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This study aims to empirically investigate solo travel behavior, comparing decision-making, destination choice, motivations, perceived experiences and constraints between the pre-pandemic and post-pandemic eras.

Using a mixed-methods approach, the study combines quantitative and qualitative data to enhance reliability and flexibility. An online survey attracted 250 respondents, providing demographic data and pandemic-related insights, complemented by eight in-depth interviews. Qualitative content analysis was used to extract key findings on motivations, constraints and destination choices.

The findings reveal that, pre-pandemic, independence and flexibility were key motivators for solo travel, with safety and budget as significant constraints. During the pandemic, half of the respondents continued solo travel, mainly within Europe, facing constraints related to destination choice and health concerns. Post-pandemic, solo travel interest resurged, emphasizing unchanged motivations but reduced concerns over companionship and planning. The study identifies a “traveling for revenge” trend post-pandemic, showcasing a desire to overcome constraints imposed during the pandemic.

The study contributes original insights into the nuanced changes in solo travel behavior due to the COVID-19 pandemic, offering a deeper understanding of solo travelers' evolving mindsets. It is one of the few studies to examine the pandemic's impact on solo traveling, providing short-term shifts in motivations and constraints with implications for the travel industry.

Trust plays a crucial role in overcoming uncertainty and reducing risks. Uncovering the trust mechanism in the sharing economy may enable sharing platforms to design more effective marketing strategies. However, existing studies have inconsistent conclusions on the trust mechanism in the sharing economy. Therefore, this study aims to investigate the antecedents and consequences of different dimensions of trust (trust in platform and trust in peers) in the sharing economy.

First, we conducted a meta-analysis of 57 related articles. We tested 13 antecedents of trust in platform (e.g. economic benefits, enjoyment, and information quality) and eight antecedents of trust in peers (e.g. offline service quality and providers’ reputation), as well as their consequences. Then, we conducted subgroup analyses to test the moderating effects of economic development level (Developed vs Developing), gender (Female-dominant vs Male-dominant), platform type (Accommodation vs Transportation), role type (Obtainers vs Providers), and uncertainty avoidance (Strong vs Weak).

The results confirm that all antecedents and consequences significantly affect trust in platform or peers to varying degrees. Moreover, trust in platform greatly enhances trust in peers. Besides, the results of the moderating effect analyses demonstrate the variability of antecedents and consequences of trust under different subgroups.

This paper provides a clear and holistic view of the trust mechanism in the sharing economy from an object-based trust perspective. The findings may offer insights into trust-building in the sharing economy.

This study aims to determine the antecedents that influence attitudes towards the use of environmentally friendly household appliance products and consumers' green purchase intention among consumers in Harare, Zimbabwe.

Data were collected from 329 consumers in Harare, Zimbabwe's commercial capital who were served from five using a structured questionnaire via an online web-based cross-sectional survey. Hypothesised relationships were tested through structural equation modelling with the aid of Smart PLS software.

Green product awareness, social influence, perceived benefit and attitude towards green appliances were found to have a significant positive effect on green purchase intention.

The study's findings may not be generalised to other contexts as sample data was only collected in Zimbabwe. Complementary cross-sectional research studies can be done in other parts of the world to enable cross-cultural comparisons and methodological validations.

The green appliance and energy saving practices are vastly growing, with many multinational appliance companies introducing green products within their product lines and adopting the concept of sustainability through modifications in production, design and consumption of household appliance products that encompass fewer harmful consequences on the environment in response to their concerns about the scarcity of natural resources, environmental well-being and the potential detriment of future generations.

Notwithstanding the limitations of the current study, the results have the potential to contribute to an improved understanding of influence attitudes towards the use of environmentally friendly household appliance products.

This study investigates the differential effectiveness of leadership styles within the German Federal Police Office, focusing on how these styles interact with employees' personal values to influence organizational identification (OI). Thus, we investigate the augmentation hypothesis and explore the moderating effects of personal values on leadership effectiveness regarding OI.

Utilizing a quantitative cross-sectional design, the study analyzes responses from 1,816 police employees via the Multifactor Leadership Questionnaire and Portraits Value Questionnaire. Hierarchical regressions are used to analyze the hypothesized associations.

The results indicate that transformational leadership significantly enhances OI more than transactional or laissez-faire leadership. Moderating effects of personal values reveal complex interactions: while transformational leadership consistently predicts higher OI, transactional leadership’s effectiveness varies according to the employees' values such as Conformity and Tradition enhancing OI, Universalism and Benevolence diminishing it. These findings suggest that leadership effectiveness in policing is contingent on aligning leadership style with the personal values of the employees.

This research contributes to the understanding of how personal values modulate the impact of leadership styles on organizational outcomes within police organizations. It underscores the necessity for police leaders to consider the value profiles of their employees to optimize OI and effectiveness. The study is among the first to systematically explore these dynamics within a law enforcement context, providing empirical evidence to inform targeted leadership development and policy-making in policing.

