Clarifying new urban mobility services based on a threefold business model framework

• We perform a systematic literature review and use 16 publications as a basis for qualitative content analysis. • As a main result, we identify (1) conventional mobility, (2) both data-driven and conventional mobility (hybrid), and (3) purely data-driven business models. • Based on both prior literature and our results, we derive a threefold business model framework for urban mobility, mapping conventional mobility, hybrid, and data-driven business models. • A first contribution is the conceptualization of conventional versus new urban mobility services, whereby the latter are formed by the group of hybrid and data-driven business models. • A second contribution lies in clarifying the MaaS concept by identifying it as a purely data-driven business model, in which mobility provision takes place via key partners. Market entrants have brought a variety of new urban mobility services over the past years, which are rooted in the sharing economy and have their origin in digitalization. Digital data serve as key resource of a business model and, accordingly, digital technologies are the basis of key activities. Building our analysis on the resource-based view and on the business model debate, we ask: what degrees of digitalization do urban mobility service business models exhibit? We perform a systematic literature review and a qualitative content analysis. As a result, we identify a continuum of highly and lowly digitalized business models. We derive a threefold business model framework, substantiated in conventional mobility, hybrid, and data-driven business models. (1) Conventional mobility business models are dominated by mobility as a key resource, digitalization is low and performed by key partners, (2) hybrid models contain both conventional mobility and data-driven key resources, and (3) data-driven models take digital data as key resources, while conventional mobility is carried out by key partners. As a first main contribution, we conceptualize conventional versus purely data-driven business models along the continuum of data-driven business model components. New urban mobility services are the group of both hybrid and data-driven business models, while conventional urban mobility stands on its own. As a second contribution, we clarify the Mobility-as-a-Service (MaaS) concept by corroborating it as a purely data-driven business model with key partners provisioning mobility.

Authors

Institutions

Publication Details

Journal
Transportation Research Interdisciplinary Perspectives
Published
2024-08-30
DOI
https://doi.org/10.1016/j.trip.2024.101207
Citations
2
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.41

Funders

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

Clarifying new urban mobility services based on a threefold business model framework

Frederik M. Metzger, Konstantin Krauss
2 citations
Transportation Research Interdisciplinary Perspectives
Transportation and Mobility Innovations
0.41
article

Clarifying new urban mobility services based on a threefold business model framework

Frederik M. Metzger, Konstantin Krauss
article en
2 citations

Abstract

• We perform a systematic literature review and use 16 publications as a basis for qualitative content analysis. • As a main result, we identify (1) conventional mobility, (2) both data-driven and conventional mobility (hybrid), and (3) purely data-driven business models. • Based on both prior literature and our results, we derive a threefold business model framework for urban mobility, mapping conventional mobility, hybrid, and data-driven business models. • A first contribution is the conceptualization of conventional versus new urban mobility services, whereby the latter are formed by the group of hybrid and data-driven business models. • A second contribution lies in clarifying the MaaS concept by identifying it as a purely data-driven business model, in which mobility provision takes place via key partners. Market entrants have brought a variety of new urban mobility services over the past years, which are rooted in the sharing economy and have their origin in digitalization. Digital data serve as key resource of a business model and, accordingly, digital technologies are the basis of key activities. Building our analysis on the resource-based view and on the business model debate, we ask: what degrees of digitalization do urban mobility service business models exhibit? We perform a systematic literature review and a qualitative content analysis. As a result, we identify a continuum of highly and lowly digitalized business models. We derive a threefold business model framework, substantiated in conventional mobility, hybrid, and data-driven business models. (1) Conventional mobility business models are dominated by mobility as a key resource, digitalization is low and performed by key partners, (2) hybrid models contain both conventional mobility and data-driven key resources, and (3) data-driven models take digital data as key resources, while conventional mobility is carried out by key partners. As a first main contribution, we conceptualize conventional versus purely data-driven business models along the continuum of data-driven business model components. New urban mobility services are the group of both hybrid and data-driven business models, while conventional urban mobility stands on its own. As a second contribution, we clarify the Mobility-as-a-Service (MaaS) concept by corroborating it as a purely data-driven business model with key partners provisioning mobility.

Transportation Research Interdisciplinary PerspectivesVol. 27
Fraunhofer Institute for Systems and Innovation Research (DE)
Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie
Sustainable cities and communities
Openalex Percentile: Top 40%
Transportation and Mobility Innovations
0.41
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.