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In response to the problem of insufficient traction/braking adhesion force caused by the existence of the third-body medium on the rail surface, this study aims to analyze the utilization of wheel-rail adhesion coefficient under different medium conditions and propose relevant measures for reasonable and optimized utilization of adhesion to ensure the traction/braking performance and operation safety of trains.

Based on the PLS-160 wheel-rail adhesion simulation test rig, the study investigates the variation patterns of maximum utilized adhesion characteristics on the rail surface under different conditions of small creepage and large slip. Through statistical analysis of multiple sets of experimental data, the statistical distribution patterns of maximum utilized adhesion on the rail surface are obtained, and a method for analyzing wheel-rail adhesion redundancy based on normal distribution is proposed. The study analyzes the utilization of traction/braking adhesion, as well as adhesion redundancy, for different medium under small creepage and large slip conditions. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived.

When the third-body medium exists on the rail surface, the train should adopt the low-level service braking to avoid the braking skidding by extending the braking distance. Compared with the current adhesion control strategy of small creepage, adopting appropriate strategies to control the train’s adhesion coefficient near the second peak point of the adhesion coefficient-slip ratio curve in large slip can effectively improve the traction/braking adhesion redundancy and the upper limit of adhesion utilization, thereby ensuring the traction/braking performance and operation safety of the train.

Most existing studies focus on the wheel-rail adhesion coefficient values and variation patterns under different medium conditions, without considering whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train. Therefore, there is a risk of traction overspeeding/braking skidding. This study analyzes whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train and whether there is redundancy. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived to further ensure operation safety of the train.

The purpose of this study is to examine the moderating role of the characteristics of the chief executive officer (CEO) on the association between CEO power and corporate social responsibility (CSR) performance.

This paper conducts multiple regression analyses to empirically test the proposed hypotheses based on a sample of US-based publicly held companies. The sample period extends from 2000 to 2018. Firm-level CSR ratings are obtained from the Kinder, Lydenberg and Domini (KLD) database (currently known as MSCI ESG STATS). Financial data and CEO data are retrieved from Compustat and ExecuComp databases, respectively. Additional test and robustness analysis are performed.

This paper shows that firms with more powerful CEOs are less likely to engage in CSR activities. The negative association between CEO power and CSR is found to be exacerbated by CEOs who are younger, more competent and overconfident; however, this negative association is mitigated by CEOs who are female. This paper also finds that gender plays a more important role among CEO characteristics. Collectively, the findings highlight the potential opportunities to better understand the role of various CEO characteristics that jointly affect CSR.

First, this is the first study providing a comprehensive empirical analysis of how various CEO characteristics jointly affect CSR. Prior studies that focus on standalone CEO characteristics offer an incomplete picture of the relation between a single CEO characteristic and a firm's CSR performance. The current study thus extends the research field by examining the association between seemingly unrelated CEO characteristics and CSR performance. The results also highlight that gender is the critical factor moderating the relationship between CEO power and CSR performance when it is compared with CEO age, ability and overconfidence. Second, the authors add to the literature on employee selection by showing that female CEOs mitigate the negative effect of managerial power on CSR performance. Although the currently available empirical research in management control systems focuses on ex-post analyses of moral hazard mitigation for incumbent employees, both the economics and management literature acknowledge ex ante evidence suggesting that employee selection is even more important. Our findings may provide insight into the selection of CEOs.

The purpose of this paper is to investigate the effects of political connections on the association between firms' business strategy and their tax aggressiveness in an emerging economy such as China.

The authors study a large sample of Chinese public firms from 2011 to 2017 using a panel regression model. In addition, a change analysis, an instrument variable test and alternative measures/samples are implemented as robustness tests.

Firms adopting innovative business strategy are more tax aggressive overall. However, innovative firms with political connections are less tax aggressive compared to those without political connections.

