International Journal of Finance and Managerial Accounting
Volume:6 Issue: 21, Spring 2021

The purpose of the present study is to test the information content of investors' emotional behavior and the quality of financial reporting by emphasizing the role of capital structure and free floats in listed companies in Tehran Stock Exchange. Initially, data on 110 companies were collected from the databases of the Iranian Stock Exchange during the years 2009 to 2018 and they were then analyzed in the framework of ANOVA method. In this study, the criteria for measuring financial reporting quality are Jones method, Ball and Shivakumar methods.The hypothesis testing results indicate the increasing influence of understanding the relationship between investors' emotional behavior and financial reporting quality on information content is influenced by capital structure. In other words, external supervision through receiving loans increases the information content of accounting items because with the addition of financing amounts, financial risk also increases, and shareholders behave more rationally with the perception of increased risk.

Sustainability and development of the audit profession is a function of the quality of auditors' services and adherence to professional standards such as independence plays a key role in this. Consequences of neglecting the quality of services and non-compliance with ethical standards can create irreparable crises. The phenomenon of audit opinion shopping is one of the unethical issues in the auditing profession that plays a role in destroying the general face of auditing and its specialized role. The purpose of this study was to investigate the relationship between the elements of corporate governance includes institutional ownership, ownership concentration, board size, and board independence and the audit opinion shopping in companies accepted in Tehran Stock Exchange (TSE). To achieve this goal, 120 companies listed on the Tehran Stock Exchange were selected between 2001 to 2016 and were tested using logistics regression. The results showed that there is a positive and significant relationship between the ownership concentration and the audit opinion shopping and there was no significant relationship between the other independent variables and the audit opinion shopping.

Selecting an appropriate portfolio making an optimal trade of between the return of assets and the associated risk of them has been always a fundamental challenge for different investors with different types of assets. The problem becomes more complex for an investor investing in private companies of which she doesn’t have enough data to evaluate its return and risk. Furthermore, this type of investment involves selecting more high risk assets which may not meet the risk attitude of the investor. In this study, a bi-objective portfolio optimization model has been developed to determine the best sets of portfolios for a private investing company. Due to the lack of data on private assets, a simulation based approach has been used to estimate the return of different assets as well as their correlations. A Covariance-Based Artificial Bee Colony is applied to solve the model. The results show that optimal portfolios consist both high-risk and low-risk assets.

An accounting information system (AIS) is a critical technology-driven asset for all organizations, whose produced and disseminated information is of paramount importance in making effective strategic decisions and reaching current organizational benefits. The quality of accounting information in these decisions depends on the performance capabilities of these systems. Previous studies have detected a number of direct organizational benefits gained through effective information technology (IT) governance. Such benefits encompass improvements in the performance of enterprise information systems, including accounting information systems. The present study aimed to examine the capacity of aligned IT-business culture as a communication mechanism in IT governance to improve the performance of the AISs in organizations. The data were collected using a questionnaire distributed among accounting experts selected from the companies listed in Tehran Stock Exchange. Partial least squares method was used to analyze the collected data. The results indicate that IT management capabilities manage to improve the AIS performance under effective guidance and control of the IT governance in spite of the environmental dynamism.

The latest researches of the analysis on financial distress show that the background of management mentally of emotional-cognitive biases has important role on identifying and creation of financial distress. Therefore, the aim of this study is an analysis of financial distress proceed by emotional-cognitive biases of organizational managers based on Narcissism approach in the listed companies of Tehran Stock Exchange through using a statistical sample including 147 firms on the year of 2019, which selected by the six determined factors of financial distress in the last researches. The result of regression analyses show that there is a significant and positive relationship between the emotional-cognitive biases of managers including overconfidence, control illusion, conservatism, optimism, loss avoidance, and regret aversion with financial distress, such as the higher level of emotional-cognitive biases of organizational managers due to more financial distress. Hence, the incidence of financial distress proceeds by the higher level of emotional-cognitive biases of managers.

 Fiscal discipline provides a mechanism for maintaining financial health and a favorable vision for listed companies by matching revenue and expenses with goal achievement programs (GAP), which, if realized, can ensure the success of these companies. Thus, this study was carried out aimed to identify and explain the factors affecting the fiscal discipline of companies listed on the Tehran Stock Exchange. The present study is considered as an applied research in terms of purpose and as a descriptive survey research in terms of method. In this study, population is listed companies that 114 companies have been selected as a sample using systematic sampling method. Analysis of research data was done using artificial neural network (ANN) and two-layer perceptron and Matlab software. The results show that the most important factors affecting fiscal discipline include financial health, financial stability, debt growth rate, capital expenditures, profitability, and firm value and information uncertainty of companies.

