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This study aims to explore blockchain potential for digital marketing (BlkChn-Mk-KAP) by developing and validating a measurement model for assessing the constructs of knowledge, attitude and practice (KAP) related to blockchain technology in digital marketing.

A four-study process was used. The first study reviewed the literature to develop a pool of possible measurement items. Using exploratory factor analysis and reliability assessments, Study 2 (n = 162) investigated the dimensionality of the items developed in Study 1. The factorial structure from Study 2 was validated in Study 3 (n = 204), and the measurement model invariance was assessed using covariance-based structural equation modelling (CB-SEM). Finally, in Study 4 (n = 203), the predictive validity of the BlkChn-Mk-KAP was tested using a CB-SEM approach, testing its constructs correlations with the perceived usefulness of blockchain for digital marketing.

The findings indicate that the BlkChn-Mk-KAP measurement model comprises three-dimensional multi-item scales: knowledge, attitude and practice.

This study introduces a promising BlkChn-Mk-KAP model to examine blockchain’s role in digital marketing. The authors acknowledge the sampling limitation in this research. To enhance the generalisability of the findings, future research should expand to different groups, including generation, gender and age. In addition, further exploration of the explicit links between blockchain knowledge, attitudes and subsequent digital marketing performance is warranted.

Educating employees about blockchain technology’s unique features can shape favourable attitudes and stimulate the utilisation of blockchain-enabled technologies in digital marketing practice. BlkChn-Mk-KAP can offer a reliable and valid instrument to benchmark marketers’ KAP of blockchain-powered digital marketing as they implement blockchain technology to gain a competitive advantage.

This study helps to adopt sustainable practices ensuring the wellbeing of the key stakeholders.

This research introduces the first validated conceptualisation and measurement model, BlkChn-Mk-KAP, to evaluate blockchain KAPs among digital marketing professionals.

This study aims to examine the unique and interaction effects of farmers’ pesticide safety knowledge and their past pesticide-related health problems experienced in the adoption of protective pesticide behaviors. The study further aims to explore whether attitude toward pesticide use mediate the relationship between pesticide safety knowledge and protective behaviors.

Data were collected from 385 Pakistani fruit and vegetable farmers using a cross-sectional survey design and were analyzed using Partial least squares structural equation modeling (PLS-SEM).

The empirical analysis revealed that pesticide safety knowledge is positively associated with protective behaviors and farmers’ attitude toward pesticide use partially mediates this relationship. The findings further show that past health problems positively influence the adoption of protective pesticide behaviors, which is amplified when pesticide safety knowledge is high.

This study findings have significant implications for policy interventions and agricultural extension programs aimed at promoting safer pesticide use.

This research contributes to the previous literature by presenting an integrative framework of the knowledge-attitude-practice model and protection motivation theory to explore the influence of farmers’ pesticide safety knowledge, past pesticide-related health experiences and attitude toward pesticide use on their adoption of protective pesticide behaviors.

This study aims to investigate climate change education (CCE), including global trends and specific implementations in China, as well as the worldwide development of CCE and its key components, including knowledge, attitudes and behavioural patterns.

The authors combined bibliometric analyses and a targeted questionnaire based on the knowledge–attitude–practise (KAP) model to investigate CCE. Initial global trends identified through VOSviewer guided the study survey, focusing on Chinese university students and educators’ knowledge, attitudes and practices.

The high level of concern about climate change among Chinese students and educators and their actual understanding of this issue often results in overconfident self-assessment. Academic specialisation significantly influences the level of climate change concern, with humanities and social sciences students and educators demonstrating higher concern than their counterparts in the natural sciences. The study highlights the essential role of effective climate policy dissemination in shaping informed attitudes and behaviours, particularly in a government-driven policy landscape like China’s. Climate policy awareness, positive emotions, self-efficacy, collective efficacy and personal experiences all positively impact Chinese youths’ climate change engagement. CCE is primarily delivered uniformly across China through policy instructions and specific courses, yet more engaging, interactive and localised educational approaches to CCE that are tailored to regional and cultural contexts are needed.

Combining bibliometric analysis with survey data, this research uniquely highlights the significance of the political context in China, emphasising the critical role of policy dissemination in shaping climate change perceptions and actions, addressing regional differences and the local context. Based on the KAP model, the study proposed a new model for implementing CCE in collectivist societies like China.

The purpose of this study is to scrutinize the influence of individual learning styles on the effectiveness of augmented reality (AR)-based learning in structural engineering. There has been a lack of research examining the correlation between learning efficiency and learning style, particularly in the context of quantitatively assessing the efficacy of AR in structural engineering education.

Using Kolb’s experiential learning theory (ELT), a model that emphasizes learning through experience, students from the construction management department are assigned four learning styles (converging, assimilating, diverging and accommodating). Performance data were gathered, appraised, and compared through the three dimensions from the Knowledge, Attitude and Practices (KAP) survey model across four categories of Kolb’s learning styles in both text-graph (TG)-based and AR-based learning settings.

