درخت حوزه‌های تخصصی

The main purpose of this research is to identify and analyze the effective factors of establishing a knowledge-based city in less developed areas. The research method is mixed (qualitative-quantitative). To carry out this research, in addition to studying documents, the ground theory method with MAXQDA12 software was used to identify the effective factors. The statistical population in this research was all experts in the field of public management, urban management, economics, managers of knowledge-based companies, and managers of Sistan and Baluchestan governorate and Zahedan municipality, which was conducted after conducting 17 theoretical saturation interviews. Finally, open, central, and selective codes were extracted and in the quantitative part, Dematal technique was used to determine the effectiveness of the effective dimensions on the establishment of a knowledge-based city. According to the semi-structured interviews, 6 dimensions (cause, main phenomenon, contextual, interveners, strategies, consequences) and 15 components (core codes), and 69 indicators (open code) were extracted for the establishment of the knowledge-based city. The Finding showed that dimensions of development, skill and expertise, education and technology, infrastructure, internationalization, institutional factor, urban knowledge development, knowledge management, foreign policies, laws and regulations, cultural-native, knowledge-based city development, policies, domestic, cultural conflict, and urban geography, in order from high impact to low impact, as well as dimensions of urban geography, cultural conflict, internal policies, knowledge-based city development, cultural-native, laws and regulations, foreign policies, knowledge management, knowledge development urban, institutional factor, internationalization, infrastructural, education and technology, skill and expertise and development are respectively from high effectiveness to low effectiveness.

Purpose: One of the debates that has received much attention by many researchers in recent years and provided a platform to examine its various fields is customer experience management. Companies can differentiate themselves from competitors, create greater customer loyalty, and provide stronger brand relations via the experiences provided to their customers. The present study is aimed to identify the changes and progress made in customer experience management. Methodology: For this purpose, the papers available in the Web of Science database were analyzed over a period of 24 years (1998 to 2022) using scientometric methods. Findings: The results of the study present a comprehensive review of the field of customer experience management by identifying its basics, provide influential works and intellectual link between the works. It is noteworthy that the present analysis reveals more cited articles, key authors, keywords, intellectual turning points, and emerging research trends in this field. Conclusion: These results help researchers to perceive the boundaries of the researches conducted in customer experience management and gain valuable scientific information through which they can determine the development process of their future studies.

The current article examines the trends and performance of research on the types of effects of the COVID-19 epidemic and the different management strategies of perishable goods supply chain disruptions during 2 years (2020-2022) using bibliometric and network analysis based on the data set from the Scopus database using VOSviewer software. The analysis designates that Kumar A. has been the most influential author in perishable goods supply chain research during the COVID-19 pandemic, and India has contributed the most in this field. The most repeated keywords were resilience, food supply, and perishable food supply chain. Citation analysis indicated that resilience and sustainability are the mainstream of research in articles with high citations. The network analysis also disclosed that resilience and sustainability are the key themes in the clusters. Furthermore, strategies for managing disruption during the COVID-19 pandemic were extracted from the highly-cited articles, which are presented in this article.

This study investigates the effects of stock anomalies on excess stock and unexplained returns of multifactorial models in the companies listed at the Tehran Stock Exchange. We selected a sample of 120 companies listed at the Tehran Stock Exchange from 2008 to 2019 using the Fama-Macbeth [18] regression approach. The results revealed that stock anomalies led to considerable differences in excess stock returns of different portfolios, implying that stock returns at different anomaly levels significantly differ. In addition, it was found that the anomalies related to stock characteristics greatly impacted explaining excess stock returns in the three-factor and five-factor models suggested by Fama and French. Besides, in different portfolios of the anomalies, the unexplained return rates were significantly different from each other. Moreover, in Fama and French's three-factor and five-factor models, different anomaly portfolios show significant differences in explaining excess stock returns.

Evaluating the performance of countries in international markets and measuring how they utilize allocated resources provides a lucid picture of the state of business management in countries also assessing performance sustainability in international markets, is one of the important issues in predicting international trade. In international markets knowledge of countries' performance leads to the recognition of their economic and non-economic management statuses even more it is used to allocate financial support of global organization. In the present article, an attempt was made to design a model capable of examining the performance of nations in international markets by both economic and non-economic dimensions in the presence of undesirable factors and two preparation and exploitation stages of existing platforms and also assessing the sustainability of countries' performance in the studied period which is quite innovative. Then, data from 21 countries, from 2010 to 2017 were evaluated to test the model. The results indicated that the model is capable of examining the performance of countries and assess the sustainability of the countries over a period of time. According to the results of this model, an attempt was made to evaluate Iran's performance status among homogeneous countries and provide a roadmap for enhancing Iran's performance

This paper sought to address the feasibility of dissecting stock price momentum in the firms listed in Tehran Stock Exchange using financial statement analysis (FSA). Different variables including those related to profitability, financial leverage and liquidity, and operating efficiency were used in this analysis. The study sample consisted of 130 firms listed in Tehran Stock Exchange over the period 2008-2019. The results showed that fundamental factors affected stock price momentum for one year in the winning portfolio and for two years in the losing one; after this period, financial information did not have a significant effect on stock price momentum. Therefore, stock price momentum performance is a function of the conformance of the past price performance to fundamentals. The results from investment strategies based on the past price performance-fundamentals conformance indicated that fundamentals cause a significant difference in stock excess returns in winning and losing portfolios.

