ABSTRACT

Innovation efficiency has become a phenomenon of global interest. This paper reviews 165 articles from academic journals of innovation efficiency, applies the data-driven text mining approach to map major streams of research and identifies widely used theories, contexts, and methods. With the evolution of innovation behaviours and research context, the literature is mainly classified to innovation, innovation efficiency, and green innovation. By investigating definition evolution, research contents, and determinants of innovation efficiency, the paper also provides the main approaches for investigation are data envelopment analysis, stochastic frontier analysis, and Malmquist index. The paper highlights the need for interdisciplinary approaches to transcend the boundaries. Development and adoption of network interaction, regulation policy effects evaluation, time-varying investigation, the use of multi-level methods, and consideration of unexplored indicators for various contexts are among the recommendations for future research.

摘要

创新效率已成为全球关注的现象。本文回顾了创新效率学术期刊上的165篇文章，应用了数据驱动的文本挖掘方法来绘制主要的研究流，并确定了广泛使用的理论，环境和方法。随着创新行为和研究背景的发展，文献主要分为创新，创新效率和绿色创新。通过研究定义演化，研究内容和创新效率的决定因素，本文还提供了主要的研究方法：数据包络分析，随机前沿分析和Malmquist指数。本文强调了跨学科方法超越边界的必要性。开发和采用网络交互，