Crowdshipping platforms thrive on speed and efficiency, but sustaining a reliable workforce requires one other ingredient: fairness.

Prof. Abhay Sobhanan, Decision Sciences area, unpacks findings from his latest research on equitable workload allocation in last-mile delivery. The paper ‘Equity-Driven Workload Allocation for Crowdsourced Last-Mile Delivery’ co-authored by Prof. Abhay, Dr. Hadi Charkhgard, University of South Florida, and Dr. Iman Dayarian, University of Alabama, examines how companies can use data-driven decision-making to strike a better balance and distribute work more fairly without significantly compromising efficiency.

The findings suggest that a modest increase in operational costs can significantly improve fairness and offer a practical path for companies looking to build stronger, more resilient gig-worker networks.

#IIMB #ReseachPublication #DecisionSciences #Crowdshipping #FairPay #WorkloadAllocation