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1 – 10 of 606The paper aims to provide a comprehensive investigation of the relationship between corporate governance (CG) structure and firm performance in Chinese listed firms from 2001 to…
Abstract
Purpose
The paper aims to provide a comprehensive investigation of the relationship between corporate governance (CG) structure and firm performance in Chinese listed firms from 2001 to 2015. The authors’ motivation derives from the fact that the CG system in China is different from those in the US, the UK, Germany, Japan and other countries.
Design/methodology/approach
A large unbalanced sample, covering more than 22,700 observations in Chinese listed firms, was used to explore, by means of a system-generalized method-of-moments (GMM) estimator, the relationship between CG structure and firm performance to remove potential sources of endogeneity.
Findings
Results show that Chinese CG structure is endogenously determined by the CG mechanisms investigated: there is no relationship between board size (including independent directors) and firm performance; CEO duality has a significantly negative effect on firm performance; concentration of ownership has a significantly positive influence on firm performance; managerial ownership is negatively correlated with firm performance; state ownership has a significantly positive effect on firm performance; and a supervisory board is positively correlated with firm performance.
Practical implications
The findings provide policymakers and firm managers with useful empirical guidance concerning CG in China.
Originality/value
Few integrative studies have examined the impact of CG structure on firm performance in China. This study adds new empirical evidence that the relation between CG structure and performance in China is endogenous and dynamic when controlling for unobserved heterogeneity, simultaneity, and dynamic endogeneity.
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Mandakini Paruthi, Harsandaldeep Kaur, Jamid Ul Islam, Aaleya Rasool and George Thomas
This study aims to investigate the influence of brand relationship quality and consumer community identification on consumer engagement. This study also examines the mediating…
Abstract
Purpose
This study aims to investigate the influence of brand relationship quality and consumer community identification on consumer engagement. This study also examines the mediating role of consumer engagement between brand relationship quality and consumer community identification with brand love. Positive word of mouth is taken as an outcome variable.
Design/methodology/approach
To test the proposed relationships, data were collected from 580 social media-based brand community followers and analysed through structural equation modelling.
Findings
Results corroborate brand relationship quality and consumer community identification as critical drivers of consumer engagement on the online platforms. The results further reveal a positive association between consumer engagement and brand love which consequently foster positive word of mouth. The findings also corroborate the partial as well as full mediating role of consumer engagement on different proposed associations.
Originality/value
This study offers an in-depth insight of specific motivations to engage consumers in the virtual domain, make them adore their brands and spread a positive word. All of these outcomes are crucial in offering competitive advantages to firms. This study validates the relevance of consumer engagement interactions in contemporary firms’ relationship marketing strategies.
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Zhenlong Peng, Aowei Han, Chenlin Wang, Hongru Jin and Xiangyu Zhang
Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC…
Abstract
Purpose
Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.
Design/methodology/approach
The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.
Findings
To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.
Originality/value
This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.
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Tao Peng, Xingliang Liu, Rui Fang, Ronghui Zhang, Yanwei Pang, Tao Wang and Yike Tong
This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety.
Abstract
Purpose
This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety.
Design/methodology/approach
The authors proposed a novel safety lane-change path planning and tracking control method for articulated vehicles. A double-Gaussian distribution was introduced to deduce the lane-change trajectories of tractor and trailer coupling characteristics of intelligent vehicles and roads. With different steering and braking maneuvers, minimum safe distances were modeled and calculated. Considering safety and ergonomics, the authors invested multilevel self-driving modes that serve as the basis of decision-making for vehicle lane-change. Furthermore, a combined controller was designed by feedback linearization and single-point preview optimization to ensure the path tracking and robust stability. Specialized hardware in the loop simulation platform was built to verify the effectiveness of the designed method.
Findings
The numerical simulation results demonstrated the path-planning model feasibility and controller-combined decision mechanism effectiveness to self-driving trucks. The proposed trajectory model could provide safety lane-change path planning, and the designed controller could ensure good tracking and robust stability for the closed-loop nonlinear system.
Originality/value
This is a fundamental research of intelligent local path planning and automatic control for articulated vehicles. There are two main contributions: the first is a more quantifiable trajectory model for self-driving articulated vehicles, which provides the opportunity to adapt vehicle and scene changes. The second involves designing a feedback linearization controller, combined with a multi-objective decision-making mode, to improve the comprehensive performance of intelligent vehicles. This study provides a valuable reference to develop advanced driving assistant system and intelligent control systems for self-driving articulated vehicles.
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Qiang Yang, Jiale Huo, Hongxiu Li, Yue Xi and Yong Liu
This study investigates how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' purchasing and gift-giving behaviors and how broadcaster…
Abstract
Purpose
This study investigates how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' purchasing and gift-giving behaviors and how broadcaster popularity moderates social interaction-oriented content's effect on the two different behaviors in live-streaming commerce.
Design/methodology/approach
A research model was proposed and empirically tested using a panel data set collected from 537 live streams via Douyin (the Chinese version of TikTok), one of the most popular live broadcast platforms in China. A fixed-effects negative binomial regression model was used to examine the proposed research model.
