Introduction:

In today’s highly competitive and technology-driven landscape, effective collaboration and the strategic utilization of knowledge and innovation across various sectors—including education, industry, and entrepreneurship—have become critically important. Universities play a pivotal role in generating scientific knowledge, advancing technological development, and cultivating skilled human capital. Meanwhile, startups—serving as engines of innovation and new business development—necessitate strong communication channels and collaboration with academic institutions to leverage their scientific and technical expertise. Mutual learning processes and the transfer of knowledge between universities and startups can significantly enhance the effectiveness of these collaborations. Consequently, there is a pressing need for both scholarly and practical models that facilitate and strengthen these learning processes and partnerships. This study aims to develop a comprehensive model of mutual learning within university-startup collaborations in the field of digital marketing, offering a practical, evidence-based framework to foster these relationships and optimize the potential inherent in this domain.

Methodology:

This research adopts an applied purpose and a qualitative approach for data collection, employing content analysis to interpret the data. The population comprised experts, professors, and managers involved in university-industry relations, as well as individuals who have launched startups. Using purposive sampling, a total of 31 interviews were conducted until reaching theoretical saturation. To ensure the validity of the findings, insights from several specialists in startups and digital marketing were incorporated. Reliability was established through the analysis of core themes and patterns in participants’ responses. Data analysis was performed through qualitative content analysis, utilizing coding techniques to identify and extract key themes and indicators.

Findings:

The derived model of mutual learning between universities and startups encompasses 13 primary categories, 39 subcategories, and 117 indicators. The main categories identified include knowledge exchange, joint innovation, skill development, strategic partnerships, performance evaluation and documentation, social networking, technology transfer, research and development, market analysis, fostering an innovation culture, resource management, training and empowerment, as well as sustainability and social responsibility.

Conclusion and Implications:

Based on these categories and indicators, a conceptual framework was structured across three interconnected layers. The foundational layer—comprising infrastructure—encompasses essential elements such as strategic partnerships, resource management, social networks, and an innovation culture, which provide the groundwork for effective collaboration. These elements, rooted in theories of strategic management and organizational culture, serve as the bedrock for fostering productive joint efforts. The process layer involves operational and executive activities carried out between universities and startups, including knowledge exchange, skill development, research and development, and technology transfer. These active processes are instrumental in generating shared value and mutual benefits. The final layer—outcomes—reflects tangible results and organizational effectiveness, demonstrating that collaborations lead to joint innovation, improved performance, and the advancement of social responsibilities and sustainability, as evidenced through performance evaluation models and organizational innovation frameworks. This comprehensive model offers a strategic pathway to enhance university-startup collaborations, ultimately contributing to innovation, economic development, and societal progress.