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The purpose of this study was to obtain valuable insights into students’ engagement and experiences within the virtual learning environment, especially in the context of crises. Among the innumerable challenges people throughout the world faced during the first year of the COVID-19 pandemic, those of students in institutions of higher education needing to engage in online academic studies are of special interest. Using an online survey, this study could predict students’ online engagement during the COVID-19 pandemic through three theoretical frameworks: the students’ academic motivation to study, the Big Five personality traits, and loneliness, and with a new tool measuring the participation in the Zoom platform.

To examine the psychological and technological factors predicting the students’ engagement, this study surveyed 547 students from different academic institutions of higher learning.

Findings show that the less lonely the students felt, the less neurotic they were, and the higher they scored in levels of extroversion, agreeableness, consciousnesses and openness to experience, the greater their engagement in their academic studies. In addition, students who were older, more educated, with higher intrinsic motivation and lower lack of motivation were more engaged in their online academic studies. Finally, participating in classes through the Zoom platform and experiencing it positively was a significant predictor of higher academic engagement.

Recognizing these factors can enable educators, institutions of higher learning, counselling services and students to obtain tools for higher engagement in online learning.

This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.

Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.

Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.

This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

Machine learning (ML), and deep learning in particular, is gaining traction across a myriad of real-life applications. Portfolio management is no exception. This paper provides a systematic literature review of deep learning applications for portfolio management. The findings are likely to be valuable for industry practitioners and researchers alike, experimenting with novel portfolio management approaches and furthering investment management practice.

This review follows the guidance and methodology of Linnenluecke et al. (2020), Massaro et al. (2016) and Fisch and Block (2018) to first identify relevant literature based on an appropriately developed search phrase, filter the resultant set of publications and present descriptive and analytical findings of the research itself and its metadata.

The authors find a strong dominance of reinforcement learning algorithms applied to the field, given their through-time portfolio management capabilities. Other well-known deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN) and its derivatives, have shown to be well-suited for time-series forecasting. Most recently, the number of papers published in the field has been increasing, potentially driven by computational advances, hardware accessibility and data availability. The review shows several promising applications and identifies future research opportunities, including better balance on the risk-reward spectrum, novel ways to reduce data dimensionality and pre-process the inputs, stronger focus on direct weights generation, novel deep learning architectures and consistent data choices.

Several systematic reviews have been conducted with a broader focus of ML applications in finance. However, to the best of the authors’ knowledge, this is the first review to focus on deep learning architectures and their applications in the investment portfolio management problem. The review also presents a novel universal taxonomy of models used.

With the technological innovation dominating higher education, the university libraries, as physical spaces, continue to play a crucial role in connecting students with knowledge. The emergence of the “Learning Commons” serves as a catalyst in the design of library spaces, renewing libraries’ roles and missions and making them popular to Millennials for new reasons. This study aims to record Greek librarians' views on the current situation in Greek academic libraries regarding physical space design, services provided and the existence of the “Learning Commons” model characteristics.

This study was conducted through an online survey structured questionnaire (closed-ended, five-point Likert scale, multiple-choice and statements questions). This study population comprised librarians working in 37 academic institutions and colleges. The collected data were subjected to descriptive statistical analysis. The research questions were answered using variables creation and the tests, t-test, ANOVA and Kruskal–Wallis. The groups of questions were tested for their reliability using the Cronbach's alpha coefficient.

In total, 186 librarians responded to this study. The responses revealed that participants were willing and ready to accept and support a different approach to academic library physical spaces use, according to the shared learning spaces model. However, this requires changes in the organization's vision, further growth and evolution. Although recently most Greek academic libraries have made significant progress in developing their services to function as information and digital hubs, they do not function as learning collaborative hubs, since the “Learning Commons” model is not reflected in their buildings.

The creation of new academic libraries according to the “common” model is a rapidly evolving issue that affects Greek libraries. This paper highlights the characteristics of libraries that should be adopted in the modern era, the new roles of academic librarians and the importance of an appropriate design of the physical space to achieve optimal learning outcomes. At the same time, this paper is one of the few that illustrates librarians', and not users', perceptions of these changes. This paper is a good research example, and the methodology for measuring this type of context could be used by other future research approaches in other countries.

The combination of mobile devices and innovative tools offers new possibilities for the development of a community of practice for design makers. Mobile learning has become an essential method that design makers should adopt. The main content of this study is to explore the characteristics of learning behaviors and learning needs of creative design makers' group in forming a community of practice in the era of mobile learning.

This study conducted questionnaire research on the potentially associated or directly associated population of design makers. The process of the study also combined observational and interview studies to compensate for the lack of questionnaire research.

Based on the support of mobile learning technology, design makers share and co-create to achieve individual development and evolution of learning organizations, and produce creative value. Design-maker communities of practice form common communities in the framework of informal organizations to support continuous individual learning. Convergent interests or concerns in making things, real-world contexts based on makerspaces and hands-on practice based on real projects are the basis for forming design-maker communities of practice. A variety of open-source hardware, software and platforms that can support mobile learning are important for the development of design-maker communities of practice. The design-maker community of practice needs group factors, activity development, physical and technical resources, spatial support and institutional norms to enhance learning behaviors and satisfy learning needs.

