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Proponents of micro-credentials envision them as vehicles for upskilling or re-skilling individuals. The study examines how integrating micro-credentials in the higher education ecosystem enhances employability. It aims to offer insights from the perspective of stakeholders who may benefit from these credentials at an institutional or individual level.

Online in-depth interviews are conducted with 65 participants from India, Nigeria, the United Arab Emirates and the United Kingdom to explore how micro-credentials can be a valuable addition to the higher education ecosystem. A multi-stakeholder approach is adopted to collect data.

The analysis highlights two possible methods of integrating micro-credentials into the higher education ecosystem. First, micro-credentials-driven courses can be offered using a blended approach that provides a flexible learning path. Second, there is also the possibility of wide-scale integration of micro-credentials as an outcome of standalone online programs. However, the effectiveness of such programs is driven by enablers like student profiles, standardization and the dynamics of the labor market. Finally, the study stipulates that micro-credentials can enhance employability.

The study's findings suggest that, for successful integration of micro-credentials, an operational understanding of micro-credentials, their enablers and strategic deliberation are critical in higher education. Institutions must identify the determinants, address technological limitations and select a suitable delivery mode to accelerate integration. However, micro-credentials can augment employability, considering the increasing emphasis on lifelong learning. An overview of the findings is presented through a comprehensive framework.

This paper aims to design an active shock absorber scheme for use in conjunction with a passive shock absorber to suppress the horizontal vibration of elevator cars in a smaller range and shorter time. The developed active shock absorber will also improve the safety and comfort of passengers driving in ultra-high-speed elevators.

A six-degree of freedom dynamic model is established according to the position and condition of the car. Then the active shock absorber and disturbance compensation-based adaptive control scheme are designed and simulated in MATLAB/Simulink. The results are analysed and compared with the traditional shock absorber.

The results show that, compared with traditional spring-based passive damping systems, the designed active shock absorber can reduce vibration displacement by 60%, peak acceleration by 50% and oscillation time by 2/3 and is more robust to different spring stiffness, damping coefficient and load.

The developed active shock absorber and its control algorithm can significantly reduce vibration amplitude and converged time. It can also adjust the damping strength according to the actual load of the elevator car, which is more suitable for high-speed elevators.

Current school leadership research has primarily utilized quantitative methods to explore the relationship between leadership and teacher learning. However, there is a notable gap in understanding how principals facilitate professional learning, especially in centralized educational settings. This study aims to address this gap by examining the role of school leadership in enhancing teacher professional learning within a highly centralized education system.

This qualitative case study delves into the lived experiences of 15 teachers and eight school leaders in eight primary schools in Mashhad, Iran. Through semistructured interviews, researchers employed open and axial coding to systematically explore and categorize qualitative data. The study focuses on understanding the role of principal leadership in facilitating teacher professional learning by connecting themes and sub-themes across transcripts.

Effective principals worked on the cultivation of a culture that champions perpetual personal growth and development, the nurturing of a collaborative learning community, and the provision of essential resources and support. Findings showed the pivotal role of principals in promoting teachers' self-development, facilitating idea exchange and acknowledging their efforts. Principals appeared as key to encouraging information sharing, fostering collective learning, promoting professional development, overseeing teaching practices and ensuring the availability of resources to cultivate a supportive climate in a centralized education context.

We concluded that in centralized education, leadership practices for promoting teacher learning share similarities and differences with decentralized settings. The findings offer guidance for principals in centralized systems, supporting them in facilitating teacher professional learning in their schools.

This study aims to determine the pedagogical and socio-emotional impacts of school closures caused by the COVID-19 pandemic in Guinea.

A descriptive, survey-based methodology was used to collect quantitative and qualitative data directly from parents and caregivers. Between February 24 and March 13, 2022, data was gathered from a study population comprising 2,955 adults residing in five communes and five prefectures of Guinea.

Half of all respondents stated that school closures had no particular impact on children in their household, and 42% stated that no intentional pedagogical activities took place during school closures. Approximately 15% of respondents stated that children experienced boredom, loneliness, sadness, depression, stress and anxiety during the school closures.

The study underscores the significance of school closure readiness and interactive learning while revealing limited emotional impact on children. The findings, while specific to Guinea, provide a foundational understanding, highlighting the complexity of pandemic effects on education and the need for adaptive strategies in vulnerable regions.

