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Digitalisation, which involves the use of digital technologies in transforming an organisation’s activities, transcends just the acquiring of emerging digital tools. Having the right people to drive the implementation of these technologies and attaining strategic organisational goals is essential. While most studies have focused on the use of emerging technologies in the construction industry, less attention has been given to the ‘people’ dimension. Therefore, this study aims to assess the people-related features needed for construction digitalisation.

The study adopted pragmatic thinking using a mixed-method approach. A Delphi was used to achieve the qualitative aspect of the research, while a questionnaire survey conducted among 222 construction professionals was used to achieve the quantitative aspect. The data gathered were analysed using frequency, percentage, mean item score, Kruskal–Wallis H test, exploratory factor analysis and confirmatory factor analysis.

Based on acceptable reliability, validity and model fit indices, the study found that the people-related factors needed for construction digitalisation can be grouped into technical capability of personnel, attracting and retaining digital talent and organisation’s digital culture.

The findings offer valuable benefits to construction organisations as understanding these identified people features can help lead to better deployment of digital tools and the attainment of the digital transformation.

This study attempts to fill the gap in the shortage of literature exploring the people dimension of construction digitalisation. The study offers an excellent theoretical backdrop for future works on digital talent for construction digitalisation, which has gained less attention in the current construction digitalisation discourse.

This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.

A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.

Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.

The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.

This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.

This paper aims to investigate the relationship between information technology (IT) capabilities, information integration and supply chain resilience within the context of a developing country.

Employing a structured questionnaire survey, the study collected cross-sectional data from 205 agro-food processing firms in Uganda, drawn from a sample of 248. The data were subsequently analyzed using SPSS version 27 to validate the hypothesized relationships.

The study findings revealed that IT capabilities and information integration are positively and significantly associated with supply chain resilience. Moreover, it established a positive and significant link between IT capabilities and information integration. The results further revealed both IT capabilities and information integration account for 62.2% of the variance in supply chain resilience (SCRES) in agro-food processing firms in Uganda. Notably, the findings revealed the partial mediating role of information integration, addressing the need to understanding the mechanisms through which IT capabilities influence SCRES.

First, the study used a cross-sectional design which makes it difficult to test causality. Some of the study variables need to be studied over time due to their inherent behavioral elements such as collaboration and information sharing. Hence, future research that could, where possible, collect longitudinal data on the study variables would add value to the findings. Second, the study was limited to agro-food processing firms in Uganda in selected districts of Kampala, Wakiso, Mukono and Jinja. Further research needs to be done in other sectors such as service industry and other geographical locations in Uganda and other developing economies to provide more generality of the findings. Third, the study was based on IT capabilities, information integration and supply chain resilience. There are other variables that affect supply chain resilience such as business continuity planning strategy, interactions between teams within an organization in building resilience, supply chain velocity, system orientation and flexibility among others which can be interesting for further research.

Managers are advised to motivate their IT-related personnel. Efficient use of IT systems by staff, especially who are skillful at self-study, enhances their ability to respond to disruptions accordingly. This enhances SCRES. Additionally, to get feedback from supply chain stakeholders, agro-food processing firms should assess the quality of their supply chain services through using IT capabilities as well as integrating their information.

This study contributes to existing literature by adopting information processing perspective to provide an empirical understanding of IT capabilities and information integration as key resources and capabilities essential for information processing in building SCRES. Furthermore, the study introduces the novel insight of the mediating role of information integration as a pathway in which IT capabilities enhance SCRES in agro-food processing firms in Uganda.

The study aims to explore digital transformation from the viewpoint of human resource management to uncover possible threads of relationship using bibliometric analysis. It also aims to identify the trending research themes within the domains of digital transformation (DT) and human resource management (HRM) collectively.

The research employs a mix of quantitative bibliometric techniques and qualitative content analysis. A corpus of 227 articles retrieved from the Scopus database was analyzed using the R-based Biblioshiny and VOS viewer.

The study shows publication trends, influential authors, leading journals, highly productive institutions, and, countries in the domain of DT and HRM. Co-citation and co-occurrence analysis was undertaken to identify the research clusters, depicting trending research themes that extensively dominate the research under this domain.

This study will serve as a ready reckoner for academicians and business leaders, giving them useful insights to make their road towards digital transformation less challenging with the assistance of human capital.

This study is one of the initial efforts to quantitatively synthesize the results of earlier publications using bibliometric techniques in the domain of DT and HRM together. It will aid researchers in locating research gaps and filling those gaps in the future.

The relationship between industrial policy and exploratory innovation is imperfect.

The authors use Chinese high-tech enterprise identification policy (HTEP) as a natural experimental group to test policy impacts, spillover effects and mechanisms of action.

First, HTEP promotes exploratory innovation. In addition, HTEP has a greater impact on non-exploratory innovation. Second, HTEP has spillover effects in two phases: HTEP (2008) and the 2016 policy reform. HTEP affects exploratory innovation in nearby non-high-tech firms, and the policy effect decreases monotonically with increasing distance from the treatment group. Third, HTEP affects innovation capacity through financing constraints, technical personnel flow and knowledge flow, which explains not only policy effects but also spillover effects. Fourth, the analysis of policy heterogeneity shows that the 2016 policy reforms reinforce the positive effect of HTEP (2008). By deducting the effects of other policies, the HTEP effect is found to be less volatile. In terms of the continuity of policy identification, continuous uninterrupted identification has a crucial impact on the improvement of firms’ innovation capacity compared to repeated certification and certification expiration. Finally, HTEP has a crowding-out effect in state-owned enterprises and large firms’ innovation.

