دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 12 2 2024 06 21 Factors Affecting the Dividend Policy of Companies: A Meta-analysis Approach عوامل موثر بر سیاست تقسیم سود شرکت‌ها: رویکرد فراتحلیل 1 16 28315 10.22108/amf.2024.138433.1809 FA یلدا حسنی کارشناس ارشد، گروه مدیریت بازرگانی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران باقر عسگرنژاد نوری دانشیار، گروه مدیریت بازرگانی، دانشکده اقتصاد و مدیریت، دانشگاه ارومیه، ارومیه، ایران قاسم زارعی دانشیار، گروه مدیریت بازرگانی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران الله یار بیگی فیروزی استادیار گروه مدیریت بازرگانی، دانشکده مدیریت و حسابداری، دانشگاه پیام نور، ایران Journal Article 2023 07 18 A dividend is considered to represent the company's financial commitment to shareholders to pay a part of their investment returns, which requires the use of appropriate policies and the identification of factors affecting it in order to manage future cash flows for the company. Various studies have been conducted that have introduced various factors affecting the dividend policy, such as capital structure, agency cost, accounting reporting, and the effective tax rate, but the results have been contradictory and scattered. For this purpose, conducting comprehensive research with a meta-analysis approach regarding determining the importance of each of the effective factors on the dividend policy in order to achieve a general summary and resolve the contradictions and dispersion of the results seems necessary. To review the previous research, first, the desired variables were determined, and then the necessary information was collected for 196 studies until 2021. Based on systematic elimination sampling, the number of remaining studies that had the necessary characteristics to enter the meta-analysis process was equal to 123 studies. We coded and entered the extracted data into CMA2 statistical software. The effect size was calculated, and the homogeneity and heterogeneity of the effect size were evaluated. The results of this study showed that the factors of corporate governance mechanism and agency cost did not affect the company's dividend policy. However, the positive effect of free cash flow factors, profitability ratios, quality of financial reporting, effective tax rate, capital structure, institutional investors, information asymmetry, ability of managers, and concentration of ownership in dividend policy was confirmed. اهداف: تقسیم سود نشان‌دهندۀ تعهد مالی شرکت به سهامداران برای پرداخت بخشی از بازده سرمایه گذاری آنها محسوب می‌شود. چنین موضوعی به به‌کارگیری سیاست‌های مناسب و شناسایی عوامل موثر بر آن برای مدیریت وجوه نقدی آتی ورودی به شرکت نیازمند است. پژوهشگران دانش مالی ‍پژوهش‌های گوناگونی انجام داده و عوامل مختلف موثر بر سیاست تقسیم سود را معرفی کرده اند. برخی از این عوامل عبارت اند از ساختار سرمایه، هزینه نمایندگی، گزارشگری حسابداری، نرخ موثر مالیاتی؛ اما نتایج تناقض و پراکندگی داشته است. روش: انجام یک پژوهش جامع و فراگیر با رویکرد فرا تحلیلی دربارۀ تعیین اهمیت هر یک از عوامل موثر برسیاست تقسیم سود برای دست یابی به جمع ‌بندی کلی و رفع تناقض ها و پراکندگی نتایج ضروری به نظر می رسد. برای بررسی پژوهش های پیشین ابتدا متغیرهای مدنظر تعیین و سپس اطلاعات لازم برای 196 پژوهش تا سال 2021 گردآوری شد. بر اساس نمونه‌گیری به روش حذف سیستماتیک، تعداد پژوهش‌های باقیمانده که ویژگی‌های لازم برای ورود در فرآیند فراتحلیل دارند، برابر با 123 مقاله به دست آمد. داده‌های استخراج شده کد بندی شده و در نرم‌افزار آماری CMA2 وارد شد. محاسبه اندازۀ اثر و ارزیابی همگنی و ناهمگنی موجود در اندازۀ اثر صورت گرفت. نتایج: نتایج نشان می دهد که عوامل ساز و کار راهبری شرکتی و هزینۀ نمایندگی در سیاست تقسیم سود شرکت‌ها تأثیر نداشته است؛ اما تأثیر مثبت عوامل جریان نقدی آزاد، نسبت‌های سودآوری، کیفیت گزارشگری مالی، نرخ مؤثر مالیاتی، ساختار سرمایه، سرمایه‌گذاران نهادی، عدم تقارن اطلاعاتی، توانایی مدیران و تمرکز مالکیت در سیاست تقسیم سود تأیید شد.

