Abstract
Carsharing is regarded to play an important part in the transition towards a more sustainable mobility system by changing how cars are used and transportation needs are met. Carsharing adopters own less cars, ride less car kilometers and depend on multiple transportation modes for their travel needs. There has been considerable interest in understanding the characteristics and motives of carsharing adopters. Yet, studies have been mostly limited to small-scale surveys, covering only specific cities or organizations and focusing on traditional B2C carsharing, disregarding the growing popularity of P2P carsharing through online platforms. This study contributes to extant research by investigating whether characteristics and motives differ between B2C and P2P carsharing adopters, and broadening the scope of the analysis to include an entire country (The Netherlands) and different carsharing provider types. First, our findings suggest that B2C and P2P carsharing adopters are rather similar in their characteristics but differ in the frequency in which they make use of carsharing and public transport. Second, we provide novel insights into the characteristics that influence a car owner to become an adopter of P2P carsharing as a provider. We find that car owners who already shared their car informally outside an online platform are also much more likely to provide their car through an online platform. We conclude with describing policy implications of our findings. Regulation should focus on shaping favorable conditions for a connected multi-modal transportation system instead of specific regulations for each carsharing business model.
| Original language | English |
|---|---|
| Pages (from-to) | 276-306 |
| Number of pages | 31 |
| Journal | Transportation Research Part D: Transport and Environment |
| Volume | 73 |
| DOIs | |
| Publication status | Published - 2019 |
Funding
Funding has been provided by the Dutch research council NWO , Dialogic , and the Rathenau Institute under the “Sustainable Business Models” program (no. 438-14-904 ). We thank TNS-NIPO for providing us with the survey data. We thank the three anonymous reviewers of this paper for their constructive critique which improved this article considerably. We thank Dr. Maryse Chappin for her help on improving the statistical analysis of our dataset. Appendix A Summary of studies included in literature review Studies BM n location Age Gender Education Income Household Car ownership Density Motives 6t (2014) B2C RT + FF 1169 Paris high Cost-savings and convenience-gaining Bardhi and Eckhardt (2012) B2C RT 40 Boston Cost-savings and convenience-gaining bcs (2016) B2C RT 3512 Germany male All sizes Low Becker et al. (2017) B2C RT + FF 1480 Basel Young male high medium All sizes Low Clavel and Floriet (2009) B2C RT 573 Paris Young male high Changes in personal circumstances; occasional use; convenience-gaining Clewlow (2016) B2C RT 2719 San Francisco Bay Area high high low Dill et al. (2017) P2P 333 owners Portland Young high low Money gains, providing to others and sustainability 240 renters Young female high low Money and time savings, convenience, gaining mobility Firnkorn and Müller (2015) B2C FF 743 Ulm Young male high high Jae-Hun (2017) B2C RT 292 South Korea Young male Cost-savings and convenience-gaining Katzev (2003) B2C RT 87 Portland Medium equal high high low Cost-savings and convenience-gaining Kawgan-Kagan (2015) B2C RT + FF 492 Berlin high high Kent et al. (2017) all 21 Sydney Changes in personal circumstances Knie et al. (2016) B2C RT + FF 1021 Munich, Berlin Medium male high small low Cost-savings and convenience-gaining Koch (2002) B2C RT