Resumo

Big data and the arrival of Autonomous Vehicles (AVs) are revolutionizing both automotive and urban mobility industries. Antonialli et al. (2019) proposed four future scenarios of urban mobility business platforms in which AVs are considered as a transport mode aiming to enhance mobility in urban environments. In such contexts, the ownership and management of large datasets is inherent for creating new business models within urban mobility systems. Thereby, these features bring up the need of choosing proper governance mechanisms for data-based transportation systems and mobility platforms.

The research problem is given by the question: How can big data impact on governance structures in autonomous urban mobility platforms scenarios? Therefore, the study aims to characterize distinct types of governance models in different scenarios of autonomous urban mobility platforms considering the big data context. The research is justified since further research is needed regarding the contributions and characterization of the most appropriate governance mechanisms to analyze and enhance the usage of big data in mobility platforms (Veneeman et al., 2018).

Antonialli et al. (2019) proposed four future scenarios for urban mobility platforms where Autonomous Vehicles- AV’s are seen as one possible transport mode. Nevertheless, a common feature among all scenarios is the role played by data. According to Veeneman et al. (2018) for managing data-driven mobility platforms three main questions emerges: 1) what kind of data is relevant and could be valuable in a mobility data platform? 2) what types of actors generate and own that data? and 3) what kind of relations do these actors have with a platform manager that could drive the governance?

Based on a qualitative and exploratory research design, we initially gathered secondary data as a way of identifying 24 specific assets (tangible and intangible ones) for plotting the governance models for each scenario. We opted to take a single example for each scenario and extrapolate them to a future where AVs are seen as a transport mode. At last, the governance models were plotted and validated qualitatively with 12 mobility researchers and specialists in Brazil and France, linked to the use of secondary data in order to subsidize the discussions as well as to support the findings.

Scenarios C and A presented predominantly hierarchical governance structures, entailing higher operational costs. Scenarios B and D have a predominantly hybrid governance structures with higher transaction costs. Big data ownership delineates each scenario’s governance mechanisms. Common definitions and standard data formats are needed for the success of platforms and, issues related to data ownership and transparency shall not be neglected. Thus, blockchain along with smart contracts may benefit all scenarios, however, the hybrid-governance scenarios are likely to benefit the most from it.

Governance mechanisms are likely to be imperfect, however, the more sophisticated the governance is, more it will encourage the ecosystem’s stakeholders to take action. Thus, governance modes must be adjusted according to: future mobility scenarios, new user behaviors, conflicts and risks, which would allow the whole ecosystem to be more flexible. Therefore, within big data contexts, complex platform structures bring up the need for more sophisticated governance structures. At last, large amounts of data are likely to bring up the need for more efficient and complex governance structures.

Antonialli, F., Gandia, R. M., Sugano, J. Y., Nicolaï, I., Miranda Neto, A. (2019). Business Platforms for Autonomous Vehicles within Urban Mobility. Proceedings of the 25th International Conference on Urban Transport and the Environment, Aveiro, Portugal, 25. Veeneman, W., Van der Voort, H., Hirschhorn, F., Steenhuisen, B., & Klievink, B. (2018). PETRA: Governance as a key success factor for big data solutions in mobility. Research in Transportation Economics, Advance online publication.