Lidan Jiang’s research while affiliated with Beijing University of Posts and Telecommunications and other places

The rapidly growing state of energy consumption and the urgency of mitigating the harmful effects of climate change have accelerated our transition to renewable energy. This paper proposes a multi-level framework for exploring the global competition to develop renewable energy technologies. Through a combination of text mining techniques and by analyzing a corpus of patents covering six renewable energy technologies from 1970 to 2019, we reveal the lifecycle of these technologies, the original sources of these technologies, their potential markets, and the different supply and demand patterns of the major countries/regions involved. The results show that solar and wind energy are currently the most widely used renewable energy sources, yet biomass is the only energy source still in its growing stage. China's patents have seen a rapid upward trend, spurred on by strong policy promotion, which runs counter to the decrease in patent applications seen in most other major countries in this area. However, China's technology imports still far outweigh its exports, indicating that there is still a sizeable gap between China and some of the more developed countries like the United States, Germany, France, and the United Kingdom in terms of high-quality, high-value patents. Accordingly, China, the United States, and Japan are currently the leading in the world's renewable energy markets. That said, the market potential of Europe, Canada, and Australia should not be underestimated. These and more themes are discussed from a political, economic, environmental, and global governance perspective. This paper provides useful insights into the global renewable energy technology landscape, particularly the competitive dynamics at play. The aim is to guide policy makers or managers on the next steps in our progress toward applying and using renewable energy at scale.

Technology development is a blend of inheritance and innovation that follows certain rules along a technology trajectory. This trajectory charts a technology's evolution and is among the best-supporting data for decision making. Technology life cycle (TLC) analysis, as one of the foundational topics in the field of technology management field, is of vital importance for describing the evolutionary path of technology. However, most current methods simply rely on static patent indicators, which neglect the dynamic aspects of a technology's development. To overcome this limitation, we propose a framework of diverse characteristics and novel procedures for identifying the entire span of a technology's life cycle from a series of patent citation networks. After retrieving patent data with a well-defined search strategy, a sequence of patent citation networks is constructed year by year. Network attribute indicators are then calculated for each of the networks and used to inform an evolution model, which reveals the TLC. To illustrate the strengths and potential of this approach, we have taken additive manufacturing technology as an example for analysis. Through the framework, we are able to demonstrate the technology at various stages of its maturity and how it has changed over time, along with some areas of competitive advantage and promising future opportunities.

This paper presents the findings from a thorough analysis of international technology diffusion (ITD) in artificial intelligence (AI) technologies. We construct a novel framework to explore the patterns of ITD in AI based on patent data published from 1970 to 2019. To this aim, we establish a nexus between technology innovation (TI) capacity and international technology diffusion (ITD) degree, and divide the countries/regions into three different groups—the leading, middle and backward. Considering the intersecting characteristic of AI technology, this paper examines the ITD patterns in the whole, single-field and intersecting-field AI technology areas. Empirical results show that: (1) Similar patterns are observed in the whole and single-field AI technology. ITD degree decreases significantly as TI capacity increases in leading countries, while it always remains high though the TI capacity improves in backward countries. Middle countries, however, show a transitional state between the two. (2) Compared to the whole AI and single-field AI technology, the pattern of ITD in intersecting-field AI technology is different. The number of nodes in the intersecting-field AI technology has decreased significantly, and the trend is more pronounced in middle and backward countries than in leading countries. These patterns imply that the technological innovation achievements of middle and backward countries will be first identified and utilized by leading countries, which will broaden the growing digital divide between countries and pose a more significant challenge to achieving technological catch-up in the future.

Addressing many of the world's contemporary challenges requires a multifaceted and integrated approach and, in this respect, interdisciplinary research (IDR) is increasingly recognized as central to both academic interests and national science policies. In spite of the growing attention given to IDR, the impact of IDR remains under-investigated. In this study, we analyzed the influence of interdisciplinarity on citation impact (particularly, WoS citation) and broader impact (particularly, PloS usage) at the article level. We measured IDR in terms of three different elements of diversity variety , balance, and disparity-as well as the integrated diversity overall. The results of negative binomial regression analysis with field fixed effects and robust standard errors show the positive effects of interdisciplinarity on both academic and broader impact. From an analysis of trends over time, the results show that higher interdisciplinary publications tend to attract more citations and have higher PLoS usage. Compared to citations, which need a more extended period to accumulate, the advantage of measuring impact with PLoS usage is its immediacy. Also, there are signs that PLoS usage and citations can mutually reinforce each other.