Search results

This study delves into the less-explored domain of teachers’ readiness for leadership roles by investigating the direct and indirect relationships between positive school culture and teachers' readiness for leadership roles through affective-identity motivation to lead, and teacher optimism.

This study employed partial least squares structural equation modelling (WPLS-SEM) for data analysis. The data were gathered from 424 elementary school teachers who do not hold any leadership positions in Xi’an, China. A total of 391 samples were used after sampling weight adjustments.

There is a significant and positive direct relationship between positive school culture and teachers’ readiness for leadership roles. Affective-identity motivation to lead and teacher optimism emerged as significant mediators in this dynamic.

This study complements and expands on the study of the relationship between positive school culture, affective-identity motivation to lead, teacher optimism and teachers' readiness for leadership role. This research has established a theoretical framework for school stakeholders to cultivate future teacher leaders.

These findings provide valuable theoretical insights into educational leadership literature and contribute to a more comprehensive understanding of the factors influencing teachers in assuming leadership roles, particularly in the context of Asian societies.

The application of steel fiber reinforced concrete (SFRC) beams is limited in practice, partially due to the lack of accurate shear strength prediction models. This study aims to develop a reliable shear strength prediction model for SFRC beams.

In this study, an artificial neural network was employed to predict the shear strength of SFRC beams, utilizing a comprehensive database of 562 experimental studies. Multiple neural networks were established with varying hyperparameters, and their performance was evaluated using statistical parameters.

The neural network with 11 neurons showed superior results than other networks. The performance evaluation, efficiency and accuracy of the selected neural network were examined using margin of deviation, k-fold cross-validation, Shapley analysis, sensitivity analysis and parametric analysis. The proposed artificial neural network model accurately predicts the shear strength and outperforms other existing equations.

This research contributes to overcoming the limitations of existing prediction models for shear strength of SFRC beams without stirrups by developing a highly accurate model based on ANN. Utilizing a comprehensive database and rigorous evaluation techniques enhances the reliability and applicability of the proposed model in practical engineering applications.

The composition of author teams is a significant factor affecting the novelty of academic papers. Existing research lacks studies focusing on institutional types and measures of novelty remained at a general level, making it difficult to analyse the types of novelty in papers and to provide a detailed explanation of novelty. This study aims to take the field of natural language processing (NLP) as an example to analyse the relationship between team institutional composition and the fine-grained novelty of academic papers.

Firstly, author teams are categorized into three types: academic institutions, industrial institutions and mixed academic and industrial institutions. Next, the authors extract four types of entities from the full paper: methods, data sets, tools and metric. The novelty of papers is evaluated using entity combination measurement methods. Additionally, pairwise combinations of different types of fine-grained entities are analysed to assess their contributions to novel papers.

The results of the study found that in the field of NLP, for industrial institutions, collaboration with academic institutions has a higher probability of producing novel papers. From the contribution rate of different types of fine-grained knowledge entities, the mixed academic and industrial institutions pay more attention to the novelty of the combination of method indicators, and the industrial institutions pay more attention to the novelty of the combination of method tools.

This paper explores the relationship between the team institutional composition and the novelty of academic papers and reveals the importance of cooperation between industry and academia through fine-grained novelty measurement, which provides key guidance for improving the quality of papers and promoting industry–university–research cooperation.

The COVID-19 outbreak has been accompanied by a massive “infodemic”, characterized by an overabundance of information, both accurate and inaccurate, making it hard for people to find trustworthy sources and reliable guidance. This study aims to investigate how the COVID-19 infodemic (i.e. information overload and untrustworthiness) influences consumers’ emotions (i.e. fear, anxiety and hope) by shaping their cognitive appraisals of the pandemic (i.e. perceived risk and uncertainty). Additionally, this study also investigates how individual differences (i.e. COVID-19 involvement and infection experience) impact their emotion formation process.

Data were collected from 815 US consumers aged between 18 and 65 in November 2021 via an online survey. Structural equation modeling and multi-group comparison from AMOS 23 were used to test the proposed relationships.

