Early-phase evaluation and screening of infrastructure investment projects using the analogy methodology

Abstract

This paper presents the Analogy Method as a pragmatic approach to address the challenges of transportation planning, under the Norwegian government's extensive investment plan of 1308 billion NOK for infrastructure improvements during 2025–2036. The plan aims to foster mobility, regional development and environmental sustainability, necessitating efficient resource allocation that meets political objectives while permitting quantifiable evaluation of impacts. Traditional analytical methods often fall short due to data limitations and time constraints faced by decision-makers. In response, this study demonstrates the broader applicability of the Analogy Method within the transportation sector with an analysis of high-speed railway impacts on regional development in the Eidsvoll and Aurskog-Høland areas. Through the comparative analysis of known phenomena with emerging projects, the Analogy Method facilitates early cost/benefit predictions, offering a strategic tool for decision-makers under pressure. This paper explores the concept of generalised travel costs (GCs) in assessing socio-economic impacts and illustrates the resulting time savings, cost efficiency and clarity in evaluations. The article outlines the method's theoretical foundation and applies it to a case study of a proposed railway station project, aiming to elucidate both the economic profitability for society and the implications for broader planning practices. In addressing two key research questions – whether the Analogy Method can effectively predict socio-economic impacts in data-scarce environments and how its application increases understanding of project benefits and costs – this paper aspires to bridge theoretical insights with practical applications. The findings encourage further exploration of the Analogy Method's potential in transportation planning and its capacity to support informed, data-driven decision-making amidst the complexities of infrastructure development.