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Under oil interruption, lubricant supply in the high-speed bearing cavity is interrupted, which reduces the bearing lubrication and cooling ability, thus leading to degradation of bearing performance or even its failure. This paper aims to study the effect of grooves at the noncontact outer ring area on the flow and thermal performance of high-speed bearings under oil interruption, which is expected to improve the resistance of existing bearings to oil interruption.

The groove was added to the noncontact outer ring area of the bearing, and a method of combining volume of fluid and MRF was adopted to systematically study and analyze the oil-gas flow field structure and the temperature field distribution in the bearing cavities.

Results show that the lubricating oil could be stored and guided by the grooves of the bearing outer ring into the key lubrication area inside the bearing cavity, which increased the oil content near the inner ring and made the oil distribution more uniform. As a result, lubrication cooling and heat dissipation performance of the bearing cavity was improved. Compared with the original bearing, the bearing with a V-shaped groove had the optimal lubrication and cooling performance.

A rolling bearing model of the noncontact outer ring area with grooves under oil interruption is established in the paper. The simulation results provide theoretical guidance for the research and development of high-speed bearings with stronger oil interruption resistance ability.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0199/

Achieving sustainability and sustainable performance has emerged as a critical area of focus for both academic research and practice. However, this pursuit faces challenges, particularly concerning the inadequacy of supply chain information. To address this issue, our study employs the organizational information processing theory to explore how adopting blockchain technology enables firms to learn from and collaborate with their supply chain partners, ultimately facilitating their sustainable performance even in the presence of organizational inertia.

Underpinned by the organizational information processing theory and drawing data from 220 manufacturing firms in China, we use structural equation modeling to test our conceptual model.

Our results demonstrate that blockchain technology adoption can significantly enhance sustainable performance. Furthermore, supply chain learning acts as a mediator between blockchain technology adoption and sustainable performance, while organizational inertia plays a negative moderating role between blockchain technology adoption and supply chain learning.

These findings extend the existing literature on blockchain technology adoption and supply chain management, offering novel insights into the pivotal role of blockchain in fostering supply chain learning and achieving sustainable performance. Our study provides valuable practical implications for managers seeking to leverage blockchain technology to enhance sustainability and facilitate organizational learning.

In the era of the digital economy, digital platform capability plays an important role in the process of firm digitization. This study aims to investigate the relationships among digital platform capability and innovation performance from the perspective of external knowledge search and resource bricolage.

This study uses the hierarchical regression and bootstrapping methods to test the theoretical framework and research hypotheses. The survey data were collected from 629 Chinese firms.

This study finds that digital platform capability has a significant positive effect on innovation performance; external knowledge search and resource bricolage both play partial mediating roles between digital platform capability and innovation performance. There exist the serial mediation effects of “digital platform capability – external knowledge search – resource bricolage – innovation performance”.

The conclusion of this study can expand the research on digital platform capability, reveal the internal mechanism of digital platform capability in firm innovation and provide ideas and inspiration for firms to improve innovation performance and realise high-quality development.

The development of regional public brands for agricultural products necessitates compelling narratives that resonate deeply with consumers. Given the distinctiveness of agricultural products, consumers prioritize the inherent connection to roots and heritage when making purchasing decisions. Therefore, crafting brand narratives must emphasize this root appeal, namely, consumers’ information appeal preference, to positively influence consumers’ brand perceptions and underscore the value of regional public brands. This study investigates this phenomenon through the lens of cue utilization theory.

Four experiments were conducted for this purpose. Study 1 examined the stimulus materials for brand story type (typical vs atypical). The purpose of study 2 was to verify whether the experimental material could be used to categorize participants' information appeal preferences (geographic vs cultural). Study 3 employed a between-subjects design with a 2 (brand story: typical vs atypical) × 2 (consumers’ information appeal preferences: cultural vs geographic) factorial design. Study 4 used a between-subjects design of 2 (brand story: typical and atypical) × 2 (consumers’ information appeal preferences: cultural vs geographic) × 2 (culturally derived power perception: individual and social).

The findings indicated that the type of brand story and consumers’ information appeal preferences interact with consumers’ brand attitudes toward regional public brands for agricultural products. In addition, a sense of place was found to mediate the interaction between the type of brand story and consumers’ information appeal preferences. Furthermore, culturally derived power perceptions moderated this mechanism.

This study offers valuable insights into marketing regional public brands for agricultural products by categorizing their brand stories into typical and non-typical narratives.

This paper is drawn on resource-based theory (RBV), dynamic capability theory (DCV) and situational strength theory (SST). It aims to investigate the relationship of entrepreneurial leadership (EL) on project success (PS) through the mediating role of dynamic capabilities (DCs), big data analytic capability (BDAC) and sustainable resilience (SR). It also explores the moderating effect of knowledge sabotage behaviour (KSB) on the relationship of BDAC and SR with PS.

