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Drawing on conservation of resources, social cognitive and self-verification theories, the current study endeavors to extend our comprehension of the mechanisms linking Islamic work ethics (IWE) to employee ethical behavior. More specifically, the current study investigates the potential impact of IWE on employees’ ethical behavior through the serial mediating roles of moral identity and felt obligation.

By utilizing two-wave data collected from 513 employee-co-worker dyads in the education sector in Turkey, we employed AMOS to conduct a confirmatory analysis and the PROCESS macro for SPSS to test the hypothesized relationships.

The results provide evidence for our hypothesized model. Our results indicate that employees with higher levels of IWE are more likely to exhibit higher levels of ethical behavior. Our results also reveal that IWE has a significant and positive impact on employees’ moral identity and sense of obligation, which in turn enhances their ethical behavior.

By integrating multiple theories, the current research addresses a dearth in the literature and provides a nomological network from Islamic work ethics to ethical employee behavior through the serial mediating role of moral identity and felt obligation. This study adds value to the literature on human resource management and work ethics by examining how IWE affects the attitudes and behaviors of employees in both the public and private sectors. Accordingly, organizations can strengthen their workforce’s moral identities and instill a sense of obligation to behave morally by incorporating workplace ethics into HRM processes.

Material selection, driven by wide and often conflicting objectives, is an important, sometimes difficult problem in material engineering. In this context, multi-criteria decision-making (MCDM) methodologies are effective. An approach of MCDM is needed to cater to criteria of material assortment simultaneously. More firms are now concerned about increasing their productivity using mathematical tools. To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material. In addition, by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the inherent ambiguities of decision-makers in paired evaluations are considered in this research. It goes on to construct a mathematical bi-objective model for determining the best item to purchase.

The entropy perspective is implemented in this paper to evaluate the weight parameters, while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system. The intermediate pipes are used to join the components of the exhaust systems. The materials usually used to manufacture intermediate pipe are SUS 436LM, SUS 430, SUS 304, SUS 436L, SUH 409 L, SUS 441 L and SUS 439L. These seven materials are evaluated based on tensile strength (TS), hardness (H), elongation (E), yield strength (YS) and cost (C). A hybrid methodology combining entropy-based criteria weighting, with the TOPSIS for alternative ranking, is pursued to identify the optimal design material for an engineered application in this paper. This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes. After that, the authors searched for and considered eight materials and evaluated them on the following five criteria: (1) TS, (2) YS, (3) H, (4) E and (5) C. The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes, on their performance and on the cost. In this structure, the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment. This essentially measures the quantity of information each criterion contribution, indicating the relative importance of these criteria better. Subsequently, the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative. The results show that SUS 309, SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.

The material matrix of the decision presented in Table 3 was normalized through Equation 5, as shown in Table 5, and the matrix was multiplied with weighting criteria ß_j. The obtained weighted normalized matrix V_ij is presented in Table 6. However, the ideal, worst and best value was ascertained by employing Equation 7. This study is based on the selection of material for the development of intermediate pipe using MCDM, and it involves four basic stages, i.e. method of translation criteria, screening process, method of ranking and search for methods. The selection was done through the TOPSIS method, and the criteria weight was obtained by the entropy method. The result showed that the top three materials are SUS 309, SUS 432L and SUS 436 LM, respectively. For the future work, it is suggested to select more alternatives and criteria. The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality (ELECTRE), Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE).