Student open feedback is an essential element to improve the teaching service. Comprehending the feedback collected daily may not be possible especially in a large classroom. There is needed an automated system that processes feedback and helps to recommend focused, precise points to the teacher stating the positives and negatives of a class. Also, the feedback texts are neither going to be grammatically correct nor going to consist only of English. Hence, an automated feedback processing system is essential that processes the mixed-language language text that provides crisp clear insights to the teachers, thus making effective student–teacher interaction.

This research is designed to analyse daily feedback from the students in grammarless English-Tamil mixed feedback and creates a dashboard that displays concise keywords regarding positive and negative aspects of the class. An ML-based system architecture is proposed for processing English-Tamil mixed grammarless feedback texts and validates the same with an experimental prototype and compares the results with other state-of-the-art models. This prototype classifies the text into different categories and provides the concise view with topic modelling techniques. This system is useful in progressive improvement of teaching learning process, subsequently leading to better teaching learning environment.

The proposed web-based architecture is validated with a prototype by comparing the results with other state-of-the-art models. The accuracy of the results is higher (>90%) in the proposed architecture than other models (<60%). The created teacher dashboard is highly recommendable and provides day-to-day recommendation for finetuning teaching and learning process. The web-based dashboard created for teachers enables them to interpret the student feedback with much ease due to the Machine learning algorithms used in implementing the web-based solution.

This system is designed to help the teachers to improve themselves in the teaching learning process with the feedback. The proposed system is a prototype that is initially tested with sample feedback texts obtained in sessions in postgraduate classrooms. The implementation of the prototype and analysis of teacher and student experience are presented as the immediate scope of this research work. This helps the teachers to get an overall view on the best teaching practices and what to improve. This work currently uses Bidirectional Encoder Representations from Transformers (BERT) uncased and in the increase of native language text the system may work with BERT multilingual.

This prototype will be implemented as a web-mobile based application. Students can submit their daily feedback through a mobile app, while teachers will access a dashboard that presents a concise overview generated by the proposed system architecture. The dashboard will also provide trend analysis, highlighting positive and negative aspects of the sessions. The system's effectiveness will be evaluated through a qualitative study, incorporating feedback from teachers and insights from students. This evaluation will help teachers gain a comprehensive understanding of the most effective teaching practices and areas needing improvement, thereby enhancing the teaching-learning process. The web-mobile application aims to Streamline the feedback process, making it easy for students to share their thoughts and for teachers to receive actionable insights. This study offers a clear and concise summary of student feedback and trend analysis from which the teachers can quickly identify patterns and make necessary adjustments to their teaching methods. Ultimately, this approach will foster a more responsive and effective educational environment, supporting continuous improvement and better student–teacher interactions. Further, the proposed system requires lesser technical knowledge and can be used by anyone.

A literature review has identified a critical need for a feedback processing system that functions at short intervals. Such a system is essential for providing teachers with concise, periodic summaries of students' open-ended feedback, which is vital for fostering continuous improvement in the teaching-learning process. The immediate processing of feedback, particularly when it contains English-mixed texts, is crucial for making timely adjustments that enhance both student performance and experience. By swiftly addressing concerns and reinforcing positive feedback, the system will improve student–teacher interactions, provide meaningful insights that contribute to progressive educational growth. This will help implement a feedback system that operates in these short intervals and allows for real-time monitoring and response to students' needs and experiences. Additionally, by highlighting areas of success, teachers can build on effective strategies and practices.

This research paper proposes a system architecture PSFAS: Progressive Student Feedback Analysis System with Multi Level Classification and Clustering that enables effective interaction between the student and the teacher with the findings from feedback and presenting an experimental prototype that can be incorporated into the regular teaching learning process, whether online or offline. It has been found from the literature review, that feedback processing is mostly done in the English language. This work proposes a system architecture that gives higher accuracy than other state-of-the art models for feedback texts having English-mix grammarless sentences.

The purpose of this paper is to overview the current state of affairs of the Indian heritage treasures, which are being identified, restored, preserved and promoted by various organizations at national and international levels with an emphasis on its documentation aspect. Lack of information about the heritage sites, structures and its significance, especially unprotected and unidentified, leads to its permanent loss. One of the prominent measures to safeguard from such irrevocable cultural deprivation is its documentation. Further, the study aims to examine the significant challenges associated with identifying unrevealed heritage assets of the country in the context of its preservation, documentation and promotion. As a suggestive measure, the study aims to propose the need for developing a comprehensive cultural heritage register assisted with technological aids focusing on community participation in taking stock of the heritage items they possess and enable them to effectively document.

