Search results for: investor sentiment

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Zhuo Feng, Ying Gao

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Public-private partnership (PPP), as an innovative way to provide infrastructures by the private sector, is being widely used throughout the world. Compared with the traditional mode, PPP emerges largely for merits of relieving public budget constraint and improving infrastructure supply efficiency by involving private funds. However, PPP projects are characterized by large scale, high investment, long payback period, and long concession period. These characteristics make PPP projects full of risks. One of the most important risks faced by the private sector is demand risk because many factors affect the real demand. If the real demand is far lower than the forecasting demand, the private sector will be got into big trouble because operating revenue is the main means for the private sector to recoup the investment and obtain profit. Therefore, it is important to study how the government compensates the private sector when the demand risk occurs in order to achieve Pareto-improvement. This research focuses on price compensation mechanism, an ex-post compensation mechanism, and analyzes, by mathematical modeling, the impact of price compensation mechanism on payoff of the private sector and consumer surplus for PPP toll road projects. This research first investigates whether or not price compensation mechanisms can obtain Pareto-improvement and, if so, then explores boundary conditions for this mechanism. The research results show that price compensation mechanism can realize Pareto-improvement under certain conditions. Especially, to make the price compensation mechanism accomplish Pareto-improvement, renegotiation costs of the government and the private sector should be lower than a certain threshold which is determined by marginal operating cost and distortionary cost of the tax. In addition, the compensation percentage should match with the price cut of the private investor when demand drops. This research aims to provide theoretical support for the government when determining compensation scope under the price compensation mechanism. Moreover, some policy implications can also be drawn from the analysis for better risk-sharing and sustainability of PPP projects.

Keywords: infrastructure, price compensation mechanism, public-private partnership, renegotiation

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Authors: Chiung-Yao Huang, Yu-Cheng Lin, Chiung-Hui Chen

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This study seeks to examine perceived environmental corporate social responsibility (ECSR) with a focus on negative environmental questions, related to intention of ethical investment intention after a environmental failure recovery. An empirical test was employed to test the hypotheses. We manipulated the information on negative ECSR activities of a hypothetical firm in a experimental design with a failure recovery treatment. The company’s negative ECSR recovery was depicted in a positive perspective (depicting a follow-up strong social action), whereas in the negative ECSR treatment it was described in a negative perspective (depicting a follow-up non social action). In both treatments, information about other key characteristics of the focal company were kept constant. Investors’ intentions to invest in the company’s stock were evaluated by multi-item scales. Results indicate that positive ECSR recovery information about a firm enhances investors’ intentions to invest in the company’s stock. In addition, perceived moral intensity has a significant impact on the intention of ethical investment and that perceived moral intensity also serves as a key moderating variable in the relationship between negative ECSR and the intention of ethical investment. Finally, theoretical and managerial implications of the findings are discussed. Practical implications: The results suggest that managers may need to be aware of perceived moral intensity as a key variable in restoring the intention of ethical investment. The results further suggest that perceived moral intensity has a direct, and it also has an moderating influence between ECSR and the intention of ethical investment. Originality/value: In an attempt to deepen the understanding of how investors perceptions of firm environmental CSR are connected with other investor‐related outcomes through ECSR recovery, the present research proposes a comprehensive model which encompasses ECSR and other key relationship constructs after a ECSR failure and recovery.

Keywords: ethical investment, Environmental Corporate Social Responsibility(ECSR), ECSR recovery, moral intensity

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

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Authors: Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

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Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits.

Keywords: Egyptian stock exchange, emerging markets, higher moment models, median models, mixed-integer linear programming, non-linear programming

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Authors: Zana Llonçari Osmani, Nita Llonçari

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In Kosovo, public rhetoric and popular sentiment position the War of 1998-99 (the war) as central to the formation of contemporary Kosovo's national identity. This period was marked by the forced massive displacement of Kosovo Albanians, the destruction of entire settlements, the loss of family members, and the profound emotional trauma experienced by civilians, particularly those who actively participated in the war as members of the Kosovo Liberation Army (KLA). Amidst these profound experiences, the Prekaz Massacre (The Massacre) is widely regarded as the defining event that preceded the final struggles of 1999 and the long-awaited attainment of independence. This study aims to explore how different visitors perceive the dominant discourse at The Memorial, a site dedicated to commemorating the Prekaz Massacre, and to identify the factors that influence their perceptions. The research employs a comprehensive mixed-method approach, combining online surveys, critical discourse analysis of visitor impressions, and content analysis of media representations. The findings of the study highlight the significant role played by original material remains in shaping visitor perceptions of The Memorial in comparison to the curated symbols and figurative representations interspersed throughout the landscape. While the design elements and physical layout of the memorial undeniably hold significance in conveying the memoryscape, there are notable shortcomings in enhancing the overall visitor experience. Visitors are still primarily influenced by the tangible remnants of the war, suggesting that there is room for improvement in how design elements can more effectively contribute to the memorial's narrative and the collective memory of the Prekaz Massacre.

Keywords: critical discourse analysis, memorialisation, national discourse, public rhetoric, war tourism

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Authors: Yijie Wang, Hanwei Cheng

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Under the Chinese educational context, the materials for patriotic education typically take the form of grand narratives. However, in post-modern times the younger members of society tend to welcome elements of more micro and personal nature. It is therefore important to explore how patriotism can be integrated into an ‘everyday’, private narrative that holds more attraction for the young. Based on semi-structured interviews of eight Chinese graduate students, this research examines how Chinese young people draw materials to establish national identity and develop love for the country from everyday-life details, as well as how they perceive, interpret and articulate their patriotism through private narratives. And implications for patriotic education are proposed accordingly. Several conclusions are drawn from the pre-interviews. Firstly, sensory experiences that remind people of their country—such as the taste of Chinese delicacies and the sound of a traditional instrument—are a major source of patriotic feelings. Secondly, the love for the country often stems from and is continued to be mediated by the emotional attachment with other people, typically significant others, and patriotism is articulated (or acknowledged) by the young as a kind of ‘sentiment’ rather than ‘faith’ or ‘belief’. Thirdly, for young people who are currently studying abroad, their birth country represents a kind of familiar, well-accustomed life or lifestyle, and any nostalgic realization of it leads to increased national belonging and sense of identity. Fourthly, the awareness of the country’s transformations—positive ones and neutral ones alike—triggers young people affections towards the country, and even negative transformations may result in promoted sense of self-involvement and therefore consolidate national identity. Implications for patriotic education can be drawn accordingly, and although the research is conducted under the Chinese context, it will hopefully contribute to the understanding of relevant fields.