https://amf.ui.ac.ir/article_28315_8890dcc66c7d386addf6ec78d8614c9f.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 12 2 2024 06 21 Impact of Financial Literacy on Saving Decisions: Insight from Aseman Project Operated by Barkat Foundation تأثیر سواد مالی بر تصمیمات پس‌اندازی ) بررسی تجربۀ طرح آسمان بنیاد برکت) 17 38 28509 10.22108/amf.2024.138869.1817 FA وحید مقدم استادیار، گروه معارف اهل البیت، دانشکدۀ الهیات و معارف اهل بیت، دانشگاه اصفهان، اصفهان، ایران هادی امیری دانشیار، گروه اقتصاد ، دانشکدۀ علوم اداری و اقتصاد، دانشگاه اصفهان، اصفهان، ایران سحر بهاری پور دانشجوی دکتری، گروه اقتصاد، دانشکده علوم اداری و اقتصاد، دانشگاه اصفهان، اصفهان، ایران فاطمه باقری دانشجوی دکتری، گروه اقتصاد، دانشکده علوم اداری و اقتصاد، دانشگاه اصفهان، اصفهان، ایران پریسا قاسمیان دانش آموخته کارشناسی ارشد، گروه اقتصاد، دانشکده علوم اداری و اقتصاد، دانشگاه اصفهان، اصفهان، ایران Journal Article 2023 08 27 This study investigated the impact of financial education on the saving decisions of members in the microfinance funds of Aseman Project operated by Barkat Foundation. Specifically, it examined how fund membership affects individuals' financial knowledge and attitudes and how these in turn influence the quality of their saving behaviors. The research data were collected through structured interviews and analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique. The findings indicated that financial knowledge had a significant positive effect on saving attitudes and behaviors. Membership in the microfinance funds was found to positively influence the participants' levels of financial knowledge and attitudes, but did not have a direct significant effect on their saving behaviors. This suggested the training provided by the microfinance institution impacted knowledge and attitudes, but did not lead to visible changes in saving behaviors and, consequently, poverty alleviation. While financial literacy is typically viewed as formal training provided to individuals, this study highlighted how membership in financial support programs could also shape financial knowledge and decision-making. This often overlooked pathway deserves greater attention in financial education research and practice. Keywords: Microfinance, Financial Literacy, Saving Decision-Making, Structural Equations, Propensity Score. Introduction One of the key debates around poverty alleviation centers on the "poverty trap" - the idea that increasing the incomes of the poor is essential for helping them escape this cycle (Easterly, 2006). Some believe that global aid can effectively lift people out of poverty, allowing them to solve their own problems (Sachs, 2005; Banerjee & Duflo, 2011). Others argue that such aid can create a culture of dependency, actually making the poor poorer and preventing assistance from reaching the right channels (Biglaiser & McGauvran, 2022; Banerjee & Duflo, 2011). Microfinance, which aims to provide sustainable access to financial resources rather than direct spending, has not yielded significant evidence of helping the poor escape the poverty trap (Adams et al., 1984; Bateman, 2010; Morduch, 2000; Banerjee et al., 2015). This may be partly due to the poor making suboptimal financial decisions in using the received funds - a problem often attributed to their low levels of financial knowledge (Wise, 2013). The lack of financial literacy among the poor underscores the need for financial education (Kaiser et al, 2022). Improving the quality of saving decisions is also considered crucial for empowerment and self-sufficiency (Rink & Barros, 2021). In other words, financial knowledge can enable better management of limited financial resources (Atlas et al., 2019). This study tested the hypothesis that the financial education provided through Aseman project operated by the microfinance institution of Barkat Foundation had increased the financial literacy of its members. Materials & Methods The study sample consisted of 113 individuals aged 18 years and above selected from 4 villages (Sohrofiroozan, Tad, Ardal, and Bajgerd) that were part of Aseman Project's microfinance fund member population of 185 people. Data were collected through semi-structured interviews and observations using a questionnaire as the primary data collection tool. The questionnaire was designed based on previous financial literacy research (Hogarth & Hilgert, 2002; Lusardi & Mitchell, 2011; Mandell, 2008; OECD, 2013) and consisted of two main parts. The first part measured financial knowledge using the core OECD financial literacy questionnaire (OECD, 2013). The reliability and validity of the variables (financial knowledge, saving attitude, and saving behavior) were assessed using Cronbach's alpha, Fornell and Larcker's method, and the SmartPLS2 software. The results showed Cronbach's alpha and composite reliability values above 0.7 for all variables, thus indicating acceptable reliability. To evaluate the impact of Aseman Project, the study examined the effect of microfinance fund membership on the dependent variables of financial knowledge, saving attitude, and saving behavior. One crucial step in policy evaluation is to ensure comparability between treatment and control groups. The Propensity Score Matching (PSM) method was used to achieve this with the PS match command in Stata software applied to compare outcomes between the two