Indutores de consumo de modais de deslocamento vinculadas ao ride-hailing no Brasil

Violin, Fábio Luciano

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urbe. Revista Brasileira de Gestão Urbana

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Sumário

Artigo Científico • urbe, Rev. Bras. Gest. Urbana 14 • 2022 • https://doi.org/10.1590/2175-3369.014.e20210111 copiar

Indutores de consumo de modais de deslocamento vinculadas ao ride-hailing no Brasil

Autoria SCIMAGO INSTITUTIONS RANKINGS

Resumo

O estudo se propôs a levantar os indutores de consumo relacionados ao deslocamento sob demanda no Brasil e contou com 3425 entrevistas cujos dados submetidos à análise fatorial exploratória e confirmatória através do software IBM SPSS Statistics. Para se ter robustez nos resultados aferidos, desenhou-se através da revisão do estado da arte e do delineamento dos pontos de incidência da oferta as variáveis de análise atinentes a realidade do país. Emergiu da pesquisa o apontamento de seis variáveis subjacentes ao processo de tomada de decisão de consumo pautadas no aspecto tecnológico da oferta e marcadas pelo senso utilitarista de uso. Como implicações teórico-práticas, os resultados corroboram com pesquisas internacionais ligando o consumo ao aspecto de interesse pessoal em detrimento do bem comum e das preocupações socioambientais apontados pelos primeiros estudos relacionados a temática. Indica-se, desse modo, avanços no campo do conhecimento ao evidenciar-se os impactos da conveniência, tecnologia e individualismo no consumo. O estudo é inovador, pois traça - através da análise confirmatória - os indicativos de direcionamento de consumo, indicando tendências a serem observadas por gestores públicos e organizações privadas, contrapondo-se aos estudos da mesma temática cuja base de observação restringe-se a uma localidade ou mesmo região.

Palavras-chave:
Economia Compartilhada; Empresas de redes de transporte; Motivadores de uso

Use Motivators	Dimensions
Use Motivators	Environmental	Social	Economic	Technological
Safety
Cost
Security Conditions
Pleasant Participation
Convenience
Accessibility
Agility
Sustainability
Saving time
Avoid Driving Drunk
Avoid Public Transport
Comfort

Use Motivators	Dimensions
Use Motivators	Environmental	Social	Economic	Technological
Social connections
Comfort
Sustainable consumption
Fare cost
Parking cost
Ease of payment
No need to drive
Avoid public transport
Data protection
Privacy issues
Pollutant reduction
Safety
Virtualization of relationships