Keywords: national identity, patriotic education, private narrative, young people

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Authors: Aishat Abdul-Qadir Zubair

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Background: The absence of Shari’ah screening methodology for companies in Nigeria has further engineered the uncertainty surrounding the acceptability of investing in certain companies by people professing the religion of Islam due to the nature of the activities carried out by these companies. There are some existing shariah screening indices in other jurisdictions whose criteria can be used to check if a company or business is shariah-compliant or not. Examples such as FTSE, DJIM, Standard and Poor to mention just a few. What these indices have tried to do is to ensure that there are benchmarks to check with before investing in companies that carry out mixed activities in their business, wherein some are halal and others may be haram. Purpose: There have been numerous studies on the need to adopt certain screening methodologies as well as call for new methods in screening companies for shariah compliance in order to suit the investments needs of Muslims in other jurisdictions. It is, however, unclear how suitable these methodologies will be to Nigeria. This paper, therefore, seeks to address this gap to consider an appropriate screening methodology to be employed in Nigeria, drawing from the experience of other jurisdictions. Methods: This study employs a triangulation of both quantitative and qualitative methods to analyze the need for Shari’ah screening of companies in Nigeria. The qualitative method is used by way of ijtihad, and this study tries to apply some Islamic Principles of Maqasid al-shari’ah as well as Qawaid al-Fiqiyyah to analyze activities of companies in order to ensure that they are indeed Shari’ah compliant. In addition, using the quantitative data gathered from the interview survey, the perspective of the investors with regards to the need for Shari’ah screening of companies in Nigeria is further analyzed. Results: The result of the study shows that there is a lack of awareness from the teeming Muslim population in Nigeria on the need for Shari’ah screening of companies in Nigeria. The result further shows that there is the need to take into cognizance the peculiar nature of company activities in Nigeria before any particular Shari’ah screening methodology is adopted and setting the necessary benchmarks. Conclusion and Implications: The study concludes that there is the need to ensure that the conscious Muslims in Nigeria screen companies for Shari’ah compliance so that they can easily identify the companies to invest in. The paper, therefore, recommends that the Nigerian government need to come up with a screening methodology that will suit the peculiar nature of companies in Nigeria. The study thus has a direct implication on the Investment regulatory bodies in Nigeria such as the Securities and Exchange Commission (SEC), Central Bank of Nigeria (CBN) as well as the investor Muslims.

Keywords: Shari'ah screening, Muslims, investors, companies

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Authors: Ourvashi Bissoon

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Sub-Saharan Africa in addition to being resource rich is increasingly being seen as having a huge growth potential and as a result, is increasingly attracting MNEs on its soil. To empirically assess the effectiveness of GDP in tracking sustainable resource use and the role played by MNEs in Sub-Saharan Africa, a panel data analysis has been undertaken for 32 countries over thirty-five years. The time horizon spans the period 1980-2014 to reflect the evolution from before the publication of the pioneering Brundtland report on sustainable development to date. Multinationals’ presence is proxied by the level of FDI stocks. The empirical investigation first focuses on the impact of trade openness and MNE presence on the traditional measure of economic growth namely the GDP growth rate, and then on the genuine savings (GS) rate, a measure of weak sustainability developed by the World Bank, which assumes the substitutability between different forms of capital and finally, the impact on the adjusted Net National Income (aNNI), a measure of green growth which caters for the depletion of natural resources is examined. For countries with significant exhaustible natural resources and important foreign investor presence, the adjusted net national income (aNNI) can be a better indicator of economic performance than GDP growth (World Bank, 2010). The issue of potential endogeneity and reverse causality is also addressed in addition to robustness tests. The findings indicate that FDI and openness contribute significantly and positively to the GDP growth of the countries in the sample; however there is a threshold level of institutional quality below which FDI has a negative impact on growth. When the GDP growth rate is substituted for the GS rate, a natural resource curse becomes evident. The rents being generated from the exploitation of natural resources are not being re-invested into other forms of capital namely human and physical capital. FDI and trade patterns may be setting the economies in the sample on a unsustainable path of resource depletion. The resource curse is confirmed when utilising the aNNI as well, thus implying that GDP growth measure may not be a reliable to capture sustainable development.

Keywords: FDI, sustainable development, genuine savings, sub-Saharan Africa

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Authors: David Muyise

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Mixed Integer Programming (MIP) is an approach that involves the optimization of a range of decision variables in order to minimize or maximize a particular objective function. The main objective of this study was to apply the MIP approach to optimize the deployment of waste plastic to fuel oil processing plants in Uganda. The processing plants are meant to reduce plastic pollution by pyrolyzing the waste plastic into a cleaner fuel that can be used to power diesel/paraffin engines, so as (1) to reduce the negative environmental impacts associated with plastic pollution and also (2) to curb down the energy gap by utilizing the fuel oil. A programming model was established and tested in two case study applications that are, small-scale applications in rural towns and large-scale deployment across major cities in the country. In order to design the supply chain, optimal decisions on the types of waste plastic to be processed, size, location and number of plants, and downstream fuel applications were concurrently made based on the payback period, investor requirements for capital cost and production cost of fuel and electricity. The model comprises qualitative data gathered from waste plastic pickers at landfills and potential investors, and quantitative data obtained from primary research. It was found out from the study that a distributed system is suitable for small rural towns, whereas a decentralized system is only suitable for big cities. Small towns of Kalagi, Mukono, Ishaka, and Jinja were found to be the ideal locations for the deployment of distributed processing systems, whereas Kampala, Mbarara, and Gulu cities were found to be the ideal locations initially utilize the decentralized pyrolysis technology system. We conclude that the model findings will be most important to investors, engineers, plant developers, and municipalities interested in waste plastic to fuel processing in Uganda and elsewhere in developing economy.

