درخت حوزه‌های تخصصی

The purpose of the research Decline of Auditors' Financial Bias in Decision making by Professionalism in Auditing: Rough Set Analysis. The research approach is of inductive-deductive type in terms of the data collection meth-od, because it was first determined based on the content analysis of the com-ponents and propositions related to the professional characteristics, then it was tried to confirm or delete the propositions based on the Delphi analysis. This research by participating 14 individuals of the audit partners with the academic degrees over a one-year period, 2018-2019. The results According to the formation of decision making matrix, the results showed that both propositions, the perceptual error of failure to separate the context from con-tent as the Halo bias and the perceptual error of the experience of fraud de-tection in the financial statement as memory bias were determined as the most influential perceptual errors in the audit profession in Iran. In addition, according to gray vikor theory analysis, it was found that the component of the audit's professional maturity was selected as the most important priority and the most effective feature for reducing the audit perceptual bias.

Many behavioral biases affect investors when making decisions.Behavioral distortions divert the investor from rational decisions, and as a result, resources are not diverted to appropriate investments.Behavioral biases can be evaluated in different types including the two phenomena of mental anchor and collective behavior of investors. In the present study, the phenomenon of collective behavior and mental anchor of investors with emphasis on significant weaknesses in internal control has been investigated. For this purpose, the data of 125 companies listed on the Tehran Stock Exchange during the period 2012 to 2018 were used.Data analysis was performed in eviews software version 10 and in order to fit the regression models,the generalized least squares method of panel data was used. The results using univariate analysis showed that there is no significant difference between the amount of behavioral biases in each of the two groups of companies with weakness and lack of weakness in internal control.While multivariate analysis of data in the form of regression models showed that the auditor's report on significant weaknesses in internal control,(which Weakness indicates high agency costs and high information asymmetry between managers and shareholders) strengthens It is the collective behavior of investors but it has no effect on their mental anchor.According to the results, it seems that the behavioral biases of investors are conditioned by the priority and importance of good and bad news in the market.As long as there is bad news in the stock market towards the company, good news can’t cause behavioral bias in investors.

The purpose of this paper is to provide a new approach to incorporating uncertainty into assessing the profitability of investment projects. In the real world, the capital budgeting problem is accompanied by uncertainty and risk associated dealing with imprecise data. The major contribution of this research is the development of a novel approach to evaluating the profitability of an investment project in uncertainty condition. At first, we presented a new discount method that can be used by investors when they wants to be able to make an investment decision. That is, we developed a new method to evaluate the profitability of investment projects by or-dered fuzzy net present value (OFNPV). In addition, ordered fuzzy numbers (OFN) are used to describe the dynamics of changes of the defined investment parameters in the assumed time horizon. By using ordered fuzzy numbers, we develop an effective tool for assessing the profitability of investment projects. This assessment tool not only enables decision-makers to decide under uncertainty conditions whether or not a given investment project should be carried out or rejected, but also facilitates selecting the most effective project, e.g. a project with the most expected probability of success.

Investor expectations future economic processes are among the crucial factors affecting their decisions. The expectations seem to play a specific role since they are unsupervised variables capable of forming observable economic phenomena. Psychological factors influence investor expectations and corporate market value. Investor sentiments was modelled with an emphasis on psychological factors based on the Grounded Theory (GT). This applied and mixed-methods at its first and second stages. The statistical population comprised 13 experts, senior managers of investment companies, and university professors. The participants were selected through purposive and snowball sampling and the process was continued until theoretical saturation. The data were collected via semi-structured interviews coded via Atlas.ta.8 software. The research data were analysed using an open coding method. The results of the research were presented in 46 categories and 6 key dimensions.

Providing credit facilities to clients can be regarded as one of the most important tasks of banks. As a result, the current research is carried out with the aim of developing a model of financial and non-financial factors that influence credit risk in the Maskan Bank. This study was divided into two sections: qualitative and quantitative. In the qualitative portion, the Delphi technique was used to identify financial and non-financial variables impacting credit risk in the Maskan Bank by interviewing 18 experts. In the quantitative section, the selected components of the questionnaire were initially created in a 5-point Likert scale. The questionnaire was then presented to 361 legal clients of Maskan Bank from the statistical sam-ple of the quantitative section. The quantitative component was completed using LISREL software and modeling the structural equations of SEM. Three primary components (financial, market, and management) and 33 sub-components were identified as financial and non-financial indicators impacting credit risk based on the results of the qualitative section. The quantitative findings also revealed that the indicators of guarantee status in the financial component, price level in the market component, and manpower motivation and productivity, as well as man-agement continuity and trade in the management component, had the largest factor loads.

