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)

The adoption of mobile payment and mobile 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. 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 their financial skills have no (...) association with intention to adopt but through perceived usefulness; 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)

Religion has been in general neglected or even seen as a taboo subject in organizational research and management practice. This is a glaring omission in the business and society and business ethics literatures. As a source of moral norms and beliefs, religion has historically played a significant role in the vast majority of societies and continues to remain relevant in almost every society. More broadly, expectations for responsible business behavior are informed by regional, national, or indigenous cultures, which in many (...) parts of the world are heavily influenced by religious belief systems and religious institutions. In this essay, we discuss examples of how religion has functioned as a macro social force affecting business and society, discuss some of the key questions and issues related to research in this domain, offer some observations about why religion may be problematic with regard to its effects on business, and conclude by summarizing the articles contained in the special issue. (shrink)

Firms are central to wealth creation and distribution, but their role in economic inequality in a society remains poorly studied. In this essay, we define and distinguish value distribution from value creation and value appropriation. We identify four value distribution mechanisms that firms engage in and argue that shareholder wealth maximization approach skews the value distribution toward shareholders and top executives, which in turn contributes to rising economic inequalities around the world. We call on organizational scholars to study the value (...) distribution role of firms and its consequences for society, and introduce the articles in this volume of the special issue on economic inequality, business, and society. (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)

_Textile sector of Pakistan is one of the great contributors in country’s economy, and also the key contributor in making the environment polluted. Textiles have lengthy and complex supply chains (SC) which have crucial role in sustainability. Energy intensive business processes, excessive use of water and hazardous chemicals, use of synthetic yarns and fibers, make it crucial to implement sustainable practices in SC of textile industries. Pakistani textile sector does not fully adopt the sustainable practices that are being used around (...) the world and it is not immediately clear to what extent the practices used in the local industry benefit the environment. The objective of this study is the analysis of ongoing sustainable practices of Yunus Textile Mills (YTM), impact of those sustainable practices and review of international sustainable practices that can be implemented at YTM. In this research quantitative and qualitative research methods have been used along with Triple Bottom Line Approach of Sustainability. Data gathered through business publication, onsite surveys & interviews. Results obtained from the study shows that sustainable practices used by Yunus textile have positive impact on environment._. (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)

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)

The World Health Organization declares coronavirus disease 2019 as a pandemic, and The World Economic Forum argues that the COVID-19-induced global lockdown is the biggest psychological experiment. This study is an attempt to empirically evaluate the possible adverse psychosocial effects caused by COVID-19-related lockdown, if any. To do so, a cross-sectional study is conducted based on a comprehensive online survey using snowball sampling to analyze the level of social and psychological impacts during the early stage of the outbreak in Pakistan. (...) The questionnaire is filled out by the residents in Pakistan including working professionals and students. We find that the development of stress due to COVID-19-induced lockdown is particularly because of mood swings. Additionally, a higher prevalence of stress in the children of highly educated mothers is evident. To assess the belief in stakeholders, we focus gender, demographics, and education. It is observed that parental education and age significantly affect the belief in several stakeholders. The lockdown-induced fear of losing job is lower in female and male children whose fathers are graduates. Lastly, we observe that food storage and “no fear of losing job” significantly increases the odds of life satisfaction. These findings have important implications in the context of social insurance, parental education, and policy related to COVID-19 at various levels. This study further facilitates to understand the factors that might affect the mental health and life satisfaction of people during such pandemics. (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 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)

Development of decision-support and intelligent agent systems necessitates mathematical descriptions of uncertainty and fuzziness in order to model vagueness. This paper seeks to present an outline of Peirce’s triadic logic as a practical new way to model vagueness in the context of artificial intelligence. Charles Sanders Peirce was an American scientist–philosopher and a great logician whose triadic logic is a culmination of the study of semiotics and the mathematical study of anti-Cantorean model of continuity and infinitesimals. After presenting Peircean semiotics (...) within AI perspective, a mathematical formulation of a Peircean triadic set is given in relationship with classical and fuzzy sets. Using basic logical operators, all possible respective implication operators, bi-equivalence operators, valid rules of inference, and associative, distributive and commutative logical properties are derived and verified through the truth function approach. In order to suggest practical directions, aggregation operators for Peirce’s triadic logic have been formulated. A mathematical formulation of a medical diagnostic problem and ER diagram of a library management system using Peirce’s triadic relation show potential for further applications of the proposed triadic set and triadic logic. Alongside, a classical AI game—The Wumpus World—is implemented to show practical efficacy in comparison with binary implementation. Besides giving some preliminary formulations for trichotomous set theory and definition of finite automaton, development of hybrid architectures for intelligent agents and evolutionary computations are discussed as potential practical avenues for Peirce’s triadic logic. (shrink)

