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There is a growing interest in incorporating spatial indicators into freight demand model systems. The indicators are measured for different areal units (e.g., census tracts or block groups) and are often used as proxy variables or aggregation layers. Model estimation results vary according to the choice of these areal units and an analyst is thus confronted with a popular decision challenge termed as 'modifiable areal unit problem' (MAUP). The variability in results due to MAUP arises since areal units can be modified in theoretically infinite ways (in terms of shape, orientation and size) and magnitude of aggregation loss in information will vary for each alternative zoning system. In effect, how well the zonal (aggregated) characteristics can describe the establishment-level (disaggregated) observations is inversely related to MAUP effects. Little is known, however, about the extent of MAUP effects in freight generation (FG) models and freight trip generation (FTG) models. This study diagnoses the implications of MAUP effects in FG and FTG models by designing alternate zoning systems (by means of different zonal variables and clustering techniques) and assessing the sensitivity of model estimation results within a framework of comparative analysis (by means of hierarchical linear models). Study results assess the presence of MAUP as alternate zoning systems resulted in wide variation in the estimated coefficients for zonal characteristics (e.g., industrial area, land value, number of establishments, distance to primary arterial) in terms of magnitude, statistical significance, and even in the direction of association (sign of the coefficient). The implication of this finding is that an analyst may design different or even counterproductive policy instruments based on the way data is aggregated to capture the role of land-use, spatial effects and built-environment in influencing freight travel patterns. MAUP effects are also found to be dependent on the metric in which freight is measured (i.e., FG or FTG) and direction in which flow is measured (i.e., production or attraction). Overall, this research improves the understanding of the parameter sensitivity and performance sensitivity of freight demand model systems to alternative spatial representations of an establishment's relative location. The research findings strongly encourage analysts to acknowledge that the results of freight travel analyses with spatial indicators are sensitive to the definition of areal units. • A novel attempt to examine the potential impacts of MAUP in measurement of FG/FTG patterns • A methodology is proposed to compare different zoning systems for developing FG/FTG models • Effects of zonal characteristics on disaggregated freight travel (FG/FTG patterns) are explored • Research findings offer insights for spatial data aggregation in freight demand model systems • Results reveal that freight travel analyses with spatial indicators are sensitive to the definition of areal units [ABSTRACT FROM AUTHOR]

This paper contributes to the emerging literature on freight studies by identifying the optimal freight traffic analysis zone (FTAZ) system at which to conduct macro-level freight travel analysis. To arrive at the optimal scale, we develop alternate zone systems by grouping census wards with similar freight-related characteristics (industrial characteristics, commercial land use characteristics, locational characteristics and socio-demographic characteristics). The resultant zone systems are analysed at multiple geographic scales and the optimal scale of each zone system is determined by performing the Brown–Forsythe test. Results suggest that a 1:3 aggregation ratio (24–28 zones) is the optimal scale for Metropolitan FTAZs, whereas the publicly available ad-hoc zone system and prior literature on National FTAZs follow 1:10 aggregation. The study findings suggest that Metropolitan planning organizations need to reconsider their existing data collection strategy, consider a larger aggregation ratio and, by extension, adopt smaller zones to ensure that both local and global freight travel characteristics are captured in freight travel analyses. [ABSTRACT FROM AUTHOR]

This paper contributes to the existing research on freight transportation, spatial and land use planning by investigating an improved spatial aggregation technique to delineate desirable freight traffic analysis zones. Zoning is a process of spatially aggregating several predefined basic spatial units (BSUs) into multiple zones. It plays a vital role in the transportation planning and decision-making process and is well-documented as the modifiable areal unit problem (MAUP). MAUP involves aggregating BSUs to obtain optimal zones satisfying specific criteria and constraints. This paper proposes an improved spatial aggregation methodology to develop a freight traffic analysis zone system by applying the multiobjective optimization concept using a genetic algorithm. The decision variables, namely, (i) Freight trip density; (ii) Number of establishments; (iii) Employment density; and (iv) Compactness, are chosen to represent the elements of freight, passenger traffic, and land use. The problem is formulated as a multiobjective network partitioning problem. The four objectives aim to create zones with better homogeneity and compactness. It is solved using a genetic algorithm with a weighted distance metric approach to prioritize the four objectives. Results show that zones resulting from the improved methodology are superior to the existing zones in terms of homogeneity of decision variables and compactness. The findings are expected to help the decision-making process of urban, transportation, and land-use planners in selecting appropriate freight traffic zone delineation strategies for a given region. • Multiobjective optimization concept is applied to develop freight traffic analysis zones (FTAZ) • Decision variables represent the characteristics of freight, passenger traffic, and land use. • Weighted distance metric approach using a genetic algorithm is used to prioritize zoning objectives • Findings suggest that FTAZs are superior to existing zones in homogeneity and compactness [ABSTRACT FROM AUTHOR]