Data was collected via Questionnaire survey through convenience sampling from the sample of 550 employees working on project in software companies. Of these, 467 response was deemed valid for analysis. The data was analysed using structural equation modelling (SEM) with SMART-PLS tool.

The study revealed a significant impact of EL on PS (p < 0.05). It also confirmed the significant mediating role of BDAC and SR (p < 0.05) in EL and PS relationship. These findings emphasize that adapting an entrepreneurial leadership style provides an environment conducive to achieving project success. Moreover, the presence of DCs like BDAC and SR enhances the organization adaptability, efficiency and firms’ endurance to disruption and strengthens their ability to navigate challenges and drive firm outcomes.

The research provides valuable insight into the role of EL as a contemporary leadership style in project-based firms that are marked by high risk and uncertainty. Also, this research is the first to examine the role of DCs, i.e. BDAC and SR as essential support in the execution of a project. Moreover, the research also highlights the importance of the effective role of DCs in achieving PS by mitigating the moderating influence of KSB. Thus, these DCs are empirically proven to facilitate EL in-driving project success in volatile environment while avoiding counterproductive work behaviour.

In the field of engineering, the fractional moments of random variables play a crucial role and are widely utilized. They are applied in various areas such as structural reliability assessment and analysis, studying the response characteristics of random vibration systems and optimizing signal processing and control systems. This study focuses on calculating the fractional moments of positive random variables encountered in engineering. This study focuses on calculating the fractional moments of positive random variables encountered in engineering.

By integrating Laplace transforms with fractional derivatives, both analytical and practical numerical solutions are derived. Furthermore, specific practical application methods are provided.

This approach allows for the stable and highly accurate calculation of fractional moments based on the integer moments of random variables. Data experiments included in this study demonstrate the effectiveness of this method in solving fractional moment calculations in engineering. Compared to traditional methods, the proposed method offers significant advantages in stability and accuracy, which can further advance research in the engineering field that employs fractional moments.

(1) Accuracy: Although the proposed method does involve some error, its error level is significantly lower than traditional methods, such as the Taylor expansion method. (2) Stability: The computational error of the proposed method is not only minimal but also remains stable within a narrow range as the fractional order varies. (3) Efficiency: Compared to the widely used Taylor expansion method, the proposed method requires only a minimal number of integer-order moments to achieve the desired results. Additionally, it avoids convergence issues during computation, greatly reducing computational resource requirements. (4) Simplicity: The application steps of the proposed method are very straightforward, offering significant advantages in practical applications.

Young construction project management practitioners (CPMPs) have unique, complex, and notable occupational mental health problems. However, there were few studies about the intervention for occupational mental health of CPMPs, and traditional intervention modes often failed to achieve significant effects. Therefore, this study aims to propose a new and effective intervention method.

Job crafting intervention was used to design an intervention experiment. A total of 72 CPMPs participated in a 10-week randomized controlled trial in China. Descriptive statistics and repeated measures analysis of variance were used to verify the effectiveness of job crafting intervention (JCI) on job crafting behaviors, job burnout, and work engagement with consideration of the impact of time.

Results showed that the intervention increased social resources, thus effectively reducing job burnout and promoting work engagement. Time also had a significant impact on cynicism, dedication, and social resources.

The authors should promote the habit of job crafting in CPMPs. Furthermore, in order to facilitate their job crafting, the authors should increase structural and social resources for them, and the authors can also encourage them to undertake challenging demands to increase their self-efficacy and the sense of achievement.

The authors bring into light a new psychological intervention approach among CPMPs, which integrates the advantages of the guidance in traditional organized intervention methods and the proactivity in individual spontaneous job crafting. The authors verify the efficacy of the JCI among CPMPs and help propose countermeasures and suggestions to improve the occupational mental health of CPMPs.

This study examines whether common directors are guilty of contagion of corporate frauds from the customer side and, if so, how contagion occurs. Moreover, it explores a way to mitigate it, which is the increased digital orientation of firms.

Secondary data analysis is applied in this paper. We extract supply chain relations from the China Stock Market and Account Research (CSMAR) database as well as corporate fraud data from the same database and the official website of the China Securities Regulatory Commission (CSRC). Digital orientations are estimated through text analysis. Poisson regression is conducted to examine the moderating effect of common directors and the moderated moderating effect of the firms’ digital orientations.

By analysing the 2,096 downstream relations from 2000 to 2021 in China, the study reveals that corporate frauds are contagious through supply chains, while only customers’ misconduct can contagion to upstream firms. The presence of common directors strengthens such supply chain contagion. Additionally, the digital orientation can mitigate the positive moderating effect of common directors on supply chain contagion.

This study highlights the importance of understanding supply chain contagion through corporate fraud by (1) emphasising the existence of the contagion effects of corporate frauds; (2) understanding the potential channel in the process of contagion; (3) considering how digital orientation can mitigate this contagion and (4) recognising that the effect of contagion comes only from the downstream, not from the upstream.

The purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.

This study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.

The implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.

These findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.

This study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.