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This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.

Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.

The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.

This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.

Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.

This paper aims to add to the existing body of literature on this subject by advocating how waqf-based entrepreneurship can be practiced in Malaysia.

The paper begins by presenting an overview of waqf and its role in entrepreneurship and proceeds by proposing a model of waqf-based entrepreneurship which is synthesized from various models existing in the Islamic world.

The paper concludes by recommending waqf-based entrepreneurship as an alternative socio-economic framework of society’s wellbeing.

The research is limited to the preliminary aspects of waqf entrepreneurship.

Waqf organization may be able to finance its own businesses through crowdfunding and other methods and also disburse waqf funds to small and large ventures.

The waqf system is a social tool that not only finances social development projects but also has social economic alternatives to assist poor and underprivileged groups in the society. This paper is toward such a socio-economic direction.

This paper might be considered the first attempt to detail the practical aspect of waqf entrepreneurship, in terms of enterprises to be financed, and how the funds to be accumulated.

The Indonesian Waqf Board and United Nation Development Program are developing green waqf in Indonesia. Development of green waqf in Indonesia as a response to save the earth from environmental damage and other social impacts. This paper aims to measure public perceptions about willingness to participate in making donations to the green waqf program in Indonesia.

Modifying the Theory of Reasoned Action framework, questionnaire data were collected from 311 Muslims in Indonesia. Data were analyzed using the partial least squares structural equation modeling method.

The findings show that attitude, subjective norm, product knowledge and trust influence the Muslims in Indonesia to donate to green waqf. In contrast, Islamic religiosity harms the intention to donate in green waqf but is insignificant.

This research was conducted using a quantitative approach with a limited sample of several communities, so the results cannot be generalized. Further investigation needs to be carried out by involving a more diverse sample to get better results. However, the results of this study can be used as an illustration of how Muslims behave in donating green waqf.

These results imply that to develop green waqf in Indonesia, especially in attracting waqf candidates willing to make donations, waqf institutions must carry out engineering to shape the attitude of prospective donors through various activities such as socialization and education of the green waqf program. Waqf institutions must also build public trust by involving public figures to campaign for the green waqf program. This will likely increase prospective donors’ active participation in donating their money to develop green waqf in Indonesia.

Waqf is a severe concern for the Indonesian Government, including waqf for the environment. To the bets of the authors’ knowledge, this paper is the first attempt to look at the behavior of the green waqf model in Indonesia. Thus, the acceleration of waqf development can be realized and is expected to impact the community significantly.

This paper aims to provide a review of the existing literature available on working capital (WC) and working capital management (WCM).

A systematic literature review (SLR) methodology is used to review 187 articles selected from referred journals, books and international conferences for the period 1980-2017.

This comprehensive review reveals that much of the focus in the existing literature is paid on investigating the empirical relationship between WCM and firm performance. Furthermore, the attention has been paid towards studying the WC practices. The behavioural aspects, qualitative studies, survey studies and systematic theory development have been ignored in most of the prior studies. These areas have a broader scope for future research.

This study is based on literature review and theoretical in nature. Therefore, it does not have any empirical results.

So far, a limited literature review studies have been conducted in WCM perspective. This review provides various emerging trends, which may be considered in future research for providing a deep understanding of WCM.

This is the first time a detailed review of WCM literature has been conducted by using SLR for the period of 1980-2017. This review will be useful for researchers, business policymaker, finance professionals and all other having direct or indirect concerns with WCM study.

This study aims to propose Islamic solutions to the Covid-19 health and economic crises, specifically using Islamic social finance (ISF) instruments, including zakat, infaq and waqf.

This study applies the qualitative content analysis method, guided by a model of composite approaches of poverty alleviation in Islam, integrated Islamic commercial and social finance (IICSF) and crisis management of Umar bin Khattab, to construct various programs and/or policy actions toward economic recovery in Indonesia.

The results show that ISF with its instruments, especially zakat, infaq and waqf could help the government and the economy to recover from the crisis. The proposed solutions include: save lives, including medical assistance using zakat-infaq and health-care waqf using waqf; save households, by creating a social safety net and graduation program using zakat-infaq; save businesses, especially micro-small enterprises (MSEs), through financial and business assistance (especially digital marketing) leveraging zakat-infaq-waqf and save financial institutions, especially micro-small financial institutions, by the development of cash waqf and the adoption of fintech and IICSF, especially in Islamic financial institutions targeting MSEs.

This study is exploratory in nature, which needs further investigations using more sophisticated qualitative and/or quantitative methods.

If the above programs using ISF instruments are implemented, the economic surplus would be re-established and the acceleration of economic recovery can be realized.

The successful adoption of ISF could at the same time reduce poverty, accelerate MSEs development and improve equitable well-being.

The Covid-19 pandemic has caused health, economic and social problems, which must be solved holistically, including ISF within IICSF.

The purpose of this paper is to explain the multi-stage dynamic process of financial distress. An attempt is made to explore multiple adverse heterogeneous events of financial distress leading a firm closer to bankruptcy progressively.

