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Article
Publication date: 27 June 2023

Paolo Saona, Laura Muro, Pablo San Martín and Ryan McWay

This study aims to investigate how gender diversity and remuneration of boards of directors’ influence earnings quality for Spanish-listed firms.

Abstract

Purpose

This study aims to investigate how gender diversity and remuneration of boards of directors’ influence earnings quality for Spanish-listed firms.

Design/methodology/approach

The sample includes 105 nonfinancial Spanish firms from 2013 to 2018, corresponding to an unbalanced panel of 491 firm-year observations. The primary empirical method uses a Tobit semiparametric estimator with firm- and industry-level fixed effects and an innovative set of measures for earnings quality developed by StarMine.

Findings

Results exhibit a positive correlation between increased gender diversity and a firm’s earnings quality, suggesting that a gender-balanced board of directors is associated with more transparent financial reporting and informative earnings. We also find a nonmonotonic, concave relationship between board remuneration and earnings quality. This indicates that beyond a certain point, excessive board compensation leads to more opportunistic manipulation of financial reporting with subsequent degradation of earnings quality.

Research limitations/implications

This study only covers nonfinancial Spanish listed firms and is silent about how alternative board features’ influence earnings quality and their informativeness.

Originality/value

This study introduces measures of earnings quality developed by StarMine that have not been used in the empirical literature before as well as measures of board gender diversity applied to a suitable Tobit semiparametric estimator for fixed effects that improves the precision of results. In addition, while most of the literature focuses on Anglo-Saxon countries, this study discusses board gender diversity and board remuneration in the underexplored context of Spain. Moreover, the hand-collected data set comprising financial reports provides previously untested board features as well as a nonlinear relationship between remuneration and earnings quality that has not been thoroughly discussed before.

Details

Gender in Management: An International Journal , vol. 39 no. 1
Type: Research Article
ISSN: 1754-2413

Keywords

Article
Publication date: 15 February 2024

Xin-Zhou Qi, Eric Ping Hung Li, Zhuangyu Wei and Zhong Ning

This study examines the impact of university science parks’ (USPs) capabilities on revenue generation and introduces regional innovation as a moderating variable. This study aims…

Abstract

Purpose

This study examines the impact of university science parks’ (USPs) capabilities on revenue generation and introduces regional innovation as a moderating variable. This study aims to provide insights into enhancing revenue generation and fully leveraging the role of USPs in promoting revenue generation.

Design/methodology/approach

This study employs system generalized method of moments (GMM) estimation for 116 universities in China from 2008 to 2020, using hierarchical regression analysis to examine the relationships between variables.

Findings

The findings suggest that USPs play a beneficial role in fostering revenue generation. Specifically, the provision of incubation funding demonstrates a positive correlation, while USPs size exhibits an inverted U-shaped pattern, with a threshold at 3.037 and a mean value of 3.712, highlighting the prevalent issue of suboptimal personnel allocation in the majority of USPs. Moreover, the analysis underscores the critical moderating influence of regional innovation, affecting the intricate interplay between USPs size, incubation funding and revenue generation.

Research limitations/implications

The single country (China) analysis relied solely on the use of secondary data. Future studies could expand the scope to include other countries and employ primary data collection. For instance, future research can further examine how regional development and USPs strategic plan impact revenue generation.

Practical implications

The study recommends that USPs managers and policymakers recognize the importance of incubation funding and determine the optimal quantity of USPs size to effectively foster revenue generation in USPs. Policymakers can use regional innovation as a moderating variable to reinforce the relationship between USPs size and incubation funding on revenue generation.

Social implications

The study’s findings can contribute to the strategic industry growth and economic development of nations by promoting revenue generation. Leveraging the role of USPs and implementing the study’s recommendations can strengthen innovation and technology capabilities, driving strategic industry growth and economic development. This can enhance global competitiveness and promote sustainable economic growth.

