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This paper aims to design a novel test device and study the wear properties and the thermal mechanisms of roller pairs in dual-freedom sliding contacts.

On the transition process of lubrication regimes, experiments were conducted with various values of running speed and slip ratio obtained by two motorized spindles. Temperature and surviving time would be obtained of GCr15/GCr15 and DLC/GCr15 friction pairs. Micro photography was obtained with a PGI 3D stylus profiler and a confocal microscopy OLS4000-3D. An empirical mode decomposition method was used to eliminate measure errors.

Results showed that, even with little initial lubricant, rolling/sliding pairs still rotated for a certain time. With the synthetic actions of the dual-freedom sliding, the loss of lubrication and the tilt, interesting helical grooves appeared. Sliding speeds had remarkable effects on survive time, temperatures and surface topographies. In addition, the equilibrium values of the temperature and the surface roughness were obtained in sufficient oil supply. Extreme wear-out conditions were obtained with starved lubrication. Diamond-like carbon coatings showed better heat resistance and better wear resistance.

This work would be critical for the life design and the heat treatment of rolling bearings in the full flood lubrication and the starved lubrication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0164/

In influencer advertising, followers engage in more frequent and timely interactions compared to nonfollowers, making them the primary audience for these advertisements. Building on this premise, this study aims to examine the impact of different influencer types, categorized by follower count, on the advertised brands.

The authors tested the hypotheses in four studies, including one secondary data analysis and three experiments.

Combining real-world data with a series of experiments, the authors show that the followers of mega-influencers (vs micro influencers) have a more positive response to the advertised brands, with more positive brand attitudes, greater purchase intentions and higher engagement. The authors call this the “mega-influencer follower effect.” It is driven by the sense of control. This effect only occurs among the followers and not nonfollowers. Moreover, the mega-influencer follower effect only existed in human influencers, not virtual influencers.

This study takes influencer followers as influencer advertising audiences and investigates the effect of influencer types (based on the number of followers) on the advertised brands; however, future research may investigate how consumers respond to brands in different categories endorsed by influencers.

The authors argue that influencer advertising audiences are more likely to be followers of the influencer. From this perspective, the results suggest that marketers should cooperate with mega-influencers.

Through emphasizing the value of followers rather than nonfollowers as audiences, this study expands the literature on influencer marketing and the explanatory mechanisms regarding which types of influencers are more effective.

The metaverse, a virtual space where one can build and explore with others using avatars, is drawing global interest. Then questions arise: What drives consumers to customize their avatars and purchase virtual items in the metaverse? Who customizes and purchases virtual items more than others? To find the answers, this study tested a research model that explains why consumers customize their avatars and buy virtual items in the metaverse.

Based on the stimuli-organism-response model, this study posits that metaverse characteristics (i.e. escapism, visual attractiveness, social interaction and autonomy) arouse consumers’ curiosity toward the metaverse, which in turn evokes avatar customization behavior and virtual item purchase intention. Survey data from 501 metaverse-experienced consumers in both the US and Korea are analyzed.

The result revealed that all four metaverse characteristics were found to stimulate consumers’ curiosity. Consumers’ curiosity enhances avatar customization behavior and purchase intention of the virtual items. Further, avatar customization behavior increases the purchase intention of virtual items.

The findings provide valuable insights into how metaverse platforms can effectively engage consumers by stimulating curiosity, especially through social interaction, and offering extensive avatar customization options and virtual items.

This study highlights how the metaverse’s open-ended experiences, user-driven customization and social interactions – unlike traditional online games – spark consumer curiosity. It emphasizes the pivotal role of curiosity in driving metaverse engagement and highlights the need to consider it as a central construct in future research. Additionally, this study provides managerial implications for virtual item purchases in the metaverse.

This study aims to find out how pomposia fruit powder (Syzygium cumini L.) mixed with roasted coffee (RCO) affected antioxidants, phytochemicals, lipid peroxidation inhibition and sensory attributes.

Pomposia fruits (Syzygium cumini L.) powder (PFP) was integrated with RCO at levels of 0.0%, 5.0%, 10.0%, 15.0% and 20.0%. RCO, PFP and binary mixtures containing RCO: PFP were evaluated for their total phenolics (TP), total flavonoids (TF), anthocyanin content (AC), antioxidant activity and phenolic compounds fractionation. The oxidative indices of coffee oil samples were measured throughout different storage intervals. Additionally, sensory characteristics of RCO enriched with different PFP doses were evaluated.

PFP samples exhibited the greatest TP content (1910 mg/100 g), whereas RCO samples had the lowest concentration (1090 mg/100 g). As more PFP was added, the corresponding coffee blends’ concentrations of TP, TF and AC were improved significantly. PFP possesses a radical-scavenging activity that is about 1.20 times more than RCO’s. DPPH (2,2-diphenyl-1-picrylhydrazyl) radical-scavenging activity jumped significantly from 74.13% in control (untreated) samples to 77.64%, 78.39% and 80.15% for samples enriched with 10.0%, 15.0% and 20% PFP, respectively. Significant increases in gallic acid, hesperidine, benzoic acid, chlorogenic acid, hispertin, catechol, quercetin, pyrogallol and rutin were detected when RCO was mixed with different quantities of PFP. At the end of storage trial, the coffee oil treated with 20% PFP had AV, PV and TBA values that were about 1.70, 1.95 and 1.66 times lower, respectively, than those of the control sample that had not had PFP addition. The RCO with 5.0% PFP achieved the greatest over acceptability grades.