Traditional approaches applied in supply chain management consider only the physical logistic operations and ignore the financial aspects of the chain. In this study, a mathematical model has been developed to address the supply chain network design problem with a value-based management approach. This model integrates both operations and financial aspects to maximize the value created and measured by shareholder value analysis (SVA) as an objective function. The results attributed to the developed model and the basic model are compared. The results indicate that creating more value for the company and its shareholders is achievable with appropriate financial decisions. To validate and show the applicability of the proposed model, it was solved by GAMS software with data provided by literature. Finally, sensitivity analyses on financial parameters were performed to evaluate the results. The results clearly reveal the improvement of using the new approach and convince managers to take advantage of the proposed approach.

The present study is aimed to present a model of earnings transparency with an artificial intelligence approach in companies listed on the Tehran Stock Exchange (TSE). For this purpose, the data of 167 companies during the years 2011 to 2018 were used to test the research hypotheses. Variable selection test performed using Lasso's artificial intelligence algorithm showed that among the criteria of the audit committee's independence management system, the non-executive managers ratio, gender diversity and among the performance criteria, the ratio of cash holding in the company, operating profit margin and accounts receivable ratio had the highest effect to explain the earnings transparency of companies and also to predict the earnings transparency of the companies in the next year, the LARS algorithm method was used. The results of prediction showed the high power of Lars artificial intelligence algorithm to predict the earnings transparency of the companies listed on Tse. Keywords: Earnings Transparency, Corporate governance and performance criteria, Artificial Intelligence Approach

Due to overlap between stock markets and financial markets, this study was an attempt to examine the herding behavior in the Iranian stock market and the crude oil, foreign exchange and gold markets. For this purpose, in this research, monthly data between 2011 and 2020 for Tehran Stock Foreign exchange were used. The results of the study based on two criteria explaining herding behavior indicate the existence of herding behavior of the stock market and crude oil, gold and foreign exchange markets. The results also show that it has had different ef-fects on herding behavior in different periods. This issue has also been different in increasing and decreasing market periods. Therefore, gold is introduced as an important asset that influences herding behavior. Also, during the decreasing period of the stock market, herding behavior is not affected by the exchange and crude oil market, and in this period, the behavior of investors and investment risks in the stock market can be predicted without considering the exchange and crude oil market.

Auditors' personality traits have a significant effect on the motivation of their financial behavior. In fact, the personal and personality traits of auditors that can be influenced by the environment play an important role in motivating individuals to engage in financially professional behaviors. Audit team norms are one of the factors in the audit firm environment that affect the auditor's behavior. In this study, the effect of auditing team norms and auditors' personality types on auditor objectivity was investigated. The Entropy technique is used to examine the importance of the norms of the audit team and the personality components of the peers, and based on the results and using the TOPSIS method, these factors affecting the objectivity of financial auditors are ranked. The statistical population of this study includes all professional auditors working in the auditing organization and private auditing institutions, members of the Iranian Society of Certified Public Accountants in 2020, including 242 members. The results showed that extroverted and responsible personality types have a positive and significant effect on auditors' objectivity. The results also showed that the norms of the audit team have a positive and significant effect on the objectivity of auditors.

The purpose of the study is to develop and test an analytical model for resilience assessment of supply chain risks against the risks of system and its individual tiers. In this regard a multi-method research approach is adopted as follows: By using data envelopment analysis (DEA) and fuzzy set theory, a fuzzy network DEA model has been proposed to assess risk in overall supply chains and their individual tiers. The proposed model is tested by surveying of 130 people as selective petrochemical companies in Iran. The survey results show a substantial variation in resilience ratings between the overall petrochemical supply chains and their individual tiers. The research findings indicate that system resilience is not necessarily indicative of the resilience of its individual tiers. On the other hand, high efficiency scores in supply chain tiers have limited influence on overall resilience of supply chain. The proposed analytical model enables the assessment of supply chain flexibility at different levels for a wide range of supply chain risks in upstream, downstream and downstream process-es.

مدیران همواره در تلاشند که در راستای اهداف خاصی که دنبال می کنند، مبلغ سود گزارش شده را دستکاری نمایند. مسئله اصلی در رابطه با این مطلب، این است که چرا مدیران به دنبال دستکاری سود هستند، چگونه سود را مدیریت می کنند و پیامد های این گونه رفتار چیست ؟ رفتار نامتقارن هزینه ها باعث می شود که مدیران شرکت ها در مواقع لزوم برای کاهش ضرر و زیان هایشان دست به مدیریت سود بزنند که با این کار از رفتار نامتقارن هزینه جلوگیری می شود . مدیران یک شرکت اغلب مسائلی نظیر برنامه ریزی و کنترل در شرکت های تجاری روبرو هستند. در مرحله برنامه ریزی مدیران به اطلاعات مربوط به گرایش هزینه ها جهت پیش بینی هزینه های آتی نیاز دارند. هدف از انجام این مطالعه بررسی تأثیر توانایی مدیران بر رابطه بین مدیریت سود و چسبندگی هزینه می باشد. بدین منظور اطلاعات مربوط به 137 شرکت پذیرفته شده در بورس تهران در بازه زمانی 1396-1400 جمع آوری گردید. پس از انجام آزمون های آماری و انتخاب روش اثرات ثابت مدل به علت وجود مشکل ناهمسانی واریانس با روش GLS برآورد گردید. نتایج نشان می دهند که مدیریت سود رابطه مثبت و معناداری با چسبندگی هزینه داشته و توانایی مدیریت این ارتباط را تضعیف می کند.