Dimensions	Variables	Authors
Economic	Reduced fare value; productivity and efficiency, financial savings.	Coelho, 2017Coelho, L. A. A., Silva, L. A. S., Andrade, M. O. A., & Maia, M. L. A. (2017). Perfil socioeconômico dos usuários da uber e fatores relevantes que influenciam a avaliação desse serviço no brasil. In 31º Congresso de Pesquisa e Ensino em Transporte da Anpet, Anais, Recife.; Filippas et al., 2020Filippas, A., Horton, J. J., & Zeckhauser, R. J. (2020). Owning, using, and renting: some simple economics of the sharing economy. Management Science, 66(9), 1-21. doi: https://doi.org/10.1287/mn sc.2019.3396 https://doi.org/https://doi.org/10.1287/... ; Benjaafar & Hu, 2020Benjaafar, S., & Hu, M. (2020). Operations management in the age of the sharing economy: What is old and what is new? Manufacturing and Service Operations Management, 22(1), 93-101. doi: https://doi.org/10.1287/msom.2019.0803 https://doi.org/https://doi.org/10.1287/...
Technological	Digital and interpersonal reliability; access to electronic devices and means of connection.	Zhu & Liu, 2020Zhu, X., & Liu, K. (2020). A systematic review and future directions of the sharing economy: business models, operational insights and environment-based utilities. Journal of Cleaner Production, 125209. doi: 10.1016/j.jclepro.2020.125209 https://doi.org/10.1016/j.jclepro.2020.1... ; Geissinger et al.,2020Geissinger, A., Laurell, C., Öberg, C., Sandström, C., & Suseno, Y. (2020). Assessing user perceptions of the interplay between the sharing, access, platform and community‐based economies. Information Technology & People, 33(3), 1037-1051. doi: 10.1108/itp-12-2019-0649 https://doi.org/10.1108/itp-12-2019-0649... ; Vaclavik et al., 2020Vaclavik, M. C., Macke, J., & Silva, D. F. (2020). ‘Do not talk to strangers’: a study on trust in Brazilian ridesharing apps. Technology in Society, 63, 2020. doi: https://doi.org/10.1016/j.techsoc.2020.101379 https://doi.org/https://doi.org/10.1016/... ; Barreto, et al., 2021Barreto, Y, Neto, R. M. S., & Carazza, L. (2021). Uber and traffic safety: evidence from Brazilian cities. Journal of Urban Economics, 123. doi: https://doi.org/10.1016/j.jue.2021.103347 https://doi.org/https://doi.org/10.1016/...
Environment	Less air pollution; reduced carbon emissions, less environmental degradation; fuel consumption.	Ertz & Leblanc-Proulx, 2018Ertz, M., & Leblanc-Proulx, S. (2018). Sustainability in the collaborative economy: A bibliometric analysis reveals emerging interest. Journal of Cleaner Production, 196,1073-1085. doi: 10.1016/j.jclepro.2018.06.095 https://doi.org/10.1016/j.jclepro.2018.0... ; Santos et al., 2019Santos, A. S., Nascimento, J. C. H. B., Rabelo Neto, A., & Barbosa, F. L. S. (2019). Determinantes da adesão aos serviços de mobilidade compartilhada: uma investigação empírica no contexto brasileiro. urbe. Revista Brasileira de Gestão Urbana, 11, e20190033. doi: https://doi.org/10.1590/2175-3369.011.e20190033 https://doi.org/https://doi.org/10.1590/... ; Curtis & Mont, 2020Mont, O., Palgan, Y. V., Bradley, K., & Zvolska, L. (2020). A decade of the sharing economy: Concepts, users, business and governance perspectives. Journal of Cleaner Production, 269, 122215. doi: 10.1016/j.jclepro.2020.122215 https://doi.org/10.1016/j.jclepro.2020.1... , Capaverde, et al., 2020Capaverde, C. B., Medeiros, I. B. D. O., Antonello, C. S., & Rodrigues, M. B. (2020). Subjectivities behind the wheel: transformations in work relations of drivers in Brazil. International Journal of Organizational Analysis, 29(1), 155-171. doi: https://doi.org/10.1108/IJOA-10-2019-1911 https://doi.org/https://doi.org/10.1108/...
Social	Social trust; generation of social relationships, perception of sharing, desire to share.	Zhu & Liu, 2020Zhu, X., & Liu, K. (2020). A systematic review and future directions of the sharing economy: business models, operational insights and environment-based utilities. Journal of Cleaner Production, 125209. doi: 10.1016/j.jclepro.2020.125209 https://doi.org/10.1016/j.jclepro.2020.1... ; Curtis & Mont, 2020Mont, O., Palgan, Y. V., Bradley, K., & Zvolska, L. (2020). A decade of the sharing economy: Concepts, users, business and governance perspectives. Journal of Cleaner Production, 269, 122215. doi: 10.1016/j.jclepro.2020.122215 https://doi.org/10.1016/j.jclepro.2020.1... , Barreto, 2021Barreto, Y, Neto, R. M. S., & Carazza, L. (2021). Uber and traffic safety: evidence from Brazilian cities. Journal of Urban Economics, 123. doi: https://doi.org/10.1016/j.jue.2021.103347 https://doi.org/https://doi.org/10.1016/...

