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As Malaysia’s educational landscape continues to evolve, there is a need to rethink the models and practices involved in the teaching and learning process. The coronavirus disease (COVID-19) pandemic, subsequent lockdowns, and movement control restrictions have contributed to the shift in education, especially in teaching and learning. Educational institutions were instructed to close during the lockdowns and this forced educators and students to communicate and engage using digital technologies. Students have no issues when it comes to embracing technology, but their ability to stay engaged and participate during lessons was of concern to educators. According to recent research, collaborative learning has been shown to be enjoyable and engaging for students, especially when it is conducted digitally using innovative learning technologies. When students show an increased level of engagement, it shows that they are actively participating and are more involved during lessons. This quantitative study looks into the relationship between variables pertaining to digital collaboration (personal factors, environmental factors, social media support, digital collaborative tools, interactivity, motivation) and student engagement toward enhanced student participation during COVID-19. The study utilizes Lev Vygotsky’s Collaborative Learning Theory alongside Albert Bandura’s Social Learning Theory. The data analysis revealed that there is a positive significant relationship between digital collaborative tools, interactivity, and motivation towards student engagement, which in turn proved that there is a positive significant relationship that can be drawn between student engagement and enhanced student participation during COVID-19.

PurposeThe purpose of this paper is to analyse how digital technologies trigger changes in the business process of manufacturing small and medium-sized enterprises (SMEs) in the Apulia Region (South Italy). As SMEs play an essential role in the process value creation of industries and countries, the article examines the enablers of Industry 4.0 in a regional contexts characterized by delay in research and development and innovation performances where the companies' competitiveness is based on limited knowledge and technological assets.Design/methodology/approachThe case study of Smart District 4.0, an ongoing project aimed to promote the digitalization of SMEs operating in the Agri–Food, Clothing–Footwear and Mechanics–Mechatronics in the Apulia Region (South Italy) is analysed. The project has been financed by the Italian Ministry of Economic Development with the final aim to sustain the digital transformation of SMEs in South Italy.FindingsThe results introduce a four levels approach of engagement of SMEs in the adoption of digital technologies, namely, digital awareness, digital enquirement, digital collaboration and digital transformation. Furthermore, for each level of engagement the study describes and discusses some relevant variables that could be used by managers and entrepreneurs to assess the level of readiness for utilization of digital technologies and how to digitalize some processes.Practical implicationsPractical implications regard the definition of a roadmap useful to assess and manage the level of digital transformation of SMEs. Limitations of the study regarding the temporal dimension of the evidences associated to the Smart District 4.0 as well as to the regional context was analysed.Originality/valueOriginality resides in the definition of a roadmap for the digital transformation of SMEs in a region where the profile of companies' digital maturity is still low.

PurposeThis paper presents a model aiming to identify the factors influencing the adoption of augmented reality (AR) for industrial services.Design/methodology/approachThe study combines a literature analysis with an empirical study conducted exploring how five large industrial companies are introducing AR for supporting the provision of technical assistance and industrial services to their installed base.FindingsThe authors identify four categories (task, workforce, context and technology) that combine 18 factors that manufacturing companies should consider when introducing AR technology to support industrial services.Originality/valueThis paper systematises the fragmented literature on technology adoption and in particular those works related to the factors affecting the adoption of AR in industrial services. Based on literature and empirical evidence, the authors propose a novel framework that can help companies in the selection of AR solution based on their specific applications and situations. This study therefore contributes also to the existing literature on the adoption of I4.0 and digital technologies in industrial services.

This study explores the integration of artificial intelligence (AI) into project management through a bibliometric analysis of scholarly publications and patents from 2001 to 2024. The paper aims to identify key trends, emerging applications, and global contributions to this evolving field. The study analyzes 51,752 patents from Lens, 5.5 million scholarly records from Google Scholar, and 436,380 records from Web of Science, providing a comprehensive overview of AI’s impact on project management. The analysis maps the evolution of AI-driven project management practices, focusing on resource allocation, risk management, and scheduling optimization. The findings reveal a substantial increase in AI-related project management research, with China and the United States leading in research output. A notable surge in publications post-2019 suggests acceleration due to the COVID-19 pandemic and the growing demand for digital transformation in project execution. Despite the rising adoption of AI in project management, research gaps persist, particularly in interdisciplinary methodologies, practical AI applications, and ethical concerns related to algorithmic decision-making. This study contributes to understanding AI’s transformative role in project management and highlights future research directions to enhance AI adoption for improved efficiency, decision-making, and project performance. The findings underscore the need for continued exploration of interdisciplinary approaches, practical implementations, and ethical considerations to foster innovation and efficiency in AI-driven project management.

