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The purpose of this research is to develop a project complexity index (PCI) model using the best and worst method (BWM) to quantitatively analyze the impact of project complexities on the performance of metro rail projects.

This study employed a two-phase research methodology. The first phase identifies complexities through a literature review and expert discussions and categorizes different types of complexities in metro rail projects. In the second phase, BWM, a robust multi-criteria decision-making (MCDM) technique, was used to prioritize key complexities, and a PCI model was developed. Further, the developed PCI was validated through case studies, and sensitivity analysis was performed to check the accuracy and applicability of the developed PCI model.

The analysis revealed that location complexity exerted the most substantial influence on project performance, followed by environmental, organizational, technological and contractual complexities. Sensitivity analysis revealed the varying impacts of complexity indices on the overall project complexity.

The study's findings offer a novel approach for measuring project complexity's impact on metro rail projects. This allows stakeholders to make informed decisions, allocate resources efficiently and plan strategically.

The existing studies on project complexity identification and quantification were limited to megaprojects other than metro rail projects. Efforts to quantitatively study and analyze the impact of project complexity on metro rail projects are left unattended. The developed PCI model and its validation contribute to the field by providing a definite method to measure and manage complexity in metro rail projects.

This research develops a theoretical framework to understand the role of big data analytics capability (BDAC) in enhancing supply chain sustainability and examines the moderating effect of green supply chain management (GSCM) practices on this relationship.

Guided by the dynamic capability view (DCV), we formulated a theoretical model and research hypotheses. We used partial least square-based structural equation modeling (PLS-SEM) to analyze data collected from 159 survey responses from Bangladeshi ready-made garments (RMG).

The statistical analysis revealed that BDAC positively impacts all three dimensions of supply chain sustainability: economic, social and environmental. Additionally, GSCM practices significantly moderate the relationship between BDAC and supply chain sustainability.

This study makes unique contributions to the operations and supply chain management literature by providing empirical evidence and theoretical insights that extend beyond the focus on single sustainability dimensions. The findings offer valuable guidelines for policymakers and managers to enhance supply chain sustainability through BDAC and GSCM practices.

This study advances the current understanding of supply chain sustainability by integrating BDAC with GSCM practices. It is among the first to empirically investigate the combined effects of BDAC on the three dimensions of sustainability – economic, social and environmental – while also exploring the moderating role of GSCM practices. By employing the DCV, this research offers a robust theoretical framework highlighting the dynamic interplay between technological and environmental capabilities in achieving sustainable supply chain performance.

This study aims to measure scientific literature on the emerging research area of “big data” in the field of “library and information science” (LIS).

This study used the “bibliometric method” for data curation. Web of Science and altmetric.com were used. Data analysis and visualisation were done using three widely used powerful data analytics software, R-bibliometrix, VOSviewer and Statistical Package for Social Sciences.

This study revealed the most preferred venues for publication. Furthermore, this study highlighted an association between the Mendeley readers of publications and citations. Furthermore, it was evident that the overall altimetric attention score (AAS) does not influence the citation score of publications. Other fascinating findings were moderate collaboration patterns overall. Furthermore, the study highlighted that big data (BD) research output and scientific influence in the LIS sector are continually increasing.

Findings related to BD analytics in LIS techniques can serve as helpful information for researchers, practitioners and policymakers.

This study contributes to the current knowledge accumulation by its unique manner of blending the two approaches, bibliometrics and altmetrics.

The increasing complexity and globalization of supply chains raise risks such as human rights abuses and environmental damage while affecting their supply chain performance (SCP), which prompted a study on supply chain due diligence (SCDD) practices. This study examines the impact of SCDD practices on the SCP. It examines if and how these relationships can be influenced by factors such as organizational culture and trust.

A conceptual model and hypotheses based on institutional theory were developed. The survey instrument captures organizations' perceptions of SCDD practices and related key performance indicators for SCP. The study collects data from 329 supply chain and logistics managers in Indian manufacturing and logistics organizations, and the hypotheses are validated using a structural equation model.

Results indicate that SCDD practices positively influence SCP. Trust and organizational culture strengthened SCDD–SCP relationships.

The study explores how organizations perceive and implement due diligence in their supply chains, highlighting areas for improvement. This understanding could help organizations enhance their supply chain management strategies, leading to better risk management, cost reduction, avoiding penalties and improved overall performance.

The main contribution of the study is to examine organizations' perceptions of SCDDA implementation and then identify its effects on supply chain performance. This is done considering trust and organizational culture as moderating factors.

This study aims to examine the mediating effects of two corporate social responsibility factors – leadership mindset and corporate commitment – on the relationship between sustainable orientation toward Industry 4.0 and environmental decision-making effectiveness.

The research model was tested using structural equation modeling based on survey data from 175 companies serving the Hajj and Umrah sector in Saudi Arabia, a sector recognized for its high level of digitalization.

The results indicate that a sustainable orientation toward Industry 4.0 and digitalization positively influences environmental decision-making effectiveness. Additionally, Corporate commitment was found to have a direct positive effect on environmental decision-making effectiveness, while leadership mindset showed no significant effect.

This study highlights the critical role of sustainable Industry 4.0, driven by digitalization, in enhancing service quality and competitive value in companies serving the Hajj and Umrah sector. These companies see digitalization as an opportunity to improve business outcomes through effective environmental strategic decisions, though its application remains challenging. The study contributes to the existing body of knowledge by providing empirical insights into the impact of digitalization on environmental decision-making effectiveness within this specific context.

