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The paper aims to apply social practice theory to clarify the process of innovation design and delivery from one successful digital innovation: the building information modelling (BIM) risk library. The paper clarifies the practices surrounding construction innovation and provides a schema useful for practitioners and technology designers through a social practice analysis.

The paper applies Schatzki's “organisation of practice” concepts to a construction project innovation to clarify how the practice of innovation revolves around understandings, rules and teleoaffectivities (emotive behaviours). Sources for the study include notes from meetings, workshops with experts and the shared artefacts of innovation.

The practice of innovation design and delivery are clarified through a social practice analysis: a distinct “field of practice” and a “schema” of generalisable prescriptions and preferences for innovation delivery being presented.

The paper informs the practice and process of innovation design and delivery; the insights clarify how collective understandings and rules of use evolve over time, becoming formalised into contracts, agreements and workplans. Practically, processes whereby innovation “sayings” evolve into innovation “doings” are clarified: a schema detailing prescriptions and preferences of practitioners and developers being presented.

The social practice analysis of one successful construction innovation is an original contribution to the body of knowledge, adding a level of detail regarding innovation design and delivery often missing from reported research.

This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.

The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.

Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.

An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

Along their journey to achieve exponential growth, startups must process a vast amount of information and make quick decisions, reevaluate and adjust strategies and simultaneously redesign their organization along with the venture lifecycle. This paper delineates the evolution of startups' organizational design and identifies the influencing factors in every phase of the lifecycle.

This study adopts an explorative qualitative approach using a multiple case study methodology for six Indonesian startups. Indonesia is chosen as an emerging country in Southeast Asia with tremendous growth in digital startup businesses.

The research findings suggest that, as they experience exponential growth, startups strive to manage the tension between being structured and being flexible and hence remain innovative by combining management-centric and employee-centric approaches. In particular, this study identified three main factors that potentially influence the evolution of startups' organizational design: founders, investors and the characteristics of business and market.

The present study focuses mainly on Indonesian digital startups and does not fully explain how the influencing factors work in each phase of the venture journey.

This study offers practical contributions for startups pursuing business growth by focusing on the importance of balancing the tension between structured and flexible organizational design and placing more attention on founders, investors and business-market characteristics.

This empirical study is among the first to delineate nuances of organizational design evolution during the startup lifecycle by adopting an explorative qualitative method.

This study aims to explore how firms can enhance their innovation processes by effectively utilizing external knowledge and employing digital technologies. Specifically, it emphasizes the role of absorptive capacity (ACAP) in external knowledge acquisition and assimilation (potential ACAP), as well as transformation and exploitation (realized ACAP), highlighting the necessity of equipping firms with digital technologies to support ACAP activities.

To achieve the research purpose, we conducted a structured literature review of academic papers sourced from Scopus-Elsevier.

The key findings encompass the identification of common digital technologies supporting ACAP and explore how these technologies contribute to knowledge acquisition, assimilation, transformation and exploitation. The main results show that social media and online communities are the most studied technologies in relation to ACAP activities. Research predominantly centres on potential ACAP – with acquisition activity more studied than assimilation – rather than realized ACAP – with only social media and online communities demonstrating full support for transformation and exploitation activities.

This research represents a pioneering joint study of ACAP and digital technologies, advancing understanding beyond organizational perspectives and expanding open innovation literature by integrating ACAP role in technology collaborations. A call for qualitative investigations into the relationship between digital technologies and ACAP emerged.

The findings offer valuable guidance to innovation managers, aiding them in selecting appropriate digital technologies to strengthen ACAP activities.

This work’s uniqueness lies in bridging the gaps between open innovation, ACAP and digital technologies, which are often studied in isolation.

The aim of this paper is to explore how multi-national corporations (MNCs) can effectively adopt artificial intelligence (AI) into their talent acquisition (TA) practices. While the potential of AI to address emerging challenges, such as talent shortages and applicant surges in specific regions, has been anecdotally highlighted, there is limited empirical evidence regarding its effective deployment and adoption in TA. As a result, this paper endeavors to develop a theoretical model that delineates the motives, barriers, procedural steps and critical factors that can aid in the effective adoption of AI in TA within MNCs.

Given the scant empirical literature on our research objective, we utilized a qualitative methodology, encompassing a multiple-case study (consisting of 19 cases across seven industries) and a grounded theory approach.

Our proposed framework, termed the Framework on Effective Adoption of AI in TA, contextualizes the motives, barriers, procedural steps and critical success factors essential for the effective adoption of AI in TA.

This paper contributes to literature on effective adoption of AI in TA and adoption theory.

Additionally, it provides guidance to TA managers seeking effective AI implementation and adoption strategies, especially in the face of emerging challenges.

To the best of the authors' knowledge, this study is unparalleled, being both grounded in theory and based on an expansive dataset that spans firms from various regions and industries. The research delves deeply into corporations' underlying motives and processes concerning the effective adoption of AI in TA.

