growth among exporters is 36.5 percent greater than that of non-exporting enterprises in the case of the sales growth measure. Exporters' average total asset growth rate is 19% greater than the rate estimated for non-exporting businesses. The study's findings indicate the need of adopting policies that promote SMEs in transition economies like Vietnam to engage in exporting activities. Furthermore, the findings show that financial assistance and suitable ownership would enable SMEs to take advantage of export opportunities to increase sales and total assets.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.1-21
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• 2023

This study is related to the performance of open innovation collaboration between startups and large corporations and financial institutions. In the life cycle of a typical company, the growth of a startup is difficult to predict. Startups that possess innovative technology but have only recently been established seek to verify their technology and capabilities by participating in open innovation with large corporations and financial institutions, and further strive to lay the foundation for corporate growth. However, if you approach it only as a theoretical coexistence plan, it will be viewed as a vague attempt from the startup's perspective. The purpose of this study is to differentiately verify the benefits of open innovation by analyzing the difference in sales growth of startups for the purpose of sales performance based on the open innovation participation of large companies and small and medium-sized companies(startups). In verifying this, the analysis was based on the sales results of the actual open innovation collaboration B2C model, and the difference was confirmed by comparing before and after collaboration. Here, the differentiation of the study was added by reflecting the corporate growth stage theory, a growth theory. When the corporate growth stage theory was excluded, it was confirmed that sales growth due to open innovation of startups was applied from the third month, and sales growth depending on participation was confirmed to be significant. On the other hand, when the corporate growth stage theory was applied, sales growth was not significant, but the difference in growth could be confirmed from the fourth month, and it was also confirmed in sales growth depending on participation. As a result, this study objectively confirms the effects that can be gained when startups participate in Open-innovation, and it is expected that Open-innovation led by large corporations, financial institutions, and government agencies will develop into a high-quality program environment.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.373-396
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• 2015

This study analyzed the determinants of high-growth firms using the technology appraisal data of the Korea Technology Finance Corporation. This study is differentiated from previous studies for three reasons. First, it analyzed the determinants of firms that will grow into high-growth firms in the future, not the characteristics of current high-growth firms. Second, it analyzed high-growth firms by dividing them in two aspects: sales and employment. In other words, they were divided into three types: the case in which a firm achieves high growth in both sales increase and creation of jobs, the case in which a firm achieves high growth in creation of jobs but low growth in sales increase, and the case in which a firm achieves high growth in only sales increase but low growth in creation of jobs. Third, this study applied the technology appraisal indicators of Kibo Technology Rating System(KTRS) by the Korea Technology Finance Corporation as the explanatory variable. As a result of analysis, it was found that a firm achieved high growth in both sales and employment if the position in the technology life cycle was appropriate and the technology readiness level was high. However, it turned out that the management system of technical manpower had conflicting effects on high growth of employment and sales. In other words, a firm that had well managed its technical manpower achieved high growth in terms of employment, but rather showed low growth in terms of sales. This result suggests the inference that firms showing high growth in employment may appear mainly in the high-tech industry where management of technical manpower is important. Accordingly, as a result of adding dummy variables that represent whether or not firms are in the high-tech industry, it was found that the result supported the inference, as firms in the high-tech industry were highly likely to achieve high growth in employment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.1-13
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• 2018

This study examines the relationship between the organizational general characteristics (industry, size, location, development stage, and company age) and success factors of Korean venture firms using secondary data. Among the industries with the highest sales figures in 2016 are food / fiber / (non) metals, and the smallest category was software development. The sectors with the highest net profit were computer / semiconductor / electronic components, and the smallest category was telecommunication equipment / broadcasting equipment. The industries with the largest sales growth rate are IT / broadcasting services and software development. The industries with the highest net profit margin of sales are energy / medical / precision, and the smallest is telecommunication equipment / broadcasting equipment. In terms of the number of employees, venture firms with more than 100 employees have the largest sales and net profit, with employees between 1 and 9 have the smallest. However, these results are predictable. In general, the number of employees is highly correlated with sales and net profit. Rather, the sales growth rate and the net profit margin of sales may be meaningful. In particular, with employees between 50 ~ 99, the growth rate of sales and the net profit margin of sales were high. In terms of location, Seoul / Incheon / Gyeonggi were the regions with the highest sales and Daejeon / Sejong / Chungcheong / Gangwon were the least regions. Gwangju / Jeolla / Jeju and Seoul / Incheon / Gyeonggi were almost similar in the areas with the largest net profit. However, Daejeon / Sejong / Chungcheong / Gangwon had the lowest net profit. Unusually, the areas with the highest sales growth rate and the highest net profit margin of sales were Gwangju / Jeolla / Jeju, and the smallest areas were Busan / Jeonnam / Ulsan In the relationship between the stage of development and the performance of the company, the sales of maturity and decline stages were the highest and establishing stage was the lowest. Net profit was also the highest in mature stage and the smallest in establishing stage. The sales growth rate shows a typical pattern in the order of establishing stage, early growth stage, high growth stage, maturity stage, and decline stage. In terms of business performance, sales and net profit are the highest with 21 years or more of company age, and the smallest is less than 3 years. In addition, the sales growth rate was the highest in three years or less, and the net profit margin of sales was the highest in 4 to 10 years. This study can present lots of useful implications by suggesting integrated research model and examining the success factors of Korean venture firms and presenting the application methods of secondary data in analyzing the current status of venture industry in Korea.

