Leveraging neuroleadership and AI-integrated capabilities: empowering entrepreneurial leaders to drive SME performance

Engineering notes

Key topics: autonomous driving. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

This conceptual article applies the RBV theory and the Technology Acceptance Model (TAM) in SMEs, intending to offer insights into entrepreneurial leadership and SME performance relationships. The research article restructures the emerging conclusions within the existing literature of entrepreneurship, leadership, neuroscience, artificial intelligence, and SMEs. It also provides an integrated new theoretical framework that consists of entrepreneurial leadership, neuroleadership, AI-integrated capabilities, and SME performance. In addition, it responds to the extant research questions on the possible connections between constructs and puts forward several connections that might develop the present organizational literature. This research article has begun the empirical investigation of small and medium enterprises’ performance with this theoretical model. Entrepreneurial leadership applies unique resources (RBV) to boost SME performance, and neuroleadership and AI-combined talents moderate this association based on perceived ease of use and usefulness (TAM) for better performance quality. This research article also fills the gap in the literature identified. To the best of the author’s knowledge, it is the first to synthesize and develop outcomes of entrepreneurship, neuroscience, and AI literature in the SME world. It also proposes a novel, integrated method to explain the entrepreneurial leadership and SME performance relationship.

Links and sources

• PDF from original source

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