Audit task Complexity, as one of the important and effective factors on the auditors' judgment and decision-making, is one of the controversial concepts in the audit field, which, due to its multidimensional nature, has led to many researches in the audit field. Despite the provision of individual indicators to measure audit task Complexity in these studies, explaining a multidimensional model to measure of this fundamental concept in auditing is a problem that requires to research. It is expected that the explanation of such an index can lead to a better understanding of this concept and its dimensions and help auditors in planning audit task as well as ways to increase the quality of judgment and decision making. Accordingly, the current research purpose is to explain a model to measure for audit task Complexity concept. For this purpose, information related to 128 companies in Tehran Stock Exchange during 2010-2019 was collected and tested through Partial Least Squares Structural Equation Modeling. Findings based on Constructive-Constructive measurement model and second-order Confirmatory Factor analysis showed that twenty-one factors effect on audit task Complexity. Also, the results showed that audit task Complexity is influenced by three dimensions of input, processing and output Complexity. These findings, in addition to explaining the concept of audit task Complexity, have helped to understand the effective factors and dimensions of this concept and can be useful in auditor's tasks planning and policy making and provide a more powerful tool to increase audit judgment quality.

Hegemonic wars have transformed their essence due to systemic changes. The concept of Structural Complexity has been utilized as a theoretical framework for research to explain the new patterns of hegemonic warfare. Structural Complexity includes principles such as emergent properties, nonlinear dynamics, adaptation, downward causality, network diffusion, non-equilibrium order, and self-regulatory mechanism. In the present study, the question was addressed as what the effects of Structural Complexity are on new patterns of hegemonic warfare in the modern international system. This research method consisted of two steps; in the first step, a theoretical and analytical model of Structural Complexity based on deductive inference was presented; in the second step, the time series analysis method was used to examine the historical trend of hegemonic wars as experimental data. According to the hypothesis of this research, the situation of Structural Complexity in the international system has caused profound changes in an important variable such as international order. The intellectual hegemony of the United States with the dimensions of productive, institutional, Structural, and compulsory power in the war against the networks of civilization and identity is challenging in Russia, Iran, and China. Hence, hegemonic wars occur in the discourse, military, economic, and technological dimensions.

One of the most important goals of the ecological management of forests is to enhance the Complexity of the structure of the forest stands. Also, despite the recommendation to increase mixing, the consequence of the presence of rare tree species on the forest ecosystem functions has not been well clarified. This research was conducted to analyze the presence and abundance of rare tree species on the Structural Complexity index in beech stands. the number of 12 one-hectare study areas with the presence of rare tree species was selected and after measuring the Structural features, the multivariate Complexity index was determined in each of the plots. We employed ten variables including stem per hectare, mean diameter at breast height, coefficient of variation of dbh, diameter Gini coefficient, number of trees with a diameter larger than 100 cm at breast height, the ratio of the number of trees in different stories, the faction of canopy gaps, amount and volume of dead woods and tree size variation to the calculation of this index. Comparing the correlation between the relative importance value of beech, Maple, and other rare tree species with the Structural Complexity index revealed the differences in Complexity variation toward the rising in the abundance of tree species. Accordingly, beech and hornbeam, as the two dominant tree species with the highest relative value, are weakly correlated with this index. While the maple and other rare tree species including alder, elm, and lime positively correlated with increasing Complexity in the structure. According to the positive effect of the presence of rare tree species on the Complexity of the structure of forest stands, it is recommended to the retention of rare tree species in stands to increase the Complexity of the forest stands structure.

Rapid environmental changes and rapid technological advancements, along with wider communication and large volumes of information, have made organizations more complex than ever, and their management has become much more difficult. The purpose of this paper was to identify the most important types of organizational Complexity in the first stage and, secondly, to determine the ranking of organizations based on the Complexity of the three types of service, agriculture, and industry organiztions. The present study in terms of research methodology is quantitative and to analyze data the hierarchical analysis process (AHP) method has been used. The statistical population consists of 16 academic experts that also work at industry, service, or agriculture field. The results showed that the most important complexities in order of importance include: Environmental Complexity (491/0), Structural Complexity (201/0), Technological Complexity (169/0) and information Complexity (140/0). Also, the results showed that the most complex organizations are as follows: industrial organizations (421/0), service organizations (348/0) and agricultural organizations (231/0).

