Document Type : Original Article
Authors
1 Ph.D. Student, Business Management, Department of Management, North Tehran Branch, Islamic Azad University, Tehran, Iran
2 Assistant Professor, Business Management, Department of Management, Ghazali Institute of Higher Education, Qazvin, Iran
3 Professor, Business Management, Department of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
4 Associate Professor, Industrial Management, Department of Management, North Tehran Branch, Islamic Azad University,Tehran, Iran
Abstract
Purpose: This study aims to develop a conceptual model for digital content marketing (DCM) by identifying its core components and dimensions.
Method: A mixed-methods approach was employed. First, in-depth interviews were conducted with 15 experts selected via snowball sampling. The interview transcripts were analyzed using MAXQDA software, yielding 137 initial codes which were synthesized into 26 subcategories. Subsequently, a quantitative survey was designed based on these findings. Using Cochran's formula, a sample of 384 users of Digikala's Instagram page was selected through simple random sampling. Data collected from this questionnaire were analyzed using structural equation modeling (SEM) with SmartPLS 3 software to test the study's hypotheses and validate the measurement model's structural validity.
Findings: The analysis of qualitative data resulted in the identification of 26 key subcategories, which were further grouped into several primary dimensions of digital content marketing. These dimensions include: External Environment (Popularity of virtual spaces, competitive landscape, technical limitations, lack of access, and the impact of COVID-19), User Characteristics (Ease of use, individual traits, and social characteristics of customers), Marketing Strategy & Content (Attractiveness of content, methods for increasing audience engagement, providing diverse services, exchanging information, using a customer-friendly style, and enhancing brand building), Organizational Capabilities (Improving technical infrastructure, fostering customer orientation, market expansion, and increasing profitability), Consumer Response (Changing customer behavior, making interactions enjoyable, and increasing participation). The quantitative results from the SEM analysis confirmed that all measured variables (loadings) were statistically significant, providing strong empirical support for the proposed conceptual model.
Conclusion: The results demonstrates that all observable variables were significant and they were confirmed. This concequences indicates that the obtained model can be used in digital content marketing.
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