Adapting Global Business Models to Disruptive Innovation and Market Dynamics: A Framework for Modern Times

In an era marked by rapid technological advancements, artificial intelligence (AI), shifting market dynamics, and heightened global interconnectedness, traditional global business models have become insufficient. This study aims to address this gap by proposing a practical, multidisciplinary framework that adapts to the current global business environment. The existing literature on international business (IB) has primarily been grounded in outdated models that fail to adequately consider emerging markets, technological disruptions, and the challenges posed by aging populations. This study critically reviews the limitations of classical frameworks, such as the OLI Eclectic Paradigm, and offers a fresh perspective on dynamic capabilities and the necessity for continuous innovation in global business models. Using a qualitative exploratory methodology, this paper examines case studies of multinational corporations (MNCs) that have successfully adapted their business models to modern realities. Our findings suggest that firms capable of embedding adaptability, innovation, and agility into their business strategies are more likely to achieve sustained global success. This research contributes to the evolving discourse on global business strategies by emphasizing the importance of dynamic capabilities in navigating the volatile, uncertain, complex, and ambiguous (VUCA) environment.

Authors

Publication Details

Journal
Journal of Organizational Management Studies
Published
2025-03-19
DOI
https://doi.org/10.5171/2025.223981
Primary Topic
Economic Issues in Ukraine
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adapting Global Business Models to Disruptive Innovation and Market Dynamics: A Framework for Modern Times

ESSBAA Elmehdi, LARAQUI Saad, JARREAU Bert
Journal of Organizational Management Studies
Economic Issues in Ukraine
article

Adapting Global Business Models to Disruptive Innovation and Market Dynamics: A Framework for Modern Times

ESSBAA Elmehdi, LARAQUI Saad, JARREAU Bert
article en

Abstract

In an era marked by rapid technological advancements, artificial intelligence (AI), shifting market dynamics, and heightened global interconnectedness, traditional global business models have become insufficient. This study aims to address this gap by proposing a practical, multidisciplinary framework that adapts to the current global business environment. The existing literature on international business (IB) has primarily been grounded in outdated models that fail to adequately consider emerging markets, technological disruptions, and the challenges posed by aging populations. This study critically reviews the limitations of classical frameworks, such as the OLI Eclectic Paradigm, and offers a fresh perspective on dynamic capabilities and the necessity for continuous innovation in global business models. Using a qualitative exploratory methodology, this paper examines case studies of multinational corporations (MNCs) that have successfully adapted their business models to modern realities. Our findings suggest that firms capable of embedding adaptability, innovation, and agility into their business strategies are more likely to achieve sustained global success. This research contributes to the evolving discourse on global business strategies by emphasizing the importance of dynamic capabilities in navigating the volatile, uncertain, complex, and ambiguous (VUCA) environment.

Journal of Organizational Management Studies
Openalex Percentile: Top 93%
Economic Issues in Ukraine
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.