Keywords: mixed integer programming, fuel oil plants, optimisation of waste plastics, plastic pollution, pyrolyzing

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Authors: Fatemeh Rouhi, Hadi Nassiri

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Earning forecast is a key element in economic decisions but there are some situations, such as conflicts of interest in financial reporting, complexity and lack of direct access to information has led to the phenomenon of information asymmetry among individuals within the organization and external investors and creditors that appear. The adverse selection and moral hazard in the investor's decision and allows direct assessment of the difficulties associated with data by users makes. In this regard, the role of trustees in corporate governance disclosure is crystallized that includes controls and procedures to ensure the lack of movement in the interests of the company's management and move in the direction of maximizing shareholder and company value. Therefore, the earning forecast of companies in the capital market and the need to identify factors influencing this study was an attempt to make relationship between moral hazard and corporate governance with earning forecast quality companies operating in the capital market and its impact on Earnings Forecasts quality by the company to be established. Getting inspiring from the theoretical basis of research, two main hypotheses and sub-hypotheses are presented in this study, which have been examined on the basis of available models, and with the use of Panel-Data method, and at the end, the conclusion has been made at the assurance level of 95% according to the meaningfulness of the model and each independent variable. In examining the models, firstly, Chow Test was used to specify either Panel Data method should be used or Pooled method. Following that Housman Test was applied to make use of Random Effects or Fixed Effects. Findings of the study show because most of the variables are positively associated with moral hazard with earnings forecasts quality, with increasing moral hazard, earning forecast quality companies listed on the Tehran Stock Exchange is increasing. Among the variables related to corporate governance, board independence variables have a significant relationship with earnings forecast accuracy and earnings forecast bias but the relationship between board size and earnings forecast quality is not statistically significant.

Keywords: corporate governance, earning forecast quality, moral hazard, financial sciences

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Authors: Manal Elsayed Elkheshin, Rasha Saleh Mansour, Mohamed Fawzy Mohamed Eldnasury, Mamdouh Elbadry Mohamed

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This research Aims to identify the main factors affecting the production and the fish consumption in Egypt, through the econometric estimation for various forms functions of fish production and fish consumption during the period (1991-2014), as the aim of this research to forecast the production and the fish consumption in Egypt until 2020, through determine the best standard methods using (ARIMA).This research also aims to the economic feasibility of the production of fish in aquaculture farms study; investment cost and represents the value of land, buildings, equipment and irrigation. Aquaculture requires three types of fish (Tilapia, carp fish, and mullet fish), and the total area of the farm, about an acre. The annual Fish production from this project about 3.5 tons. The annual investment costs of about 50500 pounds, Find conclude that the project can repay the cost of their investments after about 4 years and 5 months, and therefore recommend the implementation of the project, and internal rate of return reached (IRR) of about 22.1%, where it is clear that the rate of large internal rate of return, and achieves pound invested in this project annual return is estimated at 22.1 pounds, more than the opportunity cost, so we recommend the need to implement the project.Recommendations:1. Increasing the fish agriculture to decrease the gap of animal protein. 2.Increasing the number of mechanism fishing boats, and the provision of transport equipped to maintain the quality of fish production. 3.Encourage and attract the local and foreign investments, providing advice to the investor on the aquaculture field. 4. Action newsletters awareness of the importance of these projects where these projects resulted in a net profit after recovery in less than five years, IRR amounted to about 23%, which is much more than the opportunity cost of a bank interest rate is about 7%, helping to create work and graduates opportunities, and contribute to the reduction of imports of the fish, and improve the performance of the food trade balance.

Keywords: equation model, individual share, red meat, consumption, production, endogenous variable, exogenous variable, financial performance evaluates fish culture, feasibility study, fish production, aquaculture

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Munaza Mubeen

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The colonial Urdu literature has played a significant role in uplifting the overall status of the Indians. Taking example of the Bhopal State, the contribution of the Royal ladies holds no match in the contemporary age. Similarly, the efforts of the Begamat-e-Bhopal in the field of education had been acknowledged across the Sub-continent. It had been noticed that with the downfall of the Mughal Empire at the hands of the British Raj, the local culture in the Indian sub-continent in general and in Bhopal State in proper got deteriorated. This led to uncertainty, chaos and an anti-British sentiment which created hatred against them in the entire sub-continent. Likely, in Bhopal State, the role of women in field of education also vanished. However, this change was felt by the ladies in the Royal Household where they struggled for restoration of the status quo with their personal efforts. The prominent contributors from the Royal household included Qudseya Begum, Nawab Sikander Begum, Nawab Shah Jahan Begum and Nawab Sultan Johan-they are known as Begamat-i-Bhopal. They established schools, colleges and universities to impart formal and non-formal education respectively. Their systematic approach and continued efforts constituted a dynamic aspect of women’ empowerment. Focused on the female education, however, one of the by-products of their efforts was an introduction of socio-cultural and politico-religious awareness among the middle class womenfolk. Unfortunately, the role of these Bagamat-i-Bhopal has been left untouched or ignored by the academic scholars. This study critically analyzed the role of Beghamat-i-Bhopal regarding female education in Hindustan in general and in Bhopal in particular. Similarly, the contribution of the contemporary writers in development of female education in Bhopal has also been discussed in this paper. This paper is based on the 'historico-textual' approach following structural reason which has established a justifiable argument. The researcher, therefore, has taken into consideration all the chronological nuances in order to accord greater visibility to the contents. The data has been described, analyzed and interpreted inclusively and in generalized manner.

