Concept note · Research & mobility

Demand-driven supply activation system

Système d'activation de l'offre piloté par la demande

01The thin-market problem

In a two-sided carpooling market, matching efficiency depends on compatible offers and requests coexisting at the same time. When drivers do not know where and when demand concentrates, they hesitate to publish. Passengers, in turn, find few relevant offers. The market stays thin: few actors present simultaneously, low density of feasible matches.

This vicious cycle is not primarily a matching-algorithm problem. It is an information and incentive problem: without a credible demand signal, potential supply often remains inactive.

02Proposed approach

Our approach places demand at the start of the activation chain. Passengers first publish trip requests. The platform then measures those requests-spatially and temporally-to reveal corridors where needs aggregate.

Those measures are presented to drivers as strategic information: real demand exists for certain trips at certain times. Drivers then decide, fully autonomously, whether to publish an offer that responds to observed needs.

The platform never creates trips itself. It never forces publication. It simply turns expressed needs into actionable information that can activate latent supply already present in the mobility system (drivers who already travel but do not publish).

03Conceptual framework

The concept sits at the intersection of several research domains: market design, two-sided platforms, demand-responsive transport, and information systems. Four structuring notions underpin it.

Market Thickening

Épaississement du marché

A market becomes more efficient when more offers and requests coexist simultaneously-what market-design literature often calls a “thick” market.

By stimulating offers precisely where real demand is observed, the proposed approach aims to thicken the market locally: more compatible participants present at the right place and time, and therefore more matching opportunities.

Demand Signaling

Signalisation de la demande

Once aggregated, individual requests become economic signals. They reduce drivers’ uncertainty by making visible information that would otherwise remain fragmented or inaccessible.

  • where people want to travel;
  • at what times;
  • with what relative frequency.

Latent Supply Activation

Activation de l'offre latente

Many drivers already make trips without publishing them on a platform. That supply exists in the physical world but remains invisible to the digital market.

The proposed system does not create new trips from nothing. It reveals demand that may interest those drivers, raising the probability that they turn a travel intention into a published offer.

Reducing Information Asymmetry

Réduction de l'asymétrie d'information

In many two-sided markets, one side often lacks reliable knowledge of the other side’s conditions. In carpooling, drivers generally do not know where demand is-or how intense it is.

By making demand visible as an aggregated signal, the system reduces that asymmetry. Offer-publishing decisions become better informed, without constraining driver behavior.

04Reducing unnecessary travel

Réduction des déplacements inutiles

When the system knows where both individuals are - their origins and destinations - it becomes possible to reduce unnecessary travel associated with carpooling.

Unlike meeting at a fixed place (one person’s home, the other’s destination, or an arbitrary point), the meetup location is not predetermined. It is calculated to minimize total detour, taking each person’s respective paths into account.

This spatial optimization helps make ride sharing more acceptable for drivers and passengers alike: fewer kilometres travelled “for nothing,” better efficiency of the shared trip, and a smoother experience once supply and demand meet.

05Paradigm comparison

The essential difference is not the final match, but the order in which information flows and supply appears.

Traditional platform

  1. Driver → publishes an offer
  2. Passenger searches
  3. Matching

Proposed system

  1. Passenger → publishes a request
  2. Platform measures demand
  3. Drivers see real needs
  4. Drivers choose to publish an offer
  5. Matching
CriterionTraditionalProposed
Initial sequenceSupply firstDemand first
Platform roleBroadcast and match existing offersMeasure demand and expose it as a signal
Trip creationInitiated by the driver, often without a demand signalStill initiated by the driver, after observing demand
Available informationDemand often opaque to driversCorridors and demand intensity made visible
Driver autonomyFree to publishFree to publish - the platform imposes no trip

06Expected effects

Based on principles established in the literature on two-sided markets, market design, and demand-responsive transport, several potential benefits can be anticipated. These effects are presented as theoretical expectations-not as empirical results demonstrated by our platform alone.

  • 01higher matching rates, through local densification of offers where demand is observed;
  • 02fewer empty seats on published trips, if more offers respond to real needs;
  • 03shorter delay before a compatible offer appears;
  • 04better use of vehicles already on the road;
  • 05better knowledge of travel corridors;
  • 06increased market density (market thickness);
  • 07greater overall efficiency of the carpooling system.

These benefits remain contingent on context, adoption, and signal quality. They are research and market-engineering hypotheses, not operational guarantees.

07Scientific references

  1. 01

    Agatz, N., Erera, A., Savelsbergh, M., & Wang, X. (2012). Optimization for dynamic ride-sharing: A review. European Journal of Operational Research, 223(2), 295–303. https://doi.org/10.1016/j.ejor.2012.05.028

  2. 02

    Akerlof, G. A. (1970). The market for “lemons”: Quality uncertainty and the market mechanism. The Quarterly Journal of Economics, 84(3), 488–500. https://doi.org/10.2307/1879431

  3. 03

    Armstrong, M. (2006). Competition in two-sided markets. The RAND Journal of Economics, 37(3), 668–691. https://doi.org/10.1111/j.1756-2171.2006.tb00037.x

  4. 04

    Mageean, J., & Nelson, J. D. (2003). The evaluation of demand responsive transport services in Europe. Journal of Transport Geography, 11(4), 255–270. https://doi.org/10.1016/S0966-6923(03)00026-7

  5. 05

    Rochet, J.-C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990–1029. https://doi.org/10.1162/154247603322493212

  6. 06

    Roth, A. E. (2008). What have we learned from market design? The Economic Journal, 118(527), 285–310. https://doi.org/10.1111/j.1468-0297.2007.02121.x

  7. 07

    Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. https://doi.org/10.2307/1882010

  8. 08

    Tafreshian, A., Masoud, N., & Yin, Y. (2020). Frontiers in service science: Ride matching for peer-to-peer ride sharing: A review and future directions. Service Science, 12(2–3), 44–60. https://doi.org/10.1287/serv.2020.0258