groups. Findings The results showed that the index of saving attitude had an R-squared value of 0.95 for the dependent variable of saving behavior, indicating that the model explained a significant proportion (95%) of the variance in saving behavior. The Q-squared index, which measured the model's predictive power, had a value of 0.19 for the variable of saving attitude, suggesting moderate predictive power. For the variable of saving behavior, the Q-squared value was a strong value of 0.41. The path coefficients and significance levels revealed several key relationships: 1) Saving knowledge had a significant positive effect on saving attitude with a path coefficient of 0.53 (p<0.05). A one-standard-deviation increase in saving knowledge led to a standard deviation increase of 0.53 in saving attitude, 2) Saving knowledge also had a significant positive effect on saving behavior with a path coefficient of 0.26 (p<0.05). A one-standard-deviation increase in saving knowledge led to a standard deviation increase of 0.26 in saving behavior, and 3) Saving attitude had a significant positive effect on saving behavior with a path coefficient of 8.01 (p<0.05). A one-standard-deviation increase in saving attitude led to a standard deviation increase of 8.01 in saving behavior. The propensity score matching analysis revealed a positive and statistically significant effect of microfinance fund membership of Aseman Plan on saving knowledge. Specifically, the estimated treatment effect was 0.25, which was significant at the 5% level (t =1.96). These findings supported the first hypothesis, indicating that fund membership increased the participants' saving knowledge. Similarly, the analysis found a positive and significant treatment effect of 0.38 (t-statistic=2.26) on saving attitude at the 5% probability level. This result provided support for the second hypothesis, demonstrating that membership in Aseman microfinance funds enhanced the participants' saving attitudes. In contrast, the estimated treatment effect on saving behavior was positive (0.17) but not statistically different from zero. Consequently, the third hypothesis, which anticipated a significant effect of fund membership on saving behavior, had to be rejected based on the empirical evidence. Discussion & Conclusion The findings indicated that membership in the microfinance funds of Aseman Plan, which represented a form of saving-related decision making, had a positive impact on both saving knowledge and saving attitude among members. This supported the first two hypotheses of the study. Specifically, the results confirmed the relationships between saving knowledge and saving attitude, as well as saving attitude and saving behavior. Membership in the microfinance funds of Aseman Plan was found to significantly improve the levels of saving attitude and saving knowledge for members compared to non-members. However, the analysis did not detect a significant effect of fund membership on actual saving behavior. This suggested that while the program had been successful in enhancing financial literacy and positive saving-related mindsets, it had not yet translated into tangible changes in saving practices and outcomes. Despite the lack of a direct impact on saving behavior, the findings indicated that Aseman Plan had ancillary benefits in terms of improving financial knowledge and attitudes among participants. This "side effect" of increased financial literacy could potentially have long-term, intergenerational impacts that went beyond the immediate poverty alleviation objectives of the microfinance program. One limitation of the study was challenges in accessing and communicating with fund officials and members to conduct interviews. Future research should explore these intergenerational effects and seek to understand how the quality and quantity of financial education provided to members can be enhanced to better translate into improved saving behaviors. The key practical implication is that policymakers and program administrators should place greater emphasis on the quality and delivery of financial literacy training within microfinance initiatives. Strengthening this educational component may be crucial for maximizing the downstream impacts on actual saving outcomes and financial well-being. اهداف: هدف ارائۀ پیشنهاداتی جهت بهبود تأثیرگذاری عضویت در صندوق‌های تأمین مالی خرد ازطریق افزایش سواد مالی اعضا است. روش: داده‌های پژوهش از نتایج مصاحبه‌های ساختاریافتۀ انجام‌شده براساس پرسشنامۀ OECD و بومی‌سازی این پرسش‌نامه طبق نظر متخصصان جمع‌آوری شد. موضوعاتی که در علوم رفتاری و اجتماعی دنبال می‌شود، ماهیت چندمتغیری دارد؛ ازاین‌رو، از روش معادلات ساختاری به روش حداقل مربعات جزئی (PLS-SEM) استفاده شده است. نوآوری: سواد مالی معمولاً آموزش صریح به فرد در نظر گرفته می‌شود، اما عضویت افراد در صندوق‌ها نیز می‌تواند بر آن تأثیر داشته باشد و کیفیت تصمیم‌گیری‌های پس‌انداز را بهبود بخشد. در مطالعات انجام‌شده به این جنبه کمتر توجه شده است. نتایج: طبق یافته‌های پژوهش، دانش پس‌اندازی بر نگرش و رفتار پس‌اندازی معنادار و نگرش نیز بر رفتار پس‌اندازی تأثیر مثبت داشته ‌است. به‌علاوه، عضویت در صندوق‌ها تأثیر مثبتی بر سطح دانش و نگرش پس‌اندازی افراد داشته،‌ اما تأثیر آن بر بُعد رفتاری پس‌انداز معنادار نبوده ‌است؛ درنتیجه، آموزش‌های ارائه‌شده ازسوی مؤسسات مالی خرد بر دانش و نگرش اعضا تأثیرگذار بوده، ولی قادر به ایجاد تغییرات مشهود در رفتار آن‌ها و درنتیجه، فقرزدایی نبوده است.

