The cost elements are primarily influenced by:

- **Asset type:** Vehicle type, condition and fuel‐efficiency.

- **Utilization:** Load factor, workdays per year, kilometers per year, driver hours and other labor regulation

- **Nature of trip:** Long‐haul or short haul, road condition, altitude and terrain.

- **Financing terms:** Interest rate, depreciation parameters.

Data regarding the cost elements and their drivers were sourced from multiple industry reports and workshops with organized trucking bodies in Delhi and Kolkata.

Adding a transport cost layer to the India FDM enables robust cost‐benefit modeling of various scenarios investigated to improve the performance of the Eastern Corridor. (This could be expanded to total logistics costs in future revisions of the model.)

# **<u>Final Model Parameters</u>**

The resulting parameters of the India FDM are:

- Freight flows between 672 geographical areas: 637 districts within India, 30 of India’s ports and 5 neighboring countries (Bangladesh, Bhutan, Myanmar, Nepal and Pakistan);

- For 31 commodity groups grouped into 8 cargo types

- On the three inland modes (road, rail and IWT), as well as crude oil in pipelines;

- Aggregated per typology namely corridor and rural freight;

- Identifying mode suitability for rail‐friendly freight and waterway‐friendly freight; and

- Adding actual railway and waterway transport costs and estimating costs for nine road cost drivers to enable cost‐benefit analysis.

The result of this process is a database of about 4 million unique freight flows, to which transport costs of known flows are added and estimated for modeled flows. Each unique flow specifies how many tonnes of a specific commodity were transported between a specific origin‐destination district pair during a year and on which mode (road/rail). Each record further differentiates whether this was domestic, import or export freight and calculates the tonne‐km associated with that freight flow.

The modeling framework and outputs of the India FDM addresses the unique characteristics and requirements of freight demand modeling, discussed in the literature survey as follows:

- The heterogeneity of freight transport is addressed through commodity and spatial disaggregation and allows for policy‐relevant conclusions for specific industries and geographical areas;

- Mapping the national freight flow landscape while enabling mesoscopic applications (due to the level of disaggregation), aids prioritization towards collaborative long‐term goals, aiding the diversity of stakeholders to align conflicting requirements;

- The linkages between freight transport, the broader economy and final consumption  studied through the development of disaggregated supply and demand tables;

- The challenges with the conversion of trade data in monetary terms to trade volumes  largely circumvented through developing the bottom‐up supply and demand tables in volume terms from all available sources;

- The choice of vehicle type is included in the transport cost model to account for cost sensitivities and the requirements of specific commodity groups;

- The modal interaction between rail, road and waterways is a core component of the model;

- The regionalization of supply and demand is facilitated through the development of disaggregated supply and demand tables commencing from the most granular spatial disaggregation at which

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