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This study underscores the effectiveness of Qualitative Comparative Analysis (QCA) when compared to conventional regression analysis (CRA) in the investigation of complex human systems. Utilizing historical secondary cross-national data from Lipset & Man (1960) spanning 18 countries, where CRA may be impractical, the research emphasizes the superior performance of QCA, specifically utilizing both crisp set QCA and fuzzy set QCA. The dataset includes variables such as democracy survival and its precursors, such as gross national product per capita, urbanization, literacy rate, and industrial labor force. In contrast to conventional regression results indicating an insignificant relationship between democracy survival and its antecedents, crisp set QCA identifies two distinct combinations of antecedents associated with high levels of democracy survival, albeit with limited solution coverage. Meanwhile, fuzzy set qualitative comparative analysis (fsQCA) reveals five combinations of antecedents linked to robust democracy survival, providing adequate solution coverage and consistency. These findings suggest that fsQCA excels in capturing the intricacies of real-life scenarios in human complex systems, offering more robust empirical solutions compared to crisp set QCA and conventional regression. As a result, researchers may find value in integrating fsQCA into their new projects focused on human complex systems.

This research delves into the complex impact of High Involvement Work Practices (HIWPs) on various facets of employee well-being and service outcomes within the framework of the trichromatic service conception. Utilizing the Job Demands-Resources (JD-R) model, the study uncovers the dual, both beneficial and detrimental, effects of HIWPs on service performance, work–family conflict, subjective well-being, and work-family enrichment. Examining the conflicting paths of job demands (workload) and job resources (customer orientation), the analysis incorporates the moderating influence of a strategic contextual factor—supervisor support. Data was collected through self-administered questionnaires from 475 respondents in Pakistani banks, and the analysis employed moderated mediation analysis using SPSS, AMOS, and the PROCESS Macro. All proposed hypotheses received support. The results indicate that HIWPs enhance service performance by promoting customer orientation but concurrently escalate workload, leading to adverse consequences for subjective well-being and work–family conflict. The study underscores the importance of implementing HIWPs under supportive leadership to maximize positive outcomes and mitigate negative consequences. Ultimately, this approach enables employees to effectively serve customers, maintain a healthy work-family balance, and contribute to the long-term growth and sustainability of organizations.

This research utilizes the fsQCA technique to investigate how a combination of corporate governance conditions or factors collectively influences the performance of banks. Examining key elements such as board size, busy directors, independent directors, CEO duality, and women on the board, the research employs data collected from the annual reports of 30 banks spanning from 2010 to 2020. The necessary condition analysis (NCA) underscores that no individual condition or factor is indispensable for the ultimate outcome. Nevertheless, the sufficiency analysis reveals distinct solutions, each representing a unique set of conditions or factors sufficient to generate the outcome. The study concludes that the relationship between corporate governance characteristics and bank performance is complex and multifaceted, with neither ROA nor ROE reliant on a singular input condition or factor. The theoretical contributions of the findings align with or partially support various theories and propositions within the realm of corporate governance. Notably, the application of fsQCA contributes to enhance the methodological understanding of corporate governance studies in existing literature.

This research investigates the glass cliff effect and the positions held by women in leadership roles, focusing on their impact on operational liquidity. The study delves into the relationship between corporate governance attributes and operational liquidity in 60 non-financial companies listed on the Pakistan Stock Exchange during Covid-19. Utilizing Quine-McCluskey technique and fuzzy set Qualitative Comparative Analysis (fsQCA), it examines the combined effect of Women on the Board, Board Size, Ownership by Blockholders, Board Qualifications and Busy Directors on Operational Liquidity. The necessary condition analysis (NCA) emphasises that firms can operate without reliance on any particular variable taken in the study. The sufficiency analysis provided an expanded understanding of the three conditions leading to the same outcome both before and during the pandemic. This research highlights the significance of the glass cliff effect and emphasizes the pivotal role of women in effectively managing liquidity during times of crisis. Additionally, it provides valuable insights for policymakers regarding the impact of Covid-19 on the interplay between corporate governance characteristics and operational liquidity.

Investors and governments have drawn attention to company governance due to the 2007 financial crash. This study aims to determine the impact of board characteristics, i.e. women on the board, busy directors, blockholder ownership, and director qualification on firm financial performance based on evidence from Pakistan. Former research on the impact of board features on company financial performance is built on contradictory theoretical viewpoints and factual results, which are primarily built on regression and are equivocal. Based on the con- figurational analysis, this study clarifies previously ambiguous findings concerning the link between keyboard attributes and business financial success. This research draws upon theories, including resource dependence and agency theory. The study utilized fuzzy-set qualitative comparative analysis to examine a sample of 60 non-financial companies listed on the Pakistan Stock Exchange (PSX). Data referred to the pre-crisis period. Findings have shown that different combinations of board attributes can significantly impact a firm profitability, i.e. return on assets (ROA) and return on equity (ROE). Practical implications spotlight the policymakers need to evaluate corporations current level of regulatory and competitive development to plan strategy accordingly. It emphasises unique governance solutions for the non-financial sector.

The present study inspects the comparative effects of inside shareholding on firm value for group-affiliated firms and non-group-affiliated firms in Pakistan. The research uses the excess-value as a performance measure by employing a chop-shop approach in treatment effects regression model (TERM). The results reveal that lower level and higher level inside shareholding negatively associated with firms’ value. However, it positively relates at a moderate level. Also, inside shareholding-value relationship differs significantly for group-affiliated firms and non-group-affiliated firms. Firms with inside shareholding at lower level appear to more visible in business groups, and these firms show adverse firms’ value consistent with divergence of interest effect. Nevertheless, inside ownership firms at a higher level, namely standalone firms, negatively affect firm value with entrenchment effect. The findings also confirm non-linearity in inside shareholding-firm value relationships.

