Muhammad Khan

Globalization and technological advancement has made market competitive. To survive in market every organization needs to maintain high performance. It can only be possible when the employees working in organization perform more efficiently than competitors. Increase in competition of market has made employee performance a big question to organization for its survival in global competition. Study reveals performance of employee is affected by various component of human resource management i.e. Job satisfaction, leadership, training &development and work stress. HRM is managing people effectively and efficiently to achieve strategic aims of organization. This study focuses on analyzing the impact of HR components on performance of employee. It also compares impact of HR component respect to public and private organizations. The study finds HR components have significant positive relationship with employee performance except work stress. Study also interprets findings irrespective of organization type.

This study investigated the role of entrepreneurial passion in recognition of opportunity, developing entrepreneurial self-efficacy, and entrepreneurial intention, in the shaping of entrepreneurial actions in the presence of proactive personality. This study applied partial least squares structural equation modeling to test the hypotheses on a sample of 346 university students from Jiangsu province, China. The output of the study showed that entrepreneurial passion positively and significantly influenced entrepreneurial alertness, entrepreneurial self-efficacy to entrepreneurial intention, and entrepreneurial behavior. The findings also showed that a proactive personality positively and significantly moderated the relationship between entrepreneurial intention and entrepreneurial behavior.

The current research examines the possible outcomes of cronyism like organizational deviance, organizational cynicism, and counterproductive work behavior and also investigates the mediating variable violation of psychological contract among cronyism and its possible outcomes. Many studies have investigated the presence of organizational cronyism at the workplace and its impacts on certain variables. However, the outcomes observed in this study, i.e., OD, OCy, and counter-productive work behavior were not empirically investigated previously as per researchers’ knowledge. The second gap this study fills is the mediating effect of VPC between the studied variables. Thirdly, the study was conducted in Azad Jammu and Kashmir, Pakistan, which is almost the first attempt to investigate this phenomenon in Azad Jammu and Kashmir. Data were collected from the employees working under different ministries of Azad Jammu and Kashmir, Pakistan like education, forest, sports, information, local government, finance, and tourism. The data from 350 employees were collected through convenience sampling. The data collection process was conducted at two distinct time lags. Results show that OC significantly and positively relates with OD, OCy, and counter-productive work behavior, whereas VPC mediates the relationship among OC and OD, OC, and counter-productive work behavior. Employees enjoying special favors from the leadership seem to be more dedicated toward the organization than the employees who do not have this favor, and the ultimate result is negative for the organization.

Brain-computer interface multi-modal fusion has the potential to generate multiple commands in a highly reliable manner by alleviating the drawbacks associated with single modality. In the present work, a hybrid EEG-fNIRS BCI system—achieved through a fusion of concurrently recorded electroencephalography and functional near-infrared spectroscopy signals—is used to overcome the limitations of uni-modality and to achieve higher tasks classification. Although the hybrid approach enhances the performance of the system, the improvements are still modest due to the lack of availability of computational approaches to fuse the two modalities. To overcome this, a novel approach is proposed using Multi-resolution singular value decomposition to achieve system- and feature-based fusion. The two approaches based up different features set are compared using the KNN and Tree classifiers. The results obtained through multiple datasets show that the proposed approach can effectively fuse both modalities with improvement in the classification accuracy.

Tourism has emerged as the fastest growing industry and source of foreign exchange all across the world. Many countries owe major part of their annual earning and wealth to tourism. Pakistan is amongst the best tourism destination in the world. The main attractions for international travelers are usually, mountains, snow, desserts, beaches, plains, rivers, forests, cliffs, scenic beauty, historical places and cultural diversity. Pakistan is blessed with all of the said attractions. Up until now Pakistan had faced two major impediments towards becoming the top tourist destination, first it was not properly showcased in-front of the world and secondly in the recent past the security conditions were not suitable for international visitors. Today, it is high time for the Pakistan to become the top priority for tourists from all across the world. In this regard Social Media can play the best role possible. Various social media platforms are full of pictures and stories of people describing their experiences about the places they had been to. Secondly the governmental organizations also launch various social media office profile to show case the destinations. In this research the need of social media for the promotion of tourism in Pakistan has been focused.

