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Considering the greenwashing risk of symbolic environmental management, this study aims to distinguish the motivation for environmental investment growth (EIG) from the corporate cost stickiness and anti-stickiness perspectives.

This study analyzes the impact of substantive and symbolic environmental management on cost stickiness. Subsequently, competing hypotheses are proposed. Finally, empirical tests are conducted on Chinese A-share listed companies from 2010 to 2019.

EIG significantly improves enterprises’ cost stickiness. The cost of high EIG enterprises does not decrease significantly with a decline in income compared to other enterprises, which is consistent with the motivation for substantive environmental management. Enterprises with high asset specificity and optimistic management expectations show more obvious substantive environmental management. Government and public environmental concerns cause more pronounced substantive environmental management.

An evaluation of corporate environmental responsibility should take into account both what the company has disclosed and what it has actually done.

Governments and the public should have a comprehensive understanding of corporate environmental management. They need to strengthen their ability to recognize symbolic environmental management and support substantive environmental management.

Fundamental to the evaluation of corporate environmental responsibility, this study distinguishes the motivations for corporate EIG disclosures from the cost stickiness perspective to avoid the risk of greenwashing. Hypotheses on the impact of substantive and symbolic environmental management on cost stickiness are presented. This study verifies the substantive environmental management characteristics of listed Chinese companies.

This study aims to explore the extent to which Chinese multinational enterprises (MNEs) rely on supranational institution – the Belt and Road Initiative (BRI) – versus host country institutional quality to navigate their foreign location choice.

This study uses a conditional logit regression model using a sample of 1,302 greenfield investments by Chinese MNEs in 54 BRI participating countries during the period 2011–2018.

The results indicate that as a supranational institution, the BRI serves as a substitution mechanism to address the deficiencies in institutional quality in BRI participating countries, thereby attracting Chinese MNEs to invest in those countries. In addition, the BRI’s substitution effect on host country institutional quality is more pronounced for large MNEs, MNEs in the manufacturing industry and MNEs in inland regions.

This study expands the understanding of the BRI as a supranational institution for MNEs from emerging markets and reveals its substitution effect on the host country institutional quality. Furthermore, it highlights that MNEs with diverse characteristics gain varying degrees of benefits from the BRI.

Considering the bounded confidence of decision-makers (DMs), a new grey multi-criteria group consensus decision-making (GMCGCDM) model is established by using interval grey number (IGN), cobweb model, social network analysis (SNA) and consensus reaching process (CPR).

Firstly, the model analyzes the social relationship of DM under social networks and proposes a calculation method for DMs’ weights based on SNA. Secondly, the model defines a cobweb model to consider the preferences of decision-making alternatives in the decision-making process. The consensus degree is calculated by the area surrounded by the connections between each index value of DMs and the group. Then, the model coordinates the different opinions of various DMs to reduce the degree of bias of each DM and designs a consensus feedback mechanism based on bounded confidence to guide DMs to reach consensus.

The advantage of the proposed method is to highlight the practical application, taking the selection of low-carbon suppliers in the context of dual carbon as an example. Comparison analysis is performed to reveal the interpretability and applicability of the method.

The main contribution of this paper is to propose a new GMCGCDM model, which can not only expand the calculation method of DM’s weight and consensus degree but also reduce the time and cost of decision-making.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

This study mainly focused on the long-term effect of different risk exposure levels and prior anti-epidemic experience of healthcare workers in mitigating COVID-19 on their work stress in the post-COVID era.

The study sample included 359 physicians, 619 nurses, 229 technicians and 212 administrators, for a total of 1,419 healthcare workers working in the Lanzhou area during the investigation. Data were analyzed by multivariate regression models.

Our findings indicated that the interaction between pandemic effect mitigation experience and high-risk exposure significantly affected healthcare workers in the post-COVID era by increasing their work stress (p < 0.001) and reducing their rest time (p < 0.001). Healthcare workers may have experienced worse outcomes in the long term if they had higher levels of risk exposure and more experience in fighting epidemics. Furthermore, poor mental health (p < 0.001) and prior experience with SARS (p < 0.001) further amplified these adverse effects. However, surprisingly, we did not observe any effect of prior anti-epidemic experience or high-risk exposure on the mental health of healthcare workers in the post-COVID era (p > 0.1).

The adverse impact of COVID-19 may have left long-lasting effects on Health professionals (HPs), particularly those with high Risk exposure (RE) and more mitigation experience. Poor Mental health (MH) and previous experience in mitigating previous similar outbreaks (such as SARS) are risk factors that should be considered. Support programs must be designed and promoted to help HPs respond and improve their performance.

Our study presents compelling evidence that the COVID-19 pandemic will have long-term detrimental effects on the work stress of healthcare workers.

