Based on the Lotka–Volterra system, a pest-natural enemy model with nonlinear feedback control as well as nonlinear action threshold is introduced. The model characterizes the implementation of comprehensive prevention and control measures when the pest density reaches the nonlinear action threshold level depending on the pest density and its change rate. The mortality rate of the pest is a saturation function that strictly depends on their density while the release of natural enemies is also a nonlinear pulse term depending on (...) the density of real-time natural enemies. The exact impulsive and phase sets are given. The definition and properties of the Poincaré map corresponding to the pulse points on the phase set are provided. We investigate the existence and stability of boundary and interior order-1 periodic solution. The theoretical analysis developed in the present paper combined with nonlinear controlling measures as well as nonlinear action threshold methods and techniques laid the foundation for the establishment and analysis of other state-dependent feedback control models. (shrink)

The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron, recurrent neural network, and autoregressive integrated moving average on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA-MLP and ARIMA-RNN. Because of the complicated and noisy nature of financial data, we combine novel machine-learning techniques such as MLP and RNN with ARIMA model to predict the three stock (...) market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA-MLP and ARIMA-RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root-mean-square error and mean absolute error. Apart from this, ARIMA-MLP outperformed the ARIMA-RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA-RNN beat the ARIMA-MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time-series forecasting. (shrink)

Pervasive usage and the development of social media networks have provided the platform for the fake news to spread fast among people. Fake news often misleads people and creates wrong society perceptions. The spread of low-quality news in social media has negatively affected individuals and society. In this study, we proposed an ensemble-based deep learning model to classify news as fake or real using LIAR dataset. Due to the nature of the dataset attributes, two deep learning models were used. For (...) the textual attribute “statement,” Bi-LSTM-GRU-dense deep learning model was used, while for the remaining attributes, dense deep learning model was used. Experimental results showed that the proposed study achieved an accuracy of 0.898, recall of 0.916, precision of 0.913, and F-score of 0.914, respectively, using only statement attribute. Moreover, the outcome of the proposed models is remarkable when compared with that of the previous studies for fake news detection using LIAR dataset. (shrink)

The influential stage of Internet of Things has reformed all fields of life in general but specifically with the emergence of artificial intelligence has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources (...) and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research. (shrink)

Efficient identification of influential nodes is one of the essential aspects in the field of complex networks, which has excellent theoretical and practical significance in the real world. A valuable number of approaches have been developed and deployed in these areas where just a few have used centrality measures along with their concerning deficiencies and limitations in their studies. Therefore, to resolve these challenging issues, we propose a novel effective distance-based centrality algorithm for the identification of influential nodes in concerning (...) networks. EDBC algorithm comprises factors such as the power of K-shell, degree nodes, effective distance, and numerous levels of neighbor’s influence or neighborhood potential. The performance of the proposed algorithm is evaluated on nine real-world networks, where a susceptible infected recovered epidemic model is employed to examine the spreading dynamics of each node. Simulation results demonstrate that the proposed algorithm outperforms the existing techniques such as eigenvector, betweenness, closeness centralities, hyperlink-induced topic search, H-index, K-shell, page rank, profit leader, and gravity over a valuable margin. (shrink)

The number of comments/reviews for movies is enormous and cannot be processed manually. Therefore, machine learning techniques are used to efficiently process the user’s opinion. This research work proposes a deep neural network with seven layers for movie reviews’ sentiment analysis. The model consists of an input layer called the embedding layer, which represents the dataset as a sequence of numbers called vectors, and two consecutive layers of 1D-CNN for extracting features. A global max-pooling layer is used to reduce dimensions. (...) A dense layer for classification and a dropout layer are also used to reduce overfitting and improve generalization error in the neural network. A fully connected layer is the last layer to predict between two classes. Two movie review datasets are used and widely accepted by the research community. The first dataset contains 25,000 samples, half positive and half negative, whereas the second dataset contains 50,000 specimens of movie reviews. Our neural network model performs sentiment classification among positive and negative movie reviews called binary classification. The model achieves 92% accuracy on both datasets, which is more efficient than traditional machine learning models. (shrink)