The tourism industry has a great potential to generate foreign exchange income and stimulates employment. The industry plays an important role in the process of economic development of Iran. The capacity of an economy to benefit from tourism depends on its access to (foreign) capital to invest in its infrastructures. Given Iran's limited oil revenues and the low rate of fixed capital formation, attracting foreign tourists and foreign direct investment (FDI) are among the urgent needs. In this regard, an investigation of factors affecting these two variables are of particular importance for policymakers. The present study investigates the relationship between these two variables from 1995 to 2016 with regard to institutional quality. For this purpose, Time-Varying Parameter Vector Autoregressions was applied. The results show that foreign direct investment, institutional quality and tourism have positive correlations. With the decline of institutional quality in Iran's economy after 2000, the positive correlation between foreign direct investment and tourism has weakened. Therefore, institutional quality is one of the most important determinants of the correlation between FDI and tourism in the Iran's economy.

IMC is one of the newest perspectives and models in targeting business advertising and communications. This systematic model seeks the effectiveness and synergy of corporate communication and advertising activities. the research was aimed to design and explain the IMC model in the Tehran Stock Exchange. This research is practical and the development in terms of purpose, and hybrid quantitative and qualitative methods in terms of method. The statistical population consisted of two groups of experts, 20 specialists in the field of marketing and stock exchange from university professors and top brokerage managers of the Tehran Stock Exchange, which were selected by a snowball and purposive sampling method. Data collection tools were the in-depth study of theoretical literature and semi-structured interviews with experts. To answer the questions in the qualitative section and identify the essential components and indices of IMC, first through the in-depth study of previous research, relatively comprehensive knowledge of the literature was obtained. These factors were then interviewed in the Delphi technique in three stages, and expert opinions were applied to the model. Due to the high values of the agreement coefficient in the third stage of the interview, the indices of the conceptual model were approved by the experts. This model was identified and prioritized in four conceptual layers, ten components, and 56 indices. It was proposed and presented as the best model for combining tools and methods of IMC in the Tehran Stock Exchange.

Auditing provides an overall image of the companies’ situation. So, in addition to disclosure of historical information, disclosure of prospective information is needed by the investors, and it leads to an improved quality of reporting and decision making. The reporting variations due to business changes have caused great challenges for firms regarding the preparation of discretionary information disclosure, in particular forward-looking information. Accordingly, this study aimed at determining the significance order of forward-looking information factors and components by the qualitative grounded theory approach. To this end, by distributing a questionnaire among seven financial experts selected through judgmental purposive sampling, the factors were evaluated by the fuzzy analytical hierarchy process (fuzzy AHP). A tool was eventually proposed for weighted components to prepare and assess forward-looking information. According to the results, “predicting and analyzing managers” ranked first with the highest importance coefficient, and “future financial and non-financial information” and “future objectives and strategies” ranked the next places.

 The purpose of this study was to analyze the impact of the social and professional identity of the members of the audit committee and the characteristics of the governance system on the financial reporting quality. The modified Jones model was used to express the financial reporting quality. Given that part of the data was obtained through a questionnaire and another part by using financial statements. The research period was 2019 and the sample size was 79 companies listed in Tehran Stock Exchange. To test the research hypotheses, the method of decision making artificial intelligence method and MATLAB software were used.The results of the section of the governance system features indicate the effect of the dual role of the CEO and the ratio of institutional owners on the financial reporting quality. It can be stated that corporate governance mechanisms can reduce opportunistic behavior; they can improve the quality of information by reducing the cost of representation. Also, the results of the audit committee's benchmarks indicate the impact of the audit committee's social identity and the number of employees in internal accounting section on the financial reporting quality, which suggests that effective audit committees, as a determining factor in the financial reporting process, increase the credibility of audited financial statements. In this study, for the first time, the impact of audit committee social identity along with other characteristics of governance system on the quality of financial reporting was analyzed by artificial intelligence.

 Because of the challenges that the Customs Organization faces, some changes have been occurring in the management system of customs in different countries of the world. The Islamic Republic of Iran and the management system ruling its customs has accepted that structural change is an essential need in this sector. Hence, this study was conducted to examine the post-clearance audit and solutions and factors affecting it using the foreign trade facilitation and development approach. The extant research is applied research in terms of objective, and required data were collected from questionnaires distributed among 92 subjects including experts in customs affairs. Results showed that six criteria of risk management, customs strategies, customs human resources, importers and traders, rules and regulations, and customs infrastructures are the factors affecting an optimal post-clearance audit implementation. Customs infrastructures were introduced as the most critical factor. Accordingly, it seems that it is essential to create Customs Infrastructures as the first effective step to successful PCA.