https://amf.ui.ac.ir/article_28509_bc38a27ea5b91f683154dd269ae8aa46.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 12 2 2024 06 21 Development of a comprehensive model to predict stock prices in the stock market with an interpretive structural modeling approach توسعه مدلی جامع جهت پیش بینی قیمت سهام در بازار بورس اوراق بهادار با رویکرد مدلسازی ساختاری تفسیری 39 58 28419 10.22108/amf.2024.138983.1821 FA شیوا رضاییان دانشجوی دکتری، گروه مدیریت صنعتی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران محمد طالقانی دانشیار، گروه مدیریت صنعتی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران آزیتا شرج شریفی استادیار، گروه حسابداری، واحد نوشهر، دانشگاه آزاد اسلامی، نوشهر، ایران Journal Article 2023 09 01 The aim of this study was to develop a comprehensive model for stock price forecasting in the Tehran Stock Exchange (TSE) using a mixed Delphi-fuzzy approach of Interpretive Structural Modeling (ISM). The model incorporated technical, fundamental, macroeconomic, and emotional factors. In this study, the fuzzy Delphi method was employed to identify key criteria from the investor’s perspective among the 54 stock price prediction criteria extracted from the existing literature. Subsequently, the interpretive structural modeling method was utilized to examine the relationships between these criteria and establish a hierarchical model. The findings of the ISM revealed that the price per share and the money flow index held significant positions at the bottom of the hierarchy and exerted a strong driving force. Among the criteria occupying lower positions in the hierarchy, the exchange rate and the power indicator relative and exponential moving averages were identified as the most influential indicators. Keywords: Stock Market, Prediction Model, Fuzzy-Delphi Approach, Interpretive Structural Modeling (ISM) Introduction Stock markets play a crucial role in promoting economic growth by efficiently allocating resources and generating liquidity, particularly in urbanized smart cities. Stock market analysis encompasses both technical and fundamental approaches. Technical analysis relies on historical stock price data and technical indicators, making it particularly useful for short-term forecasts and trading strategies. On the other hand, fundamental analysis is based on the information about companies and the broader economy, focusing more on long-term forecasts and investment strategies (Latif et al., 2024). Combining technical and fundamental analysis can enhance long-term predictions. Empirical analysis of stock markets presents significant challenges. Multiple factors, such as market dynamics, industry trends, company performance, economic conditions, political events, and globalization, exert influence on stock markets. These factors are intricately interconnected, rendering the prediction of stock market behavior a complex task (Yang et al., 2020). Therefore, the primary objective of this research was to develop a framework for forecasting stock prices in the Tehran Stock Exchange (TSE) market. The proposed approach integrated a mixed Delphi-fuzzy methodology with Interpretive Structural Modeling (ISM), incorporating technical, fundamental, macroeconomic, and emotional factors into the analysis. Materials and Methods The sample consisted of two groups: investors and academic experts. The investors, who engaged in the stock market prediction and investment by analyzing technical, fundamental, and macroeconomic indicators, possessed a deep understanding of financial indicators. Due to their expertise in the field, they were considered as expert investors. To begin, a questionnaire comprising 54 initial criteria related to stock price prediction was distributed to the experts. The experts were asked to rate the importance of each criterion on a Likert scale ranging from very low (1) to very high (5). After consolidating the responses, 15 criteria were selected as significant for predicting stock prices in the stock exchange. Subsequently, a questionnaire was designed to explore the relationships between the key criteria identified. This questionnaire was administered to 10 university experts, who were requested to determine the relationships between the criteria based on theoretical foundations. Based on the responses received and employing the ISM method, the relationships between the criteria were examined and the fundamental criteria were identified. Findings In the initial phase of the fuzzy-Delphi method, the literature and previous studies were thoroughly examined to identify theoretical concepts related to stock price forecasting from 4 perspectives: technical, fundamental, macroeconomic, and behavioral perspectives. A questionnaire was then formulated to determine the priority and importance of various indicators. The indicators with the highest average importance were selected within each perspective. The results revealed that among the 54 indicators considered, 15 were identified as crucial criteria for stock price forecasting. These indicators included exponential moving averages, price channel indicator, relative strength indicator, equilibrium trading volume indicator, price indicator, price-to-earnings ratio (P/E), operating profit-to-sales ratio, gross profit-to-sales ratio, company sales growth rate, share purchase-to-sales ratio, dividend per share (DPS), money flow index (MFI), earnings per share (EPS), exchange rate, and trading volume. These indicators were deemed essential for accurate price forecasting in the stock market. Discussion & Conclusion The findings highlighted the significance of the price-to-earnings ratio and the MFI as the most important criteria for predicting stock prices. In the ISM, these criteria were positioned at the highest level (Level 8) of the hierarchy, indicating their strong driving force and considerable influence. On the other hand, the exchange rate, relative strength indicator, and exponential moving average were identified as the most influential indicators at the top levels (1 and 2) of the hierarchy. These criteria, particularly the macroeconomic components and the relative strength indicator, played a pivotal role in the stock price prediction process. اهداف: هدف این مطالعه توسعه الگویی جامع برای پیش‌بینی قیمت سهام در بورس اوراق بهادار با به‌کارگیری شناسه‌های فنی، بنیادی، کلان اقتصادی و رفتاری با استفاده از رویکرد الگوسازی ساختاری تفسیری است. روش: در این پژوهش 54 معیار از چهار بعد ابعاد اصلی تأثیرگذار بر قیمت بورس تعیین شد و در اختیار خبرگان قرار داده شد. پس از آن با استفاده از روش دلفی فازی، 15 معیار مهم انتخاب و سپس با استفاده از روش الگوسازی ساختاری - تفسیری الگوی جامع تأثیرگذارترین و تأثیرپذیرترین معیارها مشخص شده است. نوآوری: اگرچه در پژوهش‌های پیشین از تلفیق حداکثر دو بعد پیش‌بینی قیمت سهام استفاده شده، در این پژوهش سعی شده است هر بعد نماینده‌ای در پیش‌بینی قیمت سهام داشته باشد. از سوی دیگر در روش فازی میزان ابهامات به کمترین حد کاهش پیدا کند و الگوسازی ساختاری - تفسیری نمای شماتیک از میزان محرک‌بودن معیارها ارائه کرده است. نتایج: بر‌اساس یافته‌ها در الگوی الگوسازی ساختاری - تفسیری مشاهده می‌شود قیمت به سود هر سهم و شاخص جریان پول در انتهای سلسله مراتب قرار می‌گیرد و قدرت محرکه زیادی دارد. معیارهایی که در پایین سلسله مراتب قرار می‌گیرند عبارتند از نرخ ارز و اندیکارتور قدرت نسبی و میانگین متحرک نمایی که تأثیرپذیرترین شاخص‌ها هستند.

