Research Frameworks & Models

Introduction

Research frameworks in the digital economy are essential for structuring inquiry, clarifying concepts, and guiding both empirical and policy work in a rapidly evolving field. Over the past decade, scholars have developed a range of frameworks to address the complexity of digital transformation, the integration of digital technologies, and the socio-economic impacts of digitalization.

Despite these advances, the field remains fragmented, with persistent gaps in theory, measurement, and practical application. This topic synthesizes the most influential frameworks, highlights current trends, and identifies key gaps and future directions.

Major Frameworks and Models

The IBCDE Framework

One of the most comprehensive recent frameworks proposes five core perspectives to capture the complexity of the digital economy:

This framework is widely cited and adopted in recent research, providing a structured approach to understanding different dimensions of the digital economy.

Three-Level Framework

Another influential model organizes digital economy research into three interconnected levels:

This hierarchical approach helps researchers understand how technological capabilities translate into economic innovation and require appropriate governance structures.

Analytical and Measurement Frameworks

New models integrate blockchain, AI, and advanced analytics for digital economy measurement, especially in regional contexts. These frameworks propose hierarchical indices for development assessment, addressing the challenge of quantifying digital economic activity across different contexts and scales.

Sectoral and Thematic Frameworks

Circular Economy and Sustainability

Frameworks linking digital technologies to circular economy strategies identify digital functions and mechanisms for sustainability transitions. These models explore how digitalization can enable resource efficiency, waste reduction, and sustainable production patterns.

Entrepreneurial and Ecosystem Models

Conceptual frameworks for digital entrepreneurial ecosystems blend knowledge-based and platform perspectives. These models examine how digital platforms create new opportunities for entrepreneurship while reshaping traditional business ecosystems.

Smart Cities and Regional Resilience

Models address the orchestration of digital economy strategies for smart cities and regional economic resilience, often using soft systems or coupling approaches. These frameworks help policymakers understand how digital technologies can enhance urban and regional development.

Institutional and Policy Frameworks

These frameworks emphasize the role of institutions, governance, and policy systems in shaping digital transformation, with specific models developed for the EU, China, and developing economies. They recognize that digital economic development cannot be understood purely through technological or market lenses.

Current Trends and Theoretical Foundations

Bibliometric and Content Analyses

Recent studies combine bibliometric and in-depth content analysis to map the field, revealing that digital economy research is still in its infancy, with inconsistent definitions and theoretical underpinnings. This research helps identify patterns, gaps, and emerging themes in the literature.

Integration of Data and Technology

Frameworks increasingly incorporate AI, blockchain, and big data analytics to improve measurement, governance, and policy design. This trend reflects the growing recognition that understanding the digital economy requires engaging with its core technologies.

Gaps and Limitations

Fragmentation and Lack of Standardization

Persistent gaps exist in empirical studies, integration across sectors, and practical application— especially in areas like digital government, sustainability, and multiscale analysis. Multiple reviews highlight persistent fragmentation and inconsistent definitions across the field.

Contextual and Regional Gaps

Many frameworks are tailored to specific countries or regions, limiting their global applicability and comparability. This creates challenges for cross-national research and policy learning.

Measurement and Data Challenges

Ongoing difficulties exist in defining, measuring, and comparing digital economy activities across contexts, especially in developing countries. Traditional economic indicators often fail to capture the unique characteristics of digital economic activity.

Need for Integration

Sectoral models offer depth but often lack cross-sectoral integration and empirical testing. There is a growing call for more integrative, empirically validated, and context-sensitive frameworks to address these challenges and bridge persistent knowledge gaps.

Future Directions

Digital economy research frameworks have advanced the field by providing structure and direction, but significant gaps remain in theory, measurement, and practical application. Future progress depends on developing more integrated, adaptive, and empirically grounded frameworks to keep pace with the digital economy's complexity and rapid change.

Key priorities include:

• Developing standardized measurement approaches that work across contexts
• Creating more integrative frameworks that bridge sectoral boundaries
• Strengthening empirical validation of theoretical models
• Adapting frameworks to diverse regional and developmental contexts
• Incorporating emerging technologies and their economic implications