| 面向老龄社会的新兴技术预测与评价研究 |
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| 引用本文： | 黄鲁成,米兰,吴菲菲.面向老龄社会的新兴技术预测与评价研究[J].科研管理,2022,43(10):51-60. |
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| 作者姓名： | 黄鲁成 米兰 吴菲菲 |
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| 作者单位： | 1.哈尔滨工程大学经济管理学院，黑龙江 哈尔滨150001；
2.北京工业大学经济与管理学院，北京100124 |
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| 基金项目： | 国家社会科学基金重大项目：“依靠科技创新应对人口老龄化跨学科研究”（17ZDA119）。 |
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| 摘 要： | 当前面向老龄社会的新兴技术预测相关研究十分匮乏，且存在分析节点聚焦于新兴技术已知的事后分析，分析对象局限于单一技术领域的局限性，导致新兴技术预测结果即时性、可靠性不高。鉴于此，本文基于2019美国发布的《Emerging Technologies to Support an Aging Population》报告，对面向老龄社会的新兴技术领域进行全局的系统梳理与归纳，利用语义挖掘和空间向量模型深入探析专利主题与技术内涵，引入数据降维方法与可视化分析识别技术空位，并嵌入更具前瞻性的实时专家网络评论文本进行社会感知分析，有效识别并评估了养老科技潜在新兴技术。研究结果表明：通过技术空位与社会感知双重验证，有效降低了新兴技术预测结果的风险性。面向老龄社会的新兴技术趋势为：老年大数据与信息采集与处理技术、老年人出行辅助与防护技术、老年人医疗保健技术、老年智能家居技术、老年远程护理辅助系统与技术、老年人认知管理技术。
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| 关 键 词： | 老龄社会 新兴技术 技术预测 语义挖掘 社会感知 |
| 收稿时间： | 2019-09-26 |
| 修稿时间： | 2020-03-04 |
Research on forecasts and evaluation of emerging technologies for the aging society |
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| Huang Lucheng,Mi Lan,Wu Feifei.Research on forecasts and evaluation of emerging technologies for the aging society[J].Science Research Management,2022,43(10):51-60. |
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| Authors: | Huang Lucheng Mi Lan Wu Feifei |
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| Institution: | 1. School of Economics and Management, Harbin Engineering University, Harbin 150001, Heilongjiang, China;
2. School of Economics and Management, Beijing University of Technology, Beijing 100124, China; |
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| Abstract: | Population aging is a major challenge that drives the future for the next 40 years, which is just as important as the environmental challenges. In many Asian and European countries, the proportion of the older population relative to the total population has greatly increased and is still increasing, which will bring serious social problems. More experts and governments began to pay more attention to the role of technology innovation in responding to the aging society. Science, technology and innovation are widely perceived to provide the means for solving this "grand challenge" of demographic ageing. Innovations for older persons are usually referred to as gerontechnology, which is composed of two words: gerontology and technology. The literal meaning is composed of gerontology that conducts scientific research on aging and research, development and design of products, services and methods. Among them, gerontology is the scientific research on the elderly, including biological, psychological, social and medical aspects of aging. Technology includes research and development and design of new and improved technologies, products and services, covering chemistry and physics of knowledge in the fields of construction, machinery, engineering, electronics, information, communication, and so on.〖JP〗
〖JP3〗However, there exists a lack of research on the prediction of emerging gerontechnology for the current aging society, moreover, the analysis node focuses on the post-analysis of known emerging gerontechnology and the analysis object is limited to a single technical field. These limitations lead to it impossible to clearly define which of the emerging technologies applied to the aging society. Besides, the current research does not conduct an overall analysis of emerging technologies for the elderly. This is seriously inconsistent with the huge role played by the global population aging in the economic and social development process, and it also reflects that the current scholars′ research on the emerging technologies of elderly science and technology is insufficient and the research has not paid enough attention. In this context, we take the gerontechnology as the research object, and use the emerging technology prediction as a means to study the problem of emerging technology prediction for the aging society. In addition, most of the current technical prediction studies are based on single patent data and literature data, which have the limitations of time lag and greater risk of prediction results.
In view of the above limitations, this paper combines the patent data and online network data, carries out patent semantic mining through text mining technology, draws patent map by combining spatial vector model and similarity calculation. Besides, this paper carries out the comparative analysis with network crawling expert opinion topic, so as to realize the prediction and evaluation of emerging technologies towards the aging society. To be specific, firstly, based on the Emerging Technologies to Support an Aging Population report released by the United States in 2019, we systematically sorted out and summarized the emerging technologies for the aging society, so as to determine the retrieval expression of patent technologies and collect patent data. Secondly, semantic mining and similarity algorithm are used to deeply explore patent themes and technology gaps in the whole field, so as to complete the preliminary identification of emerging technologies. Finally, a comparative analysis is made between the identification results and the more forward-looking expert network comment text. Through the comparative analysis method, the identification results are effectively evaluated and supplemented to reduce the risk of the predicted results.
The comparative analysis results based on patent data semantic mining and embedded real-time network data show that, emerging technology trends supporting the aging society can be summarized as: big data and information collection and processing technology for the elderly, travel assistance and protection technology for the elderly, medical care technology for the elderly, smart home technology for the elderly, remote nursing assistance system and technology for the elderly, and cognitive management technology for the elderly. As can be seen from the results, the overall level of social cognition of products and services for the elderly is constantly improving. In addition, the integration of technologies for the elderly and high-tech is deepening, the technical content of old-age care products is constantly improving, and the development of intelligent and precise old-age care has begun to take shape.
In the current global situation where the total supply of elderly technology products and services is seriously insufficient, the structure is unreasonable, and the level is not high, how to capture the "silver economy" contains huge industrial development space, and has become an important driving force for the economic growth of various countries. An aging country should increase investment in emerging technologies for the elderly, fully tap its development potential, build a strategic core of the emerging gerontechnology system in advance, and provide technical support for the cultivation of the elderly technology industry. |
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| Keywords: | aging society emerging technology technology forecast semantic mining social perception |
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