• Journal of Distribution Science
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• v.14 no.11
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• pp.83-90
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• 2016

Purpose - During the last two years, convenient stores (CS) are emerging as one of the most fast-growing retail trades in Korea. The goal of this work is to forecast and to analyze sales at CS using ARIMA-Intervention model (IM) and exponential smoothing method (ESM), together with sales at supermarkets in South Korea. Considering that two retail trades above are homogeneous and comparable in size and purchasing items on off-line distribution channel, individual behavior and characteristic can be detected and also relative superiority of future growth can be forecasted. In particular, the rapid growth of sales at CS is regarded as an everlasting external event, or step intervention, so that IM with season variation can be examined. At the same time, Winters ESM can be investigated as an alternative to seasonal ARIMA-IM, on the assumption that the underlying series shows exponentially decreasing weights over time. In case of sales at supermarkets, the marked intervention could not be found over the underlying periods, so that only Winters ESM is considered. Research Design, Data, and Methodology - The dataset of this research is obtained from Korean Statistical Information Service (1/2010~7/2016) and Survey of Service Trend of Korea Statistics Administration. This work is exploited time series analyses such as IM, ESM and model-fitting statistics by using TSPLOT, TSMODEL, EXSMOOTH, ARIMA and MODELFIT procedures in SPSS 23.0. Results - By applying seasonal ARIMA-Intervention model to sales at CS, the steep and persisting increase can be expected over the next one year. On the other hand, we expect the rate of sales growth of supermarkets to be lagging and tied up constantly in the next 2016 year. Conclusions - Based on 2017 one-year sales forecasts for CS and supermarkets, we can yield the useful information for the development of CS and also for all retail trades. Future study is needed to analyze sales of popular items individually such as tobacco, banana milk, soju and so on and to get segmented results. Furthermore, we can expand sales forecasts to other retail trades such as department stores, hypermarkets, non-store retailing, so that comprehensive diagnostics can be delivered in the future.

• Journal of Distribution Science
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• v.18 no.1
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• pp.5-13
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• 2020

Purpose: The purpose of this study is to examine the growth and change process of Korean cosmetic market that has grown more than three times since 2000. It also examined how the growth and decline of the cosmetics brands are related to the change of the cosmetic distribution structure. Research methodology: This study tried to classify the change of the Korean cosmetics market into four stages based on the market sales information. It analyzed the sales information of Korean cosmetic companies and the relationship with the sales of the brands by distribution channel. Results: One-brand store channel had played a leading role in the market growth, and multi-brand stores have grown and a number of brands also grew through that channel since 2013. Since 2016, multi-brand stores have continued to grow and have dominated the market beyond one-brand store channel. Conclusions: The changes in sales of domestic cosmetics companies have been classified based on the distribution channel type in four stages: the emergence of one-brand store, the growth of one-brand store channel, the growth of multi-brand store channel, and the decline of one-brand store channel. In conclusion, multi-brand store channels have recently grown in the Korean cosmetics market, and this trend is expected to continue.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.739-748
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• 2020

The study aims to estimate the effect of current ratio (CR), current liability to inventory (CLI), total asset turnover (TAT), net profit margin (NPM), sales growth (SG), and company size (FS) on profit growth (PG). The research population was 18 companies in the Food and Beverage (F&B) sector listed on the Indonesia Stock Exchange (IDX) from 2014-2018. The data estimation method uses the common effect panel data regression model. The empirical findings show that the CR and CLI ratios have a negative effect on PG, while the TAT, NPM, and SG ratios have a positive effect. Company size is a factor that does not affect the growth of company profits. The results of the study imply that an increase in company profits can be achieved if the company operates efficiently and with low liquidity to encourage higher sales growth. The limitations of the research are as follows: first, this research considers only one type of industry, hence the results of this study would not be the same if applied to another type of industry. Second, the author observes profit growth by using the company's financial ratios and size and ignores other factors that may affect profit growth, for example, the number of employees, total net sales, and market capitalization.