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.

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).

Destination Image as a development which comprises of interrelated assessments converged with general impressions and convictions dependent on data preparing from an assortment of sources after some time; little research has concentrated on picture arrangement corresponding to this kind of goal, this article explores the mediating role of Online Image on the connection between E-WOM and  E-service quality, E-satisfaction, E- trust The result of Structural equation Modelling  (AMOS) path analysis affirmed that estimation model fulfilled the necessity and evidence the solidness of things, builds and correlation. All the four conditions for estimation model was met: things stacking above 0.7; unwavering composite quality (CR) above 0.7; Average Variance Extraction (AVE) above 0.5. The scholastics and industry will profit by the usage of this examination. Likewise, the tourist industry division can draw from these outcomes as references and proposals inside the impediments of the study. Future research headings were proposed to deal with the restrictions.

The steadily growing dependency over network environment introduces risk over information flow. The continuous use of various applications makes it necessary to sustain a level of security to establish safe and secure communication amongst the organizations and other networks that is under the threat of intrusions. The detection of Intrusion is the major research problem faced in the area of information security, the objective is to scrutinize threats or intrusions to secure information in the network Intrusion detection system (IDS) is one of the key to conquer against unfamiliar intrusions where intruders continuously modify their pattern and methodologies. In this paper authors introduces Intrusion detection system (IDS) framework that is deployed over KDD Cup99 dataset by using machine learning algorithms as Support Vector Machine (SVM), Naïve Bayes and Random Forest for the purpose of improving the precision, accuracy and recall value to compute the best suited algorithm.

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.

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