Keywords: colonialism, Begamaat e Bhopal, female education, State of Bhopal

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Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

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In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

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Authors: Felix O. Akinboyewa

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To say that Nigeria is faced with the problem of domestic terrorism is to say the obvious. The spate of political assassination during the fourth republic (1999-2010) is representative of what has become a growing trend. In this research, an attempt was made to examine the problems of political assassination within the context of significant categories of domestic-related terrorism in Nigeria Democracy. The central questions are: What exactly are the nature of political violence and terrorist act in the Nigeria nascent democracy? Was there any factor responsible for the politics of violence and terrorist act in the Nigeria democracy? What implications can the political violence and terrorist act have on democratic consolidation, national peace, and security? What solutions can be proffered to eradicate terrorist act and political violence in the Nigeria democracy? The study adopted a descriptive survey design which falls within the empirical research methodology. The sample size of the study consisted of 220 subjects randomly selected. The main instruments used were questionnaire and interview schedule. Data generated from the study were analyzed using descriptive statistics such as percentage and tables. The research findings showed that unemployed youths and the members of Nigeria Union of Road Transport Workers (NURTW) were the major actors in political violence in Nigeria. They have access to weapons and ammunitions which they use to terrorize the populace. The research showed that factors responsible for the political violence and terrorism in Nigeria are: poor electoral administration; election rigging; poor security system; religious and ethnic sentiment; problems of poverty and unemployment; over-exuberance and low level of education. The study also showed that electoral violence affects smooth running democracy in Nigeria. On the measures to be taken to eradicate political violence and terrorism in Nigeria, the research showed that provision of employment opportunities would go a long way to solving the problem. Civil society as an important institution can help to reduce incidence of political violence in Nigeria. Also, government has greater role to play. The study concludes that adherence to the proffered suggestions would reduce the level of political violence and terrorist act in Nigeria.

Keywords: consolidation, democracy, peace, security, terrorism, violence

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Authors: I. Rodionov, A. Semenov, E. Gosteva, O. Sokolova

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Currently, the venture capital becomes more and more advanced and effective source of the innovation project financing, connected with a high-risk level. In the developed countries, it plays a key role in transforming innovation projects into successful businesses and creating prosperity of the modern economy. Actually, in Russia there are many necessary preconditions for creation of the effective venture investment system: the network of the public institutes for innovation financing operates; there is a significant number of the small and medium-sized enterprises, capable to sell production with good market potential. However, the current system does not confirm the necessary level of efficiency in practice that can be substantially explained by the absence of the accurate plan of action to form the national venture model and by the lack of experience of successful venture deals with profitable exits in Russian economy. This paper studies the influence of various factors on the venture industry development by the example of the IT-sector in Russia. The choice of the sector is based on the fact, that this segment is the main driver of the venture capital market growth in Russia, and the necessary set of data exists. The size of investment of the second round is used as the dependent variable. To analyse the influence of the previous round such determinant as the volume of the previous (first) round investments is used. There is also used a dummy variable in regression to examine that the participation of an investor with high reputation and experience in the previous round can influence the size of the next investment round. The regression analysis of short-term interrelations between studied variables reveals prevailing influence of the volume of the first round investments on the venture investments volume of the second round. Because of the research, the participation of investors with first-class reputation has a small impact on an indicator of the value of investment of the second round. The expected positive dependence of the second round investments on the forecasted market growth rate now of the deal is also rejected. So, the most important determinant of the value of the second-round investment is the value of first–round investment, so it means that the most competitive on the Russian market are the start-up teams which can attract more money on the start, and the target market growth is not the factor of crucial importance.

Keywords: venture industry, venture investment, determinants of the venture sector development, IT-sector

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Authors: Deenadayalan Govender

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In South Africa, similar to nations globally, the prevailing tangible link between people and the state is public infrastructure. Services delivered through infrastructure to the people and to the state form a critical enabler for social development in communities and economic development in the country. In this regard, infrastructure, being the backbone to a nation’s prosperity, ideally should be effectively maintained for seamless delivery of services. South African infrastructure is in a state of deterioration, which is leading to infrastructure dysfunction and collapse and is negatively affecting development of the economy. This infrastructure deterioration stems from deficiencies in maintenance practices and strategies. From the birth of South African democracy, government has pursued socio-economic transformation and the delivery of critical basic services to decrease the broadening boundaries of disparity. In this regard, the National Infrastructure Plan borne from strategies encompassed in the National Development Plan is given priority by government in delivering strategic catalytic infrastructure projects. The National Infrastructure Plan is perceived to be the key in unlocking opportunities that generate economic growth, kerb joblessness, alleviate poverty, create new entrepreneurial prospects, and mitigate population expansion and rapid urbanisation. Socio-economic transformation benefits from new infrastructure spend is not being realised as initially anticipated. In this context, South Africa is currently in a state of weakening economic growth, with further amassed levels of joblessness, unremitting poverty and inequality. Due to investor reluctance, solicitation of strategic infrastructure funding is progressively becoming a debilitating challenge in all government institutions. Exacerbating these circumstances further, is substandard functionality of existing infrastructure subsequent to inadequate maintenance practices. This in-depth multi-sectoral study into the state of infrastructure is to understand the principal reasons for infrastructure functionality regression better; furthermore, prioritised investigations into progressive maintenance strategies is focused upon. Resultant recommendations reveal enhanced maintenance strategies, with a vision to capitalize on infrastructure design life, and also give special emphasis to socio-economic development imperatives in the long-term. The research method is principally based on descriptive methods (survey, historical, content analysis, qualitative).