The present study extracts the cultural heritage data available with the UNESCO belongs to Indian heritage assets inscribed in its World Heritage portal. The collected data has been analyzed and interpreted to overview the country's recognition at the global level. The data collected from the official portal is further explored and customized to have a lucid account. The details about the organizations and institutions working on heritage conservation and preservation activities in India are also collected. A review of published literature on the related areas has also been performed to identify the issues and challenges associated with the documentation of heritage assets to support this study. The study also included the researcher’s experience in working with cultural heritage documentation.

India holds a substantial quantity of cultural as well as natural heritage items. However, an exhaustive effort to document them at the national level is not being accomplished to its full potential. Many of the assets, inheritances or sites of cultural importance have not been fully identified, preserved or documented; hence, it is unrecalled forever once lost. Some organizations and individuals working on cultural heritage lack clarity in its function and do not follow any common standards in its documentation. For any conservation activity, documentation is prime, and the local community's support is also essential. Means of international collaboration for managing and promoting the heritage are required to be encouraged. Findings of the study demand the need for utilizing digital technologies to assist the documentation process. It emphasizes the requirement of having a web-based single window online gateway where an individual or community can dispense the knowledge and resources they possess hence contributing to heritage conservation, preservation and sustainability.

The study limited to Indian scenario and the data on the heritage sites are collected from UNESCO's World Heritage portal. Only the documentation and promotional aspects of the cultural heritage are discussed. There are many lesser-known and unprotected cultural heritage in different parts of the country with artistic value. The unique characteristics that have not been recorded anywhere are to be documented systematically to reduce the frequency and severity of losses. The implication of the study highlights the present scenario of cultural heritage documentation in India and the need for a comprehensive heritage information gateway supported with a register facility to precisely document and retrieve.

Aspects of culture which are inherited from the past to the present are to be preserved for future generations. Digital archives of cultural heritage and the use of digital tools to document them are effective mechanisms to protect and store the data on endangered heritage items. For any such conservation effort, documentation is its first step. Developing and facilitating access to an exclusive database of cultural heritage at risk boast its sustainability and can be enriched by the involvement of local communities. Public access to such a database would greatly support administrators, tourist departments, culture departments, development administration and conservation activists to gather the details of unprotected heritage items of the country, its present condition, risk of damage, etc. which further helps in its preservation, conservation, sustainability and promotion in a constructive manner.

To the authors' best knowledge, no such single and comprehensive mechanism in the country allow the individuals to contribute to the inventory list holding information about the identified, unprotected and unidentified heritage assets which are having a risk of damage, threat, decay, vulnerable, neglect, lack of use or inappropriate maintenance and development. Developing such a system with technological and data infrastructure helps to pool all the cultural heritage resources under one umbrella. It imparts the value and significance of protecting and promoting heritage inheritances and a safe haven of them from the risk of its chronic loss. The system can also support all the activities related to heritage protection and bring the local community to timely support and initiate such heritage conservation activities.

This systematic literature review aims to identify the pattern of data mining (DM) research by looking at the levels and aspects of education.

This paper reviews 113 conference and research papers from well-known publishers of educational data mining (EDM) and learning analytics-related research using a recognized literature review in computer science by Carrera-Rivera et al. (2022a). Two major stages, planning and conducting the review, were used. The databases of Elsevier, Springer, IEEE, SAI, Hindawi, MDPI, Wiley, Emerald and Sage were searched to retrieve EDM papers from the period 2017 to 2023. The papers retrieved were then filtered based on the application of DM to the three educational levels – basic, pre-tertiary and tertiary education.

EDM is concentrated on higher education. Basic education is not given the needed attention in EDM. This does not enhance inclusivity and equity. Learner performance is given much attention. Resource availability and teaching and learning are not given the needed attention.

This review is limited to only EDM. Literature from the year 2017 to 2023 is covered. Other aspects of DM and other relevant literature published in EDM outside the research period are not considered.

As the current trend of EDM shows an increase in zeal, future research in EDM should concentrate on the lower levels of education to identify the challenges of basic education which serves as the core of education. This will enable addressing the challenges of education at an early stage and facilitate getting a quality education at all levels of education. Appropriate EDM techniques for mining the data at this level should be the focus of the research. Specifically, techniques that can cater for the variation in learner abilities and the appropriate identification of learner needs should be considered.

Content sequencing is necessary in facilitating an easy understanding of concepts. Curriculum design from basic to higher education dwells much on this. Identifying the challenge of learning at the early stages will facilitate efficient learning. At the basic level of learning, data on learning should be collected by educational institutions just as it is done at the tertiary level. This will enable EDM to accurately identify the challenges and appropriate solutions to educational problems. Resource availability is a catalyst for effective teaching and learning. The attributes of a learner will enable knowing the true nature of the learner to determine the prospects of the learner.

This research has not been published in any journal. The information presented is the original knowledge of the authors. However, a pre-print of the work is in Research Square.