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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 research investigates the critical role of data governance (DG) in shaping a data-driven culture (DDC) within organizations, recognizing the transformative potential of data utilization for efficiency, opportunities, and productivity. The study delves into the influence of DG on DDC, emphasizing the mediating effect of data literacy (DL).

The study empirically assesses 125 experienced managers in Indonesian public service sector organizations using a quantitative approach. Structural Equation Modeling (SEM) analysis was chosen to examine the impact of DG on DDC and the mediating effects of DL on this relationship.

The findings highlight that both DG and DL serve as antecedents to DDC, with DL identified as a crucial mediator, explaining a significant portion of the effects between DG and DDC.

Beyond unveiling these relationships, the study discusses practical implications for organizational leaders and managers, emphasizing the need for effective policies and strategies in data-driven decision-making.

This research fills an important research gap by introducing an original model and providing empirical evidence on the dynamic interplay between DG, DL, and DDC, contributing to the evolving landscape of data-driven organizational cultures.

The study aims to use bibliometric and scientometric analysis to conduct a detailed investigation on the impact of disruptive technologies in accounting and reporting literature. To draw both academics and practitioners through accelerated research activities, the study also aims to look into the significance of these disruptive technologies, their potential and the opportunities they present for the accounting profession.

With the use of the Scopus database and a combination of accounting, reporting, auditing and technology-related keywords, 1660 research articles published between 2008 and 2023 were included in the sample. To provide graphical analysis of bibliometric data and visualize research findings such as bibliographic coupling, co-citation and keyword co-occurrence, this study used the R-biblioshiny and VOSViewer tools.

The findings demonstrate a growth in scholarly interest in the study’s area, particularly in recent years. The bibliometric analysis focuses on three key uses and applications of technology in the accounting and auditing professions: the adoption of continuous auditing and monitoring in the audit profession, the use of software tools in the audit and accounting professions and the connections between information systems and audit.

This study contributes to the literature by examining current research trends on the use of technology in the accounting and reporting professions, identifying gaps in the literature and, most importantly, proposing a research agenda for the field. This study’s data came entirely from English-language articles and reviews in the Scopus database. It also considers studies that are directly relevant to the use of technology in accounting and reporting.

In Bangladesh (BD), delays in infrastructure are common. Many previous studies have explored the causes of infrastructure delays. However, this study investigated the causes of delays by taking responses from the stakeholders who are responsible for planning, design, funding, approval and implementation. There are few studies that have related infrastructure project delays to heterogeneity in stakeholders’ perceptions.

A structural equation (SE) model is developed with 350 normally distributed data points to understand the heterogeneity in stakeholders’ perceptions regarding delays in infrastructure projects in BD. Additionally, the relative importance index (RII) approach is used to assess the responses, validating the SE model.

The study finds that among the three latent variables, “Project itself related delay” has more influence on delays in infrastructure projects. Among the observed variables under the “project itself related delay” latent variable, “DPP approval process” has the most significance. From the heterogeneity analysis, the study found differences in responses among the stakeholders from “the Engineering Department,” “the Planning Office” and “the Construction Firm/Industry.” An important class of stakeholders believes that their stage is not being delayed and that other stages require attention.

The data sample is 350. More data can improve the accuracy of the findings. Most of the respondents are civil engineers (74%) and represent the owner of the project. Sample data from more stakeholders’ will enhance the accuracy of the result.

This study addresses the requirements of Bangladeshi project stakeholders and how their interactions cause delays in projects. Furthermore, the opinions of other stakeholders are taken into consideration when determining the specific factors of individual stakeholders that are causing delays. Practically, the distance between stakeholders should be reduced. A project manager can play a role in this regard. Initiatives should be taken on how to complete the project quickly by eliminating the requirements discussed among the stakeholders and bureaucratic complications. Instead of placing blame on one another, stakeholders should take the initiative to figure out how to work together to finish the project on schedule. The Planning Commission’s approval of the Development Project Proposal (DPP) and Revised Development Project Proposal (RDPP) should be obtained as soon as possible by owner stakeholders. In order to avoid frequently changing the DPP, owners should also exercise greater caution when choosing contractors. Contractor stakeholders should use efficient and proper manpower and equipment so that unexpected delays are not created during the execution of work. Since the role of the contractor stakeholder is the most important among the three types of stakeholders, the contractor should raise awareness and urge the owners to get the RDPP approved quickly.

The findings from the study can help mitigate delays in infrastructure projects in BD, taking into account the perceptions of various stakeholders.

Responding to the continuing separation of participants and researchers in LIS participatory research, a new methodology is proposed: action partnership research design (APRD). It is asserted that APRD can mitigate or remove the hierarchical structures often inherent in the research process, thus allowing for equal contribution from all.

Building on the bonded design (BD) methodology and informed by a scoping literature review conducted by the same authors, APRD is a human-centered research approach with the goal of empowering and valuing community partnerships. APRD originates from research investigating the use of participatory design methods to foster collaboration between two potentially disparate groups, firstly with adult researchers/designers and elementary school children, and secondly with university faculty and IT professionals.

To achieve this goal, in addition to BD techniques, APRD draws inspiration from elements of indigenous and decolonization research methodologies, particularly those with an emphasis on destabilizing power hierarchies and involving research participants as full partners.

APRD, which emerged from findings from previous participatory design studies, especially those of BD, is based on the premise of partnership, recognizing that each member of a design team, whether researcher or participant/user, has unique expertise to contribute. By considering participants/users as full research partners, APRD aims to flatten the hierarchies exhibited in some LIS participatory research methodologies, where participants are treated more like research subjects than partners.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

Contemporary technological disruptions are espoused as though they stimulate sustainable growth in the built environment through the Green Internet of Things (G-IoT). Learning from discipline-specific experiences, this paper articulates recent advancements in the knowledge and concepts of G-IoT in relation to the construction and smart city sectors. It provides a scoping review for G-IoT as an overlooked dimension. Attention was paid to modern circularity, cleaner production and sustainability as key benefits of G-IoT adoption in line with the United Nations’ Sustainable Development Goals (UN-SDGs). In addition, this study also investigates the current application and adoption strategies of G-IoT.

