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In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

Augmented reality (AR) and virtual reality (VR) are increasingly recognized among technologies potentially driving the digital innovation of small and medium-sized enterprises (SMEs). Nevertheless, the implications of AR/VR adoption in innovation processes have yet to receive much attention to date, with the need to explore the issues facilitating a systematic implementation in the SME context. This study aims to investigate the possible innovation paths of SMEs as a result of AR/VR adoption.

The authors performed a multiple case study research involving six Italian SMEs in manufacturing and service sectors that are investing in AR and/or VR solutions and are digitally innovating thanks to these technologies.

AR/VR solutions lead to different types of innovation in SMEs, i.e. for innovating product or service offerings, business processes or even the business model, when AR/VR extends to the company business logic. SMEs demonstrate being able to leverage internal sources with the essential commitment of top management and low resistance of employees in all kinds of AR/VR-enabled innovations. Conversely, they involve different external innovation sources according to the type of innovation pursued. Organizational issues emerged as more relevant than technological issues.

Results contribute to the literature on digital transformation of SMEs and provide managerial guidance on innovation sources and organizational issues to be considered to effectively deploy AR/VR solutions into specific innovation paths.

This study explores the impact of emergent technologies in the innovation process along with multiple perspectives, degree of complexity, and strategic importance in the SME context.

This study aims to elaborate on the existing link between maintenance practices and the digital world while also highlighting any unaddressed potential for digital transformation in aircraft maintenance. Additionally, explore how digital technologies contribute to optimizing efficiency within the continuing airworthiness management (CAM) processes.

A literature review was performed to provide a precise review of the authority regulations on CAM processes and existing literature on digital transformation, including artificial intelligence, machine learning, neural network and big data in civil aircraft maintenance and continuing airworthiness processes. This method is used to organize, analyze and structure the body of literature to identify research gaps in the selected scope of the study.

The high position of digital technologies in preventive and predictive maintenance and the need for legislative development for using them in CAM are emphasized. Moreover, it is shown in which area of CAM scientific research has been performed regarding the application of frontier digital technologies. In addition, the gaps between maintenance practices and the digital world, along with the potential scopes of digital transformation which has not been well addressed, are identified. And finally, how digital technologies can effectively increase efficiency in CAM processes is discussed.

To the best of our knowledge, no study comprehensively determined the body of existing knowledge on the aspects of digitalization related to the field of continuing airworthiness management and aircraft maintenance. The results of this study provide a positive contribution to airlines, policymakers, manufacturers and maintenance organizations achieving additional benefits from the implementation of digital technologies in the CAM processes.

COVID-19 played a crucial role in the development and enlargement of learning via electronic media. Still, the recent fourth industrial revolution [Industry 4.0 (I4.0)] paved the road toward Education 4.0. In this regard, several research challenges arise, involving the preparation of gamification strategies in online learning environments. In this sense, this paper aims to investigate the relationship between technologies of I4.0 and gamification practices in online learning around the world. Specifically, to categorize the studies of the scientific literature in the area into knowledge domains and the mention of I4.0 technologies and to verify the relationship of these technologies with the different educational levels.

The preferred reporting items for systematic reviews and meta-analysis protocol was used as a research method with 130 papers included for full content analysis and obtained from the Web of Science.

The leading I4.0 technologies mentioned in the analyzed papers were simulation, Internet of Things and augmented/virtual reality, in this order. Although there are more mentioned technologies, the domain of knowledge to be applied and the educational level interfere in choosing these pillars. With this, the main findings of this relationship were exposed in a singular, modern, active, realist, technological framework to demonstrate how I4.0 relates to the practice of gamification in online educational environments.

To the best of the authors’ knowledge, this is the first study that brings together the relationship of gamification applied in e-learning with I4.0 technologies.

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.

This paper uses the complex proportionality assessment (COPRAS) method to examine the driving factors of Industry 4.0 (I4) technologies for lean implementation in small and medium-sized enterprises (SMEs).

Adopting I4 technology is imperative for SMEs seeking to maintain competitiveness within the manufacturing sector. A thorough understanding of the driving factors involved is required to support the implementation of I4. For this objective, the multi-criteria decision-making (MCDM) tool COPRAS was used to efficiently analyze and rank these driving elements based on their importance. These factors can help small and medium-sized firms (SMEs) prioritize their efforts and investments in I4 technologies for lean implementation.