This paper aims to systematically review the managerial literature on Industry 4.0 (I4.0) in emerging markets (EMs) through bibliometric analyses to identify incipient research streams and literature gaps and recommend avenues for future research.

This research uses bibliographic coupling analysis (BCA) to obtain a comprehensive view of the intellectual contours within the addressed literature. The primary source utilised is the Web of Science database. A total of 345 peer-reviewed journal articles were retrieved. Complementing BCA, we use social network analysis and the content analysis of articles to study the resulting literature clusters.

The results reveal four thematic clusters: (1) Adoption of I4.0 in EMs; (2) impact of I4.0 on organisational aspects and financial performance of companies and supply chains in EMs; (3) I4.0, lean management and operational performance in EMs and (4) I4.0 and the development of sustainable practices in EMs. We supplement these results with the proposal of different future avenues of research, both general and specific, for each identified cluster.

The current study has certain limitations arising from using the bibliometric method and techniques employed in the analyses.

To the best of the authors’ knowledge, there is no comprehensive literature review article on this subject. This research is deemed valuable for future scholars as it facilitates the identification of research fronts that define the forefront of knowledge, reveals current trends and sets the stage for further exploration of key issues in the field. This, in turn, can offer valuable insights to academics, policymakers and practitioners.

Supply chain disruptions are a significant risk to businesses in a global marketplace because they make it more challenging for suppliers to effectively transport goods and services to customers. Therefore, it is essential to comprehend how these disruptions affect the retail food supply chain during pandemics and explore how digitalization might help to mitigate these issues in the future.

A hybrid systematic review and analysis was conducted by retrieving data set from the scopus database using strong keyword search strategy. Later a content analysis was also done to gain more insights on the proposed research.

The results show that there are several possibilities enabling optimal scenario planning supply chain disruptions and mitigation. In this area, digitalization improves customer satisfaction and logistical efficiency, particularly in transportation and network optimization. In order to cope with uncertainty and grasp significant enhancements proactive strategies and collaboration that are guided by scenario planning and digitalization assist in developing robust supply chains that are sufficiently adaptable to adapt to shifting market conditions.

The study is limited to research papers indexed in Scopus from 2015 to 2023 with a more comprehensive review of retail food supply chain disruptions.

This research provides practical insights for retail food supply chain managers, highlighting the importance of digital maturity and scenario planning by leveraging digital tools and proactive strategies to improve logistical efficiency.

This study helps in building resilient supply chains ensures the reliable availability, and food security of essential goods, particularly during crises.

This research uniquely links digitalization and scenario planning to managing supply chain disruptions, highlighting how digital tools and strategic planning enhance resilience and adaptability in the retail food supply chain.

The purpose of this study is to investigate the determinants and the intention to use information technology (IT) audit technologies.

The research model explores the external and internal factors that influence IT audit usage in Saudi Arabia. The external factors include IT audit education, professional support provided by professional accounting and auditing bodies, external pressure and social factors. The internal factors include the firm’s organizational support, complexity of accounting information systems, IT audit competency, adoption risk, ease of use and readiness. These factors affect the intention to use IT audits, represented by the perceived benefits and intention to use IT audits, which in turn affect IT audit usage. The study uses structural equation modelling to estimate a sample size of 261 respondents.

The findings suggest that internal factors significantly influence both IT audit usage and intention to use IT audits. However, the external factors exhibit insignificant associations with IT audit usage. The findings also indicate that IT auditors in Saudi Arabia heavily rely on Microsoft Excel, Microsoft Word and email/Outlook as essential IT audit tools. However, the findings reveal that there is still a role for specialized IT audit tools such as generalized audit software and Audit Command Language but this usage is marginal.

The present study provides significant insights for auditors, companies’ boards, professional bodies and policymakers to enhance the development and usage of IT audits. The study revealed the absence of supportive external factors that policymakers and professional bodies should exercise in this regard. The findings also indicate that IT audit education and capacity programmes are required to promote competency and adoption of IT audit technologies.

The study contributes to IT auditing by identifying significant factors influencing IT audit adoption. It underlines the relevance of internal and external determinants and perceived benefits as drivers of IT audit adoption. The current study provides an original piece of research that highlights a comprehensive investigation of the determinates of IT audit usage in a developing country that is shifting towards artificial intelligence and IT advancements.

Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

The purpose of this study is to explore the disclosure of sustainable development goals (SDGs) by Indian firms and to examine the association between sustainable business practices and the disclosure of SDGs.

The study is based on large Indian non-financial firms listed in Bombay Stock Exchange 200 for six years from 2016–2017 to 2021–2022. Sustainable business practices are measured using four important indicators - the quality of sustainability discourse, compliance with Global Reporting Initiative guidelines, adoption of the guidelines of the International Integrated Reporting Council and external assurance of published reports. Content analysis is used to compute the disclosure score of SDGs and corporate sustainability performance. The authors have used a fixed effects regression model followed by Tobit model and two-stage least square model to examine the association between sustainable business practices and the disclosure of SDGs.

The results indicate an increasing trend of disclosure of SDGs by Indian firms. The empirical findings suggest a positive impact of sustainable business practices on the SDGs disclosure after controlling for firm-specific and corporate governance variables. Among the components of corporate sustainability, social and environmental factors positively influence the SDGs.

The study is a noble attempt to enrich the extant literature by providing empirical evidence on the association between sustainable business practices and disclosure of SDGs considering four important indicators of sustainable practices. The findings are useful for theoretical and practical implications.