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This study aims to investigate the relative impact of firm-created (FC) and user-generated (UG) social media marketing communication on fashionwear customers' purchase intention (CPI) in Sri Lanka. The primary objective is to identify the influence of social media marketing on the purchasing intention (PI) of customers in the fashionwear industry in Sri Lanka.

A standardized online survey was conducted, generating 312 datasets for analysis.

The empirical findings reveal that both firm-produced and UG social media fashionwear marketing communication has a significant influence on CPI. However, firm-produced social media fashionwear brands demonstrate a higher impact on CPI.

This study highlights the importance of social media marketing communication in shaping customers’ PI in the fashionwear industry in Sri Lanka. Both FC and UG content on social media platforms play a crucial role in influencing customers' intention to purchase fashionwear products. However, firm-produced social media fashionwear brands exert a stronger impact on CPI. These findings emphasize the need for marketers to incorporate effective social media strategies, including both FC and UG content, to enhance customer engagement and drive purchase decisions in the fashion-wear industry.

This paper describes an exploratory, international research collaboration that seeks to gain a deeper understanding of the development and experiences of peer leaders in higher education across different international contexts, namely the USA, Canada (CAN), Australasia (Australia and New Zealand) (ANZ), the United Kingdom (UK) and South Africa (SA).

Data are summarized and compared across each of the participating countries, providing a more global context and depth of perspective on peer leadership (PL) in higher education than is currently available in the literature.

The findings highlight some apparent differences between countries in relation to student engagement in peer leader roles and the ways in which PL is supported by higher education institutions, as well as some similarities across the different international contexts, particularly in the way peer leaders view the benefits of their involvement in PL.

These insights provide a valuable addition to the literature on PL and practical information to higher education institutions for supporting student leadership development and involvement.

The aim of this paper is to generate a streamlined, transparent and effective instrument to fairly measure the contribution made by each student to a group project within a higher education context. The primary aim is to moderate the grades of underperforming students at the end of the project. There is a secondary benefit in alerting underperforming students to raise their contribution mid-task or face a potentially reduced grade at the final stage.

The development of this multi-dimensional instrument is guided by findings from previous research. The quest is to minimise the instructor's administrative work load in applying a moderation-only instrument that is open-source and available at no cost. Based on the literature, the survey instrument seeks to apply a peer-based, equitable and transparent evaluation of each member's contribution to a group task. The survey is applied at mid-task and again at end-task in order to afford underperformers the opportunity to address contribution deficits during the final phase of the project.

The instrument, called TANDEM©, offers a transparent, streamlined, equitable, confidential and practical measure of each student's contribution to a graded group task. Students whose end-task contribution falls below the group average rating receive a proportional reduction in their personal grade. Additionally, the end-task moderation instrument captures a single-item holistic measure of relative contribution that may, in the future, serve as a surrogate for the multi-dimensional measures currently in place.

TANDEM© was developed with group sizes of four or five members in mind. There is no evidence to support its application to three-person groups. Moreover, the application was applied only amongst under-graduate students. It is yet to be applied across post-graduate groups and within online learning environments. Future research into diverse cultural settings would serve to advance understanding of how moderation is perceived across borders.

Several existing group grade moderation methods propose complex algorithms that are “black box” solutions from a student's perspective. In establishing a fair, streamlined, confidential and transparent process for peer-rated moderation, TANDEM© deploys a concise instrument with a relatively small administrative load. TANDEM © may be applied to all groups or can selectively be applied to groups that report moderate, strong or extreme levels of conflict.

Students will appreciate the opportunity to rate peer contributions to group projects. This will dissipate the negative social sentiment that may arise when fellow students benefit from the work of others. Those students seeking conflict resolution within the group will value the transparent and equitable moderation of grades as well as the positive social implications that follow.

This research forms part of an ongoing quest to present a moderation instrument that fairly identifies student contribution to a group project. Whilst the solution proposed is one of many existing alternatives, its focus is on a practical moderation-only instrument that can immediately be applied to a course or major. The benefits lie in the ease of application and minimal administrative workload. This constitutes an original contribution to the individual (course or major) coordinator who seeks to apply a moderation-only instrument without having to commit to an extensive, broad-based group optimisation programme.

This study aims to examine the relationship between internal and external factors and job satisfaction, and between job satisfaction and auditors’ performance.

This research used deductive approach. Data was gathered from 83 auditors in the Saudi Organisation for Certified Public Accountants (SOCPA) database. By implementing the partial least squares-structural equation modelling (PLS-SEM) technique, the suggested hypotheses were examined.

The results show that internal factors, i.e., achievement, advancement, recognition and growth, significantly impact job satisfaction. Subsequently, the external factors, i.e., company policies, relationship with a peer and relationship with supervisor, significantly impact job satisfaction. In contrast, work security has no relationship with job satisfaction. Furthermore, job satisfaction is a significant driver for auditors' performance.

This research sheds light on the relationships between internal and external factors, job satisfaction and auditors' performance in the Saudi context. It would be interesting to investigate these relationships in a different setting, such as a different country, time or industry. Future studies should broaden the sample frame to include different types of employees to obtain more generalisable results.

This study may help managers of auditing departments formulate appropriate strategies and design effective programs to increase the level of job satisfaction between auditors by enhancing such factors, which will lead to improving the auditors' performance.

This research provide an empirical evidence to support the theoretical assumptions of Herzberg's which is much needed.

