Providing an Appropriate Model for the Commercialization of Entrepreneurial Ideas in Knowledge-Based Companies with an Export-Oriented Approach Using a Mixed-Methods Research Design - Torabi, Majid; Hashemi Tilehnouei, Mostafa; Vakil Alroaia, Younos (Business, Marketing, and Finance Open, 2026)
In today’s global economy, companies that emphasize marketing and innovation are more capable of achieving a sustainable competitive advantage. On the other hand, the core driver of growth and development in the export sector is increasingly knowledge-based. The success of knowledge-based companies depends on their sales performance and market share; the more effective they are in the commercialization of goods and services, the greater their access to national and international markets will be. Accordingly, the present study aimed to propose a model for the commercialization of entrepreneurial ideas in knowledge-based companies with an export-oriented perspective, employing a mixed-methods research design (qualitative–quantitative). In the qualitative phase, the grounded theory approach was applied. Data were collected through semi-structured interviews with 21 experts, including university faculty members, specialists, and practitioners in the service sector, using purposive judgmental and snowball sampling. Data analysis followed the three-step coding procedure of open, axial, and selective coding. The resulting paradigmatic model consists of six causal categories (social factors; individual factors; organizational–technological factors; financial–economic factors; and legal–regulatory factors), an intervening category (mindset and support of transformational managers and leaders, universities and educational organizations, and the government), a contextual category (individual contextual conditions, socio-economic deficiencies, and intra-organizational factors), strategies (customer and market orientation, innovation orientation, international entrepreneurship culture, creativity and innovation training, and structural and industrial transformation), and consequences (individual outcomes, short-term and long-term results, national results, and regional results). In the quantitative phase, structural equation modeling (SEM) using the Partial Least Squares (PLS) technique was applied to test the proposed model. The findings revealed significant and positive reciprocal effects between internal and external latent variables. Considering the R² and Q² indices, the model demonstrated strong predictive power, and the overall model fit was high with a goodness-of-fit index of 0.659.