As one of the main challenges of the 21st century supply chain, Complexity has become a crisis, costly, and difficult for many supply chain managers. However, few studies have prioritized this strategy. This study aimed to investigate the effect of supply chain Complexity on competitiveness performance in the Iran Khodro Company. To achieve this goal, the relationship between different sources of Complexity (upstream Complexity, domestic production, and downstream Complexity) and competitiveness performance is examined using a conceptual model. The statistical population of this study included all Iran Khodro experts, whose number reached 218 in 2022. Owing to the limitations of the statistical community, all members were selected as a sample. The collection tools for this study included two standard questionnaires: the supply chain and Porter's competitiveness performance. The content validity of the questionnaires was confirmed by experts, its construct validity was confirmed by confirmatory factor analysis, and the reliability of the questionnaires was confirmed using Cronbach's alpha coefficient and the combined reliability index. The collected data were analyzed using the Structural equations in the LISREL software. The results of hypothesis testing show that, in general, supply chain Complexity has a significant inverse effect on competitiveness performance.

Extensive progress in supply chain management operations and logistics research has led to the changing nature of the competition in modern businesses. In the supply chain process, the performance of supply chain management is an important and key factor for the acquisition of competitive advantage. The purpose of this paper is to use a Structural approach-Complexity interpretation of supply chain and its role in competitiveness in automotive industry in the automotive industry. This paper is in terms of development goal, which by using the combined method, in two stages, including identification of indicators by thematic analysis method and its test was conducted using a correlational survey. The statistical population of the paper in the quality phase of the managers of Iran Khodro Company of Khuzestan province and professors and in the quantitative phase of managers, employees and staff of Iran Khodro Company of Khuzestan Province is a small part of the formation of a Structural self-interactive matrix to follow Structural and interpretive modeling. The sample size in the qualitative phase was determined by the method of judgement. The results showed that 3 main indices and 15 sub-indexes were identified as the main model factors.

Competition law is a newcomer to the legal system recently. A sound understanding of competition policy can provide us with sufficient bases to apply a fundamental and normative view of the issues of competition law. The difference in supervision and regulation determines how the market functions and in order to understand this difference one must understand competition policy. Competition policy may be based on governmental support for national production and industry or on a non-interventional and regulatory posture. Moreover, supervision, based on the principle of non-intervention in the market mechanism, is rooted in liberal ideas; however, regulation, whether as a rule or an exception, is based on the assertion that the market has been ineffective in attaining its goals. Therefore, the government will resort to interventions to regulate inefficiencies.  This paper aims to analyze Supervisory Authority in Implementing Competitive Policy by employing the description method. In this article the author tries to first delineate competition policy, its related requirements and imposed deviations to the market. Then, by defining the supervisory entity and clarifying its distinction from the regulatory institutions, the author considers the characteristics of an appropriate supervisory entity conducting a comparative study of this issue in Iran and the U.S.A. This form of Competition policy because of its applicable experiences which have been well described by recent scholarship is considered suitable for the native system.

Task features and learner variables are believed to play an important role in language outcome. Thus, the present factorial between-subject study set out to determine the main and interaction effects of task manipulation in terms of intentional reasoning and planning time and learner variables with regard to language learning aptitude on Iranian intermediate learners’ written performance in letter writing tasks. Lexical and syntactical Complexity and also accuracy were the linguistic elements measured as dependent variables in the writers’ performance. First, the participants were randomly divided into three experimental groups; each group included 70, 76, 80 participants respectively. Then, they were assigned to planning and no-planning groups within each experimental group, and there were the same number of high-aptitude and low-aptitude participants in each planning group. Three letter writing tasks with different degrees of reasoning demands (low, medium, high) were designed, and each experimental group received one of these tasks. The ones in planning groups were also given 10 extra minutes for planning before performing the tasks. The findings of MANOVA test indicated that a) providing planning time resulted in higher syntactical Complexity; b) increasing reasoning demands positively affected lexical and syntactical Complexity; c) planning time and reasoning demands interactively affected accuracy; and d) a three-way interaction effect among task features and learner variable was observed only on accuracy. The results shed some light on how external manipulated task features and internal learner variables can work together to improve task performance.

The paper aims at developing a model for improving service productivity in public organizations based on the service Complexity approach. This is an applied, descriptive qualitative and, quantitative paper. The population in the qualitative section (grounded theory) includes 16 experts in the field of productivity in the university and managers of government organizations in Tehran province who were selected by theoretical sampling method as a method of targeted sampling. The statistical population in the Structural equations section includes three categories: 1) Managers and experts of government service organizations; 2) Experts and deputies of government service organizations and, 3) Consultants and experts of government service organizations. In this section, we used multi-stage relative stratified sampling, which according to Cochran's formula, a total of 384 samples acceptable. Thus, the questionnaires were randomly distributed in each of the five regions of the country and, the data from 390 questionnaires were completed through the data analysis algorithm in PLS software. Having analyzed the interviews based on the grounded theory method and in NVivo Plus 2020 software and by open coding, we obtained 143 items as basic concepts from the text of the interviews, which were classified into 31 sub-indices and 11 main indices and five dimensions. Then, we validated and approved the results of the qualitative section through the data analysis algorithm in the PLS software. Given the research findings, we presented and fitted the model of improving service productivity in public organizations based on service Complexity in a paradigm model.