Cologne, Aachen, Bremen Medium male high medium small high Environmental motives Kopp et al. (2013) B2C FF 11,000 + 204 Munich Young male high high small Kortum (2014) B2C FF Austin high Lane (2005) B2C RT 262 Philadelphia Young high Cost-savings and convenience-gaining Le Vine and Polak (2017) B2C FF 347 London medium male high high family Martin et al. (2010) B2C RT 9635 North America Young female high Meijkamp (1998) B2C RT 337 The Netherlands Cost-savings and convenience-gaining Millard-Ball et al. (2005) B2C RT 1340 North America Young female high high low high Cost-savings and convenience-gaining Müller et al. (2015) B2C FF 4182 Munich, Berlin Young male high high Shaheen et al. (2018) P2P 1151 USA Young male high high Money and time savings, convenience, gaining mobility (for users) Money gains, providing to others and sustainability (for providers) Shaheen et al. (2005) ) B2C RT 107 San Francisco Bay Area high high SmartAgent (2011) B2C RT 453 Utrecht province Young Steer Davies Gleave (2017a) B2C RT 586 Scotland Cost-savings and convenience-gaining Steer Davies Gleave (2017b) B2C RT 2901 London Cost-savings and convenience-gaining Steer Davies Gleave (2016) B2C RT 2583 England, Wales Cost-savings and convenience-gaining Steininger et al. (1996) B2C RT 140 Austria Young high high All sizes low Cost-savings and convenience-gaining Truffer (2003) B2C RT 40 Switzerland, The Netherlands Environmental motives Wappelhorst et al. (2013) B2C RT 1479 Germany medium male high high Wilhelms et al. (2017a) P2P 31 providers and renters Germany Young medium Money and time savings, convenience, gaining mobility Wilhelms et al. (2017b) P2P 20 providers, 21 renters Germany Money and time savings, convenience, gaining mobility Appendix B Descriptive Statistics for dataset in Analysis 1.1 N Minimum Maximum Mean Std. Deviation Adoption of carsharing as a user 1835 0 1 0.13 0.336 Age 1835 18 92 49.76 15.622 Gender (male = 1, female = 2) 1835 1 2 1.54 0.499 Education 1835 1 8 5.86 1.659 Income 1458 1 27 13.94 3.945 Dummy Children in household 1835 0 1 0.23 0.423 Dummy Green party voter 1645 0 1 0.08 0.271 Dummy Public transport subscription 1826 0 1 0.42 0.494 Dummy No car in household 1835 0 1 0.20 0.404 Dummy G4 city 1835 0 1 0.27 0.445 Correlations for dataset in Analysis 1.1 1 2 3 4 5 6 7 8 9 10 1 Adopter of carsharing as a user Pearson Correlation 1 N 1835 2 Age Pearson Correlation −0.102 ** 1 N 1835 1835 3 Gender (male = 1, female = 2) Pearson Correlation −0.036 −0.148 ** 1 N 1835 1835 1835 4 Education Pearson Correlation 0.151 ** −0.165 ** 0.010 1 N 1835 1835 1835 1835 5 Income Pearson Correlation 0.026 0.068 ** −0.143 ** 0.191 ** 1 N 1458 1458 1458 1458 1458 6 Dummy Children in household Pearson Correlation 0.028 −0.310 ** 0.096 ** 0.052 * 0.152 ** 1 N 1835 1835 1835 1835 1458 1835 7 Dummy Green party voter Pearson Correlation 0.152 ** −0.052 * 0.047 0.144 ** −0.028 −0.020 1 N 1645 1645 1645 1645 1299 1645 1645 8 Dummy Public transport subscription Pearson Correlation 0.204 ** 0.045 0.010 0.121 ** −0.028 −0.141 ** 0.100 ** 1 N 1826 1826 1826 1826 1451 1826 1636 1826 9 Dummy No car in household Pearson Correlation 0.318 ** −0.166 ** 0.045 0.100 ** −0.268 ** −0.146 ** 0.142 ** 0.270 ** 1 N 1835 1835 1835 1835 1458 1835 1645 1826 1835 10 Dummy G4 city Pearson Correlation 0.136 ** −0.034 0.006 0.191 ** −0.021 −0.086 ** 0.085 ** 0.129 ** 0.297 ** 1 N 1835 1835 1835 1835 1458 1835 1645 1826 1835 1835 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Descriptive Statistics for dataset in Analysis 1.2 N Minimum Maximum Mean Std. Deviation Potential adoption of carsharing as a user 1597 0 1 0.13 0.331 Age 1351 0 1 0.09 0.291 Gender (male = 1, female = 2) 1597 18 92 50.38 15.922 Education 1597 1 2 1.54 0.498 Income 1597 1 8 5.77 1.666 Dummy Children in household 1258 1 27 13.90 3.894 Dummy Green party voter 1597 0 1 0.23 0.420 Dummy Public transport subscription 1429 0 1 0.06 0.244 Dummy No car in household 1589 0 1 0.38 0.486 Dummy G4 city 1597 0 1 0.16 0.362 Correlations for dataset in Analysis 1.2 1 2 3 4 5 6 7 8 9 10 1 Potential adopter of carsharing as a user Pearson Correlation 1 N 1597 2 Age Pearson Correlation 0.046 1 N 1597 1597 3 Gender (male = 1, female = 2) Pearson Correlation −0.124 ** −0.153 ** 1 N 1597 1597 1597 4 Education Pearson Correlation 0.014 0.104 ** −0.327 ** 1 N 1597 1597 1597 1597 5 Income Pearson Correlation −0.109 ** −0.134 ** 0.069 * 0.163 ** 1 N 1258 1258 1258 1258 1258 6 Dummy Children in household Pearson Correlation 0.065 ** 0.010 −0.154 ** 0.049 0.191 ** 1 N 1597 1597 1597 1597 1258 1597 7 Dummy Green party voter Pearson Correlation 0.054 * 0.020 −0.021 −0.093 ** −0.042 0.187 ** 1 N 1597 1597 1597 1597 1258 1597 1597 8 Dummy Public transport subscription Pearson Correlation 0.055 * 0.065 * −0.048 −0.024 −0.034 0.105 ** 0.080 ** 1 N 1429 1429 1429 1429 1118 1429 1429 1429 9 Dummy No car in household Pearson Correlation 0.083 ** 0.022 0.067 ** −0.154 ** −0.057 * 0.102 ** 0.116 ** 0.068 * 1 N 1589 1589 1589 1589 1252 1589 1589 1421 1589 10 Dummy G4 city Pearson Correlation 0.146 ** 0.066 ** −0.156 ** −0.168 ** −0.324 ** 0.051 * 0.273 ** 0.086 ** 0.210 ** 1 N 1597 1597 1597 1597 1258 1597 1597 1429 1589 1597 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Descriptive Statistics for dataset in Analysis 2 N Minimum Maximum Mean Std. Deviation Frequency of carsharing use high (1) or low (0) 198 0 1 0.57 0.496 Gender (male = 1, female = 2) 198 1 2 1.46 0.500 Age 198 23 85 45.26 12.427 Education 198 3 8 6.60 1.384 Income 168 1 27 14.35 4.134 Dummy Children in household 198 0 1 0.27 0.446 Dummy Green party voter 181 0 1 0.20 0.400 Dummy Public transport subscription 197 0 1 0.71 0.455 Dummy No car in household 198 0 1 0.60 0.491 Dummy G4 city 198 0 1 0.48 0.501 Most important reason to carshare: Costs 198 0 1 0.42 0.495 Most important reason to carshare: Costs 198 0 1 0.12 0.327 Most important reason to carshare: Convenience 198 0 1 0.07 0.257 Dummy only B2C user 198 0 1 0.66 0.476 Dummy only P2P user 198 0 1 0.12 0.327 Correlations for dataset in Analysis 2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 Frequency of carsharing use high (1) or low (0) Pearson Correlation 1 N 198 2 Gender (male = 1, female = 2) Pearson Correlation 0.051 1 N 198 198 3 Age Pearson Correlation 0.045 −0.193 ** 1 N 198 198 198 4 Dummy Children in household Pearson Correlation 0.050 0.066 −0.136 1 N 198 198 198 198 5 Income Pearson Correlation 0.078 −0.103 0.077 0.112 1 N 168 168 168 168 168 6 Education Pearson Correlation 0.134 0.130 −0.074 0.054 0.223 ** 1 N 198 198 198 198 168 198 7 Dummy G4 city Pearson Correlation −0.066 0.017 0.068 −0.111 0.054 0.036 1 N 198 198 198 198 168 198 198 8 Dummy Green party voter Pearson Correlation 0.003 −0.009 0.061 −0.011 0.046 0.221 ** −0.036 1 N 181 181 181 181 153 181 181 181 9 Dummy Public transport subscription Pearson Correlation 0.242 ** 0.036 0.082 −0.135 0.084 0.007 −0.018 0.091 1 N 197 197 197 197 167 197 197 180 197 10 Dummy No car in household Pearson Correlation 0.127 0.077 −0.036 −0.173 * −0.146 0.101 0.204 ** 0.106 0.277 ** 1 N 198 198 198 198 168 198 198 181 197 198 11 Most important reason to carshare: Costs Pearson Correlation −0.049 0.029 0.020 −0.015 −0.140 −0.007 0.024 −0.037 0.114 0.441 ** 1 N 198 198 198 198 168 198 198 181 197 198 198 12 Most important reason to carshare: Convenience Pearson Correlation 0.103 −0.005 −0.034 −0.054 −0.011 −0.038 −0.047 −0.016 −0.002 0.050 −0.316 ** 1 N 198 198 198 198 168 198 198 181 197 198 198 198 13 Most important reason to carshare: Environment Pearson Correlation 0.120 0.059 0.174 * 0.008 0.139 0.023 −0.107 0.145 0.046 −0.178 * −0.234 ** −0.102 1 N 198 198 198 198 168 198 198 181 197 198 198 198 198 14 Dummy only B2C user Pearson Correlation 0.168 * −0.030 0.082 −0.106 0.109 −0.009 0.141 * −0.050 0.078 0.193 ** 0.011 0.106 −0.049 1 N 198 198 198 198 168 198 198 181 197 198 198 198 198 198 15 Dummy only P2P user Pearson Correlation −0.303 ** −0.098 −0.020 0.051 −0.141 −0.061 0.077 0.045 −0.241 ** −0.108 0.029 −0.043 −0.042 −0.514 ** 1 N 198 198 198 198 168 198 198 181 197 198 198 198 198 198 198 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Descriptive Statistics for dataset in Analysis 3 N Minimum Maximum Mean Std. Deviation B2C or P2P carsharing user 218 1 2 1.23 0.421 Gender (male = 1, female = 2) 218 1 2 1.48 0.501 Age 218 19 85 46.05 12.833 Dummy Children in household 218 0 1 0.25 0.433 Income 184 1 27 14.22 4.281 Education 218 2 8 6.50 1.472 Dummy G4 city 218 0 1 0.44 0.497 Dummy Green party voter 201 0 1 0.19 0.396 Dummy Public transport subscription 217 0 1 0.67 0.470 Dummy No car in household 218 0 1 0.56 0.498 Most important reason to carshare: Costs 218 0 1 0.39 0.490 Most important reason to carshare: Costs 218 0 1 0.12 0.325 Most important reason to carshare: Convenience 218 0 1 0.10 0.302 Correlations for dataset in Analysis 3 1 2 3 4 5 6 7 8 9 10 11 12 13 1 B2C (1) or P2P (2) carsharing user Pearson Correlation 1 N 218 2 Gender (male = 1, female = 2) Pearson Correlation 0.003 1 N 218 218 3 Age Pearson Correlation 0.069 −0.159 * 1 N 218 218 218 4 Dummy Children in household Pearson Correlation 0.041 0.026 −0.161 * 1 N 218 218 218 218 5 Income Pearson Correlation −0.209 ** −0.201 ** 0.081 0,066 1 N 184 184 184 184 184 6 Education Pearson Correlation −0.162 * 0.034 −0.125 0.023 0.156 * 1 N 218 218 218 218 184 218 7 Dummy G4 city Pearson Correlation −0.127 −0.062 −0.029 −0.054 0.048 0.081 1 N 218 218 218 218 184 218 218 8 Dummy Green party voter Pearson Correlation −0.041 0.014 0.010 −0.004 −0.040 0.241 ** 0.003 1 N 201 201 201 201 170 201 201 201 9 Dummy Public transport subscription Pearson Correlation −0.225 ** −0.039 0.084 −0.121 0.108 0.031 0.015 0.099 1 N 217 217 217 217 183 217 217 200 217 10 Dummy No car in household Pearson Correlation −0.192 ** 0.042 −0.084 −0.128 −0.204 ** 0.082 0.228 ** 0.119 0.302 ** 1 N 218 218 218 218 184 218 218 201 217 218 11 Most important reason to carshare: Costs Pearson Correlation −0.128 0.018 −0.050 0.015 −0.156 * 0.047 0.086 −0.013 0.123 0.383 ** 1 N 218 218 218 218 184 218 218 201 217 218 218 12 Most important reason to carshare: Convenience Pearson Correlation −0.032 −0.011 −0.072 −0.014 −0.001 0.001 −0.038 −0.018 0.015 0.045 −0.297 ** 1 N 218 218 218 218 184 218 218 201 217 218 218 218 13 Most important reason to carshare: Environment Pearson Correlation 0.143 * 0.137 * 0.134 * 0.019 0.035 0.011 −0.172 * 0.099 −0.026 −0.190 ** −0.270 ** −0.123 1 N 218 218 218 218 184 218 218 201 217 218 218 218 218 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Descriptive Statistics for dataset in Analysis 4.1 N Minimum Maximum Mean Std. Deviation Adopter of P2P carsharing as provider 1489 0 1 0.03 0.166 Gender (male = 1, female = 2) 1489 1 2 1.53 0.499 Age 1489 18 92 51.01 15.359 Dummy Children in household 1489 0 1 0.26 0.439 Income 1170 1 27 14.44 3.503 Education 1489 1 8 5.78 1.644 Dummy G4 city 1489 0 1 0.21 0.408 Dummy Green party voter 1330 0 1 0.06 0.239 Dummy Public transport subscription 1481 