This study sought to develop an aggregated assessment of the literature on the resource-based view (RBV). The main aim was to map the RBV field based on a systematic literature review (SLR) of 226 academic articles published in refereed journals from 1994 to 2022.

Two bibliometric analysis methods were used: bibliographic coupling and co-citation. These measures are complementary because bibliographic coupling is retrospective in nature and co-citation is forward-looking.

The analysis identified the most influential studies, top-cited articles and journals and six major thematic clusters: RBV, customer orientation and alliance portfolio, resource-based theory, firm performance, entrepreneurial orientation (EO) and dynamic capabilities.

This research was based on a combination of bibliographic coupling and co-citation analysis. The results provide a better understanding of the RBV field’s intellectual structure, which reveals potential new lines of future research.

This study social based on cognitive theory (SCT), aims to better understand how transformational leadership affects team-level knowledge sharing and absorptive ability in the construction industry. It also examines the moderating influence of the AI-based virtual assistant on the indirect relationship between transformational leadership and team innovation through knowledge sharing and absorptive ability at the team level.

This study used a simple random sample approach to gather data from several small and medium-sized construction firms in Anhui Province, China. A total of 407 respondents, including 89 site engineers and 321 team members, provided their responses on a five-point Likert scale questionnaire.

The findings showed that AI-based virtual assistants significantly moderated the direct and indirect association between transformational leadership and knowledge sharing, and subsequently with team innovation. Unexpectedly, the findings showed that AI-based virtual assistant did not moderate the direct relationship between transformational leadership and team-level absorptive capacity.

This study adds a fresh perspective to the literature on construction management by examining team innovation driven by transformational leadership through an underlying mechanism. It is unique in that it uses the team adaptation theory to investigate the understudied relationship between transformational leadership and team innovation in the construction industry.

The dearth of leadership competencies to transform traditional industries to Industry 4.0 is a barrier to global production. This study explains the deficiencies in leadership competencies that hinder the transformation of traditional industries to Industry 4.0.

Leadership was explained into transactional leadership, digital leadership and Leadership 4.0. Then, the network of relationships between these leadership constructs was plotted in a path diagram to learn the mediating effect of digital leadership.

The results indicate that a lack of digital competencies to coordinate tasks, share information and solve problems in a digitalized environment is the barrier to the transformation.

The findings can be used in human resources (HR) management. In addition, the findings provide evidence to present the contingency theory as a universal theory of leadership.

The study is the first to assess the mediating effect of digital leadership on transactional leadership to explain the changes to strategic leadership due to the emergence of Leadership 4.0.

While previous research has demonstrated the positive effects of digital business strategies on operational efficiency, financial performance and value creation, little is known about how such strategies influence innovation performance. To address the gap, this paper aims to investigate the impact of a firm’s digital business strategy on its innovation performance.

Drawing on the dynamic capability view, this study examines the mechanism through which a digital business strategy affects innovation performance. Data were collected from 215 firms in China and analyzed using multiple regression and structural equation modeling.

The empirical analysis reveals that a firm’s digital business strategy has positive impacts on both product and process innovation performance. These impacts are partially mediated by knowledge-based dynamic capability. Additionally, a firm’s digital business strategy interacts positively with its entrepreneurial orientation in facilitating knowledge-based dynamic capability. Moreover, market turbulence enhances the strength of this interaction effect. Therefore, entrepreneurial-oriented firms operating in turbulent markets can benefit more from digital business strategies to enhance their knowledge-based dynamic capabilities and consequently improve their innovation performance.

This study contributes to the understanding of how a firm’s digital business strategy interacts with entrepreneurial orientation in turbulent markets to shape knowledge-based dynamic capability, which in turn enhances the firm’s innovation performance.

Digital transformation (DT) is among the vital factors contributing to innovation ambidexterity, especially for advanced manufacturing firms (AMFs). However, the empirical studies on the relationship between DT and innovation ambidexterity in AMFs from the perspective of knowledge management are inadequate. Therefore, this study aims to systematically analyze the impact of DT on innovation ambidexterity and its mechanism of action.

This study selects 254 listed firms within the ten key areas of “Made in China 2025,” as they occupy a key position in China’s advanced manufacturing system. Based on the knowledge-based view (KBV) and contingency theory, it constructs a model of the influence mechanism of DT on innovation ambidexterity.

The results show that the DT of AMFs positively influence innovation ambidexterity. External pressure from environmental turbulence enhances the positive relationship between DT and innovation ambidexterity, demonstrating the “resilience effect,” external knowledge search (EKS) and broadening the knowledge base mediating roles between them, highlighting the “accumulation effect.”

By identifying this mediation mechanism of DT and innovation ambidexterity, this study provides new ideas for path research on the KBV. Moreover, this study explores the triggering effect of market environmental turbulence on the DT of firms. It reveals the boundary conditions of DT acting on innovation ambidexterity, expands the research perspective on organizational resilience and enriches the theory of power change.