This study examines the impact of government divestiture on corporate environmental investment (EI) and investigates how regional development moderates this relationship. Using a sample of Chinese listed firms from 2012 to 2022, we employ a fixed-effect model to analyze the data. Our findings reveal a negative effect of government divestiture on EI. Furthermore, we observe that regional development mitigates this negative impact, indicating that firms operating in developed environments are more inclined to prioritize environmental concerns, likely due to increased stakeholder (...) monitoring. To address concerns regarding endogeneity, we utilize propensity score matching (PSM), Heckman tests, and the generalized method of moments (GMM). Overall, our results carry significant policy implications, particularly regarding the environmental consequences of privatization in emerging markets like China. (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)

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)

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)

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)

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)

Academic frauds, dishonesty and cheating are pervasive in Pakistan, but thus far less systematic research has been undertaken on the effectiveness of the policies designed for countering academic dishonesty. Generally, the success of a policy depends on a good design and appropriate implementation. The design aspect of the policies to counter academic dishonesty in Pakistan is studied elsewhere, the purpose of this article is to empirically examine the implementation stages of the same policies. In doing so, the study utilizes a (...) panel data set comprising of 60 cross-sections and 06 time series observations (2012–2017). Results of the rigorous panel regression models shows that leniency in the prescribed punishments and an exhaustive belief on the efficacy of traditional examination surveillance methods are counterproductive. The study however failed to substantiate the direct relationship of discrimination and academic dishonesty in the sample. It is therefore concluded that prescribed punishments must be awarded in letter and spirit and that there is need for coordination at different stages of the implementation. Further, the study also recommends that traditional forms of examination surveillance must be augmented using modern technology. (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 (rural/urban) 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 (SDGs) 5 of Gender Equality (GE) and SDG 8 related to decent work and economic growth. (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 (ACB) on employee work–family conflict (WFC) through coworker support (CWS). Data were gathered in a three-wave longitudinal survey of employees from private commercial banks (N= 318). A multiple linear autoregressive longitudinal mediation model was analyzed with partial least squares structural equation modeling (PLS-SEM). 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)

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)

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)

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)

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)

Health care professionals experience moral distress due to challenging ethical decision-making during patient care. Self-awareness can be associated with moral distress. This study determined the levels of and relationship between moral distress and self-awareness of health care professionals. A convenience sample of physicians and nurses was recruited. Data were collected using the Moral Distress and Self-Awareness Scales. In total, 168 physicians and 201 nurses participated with a mean age of 30.54 ± 7.87 and clinical experience of 6.40 ± 6.22 years. (...) Moderate levels of moral distress (127.07 ± 71.90) and high levels of self-awareness (70.20 ± 11.37) were found. A weak positive correlation was found between self-awareness and moral distress (r = 0.21, p < 0.001) and weak negative correlation between moral distress (r = − 0.115, p = 0.03) and age. Nurses were more self-aware, but no differences were observed in moral distress based on sex and clinical settings. A weak correlation between self-awareness and moral distress may suggest that self-awareness can increase intrapersonal tensions, contributing to distress. Further research is needed to support any conclusive relationship between moral distress and self-awareness. (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)

There are two types of stock price manipulation examined in the theoretical literature: insider trading, which involves private information that is true and the public spreading of fraudulent false information. While there is a large empirical literature on insider trading, this is the first empirical article to examine the impact of false, fraudulent public information on stock prices and trading volume. We find that such false information, even after being denied by a credible source such as the SEC, generates both (...) abnormal returns and abnormal trading volume. We also find that the effects of the false information on security returns and volume can be persistent for at least 2 weeks. In addition, we show that perpetrators of false news attacks can make potentially large profits from such market manipulations. (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)

With the advancement of scientific collaboration in the 20th century, researchers started collaborating in many research areas. Researchers and scientists no longer remain solitary individuals; instead, they collaborate to advance fundamental understandings of research topics. Various bibliometric methods are used to quantify the scientific collaboration among researchers and scientific communities. Among these different bibliometric methods, the co-authorship method is one of the most verifiable methods to quantify or analyze scientific collaboration. In this research, the initial study has been conducted to (...) analyze interdisciplinary research activities in the computer science domain. The ACM has classified the computer science fields. We selected the Journal of Universal Computer Science for experimentation purposes. The J.UCS is the first Journal of Computer Science that addresses a complete ACM topic. Using J.UCS data, the co-authorship network of the researcher up to the 2nd level was developed. Then the co-authorship network was analyzed to find interdisciplinary among scientific communities. Additionally, the results are also visualized to comprehend the interdisciplinary among the ACM categories. A whole working web-based system has been developed, and a forced directed graph technique has been implemented to understand IDR trends in ACM categories. Finally, the IDR values between the categories are computed to quantify the collaboration trends among the ACM categories. It was found that “Artificial Intelligence” and “Information Storage and Retrieval”, “Natural Language Processing and Information Storage and Retrieval”, and “Human-Computer Interface” and “Database Applications” were found the most overlapping areas by acquiring an IDR score of 0.879, 0.711, and 0.663, respectively. (shrink)

Pakistan’s evolution into a research-centric nation, recognized by Clarivate Analytics, suggests a transition towards a knowledge-based economy. However, the prevalence of academic dishonesty within Pakistan’s academic institutions raises concerns, potentially impeding the realization of its intellectual prowess. This research therefore examines the drivers of academic dishonesty in Pakistani universities, drawing on data collected from 457 students in four prominent public sector universities. Regression analysis of the dataset reveals several noteworthy findings. The study identifies that male gender, larger family size, risk (...) preference, anxiety, and susceptibility to peer influence correlate positively with academic dishonesty. Conversely, students’ socio-economic status and their perception of diminished respect for dishonest behavior act as deterrents. Furthermore, the impact of detection on academic dishonesty exhibits a threshold effect, while personal integrity/morality and punitive measures appear to have limited impact on academic dishonesty. Consequently, this study underscores the importance of addressing socio-cultural and environmental factors as pivotal elements in combating unethical academic conduct within Pakistan. (shrink)