This work compares Autometrics with dual penalization techniques such as minimax concave penalty and smoothly clipped absolute deviation under asymmetric error distributions such as exponential, gamma, and Frechet with varying sample sizes as well as predictors. Comprehensive simulations, based on a wide variety of scenarios, reveal that the methods considered show improved performance for increased sample size. In the case of low multicollinearity, these methods show good performance in terms of potency, but in gauge, shrinkage methods collapse, and higher gauge (...) leads to overspecification of the models. High levels of multicollinearity adversely affect the performance of Autometrics. In contrast, shrinkage methods are robust in presence of high multicollinearity in terms of potency, but they tend to select a massive set of irrelevant variables. Moreover, we find that expanding the data mitigates the adverse impact of high multicollinearity on Autometrics rapidly and gradually corrects the gauge of shrinkage methods. For empirical application, we take the gold prices data spanning from 1981 to 2020. While comparing the forecasting performance of all selected methods, we divide the data into two parts: data over 1981–2010 are taken as training data, and those over 2011–2020 are used as testing data. All methods are trained for the training data and then are assessed for performance through the testing data. Based on a root-mean-square error and mean absolute error, Autometrics remain the best in capturing the gold prices trend and producing better forecasts than MCP and SCAD. (shrink)

Terrorism is a global phenomenon that constantly challenges human survival. Based on the social structure, human beings adopt different strategies to overcome its negative consequences on their mind and behavior. Coping strategies and those processes essential for adjustment and survival illustrate how individuals perceive, consider, deal with, and realize a stressful situation in the era of terrorism. The study focuses on exploring coping strategies and avoidance of terrorism impacts. This research study was qualitatively designed to explore the coping strategies adaptation (...) and their influence on the former FATA individuals during the wave of terrorism in the region. The study was undertaken in five districts of erstwhile FATA, including Dara Adam Khel, Orakzai Agency, Khyber Agency, and North and South Waziristan agency. A sample size of twenty-five (25) participants was purposively selected and interviewed, ten (10) focused group discussions (FGDs) were done from each district, and the other 50 participants were chosen for ten (10) FGDs. The collected data were analyzed via the thematic analysis technique. The findings revealed that coping strategies included four different phases: the welcome, resistance, acceptance, surrender, and flee phases for overcoming threats of terrorism. Furthermore, it was also found that fear of terrorism had strongly influenced the individuals’ physical, socio-economic, psychological, emotional stress and fear, education, and social integration. The study recommended that social integration and solidarity among the people, as well as their cooperation with the government, can eliminate the threat of terrorism. (shrink)

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. (shrink)

The use of slang, abusive, and offensive language has become common practice on social media. Even though social media companies have censorship polices for slang, abusive, vulgar, and offensive language, due to limited resources and research in the automatic detection of abusive language mechanisms other than English, this condemnable act is still practiced. This study proposes USAD, a lexicon-based intelligent framework to detect abusive and slang words in Perso-Arabic-scripted Urdu Tweets. Furthermore, due to the nonavailability of the standard dataset, we (...) also design and annotate a dataset of abusive, offensive, and slang word Perso-Arabic-scripted Urdu as our second significant contribution for future research. The results show that our proposed USAD model can identify 72.6% correctly as abusive or nonabusive Tweet. Additionally, we have also identified some key factors that can help the researchers improve their abusive language detection models. (shrink)

