The study aimed to investigate the impact of behavioral biases on herding for Islamic financial products with the mediation of shariah literacy. An adopted questionnaire from several published studies was used to collect data. The data were collected from 410 respondents and were analyzed with SmartPLS. The results for the direct impact showed that self-attribution, illusion of control, and information availability have a positive and significant impact on herding for Islamic financial products while shariah literacy showed an insignificant impact on (...) herding. The results for mediation showed that previously significant and positive impact turned to insignificant when shariah literacy was introduced as mediating variable between the illusion of control, self-attribution, information availability, and herding. From a theoretical perspective, this study would contribute to the existing body of knowledge of financial decision making from shariah literacy point-out. On the other hand, the findings of this study may be useful for investors to avoid herding in the Islamic financial markets. The authors synthesize the contribution made by behavioral finance studies in extending the knowledge of herding behavior in Islamic financial products with a mediating role of shariah literacy. The key limitation of the study includes data that were collected from three districts of Punjab, Pakistan. (shrink)

This paper is concerned with the estimation of the Weibull generalized exponential distribution parameters based on the adaptive Type-II progressive censored sample. Maximum likelihood estimation, maximum product spacing, and Bayesian estimation based on Markov chain Monte Carlo methods have been determined to find the best estimation method. The Monte Carlo simulation is used to compare the three methods of estimation based on the ATIIP-censored sample, and also, we made a bootstrap confidence interval estimation. We will analyze data related to the (...) distribution about single carbon fiber and electrical data as real data cases to show how the schemes work in practice. (shrink)

A multifaceted, holistic approach to identifying potential predictors is needed to eradicate workplace bullying. The current study investigated the impact of an unfavourable organisational climate that plays a role in breeding workplace bullying. The present study also postulated that individual personality differences mediate between a caring climate and workplace bullying. Similarly, the interaction between workplace bullying and personality impacts PTSD. We also checked the role of workplace bullying as a mediator between a caring climate and PTSD. This research tested all (...) the proposed hypotheses, and the study was conducted in Pakistan. The data is analysed using the two-step partial least square structural equation modelling procedure. The first part assesses the measurement model, while in the second step, the structural model is evaluated. The results supported all the proposed hypotheses of this study. Type A behaviour moderated the caring climate—person-related bullying relationship, whereas it did not moderate the caring climate—work-related bullying in the suggested direction. Type A behaviour is moderated for both types of bullying and PTSD. Results also show significant indirect effects of a caring climate on PTSD through workplace bullying. This study will contribute theoretically to filling the literature gap on studies of climate-bullying and bullying-stress using contingency factors. (shrink)

Statistical distributions play a prominent role for modeling data in applied fields, particularly in actuarial, financial sciences, and risk management fields. Among the statistical distributions, the heavy-tailed distributions have proven the best choice to use for modeling heavy-tailed financial data. The actuaries are often in search of such types of distributions to provide the best description of the actuarial and financial data. This study presents a new power transformation to introduce a new family of heavy-tailed distributions useful for modeling heavy-tailed (...) financial data. A submodel, namely, heavy-tailed beta-power transformed Weibull model is considered to demonstrate the adequacy of the proposed method. Some actuarial measures such as value at risk, tail value at risk, tail variance, and tail variance premium are calculated. A brief simulation study based on these measures is provided. Finally, an application to the insurance loss dataset is analyzed, which revealed that the proposed distribution is a superior model among the competitors and could potentially be very adequate in describing and modeling actuarial and financial data. (shrink)