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The aim of this paper is to analyse how technological innovations in performance measurement systems make it possible to overcome some of the challenges that public healthcare organizations face where management and control are concerned. The changes that could be applied to the performance measurement system of healthcare organisations were analysed together with an evaluation of the responses developed in order to achieve these changes.

The paper contains an in-depth case-study of a public university hospital which utilises an innovative information system.

The case-study highlights how technological innovations in performance measurement systems impact the management and monitoring information system in a public university hospital, through the implementation of a multidimensional management dashboard.

The limitation of this paper is that only one case-study is analysed, albeit in depth, while it would be interesting to consider more public university hospitals.

The paper highlights the fundamental role of middle management in change processes in the healthcare sector.

The case-study highlights how critical the active involvement of middle management is in performance measurement and management, and how this is achieved thanks to the adoption of a simple, clear method which ensures comprehensible communication of the objectives, as well as the measurement of performance by means of radar plots.

This paper aims to improve the tribological properties of lithium complex greases using nanoparticles to investigate the tribological behavior of single additives (nano-TiO₂ or nano-CeO₂) and composite additives (nano-TiO₂–CeO₂) in lithium complex greases and to analyze the mechanism of their influence using a variety of characterization tools.

The morphology and microstructure of the nanoparticles were characterized by scanning electron microscopy and an X-ray diffractometer. The tribological properties of different nanoparticles, as well as compounded nanoparticles as greases, were evaluated. Average friction coefficients and wear diameters were analyzed. Scanning electron microscopy and three-dimensional topography were used to analyze the surface topography of worn steel balls. The elements present on the worn steel balls’ surface were analyzed using energy-dispersive spectroscopy and X-ray photoelectron spectroscopy.

The results showed that the coefficient of friction (COF) of grease with all three nanoparticles added was low. The grease-containing composite nanoparticles exhibited a lower COF and superior anti-wear properties. The sample displayed its optimal tribological performance when the ratio of TiO₂ to CeO₂ was 6:4, resulting in a 30.5% reduction in the COF and a 29.2% decrease in wear spot diameter compared to the original grease. Additionally, the roughness of the worn spot surface and the maximum depth of the wear mark were significantly reduced.

The main innovation of this study is the first mixing of nano-TiO₂ and nano-CeO₂ with different sizes and properties as compound lithium grease additives to significantly enhance the anti-wear and friction reduction properties of this grease. The results of friction experiments with a single additive are used as a basis to explore the synergistic lubrication mechanism of the compounded nanoparticles. This innovative approach provides a new reference and direction for future research and development of grease additives.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2023-0291/

The purpose of this paper is to investigate the friction and wear mechanisms in copper-based self-lubricating composites with MoS₂ as the lubricating phase, which provides a theoretical basis for subsequent research on high-performance copper-based self-lubricating materials.

Friction tests were performed at a speed of 100 r/min, a load of 10 N, a friction radius of 5 mm and a sliding speed of 30 min. Friction experiments were carried out at RT-500°C. The phase composition of the samples was characterized by X-ray diffraction of Cu Ka radiation, and the microstructure, morphology and elemental distribution were characterized by scanning electron microscopy and energy dispersive spectroscopy. Reactants and valences formed during the wear process were analyzed by X-ray photoelectron spectroscopy.

The addition of MoS₂ can effectively improve friction-reducing and anti-wear action of the matrix, which is beneficial to form a lubricating film on the sliding track. After analyzing different changing mechanism of the sliding tracks, the oxides and sulfides of MoS₂, MoO₂, Cu₂O, CuO and Ni(OH)₂ were detected to form a synergetic lubricating film on the sliding track, which is responsible for the excellent tribological properties from room to elevated temperature.

For self-lubrication Cu–Sn–Ni–MoS₂ material in engineering field, there are still few available references on high-temperature application.

This paper provides a theoretical basis for the following research on copper-based self-lubricating materials with high performance.

With this statement, the authors hereby certify that the manuscript is the results of their own effort and ability. They have indicated all quotes, citations and references. Furthermore, the authors have not submitted any essay, paper or thesis with similar content elsewhere. No conflict of interest exits in the submission of this manuscript.

This study aims to investigate the effect of V doping on the microstructure, chemical stability, mechanical and vacuum tribological behavior of sputtered MoS₂ coatings.

The MoS₂-V coatings are fabricated via tuning V target current by magnetron sputtering technique. The structural characteristic and elemental content of the coatings are measured by field emission scanning electron microscopy, X-ray diffractometer, electron probe X-ray micro-analyzer, Raman, X-ray photoelectron spectroscopy, high resolution transmission electron microscope and energy dispersive spectrometer. The hardness of the deposited coatings are tested by a nanoindentation technique. The vacuum tribological properties of MoS₂-V coatings are studied by a ball-on-disc tribometer.

Introducing V into the MoS₂ coatings results in a more compact microstructure. The hardness of the coatings increases with the doping of V. The MoS₂-V coating deposited at a current of 0.2 A obtains the lowest friction coefficient (0.043) under vacuum. As the amount of V doping increases, the wear rate of the coating decreases first and then increases, among which the coating deposited at a current of 0.5 A has the lowest wear rate of 2.2 × 10–6 mm³/N·m.

This work elucidates the role of V doping on the lubrication mechanism of MoS₂ coatings in a vacuum environment, and the MoS₂-V coating is expected to be applied as a solid lubricant in space environment.

The events sector is an innovative and dynamic working environment that requires a creative and diverse workforce to help it thrive. However, in the main, the events workforce is not diverse, with evidence suggesting that most leaders continue to be White and male. There has been no previous research exploring the experiences of ethnically diverse professionals in this environment. This paper aims to draw on the theory of racialised organisations to begin to address this gap and amplify the voices of ethnically diverse events professionals.