Following the increasing trend of artificial intelligence (AI) research in hospitality literature, this critical reflection paper aims to identify AI-assisted mindfulness as a critical yet under-investigated issue and to contribute feasible directions for future research.

The authors first conceptualize a framework explaining the effects of mindfulness design in AI interventions on improving human mindfulness. The authors then identify opportunities for interventions in AI-assisted mindfulness for the tourism, hospitality and events industries. Finally, the authors propose potential themes for AI-assisted mindfulness research.

This study contributes three major conceptual works. First, we conceptualize a framework of AI-assisted mindfulness, showcasing that the scope of AI-assisted mindfulness spans from AI interventions to state mindfulness and then to trait mindfulness. Second, the authors offer two approaches to strategic thinking, one from mindfulness (i.e. mindfulness-focused niche markets and activities) and one from AI applications (i.e. AI-facilitated devices and platforms), to identify opportunities for AI-assisted mindfulness interventions. Third, for both management- and marketing-oriented AI-assisted mindfulness research, the authors propose 18 themes.

This critical reflection paper offers directions for future knowledge creation in AI-assisted mindfulness in the tourism, hospitality and events industries.

To the best of the authors’ knowledge, this critical reflection paper serves as the first in hospitality and tourism literature to systematically propose the research issue of AI-assisted mindfulness, offering directions and themes for future research.

Today, with the increasing involvement of the environment and human beings business units, paying attention to fulfilling social responsibility obligations while making a profit has become increasingly necessary for achieving sustainable development goals. Attention to profit by organizations should not be without regard to their social and environmental performance. Social responsibility accounting (SRA) is an approach that can pay more attention to the social and environmental performance of companies, but it has many barriers. Therefore, the purpose of this study is to identify barriers to SRA implementation and provide strategies to overcome these barriers.

In this study, the authors identify barriers to social responsibility accounting implementation and provide strategies to overcome these barriers. By literature review, 12 barriers and seven strategies were identified and approved using the opinions of six academic experts. Interpretive structural modeling (ISM) has been used to identify significant barriers and find textual relationships between them. The fuzzy technique for order performance by similarity to ideal solution (TOPSIS) method has been used to identify and rank strategies for overcoming these barriers. This study was undertaken in Iran (an emerging market). The data has been gathered from 18 experts selected using purposive sampling and included CEOs of the organization, senior accountants and active researchers well familiar with the field of social responsibility accounting.

Based on the results of this study, the cultural differences barrier was introduced as the primary and underlying barrier of the social responsibility accounting barriers model. At the next level, barriers such as “lack of public awareness of the importance of social responsibility accounting, lack of social responsibility accounting implementation regulations and organization size” are significant barriers to social responsibility accounting implementation. Removing these barriers will help remove other barriers in this direction. In addition, the results of the TOPSIS method showed that “mandatory regulations, the introduction of guidelines and social responsibility accounting standards,” “regulatory developments and government incentive schemes to implement social responsibility accounting,” as well as “increasing public awareness of the benefits of social responsibility accounting” are some of the essential social responsibility accounting implementation strategies.

The findings of the study have implications for both professional accounting bodies for developing the necessary standards and for policymakers for adopting policies that facilitate the implementation of social responsibility accounting to achieve sustainability.

This paper creates a new perspective on the practical implementation of social responsibility accounting, closely related to improving environmental performance and increasing social welfare through improving sustainability.

Experts believe that the strategies mentioned above will be very effective and helpful in removing the barriers of the lower level of the model. To the best of the authors’ knowledge, for the first time, this study develops a model of social responsibility accounting barriers and ranks the most critical implementation strategies.

Sources highlight that lack of systematic labour training components results in low performance and productivity of labour, which leads the construction industry of many countries to face various challenges. This study aims to quantify the variations in the performance and productivity levels of labour in building construction projects through the applications of effective work-based training components.

A comprehensive literature review and a series of experts’ discussions with action-oriented communication approaches were conducted to develop a set of practices related to labour training, performance assessment and productivity measurements within a framework. The developed practices were applied to around 100 labourers working on nine building construction projects through a construction supervisory training programme.

The study presents the detailed patterns of the significant changes in labour performance and productivity levels. The majority of trained labourers have grown to perform the work process with some relevant theoretical and operational knowledge and skills. The overall results spotlight the significant behavioural changes that can be observed in workforce operations by improving labour performance, which resulted in implementing effective labour-rewarding practices within a framework.