The lack of women’s presence in firms’ top management positions reflects gender equity problems, especially in South Asia, including Pakistan, and contours a firm’s financial behavior. Based on the underpinning of the conceptual framework developed by a combination of fourteen femininity theories, the current study investigates women’s induction in top management and its impact on a firm’s financial behavior. We collected data from annual reports of 60 non-financial firms listed at the Pakistan Stock Exchange (PSX) for 2013–2019. The study uses the return of assets (ROA), firm’s stability (FSTB), and risk-taking behavior (RTB) as dependent variables. Meanwhile, board gender diversity (BGD), female CEO (FCEO), female director-general (FDG), and female in audit committee (FIAC) are taken as independent variables. A multiple regression diagnostics approach is applied to analyze the data. The study reveals the positive impact of BGD on ROA and FSTB. However, this effect is adverse to RTB. The FIAC shows a positive (negative) impact on ROA (RTB). It also finds a negative impact of FCEO and FDG on ROA and FSTB.

This study observed empirically the impact of corporate governance index on dividend payout policy by using the data of seventeen textile firms listed in Karachi Stock Exchange. The data covered the five years period from 2009 to 2013. The data were gathered from financial statements of all the sample firms. Multiple regression models were used to check the impact of corporate governance on dividend policy. No effect of corporate governance index on firm dividend policy was found, and the largest shareholders also had no impact on dividend pay-out policy. The association between payout policy and stock value was found to be significant positive. Gross profit margin and operating profit margin had significant positive impact on firm’s dividend payout policy. There is a significant correlation between firm performance and payout policy.

To facilitate the uncertainty analysis of a finite element multiphase multi-component transport model MOFAT, this paper provides guidance on latin hypercube sampling Monte Carlo (LHS-MC) sample size selection. To evaluate the ability of LHS-MC to produce output cumulative distribution functions (cdfs) that replicate random sampling Monte Carlo (RS-MC) cdfs, output cdfs obtained with LHS-MC sample sizes of 100, 300, and 500, and a RS-MC sample size of 10 000 are compared using the two sample Kolmogorov-Smimov test. The LHS-MC cdfs for the three different sample sizes are able to accurately replicate the corresponding RS-MC cdfs for benzene, toluene, ethylbenzene, and xylene (BTEX) concentrations in the water, gas, and solid phases. The stability of LHS-MC is also evaluated by comparing three replicates of a LHS-MC sample. The three replicates are all able to accurately replicate the corresponding RS-MC cdfs for all BTEX concentrations in all three phases. Key words: uncertainty analysis, Monte Carlo, latin hypercube sampling, sample size, MOFAT, multiphase, multi-component. Dans le but de faciliter l'analyse d'incertitude d'un modele MOFAT de transport a elements finis polyphase et a multicomposantes, cet article se veut un guide pour la selection de la dimension de l'echantillonnage latin hypercube Monte Carlo (LHS-MC). Pour evaluer la capacite du LHS-MC a produire des fonctions de distribution cumulative (cdfs) qui reproduit les cdfs de l'echantillonnage aleatoire Monte Carlo (RS-MC), les cdfs de sortie obtenues avec des tailles d'echantillons LHS-MC de 100, 300 et 500 ainsi qu'un echantillon RS-MC de taille 10,000 sont comparees en utilisant les tests de Kolmogoroff-Smirnoff a deux echantillons. Les cdfs LHS-MC pour les trois differentes tailles d'echantillons peuvent reproduire avec precision les cdfs RS-MC correspondantes pour les concentrations de benzene, de toluene, d'ethylbenzene et de xylene (BTEX) dans les phases liquides, gazeuses et solides. La stabilite du LHS-MC est egalement evaluee en comparant trois replicats d'un LHS-MC. Les trois replicats peuvent tous reproduire precisement les cdfs RS-MC correspondantes pour toutes les concentrations de BTEX dans les trois phases. Mots-cles : analyse d'incertitude, Monte Carlo, echantillonnage latin hypercube, taille de l'echantillon, MOFAT, polyphase, multicomposantes. [Traduit par la Redaction], Introduction The description and characterization of uncertainty introduced into the modelling process by parametric variability is an important component of any Tier 3 Risk Based Corrective Action (RBCA) of petroleum [...]

Environmental risk management strategy often encounters conflicting criteria of a subjective and objective nature that are associated with a particular management system concerning multicriteria decision making. In this study, a combination of subjective and objective criteria for risk management has been applied for drinking water treatment technology. Fuzzy set theory has been incorporated in this study. Fuzzy triangular membership functions have been developed to capture uncertainties of the model parameter values. The analytic hierarchy process has been incorporated to construct subjective priority schemes for different hierarchy level attributes. In developing subjective priority schemes, flexible ranges of importance were considered; thus the uncertainties associated with crisp values were incorporated. Using the concept of entropy, subjective importance of the objective attributes have been transformed into integrated importance. The overall ranking was evaluated based on subjective and objective criteria. An example of human health risk management from drinking water disinfection by-products has been presented through several drinking water treatment technologies. Finally, the best treatment technology is outlined. DOI: 10.1061/(ASCE)0733-9372(2006) 132:10(1264) CE Database subject headings: Public health; Decision making; Disinfection; Fuzzy sets; Uncertainty principles.