Computer vision and human–computer interaction are essential in many technological fields. Researchers in CV are particularly interested in real-time object detection techniques, which have a wide range of applications, including inspection systems. In this study, we design and implement real-time object detection and recognition systems using the single-shoot detector algorithm and deep learning techniques with pre-trained models. The system can detect static and moving objects in real-time and recognize the object’s class. The primary goals of this research were to investigate (...) and develop a real-time object detection system that employs deep learning and neural systems for real-time object detection and recognition. In addition, we evaluated the free available, pre-trained models with the SSD algorithm on various types of datasets to determine which models have high accuracy and speed when detecting an object. Moreover, the system is required to be operational on reasonable equipment. We tried and evaluated several deep learning structures and techniques during the coding procedure and developed and proposed a highly accurate and efficient object detection system. This system utilizes freely available datasets such as MS Common Objects in Context, PASCAL VOC, and Kitti. We evaluated our system’s accuracy using various metrics such as precision and recall. The proposed system achieved a high accuracy of 97% while detecting and recognizing real-time objects. (shrink)

The purpose of this research is to highlight the relationship between green product attributes and consumer trust that influence consumers’ decision to purchase green products in the context of Pakistan. This study contributes to determining quantitatively how green product attributes such as physical, perceptual, and reflexive attributes influence consumers’ trust to purchase a green product and investigates the mediating role of green marketing. Data was collected from different industrial sectors through a survey questionnaire. We employed Structural Equation Modeling using the (...) SMART-PLS software to check the reliability and validity of the constructs, and to test the hypotheses. This study reveals variations in terms of shaping the sustainable consumers’ buying behavior by modifying product attributes and green marketing strategies that are in congruence with the proposed hypotheses of this study. In the end, the findings and interpretations of the results are given which can guide the managers to develop effective green marketing campaigns in reshaping the purchase intentions of consumers toward their green products. (shrink)

This research explores the effect of servant leadership on prosocial rule-breaking (PSRB) and the mediating mechanism of public service motivation (PSM) between the association of servant leadership and PSRB. The said phenomenon is examined in the civil service context of Pakistan during the continuing crises of the COVID-19 pandemic, a situation where the traditional civil service policy and rule system has become highly complicated for passionate employees’ service performance and efficiency, and where servant leadership has received greater attention for inspiring (...) the attitudinal and behavioral outcomes of frontline workers during the pandemic. Data were collected from 546 frontline workers of the corona relief tiger force. The findings of the study revealed that servant leadership has a significant effect on PSRB and PSM, and that PSM significantly promotes PSRB. The results also revealed that servant leadership has a significant impact on PSRBviaengendering PSM. (shrink)

Background. Imposter syndrome, associated with self-doubt and fear despite clear accomplishments and competencies, is frequently detected in medical students and has a negative impact on their well-being. This study aimed to predict the students’ IS using the machine learning ensemble approach. Methods. This study was a cross-sectional design among medical students in Bangladesh. Data were collected from February to July 2020 through snowball sampling technique across medical colleges in Bangladesh. In this study, we employed three different machine learning techniques such (...) as neural network, random forest, and ensemble learning to compare the accuracy of prediction of the IS. Results. In total, 500 students completed the questionnaire. We used the YIS scale to determine the presence of IS among medical students. The ensemble model has the highest accuracy of this predictive model, with 96.4%, while the individual accuracy of random forest and neural network is 93.5% and 96.3%, respectively. We used different performance matrices to compare the results of the models. Finally, we compared feature importance scores between neural network and random forest model. The top feature of the neural network model is Y7, and the top feature of the random forest model is Y2, which is second among the top features of the neural network model. Conclusions. Imposter syndrome is an emerging mental illness in Bangladesh and requires the immediate attention of researchers. For instance, in order to reduce the impact of IS, identifying key factors responsible for IS is an important step. Machine learning methods can be employed to identify the potential sources responsible for IS. Similarly, determining how each factor contributes to the IS condition among medical students could be a potential future direction. (shrink)

Internet of Things is expanding and evolves into all aspects of the society. Research and developments in the field of IoT have shown the possibility of producing huge volume of data and computation among different devices of the IoT. The data collected from IoT devices are transferred to a central server which can further be retrieved and accessed by the service providers for analyzing, processing, and using. Industrial Internet of Health Things is the expansion of the Internet of Health Things (...) which plays an important role in observing, consulting, monitoring, and treatment process of remote exchange data processes. The linkage of computation and interoperability are supported through various intelligent sensors, controllers, and actuators. The role of parallel computing for efficient and Intelligent Industrial Internet of Health Things is obvious to analyze and process different healthcare situations. A detailed overview of this existing literature is needed through which the research community will provide new solutions for efficient healthcare with the help of IoT based on parallel computing. Therefore, the current study presents a detailed overview of the existing literature for facilitating IIoHT. (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to preserve privacy. Previously, (...) we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)

Business Ethics, the Environment & Responsibility, EarlyView.

