City logistics involves movement of city goods in urban areas respecting the municipal and administrative guidelines. The key goals of city logistics planning are maximizing vehicle movement and utilization, while minimising vehicle emissions and traffic congestion. Collaboration is vital to managing city logistics operations efficiently. Collaboration can take place in the form of goods consolidation, sharing of resources, information sharing, and so on. Two categories of models are proposed to evaluate these collaboration strategies. At the macro level, we present the collaboration matrix model; and at the micro level, we present the operational level model. The macro-level model focuses on the strategic decision making process necessary for stakeholders' collaboration given the socio-cultural characteristics, economic, and environmental constraint factors, while the micro-level model applies the collaboration decision-making criteria derived from the macro-level analytic result to improve the activities of the city logistics operators. Results of the computational testing of our methodology on vehicle selection, goods to vehicle assignment, goods distribution and environmental impact assessment are discussed, showing that the collaboration strategies of stakeholders, if optimized, can improve city logistics operations. The proposed work is novel and has strong practical applicability for logistics planners and decision makers in planning right collaboration strategies for sustainable city logistics operations.

In response to current economic downturn coupled with intense global competition, the concept of supply chain collaboration has emerged as a possible solution for firms aiming to gain competitive advantage through cost reduction, increased asset utilization and improving service levels. In this chapter, the authors address the problem of collaboration planning between multiple retailers and/or suppliers in a supply chain network. Three problems are considered, namely partner selection, collaboration strategy selection, and profit allocation, among the partners entering into a collaboration. Three techniques, namely cluster analysis, analytical network process (ANP), and game theory, are used for this purpose. Partner selection for collaboration is done using cluster analysis and analytical network process (ANP) while collaboration strategy selection is made through the application of game theory. The profit allocation among collaborating partners is performed using Shapley method. A numerical application is provided.