Typology of resistant adopters and policy implications for autonomous shipping: Evidence from the Rhine River

• Identifies three autonomous inland shipping adopter groups—early adopters, a silent majority, and laggards—positioned along a continuum of openness and resistance. • Provides empirical evidence from the Rhine corridor showing that adoption is fragmented and gradual, challenging classical S-shaped diffusion and timing-based adopter typologies. • Demonstrates that resistance to autonomous shipping is structurally embedded in organizational capacity, fleet characteristics, and regulatory uncertainty rather than purely attitudinal. • Interprets marketing strategies towards resistant innovation: vertical cooperation and horizontal coopetition as stage-dependent coordination logics that align differently with heterogeneous adopter groups over the course of innovation diffusion. Autonomous shipping is expected to transform inland waterway transport, yet empirical evidence on how shipowners differ in their adoption positions remains limited. This article investigates adoption dynamics in the Rhine River corridor using a mixed-method design. Semi-structured interviews informed survey development, and survey responses from inland shipowners ( N = 47 ) were analysed using Multiple Correspondence Analysis. The analysis identifies three adopter typologies: early adopters, a silent majority, and laggards, which are positioned along a continuum of openness and resistance. The results suggest that resistance is not uniform but varies with organizational capacity, fleet retrofit constraints, perceived regulatory, and operational uncertainty. Adoption therefore appears fragmented and gradual, rather than consistent with a conventional S-shaped diffusion pattern. Building on these findings, the article develops a stage-based interpretative framework based on empirical data. This framework links adopter heterogeneity to the literature on resistant innovation and diffusion. Early diffusion aligns with niche-oriented vertical cooperation among pioneers. Broader diffusion increases the emphasis on visibility, collective learning, coordination, and standardisation. Rather than prescribing specific instruments, the article illustrates how policy and governance approaches may align differently with heterogeneous adoption capacities as innovation matures.

Authors

Institutions

Publication Details

Journal
Transportation Research Interdisciplinary Perspectives
Published
2026-05-01
DOI
https://doi.org/10.1016/j.trip.2026.102017
Primary Topic
Business Strategy and Innovation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Typology of resistant adopters and policy implications for autonomous shipping: Evidence from the Rhine River

Terje Andreas Mathisen, Roberto Rivas Hermann, Oleg Nenadić, Dhaneswara Al Amien
Transportation Research Interdisciplinary Perspectives
Business Strategy and Innovation
article

Typology of resistant adopters and policy implications for autonomous shipping: Evidence from the Rhine River

Terje Andreas Mathisen, Roberto Rivas Hermann, Oleg Nenadić, Dhaneswara Al Amien
article en

Abstract

• Identifies three autonomous inland shipping adopter groups—early adopters, a silent majority, and laggards—positioned along a continuum of openness and resistance. • Provides empirical evidence from the Rhine corridor showing that adoption is fragmented and gradual, challenging classical S-shaped diffusion and timing-based adopter typologies. • Demonstrates that resistance to autonomous shipping is structurally embedded in organizational capacity, fleet characteristics, and regulatory uncertainty rather than purely attitudinal. • Interprets marketing strategies towards resistant innovation: vertical cooperation and horizontal coopetition as stage-dependent coordination logics that align differently with heterogeneous adopter groups over the course of innovation diffusion. Autonomous shipping is expected to transform inland waterway transport, yet empirical evidence on how shipowners differ in their adoption positions remains limited. This article investigates adoption dynamics in the Rhine River corridor using a mixed-method design. Semi-structured interviews informed survey development, and survey responses from inland shipowners ( N = 47 ) were analysed using Multiple Correspondence Analysis. The analysis identifies three adopter typologies: early adopters, a silent majority, and laggards, which are positioned along a continuum of openness and resistance. The results suggest that resistance is not uniform but varies with organizational capacity, fleet retrofit constraints, perceived regulatory, and operational uncertainty. Adoption therefore appears fragmented and gradual, rather than consistent with a conventional S-shaped diffusion pattern. Building on these findings, the article develops a stage-based interpretative framework based on empirical data. This framework links adopter heterogeneity to the literature on resistant innovation and diffusion. Early diffusion aligns with niche-oriented vertical cooperation among pioneers. Broader diffusion increases the emphasis on visibility, collective learning, coordination, and standardisation. Rather than prescribing specific instruments, the article illustrates how policy and governance approaches may align differently with heterogeneous adoption capacities as innovation matures.

Transportation Research Interdisciplinary PerspectivesVol. 37
Nord University (NO)
H2020 Marie Skłodowska-Curie Actions
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Business Strategy and Innovation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.