We investigate and analyze the dynamics of hepatitis B with various infection phases and multiple routes of transmission. We formulate the model and then fractionalize it using the concept of fractional calculus. For the purpose of fractionalizing, we use the Caputo–Fabrizio operator. Once we develop the model under consideration, existence and uniqueness analysis will be discussed. We use fixed point theory for the existence and uniqueness analysis. We also prove that the model under consideration possesses a bounded and positive solution. (...) We then find the basic reproductive number to perform the steady-state analysis and to show that the fractional-order epidemiological model is locally and globally asymptotically stable under certain conditions. For the local and global analysis, we use linearization, mean value theorem, and fractional Barbalat’s lemma, respectively. Finally, we perform some numerical findings to support the analytical work with the help of graphical representations. (shrink)

For efficient energy distribution, microgrids provide significant assistance to main grids and act as a bridge between the power generation and consumption. Renewable energy generation resources, particularly photovoltaics, are considered as a clean source of energy but are highly complex, volatile, and intermittent in nature making their forecasting challenging. Thus, a reliable, optimized, and a robust forecasting method deployed at MG objectifies these challenges by providing accurate renewable energy production forecasting and establishing a precise power generation and consumption matching at (...) MG. Furthermore, it ensures effective planning, operation, and acquisition from the main grid in the case of superior or inferior amounts of energy, respectively. Therefore, in this work, we develop an end-to-end hybrid network for automatic PV power forecasting, comprising three basic steps. Firstly, data preprocessing is performed to normalize, remove the outliers, and deal with the missing values prominently. Next, the temporal features are extracted using deep sequential modelling schemes, followed by the extraction of spatial features via convolutional neural networks. These features are then fed to fully connected layers for optimal PV power forecasting. In the third step, the proposed model is evaluated on publicly available PV power generation datasets, where its performance reveals lower error rates when compared to state-of-the-art methods. (shrink)

Efficient community detection in a complex network is considered an interesting issue due to its vast applications in many prevailing areas such as biology, chemistry, linguistics, social sciences, and others. There are several algorithms available for network community detection. This study proposed the Sigmoid Fish Swarm Optimization algorithm to discover efficient network communities. Our proposed algorithm uses the sigmoid function for various fish moves in a swarm, including Prey, Follow, Swarm, and Free Move, for better movement and community detection. The (...) proposed SiFSO algorithm’s performance is tested against state-of-the-art particle swarm optimization algorithms in Q-modularity and normalized mutual information. The results showed that the proposed SiFSO algorithm is 0.0014% better in terms of Q-modularity and 0.1187% better in terms of NMI than the other selected algorithms. (shrink)

Acute Myeloid Leukemia is a kind of fatal blood cancer with a high death rate caused by abnormal cells’ rapid growth in the human body. The usual method to detect AML is the manual microscopic examination of the blood sample, which is tedious and time-consuming and requires a skilled medical operator for accurate detection. In this work, we proposed an AlexNet-based classification model to detect Acute Myeloid Leukemia in microscopic blood images and compared its performance with LeNet-5-based model in Precision, (...) Recall, Accuracy, and Quadratic Loss. The experiments are conducted on a dataset of four thousand blood smear samples. The results show that AlexNet was able to identify 88.9% of images correctly with 87.4% precision and 98.58% accuracy, whereas LeNet-5 correctly identified 85.3% of images with 83.6% precision and 96.25% accuracy. (shrink)