This paper contributes to the understanding of firms' tax behaviors in an emerging economy setting. It suggests that there are costs associated with political connections, such as foregone tax saving opportunities, which are understudies in the prior literature.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

While prior research in the area of intellectual capital (IC) disclosure has mainly focused on firm, board and audit committee characteristics, there is little research on whether managerial characteristics are associated with IC disclosure. This study aims to examine the relationship between managerial ability (MA) and the extent of IC disclosure.

The study sample comprises 1,098 firm-year observations of Iranian listed firms during 2012–2017. This study uses the checklist developed by Li et al. (2008) and adopts a content analysis approach and calculates the IC disclosure index in 62 dimensions within three categories: human capital, structural capital and relational capital. To measure MA, this study uses the managerial ability score (MA-Score) developed by Demerjian et al. (2012) for Iranian firms.

The results show that MA is significantly and negatively associated with the overall extent of IC disclosure and all the three components of IC (human capital, structural capital and relational capital). Further analysis shows that the interaction between MA and firm performance is positive and significant, suggesting that the negative relationship between MA and IC disclosure is less pronounced for high-performing firms. This study addresses the potential endogeneity issue by using the propensity score matching approach. The findings are also robust to the alternative measure of MA.

This study contributes to both the MA literature and the IC disclosure literature. To the best of the authors' knowledge, this study is the first to provide empirical evidence on the relationship between MA and IC disclosure.

Currently, there is a conflict in developing countries between the requirements for the self-development of forestry and the insufficient investment in the forestry sector, and the forest ticket system is an innovative forestry management method to solve this contradiction. In the research on the forest ticket system, the study of its price formation mechanism is relatively important. The key issues of the forest ticket system are how to form the forest ticket price and whether the forest ticket pricing methods are reasonable. Solving these problems is the purpose of this study.

This study will use three methods, namely the forest ecosystem service value evaluation index method, the ecosystem service value based on per unit area evaluation method and the contingent valuation method, to study the forest ticket price formation mechanism, filling the gap in the current research on forest ticket pricing methods. It will analyze how these three pricing methods specifically price the forest ticket and evaluate whether these pricing methods are reasonable. This study will then summarize and comprehensively study the forest ticket price formation mechanism and provide policy recommendations for decision-making departments.

The contingent valuation method and the forest ecosystem service value evaluation index method should be mainly used and given priority in the forest ticket pricing process. When the forest ticket is mainly issued for local residents' willingness to compensate for the forestry ecological value, the contingent valuation method should be mainly considered; when the forest ticket is mainly issued for compensating for the ecological value of local used forest land, the forest ecosystem service value evaluation index method should be mainly considered. The ecosystem service value based on per unit area evaluation method does not need to be the focus.

Compared with existing research studies, which focus more on the forest ticket system itself and the definition of forest ticket, this study mainly focuses on the forest ticket price formation mechanism, emphasizing how to form the forest ticket price and whether the forest ticket pricing methods are reasonable, which has a certain degree of innovation and research value and can partially fill the gap in related fields. At the same time, this study has certain help for the enrichment of the forest ticket system and the extension of related research studies.

Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.

To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.

Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.

This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.

This study aims to widen the understanding of how remote work shapes the feedback environment by examining the perceptions of leaders and subordinates of daily, dyadic feedback interactions. The emphasis is on understanding how reciprocity within leader-member exchange (LMX) relationships manifests and how it influences the feedback dynamics.

Template analysis of a qualitative data set consisting of 81 semi-structured interviews with leaders (n = 29) and remote working subordinates (n = 52) was performed.

Drawing on the theoretical frameworks of the feedback environment and the leader-member exchange, the findings demonstrate the imbalance between the efforts of leaders and subordinates in building and maintaining a favourable feedback environment in the remote work context. The results of this study highlight the importance of the dyadic nature of feedback interactions, calling for a more proactive role from subordinates.

Given the estimation that the COVID-19 pandemic has permanently changed the way organizations work, leaders, subordinates and HR practitioners will benefit from advancing their understanding of the characteristics of dyadic, daily feedback interaction in remote work.

Qualitative research on feedback and leader-member exchange interactions in remote work that combines the perceptions of leaders and subordinates is sparse.