نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکتری، گروه مدیریت تکنولوژی، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
2 گروه مدیریت صنعتی، واحد کرج، دانشگاه آزاد اسلامی، کرج، ایران.
3 استادیار، گروه مدیریت، واحد شیراز، دانشگاه آزاد اسلامی، شیراز، ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
In the digital transformation era and increasing technological complexity, technology scouting has become vital for maintaining organizational competitiveness. This study, aiming to identify new research areas of artificial intelligence in technology scouting systems of high-tech companies, employed text mining methods to analyze 70 reputable scientific articles published between 2014 and 2024. The analysis process included data cleansing, key concept identification, topic modeling, and machine learning-based concept clustering. The findings indicate that artificial intelligence plays a crucial role in enhancing the efficiency and accuracy of technology scouting systems. Frequency analysis and concept clustering showed that deep learning algorithms with a frequency of 450, advanced sentiment analysis with a frequency of 380, and intelligent recommender systems with a frequency of 320 are among the most important identified concepts. Sentiment analysis of the texts showed that 65% of perspectives on the application of AI in technology scouting are positive. Additionally, five strategic areas were identified: emerging technologies, new scouting methods, extensive applications of artificial intelligence, ethical and technical challenges, and key industrial domains. This research emphasizes the importance of combining artificial intelligence capabilities with human expertise for more effective scouting, encompassing improved predictive accuracy, increased analysis speed, and broader coverage of resources.
کلیدواژه‌ها [English]
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