In step with rapid advancements in computer vision, vehicle classification demonstrates a considerable potential to reshape intelligent transportation systems. In the last couple of decades, image processing and pattern recognition-based vehicle classification systems have been used to improve the effectiveness of automated highway toll collection and traffic monitoring systems. However, these methods are trained on limited handcrafted features extracted from small datasets, which do not cater the real-time road traffic conditions. Deep learning-based classification systems have been proposed to incorporate the (...) above-mentioned issues in traditional methods. However, convolutional neural networks require piles of data including noise, weather, and illumination factors to ensure robustness in real-time applications. Moreover, there is no generalized dataset available to validate the efficacy of vehicle classification systems. To overcome these issues, we propose a convolutional neural network-based vehicle classification system to improve robustness of vehicle classification in real-time applications. We present a vehicle dataset comprising of 10,000 images categorized into six-common vehicle classes considering adverse illuminous conditions to achieve robustness in real-time vehicle classification systems. Initially, pretrained AlexNet, GoogleNet, Inception-v3, VGG, and ResNet are fine-tuned on self-constructed vehicle dataset to evaluate their performance in terms of accuracy and convergence. Based on better performance, ResNet architecture is further improved by adding a new classification block in the network. To ensure generalization, we fine-tuned the network on the public VeRi dataset containing 50,000 images, which have been categorized into six vehicle classes. Finally, a comparison study has been carried out between the proposed and existing vehicle classification methods to evaluate the effectiveness of the proposed vehicle classification system. Consequently, our proposed system achieved 99.68%, 99.65%, and 99.56% accuracy, precision, and F1-score on our self-constructed dataset. (shrink)

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)

The objective of this study was to address the paradox of citizenship cost by hypothesizing an indirect rather than a direct effect of altruistic citizenship behavior on employee work–family conflict through coworker support. Data were gathered in a three-wave longitudinal survey of employees from private commercial banks. A multiple linear autoregressive longitudinal mediation model was analyzed with partial least squares structural equation modeling. The results indicate that rather than directly, ACB affects indirectly employee WFC through CWS. This indirect effect is (...) negative, which reflects that the costs of citizenship behavior are paradoxical. The present study contributes to the ongoing debate on the positive and negative outcomes of employee citizenship behavior by providing empirical evidence on the beneficial rather than harmful effect of performing such behavior. For organizational managers, promoting a culture of CWS by encouraging altruistic behaviors can be a most viable strategy to reduce WFC among their employees. The study discusses its limitations and provides future research directions. (shrink)

It was not long ago when technological emergence fundamentally changed the landscape of global businesses. Following that, business operations started shifting away from traditional to advance digitalized processes. These digitalized processes gave a further boost to the e-commerce industry, making the online environment more competitive. Despite the growing trend, there has always been a consumer market that is not involved in online shopping, and this gap is huge when it comes to consumers from developing countries, specifically Pakistan. On contrary, the (...) recent COVID-19 pandemic has brought drastic changes to the way consumers used to form their intention and behave toward digitalized solutions in pre COVID-19 times. Evidence shows that the global e-commerce industry has touched phenomenal growth during COVID-19, whereas Pakistan's e-commerce industry still holds a huge potential and has not fully boomed yet. These facts pave new avenues for marketers to cater to this consumer market for long-term growth. Hence, the study provides insights into how consumers' online buying behavior has transformed during the COVID-19 pandemic in the context of Pakistan. The study presents a framework based on the Technology Acceptance Model and Theory of Planned Behavior. Furthermore, the moderating role of gender and payment mode has also been examined. For the analysis of variables, the partial least squares method was used to conduct structural equation modeling by collecting data from 266 respondents. The results show a significant and positive impact of perceived benefits, perceived ease of use, perceived enjoyment, and social influence on consumers' intention, but they also show an insignificant impact of gender and payment mode as a moderating variable on PEOU-BI and BI-AB, respectively. The results are of utmost significance for Pakistani businesses, marketers, and e-traders to streamline their business practices accordingly. Lastly, the proposed framework demonstrates new directions for future research to work upon. (shrink)

