International Journal of Finance and Managerial Accounting
Volume:3 Issue: 9, Spring 2018

Companies today face the challenge of adopting proper supply chain sustainability (SCS) strategies and practices to respond effectively to emerging global sustainability initiatives. Business sustainability has become a strategic imperative, with a focus on both financial and non-financial sustainability performance, which creates shared value for all stakeholders. This paper examines the integration of business sustainability into SCS by presenting a model consisting of sustainability theories, sustainability continuous improvement, and sustainability best practices. Companies can use the suggested model to integrate both financial and non-financial sustainability performance information into business models, corporate culture, and supply chain management. This paper also presents several best practices of supply chain sustainability performance by investigating the SCS of a sample of high-profile companies worldwide across many industries. The suggested model and best practices of SCS in this study have implications for policymakers, regulators, standard-setters, management, researchers, and educators. Propositions are posited for the suggested model in promoting business sustainability and SCS strategies.

The aim of this study was to investigate accounting principles of integrated management using a critical approach. To this end, in this study, we used four principles of relevance, influence, value, and trust as the global management accounting principles. The research questions and hypotheses were developed based on the critical thinking that management accounting is not currently convincing both in theory and practice. This study is considered a survey research as it used questionnaires to collect experimental data for testing the research hypotheses. The results of statistical tests performed in this study indicated that the respondents had positive attitudes toward the four afore-mentioned principles and this they can be considered as global management accounting principles.

One of the most important duties of financial economy is modeling and forecasting the volatilities of price of risky assets. From analysts and policy makers’ view, price volatility is a key variable contributing to perception of market volatilities. Therefore, analysts need to have an appropriate of forecast of price volatility as a necessary input to perform duties such as risk management, portfolio allotment, assessment of at-risk value, pricing, authority of transaction and future contracts. Accordingly, in the present study, using TVP-SV and PLS models and comparison them with the method OLS in MATLAB and XLSTAT software in the period from 2003-01 to 2016-06 (monthly) the effect of actual variables (industrial production, investment of actual sector in housing, economic growth, share of government expenses to GDP and growth rate of nonoil export) and monetary variables (inflation, money arena, oil price, domestic price of gold) on return of the Tehran Stock Exchange is investigated. Based on the PLS model, it was concluded that variables of economic growth and oil price affected the efficiency of the Tehran Stock Exchange more than other variables. Then, variables of economic growth and oil price were entered to the TVP-SV model. According to results, the model TVP is more efficient than the OLS one. In addition, the TVP-SV model after pause of stock return, economic growth during the period had the highest efficiency on stock return.

Due to the integration and interrelatedness of the global economy in recent decades, the onset of financial crisis from the U.S. economy and its diffusion to the other global economies has led to the most important events and global financial crisis at the beginning of the third millennium. This investigation aims to examine the impact of financial distress on tax avoidance of the listed companies in Tehran stock exchange during the global financial crisis. All listed companies in Tehran stock exchange were selected as the statistical population of the research during 2003 to 2013. In this investigation, the base year (crisis) is 2008 and 2003 to 2008 as before the financial crisis and 2008 to 2013 is regarded after the crisis period. 90 firms were selected through the systematic elimination method. Heteroskedasticity, F-Limer, Hausman and Lin-Levene tests were used as pretest and regression test as post test to confirm/reject the research hypotheses. EVIEWS9 software was used in this research to analyze data. The results showed that there is no significant relation between financial distress and tax avoidance of the listed companies in Tehran stock exchange.

Today, women are considered as one of the main pillars of corporate decision making, which can contribute to the development and promotion of corporate initiatives and projects within the framework of the development of trust and confidence of shareholders and society. The purpose of this research is to investigate the association between the presence of women on boards of directors and tax avoidance in firms listed on the Tehran Stock Exchange. To do so, a sample of 97 companies were surveyed during the years 2011 to 2015 and tested using multivariate regression models based on panel data. The results of the research showed that the presence of women on corporate boards reduces corporate tax avoidance. Moreover, Additional analysis reveals that the negative association between presence of women on boards and corporate tax avoidance is more pronounced in larger firms. The findings of current study not only fill existing gaps in the field, but also help investors, tax regulators and other accounting stakeholders make informed decisions

One of the most important methods of opacity accounting information by management is to accelerate the identification of good news versus delaying the identification of bad news on profits, but there is always a final level of accumulation of bad news in the company, and by reaching that its final level, these bad news will be released, which will lead to a Stock Price Crash Risk. In fact, stock price collapse is a phenomenon in which stock prices are subject to severe negative and sudden adjustments. Accordingly, the first purpose of this research is to model the Stock Price Crash Risk of the listed companies at the Tehran Stock Exchange by using an optimal algorithm The cumulative particles and comparison with the results of logistic regression model. To this, a hypothesis was developed for the study of this issue and the data of 101 listed companies of Tehran Stock Exchange for the period between 2010 and 2014 were analyzed. First, 14 independent variables were introduced as inputs of the combined genetic algorithm and artificial neural network, which was considered as a feature selection method, and 7 optimal variables were selected. Then, using particle cumulative algorithm and logistic regression, predicted The Crashs. To calculate the Stock Price Crash Risk, a Stock Price Crash Period criterion has been used. In The Second Stage, the particle algorithm was used as a feature selection, and this time, to calculate the Crash risk, the NCSKEW criterion was used. Finally, the optimal variables were entered into the Ant Colony algorithm and the results were compared with the multivariable regression. In the second step, MSE and MAE were used to compare the results. The results of the research show that the particle Swarm Optimization and Ant colony are more able than traditional regression (lojestic and multivariable) to predict the Crashs. Therefore, the research hypothesises are confirmed.

The existence of an active and prosperous capital market is always recognized as one of the signs of international development in the countries. The most important issue faced by investors in these markets is the decision to choose the appropriate securities for investment and formation of optimal portfolio. The rating of companies accepted in stock exchange is a complete mirror of their status and is a measure of investment. This will increase the competitiveness, development and market efficiency.
In this research, the top 20 companies listed in Tehran Stock Exchange during the third quarter of 2015 are ranked according to financial ratios. In previous studies, optimal portfolio has been determined using data envelopment analysis models and multi-criteria decision making techniques, but the present study combines these two techniques to evaluate and determine the most efficient portfolio. Accordingly, the performance scores of each model are obtained using one of the data envelopment analysis model and then, the weight of each index is obtained using the network analysis process through multi-criteria decision-making techniques.

Considering necessity of recognizing the knowledge-based economy and achieving its foundations in Iran, the main issue of this research is to clarify the relationship between intellectual capital and Refined EVA in insurance companies which are member of Tehran Stock Exchange. In this research, the Refined EVA index was used to evaluate and measure the intellectual capital of the Palick model and also to quantify the economic performance. Accordingly, information about 15 insurance companies during the period of 2011-2016 was analyzed to examine the relationship between these variables. The collected data are calculated using Excel software and analyzed with Eviews®. The results indicated that there is a significant and positive relationship between the components of intellectual capital (human capital, physical capital, and structural capital) with Refined EVA; as an issue that has a decisive role in the success or failure of companies in competitive markets.