Designing a Smart Marketing Strategy Model for the Ministry of Agriculture Jihad: A Digital Transformation–Based Approach

Abstract

This study aimed to design and validate a digital transformation–based smart marketing strategy model for the Ministry of Agriculture Jihad by identifying its key components, determining their causal and hierarchical relationships, and evaluating the empirical adequacy of the proposed model. An applied exploratory sequential mixed-methods design was employed. In the qualitative phase, a seven-stage meta-synthesis was conducted on Persian and international studies published between 1991 and 2026, resulting in the selection of 33 high-quality studies from 308 initially retrieved records. Extracted codes were synthesized through qualitative content analysis and prioritized using Shannon entropy. In the second phase, 25 experts in agricultural management, marketing, technology, and digital transformation participated in interpretive structural modeling to determine the hierarchical relationships among the identified components. In the quantitative phase, a researcher-developed questionnaire was electronically administered to managers and experts of the Ministry and provincial Agricultural Jihad organizations. A total of 668 valid responses were analyzed using partial least squares structural equation modeling in SmartPLS. Reliability, convergent validity, discriminant validity, multicollinearity, effect size, explanatory power, and predictive relevance were assessed. The meta-synthesis identified 37 dimensions classified into 13 principal components. Shannon entropy showed that entry into online markets and digital-marketing education had the highest importance coefficients, followed by support for agricultural startups. Interpretive structural modeling placed supportive policies and regulations and digital and technological infrastructure at the foundational level, while sustainability and smart agriculture emerged as the most dependent final outcome. Cronbach’s alpha and composite reliability coefficients exceeded 0.70, average variance extracted values were above 0.50, and both Fornell–Larcker and HTMT criteria confirmed discriminant validity. All variance inflation factors were below 3. Positive Q² coefficients confirmed predictive relevance, and the structural model explained approximately 65% of the variance in the endogenous constructs. Smart marketing in the Ministry of Agriculture Jihad should be implemented as an integrated transformation process beginning with supportive regulation and digital infrastructure, progressing through analytical capability, farmer empowerment, knowledge management, supply-chain integration, innovation, and market development, and ultimately leading to customer value, brand development, and sustainable smart agriculture.