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Microfinance institutions (MFI) must adapt to rapidly changing market conditions, including stringent regulations and diverse customer demands, necessitating a high absorptive capacity. This research elucidates how organizational culture promotes knowledge sharing, thereby enhancing an organization’s ability to absorb and utilize new knowledge, with particular attention to the moderating role of MFI size.

Data were collected from 450 randomly selected employees of MFIs in Pakistan. Hypotheses were tested using structural equation modeling in WarpPLS 8.0.

The findings show that knowledge sharing mediates the relationship between organizational culture and absorptive capacity. The impact is more pronounced in larger MFIs, while smaller MFIs exhibit greater agility in adapting to new knowledge.

MFIs, particularly in dynamic markets like Pakistan, should enhance their absorptive capacity by fostering an organizational culture that promotes knowledge sharing. While larger MFIs benefit from structured knowledge-sharing practices, they should address potential bureaucratic impediments to maintain agility.

By improving absorptive capacity, MFIs can better innovate and tailor their services to underserved communities, contributing to financial inclusion and poverty alleviation in Pakistan. This research provides insights for policymakers and practitioners on fostering sustainable development through strategic organizational practices in MFIs.

The findings offer a practical framework linking theoretical concepts from the resource-based and knowledge-based views to real-world applications, particularly in developing economies. It emphasizes the crucial role of organizational culture in enabling MFIs to adapt and thrive in challenging environments.

This study aims to explore and analyze the issues in weightages-based profit distribution mechanism in Islamic banks from Shari’ah, practical and regulatory perspectives.

A qualitative research approach was used in this study based on primary data collected through semi-structured interviews from Shari’ah practitioners and senior industry experts in the field of pool management in the Islamic Financial Services Industry of Pakistan.

The current study found that the weightages-based mechanism conforms to the rules of Mudarabah and; therefore, permissible. However, the elements of exploitation, transparency and fairness require further research, as these elements seem to exist in this mechanism. It was also found that there are many loopholes in the regulatory guidelines for pool management in Islamic banking institutions (IBIs) in Pakistan resulting in practical issues.

The findings of this study may help improve pool management in IBIs, which in turn may cater the objections raised by academicians, customers and industry experts. Moreover, the alternative solution based on the findings of this study can be transformed into a proposal for regulators to take necessary actions against unfair profit distribution and issue further improved guidelines for IBIs in Pakistan.

To the best of the authors’ knowledge, very limited studies have been conducted on pool management particularly with issues from different perspectives and alternative solutions have been suggested that may act as a proposal for IBIs as well as regulatory authorities.

The study highlights our findings, including the confirmation of phase stability through XRD analysis, the characterization of optical properties revealing high absorption and conductivity and the analysis of mechanical stability through elastic constants. Additionally, we present detailed results on the band gap, EELS analysis and the suitability of SrZrO3 perovskite oxides for next-generation optoelectronic devices.

Cubic SrZrO₃ perovskite oxides were designed within the framework of density functional theory (DFT) via the CASTEP code under varying stress conditions (0–100 GPa), aiming to explore the key properties for diverse applications. The phase stability was confirmed by XRD analysis. From 0 to 40 GPa, there is an increase in the band gap from 3.330 to 3.615 eV, while it narrows from 3.493 to 3.155 eV beyond 60 GPa. The optical characteristics revealed high absorption, superior conductivity and a lower loss function. Significantly, the elastic constants (C₁₁, C₁₂ and C₄₄) satisfy the Born-stability criterion, ensuring the mechanical stability of the compound. Additionally, the Poisson’s ratio, Pugh ratio (B/G), Frantsevich ratio, Cauchy pressure (P_C) and anisotropy factor ensured both ductile and anisotropic characteristics. Higher values of Young’s modulus and shear modulus signify a superior ability to withstand longitudinal stresses. In the EELS analysis, distinctive energy-loss peaks resulting from absorption and emission correlated with diverse electronic transitions and energy levels associated with Sr, Zr and O atoms are used to probe the precise exploration of the electronic and optical characteristics of materials with a high degree of accuracy. Based on these findings, the designed SrZrO₃ perovskite oxides are particularly suitable for applications in various optoelectronic devices.