Keywords: infrastructure, maintenance, socio-economic, strategies

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Authors: Brennan Lodge

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Cybersecurity professionals have long been embroiled in a digital arms race, confronting increasingly sophisticated threats with innovative solutions. The field of cybersecurity is in an unending race against malicious adversaries. As threats evolve in complexity, the tools used to defend against them need to advance even faster. Burdened with a vast arsenal of tools and an expansive scope of threat intelligence, analysts frequently navigate a complex web, trying to discern patterns amidst information overload. Herein lies the potential of Retrieval Augmented Generation (RAG). By combining the capabilities of Large Language Models (LLMs) with a generative AI facet, RAG brings to the table an unparalleled ability for real-time cross-referencing, bridging the gap between raw data and actionable insights. Imagine an analyst named Sarah working at a global Fortune 500 company. Every day, Sarah navigates a maze of diverse knowledge bases, real-time threat intelligence, and her company's vast proprietary data, from network specifics to intricate technical blueprints. One day, she's challenged by a potential breach through a personal device due to the company's global "Bring Your Own Device" policy. With the clock ticking, Sarah has mere minutes to trace the malware's origin, all while considering complex regional regulations. As she races against the benchmark of Mean Time To Resolution (MTTR), she wonders: Could "Cozy Bear" with its notorious malware tactic, HAMMERTOSS, be behind this? Balancing policy intricacies, global network considerations, and ever-emerging cyber threats, Sarah's role epitomizes the intense challenges faced by today's cybersecurity analysts. While analysts grapple with this array of intricate, time-sensitive challenges, the necessity for precision and efficiency is key. RAG technology—a cutting-edge advancement in Gen AI—is a promising solution. Designed to assimilate diverse data sources such as cyber advisory notices, phishing email sentiment, secure and insecure code examples, information security policy documentation, and the MITRE ATT&CK framework, RAG equips analysts with real-time querying capabilities through a vector database and a cross referenced concise response from a Gen AI model. Traditional relational databases often necessitate a tedious process of filtering through numerous entries. Now, with the synergy of vector databases and Gen AI models, analysts can rapidly access both contextually or semantically akin data points. This augmented approach equips analysts with a comprehensive understanding of the prevailing cyber threats, elevating the robustness of cybersecurity defenses and upskilling the analyst and team, too. Vector databases underpin the knowledge translation in Gen AI. They bridge the gap between raw data and translation into meaningful insights, ensuring that analysts are equipped with comprehensive and relevant information. This superior capability of the RAG framework, with its impressive depth and precision, finds application across a broad spectrum of cybersecurity challenges. Let's delve into some use cases where its potential becomes particularly evident: Phishing Email Sentiment Analysis: Phishing remains a predominant vector for cybersecurity breaches. Leveraging RAG's capabilities, analysts can not only assess the potential malevolence of an email but can also understand the context behind it. By cross-referencing patterns from varied data sources in real-time, the detection process evolves from a mere content evaluation to a holistic understanding of attacker tactics, behaviors, and evolving profiles. This allows for the identification of nuanced phishing strategies that might otherwise go undetected. Insecure Code Analysis: Software vulnerabilities form a critical entry point for cyber adversaries. With RAG, the process of code evaluation undergoes a transformation. Instead of manual code reviews, the system pulls insights from vector databases and historical code snippets marked as insecure, enabling detection of vulnerabilities based on historical patterns, emerging threat vectors, and even predictive threat modeling. This ensures that even the most obfuscated or embedded vulnerabilities are identified, and corrective measures can be promptly implemented. Vulnerability and Upskill Advisory: In the fast-paced world of cybersecurity, staying updated is paramount. Through RAG's capabilities, analysts are not only made aware of real-time vulnerabilities but are also guided on the necessary skills and tools needed to combat them. By dynamically sourcing data through vulnerability advisories, news on advanced persistent threats, and tactics to defend, RAG ensures that analysts are not only reactive to threats but are also proactively upskilled, thereby bolstering their defense mechanisms. Information Security Policies for Compliance Teams: Compliance remains at the heart of many organizational cybersecurity strategies. However, with ever-shifting regulatory landscapes, staying compliant becomes a moving target. RAG's ability to source real-time data ensures that compliance teams always have access to the latest policy changes, guidelines, and best practices. This not only facilitates adherence to current standards but also anticipates future shifts, assists with audits, and ensures that organizations remain ahead of the compliance curve. Fusing a RAG architecture with platforms like Slack amplifies its practical utility. Slack, known for its real-time communication prowess, seamlessly evolves into more than just a messaging platform in this context. Cybersecurity analysts can pose intricate queries within Slack and, almost instantaneously, receive comprehensive feedback powered by the harmonious interplay of RAG and Gen AI. This integration effectively transforms Slack into an AI-augmented chatbot-like assistant for cybersecurity professionals, always ready to provide informed insights on-demand, making it an indispensable ally in the ever-evolving cyber battlefield. Navigating the vast landscape of cybersecurity, analysts often encounter unfamiliar terminologies and techniques., analysts require tools that not only detect or inform them of threats, like CISA (U.S Cybersecurity Infrastructure Security Agency) Advisories, but also interpret and communicate them effectively. Consider a junior cybersecurity analyst named Alex, who comes across the term "Kerberoasting" while reviewing a network log. Unfamiliar with its intricacies, Alex turns to Slack to pose a query: "chat explain is Kerberoasting, using CISA." Almost instantaneously, Slack, powered by the harmonious interplay of RAG and Gen AI, provides a detailed response, cross-referencing a recent cyber advisory on the technique. It explains how attackers can exploit the Kerberos Ticket Granting Service to decipher service account passwords, potentially compromising a network. In this dynamic realm of cybersecurity, the blend of RAG and Generative AI represents more than just a technological leap. It embodies a paradigm shift, promising a future where human expertise and AI-driven precision join forces. As cyber threats continue their relentless advance, this synergy ensures that defenders are equipped with an arsenal that's not just reactive, but also profoundly insightful. No longer should analysts be submerged in a deluge of data without direction. Instead, they should be empowered, to discern, act, and preempt with unparalleled clarity and confidence. By harmoniously intertwining human discernment with AI capabilities, we should chart a path towards a future where cybersecurity is not just about defense, but about achieving a strategic advantage, paving the way for a safer, informed and a more secure digital horizon.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