Originality/value

This study introduces regional innovation as a moderating variable and provides empirical evidence of its influence on the relationship between USPs size and incubation funding on revenue generation. This adds value to research to the existing literature on USPs and revenue generation by showcasing the importance of examining the regional impact in research and innovation.

Details

International Journal of Entrepreneurial Behavior & Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2554

Keywords

Article
Publication date: 11 March 2024

Jianjun Yao and Yingzhao Li

Weak repeatability is observed in handcrafted keypoints, leading to tracking failures in visual simultaneous localization and mapping (SLAM) systems under challenging scenarios…

Abstract

Purpose

Weak repeatability is observed in handcrafted keypoints, leading to tracking failures in visual simultaneous localization and mapping (SLAM) systems under challenging scenarios such as illumination change, rapid rotation and large angle of view variation. In contrast, learning-based keypoints exhibit higher repetition but entail considerable computational costs. This paper proposes an innovative algorithm for keypoint extraction, aiming to strike an equilibrium between precision and efficiency. This paper aims to attain accurate, robust and versatile visual localization in scenes of formidable complexity.

Design/methodology/approach

SiLK-SLAM initially refines the cutting-edge learning-based extractor, SiLK, and introduces an innovative postprocessing algorithm for keypoint homogenization and operational efficiency. Furthermore, SiLK-SLAM devises a reliable relocalization strategy called PCPnP, leveraging progressive and consistent sampling, thereby bolstering its robustness.

Findings

Empirical evaluations conducted on TUM, KITTI and EuRoC data sets substantiate SiLK-SLAM’s superior localization accuracy compared to ORB-SLAM3 and other methods. Compared to ORB-SLAM3, SiLK-SLAM demonstrates an enhancement in localization accuracy even by 70.99%, 87.20% and 85.27% across the three data sets. The relocalization experiments demonstrate SiLK-SLAM’s capability in producing precise and repeatable keypoints, showcasing its robustness in challenging environments.

Originality/value

The SiLK-SLAM achieves exceedingly elevated localization accuracy and resilience in formidable scenarios, holding paramount importance in enhancing the autonomy of robots navigating intricate environments. Code is available at https://github.com/Pepper-FlavoredChewingGum/SiLK-SLAM.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

Open Access
Article
Publication date: 26 January 2024

Alana Vandebeek, Wim Voordeckers, Jolien Huybrechts and Frank Lambrechts

The purpose of this study is to examine how informational faultlines on a board affect the management of knowledge owned by directors and the consequences on organizational…

Abstract

Purpose

The purpose of this study is to examine how informational faultlines on a board affect the management of knowledge owned by directors and the consequences on organizational performance. In this study, informational faultlines are defined as hypothetical lines that divide a group into relatively homogeneous subgroups based on the alignment of several informational attributes among board members.

Design/methodology/approach

The study uses unique hand-collected panel data covering 7,247 board members at 106 publicly traded firms to provide strong support for the hypothesized U-shaped relationship. The authors use a fixed effects approach and a system generalized method of moments approach to test the hypothesis.

Findings

The study finds that the relationship between informational faultlines on a board and organizational performance is U shaped, with the least optimal organizational performance experienced when boards have moderate informational faultlines. More specifically, informational faultlines within boards are negatively related to organizational performance across the weak-to-moderate range of informational faultlines and positively related to organizational performance across the moderate-to-strong range.

Research limitations/implications

By explaining the mechanisms through which informational faultlines are related to organizational performance, the authors contribute to the literature in a number of ways. By conceptualizing how the management of knowledge plays an important role in the particular setting of corporate boards, the authors add not only to literature on knowledge management but also to the faultline and corporate governance literature.

Originality/value

This study offers a rationale for prior mixed findings by providing an alternative theoretical basis to explain the effect of informational faultlines within boards on organizational performance. To advance the field, the authors build on the concept of knowledge demonstrability to illuminate how informational faultlines affect the management of knowledge within boards, which will translate to organizational performance.

