Diffusion of Innovation in Technological Platforms: The Uber Case
| Autor | Wilquer Silvano de Souza Ferreira/Glaucia Maria Vasconcellos Vale/Victor Silva Corrêa |
https://bar.anpad.org.br
BAR − Brazilian Administration Review
Vol. 19, No. 3, Art. 3, e210101, 2022
https://doi.org/10.1590/1807-7692bar2022210101
Research Article
Diffusion of Innovation in Technological Platforms:
The Uber Case
Wilquer Silvano de Souza Ferreira1
Glaucia Maria Vasconcellos Vale1
Victor Silva Corrêa2
1 Pontifícia Universidade Católica de Minas Gerais, Belo Horizonte, MG, Brazil
2 Universidade Paulista, São Paulo, SP, Brazil
Received October 13, 2021. This paper was with the authors for one revision. Accepted June 04, 2022.
First published online July 07, 2022.
Editor-in-Chief: Ivan Lapuente Garrido (Universidade do Vale do Rio dos Sinos, Brazil).
Associate Editor: Victor Rafael R. Celestino (Universidade de Brasília, Brazil).
Reviewers: Vitor Koki da Costa Nogami (Universidade Estadual de Maringá, Brazil), Verônica Angélica Freitas
de Paula (Universidade Federal de Uberlândia, Brazil) and two anonymous reviewers.
Editorial assistants: Kler Godoy and Simone Rafael (ANPAD, Maringá, Brazil).
W. S. de S. Ferreira, G. M. V. Vale, V. S. Corrêa 2
ABSTRACT
Objective: diffusion theory suggests that customers adopt innovation. However, no research has examined
the differences between peers and the balance required of a peer-to-peer platform in the diffusion process.
This article investigates whether there was a peer-to-peer balance in the diffusion process of a technological
platform, represented here by the Uber case. Methods: a total of 843 Uber users, comprising 397 drivers
and 446 customers, took part in a probabilistic sample survey in Belo Horizonte, Brazil. The study tests
the hypothesis of P2P platform diffusion balance along Rogers’ curve with Levene’s and t-test. Results:
the findings are counterintuitive and unexpected. Although the authors expected passengers and drivers
to show a similar predisposition for Uber’s adoption, empirical data did not confirm this. In contrast to
the literature, which predicts that adoption occurs mainly in the initial phases, drivers’ predisposition
showed a constant diffusion curve. Conclusions: considering the peer-to-peer platform context, this article
shows that the balance between peers can still be present considering the multiple actors involved, which
shows a proposition for this research. Besides, this article develops the ‘technological readiness indicator,’
thus enabling a better understanding of different empirical contexts.
Keywords: technological platforms; peer-to-peer; Uber; Brazil.
JEL Code: O33, Q55.
Diffusion of innovation in technological platforms: The Uber case 3
INTRODUCTION
Diffusion, defined as the transmitting process of a given innovation or novelty to a given group
or social system, is an essential part of any successful innovation (Ali, Raza, Puah, & Amin, 2019;
Bhardwaj, 2020; Hadengue, Marcellis-Warin, & Warin, 2017; Zvolska, Palgan, & Mont, 2019).
“Diffusion is a process where innovation is communicated to the social system” (Ali et al., 2019,
p. 624). This process takes place over time through various channels. It usually occurs from
person to person through the influencing and convincing capacity that early adopters have on
people close to them. This ability to convince people leads others to adopt these novelties,
replacing previous practices and procedures (Rogers, 1962; 2003). In other words, when an
innovation appears and spreads, the number of adopters increases, the user experiences
accumulate, and the risks of adoption tend to decrease, which results in an increase in diffusion
(Bhardwaj, 2020; Dedehayir, Ortt, Riverola, & Miralles, 2017). Several technological platforms
are spreading rapidly as a result of diffusion, including Uber.
The platform appeared in 2009 in San Francisco, California, and has since changed the transport
market’s functioning, affected urban mobility, and even how people report and use the available
resources (Azevedo, Pongeluppe, Morgulis, & Ito, 2015; Barbour & Luiz, 2019). For example,
“the Uber network is now available in 475 cities in 75 countries” (Barbour & Luiz, 2019, p. 38).
For Uber and other consumer platforms based on ‘peer-to-peer’ systems, i.e., platforms that
directly connect people who transact with each other, the diffusion process seeks a balance
between tradeoffs and implies the winning over of two types of adopters or users: the end
consumers (passengers); and the service providers (drivers). This characteristic makes the
diffusion of this kind of innovation more complex (Matzler, Veider, & Kathan, 2015). The
greatest challenge for peer-to-peer technological platforms is the necessity of designing
intermediation systems capable of integrating organic and economically independent entities (Pu
& Pathranarakul, 2019). For Chen, Yang, and Liu (2004), if suppliers’ and clients’ needs are not
balanced, the system will become unbalanced and eventually collapse.
There is already comprehensive literature on the diffusion of innovation focusing on adopting
novel technologies (Currie & Spyridonidis, 2019; Lai 2017; Marques, Lontra, Wanke, &
Antunes, 2021). However, such literature has been limited to the adoption of novel technologies
only by consumers and focuses on describing the variables involved in user adoption (Cheng,
2016; Chu & Chen, 2016; Marangunić & Granić, 2015; Rahman, Lesch, Horrey, &
Strawderman, 2017; Rondan-Cataluña, Arenas-Gaitán, & Ramírez-Correa, 2015; Scherer,
Siddiq, & Tondeur, 2019; Williams, Rana, & Dwivedi, 2015). Although still incipient, there is
also some literature on the specific field of diffusion in novel technologies and technological
platforms, including Uber (Borowiak & Ji, 2019; Geissinger, Laurell, & Sandström, 2020; Guda
& Subramanian, 2019; Hall & Krueger, 2018; Laurell & Sandström, 2016; Min, So, & Jeong,
2019; Peticca-Harris, Gama, & Ravishankar, 2020; Shokoohyar, Sobhani, & Nargesi, 2020).
However, these studies have disregarded the diffusion curve focusing on the peer-to-peer
technological platforms process, its different user technological readiness in each phase of the
process, and how the P2P balance, necessary for platform diffusion (Bresnahan & Greenstein,
2014; Matzler et al., 2015), occurs along the diffusion process, which are topics that will be
discussed in the present paper. Recently, some scholars have emphasized the need for practical
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