Fuzzy sets and fuzzy logics are used to model events with imprecise, incomplete, and uncertain information. Researchers have developed numerous methods and techniques to cope with fuzziness or uncertainty. This research intends to introduce the novel concepts of complex neutrosophic relations and its types based on the idea of complex neutrosophic sets. In addition, these concepts are supported by suitable examples. A CNR discusses the quality of a relationship using the degree of membership, the degree of abstinence, and the degree (...) of nonmembership. Each of these degrees is a complex number from the unit circle in a complex plane. The real part of complex-valued degrees represents the amplitude term, while the imaginary part represents the phase term. This property empowers CNRs to model multidimensional variables. Moreover, some interesting properties and useful results have also been proved. Furthermore, the practicality of the proposed concepts is verified by an application, which discusses the use of the proposed concepts in statistical decision-making. Additionally, a comparative analysis between the novel concepts of CNRs and the existing methods is carried out. (shrink)

This book analyses the state of development of Muslims at the regional level. It explains the linkages between the findings of global, national, and state-level studies with regard to the current status of Muslims and broadens understanding of Muslims and their participation in virtually all major sectors, including the economy, housing, demography, health, migration, state policy, and affirmative action. The book presents the challenges faced by the community and reflects upon the socio-economic and educational conditions of Muslims in Telangana State. (...) It presents a comparative analysis of mortality data, maternal health, delivery care, and child immunization, as well as reproductive health aspects and children’s nutritional status. It shares valuable insights into the impacts of emigration and internal migration on health among local Muslims and presents a detailed analysis of data from the Census of India, NSSO, and Commission of Inquiry on Socio-Economic and Educational Status of Muslims regarding the social, economic, and demographic situation of Muslims in Telangana, as well as their opportunities for development under the newly formed state government. The book would be of great interest to scholars and researchers in development economics, sociology, politics, history, cultural studies, minority studies, Islamic studies, and policy studies, as well as policymakers, civil society activists, and those working in media and journalism. (shrink)

Every person always experiences life changes. Positive or negative life changes cause stress. Retirement represents one of life changes which can cause stress. Stress is an organism’s phyciological and psychological responses that can cause unpleasant situation and make mental and emotional dysfunction. Resilient people are more to see changes as opportunity to grow rather than as stressors. Resiliency is the ability to bounce back quickly from misfortune and successfully adapt in a smart way to adverse with more power. This quantitative (...) research represents a non-experimental method using questionnaires with Likert scale as the instrument to find correlation between resiliency and stress in the preparatory phase of retirement. There were 32 participant (male & female) from various tribes and religions. Result indicates that there is no correlation between resiliency and stress.  . (shrink)

Women entrepreneurs innovate, initiate, engage, and run business enterprises to contribute the domestic development. Women entrepreneurs think and start taking risks of operating enterprises and combine various factors involved in production to deal with the uncertain business environment. Entrepreneurship and technological innovation play a crucial role in developing the economy by creating job opportunities, improving skills, and executing new ideas. It has a significant impact on the income of the household. The study focused on investigating the role of women’s entrepreneurship (...) and innovation technologies in contributing to household income in the challenging situation of the pandemic COVID-19. The paper emphasized identifying the determinants of female entrepreneurial contribution toward household income. This study collected data from selected rural and urban areas of district Faisalabad through a self-administered questionnaire. Investigators interviewed female entrepreneurs and chose them through the snowball sampling technique from a population of purposively selected female-run businesses. Interviews were conducted with women entrepreneurs to gather relevant information for the survey investigation at their workplaces and home. The effects of various factors, including age, education, family size, income from other sources, time allocated to entrepreneurial activity, firm size, and location were estimated empirically using an ordered logit model. The study findings exhibited a positive and significant role of respondents’ education, family size, time allocated to entrepreneurial activities, and firm size. The survey outcomes also indicated that the contribution of entrepreneurial income to household income in the rural areas is significantly higher than that in urban areas. This study signifies that regulations against gender discrimination in public and private institutions are helpful. Besides, encouraging an environment for entrepreneurial culture among women in the country would increase family income. The study’s findings and policy implications directly link to Sustainable Development Goal 5 of Gender Equality and SDG 8 related to decent work and economic growth. (shrink)

Mostly consists of works composed in Tibetan, with translations into Mongolian, on the Soyombo script.

