Original Research

Use of causal loop diagrams to assess future drivers and trends in South African transport

Frederik C. Rust, Leslie R. Sampson, Adriana A. Cachia, Benoit M. Verhaeghe, Helena S. Fourie, Michelle A. Smit
Journal of Transport and Supply Chain Management | Vol 17 | a958 | DOI: https://doi.org/10.4102/jtscm.v17i0.958 | © 2023 Frederik C. Rust, Leslie R. Sampson, Adriana A. Cachia, Benoit M. Verhaeghe, Helena S. Fourie, Michelle A. Smit | This work is licensed under CC Attribution 4.0
Submitted: 26 May 2023 | Published: 27 November 2023

About the author(s)

Frederik C. Rust, PERC (Pty) Ltd, Hermanus, South Africa
Leslie R. Sampson, Sampson Consulting, Pretoria, South Africa
Adriana A. Cachia, Adelle Cachia Consulting, Pretoria, South Africa
Benoit M. Verhaeghe, Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa
Helena S. Fourie, The South African National Roads Agency SOC Ltd (SANRAL), Pretoria, South Africa
Michelle A. Smit, Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa

Abstract

Background: In view of limited funding, research and development (R&D) investment needs to be optimised for future impact. Road transport R&D is complex and vary from road materials, design and traffic control to safety.

Objectives: Future drivers, trends and technologies in the South African road transport sector were determined and rated. Causal loop diagrams (CLDs) were used to determine how they will influence the sector and potential future R&D focus areas.

Method: Literature reviews, stakeholder interviews and workshops assessed the prevailing state of the sector and identified and rated the drivers, trends and technologies that will impact it. A novel method for structured technology foresight using CLDs was used to analyse the interrelationship between these elements and to determine the gaps in knowledge and the technologies required to position the sector for the future.

Results: Eighteen mega-drivers, 28 industry drivers, 53 trends and 79 key technologies were identified and rated by 98 workshop participants. The CLD analysis provided insight into the characteristics of the transport system and enhanced the understanding of the complexity of the system. Research focus areas were identified to position the transport sector for the future.

Conclusion: Causal loop diagrams were used effectively to demonstrate the interrelationships between and influence of drivers, trends and technologies on the transport sector and to identify gaps in knowledge.

Contribution: The current and future drivers, trends and technologies in the transport sector were identified and CLDs used to assess the relationships between them which led to the identification of new focus areas for R&D.


Keywords

technology foresight; futures study; R&D; transport sector; causal loop diagram.

JEL Codes

R40: General

Sustainable Development Goal

Goal 9: Industry, innovation and infrastructure

Metrics

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