This article reviews some of the ethical aspects of collaborative research. Scientific collaboration has known potential benefits but it’s a challenging task to successfully accomplish a collaborative venture on ethically sound grounds. Current trends in international healthcare research collaboration reflect limited benefits for the majority of world population. Research collaboration between scientists of academia and industry usually has financial considerations. Successful cross-cultural and international collaborations have to overcome many regional and global barriers. Despite these difficulties, many scientific collaborations usually begin (...) with an informal meeting or contact. With advancement in global communications, scientists have greater responsibility towards the world community while considering the impact of their collaborative partnerships. I review the basic factors that are required for forging a collaborative partnership and responsible attitudes to sustain the relationship. Finally I conclude that scientists in healthcare research can play important roles beyond collaborations and contribute to bringing harmony, resolving differences across the nations and countries in today’s troubled world. (shrink)

This declaration ponders the impacts of Joule warm, separation, and warming radiation for the progression of MHD Sutterby nanofluid past over an all-inclusive chamber. The wonder of warmth and mass conduction is demonstrated under warm conductivity relying upon temperature and dispersion coefficients individually. Besides, the conventional Fourier and Fick laws have been applied in the outflows of warm and mass transport. The control model comprising of a progression of coupled incomplete differential conditions is changed over into a standard arrangement of (...) nonlinear coupled differential conditions by reasonable likeness changes. The subsequent arrangement of articulations is systematically treated through an ideal homotopic method. The impacts of various dimensionless stream boundaries on the speed, temperature, and focus fields are delineated through diagrams. The range of some parameters involved is assumed for the convergent solution as 0 < R e < 10, 0 < P r < 6.5, 0 < E c < 40, 0 < R d < 1.5, 0 < S 1 < 0.5, 0 < S 2 < 0.5, 0 < L e < 0.5, 0 < N t < 2.5, and 0 < N b < 2.0. The patterns of skin friction coefficient, local Nusselt, and Sherwood numbers are examined via bar charts. The principle consequence of the proposed study is that the decay of the speed for the Sutterby liquid boundary, the deterioration of the variable warm conductivity, the temperature, and the radiation increase the framework temperature. The delineation boundaries show the opposite conduct for the temperature and fixation outskirts layers. (shrink)

Student retention is an important concern for higher education institutions. The present study tested self-efficacy variable to examine the impact of personal ability of freshmen in their decision to stay in the institution of higher education. The data was collected from both public and private sector universities in Karachi. A survey method was used to collect the data from 645 students from public and private sector universities. The data was analyses on IBM SPSS Statistics 20. The result showed that self-efficacy (...) have a strong influence on intention of freshmen to stay in the same university. The impact of self-efficacy was the same for both public and private sector universities. It was recommended to include self-efficacy as a factor in retention studies. (shrink)

The present volume is a collection of original articles of high quality on the Philosophy of Science by philosophers and scientists of international repute. As the title of the book suggests, it looks at the various points of view of leading practitioners, as well as philosophers on the nature and structure of our knowledge of the physical world. The present work brings forth the fundamental ideas of Bacon, Galileo, Newton, Descartes, Popper, Einstein, Thomas Kuhn and several other leading scientists and (...) philosophers. (shrink)

The development of ideologies in re-construction and transformation of the Indian subcontinent during and after its division into new nation states in 1947emerged as the fault lines in its structural and organizational imbalances, which is an interesting phenomenon and at times led to the violent and radical political discourses. This ideological transformation became imbalanced, due to the exploitation by opportunists in state and political elements, through consciously planned attitude especially in dogma, religious traditions, ethnicity and political/state governance thereby fulfilling ulterior (...) motives. Resultantly, violence and conflicts emerged in both the fragile states of the Indian subcontinent besides undergoing a series of dictatorship, one party rule, manipulation of elites, and ethnic or national polarization ultimately leading to the weak governmental structure. This research was aimed at ascertaining both at theoretical and practical levels, the causes of intricacies involved in transformation of religious ideology into a fault line besides suppressing ethnic and identity markers of traditional society like Pakistan, exploiting the structural organization of political governments through state/bureaucratic regimes. It was discovered that this transformation became such due to the indulgence of state elements and their practices besides illiberal democratic governments, which were also leading to the violence and militancy where ideology/religion has been used for parochial political interests embodied in desires to hang on to power. Henceforth, the power made the dismemberment of joint Pakistan in post-1971era, whereas continuously challenged the fragile integrity after 1971. (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)

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)

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)

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)

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)

Climate change and farming malpractices are harmful to the globe's productive soil and biodiversity, thereby posing a hazard to the survival of future generations. Innovative technologies provide continuous smart conservation solutions, such as regenerative farming, to confront the ongoing climate crisis and maintain biodiversity. Albeit, regenerative farming has the potential to conserve climate change by upgrading the soil's organic materials and reinstating biodiversity leading to carbon attenuation. However, a critical problem remains concerning adapting conservation farming practices that can assist low-income (...) farmers. In this scenario, theoretical-driven communication campaigns are critical for addressing individuals' resistance to innovation. Thereby, this research uncovers the moderating influence of the numerous communication tools in determining the adoption of regenerative farming through diminishing farmers' resistance to innovation. The study employed a cross-sectional design vis-à-vis a survey method. A sample of 863 farmers participated by responding to the self-administrated questionnaire. In line with prior theories, the study's results identified that communication campaigns such as public service advertisements and informative scientific documentaries could reduce the resistance to innovation that increases the attitude toward the adoption of regenerative farming with varied intensity. Besides, informational support also remained a significant contributor in determining the intention to adopt regenerative farming. This specifies that implanting habits of conservation farming requires the initiation of communication campaigns using different media content. These results may be advantageous for policymakers to influence farmers' intentions to adopt regenerative farming. (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)

