نشریه مهندسی مدیریت نوین
سال نهم شماره 4 (زمستان 1402)

In data envelopment analysis, different models are developed in different fields with different data for evaluation and ranking of DMUs. While in many applications issues, unit managers are faced with stochastic data, and they need a method to evaluate their supervised units in a way that can evaluate and rank such DMUs. When working with stochastic data, considering the probability of occurrence of unpredictable states (the level of error) provided by managers, the DMUs are evaluated. In this paper using Probability statistics techniques and normal distribution and the BCC model with undesirable outputs and a specific risk ofSpecified,a new stochastic model called Expected Ranking Criterion is introduced. Based on this,the stochastic cross-efficiency evaluation. Given the non-uniqueness of resulting optimal solutions, a model is introduced for rating priorities by which cross-efficiency is performed using aggressive method. The proposed model is implemented for 32 thermal power plants with stochastic inputs and undesirable outputs.

Company reports are one of the most important sources of obtaining information, so that the theoretical foundations of accounting and reporting in most countries state that the general purpose of company reporting is to provide information. The purpose of this research is to determine the factors influencing the voluntary disclosure of non-financial information from the perspective of institutional theory. In this research, a qualitative research method has been used, which is a combination of resource review and Delphi method, at first it was used by using the resource review method and background studies, the factors affecting information disclosure were identified with the approach of voluntary disclosure of non-financial information, then to The categories of identified factors were discussed. In order to determine the factors affecting the voluntary disclosure of information, the Delphi method has been used.The statistical population of the present study were accounting specialists and experts who are experts in accounting and auditing, who were 20 people (10 academic and 10 executive) and were selected as a snowball. The findings of the resource review section showed that 33 indicators were identified and finally the known concepts were categorized into five groups. The desired indicators were included in the Delphi questionnaire through the literature review while presenting to the experts after the initial content validity and 17 out of 20 people They confirmed the indicators and the validity percentage was 85%, so the validity of the model was confirmed through the Delphi method.The results show that in three groups; 1) Involuntary factors and voluntary disclosure of non-financial information; 2) specific discretionary factors of the company and voluntary disclosure of non-financial information; 3) Normative factors and voluntary disclosure of non-financial information, 25 indicators were confirmed.

In today's highly competitive world, web financial reporting plays an important role in creating simple solutions to identify and compare the business performance of businesses. The purpose of this study is to provide a comprehensive model for performing financial reporting on the web, taking into account different indicators, using the mathematical method. The method of this research is applied in terms of purpose and in terms of the type of implementation strategy, descriptive survey and statistical population of financial and accounting experts, which has been selected by judgment. In this study, by adopting the fuzzy Delphi method, for companies listed on the Tehran Stock Exchange, a web-based reporting model was proposed and indicators and effective factors for web-based reporting were identified and ranked. The instruments used in the research were a questionnaire and the components of the model were identified and confirmed using a multi-criteria decision model (Shannon entropy) as well as confirmatory factor analysis.Findings show that the proposed model for web financial reporting, which is designed based on eight organizational, financial, economic, social, political, human, technological and cultural indicators as the main indicators, with 62 factors, is appropriate and skewed. Has less than individual criteria.Providing a good model for web-based financial reporting in companies improves the efficiency, timeliness and honest representation of financial information, and facilitates data analysis.

The purpose of this research is to identify and prioritize supply chain risks based on a balanced scorecard and provide solutions for supply chain resilience. In order to identify supply chain risks, sources, articles and books in the field of supply chain and supply chain risk were reviewed and studied. And finally, a list of risks related to the supply chain was prepared. Then the risks in Tarabgin Company were categorized based on the five dimensions of the balanced scorecard. In this step, the FMEA method was used to score the risks. In the next step of the research, The prioritization of the dimensions of the balanced scorecard was based on the innovative method that was formed based on three indicators of FMEA, i.e. intensity, occurrence and diagnosis, and the multi-indicator decision-making method of AHP, and the ranking of the dimensions of the balanced scorecard was obtained, and then again from the three The FMEA index was used and this time with the help of the TOPSIS decision-making method, the risks that were placed in each category were ranked. Finally, in the last step, based on the risks, solutions and resilience strategies that were obtained from the study of the sources of this field, they were presented. To make the supply chain resilience of Tarabgin company possible. The obtained results show that the customer dimension has the highest priority and the growth and learning dimension has the lowest priority for Tarabgin Zob Ahan Isfahan Company.

The relationship between auditing mechanisms and financial reporting has been investigated quantitatively in different time periods and in numerous researches. But the evidence shows contradictory results of the effect of supervision and auditor's role on the quality of financial reporting. Based on this, the role of the auditor's supervision on the quality of financial reporting was examined from the perspective of divergence and convergence. The method used is the meta-analysis technique for the years 2006 to 2019. The collection of researches is using the website of the Ministry of Science. Finally, eighteen studies were selected according to the availability of information and having the conditions of the investigated variables to implement the meta-analysis technique. The meta-analysis evidence showed that regardless of the contradictory evidence of the effect of internal and external audits of the auditor on the quality of financial reporting, the characteristics of the audit committee, the characteristics of independent auditors, and the characteristics of internal auditors have a positive and significant effect on the quality of financial reporting. Also, the corporate governance system has a moderating role on the relationship between the types of audits and the quality of financial reporting. Based on this, the present study, using the meta-analysis technique, has investigated the contradictions in empirical researches related to the divergence and convergence of auditor supervision and the quality of financial reporting.

Today, the shopping center is no longer a place for transaction purposes where customers go to if they need a product or service, but it is a place for social purposes. Shoppers may become confused if they perceive a social environment as too stimulating or inappropriate. The aim of the current research is to combine interpretive structural modeling and machine learning to stratify factors affecting customer confusion in choosing a retail store. In order to select the features that are most related to the target variables and can provide the best performance in predicting and interpreting the model, feature selection using a neural network has been used. The proposed approach initially reduces the computational complexity in solving the design problem by reducing the dimensions of the problem space through the training of a type of multilayer neural networks. 7 factors affecting customer confusion were extracted based on this neural network model, classified in 5 levels using interpretative structural modeling, and the related model was drawn. In this category, the variables of a wide variety of store brands, loyalty programs and the concentration of stores in one location, the greatest power of influence (influence) and perceived risk, individual and demographic factors and the volume of information show the most dependence (influence) and the variable of the commodity factor is the only It is a variable that has a two-way relationship with other variables.