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Based on Binary Logit Model Analysis on Characteristics of Sharing Bicycle Travel Taking Fucheng District of Mianyang City As an Example

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Based on Binary Logit Model Analysis on Characteristics of Sharing Bicycle Travel Taking Fucheng District of Mianyang City As an Example Open Journal of Social Sciences, 2020, 8, 260-273 https://www.scirp.org/journal/jss ISSN Online: 2327-5960 ISSN Print: 2327-5952 Based on Binary Logit Model Analysis on Characteristics of Sharing Bicycle Travel Taking Fucheng District of Mianyang City as an Example Tingting An, Langong Hou* School of Civil Engineering and Architecture, Southwest University of Science and Technology, Mianyang, China How to cite this paper: An, T. T., & Hou, Abstract L. G. (2020). Based on Binary Logit Model Analysis on Characteristics of Sharing The study of urban shared bike travel characteristics is the premise of sus- Bicycle Travel Taking Fucheng District of tainable development of shared bike. In this paper, using the form of a ques- Mianyang City as an Example. Open Jour- tionnaire, the citizens of Fucheng District of Mianyang City were investigated nal of Social Sciences, 8, 260-273. https://doi.org/10.4236/jss.2020.84019 and obtained 98 Valid data. Analysis of travel characteristics is based on sur- vey data, and studies the factors affecting the use of shared bicycles, combined Received: December 18, 2019 with the establishment of travel behavior theory Logit model, with the aid of Accepted: April 17, 2020 Published: April 20, 2020 SPSS Calculate with software. The results showed that women were more likely to choose shared bike trips than men; those who chose shared bikes Copyright © 2020 by author(s) and tended to be younger; those who shared bikes were more favored by students Scientific Research Publishing Inc. and office workers; those with higher education levels were more likely to This work is licensed under the Creative Commons Attribution International choose shared bike trips; and those with higher education levels were the most License (CC BY 4.0). significantly affected. http://creativecommons.org/licenses/by/4.0/ Open Access Keywords Slow Motion System, Shared Bicycle, Travel Characteristics, Logit Model, Mianyang City 1. Introduction As one of the “new four great inventions” in China, shared bicycle has aroused extensive attention of many scholars at home and abroad (Wei, Mo, & Liu, 2018). This paper analyzes the problems of shared bicycle parking, deposit safety and vehicle maintenance, and puts forward concrete solutions from different angles (Wang, Yu, & Dun, 2018). This paper studies the optimal scheduling DOI: 10.4236/jss.2020.84019 Apr. 20, 2020 260 Open Journal of Social Sciences T. T. An, L. G. Hou problem of shared bicycle, analyzes the factors affecting the demand of shared bicycle, and proposes an optimal scheduling scheme based on multi-objective programming (Yu, 2018). Using analytic hierarchy process to screen out the in- dex which has a greater impact on the demand of shared bicycle LM Neural network gets the weight of each index, and gives reasonable suggestions for the forecast of shared bicycle demand (Wang, 2018). Based on the location informa- tion of shared bikes and other data, visually revealed the laws of residents’ travel hotspots and spatial and temporal characteristics (Wang, Li, Xu, Ma, & Wei, 2018). Considering the age distribution, the market demand model of shared bi- kes was established, and the release model of shared bikes was established by Markov chain to determine the number of release points of Shared bikes (Gan, Zhang, Huang, & Hu, 2018). Aiming at the shortage of shared bicycle intelligent parking points in rush hour, a parking point assignment algorithm based on improved genetic algorithm is proposed (Shi, Chen, & Xu, 2019). Based on the analytic hierarchy process (AHP), this paper studies the influence and develop- ment of shared bicycle and shared car on urban traffic (Wang, 2019). An ARIMA model was proposed to predict the bicycle demand and status at the sta- tion by analyzing the number of bicycles and local population movement data in the Barcelona community (Kaltenbrunner, Meza, Grivolla, et al., 2010). The li- near regression model was used to forecast the demand of bicycle in New York City (Singhvi, Singhvi, Frazier, et al., 2015). Based on the historical data of Zhongshan public bicycle system, the influence of scenic spots on travel demand and the ratio of site demand to supply are studied by using multiple linear re- gression model (Zhou, Wang, Zhong, et al., 2018). The proposal is based on MART Regression and Lasso. The final destination and vehicle duration were predicted by two regression models. Summarizing the literatures, it is found that domestic and foreign scholars pay more attention to the sharing of bicycle poli- cy, the status quo, demand, the number of drop points and optimal dispatching, and lack of exploration of the characteristics of riders (Zhang, Pan, Li, et al., 2016). Therefore, this paper will study the characteristics of shared bicycle travel from the perspective of traffic planning, in order to analyze the factors affecting the development of shared bicycle. Based on the travel behavior theory, a bi- nomial choice of shared bicycle travel was established Logit based on the survey data, the model parameters were calibrated to determine the significant factors affecting the shared bicycle travel decision. 