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Despite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.

A systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.

The study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.

The findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.

This study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.

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 paper aims to present a systematic literature review to analyze interrelated enablers of Industry 4.0 for implementation. Industry 4.0 is an integrated manufacturing strategy embedded with disruptive technologies. Adapting these technologies with the present industrial scenario is dependent on understanding the dynamics of various critical enablers in the existing literature. In this paper, an effort has been taken to validate and reinforce these enablers by experts in the field of Industry 4.0 for implementation.

A mixed-methodology is designed in this paper. A text mining approach with an expert’s linguistic assessment method is planned to discover the enablers from literature 2010 to 2019. The most critical enablers and their dependencies on other enablers are studied by using correlation analysis.

The research explores the power driving enablers in three groups: technology, features and requirements for implementing Industry 4.0 in the existing factory. In each group, a high degree of associated and dependent enablers is fragmented in detail.

This paper will benefit the research communities and practitioners to understand the significance of an integrated ecosystem of Industry 4.0 technologies, features and requirements for implementation.

The text mining approach integrated with expert’s linguistic assessment to explore the pairwise relationship among the enablers using word correlation is a novel approach in this paper. Moreover, to best of the authors’ knowledge, this is the first-ever attempt to conduct a structured literature review combined with text analysis and linguistic assessment to identify the enablers of Industry 4.0 for implementation.

Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.

The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.

This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.

This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.

By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.

This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.

The paper aims to contribute to a better understanding of the drivers for the use of Industry 4.0 technologies by investigating (1) what motivates companies to consider using I4 technologies and (2) what enables (or hinders) the intention to use I4 technologies to translate into their actual use.

The study uses survey data collected from a sample of export-oriented manufacturing companies with more than 10 employees. Final analysis is conducted on 124 companies.

The results show that companies are proactively approaching I4. Only efficiency motives and expected competitive advantage have a positive effect on the intention to use I4 technologies, which in turn positively influences their actual use. The external, legitimacy-based, motives do not play a significant role in explaining the intention to use. With respect to I4 technology enablers, employee competency positively moderates and availability of finance negatively moderates the relationship between intention to use and actual use.

The work extends the existing knowledge base on I4 technology drivers in companies that are not major global trendsetters but are heavily embedded in the value chains of companies from the most industrially developed economies. The study is limited to manufacturing companies in a small European economy and should be retested in other contexts.

The study can help managers implement I4 technologies in their companies more successfully.

We take a novel research approach by proposing a framework that clearly distinguishes between motives and enablers for the use of I4 technologies.

The purpose of this study is two-fold. First, to identify and encapsulate the enablers that can facilitate technology integration in higher education and second, to understand and analyze the interplay between technology agility enablers.

The study used the Total Interpretive Structural Modeling (TISM) approach to construct a theoretical model of the technology agility enablers in higher education and MICMAC analysis for ranking and segregating the enablers based on their dependence power into four categories: Autonomous, Dependent, Linkage and Independent.

The study helped identify eight technology agility enablers, with the Covid-19 pandemic as the most significant enabler. The Covid-19 pandemic has catalyzed the diffusion of technology across the education sector in India, including tertiary higher education. The study revealed government initiatives and institutional commitment as other enablers that can promote technology agility in higher education.

The results of this study would assist the policymakers and management of universities and colleges in understanding the important enablers that can facilitate technology integration in higher education.

Research in the past on technology adoption in higher education has looked into each enabler in isolation. This research provides a comprehensive view of the enablers and has attempted to establish a multidirectional interplay between the enablers.

High rate of accidents continue to plague the construction industry. The advancements in safety technologies can ameliorate construction health and safety (H&S). This paper aims to explore the use of emerging technologies as an effective solution for improving safety in construction projects.

Following a detailed literature review, a questionnaire survey was developed encompassing ten technologies for safety management and ten safety enablers using technologies in construction. A total of 133 responses were gathered from Malaysian construction practitioners. The collected quantitative data were subjected to descriptive and inferential statistical analyses to determine the meaningful relationships between the variables.

