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The very essence of internationalisation, which depends heavily on academic mobility and cross-border interactions, has been adversely affected due to the COVID-19 pandemic and has been associated with a significant decline in student and staff mobility in South Africa and around the world. Nonetheless, it has also catalysed innovation and inspired new approaches to teaching and learning that have the potential to transform the future of higher education. In the aftermath of the COVID-19 pandemic, higher education institutions are grappling with a fundamental question that goes beyond the practicalities of internationalisation: How can we re-envision the concept of internationalisation to meet the challenges of the new normal? This question calls for a deeper reflection on the nature of internationalisation itself. How can we ensure that cross-border interactions and exchanges continue to foster a sense of global community and intercultural understanding, even in a world that is physically distanced? This chapter seeks to explore the profound implications of the pandemic on the internationalisation of higher education (IHE) in South Africa. It aims to critically examine the present challenges to internationalisation and the strategies that have been developed to address them in the context of the post-pandemic world. The chapter employs a critical reflection approach through the use of qualitative research, systematic literature review, and document analysis. By utilising these methodologies, it seeks to delve deeper into the implications of the pandemic on the IHE in South Africa.

Knowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.

Drawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.

TMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.

Developers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.

This study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

Education to an international standard that can provide successful careers has arguably been the main drive of many parents to allocate scarce financial resources to the education of their progenies. Competition for high-calibre degrees has seen an explosion of opportunity in the private education sector. As many Global South countries do not have the equivalent control of standards provided in the United Kingdom (UK) by the Quality Assurance Agency, this can lead to dissatisfaction with the qualifications received in the Global South. This chapter aims to explore the factors influencing participation in higher education in the Global North versus the Global South, particularly where these relate to or vary by locality, and the relative influence these have on the propensity of the learners living in these areas to progress into higher education in local universities. The conceptual framework and methodology provided in this chapter show the differences between transnational education (TNE) as primarily a standalone or independent activity supported by a UK higher education institution (HEI)/provider versus being a collaborative effort between a UK host university and a South/Southeast Asian HEI university partner. The methodology provides a strategy for UK host institutions to best provide carefully aligned independent or collaborative partnerships with the partner country regulatory bodies. The chapter concludes with the author’s personal reflections and recommendations based on decades of collaborative and independent university provision of TNE. These reflections are focused on design-based courses in selected South/Southeast Asian HEI partnerships with the College of Architecture and Design at Birmingham City University.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

This study focuses on the triadic multilevel psychic distance (MPD) between the firm, target market and bridge-maker and its consequences for firm internationalization. Specifically, it spotlights the triadic psychic distance between firms, the levels of psychic distance in the target market (country and business) and the bridge-maker. Therefore, this study examines the triadic MPD among these three entities and its impact on firm internationalization.

This study uses qualitative and case study research approaches. It is based on 8 case companies and 24 internationalization cases. Secondary data were collected, and interviews with bridge-makers and industry experts were conducted.

The study found that MPD appeared in the triad. The MPD between firms and markets is related to country-specific differences and business difficulties. The MPD between the firm and the bridge-maker is based on the latter’s lack of knowledge vis-à-vis bridging the firm’s MPD. Finally, the MPD between bridge-makers and the market is based on the former’s lack of knowledge of the home country’s business difficulties.

This is the first study to develop and adopt a triadic multilevel psychic distance conceptualization that provides evidence for and sheds light on the triadic MPD and its effect on firm internationalization. This study identifies the reasons behind triadic MPD in connection to firm internationalization. Notably, firm internationalization is interdependent on the triadic MPD setting between the firm, bridge-maker and target market. It has theoretical value and contributes to the recent advancement in the understanding of MPD in international marketing literature.

Digital transformation misalignment refers to disparities in digital transformation levels between suppliers and buyers across the production and operation process. It has negatively affected supply chain stability. However, the existing research concerning the economic consequences has not been adequately addressed. Therefore, this paper aims to investigate whether such digital transformation misalignment increases supplier financial risk and to identify the factors influencing this relationship.

This paper examines binary combinations of suppliers and buyers listed on China’s A-share market between 2011 and 2021. This group constitutes a sample to empirically test the influence of digital transformation misalignment on the supplier’s financial risk, as well as the moderating effect of the geographical and organizational distances.

The paper’s findings demonstrate that digital transformation misalignment has indeed a significant increase in the supplier’s financial risk. Moreover, the impact is more intense when the geographical or organizational distance between the supplier and the buyer is relatively large.

The existing literature rarely explores the potential risks arising from digital transformation misalignment between supply chain partners. Therefore, this paper fills a notable gap as it is the first to study the impact of digital transformation misalignment on the supplier’s financial risk and the specific applied mechanisms. The contribution significantly improves the field of corporate digital transformation, particularly, within the context of supply chain management.

This chapter examines the internationalisation of public higher education in Brazil using the theoretical triptych of internationalisation as developed by leading scholars in the field: internationalisation at home (IaH), internationalisation abroad (IA), and internationalisation at a distance (IaD). This framework – while rooted in knowledge, systems, and scholarship from researchers and institutions in the Global North – is a constructive tool for categorising and understanding internationalisation at Brazil’s higher education institutions (HEIs) when coupled with an exploration of the history, context, policy, and dynamics of internationalisation efforts. The chapter then summarises and underscores recent and important scholarship by Brazilian researchers and others in the Global South that describes the history of the nation’s internationalisation efforts. It also critiques the powerful influence that Global North-centred objectives and priorities for internationalisation have on the process at Brazilian HEIs. Following a discussion of the theoretical framework and relevant literature, the chapter provides a case study of internationalisation efforts and initiatives of an elite public university, the Universidade Federal de Minas Gerais (UFMG). Content analysis of UFMG’s website and publicly available reports and data demonstrates a high level of institutional internationalisation that has unfolded in recent years, stimulated by federal funding and guided by a strategic framework developed within the Ministry of Education. An analysis of UFMG’s mission, partnerships and programmes finds that the institution serves as an example of internationalisation in Brazil’s public higher education context, as its programmes and initiatives exemplify the overarching objectives of internationalisation in Brazilian higher education.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.

Small and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used by SMEs these days is the implementation of lean manufacturing to get solutions for various issues they encounter. But is lean getting sustained over time? The purpose of this research is to design a Sustainable Lean Performance Index (SLPI) to assess the sustainability of lean systems and to pinpoint the variables that might be present as potential lean system inhibitors which hinder the sustainability of leanness.

A multi-level sustainable lean performance model is constructed and presented based on the literature research, field investigation and survey conducted by administering a questionnaire. Fuzzy logic approach is used to analyse the multi-level model.

SLPI for the SMEs is found using fuzzy logic approach. Additionally, the ranking score system is applied to categorise attributes into weak and strong categories. The performance of the current lean system is determined to be “fair” based on the Euclidean distance approach and the SLPI for SMEs.

This work is concentrated only in South India because of the country’s vast geographical area and rich and wide diversity in industrial culture of the nation. Hence, more work can be done incorporating the other parts of the country and can analyse the lean behaviour in a comparative manner.

The generalised sustainable lean model analysed using fuzzy logic identifies the inhibitors and level of performance of SMEs in South India. This can be implemented to find out the level of performance in the SMEs after a deeper study and analysis around the SMEs of the country.

The sustainable assessment of lean parameters in the SMEs of India is found to be very less in literature, and it lacks profundity. The model established in this study assesses the sustainability of the lean methodology adopted in SMEs by considering the lean and sustainability attributes along with enablers like technology, ethics, customer satisfaction and innovation with the aid of fuzzy logic.