Planning, designing and conducting establishment-based freight surveys: A synthesis of the literature, case-study examples and recommendations for best practices in future surveys

The state-of-practice in planning, designing, and conducting freight surveys leave much to be desired, even in the era of big data analytics. This paper addresses this issue by providing a comprehensive, yet, inexpensive integrated data collection framework for conducting establishment-based freight survey (EBFS). The paper demonstrates the application of the proposed framework by implementing it in eight cities across two geographically dissimilar states of India. This is the first freight survey of its kind in terms of scale and scope in developing countries, where there is no established practice in freight data collection. Guidelines are suggested for overcoming challenges in EBFS such as: (a) efficient allocation of survey resources within budgetary constraints; (b) effective survey instrument design for reducing the respondent burden; (c) determination of sample size requirements and the expected number of sampling units to be contacted (d) development of sampling strategies using sampling frames with limited auxiliary information; and (e) data collection strategies to improve response rates. The heuristics for allocation of survey resources are mathematically formulated and predicted using the web-based survey responses obtained from planners of past surveys. Trade-off scenarios between different components of survey resources (money, time, and manpower) are presented to enable the planners to arrive at a suitable EBFS design for meeting research requirements within resource constraints. Analysis of results suggest that the response rates for EBFS are largely linked to the physical characteristics of commodities and city demography. The discussions provided on resource allocation, survey instrument design, sampling design, pilot surveys, interviewer training, response rate improvement strategies, and data processing are expected to guide for best practices in future surveys. In sum, the literature synthesis, case-study illustrations, and the proposed framework for EBFS design are expected to strengthen the state-of-practice of EBFS by making the rigorous random sample surveys less expensive, more systematic, and in turn, replacing the need to opt for convenience samples.