Linlin Wang, Zhaofang Chu, Wan Jiang and Yifan Xu
This study aims to build on equity theory to assess the effect of chief executive officer (CEO) underpayment on the accumulation of firm-specific knowledge, accounting for the…
Abstract
Purpose
This study aims to build on equity theory to assess the effect of chief executive officer (CEO) underpayment on the accumulation of firm-specific knowledge, accounting for the moderating effects of the CEO compensation gap and the clarity of the board’s informal hierarchy.
Design/methodology/approach
This study starts with all firms listed in the Execucomp database for the period 1992 to 2006. Then, all data sources are merged and entries with missing information are excluded. The final data set used for model estimations includes 1,152 firm-year observations. The command xtreg in Stata 12 with the fixed-effect option (fe) is used to estimate the relationship between CEO underpayment and firm-specific knowledge.
Findings
This study proposed and examined the role of CEO underpayment in discouraging CEO willingness to invest firm-specific human capital and, accordingly, to adopt a strategy of accumulating lower levels of firm-specific knowledge assets. The empirical analyses strongly support this argument. Moreover, CEO compensation gaps and the informal hierarchy of boards negatively moderated this relationship. That is, CEO underpayment had a weaker negative effect on firm-specific knowledge when the CEO compensation gap and the clarity of the board’s informal hierarchy were high.
Originality/value
Prior studies from the knowledge-based perspective have focused on the importance of firm-specific knowledge in enabling a firm to achieve superior financial performance. However, relatively little attention has been paid to CEOs’ willingness to accumulate firm-specific knowledge. The present study contributes to the knowledge-based view of the firm. This study integrates equity theory with the knowledge-based view of the firm by highlighting how unfair compensation of CEOs may discourage them to fully realize a firm’s potential to generate specific knowledge. By incorporating the fairness issue of CEO compensation into the knowledge-based view, this study contributes to a deeper understanding of the origins of firm-specific knowledge.
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Yifan Xu, Xiang Gu, Qinghua Meng, Bin Wang and Jun Fan
This paper aims to show a series of hydrogels with adjustable mechanical properties, which can be cured quickly with visible light. The hydrogel is prepared conveniently with…
Abstract
Purpose
This paper aims to show a series of hydrogels with adjustable mechanical properties, which can be cured quickly with visible light. The hydrogel is prepared conveniently with hydroxyethyl acrylate, cross-linker, gelatin and photoinitiator, and can be printed into certain 3D patterns with the direct ink write (DIW) 3D printer designed and developed by the research group.
Design/methodology/approach
In this paper, the authors designed a composite sensitization initiation system that is suitable for hydrogels. The concentration of photoinitiator, gelatin and cross-linker was studied to optimize the curing efficiency and adjust the mechanical properties. A DIW 3D printer was designed for the printing of hydrogel. Pre-gel solution was loaded into printer for printing into established models. The models were made and sliced with software.
Findings
The hydrogels can be cured efficiently with 405-nm visible light. While adding various content of gelatin and cross-linker, the mechanical properties of hydrogels show from soft and fragile (elastic modulus of 121.18 kPa and work of tension of 218.11 kJ·m−3) to rigid and tough (elastic modulus of 505.15 kPa and work of tension of 969.00 kJ·m−3). The hydrogels have high capacity of water absorption. With the DIW 3D printer, pre-gel hydrogel solution can be printed into objects with certain dimension.
Originality/value
In this work, a composite sensitization initiation system was designed, and fast curing hydrogels with adjustable mechanical properties had been prepared conveniently, which has high equilibrium water content and 3D printability with the DIW 3D printer.
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Yifan Zhang, Jianyang Zhu, Xu Wang, Yaochi Zhang and Le Gu
Under oil interruption, lubricant supply in the high-speed bearing cavity is interrupted, which reduces the bearing lubrication and cooling ability, thus leading to degradation of…
Abstract
Purpose
Under oil interruption, lubricant supply in the high-speed bearing cavity is interrupted, which reduces the bearing lubrication and cooling ability, thus leading to degradation of bearing performance or even its failure. This paper aims to study the effect of grooves at the noncontact outer ring area on the flow and thermal performance of high-speed bearings under oil interruption, which is expected to improve the resistance of existing bearings to oil interruption.
