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The ability of a business to outperform its rivals is known as its competitive edge, and it presents special difficulties in the context of the “digital revolution,” or the fourth industrial revolution. To obtain a competitive edge in the startup operations 4.0 era, this study aims to examine the organizational, technological and competence-related challenges presented by Industry 4.0. It does this by concentrating on the tools, competencies, methods, approaches, tools and strategies that are crucial. Using the Total Interpretive Structural Modeling (TISM) technique, the goal is to find, analyze and classify enablers for startup operations 4.0.

A closed-ended questionnaire and planned interviews were used in the data collection process. In startup operations 4.0, the cross-impact matrix multiplication applied to classification method is used to rank and categorize competitive advantage factors, whereas the TISM technique is used to analyze how components interact.

The study highlights the critical significance of the “Internet of Things (IoT),” “information technologies,” “technological platforms,” “employee empowerment,” “augmented reality (AR)” and “operational technologies” in its identification of 12 enablers for startup operations 4.0.

The main focus of the study is on the variables that affect startup operations 4.0’s competitive advantage.

Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research.

Large businesses have been profoundly impacted by Industry 4.0 principles; however, startup operations 4.0’s competitive advantage has not received as much attention. This paper offers a fresh take on the concept of competitive advantage in startup operations 4.0 research.

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

The need to improve sustainable construction with the appropriate technology adoption in the fourth and fifth industrial revolutions cannot be overemphasized. This study modelled the adoption of Internet of things (IoT) technologies in the construction industry to improve sustainable construction. Consequently, the study would assist construction stakeholders and policymakers in achieving sustainable construction through concerted efforts toward improving IoT adoption.

The study obtained the IoT technologies and the challenges of IoT adoption in the construction industry through a literature review. Subsequently, the awareness (knowledge of the existence and uses) of IoT technologies, the significance of the challenges and the level of adoption of the IoT technologies were tested on construction stakeholders in Kigali with a structured questionnaire. Consequently, a structural equation model of IoT adoption was developed.

The structural equation model indicates the relationship between the awareness, challenges and adoption of IoT technologies. It equally describes the effect sizes of the awareness and challenges of IoT on the adoption of IoT technologies.

This study is beneficial to construction stakeholders as it portrays the exclusive impacts of the awareness and the challenges of IoT technologies on the adoption of IoT. The study also benefits the government and policymakers as it provides a basis for intensifying efforts to create awareness and mitigate the challenges of IoT adoption for sustainable construction. The study also provides a basis for future studies on IoT adoption in the construction industry.

There are several studies on the adoption of IoT. There is however scarcity of studies on how the awareness and the challenges of IoT technologies impact the adoption of IoT in the construction industry. Thus, this study bridges the gap by modelling the adoption of IoT technologies for improved sustainable construction.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

This paper aims to provide insight into the evolving relationship between humans and machines, understanding its multifaceted impact on our lifestyle and landscape in the past as well as in the present, with implications for the near future. It uses bibliometric analysis combined with a systematic literature review to identify themes, trace historical developments and offer a direction for future human–machine interactions (HMIs).

To provide thorough coverage of publications from the previous four decades, the first section presents a text-based cluster bibliometric analysis based on 305 articles from 2,293 initial papers in the Scopus and Web of Science databases produced between 1984 and 2022. The authors used VOS viewer software to identify the most prominent themes through cluster identification. This paper presents a systematic literature review of 63 qualified papers using the PRISMA framework.

Next, the systematic literature review and bibliometric analysis revealed four major historical themes and future directions. The results highlight four major research themes for the future: from Taylorism to advanced technologies; machine learning and innovation; Industry 4.0, Society 5.0 and cyber–physical system; and psychology and emotions.

There is growing anxiety among humankind that in the future, machines will overtake humans to replace them in various roles. The current study investigates the evolution of HMIs from their historical roots to Society 5.0, which is understood to be a human-centred society. It balances economic advancement with the resolution of social problems through a system that radically integrates cyberspace and physical space. This paper contributes to research and current limited knowledge by identifying relevant themes and offering scope for future research directions. A close look at the analysis posits that humans and machines complement each other in various roles. Machines reduce the mechanical work of human beings, bringing the elements of humanism and compassion to mechanical tasks. However, in the future, smart innovations may yield machines with unmatched dexterity and capability unthinkable today.

