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This study aims to understand how distributed agile teams (DATs), encouraged by globalisation, and recently accelerated by the COVID-19 outbreak, adopt agile practices to achieve project goals by working virtually.

This study developed a multiple-case study involving four companies undergoing several changes, especially during the COVID-19 pandemic. The authors collected data mainly through in-depth, face-to-face interviews with seven key informants. Moreover, this study operates data triangulation by referring to secondary data sources and developing a grounded theory data analysis.

The findings highlight three main categories associated with the DAT functioning, namely, “DATs’ implementation issues”, “elements supporting DATs’ implementation” and “outcomes of DATs’ implementation”, that show DATs’ primary triggers, critical aspects and supportive actions for team functioning.

This paper produced valuable theoretical knowledge of DATs’ dynamics within a socio-technical approach that distinguishes soft and hard variables supporting DAT implementation. Moreover, the evidence provides useful suggestions for managers about creating an objective-oriented virtual work environment based on DATs’ self-organisation, digitally shared leadership and occasional on-site socialisation.

This paper provides new and interesting insights that bring to evidence the main variables related to DATs’ adoption and dynamics, showing supporting activities that enhanced their operativity. It provides a valuable descriptive framework for academics and practitioners to understand DATs’ functioning better and take action to improve their implementation.

The paper uses foundation models to integrate the green approach in Logistics 5.0. Such integration is innovative in logistics and leads to a more sustainable and prosperous future. By harnessing the power of foundation models and incorporating sustainable principles, this paper can systematize the logistics industry’s environmental framework, increase its social responsibility and ensure its long-term economic viability.

Generalizing environmental sustainability goals requires a multi-layered innovation approach incorporating corporate philosophy, products, processes and business models. In this paper, this comprehensive approach is not just a strategy but a necessity in the current global context. This paper uses the sustainability-oriented innovation (SOI) method, crucial for achieving explicit environmental, social and economic impacts.

Artificial intelligence, especially foundation models, can contribute to green logistics by optimizing routes, reducing packaging waste, improving warehouse layouts and other functions presented in the paper. At the same time, they can also consider social, economic and governance goals.

Artificial intelligence algorithms present challenges such as high initial investment, regulatory compliance and technological integration.

The paper contains implications for developing environmentally sustainable logistics, which is currently one of the most significant challenges. The framework presented can apply to logistics companies.

This paper fulfills an identified need to study sustainability in logistics. The framework is entirely original and not present in the literature. It is essential to help design and implement innovative logistics approaches.

The logistics industry has undergone a tremendous transformation. This transformation is necessary to cope with the fundamental changes in customer expectations and the need for digitalization imposed by the pandemic, changes in the socioeconomic world, and innovative technology solutions. This paper aims to present digital transformation as an integrated framework for transforming the operating model and applying advanced solutions to the ecosystem of a quintile logistics (5PL) company. 5PL operators are typically an ecosystem. Loosely coupled or self-organized entities that collaborate in a symbiotic relationship represent this ecosystem. They aim to jointly develop capabilities, create innovative services or solutions, share knowledge, facilitate transactions, and leverage network synergies in a logistics environment to provide optimized or novel customer- or partner-centric solutions (Lamberjohann and Otto, 2020).

Currently, there is no single definition of an integrated logistics operations model in 5PL practice, so the qualitative method used in this paper allows for investigation from an exploratory perspective. The paper follows a qualitative research methodology, collecting and analyzing data/facts through interviews and visits to subject matter experts, industry practitioners, and academic researchers, combined with an extensive review of academic publications, industry reports, and written and media content from established organizations in the marketplace. This paper follows a qualitative research methodology, as it is an inquiry rather than a statistical study. The qualitative method allows the study of the concepts of phenomena and definitions, their characteristics, and the defining features that serve as the basis (Berg, 2007). It emphasizes generalized interpretation and deeper understanding of concepts, which would be more difficult in quantitative, statistically based research. Fact-finding was conducted in two ways: in-depth interviews with experts from academia, information and communication technology organizations, and key players in the logistics industry; and academic publications, industry reports, and written and media content from established national and international organizations in the market.

The operations model introduced considers six aspects: persons, processes, platforms, partners, protection and preservation. A virtual team approach can support the personal side of the 5PL ecosystem’s digital transformation. Managing a 5PL ecosystem should be based on collaborative planning, forecasting, and replenishment methods (Parsa et al., 2020). A digital platform can support trust among the stakeholders in the ecosystem. A blockchain solution can powerfully support the 5PL ecosystem from partner relationships’ points of view. The implementation of a cybersecurity reference model is important for protection (Bandari, 2023). Reverse logistics and an integrated approach support the preservation of the ecosystem.

While the author has experience applying the different components of the operations model presented, it would be interesting to find a 5PL that would use all the components presented in an integrated way. The operations model presented applies to any similar ecosystem with minor adaptations.

