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This paper aims to systematically review the literature on digital supply chain (DSC), big data (BD) and manufacturing lead time (MLT) in industrial companies.

This study provides a systematic review of the 99 research on this subject that was published between 2015 and 2022. Studies were found in the Scopus database. This review also identifies gaps in the literature, highlights conflicting results, examines prospective data sources for empirical researchers and offers suggestions for choosing promising research subjects in the future.

This study performed a thorough literature review to a developing field of inquiry in order to identify the impact of the digital supply chain, BD and manufacturing lean time, an area that has received little attention in the literature. Future pathways and ramifications are also offered based on the literature content search. The results showed that BD improves DSC performance through resilience and innovation of the DSC. MLT and DSC integration were found to be positively correlated, according to the results.

Although the production lead time is preferable to boost customer value and supply reliability, the long lead time hurts the DSC’s ability to compete. DSC integration also improves coordination and streamlines processes. The researchers suggest fostering organizational flexibility, information exchange to accomplish DSC integration and adaptable behaviors including responsiveness and alertness.

This study attempts to explore the linkages between reliable big and cloud data analytics capabilities (RB&CDACs) and the comparative advantage (CA) that applies in the manufacturing sector in the countries located in North Africa (NA). These are considered developing countries through generating green product innovation (GPI) and using green process innovations (GPrLs) in their processes and functions as mediating factors, as well as the moderating role of data-driven competitive sustainability (DDCS).

To achieve the aim of this study, 346 useable surveys out of 1,601 were analyzed, and valid responses were retrieved for analysis, representing a 21.6% response rate by applying the quantitative methodology for collecting primary data. Convergent validity and discriminant validity tests were applied to structural equation modeling (SEM) in the CB-covariance-based structural equation modeling (SEM) program, and the data reliability was confirmed. Additionally, a multivariate analysis technique was used via CB-SEM, as hypothesized relationships were evaluated through confirmatory factor analysis (CFA), and then the hypotheses were tested through a structural model. Further, a bootstrapping technique was used to analyze the data. We included GPI and GPrI as mediating factors, while using DDCS as a moderated factor.

The empirical findings indicated that the proposed moderated-mediation model was accepted due to the relationships between the constructs being statistically significant. Further, the findings showed that there is a significant positive effect in the relationship between reliable BCDA capabilities and CAs as well as a mediating effect of GPI and GPrI, which is supported by the proposed formulated hypothesis. Additionally, the findings confirmed that there is a moderating effect represented by data-driven competitive advantage suitability between GPI, GPrI and CA.

One of the main limitations of this study is that an applied cross-sectional study provides a snapshot at a given moment in time. Furthermore, it used only one type of methodological approach (i.e. quantitative) rather than using mixed methods to reach more accurate data.

This study developed a theoretical model that is obtained from reliable BCDA capabilities, CA, DDCS, green innovation and GPrI. Thus, this piece of work bridges the existing research gap in the literature by testing the moderated-mediation model with a focus on the manufacturing sector that benefits from big data analytics capabilities to improve levels of GPI and competitive advantage. Finally, this study is considered a road map and gaudiness for the importance of applying these factors, which offers new valuable information and findings for managers, practitioners and decision-makers in the manufacturing sector in the NA region.

This paper aims to identify potential barriers to Industry 4.0 adoption for manufacturers and examine the changes that must be made to production processes to implement Industry 4.0 successfully. It aims to develop technology by assisting with the successful implementation of Industry 4.0 in the manufacturing process by using smart system techniques.

Multiple case studies are used in this paper by using the smart system and Matlab, and semi-structured interviews are used to collect qualitative data.

Standardization, management support, skills, and costs have been cited as challenges for most businesses. Most businesses struggle with data interoperability. Complexity, information security, scalability, and network externalities provide challenges for some businesses. Environmental concerns are less likely to affect businesses with higher degrees of maturity. Additionally, it enables the Technical Director’s expertise to participate in the measurement using ambiguous input and output using language phrases. The outcomes of the numerous tests conducted on the approaches are extensively studied in the provided method.

In this research, a multiple-case study aims to carry out a thorough investigation of the issue in its actual setting.

The purpose of this study is to comprehensively explore the impact of digitalization on healthcare supply chains (HcSCs). It seeks to understand how digital technologies enhance efficiency, transparency and responsiveness within these complex logistical systems. The study aims to provide a holistic view of the transformative potential of digitalization in the healthcare sector, with a particular focus on improving patient care and streamlining operational processes.

This research employs a systematic review methodology, carefully curating a selection of 45 relevant articles from 66 articles rigorously screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to provide a holistic view. It follows established systematic review protocols, incorporating a meticulous search strategy and precise keyword selection. The chosen research design enables a comprehensive examination of the existing body of knowledge concerning digital platforms, real-time tracking technologies, transparency and responsiveness in the context of HcSCs.

The findings of this study emphasize the pivotal role of digital technologies in reshaping HcSCs. Digital platforms, real-time tracking systems and technological integrations substantially enhance efficiency, transparency and responsiveness. Data-driven decision-making, improved communication and agile responses to dynamic demands are key aspects. These findings underscore the transformative impact of digitalization on healthcare logistics, emphasizing the potential for streamlined operations, enhanced patient care and more efficient resource allocation.