CASTEP codes were utilized to design the cubic SrZrO₃ perovskite under varying stress conditions ranging from 0 to 100 GPa. The phase stability was confirmed through XRD analysis. A distinctive trend in the band gap was observed: an increase from 3.330 eV to 3.615 eV as the stress increased from 0 to 40 GPa and a decrease from 3.493 to 3.155 above 60 GPa. A higher absorption and conductivity and a lower loss function were found for the optical properties. The mechanical stability was ensured by elastic constants (C₁₁, C₁₂, and C₄₄) satisfying the Born-stability criteria. Additionally, the Poisson’s ratio, Pugh’s ratio (B/G), Frantsevich ratio, Cauchy pressure (P_C) and anisotropy factor were used to verify the ductility and anisotropy of the materials. Higher values of Young’s modulus and shear modulus indicate a superior ability to withstand longitudinal stresses. EELS analysis revealed distinctive energy-loss peaks associated with Sr, Zr and O atoms, enabling precise exploration of the electronic and optical characteristics with a high degree of accuracy. As expected, the designed SrZrO₃ perovskite oxides exhibit favorable properties, making them particularly suitable for next-generation optoelectronic devices.

In this study, we utilized DFT within the CASTEP code framework to investigate the properties of cubic SrZrO₃ perovskite oxides under varying stress conditions ranging from 0 to 100 GPa. Our research aimed to explore the key properties of SrZrO₃ for diverse applications, particularly in optoelectronic devices.

This study aims to investigate the relationship between corporate governance characteristics and the financial performance of both Islamic and conventional banks in the context of an emerging market, i.e. Malaysia.

This study includes 300 bank-year observations from Islamic and conventional banks over the period 2010–2021. The dynamic panel model (generalized method of moments [GMM]) was considered the primary estimation model that solves simultaneity, endogeneity and omitted variable problems as most governance variables are endogenous by nature. Hence, static models are considered biased after conducting the DWH test of endogeneity, and considering dynamic panel GMM is valid proven by Sargan and Hensen and first-order (ARI) and second-order (ARII) tests.

Based on the regression results, the authors discovered that board size, female participation in the board and director remuneration have a significant positive impact on bank performance, whereas board meetings have a significant negative impact. Furthermore, the board governance structure of commercial banks is found to be more passive than that of Islamic banks.

The study’s findings added a new dimension to governance research, which could be a valuable source of knowledge for policymakers, investors and regulators looking to improve existing governance mechanisms for better performance of conventional and Islamic banks.

The goal of this study is to add to the existing literature by focusing on the impact of female board participation and other board governance mechanisms in both conventional and Islamic banks on bank performance.

This study, grounded in ambidexterity theory, aims to investigate how paradoxical leadership (PXL) fosters team creativity in high-tech manufacturing companies, with team ambidexterity as a mediator and leader vision as a moderator. Given the fast-paced, innovation-driven demands of the high-tech sector, this research provides insights into how managers can effectively balance contradictory behaviors to drive team innovation.

Data was collected through a two-wave survey from team leaders and members across 169 teams in high-tech manufacturing companies. The time interval between data collection waves was two weeks. The data was aggregated at the team level using estimates for interrater reliability and interrater agreement. The structural equation modeling in R was used to test hypotheses.

The findings indicate that PXL positively impacts team creativity directly and through its influence on team ambidexterity. Team ambidexterity mediates the relationship between PXL and team creativity, while leader vision moderates the effects of PXL on team ambidexterity.

PXL benefits high-performance teams in technology sectors, such as software development, where rapid innovation and iterative processes are essential. In health care, PXL can optimize team dynamics, enabling medical research and patient care delivery breakthroughs. Regular training in ambidextrous thinking and feedback mechanisms makes this approach actionable for managers striving to cultivate creativity in high-stakes environments.

This study extends ambidexterity theory by linking PXL and team ambidexterity to team creativity. It provides high-tech manufacturing managers with concrete strategies to balance exploration and exploitation. These findings highlight actionable pathways for companies to sustain innovation in competitive, technology-driven industries.

Sustainability is a pressing global issue that affects everyone on the planet. This study aims to provide a deeper understanding of the nuanced interplay between mindful organizing (MO), organizational learning capability (OLC), leadership commitment to sustainable development goals (SDGs) and sustainability performance, adopting the theoretical foundation of organizational learning.

The survey data from 728 middle management employees of exporting firms in Pakistan were collected at two points. The mediated moderation analysis was performed through structural equation modeling in AMOS 26.