Current development in a deep neural network has given an opportunity to a novel framework for the reconstruction of a holographic image and a phase recovery method with real-time performance. There are many deep learning-based techniques that have been proposed for the holographic image reconstruction, but these deep learning-based methods can still lack in performance, time complexity, accuracy, and real-time performance. Due to iterative calculation, the generation of a CGH requires a long computation time. A novel deep generative adversarial network holography framework is proposed for hologram reconstruction. This novel framework consists of two phases. In phase one, we used the Fresnel-based method to make the dataset. In the second phase, we trained the raw input image and holographic label image data from phase one acquired images. Our method has the capability of the noniterative process of computer-generated holograms. The experimental results have demonstrated that the proposed method outperforms the existing methods.

Synthesizing theories of ethical leadership, psychological climate, pro-environmental behavior, and gender, first, we proposed and tested a model linking supervisors’ ethical leadership and organizational environmental citizenship behavior via green psychological climate. Then we tested the moderating effect of gender on the indirect (via green psychological environment) relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Time-lagged (three waves, two months apart) survey data were collected from 447 employees in various manufacturing and service sector firms operating in China. Data were analyzed using structural equation modeling, bootstrapping, and multi-group technique to test the hypothesized relationships. The results showed a positive relationship between employee ratings of supervisors’ ethical leadership and organizational environmental citizenship behavior. Moreover, green psychological climate mediates the relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Importantly, the multi-group analysis revealed that gender moderates the indirect relationship (via green psychological climate) between supervisors’ ethical leadership and organizational environmental citizenship behavior. The study carries useful practical implications for policymakers and managers concerned about environmental sustainability.

Academic performance is among the several components of academic success. Many factors, including socioeconomic status, student temperament and motivation, peer and parental support influence academic performance. Our study aims to investigate the determinants of academic performance with emphasis on the role of parental styles in adolescent students in Peshawar Pakistan. A total of 456 students from 4 public and 4 private schools were interviewed. Academic performance was assessed based on self-reported grades in the latest internal examinations. Parenting styles were assessed through the administration of the Parental bonding instrument. Regression analysis was conducted to assess the influence of socio-demographic factors and parenting styles on academic performance. Factors associated with and differences between “care” and “overprotection” scores of fathers and mothers were analyzed. Higher socio-economic status, father’s education level and higher care scores were independently associated with better academic performance in adolescent students. Affectionless control was the most common parenting style for fathers and mothers. When adapted by the father, it was also the only parenting style independently improving academic performance. Overall, mean “care” scores were higher for mothers and mean “overprotection” scores were higher for fathers. Parenting workshops and school activities emphasizing the involvement of mothers and fathers in the parenting of adolescent students might have a positive influence on their academic performance. Affectionless control may be associated with improved academics but the emotional and psychosocial effects of this style of parenting need to be investigated before recommendations are made.

Unmanned aerial vehicles, particularly quadcopters, have several medical, agriculture, surveillance, and security applications. However, the use of this innovative technology for civilian applications is still very limited in low-income countries due to the high cost, whereas low-cost controllers available in the market are often tuned using the hit and trial approach and are limited for specific applications. This paper addresses this issue and presents a novel proof of concept low-cost quadcopter UAV design approach using a systematic Model-Based Design method for mathematical modeling, simulation, real-time testing, and prototyping. The quadcopter dynamic model is developed, and controllers are designed using Proportional Integral, and Derivative, Pole Placement, and Linear Quadratic Regulator control strategies. The stability of the controllers is also checked using Lyapunov stability analysis. For verification and validation of the design, Software-in-the-Loop, Processor-in-the-Loop, Hardware-in-the-loop testing, and Rapid Control Prototyping have been performed. The V&V methods of the MBD approach showed practically valid results with a stable flight of the quadcopter prototype. The proposed low-cost POC quadcopter design approach can be easily modified to have enhanced features, and quadcopters with different design parameters can be assembled using this approach for a diverse range of applications.

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.

This article aims to improve the understanding of corporate governance and environmental reporting literature by analyzing the impact of board gender diversity (BGD) on environmental performance, environmental disclosure, and greenwashing behavior. The panel regression estimation technique with fixed effects was applied to Chinese firm data. As a result, it was found that more women who served on corporate boards enhanced the company's environmental performance and disclosures while limiting greenwashing behavior. The result indicated that women in top management play a constructive role in establishing firms' active environmental initiatives. Furthermore, this relationship was nonlinear and exponentially increased when women's representation reached the threshold of 33.5% representation on board or higher. Based on the findings, no internal bias was found even after other governance and firm-level control factors and probable endogenies were considered and variable biases were omitted. Notably, the results present important implications for regulators and policymakers by highlighting the influential role of BGD in promoting environmentally responsible practices and reducing greenwashing.

