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While researchers recognize the significance of philanthropic donations in disaster relief and recovery, the benefits that firms derive from such donations remain unclear, particularly when firms are adversely impacted by the disaster. To address this gap, this study seeks to elucidate the impact of various donation strategies on firm resilience in the context of the COVID-19 pandemic.

Based on the hand-collected data on donations, the authors employ ordinary least squares regressions to investigate the effectiveness of various donation strategies – including type, timing and location – in enhancing firm resilience in terms of the severity of stock price losses during the pandemic. To address potential endogeneity concerns, the authors use a two-stage least squares regression with instrumental variables.

This study finds robust evidence that certain donation strategies are more effective at mitigating stock price losses during the pandemic. Specifically, the authors find that in-kind donations (compared to monetary ones), earlier donations (compared to later ones) and donations targeting severely impacted areas (Hubei province vs. other places) are more effective methods to reduce the severity of stock price losses.

This study points out an alternative mechanism through which donations influence firm resilience during a crisis context and provides important managerial implications for firms to better engage in disaster donations.

Drawing on absorptive capacity theory, this study explores the impacts of supply visibility and demand visibility on product innovation (i.e. exploratory and exploitative innovation), and it examines how supplier integration, customer integration and internal integration mediate these impacts.

The authors employ empirical survey data from 200 Chinese manufacturers and use structural equation modeling to test the proposed relationships.

The results show that supply visibility is positively related to supplier integration and internal integration and that demand visibility is positively related to customer integration. Furthermore, only customer integration and internal integration positively relate to exploratory and exploitative innovation.

First, this study emphasizes that supply visibility and demand visibility are important sources of a firm's innovation performance and that supply chain integration increases focal firms' capability of exploiting information and facilitates product innovation. Second, the study shows that supply visibility and demand visibility have distinct effects on three dimensions of supply chain integration and exploratory and exploitative innovation. The study also provides significant managerial guidelines for effectively leveraging supply chain visibility and integration in the promotion of product innovation.

This study addresses an important research question regarding how supplier-base concentration affects buyer efficiency. Drawing on the contradicting views of transaction cost theory (TCT) and resource dependence theory (RDT), the authors explore the main effect of supplier-base concentration on buyer efficiency and how this effect is contingent on buyers' characteristics (i.e. research and development (R&D) expenditure and market share).

Based on data collected from the Chinese manufacturing firms listed on National Equities Exchange and Quotations (NEEQ) between 2015 and 2019, the authors use a fixed-effect model as well as a two-stage least squares model to test the predictions.

The authors find that supplier-base concentration has a positive effect on buyer efficiency. In addition, when a buyer has higher levels of R&D expenditure and market share, the positive relationship between supplier-base concentration and buyer efficiency is strengthened.

This study contributes to a better understanding of the effect of supplier-base concentration. First, the authors provide theoretical and empirical evidence of the positive effect of supplier-base concentration on buyer efficiency. Second, the authors reveal the underlying mechanism of how to counter the potential drawbacks and benefit more from supply base reduction by introducing R&D expenditure and market share as contingencies.

This study aims to explore how different patterns of IT use influence different types of green supply chain management (GSCM) with customers, and in turn, environmental and economic performance.

Based on data collected from 206 manufacturing companies in China, the authors used structural equation modeling (SEM) with the maximum-likelihood estimation (MLE) method to test the conceptual model and the related hypotheses.

The results show that both IT use for exploitation and IT use for exploration are positively related to green strategy alignment and green process coordination, whereas the relationship between IT use for exploration and green strategy alignment is weaker. This study also finds that green strategy alignment has a marginal positive effect on economic performance, whereas its effect on environmental performance is not significant. Green process coordination has a positive effect on environmental performance, whereas its effect on economic performance is not significant.

This study extends the value of IT use in the GSCM field, enriching both literature on IT and GSCM. The findings provide significant managerial implications for managers to leverage IT resources to enhance GSCM and the corresponding performance.

With the development of automation technology, the accuracy, bearing capacity and self-adaptation requirements of wheeled mobile robots are more and more demanding under various complex conditions, which will urge designers such shortcomings as the low accuracy, poor flexibility and weak obstacle crossing ability of traditional heavy haul vehicles and improve the wear resistance and bearing capacity of traditional omnidirectional wheels.

The optimal configuration for heavy payload transportation is obtained by building sliding friction consumption model of traditional wheels with different driving types based on Hertz tangential contact theory. The heavy payload omnidirectional wheel with a double-wheel steering and a coupled differential wheel driving is designed with the optimal configuration. The wheel consists of a differential gear train unit and a nonindependent suspension unit. Kinematics model of the wheel is established and relative parameters are optimized.

The prototype experiments show that the wheel has higher motion accuracy and environment adaptability. The results are consistent with the theoretical calculation, which show that the accuracy is more than 50% higher than that of differential prototype. The motion stability and the accuracy of the coupled differential omnidirectional wheel are better than those of the traditional omnidirectional wheels during the moving and obstacle crossing process under complex conditions, which verifies the correctness and advantages of the design.

Aiming at the specific application of heavy payload omnidirectional transportation, a new omnidirectional mobile mechanism with a two-wheel coupling drive structure and an adaptive mechanism is proposed. The simulation and experimental results show that it can realize the high-precision heavy-load omnidirectional movement, the effective contact with the ground and improve the adaptability to the rugged ground. It is flexible, simple and modular and can be widely applied to transportation, exploration, detection and other related industrial fields.