https://amf.ui.ac.ir/article_28419_539d0b2939925887c3c87b68f6786d70.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 12 2 2024 06 21 Designing a Forecasting Model and Evaluating the Strategic Cooperation between the Banking System and Fintech Startups using the Adaptive Neural Fuzzy Inference System (ANFIS) طراحی الگوی پیش‌بینی و ارزیابی همکاری راهبردی نظام بانکی و استارتاپ‌های فینتک با رویکرد استنتاج فازی عصبی ـ تطبیقی 59 80 28316 10.22108/amf.2024.138687.1813 FA آرش عنصری دانشجوی دکتری، گروه مدیریت تکنولوژی، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران عباس خمسه دانشیار، گروه مدیریت صنعتی، واحد کرج، دانشگاه آزاد اسلامی، کرج، ایران تقی ترابی دانشیار، گروه اقتصاد، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران حمیدرضا یزدانی دانشیار، دانشکده مدیریت و حسابداری، دانشکدگان فارابی، دانشگاه تهران، تهران، ایران Journal Article 2023 08 10 This research aims to develop a robust predictive model for evaluating the strategic cooperation between Iran's banking system and fintech startups. Leveraging insights from 14 experts within the banking and fintech sectors, a hybrid methodology involving the foundation's interview tool and data analysis was employed. Thirty-one indicators, categorized into six key factors influencing strategic cooperation, were identified. Using a fuzzy approach and MATLAB software, a conceptual model was crafted to assess the strategic cooperation of the banking system with fintech startups. Input from 320 industry professionals and managers further enriched the analysis. The findings underscore the pivotal dimensions shaping this cooperation, including barriers to entry, external factors, explanatory elements, varying cooperation levels, consequences of collaboration, and the motivations driving banks and fintechs. The level of strategic cooperation was determined to be in the medium to high range. Notably, the Anfis-designed model exhibited acceptable validity and predictive power. This study contributes not only by unraveling critical cooperation dimensions but also by furnishing a reliable predictive tool. The comprehensive approach, amalgamating expert insights, diverse indicators, and advanced analytical tools offers valuable insights to fortify strategic cooperation in the banking-fintech nexus. Keywords: Startup, Fintech, Strategic Cooperation, Banking System, Fuzzy Inference System. Introduction The rapid evolution of financial technology (fintech) has instigated a profound transformation in the global banking sector, challenging established norms and prompting the need for strategic collaboration (Li et al., 2023). In response, this study delves into the strategic cooperation between traditional banks and fintech startups, recognizing that these entities must leverage each other's strengths, share resources, and attain common objectives (Jia et al., 2023). Collaboration between banks and fintech startups unlocks numerous benefits, enhancing growth and innovation within the financial ecosystem. Banks with regulatory knowledge and expansive customer bases provide fintech access to networks and financial resources. Concurrently, fintechs, with technical expertise and disruptive ideas, propel technological advancements and accelerate processes (Hu et al., 2019). Despite the extensive exploration of fintech's impact, a research gap persists in understanding the dimensions influencing strategic cooperation between banks and fintech startups (Yang & Wang, 2022). In the context of Iran's burgeoning fintech sector, the dynamics of strategic cooperation with traditional banks remain largely unexplored. This study addresses this gap by crafting a comprehensive model through a literature review, in-depth interviews, and content analysis. The primary research question guiding this inquiry is: What dimensions and key components influence strategic cooperation between Iran's banking system and fintech startups? This research is pivotal, uncovering untapped potential in Iranian collaboration and providing a framework for policymakers and industry stakeholders. It facilitates efficient collaboration, fosters innovation, improves financial services, and benefits customers and the Iranian banking industry. Materials and Methods Employing a grounded theory approach, this study formulates, rather than tests, theories through inductive reasoning. Initially, a semi-structured questionnaire was designed, informed by the literature, and administered to 14 experts with a minimum of a master's degree, and over a decade of experience in digital banking, startup management, and fintech. Utilizing snowball sampling, interviews achieved theoretical saturation by the twelfth, with two additional interviews for verification. ATLAS.ti software facilitated data analysis, extracting dimensions used to formulate and test a model via a questionnaire. Face and content validities, along with Cronbach's alpha, ensured questionnaire reliability. Calculating a sample size of 291 with Sample Power v3.0.1, 321 questionnaires were distributed, receiving 320 responses from experienced banking and fintech professionals. Respondents, purposively selected, rated strategic cooperation on a scale of 0 to 10. Neuro-adaptive fuzzy inference system (ANFIS) was employed for inference rule design using MATLAB. ANFIS, a blend of fuzzy inference and neural networks, was chosen for its capacity for nonlinear problem-solving. The model's accuracy surpasses regression, aligning with reality for precise forecasting (Azar & Faraji, 