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PurposeThe purpose of this research is to gain a better understanding of how a crowd-shipping platform can achieve a critical mass of senders and carrier crowd members to yield network effects that are necessary for the platform to grow and thrive. Specifically, this research studies the participation decisions of both senders and carriers over time and the impacts of the resulting feedback loop on platform growth and performance.Design/methodology/approachAn agent-based model is developed and used to study dynamic behavior and network effects within a simulated crowd-shipping platform. The model allows both carriers and senders to be represented as autonomous, heterogeneous and adaptive agents, whose decisions to participate in the platform impact the participation of other agents over time. Survey data inform the logic governing agent decisions and behaviors.FindingsThe feedback loop created by individual sender and carrier agents' participation decisions generates complex and dynamic network effects that are observable at the platform level. Experimental results demonstrate the importance of having sufficient crowd carriers available when the platform is initially launched, as well as ensuring that sender and carrier participation remains balanced as the platform grows over time.Research limitations/implicationsThe model successfully demonstrates the power of agent-based modeling (ABM) in analyzing network effects in crowd-shipping systems. However, the model has not yet been fully validated with data from a real-world crowd-shipping platform. Furthermore, the model's geographic scope is limited to a single census tract. Platform behavior will likely differ across geographic regions, with varying demographics and sender/carrier density.Practical implicationsThe modeling approach can be used to provide the manager of a volunteer-based crowd-shipping program for food rescue with insights on how to achieve a critical mass of participants, with an appropriate balance between the number of restaurant food donation delivery requests and the number of crowd-shippers available and willing to make those deliveries.Social implicationsThis research can help a crowd-shipping platform for urban food rescue to grow and become self-sustainable, thereby serving more food-insecure people.Originality/valueThe model represents both senders and the carrier crowd as autonomous, heterogeneous and adaptive agents, such that network effects resulting from their interactions can emerge and be observed over time. The model was designed to study a volunteer crowd-shipping platform for food rescue, with participant motivations driven by personal values and social factors, rather than monetary incentives.

Crowd-shipping platforms have the potential to serve as flexible and low-cost logistics solutions for small and medium-sized enterprises (SMEs), which tend to have proportionally higher logistics costs than large companies. By increasing visibility and access to underutilized vehicle capacity, crowd-shipping platforms can offer lower rates than traditional delivery services. Leveraging excess capacity on premeditated delivery trips can also improve logistics efficiency and reduce emissions. However, high platform fees, insufficient carriers, and difficulty finding suitable platforms are common barriers to widespread adoption. This research evaluates the degree to which existing commercial crowd-shipping platforms can provide suitable transportation solutions for SMEs. A systematic search yielded 400 platforms, which were evaluated for SME suitability by requesting quotes for delivery service from each platform, based on typical shipping requirements of two agriculture-based SMEs in Texas. The responses and quotes that were received, as well as feedback from the case study SMEs, indicate that most existing platforms are unlikely to meet the needs of SME shippers. The results suggest ways in which crowd-shipping platform managers could take advantage of this market opportunity by tailoring the services and features of their platforms to better meet the expectations of SMEs.

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