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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.

The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.

The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.

This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.

By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

Strategic flexibility (SF) has become increasingly important for firms because of the fast changes in the external environment. In line with the practical importance of SF, an emerging research field has developed around it that has attempted to understand the nature of SF and the key relationships. The aim of this study is to unveil the semantic structure of the recent literature on SF and to suggest new promising areas for future research.

The authors conduct a systematic literature review with a bibliographic analysis technique, which allows authors to identify the main recent streams in the literature, as well as offer reflections and suggestions for future research.

The authors uncover three main emerging areas in the research on SF, namely SF as a dynamic capability, the role of knowledge management for SF and the relationship between a firm SF and the external environment. The authors put forward three avenues for future research on SF: Avenue 1. SF, business model innovation (BMI) and other dynamic capabilities (DC), Avenue 2. Digital technologies and SF/organizational agility and Avenue 3. SF and sustainability. Articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2, thus paving the way for filling some of the identified gaps regarding the relationship between SF and digitalization.

To the best of authors’ knowledge, this is the first literature review on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. The review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time, as well as by presenting three main avenues for further developing authors’ knowledge around SF.

To proactively draw efficient maintenance plans, road agencies should be able to forecast main road distress parameters, such as cracking, rutting, deflection and International Roughness Index (IRI). Nonetheless, the behavior of those parameters throughout pavement life cycles is associated with high uncertainty, resulting from various interrelated factors that fluctuate over time. This study aims to propose the use of dynamic Bayesian belief networks for the development of time-series prediction models to probabilistically forecast road distress parameters.

While Bayesian belief network (BBN) has the merit of capturing uncertainty associated with variables in a domain, dynamic BBNs, in particular, are deemed ideal for forecasting road distress over time due to its Markovian and invariant transition probability properties. Four dynamic BBN models are developed to represent rutting, deflection, cracking and IRI, using pavement data collected from 32 major road sections in the United Arab Emirates between 2013 and 2019. Those models are based on several factors affecting pavement deterioration, which are classified into three categories traffic factors, environmental factors and road-specific factors.

The four developed performance prediction models achieved an overall precision and reliability rate of over 80%.

The proposed approach provides flexibility to illustrate road conditions under various scenarios, which is beneficial for pavement maintainers in obtaining a realistic representation of expected future road conditions, where maintenance efforts could be prioritized and optimized.

Building on the theory of brand psychological ownership, this paper aims to explore the mediating role of brand psychological ownership in the relationship between brand personality (innocence/coolness) and consumers’ preferences, as well as identify the boundary conditions of this relationship.

To test the hypotheses, a series of four experiments were conducted in Wuhan, a city in southern China, using questionnaires administered at two universities and two supermarkets. Hypotheses were tested using PLS-SEM in SmartPLS 4.

The results indicate that brand personality, specifically the dimensions of innocence and coolness, has a significant impact on consumers’ brand preferences. Brands with a cool personality are preferred over those with an innocent personality. Moreover, the relationship between brand personality and consumers’ brand preferences is moderated by power motivation and identity centrality.

This study contributes to the literature by differentiating between brand personality of innocence and coolness as two separate constructs and proposing brand psychological ownership as a mechanism through which brand personality affects brand preferences. The study’s samples were drawn from universities and supermarkets in southern China, providing evidence for the significant moderating effects of power motivation and identity centrality on consumers’ brand preferences.

This empirical research examined the factors and conditions that contribute to the success of international strategic learning alliances. The study aimed to provide organisations with evidence-based insights and recommendations that can help them to create more effective and sustainable partnerships and to leverage collaborative learning to drive innovation and growth. The examination is performed using game theory as a mathematical framework to analyse the interaction of the decision-makers, where one alliance's decision is contingent on the decision made by others in the partnership. There are 20 possible games out of 120 outcomes that can be grouped into four different types; each type has been divided into several categories.

The research methodology included secondary and primary data collection using empirical data, the Delphi technique for obtaining qualitative data, a research questionnaire for collecting quantitative data and computer simulation (1,000 cases, network resources and cooperative game theory). The key variables collected and measured when analysing a strategic alliance were identified, grouped and mapped into the developed model.

Most respondents ranked reputation and mutual benefits in Type 1 games relatively high, averaging 4.1 and 3.85 of a possible 5. That is significantly higher than net transfer benefits, ranked at 0.61. The a priori model demonstrate that Type 1 games are the most used in cooperative games and in-game distribution, 40% of all four types of games. This is also confirmed by the random landscape model, approximately 50%. The results of the empirical data in a combination of payoff characteristics for Type 1 games show that joint and reputation benefits are critical for the success of cooperation.

