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This study aims to form composite solid lubricant coatings on the surface of bearing steel, which can significantly improve the tribological properties of thrust cylindrical roller bearings (TCRBs). Phosphating films possess microscopic porosity that typically needs to be sealed with oil, grease or wax. Due to its unique crystal structure, the phosphating film itself also exhibits a certain degree of lubricity. In this study, solid lubricants are used to fill the pores of the phosphating film. By combining the phosphating film with solid lubricants, lubrication and wear reduction can be achieved.

In this study, the surfaces of the shaft washer (WS) and seat washer (GS) were treated with zinc-phosphating. Subsequently, a solid lubricant solution (polytetrafluoroethylene [PTFE], MoS₂ and graphite) was sprayed onto the phosphated samples at concentrations of 1 , 2  and 3 g/L. The porous and adsorptive nature of the phosphating film was used to embed the solid lubricant particles into the film, thus forming a composite lubrication layer containing solid lubricants on the surface of the bearing steel.

The addition of solid lubricant materials has shown significant potential in reducing wear losses compared with phosphated samples without such additives. Increasing the amount of solid lubricant added can facilitate the formation of a transfer film, which further enhances the protective properties. However, it is important to note that excessive amounts of solid lubricant material can contribute to seizure, leading to increased wear losses of the cage and a higher average coefficient of friction (ACOF).By spraying a PTFE solution with a concentration of 2 g/L, the lowest ACOF and cage wear loss were achieved, resulting in reductions of 60.5% for the ACOF and 89.4% for the cage wear loss. Similarly, when spraying a graphite solution with a concentration of 3 g/L, the lowest wear losses for GS and WS were observed, with reductions of 51.7% for GS wear loss and 38.9% for WS wear loss.

The combination of the phosphating film and solid lubricants aims to achieve lubrication and wear reduction, providing a new approach to wear-resistant technology for TCRBs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0231/

This research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.

This study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.

Results indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.

This research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.

A research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.

This study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.

This study explores the economic impact of the COVID-19 crisis on herding behaviour in the Australian equity market by considering liquidity, government interventions and sentiment contagion.

This study utilizes a daily dataset of the top 500 stocks in the Australian market from January 2009 to December 2021. Both predictive regression and portfolio approaches are employed to consider the impact of COVID-19 on herding intention.

This study confirms that herding propensity is more pronounced at the beginning of the crisis and becomes less significant towards later phases when reverse herding is more visible. Investors herd more toward sectors with less available information on financial support from the government during the financial meltdown. Conditioning the stock liquidity, herding is only detectable during highly liquid periods and high-liquid stocks, which is more observable during the initial phases of the crisis. Further, the mood contagion from the United States (US) market to Australian market and asymmetric herding intention are evident during the pandemic.

This is the first study to shed further light on the impact of a health crisis on the trading behaviour of Australian investors, which is driven by liquidity, public information and sentiment. Notwithstanding the theoretical contributions to the prior literature, several practical implications are proposed for businesses, policymakers and investors during uncertainty periods.

This study aims to assess the technological capability of Chinese internet platforms (BAT: Baidu, Alibaba, Tencent) compared to US ones (GAFA: Google, Amazon, Facebook, Apple). More specifically, this study explores Baidu’s technological catching-up process with Google by analyzing their patent textual information.

The authors retrieved 26,383 Google patents and 6,695 Baidu patents from PATSTAT 2019 Spring version. The collected patent documents were vectorized using the Word2Vec model first, and then K-means clustering was applied to visualize the technological space of two firms. Finally, novel indicators were proposed to capture the technological catching-up process between Baidu and Google.

The results show that Baidu follows a trend of US rather than Chinese technology which suggests Baidu is aggressively seeking to catch up with US players in the process of its technological development. At the same time, the impact index of Baidu patents increases over time, reflecting its upgrading of technological competitiveness.

This study proposed a new method to analyze technology mapping and evolution based on patent text information. As both US and China are crucial players in the internet industry, it is vital for policymakers in third countries to understand the technological capacity and competitiveness of both countries to develop strategic partnerships effectively.