Analyzing Transfer Commuting Attitudes Using a Market Segmentation Approach

Commuting by transfer in the public transit network is a green travel choice compared to private cars which should be encouraged when direct transit lines cannot take the commuters to their destinations. Therefore, transfer commuting attitudes are important for finding appropriate ways to attract mo...
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Autor*in:	Jiao Ye [verfasserIn] Jun Chen [verfasserIn] Hua Bai [verfasserIn] Yifan Yue [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	transfer commuting attitudinal survey market segmentation structural equation modelling (SEM) K-means clustering

Übergeordnetes Werk:	In: Sustainability - MDPI AG, 2009, 10(2018), 7, p 2194
Übergeordnetes Werk:	volume:10 ; year:2018 ; number:7, p 2194

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/su10072194

Katalog-ID:	DOAJ075843226

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520			\|a Commuting by transfer in the public transit network is a green travel choice compared to private cars which should be encouraged when direct transit lines cannot take the commuters to their destinations. Therefore, transfer commuting attitudes are important for finding appropriate ways to attract more transfer commuters. Firstly, since attitudes are usually unobserved, a combined revealed preference (RP) and stated preference (SP) survey was conducted in Nanjing, China to obtain the observed attitudinal variables. Then the market segmentation approach including the factor analysis, the structural equation modelling (SEM) model and the K-means clustering method was used to identify the underlying attitudinal factors and variables and analyze the interrelationship between them. Six segments were identified by four key factors including the willingness to transfer, the sensitivity to time, the need for flexibility and the desire for comfort. The sensitivity to time is the most important factor for commuters influencing their willingness to transfer. The socio-economic features of each segment were also analyzed and compared. The result shows that socio-economic features have a great impact on the willingness to transfer. Corresponding policy and strategy implications to increase transfer commuting proportion were finally proposed.
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allfieldsSound	10.3390/su10072194 doi (DE-627)DOAJ075843226 (DE-599)DOAJaed67e6015e74f6a91e96b7f42fbe6e8 DE-627 ger DE-627 rakwb eng TD194-195 TJ807-830 GE1-350 Jiao Ye verfasserin aut Analyzing Transfer Commuting Attitudes Using a Market Segmentation Approach 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Commuting by transfer in the public transit network is a green travel choice compared to private cars which should be encouraged when direct transit lines cannot take the commuters to their destinations. Therefore, transfer commuting attitudes are important for finding appropriate ways to attract more transfer commuters. Firstly, since attitudes are usually unobserved, a combined revealed preference (RP) and stated preference (SP) survey was conducted in Nanjing, China to obtain the observed attitudinal variables. Then the market segmentation approach including the factor analysis, the structural equation modelling (SEM) model and the K-means clustering method was used to identify the underlying attitudinal factors and variables and analyze the interrelationship between them. Six segments were identified by four key factors including the willingness to transfer, the sensitivity to time, the need for flexibility and the desire for comfort. The sensitivity to time is the most important factor for commuters influencing their willingness to transfer. The socio-economic features of each segment were also analyzed and compared. The result shows that socio-economic features have a great impact on the willingness to transfer. Corresponding policy and strategy implications to increase transfer commuting proportion were finally proposed. transfer commuting attitudinal survey market segmentation structural equation modelling (SEM) K-means clustering Environmental effects of industries and plants Renewable energy sources Environmental sciences Jun Chen verfasserin aut Hua Bai verfasserin aut Yifan Yue verfasserin aut In Sustainability MDPI AG, 2009 10(2018), 7, p 2194 (DE-627)610604120 (DE-600)2518383-7 20711050 nnns volume:10 year:2018 number:7, p 2194 https://doi.org/10.3390/su10072194 kostenfrei https://doaj.org/article/aed67e6015e74f6a91e96b7f42fbe6e8 kostenfrei http://www.mdpi.com/2071-1050/10/7/2194 kostenfrei https://doaj.org/toc/2071-1050 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 10 2018 7, p 2194
language	English
source	In Sustainability 10(2018), 7, p 2194 volume:10 year:2018 number:7, p 2194
sourceStr	In Sustainability 10(2018), 7, p 2194 volume:10 year:2018 number:7, p 2194
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topic_facet	transfer commuting attitudinal survey market segmentation structural equation modelling (SEM) K-means clustering Environmental effects of industries and plants Renewable energy sources Environmental sciences
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container_title	Sustainability
authorswithroles_txt_mv	Jiao Ye @@aut@@ Jun Chen @@aut@@ Hua Bai @@aut@@ Yifan Yue @@aut@@
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callnumber-first	T - Technology
author	Jiao Ye