This paper attempts to explore the ambiguous and dynamic relationships between humans and machines. The present study combines systematic review and bibliometric analysis to identify prominent trends and themes. This provides a more robust and systematic encapsulation of this evolution and interaction, from Taylorism to Society 5.0. The principles of Taylorism are extended and redefined in the context of HMIs, especially advanced technologies.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

The technological and digital revolution has introduced important changes in the tourism industry. However, capturing the extent of the new tourism 4.0 paradigm is still difficult. This study aims to assess the dimensions related to the concepts of industry 4.0 in tourism and hospitality, tourism innovation and tourism ecosystem when considered simultaneously, and their role in promoting a new wave of competitiveness in the tourism industry.

A bibliometric study was conducted based on tourism 4.0, hotel 4.0, tourism innovation and tourism ecosystem using 120 eligible articles published between 2008 and 2021 from the Web of Science database.

This study demonstrated the advances in industry 4.0 in tourism and hospitality publications over 13 years and identified five interconnected dimensions: (1) knowledge transfer in tourism; (2) networking tourism innovation; (3) sources of tourism innovation; (4) smart tourism ecosystem and (5) innovation research in tourism. It was also concluded that tourism development should be a regional competence based on strategic networking and externalisation of regional knowledge flows.

This bibliometric review provides important implications and recommendations for several players of industry 4.0 in tourism and hospitality and policymakers. Not only did it make it possible to create a state of art, but also to categorise the existing interconnections between the dimensions of Tourism 4.0, Hotel 4.0, Tourism innovation and Tourism ecosystem to optimise its implementation and generate greater value. In addition, practical implications were inferred that improve the tourism sector’s competitiveness, helping strategic decision-making at the level of policymakers and actors in this sector.

Apart from state of the art, this bibliometric review made it possible to categorise the existing interconnections between the dimensions of tourism 4.0, hotel 4.0, tourism innovation and tourism ecosystem to optimise its implementation and generate greater value. Practical implications were inferred that improve the tourism sector’s competitiveness, helping strategic decision-making at the level of policymakers and several players in this sector.

This study addresses the existing literature gap in the interconnection of industry 4.0 with tourism and hospitality by describing the most relevant conceptual interconnections and setting practical implications for improving the competitiveness of the tourism industry. Furthermore, it integrates previous studies and outlines future lines of investigation.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

Considering the importance and the broad applications of the Fourth Industrial Revolution in various organizations and industries and enjoying the many benefits of this digital transformation framework, organizations need to measure their Industry 4.0 readiness as a starting point and take steps to achieve the strategic goals of Industry 4.0. This study aims to design a comprehensive and practical model that can determine Industry 4.0 readiness level, allowing organizations to implement and exploit technological constituents of this phenomenon.

A systematic literature review (SLR) methodology was used to evaluate and summarize a clear and comprehensive literature overview of Industry 4.0 readiness models and to certify the validity and transparency of the review process. After reviewing 71 articles and survey and then the consensus of Industry 4.0 experts, the 10 dimensions of the 4.0 Industry readiness model were finalized with their indicators having the most frequency in the published articles and models.

The application of the SLR to the development of the new Industry 4.0 readiness model which includes 10 dimensions and 37 indicators and can assess the Industry 4.0 readiness of firms and industries accurately and effectively.

An extensive review of the previous literature yielded the current Industry 4.0 readiness model. The comprehensiveness of this model leads to its wide application in different companies. Future research suggestions are presented at the end of the manuscript.

The concept of the Fourth Industrial Revolution and the application of its technologies are vague and complicated for many organizations and managers, while the need to implement the components and technologies of Industry 4.0 is essential to achieve organizational goals. The presented readiness model helps companies to measure their readiness to enter the Fourth Industrial Revolution and achieve long-term goals.

In this study, an attempt was made to examine the Industry 4.0 readiness models thoroughly and extensively and identify their different approaches. Finally, a comprehensive and multi-dimensional readiness model is presented to assess the position of organizations in order to enter Industry 4.0.