Research on cross-border learning alliances has several implications. Managerial implications can help managers to understand the challenges and benefits of engaging in these activities. They can use this knowledge to develop strategies to improve the effectiveness of their cross-border learning alliances. Practical implications, the development of game theory and cross-border models can be applied in effective decision-making in a variety of complex contexts. Learning alliances have important policy implications, particularly in trade, investment and innovation. Policymakers must consider the potential benefits and risks of these collaborations and develop policies that encourage and support them while mitigating potential negative impacts.

International learning alliances have become a popular strategy for firms seeking to gain access to new knowledge, capabilities and markets in foreign countries. The originality of this research lies in its ability to contribute to the understanding of the dynamics and outcomes of these complex relationships in a novel and meaningful way.

This paper aims to establish a theoretical framework that can comprehensively explain the executive compensation in state-owned enterprises (SOEs) within the context of socialism with Chinese characteristics.

The author develops a theoretical framework for executive compensation in SOEs from the perspective of Marxist economics and points out that the executives in SOEs are engaged in management labor, and their compensation should adhere to the principle of distribution according to labor contribution.

Based on this theory, the author posits that the continuous upward trend of executive compensation in SOEs, is consistent with the trend of SOEs' ongoing expansion, which reflects a continuous improvement of SOE executives' management labor in both quality and quantity.

It is necessary to start with Marxist economic theory and scientifically study the issue of SOE executive compensation, adhere to the principle of distribution according to work in the context of a socialist market economy and implement the specific guideline of the Party Central Committee; only in this way can the long-term healthy development of SOEs be promoted continuously.

This paper examines whether following a health crisis the use of health and safety protocols and hotel brand awareness influences hotel perceived value and intention to visit.

Using an experimental design, the study evaluates the effectiveness of the use of health and safety protocols and the moderating effect of brand awareness on perceived value and intention to visit.

The results show that the hotels using health and safety protocols (compared to those that do not use them) will achieve a higher perceived value and intention to visit. In addition, the awareness of brand does not moderate the effect of the health and safety protocols on perceived value and intention to visit.

This research identifies mechanisms for future consideration by hotel companies to promote the recovery of their activity after a health crisis. Specifically, using health and safety protocols will result in the market evaluating the brand more highly and produce a greater intention to visit. At the same time, the research indicates that regardless of whether the brand is well-known or not, the use of a health and safety protocol is advantageous.

This study offers new insights that can be useful for developing a resilient hotel sector in the face of future health crises. Specifically, the results show progress in understanding the effects that the use of health and safety protocols and brand awareness have on key consumer variables for the recovery of the sector in a post-pandemic context.

The research carried out a bibliometric analysis of the literature on environmental sustainability from a demand perspective by analyzing the scientific contributions published in the last twenty years.

A bibliometric analysis was carried out to outline the scientific studies development, identifying the most discussed topics and those that would require future research. In total, 274 articles published between 1999 and 2021 were collected through the Web of Science database and analyzed with the SciMAT software.

By systematizing the literature results, the study revealed a steady growth in the number of publications and in the research areas, highlighting a substantial evolution of the research topic.

The study contribute for conceptual, methodological and thematic development of the topic, systematizing the results of existing studies and providing useful indications for the promotion of sustainable consumer habits.

The study attempts to bridge the gap in current literature by offering a holistic view on the role of consumer behavior in pursuing sustainability goals, identifying both the most treated areas and the emerging ones that can represent opportunities for future research.

Background: This paper examines the impact of coronavirus COVID-19 outbreak on employees’ mental health, specifically psychological distress and depression. It aims at identifying the main stressors during and post COVID-19, examining the main moderating factors which may mitigate or aggravate the impact of COVID-19 on employees’ mental health and finally to suggest recommendations from a human resource management perspective to mitigate COVID-19’s impact on employees’ mental health.

Methods: This paper is a literature review. The search for articles was made in Google scholar, Web of Science and Semantic scholar. We used a combination of terms related to coronavirus OR COVID-19, workplace and mental health. Due to the paucity of studies on the COVID-19 impact on employees’ mental health, we had to draw on studies on recent epidemics.

Results: The identified literature reports a negative impact of COVID-19 on individual’s mental health. Stressors include perception of safety, threat and risk of contagion, infobesity versus the unknown, quarantine and confinement, stigma and social exclusion as well as financial loss and job insecurity. Furthermore, three dimensions of moderating factors have been identified: organizational, institutional and individual factors. In addition, a list of recommendations has been presented to mitigate the impact of COVID-19 on the employee’s mental health, during and after the outbreak, from a human resource management perspective.

Conclusions: Coronavirus is new and is in a rapid progress while writing this paper. Most of current research are biomedical focusing on individuals’ physical health. In this context, mental health issues seem overlooked. This paper helps to broaden the scope of research on workplace mental health, by examining the impact of a complex new pandemic: COVID-19 on employees’ mental health, from social sciences perceptive, mobilizing psychology and human resource management.