Sample comprises 321 ongoing, 54 suspended and 91 delisted non-financial firms from Pakistan Stock Exchange. Financial distress is segregated into three stages, i.e. profit reduction, mild liquidity (ML) and severe liquidity (SL). Flow diagrams are used to explain the transition of healthy firms through proposed stages of financial distress.

Results showed that firms liquidated/winding-up by court documented SL problems and closed their operations well before the delisting year. It is found that healthy firms are more likely to face SL when faced ML problem at first stage. Distressed firms can recover to a healthy position at any stage, however after approaching to SL, recovery is less expected.

The proposed process will provide a foundation for future studies to develop more relevant, robust and accurate early warning system of corporate failure that will help stakeholders to respond potential crisis accordingly and timely.

Previously, most of the studies used the ex post definition of bankruptcy that is criticized due to the contextual application, sample bias and non-segregation by the degree of liquidity problems. The originality of the proposed ex ante model is its segregation into a three-stage process that can be generalized regardless of specific bankruptcy law.

This study examines direct effect of leader-member exchange (LMEX) and learning orientation (LEOR) on workplace innovation (WPIN) and indirect effect between underline relationships in presence of mediators such as creative self-efficacy (CRSE), thrive at work (THAW), task interdependence (TAIN) work significance (WOSI) and creative performance (CRPE). Moreover, this study investigates the serial mediating effect of CRSE, WOSI, THAW, TAIN and CRPE between LMEX, LEOR and WPIN in entrepreneurial small and medium-sized enterprises (SMEs).

This study collected a total of 286 usable responses from entrepreneurial SMEs in three major business cities in Pakistan. In this cross-sectional study, data were gathered through self-administered surveys using purposive sampling approach and tested hypotheses using structural equation modeling (SEM).

The findings suggested insignificant direct effect of LMEX and LEOR on WPIN in the presence of mediators. Interestingly, CRSE, THAW, TAIN and CRPE were identified as significant mediators between LMEX, LEOR and WPIN. However, WOSI was found to be an insignificant mediator in the observed context. Moreover, the results revealed significant serial mediating effect of CRSE and CRPE with work context elements such as THAW and TAIN between LMEX, LEOR and WPIN, while serial mediating effect of WOSI in underline relationships found insignificant.

The study emphasizes that chief executive officers (CEOs) of entrepreneurial SMEs should prioritize individual, team and organizational factors to improve WPIN for competitiveness. Entrepreneurial management should focus on building strong relationships with employees to foster creativity and create a learning-oriented work environment that improves motivation and collaboration, thereby boosting employees' CRSE and CRPE, leading to enhanced WPIN.

This research offered a novel research framework and identified critical mediators and serial mediators between LMEX, LEOR and WPIN for entrepreneurial SMEs in developing countries, a domain grossly underrepresented in the literature.

The purpose of this study is to draw from the conservation of resources (COR) theory and investigate two separate models termed Model A and Model B. Model A examines the mediating role of life satisfaction (LS) on the relationship between servant leadership (SL) and lecturers’ attitudinal loyalty (AL) and behavioral loyalty (BL). Model B examines the sequential mediating role of LS and AL on the link between SL and BL.

Data were collected using a cross-sectional survey from 247 public university lecturers which were analyzed through SPSS, structural equation model (AMOS 23), and PROCESS Macro v4.0.

Study findings revealed that LS fully and partially mediates the relationships between SL and lecturers’ AL and BL, respectively. Furthermore, LS and AL sequentially mediate the relationship between SL and BL.

The study provides insight to university management into how their selfless and caring behavior can contribute to lecturers' retention. As such, university management should provide an environment that fosters a culture of selfless and caring leadership behavior.

The study contributes to the theoretical development of SL by explicating the mechanism that links SL and positive outcomes in the workplace. The major contribution lies in exploring the mediating role of LS on the link between SL and lecturers’ AL and BL on one hand and the sequential mediating role of LS and AL on the link between SL and BL on the other hand in a context characterized by high-power distance.

The research objective was to check the impact of industry 4 (I4) technologies on environmental sustainability (ENS) with the mediating role of green supply chain management (GSCM) of textile companies in Saudi Arabia.

Data was collected from those respondents who were linked with management and also have knowledge of I4 technologies. The researchers distributed 500 questionnaires among respondents for data collection, 350 questionnaires were received, and used for analysis. The researchers employed the quantitative research approach and cross-sectional research design.

The results indicate that I4 has a positive effect on ENS and GSCM practices except for green purchasing where I4 has an insignificant impact on green purchasing. On the other hand, GSCM practices also significantly mediate between I4 and ENS except for green purchasing which has an insignificant mediating effect.

This study has a great theoretical contribution to literature as it provides strategic insight to managers as well as policymakers. From the perspective of resource-based view, this study is supportive to use I4 technology practices in GSCM. Furthermore, the current research suggests managers to implement I4 technologies and adopt the GSCM practices. These practices should be part of environmental strategies. The implementation of these practices will assist in building a strong reputation and satisfaction of customers and to fulfill the requisites of stakeholders.

The research was conducted with the extended framework of the mediating effect of GSCM between I4 and ENS of Saudi Arabia textile companies which are considered to be a pioneer study in the extant literature.

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.