Despite the systematic methodology, this study is subject to certain limitations. It relies on existing literature, which may not cover the most recent developments in the rapidly evolving field of digital HcSCs. Furthermore, the study may be influenced by publication bias. The implications suggest the need for continued research to explore emerging digital technologies and their effects on healthcare logistics, ensuring that supply chains remain agile and responsive.

The practical implications of this research are significant for HcSC managers with insights into digital technologies to enhance transparency and collaboration and improve resource visibility. The integration of data analytics can lead to more effective inventory management and demand forecasting. Blockchain (BC) technology can ensure transparent and secure transactions, fostering trust among stakeholders. For practitioners, this research offers actionable guidance for navigating the digital age, promoting operational efficiency and ensuring a consistent supply of essential medical products. Researchers can use these insights as a foundation for further exploration into the potential of digitalization in HcSCs.

The social implications of digitalization in HcSCs are far-reaching. They encompass improved patient care, as digital technologies enhance the efficiency, transparency and responsiveness of supply chains. This translates to better access to critical medical supplies, potentially reducing healthcare disparities and benefiting underserved populations. Enhanced patient safety is a significant social outcome, as transparent and secure transactions enabled by technologies like BC mitigate the risks associated with counterfeit medications. Furthermore, digitalization builds trust among stakeholders, promotes accountability and fosters resilient healthcare systems, which are capable of responding effectively to crises. It also has the potential to make healthcare more affordable, contributing to increased healthcare access and transparency in decision-making.

The originality and value of this study lie in its comprehensive synthesis of diverse findings related to digitalization in HcSCs. While prior studies have examined isolated facets of digital technology adoption, this research provides a comprehensive overview. It contributes to a deeper understanding of the transformative potential of digitalization within the healthcare sector, offering practical approaches to enhance patient care and streamline operations.

In light of Bangladesh’s economy, the goal of this study is to examine the “Twin Deficit Hypothesis (TDH),” which refers to a link between the budget deficit and the current account deficit. This study used yearly time series data from 1980 to 2020 to investigate the phenomena.

A multivariate autoregressive distributive lag (ARDL) model has been presented for empirical investigation, with the ARDL bound test investigating the co-integration between the inadequacies. As some of the variables in the bound test lack co-integration, the study adds a multivariate vector autoregressive (VAR) model later on.

With evidence of the result, the study supports the validation of twin deficit hypothesis in Bangladesh economy since both current account deficit and fiscal deficit affects each other significantly whereas Granger causality test confirms that fiscal deficit causes current account deficit but not the other way around.

The government should maintain a restrictive monetary policy in order to stabilize the current account deficit.

The novelty of this study is the incorporation of inflation, real exchange rate and GDP per capital to TDH that together form the basis for a macroeconomic snapshot of the economy.

Since previous literature provides fragmented and conflicting results about the use of digital data for product innovation, the article aims to comprehensively explore and shed light on how agri-food firms utilise external and internal digital data sources when dealing with different product innovations, such as incremental, architecture and radical innovation.

This paper adopts an exploratory multiple-case study and a theory-building process, focussing on the agri-food industry. We collected primary and secondary data from eight manufacturing companies.

The findings of this research show an empirical framework of six agri-food firms’ digital data utilisation behaviours: the supervisor, the passive supervisor, the developer, the passive developer, the pathfinder and the conjunction behaviour. These digital data utilisation behaviours vary according to a combination of data sources, such as internal data related to inside phenomenon measures (e.g. data generated by sensors installed in the production plan) or external data (e.g., market trends, overall sector sales), and innovation purposes.

This article offers guiding principles that assist agri-food companies when utilising internal and external digital data sources for specific product innovation outcomes such as incremental, architectural and radical innovation.

The significance of external and internal data sources in stimulating product innovation has garnered substantial attention within academic discussions, highlighting the critical importance of analysing digital data for driving such innovation. Nonetheless, the predominant approach is to study a single innovation outcome through the lens of digital technology. In contrast, our study stands out by adopting a fundamental perspective on data sources, enabling a more nuanced explanation of the overall product innovation outcomes within the agri-food sector.

This paper aims to examine the consequences of board diversity (BD) in Kuwait. In particular, it examines the impact of BD (gender, age and nationality) on earnings management (EM).

The research uses data from 103 non-financial Kuwaiti-listed companies from 2010 to 2017. The data is collected from the companies’ data from secondary sources such as their annual reports. The data analysis methods are correlation, multi-regression and robust regression. EM is measured using the modified Jones model (1995) and Kothari et al. (2005).

The findings show a negative association between gender diversity (GD) and EM. It also found a positive relationship between age diversity (AD) and EM and no relationship between national diversity (ND) and EM.

This study’s results have significant implications for investors. The practical empirical findings indicate that GD on the board did not impact on EM. Also, it is more important to have senior directors on the board than AD to reduce EM. There is no need to employ any foreigners because they do not affect EM.