Prince of philosophers -- The emergence of Islam -- Boy genius -- Court physician -- A traveling philosopher -- Death of an intellectual -- A lasting legacy.

Time and Fantasy in Narratives of Jihad: The Case of the Islami Jamiat-I-Tuleba in Karachi This article proposes an analytical framework for thinking about violence in the Islami Jamiat-i-Tuleba (IJT), the student organization of Jamaat e Islami (JI), Pakistan's longstanding Islamist party. It prioritises the intersection of the psychic and the social, and the role of politics, history and biography in mediating the modalities, narration and praxis of violence in the city of Karachi. The dominant explanations tend to emphasise political (...) instrumentalism, and structural and ideological factors, and to "Islamicise" the violence, collapsing Islamic rhetoric into an extemporization of conditions, ignoring the deep affective appeal of violence to individuals, and leaving unelaborated the role of intersecting national, local and individual contexts and temporalities in structuring political subjectivity and violent action. (shrink)

In this study, we implemented a new numerical method known as the Chebyshev Pseudospectral method for solving nonlinear delay differential equations having fractional order. The fractional derivative is defined in Caputo manner. The proposed method is simple, effective, and straightforward as compared to other numerical techniques. To check the validity and accuracy of the proposed method, some illustrative examples are solved by using the present scenario. The obtained results have confirmed the greater accuracy than the modified Laguerre wavelet method, the (...) Chebyshev wavelet method, and the modified wavelet-based algorithm. Moreover, based on the novelty and scientific importance, the present method can be extended to solve other nonlinear fractional-order delay differential equations. (shrink)

This manuscript draws on the moral norms arising from the nuanced accounts of epistemic (in)justice and social identity in relational autonomy to normatively assess and articulate the ethical problems associated with using AI in patient care in light of the Black Box problem. The article also describes how black-boxed AI may be used within the healthcare system. The manuscript highlights what needs to happen to align AI with the moral norms it draws on. Deeper thinking – from other backgrounds other (...) than decolonial scholarship and relational autonomy – about the impact of AI on the human experience needs to be done to appreciate any other barriers that may exist. Future studies can take up this task. (shrink)

Volume 34, Issue 2-3, June - September 2024.

Research suggests that ethical leadership influences employees’ behavior and organizational functioning. Thus, the purpose of this study is to investigate the role of ethical leadership in the improvement of employees’ innovative performance. Specifically, this research developed and tested a framework about the intermediating mechanism of social capital in the relationship between ethical leadership and employees’ innovative performance. The current study integrated assumptions of social learning and social exchange theories, which postulate that the leadership has a direct effect on the employees’ (...) conduct, principally through role modeling and the reciprocal landscape. Data were collected through in-person administered questionnaire-based survey from 297 employees working in the manufacturing sectors of Pakistan. The conceptual model of our research was analyzed applying Structural Equation Modeling (SEM). The results exhibited that the ethical leadership plays an important role in fostering employees’ innovative performance. The present study also found that social capital plays an intermediating role between the ethical leadership and employees’ innovative performance relationship. The current study contributed to the leadership and innovation literature and provided insights in examining the ethical leadership-employees’ innovative performance relationship through the intermediating mechanism of social capital. (shrink)