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Authors: Abdul Kader

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This paper attempts to investigate several contributory factors to recent volatility in the Islamic Banking sector of Bangladesh. In particular, the study explores corporate governance, credit management, credit regulations, inept board of directors, using religious sentiment as a means to deceive general people, and the degree of political interference as potential contributory factors. To find the correlation among different variables, semi-structured questionnaires were distributed among the clients, bank managers, some Banking scholars and ex-members of the board of directors of three Islamic Banks in Bangladesh. Later, ten interviews were collected from key informants to gain in-depth information about the present mismanagement of Islamic Banks in Bangladesh. After then, data were analyzed using statistical software and substantiated by secondary sources like newspapers, reports and investigative reports aired in screen media. The paper found a correlation between almost all contributory factors and recent unstable conditions in the Islamic banking sector. After performing regression analysis, this paper found a more significant relationship between some of the contributory factors with Banking volatility than others. For instance, credit management, inept board of directors, depriving customers of proving no profit in the name of business—no interest-- and political interference have a strong significant positive correlation with the present poor condition of Islamic Banking. This paper concludes that while internal management is important in recovering the losses, the government needs to ensure framing better policy for the Islamic Banking system, Central Bank needs to supervise and monitor all Islamic banks meticulously and loan receivers must go through the impartial evaluation and approved by the representatives of the Central Shariah Board. This paper also recommends that there is a need to strengthen the auditing system and improve regulatory oversight of the Islamic Banks in Bangladesh. Policy recommendations that this paper put forward could provide an outline for dealing with the existing challenging condition of Islamic Banks and these could be applied to similar problems in other countries where the Islamic Banking model exists.

Keywords: Islamic bank, volatility in banking sector, shariah law, credit management, political interference

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Authors: Syauqi Asfiya R.

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This study examines the constraints faced by Islamic boarding school (Pesantren) in Indonesia in effectively addressing physical violence within their educational institutions. The vulnerability to violence in the education sector remains pervasive, including in Pesantren, primarily due to the residential nature of the boarding school system, which necessitates round-the-clock interaction among students from diverse backgrounds. Additionally, environmental factors, parenting styles, individual characteristics, and media influences further complicate the conditions within Pesantren. Numerous cases of physical violence have been reported, underscoring the need to identify the constraints of violence prevention strategies implemented by Pesantren. Adopting a case study approach, this research focuses on a Modern Pesantren in Tangerang and utilizes interviews conducted with 20 victims of violence to explore the aspects of Pesantren's violence prevention strategies that may have been overlooked. The findings indicate that many students face a dilemma when reporting the violence they experience, as the imposed sanctions often prove excessively severe and carry the risk of exacerbating the violence perpetrated by the offenders. Consequently, numerous victims choose to remain silent, thereby enabling the perpetuation of violence. Moreover, senior students (mudabbir) are prohibited from giving punishment, but there are still many who punish other students based on their personal moods. Furthermore, violence is also perpetrated by religious teachers (ustadz), despite their responsibility for addressing such issues. The evaluation process often follows a unidirectional approach wherein the santri have limited freedom compared to the Mudabbir or ustadz when it comes to providing feedback. Additionally, sentiment within specific student generations is reinforced due to the segregation of dormitories based on cohorts. Lastly, the absence of psychologists to address the trauma experienced by victims further exacerbates the situation. This research sheds light on the constraints faced by Pesantren in effectively preventing physical violence and emphasizes the importance of implementing comprehensive measures to create safer and nurturing learning environments within these institutions.

Keywords: physical violence, islam, boarding school, constraint

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Authors: Tanapond S.

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Typically, most of the controlling firms are relate to family firms which are widespread and important for economic growth particularly in Asian Pacific region. The unique characteristics of the controlling families tend to play an important role in determining the corporate policies such as dividend policy. Given the complexity of the family business phenomenon, the empirical evidence has been unclear on how the families behind business groups influence dividend policy in Asian markets with the prevalent existence of cross-shareholdings and pyramidal structure. Dividend policy as one of an important determinant of firm value could also be implemented in order to examine the effect of the controlling families behind business groups on strategic decisions-making in terms of a governance perspective and agency problems. The purpose of this paper is to investigate the impact of ownership structure and concentration which are influential internal corporate governance mechanisms in family firms on dividend decision-making. Using panel data and constructing a unique dataset of family ownership and control through hand-collecting information from the nonfinancial companies listed in Stock Exchange of Thailand (SET) between 2000 and 2015, the study finds that family firms with large stakes distribute higher dividends than family firms with small stakes. Family ownership can mitigate the agency problems and the expropriation of minority investors in family firms. To provide insight into the distinguish between ownership rights and control rights, this study examines specific firm characteristics including the degrees of concentration of controlling shareholders by classifying family ownership in different categories. The results show that controlling families with large deviation between voting rights and cash flow rights have more power and affect lower dividend payment. These situations become worse when second blockholders are families. To the best knowledge of the researcher, this study is the first to examine the association between family firms’ characteristics and dividend policy from the corporate governance perspectives in Thailand with weak investor protection environment and high ownership concentration. This research also underscores the importance of family control especially in a context in which family business groups and pyramidal structure are prevalent. As a result, academics and policy makers can develop markets and corporate policies to eliminate agency problem.

