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With the rapid development of web-based ideation platforms, firms are increasingly reaching outside their boundaries to obtain ideas, which makes idea evaluation tricky and ineffective. Numerous studies have investigated the antecedents of idea quality, but few have focused on the fragmented and contradictory conclusions these studies have drawn. Thus, the purpose of this paper is to disentangle conflicting findings regarding factors affecting idea quality.

A total of 41 independent samples from 40 articles published between 2009 and 2020 were retrieved and encoded to conduct a meta-analysis. By using Comprehensive Meta-analysis 3.0 (CMA 3.0) software, the relationship between identified influencing factors and idea quality, and the moderating effects of potential variables were investigated.

Factors affecting idea quality were summarized and divided into three categories: idea-related factors, ideator-related factors and platform-related factors. The results indicated that all proposed factors (idea length, supporting evidence, past success, past submissions, past comments, votes received and comments received) had significant positive effects on idea quality. Moreover, the measurement of idea quality and idea type was the causative factor for the inconsistent findings, whereas the moderating effect of platform type was not significant.

This study systematically synthesized the existing research on the factors influencing idea quality and helped to reconcile the mixed results. The findings serve to enrich current knowledge of idea evaluation in the online context, which could have important implications for both scholars and practitioners.

Periodic inspection of bridge cables is essential, and cable-climbing robots can replace human workers to perform risky tasks and improve inspection efficiency. However, cable inspection robots often fail to surmount large obstacles and cable clamps. The purpose of this paper is to develop a practical cable inspection robot with stronger obstacle-surmounting performance and circumferential rotation capability.

A cable inspection robot with novel elastic suspension mechanisms and circumferential rotation mechanisms is designed and proposed in this study. The supporting force and spring deformation of the elastic suspension are investigated and calculated. Dynamic analysis of obstacle surmounting and circumferential rotation is performed. Experiments are conducted on vertical and inclined cables to test the obstacle-surmounting performance and cable-clamp passing of the robot. The practicality of the robot is then verified in field tests.

With its elastic suspension mechanisms, the cable inspection robot can carry a 12.4 kg payload and stably climb a vertical cable. The maximum heights of obstacles surmounted by the driving wheels and the passive wheels of the robot are 15 mm and 13 mm, respectively. Equipped with circumferential rotation mechanisms, the robot can flexibly rotate and successfully pass cable clamps.

The novel elastic suspension mechanism and circumferential rotation mechanism improve the performance of the cable inspection robot and solve the problem of surmounting obstacles and cable clamps. Application of the robot can promote the automation of bridge cable inspection.

The paper aims to examine the corporate social responsibility (CSR) activity of audit firms.

Using hand-collected data on all Chinese audit firms’ CSR activities from 2007 to 2020, this study constructs two measures to proxy for audit firms’ CSR engagement: a dummy variable to indicate whether an auditor engages in CSR activities in year t and the frequency with which auditors conduct CSR activities in year t. The authors use ordinary least squares regression as a baseline methodology, along with the entropy balancing method and instrumental variable approach to alleviate potential endogeneity concerns.

The baseline results show that socially responsible audit firms provide higher quality audit services than their counterparts. In particular, the authors find that clients audited by socially responsible audit firms are less likely to receive an aggressively clean opinion. Moreover, the findings suggest that CSR activities related to community and employees are more relevant in improving audit quality compared with those related to other dimensions of CSR. Further analyses show that capital markets and audit clients react positively to audit-firm CSR activity. Audit firms engaging in CSR increase their audit inputs in response to risky clients, as compared with their counterparts. Finally, cross-sectional analyses show that the positive relationship is more pronounced for non-Big 4 and non-industry experts and is attenuated by within-firm geographic dispersion. In terms of client characteristics, the positive effect of audit-firm CSR is stronger when their clients face the higher financial risk or have lower CSR awareness than others. Taken together, these findings are consistent with the ethical view of audit-firm CSR engagement.

The study advances investors’ understanding of audit-firm CSR engagement and helps them evaluate the credibility of audited financial reports. Besides, the findings may also help guide the audit firms to conduct more CSR activities and help guide the audit clients to choose CSR audit firms.

To the best of the authors’ knowledge, this study provides the first large-sample evidence by empirically examining the association between audit-firm CSR activity and audit service performance. Besides, this paper also explores audit-firm CSR activity from two competing perspectives, thereby providing a comprehensive understanding of this issue. Finally, this work responds to the call for more CSR research in emerging markets.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.