Edmund Burke’s speeches and writings during the trial of Warren Hastings—from 1788 to 1795—remain one of the most comprehensive assessments of the effects of colonial trade and territorial expansion on Britain’s nationalist self. A rhetorical reading of his prosecution speeches reveals how they affected the public response to the trial by evoking the sublime and framing terror as the basic feature of Britain’s mercantile imperialist agenda in the colonies. Moreover, by associating Hastings’s governance of Bengal with sublime terror, Burke altered (...) the interpretations of virtue and corruption, thus distancing both Britain and India from the rampant profiteering of the East India Company. Burke’s critique of the degenerative influences of commercial imperialism along with the reformulation of his ideas in subsequent colonial historiography is crucial for assessing how the aesthetics of the sublime conferred greater moral force to the sporadic and fragmented reports about the Company’s abuses of power in India. (shrink)

The coronavirus disease 2019 pandemic and its effects on an individual’s life have altered the consumer behavior. In the context of purchase and consumption, a shift from conventional to green purchase has been noticed. Although the factors underlying this shift were relatively unexplored, the study aimed to identify the factors that influenced a significant role in the green purchases during the outbreak and the relationship of these factors with green purchase behavior. Subsequently, this study investigates and interprets the role of (...) fear of COVID-19, psychological distress, and mortality salience in predicting consumer’s GPB. This research adopted a quantitative methodology using data collected from 432 respondents in various cities across Pakistan. Smart-PLS 3 was used to evaluate the measurement model, structural model, and multi-group analysis. Despite having the negative psychological and physical impact of the pandemic, a significant proportion of customers have switched to healthier and sustainable products. This research revealed that the FCV, PD, and MS plays a substantial role in adopting GPB. All the direct relationships were positive and significant. In addition, MS and PD partially mediate the effect of FCV on GPB. Furthermore, the MGA revealed that the infected respondents were interested in purchasing green products than uninfected respondents due to their FCV; conversely, the PD and MS were higher in uninfected individuals than infected ones. However, there is a vast literature on GPB, but little has investigated the cumulative impact of FCV, PD, and MS on GPB. (shrink)

Behavioral Finance is an evolving field that studies how psychological factors affect decision making under uncertainty. This study seeks to find the influence of certain identified behavioral financial biases on the decision-making process of investors in developing countries. This research examines the moderating effect of Information asymmetry on the two most important and commonly used cognitive biases, namely Anchoring bias and Optimism bias and decision making and investigates whether Risk perception mediates the relationship between them or not. Quantitative research has (...) been conducted using a structured questionnaire for data collection. After completing the pilot study, a questionnaire was designed and sent to investors via online channels. Data has been collected from 317 real estate investors. Mediation analysis has been performed using model 4 and moderation analysis by applying model 15 of Process Macros for the interaction effect. The study investigated that both cognitive biases have a significant positive effect on investors’ decisions and Risk perception also significantly mediates the relationship between them. Consistency with other studies suggests that Information asymmetry has a significant moderating effect. The proposed conceptual model provides insight into how investors’ decisions are influenced by behavioral biases in the real estate sector and enhances the understanding of cognitive biases in the real estate sector. This study is recommended for real estate investors and policymakers of emerging and developed countries. The current study is the first of its kind, focusing on cognitive biases on investment decisions with mediating role of Risk perception and the moderating effect of Information asymmetry. (shrink)

One of the goals of happiness research is to identify the key factors that influence it. Therefore, the present research is designed to examine the determining factors of subjective wellbeing in Pakistan. The present research is conducted by collecting the data of 1,566 households in Punjab, Pakistan, using the ordered logit and tobit model. The findings of this research confirm that income, education, government effectiveness, no perceived corruption, and perceived institutional quality improve wellbeing, while lower trust in family and friends, (...) poor health status, living on rent, and dissatisfaction with the services of hospitals lower the level of wellbeing. But individuals with more social ties, who face barriers in health services, live more happily satisfied with their lives. Crime victimization and worrisome terrorism also lower the level of SWB. Findings of research strongly emphasize policymakers and government institutions to improve their quality and take essential measures for improving the governance structure. (shrink)

Business Ethics: A European Review, EarlyView.

