Conceptualizing freight generation for transport and land use planning: A review and synthesis of the literature. (February 2019) - McLeod, Sam; Schapper, Jake H.M.; Curtis, Carey; Graham, Giles
Abstract: Freight generation and movement patterns are not well understood by planners and policy-makers tasked with making complex strategic land use and transport planning decisions. In the absence of detailed planning evidence, they may rely on scant or anecdotal data, extrapolated and presented through complex quantitative models. Unfortunately, predictive model outputs can fail to accurately match observed outcomes, and such models cannot predict complex long-term phenomena which may transformatively disrupt freight production and movement patterns. Through a review of the literature, we apply Porter's Diamond Model of Competitive Advantage (Porter 1990) to develop a novel conceptual framework for freight generation. We illustrate how emerging themes and new evidence of relevant economic, environmental, social, and governmental factors can be meaningfully structured within this conceptual framework. By compiling recent evidence of spatio-temporal complexity from the literature, we highlight the utility of such a framework in assisting planners and decision-makers to incorporate a wider set of freight generation factors – particularly demand factors, land use relocation effects, shifting firm strategies, and emerging transport technologies – in the practices of understanding, modeling, planning, and managing urban freight. Application of the framework should assist in ensuring that significant factors and phenomena are not ignored in critical planning decisions, encourage the input of a more diverse set of planning expertise at the policy-making table, and throw renewed emphasis on potential qualitative and mixed-methods freight case study research. Highlights: Existing freight transport models may not effectively support urban land use planning. Freight generation is influenced by a magnitude of complex factors. A conceptual framework for structuring knowledge about freight is proposed. This framework may complement and improve the use of modeling in decision-making.