The results indicate a positive relationship between MO and sustainability performance. The mediating effect of OLC highlights that firms that acquire, assimilate and apply knowledge and insights leverage their MO strategies to improve sustainability performance more effectively. Additionally, the leadership commitment to SDGs amplifies the positive effect of OLC on sustainability performance.

These results have important implications for managers and policymakers who seek to promote sustainability in organizations. The findings suggest that cultivating a mindful organizational culture and investing in learning capability enhance sustainability performance. Exporting firms should develop comprehensive learning programs that embed mindfulness and sustainability into the core of organizational culture. More interdisciplinary research is needed to integrate insights from environmental science, psychology, management and organizational behavior.

This research stands out for its integrative approach, practical relevance, empirical examination of important concepts and alignment with global sustainability goals. Exporting firms must understand how organizational learning capabilities and MO can be harnessed to achieve sustainable outcomes.

Green investment funds are still imperative in clarifying the fundamental components of their relationship to sustainability. This study aims to investigate the impact of different factors, such as green product design and innovation, green product entry barriers and green environmental awareness, on the success of green investment funds projects to finance environmentally friendly products. The research also investigates how green investment funds facilitate these factors to encourage environmentally sustainable business.

This paper used a questionnaire to collect insights from 210 green entrepreneurs in Asia, Africa, Europe and America. The data were then investigated using statistical tools, such as quantitative analysis of green entrepreneur surveys collected from various industries. The relationship between green product design and innovation, barriers to entry, environmental awareness and green entrepreneurship performance was investigated using partial least squares structural equation modelling, with green investment funds as a mediator.

The results indicate that every construct/variable included in the study supported the success of the sustainable business. The observation was made that the development phase tends to diminish the positive relationship between the success of green investment funds and green product codesign strategies. Implementing green product design and innovation improves the success of a green firm. Also, the progress of such companies might be hindered by entry barriers, and corporate performance is improved by environmentalism. This study found the role of green investment funds in promoting product innovation and positive environmental outcomes while reducing barriers to entry.

Given these results, this work provides a theoretical explanation. Also, it gives doable recommendations for more successful green investment funds of environmentally friendly goods. The analysis emphasises the need for green product innovation and investment funds to mitigate entry obstacles. Corporate entities, investors and lawmakers receive pragmatic guidance on sustainable business practices.

This research, unique because of its multidisciplinary methodology and theoretical advances, examines the relationship between business, finance and sustainability. It provides valuable insights for academics, professionals and decision-makers, enhancing the understanding of green investment and entrepreneurship and offering practical global sustainable economic growth strategies. This paper investigates the impact of green investment funds on product innovation, entry obstacles, environmental consciousness and the success of green entrepreneurs. To the best of the author’s knowledge, this study is one of the limited numbers that models these features, enhancing the precision of green project success information.

By addressing the dearth of literature on the subject of cybersecurity risks and artificial intelligence (AI), this study aims to close a research gap by concentrating on the ever-changing environment of online social networks (OSNs) and technology. The main goals are to classify cyberattacks into categories like malware, phishing/spam and network intrusion detection; to identify efficient algorithms for preventing cyber threats; to review relevant literature from 2019 to 2020; and to use machine learning algorithms to detect suspicious behavior related to malware. The study offers a novel framework that suggests particular machine learning algorithms for every kind of cyber threat, hence improving cybersecurity knowledge and reaction capacities. This makes the research useful for examining the impact of cybersecurity on smart cities.

Thirty papers have been examined on AI and machine learning algorithms, including K-nearest-neighbor (KNN), convolutional neural networks (CNN) and Random Forest (RF), that were published in 2019 and 2020. Using analytical software (NVivo), a qualitative approach is used to retrieve pertinent data from the chosen research. The researchers divide cyberattacks into three groups: network intrusion detection, phishing/spam and malware.

The study’s conclusions center on how AI and machine learning algorithms linked to cybersecurity are reviewed in the literature, how cyberattacks are classified and how an inventive framework for identifying and reducing risks is proposed. This makes the research useful for researching the implications of cybersecurity for smart cities.