2017). ANFIS building involves clustering the output variable and fuzzy expansion in input spaces, forming a rule base. This approach ensures flexibility in adjusting weights, presenting a superior alternative to multivariate regressions. The study adheres to a systematic process, from data collection to ANFIS modeling, to scrutinize the adaptive neural fuzzy system intricacies (Azar & Faraji, 2017). Findings The study unfolds an innovative framework, leveraging an Adaptive Neural Fuzzy Inference System (ANFIS), to scrutinize strategic collaboration dynamics between Iran's banking realm and burgeoning fintech enterprises. In this endeavor, six pivotal dimensions, embracing collaboration incentives, influential factors, diverse cooperation levels, external organizational elements, hurdles, and resultant outcomes, constitute the ANFIS inputs. The resulting mathematical model incorporates a principal ANFIS and six sub-ANFIS modules, each scrutinizing the ramifications of a specific dimension, illustrated in Table 1. Table 1: Research Dimensions and Components Components Symbol Dimensions Main component Market development needs (MD), Financial aspects (FA), Innovation motivations (IM), Emerging business ecosystem (BE) SCM Strategic Cooperation Motivations Strategic cooperation between the banking system and fin-tech startups (SCOBF) Digital transformation (DT), Technology infrastructures (TI), Structural factors (SF), Organizational factors (OF), Cultural factors (CF), Manager tact (MT), Trust making (TM), Legal features (LF) EFOC Effective Factors on Cooperation Conventional cooperation (CC), Strategic cooperation (SC), Dynamic cooperation (DC) LCBF Levels of Cooperation Between Banks and Fintech Peripheral factors (PF). International factors (IF), Law making (LM), Policy making (PM), Government and parliament (GP), Banking syndication (BS) EOF External Organizational Factors Technology limitations (TL), Economic barriers (EB), Procedure barriers (PB), Security challenges (SC), Legal barriers (LB) SCB Strategic Cooperation Barriers Business development (BD), Value making (VM), Efficiency improvement (EI), Transparency improvement (TM), Risk indicators (RI) SCO Strategic Cooperation Outcomes Moreover, the ANFIS design integrates Gaussian functions, ensuring differentiability and adaptability to diverse data patterns. The initial membership functions, depicted in Figure 1, set the stage for subsequent modeling by illustrating the shape and characteristics of linguistic variables in the ANFIS system. These initial functions provide the groundwork for the ANFIS to effectively capture the intricacies and relationships inherent in the strategic cooperation between the banking system and fintech startups. Figure 1: Initial membership function for evaluating the strategic cooperation of the banking system and fintech startups The study proceeds to the ANFIS training and error analysis phase, employing both backpropagation and hybrid methods. The average error of 7.7 * 10-8 showcases the high validity and accuracy of the model. The subsequent implementation of the mathematical model, as detailed in Table 2, illustrates the input and output values for the main model, offering a comprehensive overview of the strategic cooperation evaluation. Table 2: ANFIS Input and Output Values for Strategic Cooperation SCOBF SCO SCB EOF LCBF EFOC SCM Input variables 7.60 6.17 6.9 6.68 6.17 6.6 6 Output values Furthermore, the model undergoes meticulous validation through dataset testing and limit condition testing, ensuring its applicability, accuracy, and reliability. Additionally, sensitivity analysis and impact rate ranking of research dimensions underscore the pivotal role of overcoming barriers, as encapsulated by the dimension "SCB", in shaping and fostering effective strategic cooperation. Discussion and Conclusions The research concludes with a comprehensive exploration of strategic cooperation between Iran's banking sector and fintech startups, illuminating key dimensions that significantly influence collaboration. The study introduces a robust model comprising 31 indicators across six factors, elucidating the intricacies of strategic cooperation. Emphasizing the transformative potential of collaboration, the analysis pinpoints crucial dimensions, including barriers, organizational factors, effective cooperation factors, and motivational aspects. The model, evaluating strategic cooperation at a commendable score of 7.06, underlines the prospect for innovation and positive transformation in financial services. Recommendations for policymakers, industry stakeholders, and regulators are delineated, focusing on fostering a culture of cooperation, facilitating strategic partnerships, embracing digital transformation, ensuring regulatory support, prioritizing talent acquisition, and developing customer-centric solutions. These proposals aim to cultivate an environment conducive to effective collaboration, innovation, and sustainable growth in the Iranian banking industry. The study identifies limitations, cautioning against generalizing findings to other regions and industries. Acknowledging biases associated with self-reported data, suggests future research adopt mixed-method approaches. Encouraging longitudinal studies and exploration of additional dimensions, such as technological advancements and cultural factors, is advised. The call for knowledge exchange between researchers, practitioners, and policymakers emerges as a key theme, underscoring