The increasing complexity of patient care and workforce shortages in healthcare systems necessitate improved interprofessional interaction. Digital technologies offer promising solutions to facilitate such interaction across healthcare settings. This scoping review aimed to identify, categorize, and assess digital technologies that support interprofessional interaction among healthcare professionals, using the NASSS framework to evaluate their implementation context and impact. A systematic search was conducted across five databases. The eligible studies examined digital tools enabling interaction between different professional groups in healthcare. Data from 407 studies were extracted and coded using four NASSS domains (Condition, Technology, Value Proposition, and Adopter System). Thematic analysis and visualizations were employed to synthesize findings. Seven primary technology categories were identified. Most technologies were implemented at the organizational level, primarily within hospital and intersectoral care settings, with oncology being the most common clinical focus. While many tools showed positive impacts on workflow efficiency, access to specialist expertise, and team communication, challenges relating to usability, data privacy, role ambiguity, and staff workload were also reported. Value propositions and impacts on staff varied significantly across technologies. Digitally supported interprofessional interaction holds promise for enhancing communication, collaboration, and efficiency in delivering healthcare. However, successful adoption depends on aligning technological design with clinical workflows, involving end-users in development, and addressing regulatory, ethical, and organizational challenges.

Addressing the urgent need for sustainable transformation in higher education, this paper explores how a collaborative action research group of teacher educators from different institutions contributed to higher education transformation through sustainable education approaches. Drawing on cultural–historical activity theory (CHAT), we analyze how cross-institutional partnerships fostered personal and professional development through digital collaboration, regular online meetings, and reflective dialogue. The study employed participatory action research, using weekly reflective journals and group meetings as mediating tools supporting sustained professional learning. Findings indicate that building common ground across institutional contexts and investing in trust-building cultivated a meaningful collaborative environment, a “third space” that mediated expansive learning and professional transformation. Within this space, the diversity of institutional backgrounds enriched the activity system, and productive contradictions served as generative mechanisms that catalyze expansive learning by exposing participants to diverse institutional perspectives. The study further shows that sustainable collaboration emerged not from formal institutional structures but from shared ownership, cultural alignment, and relational commitment. These social and cultural processes supported the development of systems-thinking, strategic-thinking, and interpersonal competencies supporting sustainable professional development. The study highlights the potential of sustainable cross-institutional spaces as a model for professional growth in higher education.

The major aim of the study is to examine the impact of Digital Collaboration (DC) and Analytics Capability (AC) on Supply Chain Resilience (SCRES). The study used data gathered from senior managers of the food processing industry in Jordan using a self-reported questionnaire designed and distributed to a purposive sample via email. A purposive sample consisted of 200 managers. To achieve the aim of the study, Structural Equation Modeling (SEM) with Partial Least Squares (PLS) was used for analysis. Responses used in data analysis composed 71% of the distributed questionnaires. The study results supported the hypotheses that AC has positive significant effects on DC and visibility of the SCRES while DC shows significant effects on velocity and flexibility of the supply chain. The study contributes to the body of knowledge on Resource-based view (RBV) and Supply chain literature by emphasizing that the AC between companies is a key antecedent of DC as well as AC and DC are crucial prerequisites for organizations to improve their performance by supporting the resilience of their supply chains. In light of the study results, managers and decision-makers need to prioritize and invest in improving their AC and fostering DC due to their impact on SCRES, which is especially critical considering the increasing challenges that organizations are currently facing, the increasing state of uncertainty in the external environment, and the limited ability of organizations to predict their ability to obtain the resources and production inputs they need.In today’s dynamic and unpredictable business environment, the importance of supply chain resilience, analytics capability, and digital collaboration cannot be overstated. These elements serve as the backbone of organizations striving to thrive in an era marked by rapid technological advancements, global connectivity, and unforeseen disruptions, such as the recent global health crisis. Our article delves into the critical intersection of these three vital components and their profound impact on the sustainability and success of modern businesses. We seek to contribute to the advancement of knowledge in the field of supply chain management. Our findings aim to benefit practitioners, researchers, policymakers, and the broader public by promoting more resilient, efficient, and sustainable supply chains. In doing so, we hope to inspire organizations to embrace the transformative potential of analytics capability and digital collaboration, ultimately strengthening supply chain resilience in an increasingly interconnected world.