Serious study of terrorism requires a proper understanding of why individuals turn extremism md what motivates them to join terrorist organizations. This essay analyzes socio-economic, cultural, religious, and psychological dimensions in a comprehensive framework gauging the "root causes" of terrorism The analysis is based on data collected from Pakistan-based organtations serving as allies of Al-Qaeda. The results indicate that almost all sample resporuients involved in terrorism were unmarried males exposed to fundamentalist teachings of the Qur'an. All believed that if they sacrificed themselves for the sake of their religion, they would be blessed with paradise in life after death. The essay employs relevant models in order to identify empirically the effects of education, an individual's age, household income, and rural or urban residence. The resulting evidence on the individual level suggests that both higher standards of living and education are negatively associated with participation in terrorist activities.

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.

During the COVID-19 outbreak, educational institutions were closed, and students worldwide were confined to their homes. In an educational environment, students depend on collaborative learning to improve their learning performance. This study aimed to increase the understanding of social media adoption among students during the COVID-19 pandemic for the purpose of CL. Social media provides a learning platform that enables students to easily communicate with their peers and subject specialists, and is conducive to students' CL. This study addresses the key concept of CL during the COVID-19 pandemic by assessing social media use among students in higher education. The relationship between social media use and students' performance is crucial to understanding the role of social media during a pandemic. This study is based on constructivism theory and the technology acceptance model. Structural equation modeling was used to analyze the conceptual model using SmartPLS. The research findings indicate that social media plays an important role during the pandemic because it provides opportunities for students to enhance CL under the aforementioned situations. This study makes noteworthy theoretical and practical contributions.

Given the dearth of research examining the distinctions across various facets of employee knowledge-hiding (KH) behaviors, there is little known about why and when leadership negatively influences playing dumb and evasive hiding but positively influences rationalized hiding. The present study fills this void by hypothesizing that employee justice orientation (JO) acts as a mediator of the associations of ethical leadership (EL) with different facets of employee KH behaviors. We also propose employee conscientiousness moderates the relationship of EL with JO and the indirect relationships of ethical leadership with distinct variants of employee KH behaviors. The results based on time-lagged data from 387 employees provide support for the hypothesized relationships. Together, our research provides a more nuanced account of the influence of leadership on employee KH behaviors that can facilitate the development of more appropriate interventions to deal with the intricate problems related to employee KH behaviors.

Generally toxic employees are under performers, yet some get better salaries and excel at workplace, getting positioned at higher ranks. This research assesses the relationship between the dark triad (Narcissism, Machiavellianism, and Psychopathy) and perceived victimization with a focus on the mediating effect of abusive supervision and the moderating effect of mindfulness. The data were gathered in three waves. Both the structural equation model with partial least square and Process were used to analyze the data. The study findings suggest that abusive supervision plays a mediating role in the association between the dark triad and perceived victimization. However, the results did not support the mediating role of abusive supervision in the association between narcissism and perceived victimization. Moreover, the findings suggest that mindfulness weakens the effect of abusive supervision on perceived victimization. Furthermore, our findings support the mediated-moderation model. Theoretical and practical implications of the results are also discussed.

This study explores the impact of CEO ability on corporate environmental sustainability information disclosure. We take samples from Chinese A-share listed companies from 2010 to 2019 and use the ordinary least squares as a baseline regression model to check the relationship between CEO ability and corporate environmental sustainability information disclosure. Our findings are robust to different corporate environmental sustainability information disclosure measures and CEO ability. We found a positive association between CEO ability and corporate environmental sustainability information disclosure; thus, firms with a more able CEO are more likely to disclose more corporate environmental sustainability information. Our results also found a significant negative interaction coefficient between CEO ability and CEO career concerns. As the CEO grows older, his/her ability decreases; therefore, corporate environmental sustainability information disclosure reduces. Furthermore, we document that a female CEO strengthens the relationship between CEO ability and corporate environmental sustainability information disclosure. The study results are important for understanding corporate environmental responsibility development and implementation, particularly in China.