This paper addresses operations models and digital transformation challenges for optimizing 5PL operators. It provides several opportunities and considerations for 5PL operators interested in improving their management and operations to cope with the growing challenges of today’s world.

The competitiveness and long-term performance of 5PL operators depend on selecting and carefully implementing their operations models. This paper emphasizes the importance of using advanced operations models.

The operations model derives from the author’s personal experiences in research and the innovative application of these models to logistics operators (DHL, UPS, Poste Italiane and others). This paper brings together academic and industry perspectives and operations models in an integrated business digital transformation. This paper defines an original optimal operations model for a 5PL operator and can add sustainable value to organizations and society. In doing so, it outlines different solution requirements, the critical success factors and the challenges for solutions and brings logistical performance objectives when implementing a digital business transformation.

The purpose of this study is to investigate how Industry 4.0 (IR 4.0) operates within the context of the post-COVID-19 environment and its impact on the economic, environmental and social sustainability of the manufacturing industry in a developing economy. By delving into this subject, the authors aim to understand the mechanisms through which IR 4.0 influences various facets of sustainability within the manufacturing sector.

A cross-sectional research design is used using purposive sampling and hypotheses were developed based on seminal theories and literature. Data was collected from 191 Malaysian manufacturing firms that use IR 4.0 technologies. The partial least squares structural equation modeling technique was used to explore how post-COVID uncertainty environment impacts manufacturing sustainability through IR 4.0 adoption.

During the highly uncertain era of the post-COVID-19 pandemic, the implementation of IR 4.0 adoption has had a favorable effect on the manufacturing industry, enhancing process efficiency, automation and data granularity. However, it is worth noting that automation does not significantly contribute to environmental sustainability and data granularity does not have a noteworthy impact on economic sustainability. On the other hand, process efficiency has a positive and significant influence on all three dimensions of sustainability. Moreover, data granularity positively affects environmental sustainability, whereas automation positively impacts both social and economic sustainability.

This study emphasizes the importance of policy interventions to harness the transformative power of IR 4.0 and address the identified concerns. In addition, the findings offer valuable insights for mid-level operational managers, enabling them to actively participate in the creation of sustainable policies in partnership with top management. It is expected that these actions, which involve making necessary adjustments in the manufacturing process, will yield tangible outcomes for sustainable development.

This study offers valuable insights into the relationship between the uncertain post-COVID-19 environment, referred to as hyper-uncertainty and the adoption of IR 4.0 in the context of manufacturing sustainability.

Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general overview of the academic landscape concerning PPP.

To offer a nuanced perspective, the study adopts the Latent Dirichlet Allocation (LDA) methodology to meticulously analyse 3,057 journal articles, mapping out the thematic contours within the PPP domain.

The analysis highlights PPP's pivotal role in harmonising public policy goals with private sector agility, notably in areas like disaster-ready sustainable infrastructure and addressing rapid urbanisation challenges. The emphasis within the literature on financial, risk, and performance aspects accentuates the complexities inherent in financing PPP and the critical need for practical evaluation tools. An emerging focus on healthcare within PPP indicates potential for more insightful research, especially amid ongoing global health crises.

This study pioneers the application of LDA for an all-encompassing examination of PPP-related academic works, presenting unique theoretical and practical insights into the diverse facets of PPP.

This study aims to investigate whether there are disparities in research and development (R&D) internationalization between latecomers from economy-level technological disparities and firms with ownership-specific technological capability differences in the wind turbine industry.

Employing econometric analysis based on patent indicators, the authors examine the patent data assigned by the United States Patent and Trademark Office (USPTO) to the technologically advanced economy and the technologically emerging economy.

This study finds that latecomers from technologically advanced economies behave with no difference from early leaders in terms of international co-invention (INCO) but do show differences in another indicator – native ownership of foreign inventors (NOFIs). Additionally, latecomers from economy-level technological disparity show significant differences both in both INCO and NOFI. These results indicate that the latecomers from technologically advanced economies not only possess the nature of latecomers which motivates them to seek knowledge from foreign economies but also benefit from their advanced home base, thereby prompting them to internationalize and access cost-effective R&D resources. Moreover, the results demonstrate that latecomers from technologically emerging economies are more prone to engage in R&D internationalization to augment their own home base compared with firms from advanced economy.

This study extends the literature on R&D internationalization by introducing novel perspectives. It distinguishes some apparent distinctions of the tendency of R&D internationalization between latecomers under economy-level technological disparity as well as firms from ownership-specific technological capabilities differences. Additionally, this study disaggregates R&D internationalization into twin key dimensions: INCO and NOFI. These findings allow for a comprehensive understanding of the differences in the firm's R&D internationalization under economy-level technological disparities and ownership-specific technological differences. These findings offer valuable insights for decision-makers in navigating global innovation activities by highlighting the diverse economy-level technological advantages as well as ownership-specific advantages.