Findings revealed that the most effective emerging technologies for safety management are: building information modelling (BIM), wearable safety technologies and robotics and automation (R&A). The leading safety enablers are related to improve hazard identification, reinforce safety planning, enhance safety inspection, enhance safety monitoring and supervision and raise safety awareness.

Safety is immensely essential in transforming the construction industry into a robustly developed industry with high safety and quality standards. The adoption of safety technologies in construction projects can drive the industry towards the path of Construction 4.0.

The construction industry has historically been slow to adopt new technology. This study contributes to advancing the body of knowledge in the area of incorporating emerging technologies to further construction safety science and management in the context of the developing world. By taking cognisance of the pertinent emerging technologies for safety management and the safety enablers involved, construction safety can be enhanced using integrated technological solutions.

This study focuses on the adoption of wearable technologies in a context where care-providing organizations can offer, in collaboration with caregivers, better care. Drawing on dual-factor theory and from the caregiver perspective, this study identifies and examines factors of technology adoption in four developing countries.

This study was undertaken using a quantitative approach. A survey was distributed among 1,013 caregivers in four developing countries in Asia including Iran, Azerbaijan, Turkmenistan and Iraq and collected quantitative data for model validation and hypotheses analysis. Building on the technology adoption literature, we identified six constructs that impact the behavioral intention of caregivers to use wearable technologies in aged care-providing organizations.

Our dual-factor model was successfully validated, and all hypotheses were supported. However, different results were found in the selected countries within the cross-country analysis.

This study has significant implications for the study of emerging technologies in aged care service operations. It provides a theoretical framework that may be adapted for future research, enabling practitioners in aged care to better understand the crucial role of technology adoption in service operations. Less attention was paid to the adoption of wearable technologies in aged care, particularly in developing countries, where healthcare services in aged care impose heavy costs on care providers.

In the modern digital age technologies like Industry 4.0 has revolutionized the manufacturing sector. There are many economic and technological advantages of digitalization. Along with economic benefits, manufacturing enterprises especially small and medium enterprises (SMEs) need to take advantage of digitalization in strengthening their social performance. Observing the importance of social performance of Indian SMEs and availability of limited research in this direction, the current study has done a holistic analysis of social performance enablers.

A systematic literature review with a series of personal interviews of experts has been conducted to identify the enablers of social performance and supportive digital technologies. A fuzzy decision-making trial and evaluation laboratory (DEMATEL) approach has been applied to find the degree of influence and interrelation between enablers. Sensitivity analysis is also performed to validate the results obtained.

Authors observed that policies of corporate and social responsibility, support by top management, awareness of social performance issues, and ethical practices and collaboration amongst supply chain members are leading causing enablers of social performance. Preparedness for the uncertainty of pandemics, improved work conditions and ergonomics, green practices, improvement in global business and improved living standards of employees and their families are leading the effect group of enablers. Further authors also observed that social media, information and communication technologies (ICT), websites, smart surveillance, e-mails and cloud computing are few supportive digital technologies of social performance issues.

SMEs all over the globe are passing through a transition due to digitalization and influence of pandemics. The finding of current study highlights the importance of strategic management of social performance enablers. Since the research is very limited in the social performance area, especially in Indian SMEs, this study makes a notable contribution to the literature too.

Novelty of this study is that social performance enablers of Indian SMEs in the digital era have been analysed holistically. The content of this research is the original work of the authors and has not been submitted for any other publication.

This paper combines prospect theory (PT) and the technology acceptance model (TAM) proposing that technology anxiety (TA), risk averseness (RA), concern and resistance to use inhibit technology acceptance, while trust, social influence (SI) and compatibility are enablers to technology acceptance, particularly in the context of consumer adoption of retail technologies during crises.

A review of PT and TAM literature was conducted to develop a model which considers the impact of inhibitors and enablers on retail technology acceptance.

This investigation establishes a theoretical model of mid-crisis retail technology adoption behavior that can be tested quantitatively. Several propositions regarding relationships between proposed inhibitors, enablers and TAM are presented, as well as implications for future research.

This investigation further integrates PT and TAM, proposing that PT is an appropriate framework to investigate inhibitors and enablers of retail technology acceptance during crises.