Keywords: agency theory, dividend policy, family control, Thailand

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Authors: Hasan Al Banna, Nazmus Sakib, Anjan Roy

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From the perspective of the underdeveloped countries such as Bangladesh, health issue can readily be pointed out as the most demanding but the least promoted concern due to lack of initiatives from both government and NGOs. Furthermore an worldwide scenario is that most death and suffering from various pathogenic and non-pathogenic diseases occur due to delay diagnosis, and this happen for the lacking of regular health check-up facility or tradition. In this epistle, an innovative proposal on social business can be introduced to ensure the one-stop medical facility to the door-step of the rural society and create jobs for the educated rural youths to serve their own people. To illustrate the policy, this newly proposed organization will work as a health club which will offer a life-time membership to villagers within a very affordable fee of 250 BDT (2.63 Euro) per month. In this package the members will get the facility of tri-monthly full health check-up by specialist doctors, a health record book and computerized health database for each member and anytime medical consultancy for the members only. We will also organize free medical campaign and workshops on nutrition, sanitation, adulteration, pregnancy-care, child-health etc with the assistance of different sponsors. Among other services that will be provided on payment include emergency ambulance facility in low rents, quality diagnostic lab and 24-hour dispensary facility. Likewise, this policy will involve local educated people by recruiting them after providing intensive courses on nursing and other medical instrumental skills. Henceforth, the engagement of local youth will make the program more acceptable to the rural community. In the later part of this paper, a survey report on Daragram union of Manikganj district, Bangladesh, having population above 25000, will be presented to delineate the scenario how this policy can repay the initial capital expense of BDT 7 million (around 73381 Euro) within 5 years and how I can realistically earn handsome revenue from the first month of business. To recapitulate, this policy is very promising to enlighten the underprivileged community by providing health assurance, and alleviating unemployment besides the investor’s financial profit.

Keywords: create job for the rural people, handsome financial profit, quality health services, underprivileged areas of underdeveloped countries

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Authors: Muhammad Tahir, Mushtaq Muhammad

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Capital structure is one of the key decisions taken by the financial managers. This study aims to investigate the factors influencing capital structure decision in Oil and Gas industry of Pakistan using secondary data from published annual reports of listed Oil and Gas Companies of Pakistan. This study covers the time-period from 2008-2014. Capital structure can be affected by profitability, firm size, growth opportunities, dividend payout, liquidity, business risk, and ownership structure. Panel data technique with Ordinary least square (OLS) regression model has been used to find the impact of set of explanatory variables on the capital structure using the Stata. OLS regression results suggest that dividend payout, firm size and government ownership have the most significant impact on financial leverage. Dividend payout and government ownership are found to have significant negative association with financial leverage however firm size indicated positive relationship with financial leverage. Other variables having significant link with financial leverage includes growth opportunities, liquidity and business risk. Results reveal significant positive association between growth opportunities and financial leverage whereas liquidity and business risk are negatively correlated with financial leverage. Profitability and managerial ownership exhibited insignificant relationship with financial leverage. This study contributes to existing Managerial Finance literature with certain managerial implications. Academically, this research study describes the factors affecting capital structure decision of Oil and Gas Companies in Pakistan and adds latest empirical evidence to existing financial literature in Pakistan. Researchers have studies capital structure in Pakistan in general and industry at specific, nevertheless still there is limited literature on this issue. This study will be an attempt to fill this gap in the academic literature. This study has practical implication on both firm level and individual investor/ lenders level. Results of this study can be useful for investors/ lenders in making investment and lending decisions. Further, results of this study can be useful for financial managers to frame optimal capital structure keeping in consideration the factors that can affect capital structure decision as revealed by this study. These results will help financial managers to decide whether to issue stock or issue debt for future investment projects.

Keywords: capital structure, multicollinearity, ordinary least square (OLS), panel data

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Authors: Nino Damenia

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The paper discusses the risks arising in agriculture in Georgia, the possibilities of their acceptance and prevention, the threat created by the pandemic crisis, and the state programs for overcoming them. The share of agriculture in the country's GDP is 8.3%. Over the past five years, Georgia has imported $ 5.9 billion worth of agri-food products. Despite these figures, agriculture has become an important sector for the Georgian government since 2012, as evidenced by the more than 1.5 billion GEL spent from the 2012-2020 budget for agricultural development. Any field of agriculture, be it poultry, livestock, cereals, fruits, or vegetables, is very sensitive to various climatic and viral risks. Avoiding these risks requires additional investment. It is noteworthy that small farms are mainly affected by the risks, while relatively large farms face fewer problems because they are relatively prepared to face the problems and can avoid them more easily. An example of viral risk in the article is the export of hazelnuts, which has quite a lot of potential. Due to the spoilage of the crop caused by Brown Marmorated Stink Bug (BMSB), hazelnut exports have declined considerably over the years. If the volume of hazelnuts exported in 2016 was 179 378 thousand USD, due to the deficit caused by Brown Marmorated Stink Bug (BMSB) in 2018, it became 57 124 thousand USD. And after the situation was relatively settled, hazelnut seedlings were poisoned. By 2020, this figure improved to 91,088 thousand US dollars. The development of the agricultural sector and the reduction of risks require technological development, investor interest, and even more state support to enable more small farms to have the potential for greater production and sustainable development. The aim of the study is to identify the risks arising in the agricultural sector of Georgia before and after the pandemic, to evaluate them, compare them with the agriculture of some European countries, and to develop the necessary recommendations to avoid the emerging risks. The research uses methods of analysis and synthesis, observation, induction, deduction, and analysis of statistics. The paper is based on both Georgian and foreign scientific research, as well as state-published documentation on agricultural assistance programs. The research is based on the analysis of data published by the European Statistics Office, the National Statistics Office of Georgia, and many other organizations. The results of the study and the recommendations will help reduce the risks in agriculture in Georgia and, in general, to identify the existing potential and the development of the sector as a whole.