Findings
This study's results show that social interaction-oriented content in broadcasters' live speech has an inverted U-shaped relationship with broadcast viewers' purchasing behavior and shares a positive linear relationship with viewers' gift-giving behavior. Furthermore, broadcaster popularity significantly moderates the effect of social interaction-oriented content on viewers' purchasing and gift-giving behaviors.
Originality/value
This research enriches the literature on live-streaming commerce by investigating how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' product-purchasing and gift-giving behaviors from the perspective of broadcast viewers' attention. Moreover, this study provides some practical guidelines for developing live speech content in the live-streaming commerce context.
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Xiaomei Jiang, Shuo Wang, Wenjian Liu and Yun Yang
Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these…
Abstract
Purpose
Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.
Design/methodology/approach
In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.
Findings
The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.
Originality/value
The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.
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This paper aims to examine the impact of adverse personality traits (alexithymia, social inhibition, negative affectivity) and supervisor knowledge hiding on individual knowledge…
Abstract
Purpose
This paper aims to examine the impact of adverse personality traits (alexithymia, social inhibition, negative affectivity) and supervisor knowledge hiding on individual knowledge hiding. This study also explores the moderating role of positive affectivity.
Design/methodology/approach
Partial least squares path modeling and data collected from 518 Polish employees with higher education and extensive professional experience recruited via an Ariadna survey panel were used to test the research hypotheses.
Findings
Two dimensions of alexithymia were considered: difficulty identifying feelings (DIF) and difficulty describing feelings (DDF). DIF has a direct impact on individual hiding, whereas DDF has an indirect impact, via social inhibition. Negative affectivity is a predictor of social inhibition, which enhances knowledge hiding. Positive affectivity slightly weakens the positive and strong effect of supervisor knowledge hiding on subordinate knowledge hiding.
Practical implications
Because alexithymia, social inhibition and negative affectivity may predispose employees to knowledge hiding, managers should identify these personality traits among job applicants and hired employees to make appropriate employment decisions. Moreover, managers should be aware that hiding knowledge by a supervisor may be imitated by subordinates.
Originality/value
Based on conservation of resources theory, this study investigates previously unexplored relationships among alexithymia, social inhibition, affectivity and knowledge hiding.
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Grace W.Y. Wang, Zhisen Yang, Di Zhang, Anqiang Huang and Zaili Yang
This study aims to develop an assessment methodology using a Bayesian network (BN) to predict the failure probability of oil tanker shipping firms.
Abstract
Purpose
This study aims to develop an assessment methodology using a Bayesian network (BN) to predict the failure probability of oil tanker shipping firms.
Design/methodology/approach
This paper proposes a bankruptcy prediction model by applying the hybrid of logistic regression and Bayesian probabilistic networks.
Findings
The proposed model shows its potential of contributing to a powerful tool to predict financial bankruptcy of shipping operators, and provides important insights to the maritime community as to what performance measures should be taken to ensure the shipping companies’ financial soundness under dynamic environments.
Research limitations/implications
The model and its associated variables can be expanded to include more factors for an in-depth analysis in future when the detailed information at firm level becomes available.
Practical implications
The results of this study can be implemented to oil tanker shipping firms as a prediction tool for bankruptcy rate.
Originality/value
Incorporating quantitative statistical measurement, the application of BN in financial risk management provides advantages to develop a powerful early warning system in shipping, which has unique characteristics such as capital intensive and mobile assets, possibly leading to catastrophic consequences.
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The paper intends to show the role of fear of COVID-19 and the relevance of customer empowerment (CU_EMP) and customers’ perceived value of digital service transactions…
Abstract
Purpose
The paper intends to show the role of fear of COVID-19 and the relevance of customer empowerment (CU_EMP) and customers’ perceived value of digital service transactions (CU_PV_DST) in promoting green bank service purchase intention (GBS_PI), despite the antagonistic impacts brought in other sectors and the relevance of customer empowerment (CU_EMP) and customers’ perceived value of digital service transactions (CU_PV_DST) as important mediating variables of the relation.
Design/methodology/approach
The structured questionnaire helped collect survey data from 323 small business people. The model relationship was assessed through EFA, CFA by SPSS-AMOS and SEM using bootstrapping procedures in Smart-PLS.
Findings
The findings of this study show that there is a significant effect of fear of COVID-19 pandemic (F_COVID-19P) on CU_EMP and GBS_PI. CU_EMP influences GBS_PI, whereas F_COVID-19P influences GBS_PI indirectly via CU_EMP. Furthermore, there is a substantial effect of F_COVID-19P on CU_PV_DST and GBS_PI. Thus, F_COVID-19P significantly influences GBS_PI indirectly via CU_PV_DST.
Practical implications
Capitalizing on the COVID-19 wave by empowering customers technologically, improving the legal framework and increasing the perceived value of green service by using an innovative mechanism. In addition, fostering cultural change and emphasizing altruistic values through green advertisements have been explored in this study.
Social implications
Green services are healthier for smart/green economy and are health-protective for coping with health risks.
Originality/value
This study helps in understanding the theories used in this context by linking them to F_COVID-19P with CU_EMP, CU_PV_DST and GBS_PI and contributes to the literature of both. Furthermore, this is the only study that has used SEM to study this kind of interrelation.
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