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The purpose of this article is to investigate the influence that firm-specific characteristics, such as organisational capabilities, risk management methods and stakeholder relationships, have on political risks (PRs) that are associated with multinational construction projects in Pakistan.

The methodology employed in this investigation involved the acquisition of data through the use of questionnaires administered to experts in the construction industry. The research applied a quantitative method, and the sources of the data are from the Pakistani stakeholders. One hundred questionnaires were used for the data collection during field visits. Based on the data, it has been ensured that the valid questionnaires were utilised, and the data were tested for validity and reliability. The analysis tool utilised was SPSS software. For the questionnaire, a total of 15 firm-specific factors were considered in order to design the survey, which specifically targeted the identified features. The factors identified as risks were investigated using quantitative method to determine firm-specific risks.

It was found that when stakeholders have a better grasp of these dynamics, they are better able to strengthen their resilience and efficacy in managing PRs, which ultimately increases the likelihood that the project will be successful.

International construction projects (ICPs) in emerging countries are substantially impacted by PRs, which can have a considerable impact on their success and sustainability. The study is localised and not generic as it is limited to Pakistan, and the risk factors considered are firm-specific but related to PRs.

By identifying key risk factors, these firms can develop targeted risk management strategies, leading to enhanced decision-making and more efficient resource allocation. Effective strategies include diversification, local partnerships and comprehensive risk assessments tailored to the unique challenges faced by international contracting firms in Pakistan.

ICPs in emerging countries like Pakistan face critical problems, which include the presence of PRs. Although the larger political environment plays a significant part, the manner in which businesses navigate and mitigate PRs is also influenced by firm-specific elements.

The study is novel in terms of the factors looked at, the data, the conceptual framework and the findings of the study. The dynamic political scene, which is characterised by instability, policy changes, corruption and geopolitical conflicts, poses significant dangers to the timeliness of projects, the expenses of such projects and the investments that are made in those projects.

This study explores the factors influencing knowledge hiding (KH) in international construction projects (ICPs), focussing on the role of ethnic minorities (EMs) and interpersonal distrust (ID). It also aims to understand how these factors influence KH and explore the mediating effect of ID on the relationship between EMs and KH.

A survey questionnaire was developed and distributed to professionals participating in ICPs. We used structural equation modelling (SEM) to analyse 294 valid responses, examining the effect of EMs, ID and demographic variables on KH behaviours. Our approach integrates insights from social identity theory (SIT) and actor network theory (ANT) to provide a comprehensive framework for understanding the observed dynamics.

The findings reveal that EMs significantly influence KH behaviours, with ID partially mediating this relationship. Additionally, demographic variables such as gender and age also play significant roles in KH behaviours. However, the degree of education did not show a significant impact on KH. Our results emphasise the critical importance of addressing ID and fostering inclusive environments to reduce KH.

While our study sheds light on the complex dynamics of KH in ICPs, further research could explore additional contextual factors and organisational influences. While our study emphasises the importance of inclusive practices and trust-building to mitigate KH, it also recognises the need for a deeper understanding of power dynamics and organisational contexts.

Our findings underscore the importance of creating transparent and inclusive cultures of knowledge sharing (KS). Implementing inclusion initiatives and providing cultural awareness training can enhance project outcomes and organisational success. We also propose a practical framework to mitigate KH by promoting trust, inclusivity and effective KS practices.

This study contributes to the understanding of knowledge management in multicultural project teams by integrating SIT and ANT, offering a comprehensive perspective on the factors driving KH in ICPs. The findings pave the way for future investigations into power dynamics and organisational contexts within ICPs.

The purpose of this study is to examine the effect of country- and firm-specific factors on foreign investment in Pakistan.

This study uses time-series data for country-level determinants and uses panel data for 100 listed non-financial companies selected based on market capitalisation from 2005 to 2015.

Findings suggest that the stock market returns and liquidity of the country significantly positively influence the foreign portfolio investment (FPI) in Pakistan. Whereas, economic growth surprisingly is negatively related to foreign portfolio investment. In addition, findings reveal that firm size, financial leverage, dividend yield and global depositary receipts (GDR) have a positive impact on the total foreign investment at firm level. Further, foreign institutional investors prefer to invest in those firms that are large, pay high dividends and issue GDR. Furthermore, findings suggest that foreign direct investors tend to invest in firms that are financially leveraged and have low capital gain yield.