The current study investigates whether tournament incentives motivate chief executive officer to be socially responsible. Furthermore, it explores the role of sub-national institutional contingencies [i.e., state-owned enterprises vs. non-SOEs, foreign-owned entities vs. non-FOEs, cross-listed vs. non-cross-listed, developed region] in CEO tournament incentives and the corporate social responsibility performance relationship. Data were collected from all A-shared companies listed in the stock exchanges of China from 2014 to 2019. The study uses the baseline methodology of ordinary least squares and cluster OLS regression. (...) Moreover, firm-fixed effects regression, two-stage least squares regression, and propensity score matching deal with the endogeneity problem and check the robustness of the results. The results provide reliable evidence that tournament incentives motivate CEOs to be more socially responsible. On the other hand, sub-national institutional contingencies positively affect the association between CEO tournament incentives and CSRP. The findings have important implications for companies and regulators who wish to enhance CSP by providing incentives to top managers. (shrink)

BackgroundCOVID-19 break out has created panic and fear in society. A strict kind of lockdown was imposed in Wuhan, Hubei province of China. During home confinement due to lockdown, people face multidimensional issues. The present study explored the psychological impacts of COVID-19 home confinement during the lockdown period and Wuhan’s residents’ attitude toward physical activity.MethodsA cross-sectional online survey was conducted to collect the primary data according to the study objectives. The population was Wuhan residents who were in home confinement. A (...) total of 2280 participant’s reply to the online questionnaire survey and collected data after quantifying the data, about 2200 ; about female, about male, others about, and about were not disclosed their gender participants responses were used for analysis. The collected data were analyzed through appropriate statistical techniques.ResultsAccording to results, H1 is supported with β = −40.793, t = 57.835, p = 0.000, which claimed a negative association between COVID-19 lockdown policy and behavior and attitude. Results for H2 reveals that the COVID-19 lockdown policy have negative influence on emotional control with β = −0.769, t = 46.766, p = 0.000 and it is supported. H3 documented a significant positive relationship between COVID-19 lockdown policy and lockdown period psychological impact, which means lockdown policy, is the main reason to increase the lockdown psychological impact. Further, COVID-19 lockdown policy have negative influence on physical activity and self-belief with β = −0.657, t = 32.766, p = 0.000 and β = −0.620, t = −6.766, p = 0.000 respectively. H6 stated that there is a positive impact of behavior and attitude toward physical activity. The results for H6, behavior, and attitude affecting the physical activity with β = 0.401, t = 10, p = 0.000, which is supported.ConclusionCOVID-19 home confinement created various psychological impacts, negatively affecting the emotional state due to depression and anxiety. Physical activity is the best strategy to manage human nature’s psychological issues, and people’s attitudes were positive toward physical activity during home confinement. However, the lockdown policy also affects physical activity participation negatively, and a sedentary lifestyle prevailed during home confinement. (shrink)

Data analytics, machine intelligence, and other cognitive algorithms have been employed in predicting various types of diseases in health care. The revolution of artificial neural networks in the medical discipline emerged for data-driven applications, particularly in the healthcare domain. It ranges from diagnosis of various diseases, medical image processing, decision support system, and disease prediction. The intention of conducting the research is to ascertain the impact of parameters on diabetes data to predict whether a particular patient has a disease or (...) not. This paper develops an improved ANN model trained using an artificial backpropagation scaled conjugate gradient neural network algorithm to predict diabetes effectively. For validating the performance of the proposed model, we conduct a large set of experiments on a Pima Indian Diabetes dataset using accuracy and mean squared error as evaluation metrics. We use different number of neurons in the hidden layer, ranging from 5 to 50, to train the ANN models. The experimental results show that the ABP-SCGNN model, containing 20 neurons, attains 93% accuracy on the validation set, which is higher than using the other ANNs models. This result confirms the model’s effectiveness and efficiency in predicting diabetes disease from the required data attributes. (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)

