• Title/Summary/Keyword: Promising SMEs in Export

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The Influence of Export Promotion Programs on SMEs' Export Performance: Focusing on Promising SMEs in Export (수출유망중소기업 지원프로그램이 수출성과에 미치는 영향에 관한 연구)

  • Jaekyung Ko;Chulhyung Park;Chang-Yong Han
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.2
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    • pp.95-107
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    • 2023
  • The purpose of this study is to investigate the impact of export promotion programs (EPPs) on the export performance of small- and medium-sized enterprises (SMEs), with a specific focus on the influence of EPPs for promising SMEs in the export market. Using data on SMEs provided by the Industrial Bank of Korea (IBK), we conducted a fixed-effects model analysis from 2016 to 2019. Our study shows that EPPs have a positive and significant relationship with export intensity. Further analysis reveals that SMEs utilizing the financing support system provided by EPPs tend to improve their export growth and financial performance relative to their counterparts. While EPPs can assist SMEs with their internationalization efforts, their similarity and redundancy are recognized as potential limitations. This study complements the existing literature that has mainly focused on surveys and cross-sectional analysis by specifying the research subject to promising SMEs in export, and analyzing the effects of the export promotion program supported by IBK Industrial Bank. The results of this study are expected to provide implications for improving SMEs' export capabilities.

A Study on the Selection Model of Promising Export Items Applicable to the Defense SMEs (방산 중소기업에 적용 가능한 유망수출품목 선정모형에 관한 연구)

  • Won, Jun-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.7
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    • pp.321-330
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    • 2020
  • The defense industry has recently been focused on boosting exports of weapon systems. Investigation and selection of promising export items for SMEs in the defense industry is essential to establish a defense promotion policy. This study presents a model for selecting promising export items applicable to the defense industry through case studies, such as criteria for selecting promising items from other organizations. The evaluation index is largely composed of three categories, competitiveness of the item itself, capabilities of the exporter, and ripple effect of the export, and consists of eight detailed evaluation indicators. The relative weight between categories was calculated through the AHP method. In the selection model, if a certain score is exceeded, it is then possible to adopt a promising item or verify validity. In particular, promising items were selected by applying this methodology to those involved in the defense industry. Using the model presented in this study, it is expected that domestic small and medium-sized enterprises with relatively high export competitiveness and excellent quality items will be given priority, and more effective and intensive export support will be possible.

An Empirical Study on Determinants affecting to the Perceived Organizational Performances of Korean Organizations Promoting SMEs' Export (중소기업 수출지원기관의 조직성과에 영향을 미치는 요인에 관한 실증연구)

  • Kim, Jae-Woo;Jeong, Yoon-Say
    • International Commerce and Information Review
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    • v.14 no.4
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    • pp.275-295
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    • 2012
  • Korea's economic development started from early 1960s over war devastation. Korean government drove promoting export with its all efforts. In 2011, Korea joined the "USD 1 trillion trade club" as the 9th nation in the world. It is true that the growth of Korean exports has greatly contributed to the development of Korean economy, and that workers in the export promoting organizations also contributed to such a tremendous performance. Still, there are a number of SMEs waiting for more support from the export promoting organizations. This paper tried to identify the determinants of organizational performances of export promoting organization workers with particular focus on their public service motivation and self-esteem. Our findings are as follows; Workers' public service motivation and self-esteem are strongly related to their organizational commitment, job satisfaction, organizational performances. In addition, the workers show a different level of intrinsic and extrinsic satisfaction when it comes to public service and customer satisfaction. This reflects the employees of export promoting organizations have more focused on the value and accomplishment of their performances in workplace. Women and younger workers within the organizations tend to have weaker organizational commitment. In conclusion, we recommend that it is important to increase the women's organizational commitment and develop more inspirational personnel programs to younger workers within the organizations in order to support Korea's promising SMEs in a more practical manner.

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On the Development of Alibaba.com

  • Wang, Guo-an
    • International Commerce and Information Review
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    • v.4 no.2
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    • pp.223-231
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    • 2002
  • Alibaba.com has developed very fast and created a miracle in the international e-business community since it was established just three years ago. The paper at first introduces its rapid development from its establishment, the construction of its websites and its e-products and e-services, its mode of operation and corporate culture. Secondly it analyses the reasons why it has not only survived, but also developed very fast and begun to make profits despite the cut-throat competition in the e-business community in the tough e-environment in China. Then it displays and analyzes its competitive edges and the challenges it is confronted with. Finally it predicts its promising future.

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Export Prediction Using Separated Learning Method and Recommendation of Potential Export Countries (분리학습 모델을 이용한 수출액 예측 및 수출 유망국가 추천)

  • Jang, Yeongjin;Won, Jongkwan;Lee, Chaerok
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.69-88
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    • 2022
  • One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

Machine Learning Model for Recommending Products and Estimating Sales Prices of Reverse Direct Purchase (역직구 상품 추천 및 판매가 추정을 위한 머신러닝 모델)

  • Kyu Ik Kim;Berdibayev Yergali;Soo Hyung Kim;Jin Suk Kim
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.2
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    • pp.176-182
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    • 2023
  • With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

A policy case study for cultivation of global small giant companies in Healthcare areas: Focusing on German case (보건의료 분야 글로벌 강소기업 육성을 위한 정책사례연구: 독일을 중심으로)

  • Kim, Na-Hyeong;Han, Neung-Ho;Pak, Myong-Sop
    • Korea Trade Review
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    • v.42 no.4
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    • pp.69-91
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    • 2017
  • Since the global financial crisis, major countries have been executing policies related to two top-priority goals to create more jobs: revitalization of entrepreneur activity and the cultivation of small and medium-sized companies. In South Korea, the interest of policy makers is increasingly focusing on the role of SMEs that have a technological competitive edge in the realization of a "job-centered creative economy." Due to the nature of the field, the health and medical industry requires a particularly long time until the achievement of industrialization, Also, because of the complex distribution structure, it is essential for related government ministries and institutions to jointly devise strategies. A lack of policy supports for the industry has thus far resulted in its development being relegated for the most part of small and medium-sized companies, which consequently means low global competitiveness. Now is the time for the South Korean government to provide the revolutionary supported options and strategies. This study aims to propose a general policy direction and policy areas for the cultivation of Korea's small and medium-sized companies in the healthcare industry into global small giant companies through an exploration of the German case. It is crucial to first cultivate the international competitiveness of Korean small and medium-sized companies (as in the case of Germany) so that they can grow into global small giant companies. Another important task is the creation of an environment that expedites the qualitative growth of promising SMEs as well as technological development. After securing competitiveness in terms of both product quality and technology in the global health market, substantive policy supports will be necessary to cultivate global small giant companies that are export-based (e.g. job creation effect, sales value added).

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