Online reviews play a crucial role in the consumer decision-making process in the glamping industry. Some reviews are misleading; therefore, users need to identify credible reviews to form objective opinions. This study examined dimensions of perceived review credibility and its influence on purchase intention within the glamping business. Online surveys were conducted with respondents with relevant travel experiences to examine the key credibility factors. Findings identified that review length, amount of detail, writing style, and travelers’ images; as well as mixed, moderate, and two-sided reviews influence perceived review credibility. It was also found that perceived review credibility influences purchase intention; that management response impacts perceived company credibility and purchase intention; and that personalized management response is valuable for the perceived credibility and purchase intention. A revised conceptual framework was developed to demonstrate the sources of perceived credible online reviews and the role of management responses in the reviews. In addition to the theoretical contribution, this study can have practical marketing implications for businesses when creating online promotional material for their products and engaging with customers

This research aims to evaluate the effect of consumer traits, service quality, perception-based factors, customer satisfaction, and e-trust on electronic brand love and e-loyalty. In this study, a cross-sectional survey is conducted based on the questionnaire method to collect data from a sample of 300 customers of the Digikala Website in Isfahan, Iran. Structural equation modeling (SEM) is used to test the research hypotheses. According to the results, the service quality, consumer traits, and perception-based factors significantly affected customer satisfaction. Also, e-brand love had a significant impact on e-trust and e-loyalty; e-trust significantly affected e-brand love and e-loyalty, and e-brand love had a significant impact on e-loyalty. To the best of the authors’ knowledge, this research stands among the first to evaluate the factors affecting electronic brand love and loyalty. The evaluation of brand love on loyalty demonstrated that the greater the amount of love and fascination with a brand, the higher the positive effect on consumer loyalty. Overall, managers are recommended to do their best to eliminate misunderstandings and create an interest in consumers, ultimately leading to greater customer loyalty. Managers should pay more attention to brand experience dimensions, such as sensory marketing. In this regard, creating a brand community by e-retailers is very helpful.

With the rapid advancement of information and communication technology (ICT), public administration has adopted the concept of e-government. The academic literature produced many studies in the field of E-government (E-GOV) services, however, there is limited research on such services from the perspective of bibliometric and Network analysis. Therefore, this study aims to present a bibliometric and network analysis of the E-government services literature review obtained from the Scopus database, published between 2011 to 2021. This study uses a five-step method including (1) defining keywords, (2) initializing search outcomes, (3) inclusion and exclusion of some elements of the initial result, (4) compiling initial data statistics, and (5) undertaking analysis of data. The analysis starts by identifying more than 4,880 published articles related to E-government services published between 2011 and 2021. The study findings revealed that the highest number of publications on the E-government Service was in 2019 (102 articles), the top contributing affiliation was Brunel University London, the leading influential country was the USA, and the top contributing Source was Electronic Government. Furthermore, Lu J. occupied the first rank in the list of the most influential authors in terms of citations, while Weerakkody V. occupied the list of the top authors with high publications 20 papers. Likewise, this study showed that there is a collaboration among some authors. This research identified four research clusters by which researchers could be encouraged to widen the research of E-government services in the future. The bibliometric and network analysis of E-government services helps to graphically display the publication's assessment over time and identify domains of current studies' interests and potential directions for further studies. Finally, this research draws a roadmap for future investigation into E-government services.

