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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 qualitative study assesses the enablers of the work of a novel, self-managing digital pedagogy peer support team in a Finnish higher education institution.

This study employs a qualitative methodology with in-depth interviews of five digital pedagogy facilitators. The data collected are analyzed with the ATLAS.ti software. The analytical approach follows a deductive method, applying the categories derived from Magpili and Pazos (2018) who investigated the input variables of self-managing teams through their extensive literature review.

The primary findings underscore the suitability of Magpili and Pazos' variables for evaluating the performance enablers of self-managing teams. Furthermore, the findings emphasize the significance of leadership and effective communication as essential prerequisites for achieving elevated performance levels.

This study focuses on the enablers of team performance from the perspective of the team members. To enhance comprehensiveness, subsequent phases should incorporate viewpoints from clients, namely peer instructors, and focus on the mediator and outcome aspects of the team effectiveness framework.

This study offers actionable recommendations for higher education institutions aiming to adopt a peer mentor model akin to the one delineated in the study.

This study analyzes a collaborative approach to advancing digital pedagogy within higher education institutions and discusses the enablers for successful performance within self-managing teams.

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 endeavors to create a predictive model for the energy consumption associated with the multi-material fused deposition modeling (FDM) printing process.

An online measurement system for monitoring power and temperature has been integrated into the dual-extruder FDM printer. This system enables a comprehensive study of energy consumption during the dual-material FDM printing process, achieved by breaking down the entire dual-material printing procedure into distinct operational modes. Concurrently, the analysis of the G-code related to the dual-material FDM printing process is carried out.

This work involves an investigation of the execution instructions that delineate the tooling plan for FDM. We measure and simulate the nozzle temperature distributions with varying filament materials. In our work, we capture intricate details of energy consumption accurately, enabling us to predict fluctuations in power demand across different operational phases of multi-material FDM 3D printing processes.

This work establishes a model for quantifying the energy consumption of the dual-material FDM printing process. This model carries significant implications for enhancing the design of 3D printers and advancing their sustainability in mobile manufacturing endeavors.

This study aims to determine how the applications of blockchain technology (BT) can play a crucial role in managing financial flows in the humanitarian supply chain (HSC) and what benefits and challenges are associated with BT in a humanitarian setting.

The present study used a qualitative research approach, incorporating a systematic literature review and conducting semi-structured interviews with 12 experts in the fields of humanitarian operations, supply chain management, fintech and information technology.

The findings show that the humanitarian sector has the potential to reap significant benefits from BT, including secure data exchange, efficient SCM, streamlined donor financing, cost-effective financial transactions, smooth digital cash flow management and the facilitation of cash programs and crowdfunding. Despite the promising prospects, this study also illuminated various challenges associated with the application of BT in the HSC. Key challenges identified include scalability issues, high cost and resource requirements, lack of network reliability, data privacy, supply chain integration, knowledge and training gaps, regulatory frameworks and ethical considerations. Moreover, the study highlighted the importance of implementing mitigation strategies to address the challenges effectively.

The present study is confined to exploring the benefits, challenges and corresponding mitigation strategies. The research uses a semi-structured interview method as the primary research approach.

This study adds to the existing body of knowledge concerning BT and HSC by explaining the pivotal role of BT in improving the financial flow within HSC. Moreover, it addresses a notable research gap, as there is a scarcity of studies that holistically cover the expert perspectives on benefits, challenges and strategies related to blockchain applications for effective financial flows within humanitarian settings. Consequently, this study seeks to bridge this knowledge gap and provide valuable insights into this critical area.

The purpose of this paper is to compare nine different models to evaluate consumer credit risk, which are the following: Logistic Regression (LR), Naive Bayes (NB), Linear Discriminant Analysis (LDA), k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), Classification and Regression Tree (CART), Artificial Neural Network (ANN), Random Forest (RF) and Gradient Boosting Decision Tree (GBDT) in Peer-to-Peer (P2P) Lending.

The author uses data from P2P Lending Club (LC) to assess the efficiency of a variety of classification models across different economic scenarios and to compare the ranking results of credit risk models in P2P lending through three families of evaluation metrics.

The results from this research indicate that the risk classification models in the 2013–2019 economic period show greater measurement efficiency than for the difficult 2007–2012 period. Besides, the results of ranking models for predicting default risk show that GBDT is the best model for most of the metrics or metric families included in the study. The findings of this study also support the results of Tsai et al. (2014) and Teplý and Polena (2019) that LR, ANN and LDA models classify loan applications quite stably and accurately, while CART, k-NN and NB show the worst performance when predicting borrower default risk on P2P loan data.

The main contributions of the research to the empirical literature review include: comparing nine prediction models of consumer loan application risk through statistical and machine learning algorithms evaluated by the performance measures according to three separate families of metrics (threshold, ranking and probabilistic metrics) that are consistent with the existing data characteristics of the LC lending platform through two periods of reviewing the current economic situation and platform development.

Passive investing has established itself as the dominant force in the world of professionally managed assets, surpassing the concept of index funds. Its meteoric rise is fueled by investors’ preference for its dual benefits of strong diversification and low cost. A comprehensive study of the economic model, addressed areas and market structure has not yet been conducted, despite the existence of numerous studies on more specific topics. To address this gap, this paper examines 943 articles on passive investing published between 1998 and 2022 in SCOPUS and Web of Science.