Dimensions	Motivators
Cost	Reduced rate; Elimination of expenses.
Technological Convenience	Technological Availability; Data security.
Convenience of use	Time convenience; Travel security; Boarding convenience.
Usage experience	Socialization; Expectation of benefits; Absence of requirements
Environmental benefits	Vehicle reduction; Pollutant reduction
Social benefits	Valuing the professional; Generation of individual income

Dimension	Cronbach's alpha	Cronbach's alpha based on standardized items
Dimension	Cronbach's alpha	Total (own value)	% Variation
1	0.886	5.642	40.301
2	0.686	2.753	19.665
Total	0.949^a	8.395	59.966

Kaiser-Meyer-Olkin measure of sampling adequacy		0.891
Bartlett's sphericity test	Chi-square aprox.	34580,517
	df	91
	Sig.	0.000

Components	Initial eigenvalues			Extraction of sums from square loads			Rotating sums of square loads
	Total	% variation	% cumulative	Total	% variation	% cumulative	Total
1	5.642	40.301	40.301	5.642	40.301	40.301	4.371
2	2.753	19.665	59.966	2.753	19.665	59.966	3.404
3	1.419	10.139	70.105	1.419	10.139	70.105	1.711
4	1.164	8.315	78.420	1.164	8.315	78.420	1.494
5	0.645	4.607	83.026
6	0.430	3.074	86.100
7	0.378	2.699	88.799
8	0.342	2.440	91.239
9	0.314	2.244	93.484
10	0.294	2.103	95.587
11	0.213	1.521	97.108
12	0.185	1.319	98.427
13	0.116	0.830	99.257
14	0.104	0.743	100.000

	Factors
	1	2	3	4
Reduced Rate	0.875	--	--	--
Technological Availability	0.844	--	--	--
Expectation of Benefits	0.860	--	--	--
Time Convenience	--	0.774	--	--
Boarding Convenience	--	0.699	--	--
Data Security	--	0.701	--	--
Travel Safety	--	0.694	--	--
Elimination of Expenses	--	--	--	0.643
Socialization	--	--	--	0.615
Absence of Requirements	--	--	--	0.746
Pollutant Reduction	--	--	0.854	--
Reduction of Circulating Vehicles	--	--	0.863	--
Valuing the Professional	--	--	--	0.738
Generation of Individual Income	--	--	--	0.776

Models	Absolute adjustment measures				Incremental Adjustment Measures					Parsimony-Adjusted Measures
Models	X ²	RMSEA	RMR	GFI	AGFI	CFI	IFI Delta 2	TLI	NFI	PRATIO	PCFI	PNFI	AIC
Model 1	0.000	0.248	0.77	0.541	0.374	0.529	0.529	0.444	0.528	0.846	0.448	0.447	16397,499

Variables	Regression weights			Variances				Intercepts			Standardized regression weights		Multiple Square
Variables	Estimated	S.E.	C.R.	P	Estimated	S.E.	C.R.	P	Estimated	S.E.	C.R.	P
Travel Safety	1.109	0.033	33.516	***	0.312	0.009	35.224	***	3.433	0.023	173.554	***	0.615	0.378
Convenience Boarding	1.586	0.040	40.126	***	0.326	0.011	29.469	***	3.907	0.014	228.060	***	0.737	0. 543
Time Convenience	0.775	0.029	26.438	***	0.287	0.008	37.964	***	3.755	0.014	255.422	***	0.494	0.244
Expectation of Benefits	0.826	0.023	35.919	***	0.117	0.004	30.183	***	4.235	0.015	251.102	***	0.689	0.474
Technological Availability	0.932	0.022	43.236	***	0.091	0.003	28.415	***	4.392	0.017	244.401	***	0.773	0.597
Reduced Rate	1.000			***	0.083	0.003	26.039	***	4.222	0.015	243.281	***	0.806	0.649

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[1] FLV, Assistant Professor, Doctor in Environment and Regional Development, e-mail: fabio.violin@unesp.br