bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on the remaining useful life prediction method of hydraulic slide valve based on degradation-competition failure sharing random effect identification
Authors: Yang Xiao , Qian Xinbo 
Published: May 2024

Purpose
Hydraulic slide valve failure often results from competing failure modes, termed competitive failure. To enhance prediction accuracy for hydraulic slide valve remaining useful life, the authors propose a method incorporating competitive failure and Monte Carlo simulation. This method allows for more accurate prediction of hydraulic slide valve remaining useful life.

Design/methodology/approach
In this paper, the competitive failure mode of the hydraulic slide valve is analyzed by studying the two failure modes of the hydraulic slide valve, and the prediction of the remaining useful life of the hydraulic slide valve is studied by using the sample set generated by Monte Carlo simulation and the competitive failure joint model.

Findings
The results show that the proposed prediction method based on competitive failure and Monte Carlo simulation is more accurate than the traditional Bayesian joint model prediction method when dealing with the failure mode competition phenomenon of hydraulic slide valve.

Originality/value
In this paper, the remaining useful life prediction of hydraulic slide valve with competitive failure characteristics is studied, which provides a new idea for the remaining useful life prediction method.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2023-0361/
To disclose or to protect? Predicting social media users’ behavioral intention toward privacy
Authors: Chen Minghong , Huang Xiumei , Qi Xianjun 
Published: May 2024

PurposeIn the paradox of personalized services and privacy risks, what factors influence users’ decisions is considered an interesting issue worth exploring. The current study aims to empirically explore privacy behavior of social media users by developing a theoretical model based on privacy calculus theory.Design/methodology/approachPrivacy risks, conceptualized as natural risks and integrated risks, were proposed to affect the intention of privacy disclosure and protection. The model was validated through a hybrid approach of structural equation modeling (SEM)-artificial neural network (ANN) to analyze the data collected from 527 effective responses.FindingsThe results from the SEM analysis indicated that social interaction and perceived enjoyment were strong determinants of perceived benefits, which in turn played a dominant role in the intention to disclose the privacy in social media. Similarly, trust and privacy invasion experience were significantly related to perceived risks that had the most considerable effect on users’ privacy protection intention. And the following ANN models revealed consistent relationships and rankings with the SEM results.Originality/valueThis study broadened the application perspective of privacy calculus theory to identify both linear and non-linear effects of privacy risks and privacy benefits on users’ intention to disclose or protect their privacy by using a state-of-the-art methodological approach combining SEM and ANN.
Destination advocacy behaviour of residents: examining the role of psychological ownership
Authors: Gupta Anil , Singh Vattan 
Published: May 2024

PurposeThe purpose of this study is to investigate the impact of psychological ownership (PO) on residents’ destination advocacy (DA) behaviour in the context of emerging tourist destinations and to assess the role of attitude as a mediator in the relationship.Design/methodology/approachA quantitative methodology was used and primary data was collected via an online survey to a sample of 333 residents from emerging tourist destinations in India. This study used the partial least squares (PLS) method to test the hypotheses.FindingsThe results indicate that residents’ knowledge about their hometown positively influences PO which in turn affects DA behaviour. Furthermore, PO influences attitude which in turn significantly influences DA behaviour. Additionally, the findings reveal the mediating role of attitude between PO and residents’ advocacy behavioural outcomes.Research limitations/implicationsThis study advances the concept that residents are important stakeholders who can promote a destination. Local authorities should prioritise residents over tourists and incorporate their image, identity, personality, style and values into destination promotion. They can also improve destination services to boost residents' positive attitudes.Originality/valueThe uniqueness of the study lies in associating PO and outcome as DA behaviour. The model suggests that enhancing PO of their hometown among the residents can have significant advantages for tourism development.
Greening the hospitality industry: examining institutional influences and perceived benefits of EMS in Malaysian SME hotels
Authors: Hamzah Hanafi , Wahab Siti Norida , Othman Norashida , Ferguson Gaven 
Published: May 2024

PurposeThe majority of Malaysian firms are small and medium-sized enterprises (SMEs), and the hospitality industry is no exception. However, a study on environmental management systems (EMS) reveals that relatively few studies have observed EMS implementation in small and medium-sized enterprises hotels (SMEHs). Hence, this study aims to determine the link between institutional influences and mediating effects of top managers' perceived benefits toward EMS implementation by Malaysian SMEHs.Design/methodology/approachThe results of a questionnaire survey of 252 SMEHs managerial-level professionals using Smart-PLS software provide some explanation for the marginal action taken by these SMEHs to improve their environmental performance.FindingsBased on the findings, five variables might stimulate the implementation of an EMS: regulatory influences, customer influences, competitor influences, employee influences and manager attributes influences.Research limitations/implicationsThis study significantly advances understanding of EMS and SMEHs, offering a replicable research framework applicable across industries and countries. Scholars can leverage the framework for further exploration, while managers should recognize institutional influences on EMS implementation.Originality/valueGiven that this study is one of the few that investigates the institutional influences and perceived benefits of EMS implementation, it may provide valuable information for future research on the hospitality industry and the SMEHs among researchers and practitioners.
Nurturing trust in Islamic banking within the metaverse for market success
Authors: Al-Afeef Mohammad , Jaradat Hana , Al-Smadi Raed Walid , Al Shbail Mohannad 
Published: May 2024