The study utilizes the most pertinent tools for conducting a systematic review by the PRISMA framework. This article is the result of SLR and extensive bibliometric analysis. Contextualized systematic literature review is used to screen and select bibliographic data, which is then subjected to a variety of bibliometric analyses. The study provides a bibliometric overview of works on passive investment research that are indexed in Scopus and Web of Science. Bibliometrix, VoS Viewer and Cite Space are the tools used to conduct content and network analysis, to ascertain the present state of research, as well as its focus and direction.

Our exhaustive analysis yields important findings. One, the previous decade has witnessed a substantial increase in the number of publications and citations; in particular, the inter-disciplinary and international scope of related research has expanded; Second, the top three clusters on “active versus passive funds,” “price discovery and market structures” and “exchange-traded funds (ETFs) as an alternative” account for more than fifty percent of the domain’s knowledge; Third, “Leveraged ETFs (LETFs)” and “environmental, social and governance (ESG)” are the two emerging themes in the passive investing research. Fourth, despite its many benefits, passive investing is not suitable for everyone. To get the most out of what passive investing has to offer, investors, intermediaries and regulators must all exercise sufficient caution. Our study makes a substantial contribution to the field by conducting a comprehensive bibliometric analysis of the existing literature, highlighting key findings and implications, as well as future research directions.

While the study contributes significantly to the field of knowledge, it has several limitations that must be considered when interpreting its findings and implications. With our emphasis on academic journals, the study analyzed only peer-reviewed journal articles, excluding conference papers, reports and technical articles. While we are confident that our approach resulted in a comprehensive and representative database, our reliance on Elsevier Scopus and Web of Science may have resulted in us overlooking relevant work accessible only through other databases. Additionally, specific bibliometric properties may not be time-stable, and certain common distribution patterns of the passive investing literature may still be developing.

With this study, it has been possible to observe and chart the high growth trajectory of passive investing research globally, especially post-US subprime crisis. Despite the widespread adoption of passive investing as an investment strategy, it is not a one-size-fits-all proposition. Market conditions change constantly, and it frequently requires an informed eye to determine when and how much to shift away from active investments and toward passive ones. Currency ETFs enable investors to implement a carry trade strategy in their portfolios; however, as a word of caution, currency stability and liquidity can play a significant role in international ETFs. Similarly, LETFs may be better suited for dynamic strategies and offer less value to a long-term investor. Lastly, the importance of investor education cannot be underestimated in the name of the highly diversified portfolio when using passive alternatives, for which necessary efforts are required by regulators and investors alike.

The inexorable trend to passive investing creates numerous issues for fund management, including fee and revenue pressure, which forces traditional managers to seek new revenue streams, such as illiquid and private assets, which also implies increased portfolio risk. Additionally, the increased transparency and efficiency associated with the ETF market indicates that managers must rethink the entire value chain, beginning with technology and the way investments interact. Passive investments have triggered changes in market structure that are still not fully understood or factored in. Active management and a range of valuation opinions on whether a price is “too low” or “too high” provide much-needed depth to a market as it attempts to strike a delicate balance between demand and supply forces, ensuring liquidity at all price points.

I hereby certify that I am the sole author of this paper and that no part of this manuscript has been published or submitted for publication.

Professional development (PD) is an essential component of continuing learning for in-service teachers. This paper discusses a school-based example of using the best practice of coaching in early childhood education supported by a professional development school partnership. We explain how a teacher identified need led to a collaborative, multistep approach to meeting that need in connection to State mandates.

In this research, we used a case study methodological approach with a team of preschool teachers at one school. The model combines use of PD sessions, classroom coaching, classroom observation and reflection.

Teachers’ feedback indicates that using the strategy positively impacted most of the participants’ ability to support communication, community-building and inclusive practices in their classrooms. The data that emerged in the following year evidenced increased use of visual supports in classrooms, use in connection with literacy goals and interest in creating new uses in the school.

This article contributes an action-oriented school-based example of bridging research to practice to support teachers’ needs through PD and coaching in a PDS. The design and practical implications may interest preschool educators, instructional coaches, administrators, professional development schools and others involved with monitoring teacher development initiatives.

This study examines the dynamics of innovative auditing practices in the digital age, with a specific focus on auditor competencies. Within this scope, we highlight the necessity of redefining auditing practices and the essential adaptation required from auditors. The primary objective is to understand comprehensively how auditor competencies can be strengthened to meet the challenges posed by innovative audit practices.

A Systematic Literature Review (SLR) was conducted to explore this theme, ensuring rigor and credibility in the outcomes. The results emphasize the importance of auditors strengthening professional competencies, embracing technological agility, and promoting ongoing professional development initiatives.

The triadic framework comprising—Auditor, Auditing Practices, and Digital Audits— forms the basis for innovative audit practices. This manuscript further discusses the transition of advanced technologies, laying the groundwork for the evolution of auditing practices. Through a systematic assessment of the literature, this study develops a framework for innovative, ethically driven, and effective auditing practices, ensuring the occupation's relevance and value. Future investigations should focus on the ethical implications of automation in auditing practices and develop innovative frameworks tailored to diverse organizational contexts.

The study addresses a contemporary issue by examining the evolving nature of auditing practices considering digital transformation. Practical implications highlight the enhancement of auditor roles in digital transformation, covering ethics, technological adaptation, and continuous development to uphold the profession's integrity. This focus acknowledges the changing dynamics of business and the growing role of technology in auditing processes.