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)

Coronavirus disease 2019 pandemic is continuing to have severe effects on tourism-related industries, as safety precautions have become essential to follow. Based on this, this study aims to explore the role of perceptions of the tourist of safety in tourism destination choice with the mediating effect of tourist trust in the context of the Chinese tourism sector. In addition, this study considers improvements to safety measures for sustainable tourism and the benefits of the technology transformation in the travel industry because (...) of COVID-19. For this study, a quantitative approach was used, and data were collected through convenient sampling. The questionnaire was measured on a 5-point Likert scale, and a cross-sectional approach was adopted for data analysis. The findings of this study show that the effect of the perceived safety of the social environment, perceived safety of facility and equipment elements, perceived safety of human elements, perceived safety of management elements, and perceived safety of natural environments is significant and positive on the tourist destination choice. In addition, TT is a significant mediator between these elements and TDC. Furthermore, this study concluded that COVID-19 had increased travel anxiety, with particularly negative effects on the Chinese tourism sector, but that the adoption of perceived safety measures could be beneficial in regaining TT for traveling, eventually giving tourists confidence in choosing their traveling destination. (shrink)

The following discussion with philosopher and political scientist Wendy Brown seeks to apply her provocative and indispensable ideas to recent political events and problems, in particular focusing on her work in Undoing the Demos and returning briefly to consider Politics Out of History in today’s context. The questions were collectively authored and the interview itself was conducted by Sebastian Raza via Skype on 23 May 2017. We would like to thank Wendy Brown for the generous contribution of her time (...) and for answering the questions so directly and clearly. (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)

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)

Statistical distributions have great applicability for modeling data in almost every applied sector. Among the available classical distributions, the inverse Weibull distribution has received considerable attention. In the practice of distribution theory, numerous methods have been studied and suggested/introduced to increase the flexibility level of the traditional probability distributions. In this paper, we implement different distribution methods to obtain five new different versions of the inverse Weibull model. The new modifications of the inverse Weibull model are called the logarithm transformed-inverse (...) Weibull, a flexible reduced logarithmic-inverse Weibull, the weighted TX-inverse Weibull, a new generalized-inverse Weibull, and the alpha power transformed extended-inverse Weibull distributions. To illustrate the flexibility and applicability of the new modifications of the inverse Weibull model, a biomedical data set is analyzed. The data set consists of 108 observations and represents the mortality rate of the COVID-19-infected patients. The practical application shows that the new generalized-inverse Weibull is the best modification of the inverse Weibull distribution. (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)

Security has always been a force multiplier to concentrate over the traditional military stockpile for the perceived threats in the modern days of nation states focused on the conceptualization of non-traditional security dwelling into integration, like European Union’s regional cooperation rather than towards diverting assets on further devolutions or disintegrations over the phenomenon of ‘security dilemma’ as is the case of India and Pakistan. Indeed, the later phenomenological conceptual framework had never diminished in its essence which forced the welfare states (...) as well as the major powers including USA to maintain traditional military hardware in the age of 5th generation of warfare. India and Pakistan remained into zenith of vicious cycle of stock piling of latest weaponry under the outcome of irrational conclusions of prisoner’s dilemma of the belligerents fuelling traditional enthusiasm of ethnic and religious vehemence. This research is an effort to find out the gaps in easing the tensions over the détente and interdependent security while moving towards non-traditional security and instead of transforming both the states into welfare states or formerly highlighted integration of the region. Resultantly, the shedding away of the existing survival and deterrence phase led to the devolution of traditional hype of grotesque nuclear flash point. (shrink)

Given that personal source of information is preferred by the customers over company-generated marketing communications, promoting advocacy behavior among customers is of much importance for every organization. Literature suggests that an organization's corporate social responsibility (CSR) activities significantly influence individual behavior. However, the advocacy behavior of customers (ADB), from a CSR perspective, did not receive due attention. To address this literature gap, the current study attempts to explore the relationship among CSR and ADB with the intervening role of brand admiration (...) (BA). To collect the data, customers of a large fast-food service organization in Pakistan were approached. The proposed relationships were tested through the structural equation modeling (SEM) technique. The statistical evidence verifies a positive link between CSR and ADB, while BA mediated this relationship. These findings will be supportive to the fast-food business to realize the critical role of CSR for a meaningful customer-company relationship in the face of competition. (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)