Collaborative Consumption in Peer-to-Peer Car Sharing: Models, Analysis, and Experiments

Principal Investigator(s):

Saifallah Benjaafar, Former Professor, Industrial and Systems Engineering

Project summary:

Collaborative consumption raises several important questions. How does collaborative consumption affect ownership and usage of resources? Is it necessarily the case that collaborative consumption leads to greater sustainability (i.e., leads to lower ownership, lower usage, or both)? Who benefits most from collaborative consumption: those who own, those who rent, or the platform that matches owners and renters? How would the platform set prices, commissions, and membership fees, and under what conditions would choices for these parameters lead to socially desirable outcomes? Are there social and behavioral factors that affect the extent to which owners would be willing to rent and renters would be willing to forego ownership (e.g., moral hazard because renters may not be as careful with the product they rent as they would with a product they own, or information asymmetry because renters may not know the true quality of the product before renting it)? To what extent would online, two-way reputation systems induce greater collaborative consumption and who profits most? Are there public policies that, if enacted, would ensure that collaborative consumption would lead to higher social welfare?

In this research project, the plan is to address the above and other related questions. Researchers are using peer-to-peer car sharing as a primary application. However, it is expected that the models, analysis, and results apply more broadly to other forms of resource sharing. Outcomes from the research will include:

  1. 1) models to analyze collaborative consumption at varying scales,
  2. 2) analysis and managerial insights regarding the impact of collaborative consumption on ownership, usage, the surplus of renters and owners, and social welfare (including impact on the environment),
  3. 3) decision-support tools for platforms regarding the optimal choice of rental prices, commissions, and membership fees,
  4. 4) public policy recommendations for governments regarding how best to regulate collaborative consumption to ensure that total welfare is enhanced,
  5. 5) insights from behavioral study regarding decision-making biases that may affect the outcomes of collaborative consumption, and
  6. 6) a series of case studies to validate the study's models and analysis using parameter values calibrated based on actual data from multiple regions in the U.S. and internationally.

The research is multi-disciplinary and draws on methods from transportation science, economics, game theory, operations research, and the behavioral sciences. Moreover, the research combines analytical modeling, behavioral studies and empirical analysis.

Project details: