Search results

This study examines the impact of five dimensions of decent work on the faculty engagement in Pakistan’s higher education institutions. Furthermore, it examines the moderating influence of intrinsic religiosity on the associations above.

This research employed a cross-sectional approach to collect data from 542 faculty members working with higher education institutions through electronic and in-person questionnaire administration.

The findings indicate that safe interpersonal working conditions, opportunities for free time and rest, adequate compensation, and the availability of healthcare services significantly positively impact the level of work engagement among faculty members. Additionally, the research revealed that intrinsic religiosity reinforces the previously established significant associations.

The research acknowledges specific constraints that could impact the applicability of its findings, including the utilization of a cross-sectional methodology, the dependence on self-reported information, and the possibility of sample biases. Subsequent investigations may rectify these constraints to provide a more all-encompassing comprehension of the subject matter.

The findings possess practical significance for the management of HEIs in cultivating an ideal working atmosphere for faculty members. Ensuring adequate compensation, secure working environments and healthcare accessibility is underscored to enhance faculty engagement. Furthermore, acknowledging the significance of intrinsic religiosity can improve faculty engagement.

This research contributes to the current body of literature by investigating the complex relationship among decent work, faculty engagement, and intrinsic religiosity in the specific context of higher education institutions in Pakistan.

This paper aims to introduce a sensorized surgical grasper with a novel flexible capacitive tactile force sensor integrated within the surgical grasper for minimally invasive surgery (MIS) and robot-assisted MIS (RMIS) procedures.

The proposed sensor offers a unique configuration of sensing electrodes with one top excitation electrode and three bottom electrodes enabling the measurement of normal and shear forces without incorporating any complex decoupling algorithms. The design of the sensor is optimized using finite-element method simulations, ensuring efficiency and reliability.

Experimental validation, real-time sensor response and application in lump detection through stiffness assessment demonstrate the decoupled force response (0–5 N normal range and 0–2 N shear range) with high sensitivity 0.0124/N, repeatability and hysteresis response with 5.65% and 4.7% errors respectively.

The compact design of the sensor makes it compliant with surgical graspers and therefore enhances the overall efficiency of robotic surgical procedures. The sensorized surgical grasper is fabricated using conventional machining and rapid prototyping techniques, presenting a cost-effective solution for adoption.

This study investigates the influence of paradoxical leadership on employee transformative learning in higher education institutions (HEIs). Based on paradox theory, this research examines how a paradoxical mindset mediates this relationship and explores the moderating role of employees’ moral values in developing a paradoxical mindset and fostering transformative learning.

The research adopted a quantitative approach. In three phases, data were collected from 411 randomly selected faculty members of HEIs in Pakistan to assess their perceptions of paradoxical leadership, followers’ paradoxical mindset, moral values and transformative learning outcomes. Structural equation modeling was employed for analysis in AMOS26.

The findings reveal paradoxical leadership’s positive and significant impact on transformative learning, mediated by developing a paradoxical mindset. Moral values positively moderate the relationship between paradoxical leadership and developing a paradoxical mindset. However, the moderating effect of moral values on the link between a paradoxical mindset and transformative learning was insignificant.

The study suggests that organizations, particularly HEIs, should cultivate paradoxical leadership to navigate inherent tensions and contradictions, fostering an environment conducive to transformative learning. Developing a paradoxical mindset among employees is crucial for enhancing adaptability and learning, with moral values playing a pivotal role in amplifying the effectiveness of paradoxical leadership.

This study contributes to the literature by providing empirical evidence on the mechanism through which paradoxical leadership influences transformative learning. It extends paradox theory to the context of transformative learning, highlighting the importance of cognitive and ethical dimensions in leadership and learning processes within HEIs.

This research explains the critical role of technological readiness and green dynamic capabilities in enhancing the sustainability performance of manufacturing firms, which is pivotal for achieving the United Nations’ Sustainable Development Goals. The theoretical framework is grounded in the dynamic capability theory, positing that technological readiness enhances a firm’s green dynamic capabilities, and employee green behavior moderates the effect on the sustainability performance of manufacturing firms.

Quantitative data from 1,660 managerial employees of a diverse sample of manufacturing firms was aggregated at the firm level using interclass correlation and interrater agreement, ensuring robustness using at least two responses per firm. With the final dataset of 418 firms, structural equation modeling was conducted using AMOS26.

The findings reveal that technological readiness positively affects sustainability performance and enhances it through green dynamic capabilities. Furthermore, the study highlights the positive moderating role of employees’ green behavior, amplifying the impact of green dynamic capabilities on sustainability performance.

This research makes a novel contribution to the body of knowledge by integrating dynamic capability theory with empirical evidence on sustainability performance. It represents a significant step toward promoting a more sustainable and responsible future for organizations and society and provides comprehensive insights into the complex interplay of these variables. These insights are crucial for academia, industry practitioners and policymakers striving to foster sustainable practices within the manufacturing sector.

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.

This study aims to investigate the relationship between different hedonic (e.g. enjoyment and escapism) and utilitarian (e.g. achievement and challenge) gratifications and continuous intention to play eSports, considering the mediating role of gamer’s satisfaction. Uses and Gratification theory (U&G) has been employed as the study’s theoretical framework.

The present study used a survey research method and a self-administered questionnaire to collect the data. The data was gathered on-site from students of three universities in Pakistan’s Islamabad and Rawalpindi regions. Study respondents involved people from Gen Z and Gen Y aged between 18 to 25 and 26 to 40. A total of 401 responses were evaluated using the partial least squares structural equation modeling (PLS-SEM) and necessary condition analysis (NCA).

The PLS-SEM findings evidence that eSports players’ hedonic (e.g. enjoyment and escapism) and utilitarian (e.g. challenge) gratification positively impact gamers’ satisfaction, which subsequently drives eSports gamers’ continuance intention behavior. Furthermore, gamers’ satisfaction positively mediated the relationship between gratifications (e.g. enjoyment and escapism refer to hedonic, whereas achievement and challenge represent utilitarian) and continuance intentions. NCA on eSports gamers’ satisfaction and continuance intention identified critical predictive factors. The analysis revealed that only enjoyment is necessary for predicting satisfaction. Interestingly, NCA results also indicated that enjoyment, achievement, escapism, challenge and satisfaction are all necessary for predicting eSports gamers’ continuance intention.

This study investigates the mediating role of eSports gamers’ satisfaction between gamers’ perceived gratifications (i.e. enjoyment, escapism, achievement, challenge) and their continuous intention to play in the Pakistani context. More importantly, we employ a multi-method approach (e.g. a combined approach of PLS-SEM with NCA) to determine the sufficient and necessary conditions of the outcome variable comprising satisfaction and continuous intention.

This study aims to examine the understudied topic of Islamic entrepreneurship by adapting the framework of waqf-based entrepreneurship to identify the crucial factors driving waqf-based entrepreneurs’ motivation.

A partial least squares structural equation model was used to validate the hypotheses, and in-depth interviews were conducted to gain deeper insights into the findings.

The key findings revealed that self-commitment, entrepreneurial skills and family support exert a significant and positive influence on waqfpreneurs’ motivation to engage in waqf-based entrepreneurship, with self-commitment playing a mediating role between self-actualisation and waqfpreneurial motivation. Additionally, the study proposes categorisations of waqfpreneurs based on the volume of waqf funds managed; their capacity to execute waqf-based entrepreneurship; and institutional performance metrics.

The limited sample size restricts the generalisability of the study. Future research should use a larger sample to generate more broadly applicable results. In addition, the methodology can be replicated in other countries to identify new factors influencing waqfpreneurs’ motivation or to uncover aspects not explored in this research. Future studies could also use qualitative methodologies such as grounded theory, ethnography or case studies. This would allow for a deeper exploration of motivational factors not yet captured, directly from the lived experiences of waqfpreneurs/nazhirs.

