DEVELOPING A DIGITAL ECOSYSTEM IN TRANSPORT: THEORETICAL FOUNDATIONS AND GLOBAL EXPERIENCE

Abstract

In recent years, the modernization of public transport systems has become a key factor in sustainable urban development, especially in rapidly urbanizing countries such as Uzbekistan. The shift from traditional transport models to digital ecosystems is driven by the need to achieve efficiency, convenience, and sustainability. A digital transport ecosystem represents a network of interconnected components and technological services that facilitate delivery, management, and optimization within transport systems.

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Komilov , A. . (2025). DEVELOPING A DIGITAL ECOSYSTEM IN TRANSPORT: THEORETICAL FOUNDATIONS AND GLOBAL EXPERIENCE. Social Sciences in the Modern World: Theoretical and Practical Research, 4(19), 36–39. Retrieved from https://inlibrary.uz/index.php/zdif/article/view/134825
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Abstract

In recent years, the modernization of public transport systems has become a key factor in sustainable urban development, especially in rapidly urbanizing countries such as Uzbekistan. The shift from traditional transport models to digital ecosystems is driven by the need to achieve efficiency, convenience, and sustainability. A digital transport ecosystem represents a network of interconnected components and technological services that facilitate delivery, management, and optimization within transport systems.


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DEVELOPING A DIGITAL ECOSYSTEM IN TRANSPORT: THEORETICAL

FOUNDATIONS AND GLOBAL EXPERIENCE

Komilov Asror Akmalovich

PHD student of Graduate School of Business and Entrepreneurship

https://doi.org/10.5281/zenodo.16812417

In recent years, the modernization of public transport systems has become a key factor in

sustainable urban development, especially in rapidly urbanizing countries such as Uzbekistan.
The shift from traditional transport models to digital ecosystems is driven by the need to
achieve efficiency, convenience, and sustainability. A digital transport ecosystem represents a
network of interconnected components and technological services that facilitate delivery,
management, and optimization within transport systems. This ecosystem is characterized by
collaboration between government agencies, private sector enterprises, and end-users, and is
supported by advanced technologies such as the Internet of Things (IoT), Artificial Intelligence
(AI), big data analytics, mobile applications, and blockchain

1

. A digital ecosystem in public

transport can be broadly defined as a network of interconnected components and technological
services that facilitate efficient management and optimization of transportation. This
ecosystem is built on data interoperability, platform-based collaboration, and stakeholder
engagement, ensuring transparency and effective information exchange between different
modes of transport. Mobility services increasingly rely on seamless integration with existing
infrastructure, resource optimization, and the reduction of inefficiencies

2

.

Uzbekistan is currently implementing digital transformation in the transport sector in line

with the “Digital Uzbekistan 2030” strategy. The Presidential Decree of the Republic of
Uzbekistan No. PF-6269 dated July 24, 2021,

On measures to improve the infrastructure of public

services and expand the population’s access to public services

, provides a foundation for

introducing digital services, improving management systems, and increasing operational
efficiency. However, several challenges remain, such as shortcomings in technological
infrastructure, regulatory barriers, and issues of digital literacy. The digitalization gap between
urban and rural areas also poses a significant problem.

This thesis examines the theoretical foundations of the digital transport ecosystem, its

application in Uzbekistan, the main components of an integrated transport ecosystem,
implementation strategies, challenges, legal frameworks, and the proposed model for
digitalizing transport in Uzbekistan.

Theoretical foundations of the digital ecosystem in public transport

:

Systems Theory and Transport Digitalization:

Introduced by Bertalanffy (1968), the

General Systems Theory (GST) describes a system as a set of interconnected and dynamically
interacting components that maintain overall integrity

3

. The transport system is an example of

this, where various components—including vehicles, passengers, infrastructure, and
operators—must function effectively in coordination with one another.

The key principles of GST relevant to digital transport ecosystems include:

1

Ashurov, D.Z., Makhmudova, G., & Razakova, B. (2022). Development of digital ecosystem and formation of digital

platforms in Uzbekistan

2

Cohen, A.P., Shaheen, S.A., & Farrar, E.M. (2021). Urban air mobility: History, ecosystem, market potential, and

challenges.

IEEE Transactions on Intelligent Transportation Systems

, 22(9), 6074-6087

3

Bertalanffy, L. (1968). General System Theory: Foundations, Development, Applications.


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37

1.

Holism

The transport system is composed of the sum of its individual components, with

functionality emerging from the interactions between vehicles, infrastructure, and users

.

2.

Hierarchical structure

– The transport system consists of several levels that connect

smaller subsystems (e.g., national transit, urban transit, micromobility services).

3.

Open and closed systems

Open transport systems interact with their environment,

adapting routes and schedules based on real-time data.

4.

Feedback

AI-driven transport management systems use sensor data and passenger

feedback to optimize operations.

Applying systems theory to public transport digitalization enables real-time integration

of various transport modes, efficient fleet management through IoT, and demand forecasting
using AI. For example, Singapore’s Smart City Transport system leverages IoT and AI to
optimize bus schedules in real time based on passenger demand

4

.

Platform theory and the role of digital platforms in transport:

Platform theory explains how

digital platforms create added value by facilitating interactions between multiple user groups.
Digital platforms leverage network effects to scale operations with minimal cost

5

.