This study uses the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) review approach. Resources are drawn from Scopus and Web of Science repositories using apt search strings that reflect applications of G-IoT in the built environment in relation to construction management, urban planning, societies and infrastructure. Thematic analysis was used to analyze pertinent themes in the retrieved articles.

G-IoT is an overlooked dimension in construction and smart cities so far. Thirty-three scholarly articles were reviewed from a total of 82 articles retrieved, from which five themes were identified: G-IoT in buildings, computing, sustainability, waste management and tracking and monitoring. Among other applications, findings show that G-IoT is prominent in smart urban services, healthcare, traffic management, green computing, environmental protection, site safety and waste management. Applicable strategies to hasten adoption include raising awareness, financial incentives, dedicated work approaches, G-IoT technologies and purposeful capacity building among stakeholders. The future of G-IoT in construction and smart city research is in smart drones, building information modeling, digital twins, 3D printing, green computing, robotics and policies that incentivize adoption.

This study adds to the normative literature on envisioning potential strategies for adoption and the future of G-IoT in construction and smart cities as an overlooked dimension. No previous study to date has reviewed pertinent literature in this area, intending to investigate the current applications, adoption strategies and future direction of G-IoT in construction and smart cities. Researchers can expand on the current study by exploring the identified G-IoT applications and adoption strategies in detail, and practitioners can develop implementation policies, regulations and guidelines for holistic G-IoT adoption.

The purpose of the research is to recognize and rank the barriers preventing Industry 4.0 (I4.0) adoption in Bangladesh’s food and beverage industries. It aims to highlight the major difficulties the sector is currently facing and offer a hierarchical framework for evaluating these barriers.

An exhaustive literature review was conducted along with expert interviews with academics and industry professionals to identify and assess the barriers. The interpretive structural modeling and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (ISM-MICMAC) approach was used to classify the identified barriers based on driving and dependent power and understand the interrelationships among them.

A total of 20 barriers to I4.0 adoption in the food and beverage sector of Bangladesh were identified. The top tier of significant barriers includes “Financial constraints,” “Lack of management support,” “Lack of research and development team,” “Lack of adequate skills in the workforce,” “Lack of digital strategy alongside resource scarcity” and “Employee resistance to change.”.

The created hierarchical framework offers a useful tool for dealing with the noted barriers and assisting with the successful adoption of I4.0 in the food and beverage sector. Businesses can overcome financial constraints by allocating enough resources and obtaining management support. By creating a focused research and development team and giving the workforce the necessary training, the lack of knowledge and skills can be overcome. By developing a thorough digital strategy and making sure that the necessary resources are available, resource scarcity can be overcome. Furthermore, effective change management methods can support the adoption of I4.0 technologies by overcoming employee resistance to change.

By concentrating specifically on the difficulties encountered by the food and beverage industries in Bangladesh as it attempts to adopt I4.0, this study contributes to the body of existing literature. The study’s originality lies in its thorough analysis of barriers and the use of the ISM-MICMAC approach to comprehend how these barriers interact with one another.

The literature has dealt with the relationship between board characteristics (BC) and firm performance (FP) on a large scale. However, it yielded inconsistent results. Thus, this paper aims to examine the indirect relationship between BC and FP through the mediating role of the capital structure (CS).

This study used a sample of 528 non-financial companies listed on Bursa Malaysia from 2015 to 2019. Also, a two-step system generalised method of moments estimation technique was applied.

The results show that board diversity and the frequency of board meetings positively affect financial performance, and it is negatively influenced by board turnover, size and independence. Also, the results indicate a positive relationship between the independence of the board and all CS variables. Importantly, the findings support the policy-setting role of the board of directors where CS (measured by total debt and short-term debt) suppresses some governance mechanisms’ detrimental effect on FP. Hence, the board of directors, apart from the monitoring function, introduce various policies (financial and non-financial) that enhance the overall performance of companies.

These results are consistent with the agency’s perspective that management practices in selecting the optimal capital reduce agency costs and improve performance. The findings contribute to developing a broader theoretical framework that accounts for the policy-setting role of the board of directors. The current study model of corporate governance offers insight for policymakers into the role of corporate governance other than monitoring functions in organisations and how CS should be taken into consideration with corporate governance and FP association.

The purpose of this study is to observe the practice of integrated reporting (IR) and investigate the impact of board characteristics on IR in three South Asian economies: Bangladesh, India and Sri Lanka.

The study uses the content analysis approach to measure the integrated reporting index (IRI) based on a structured checklist. To examine the impact of board characteristics (board size, board independence and gender diversity) on IRI, a multivariate analysis using pooled ordinary least square with panel-corrected standard error (PCSE) model has been conducted.

The content analysis findings show that the disclosure practice of IR is highest in India, followed by Sri Lanka and Bangladesh. The regression result indicates that all the proxies of board characteristics have a positive and significant impact on IRI.

The study’s outcomes may not be generalised for every region due to the differences in institutional contexts.

The findings of this study will assist the policymakers in understanding the importance of effective boards in enhancing the IR practice in their respective countries where the adoption of IR is still a voluntary requirement.

To the best of the authors’ knowledge, this is the first study in the field of existing literature to conduct a comparative analysis of IR practice among three South Asian countries. It shows how an effective board improves IR practice using a broader institutional context by underpinning the agency theory and legitimacy theory.