A study demonstrates that AI tools, when aligned with carbon emission strategies and sustainability regulations, significantly boost environmental performance in Pakistani SMEs by improving resource efficiency and waste reduction, validated with PLS-SEM analysis on 387 firms.
Key points
AI adoption in 387 Pakistani SMEs shows a direct positive effect on environmental performance (β=0.269, p<0.001).
External factors—carbon emission strategies and sustainability regulations—mediate AI’s impact (indirect β=0.217, p<0.003) and directly boost performance (β=0.259, p<0.001).
Construct validity confirmed with Cronbach’s α>0.70, composite reliability>0.70, and AVE>0.50 in PLS-SEM measurement model.
Why it matters:
Coupling AI adoption with regulatory frameworks unlocks powerful sustainability benefits for SMEs, offering a scalable model for green transitions in emerging markets.
Q&A
What is dynamic capability theory?
How does PLS-SEM work in research?
What role do external environmental factors play?
What distinguishes carbon emission strategies from sustainability regulations?
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Academy
Dynamic Capability Theory
Dynamic Capability Theory explains how organizations develop and reconfigure their internal skills, processes, and resources to respond effectively to changing external conditions. Unlike routine capabilities that focus on day-to-day operations, dynamic capabilities emphasize three critical activities:
- Sensing: Identifying opportunities and threats in the business environment by gathering and interpreting data.
- Seizing: Mobilizing resources to capture opportunities, such as investing in new technologies or partnerships.
- Transforming: Continuously reconfiguring organizational structures and processes to integrate innovations and maintain competitiveness.
In the context of sustainability, Dynamic Capability Theory helps explain how small and medium-sized enterprises (SMEs) adopt green technologies—for example, artificial intelligence (AI) tools that monitor energy use or optimize waste management. By sensing environmental challenges, seizing AI-driven solutions, and transforming operations, SMEs can achieve significant environmental performance improvements. This framework underscores the strategic importance of aligning technological initiatives with external pressures, such as regulations and market demands, to drive sustainable growth.
Sustainability Regulations
Sustainability regulations are legal frameworks and policies aimed at protecting the environment and promoting sustainable practices across industries. They typically cover areas such as emissions, waste management, water usage, and resource conservation. Key elements include:
- Emission Limits: Caps on greenhouse gases and pollutants that industries can release, often enforced through permits or fines.
- Resource Conservation: Standards for efficient use of materials, water, and energy, encouraging businesses to minimize waste.
- Reporting Requirements: Mandatory disclosure of environmental impact, driving transparency and accountability.
- Incentives and Penalties: Financial rewards for green investments or penalties for non-compliance, which steer corporate behavior.
For SMEs, navigating sustainability regulations can be challenging due to limited resources and technical expertise. However, by integrating AI tools that automate monitoring and compliance reporting, SMEs can streamline adherence to regulations. These AI systems collect real-time environmental data, generate compliance reports, and provide actionable insights to reduce emissions and waste. The synergy between AI innovation and policy enforcement empowers SMEs to meet legal requirements while enhancing their environmental performance.
Why this matters: Understanding Dynamic Capability Theory and sustainability regulations helps business leaders and technology developers design solutions that align internal innovation processes with external policy demands, ultimately driving measurable sustainability outcomes for organizations.
