Business Model Innovation for Sustainable Development: Evidence From the Forest Mapping Technology Sector in Finland
Year: 2025
Type: article
Abstract: ABSTRACT Forests play a critical role in mitigating climate change, protecting biodiversity, and enhancing ecosystem resilience. However, sustainable forest management requires innovative approaches that integrate ecological and economic considerations. Recent advances in remote sensing, LiDAR, and artificial intelligence (AI) have revolutionized forest mapping by providing exceptional precision and scalability. Despite the potential of these technologies, their successful adoption in forestry is not guaranteed. The key challenge lies in integrating these technological capabilities into business models supporting economic viability and sustainability goals. This study addresses this gap by investigating how Business Model Innovation (BMI) facilitates the integration of advanced technologies in forest management, focusing on the strategic alignment of technological capabilities with sustainable development outcomes. Employing a qualitative case study methodology, this research draws on semi‐structured interviews with knowledgeable informants from Finland's forestry sector, including researchers, industry experts, and policymakers. Using the Gioia methodology for data analysis, the study uncovers key themes related to stakeholder collaboration, cost optimization, value creation, and scalability in technology adoption. The findings demonstrate that innovative business models are crucial for harnessing the full potential of AI and LiDAR technologies, as they enhance precision in forest mapping while addressing challenges related to cost and scalability. BMI emerges as a vital enabler, fostering partnerships, optimizing value delivery, and promoting resilient, development‐oriented forestry practices.
Source: Business Strategy & Development
DOI: 10.1002/bsd2.70214
Authors: Ghazale Kordi, Jari Salo
Institution: University of Helsinki
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,240
OpenAlex ID: W4414039470