The findings indicate that AR-based materials positively impact structural engineering education by enhancing overall learning performance more than TG-based materials. It is also found that the learning style has a profound influence on learning effectiveness, with AR technology markedly improving the information retrieval processes, particularly for converging and assimilating learners, then diverging learners, with a less significant impact on accommodating learners.

These results corroborate prior research analyzing learners' outcomes with hypermedia and informational learning systems. It was found that learners with an “abstract” approach (convergers and assimilators) outperform those with a “concrete” approach (divergers and accommodators). This research emphasizes the importance of considering learning styles before integrating technologies into civil engineering education, thereby assisting software developers and educational institutions in creating more effective teaching materials tailored to specific learning styles.

We seek to contribute to the literature by comparing and analyzing the relationship between Australian and Taiwanese students regarding environmental value attitude, action intention and green marketing intention. Specifically, by comparing the green marketing intention of hospitality and tourism (H&T) students in the East with that in the West.

A well-designed curriculum examines student thinking and behavior (learn). This study compares and analyzes the value and attitude and the application of big data to green marketing among Taiwanese and Australian university students using the stimulus-organism-response (S-O-R) model. Structural equation modeling (SEM) was used to test the hypotheses in a sample of 633 H&T students in Taiwan (389) and Australia (244).

This study also shows how the national differences between Australia and Taiwan have interference effects on the relationship between value attitudes and action intentions and between action intentions and the green marketing intention. We also combined the application of big data and related variables and estimated the mediating effect of related variables to evaluate the impact on action intentions and green marketing of big data applications.

There are significant differences in the sustainable behavior and intentions of H&T higher education students that reflect the educational differences between the East and the West. These different results may be due to a lack of natural resources and the relatively smaller size of Taiwan. With the strengthening of environmental action intention (AI) and green marketing intention (GMI), Taiwanese hospitality and management (H&M) students' sense of crisis increases, and their performance in GMI is slightly higher than that in Australia.

These findings indicate that it is necessary to consider students' ecological concepts, environmental knowledge, environmental value attitude and environmental action intention to improve their intentions to engage in green marketing under the stimulus-organism-response (S-O-R) framework. We also found that environmental knowledge has a mediating effect on the relationship between ecological concepts and environmental value attitude.

Based on the knowledge-attitude-behavior model, this study is aimed at investigating the influential mechanism underlying the purchase of green clothing by dividing this clothing category into green home-in wear and home-out wear within the context of green consumption. The mediating effects of perceived greenwashing (PG), perceived value (PV) and expected moral benefit (EMB) and the moderating effect of green clothing type (GCT) were examined.

The data for this study were collected from 366 valid samples through a between-subject design survey administered in China. Moderation analysis and mediation analysis using SPSS/PROCESS macro were applied to test the proposed hypotheses.

The results indicate that consumers' level of environmental knowledge (EKL) not only has a direct effect on purchase intention (PI) but also has an indirect effect through perceived value and expected moral benefit. However, perceived greenwashing did not play a mediating role in this relationship.

The study's findings show a moderating effect of green clothing type (green home-in wear vs green home-out wear). That is, compared to green home-out wear, the relationship between expected moral benefit and perceived greenwashing for green home-in wear had a weaker negative effect on purchase intentions.

This study aims to analyse a new model to assess the sustainable behaviours, sustainable attitudes and sustainable knowledge on sport practitioners.

This paper employs a scale of 44 items divided into three different dimensions to analyse the knowledge, attitudes and behaviours towards sustainable development on 227 sport participants.

Through this study the authors have been able to obtain a reliable scale that allows us to analyse and the knowledge, attitudes and sustainable behaviours of physical and sports education practitioners.

Both psychometric properties of the initial scale and the differences between studies contexts may affect the results of the present analysis. Therefore, new studies are needed in order to analyse how sport physical activities influence sustainable behaviours among physical activity and sport practitioners.

In this work the authors present a valid and reliable tool for the study of the environmental knowledge, attitudes and behaviours of physical activity and sport practitioners.

Regarding the importance of sport in relation to sustainable development, this work is the first to adapt a scale to the context of practitioners of physical activity and sport in order to improve the understanding of how physical activity and sport affect sustainable behaviours, serving as a starting point for future research in sustainable development sports field.

The purpose of this study is to explore informetrics researchers' use of social media for academic activities, their attitudes to the applicability of altmetrics in research evaluation, the factors influencing their attitudes, and the main opportunities and weaknesses of using altmetrics.

A survey using a questionnaire was conducted with researchers who participated in the 16th International Conference on Scientometrics and Informetrics ISSI 2017 and a sample of 125 respondents was obtained.

Progressively more researchers are using social media for different types of academic activities. The study found that many factors affect informetrics researchers' attitudes in different application scenarios with respect to research evaluation. Researchers who have studied altmetrics and who began using social media platforms recently or frequently have more positive attitudes. Academic users and social users have statistically significantly disparate attitudes toward altmetrics in different disciplines and different application scenarios.

Our study only focused on 125 informetrics researchers, who participated in ISSI 2017. We mainly used the questionnaire method, but did not conduct in-depth interviews with the researcher's views.