Islamic financial institutions (IFIs) are emerging as prominent players in the financial world and are increasingly known for their conservative socially responsible investment (SRI). Being the Shari'a regulators and monitors of IFIs, the Shari'a departments are expected to implement the Islamic perspective of SRI – drawn from Shari'a principles – in their respective institutions. The purpose of this paper is to develop an SRI framework applicable to IFIs and other Shari'a compliant entities and assess its applicability within Shari'a departments of (...) two Islamic banks. This paper involves cross-case analysis based on interviews with Shari'a department officials in two settings differentiated by their respective independence. The proposed framework consists of required, expected and desired SRI aspects as applicable to IFIs. The findings reveal that the required aspects are uniformly observed by the two cases. There are, however, variations when it comes to observing the expected and desired ethical SRI aspects that may be driven by the independence of the Shari'a boards. This inconsistency and non-adherence of expected and desired aspects may lead to reputational risks in the long run. (shrink)

Islamic Financial Institutions have recently witnessed remarkable growth driven by their holistic business model. The key differentiator of IFIs is their Shari’a-based business proposition which often requires some financial sacrifices, e.g. being ethical, responsible and philanthropic. It also requires them to refrain from investments in tobacco, alcohol, pornography or earning interest. For IFIs’ sponsors and managers, however, the key motivational factor for entering the Islamic financial market is not the achievement of Shari’a objectives through the holistic business model, but rather (...) the urge to tap this highly profitable market where customers are inclined to pay a premium for Shari’a compliance. In order for IFIs to be accepted by the market, their financial instruments need to be approved by Shari’a scholars, known for their integrity and expertise in Shari’a. One can therefore expect potential tensions between IFIs’ managers and Shari’a scholars. The purpose of this research is to probe the hidden struggle between managers and Shari’a scholars in pursuit of their respective objectives. The study investigates this phenomenon using grounded theory as a methodological framework based on data collected from three IFIs from two countries. The findings reveal that Shari’a scholars and managers of IFIs have divergent objectives, which creates incongruence of objectives at the strategic level. The findings illustrate the tension and latent struggle for Shari’a compliance, which has been termed as ‘Fatwa Repositioning’ resulting in four possible consequences: deep, reasonable, minimum and superficial Shari’a compliance. Fatwa Repositioning is the core category of this study, which exhibits how managers and Shari’a scholars struggle to position the Shari’a compliance of their institutions so as to best serve their respective objectives. Interestingly, Shari’a scholars are seemingly not always in control of what they are supposed to be controlling, i.e. Shari’a compliance. (shrink)

Because ports are considered to be the heart of the maritime transportation system, thereby assessing port performance is necessary for a nation’s development and economic success. This study proposes a novel metric, namely, “_port performance index (PPI)_”, to determine the overall performance and utilization of inland waterway ports based on six criteria,_ port facility, port availability, port economics, port service, port connectivity, and port environment_. Unlike existing literature, which mainly ranks ports based on quantitative factors, this study utilizes a Bayesian (...) Network (BN) model that focuses on both quantitative and qualitative factors to rank a port. The assessment of inland waterway port performance is further analyzed based on different advanced techniques such as sensitivity analysis and belief propagation. Insights drawn from the study show that all the six criteria are necessary to predict PPI. The study also showed that port service has the highest impact while port economics has the lowest impact among the six criteria on PPI for inland waterway ports. (shrink)

If Place Spirituality is considered as an attachment experience to a geographic place or an “object,” for Muslims this concept can be explained by the sharia or Islamic law. However, in the highest level of experience as a Muslim, one may attach to God everywhere and at all times, without consideration of any place, time, or object. This experience can clearly be understood with the explanation of the three levels for Muslims: sharia or “conceptual knowledge,” tariqa or “experiential knowledge,” and (...) ma’rifa or “divine spiritual experiences” or “spiritual consciousness”. At the first and second levels, one may have a Place Spirituality, while at the third level the understanding of and connection to God might be enhanced, and the experience to connect to God can be everywhere, all the time. (shrink)