The results provide important conclusions for material selection in this targeted application, verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

The chapters emphasise the importance of data management from the perspective of the business management process, where big data is the most crucial and pressing technical and business issue in the modern realm of technology. The same data has a significant influence on the current financial environment. Organisations are facing challenges in explicating complicated financial data manually and using it to drive their decision-making processes. Data-driven decision-making is a dominant tool for any professional. It enhances precision, alleviates risk, improves efficacy, aids financial management, offers customer insights, provides a competitive edge, supports strategic planning, enables performance tracking, fosters innovation and has predictive capabilities. The power of data makes the organisation more prosperous and resilient in the face of change. By making informed decisions based on data and analytics, organisations can unlock their full potential and achieve sustainable growth. The chapter suggests a data-driven culture in the organisation with the help of strategising in terms of data collection, analytics and data management by establishing governance and regulatory practices to ensure data security and integrity. The latter part covers the forecasting and transformative ability of data by integrating machine learning and deep learning models. The chapter also covers the visualisation perspective of the data by transforming the information into a visual setting, illuminating the hidden insights and making them tangible and relatable. The chapter closes with a suggestion for managers to stay competitive, make more reasoned and sound decisions and adapt to the evolving business environment.

This study aims to examine the predictive power of childhood adversity and severity of positive symptoms on suicidality, controlling for selected sociodemographics factors, among hospitalized patients diagnosed with schizophrenia in Jordan.

This study used a descriptive-explorative design. The study was conducted at two major psychiatric hospitals in Jordan. The targeted sample was 66 patients diagnosed with schizophrenia. Data was collected using a structured format in the period February–April 2024.

A two-step multiple hierarchical regression analysis was conducted. In the first model, childhood adversity and the severity of positive symptoms were entered. In the second model, sociodemographic variables were entered. The analysis revealed that the first model (F = 5.35, p = 0.007) was statistically significant. The second model (F = 717, p < 0.001) was statistically significant. Furthermore, the analysis revealed that childhood adversity was not a significant predictor for suicidality. However, positive symptoms and patients’ demographics (age, number of hospitalizations and length of being diagnosed with schizophrenia) were significant predictors of suicidality. The analysis revealed that childhood adversity was not a significant predictor of suicidality. However, positive symptoms and patients’ demographics (age, number of hospitalizations and length of being diagnosed with schizophrenia) were significant predictors of suicidality.

One limitation of this study is related to the sample and the setting where there were only 66 patients recruited from governmental hospitals within inpatient wards. Thus, the upcoming studies should include more participants from private hospitals and different hospital settings including outpatient and emergency departments.

The research provides empirical insights that positive symptoms, age hospitalization and schizophrenia diagnosis length were significant predictors of suicidality. At the same time, childhood adversity was not a significant predictor of suicidality.

The current research contributes to expanding mental health studies. Moreover, this study enlarges the body of knowledge in the academic world and clinical settings. It supports the disciplines of psychology, mental health and social sciences by increasing knowledge of the complicated relationships among childhood adversity, positive symptoms and suicidality.

This paper fulfills an identified need to study childhood adversity with comorbid psychiatric disorders such as schizophrenia, as well as psychiatric mental health covariates.

The authors examined how employee led exchange benefits the organizations. Specifically, the authors aim at investigating the mediating role of family supportive supervision between employee performance and taking charge behavior. The authors further examined leader-member exchange (LMX) as a boundary condition between employee performance and family supportive supervision.

The authors collected data from 295 employees and their supervisors working in various public sector organizations of Pakistan on a convenience basis. Specifically, data on family supportive supervision and LMX was collected from employees; whereas, data on employee performance and taking charge was collected from their supervisors between June–September 2021.

The statistical analysis reveals that high-performing employees are reciprocated by the high family-supportive supervision which increases their work-life balance and they further reciprocate by showing a propensity to take charge. In addition, LMX is noted to strengthen the association between employees' performance and family supportive supervision.

This study explains how managers can extend the stream of employees' performance by highlighting the role of family-supportive supervision and LMX. The managers through high LMX and provision of family-supportive supervision can boost the employees' outcomes from job performance to extra-role performance (i.e. taking charge).

This study adds value to the existing body of knowledge by considering performance as a predictor of various organizational-level consequences. Recent studies have considered the negative consequences of employees' performance, while the positive aspect has been called for an investigation.

This study aims to investigate the effect of seasonality caused by fasting as a religious practice on trading activity.

