متن کاوی شکافهای بین علم و فناوری
ترجمه نشده

متن کاوی شکافهای بین علم و فناوری

عنوان فارسی مقاله: پیش بینی روند فناوری با استفاده از متن کاوی شکافهای بین علم و فناوری: مورد فناوری سلول خورشیدی پروسکایت
عنوان انگلیسی مقاله: Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology
مجله/کنفرانس: پیش بینی فناورانه و تغییرات اجتماعی – Technological Forecasting and Social Change
رشته های تحصیلی مرتبط: مدیریت
گرایش های تحصیلی مرتبط: مدیریت نوآوری و فناوری
کلمات کلیدی فارسی: روند فناوری، پیش بینی فناوری، متن کاوی، فناوری سلول خورشیدی پروسکایت
کلمات کلیدی انگلیسی: Technology trend، Technology forecasting، Text mining، Perovskite solar cell technology
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.techfore.2019.01.012
دانشگاه: College of Economics and Management, Beijing University of Technology, Beijing, China
صفحات مقاله انگلیسی: 18
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.852 در سال 2018
شاخص H_index: 93 در سال 2019
شاخص SJR: 1.422 در سال 2018
شناسه ISSN: 0040-1625
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13362
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1-Introduction

2-Literature review

3-Methodology

4-Case study

5-Discussion

6-Conclusions and future study

Acknowledgements

Appendix I

References

بخشی از مقاله (انگلیسی)

Abstract

How to detect and identify the future trends of emerging technologies as early as possible is crucial for government R&D strategic planning and enterprises’ practices. To avoid the weakness of using only scientific papers or patents to study the development trends of emerging technologies, this paper proposes a framework that uses scientific papers and patents as data resources and integrates the text mining and expert judgment approaches to identify technology evolution paths and forecast technology development trends within the short term. The perovskite solar cell technology is selected as a case study. In this case, the text mining and expert judgment methods are applied to analyze the technology evolution path, and gaps analysis between science and technology is used to forecast the technology development trend. This paper will contribute to the technology forecasting and foresight methodology, and will be of interest to solar photovoltaic technology R&D experts.

Introduction

In recent years, we have witnessed the emergence of major advancements in new technologies that have disruptive characteristics, such as information technology, nanotechnology, biotechnology, and new material technology. The emergence and development of these new technologies not only changed the global competitive structure, but also created new industries, changed the lives of people, and changed the socio-economic production mode (Rifkin, 2011). Identifying the future trends of these new technologies as early as possible is crucial for governments’ and enterprises’ research and development (R& D) strategic planning to gain a first-mover advantage in future global competition. Many decision makers are aware of the significance of understanding of the emergence path, and identifying the future development trends of these new technologies for an organization’s competitiveness and sustainable development when facing the wave of revolutionary technological changes (Li et al., 2015). Therefore, it becomes a strategic concern for public sectors and enterprises to identify and grasp the opportunity to develop their new technologies, which will ultimately contribute to their international competitiveness and sustainable development. This strategic issue raises one question: How can one detect and forecast the future development trend of these emerging technologies given the better understanding of their emergence? In response to this question, this paper develops a framework for detecting and forecasting the future development trend of these emerging technologies, based on an understanding of their existing evolution path and the identification of the gaps between science and technology.