0 1 0.36 0.481 Dummy provision to friends and family 1474 0 1 0.35 0.479 Crime rate in municipality 1486 17.4 1382 70.63 66.18 Correlations for dataset in Analysis 4.1 1 2 3 4 5 6 7 8 9 10 11 1 Adopter of P2P carsharing as provider Pearson Correlation 1 N 1489 2 Gender (male = 1, female = 2) Pearson Correlation −0.037 1 N 1489 1489 3 Age Pearson Correlation −0.082 ** −0.144 ** 1 N 1489 1489 1489 4 Dummy Children in household Pearson Correlation 0.035 0.103 ** −0.382 ** 1 N 1489 1489 1489 1489 5 Income Pearson Correlation 0.035 −0.125 ** −0.055 0.117 ** 1 N 1170 1170 1170 1170 1170 6 Education Pearson Correlation 0.112 ** −0.033 −0.136 ** 0.076 ** 0.267 ** 1 N 1489 1489 1489 1489 1170 1489 7 Dummy G4 city Pearson Correlation 0.062 * 0.003 −0.015 −0.052 * 0.035 0.161 ** 1 N 1489 1489 1489 1489 1170 1489 1489 8 Dummy Green party voter Pearson Correlation 0.079 ** 0.045 −0.016 −0.012 −0.003 0.096 ** 0.059 * 1 N 1330 1330 1330 1330 1040 1330 1330 1330 9 Dummy Public transport subscription Pearson Correlation 0.121 ** −0.013 0.131 ** −0.135 ** −0.002 0.064 * 0.064 * 0.065 * 1 N 1481 1481 1481 1481 1164 1481 1481 1322 1481 10 Dummy provision to friends and family Pearson Correlation 0.117 ** 0.062 * 0.045 0.002 −0.076 ** 0.087 ** 0.043 0.028 0.029 1 N 1474 1474 1474 1474 1160 1474 1474 1315 1466 1474 11 Crime rate in municipality Pearson Correlation 0.022 0.023 −0.003 −0.018 0.032 0.101 ** 0.343 ** 0.004 0.043 0.067 * 1 N 1486 1486 1486 1486 1168 1486 1486 1328 1478 1471 1486 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Descriptive Statistics for dataset in Analysis 4.2 N Minimum Maximum Mean Std. Deviation Potential adopter of P2P carsharing as provider 1447 0 1 0.10 0.304 Gender (male = 1, female = 2) 1447 1 2 1.53 0.499 Age 1447 18 92 51.17 15.427 Dummy Children in household 1447 0 1 0.26 0.437 Income 1135 1 27 14.42 3.493 Education 1447 1 8 5.76 1.642 Dummy G4 city 1447 0 1 0.21 0.407 Dummy Green party voter 1295 0 1 0.06 0.235 Dummy Public transport subscription 1439 0 1 0.36 0.480 Dummy provision to friends and family 1445 0 1 0.35 0.476 Crime rate in municipality 1445 17.40 1382 70.4846 66.94 Correlations for dataset in Analysis 4.2 1 2 3 4 5 6 7 8 9 10 11 1 Potential adopter of P2P carsharing as provider Pearson Correlation 1 N 1351 2 Gender (male = 1, female = 2) Pearson Correlation 0.036 1 N 1351 1447 3 Age Pearson Correlation −0.102 ** −0.146 ** 1 N 1351 1447 1447 4 Dummy Children in household Pearson Correlation 0.018 0.109 ** −0.385 ** 1 N 1351 1447 1447 1447 5 Income Pearson Correlation −0.099 ** −80.119 ** −0.057 0.112 ** 1 N 1057 1135 1135 1135 1135 6 Education Pearson Correlation 0.037 −0.030 −0.132 ** 0.073 ** 0.264 ** 1 N 1351 1447 1447 1447 1135 1447 7 Dummy G4 city Pearson Correlation 0.016 −0.003 −0.013 −0.052 * 0.034 0.165 ** 1 N 1351 1447 1447 1447 1135 1447 1447 8 Dummy Green party voter Pearson Correlation 0.026 0.043 −0.013 −0.009 −0.010 0.089 ** 0.056 * 1 N 1209 1295 1295 1295 1012 1295 1295 1295 9 Dummy Public transport subscription Pearson Correlation 0.060 * −0.010 0.131 ** −0.137 ** −0.004 0.064 * 0.057 * 0.056 * 1 N 1343 1439 1439 1439 1129 1439 1439 1287 1439 10 Dummy provision to friends and family Pearson Correlation 0.100 ** 0.065 * 0.050 −0.009 −0.078 ** 0.081 ** 0.050 0.031 0.021 1 N 1339 1432 1432 1432 1125 1432 1432 1280 1424 1432 11 Crime rate in municipality Pearson Correlation 0.040 0.023 −0.005 −0.017 0.032 0.103 ** 0.341 ** 0.000 0.039 0.070 ** 1 N 1349 1445 1445 1445 1134 1445 1445 1293 1437 1430 1445 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Keywords
- Business-to-consumer
- Carsharing
- Innovation adoption
- Peer-to-peer
- Sharing economy
- Two-sided platform