The present study was an attempt to explain the effect of time pressure on auditors on earnings quality, with an emphasis on the adjusting role of the auditor tenure. For this applied research, a descriptive-correlational method was used. Theoretical basis and statistical data of the study were collected using desk and field studies from 2014 to2019. Data of 105 companies were collected from capital market companies (Tehran Stock Exchange) as a statistical sample, through systematic elimination. The research hypotheses were tested using regression analysis statistical method with combined data at a level of 5% error using EViews. The results of the data analysis indicated that the time pressure on auditors reduces the earnings quality. In addition, the result of the second hypothesis indicated that the auditor tenure intensifies the negative relationship between the time pressure on auditors and earnings quality. In other words, increased time pressure on the auditor decreases earnings quality. The probable reason is that when auditors are under time pressure, the legal requirements of work, the exercise of strict control by supervisors, and the requirements of employers, in other words, they are under workload pressure, auditors will have far more unethical decisions and behaviors.

 In case that controlling mechanisms such as auditors, supervisory auditors and others be inefficient, conditions get ready for management so that they can manipulate earnings with the aim of reaching to the desired results in the reports such as preparing the expectations of analysts, preventing loss, having access to a growth process or smoothing the level of reported earnings. Therefore, specific experiences of auditors can develop professional auditing knowledge and have various effects on estimating the parameters and indexes such as earning management. The current research aimed at identifying tacit knowledge factors and managers` experiences in the earning management behavioral pattern using Delphi method. Statistical population of this study included official auditors and financial experts. To collect data, interview method based on the questionnaire was utilized. The personal and individual effects, experiences and tacit knowledge of taxes, accounting and financial experiences and tacit knowledge, management experiences and tacit knowledge, auditing experiences and tacit knowledge, political experiences and tacit knowledge, experiences and tacit knowledge of working rules and social security were among experiences and tacit knowledge criteria of managers regarding earning management. The results indicated that respectively, auditing experiences and tacit knowledge, experiences and tacit knowledge of working rules and social security, experiences and tacit knowledge of taxes, personal and individual experiences and tacit knowledge, accounting and financial experiences and tacit knowledge, experiences and tacit knowledge of other fields, political experiences and tacit knowledge and management experiences and tacit knowledge were effective on earning management

This study evaluated the relationship between behavioral bias with an emphasis on perception bias and earnings management incentives among financial analysts, accountants, and auditors. The sample of this study included 10 experts in the fields of accounting and auditing. In terms of the technical dimension, the fuzzy method was used to include uncertainty in the research. Instead of using a pairwise comparison of factors, the non-rank comparison of the ELECTRE III method with a systematic review was used to study and rank the different dimensions of perception bias factors affecting the types of earnings management through the Delphi method and the opinion of the elite. The results of the study indicated that out of 65 variables of perception bias affecting the role of earnings management, 27 top biases were identified and prioritized. The obtained results showed that the highest effect on earnings management types was related to overconfidence bias, regret aversion, and self-serving bias being at the first to third ranks. Besides, based on the scenario-building in developing an optimal model, the model with a significant relationship between perception bias and all types of earnings management (real, accrual, efficient, and opportunistic earnings management) significantly was more accurate than those in which the relationship between perception bias with some types of earnings management was considered.

Enterprise risk management has a high impact on the improvement of a high-risk an organized culture of an organization in such a way, that it creates a transparent responsibility in relation to the enterprise risks like bankruptcy risk. Risk management operations, shift from a controlling role toward operative role and coordinator of risk management activities in such a way that the risks are clearly accepted by those who are responsible for decision making in the risk. Therefore, in this study has been paid to the assessment of Enterprise Risk Management (ERM) effect on bankruptcy risk using weed optimization and particles swarm optimization algorithms. To do this research a sample of 107 enterprises which are accepted in Tehran Stock Exchange are selected using sampling method. This study has been done in Tehran stock exchange in the period of 1392-1397. Multivariable regression using data panel and optimized algorithm is the implemented statistical method in this research. The result of this research shows that weed optimization and particles swarm optimization algorithms are capable of predicting bankruptcy risk using elements of ERM. In addition, comparing these two methods of optimization, particles swarm optimization is more efficient in the prediction of bankruptcy risk using ERM variable. Keywords: Enterprise Risk Management (ERM), bankruptcy risk, weed optimization algorithm, particles swarm optimization algorithm.