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Circularity has acted as an essential phenomenon for small and medium enterprises (SMEs) in emerging economies, pressuring entrepreneurs to its adoption in their businesses. During the adoption and implementation of circularity, entrepreneurs or circular entrepreneurs (to be precise) are facing various challenges to its effective functioning. However, the scholarly literature has offered limited research into this phenomenon. Thus, the purpose of this research is to identify the various barriers and sub-barriers for circular entrepreneurs to adopt circularity in SMEs of emerging economies.

A combined qualitative and quantitative approach was employed to achieve the objectives of the study. In the first stage, through an extensive literature review, a list of barriers was identified and in the second stage, a deductive approach was employed to finalize the barriers. Finally, Best-Worst Method (BWM), a multi-criteria decision-making (MCDM) method, was used to analyse the significant importance of the barriers.

The findings of the study suggested the “financial barrier” as the first-ranked barrier in the adoption of Circular Business Models (CBMs), followed by the “regulatory and operational barrier” as the top second and third barriers. In terms of sub-barriers, “lack of access to funding and capital” has been identified as the top sub-barrier in the adoption of CBM, followed by “excessive regulations and red tape” and “challenges due to ambiguity of the concept”.

To transition from a circular to a linear business approach considerably quicker and smoother, entrepreneurs may utilize the findings of this study as a blueprint for the steps to overcome the barriers in a linear to a circular transition.

This research differentiates from other studies due to solicited input directly from the people who are most familiar with the challenges of making the transition from linear to CBM, i.e. the entrepreneurs themselves.

The purpose of this paper is to investigate, from a thorough review of the literature, the role of metaverse-based quality 4.0 (MV-based Q4.0) in achieving manufacturing resilience (MFGRES). Based on a categorization of MV-based Q4.0 enabler technologies and MFGRES antecedents, the paper provides a conceptual framework depicting the relationship between both areas while exploring existing knowledge in current literature.

The paper is structured as a comprehensive systematic literature review (SLR) at the intersection of MV-based Q4.0 and MFGRES fields. From the Scopus database up to 2023, a final sample of 182 papers is selected based on the inclusion/exclusion criteria that shape the knowledge base of the research.

In light of the classification of reviewed papers, the findings show that artificial intelligence is especially well-suited to enhancing MFGRES. Transparency and flexibility are the resilience enablers that gain most from the implementation of MV-based Q4.0. Through analysis and synthesis of the literature, the study reveals the lack of an integrated approach combining both MV-based Q4.0 and MFGRES. This is particularly clear during disruptions.

This study has a significant impact on managers and businesses. It also advances knowledge of the importance of MV-based Q4.0 in achieving MFGRES and gaining its full rewards.

This paper makes significant recommendations for academics, particularly those who are interested in the metaverse concept within MFGRES. The study also helps managers by illuminating a key area to concentrate on for the improvement of MFGRES within their organizations. In light of this, future research directions are suggested.

The literature that is presently available on sustainable supply chain management (SSCM) combining optimization and industry 4.0 techniques falls short in its depictions of the recent developments, budding pertinent areas and the importance of SSCM in the growth of industrial economies around the world. This article's main objective is to analyze current trends, highlight the latest initiatives and perform a meta-analysis of the literature that is currently accessible in the SSCM area with a special focus on optimization and industry 4.0 techniques. The paper also proposes a conceptual framework that will assist in illuminating how the ideas of optimization and industry 4.0 may contribute to realizing sustainability in supply chains.

The proposed study systematically reviews 85 research publications published between 2010 and 2022 in referenced peer-reviewed journals in diverse fields, including engineering, business and management, services and healthcare. Numerous categories are considered throughout the examination of the literature, including year-wise publications, prominent journals, type of research design, concerned industry and research technique used.

The study demonstrates a deeper comprehension of the literature in the field and its evolution throughout numerous industry sectors, which is helpful for both practitioners and academics. The results from the content analysis highlight various future research opportunities in the domain.

This is one of the first research articles that have attempted to establish, analyze and highlight the current trends and initiatives in the SSCM domain from an optimization and industry 4.0 techniques viewpoint. The cluster-based future research propositions also enhance the novelty of the study.

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

Over the next decade, humanity is going to face big environmental problems, and considering these serious issues, businesses are adopting environmentally responsible practices. To put forward specific measures to achieve a more prosperous environmental future, this study aims to develop an environment-based perspective framework by integrating the Internet of Things (IoT) technology into a sustainable automotive supply chain (SASC).

The study presents a conceptual environmental framework – based on 29 factors constituting four stakeholders' rectifications – that holistically assess the SASC operations as part of the ReSOLVE model utilizing IoT. Then, experts from the SASC, IoT and sustainability areas participated in two rigorous rounds of a Delphi study to validate the framework.

The results indicate that the conceptual environmental framework proposed would help companies enhance the connectivity between major IoT tools in SASC, which would help develop congruent strategies for inducing sustainable growth.

This study adds value to existing knowledge on SASC sustainability and digitalization in the context where the SASC is under enormous pressure, competitiveness and increased variability.

The study aims to highlight the barriers faced by the entrepreneurs toward achieving sustainability in business and innovation cultivation by offering solutions for academicians, practitioners and policymakers. The study uses the resource-based view (RBV) theory to discuss how an organization’s resources and capabilities influence the competitive ambience and barriers faced by entrepreneurs.

The present research uses grey-causal modelling (GSC) to analyse the barriers against successful entrepreneurship.