This study evaluates and prioritizes the nine I4 factors according to the perceptions of SMEs. The ranking offers significant insights into the factors SMEs consider more accessible and effective when adopting I4 technologies.

The author's original contribution is to examine I4 driving factors for lean implementation in SMEs using COPRAS.

Company goals, behaviors and decision-making processes may differ depending on whether a given company decides to engage in the Industry 4.0 (I4.0) paradigm as a user or as a provider of I4.0-based solutions. This paper will consider this question in-depth by focusing on the extent to which the innovation ecosystem (IES) affects these two main strategies.

The authors' study aims to analyze the impact of a regional information and communication technology (ICT) ecosystem on the implementation of I4.0 at the company level by using an original survey of 123 companies that are already engaged in the implementation of I4.0 in the French region of Hauts-de-France and by employing two sets of logit models.

The authors' empirical study demonstrates the importance of an innovation ecosystem-based strategy for I4.0 technology provision. It reveals that engaging in R&D collaborative projects and developing links and complex relationships with heterogeneous actors within the IES positively affects the likelihood of a given firm deciding to implement I4.0 as a provider of I4.0-based solutions. This does not, however, affect the probability of a firm engaging in the I4.0 paradigm as a user of technologies and solutions.

From a policy standpoint, this study could encourage decision-makers to engage with I4.0 development by developing policies targeting the reinforcement of IES at a regional level. This could also help to accelerate the adoption of I4.0 technologies by manufacturing companies and foster the development of I4.0-based solutions through specific company-targeted policies. The authors' study supports the need for manufacturing company managers to evaluate and identify the best technological strategies related to the I4.0 paradigm that meet their specific needs.

The authors' study shows that the decision to engage in the I4.0 paradigm as providers of I4.0-based solutions is more likely to rely on an innovation ecosystem-based strategy, while the decision to engage in the I4.0 paradigm as users of I4.0-based solutions is more likely to rely on the company’s internal strategies, resources and demand-side benefits.

This chapter discussed the implementation of the digital twin (DT) idea into construction. Through the adoption of DTs into construction practices, construction professionals have been able to project an identical virtual concept of sections of the project execution right from the onset. In the introduction and discussing of its origin, the DT was further assessed about its applications in construction beneficial in enhancing project delivery. Other sections like barriers, drivers and benefits of the DT in construction summarised what this chapter represents in terms of discussing the new involvement of digital tools in construction execution, management and sustainability.

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.

The aim of this research is to enlighten the methodology model of Industrial Design Structure (IDeS) that integrates the internal and external customer feedback embodied both in methods of quality function deployment (QFD) and as basis of design for six sigma (DFSS) steps to systematically bring the information across the entire organization, saving overall product development time and resources.

The paper describes the state of the art enlightened to establish the disadvantages and challenges of other methods taken into consideration in the study like QFD and DFSS that, together with the need of companies to react fast to changes they need to straightforwardly implement product development information across all departments, leading to a mass customization infrastructure. Several application trials of this methodology have been cited.

The IDeS method has established to been able to integrate other well-known methodologies to gather technical specifications starting from voice of customers (VOCs) like QFD that served to canalize the generalist approach of define, measure, analyze, design and verify (DMADV) of DFSS in order to reach into a larger share of the organization and englobe by following the overall product design steps of an industrial project.

The research approach chosen for this document presents the concept of a methodology ought to operate most internal branches in a company driven by product design requirements and guidelines. Therefore, researchers are encouraged to develop further studies on the IDeS method are required in order to adapt this methodology to specific management tools that would help to ease information gathering for immediate analysis and modification.

The paper implicates that a need to interchange information systematically across all subdivisions in the organization, as brisk response to VOC reactions is needed to thrive in the market nowadays, leading to a fast product customization scene. However, the industry is heading into adopting an individual customer-centered product conceptualization ought to be driven by design as a key for individualizing an object. Afterward by taking this concept broadly and adopting it would lead to implement a company organization that would be directly affected by the customer's input.

The methodology described aims to enable organizations to portray fast and accurate product prototyping, by exploiting technologies from Industry 4.0.

This concept proposes a method to canalize the implementation of DFSS by using the DMADV approach, whilst assessing the challenges of adaptation and keeping up with cultural pace that impacts the behavior of buying and consumption and moreover implementing a seamless communication within all departments in the organization to share the development progress and change requests by using similar information technology tools. This would imply important savings in resources, whilst delivering quality products to the society.