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Corporate innovation legitimacy is the key guarantee for listed companies to obtain returns from innovation activities. The purpose of this paper is to investigate the effect of analyst coverage on corporate innovation legitimacy based on effective supervision hypothesis and market pressure hypothesis. Moreover, it examines the moderating effect of analyst coverage characteristics, individual corporate behavior, external governance mechanism on the relationship between analyst coverage and corporate innovation legitimacy. The hypotheses are tested using a data set of Shanghai and Shenzhen A-share listed companies from China Research Data Service Platform (CNRDS) database, Hexun.com and CSMAR database. To overcome sample selection bias and reverse causality, this paper conduct robustness test using propensity score matching, lag variable, substitution variable and sample reduction to ensure the reliability of the research conclusions. Findings show that analyst coverage can effectively improve the innovation legitimacy of listed companies. In addition, based on the heterogeneity of the above relationship in different contexts, further research finds that the depth of analyst tracking, and the assessment of analyst optimism strengthen the positive impact of analyst coverage on innovation legitimacy. The implementation of green social responsibility brings a good reputation for the company, thereby helping analysts to focus on improving the legitimacy of innovation; In the market environment with relatively perfect external governance mechanism, the stronger the effect of analyst coverage on corporate innovation legitimacy. Prior studies mostly considered the R&D investment and other factors to overlook how other dimensions influence companies from the perspective of quantity. The research conclusion confirms the significance of analyst coverage as an external corporate governance mechanism, further enriches the theoretical research framework of innovation legitimacy, and has certain reference value for the improvement of innovation quality of listed companies. [ABSTRACT FROM AUTHOR]

Probabilistic site characterization is the cornerstone of data-centric geotechnics, which underpins the digitalization in geotechnical engineering. The essential aspect of probabilistic site characterization is to reasonably infer the probability density distributions of geotechnical parameters, based on field and laboratory data. In this paper, a clay property database, SZ-CLAY/11/5130, was established by collecting geotechnical investigation reports from 52 engineering projects in Shenzhen city. This SZ-CLAY/11/5130 database was first compared with the global clay database CLAY/10/7490 and the Shanghai clay database SH-CLAY/11/4051, in terms of their sample ranges, correlations, and scatter plots. Then, the multivariate probability distribution of eight clay parameters was established using the training records selected from SZ-CLAY/11/5130, to characterize the generic correlations between multiple clay parameters. Based on Bayesian theory, the posterior distributions of clay mechanical parameters from a construction site in Shenzhen city were updated using both the site-specific correlations and the generic correlations given by SZ-CLAY/11/5130. The constructed multivariate probability density distribution is necessary for this updating step. [ABSTRACT FROM AUTHOR]