The discovery and construction of these associated factors can help creative design practitioners form a lasting and virtuous organizational development. This study facilitates the formation of a social network for learning and knowledge sharing among design-maker communities of practice. It enhances the innovation ability and enthusiasm of design makers according to the population characteristics and learning needs of design makers. This study also facilitates the generation of a positive adaptive maker culture and maker spirit within design maker organizations.

This study aims to investigate the favourable conditions that influence transgenerational value transmission (TVT), value acceptance and value similarity between generations in indigenous African business-owning families.

This study adopts a multiple case study design and draws on semi-structured face-to-face interviews to collect data from participants in seven indigenous Black business-owning families located in South Africa. The software ATLAS.ti was utilised to manage the data and reflexive thematic analysis was undertaken.

The analysis reveal four themes describing how transmission factors facilitate favourable conditions for successful TVT in IBSA business-owning families, namely, authoritarian parenting, a loving and connected family relational climate, the continuous reinforcement of autonomy during childhood development and family authenticity in the face of societies dominant values climate. Furthermore, value similarity is perceived to exist among the different family generations in the business-owning families.

This study is among the first to adopt the value acquisition model to empirically examine successful TVT and examine the extent of value similarity or dissimilarity, using the business-owning family as the unit of analysis. Novel contributions to family business literature and practices are proposing a model for TVT in an African context and studying relationships from a business-owning family perspective. The model for TVT could be used to socialise the NextGen members into value sets and behaviours that help business-owning families preserve their entrepreneurial legacy and family business longevity.

This paper explores the impact of interior design education and its effectiveness in the work environment for women in the United Arab Emirates (UAE), as they are the primary recipients of interior design programs. The analysis focuses on the role of women in interior design in the Gulf countries and the update of an interior design program curriculum as part of the continuous development program requested by the UAE Commission of Academic Accreditation (CAA) of the national Ministry of Education (MoE).

The research adopts different methodologies: an academic annual effectiveness report (AER), requirements of relevant international and regional accreditation bodies and a double round of surveys and interviews with female students, alumni, instructors and professionals.

The article collects and compares data from different perspectives, from the academic to the professional point of view, discussing challenges and opportunities for female students in contemporary interior design in the UAE. After collecting the necessary feedback on the strengths and weaknesses of the bachelor’s program, a set of informed recommendations has been developed, approved and introduced during the academic year 2022/2023. At the end of the year, a second feedback from faculty and external reviewers was gathered and analyzed, providing preliminary insights into the effectiveness of the curricular revisions and highlighting the significant benefits for the female students.

The paper discusses the comprehensive and up-to-date combination of traditional elements, innovative approaches and sustainable practices, alongside the strategic planning of the United Arab Emirates, proposed to enhance female learning experiences while reinforcing their skills and competencies for their future careers.

The purpose of this study was to develop a suitable module for digital conservation of traditional knowledge of medicinal plants (MPs) used by tribal communities living in the Anuppur district of Madhya Pradesh, Central India.

The research used a qualitative approach to gather the data of MPs through the use of literature review and field survey. Based on the acquired data, a prototype digital learning system was constructed and assessed. This study used digital learning technologies to assess the requirements for transmitting traditional knowledge of important MPs used by tribal communities so that people can absorb and conserve them.

Over time, the focus on the digital conservation of traditional MP’s knowledge has progressively increased globally. Despite the rise in this field of study, information technology methods to preserve and distribute traditional knowledge of MPs have remained a few. When adopting digital learning to maintain traditional knowledge of MPs, it was discovered that it would be necessary to engage with relevant knowledge keepers, use multimedia, and provide content in local languages.

This study helps in conservation of important MP species that are having biologically important therapeutic compounds meant for treating various ailments. Older generations of various tribal communities mainly hold traditional knowledge of important MPs, and unless it is preserved, it will perish along with its caretakers.

It is worth looking at a digital platform that can help future generations to maintain traditional knowledge of MPs, as it is a dynamic and ever-changing, it must involve a digital tool for its future conservation. Current methods for maintaining traditional knowledge of MPs were ineffective and constrained by space and time.

“Can artificial intelligence produce architectural plan schemes?” discussion is the starting point of this study. The aim of this paper is to question whether this will be a new method in architectural design by producing plans with artificial intelligence interfaces working with human–computer interaction and to create a discussion environment.

The main research topic is the evaluation of architectural design decisions with the text-to-image generation AI algorithms method based on shape grammar rules. First, a sample space consisting of Palladio plans or plan diagrams was created. Plan diagram production experiments were made with different interfaces (Midjourney, Dall-e2, Stable Diffusion, Craiyon, Nightcafe), and alternative plan diagrams were recorded as outputs. The discussion of the outputs has been made over architectural design and space.

In the conceptual design phase of the architectural discipline and in the production of architectural plan scheme, AI algorithms are trending. This interaction imposes a new responsibility on architects. AI can create paradigm shifts in architectural processes with its tools with high data processing potential. On the other hand, in this study, it is emphasized that architecture is not just an act of producing visuals, but a functional act of producing visuals.

The technology is effective in producing architectural plans and directing them to artificial intelligence algorithms. With this study, multi-alternative architectural plan productions were tried with text-to-image bots with fast results. In this direction, a new method proposal has been developed for the conceptual design phase in architecture.