واکاوی ابعاد و مولفه های موثر بر انتقال فناوری از دیدگاه انتقال دهنده فناوری: با روش فراترکیب (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
امروزه به دلیل پیشرفت های فناورانه، بسیاری از گیرندگان پیشین فناوری به عنوان انتقال دهنده فناوری عمل می نمایند و این امر پیچیدگی های جدیدی در فرآیند انتقال فناوری ایجاد کرده است. لذا این پژوهش به دنبال پاسخ به این سؤال است که ابعاد و مؤلفه های مؤثر بر انتقال فناوری از دیدگاه انتقال دهنده فناوری کدم اند؟ در این پژوهش، از رویکرد مرور نظام مند ادبیات با بهره گیری از روش فراترکیب مبتنی بر دستورالعمل سندلوفسکی و باروسو استفاده شده است. طی مرور نظام مند 188 مقاله اولیه، درنهایت 33 مقاله مرتبط باهدف پژوهش انتخاب شدند. معیارهای ورود شامل مقالات منتشرشده در خصوص انتقال فناوری از دیدگاه دهنده فناوری بین سال های 2008 تا 2024 برای مقالات انگلیسی و 1398 تا 1403 برای مقالات فارسی بوده است. برای ارزیابی پایایی یافته ها از ضریب کاپا استفاده شده است که مقدار 75/0 پایایی قابل قبولی را نشان می دهد. برای اعتبارسنجی مدل پیشنهادی و افزایش مقبولیت آن، از روش های بررسی توسط متخصصان این زمینه استفاده و نتایج به دست آمده توسط آنان بررسی و تأیید شده است. بر اساس یافته ها، مهم ترین ابعاد تأثیرگذار بر انتقال فناوری از منظر انتقال دهنده فناوری، شامل 127 مؤلفه که در 12 بعد اصلی شامل قوانین و سیاست ها، ظرفیت جذب فناوری، فرهنگ، عوامل اقتصادی، همکاری و ارتباطات، تجاری سازی فناوری، منابع انسانی، آموزش، مالکیت فکری، انطباق فناوری، ارزیابی فناوری، جذب و تحلیل فناوری دسته بندی شده اند.Analyzing the Dimensions and Components Affecting Technology Transfer from the Perspective of the Technology Transferor: with Meta-Synthesis Method
Nowadays, due to technological advances, many technology recipients act as technology providers, which has created new complexities in the technology transfer process. Therefore, this study seeks to answer the question of what the dimensions and components are that affect technology transfer from the perspective of the transferor. In this study, Sandelowski and Barroso's meta-synthesis qualitative approach was used. During a systematic review of 188 initial articles, 33 articles related to the research objective were finally selected. The inclusion criteria comprised articles published from the perspective of the technology provider between 2008 and 2024. The kappa coefficient was used to assess the reliability of the findings, which showed an acceptable reliability of 0.75. To validate the proposed model and increase its acceptability, review methods were used by experts in this field. The results identified 127 components in 12 main dimensions. They are categorized into laws and policies, technology absorptive capacity, culture, economic factors, cooperation and communication, technology commercialization, human resources, training, intellectual property, technology adaptation, technology assessment, and technology absorption. Introduction Over the past two decades, the trend of technology transfer has changed significantly. Emerging economies, such as Brazil and India, once primarily recipients of imported technologies, have emerged as key players in the global technology transfer landscape, increasingly acting as transferors (Lee, 2013). Despite extensive research on technology transfer, the literature has predominantly focused on the recipient’s perspective. This study aims to address this research gap by systematically identifying and categorizing the dimensions and components that impact technology transfer from the perspective of the transferor. By conducting a systematic literature review, this study develops a theoretical framework that not only lays the groundwork for future measurement tools but also ensures practical applicability in developing economies, such as Iran, through expert validation. This research provides a structured categorization of key factors, offering both theoretical insights and practical implications for improving policymaking in technology transfer initiatives. esearch Background The literature on technology transfer from the transferor’s perspective, though limited, provides critical insights into the factors influencing the process. Olakada et al. (2024) investigated the impact of technology transfer on the performance of Nigeria’s oil and gas sector through technology licensing, emphasizing dimensions such as the type of technology, licensing conditions, technical support, transparency, trust, and the institutional environment. Similarly, Sampson (2024) identified the risk of imitation, value chain type, contract type, intellectual property policies, technology development, and institutional frameworks as key determinants affecting technology transfer from the transferor’s viewpoint. In the pharmaceutical industry, Pajayatil et al. (2023) highlighted factors critical to successful technology transfer from the transferor’s perspective, including documented knowledge, employee training, analytical methods, collaboration and coordination, initial assessments and redesign, production and packaging methods, and equipment and machinery. Hipp et al. (2024), in their examination of barriers to technology transfer, underscored the influence of economic factors, international collaborations, knowledge production, accumulation, and dissemination on the transfer process. Method This study, aiming to identify the dimensions and components influencing technology