Experiences like pains, pleasures, and emotions have affective phenomenal character: they feel pleasant or unpleasant. Imperativism proposes to explain affective phenomenal character by appeal to imperative content, a kind of intentional content that directs rather than describes. We argue that imperativism is on the right track, but has been developed in the wrong way. There are two varieties of imperativism on the market: first-order and higher-order. We show that neither is successful, and offer in their place a new theory: reflexive (...) imperativism. Our proposal is that an experience P feels pleasant in virtue of being constituted by a Command with reflexive imperative content, while an experience U feels unpleasant in virtue of being constituted by a Command with reflexive imperative content : More of P!Less of U! If you need a slogan: experiences have affective phenomenal character in virtue of commanding us Get more of me! Get less of me! (shrink)

The New Towns Movement began in England and later spread world-wide in response to the increasing concern felt at the deterioration of the quality of life in the large cities under the impact of industrialization. The New Towns, it was felt, would combine the advantages of life in the country with that of life in the city. They would be small communities of between 30.000 and 60.000 inhabitants. Their principal characteristics were to be a balanced economy and a well-defined pattern (...) of industrial, commercial and residential zones. (shrink)

Affective experiences such as pains, pleasures, and emotions have affective phenomenology: they feel pleasant. This type of phenomenology has a loopy regulatory profile: it often motivates us to act a certain way, and these actions typically end up regulating our affective experiences back. For example, the pleasure you get by tasting your morning coffee motivates you to drink more of it, and this in turn results in you obtaining another pleasant gustatory experience. In this article, we argue that reflexive imperativism (...) is the only intentionalist account of affective phenomenology—probably, the only account at all—that is able to make sense of its loopy regulatory profile. (shrink)

On November 2019, the world commemorated the 30th anniversary of the United Nations’ Convention on the Rights of the Child. The UNCRC noted that “the press and other media have essential fu...

Within the Ideological Surround Model of the social sciences and religion, so-called “universal” perspectives within the psychology of religion can dialogically clarify and be clarified by the “particular” elements of Muslim commitment. This study developed new scales for operationalizing the experience and behavior of Pakistani Muslims during Ramadan. In a sample of university students, one set of experiential factors apparently facilitated, whereas another interfered with the practices of Ramadan. Intrinsic and Extrinsic Personal Religious Orientations correlated with greater and the Extrinsic (...) Social motivation with lower levels of involvement in Ramadan. Relative to these religious orientation measures, Ramadan experience scales displayed incremental validity by explaining additional variance in Ramadan behavior. Women proved to be more religious than men. At the most general level, these data further supported the dialogic assumptions of the Ideological Surround Model of research in the psychology of religion. (shrink)

_A portion of the revenue from this book’s sales will be donated to Doctors Without Borders to assist the humanitarian work of nurses, doctors, and other health care providers in the fight against COVID-19 and beyond._ _Concepts and Cases in Nursing Ethics_ is an introduction to contemporary ethical issues in health care, designed especially for Canadian audiences. The book is organized around six key concepts: beneficence, autonomy, truth-telling, confidentiality, justice, and integrity. Each of these concepts is explained and discussed with (...) reference to professional and legal norms. The discussion is then supplemented by case studies that exemplify the relevant concepts and show how each applies in health care and nursing practice. This new fourth edition includes an added chapter on end-of-life issues, and it is revised throughout to reflect the latest developments on topics such as global health ethics, cultural competence, social media, and palliative sedation, as well as ethical issues relating to COVID-19. (shrink)

Until recently, scientific consensus held firm that genetically manipulated embryos created through methods including Mitochondrial Replacement Therapy or human germline genome editing should not be used to initiate a pregnancy. In countries that have relevant laws pertaining to heritable human germline modifications, the vast majority prohibit or restrict this practice. In the last several years, scholars have observed a transformation of scientific and policy restrictions with insistent calls for creating a regulatory pathway. Multiple stakeholders highlight the role of social consensus (...) and public engagement for governance of heritable human germline modifications. However, in the drive to gain public acceptance and lift restrictions, some proponents provide distorted or misleading narratives designed to influence public perception and incrementally shift the consensus. This article describes eight discrete strategies that proponents employ to influence framing, sway public opinion, and revise policymaking of human germline modifications in a manner that undermines honest engagement. (shrink)