Information overload increased one’s perceived risk and perceived uncertainty of COVID-19, which, in turn, structured the emotional states of fear, anxiety and hope. Information untrustworthiness had a significant impact on risk perception, which led to an increased feeling of fear. Additionally, individuals’ COVID-19 involvement and their infection experience with the coronavirus were found to moderate the cognitive appraisal process in developing emotions.

This study offers insights into the relationships between the information landscape and cognitive appraisals regarding health crises, specifically the COVID-19 pandemic. Not only enriching emotional well-being literature, it also lends managerial implications for effective communication strategies in global health emergencies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2023-0616

The purpose of this study is to investigate the influence of light intensity and sources of carbon and nitrogen on the cultivation of Spirulina maxima.

Cultures were carried out in a modified Zarrouk medium using urea, sodium acetate and glycerol. A Taguchi experimental design was used to evaluate the effect on the production of biocompounds: productivities in biomass, carbohydrates, phycocyanin and biochar were analyzed.

Statistical data analysis revealed that light intensity and sodium acetate concentration were the most important factors, being significant in three of the four response variables studied. The highest productivities in biomass (46.94 mg.L⁻¹.d⁻¹), carbohydrates (6.11 mg.L⁻¹.d⁻¹), phycocyanin (3.62 mg.L⁻¹.d⁻¹) and biochar (22, 48 mg.L⁻¹.d⁻¹) were achieved in experiment 4 of the Taguchi matrix, highlighting as the ideal condition for the production of biomass, carbohydrates and phycocyanin.

Sodium acetate and urea can be considered, respectively, as potential sources of carbon and nitrogen to increase Spirulina maxima productivity. From the results, an optimized cultivation condition for the sustainable production of bioproducts was obtained.

This work focuses on the study of the influence of light intensity and the use of alternative sources of nitrogen and carbon on the growth of Spirulina maxima, as well as on the influence on the productivity of biomass and biocompounds. There are few studies in the literature focused on the phycocyanin production from microalgae, justifying the need to deepen the subject.

This study aims to examine the factors influencing customer love (physical environment, food quality, customer-to-customer interaction and innovativeness) and revisits intention in the restaurant industry in Bangladesh.

This study applied a quantitative technique that exceedingly prescribed a methodological approach to positivism from a philosophical stance. Following the purposive sampling, 456 questionnaires were distributed, and 394 were received from the restaurant customer for analysis.

Using the partial least squares-structural equation modeling (PLS-SEM), the salient findings have shown that physical environment, food quality, customer-to-customer interaction and innovativeness have a positive and significant effect on customer love. Besides, customer love is fully mediated between the influencing factors of customer love and revisit intention. The findings also show that customer experience quality actively moderates the factors influencing customer love. Finally, customer love has a positive and significant effect on revisit intention.

Restaurant managers may benefit from the study’s findings. It can be an essential blueprint for theoretical and practical implications. The study also recommends increasing the restaurant’s performance and remaining experienced customers for future transactions.

The present study aims to investigate factors influencing Gen-Z consumers' “green food purchase intention” and “healthy lifestyle”. Guided by the attribution theory, “perceived usefulness of green food”, “food safety concerns” (internal attributes), “perceived threat of environmental problems” and “green peer influence” (external attributes) are considered the predictors of “attitude towards green food”, which eventually lead to a healthy lifestyle and green food purchase intention. Besides, “fear of pandemic recurrence” and “greenwash” are tested as moderators.

The Structural Equation Modelling-Partial Least Squares (PLS-SEM) technique was employed for the model testing. An online questionnaire survey was conducted among Gen-Z Chinese adults, which yielded 556 complete, valid responses.

The findings indicate that “consumers' attitudes towards green food” are positively influenced by “perceived threat of environmental problems”, “perceived usefulness of green food”, “concerns about food safety”, and the influence of “green peers”. In addition, results revealed that “attitude toward green food” exerts a positive effect on “healthy lifestyle” and “green food purchase intention”. The study supports the moderating role of “perceived greenwash” in the relationship between “attitude” and “intention to purchase green food”. However, there was no evidence to support the moderating effect of “fear of pandemic recurrence” in relation to a “healthy lifestyle”.