Due to the existence of various paradigms and theories in accounting and various methods introduced to measure accounting values, as well as the lack of a complete and well-defined framework of these theories in terms of sociological paradigms, we decided to analyze sociology from theories. To achieve this goal, we used the content analysis method. In this way, first by examining the schools and theories of sociology and the main paradigm of positivism, interpretiveness, identification and components that were the characteristics of these paradigms were extracted and categorized from the themes and then the outputs were approved by sociology professors. And then accounting measurement theories and various theories using the method of taking notes from books and texts and articles extracted and sociological components in the context of accounting theories are searched and analyzed and at the end of accounting theories according to The extracted themes and their analytical codes are classified and analyzed and interpreted based on the obtained results. The results of the analysis of themes, new theories of accounting measurement tend to interpretism in which the role of the accountant is more prominent and historical cost theory is classified as a positivist sociological theory.

One of the strategies used in active portfolio management is the "network matrix model "which can be used to form different portfolios with different characteristics of stocks or companies. In this study, with the data of 156 companies listed on the Tehran Stock Exchange during the period 2011 to 2018 using the network matrix model and based on throughput accounting criteria, portfolio formation and their performance with the portfolios of the new network matrix model (Defensive, neutral and aggressive stocks) and market portfolio were compared. The results show that the proposed network matrix model portfolios based on throughput accounting criteria have higher performance than the new network matrix model in terms of Sharpe, Sortino, upside potential, and omega criteria. Also, portfolios consisting of stocks of companies with high system performance, in addition to the above criteria, have higher performance in terms of Jensen's Alpha criteria than the new network matrix model, and in terms of upside potential and omega criteria, have higher performance than the market portfolio. The performance of portfolios consisting of stocks of companies with low system performance has a stronger correlation with the market portfolio compared to the new network matrix model.

In this paper, first, the stochastic differential equations are introduced as well as the definition and basic theories about Monte Carlo and quasi-Monte Carlo and Sobel and Halton sequences are expressed. Indeed, we introduce and use simulations under these methods to compare the efficiency of the solutions, which the results show that the approximation of the resulting Sobel sequence is much better than other stochastic methods. The comparison of the efficiency of random and quasi-random methods, the geometric Brownian movement and the price index of Tehran stock (equal weight and weight-value) is studied. The results show that the quasi-Monte Carlo method is better than other methods.

This study examines the relationship between stock liquidity and return predicta-bility of 116 publicly-traded firms in Tehran Stock Exchange (TSE). To this end, we constructed a dated-regular frequency of time series with total 40128 stock-firm observations. After calculating daily bid-ask spreads and stock returns, the observations were classified based on liquidity into three classes and the return predictability was investigated across different classes using a set of parametric tests. The results exhibit signs of return autocorrelation and non-independence over three liquidity groups. Our findings didn’t show a connection between stock liquidity and market efficiency. The Hurst exponent also revealed mean reversion of returns series across different liquidity classes. We conclude that stock liquidity doesn’t play a significant role in market efficiency and return predictability of stocks in TSE. In case of TSE as other emerging markets, due to the small num-ber of traders (the need for more trading activity) and low market making activi-ties, both the cost of trading increases and the reaction to stock price information is delayed, resulting in predictability of price /return.

One of the important issues in the supply chain is the selection of reliable and efficient suppliers, which improves performance and competitive advantage. Therefore, the aim of this research is to implement two evaluation models based on failure rate and NDEA with the approach of choosing the right supplier in 7 separate supply chains of an electrical appliance manufacturing company in Shiraz. In this direction, a series-parallel system was used to evaluate based on the failure rate, which at the first level examines the reliability of the suppliers and at the second level examines the reliability of the devices required for the production of electrical appliances. And in order to calculate the efficiency of suppliers, the NDEA model was also used. The results showed that both presented approaches are suitable for evaluating the performance of the supply chain, because the performance rating of both models has high resolution.

Without utilization of computer and its related technology, modern day’s life cannot be headway. It has also transformed into an incredibly troublesome task. The genuine challenges included are shorter life cycles, cost effective and higher software quality goals. Despite these challenges the software developers have started to give cautious thought on to the procedure to develop software, testing and reliability investigation of software and to reinforce the method. Developer most fundamental decisions related to the perfect release time of Software. Software development method incorporates a piece of vulnerabilities and ambiguities. We have proposed a multi objective software release time issue under fuzzy environment using a software reliability growth model to overcome such vulnerabilities and ambiguities. Further we have discussed the fuzzy environment framework to deal with the issue. Considering model and issue, we can especially address the issue of when to release software under these conditions. Results are illustrated numerically.