Informetrics researchers are participants in social media and major researchers of altmetrics. Previous research has examined their use of social media, and this study combines this use of social media with their attitudes to altmetrics to explore the value of altmetrics from a particular perspective. The paper also provides suggestions for the application of altmetrics in research evaluation.

The study examines the interrelationships of food safety knowledge, attitudes and practices, and the moderating effect of food safety training on the said interrelationships.

Predictive-causal was the primary research design used and partial least squares – structural equation modelling (PLS-SEM) was the statistical technique applied.

Results showed that food safety knowledge significantly and positively influences attitudes towards food safety. It was further revealed that attitudes toward food safety and food safety practices are also significantly and positively related. Moderation analysis indicated that food safety training moderates the significant and positive relationship between attitudes towards food safety and food safety practices.

The present study has limitations. First, the unit of analysis is focused on food handlers in fast-food restaurants in Angeles City, Philippines. Other researchers may come up with similar studies on a larger scale – provincial, regional or national. Second, only food safety training as a construct was used as a moderator on the hypothesized relationships of the structural model. Other studies may expand and explore other moderating variables and/or mediating constructs that may affect the said hypothesized relationships.

Based on the present study, food safety knowledge was found to have a huge significant and direct influence on attitudes of fast-food restaurant food handlers towards food safety, as evidenced by the computed effect size. In short, knowledge on food safety is an integral factor when it comes to enhancing food safety attitudes of fast-food restaurant food handlers. When fast-food restaurant food handlers are well-equipped with the right food safety knowledge, they become more aware of the different food safety protocols and other pertinent food safety guidelines and procedures which can lead to favorable food safety attitudes.

The present study highlighted the moderating effect of food safety training on the relationship between attitudes toward food safety and food safety practices. Therefore, regular attendance of food handlers to food safety training is crucial in developing acceptable attitudes toward food safety, which in turn, favorably affect their food safety practices in fast-food restaurants.

The current study utilized PLS-SEM, a second-generation statistical technique, to measure the hypothesized relationships as compared to correlation tests performed by prior studies on the interrelationships of food safety knowledge, attitudes toward food safety and food safety practices. PLS-SEM is suitable for this type of research design – predictive-causal – since this study involves model development and prediction. Furthermore, it employed moderation analysis to measure the moderating effects of food safety training on the identified hypothesized relationships of the structural model. Hence, methodologically, the present study employed new ways and insights in measuring the interrelationships of food safety knowledge, attitudes and practices.

Questionnaire studies of knowledge, attitude and practice (KAP) are effective research in the field of health, which have many shortcomings. The purpose of this research is to propose an automatic questionnaire-free method based on deep learning techniques to address the shortcomings of common methods. Next, the aim of this research is to use the proposed method with public comments on Twitter to get the gaps in KAP of people regarding COVID-19.

In this paper, two models are proposed to achieve the mentioned purposes, the first one for attitude and the other for people’s knowledge and practice. First, the authors collect some tweets from Twitter and label them. After that, the authors preprocess the collected textual data. Then, the text representation vector for each tweet is extracted using BERT-BiGRU or XLNet-GRU. Finally, for the knowledge and practice problem, a multi-label classifier with 16 classes representing health guidelines is proposed. Also, for the attitude problem, a multi-class classifier with three classes (positive, negative and neutral) is proposed.

Labeling quality has a direct relationship with the performance of the final model, the authors calculated the inter-rater reliability using the Krippendorf alpha coefficient, which shows the reliability of the assessment in both problems. In the problem of knowledge and practice, 87% and in the problem of people’s attitude, 95% agreement was reached. The high agreement obtained indicates the reliability of the dataset and warrants the assessment. The proposed models in both problems were evaluated with some metrics, which shows that both proposed models perform better than the common methods. Our analyses for KAP are more efficient than questionnaire methods. Our method has solved many shortcomings of questionnaires, the most important of which is increasing the speed of evaluation, increasing the studied population and receiving reliable opinions to get accurate results.

Our research is based on social network datasets. This data cannot provide the possibility to discover the public information of users definitively. Addressing this limitation can have a lot of complexity and little certainty, so in this research, the authors presented our final analysis independent of the public information of users.

Combining recurrent neural networks with methods based on the attention mechanism improves the performance of the model and solves the need for large training data. Also, using these methods is effective in the process of improving the implementation of KAP research and eliminating its shortcomings. These results can be used in other text processing tasks and cause their improvement. The results of the analysis on the attitude, practice and knowledge of people regarding the health guidelines lead to the effective planning and implementation of health decisions and interventions and required training by health institutions. The results of this research show the effective relationship between attitude, practice and knowledge. People are better at following health guidelines than being aware of COVID-19. Despite many tensions during the epidemic, most people still discuss the issue with a positive attitude.

To the best of our knowledge, so far, no text processing-based method has been proposed to perform KAP research. Also, our method benefits from the most valuable data of today’s era (i.e. social networks), which is the expression of people’s experiences, facts and free opinions. Therefore, our final analysis provides more realistic results.