spellingShingle	Jiao Ye misc TD194-195 misc TJ807-830 misc GE1-350 misc transfer commuting misc attitudinal survey misc market segmentation misc structural equation modelling (SEM) misc K-means clustering misc Environmental effects of industries and plants misc Renewable energy sources misc Environmental sciences Analyzing Transfer Commuting Attitudes Using a Market Segmentation Approach
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topic_title	TD194-195 TJ807-830 GE1-350 Analyzing Transfer Commuting Attitudes Using a Market Segmentation Approach transfer commuting attitudinal survey market segmentation structural equation modelling (SEM) K-means clustering
topic	misc TD194-195 misc TJ807-830 misc GE1-350 misc transfer commuting misc attitudinal survey misc market segmentation misc structural equation modelling (SEM) misc K-means clustering misc Environmental effects of industries and plants misc Renewable energy sources misc Environmental sciences
topic_unstemmed	misc TD194-195 misc TJ807-830 misc GE1-350 misc transfer commuting misc attitudinal survey misc market segmentation misc structural equation modelling (SEM) misc K-means clustering misc Environmental effects of industries and plants misc Renewable energy sources misc Environmental sciences
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title	Analyzing Transfer Commuting Attitudes Using a Market Segmentation Approach
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title_sort	analyzing transfer commuting attitudes using a market segmentation approach
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title_auth	Analyzing Transfer Commuting Attitudes Using a Market Segmentation Approach
abstract	Commuting by transfer in the public transit network is a green travel choice compared to private cars which should be encouraged when direct transit lines cannot take the commuters to their destinations. Therefore, transfer commuting attitudes are important for finding appropriate ways to attract more transfer commuters. Firstly, since attitudes are usually unobserved, a combined revealed preference (RP) and stated preference (SP) survey was conducted in Nanjing, China to obtain the observed attitudinal variables. Then the market segmentation approach including the factor analysis, the structural equation modelling (SEM) model and the K-means clustering method was used to identify the underlying attitudinal factors and variables and analyze the interrelationship between them. Six segments were identified by four key factors including the willingness to transfer, the sensitivity to time, the need for flexibility and the desire for comfort. The sensitivity to time is the most important factor for commuters influencing their willingness to transfer. The socio-economic features of each segment were also analyzed and compared. The result shows that socio-economic features have a great impact on the willingness to transfer. Corresponding policy and strategy implications to increase transfer commuting proportion were finally proposed.
abstractGer	Commuting by transfer in the public transit network is a green travel choice compared to private cars which should be encouraged when direct transit lines cannot take the commuters to their destinations. Therefore, transfer commuting attitudes are important for finding appropriate ways to attract more transfer commuters. Firstly, since attitudes are usually unobserved, a combined revealed preference (RP) and stated preference (SP) survey was conducted in Nanjing, China to obtain the observed attitudinal variables. Then the market segmentation approach including the factor analysis, the structural equation modelling (SEM) model and the K-means clustering method was used to identify the underlying attitudinal factors and variables and analyze the interrelationship between them. Six segments were identified by four key factors including the willingness to transfer, the sensitivity to time, the need for flexibility and the desire for comfort. The sensitivity to time is the most important factor for commuters influencing their willingness to transfer. The socio-economic features of each segment were also analyzed and compared. The result shows that socio-economic features have a great impact on the willingness to transfer. Corresponding policy and strategy implications to increase transfer commuting proportion were finally proposed.
abstract_unstemmed	Commuting by transfer in the public transit network is a green travel choice compared to private cars which should be encouraged when direct transit lines cannot take the commuters to their destinations. Therefore, transfer commuting attitudes are important for finding appropriate ways to attract more transfer commuters. Firstly, since attitudes are usually unobserved, a combined revealed preference (RP) and stated preference (SP) survey was conducted in Nanjing, China to obtain the observed attitudinal variables. Then the market segmentation approach including the factor analysis, the structural equation modelling (SEM) model and the K-means clustering method was used to identify the underlying attitudinal factors and variables and analyze the interrelationship between them. Six segments were identified by four key factors including the willingness to transfer, the sensitivity to time, the need for flexibility and the desire for comfort. The sensitivity to time is the most important factor for commuters influencing their willingness to transfer. The socio-economic features of each segment were also analyzed and compared. The result shows that socio-economic features have a great impact on the willingness to transfer. Corresponding policy and strategy implications to increase transfer commuting proportion were finally proposed.
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