the importance of collaboration to deepen industry insights. In essence, while providing valuable insights, the research acknowledges its limitations and proposes a roadmap for future investigations. By addressing these limitations and embracing the outlined recommendations, the field can advance, expanding knowledge and adapting to the evolving dynamics of the banking and fintech sectors. اهداف: این پژوهش با هدف ارائۀ الگوی پیش‌بینی و ارزیابی همکاری راهبردی نظام بانکی ایران با استارتاپ‌های حوزۀ فینتک انجام شده است. روش: از ابزار مصاحبه و روش داده‌بنیاد برای بهره‌گیری از نظرات خبرگان استفاده شده است که شامل 14 نفر از خبرگان نظام بانکی و شرکت‌های حوزه فینتک بوده‌اند. 31 شاخص در قالب شش عامل مؤثر بر همکاری راهبردی نظام بانکی و استارتاپ‌های فینتک شناسایی و برمبنای آن، الگوی مفهومی پژوهش طراحی شد. سپس با استفاده از رویکرد فازی و نرم‌افزار متلب، همکاری راهبردی نظام بانکی با استارتاپ‌های فینتک با استفاده از نظرات 320 نفر از مدیران و متخصصان فعال در صنعت بانکداری و استارتاپ‌های حوزۀ فینتک ارزیابی شد یافته‌ها: نتایج نشان می‌دهد که مهم‌ترین ابعاد مؤثر بر همکاری راهبردی نظام بانکی با استارتاپ‌های فینتک به‌ترتیبِ اهمیت عبارتنداز: موانع و مشکلات ورود به همکاری‌های راهبردی، ابعاد و مؤلفه‌های برون‌سازمانی، عوامل تبیین‌کنندۀ همکاری بانک‌ها و فینتک‌ها، انواع سطوح همکاری بانک‌ها و فینتک‌ها، پیامدهای ورود به همکاری‌های راهبردی، انگیزۀ بانک‌ها و فینتک‌ها در ورود به همکاری. سطح همکاری راهبردی نظام بانکی و استارتاپ‌های فینتک در محدودۀ متوسط رو به بالا قرار دارد. باتوجه‌به میزان خطای به‌دست‌آمده و نبود پدیدۀ فراـ‌انطباق در انفیس طراحی‌شده، الگوی مذکور اعتبار پذیرفتنی و قدرت بالایی برای پیش‌بینی دارد. نوآوری: این پژوهش نه‌تنها با آشکارسازی ابعاد مهم همکاری، بلکه با ارائۀ یک الگوی پیش‌بینی معتبر یاری می‌رساند. این پژوهش به‌دلیلِ رویکرد جامع خود، ترکیب دیدگاه‌های متخصصان، شاخص‌های گوناگون، و ابزارهای تحلیلی پیشرفته، بینش‌های ارزشمندی را برای تقویت همکاری راهبردی میان نظام بانکی و استارتاپ‌های فینتک ارائه می‌دهد.

https://amf.ui.ac.ir/article_28316_bd2a8dba4466558251b6e03608f4b70a.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 12 2 2024 06 21 A Pattern for Iron Ore Mines Financing الگویی برای بهبود تأمین مالی معادن سنگ آهن 81 112 28329 10.22108/amf.2024.136679.1785 FA مهدی علی حسینی دکتری مدیریت مالی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران محمدهاشم بت شکن دانشیار، گروه مالی و بانکداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران امیرحسین مزینی دانشیار، پژوهشکده اقتصاد، دانشگاه تربیت مدرس، تهران، ایران مسلم پیمانی فروشانی استادیار، گروه مالی و بانکداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبایی، تهران، ایران Journal Article 2023 04 06 Acknowledging the lack of financial resources in the field of mining, researchers have found a solution in the use of new tools. Despite the existence of tools, the mining sector still lacks financial resources. Therefore, this research aims to provide a comprehensive solution, taking into account domestic and foreign theoretical and experimental background, to solve the problem of lack of financial resources in iron ore mines. For this purpose, this research firstly studies the available sources through theme analysis, the main themes including 48 basic themes, 10 organizing themes, and 3 comprehensive themes. It then extracts the conceptual model of the mining financing pattern in three levels of dimensions, components, and indicators. Then, this conceptual model, along with the solutions to improve the identified indicators, have been submitted to the expert survey using a questionnaire. The experts were selected by purposive sampling and their answers were analyzed by confirmatory factor analysis. Finally, the conceptual model and solutions obtained from the studies of this research were confirmed. The most important solutions have been presented to solve the budget deficit, adjust the policies of the central bank, manage risk, increase the efficiency of the industry, improve the rules and regulations, and make the institutions more efficient. Keywords: Financing Model, Mines, Iron Ore Mines, Iran. Introduction Despite the existing capacity, Iran's mining industry has not been very successful. Benefiting from these large resources, as well as the availability of low-priced energy and a favorable labor force, the special regional position and the competitiveness of its products in the regional and world markets should be used to participate in this sector in international trade and markets. The necessary measures should be taken and sufficient facilities should be provided for it. Despite the investments made in the mining sector, this sector has not yet found its real position in the whole economy and there is a big gap between the existing capacities and the current situation. The field of mines and industries related to mining is one of the most important economic sectors of countries that are rich in mineral resources. This section has many previous and subsequent relationships that add to its importance. Until now, there has been some research on the financing of mines. But so far, no research has been done that specifically and accurately examines the problem of financing mines and provides a comprehensive solution or even explains the dimensions of this problem. Therefore, this research seeks to provide a comprehensive solution to improve the financing of iron ore mines. In this study, the theoretical foundations and background of the research has been discussed first. Then, presenting the summary of the findings in the primary studies in the section on