In today's era, emerging technologies have rapidly transformed traditional industrial paradigms, generating both significant opportunities and complex challenges. Effectively leveraging these opportunities while mitigating the associated risks requires a foundation in strategic business management (Mirzaei & Darbani, 2023). Striking a balance between the integration of smart technologies and strategic decision-making has become a critical success factor for contemporary industries and enterprises. Consequently, leading organizations are revisiting and realigning their strategies to match the realities of the technological age (Toraca et al., 2024). By combining smart technologies with traditional strategic management principles, managers can make faster, more efficient, and more comprehensive decisions that address both internal dynamics and external forces (Dongal & Leonardo, 2022). To adopt a strategic approach in capitalizing on these advancements, lessons from globally successful countries can be invaluable. Over the past five decades, East Asian nations—most notably China—have achieved remarkable progress through intelligent strategic management. Adapting such experiences may offer effective solutions for Iran as well (Najafi & Malekakhlaq, 2024).
This study is an applied-developmental research from a purpose-oriented perspective, conducted with the aim of designing a smart strategic management model inspired by China’s experience (case study: automotive industry exports). Based on the data collection method, the research is classified as a survey and cross-sectional study. To achieve the research objectives, an exploratory mixed-methods design was adopted.
In the qualitative phase, a comprehensive database search yielded 36 articles related to China’s automobile exports. After applying purposive sampling techniques, 28 relevant articles were selected and subjected to qualitative analysis. The quantitative phase targeted managers within the national automotive industry who are involved in strategic planning and the export of domestic vehicles. Using purposive sampling, 12 participants were selected for the quantitative analysis and for contributing to the development of the research model.
The primary tools for data collection included library resources, credible domestic and international articles, and a structured questionnaire. To ensure the validity of the qualitative component, the CASP (Critical Appraisal Skills Programme) model was utilized. Articles were assessed based on ten CASP criteria, and only those scoring above 21 were included in the study.
For the validation of the questionnaire, content validity was confirmed through expert review. A meta-synthesis approach was used to identify the foundational categories and develop the initial conceptual model. In the second phase, the Structural Interpretive Modeling (ISM) method was employed. ISM calculations were performed using MicMac software.
In the first stage, the research categories were identified using the meta-synthesis method. Meta-synthesis is employed to integrate findings from multiple qualitative studies in order to generate comprehensive and interpretive insights. Unlike quantitative meta-analysis—which aggregates statistical data from previous studies—meta-synthesis focuses on the synthesis of interpretations derived from the original qualitative data of selected research.
Essentially, meta-synthesis is a qualitative research approach that draws upon the results of prior studies on a common topic to build a deeper understanding. In this method, the researcher integrates secondary data and interpretations from existing literature to address the objectives of the current study and derive new insights.
To meet the research objectives, the meta-synthesis approach was applied based on the model proposed by Sandelowski and Barroso (2007).
The constructs collected from the articles are: branding and international marketing of Chinese automobiles, technology transfer policy, foreign investment policies, smart trade policy, tariff policies, smart energy policy, government policy.
Keywords:Based on the research model, it was found that government policymaking influences both smart policymaking in the energy sector and tariff policy design. These two components, in turn, affect smart trade policymaking, which subsequently drives foreign investment strategies and technology transfer policies. Ultimately, through their mutual interactions, these factors contribute to the development of branding and international marketing strategies in China’s automotive industry.