Agent-based modeling approach for evaluating underground logistics system benefits and long-term development in megacities - Wanjie Hu; Jianjun Dong; Jingfeng Yuan; Rui Ren; Zhilong Chen; Helan Cheng (Journal of Management Science and Engineering, 2022)
Mobility, pollution, and other barriers against sustainable goods movement are pushing local administrators to seek innovations in urban transportation infrastructure. The urban underground logistics system (ULS) has been recognized as a prospective alternative to realize large-scale automated freight distribution within and around megacities. This paper proposes an integrated approach combing system dynamics and agent-based modeling to evaluate the long-term development and operating status of a city-wide ULS project. The project boundaries regarding underground network expansion, stakeholders’ attributes, and social-environmental benefit metrics were structured as eight highly-interacted agent modules. Critical decision variables of agents in terms of supply-demand equilibrium, investment plan, pricing-to-market and willingness-to-pay were incorporated into three formulized subsystem models. From empirical perspective, the urban territory of Beijing, China, was taken as a case to simulate the development footprints of ULS project under different funding options and market acceptance degrees. Results show that ULS has significant competence with respect to service capacity and profitability, while enabling billions of dollars of external cost-saving annually. Moreover, the comprehensive performance of ULS project regarding economic incomes, benefits, market demand, and construction schedule can reach satisfactory trade-offs through adaptively adjusting the funding policies, incentives and pricing portfolios during project development.