Comparing Analytical Approaches for Bike Station Expansion: A Location-Allocation Study in Trondheim, Norway

TL;DR

This study compares three different analytical models for bike station expansion in Trondheim, Norway, revealing how each approach influences spatial prioritisation and providing insights for urban mobility planning.

Contribution

It introduces a unified framework to compare classical and data-driven location-allocation models for bike-sharing expansion, highlighting their differences and practical implications.

Findings

WLC prioritises population and transit demand coverage.

MCLP emphasizes geographic reach and spatial distribution.

SSE balances demand with accessibility and identifies key expansion sites.

Abstract

The strategic placement of bike-sharing infrastructure shapes urban accessibility and mobility outcomes. However, station-allocation approaches vary in their assumptions and decision logic. This study examines how alternative modelling paradigms prioritise urban space when applied to the same planning problem in Trondheim, Norway. We developed a unified analytical framework to compare three location-allocation approaches: weighted linear combination (WLC), maximal covering location problem (MCLP), and a data-driven suitability score based on exogenous spatial features (SSE). Each model designs a 68-station bike-sharing network from scratch using the same 24 spatial features and hierarchical weighting scheme. The resulting configurations are compared with the existing network, and consensus-based synthesis identifies 12 priority locations for expansion. The findings reveal systematic differences in spatial prioritisation across modelling approaches. WLC achieves the strongest coverage of population and transit demand, MCLP produces the widest spatial distribution prioritising geographic reach, and SSE balances demand intensity with accessibility. All model-derived configurations diverge from the existing network, highlighting the influence of historical and institutional factors on real-world deployment. Consensus synthesis identifies 12 expansion sites characterised by multimodal integration potential, underserved residential clusters, and high latent demand. This analysis demonstrates that methodological choices fundamentally shape spatial decision-support outcomes. By systematically evaluating classical optimisation and data-driven approaches under controlled conditions, the study provides evidence-based recommendations for bike-sharing network expansion and clarifies the strengths and limitations of alternative analytical frameworks for location-allocation planning.