Details

Journal of Knowledge Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 14 December 2023

Yihu Tang, Li Huang and Xianghui Meng

The contact and lubrication performances, which were previously estimated assuming a Gaussian surface, are insufficient due to the non-Gaussian surface characteristics of the…

Abstract

Purpose

The contact and lubrication performances, which were previously estimated assuming a Gaussian surface, are insufficient due to the non-Gaussian surface characteristics of the honing liner. The purpose of this study is to analyze the liner honing surface and examine its effects on the contact and flow performance.

Design/methodology/approach

The fast Fourier transform (FFT) method was used to generate the liner honing texture. Subsequently, an elastoplastic contact model based on boundary element theory was constructed and simulated for the honing surface. The results were compared with those obtained using a Gaussian surface. In addition, flow factors of the honing surfaces were also compared.

Findings

The contact pressure and flow factors demonstrate significant disparities when dealing with non-Gaussian surfaces. In the deterministic model, the pressure exhibits considerably diminished magnitudes and a more evenly distribution. Moreover, when the gap between surfaces is narrow, the discrepancy in flow factor across different directions on the real honing surface becomes more prominent compared with the Gaussian surface.

Originality/value

The model incorporates the influence of the non-Gaussian honing surface, thereby enabling more accurate prediction.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0198/

Details

Industrial Lubrication and Tribology, vol. 76 no. 1
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 5 December 2023

S. Rama Krishna, J. Sathish, Talari Rahul Mani Datta and S. Raghu Vamsi

Ensuring the early detection of structural issues in aircraft is crucial for preserving human lives. One effective approach involves identifying cracks in composite structures…

Abstract

Purpose

Ensuring the early detection of structural issues in aircraft is crucial for preserving human lives. One effective approach involves identifying cracks in composite structures. This paper employs experimental modal analysis and a multi-variable Gaussian process regression method to detect and locate cracks in glass fiber composite beams.

Design/methodology/approach

The present study proposes Gaussian process regression model trained by the first three natural frequencies determined experimentally using a roving impact hammer method with crystal four-channel analyzer, uniaxial accelerometer and experimental modal analysis software. The first three natural frequencies of the cracked composite beams obtained from experimental modal analysis are used to train a multi-variable Gaussian process regression model for crack localization. Radial basis function is used as a kernel function, and hyperparameters are optimized using the negative log marginal likelihood function. Bayesian conditional probability likelihood function is used to estimate the mean and variance for crack localization in composite structures.

Findings

The efficiency of Gaussian process regression is improved in the present work with the normalization of input data. The fitted Gaussian process regression model validates with experimental modal analysis for crack localization in composite structures. The discrepancy between predicted and measured values is 1.8%, indicating strong agreement between the experimental modal analysis and Gaussian process regression methods. Compared to other recent methods in the literature, this approach significantly improves efficiency and reduces error from 18.4% to 1.8%. Gaussian process regression is an efficient machine learning algorithm for crack localization in composite structures.

Originality/value

The experimental modal analysis results are first utilized for crack localization in cracked composite structures. Additionally, the input data are normalized and employed in a machine learning algorithm, such as the multi-variable Gaussian process regression method, to efficiently determine the crack location in these structures.

Details

International Journal of Structural Integrity, vol. 15 no. 1
Type: Research Article
ISSN: 1757-9864

Keywords

Article
Publication date: 8 September 2022

Johnny Kwok Wai Wong, Mojtaba Maghrebi, Alireza Ahmadian Fard Fini, Mohammad Amin Alizadeh Golestani, Mahdi Ahmadnia and Michael Er

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes…

Abstract

Purpose

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

Design/methodology/approach

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

Findings

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

Originality/value

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

Details

Construction Innovation , vol. 24 no. 2
Type: Research Article
ISSN: 1471-4175

Keywords

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