Although the study findings were limited to the Sri Lankan context, the proposed practices can be applied to the industry practices of the construction sector of other developing countries and the other developing industries in similar ways/scenarios.

The study outcomes contribute to uplifting the work qualities of labourers with life-long learning opportunities and unlocking the potential barriers for expanding the local labour supply while controlling the excessive inclination of the local firms towards foreign labour. This paper describes further implications and future scopes of the study elaborately.

The study provides generalised mechanisms and practices that transform the labour characteristics and add new attributes for strengthening the values of construction supervision practices to obtain well-improved work outputs. The study outcomes reinforce the chain relationships among the training elements, labour performance and productivity levels, leading to upgrading current planning and operational management practices, especially adding constructive mechanisms in resource levelling and productivity benchmarking practices.

The need to enhance student support is evident in higher education (HE) curricula. In addition to the complications created by the COVID-19 pandemic, the current strategies used in academia are criticised for their lack of appropriate student support in HE. The study focused on the themes under Section 4 of the National Student Survey (NSS): availability to contact tutors, receiving good advice and guidance and availability of good advice. The study aimed to provide recommendations for enhancing academic support by developing drivers that need implementation during course delivery.

A documental analysis and a qualitative survey were adopted for this study. A documental analysis of 334 mid-module reviews (MMRs) from levels three to six students in the built environment (BE) discipline. Critical themes identified from the MMRs were fed forward in developing a questionnaire for academics. A sample of 23 academics, including a Head of school, a Principal lecturer, Subject leads and Lecturers, participated in the questionnaire survey. Content analysis is adopted through questionnaire data to develop drivers to enhance academic support in BE. These drivers are then modelled by interpretive structural modelling (ISM) to identify their correlation to NSS Section 4 themes. A level partition analysis establishes how influential they are in enhancing academic support.

The study identified nine drivers, where two drivers were categorised as fundamental, two as significant, four as important, and one insignificant in enhancing academic support in HE. Module leaders’/tutors’ improving awareness and detailing how academic support is provided were identified as fundamental. Differentiating roles in giving advice and the importance of one-to-one meetings were identified as significant. A level partitioning diagram was developed from the nine drivers to illustrate how these drivers need to be implemented to promote the best practices in academic support in HE.

The identified drivers and their categories can be used to set prioritised guidelines for academics and other educational institutions to improve students’ overall satisfaction.

Novelty from the study will be the developed drivers and the level partitioning diagram to assist academics and academic institutions in successfully integrating academic support into HE curricula.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.

This study aims to address the existing knowledge gap by investigating teachers’ adoption of ChatGPT for educational purposes. The study specifically focuses on identifying the factors that motivate and inhibit teachers in adoption of ChatGPT in higher education institutions (HEIs).

This research has used interpretative phenomenological analysis – a qualitative approach. Through in-depth interviews among the teachers, data was collected to identify the motivating and inhibiting factors that impacted teachers’ willingness to adopt ChatGPT. The data was collected from 48 teachers working across HEIs of Uttarakhand region in India.

The analysis revealed seven themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purposes. These include time factor, tool for competitive edge, learning enhancement tool for students, research facilitator, benefits in educational settings, troubleshooter and easy to use. On the other hand, inhibiting factors comprise five themes, which include technical difficulties, limited features for educational and research purposes, tool for handicapping innovation and creativity, lack of personal touch and ethical considerations.

The findings will be valuable for HEIs in establishing policies that promote the appropriate and effective use of ChatGPT. Moreover, the study provides recommendations to ChatGPT solution providers for improving ChatGPT services for effective adoption of ChatGPT among teachers and implementation at HEIs. Further, it contributes to the body of literature by filling a knowledge gap about teacher adoption of ChatGPT in the HEIs. Through qualitative research, the study has pinpointed specific motivating and inhibiting factors that affect teacher adoption of ChatGPT.

Unlike previous studies that primarily explored the potential advantages and drawbacks of ChatGPT in education, this research study delves deeper into the topic. It makes a substantial contribution to our understanding of ChatGPT adoption among teachers by identifying distinct factors that either motivate or inhibit teachers from adopting ChatGPT for job related purposes. The study provides novel insights that were previously mislaid, thereby introducing a fresh perspective to the existing literature