PurposeThis study aims to investigate the impact of trust in the metaverse on the Islamic banking sector, particularly in facilitating market success. Additionally, it seeks to explore the relationship between metaverse-driven brand image, product features, service quality and overall performance in the market.Design/methodology/approachData were collected from 187 participants in Jordan, with the SmartPLS software used to test the hypotheses.FindingsThe findings reveal a significant impact of metaverse-enhanced brand image, product features and service quality on Islamic banking market performance. Furthermore, customer trust in the metaverse plays a significant role in shaping the relationship between product features, service quality and Islamic banking market performance.Originality/valueThe study’s practical implications still suggest the need for a more holistic metaverse-driven approach. Investing in service quality initiatives alone may not adequately build and sustain customer trust in the metaverse. Instead, transparent communication on ethical practices in the metaverse is required to reinforce trust and magnify the positive influence of superior service quality in the metaverse.
Mental Health First Aid™ for Deaf communities: responses to a lack of national Deaf mental health service provision
Authors: Terry Julia , Robins-Talbot Cathie 
Published: May 2024

Purpose
For over 15 years, Mental Health First Aid™ (MHFA) has successfully been delivered in Wales, United Kingdom, with growing interest in the MHFA programme and increasing course attendees. Trainers, aware of the need for support, know the importance of MHFA being accessible for different communities and learner groups. MHFA has always focused on increasing mental health literacy. One marginalised group, with lower mental health literacy than the general population, is Deaf people, a group with increased risk of mental health problems. This paper aims to provide insights about why Deaf people are twice as likely as hearing people to experience mental health problems.

Design/methodology/approach
During this paper, the authors have used four focal points i) exploring situational contexts for Deaf people; ii) reasons why Deaf individuals are at greater risk of mental health problems; iii) the authors explore a project, “Hear Deaf”, and implementation of MHFA Wales by Deaf MHFA trainers; and iv) initiatives to influence and impact on policymakers.

Findings
During the project, nine MHFA courses were delivered to Deaf communities across different locations in Wales, often with information and advertisements circulated directly to Deaf communities through Deaf clubs, resulting in 120 Deaf people trained. The authors conclude with their own reflections as a researcher and an MHFA who work predominantly with Deaf communities.

Originality/value
This paper provides a discussion on the specific risks for Deaf people around mental health and the importance of mental health promotion programmes for Deaf communities. Further research is needed regarding the impact of MHFA on Deaf populations.
The impact of augmented reality on consumer behavior: a focus on value development, leading to brand engagement and purchase intention
Authors: Negm Eiman 
Published: May 2024

PurposeThis study investigates the impact of augmented reality (AR) on consumers’ shopping process, focusing on value creation, brand engagement and purchasing intents.Design/methodology/approachThis quantitative deductive study analyzed 393 questionnaires through non-probability sampling. A cross-sectional timeframe was applied; data collection took place in May 2023 to provide a snapshot of Egyptian consumers’ responses to AR. Once the needed data were collected, statistical analyses were conducted through the statistical package for social science (SPSS).FindingsThis study shows that in the shopping process, AR vividness, interactivity and informativeness lead consumers to develop utilitarian values toward the technology, and AR interactivity generates hedonic values towards the technology. When consumers sense the hedonic and utilitarian values, it impacts consumers purchase intention. Hedonic value in AR leads to consumers’ brand content consumption and creation; utilitarian value in AR leads to consumers’ brand content consumption, contribution and creation.Practical implicationsAR developers, brand managers and marketers may use this study to understand the current AR landscape and consumer responses toward AR (value development, purchase intention and brand engagement). With these insights, they can make better strategic decisions that include AR usage in brand marketing tactics.Originality/valueThis study develops conclusions to grasp more clearly and in-depth why and how AR impacts consumers’ shopping process. This study addresses various literature gaps, enhancing the understanding of AR: the salient AR attributes that offer consumers hedonic and utilitarian values and how AR influences consumer behavior, specifically when it comes to the development of brand engagement and purchase intents.
Semantic network analysis in consumer and marketing research: application areas in phygital contexts
Authors: Schöps Jonathan David , Jaufenthaler Philipp 
Published: May 2024

