• Title/Summary/Keyword: CAGR model

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Forecasting methodology of future demand market (미래 수요시장의 예측 방법론)

  • Oh, Sang-young
    • Journal of Digital Convergence
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    • v.18 no.2
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    • pp.205-211
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    • 2020
  • The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

A Study on Demand Forecasting Change of Korea's Imported Wine Market after COVID-19 Pandemic (코로나 팬데믹 이후 국내 수입와인 시장의 수요예측 변화 연구)

  • Jihyung Kim
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.189-200
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    • 2023
  • At the beginning of the COVID-19 pandemic, Korea's wine market had shrunk as other countries. However, right after the pandemic, Korea's imported wine consumption had been increased 69.6%. Because of the ban on overseas travel, wine was consumed in the domestic market. And consumption of high-end wines were increased significantly due to revenge spending and home drinking. However, from 2022 Korea's wine market has begun to shrink sharply again. Therefore this study forecasts the size of imported wine market by 2032 to provide useful information to wine related business entities. KITA(Korea International Trade Association)'s 95 time-series data per quarter from Q1 of 2001 to Q3 of 2023 was utilized in this research. The accuracy of model was tested based on value of MAPE. And ARIMA model was chosen to forecast the size of market value and Winter's multiplicative model was used for the size of market volume. The result of ARIMA model for the value (MAPE=10.56%) shows that the size of market value in 2032 will be increased up to USD $1,023,619, CAGR=6.22% which is 101% bigger than its size of 2023. On the other hand, the volume of imported wine market (MAPE=10.56%) will be increased up to 64,691,329 tons, CAGR=-0.61% which is only 15.12% bigger than its size of 2023. The result implies that the value of Korea's wine market will continue to grow despite the recent decline. And the high-end wine market will account for most of the increase.

A Study on the Priority of Site Selection for Hydrogen Vehicle Charging Facilities in Seoul Using a Market Demand Prediction Model (시장수요예측 모델을 활용한 서울시 수소차 충전시설의 입지선정 우선순위에 관한 연구)

  • Jin Sick, Kim;Kook Jin, Jang;Joo Yeoun, Lee;Myoung Sug, Jung
    • Journal of the Korean Society of Systems Engineering
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    • v.18 no.2
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    • pp.140-148
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    • 2022
  • Hydrogen is expected to be widely applied in most sectors within the current energy system, such as transportation and logistics, and is expected to be economically and technologically utilized as a power source to achieve vehiclebon emission reduction. In particular, the construction of hydrogen charging station infrastructure will not only support the distribution of hydrogen electric vehicles, but also play an important role in building a hydrogen logistics system. Therefore, This paper suggest additional charging infrastructure areas in Seoul with a focus on supply according to the annual average growth rate (CAGR), centering on Seoul, where hydrogen vehicles are most widely distributed. As of February 2022, hydrogen charging infrastructures were installed in Gangseo-gu, Gangdong-gu, Mapo-gu, Jung-gu, and Seocho-gu in downtown Seoul. Next, looking at the number of hydrogen vehicles by administrative dong in Seoul from 2018 to 2022, Seocho-gu has the most with 246 as of 2022, and Dongjak-gu has the highest average growth rate of 215.4% with a CAGR of 215.4%. Therefore, as a result of CAGR analysis, Dongjak-gu is expected to supply the most hydrogen vehicles in the future, and Seocho-gu currently has the most hydrogen vehicles, so it is likely that additional hydrogen charging infrastructure will be needed between Dongjak-gu and Seocho-gu.

The Performance Analysis of Container Terminals in Vietnam using DEA-Malmquist

  • NGUYEN, Dai Duong;Park, Gyei-Kark;Choi, Kyoung-Hoon
    • Journal of Navigation and Port Research
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    • v.43 no.2
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    • pp.101-109
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    • 2019
  • Seaports play a vital role in the economic development of countries, especially for countries having long coastlines such as Vietnam Seaport industry in Vietnam has witnessed an impressive development in recent years. The national cargo throughput in the period 2013-2017 achieved a compounded annual growth rate (CAGR) of 11.8%/year, higher than that of the world (5.1%). However, the differences in planning policies and infrastructure systems has led to the differences in port performance efficiency of regional ports. Therefore, it is necessary to have a general and accurate view of the picture of Vietnam's seaport. The objective of this study was to analyze the relative efficiencies of 26 Vietnam container terminals using traditional output-oriented CCR and BCC DEA model. Malmquist P roductivity Index (MP I) was also applied to evaluate changes in container terminals productivity over time.

A Study of Analysis for Domestic Airport Efficiency Considering Undesirable Output (유해산출물을 고려한 국내 공항 효율성 측정에 관한 연구)

  • Kang, Dalwon;Jeong, Donghun;Jeon, Seungjoon
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.26 no.4
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    • pp.27-35
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    • 2018
  • Recently, Intense competition is expected to bring about continuous change with the rapid global aviation industry. In particular, domestic passenger demand has been steadily increasing over the past five years, with domestic and international shipments growing at a CAGR of 8.4% and 10.0%, respectively. In addition to the economic value of the airport, social interest due to greenhouse gas emissions is also rising. In this study, we analyzed the efficiency of airport operation by using DEA model(Directional Technology Distance Function) considering undesirable output for 14 airports in Korea. As a result of analysis, all airports except Gimhae, Yangyang, Cheongju and Yeosu were analyzed as efficient airports. However, only Gimpo, Gimhae, Jeju, Muan, Daegu and Gwangju were analyzed as efficient airports considering the undesirable output.