Qualitative, semi-structured interviews were conducted with 17 ethnically diverse event managers working in the UK events industry.

Covert and overt forms of racism and discrimination remain ubiquitous within the culture of event organisations, and in a number of guises, ranging from regular racialised microaggressions to more subtle forms of exclusion. The events industry needs to do more than pay lip service to neoliberal notions of diversity and acknowledge the ways in which racial relations of power shape the industry and the experiences of individuals within it, and design interventions to address these issues.

To the best of the authors’ knowledge, this study is the first to apply the theory of racialised organisations to the events industry, recognising the centrality of race and racism to events organisations and careers. In so doing, it offers essential insight into race and ethnicity in this sector and contributes to ongoing efforts to integrate race and racism within theorising in management and organisation studies.

Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation process to ensure remedial actions. This study aims to conduct an experimental research to detect anomalies in the evaluation methods.

Experimental research is conducted with scientific approach and design. The researchers categorized anomaly into three categories, namely, an anomaly in criteria assessment, subject anomaly and anomaly in subject marks allocation. The different anomaly detection algorithms are used to educate data through the software R, and the results are summarized in the tables.

The data points occurring in all algorithms are finally detected as an anomaly. The anomaly identifies the data points that deviate from the data set’s normal behavior. The subject which is consistently identified as anomalous by the different techniques is marked as an anomaly in evaluation. After identification, one can drill down to more details into the title of anomalies in the evaluation criteria.

This paper proposes an analytical model for the course evaluation process and demonstrates the use of actionable analytics to detect anomalies in the evaluation process.

Construction safety is heavily affected by using new technologies in this growing trend of technology adoption. Especially, safety performance is enhanced through the utilization of some effective technologies such as artificial intelligence, virtual reality, BIM and wearable devices. Therefore, the main purpose of this study is to investigate the influence of emerging technologies on construction safety performance and quantify the relationship between those. The proposed components of emerging technologies are BIM, GIS, VR, RFID, AI, ML, eye tracking and serious games and wearable devices, whereas the dimensions of construction safety performance are safety planning, safety training, safety inspection and monitoring, safety audits and reviews and safety leadership.

A structural model was composed consisting of emerging technologies and safety performance indicators. Then, a questionnaire was designed and administered to construction professionals, and data from 167 projects were analyzed using structural equation modeling. The data were analyzed by using software, called SPSS AMOS.

The analysis of the structural model proves that there is a positive and significant relationship between emerging technologies and construction safety performance. Moreover, the factor loadings for each factor were found to be high indicating a good representation of the construct by the components developed. Among the technologies, BIM, robotics and automation, AI and wearable devices were detected to be the most significant technologies in terms of impacting safety performance.

The study contributes to the body of knowledge in that it develops a conceptual framework consisting of specific technologies in terms of emerging technologies, reveals the impact of such technologies on safety performance and proposes several tools and strategies for enabling effective safety management along the project lifecycle. Industry practitioners may benefit from the framework developed by adopting such technologies to enhance their safety performance on construction projects.

Aluminum alloy is considered an ideal material in aerospace, automobile and other fields because of its lightweight, high specific strength and easy processing. However, low hardness and strength of the surface of aluminum alloys are the main factors that limit their applications. The purpose of this study is to obtain a composite coating with high hardness and lubricating properties by applying GO–PVA over MAO coating.

A pulsed bipolar power supply was used as power supply to prepare the micro-arc oxidation (MAO) coating on 6061 aluminum sample. Then a graphene oxide-polyvinyl alcohol (GO–PVA) composite coating was prepared on MAO coating for subsequent experiments. Samples were characterized by Fourier infrared spectroscopy, X-ray diffraction, Raman spectroscopy and thermogravimetric analysis. The friction test is carried out by the relative movement of the copper ball and the aluminum disk on the friction tester.

Results showed that the friction coefficient of MAO samples was reduced by 80% after treated with GO–PVA composite film.

This research has made a certain contribution to the surface hardness and tribological issues involved in the lightweight design of aluminum alloys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0427/

The COVID-19 pandemic severely impacted tourism, and the hotel and restaurant industry was the most affected sector, which faced issues related to business uncertainty and unemployment during the crisis. The analysis of recovery time and the influence factors is significant to support policymakers in developing an effective response and mitigating the risks associated with the tourism crisis. This study aims to investigate numerous factors affecting the recovery time of the hotel and restaurant sector after the COVID-19 crisis by using survival analysis.

This study uses the quarterly value added with the observation time from quarter 1 in 2020 to quarter 1 in 2023 to measure the recovery status. The recovery time refers to the number of quarters needed for the hotel and restaurant sector to get value added equal to or exceed the value added before the crisis. This study applies survival models, including lognormal regression, Weibull regression, and Cox regression, to investigate the effect of numerous factors on the hazard ratio of recovery time of hotels and restaurants after the COVID-19 crisis. This model accommodates all cases, including “recovered” and “not recovered yet” areas.

The empirical findings represented that the Cox regression model stratified by the area type fit the data well. The priority tourism areas had a longer recovery time than the non-priority areas, but they had a higher probability of recovery from a crisis of the same magnitude. The size of the regional gross domestic product, decentralization funds, multiplier effect, recovery time of transportation, and recovery time of the service sector had a significant impact on the probability of recovery.

This study contributes to the literature by examining the recovery time of the hotel and restaurant sector across Indonesian provinces after the COVID-19 crisis. Employing survival analysis, this study identifies the pivotal factors affecting the probability of recovery. Moreover, this study stands as a pioneer in investigating the multiplier effect of the regional tourism and its impact on the speed of recovery.