PurposeLarge-scale text-based data increasingly poses methodological challenges due to its size, scope and nature, requiring sophisticated methods for managing, visualizing, analyzing and interpreting such data. This paper aims to propose semantic network analysis (SemNA) as one possible solution to these challenges, showcasing its potential for consumer and marketing researchers through three application areas in phygital contexts.Design/methodology/approachThis paper outlines three general application areas for SemNA in phygital contexts and presents specific use cases, data collection methodologies, analyses, findings and discussions for each application area.FindingsThe paper uncovers three application areas and use cases where SemNA holds promise for providing valuable insights and driving further adoption of the method: (1) Investigating phygital experiences and consumption phenomena; (2) Exploring phygital consumer and market discourse, trends and practices; and (3) Capturing phygital social constructs.Research limitations/implicationsThe limitations section highlights the specific challenges of the qualitative, interpretivist approach to SemNA, along with general methodological constraints.Practical implicationsPractical implications highlight SemNA as a pragmatic tool for managers to analyze and visualize company-/brand-related data, supporting strategic decision-making in physical, digital and phygital spaces.Originality/valueThis paper contributes to the expanding body of computational, tool-based methods by providing an overview of application areas for the qualitative, interpretivist approach to SemNA in consumer and marketing research. It emphasizes the diversity of research contexts and data, where the boundaries between physical and digital spaces have become increasingly intertwined with physical and digital elements closely integrated – a phenomenon known as phygital.
Machine learning methods for financial forecasting and trading profitability: Evidence during the Russia–Ukraine war
Authors: Peng Yaohao , Souza João Gabriel de Moraes 
Published: May 2024

PurposeThis study aims to evaluate the effectiveness of machine learning models to yield profitability over the market benchmark, notably in periods of systemic instability, such as the ongoing war between Russia and Ukraine.Design/methodology/approachThis study made computational experiments using support vector machine (SVM) classifiers to predict stock price movements for three financial markets and construct profitable trading strategies to subsidize investors’ decision-making.FindingsOn average, machine learning models outperformed the market benchmarks during the more volatile period of the Russia–Ukraine war, but not during the period before the conflict. Moreover, the hyperparameter combinations for which the profitability is superior were found to be highly sensitive to small variations during the model training process.Practical implicationsInvestors should proceed with caution when applying machine learning models for stock price forecasting and trading recommendations, as their superior performance for volatile periods – in terms of generating abnormal gains over the market – was not observed for a period of relative stability in the economy.Originality/valueThis paper’s approach to search for financial strategies that succeed in outperforming the market provides empirical evidence about the effectiveness of state-of-the-art machine learning techniques before and after the conflict deflagration, which is of potential value for researchers in quantitative finance and market professionals who operate in the financial segment.
Evaluating Taiwan's economic and labour market recovery strategies against COVID‐19
Authors: Lai Wei‐Wen , Wu Chia‐Hsuan , Liu Meng‐Chun , Wang Jiann‐Chyuan 
Published: May 2024

AbstractSince its emergence in 2020, COVID‐19 has profoundly influenced the Taiwan economy and employment landscape, leading to differential impacts across sectors. In response to this unprecedented crisis, the Taiwanese government promptly enacted the “Special Regulations on the Prevention and Rescue of Severe Specific Infectious Pneumonia” on February 25, 2020, which came into force on March 13. This study examines the pandemic's effects through various stages, with a particular focus on the service industry, the sector most affected owing to diminished domestic demand. Using a computable general equilibrium model by integrating monthly changes, the study assess the effectiveness of the Taiwan government's interventions in mitigating job losses and stabilising the economy. Our findings indicate that without the government's relief and revitalisation measures, unemployment rates would have surged significantly. The study underscores the critical role of policy interventions in mitigating the economic impacts of the pandemic.
Managers' career preferences and corporate culture
Authors: Abernethy Margaret A. , Hung Chung‐Yu , Jiang Like 
Published: May 2024

AbstractBuilding effective corporate culture is challenging as it requires senior managers to embed shared values within the firm. Yet some firms can do so, and some cannot. This study examines whether managers' career preferences influence manager‐employee value misalignment and weaken corporate culture. Career preferences for job‐hopping provide incentives for managers to signal their leadership quality in the labor market. We capture managers' and employees' attention allocation across different cultural values using data from conference calls and Glassdoor. We predict and find that job‐hopping managers direct their attention away from soft cultural values (e.g., respect and integrity) that are less observable by the external labor market. Furthermore, job‐hopping managers who pay insufficient attention to soft cultural values fail to address the concerns that employees have in their everyday work, resulting in lower overall employee culture ratings. Our study highlights the significance of managers' career preferences in shaping different cultural values and offers implications for firms selecting senior managers.
Using natural language processing in emergency medicine health service research: A systematic review and meta‐analysis
Authors: Wang Hao , Alanis Naomi , Haygood Laura , Swoboda Thomas K. , Hoot Nathan , Phillips Daniel , Knowles Heidi , Stinson Sara Ann , Mehta Prachi , Sambamoorthi Usha 
Published: May 2024