The purpose of this study is to examine various data sources to identify trends and themes in humanitarian supply chain management (HSCM) in the digital age.

In this study, various data sources such as published literature and social media content from Twitter, LinkedIn, blogs and forums are used to identify trending topics and themes on HSCM using topic modelling.

The study examined 33 published literature and more than 94,000 documents, including tweets and expert opinions, and identified eight themes related to HSCM in the digital age namely “Digital technology enabled global partnerships”, “Digital tech enabled sustainability”, “Digital tech enabled risk reduction for climate changes and uncertainties”, “Digital tech enabled preparedness, response and resilience”, “Digital tech enabled health system enhancement”, “Digital tech enabled food system enhancement”, “Digital tech enabled ethical process and systems” and “Digital tech enabled humanitarian logistics”. The study also proposed a framework of drivers, processes and impacts for each theme and directions for future research.

Previous research has predominantly relied on published literature to identify emerging themes and trends on a particular topic. This study is unique because it examines the ability of social media sources such as blogs, websites, forums and published literature to reveal evolving patterns and trends in HSCM in the digital age.

This article summarizes practitioner observations on three research questions. First, the factors that lead to the emergence and persistence of such teams. Second, the repercussions of siloed teams. And third, practical suggestions and recommendations that practitioners can employ to prevent silo formation or address existing silos. This article thus complements recent academic work that has previously explored the formation of silos.

The authors used the input of current team leads from a focus group along with their consulting experience to explore these three research questions. The team lead input and consulting expertise are integrated with academic research on silos.

The emergence and persistence of silos was mostly attributed to company characteristics (size, growth and stakeholder management) as well as communication inefficiencies (lack of role clarity and ownership within teams), which in turn were impacted by situational variables (pandemic and turnover). The authors noted the effect of team composition effects, team competition and organizational changes (rapid growth and restructuring) as potential contributors to the formation and persistence of silos. The team lead experts and our consulting experiences were congruent with the literature focused on repercussions of silos, from poor information exchanges to inefficiencies, divisions and perceived isolation of teams from the organization. Solutions focused on project organization and documentation as well as the adoption of new decision-making tools and practices, and the creation of more exchange and learning opportunities. The authors added additional options to promote more visibility, appreciation, proactive monitoring within teams and organizational identification initiatives.

The current article adds a pragmatic perspective to silos and how organizations can address these when they become problematic and hinder performance and collaboration.

This study aims to explore the potential benefits of integrating Artificial Intelligence (AI) with Social Emotional Learning (SEL) in educational settings.

A systematic review of emerging AI technologies such as virtual reality, chatbots, sentiment analysis tools, gamification and wearable devices is conducted to assess their applicability in enhancing SEL.

AI technologies present opportunities for personalized support, increased engagement, empathy development and promotion of well-being within SEL frameworks.

Future research should focus on addressing ethical concerns, fostering interdisciplinary collaborations, conducting longitudinal studies, promoting cultural sensitivity and developing robust ecosystems for AI in SEL.

This study contributes by outlining pathways for leveraging AI to create inclusive and supportive learning environments that nurture students' socio-emotional competencies, preparing them for success in a globally connected world.

This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.

The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.

Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.

The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.

The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.

By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.

Further investigation is needed of network effectiveness in healthcare and how it is influenced by unpredictable events like COVID-19. Based on Provan and Milward’s (2001) framework, this study investigates the effectiveness criteria of healthcare networks and their potential contribution to network effectiveness during the pandemic’s challenges.

This research employs an explanatory case study in a local area of Italy’s Lombardy Region and analyzes network effectiveness at the network level based on network member perceptions.

Network effectiveness refers to the network’s ability to address patient needs, guaranteeing services through network members' coordinated efforts and a central coordinator that facilitates their interaction. Members’ capacity to strengthen their roles played a crucial part in sustaining network effectiveness when COVID-19 revised other members’ priorities and threatened achievement of network goals.

This study’s findings equip healthcare managers and policymakers with knowledge about network effectiveness criteria at the network level, offering suggestions for managerial practices and network design to address exogenous shocks.

This study identifies factors that influence network effectiveness criteria and provides insight into how network members can contribute to sustaining effectiveness during crises.

This paper aimed to determine the self- and co-regulation influences on the community of inquiry (CoI) for collaborative online learning.

A quantitative survey was used on a sample of (N = 626) enrolled postgraduate students in a South African Open Distance and e-Learning (ODeL) university. The measuring instruments were the CoI and the shared metacognitive surveys. Correlation and multiple regression analyses were used to determine the association and influence of self- and co-regulation on the CoI.

The results indicated that self- and co-regulation related to the CoI (teaching, cognitive and social) presences. In addition, the results revealed that self- and co-regulation influence the CoI presences. Self-regulation had the highest influence on teaching and cognitive presence, while co-regulation influenced social presence.

The study’s convenience sampling method from a single university limited the applicability of the findings to other online learning environments.

Higher educational teachers who encourage student self- and co-regulation may enhance their online teaching, cognitive and social presence when studying online. The research’s findings may be valuable to teachers to enable them to provide a more collaborative and interactive online learning environment and promote productive online communities.

This study contributes to the body of knowledge about the relationship between teaching, social and cognitive presence and self- and co-regulation within the CoI framework. Furthermore, there has also been limited research focussing on the dynamics of shared metacognition within the CoI framework in an ODeL context.