درخت حوزه‌های تخصصی

Religious tourism is one of the world's most critical current types of tourism, especially in Islamic countries such as Iran, which has a high potential for development and progress in this field. However, the development of this type of tourism in our country is not restricted to only religious cities but includes other cities in Iran. With its religious-pilgrimage functions, Sari city in Mazandaran province provides an appropriate ground for developing religious tourism as one of the main forms of tourism. The present research first conducted a set of observations in the region after studying library documents using the field method. After analyzing data from the observations, research questions were evaluated by organizations, experts, and the local community. The results were quantitatively examined by SWOT analysis. Finally, according to extracted concepts from qualitative and quantitative analysis, a model for the development of religious tourism was obtained based on library and field studies using interviews and then evaluated by experts. Results show that religious places of Sari city aren’t on the list of development priorities. It presents a model for development in this region with more challenges. Therefore, the qualitative and quantitative analysis results of this research imply a very appropriate situation and a high potential for religious tourism, emphasizing Imamzadeh in Sari city.

Efficient market hypothesis predicts that capital markets are beset with cer-tain biases which result from wrong estimation, and negatively influence shareholders’ expectations for higher returns, which in turn affects invest-ment efficiency, financial constraints and corporate performance efficacy in competitive markets, and eventually mitigates firm value. The present study aims at examining the impact of CEOs’ perceptual biases on investment efficiency and financing constraints of the firms listed on the Tehran Stock Exchange over the period 2013-2017. Earnings forecast error and CEOs’ overconfidence biases serve as the measure of CEO’s perceptual biases, the model developed by Biddle et al (2009) is employed to proxy for investment efficiency, and KZ model is also adopted to calculate financing constraints. The results reveal that both earnings forecast error and overconfidence biases negatively affect investment efficiency, while they positively influence cor-porate financing constraints.

K nearest neighbor algorithm is one of the most frequently used techniques in data mining for its integrity and performance. Though the KNN algorithm is highly effective in many cases, it has some essential deficiencies, which affects the classification accuracy of the algorithm. First, the effectiveness of the algorithm is affected by redundant and irrelevant features. Furthermore, this algorithm does not consider the differences between samples, which led the algorithm to have inaccurate predictions. In this paper, we proposed a novel scheme for improving the accuracy of the KNN classification algorithm based on the new weighting technique and stepwise feature selection. First, we used a stepwise feature selection method to eliminate irrelevant features and select highly correlated features with the class category. Then a new weighting method was proposed to give authority value to each sample in train dataset based on neighbor categories and Euclidean distances. This weighting approach gives a higher preference to samples that have neighbors with close Euclidean distance while they are in the same category, which can effectively increase the classification accuracy of the algorithm. We evaluated the accuracy rate of the proposed method and analyzed it with the traditional KNN algorithm and some similar works with the use of five real-world UCI datasets. The experiment results determined that the proposed scheme (denoted by WAD-KNN) performed better than the traditional KNN algorithm and considered approaches with the improvement of approximately 10% accuracy.

The objective of the research is to clarify what Blockchain technique is and the developments of its various uses, and identify the accounting perspective of this technique and the possibility of using it in accounting work. It also aims at demonstrating how to utilize its Blockchain technique in accounting information systems, and identify the most important potential effects of the use of technique in accounting information systems. To achieve the research objectives, a descriptive approach was adopted to discuss the fundamentals of Blockchain technique and its most important accounting implications, in addition, its significance for the usefulness and reliability of the development of automated computing accounting systems. The researchers concluded that the use of Blockchain technology for accounting work requires analysis of the related impact on the development of accounting information systems in terms of their implementations and modules, with the need to fully transition in the design of accounting information systems to electronic sophisticated programs and applications developed and technologically advanced.