Qinqin Li, Yujie Xiao, Yuzhuo Qiu, Xiaoling Xu and Caichun Chai
The purpose of this paper is to examine the impact of carbon permit allocation rules (grandfathering mechanism and benchmarking mechanism) on incentive contracts provided by the…
Abstract
Purpose
The purpose of this paper is to examine the impact of carbon permit allocation rules (grandfathering mechanism and benchmarking mechanism) on incentive contracts provided by the retailer to encourage the manufacturer to invest more in reducing carbon emissions.
Design/methodology/approach
The authors consider a two-echelon supply chain in which the retailer offers three contracts (wholesale price contract, cost-sharing contract and revenue-sharing contract) to the manufacturer. Based on the two carbon permit allocation rules, i.e. grandfathering mechanism and benchmarking mechanism, six scenarios are examined. The optimal price and carbon emission reduction decisions and members’ equilibrium profits under six scenarios are analyzed and compared.
Findings
The results suggest that the revenue-sharing contract can more effectively stimulate the manufacturer to reduce carbon emissions compared to the cost-sharing contract. The cost-sharing contract can help to achieve the highest environmental performance, whereas the implementation of revenue-sharing contract can attain the highest social welfare. The benchmarking mechanism is more effective for the government to prompt the manufacturer to produce low-carbon products than the grandfathering mechanism. Although a loose carbon policy can expand the total emissions, it can improve the social welfare.
Practical implications
These results can provide operational insights for the retailer in how to use incentive contract to encourage the manufacturer to curb carbon emissions and offer managerial insights for the government to make policy decisions on carbon permit allocation rules.
Originality/value
This paper contributes to the literature regarding to firm’s carbon emissions reduction decisions under cap-and-trade policy and highlights the importance of carbon permit allocation methods in curbing carbon emissions.
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Jing Quan, Jih-Yu Mao, Yujie Shi and Xiao Liang
This study investigates why and when undermined employees exhibit deviant behavior toward coworkers. Drawing upon social exchange theory, coworker undermining reduces employee…
Abstract
Purpose
This study investigates why and when undermined employees exhibit deviant behavior toward coworkers. Drawing upon social exchange theory, coworker undermining reduces employee organization-based self-esteem (OBSE), which in turn, fosters employee negative reciprocal behavior in the form of interpersonal deviance. In addition, this study examines the moderating role of relational-interdependent self-construal (RISC) in affecting the indirect effect.
Design/methodology/approach
Data were collected from a two-wave survey. Participants were 316 employees of a service company in western China. Ordinary least squares regressions were used to test the hypothesized relationships.
Findings
Coworker undermining is positively related to employee interpersonal deviance, mediated by decreased employee OBSE. In addition, this indirect relationship is more salient for employees with a higher than lower RISC.
Originality/value
This study suggests that employee OBSE serves as an explanation for why coworker undermining leads to employees’ antagonistic consequences. Furthermore, this study highlights the boundary-condition role of RISC in the influence process.
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Weihua Liu, Jiahe Hou, Yujie Wang and Ou Tang
Drawing on the stakeholder theory, this study aims to empirically analyse the impact of platform enterprises’ corporate social responsibility (CSR) announcements on corporate…
Abstract
Purpose
Drawing on the stakeholder theory, this study aims to empirically analyse the impact of platform enterprises’ corporate social responsibility (CSR) announcements on corporate stock market value. This study also estimates the moderating effect of stakeholder orientation and responsibility categories of CSR announcements, the platform enterprise type and the degree of CSR disclosure.
Design/methodology/approach
The event study method is used to analyse the change in stock market value of 191 CSR announcements from 137 Chinese platform enterprises. In addition, a case analysis is presented for two platform enterprises with the best practices to validate and complement study findings.
Findings
CSR announcements improve platform enterprises’ stock market value. Specifically, CSR announcements responding to platform enterprises’ external stakeholders, and CSR announcements with economic responsibility, have obvious positive impacts on stock market value. Furthermore, the maker platform’s CSR announcement has a more positive impact on stock market value than the exchange platform.
Originality/value
To the best of the authors’ knowledge, this study is the first attempt to identify the link between platform enterprises’ CSR announcements and stock market performance by empirical evidence, and it contributes to new knowledge of operating and evaluating platform enterprises’ CSR.
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Yujie Cheng, Hang Yuan, Hongmei Liu and Chen Lu
The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale…
Abstract
Purpose
The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale invariant feature transform (SIFT) algorithm. This method is different from those methods extracting fault feature directly from the traditional one-dimensional domain.
Design/methodology/approach
The vibration signal of rolling bearings is first transformed into a two-dimensional image. Then, the SIFT algorithm is applied to the image to extract the scale invariant feature vector which is highly distinctive and insensitive to noises and working condition variation. As the extracted feature vector is high-dimensional, kernel principal component analysis (KPCA) algorithm is utilized to reduce the dimension of the feature vector, and singular value decomposition technique is used to extract the singular values of the reduced feature vector. Finally, these singular values are introduced into a support vector machine (SVM) classifier to realize fault classification.
Findings
The experiment results show a high fault classification accuracy based on the proposed method.