The practical implications of this research are noteworthy, particularly in the realms of technology, AI, machine learning and innovation. The utilization of the NVivo technique enhances decision-making in uncertain situations, making the study’s results more reliable. The findings showcase the applicability of tools in analyzing malicious cyberattacks to address issues related to social media attacks, emphasizing their practical utility. The study’s relevance is further highlighted by a real-world example, where a Kuwaiti public sector fell victim to a malware attack, underlining the importance of cybersecurity measures aligned with the New Kuwait 2035 strategic development plan. The innovative framework presented in the research guides the selection of algorithms for detecting specific malicious attacks, offering practical insights for securing information technology (IT) infrastructure in Kuwait.

The rapid digitization in Kuwait, accelerated by the COVID-19 pandemic, underscores the pivotal role of technology in government services. Ma’murov et al. (2023) emphasize the significance of digitization, particularly in accessing and verifying COVID-19 information. The call for a dedicated digital library for preserving pandemic-related material aligns with the evolving digital landscape. Cybersecurity emerges as a critical concern in Kuwait and the Gulf Cooperation Council (GCC), necessitating transnational cooperation (Nasser Alshabib and Tiago Martins, 2022). In the local context, the inefficiency of information security systems and low awareness among government employees pose cybersecurity challenges (Abdulkareem et al., 2014). Social media’s role during the pandemic highlights its significance, yet the need for cybersecurity in this domain remains underexplored (Ma’murov et al., 2023; Safi et al., 2023).

The unique aspect of the paper is its in-depth investigation of the relationship between cybersecurity and AI in OSNs. It uses a special application of machine learning methods, including CNN, RF and KNN, to identify suspicious behavior patterns linked to malware. The detailed analysis of 30 research papers released between 2019 and 2020, which informs the choice of suitable algorithms for diverse cyber threats, further emphasizes the study’s uniqueness. The novel framework that has been suggested categorizes assaults and suggests certain machine learning techniques for identification, offering a useful instrument to improve comprehension and reactions to a variety of cybersecurity issues.

This study aims to investigate the relationship between patient satisfaction (PS) and the parameters in healthcare and supply chain management (HLSCM).

The structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) method have been employed to identify correlation and possible configuration of causal factors that influence PS, including lack of resilience (LS), lack of visibility (LV), cost management (CM) and integration and interoperability (II).

The results from SEM confirmed that PS is highly correlated with lack of visibility, CM and II as critical parameters. Moreover, fsQCA findings state that the configuration of high levels of both resilience and lack of visibility, as well as high levels of II, are crucial for PS.

The researchers also identified the configuration of factors that lead to low PS. The study’s results could assist healthcare providers in improving their supply chain operations, resulting in more effective and efficient healthcare service delivery and ultimately improving PS.

The fsQCA method used in the study provides a more nuanced understanding of the complex interplay between these factors. The inclusion of supply chain management characteristics as parameters in the evaluation of PS is a novel aspect of this research. Previous studies largely focused on more traditional factors such as physical care, waiting times and hospital amenities. By considering supply chain management factors, this study provides insights into an under-explored area of PS research, which has important implications for healthcare providers looking to improve their operations and PS.

This study addresses the growing cyber risks of banks by proposing an innovative, end-to-end dual-layer blockchain-based cyber fraud (CF) response system that integrates Safeguard (SG) and Block guard (BG) mechanisms. The comprehensive solution offers an actionable framework for bank managers to mitigate CFs by prioritizing fraud detection, leveraging early warning signals (EWS), and implementing tailored, need-based control measures before, during, and after a fraud event.

The study uses a multi-method approach, beginning with an extensive literature review on fraud identification, assessment, and prevention strategies. A theoretical framework is constructed to support the proposed SG and BG measures. Machine learning-based data analysis, using Artificial Neural Networks, is employed to dynamically assess the severity of CFs in real time. A managerial action plan for each phase of the fraud lifecycle is presented.

The research underscores the necessity for an adaptable, dual-layered response system that transitions from reactive to proactive and predictive mitigation strategies. The study introduces a novel approach incorporating SG and BG mitigation measures, enabling managers to detect early warning signals and implement robust post-fraud interventions.

The dual-layer approach enhances the sector's resilience to CFs by providing a robust, adaptive framework for fraud prevention and mitigation. This approach helps maintain stability, SG the bank's reputation, and improve overall risk management practices.

This study is unique in its development of an integrated SG and BG response system, combining machine learning, blockchain technology, early warning signals, and a structured before-during-after fraud control model. The research also highlights the critical role of bank managers in implementing and overseeing this innovative response system.