This study is a pioneer in utilizing the attribution theory to predict the drivers of a “healthy lifestyle” and the “intention to purchase green foods”. Furthermore, this study predicted the moderating influence of “fear of pandemic recurrence” on the relationship between attitude and “healthy lifestyle”, a link that has not been tested in previous research. Furthermore, it introduces a novel examination of the moderating effect of “perceived greenwash” on the relationship between “attitudes” and “purchase intentions”.

The purpose of this study is to examine the relationships between tourists’ motivations, perception of tourism impacts, place attachment (PA) and loyalty toward Jallianwala Bagh, a dark heritage site in Punjab, India.

A mixed-method approach comprising qualitative and quantitative methods was used. Semi-structured interviews and the Delphi method helped generate a 34-item survey instrument. A sample size of 869 respondents was obtained, split into two subsets for exploratory factor analysis and confirmatory factor analysis.

Seven out of nine hypotheses were supported. Motivated tourists perceived higher positive tourism impacts but lower negative tourism impacts. Higher perceptions of positive tourism impacts increased both PA and loyalty to the destination. Surprisingly, the perception of negative tourism impacts did not significantly affect tourist loyalty, contrary to some previous research.

This study informs stakeholders about tourists’ cognitive and affective responses at a dark tourism site, aiding in the planning and development of sustainable tourism strategies.

By understanding the tourists’ motivations and perceptions, stakeholders can manage tourism impacts more effectively, ensuring that tourists’ experiences align with sustainable practices.

This study enriches the understanding of the tourists’ complex interactions with dark heritage sites. It introduces a new angle by examining how motivations, PA and perceptions of tourism impacts influence tourist loyalty, especially in the context of dark tourism.

The purpose of this paper is to shed light on the protection motivation theory’s (PMT) maladaptive coping response to anti-Covid-19 preventive persuasive appeals. PMT is based on coping appraisal that may lead to either an adaptive- or a maladaptive coping response. It has been suggested that the maladaptive coping response is not sufficiently investigated and can be represented by individuals’ resistance to anti-Covid-19 persuasive messages. It has been also supposed that resistance is predicted and modeled through a set of cognitive, affective and individual factors such as information processing style, fear arousal, gender and coping self-efficacy.

An experiment and a survey were conducted online on a random sample of 290 individuals. The sample was divided into two groups, each of which was exposed to an anti-Covid-19 persuasive message.

The findings show that resistance to anti-Covid-19 persuasion is not directly predicted by the individual’s exposure to the message, but channeled through an affective and a cognitive process. It was also reported that resistance is predicted by both the reflective and the nonreflective information processing styles, which are in turn predicted by a high versus a low fear arousal. Fear arousal level was shown to be moderated by gender and coping self-efficacy.

This research brings additional insight to the PMT in so far that it highlights the maladaptive coping response through resistance to persuasion in a pandemic context.

This paper aims to investigate the influence of cybersecurity awareness and compliance attitudes on the protective behaviours exhibited by employees. This study also aims to explore the complex correlation between the level of awareness about cybersecurity measures and attitudes towards compliance with these measures. Additionally, it looks at how these factors collectively impact employees’ behaviour to protect organisational assets and information.

This study uses a quantitative research methodology in which primary data are gathered using a survey questionnaire distributed to personnel employed at Vietnamese organisations. The data are analysed, and the validity of the measurement and structural equation model is assessed using a partial least squares–structural equation model approach after the collection of all the survey responses.

The provision of policies and security education, training and awareness programmes are strongly and positively associated with cybersecurity awareness. Moreover, cybersecurity awareness plays an important role in shaping attitudes and intentions towards information security policy compliance (ISPC). Attitude is positively associated with intention towards ISPC and employee protective behaviour. Finally, the intention towards ISPC is significant in shaping employee protective behaviour.

This study contributes to the understanding of the antecedents of cybersecurity in developing countries such as Vietnam. Furthermore, it provides a comprehensive framework for understanding intention and protective behaviour through cybersecurity awareness and compliance attitudes. By combining the theory of planned behaviour and protection motivation theory with institutional governance, this study extends previous research on the effects of these variables on employee protective behaviour.