Chengyun Liu, Kun Su and Miaomiao Zhang
This study aims to examine whether and how gender diversity on corporate boards is associated with voluntary nonfinancial disclosures, particularly water disclosures.
Abstract
Purpose
This study aims to examine whether and how gender diversity on corporate boards is associated with voluntary nonfinancial disclosures, particularly water disclosures.
Design/methodology/approach
This study uses corporate water information disclosure data from Chinese listed firms between 2010 and 2018 to conduct regression analyses to examine the association between female directors and water information disclosure.
Findings
Empirical results show that female directors have a significantly positive association with corporate water information disclosure. Additionally, internal industry water sensitivity of firms moderates this significant relationship.
Originality/value
This study determined that female directors can promote not only water disclosure but also positive corporate water performance, reflecting the consistency of words and deeds of female directors in voluntary nonfinancial disclosures.
Details
Keywords
Nianfei Gan, Miaomiao Zhang, Bing Zhou, Tian Chai, Xiaojian Wu and Yougang Bian
The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.
Abstract
Purpose
The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.
Design/methodology/approach
To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.
Findings
Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.
Originality/value
It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.