No abstract

PurposeThe 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.Design/methodology/approachThis work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.FindingsThe research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.Originality/valueThe finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

Summary Length–weight relationships (LWRs) of three Chinese endemic fish species (Gymnocypris eckloni eckloni Herzenstein, 1891, Platypharodon extremus Herzenstein, 1891 and Triplophysa pseudoscleroptera (Zhu & Wu, 1981)) were analyzed, collecting from the upper Yellow River (Xunhua and Guide Counties, Qinghai Province). Totally 347 specimens monthly collected by gill nets with 40 mm mesh size and traps with 5 m length from August to October 2014, were used to estimate the relationship parameters. The allometric factor b values ranged from 2.96 in T. pseudoscleroptera to 3.33 in G. eckloni eckloni. The condition factor a values varies between 0.0063 and 0.0175 in three species. Three WLRs of fishes distributed in the upper Yellow River were firstly reported and will fill in some of the empty spaces on endemic species in the Fishbase.