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The purpose of this study is to investigate the impact of logistics capabilities on the relationship between information sharing (INS) and logistics performance of Sudanese industrial companies.

This descriptive study investigates the relationship between INS and logistics performance in Sudanese industrial companies. A five-point scale questionnaire surveyed a non-probability sample of 262 logistics, supply chain and operations managers. Structural equation modeling has been used to test the relationship between the variables.

The results revealed that there is no direct positive relationship between logistics INS and logistics performance, while there is an indirect relationship through logistics capabilities. The findings confirmed that there is a positive relationship between logistics INS and logistics capabilities.

There are several limitations in this study. This study is limited to certain businesses and has a small sample size, which may impact the capacity to apply the findings to a broader context. The sample was based on the current manufacturing companies in Sudan, which are distinguished by certain characteristics in terms of number, business stability and other factors. Because of these factors, the findings may not accurately reflect the actual situation. Industrywise, this study focused on manufacturers, whereas logistics is based on a chain of partners and involved parties. Including them in any future investigation could lead to meaningful findings and discoveries. Furthermore, the data collection’s cross-sectional form may not comprehensively reflect the temporal dynamics of logistical activities. Future research may address these constraints by investigating the efficacy of diverse logistical capabilities in other businesses and circumstances. The construct of the variables is a single-dimension construct, which does not reflect all the practices associated with INS, logistics capabilities and logistics performance. Furthermore, there is an opportunity to explore further the impact of INS on important logistical performance metrics, such as order lead time, on-time delivery and inventory management. One potential area for future investigation is the study of logistics information-sharing technologies, specifically utilizing data analytics and machine learning. In such a context, deep insight and understanding of logistics capabilities and performance require more qualitative analysis; therefore, future research could fill this gap and provide deeper insight.

For practitioners in the small and medium-sized enterprise sector in Sudan, these findings suggest enhancing their operations, particularly by investing in information-sharing technologies that improve stakeholder coordination. Actively engage supply chain partners in the logistics information system to ensure timely and accurate information flows to all. However, it’s important to be aware of potential challenges, such as the high costs and complex design of these systems and potential resistance to change within businesses. Policymakers play a crucial role in this process, as they can use these findings to establish industry-wide standards or incentives that promote the use of advanced logistical capabilities; besides that, policymakers need to invest in building genuine information channels and systems that inform the industry and clear the ambiguity.

This study establishes a relationship between INS and logistics performance, which will be interpreted by logistics capabilities to enhance the logistics performance of Sudanese logistic businesses in an underdeveloped context characterized by a weak logistics industry and logistics capabilities. It suggests that companies should prioritize logistics INS and investment in INS technology to enhance their logistics capabilities.

This present study uses political, economic, social, technological, legal and environmental (PESTLE) analysis and the strategic management theory to examine how external factors, namely the coronavirus (COVID-19) pandemic, the industrial revolution (IR) 4.0 technologies, the fuel price crisis and Sultanate of Oman Logistics Strategy (SOLS) 2040, affect the performance of container terminals in Oman.

A hybrid decision-making method that combined the analytical hierarchy process technique and Bayesian network model was used to achieve the objective of the present study.

The COVID-19 pandemic (54.60%) most significantly affected the performance of container terminals in Oman, followed by IR 4.0 technologies (19.66%), SOLS (17.00%) and fuel price crisis (8.74%). Container terminals in Oman were also found to perform “moderately,” considering the uncertainty of external factors.

This study enriches existing literature by using PESTLE analysis to assess the impact of the external business environment on firm performance in the context of the maritime industry as well as highlights how challenging external environmental factors affect the performance of container terminals in Oman.

This study contributes to developing novel study models and determining the performance level of container terminals in Oman considering integrated uncertainties and external factors such as the COVID-19 pandemic, IR 4.0 technologies, the SOLS 2040 and the fuel price crisis.

This study investigates the role of market concentration and efficiency in banking system stability during the COVID-19 pandemic. We empirically test the hypothesis that market concentration and efficiency are significant determinants of bank performance and stability during the time of crises, using a sample of 575 banks in 20 countries in the Middle East and North Africa (MENA).

The main sources of bank data are the BankScope and BankFocus (Bureau van Dijk) databases, World Bank development indicators, and official websites of banks in MENA countries. This study combined descriptive and analytical approaches. We utilize a panel dataset and adopt panel data econometric techniques such as fixed/random effects and the Generalized Method of Moments (GMM) estimator.

The results reveal that market concentration negatively affects bank profitability, whereas improved efficiency further enhances bank performance and contributes to the banking sector’s overall stability. Furthermore, our analysis indicates that during the COVID-19 pandemic, bank stability strongly depended on the level of market concentration, but not on bank efficiency. However, more efficient banks are more profitable and stable if the banking institutions are Islamic. Similarly, Islamic banks with the same level of efficiency demonstrated better overall financial performance during the pandemic than their conventional peers did.

The main limitation is related to the period of COVID-19 pandemic that was covered in this paper (2020–2021). Therefore, further investigation of the COVID-19 effects on bank profitability and risk will require an extended period of the pandemic crisis, including 2022.

This study provides information that will enable bank managers and policymakers in MENA countries to assess the growing impact of market concentration and efficiency on the banking sector stability. It also helps them in formulating suitable strategies to mitigate the adverse consequences of the COVID-19 pandemic. Our recommendations are useful guides for policymakers and regulators in countries where Islamic and conventional banking systems co-exist and compete, based on different business models and risk management practices.

The authors contribute to the banking stability literature by investigating the role of market concentration and efficiency as the main determinants of bank performance and stability during the COVID-19 pandemic. This study is the first to analyze banking sector stability in the MENA region, using both individual and risk-adjusted aggregated performance measures.

One of the main challenge when launching new banking services is to overcome resistance to change so as to accelerate market acceptance. This is the case of an Islamic credit card (ICC). Grounded in innovation diffusion theory (IDT) and theory of reasoned action (TRA), this paper aims to study the purposes and empirically tests an integrated model to explore, which factors influence of ICC.

Partial least squares and structural equation modeling was used to assess the hypotheses. Accordingly, the empirical results, obtained in a sample of 762 bank customers.

Intentions to use of ICC are mostly determined by relative advantage, compatibility, customer awareness, satisfaction and attitude. The combination of IDT and TRA significantly explain the ICC adoption.

This research has provided a theoretical understanding of the ICC adoption determinants with the intent of promoting a more in-depth understanding of various elements influencing acceptance and usage of this Islamic banking service.

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.