Document Type : Research Article
Authors
Department of Management, Faculty of Humanities, Ilam University, Ilam, Iran.
Abstract
Introduction: In today’s competitive and technology-driven environment, effective collaboration and the exchange and utilization of knowledge and innovation across different sectors, including education, industry, and entrepreneurship, have become increasingly important. Universities play a critical role in generating scientific knowledge, developing technologies, and educating skilled human resources, while startups, as drivers of innovation and new business development, require effective engagement with universities to access their scientific and technical expertise. In this context, bidirectional learning and knowledge exchange between universities and startups can substantially enhance the effectiveness of such collaborations. Accordingly, there is a need for scientific and practical models that can facilitate and strengthen these learning processes. This study aimed to develop a model of the bidirectional learning process in university–startup collaborations in the field of digital marketing, thereby providing an evidence-based and practical framework for strengthening these partnerships and leveraging their potential more effectively.
Methodology: This applied study employed a qualitative research approach using qualitative content analysis. The study population comprised experts, university faculty members, and managers involved in university–industry relations, as well as startup founders. Participants were selected through purposive sampling, and 31 in-depth interviews were conducted until theoretical saturation was reached. To enhance the validity and credibility of the findings, the emerging results were reviewed by experts in the fields of startups and digital marketing. The reliability of the findings was assessed through the consistency of themes identified across participants’ responses. Data were analyzed using qualitative content analysis, involving systematic coding and the identification and extraction of key themes and concepts.
Findings: The findings resulted in a bidirectional learning model comprising 13 main categories, 39 subcategories, and 117 indicators. The main categories included knowledge exchange, joint innovation, skill development, strategic partnerships, performance evaluation and documentation, social networking, technology transfer, research and development, market analysis, innovation culture, resource management, education and capacity building, sustainability, and social responsibility.
Conclusion/Implications: Based on the identified categories and indicators, the conceptual model was structured into three interconnected layers: foundational, process, and outcome. The foundational layer comprises the structural and cultural elements that provide the context for effective collaboration, including strategic partnerships, resource management, social networks, and innovation culture. The process layer encompasses the operational interactions and collaborative activities between universities and startups, including knowledge exchange, skill development, research and development, and technology transfer. These processes facilitate the creation of shared value through active knowledge and resource exchange. The outcome layer represents the tangible results and effectiveness of university–startup collaboration, including joint innovation, improved organizational performance, social responsibility, and sustainability. Overall, the proposed model provides a comprehensive framework for understanding and strengthening bidirectional learning between universities and startups and can support the development of more effective collaborative mechanisms in digital marketing.
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