As the global urgency for environmental sustainability intensifies, leadership plays a pivotal role in shaping eco-friendly behaviors within organizations and beyond. This study examines the role of green inclusive leadership (GIL) in fostering pro-environmental behaviors within the hospitality industry, utilizing the ability, motivation, and opportunity (AMO) theory as a conceptual framework to explain how GIL influences sustainable behaviors. The study highlights AMO as a theoretical model that outlines how AMO can drive organizational success, while addressing motivation as a practical driver (...) of employee behavior. Time-lagged data were gathered from hotel employees and managers in Pakistan. The findings demonstrate that GIL positively affects employees' voluntary green behaviors both at work and in their personal lives. This relationship is mediated by a green work climate and environmental commitment, highlighting the spillover effect from workplace behaviors to daily life. The originality of this work lies in its novel application of AMO theory beyond the workplace, offering insights into how leadership can inspire sustainable actions that extend beyond organizational boundaries, especially in a high-impact sector like hospitality. (shrink)

Since the 1980s, Western and European multinational corporations, notably clothing and fashion brands, have shifted their production to developing nations, particularly in the ready-made garments (RMG)-producing countries like Bangladesh. This shift, driven by the dominant economic and political doctrines of globalisation and neoliberalism, has led to the deliberate targeting of developing nations to exploit their abundant labour forces and strengthen global capitalism. The RMG industry in Bangladesh, a prime example, pays its workers meagre wages. However, it is the global brands, (...) through their outsourcing practices, that hold significant power and contribute to the exploitation of RMG workers in Bangladesh while reaping substantial profits. This article highlights these issues and urgently calls for essential policy recommendations to reform the minimum wage structure for RMG workers in Bangladesh. (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)

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 adoption of mobile payment (m-payment) and mobile banking (m-banking) is low in several countries, despite its associated benefits. The present study examines the impact of Pakistani consumers’ financial skills and digital literacy on their intention to adopt m-payment/m-banking using the Technology Acceptance Model (TAM). The data were collected from 454 individual smartphone users residing in Punjab province via an online and offline questionnaire survey. Structural equation modeling was used to analyze the consumers’ data. The results endorse that (1) their (...) financial skills have no association with intention to adopt but through perceived usefulness; (2) their digital literacy bridges a strong association with intention and through perceived ease of use. Furthermore, this study discusses the theoretical and practical implications of the findings, as well as limitations and future directions. (shrink)

According to the United Nations, the Rohingya people are the most persecuted minority group in the world. The atrocities perpetrated by Myanmar authorities could by any reckoning be called ethnic cleansing. This paper delves into the level of discrimination against the Rohingya population perpetrated by Myanmar authorities in myriad of ways. A team of researchers interviewed 37 victims. The pattern of persecution goes back to 1948 – the year when the country achieved independence from their British colonizers. Today, this population (...) group is the single largest “stateless” community after Palestinians in the world. Their “statelessness” or lack of citizenship increases their vulnerability owing to the lack of entitlements to any legal protection from the government. Without citizenship, they are deprived of basic rights such as access to health services, education and employment. The illiteracy rate among the Rohingya, for example, is a staggering 80 percent. However, so far, no unified responses either from the ASEAN or the EU were provided to the crisis. As a result, the level of discrimination against and brutality towards them kept escalating. (shrink)

The purpose of this article is to look at how migration and culture interact to shape the migration landscape in Southeast Asian countries. Within the scope of migration study, there has been a lack of attention paid to the importance of culture. Scholars may have lost sight of the importance of culture due to a sustained and continuous concentration on socioeconomic concerns. The research claims that one of the aspects that influences migration decision-making is culture. To back up our claim, (...) we performed qualitative research in Malaysia, Thailand, and Brunei. Through the lens of acculturation, enculturation, and deculturation, the study highlights a vital problem of whether migration influences culture or the other way around or whether migration itself becomes a part of a culture. (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)

Proposals to release genetically engineered organisms in the wild raise complex ethical issues related to their safe and equitable implementation. While there is broad agreement that community and public engagement is vital to decision‐making in this context, more discussion is needed about who should be engaged in such activities and in what ways. This article identifies Indigenous peoples as key stakeholders in decisions about gene‐editing in the wild and argues that engagement activities need not only include Indigenous peoples but also (...) be designed, conducted, and analyzed in ways that confront longstanding power imbalances that dismiss Indigenous expertise. We offer specific recommendations to guide deliberative activities to not only be inclusive of Indigenous peoples but also to empower their diverse, situated knowledges. We call on those committed to the inclusive design of broad public deliberation to pursue strategies that shift dominant power dynamics to include Indigenous communities in more meaningful ways. (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)

Originally published in 1981, this book considers one particular area of econometrics- the linear model- where significant recent advances have been made. It considers both single and multiequation models with varying co-efficients, explains the various theories and techniques connected with these and goes on to describe the various applications of the models. Whilst the detailed explanation of the models will interest primarily econometrics specialists, the implications of the advances outlined and the applications of the models will intrest a wide range (...) of economists. (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)

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)

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)

Business Ethics: A European Review, EarlyView.