At the country level, this study recommends that stock market performance, economic growth and foreign reserves of the country should be maintained and improved to attract FPI. At the firm level, this study recommends issuance of global depositary receipts and high dividend payouts for those firms that are interested in institutional investment in Pakistan.

To the best of authors' knowledge, this study is the first that examines the effect of firm-level factors along with country-level factors on foreign investment in Pakistan.

Financial literacy is a crucial element of financial decision-making, exerting significant influence on the behaviour of individual investors, while making budgetary, house financing, stock investing and retirement planning decisions. So, the purpose of this research is to determine the relationship between financial literacy and behavioural biases of individual investors in Pakistan.

In this research paper, a sample of 300 observations was obtained through questionnaires from individual investors residing in Lahore and invested in Pakistan Stock Exchange. The data obtained, was passed through Cronbach’s Alpha and Exploratory Factor Analysis (EFA). The hypothesis developed for the research was tested by Pearson’s Chi-square and Ordinal Regression Analysis.

The hypothesis testing of the research concluded that there is a negative association between financial literacy and behavioural biases of individual investors. So, it means; with an increase in level of financial literacy, the likelihood of investor facing behavioural biases reduces. It also appeared that male respondents have more financial literacy than female respondents

Previous studies in the field of finance, identified different factors causing the financial behaviour of individual investor of Pakistan, and also focused on level of financial literacy in Pakistan, but these studies have not emphasized the crucial relationship between financial literacy and behavioural biases of individual investors. Thus, the unique empirical analysis developed in this paper has accentuated the financial literacy as a factor that mitigates behavioural biases of individual investor.

As the global focus on supply chain management has shifted toward the importance of digitalization, resilience and sustainability to ensure viability, this paradigm merits special consideration in the industrial supplier selection process in a VUCA (Volatile, Uncertain, Complex and Ambiguous) world. Additionally, the increasing geopolitical challenges further complicate the industrial supplier selection process, necessitating robust decision-making frameworks. Thus, this paper aims to present a decision-making system using a fuzzy inference system (FIS) for industrial supplier evaluation and selection, considering a new criterion: viability.

Fuzzy set theory, particularly a FIS, is used to address the subjectivity of decision-makers’ preferences. The suggested method’s validity is evaluated using a real automotive case study for industrial supplier selection situations.

Seventeen key criteria for viable industrial supplier selection were identified and used to evaluate and select the case study firm’s industrial supplier. The chosen supplier (B) demonstrated superior resilience, sustainability and digitalization capabilities, making it preferable to others. Specifically, supplier (B) exhibited exceptional adaptability to disruptions, a strong commitment to sustainable practices and advanced digital integration that enhances operational efficiency.

This study provides valuable insights for researchers and professionals by proposing a comprehensive industrial supplier selection system. Integrating diverse criteria is essential for viable performance in supply chains that enhances robustness and adaptability, supporting more strategic decision-making in supplier evaluation amid global and network-related challenges.

This novel paper introduces a new criterion, i.e. viability, in the industrial supplier selection process in the VUCA environment. In addition, it proposes a decision-making system for viable supplier performance evaluation. Furthermore, it validates the proposed FIS in an automotive case study.

This study aims to empirically explore e-banking service quality and its impact on the e-banking loyalty through a mediating impact of e-banking satisfaction. The account holders of three domestic systemically important banks of Pakistan were surveyed during COVID-19 to examine the electronic services provided by these banks.

The data was collected through an adapted questionnaire by using emails and messaging applications. The database of a local marketing company in Pakistan was used, and 976 responses were included in the analysis. The structured equation modeling was used to test the propositions of study.

The findings delineate that reliability and website design proved to increase e-banking loyalty, particularly during COVID-19. The link between e-banking privacy and security and e-banking loyalty was proved as fully mediated by e-banking satisfaction; however, indirect effect of the reliability and website design with e-banking loyalty was partially mediated.

In strategic planning of e-banking mechanisms and the associated consumer behavior, the results of this study can be helpful for policymakers. In case of similar epidemics and natural calamities, consumers may depict similar behavior as shown during the lockdown and social distancing during COVID-19; hence, the study can help regulatory bodies in preparing their safety roadmap.

The mediating effect of e-banking satisfaction between privacy & Security and e-banking loyalty implies that customer give importance to secure e-banking platforms. There can be a variation in their loyalty because of privacy concerns. The application of cognitive–motivational–relational (CMR) theory in a relationship between e-banking service quality and e-banking loyalty with a mediating role of satisfaction is an emotional response to capture the behavioral changes during COVID-19. It enables researchers to understand the CMR theory concerning COVID-19 and e-banking perspective.

