نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیارگروه مدیریت فناوری، دانشکده مدیریت و حسابداری، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران
2 استادیار، گروه مدیریت صنعتی و فناوری، دانشگاه آزاد اسلامی، واحد تهران مرکزی، تهران، ایران
3 دانشجوی دکتری مدیریت فناوری ، دانشکده مدیریت و حسابداری ، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
In recent decades, foresight has evolved from a technological forecasting tool into a mechanism for anticipatory governance and policy learning. However, the research background in this field remains fragmented and interdisciplinary, and no integrated picture of its conceptual clusters and evolutionary trajectory over time has been clearly presented. The aim of this study is to map the knowledge structure and analyze the conceptual evolution of foresight in technology policy and innovation governance during the period from 1967 to 2025 using a bibliometric approach. The data were extracted in October 2025 from the Web of Science database using a title-field search based on a standardized query, resulting in a total of 919 records. The analyses were conducted using the Bibliometrix package in R Studio software and included keyword co-occurrence analysis, co-word network clustering, thematic mapping based on density and centrality indicators, and thematic evolution analysis across four time periods. The findings indicate that the conceptual core of the field is formed around the linkage between “foresight,” “technology assessment,” and “innovation.” Alongside this core, themes related to governance and grand challenges, mature applications in the health sector (including health technology assessment and trend monitoring), as well as sustainability and energy transition, are highly prominent. Furthermore, in recent years, digitalization and artificial intelligence have moved closer to the conceptual core, strengthening the field’s trajectory toward data-driven foresight and anticipatory governance. Based on these findings, it is recommended that in Iran, foresight should be institutionalized within the science, technology, and innovation policy cycle, its connection with technology assessment should be strengthened, and data infrastructure along with governance and data ethics frameworks should be developed to support intelligent foresight.
کلیدواژهها [English]
)