transfer from the transferor’s perspective, employed an applied, qualitative approach based on systematic literature review and meta-synthesis, following the seven-stage model of Sandelowski and Barroso (2007). Data were collected from credible journals, databases, and institutional websites. The time frame covered English articles from 2008 to 2024 and Persian articles from 1398 to 1403. From an initial set of 188 articles, 59 were selected based on relevance and alignment with research objectives. These were evaluated using the 32-item COREQ checklist, leading to the selection of 33 high- and medium-quality articles for final analysis. To assess reliability, the kappa coefficient was applied, yielding a value of 0.75, indicating strong inter-rater agreement. Model validation involved a multi-stage expert review process. A panel of five experts—with master’s or doctoral degrees and over a decade of experience in technology transfer—was purposefully selected. Data were gathered through in-depth interviews across several sessions using triangulation, iterative reviews, and peer validation. Experts were chosen based on academic background and practical experience. Their feedback refined the conceptual framework, ensuring both reliability and contextual applicability, particularly in developing countries. Discussion and Results This study aimed to identify the dimensions and components influencing technology transfer from the provider’s perspective, offering a comprehensive view of its complexity. Economic factors—such as export volume, inflation, and exchange rates—directly impact provider decisions by shaping financial frameworks and offering participation incentives. Supportive legal structures and transparent policies are also essential, as they foster trust and streamline bureaucratic processes. Organizational culture emerged as another key factor; unmanaged cultural differences between provider and recipient can hinder effectiveness. Strengthening mutual understanding and intercultural communication is thus vital. Additionally, the recipient’s absorptive capacity significantly affects success. Organizations with robust infrastructure and knowledge systems are better positioned to integrate new technologies. Qualified and continuously trained human resources are foundational for transferring both explicit and tacit knowledge. Effective commercialization is equally important; technology must have market viability and economic potential, necessitating solid marketing strategies and opportunity assessments. Intellectual property rights also play a central role—clear legal protections enhance provider willingness by minimizing risks of misuse or unauthorized replication. Technology assessment—including competitiveness, complexity, and applicability—is crucial for preparing technologies for transfer and reducing uncertainties. The provider actively participates in the absorption phase by delivering structured knowledge, including models, design elements, and technical components, aligned with contractual terms. Technological adaptation is another critical dimension. Aligning imported technologies with local standards, culture, and resources improves their effectiveness and sustainability. Finally, successful transfer depends on collaboration among governments, providers, recipients, research centers, and industries. Enhancing such cooperation supports knowledge sharing, process refinement, opportunity recognition, cost efficiency, and productivity growth. Conclusion This study employed a meta-synthesis approach to explore the key dimensions and components influencing technology transfer from the provider’s perspective. Through the systematic review of 33 selected articles, 127 initial conceptual codes were extracted, leading to the identification of 12 core components forming a conceptual framework that clarifies the complex dynamics of the transfer process in both national and international contexts. The findings emphasize the crucial role of organizational culture, effective collaboration with recipients, and human capital development. These components, if optimized, can significantly enhance technology transfer initiatives within Iranian tech-based organizations. Policymakers can also draw on the conceptual insights to refine support structures and policies. Legal and regulatory frameworks, intellectual property rights, commercialization, and economic factors emerged as vital enablers. These dimensions help identify structural barriers and shape targeted interventions, particularly in cross-border technology transfer projects. While grounded in qualitative analysis and theoretical modeling, this framework offers practical applications—such as developing assessment checklists and operational indicators based on the identified components. However, the absence of empirical validation marks a key limitation. Future studies should employ field-based methods and structured techniques like fuzzy Delphi and agent-based simulation (e.g., using AnyLogic) to test and localize the framework. Additionally, since the components were not prioritized, multi-criteria decision-making methods like WASPAS are recommended to rank factors and guide the development of a more effective, context-specific operational model for technology transfer.
تبلیغات