To the best of the authors’ knowledge, this study was the first study to evaluate the effect of incorporating various level of pomposia fruit powder into RCO. The findings shows that adding different concentrations of pomposia fruit powder into RCO can indeed enhance the radical-scavenging activity of the coffee and potentially extend its shelf life.

In response, this study developed a mathematical and computational method, through spatial configurations with justified plan graph (JPG), drawn from Space Syntax to extract essential information of the spatial topology of 13 valuable traditional courtyard houses located in Toon historical city of Iran.

Historical vernacular housing has always been designed to incorporate and reflect the local lifestyle and cultural conditions. “Courtyard” is a fundamental part of traditional Iranian houses. This traditional building type includes a walled boundary and a complex of open, semi-enclosed and enclosed spaces. This study investigates the traditional houses in Toon historical town. Toon is one of the ancient towns in southeast Iran, including old courtyard houses in its heritage context. The spatial influence of the courtyard contributes to the formation of this famous architectural type.

The results show the remarkable impact of this space on dominating the plan of traditional Toon houses configuration compared to other spaces in all cases. Furthermore, spatial accessibility has changed over time, and the Safavid period had a higher level of integration and lower level of accessibility (mean i = 7.03) rather than the Qajar period (mean i = 6.34); also, privacy has decreased progressively.

The knowledge of characteristics of this historical architecture needs to be gathered for the preservation and conservation of the built heritage. Hence, the principle behind traditional Iranian courtyards was investigated to recognize the difference between the spatial influence of the courtyard and other spaces and the changes in the courtyard over time.

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.

This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.

The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.

The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

This study aims to investigate the influence of corporate governance (CG) on environmental disclosure (ED) practices within UK and US firms, addressing the contemporary challenges confronting firms in both contexts.

Using the dynamic panel regression framework of system generalised method of moment (GMM), this study analyses a sample comprising 121 FTSE and 200 S&P firms from 2010 to 2020.

The findings emphasise the dynamic nature of ED practices among UK and US firms, demonstrating their propensity to swiftly adjust to desired levels whenever deviations occur. Besides, this study identifies board independence and the frequency of board meetings as significant determinants of ED for UK firms. In contrast, for US firms, board independence and audit committee independence are found to be significant determinants of ED.

The research highlights the fundamental role played by CG in shaping how firms in the UK and the US navigate agency problems and respond to diverse stakeholder demands through ED in their annual reports. This study advocates for the promotion of robust governance systems that concurrently serve the purposes of accountability and monitoring to bridge the information expectation gap between firms and stakeholders. The findings reinforce the necessity for regulatory initiatives involving policy formulation and corporate oversight to enhance private sector awareness regarding environmental reporting practices.

This study contributes to the scarce literature on the impact of board and audit committee characteristics on ED practices in the UK and US contexts. In addition, by using the system GMM estimation technique, this study provides robust and updated evidence that addresses the weaknesses inherent in previous studies.

The vehicle routing problem (VRP) is critical for the successful execution of logistics activities. However, there is strong evidence that efficiently solving the VRP is often complicated and requires more powerful – and possibly intelligent – support tools. In accordance with this necessity, the present study proposes a decision support system (DSS) applicable to the VRP, which includes both initial planning and replanning phases to support the real-time operations.

The proposed DSS lies at the basis of resilience thinking to provide a capacity to absorb and withstand the impact of disruptions, where resilience is connected with the factors of preparedness, flexibility and redundancy. These factors are approached in this study through a number of operational strategies in the reactive and proactive modes. The DSS includes a multi-layer perceptron neural network to predict changes that may arise in dynamic contexts, a modified k-means clustering algorithm to group customers with both static and dynamic attributes and two mixed-integer programming models to produce primary and alternate routing plans.

The research is motivated by the operational challenges faced by a collaborative networked clinical laboratory, which seeks to enhance efficiency and productivity in the daily management of medical sample collection and delivery through the implementation of increased automation. The findings reveal that centralized planning leads to heightened vulnerability in route planning and increased costs for replanning. Furthermore, the effectiveness of resilience-enhancement strategies varies based on the source and level of uncertainty.

The contributions of this paper are as follows: incorporating resilience thinking into the operational planning of logistics services, managing the decision-making of transport and collection companies through a DSS framework to ensure proper support to real-time operations, addressing the clustered VRP in a dynamic setting and adopting forecasting approaches to cover possible sources of dynamism.

In recent years, the concept of logistics cluster has attracted the attention of several researchers and practitioners. It is an agglomeration of different types of companies and operations: notably, those providing logistics services, such as supply chain organization, storage and distribution. The paper focuses on this concept by examining the factors influencing logistics service providers (LSPs) to enter the logistics clusters.

An exploratory qualitative study based on semi-structured interviews was conducted. Regarding the sample size, the author interviewed 31 professionals belonging to logistics clusters located in the Moroccan economic metropolis: Casablanca.

The results show that the cost reduction, the reputation of the cluster, the learning from other LSP, the communal services, the geographical proximity, and the role of public authorities are the main factors impacting the entry of LSPs into these clusters.

The findings of this study provide several practical insights for LSPs, government authorities, and cluster managers. For LSPs, understanding the key factors influencing their entry into logistics clusters—such as cost reduction, proximity and the role of public authorities—enables them to make strategic decisions that optimize their operations and enhance competitiveness. For cluster managers, the study highlights the importance of maintaining a strong cluster reputation and fostering collaboration between LSPs to attract new entrants. Finally, public authorities can leverage the insights to design policies that incentivize LSPs to join clusters by providing infrastructure, financial support and governance structures that align with industry needs.

This theme has never been investigated. Therefore, this research expands the literature review and tries to examine this gap of literature by studying the factors that can affect the adhesion of LSPs to these clusters.