Performance Analysis of Trading Strategy using Gradient Boosting Machine Learning and Genetic Algorithm

  • Jang, Phil-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.11
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    • pp.147-155
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    • 2022
  • In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.

In Search of Corporate Growth and Scaleup: What Strategies Drive Unicorns and Hyper-Growing Companies?

  • Lee, Young-Dall;Oh, Soyoung
    • 한국벤처창업학회:학술대회논문집
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    • 2021.04a
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    • pp.33-42
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    • 2021
  • Based on the findings of Lee et al.(2020) and Lee & Oh(2021), this paper aims to fill the gap in our knowledge regarding the relationship between strategic choices and corporate growth by utilizing a novel dataset of 'Unicorn' and 'Hyper-growing' companies. Two previous studies provide coherent findings that the relationship between firms' strategies and their performance should be explored under a more comprehensive framework with consideration of both internal and external factors. Therefore, in this study, we apply a single conceptual framework to two different datasets, which considers the strategy factors as independent variables, and the industry(market) and the firm age as moderating variables. For our dependent variables, valuations for unicorn companies and revenue CAGR for hyper-growing companies are used after categorizing them into three uniform groups. The strategy variables include 'Generic (Cost-leadership, Differentiation, focus) strategies', 'Growth(Organic, M&A) strategies', 'Leading(Pioneer, Fast-follower) strategies', 'Target market(B2B, B2C, B2G, C2C) strategies', 'Global(Global, Local) strategies', 'Digital(Online, Offline) strategies.' For industry(market) factors, it consists of historical growth rate for industries and economic, demographic, and regulatory aspects of states and countries. To overcome the differences in their units, they are also uniformly categorized into multiple groups. Before we conduct a regression analysis, we analyze the industry distribution of the 'Unicorn' and the 'Hyper-growing' companies with descriptive statistics at the integrated and individual levels. Next, we employ hierarchical regression models on Study A('Unicorn' companies in 2019) and Study B('Hyper-growing' companies in 2019) under the same comprehensive framework. We then analyze the relationship between the 'strategy' and the 'performance' factors with two different approaches: 1) an integrated regression model with both the sample of Study A and B and 2) respective regression models on Study A and B. This empirical study aims to provide a complete understanding and a reference to which strategy factors should be considered to promote firms' scale-up and growth.

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An Exploratory Study on the Industry/Market Characteristics of the 'Hyper-Growing Companies' and the Firm Strategies: A Focus on Firms with more than Annual Revenue of 100 Million dollars from 'Inc. the 5,000 Fastest-Growing Private Companies in America' (초고성장 기업의 산업/시장 특성과 전략 선택에 대한 탐색적 연구: 'Inc. the 5,000 Fastest-Growing Private Companies in America' 기업 중 연간 매출액 1억 달러 이상 기업을 중심으로)

  • Lee, Young-Dall;Oh, Soyoung
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.2
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    • pp.51-78
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    • 2021
  • Followed by 'start-up', the theme of 'scale-up' has been considered as an important agenda in both corporate and policy spheres. In particular, although it is a term commonly used in industry and policy fields, even a conceptual definition has not been achieved from the academic perspective. "Corporate Growth" in the academic aspect and "Business Growth" in the practical management field have different understandings (Achtenhagen et al., 2010). Previous research on corporate growth has not departed from Penrose(1959)'s "Firm as a bundle of resources" and "the role of managers". Based on the theory and background of economics, existing research has mainly examined factors that contribute to firms' growth and their growth patterns. Comparatively, we lack knowledge on the firms' growth with a focus on 'annual revenue growth rate'. In the early stage of the firms, they tend to exhibit a high growth rate as it started with a lower level of annual revenue. However, when the firms reach annual revenue of more than 100 billion KRW, a threshold to be classified as a 'middle-standing enterprise' by Korean standards, they are unlikely to reach a high level of revenue growth rate. In our study, we used our sample of 333 companies (6.7% out of 5,000 'fastest-growing' companies) which reached 15% of the compound annual growth rate in the last three years with more than USD 100 million. It shows that sustaining 'high-growth' above a certain firm size is difficult. The study focuses on firms with annual revenue of more than $100 billion (approximately 120 billion KRW) from the 'Inc. 2020 fast-growing companies 5,000' list. The companies have been categorized into 1) Fast-growing companies (revenue CAGR 15%~40% between 2016 and 2019), 2) Hyper-growing companies (40%~99.9%), and 3) Super-growing (100% or more) with in-depth analysis of each group's characteristics. Also, the relationship between the revenue growth rate, individual company's strategy choice (market orientation, generic strategy, growth strategy, pioneer strategy), industry/market environment, and firm age is investigated with a quantitative approach. Through conducting the study, it aims to provide a reference to the 'Hyper-Growing Model' that combines the paths and factors of growth strategies. For policymakers, our study intends to provide a reference to which factors or environmental variables should be considered for 'optimal effective combinations' to promote firms' growth.