Design/methodology/approach
The groove was added to the noncontact outer ring area of the bearing, and a method of combining volume of fluid and MRF was adopted to systematically study and analyze the oil-gas flow field structure and the temperature field distribution in the bearing cavities.
Findings
Results show that the lubricating oil could be stored and guided by the grooves of the bearing outer ring into the key lubrication area inside the bearing cavity, which increased the oil content near the inner ring and made the oil distribution more uniform. As a result, lubrication cooling and heat dissipation performance of the bearing cavity was improved. Compared with the original bearing, the bearing with a V-shaped groove had the optimal lubrication and cooling performance.
Originality/value
A rolling bearing model of the noncontact outer ring area with grooves under oil interruption is established in the paper. The simulation results provide theoretical guidance for the research and development of high-speed bearings with stronger oil interruption resistance ability.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0199/
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Wenshen Xu, Yifan Zhang, Xinhang Jiang, Jun Lian and Ye Lin
In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference…
Abstract
Purpose
In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.
Design/methodology/approach
First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.
Findings
MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.
Originality/value
This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.
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Shenghua Zhou, S. Thomas Ng, Sang Hoon Lee, Frank J. Xu and Yifan Yang
In the architecture, engineering and construction (AEC) industry, technology developers have difficulties in fully understanding user needs due to the high domain knowledge…
Abstract
Purpose
In the architecture, engineering and construction (AEC) industry, technology developers have difficulties in fully understanding user needs due to the high domain knowledge threshold and the lack of effective and efficient methods to minimise information asymmetry between technology developers and AEC users. The paper aims to discuss this issue.
Design/methodology/approach
A synthetic approach combining domain knowledge and text mining techniques is proposed to help capture user needs, which is demonstrated using building information modelling (BIM) apps as a case. The synthetic approach includes the: collection and cleansing of BIM apps’ attribute data and users’ comments; incorporation of domain knowledge into the collected comments; performance of a sentiment analysis to distinguish positive and negative comments; exploration of the relationships between user sentiments and BIM apps’ attributes to unveil user preferences; and establishment of a topic model to identify problems frequently raised by users.
Findings
The results show that those BIM app categories with high user interest but low sentiments or supplies, such as “reality capture”, “interoperability” and “structural simulation and analysis”, should deserve greater efforts and attention from developers. BIM apps with continual updates and of small size are more preferred by users. Problems related to the “support for new Revit”, “import & export” and “external linkage” are most frequently complained by users.
Originality/value
The main contributions of this work include: the innovative application of text mining techniques to identify user needs to drive BIM apps development; and the development of a synthetic approach to orchestrating domain knowledge, text mining techniques (i.e. sentiment analysis and topic modelling) and statistical methods in order to help extract user needs for promoting the success of emerging technologies in the AEC industry.
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Yiming Li, Xukan Xu, Muhammad Riaz and Yifan Su
This study aims to use geographical information on social media for public opinion risk identification during a crisis.
Abstract
Purpose
This study aims to use geographical information on social media for public opinion risk identification during a crisis.
Design/methodology/approach
This study constructs a double-layer network that associates the online public opinion with geographical information. In the double-layer network, Gaussian process regression is used to train the prediction model for geographical locations. Second, cross-space information flow is described using local government data availability and regional internet development indicators. Finally, the structural characteristics and information flow of the double-layer network are explored to capture public opinion risks in a fine-grained manner. This study used the early stages of the COVID-19 outbreak for validation analyses, and it collected more than 90,000 pieces of public opinion data from microblogs.
Findings
In the early stages of the COVID-19 outbreak, the double-layer network exhibited a radiating state, and the information dissemination was more dependent on the nodes with higher in-degree. Moreover, the double-layer network structure showed geographical differences. The risk contagion was more significant in areas where information flow was prominent, but the influence of nodes was reduced.
Originality/value
Public opinion risk identification that incorporates geographical scenarios contributes to enhanced situational awareness. This study not only effectively extends geographical information on social media, but also provides valuable insights for accurately responding to public opinion.