This paper contributes to the existing literature in several ways. First, the authors enrich the literature on industrial policy through exploratory innovation research. While previous studies have focused on R&D investment and patents (Dai and Wang, 2019), exploratory innovation helps firms break away from the inherent knowledge mindset and achieve sustainable innovation. Second, few studies have explored the characteristics of industrial policies. In this paper, the authors subdivide the sample into repeated certification, continuous certification and certification expiration according to high-tech enterprise identification. In addition, the authors compare the differences in policy implementation effects between the 2016 policy reform and the 2008 policy to provide new directions for business managers and policy makers. Third, innovation factors guided by industrial policies may cluster in specific regions, which in turn manifest externalities. This is when the policy spillover effect is worth considering. This paper fills a gap in the industrial policy literature by examining the spillover effects. Finally, this paper also explores the mechanisms of policy effects from three perspectives: financing constraints, technician mobility and knowledge mobility, which can affect not only the innovation of beneficiary firms directly but also indirectly the innovation of neighboring non-beneficiary firms.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

This study aimed to investigate and analyze the level of awareness and adoption of distributed ledger technologies (DLTs) within the Nigerian construction industry. The focus was on addressing the current state of DLT utilization, identifying challenges and opportunities and proposing strategies to enhance the integration of DLTs into the construction processes and practices of Nigerian professionals and organizations.

The research was underpinned by a robust theoretical and conceptual framework, drawing from established theories of technology adoption. A comprehensive literature review guided the identification of various DLT types. This informed the development of a well-structured questionnaire, which was then distributed to Nigerian construction professionals. The collected data underwent analysis using percentages, frequencies, mean scores, the Kruskal–Wallis H-test and the Shapiro–Wilk test.

A significant finding of this study reveals a generally low awareness and implementation of DLT among construction professionals in Nigeria. These findings emphasize the urgent need for comprehensive strategies to bridge the gap between awareness and adoption of DLT within the Nigerian construction industry.

Industry associations, regulatory bodies and educational institutions can collaborate to develop specialized programs aimed at familiarizing professionals with the benefits and applications of DLTs. Additionally, technology providers and policymakers can leverage these findings to design user-friendly interfaces and guidelines for seamless DLT integration into construction processes.

This study contributes to the existing body of knowledge by providing a comprehensive assessment of the awareness and adoption of DLTs specifically within the Nigerian construction industry. While the global recognition of DLT’s potential in construction is acknowledged, this research delves into a regional context, shedding light on the specific opportunities within Nigeria. Furthermore, the study’s identification of a gap between awareness and implementation highlights a critical area for future exploration and development in the field of construction technology adoption.

The literature mainly concentrates on the relationships between externally oriented digital transformation (ExtDT), big data analytics capability (BDAC) and business model innovation (BMI) from an intra-organizational perspective. However, it is acknowledged that the external environment shapes the firm's strategy and affects innovation outcomes. Embracing an external environment perspective, the authors aim to fill this gap. The authors develop and test a moderated mediation model linking ExtDT to BMI. Drawing on the dynamic capabilities view, the authors' model posits that the effect of ExtDT on BMI is mediated by BDAC, while environmental hostility (EH) moderates these relationships.

The authors adopt a quantitative approach based on bootstrapped partial least square-path modeling (PLS-PM) to analyze a sample of 200 Italian data-driven SMEs.

The results highlight that ExtDT and BDAC positively affect BMI. The findings also indicate that ExtDT is an antecedent of BMI that is less disruptive than BDAC. The authors also obtain that ExtDT solely does not lead to BDAC. Interestingly, the effect of BDAC on BMI increases when EH moderates the relationship.

Analyzing the relationships between ExtDT, BDAC and BMI from an external environment perspective is an underexplored area of research. The authors contribute to this topic by evaluating how EH interacts with ExtDT and BDAC toward BMI.

Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

This study offers an in-depth examination of Google Bard, an advanced artificial intelligence chatbot created by Google, focusing specifically on its potential impact on academic research. This discussion aims to comprehensively explore the features of Google Bard, highlighting its capabilities in data management, facilitating collaborative discussions, and enhancing accessibility to complex research. In addition to the aforementioned positive characteristics, we will also delve into the limitations and ethical considerations associated with this innovative device. The functionality of the system is constrained by the limitations imposed by its pre-established algorithms and training data. In addition, there are significant concerns regarding data privacy, potential biases in its responses stemming from its training data, and the wider societal implications associated with a heavy reliance on machine-generated content. Ensuring responsible and ethical utilization of Bard necessitates Google's provision of transparent communication regarding its development process. In light of the prominent functionalities demonstrated by Google Bard, it is imperative for researchers to engage in a rigorous examination of the information it presents, thereby safeguarding against the inadvertent propagation of misinformation or biased viewpoints. This will lay the groundwork for its effective integration into the academic research methodology.