It contributes to the growing body of literature on BD by investigating its effect on EM. Furthermore, building on the broader literature on gender, age and ND by highlighting the critical role that women, young people and foreign directors play in improving boards' monitoring role on EM. More specifically, it contributes to existing knowledge, provides a theoretical contribution and makes a methodological contribution.

The purpose of this study is to delve into the complex interplay between earnings management (EM), the International Financial Reporting Standards (IFRS) implementation and the reporting lag (RL) within the specific context of the Gulf Cooperation Council (GCC) region, with a particular emphasis on the Saudi context, offering insights into their influence on financial reporting practices.

Using a panel data set of 135 Saudi companies over an eight-year period, covering four years before and after the mandatory adoption of IFRS in 2017, this study investigates the Saudi financial reporting landscape. It uses interaction moderation analysis to explore variable effects and includes robustness analyses to validate the findings.

The findings reveal three key outcomes. First, they challenge conventional expectations by showing no significant impact of discretionary accruals (DACC) on RL, contrary to established accounting theories. This deviation is attributed to unique market characteristics within the GCC region, including family-owned businesses, government involvement and distinct regulations, with specific insights relevant to Saudi Arabia. Second, an unexpected positive association between IFRS adoption and RL in Saudi Arabia emerged. Several contextual factors contribute, including transition costs, compliance expenses, institutional dynamics and reconciling IFRS with local Shariah principles. Most importantly, IFRS adoption significantly reduced RL, especially for companies with high DACC levels. This highlights IFRS’s transformative role, emphasizes aligning EM with international standards for investor confidence and mitigating nonconformity risks in the GCC region’s business landscape.

The research findings carry significant practical implications for companies operating within the GCC region, accentuating the strategic imperative of timely financial reporting to bolster credibility, align with international standards and fortify investor confidence. Moreover, regulators and policymakers are urged to consider tailoring accounting regulations to accommodate the distinctive GCC context, thereby adeptly addressing the intricacies stemming from the interplay of EM, IFRS adoption and RL dynamics in the region.

This study adds to the current body of literature by highlighting the significant moderating influence of IFRS transition on the nexus between DACC and RL. It underscores the crucial role of this global accounting framework in reshaping financial reporting practices.

This study aims to address the critical challenge of implementing lean manufacturing (LM) in emerging economies, where sustainability complexities on the production floor hinder production efficiency and the transition towards a circular economy (CE). Addressing a gap in existing research, the paper introduces a path analysis model to systematically identify, prioritize and overcome LM implementation barriers, aiming to enhance performance through strategic removal.

The authors used a mixed-method approach, combining empirical survey data with literature reviews to pinpoint key LM barriers. Using the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) along with the Network Knowledge (NK) method, they mapped causal relationships and barrier intensities. This formed the basis for developing a path simulation algorithm, integrating heuristic considerations for practical decision-making.

This analysis reveals that the primary barriers to LM adoption is the negative perception and inadequate understanding of lean tools and CE principles. The study provides a strategic framework for managers, offering new insights into barrier prioritization and overcoming strategies to facilitate successful LM adoption.

This research provides a strategic pathway for overcoming LM implementation barriers, empowering managers in emerging economies to enhance sustainability and competitive advantage through LM and CE integration. It emphasizes the significance of structured barrier management in the manufacturing sector.

This research pioneers a systematic exploration of LM implementation barriers in the CE context, making a significant contribution to the literature. It identifies, evaluates barriers and proposes a practical model for overcoming them, enriching sustainable manufacturing practices in emerging markets.

The purpose of the study is to investigate the influence of training and development and work–life balance on employee engagement and job performance at private banks in Bangladesh. This study also investigates the indirect influence of training and development and work–life balance on the job performance of private banks through the mediating role of employee engagement.

The present study used a self-administered survey questionnaire to collect data from the private bank staff who had been working in the existing bank for more than one year. In this study, 450 survey questionnaires were distributed to the respondents and received 346 useful responses (76.88% response rate). The SmartPLS 4 software was used to determine the reliability and validity of the constructs. The SmartPLS 4 software was also used to test the hypothesised path coefficients via Partial Least Squares Structural Equation Modelling (PLS-SEM).

The findings of the study indicate that both training and development and work–life balance significantly influence employee engagement and job performance in the private banks. The findings also indicate that both training and development and work–life balance indirectly significantly influence the job performance of the private bank through the mediating role of employee engagement.

This study suggests various practical implications. Managers should provide opportunities for employees to actively participate in employee training. The present study also suggests that managers should also prioritise and model a healthy work–life balance because when leaders value work–life balance, employees feel empowered. The findings of the study suggest that organisations should design effective employee development programmes and foster a supportive work environment to motivate their employees to contribute to organisational success.

This study makes significant theoretical contributions to the existing literature on employee engagement and job performance. The present study enhances theoretical depth by highlighting the mediating role of job engagement in achieving job performance, offering a new perspective on the relationship between these variables and paving the way for targeted interventions. The present study also enriches the existing body of literature by examining the impact of training and development and work–life balance through the lens of organisational support theory, presenting a comprehensive understanding of the intricate dynamics at play.