The paper assesses the moderating function of institutions in the financial development and environmental nexus covering India for the time period 1980–2019.

Deviating from extant literature which has mostly used emissions of major greenhouse gasses as a measure of environmental quality, the present study uses a broad measure of environmental quality called ecological footprint (EFP). Financial development is measured using a robust proxy recently introduced by International Monetary Fund (IMF). This index is multifaceted and covers three broad dimensions of financial sector in terms of depth, efficiency and access of both financial institutions and markets, thus outperforming the exclusively bank-based measures used in the past literature. Further institutional quality index is generated using the data from international country risk guide. Finally, autoregressive distributed lag model is used for the empirical estimation of short-run and long-run results.

The empirical estimates reveal that financial development and institutional quality are good for long-run environmental sustainability of India, whereas economic growth degrades the environment in the long- run. The results also attest to the existence of pollution heaven hypothesis in India for long run. Furthermore, regarding the moderating role of institutions, the study reveals that institutional quality complements financial development in affecting environment in the short run. While as, in the long run, they play a substitutive role whereby sound institutions cover-up the inefficiencies in financial system.

First, the paper uses the index of financial development developed by the IMF in order to quantify the level of financial development in India overtime. The index is based on three key dimensions of financial development such as the depth, efficiency and access of both financial institutions and markets. However, the index completely neglects the role of financial stability in determining financial development. Thus, future studies that are based on this IMF introduced index of financial development should incorporate the stability dimension to it. Second, this empirical study focused exclusively on India and employed aggregate EFP to measure environmental quality. Further studies can complement the content of this research by conducting similar studies to capture country-specific characteristics of other emerging economies and also scrutinize the impact on the six sub-indices of EFP.

The results of the study reveal that the effect of financial development, and institutions on ecological footprint is sensitive to time dynamics. Moreover, the findings offer important policy implications to government and policy makers in India on how to curb the menace of environmental degradation.

The paper addresses the gap in the literature by examining the moderating role of institutional quality in the financial development and ecological footprint nexus in India. Furthermore, the authors employ a robust proxy for both financial development and environmental quality unlike extant studies on India.

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 explore the phenomenon of Islamic religious communication and how Islamic banks in Pakistan use religion-based communication, along with its expected outcomes.

Transcendental phenomenology approach is opted using a multi-stage data collection strategy consisting of observations, documentary reviews and semi-structural interviews to get deep into the phenomenon in a particular context.

Findings highlight Islamic religious communication as workplace Islamic da’wah that is majorly categorized into compulsive da’wah, objectics da’wah and impulsive da’wah, serving its role in bringing spirituality to work through work-faith integration.

The finding of the study can be used in planning, formulating and implementing Islamic da’wah-based model to induce spirituality at work.

This study is the first of its type exploring Islamic da’wah in an organizational context as a mean to bring spirituality at work.

The board structure (BS) is pivotal in modern corporate governance (CG). This study aims to investigate BS variables (BSIZE, BIND and chief executive officer [CEO] duality) and their correlation with risk-taking behavior indicators, enriching the understanding of how CG shapes financial institutions’ (FIs) decision-making in Pakistan.

By scrutinizing data from 67 financial entities listed on the Stock Exchange of Pakistan spanning from 2011 to 2022 through panel data regression techniques, the research emphasizes that BS holds a substantial influence over the risk tendencies exhibited by these firms.

Key findings suggest that board size has a positive influence, aligned with previous CG research. Smaller boards perform better and avoid excessive risk-taking, contrasting some negative relationship claims. More independent directors are recommended to curtail risk and financial disruption. Holding both CEO and chair roles reduces risk exposure, resonating with reputational and employment risk theory. It is essential to recognize that BS’s impact on risk-taking is nuanced and context-dependent.

Policymakers, scholars, practitioners and investors working in the market for financial companies might greatly benefit from the empirical findings of this study. Imposing mandates on FIs to uphold adequate capital reserves functions as a safeguard against unforeseen losses, thereby diminishing the probability of unwarranted risk-taking.

Prior studies in this domain predominantly focus on nonfinancial sectors. In addition, existing research often explores the relationship between BS and firm risk-taking solely within the banking sector, overlooking other FIs. This study contributes by using a comprehensive data set encompassing all types of FIs, thus extending the existing literature.