Keywords: risk, agriculture, pandemi, brown marmorated stink bug (BMSB)

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Authors: Selifontova Darya Yurievna

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The study of the process of the emergence and evolution of socio-cultural ideas about the "Asian states" in the context of the development of US cinema in 1941-1945 will contribute both to the approbation of a new approach to the classical subject and will allow using the methodological tools of history, political science, philology, sociology for understanding modern military-political, historical, ideological, socio-cultural processes on a concrete example. This is especially important for understanding the process of constructing the image of the Japanese Empire in the USA. Assessments and images of China and Japan in World War II, created in American cinema, had an immediate impact on the media, public sentiment, and opinions. During the war, the US cinema created new myths and actively exploited old ones, combining them with traditional Hollywood cliches - all this served as a basis for creating the image of China and the Japanese Empire on the screen, which were necessary to solve many foreign policy and domestic political tasks related to the construction of two completely different, but at the same time, similar images of Asia (China and the Japanese Empire). In modern studies devoted to the history of wars, the study of the specifics of the information confrontation of the parties is in demand. A special role in this confrontation is played by propaganda through cinema, which uses images, historical symbols, and stable metaphors, the appeal to which can form a certain public reaction. Soviet documentaries of the war years are proof of this. The relevance of the topic is due to the fact that cinema as a means of propaganda was very popular and in demand during the Second World War. This period was the time of creation of real masterpieces in the field of propaganda films, in the documentary space of the cinema of 1941 – 1945. The traditions of depicting the Second World War were laid down. The study of the peculiarities of visualization and mythologization of the Second World War in Soviet cinema is the most important stage for studying the development of the specifics of propaganda methods since the methods and techniques of depicting the war formed in 1941-1945 are also significant at the present stage of the study of society.

Keywords: asian countries, politics, sociology, domestic politics, USA, cinema

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Authors: Derya Gül Ünlü, Oguz Kuş

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The branding of a country means that the country has its own position different from other countries in its region and thus it is perceived more specifically. It is made possible by the branding efforts of a country and the uniqueness of all the national structures, by presenting it in a specific way, by creating the desired image and attracting tourists and foreign investors. Establishing a national brand involves, in a sense, the process of managing the perceptions of the citizens of the other country about the target country, by structuring the image of the country permanently and holistically. By this means, countries are not easily affected by their crisis of international relations. Therefore, within the scope of the research that will be carried out from this point, it is aimed to show how the warplane downing crisis between Turkey and Russia is perceived on social media. The Russian warplane was downed by Turkey on November 24, 2015, on the grounds that Turkey violated the airspace on the Syrian border. Whereupon the relations between the two countries have been tensed, and Russia has called on its citizens not to go to Turkey and citizens in Turkey to return to their countries. Moreover, relations between two countries have been weakened, for example, tourism tours organized in Russia to Turkey and visa-free travel were canceled and all military dialogue was cut off. After the event, various news sites on social media published plenty of news related to topic and the readers made various comments about the event and Turkey. In this context, an investigation into the perception of Turkey's national brand before and after the warplane downing crisis has been conducted. through comments fetched from the reports on the BBC World, and from Al Jazeera English news sites on Facebook accounts, which takes place widely in the social media. In order to realize study, user comments were fetched from jet downing-related news which are published on Facebook fan-page of BBC World Service, and Al Jazeera English. Regarding this, all the news published between 24.10.2015-24.12.2015 and containing Turk and Turkey keyword in its title composed data set of our study. Afterwards, comments written to these news were analyzed via text mining technique. Furthermore, by sentiment analysis, it was intended to reveal reader’s emotions before and after the crisis.

Keywords: Al Jazeera English, BBC World, country branding, social media, text mining

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Authors: Erica Siqueira, Adriana Bin, Rachel Stefanuto

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The paper aims to identify and to discuss the impact and results of ex-ante, mid-term and ex-post evaluation initiatives in Brazilian Social Enterprises from the point of view of the entrepreneurs and investors, highlighting the processes involved in these activities and their aftereffects. The study was conducted using a descriptive methodology, primarily qualitative. A multiple-case study was used, and, for that, semi-structured interviews were conducted with ten entrepreneurs in the (i) social finance, (ii) education, (iii) health, (iv) citizenship and (v) green tech fields, as well as three representatives of various impact investments, which are (i) venture capital, (ii) loan and (iii) equity interest areas. Convenience (non-probabilistic) sampling was adopted to select both businesses and investors, who voluntarily contributed to the research. The evaluation is still incipient in most of the studied business cases. Some stand out by adopting well-known methodologies like Global Impact Investing Report System (GIIRS), but still, have a lot to improve in several aspects. Most of these enterprises use nonexperimental research conducted by their own employees, which is ordinarily not understood as 'golden standard' to some authors in the area. Nevertheless, from the entrepreneur point of view, it is possible to identify that most of them including those routines in some extent in their day-by-day activities, despite the difficulty they have of the business in general. In turn, the investors do not have overall directions to establish evaluation initiatives in respective enterprises; they are funding. There is a mechanism of trust, and this is, usually, enough to prove the impact for all stakeholders. The work concludes that there is a large gap between what the literature states in regard to what should be the best practices in these businesses and what the enterprises really do. The evaluation initiatives must be included in some extension in all enterprises in order to confirm social impact that they realize. Here it is recommended the development and adoption of more flexible evaluation mechanisms that consider the complexity involved in these businesses’ routines. The reflections of the research also suggest important implications for the field of Social Enterprises, whose practices are far from what the theory preaches. It highlights the risk of the legitimacy of these enterprises that identify themselves as 'social impact', sometimes without the proper proof based on causality data. Consequently, this makes the field of social entrepreneurship fragile and susceptible to questioning, weakening the ecosystem as a whole. In this way, the top priorities of these enterprises must be handled together with the results and impact measurement activities. Likewise, it is recommended to perform further investigations that consider the trade-offs between impact versus profit. In addition, research about gender, the entrepreneur motivation to call themselves as Social Enterprises, and the possible unintended consequences from these businesses also should be investigated.

Keywords: evaluation practices, impact, results, social enterprise, social entrepreneurship ecosystem

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