A platform is typically a multi-sided market or service that enables transactions and

exchanges between various participants (e.g., passengers, transit operators, freight carriers,
app developers). Platform theory explains how multi-sided platforms generate strong network
effects: as more users and service providers join, the platform’s value increases and innovation
accelerates. In the transport context, Mobility-as-a-Service (MaaS) applications, ride-sharing
marketplaces, and logistics hubs serve as platforms that integrate data and services. Platforms
can be categorized into the following types:

Transaction platforms

facilitate exchanges between different user groups. Examples:

eBay (buyers/sellers), PayPal (money transfers), DoorDash (restaurants/delivery
drivers/customers).

Innovation platforms

provide a foundation for participating parties to develop

innovative products and services. Examples: Apple iOS, Google Play, Amazon AWS.

Hybrid platforms

– combine transaction and innovation functions. Examples: Amazon

(marketplace + AWS cloud services), Microsoft (Windows OS + Xbox gaming ecosystems).

Industrial platforms

– designed for manufacturing and the Internet of Things (IoT).

Business ecosystem model in transport

: The business ecosystem model describes how

companies operate not individually, but within a dynamic network of interdependent actors —
including suppliers, customers, competitors, and other stakeholders — that collectively
manage innovation and value creation

6

.

In transport, this means that traditional competitors (e.g., public and private transit) and

new entrants (mobility startups, technology providers) form a network of suppliers,
complementors, and customers. Thus, business ecosystem theory reminds us that successful
digital transport systems require synergy among regulators, infrastructure owners, technology

4

Gohar, A. & Nencioni, G. (2021). The role of 5G technologies in a smart city: The case for intelligent

transportation systems.

Sustainability

, 13(9), 5188.

5

Rochet, J.C., & Tirole, J. (2003). Platform competition in two-sided markets.

Journal of the European Economic

Association

, 1(4), 990-1029.

6

Moore, J.F. (1993). Predators and prey: A new ecology of competition.

Harvard Business Review

, 71(3), 75-86.


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companies, and end users. A collective strategy — such as coordinated innovation, joint
investments, and adaptive regulations — often replaces purely competitive behavior to foster
the overall development of the ecosystem.

Comparative analysis of traditional and ecosystem-based business models

Traditional business

Ecosystem-based business

Linear value chain

Network, non-linear relationships

Competition-based strategy

Cooperation + competition (co-opetition)

Independent business operations

Interdependent stakeholder system

Focus on individual enterprise growth

Striving for shared value creation

Applying the business ecosystem model enables better coordination between private and

public transport providers, supporting seamless multimodal mobility solutions

7

. Several global

case studies demonstrate the advantages of digital ecosystems in transport:

•Helsinki’s mobility model integrates ride-sharing, public transport, and micromobility

into a single digital platform, enhancing user convenience and reducing congestion.

• China’s smart public transport system uses AI-based predictive analytics to improve

planning and fleet management.

• Estonia’s X-Road system ensures seamless data exchange between transport agencies

and users, improving efficiency and transparency.

• In Chicago, the Launchpad project employs a fully digital platform that integrates

various modes of transport, enabling users to plan journeys involving buses, trains, and
rideshares through a single app. Public participation in solution design is a key factor in
Launchpad’s success—engaging citizens during the design phase and gathering feedback
ensures that services effectively meet user needs, highlighting the importance of participatory
approaches in public transport digitalization.

References:

Используемая Литература:

Foydalanilgan adabiyotlar:

1.

Ashurov, D.Z., Makhmudova, G., & Razakova, B. (2022). Development of digital ecosystem

and formation of digital platforms in Uzbekistan
2.

Cohen, A.P., Shaheen, S.A., & Farrar, E.M. (2021). Urban air mobility: History, ecosystem,

market potential, and challenges.

IEEE Transactions on Intelligent Transportation Systems

,

22(9), 6074-6087
3.

Bertalanffy, L. (1968). General System Theory: Foundations, Development, Applications.

4.

Gohar, A. & Nencioni, G. (2021). The role of 5G technologies in a smart city: The case for

intelligent transportation systems.

Sustainability

, 13(9), 5188.

5.

Rochet, J.C., & Tirole, J. (2003). Platform competition in two-sided markets.

Journal of the

European Economic Association

, 1(4), 990-1029.

7

Evans, D.S., & Schmalensee, R. (2016).

Matchmakers: The New Economics of Multisided Platforms

.

Harvard Business Review Press.


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39

6.

Moore, J.F. (1993). Predators and prey: A new ecology of competition.

Harvard Business

Review

, 71(3), 75-86.

7.

Evans, D.S., & Schmalensee, R. (2016).

Matchmakers: The New Economics of Multisided

Platforms

. Harvard Business Review Press.

References

Ashurov, D.Z., Makhmudova, G., & Razakova, B. (2022). Development of digital ecosystem and formation of digital platforms in Uzbekistan

Cohen, A.P., Shaheen, S.A., & Farrar, E.M. (2021). Urban air mobility: History, ecosystem, market potential, and challenges. IEEE Transactions on Intelligent Transportation Systems, 22(9), 6074-6087

Bertalanffy, L. (1968). General System Theory: Foundations, Development, Applications.

Gohar, A. & Nencioni, G. (2021). The role of 5G technologies in a smart city: The case for intelligent transportation systems. Sustainability, 13(9), 5188.

Rochet, J.C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990-1029.

Moore, J.F. (1993). Predators and prey: A new ecology of competition. Harvard Business Review, 71(3), 75-86.

Evans, D.S., & Schmalensee, R. (2016). Matchmakers: The New Economics of Multisided Platforms. Harvard Business Review Press.