https://www.nowavari.ir/ Innovation Management Journal en daily 1 Fri, 22 May 2026 00:00:00 +0330 Fri, 22 May 2026 00:00:00 +0330 https://www.nowavari.ir/article_252301.html Customs support policies are used to enhance the competitiveness of knowledge-based firms by reducing costs, facilitating access to production inputs, and strengthening innovation capacity. The aim of this study is to develop a framework for evaluating customs support programs in Iran. This research adopts a mixed-methods approach. First, an evaluation framework was developed through a review of the literature, analysis of policy documents, and consultation with experts. The framework distinguishes three levels of evaluation: outputs (e.g., process facilitation and cost reduction), outcomes (improvements in firm performance), and impacts (export growth and enhanced competitiveness). Second, the support programs were assessed using available implementation data. Given the recent implementation of programs and the limited availability of firm-level performance data, the analysis focuses on outputs and outcomes. The geographical scope of the study covers knowledge-based firms in Iran, while the temporal scope spans the implementation periods of the programs, mainly from 2016 to 2025. The findings indicate that support policies have contributed to streamlining procedures, reducing administrative barriers, and improving firms’ access to inputs and equipment. However, their contribution to improvements in firms’ economic and innovation performance cannot be assessed. Therefore, strengthening evaluation systems, developing integrated data infrastructures, and aligning customs support measures with broader innovation policy objectives are essential prerequisites for assessing the long-term impacts of these policies. https://www.nowavari.ir/article_252302.html With the expansion of artificial intelligence and the gradual shift in countries’ focus from algorithm development to organizational deployment, the importance of institutions that act as intermediaries between technology, innovation ecosystem actors, and market needs has increased. “AI intermediary firms” are among such institutions and require structural, institutional, technical, and technological requirements to effectively fulfill their role in AI utilization. This study aims to identify and prioritize these requirements within the innovation ecosystem of mining industries. In the first stage, a preliminary list of requirements was extracted through a review of the literature and analysis of relevant policy documents, and then organized into conceptual dimensions. These dimensions were refined and finalized based on expert opinions in artificial intelligence and innovation. In the quantitative phase, the final requirements were prioritized using experts’ ordinal judgments, and agreement levels and ranking differences were examined. The findings indicate that all extracted dimensions are statistically significant. The highest agreement is associated with human capital and key expertise, business models and investment, and technical and operational infrastructure, whereas commercial capabilities and business development show the lowest consensus. The results provide an integrated view of the formation and performance requirements of AI intermediary firms and can serve as a basis for policymakers and managers to strengthen capacity building, facilitate technology utilization, and improve AI governance. https://www.nowavari.ir/article_252303.html The Internet of Things (IoT), as a key technology of the digital transformation era, has experienced rapid growth, increasing the need to identify its emerging trends for researchers, policymakers, and technology managers. This study aims to identify emerging trends in IoT technology based on patent data analysis and artificial intelligence (AI) methods, particularly text mining. This applied study was conducted using a descriptive-analytical approach and a data science methodology. The required data were extracted from the global patent database Lens and, after preprocessing, active IoT-related patents were analyzed. To identify technological trends, International Patent Classification (IPC) analysis, text mining of patent titles, and frequency analysis of keywords and applications were employed. The results showed a significant increase in IoT-related patent activity in recent years, with Samsung, IBM, Qualcomm, Intel, LG, and Cisco identified as major players. IPC analysis indicated that innovations primarily focus on wireless communications, network management, information security, and data processing. Text-mining findings revealed that smart living, smart industry and manufacturing, and smart monitoring are among the major emerging IoT trends. Furthermore, autonomous vehicles, smart factories, and things as customers were identified as major applications of this technology. The findings can support technology policymaking, research and development planning, and technology foresight in digital technologies.