2. Overview of Study Area and Study Methods 2.1. Overview of the Study Area Figure 1 shows the scope of the study area. The Fucheng District is an important part of the central city of Mianyang City. It is located in the west of the central part of Mianyang City, Sichuan Province. The capital of Chengdu 98 km. Resi- dent Population of Fucheng District in 2017 92.87 Ten thousand people, high DOI: 10.4236/jss.2020.84019 261 Open Journal of Social Sciences T. T. An, L. G. Hou Figure 1. Study area map. urbanization rate 77.71% male to female sex ratio 1:1, 60 near the mouth of the elderly over the age of 150,000 people. Large-scale commerce, residential areas, health institutions, schools and other facilities in the region are relatively com- plete. However, the public transport system in the study area is still not perfect, there are few bus lines, the phenomenon of shared bicycles, and the lack of sys- tematic planning of bicycle lane system. The research on the characteristics of shared bicycle travel is the basis of reasonable launch of shared bicycle and scientific planning of non-motorized road, which can effectively solve urban traffic problems. 2.2. Research Methods 2.2.1. Questionnaire Method Based on the collection of field survey questionnaire, a total of 98 valid data on the use of shared bicycles were obtained from Fucheng District of Mianyang City. The questionnaire contained two types of information: personal characte- ristics and travel characteristics. Personal characteristics included whether to use shared bicycles, gender, age, education level, occupation type, travel characteris- tics including riding hot spots, travel purpose, riding duration, frequency of use, and expected drop point. The contents of the questionnaire are shown in Table 1 to Table 2 As can be seen from the analysis of the returned questionnaire, i.e. 98 Ac- cording to gender, among the survey subjects: 45 Male position, 53 Female gender ratio is similar 1:1 (see Table 3, Table 4); by whether or not shared bikes were used, where 76 Shared bicycles have been used by some people, 22 The survey object has not used shared bicycle, so the prevalence of shared bicycle in DOI: 10.4236/jss.2020.84019 262 Open Journal of Social Sciences T. T. An, L. G. Hou Table 1. Information on personal characteristics. Whether shared Gender Occupation Age Level of education bicycle is used or not Junior high school and Yes Male Students Under 20 below High school/technical No Female Self-employed 20 - 30 years secondary school Staff member of the 30 - 40 College/Bachelor company Postgraduate and Public institutions 40 - 50 years above Freelance occupation 50 - 60 years Other Over 60 Table 2. Travel characteristics information. Weekly riding Riding Desired Travel purpose Use hotspot area frequency duration/time Drop Point ≤1 time 5 minutes Commute Residential area Bus station 1 - 2 times 5 - 10 minutes Up and Down Near bus stop Residential area 3 - 5 times 10 - 20 minutes Official business School Learning Shopping and 6 - 10 times 20 - 30 minutes Commercial District Office area entertainment More than 30 Commercial More than 10 times Leisure Fitness Public Service Area minutes District Other Other Park Scenic Area Other attractions Table 3. Gender data collection. Gender Number of patients Male 45 Female sex 53 Table 4. Whether shared cycling data collection is used. Whether shared bicycle is used or not Number of patients Yes 76 No 22 Fucheng District of Mianyang City is high 78%, However, there are still a few people who do not choose to use shared bicycles (see Table 4); by age: 20 those under the age of 18 Bit, 20 - 30 Yrs is 35 bit, 11 position 30 - 40 age, 40 - 50 of the age of 21 man, 50 - 60 And 60 Above the age of 8 According to the occupa- tion, there are 33 students, 10 self-employed persons, 15 employees of the com- DOI: 10.4236/jss.2020.84019 263 Open Journal of Social Sciences T. T. An, L. G. Hou pany, 11 employees of public institutions and 13 freelancers (see Table 5); ac- cording to the level of education, there are 11 persons with junior high school diploma or below, 31 persons with senior high school/technical secondary school diploma, 55 persons with junior college/technical college diploma and only 1 person with post-graduate diploma or above. The educational level is concentrated in the range of high school to undergraduate, which is consistent with the overall educational level of Mianyang City residents and has research significance, as shown in Table 6. 2.2.2.
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