The research focuses on the usefulness of dynamic capabilities, managing and cooperating resources in the entrepreneurship setting. The paper highlights the importance of resource gathering and nurturing as a method to combat scarcity. This research further identifies that financial limitations, regulatory obstacles, challenges to sourcing qualified labour, poor infrastructure and technology, limited mentorship opportunities, lack of scalability, low initial cost barriers in product development and risk-averse attitudes are the major factors hindering entrepreneurs from obtaining sustainable business and innovation.

The contribution of this research to the literature is that it assesses RBV theory within the realm of entrepreneurship, providing a different perspective on resources and capabilities as well as the challenges faced by entrepreneurs. The systematic approach to the analysis and prioritization of various barriers is innovative, and it adds knowledge in this area.

The rise of the coronavirus disease 2019 (COVID-19) pandemic has enabled researchers and industry professionals to reinvent their strategies for basic economic understanding. Two years after the outbreak of the pandemic, businesses are now trying to adapt to the impact it has brought, hoping to receive support as it did in the past. However, before this feat can be accomplished, it is imperative to understand the recovery hurdles created by the pandemic. This research aims to fill the literature gaps by examining the challenges during recovery within the creative small and medium-sized enterprise (SME) industry, as there are few relevant studies that focus on this field.

Through a methodical bibliometric literature review and network analysis, the paper intends to critically explore relevant recovery challenges within the field while providing answers to the appropriate research questions. A total of 43 articles were selected for an in-depth review. Using the analysis from the selected articles as a guide, a framework was developed to address the recovery challenges alongside the recommended propositions.

The findings from this paper suggest that a lack of synergy among four major categories (governmental, supply chain, organizational and stakeholders) contributes to recovery challenges within the field of research.

The review also offers clarification in understanding the current and upcoming trends within the creative industry, SMEs and COVID-19. This paper can thus help researchers, industry practitioners and managers discover and analyze the recovery challenges brought about by the COVID-19 pandemic.

Successful digital transformation requires a change in organisational structures, processes, capabilities and competencies. Digital transformation research is more influenced by the technology adaptation model and hence focuses on people's attitudes, behaviour and abilities. Recently, employee agility has attracted attention in the context of technology adoption and Industry 4.0. The current research explores the relationship between employee agility and digital technology adoption in the context of digital transformation by adopting the systematic literature review method.

Following the attitude–ability-behaviour–outcome framework, the research explored the specific agile ability, attitude and behaviour characteristics useful for digital transformation. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework consisting of (1) initiation, (2) screening, (3) evaluation and (4) confirming inclusion (Ambika et al., 2023), the study identified 19 papers from SCOPUS indexed journals.

The study result found that agile attitude characteristics such as collaborative mindset, computer self-efficacy, ambiguity aversiveness, etc. are influencing the digital transformation process. Agile abilities like basic computer knowledge, previous technical experience, cognitive abilities, innovation capability, digital competence training and supporting proper knowledge management practices also influence digital transformation. Finally, agile behaviour such as relationship building, knowledge-sharing behaviour, promoting values of learning, risk-taking and experimenting, rewarding innovativeness and customer-centric innovation and displaying adaptability, resilience and commitment to change, etc. are found to drive digital transformation.

Research on workforce agility and digital transformation is scarce. The current study contributes to benchmarking research by exploring specific agile attitudes, abilities and behaviour characteristics relevant to digital transformation, especially in the era of Industry 4.0.

Sustainability performances (SPs) are the most crucial performances for an organisation in today's world, and they can be measured by economic, social, and environmental metrics. Previous research has not been clear on the role of total productive maintenance (TPM) in the context of sustainability, which motivates the authors to investigate the relationship between TPM and various SPs of the manufacturing firm. Therefore, current research investigates the relationship between TPM and the overall sustainability of the manufacturing firm from the perspective of resource-based view (RBV) theory.

The current study proposed, tested and validated a conceptual framework using partial least squares structural equation modelling (PLS-SEM). A total of 326 responses were received to validate the conceptual framework in smartsPLS 3.0 software.

The research outcomes indicate that TPM considerably impacts a manufacturing firm's economic, environmental and social performance.

This research demonstrates that outstanding shop floor behaviour, such as TPM, can become an important asset to offer competitive advantages in a manufacturing firm. Similarly, TPM might serve as a roadmap for leveraging overall sustainability for manufacturing companies. The study indicates the establishment of a sustainability-oriented training protocol while practising TPM.

No past investigation indicates that a shop floor activity like TPM could be used as an input to offer sustainability in a single index for a manufacturing firm from the perception of RBV theory.

The purpose of this paper spans twofold. Firstly, to investigate Human Resource Management practices (HRMP) adopted by organisations during the pandemic. Secondly, to bundle similar HRMP into Human Resource Management (HRM) bundles that provided unhindered organisational support to employees during the crisis.

The authors conducted 39 in-depth interviews across industries using a semi-structured interview schedule. Thereafter, the authors transcribed the interviews verbatim and analysed them thematically using MAXQDA 2021.

The study identifies effective practices during times of uncertainty and how soft HRM practices helped organisations survive during a crisis. When bundled together, these practices enabled organisations to continue operations during the pandemic, keeping their employees engaged and motivated.

Based on the learnings from the COVID-19 pandemic, the study provides a toolkit of HRMP bundles that organisations can adopt for future crisis management, enhancing the organisations’ absorptive capacity.

The study investigates the practices incorporated during COVID-19, leading to the identification of soft HRM bundles. The study adds value to the existing domain of HRM by including a unique set of soft HRMP bundles that have not been discussed in earlier studies and could be of high utility to organisations during the crisis.