National freight demand modelling: a tool for macrologistics management

Abstract

Purpose The purpose of this paper is to present the results of South Africa’s national freight demand model and related logistics cost models, and to illustrate the application of the modelling outputs to inform macrologistics policy. Design/methodology/approach Spatially and sectorally disaggregated supply and demand data are developed using the input-output (I-O) model of the economy as a platform, augmented by actual data. Supply and demand interaction is translated into freight flows via a gravity model. The logistics costs model is a bottom-up aggregation of logistics-related costs for these freight flows. Findings South Africa’s logistics costs are higher than in developed countries. Road freight volumes constitute 80 per cent of long-distance corridor freight, while road transport contributes more than 80 per cent to the country’s transport costs. These challenges raise concerns regarding the competitiveness of international trade, as well as the impact of transport externalities. The case studies highlight that domestic logistics costs are the biggest cost contributor to international trade logistics costs and can be reduced through inter alia modal shift. Modal shift can be induced through the internalisation of freight externality costs. Results show that externality cost internalisation can eradicate the societal cost of freight transport in South Africa without increasing macroeconomic freight costs. Research limitations/implications Systematic spatially disaggregated commodity-level data are limited. There is however a wealth of supply, demand and freight flow information collected by the public and private sector. Initiatives to create an appreciation of the intrinsic value of such information and to leverage data sources will improve freight demand modelling in emerging economies. Originality/value A spatially and sectorally disaggregated national freight demand model, and related logistics costs models, utilising actual and modelled data, balanced via the national I-O model, provides opportunities for increased accuracy of outputs and diverse application possibilities.

The macrologistics effect of a state-owned enterprise, Transnet, on the South African economy

“…Furthermore, the 'agriculture' segment includes rural interchanges, which are flows between farming areas that are low density and seasonal. The development of freight flow segmentation is based on research conducted to determine all flows in South Africa and categorise these to enable macrologistics planning (Havenga 2012;Havenga & Simpson 2018b).…”

“…The freight demand data are provided by GAIN Group's South African Freight Demand Model, which estimates sectorally disaggregated supply (production and imports) and demand (intermediate domestic demand, final domestic demand and exports) of commodities in predefined geographical areas, the aggregate of which reflects total supply and demand for South Africa. A more technical description of the model is published in studies by Havenga (2007:160-179), Havenga (2013), Havenga and Simpson (2018b) and Havenga et al (2020:138-172).…”

Analysis of Factors Affecting Freight Demand Based on Input-Output Model

“…Rey [64] discussed the application of econometrics in the inputoutput table model and studied the alternative methods and models of the input-output model. Havenga and Simpson [65] used an economic input-output (I-O) model as a platform, supplemented by actual data, developed supply and demand data classified by space and sector, and converted the supply and demand of South African freight into a freight flow through a gravity model. e above literature has conducted a lot of research on the application of inputoutput models from the perspective of theory and practice and provided theoretical and methodological support for the research of this paper.…”

Macrologistic performance and logistics commitments in sales contracts in international supply chains

“…A rich body of empirical research confirms that efficient infrastructure and trade logistics are positively linked to export performance, thus benefitting individual traders and the economy's balance of trade (World Bank, 2018). However, low macrologistic performance may be a challenge in terms of increased logistics and total delivery costs in low- and medium-performing countries (Havenga and Simpson, 2018; Lorentz et al , 2015). Indeed, underdeveloped transport infrastructure might create barriers even in cross-border business cooperation among neighbouring countries (Setnikar Cankar et al , 2014).…”