The study provides evidence of the key factors that influence waqf-based entrepreneurship, contributing to the literature on entrepreneurship and waqf. It also offers valuable insights for the government and other stakeholders into strategies to motivate waqf-based entrepreneurs, ultimately fostering the development of waqf assets, value creation and sustainable waqf benefit distribution.

The study aims to address the lack of research on Islamic entrepreneurship by specifically modifying the framework of waqf-based entrepreneurship to investigate the key factors that influence individuals’ motivation to conduct waqf-based entrepreneurship and management activities.

The purpose of this study is to investigate how Industry 4.0 (IR 4.0) operates within the context of the post-COVID-19 environment and its impact on the economic, environmental and social sustainability of the manufacturing industry in a developing economy. By delving into this subject, the authors aim to understand the mechanisms through which IR 4.0 influences various facets of sustainability within the manufacturing sector.

A cross-sectional research design is used using purposive sampling and hypotheses were developed based on seminal theories and literature. Data was collected from 191 Malaysian manufacturing firms that use IR 4.0 technologies. The partial least squares structural equation modeling technique was used to explore how post-COVID uncertainty environment impacts manufacturing sustainability through IR 4.0 adoption.

During the highly uncertain era of the post-COVID-19 pandemic, the implementation of IR 4.0 adoption has had a favorable effect on the manufacturing industry, enhancing process efficiency, automation and data granularity. However, it is worth noting that automation does not significantly contribute to environmental sustainability and data granularity does not have a noteworthy impact on economic sustainability. On the other hand, process efficiency has a positive and significant influence on all three dimensions of sustainability. Moreover, data granularity positively affects environmental sustainability, whereas automation positively impacts both social and economic sustainability.

This study emphasizes the importance of policy interventions to harness the transformative power of IR 4.0 and address the identified concerns. In addition, the findings offer valuable insights for mid-level operational managers, enabling them to actively participate in the creation of sustainable policies in partnership with top management. It is expected that these actions, which involve making necessary adjustments in the manufacturing process, will yield tangible outcomes for sustainable development.

This study offers valuable insights into the relationship between the uncertain post-COVID-19 environment, referred to as hyper-uncertainty and the adoption of IR 4.0 in the context of manufacturing sustainability.

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.

An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R²), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.

The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.

This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.

Exploiting a sample of 80 conventional banks (CBs) and 35 Islamic banks (IBs), this study aims to distinguish the IBs’ performance from their conventional peers in 7 Middel East and North Africa (MENA) economies over the period 2005–2014 covering the 2008 GFC.

To avoid misleading results, this research used panel-corrected data from outliers effects by quantile method. Then, following the use of the two-sided Student’s t-test and the discriminant function analysis (DFA), we adopt nonlinear panel models (Random Logit and Pooled Probit) to further distinguish between banks. Then, we focus on the stability side through dynamic Generalized method of moment (GMM) linear models and interaction variables to capture the 2008 global financial crisis (GFC) impact on IB performance.

Univariate tests show that IBs are, on average, less profitable, more liquid and capitalized, less stable, have higher credit risk and are more solvent than CBs. In addition, the difference between the two types of banks was significant pre- and post-GFC; IBs are more profitable pre-GFC and more solvent post-GFC. In accordance with the univariate t-test results, the nonlinear pooled probit model (random logit) confirms that banks, which have more liquidity, are better capitalized, more solvent and less stable (less stable) are more likely to be IBs. From the DFA, stability was the first financial ratio important to discriminate between the two types of banks. In line with the DFA results, from the dynamic models, once the interaction variables are integrated, the GMM estimation result suggests that stronger macroeconomic stability and higher profitability, capital adequacy ratio (CAP) and liquidity are linked to increased IBs stability in the 7 MENA economies post-2008 GFC.

The present study contributes to the ongoing debate by conducting a formal empirical analysis, taking account of a range of considerations (outliers correction, interaction variables and 2008 GFC impacts) that to the best of our knowledge have not been considered by prior studies for the MENA zone.