AbstractObjectivesNatural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to identify and categorize unstructured data within the emergency medicine (EM) setting.MethodsWe systematically searched publications related to EM research and NLP across databases including MEDLINE, Embase, Scopus, CENTRAL, and ProQuest Dissertations & Theses Global. Independent reviewers screened, reviewed, and evaluated article quality and bias. NLP usage was categorized into syndromic surveillance, radiologic interpretation, and identification of specific diseases/events/syndromes, with respective sensitivity analysis reported. Performance metrics for NLP usage were calculated and the overall area under the summary of receiver operating characteristic curve (SROC) was determined.ResultsA total of 27 studies underwent meta‐analysis. Findings indicated an overall mean sensitivity (recall) of 82%–87%, specificity of 95%, with the area under the SROC at 0.96 (95% CI 0.94–0.98). Optimal performance using NLP was observed in radiologic interpretation, demonstrating an overall mean sensitivity of 93% and specificity of 96%.ConclusionsOur analysis revealed a generally favorable performance accuracy in using NLP within EM research, particularly in the realm of radiologic interpretation. Consequently, we advocate for the adoption of NLP‐based research to augment EM health care management.
Development of a minimum clinical dataset for preoperative comprehensive geriatric assessment using a modified Delphi technique
Authors: Lodge Margot , Aitken Rachel , Chong Yih Harng , Thillainadesan Janani 
Published: May 2024

AbstractObjectiveTo construct a standardised, consensus‐guided minimum clinical dataset (MCDS) for preoperative comprehensive geriatric assessment and optimisation (CGA) in Australia and Aotearoa New Zealand.MethodsWe conducted a review of the international perioperative literature to identify CGA domains and tools for potential inclusion in the MCDS. We invited members of the Australian and New Zealand Society for Geriatric Medicine to participate in a Delphi study to obtain consensus on MCDS tools. Participants were asked to rate proposed tools using Likert scales (when >2 tools) or make a binary choice between two proposed tools. Consensus was considered to be achieved when there was at least 75% concordance between the two rounds amongst the participants, and at least one variable attaining over 50% of participants' votes. Domains that did not achieve consensus in Round 1 were carried over to Round 2.ResultsThere were 73 participants in Round 1 of the Delphi study and 47 participants in Round 2. Consensus was achieved on tool/s recommended for every MCDS domain: Clinical Frailty Scale (frailty); sMMSE, RUDAS, MoCA (cognition); 4AT (delirium); timed‐up‐and‐go (physical function); GDS‐15 (mood); Barthel Index (functional status); and MUST (malnutrition).ConclusionsWe recommend clinicians delivering preoperative CGA consider the use of the MCDS we have constructed when assessing older people contemplating surgery, as part of a multicomponent and multidisciplinary approach to optimising perioperative outcomes.
DIY your captures when everything else fails: Description of an artisanal dart launcher with an assessment of the medium‐term response in a primate
Authors: Corbeau Alexandre , Minot Elsa , Tanvier Clara , Le Gouar Pascaline , Péron Guillaume 
Published: May 2024

AbstractWhen our dart guns failed in Morocco, we devised an artisanal pressurised air launcher to replace them. The effective shooting range was between 12 and 20 m, which made it possible to capture wild Barbary macaques (Macaca sylvanus), from groups that would not allow for a closer approach or enter any trap. To assess the effect of that method of capture, we monitored the groups on foot before and after the captures. We looked for evidence of a change in risk perception after the captures. We did not uncover any such evidence in the step lengths, turning angles, home range area, frequency of rest while on the ground or frequency of social interactions. We conclude that for the study animals, being captured with our artisanal dart launcher, had a similar effect to being darted with a professional gun, and we intend this note as an inspiration to other field operators finding themselves in a similar predicament.
In response to “Health and healthcare of people with learning disabilities in the United Kingdom through the COVID‐19 pandemic” (Chris Hatton and colleagues)
Authors: Loblinzk Julie , Strnadová Iva 
Published: May 2024

AbstractWe chose to respond to this paper because bad things are happening in health care for people with intellectual disabilities. We met with Chris Hatton, one of the authors of the article. There were things we liked about the article, things we liked about the study that were not in the article and things we asked Chris about. We enjoyed talking to Chris about the study and writing our response.