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This study aims to evaluate the influence of oleic acid (OA)-capped Al₂O₃ nanoparticles on the tribological performance of conventional lube oil. The goal is to determine the optimal nanoparticle concentration that enhances lubricant efficiency by reducing friction and wear.

The research involved preparing nanolubricants with four different concentrations of Al₂O₃ nanoparticles: 0.05, 0.1, 0.25 and 0.5 wt.%. Tribological performance was assessed using a four-ball tribotester, which measured the coefficient of friction (COF) and wear scar diameter (WSD) under standardized testing conditions.

The experimental results revealed that the nanolubricant containing 0.1 wt.% OA-Al₂O₃ nanoparticles exhibited the most significant improvement in tribological performance. This formulation achieved a 38.84% reduction in COF and a 23.87% reduction in WSD compared to the base lubricant. These findings demonstrate the effectiveness of incorporating OA-capped Al₂O₃ nanoparticles in reducing friction and wear, thereby enhancing the overall performance of conventional lubricants.

This study demonstrates the benefits of OA-capped Al₂O₃ nanoparticles in lubricants, including a 38.84% reduction in COF and a 23.87% reduction in WSD. By systematically analyzing different nanoparticle concentrations, it identified that 0.1% by weight of nanoparticles is the most effective formulation for reducing friction and wear.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0236/

The main impetus of the present analysis is to inspect the effect of psychological capital (PsyCap) on entrepreneurial intentions (EI) amongst college students and to test the mediation role of individual expectancy between PsyCap and EI.

The cross-sectional data of the university students enrolled in business management and engineering courses served as the foundation for the quantitative study design. To test the formulated hypothesis, PLS-SEM is utilized for analyzing the structural relationships between dependent and independent variables.

The results indicate that PsyCap significantly impacts the EI of collegiate students pursuing engineering and management courses. However, individual expectancy plays a partial mediating role between the PsyCap and EI of college students.

This research provides an assessment of the effect of PsyCap on the EI of college students with the partial mediating effect of individual expectancy. The findings deliver the enhancement of the EI literature.

The study outcomes are helpful to educators, university administrators, curriculum developers and entrepreneurial policy planners to realize the role of individual expectancies of students’ entrepreneurs on their EI.

The student entrepreneur community recognizes that individual students with stronger levels of entrepreneurial PsyCap having further probability tend to become future entrepreneurs.

The present analysis is original and holds novelty in the form of the mediating role of individual expectancies between PsyCap and EI of students.

With the technological advancements in the sphere of hospitality and tourism, the significant development has been pragmatic in the industry structures, processes and practices. The worth of innovation in the tourism industry is multifaceted which not only resulted in costs reduction, enhance operational efficiency and service quality upgrade but also enhanced customer experience. This chapter aims to review the articles, papers and books chapters published in various journals in the hospitality and tourism industry area through the lens of technological developments and disruptive innovations. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, VOSviewer and word cloud are the tools applied for papers selection, analysis and the visual representation of the most researched themes. The findings reveal that the many researches being conducted post 2016 in this sphere. The information and communications technology (ICT) devices usage, robotics, artificial intelligence (AI), Radio Frequency Identification (RFID), Blockchain technology (BCT), and digital payments are considered as the crucial factors. The study emphasizes to put on better understanding of innovative disruptions in this sphere, layout plan for future research, and enable the decision-makers and authorities to make futuristic policies to stay competitive.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

This study aims to evaluate the low energy impact characteristics of 3D printed carbon fiber thermoplastic and thermoset polymer composite using the Izod impact test. The effects of infill density are examined on the Izod impact properties of 3D printed thermoset polymer and thermoplastic composite specimens. Furthermore, a thorough investigation is conducted into the effect of heat treatment using a hot-air oven on both types of 3D printed composite specimens. To characterize the impact characteristics of each specimen, the fracture surfaces caused by impact load are inspected, and the fracture mechanism is studied using scanning electron micrographs.

Izod Impact specimens of thermoset (epoxy resin) and thermoplastic carbon fiber of different infill density (70, 75, 80, 85, 90 and 100%) are fabricated using the different fiber impregnation 3D printing process. To carry out the heat treatment process, printing of composites is done for each infill design from both thermoset and thermoplastic composites and the impact characteristics of specimens are evaluated on a pendulum test-rig using the ASTM D-256 standard. Using a scanning electron microscope, each fracture zone underwent four separate scanning processes, ranging in size from 2 µm to 100 µm.