The Digital Transformation (DX) megatrend is fundamentally disrupting and changing the nature of work, business, and industry at a rapid pace. Although the notion of DX has garnered much research interest from practitioners, scholarship on this topic is somehow lagging behind, possibly because of the lack of theoretical frameworks on DX. Recently, most Japanese firms have begun to use diverse digital technologies to sustain their competitive advantages. However, the return of investment on digital technologies has not been as high as expected for some firms. Furthermore, as the visions of Industry 5.0 describe sustainable, resilient, and human-centered future factories that will require smart and resilient capabilities both from next-generation manufacturing systems and human operators, it is necessary to design resilient human–machine collaborations within factories. To this end, this paper presents a research model between DX technologies and scientific problem-solving in terms of deduction, induction, and abduction inference structures as an approach to resilient human–machine collaborations. The purpose of this research is to analyze the difference in the utilization pattern of the digital technology of American, German, and Japanese firms based on three types of decision-making methods. Next, we apply this framework in a comparative case study of two Japanese firms and one German firm, where we find that there is a difference in DX technologies utilization among the Japanese and German firms. We assert that the utilization of IoT technology in the United States and Germany is pursuing IoT with the aim of autonomous control, whereas Japanese firms prioritize robot–human collaboration. Finally, we discuss how our findings contribute to the burgeoning field of resilient human–machine collaborations by showing the distinct roles of deduction, induction, and abduction inference structures. Furthermore, our research contributes to international comparative studies to identify the difference in national IT utilization. Lessons and implications are discussed.

Literature on digital collaboration often focuses on individual aspects, but rarely combines them into a unified, practical and sustainability-friendly management tool. The paper fills this critical gap by presenting a comprehensive framework for enhancing digital collaboration, integrating AI, and aligning digital collaboration strategies with broader sustainability objectives. The framework includes four phases and 31 factors categorised into four dimensions. The framework is validated through a case study that combines qualitative (expert interviews) and quantitative (employee survey) approaches, as well as Mayring’s content analysis and the CARL analytical framework. The study reveals that fragmented tool use undermines collaboration maturity across all dimensions, while the integration of AI enhances collaboration outcomes and mitigates digital fatigue. A dual-core collaboration setup contributes to stronger strategic alignment, with the monitoring benefits framework facilitating sustainable improvement tracking. This way, the framework addresses digital fragmentation, tool redundancy, and deficient digital cooperation, leading to increased digital collaboration maturity and alignment with sustainability objectives. The proposed framework offers theoretical, managerial, and societal value by bridging the gap between digital transformation theory and sustainable organisational practice.

Purpose>Covid-19 outbreak has compelled the world-wide education system to use the digital collaboration platform (DCP) for online learning, for robust inclusive sustainable education. The purpose of this paper is to understand the adoption intention and effectiveness of DCP using technology acceptance model (TAM) for online learning among students studying in higher education institutes (HEIs) in India.Design/methodology/approach>A structured questionnaire has been adopted to survey and collect data from 324 students studying in HEI of Maharashtra state in India. The questionnaire consisted of 28 constructs. The constructs in this section were measured using a five-point Likert scale ranging. In the first step, first-order confirmatory factor analysis is carried out by using the software IBM AMOS-20. The initial model is generated for six constructs, and outcomes are used to analyze the model’s goodness of fit and construct validity. In second step, structural equation modelling is carried out to do the path analysis of the proposed model.Findings>The findings connote that the interactivity, cost-effectiveness and the core TAM constructs as perceived usefulness form positive attitude towards usage of DCP and intention to adopt it in near future by the students of HEI of India. The research is an attempt to provide possible explanations for the epochal relationships between the constructs and discusses the usage of information, which can be further used to enhance the acceptance of DCP among students in urban as well as rural India.Research limitations/implications>The results and findings will provide a direction to the various stakeholders such as educators, management, learners and the parents on the adoption intention of digital collaborative platform from a learner’s point of view. This will lead to the knowledge which will help in practical implementations of these technologies.Practical implications>The results and findings will provide a direction to the various stakeholders such as educators, management, learners and the parents on the adoption intention of DCP from learner’s point of view. This will lead to the knowledge which will help in practical implementations of these technologies. The findings imply that the interactivity, cost-effectiveness and the core constructs of TAM such as perceived usefulness form positive attitude towards usage of DCP and intention to adopt it in near future by the students of HEI of India. This research provides possible explanations for the significant relationships between the constructs and discusses how this information can be used to enhance the acceptance of DCP among students in urban as well as rural India.Social implications>This research provides possible explanations for the significant relationships between the constructs and discusses how this information can be used to enhance the acceptance of DCP among students in urban as well as rural India, which is the need of hour for sustainable education.Originality/value>There are tremendous studies on online learning and use of digital platforms including the constructs of TAM but in the times of Covid-19, where it has become mandatory for all educational institutes to use the digital collaborative platform for continuance of education. The study is original and is an attempt to understand students’ perspective towards usage of DCP and its effectiveness in learning in the rural parts of Maharashtra from where the students hail to study in HEI in Pune and Mumbai.