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Yuxuan Wu, Wenyuan Xu, Tianlai Yu and Yifan Wang
Polyurethane concrete (PUC), as a new type of steel bridge deck paving material, the bond-slip pattern at the interface with the steel plate is not yet clear. In this study, the…
Abstract
Purpose
Polyurethane concrete (PUC), as a new type of steel bridge deck paving material, the bond-slip pattern at the interface with the steel plate is not yet clear. In this study, the mechanical properties of the PUC and steel plate interface under the coupled action of temperature, normal force and tangential force were explored through shear tests and numerical simulations. An analytical model for bond-slip at the PUC/steel plate interface and a predictive model for the shear strength of the PUC/steel plate interface were developed.
Design/methodology/approach
The new shear test device designed in this paper overcomes the defect that the traditional oblique shear test cannot test the interface shear performance under the condition of fixed normal force. The universal testing machine (UTM) test machine was used to adjust the test temperature conditions. Combined with the results of the bond-slip test, the finite element simulation of the interface is completed by using the COHENSIVE unit to analyze the local stress distribution characteristics of the interface. The use of variance-based uncertainty analysis guaranteed the validity of the simulation.
Findings
The shear strength (τf) at the PUC-plate interface was negatively correlated with temperature while it was positively correlated with normal stress. The effect of temperature on the shear properties was more significant than that of normal stress. The slip corresponding to the maximum shear (D1) positively correlates with both temperature and normal stress. The interfacial shear ductility improves with increasing temperature.
Originality/value
Based on the PUC bond-slip measured curves, the relationship between bond stress and slip at different stages was analyzed, and the bond-slip analytical model at different stages was established; the model was defined by key parameters such as elastic ultimate shear stress τ0, peak stress τf and interface fracture energy Gf.
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Bingjun Li, Shuhua Zhang, Wenyan Li and Yifan Zhang
Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the…
Abstract
Purpose
Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.
Design/methodology/approach
Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.
Findings
The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.
Originality/value
By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.
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Qingfeng Meng, Yifan Zhang, Zhen Li, Weixiang Shi, Jun Wang, Yanhui Sun, Li Xu and Xiangyu Wang
The purpose of this paper is to summarize the current applications of BIM, the integration of related technologies and the tendencies and challenges systematically.
Abstract
Purpose
The purpose of this paper is to summarize the current applications of BIM, the integration of related technologies and the tendencies and challenges systematically.
Design/methodology/approach
Using quantitative and qualitative bibliometric statistical methods, the current mode of interaction between BIM and other related technologies is summarized.
Findings
This paper identified 24 different BIM applications in the life cycle. From two perspectives, the implementation status of BIM applications and integrated technologies are respectively studied. The future industry development framework is drawn comprehensively. We summarized the challenges of BIM applications from the perspectives of management, technology and promotion, and confirmed that most of the challenges come from the two driving factors of promotion and management.
Research limitations/implications
The technical challenges reviewed in this paper are from the collected literature we have extracted, which is only a part of the practical challenges and not comprehensive enough.
Practical implications
We summarized the current mode of interactive use of BIM and sorted out the challenges faced by BIM applications to provide reference for the risks and challenges faced by the future industry.
Originality/value
There is little literature to integrate BIM applications and to establish BIM related challenges and risk frameworks. In this paper, we provide a review of the current implementation level of BIM and the risks and challenges of stakeholders through three aspects of management, technology and promotion.
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Yifan Shi, Yuan Wang, Xiaozhou Liu and Ping Wang
Straightness measurement of rail weld joint is of essential importance to railway maintenance. Due to the lack of efficient measurement equipment, there has been limited in-depth…
Abstract
Purpose
Straightness measurement of rail weld joint is of essential importance to railway maintenance. Due to the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a 5-m wavelength range, leaving a significant knowledge gap in this field.
Design/methodology/approach
In this study, the authors used the well-established inertial reference method (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methods have been applied in different types of rail straightness measurement trollies, respectively. These instruments were tested in a high-speed rail section within a certain region of China. The test results were ultimately validated through using traditional straightedge and feeler gauge methods as reference data to evaluate the rail weld joint straightness within the 5-m wavelength range.
Findings
The research reveals that IR-method and MCR-method produce reasonably similar measurement results for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy for wavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed, carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.
Originality/value
The research compare two methods’ measurement effects in a longer wavelength range and demonstrate the superiority of MCR-method.