Efficiency and reliability in (city) logistics and supply chain planning is key to remain competitive and improve sustainability. The objective of this project is to research, build and test (in practice) advanced decision support systems for both multi-channel (retail, detail and e-tail) and multi-company collaboration. The starting point of our multi-channel and multi-company decision support systems involves connectivity, allowing data to be exchanged, shared and connected. Once connectivity is in place, intelligence needs to be built in order to make use of these comprehensive data sources. An information sharing platform will be developed which encapsulates information about the different processes, external factors (e.g. weather, vacation, etc.) and uses that information to provide effective decisions support services to its users. Specifically, adequate, timely and accurate information, based on various data sources is required. This could be (real‐time) information aggregated from multiple sources, including (cooperative) devices, such as transportation infrastructure sensors, but of course also the various information systems from the logistics service providers, shippers etc. The decision support systems to be developed will focus on collaboration. In the different distribution channels companies can benefit a lot from cooperation. Think of using the Retail network to position trailers close to cities, from which Detail and E-tail distribution could be handled. As such, the Retail network brings value for Detail and E-tail distribution. In Detail and E-tail networks, large consolidated volumes need to be transported, for which the Retail network could be used.

Contributing to the development of smart cities/regions, this research program will execute, as a co-production between universities and professional organizations, a series of integrated academic and applied projects that will deliver (1) a novel model system to predict the demand for hybrid public transport systems, involving demand responsive transport services that are flexible in route and schedule and (self-)organized through ICT platforms, (ii) advanced models for the optimal design of such systems and the simulation of their performance, (iii) an evaluation framework addressing institutional and organizational aspects of implementing such innovations, (iv) a series of pilot and showcase that are co-developed with non-academic members of the consortium, and (v) networking with key international academic and professional networks to discuss strategies and solutions. The demand model system will be founded flexible computer-assisted scheduling of activities and associated travel, supported by mobile ICT platforms. The response to such highly flexible demand will be unconventional transport mode chains. Intelligent demand forecasts will serve as input for the models that optimize the design of such systems, based on a simulation of their performance, co-processing individual demand and aggregate organization of supply. Governance and institutional aspects, influencing successful implementation of innovative transport systems and services will be addressed using a game theoretic framework and an adaptive planning approach. The project will develop contours of future demand-driven transport in smart cities/regions, and the key concepts, design principles and decision tools considering the roles and needs of the various stakeholders, considering the trend of a sharing economy.