Originality/value
The proposed approach for rolling bearing fault diagnosis based on SIFT-KPCA and SVM is highly effective in the experiment. The practical value in engineering application of this method can be researched in the future.
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This chapter presents a theoretical framework of the industrial relations (IR) system in China’s coal mining industry, combining the roles of management organizations, workers…
Abstract
This chapter presents a theoretical framework of the industrial relations (IR) system in China’s coal mining industry, combining the roles of management organizations, workers, and trade unions, as well as government agencies. It is one of the first empirical attempts to investigate the relationship between human resource (HR) practices, labor relations, and occupational safety in China’s coal mining industry over the past 60 years, based on the secondary data on coal mining accidents and case studies of two state-owned coal mines in a northern city in Anhui Province, China. The fluctuating occupational safety has been affected by government regulations over different time spans, marked by key political agendas, and by coal mining firms taking concrete measures to respond to these regulations, while exhibiting differing safety performance in state-owned versus township-and-village-owned mines. The field studies compared a safety-oriented to a cost-control-oriented HR and labor relations system, and their influences on safety performance. Coal mining firms and practitioners are advised to shift the traditional personnel management paradigm to a modern HR management system. In addition, although workers are often blamed directly for accidents, it is suggested that workers’ participation and voice in various processes of decision-making and policy implementation, and trade unions’ active involvement in protecting workers from occupational hazards, be encouraged.
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Xinchuang Xu, Wenao Wang, Yuan Zeng, Yujie Dong and Hanzhou Hao
The paper aims to explore the correlation between the agglomeration of regional innovation elements and the attraction of talent.
Abstract
Purpose
The paper aims to explore the correlation between the agglomeration of regional innovation elements and the attraction of talent.
Design/methodology/approach
This paper uses the factor analysis method to measure the innovation elements index (IEI). The proportion of the regional resident population and registered population is used to measure the attractiveness of talents. The PVAR model is used to analyze the interaction between innovation element agglomeration and talent attraction.
Findings
(1) According to the annual increase rate of IEI, the order is eastern region > central region > western region. (2) Panel vector autoregressive (PVAR) research shows that the agglomeration of innovation factors has a short-term thrust on the attraction of regional talents. (3) The agglomeration of innovative elements is the Granger cause of talent attraction; talent attraction is not the Granger reason for the agglomeration of innovative elements. (4) Pulse analysis and variance decomposition show that the agglomeration of innovative elements has a one-way positive effect on talent attraction.
Research limitations/implications
This study takes China’s provincial panel data as a sample without considering the differences between cities. There may be significant differences in innovation factor agglomeration and talent attraction in different cities.
Practical implications
The findings of this study provide valuable insights into innovation ecosystem practices. Policymakers should pay close attention to promoting the agglomeration of innovation factors by optimizing the innovation ecosystem in order to increase the attractiveness of talents.
Originality/value
(1) This study uses the proportion of regional resident population and household registration population to measure the attractiveness of talents, which is more realistic. (2) This paper is one of the few that examines the relationship between innovation factor agglomeration and talent attraction.
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Na Zhang, Yu Yang, Jiafu Su and Yujie Zheng
Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically…
Abstract
Purpose
Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically express and manage the complex products design process.
Design/methodology/approach
To solve these problems, a supernetwork model of complex products design is constructed and analyzed in this paper. First, the design elements (customer demands, design agents, product structures, design tasks and design resources) are identified and analyzed, then the sub-network of design elements are built. Based on this, a supernetwork model of complex products design is constructed with the analysis of the relationship among sub-networks. Second, some typical and physical characteristics (robustness, vulnerability, degree and betweenness) of the supernetwork were calculated to analyze the performance of supernetwork and the features of complex product design process.
Findings
The design process of a wind turbine is studied as a case to illustrate the approach in this paper. The supernetwork can provide more information about collaborative design process of wind turbine than traditional models. Moreover, it can help managers and designers to manage the collaborative design process and improve collaborative design efficiency of wind turbine.
Originality/value
The authors find a new method (complex network or supernetwork) to describe and analyze complex mechanical product design.
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Jinzhou Li, Jie Ma, Yujie Hu, Li Zhang, Zhijie Liu and Shiying Sun
This study aims to tackle control challenges in soft robots by proposing a visually-guided reinforcement learning approach. Precise tip trajectory tracking is achieved for a soft…
Abstract
Purpose
This study aims to tackle control challenges in soft robots by proposing a visually-guided reinforcement learning approach. Precise tip trajectory tracking is achieved for a soft arm manipulator.
Design/methodology/approach
A closed-loop control strategy uses deep learning-powered perception and model-free reinforcement learning. Visual feedback detects the arm’s tip while efficient policy search is conducted via interactive sample collection.
Findings
Physical experiments demonstrate a soft arm successfully transporting objects by learning coordinated actuation policies guided by visual observations, without analytical models.
Research limitations/implications
Constraints potentially include simulator gaps and dynamical variations. Future work will focus on enhancing adaptation capabilities.
Practical implications
By eliminating assumptions on precise analytical models or instrumentation requirements, the proposed data-driven framework offers a practical solution for real-world control challenges in soft systems.
Originality/value
This research provides an effective methodology integrating robust machine perception and learning for intelligent autonomous control of soft robots with complex morphologies.