Search results

Surgery is predominantly a masculine profession worldwide and has largely excluded women in leadership positions. This paper aims to examine the representation of women surgeons in leadership positions in Pakistan.

Data were drawn from larger qualitative research examining the experiences of women surgeons in Pakistani hospitals. The data comprises in-depth interviews with ten doctors working in the Rawalpindi and Islamabad cities. The participants were selected by using the purposive sampling method and data were analyzed using thematic analysis.

This study included participants from diverse surgical specialties from different stages of their career with two having leadership experience. Based on participants’ perspectives several factors are responsible for this exclusion of women in leadership positions. The most prominent among these were long working hours for surgical leaders, greater responsibilities assigned to leadership positions, gender stereotypes and work–family conflict. Due to masculine hegemony, women were considered less capable and they were expected to have masculine traits to work as successful leaders. Interestingly, some participants had internalized such stereotypes and showed a lack of interest and lack of capabilities for surgical leadership as evident from their narratives.

The findings of this paper are drawn from the perspectives of ten women surgeons working in Islamabad and Rawalpindi cities of Pakistan who were selected using a convenient sampling method. Hence, the results cannot be generalized to the larger population of women surgeons working in other cities of the country. Nevertheless, this study is unique in the sense that it provides useful insight into the experiences of the women surgeons and their perspectives on surgical leadership in Pakistani hospitals. Academically, it contributes to the global debates on surgical leadership by providing empirical evidence from Pakistan.

This paper contributes to the larger debates on the under-representation of women in leadership positions in surgery by unveiling the experiences of female surgeons from Pakistan. It calls for the need for structural changes in health management and policy to accommodate women surgeons. Organizational efforts could minimize some hurdles and encourage more women to take on more formal leadership roles. The authors also call for an increasing number of women in surgery to pave the way for creating new leadership opportunities.

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.

This study aims to find the determinants of internal and external customer satisfaction of Islamic banks of Pakistan through service quality indicators that are assurance, reliance, empathy, tangibility, responsiveness. Compliance has also been added as a determinant of customer satisfaction. In this study, customers are divided into two groups, internal customers are those who are an employee in the Islamic bank and also an account holder. While external customers are account holders only in Islamic banks of Pakistan.

In this study, a quantitative research approach is used for analyzing the behavior of internal and external customers of Islamic banks in Pakistan. The instrument which is used to analyze the study’s data, is a structured five-point Likert-scale questionnaire. The structural model was analyzed with the help of the partial least squares structural equation modeling approach.

This study concluded that internal customers of Islamic banking are well aware and have full information and their level of satisfaction is positive toward the bank’s services. While external customers feel satisfied while using the Islamic banking services in Pakistan. Service quality indicators are positively and significantly related to customer satisfaction in the external customer model. On the other hand, some of the indicators are not showing a significant impact on the internal customer multi-group analysis shows a difference of coefficients are insignificant between internal and external customers.

This study helps policymakers, to understand the behavior of internal and external customers of Islamic banking in Pakistan for creating favorable policies for an interest-free banking service.

This research study provides an analysis of the customer satisfaction of Islamic banks in Pakistan by dividing Islamic bank customers into two groups (internal and external customers). The purpose for dividing Islamic bank customers into two groups is that this study wants to highlight that external customer’s perception is the same as internal customers or not? Before this study, it is difficult to find single research on this topic, whereas only one study is find-out on the factors that affect internet banking adoption among internal and external customers.

Heavy equipment residual value forecasting is dynamic as it relies on the age, type, brand and model of the equipment, ranking condition, place of sale, operating hours and other macroeconomic gauges. The main objective of this study is to predict the residual value of the main types of heavy construction equipment. The residual value of heavy construction equipment is predicted via deep learning (DL) and machine learning (ML) approaches.

Based on deep and machine learning regression network integrated with data mining, random forest (RF), decision tree (DT), deep neural network (DNN) and linear regression (LR)-based modeling decision support models are developed. This research aims to forecast the residual value for different types of heavy construction equipment. A comprehensive investigation of publicly accessible auction data related to various types and categories of construction equipment was utilized to generate the model's training and testing datasets. In total, four performance metrics (i.e. the mean absolute error (MAE), mean squared error (MSE), the mean absolute percentage error (MAPE) and coefficient of determination (R2)) were used to measure and compare the developed algorithms' accuracy.

