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• W2804345352 abstract "This study aims to explore factors that affect carsharing demand characteristics in different time periods based on EVCARD transaction data, which is the largest station-based one-way carsharing program in Shanghai, China. Monthly usage intensity and degree of usage imbalance are used as proxies of demand. This study uses three groups of independent variables: carsharing station attributes, built environment (density, diversity, design, and destination accessibility), and transportation facilities. The adaptive elastic net regression is developed to identify factors that influence carsharing usage intensity and degree of usage imbalance after factor selection using extra-randomized-tree algorithm. Finally, a station layout is proposed according to both usage intensity and degree of imbalance. The main results of this study are presented as follows: <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mo stretchy=false>(</mml:mo><mml:mn fontstyle=italic>1</mml:mn><mml:mo stretchy=false>)</mml:mo></mml:math> different effects of built environment and transportation factors cause dynamic demand across different time periods; <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M2><mml:mo stretchy=false>(</mml:mo><mml:mn fontstyle=italic>2</mml:mn><mml:mo stretchy=false>)</mml:mo></mml:math> factors with positive and negative effect on carsharing demand are divided clearly for guidance of the carsharing station layout; <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M3><mml:mo stretchy=false>(</mml:mo><mml:mn fontstyle=italic>3</mml:mn><mml:mo stretchy=false>)</mml:mo></mml:math> public parking space leads to more personal vehicle trip compared to a carsharing trip; and <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M4><mml:mo stretchy=false>(</mml:mo><mml:mn fontstyle=italic>4</mml:mn><mml:mo stretchy=false>)</mml:mo></mml:math> as public transportation, the relationship of the metro and carsharing is complementary. However, the bus stop and carsharing have a competitive relationship. This study provides a carsharing layout method based on both usage intensity and degree of imbalance. Furthermore, several policies concerning carsharing are proposed." @default.
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• W2804345352 date "2018-01-01" @default.
• W2804345352 modified "2023-10-15" @default.
• W2804345352 title "Locating Station of One-Way Carsharing Based on Spatial Demand Characteristics" @default.
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• W2804345352 doi "https://doi.org/10.1155/2018/5493632" @default.
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