The role of green blue ocean strategy in enhancing frugal innovation through IoT and AI: A resource-based view perspective

PURPOSE: This study explores the role of Green Blue Ocean Strategy (GBOS) in promoting frugal innovation by leveraging IoT and AI from an RBV theoretical perspective, targeting creative entrepreneurs in Central Java, Indonesia. METHODOLOGY: A quantitative approach was used, with Structural Equation Modelling (SEM) analyzed via AMOS. Data from 262 creative entrepreneurs were collected through an online closed questionnaire using purposive sampling. FINDINGS: The study reveals that (1) IoT does not significantly impact frugal innovation, (2) AI positively influences frugal innovation, and (3) GBOS effectively mediates the relationship between IoT, AI, and frugal innovation, suggesting that integrating sustainable strategies with technology can lead to more cost-effective and inclusive innovations. IMPLICATIONS for theory and practice: The study extends the RBV framework by integrating the GBOS concept, demonstrating its effectiveness in optimizing digital technology for sustainability-driven innovation. It contributes to the literature on sustainability strategies and the Resource-Based View by introducing a novel theoretical model that links GBOS, IoT, and AI with frugal innovation. Practically, GBOS offers a pathway for creative entrepreneurs to overcome resource constraints and achieve competitive advantages through sustainable practices. ORIGINALITY AND VALUE: This study introduces Green Blue Ocean Strategy (GBOS) as a novel conceptual framework that extends the traditional Blue Ocean Strategy (BOS) by integrating sustainability principles. GBOS addresses both economic and environmental concerns, enabling businesses to achieve cost-effective innovation. Grounded in the Resource-Based View (RBV), this study systematically develops and empirically tests GBOS by linking it with IoT, AI, and frugal innovation. The framework offers a new lens for sustainable competitive advantage in resource-constrained environments.