The developed algorithm's efficiency has been demonstrated by comparing the deep and machine learning predictions with real residual value. The accuracy of the results obtained by different proposed modeling techniques was comparable based on the performance evaluation metrics. DT shows the highest accuracy of 0.9111 versus RF with an accuracy of 0.8123, followed by DNN with an accuracy of 0.7755 and the linear regression with an accuracy of 0.5967.

The proposed novel model is designed as a supportive tool for construction project managers for equipment selling, purchasing, overhauling, repairing, disposing and replacing decisions.

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 purpose of this paper is to explore the path of motivation leading to organizational commitment resulting in reduced turnover intentions (TIs). It examine the relationship between dimensions of motivation (amotivation, introjected regulations (IRs) and intrinsic motivation (IM)) with dimensions of commitment (affective, normative and continuance). Furthermore, it test the effect of these three dimensions of commitment on TIs.

A sample of 467 teachers working in public schools in Dhofar Governate in Sultanate of Oman was selected for the study. A path analysis was conducted to test the hypothesized model.

The analysis unveils that teacher’s TIs can be reduced with a right mix of motivation and commitment. Furthermore, amotivation is only linked to affective commitment and this linkage is positive; IRs positively affect continuance and normative commitment (NC); and IM positively affects affective commitment and NC. Moreover, a significant negative effect of affective, normative and continuance commitment is found on TIs.

This research sheds light on how motivation can indirectly affect TI through commitment. This study is of immense importance as it focuses on the education sector in Oman especially in Dhofar Governate.

This paper aims to address the relationship of teachers’ technological pedagogical content knowledge (TPACK) and their technology proficiency according to the International Society for Technology in Education Standards for Teachers (ISTE-ST) in public and private universities of Karachi, Pakistan.

Quantitative approach with survey research design was used. In total, 520 teachers of public and private universities were selected on the basis of simple random sampling technique. Data was collected through questionnaire distribution.

Strong significant correlation was found between teacher’ TPACK and teachers’ technology proficiency, teachers’ ability to engage in professional development and teachers’ ability to promote digital citizenship and responsibilities in students.

TPACK and ISTE-ST are used for effective teaching. TPACK is used to measure teachers’ ability to integrate technology in their teaching, while ISTE-ST is used to measure the proficiency technology integration. This study is unique as it discusses the relationship of TPACK and ISTE-ST framework in term of teachers’ ability to promote digital citizenship and responsibilities in students and teachers’ ability to engage themselves in professional development program.

This book is essential for anyone in artificial intelligence (AI) and destination management in the tourism industry or government. The book includes both theoretical and practical writings for stakeholders. In all chapters, we provide titles including AI, regenerative and green destinations, sustainable tourism, tourist motivations and expectations, good examples of smart destinations and regions, the regeneration of the tourism industry via AI, rethinking tourism activities and products, current issues in robots, self-service technology, effect of pandemic on smart destinations, sustainable gastronomy and regenerative tourism and tourism issues are discussed in the management plans of the centralisation. This book provides cases and empirical studies that deal in depth with the current situation, challenges, solutions and future strategies after technological development of tourism and increasing interest on smart destinations from a responsible perspective, for readers with an equitable interest or involvement with the organizations in inquiry.

The purpose of this study was to evaluate the psychosocial impact during the current epidemic situation of COVID-19 in Pakistan.

A total of 1,149 respondents were recruited in the study. Mental health status and psychological impact of COVID-19 outbreak were measured by impact of events scale–revised (IES-R) instrument and depression, anxiety and stress scales (DASS-21), respectively.

Results of IES-R revealed moderate or severe psychological impact in 13.05% respondents (score > 33). DAAS score revealed that severe and extremely severe depression (score: 21–42), anxiety (score: 15–42) and stress (score: 27–42) were reported in 6.35%, 6.87% and 2.78% respondents, respectively. Higher levels of stress, anxiety and depression were recorded in female gender, student, medical professionals, farmer and daily wages employed, exhibiting significant (p < 0.05) association with psychological impact of the COVID-19 outbreak. Majority of respondents received increased support, shared feeling and family care.

Mild to moderate psychological impact on mental health status was recorded in this study, which enables further planning and opportunities for health authorities to design psychological interventions for the improvement of negative psychological impact of COVID-19 epidemic in vulnerable groups.