A passive brain–computer interface based upon functional near-infrared spectroscopy brain signals is used for earlier detection of human drowsiness during driving tasks. This BCI modality acquired hemodynamic signals of 13 healthy subjects from the right dorsolateral prefrontal cortex of the brain. Drowsiness activity is recorded using a continuous-wave fNIRS system and eight channels over the right DPFC. During the experiment, sleep-deprived subjects drove a vehicle in a driving simulator while their cerebral oxygen regulation state was continuously measured. Vector phase analysis (...) was used as a classifier to detect drowsiness state along with sleep stage-based threshold criteria. Extensive training and testing with various feature sets and classifiers are done to justify the adaptation of threshold criteria for any subject without requiring recalibration. Three statistical features along with six VPA features were used. The average accuracies for the five classifiers are 90.9% for discriminant analysis, 92.5% for support vector machines, 92.3% for nearest neighbors, 92.4% for both decision trees, and ensembles over all subjects’ data. Trajectory slopes of CORE vector magnitude and angle: m and m are the best-performing features, along with ensemble classifier with the highest accuracy of 95.3% and minimum computation time of 40 ms. The statistical significance of the results is validated with a p-value of less than 0.05. The proposed passive BCI scheme demonstrates a promising technique for online drowsiness detection using VPA along with sleep stage classification. (shrink)

This research article aims to evaluate the characteristics of ecotourism destination loyalty in light of destination attachment, destination equity framed by perceived value, and tourist experience. Thus, the attributes of ecotourism destination branding in formulating tourist loyalty are examined. The study is of significant importance for developing economies having natural tourist destinations. A total of 358 questionnaires were filled through wjx, and a SmartPLS-based structural equation modeling tool was used to analyze the data obtained from eco-tourists. The software is essential (...) for complex structural models, including multiple indicators, and relationships. The empirical results exhibit that perceived value and tourist experience significantly contribute to destination loyalty and equity, eventually influencing tourist destination loyalty. Moreover, destination memory moderates the relationship between destination attachment, destination equity, and destination loyalty. Further, destination attachment and destination equity mediate the relationship between the perceived value, experience, and destination loyalty. Additionally, the study extends the tourist consumption theory to the ecotourism literature. Besides the theoretical contribution, the study makes a practical contribution to practitioners. For instance, perceived value is a prime contributor to tourist destination loyalty. In perceived value, the most important factor is good value for money. Such practical contribution will provide a pathway to the strategic formation of business. (shrink)

Measuring and evaluating a learner’s learning ability is always the focus of every person whose aim is to develop strategies and plans for their learners to improve the learning process. For example, classroom assessments, self-assessment using computer systems such as Intelligent Tutoring Systems, and other approaches are available. Assessment of metacognition is one of these techniques. Having the ability to evaluate and monitor one’s learning is known as metacognition. An individual can then propose adjustments to their learning process based on (...) this assessment. By monitoring, improving, and planning their activities, learners who can manage their cognitive skills are better able to manage their knowledge about a particular subject. It is common knowledge that students’ metacognitive and self-assessment skills and abilities have been extensively studied, but no research has been carried out on the mistakes that novice developers make because they do not use their self-assessment abilities enough. This study aims to assess the metacognitive skills and abilities of novice software developers working in the industry and to describe the consequences of awareness of metacognition on their performance. In the proposed study, we experimented with novice software developers and collected data using Devskiller and a self-assessment log to analyze their use of self-regulation skills. The proposed study showed that when developers are asked to reflect upon their work, they become more informed about their habitual mistakes, and using a self-assessment log helps them highlight their repetitive mistakes and experiences which allows them to improve their performance on future tasks. (shrink)

Abortion is the most common and controversial issue in many parts of the world. Approximately 46 million abortions are performed worldwide every year. The world ratio is 26 induced abortions per 100 known pregnancies. Pakistan has an estimated abortion rate of 29 abortions per 1,000 women of reproductive age, despite the procedure being illegal except to save a woman’s life. 890,000 abortions are performed annually in Pakistan. Many government and non-government organizations are working on the issue of abortion. Muslim jurists (...) are unanimous in declaring that after the fetus is completely formed and has been given a soul, abortion is haram (forbidden). (shrink)

Volume 25, Issue 3, May 2020, Page 367-369.