درخت حوزه‌های تخصصی

The purpose of this paper is to investigate the role of political instability in the context of the association between board of directors (BOD) and audit committee (AC) quality as indicators of corporate governance effectiveness and earnings management (EM). The non-financial listed companies on the Palestine Exchange (PEX) between the period from 2011 to 2018 were the samples of the study. Based on the OLS regression results by using a panel data of 232 observations, the findings show that the BOD quality is positively related to EM, while AC quality is negatively associated with EM. The results also reveal that political instability plays a moderating role by weakening the relationship between the AC quality and EM during the severe unstable political situation, while the BOD quality is negatively associated with EM under the same situation. This finding implies that the BODs might substitute ACs under severe political instabilities to protect the stockholders and stakeholders’ interests. Unlike most previous studies, this article addresses political instability as a moderating variable for the relationship between the BOD and AC quality as a composite measure of EM in the most emerging and smallest stock market in the region. The results of this work may assist the regulatory bodies, policymakers, and practitioners in revising the corporate governance code to promote the efficiency of the BOD and AC monitoring functions for the purpose to improve the faithfulness and reliability of financial reports and also to deter the management from engaging in critical levels of EM.

After the Coronavirus diseases (COVID-19) outbreak, the Whole world witnessed the strangest buying behavior within the customers. Suddenly masks, hand sanitizers, and toilet papers became the priority list of the customers. High demand and lesser availability of essentials products like masks, toilet papers, and hand sanitizers create a chaotic situation inside the retail outlet's stores.  The buyer’s behavior and the chaotic scenario inside a retail outlet drew the attention of several consumer psychologists, academicians, and researchers. A panic buying situation is the most common behavior that exists in a time of crisis. This paper discusses the panic buying situation briefly during COVID-19. However, a few types of research and studies were captured in the panic buying behavior. The current study examined the factors that influenced the customers buying decisions during the COVID-19 outbreak and secondly, it examined to what extent the buying decision of a customer creates a panic situation. Furthermore, the study looked at the emotional and cognitive responses of the individuals which play a pivotal role in influencing customer decision making the journey. Qualitative content analysis and thematic methodology were considered for data analysis. The results indicated that fear and uncertainties were the key emotional responses; whereas rumors, fallacious thinking, and survivalist psychological were the key cognitive responses that influenced the customer decision journey.

As electronic commerce has gained widespread popularity, payments made for users' transactions through credit cards also gained an equal amount of reputation. Whenever shopping through the web is made, the chance for the occurrence of fraudulent activities are escalating. In this paper, we have proposed a three-phase scheme to detect fraudulent activities. A profile for the card users based on their behavior is created by employing a machine learning technique in the second phase extraction of a precise communicative pattern for the card users depending upon the accumulated transactions and the user's earlier transactions. A collection of classifiers are then trained based on all behavioral pattern. The trained collection of classifiers are then used to detect the fraudulent online activities that occurred. If an emerging transaction is fraudulent, feedback is taken, which resolves the drift's difficulty in the notion. Experiments performed indicated that the proposed scheme works better than other schemes.

This paper focuses on the problems of company’s sustainable management in an emergent environment. The authors’ vision of the functioning peculiarities in the formulation of a company’s strategy based on the information support is presented in the article. The world experience of studying the development of investment projects in companies of different industry sectors is investigated and analyzed according to the economic and mathematical modeling. A multivariate model of evaluation and selection of the investment project based on the hierarchy criterion of company's economic objectives with the information technology is developed as an embodiment of the strategic goal of ensuring the company's sustainability. The essence of the hierarchy criterion method is to determine the order and the value of priority of each individual criterion, thus, application of this method allows providing recommendations for making an effective management decision in unpredictable environment. The proposed model based on the hierarchy criterion of company’s economic tasks allows providing sustainability in emergent environment. The analysis and substantiation of the necessity of applying the proposed model with the information technology support is presented in this paper.

The modeling engineering of psychotherapeutic approaches to diabetic patients has a positive impact on the quality of the support process and organizational, personal and professional development, in the sense that the education and neuro-educational training project constitutes a powerful human resources management vector. The research would attempt to analyze therapeutic education models and corresponding health promotion approaches, as well as the identification of methods and techniques used in health practice As a result, the quality of the neuro-educational approaches is the guarantor of the effectiveness of the recommended support system. Adopting this imperative highlight, a new PCA patient-centered approach. This major concern therefore calls on the medical profession to question the impact and effects of collaborative support in the process of building and developing the conceptual, procedural and behavioral skills of diabetic patients which facilitate their self-knowledge, their self-determination and their awareness of the factors of therapeutic effectiveness and the promotion of their physical, moral, social and psychological well-being. It prompts us to ask ourselves how the different care teams and support actors organize and coordinate their andragogical actions, with a view to complementarity and synergy. We proceed, through a descriptive and exploratory research approach, opting for a so-called longitudinal survey, by a semi-directive questionnaire and by an interview technique. By comparing the results of the study with the validation interviews, it emerges that appropriate attention must be paid to the support process to allow the diabetic patient to master all the components of reflective therapeutic practice and to achieve his personal and organizational development necessary for the development of a subject actor of change and innovation. This support system engineering will define the frame of reference, including the ethical values ​​and the basis of the required professional skills which will be applicable to any program for the development of cognitive and behavioral skills in diabetic patients. The new vision will be built around adapted support practices, collaborative approaches, a comprehensive, harmonious and balanced therapeutic education program, personalized training courses and inclusive evaluation methods that go well beyond validation and tenure. (Towards a sick-centered vocation).

The E-commerce has been grown rapidly with the rise in the number of business entities. The expansion of e-commerce businesses, however, has created challenges to the tax authorities around the world. Due to the way in which e-commerce is being carry out, it may provide tax planning opportunities. This study aims to explore whether businesses that conducted e-commerce in Malaysia has the intention to do tax planning. Interviews were conducted with e-commerce business administrators. Result indicates that tax issues is not the main motivations for companies to do e-commerce. This indicates that other factors are more important for e-commerce businesses to consider in their planning stage

World of technology provides everyone with a great outlet to give their opinion, using social media like Twitter and other platforms. This paper employs machine learning methods for text analysis to obtain sentiments of reviews by the people on twitter. Sentiment analysis of the text uses Natural language processing, a machine learning technique to tell the orientation of opinion of a piece of text. This system extracts attributes from the piece of writing such as a) The polarity of text, whether the speaker is criticizing or appreciating, b) The topic of discussion, subject of the text. A comparison of the work done so far on sentiment analysis on tweets has been shown. A detailed discussion on feature extraction and feature representation is provided. Comparison of six classifiers: Naïve Bayes, Decision Tree, Logistic Regression, Support Vector Machine, XGBoost and Random Forest, based on their accuracy depending upon type of feature, is shown. Moreover, this paper also provides sentiment analysis of political views and public opinion on lockdown in India. Tweets with ‘#lockdown’ are analysed for their sentiment categorically and a schematic analysis is shown.