In large-scale environments and unstructured scenarios, the accuracy and robustness of traditional light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) algorithms are reduced, and the algorithms might even be completely ineffective. To overcome these problems, this study aims to propose a 3D LiDAR SLAM method for ground-based mobile robots, which uses a 3D LiDAR fusion inertial measurement unit (IMU) to establish an environment map and realize real-time localization.

First, we use a normal distributions transform (NDT) algorithm based on a local map with a corresponding motion prediction model for point cloud registration in the front-end. Next, point cloud features are tightly coupled with IMU angle constraints, ground constraints and gravity constraints for graph-based optimization in the back-end. Subsequently, the cumulative error is reduced by adding loop closure detection.

The algorithm is tested using a public data set containing indoor and outdoor scenarios. The results confirm that the proposed algorithm has high accuracy and robustness.

To improve the accuracy and robustness of SLAM, this method proposed in the paper introduced the NDT algorithm in the front-end and designed ground constraints and gravity constraints in the back-end. The proposed method has a satisfactory performance when applied to ground-based mobile robots in complex environments experiments.

This paper aims to explore the developing trend of higher pedagogy, to promote the research of higher pedagogy to be more canonical and scientific and to improve the higher education theory.

The utility research uses a method of quantitative study, namely “content analysis”, to estimate and analyze the higher education theory literature on ten dimensionalities which include theme, author, abstract, keywords, subject, proposing of the issue, definition of key terms, research methods, conclusion, reference and annotations from 1996 to 2006 in China.

The analysis of the selected 250 academic theses and reports in the field of higher education shows that academic research and theoretical standard have been improved, meanwhile academic criterion have been formed by degrees in higher pedagogy within ten years. At the same time, there are still some problems in the papers and reports the authors have selected such as title, key words, proposing of the issue, researching method and conclusion.

This paper sums up the trend of research on higher education in China for the past ten years, and points out the problems in this trend and then proposes ways to improve the research of higher education in China.

The objective of the present work was to study the influence of chemical compositions of five naphthenic acids (NAs) extracted from Liaohe crude oil on their corrosivity.

Fourier‐transform infrared spectrometry and electron impact mass spectrometry were used to characterize the chemical structures and compositions if five NAs. The corrosivities of the NAs were assessed by stagnant NA corrosion (NAC) tests. An attempt was made to identify any correlation between the chemical composition of the NAs and their corrosiveness.

The acidic species in all five NA samples were saturated aliphatic and naphthenic acids and the amount of aromatic and unsaturated acids was negligible. A relationship between the carboxylic acid distribution and the molecular weight was obtained. Most of the carboxylic acids in five NAs contained 0‐3 ring structures. NAs with lower molecular weight and fewer ring structures usually were more corrosive.

The findings have important implications for assessing the corrosivity of acidic crude oils from various resources.

The purpose of this paper is to estimate the contact-consistent object poses during contact-rich manipulation tasks based only on visual sensors.

The method follows a four-step procedure. Initially, the raw object poses are retrieved using the available object pose estimation method and filtered using Kalman filter with nominal model; second, a group of particles are randomly generated for each pose and evaluated the corresponding object contact state using the contact simulation software. A probability guided particle averaging method is proposed to balance the accuracy and safety issues; third, the independently estimated contact states are fused in a hidden Markov model to remove the abnormal contact state observations; finally, the object poses are refined by averaging the contact state consistent particles.

The experiments are performed to evaluate the effectiveness of the proposed methods. The results show that the method can achieve smooth and accurate pose estimation results and the estimated contact states are consistent with ground truth.

This paper proposes a method to obtain contact-consistent poses and contact states of objects using only visual sensors. The method tries to recover the true contact state from inaccurate visual information by fusing contact simulations results and contact consistency assumptions. The method can be used to extract pose and contact information from object manipulation tasks by just observing the demonstration, which can provide a new way for the robot to learn complex manipulation tasks.

In the wake of the COVID-19 outbreak understanding the behavioral dynamics and role of knowledge-oriented leadership (KOL) in driving knowledge worker performance (KWP) is paramount for organizations striving to adapt and thrive in the post-pandemic era. Drawing on the path-goal theory, this study explores the impact of KOL on KWP. In addition, this study seeks to examine both the direct and indirect influences of KOL on KWP via digital orientation (DO) and digital citizenship practices (DCP), especially for higher education institutions (HEIs) located in China.

The sample consisted of 319 academic staff from HEIs in China. The study used Smart-PLS 4.0 for analytical examination.

The results indicate that the impact of knowledge-oriented leadership on KWP is negligible. Furthermore, DCP and DO partially mediate the relationship between KOL and KWP. The findings of this research have practical implications for Chinese HEIs and organizations across industries, providing insights into how to navigate the complexities of the post-pandemic work environment and effectively harness digitalization to optimize the KWP.

The implications of this research extend beyond the HEIs, providing organizations in various industries with evidence-based strategies to promote effective leadership, foster digital skills, and cultivate a culture of digital citizenship in the post-pandemic work landscape.

Despite the increasing significance of KOL in the higher education sector, there is a dearth of studies establishing a relationship between KOL and KWP in HEIs. The present study seeks to fill this gap by examining the association among KOL, KWP, DO, and DCP in HEIs during the post-pandemic. This research provides significant contributions to the existing literature on the topic by scientifically exploring the association between KOL and KWP by examining the intervention mechanism of both digital citizenship practices and digital orientation.