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It is shown in the literature that the Arellano–Bond type generalized method of moments (GMM) of dynamic panel models is asymptotically biased (e.g., Hsiao & Zhang, 2015; Hsiao & Zhou, 2017). To correct the asymptotical bias of Arellano–Bond GMM, the authors suggest to use the jackknife instrumental variables estimation (JIVE) and also show that the JIVE of Arellano–Bond GMM is indeed asymptotically unbiased. Monte Carlo studies are conducted to compare the performance of the JIVE as well as Arellano–Bond GMM for linear dynamic panels. The authors demonstrate that the reliability of statistical inference depends critically on whether an estimator is asymptotically unbiased or not.

The authors consider the quasi maximum likelihood (MLE) estimation of dynamic panel models with interactive effects based on the Ahn et al. (2001, 2013) quasi-differencing methods to remove the interactive effects. The authors show that the quasi-difference MLE (QDMLE) over time is inconsistent when N→∞ whether T is fixed or goes to infinity. On the other hand, the QDMLE is consistent and asymptotically unbiased if the difference is taken over individuals when T is large whether N is fixed or large. Monte Carlo studies are conducted to compare the performance of the QDMLE using different quasi-difference methods.

Panel data provide the possibilities of estimating individual treatment effects for multiple individuals. Two issues are considered: (1) differences in the estimated individual treatment effects are due to heterogeneity or a chance mechanism? (2) what is the best way to estimate the average treatment effects? Testing and aggregation methods are suggested. Monte Carlo simulations are also conducted to shed light on these two issues. An empirical analysis on the involvement of underground organization in China’s Peer-to-Peer (P2P) activities through the “anti-gang” campaign is also provided.

This paper aimed to examine the role of knowledge sharing among member enterprises between collaborative innovation activities and innovation performance and between building information modeling (BIM) application and innovation performance in the construction supply chain.

The structural equation model was used in this study. First, the hypothesis of the relationship between collaborative innovation activities, BIM application, knowledge sharing and innovation performance in the construction supply chain was proposed based on experience; then, the research data were collected by investigation; finally, this hypothesis was tested through data analysis.

(1) Collaborative innovation activities in the construction supply chain had a positive impact on explicit knowledge sharing, tacit knowledge sharing and innovation performance. (2) BIM application had a positive impact on explicit knowledge sharing and innovation performance, while it had no significant impact on tacit knowledge sharing. (3) Explicit knowledge sharing had no positive effect on innovation performance, while tacit knowledge sharing had positive effect on organizational performance. (4) Tacit knowledge sharing produced partial mediating effect between collaborative innovation activities, BIM application and innovation performance, while explicit knowledge sharing produced complete mediating effect between BIM application and tacit knowledge sharing.

A relationship model among collaborative innovation activities, BIM application, explicit and tacit knowledge sharing and innovation performance in the construction supply chain was proposed, and the rationality of the model was verified by empirical analysis. Discovering the relationships between these factors can be not only conducive to mastering the effect of explicit and tacit knowledge sharing in the collaborative innovation process of construction supply chain, but also play a guiding role for the function development of BIM.

This study aims to explore whether investors’ inattention is associated with firms’ environmental, social and governance (ESG) decoupling, which is defined as the misalignment between the implementation and incorporation of ESG policies.

Focusing on a sample of the components of ESG ratings for China Securities Index (CSI) 300 companies between 2017 and 2019, the authors test the relationship between firms’ ESG decoupling level and mutual fund investors’ distraction by applying exogenous shocks to their portfolios.

The results show that firms with distracted mutual fund investors engage in more external than internal ESG actions, leading to a high ESG decoupling level. Mutual fund investors use “threat of exit” rather than “voice” as a governance mechanism to influence corporate ESG decoupling. While external ESG actions mitigate stock price crash risk, internal ESG actions increase firm value; firms with a high ESG decoupling level suffer lower valuations.

This study has implications for increasing the congruence between firms’ external and internal ESG actions, thereby improving firms’ ESG performance and long-term economic outcomes.

This paper helps policy-makers and regulators to reassess how ESG policies can be implemented to be consistent with organizations’ core business activities.

Contributing to prior studies of greenwashing and corporate social responsibility decoupling, this paper extends decoupling literature by revisiting ESG impacts in an integrated framework and explores the antecedents of corporate ESG decoupling from the perspective of institutional investor monitoring.

To paint large workpieces automatically, painting manipulators with hollow wrists must be transported by mobile platforms to different positions because of their limited workspaces. This paper aims to provide a visualization method for finding appropriate base positions (BPs) and maximum painting areas for manipulators.

This paper begins by analyzing the motion characteristics of manipulators possessing a spherical wrist and summarizing them into three constraints – positioning, orientation and singularity avoidance. The hollow wrist is simplified and considered as spherical by introducing the concepts of an inner wrist center and an outer wrist center. Taking the three constraints into consideration, the boundaries of the manipulating space are formulated analytically. Finally, to verify the method, the space obtained is applied to determine the maximum painting areas for flat, cylindrical and conical surfaces. Experiments of robotic painting were used to confirm the results.

Compared with previous studies, the maximum areas obtained using the proposed method increased by 17-131 per cent with an algorithm of lower complexity, and the process remained visually intuitive, thereby demonstrating that the method of manipulating space is more effective.

Such a method allows individuals to visualize the entire painting area at the current BP, thereby maximizing painting areas or optimizing BPs. It opens a black box that is the relationship between BPs and blocks. The method can also be used to choose the best configuration for painting manipulators, select the end-effector structure parameters, split surfaces into blocks, etc.