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1 – 9 of 9Tao Pang, Wenwen Xiao, Yilin Liu, Tao Wang, Jie Liu and Mingke Gao
This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the…
Abstract
Purpose
This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.
Design/methodology/approach
Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.
Findings
The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.
Originality/value
The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.
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Fateh Saci, Sajjad M. Jasimuddin and Justin Zuopeng Zhang
This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the…
Abstract
Purpose
This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.
Design/methodology/approach
Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.
Findings
The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.
Practical implications
The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.
Originality/value
The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.
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Furong Jia and Jie Yu
Gamification is a strategic approach employed by practitioners to foster meaningful engagement and enhance the acceptance of recommendations. Gamification affordances (e.g…
Abstract
Purpose
Gamification is a strategic approach employed by practitioners to foster meaningful engagement and enhance the acceptance of recommendations. Gamification affordances (e.g. achievement, self-expression, interaction, and cooperation) catalyze significant psychological processes in consumers, leading to behavioral changes. Despite its application, a gap remains in understanding how these gamification affordances in e-commerce contexts impact customers' perceived values and drive recommendation acceptances.
Design/methodology/approach
Employing affordance theory and perceived value theory as our foundation, we have crafted a comprehensive framework that addresses the multifaceted nature of e-commerce gamification, thereby unifying the fragmented knowledge in this area. We implemented a quantitative research design to empirically test the proposed model.
Findings
The research reveals that the four principal affordances of gamification – achievement, self-expression, interaction, and cooperation – significantly enrich consumer values across hedonic, utilitarian, and social dimensions. This enrichment facilitates an increased propensity for accepting recommendations.
Originality/value
This study provides a novel lens through which to view the influence of gamification affordances on recommendation acceptance within gamified e-commerce settings. It delineates the effects of each affordance on consumers' perceived value and highlights the pivotal affordances that shape gamified e-commerce experiences. These insights yield actionable strategies for practitioners aiming to refine e-commerce gamification designs and cultivate more engaging consumer interactions.
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This study investigated the impact of entrepreneurship education on the international entrepreneurship intention of the university students while considering the mediating roles…
Abstract
Purpose
This study investigated the impact of entrepreneurship education on the international entrepreneurship intention of the university students while considering the mediating roles of entrepreneurship alertness, proactive personality, innovative behaviour and the moderating role of global mindset in this relationship.
Design/methodology/approach
The research employs a survey methodology, utilising a structured questionnaire for data collection. The study specifically concentrates on students enrolled at Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED) in Ghana, drawing its sample from six academic programmes within the university. Data analysis is conducted using structural equation modeling (SEM).
Findings
The findings of this research revealed that entrepreneurship education exerts a positive influence on the international entrepreneurial intention. Furthermore, entrepreneurship alertness acts as a mediator in the relationship between entrepreneurship education and innovative behaviour. Similarly, a proactive personality serves as a mediating factor between entrepreneurship education and innovative behaviour. Moreover, innovative behaviour operates as a mediator in the relationship between entrepreneurship education and international entrepreneurship intention. Additionally, a global mindset plays a crucial moderating role in the connection between entrepreneurship education and international entrepreneurship intention.
Originality/value
This study makes a significant contribution to the field by shedding light on the mediating roles of proactive personality, entrepreneurial alertness, innovative behaviour and global mindset moderating the relationship between entrepreneurship education and international entrepreneurship intention. These insights offer fresh perspectives on the complex dynamics at play in the realm of entrepreneurship education and its impact on students' intentions for the international entrepreneurship.
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Anxia Wan, Qianqian Huang, Ehsan Elahi and Benhong Peng
The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for…
Abstract
Purpose
The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.
Design/methodology/approach
The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.
Findings
The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.
Originality/value
In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.
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Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable…
Abstract
Purpose
Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.
Design/methodology/approach
An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.
Findings
On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.
Originality/value
The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.
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Yuchun Huang, Haishu Ma, Yubo Meng and Yazhou Mao
This paper aims to study the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti3C2 to improve the tribological properties of M50 bearing steel with microporous channels.
Abstract
Purpose
This paper aims to study the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti3C2 to improve the tribological properties of M50 bearing steel with microporous channels.
Design/methodology/approach
M50 matrix self-lubricating composites (MMSC) were designed and prepared by filling Sn–Ag–Cu and MXene–Ti3C2 in the microporous channels of M50 bearing steel. The tribology performance testing of as-prepared samples was executed with a multifunction tribometer. The optimum hole size and lubricant content, as well as self-lubricating mechanism of MMSC, were studied.
Findings
The tribological properties of MMSC are strongly dependent on the synergistic lubrication effect of MXene–Ti3C2 and Sn–Ag–Cu. When the hole size of microchannel is 1 mm and the content of MXene–Ti3C2 in mixed lubricant is 4 wt.%, MMSC shows the lowest friction coefficient and wear rate. The Sn–Ag–Cu and MXene–Ti3C2 are extruded from the microporous channels and spread to the friction interface, and a relatively complete lubricating film is formed at the friction interface. Meanwhile, the synergistic lubrication of Sn–Ag–Cu and MXene–Ti3C2 can improve the stability of the lubricating film, thus the excellent tribological property of MMSC is obtained.
Originality/value
The results help in deep understanding of the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti3C2 on the tribological properties of M50 bearing steel. This work also provides a useful reference for the tribological design of mechanical components by combining surface texture with solid lubrication.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0381/
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Ziyuan Ma, Huajun Gong and Xinhua Wang
The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for…
Abstract
Purpose
The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.
Design/methodology/approach
First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.
Findings
It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.
Originality/value
A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.
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Atefeh Hemmati, Mani Zarei and Amir Masoud Rahmani
Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of…
Abstract
Purpose
Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.
Design/methodology/approach
This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.
Findings
This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.
Research limitations/implications
This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.
Originality/value
This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.
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