This study explores to identify the characteristics of the business model by comparing and analyzing the value creation between two cases, and to be successful in business model innovation. In order for the pursuit of purposes, domestic and international firm' business model cases are analyzed. Regarding the business model innovation, huge differences are found between two cases. First, a clear customer value proposal is important. Netflix is constantly monitoring the customer's needs and satisfactions to improve value proposition, while Joycube, domestic firm does not adjust to meet the change of the customer's behaviors. Second, the business model innovation should be taking into account the customer's behaviors in the constant changing market environments. For the growth, firms should consider strategic monitoring the market environments, and find a novelty of the markets, and to create the jump through business model innovation
In this paper, we propose a quadratic (nonlinear) regression model that forecasts daily demands of electric power in summer. For cost-effective production (and/or procurement) of electric power, forecasting demands of electric power with accuracy is important, especially in summer when temperature is high. In the literature, temperature and daily demands of preceding days are typically employed to construct forecasting models. While, we consider another factor, day of the week, together with temperature and daily demands of preceding days. For validating the proposed model, we demonstrate the forecasting accuracy in terms of MAPE(Mean Absolute Percentage Error) and MPE(Maximum Percentage Error) using field data from KEPCO(Korea Electric Power Corporation) in comparison with two forecasting models in the literature. When compared with the two benchmarks, the proposed forecasting model performs far better providing MAPE and MPE not exceeding 3.08% and 8.99%, respectively, in summer from 2005 to 2009.
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