Asia Pacific Business Review

Rethinking AI-based business ecosystem in the Asia Pacific

The Asia-Pacific region stands at the vanguard of AI-driven digital transformation, where cutting-edge technologies like machine learning, big data analytics, and intelligent automation are reshaping business ecosystems, managerial practices, and sustainable development strategies. This special issue critically examines the dynamic interplay between artificial intelligence (AI) and emerging business models across the region, focusing on three core pillars: innovation, ethics, and governance.

In recent years, the rapid pace of technological advancements has significantly influenced various industries, prompting strategic shifts in business models, operational processes, and market approaches (Zhuo & Chen, 2023). AI is revolutionizing strategic decision-making, supply chain resilience, and consumer engagement in the Asia-Pacific (Cheng et al., 2024). AI-powered personalization and algorithmic optimization are redefining digital marketing, while integrated platforms accelerate innovation cycles and organizational agility. Studies highlight AI’s dual role as an enabler of green innovation and knowledge spillover across industries (Liu et al., 2020; Huang et al., 2022; Chin et al., 2025), yet its disruptive impacts on labor markets and institutional frameworks remain understudied in culturally diverse, fragmented economies (Rowley et al., 2004; Chin et al., 2023; Chin et al., 2024b).

Transformative business models and economic dynamics delve into how innovative business strategies reshape market landscapes and influence economic trends (Liu et al., 2020; Chin et al., 2025). Asia-Pacific region’s digital economy is being rewired by AI-driven platforms that foster collaborative innovation and shorten product lifecycles. Research reveals a quadratic relationship between AI adoption and ecosystem-based business models, underscoring the technology’s potential to enhance cross-industry collaboration (Chin et al., 2024a; Huang et al., 2025). Meanwhile, AI-integrated trade financing and corporate governance frameworks are redefining financial performance metrics and stakeholder priorities, including a narrowing gap between internal and external CSR initiatives (Zhang & Chin, 2025).

Governance dilemmas involve balancing competing interests and ethical imperatives, such as transparency versus privacy, accountability versus autonomy, and equity versus efficiency. The proliferation of AI in marketing and social media amplifies concerns over algorithmic bias, privacy erosion, and trust deficits (Yang & Lin, 2014). Shadow AI practices in metaverse-based economies, for instance, exhibit an inverted U-shaped relationship with organizational knowledge leakage (Chin et al., 2025), emphasizing the need for robust governance frameworks. Balancing innovation with ethical AI deployment emerges as critical to sustaining competitive advantages in dynamic markets.

List of topic areas include but are not limited to:

• AI-Augmented Human Decision-Making
• Human Well-being with AI Interaction
• AI-Driven Digital Transformation
• AI Ethics and Trust in Cross-Cultural Governance
• Labor Market Disruption & Reskilling
• Sustainable AI Innovation Ecosystems
• AI-Enabled Crisis Management
• Global Green Value Chain Reconfiguration
• Indigenous Knowledge & AI Fusion
• ESG-Driven AI Entrepreneurship

References

Cheng, W., Li, C., & Zhao, T. (2024). The stages of enterprise digital transformation and its impact on internal control: Evidence from China. International Review of Financial Analysis, 92, 103079. 

Chin, T., Cheng, T. C. E., Wang, C., & Huang, L. (2024a). Combining artificial and human intelligence to manage cross-cultural knowledge in humanitarian logistics: a Yin–Yang dialectic systems view of knowledge creation. Journal of Knowledge Management.

Chin, T., Ghouri, M. W. A., Jin, J., & Deveci, M. (2024b). AI technologies affording the orchestration of ecosystem-based business models: the moderating role of AI knowledge spillover. Humanities and Social Sciences Communications, 11(1), 1-13.

Chin, T., Jin, J., Wang, S., Caputo, F., & Rowley, C. (2023). Cross-cultural legitimacy for orchestrating ecosystem-based business models in China: A Yin-Yang dialectical systems view. Asia Pacific Business Review, 1–24. 

Chin, T., Li, Q., Mirone, F., & Papa, A. (2025). Conflicting impacts of shadow AI usage on knowledge leakage in metaverse-based business models: A Yin-Yang paradox framing. Technology in Society, 81, 102793.

Huang, L., Wang, C., Chin, T., Huang, J., & Cheng, X. (2022). Technological knowledge coupling and green innovation in manufacturing firms: Moderating roles of mimetic pressure and environmental identity. International Journal of Production Economics, 248, 108482.

Huang, L., Chin, T., Papa, A., & Pisano, P. (2025). Artificial intelligence augmenting human intelligence for manufacturing firms to create green value: Towards a technology adoption perspective. Technological Forecasting and Social Change, 213, 124013.

Liu, J., Chang, H., Forrest, J. Y. L., & Yang, B. (2020). Influence of artificial intelligence on technological innovation: Evidence from the panel data of China's manufacturing sectors. Technological Forecasting and Social Change, 158, 120142.

Rowley, C., Benson, J., & Warner, M. (2004). Towards an Asian model of human resource management? A comparative analysis of China, Japan and South Korea. The International Journal of Human Resource Management, 15(4–5), 917–933.

Yang, H. L., & Lin, C. L. (2014). Why do people stick to Facebook web site? A value theory-based view. Information Technology & People, 27(1), 21-37.

Zhang, Y., Chin, T., & Al-Wazer, R. (2025). Good neighbors but bad employers? How corporate digital transformation affects incongruence between external and internal corporate social responsibility. Technological Forecasting and Social Change, 210, 123858.

Zhuo, C., & Chen, J. (2023). Can digital transformation overcome the enterprise innovation dilemma: Effect, mechanism and effective boundary. Technological Forecasting and Social Change, 190, 122378