The authors use an unbiased sample of daily trading by individuals and institutions on the Boursa Kuwait. The authors use panel data on trading activities and Tobit regression models to examine the effect of Muslims’ religious practice of fasting during the holy month of Ramadan on trading behavior.

The authors find that during the holy month of Ramadan, Muslims’ religious practice of fasting leads to a decline in the frequency of both overall stock market trading and the ratio of individual trading volume to total trading volume. The authors find a significant decrease in individual buy-side trading as a proportion of total trading volume and simultaneously a significant increase in institutional buy-side trading.

This study’s findings have important implications for the main players in stock markets of countries with a Muslim majority. Market-makers should be aware of the significant increase in the proportion of institutional buy-side trading volume to total trading volume to minimize the cost of trading with better-informed traders (adverse selection).

To the best of the authors’ knowledge, this is the first study that investigates individuals’ trading activity during Ramadan.

This study explores the factors that contribute to fan loyalty for a losing sports team, with a specific focus on the Karachi Kings in the Pakistan Super League. The research aims to uncover the motives that influence fans’ unwavering support for a team that consistently underperforms.

A qualitative research design was utilized, involving semi-structured interviews with a diverse sample of Karachi Kings fans. Data were analyzed using grounded theory principles to uncover key themes. This approach allowed for an in-depth understanding of the underlying psychological and sociocultural factors. Grounded theory was chosen to systematically generate insights from data, particularly because fan loyalty in current contexts remains underexplored.

The research identified five main themes that influence fan loyalty: identity integration, emotional attachment, cognitive coherence, behavioral consistency and social connectivity. Fans exhibited a strong psychological connection to the Karachi Kings, fueled by regional pride, shared experiences and a sense of community. The findings emphasize the importance of creating a strong fan community and nurturing emotional bonds through consistent engagement and shared experiences.

This study demonstrated how psychological and sociocultural factors combine to sustain support for a losing team. It broadens the understanding of sports fandom by emphasizing that fan loyalty extends beyond a team’s success or failure, being deeply rooted in identity, emotions and social connections. This research offers a nuanced view of fan behavior in a non-Western context and provides valuable insights for developing marketing strategies and fostering community engagement in sports management.

The present work aims to prepare biocomposites blend based on linear low density polyethylene/ starch without using harmful chemicals to improve the adhesion between two phases. Also, the efficiency of essential oils as green plasticizers and natural antimicrobial agents were evaluated.

Barrier properties and biodegradation behavior of linear low density polyethylene/starch (LLDPE/starch) blends plasticized with different essential oils including moringa oleifera and castor oils wereassessed as a comparison with traditional plasticizer such as glycerol. Biodegradation behavior forLLDPE/starch blends was monitored by soil burial test. The composted samples were recovered then washed followed by drying, and weighting samples after 30, 60, and 90 days to assess the change in weight loss. Also, mechanical properties including retention values of tensile strength and elongation at break were measured before and after composting. Furthermore, scanning electron microscope (SEM) was used to evaluate the change in the morphology of the polymeric blends. In addition to, the antimicrobial activity of plasticized LLDPE/starch blends films was evaluated using a standard plate counting technique.

The results illustrate that the water vapor transition rate increases from 2.5 g m⁻² 24 h⁻¹ for LLDPE/5starch to 4.21 g m⁻² 24 h⁻¹ and 4.43 g m⁻² 24 h⁻¹ for castor and moringa oleifera respectively. Also, the retained tensile strength values of all blends decrease gradually with increasing composting period. Unplasticized LLDPE/5starch showed highest tensile strength retention of 91.6% compared to the other blends that were 89.61, 88.49 and 86.91 for the plasticized LLDPE/5starch with glycerol, castor and M. oleifera oils respectively. As well as, the presence of essential oils in LLDPE/ starch blends increase the inhibition growth of escherichia coli, candida albicans and staphylococcus aureus.

The objective of this work is to develop cost-effective and environmentally-friendly methods for preparing biodegradable polymers suitable for packaging applications.