The impact resistance of the 3D printed thermoset and thermoplastic composite material is significantly influenced by the type of fiber placement and infill density in the matrix substrate. Because of the weak interfacial strength between the layers of fiber and polyamide 6, the specimen printed with continuous fiber implanted at the part exhibited reduced impact resistance. At 75% infill density, the impact specimen printed with coextruded fiber showed the highest impact resistance with a 367.02% greater magnitude than the continuous fiber specimen with the same infill density.

This work presents a novel approach to analyze the low energy impact characteristics and three-dimensional printing of carbon fiber reinforced thermoplastic and carbon fiber reinforced thermoset and thermoplastic composite material.

This study aims to examine the impact of specific printing factors, such as layer height, line width and build orientation, on the overall quality of fused filament fabrication (FFF) 3D printed structures. The project also intends to use response surface methodology (RSM) to maximize ultimate tensile strength (UTS) while lowering surface roughness and printing time.

This study used an FFF printer to fabricate samples of polylactic acid (PLA), which were then subjected to assessments of tensile strength and surface roughness. A tensile test was conducted under standardized conditions according to the ASTM D638 standard test method using the AG-50 kN Shimadzu Autograph. The Mitutoyo Surftest SJ-210, which utilizes a needle-tipped inductive method, was used to determine surface roughness. RSM was used for optimization.

This work provides useful insights into how the printing parameters affect FFF 3D printed structures, which may be used to optimize the printing process and improve PLA-based 3D printed products' qualities. The determined optimal values for building orientation, layer height and line width were 0°, 0.1 mm and 0.6 mm, respectively. The total desirability value of 0.80 implies desirable outcomes, and good agreement between experimental and projected response values supports the suggested models.

Previous RSM studies for 3D printing parameter optimization focused on mechanical properties or surface aspects, however, few examined multiple responses and their interactions. This study emphasizes the relevance of FFF parameters like line width, which are often overlooked but can dramatically impact printing quality. Mechanical properties, surface quality and printing time are integrated to comprehend optimization holistically.

The purpose of this paper is to study current practices in adopting blockchain technology amongst export companies in West Sweden and to capture their CEOs’ knowledge of and attitudes towards blockchains.

Factors enabling or hindering the adoption of blockchains were identified from a comprehensive literature review and a survey of 72 chief executive officers (CEOs) of export-oriented firms in West Sweden, all with turnovers exceeding €2m, regarding their knowledge of and attitudes towards blockchains.

Blockchain technology is not currently perceived to provide benefits that would outweigh the costs of introducing it into West Sweden’s export firms. Nevertheless, the findings suggest that such technology, though currently too immature to meet today’s industrial requirements, could experience more widespread use if certain key factors (i.e. lower cost, traceability, improved security or trustworthiness and new blockchain-enabled business models) are prioritised.

Answered by 72 CEOs, the survey achieved a response rate of 6%, meaning that the findings are only exploratory. Even so, they offer new insights into CEOs’ attitudes towards blockchain technology.

The CEOs reported comparatively limited knowledge of and experience with implementing blockchains, the lack of which has hampered their large-scale implementation in multi-actor supply chains.

Negative sentiment amongst CEOs towards blockchain technology may lower on-the-job satisfaction amongst tech personnel aspiring to develop and implement blockchain applications in their firms.

Knowledge of and attitudes towards blockchain technology amongst top-level managers, as well as about factors enabling or hindering its adoption, guide managers in crafting strategies for implementing blockchains in their organisations and maximising the benefits therein. Unlike past studies focussing on technological aspects or views of experts and middle-management, the study was designed to capture the views of CEOs.

Past research has emphasised the potential for conversational artificial intelligence (AI) to disrupt services. Conversely, the literature recognises customer expectations as fundamental to service quality and customer satisfaction. However, the understanding of users’ expectations for conversational AI services is currently limited. Building upon previous research that has underscored the importance of users’ expertise, this study aims to provide valuable insights into the expectations of users with varying levels of expertise.

Forty-five semi-structured interviews were conducted, on three populations: experts, quasi-experts and non-experts from various countries including Japan, France and the USA. This includes 10 experts and 11 quasi-experts, as in professionals in conversational AI and related domains. And 25 non-experts, as in individuals without professional or advanced academic training in AI.

Findings suggest that users’ expectations depend on their expertise, how much they value human contact and why they are using these services. For instance, the higher the expertise the less anthropomorphism was stated to matter compared to technical characteristics, which could be due to a disenchantment effect. Other results include expectations shared by all users such as a need for more ethics including public interest.

The study provides insights into a key yet relatively unexplored area: it defines three major expectations categories (anthropomorphic, technical and ethical) and the associated expectations of each user groups based on expertise. To the best of the authors’ knowledge, it also highlights expectations never detected before as such in the literature such as explainability.