Research conducted with ethical values is the need of modern world and great benefit to the society in general and human beings in particular. Clinical research basically focuses on improving human health individually by improving current trends, methodologies and identifying innovative methods of treatment. Public health research is mainly concerned with the health of the entire populace. No standard rules can be formulated for conducting any form of research ethically; however following some basic ethical values can assure ethical conduct of research. In any research study whether that is public health research or clinical research, the importance is need to be to recognize an ethical standard that respects individuals autonomy and communitys wellbeing. Ethical values in research studies can be achieved by requiring individuals and communitys collective collaboration for the protection of individuals autonomy, dignity and wellbeing.

Internet of Things-based environments pose various challenges due to their anytime/anywhere computing, and the efficient cryptographic based key management is one of the major challenges in Internet of Things. The key management life cycle consists of initialization, key generation, key registration, key backup, key update, key recovery, and key revocation. Our contribution in this paper is to summarize the state-of-the-art key management schemes and techniques in different scenarios, such as mobile ad hoc networks, wireless sensor networks, and the Internet of Things environments. Further different issues related specifically to the Internet of Things environment are discussed and the causes and effects pertaining to the security breach for Internet of Things are identified. Furthermore, in this research work, we develop a novel permutation of threshold and identity-based key management schemes for the Internet of Things environment and have proposed future directions to counteract the attacks on confidentiality, integrity, authentication, and availability of security services in the Internet of Things environment and identified the two key management schemes, that is, identity and threshold schemes for Internet of Things, to resolve Internet of Things key management issues and maximum possible security services effective implementation. We evaluate our scheme with the help of mathematical and statistical techniques.

Jensen’s inequality is one of the fundamental inequalities which has several applications in almost every field of science. In 2003, Mercer gave a variant of Jensen’s inequality which is known as Jensen–Mercer’s inequality. The purpose of this article is to propose new bounds for Csiszár and related divergences by means of Jensen–Mercer’s inequality. Also, we investigate several new bounds for Zipf–Mandelbrot entropy. The idea of this article may further stimulate research on information theory with the help of Jensen–Mercer’s inequality.

This study aims to investigate the impact of stakeholders’ views on the practices of green innovation (GI), consequent effect on environmental and organizational performance (OP), and moderating influence of innovation orientation. A quantitative method was employed for the sample size of 515 responses. To accumulate the data from the respondents, convenient random sampling was used. Data were collected from manufacturing and services firms through a field survey by using a closed-ended questionnaire based in the Punjab province of Pakistan. The analysis was done using the structural equation model of the partial least square analysis method. Our findings proved a positive and significant link between stakeholders’ views on GI practices. A significant association has been found between GI practices and environmental and OP. The moderating effect was found to be negative but statistically significant. This research offers numerous contributions and provides decision-making insinuations.

With the development of wireless technology, two basic wireless network models that are commonly used, known as infrastructure and wireless ad hoc networks, have been developed. In the literature, it has been observed that channel contention is one of the main reasons for packet drop in WANETs. To handle this problem, this paper presents a routing protocol named CCBR. CCBR tries to determine a least contended path between the endpoints to increase packet delivery ratio and to reduce packet delay and normalized routing overhead. Moreover, throughout the active data section, each intermediate node computes its channel contention value. If an intermediate node detects an increase in channel contention, it notifies the source node. Then the source node determines another least contended route for transmission. The advantages of CCBR are verified in our NS2-based performance study, and the results show that CCBR outperforms ad hoc on-demand distance vector in terms of packet delivery ratio, end-to-end delay, and routing overhead by 4% to 9%.

Most of the IoT-based smart systems require low latency and crisp response time for their applications. Achieving the demand of this high Quality of Service becomes quite challenging when computationally intensive tasks are offloaded to the cloud for execution. Edge computing therein plays an important role by introducing low network latency, quick response, and high bandwidth. However, offloading computations at a large scale overwhelms the edge server with many requests and the scalability issue originates. To address the above issues, an efficient resource management technique is required to maintain the workload over the edge and ensure the reduction of response time for IoT applications. Therefore, in this paper, we introduce a metaheuristic and nature-inspired Artificial Bee Colony optimization technique that effectively manages the workload over the edge server under the strict constraints of low network latency and quick response time. The numerical results show that the proposed ABC algorithm has outperformed Particle Swarm Optimization, Ant Colony Optimization, and Round-Robin Scheduling algorithms by producing low response time and effectively managing the workload over the edge server. Furthermore, the proposed technique scales the edge server to meet the demand of high QoS for IoT applications.