China’s foreign aid efforts in Africa remain contentious. Chinese foreign aid tends to be different from “traditional” development assistance in that it frequently involves firms as the implementing agents of projects. Firms bring unique resources to public–private partnerships (PPPs) formed with government agencies, but their possible self-interested nature also gives rise to concerns over their development impact. Yet, on a larger scale, little is known about the characteristics of Chinese PPPs in foreign aid. Using project-level data available for 1,308 Chinese aid projects in 50 countries across Africa, the author characterizes the projects undertaken by firms and government agencies in a PPP and contrasts them to those executed by Chinese government agencies without firm involvement. This exploratory data analysis suggests that important differences apply, as Chinese PPPs tend to target different sustainable development goals (SDGs), work on the basis of distinct aid conditions, and implement projects that tend to be larger than those that are solely run by government agencies. Such observations raise important questions of an ethical, theoretical, and international nature, and warrant further research. The author develops a research agenda that aims at issues particularly important for business ethics scholars, organization theorists, and international business scholarship.

The purposes of this paper are optimization of high speed reducer in electric vehicles based on the analysis of lubrication and verification of simulation accuracy and optimization results.

The traditional CFD method presents poor applicability to complex geometric problems due to grid deformity. Therefore, moving particle semi-implicit (MPS) method is applied in this study to simulate lubrication of the reducer and analyze the influence of input speed and lubrication system design on the distribution. According to the results, the reducer is optimized. Meanwhile, the experiments for lubrication and churning power loss is carried out to verify the accuracy of simulation and optimization effects.

The flow field of lubricant inside the reducer is obtained. The lubrication system of reducer needs to be improved. Simulation and experiment show that the optimization is sufficient and efficient.

According to the simulation of lubrication, the reducer is optimized. The lubrication experimental setup is established. The conclusion of paper can provide the method and tool for reducer in electric vehicle.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0123/

In order to solve the decision-making problem that the attributive weight and attributive value are both interval grey numbers, this paper tries to construct a multi-attribute grey decision-making model based on generalized greyness of interval grey number.

Firstly, according to the nature of the generalized gresness of interval grey number, the generalized weighted greyness distance between interval grey numbers is given, and the transformation relationship between greyness distance and real number distance is analyzed. Then according to the objective function that the square sum of generalized weighted greyness distances from the decision scheme to the best scheme and the worst scheme is the minimum, a multi-attribute grey decision-making model is constructed, and the simplified form of the model is given. Finally, the grey decision-making model proposed in this paper is applied to the evaluation of technological innovation capability of 6 provinces in China to verify the effectiveness of the model.

The results show that the grey decision-making model proposed in this paper has a strict mathematical foundation, clear physical meaning, simple calculation and easy programming. The application example shows that the grey decision model in this paper is feasible and effective. The research results not only enrich the grey system theory, but also provide a new way for the decision-making problem that the attributive weights and attributive values are interval grey numbers.

The decision-making model proposed in this paper does not need to seek the optimal solution of the attributive weight and the attributive value, and can save the decision-making labor and capital investment. The model in this paper is also suitable for the decision-making problem that deals with the coexistence of interval grey numbers and real numbers.

The paper succeeds in realizing the multi-attribute grey decision-making model based on generalized gresness and its simplified forms, which provide a new method for grey decision analysis.

Drawing on social information processing theory (SIP), this paper examines whether and how humble leadership affects employees' service improvisation (ESI) in the hospitality industry. Further, the study investigates the mediating role of psychological safety and the moderating role of creative self-efficacy (CSE).

To test the proposed relationships, the study adopts a cross-sectional design, administering questionnaires to 456 frontline staff in Egypt’s hospitality industry across three main sectors: restaurants, hotels and travel agencies. SPSS 27 and AMOS 22 were used for statistical analysis.

The study reveals a positive relationship between humble leadership and ESI, partially mediated by psychological safety. Furthermore, CSE not only strengthens the relationship between psychological safety and ESI but also enhances the indirect effect of humble leadership on ESI via psychological safety.

The study offers valuable insights for practitioners in the hospitality industry. To boost ESI, organizations can incorporate humble leadership attributes into their leadership development programs. Fostering a psychologically safe workplace would facilitate the positive impact of humble leadership on ESI. Recognizing CSE as a pivotal moderator underscores the importance of strategically selecting and developing employees with high CSE. These insights aim to cultivate a more service-oriented and effective workforce in the hospitality industry.

This study significantly contributes to leadership research in the hospitality industry by uncovering a previously unexplored link between humble leadership and ESI. Exploring psychological safety as a mediator and CSE as a moderator enhances our comprehension of how and when humble leadership influences ESI.