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This study aims to assess the technological capability of Chinese internet platforms (BAT: Baidu, Alibaba, Tencent) compared to US ones (GAFA: Google, Amazon, Facebook, Apple). More specifically, this study explores Baidu’s technological catching-up process with Google by analyzing their patent textual information.

The authors retrieved 26,383 Google patents and 6,695 Baidu patents from PATSTAT 2019 Spring version. The collected patent documents were vectorized using the Word2Vec model first, and then K-means clustering was applied to visualize the technological space of two firms. Finally, novel indicators were proposed to capture the technological catching-up process between Baidu and Google.

The results show that Baidu follows a trend of US rather than Chinese technology which suggests Baidu is aggressively seeking to catch up with US players in the process of its technological development. At the same time, the impact index of Baidu patents increases over time, reflecting its upgrading of technological competitiveness.

This study proposed a new method to analyze technology mapping and evolution based on patent text information. As both US and China are crucial players in the internet industry, it is vital for policymakers in third countries to understand the technological capacity and competitiveness of both countries to develop strategic partnerships effectively.

The demand for electric vehicles (EVs) has significantly increased in recent years, though some countries like Sri Lanka have reported the opposite direction compared to the global trend. Hence, this study focused on identifying factors affecting EV purchase intention and barriers to the widespread adoption of EVs in a developing country context. Also, this study presents an overview of the theoretical perspectives utilized for understanding consumer intentions and adoption behavior toward alternative fuel vehicles (AFVs).

The questionnaire method was employed, and 394 individuals who lived in Colombo City, Sri Lanka, with valid driving licenses and a hybrid or conventional vehicle were the study sample. The partial least squares structural equation modeling (PLS-SEM) was used to test the research hypothesis.

The findings confirmed that the three relationships between the unified theory of acceptance and use of technology (UTAUT) variables and EV purchase intention are significant, and there is no significant moderator effect from the consumer’s perceived risk.

These results offer useful information for governments and EV companies to better understand consumer behavior toward purchasing EVs.