theoretical foundations and background of the research, the method used in this research is described. After stating the research method, the findings of this study are stated and the conclusion is presented at the end. Materials and Methods The first step of this research was to collect data from existing documents, questionnaires, and interviews. Therefore, in the first stage, the data collection tool is document review and interview. At this stage, all materials related to the financing of mines, including financing methods, issues and problems, complications, special features of the mine that affect financing, and ways to improve the financing of mines were reviewed. In the second step, the information obtained from the previous step was analyzed through thematic analysis. By studying the texts, first, the themes are identified from the specification or concept of the studied text and then the category of the theme is determined based on its inclusion. Since these themes have been identified according to the researcher's opinion, to complete it, a table of themes was presented to the experts and they were interviewed through a semi-structured questionnaire. The content analysis of the interviews was done using MAXQDA software. At this stage, the final number of themes along with their class is concluded. In addition, based on the analysis of the output of this software, a conceptual model of mining financing was extracted, which shows all the components affecting the country's mining financing system. To validate the model, experts were asked through a researcher-made questionnaire. The answers to the questions were set on a Likert scale from one to five. After receiving the answers, quantitative analysis was done on the data. First, the validity and reliability of the questionnaire were checked, and after its confirmation, the evaluation of the structural part and the overall fit of the model was done using the method of confirmatory factor analysis. Findings In the qualitative part of the research, which is the first step, themes and classifications were obtained. These themes were identified in three levels dimensions, components, and indicators. The next step is to show the relationship between the identified themes. Since the results of studies and interviews were entered into the MAXQDA software from the beginning, this software was also used to show the network of identified themes. By using the overarching, organized, and basic themes identified and the relationships discovered by the software, the obtained conceptual model can be presented as follows: Figure 1: The conceptual model Kolmogorov-Smirnov test was used to check the normality of the distribution of variables. Considering that the significance level of the distribution of variables is less than 5% (non-normal); therefore, SmartPLS software has been used for analysis. In addition to Cronbach's alpha method, the reliability of the questions was evaluated using the methods of coefficient of factor loadings, significance of factor loadings, composite reliability, shared reliability, and rho_A reliability, and all of them confirmed the reliability. The validity of the questions was also investigated using the face validity method, divergent validity using two Fornell-Larker methods, and mutual factor loadings, all of which indicated the validity of the questions. The evaluation of the structural part of the model has been done with the R2 criterion. The endogenous structures of the model with a value of more than 0/74 have a strong structural relationship, and this indicates the strength of the structural part of the model. To evaluate the confirmatory factor analysis model, the second root index of the estimation of the variance of the approximation error has been used. According to Joseph et al. (2017), the limit of this index is 0.1. For the model, the value of this index is equal to 0.078, less than the value of 0.1, and one can say that the model has a good fit with the factor structure and the theoretical foundation of the research. On the other hand, according to the opinion of Ringle and Sarstedt (2016), the acceptable value is less than 0/08 and it is also acceptable from this point of view. Discussion and Conclusions Based on the findings, it can be said that the model has a good fit with the factor structure and the theoretical foundation of the research; therefore, the initial conceptual model is confirmed. In addition to confirming the model, experts were asked about financing solutions for iron ore mines. These solutions have been obtained from primary research studies on existing documents and interviews. In the following, the opinions of the experts obtained from the analysis of the information obtained from the questionnaires has been summarized. Freeing the price of energy carriers of mining companies and allocating it to mining sector development projects will improve the financing of iron ore mines. Providing tax incentives and reducing export duties on iron ore products will make it easier to finance iron ore mines. The policy of the central bank should move towards the liberalization of the exchange rate in the pricing of mineral products. Accepting a mining license as an acceptable collateral with banks can help finance iron ore mines through the banking network. The initial stages of mine development, i.e. mine exploration, are associated with risk. According to the information obtained, this risk is one of the most fundamental obstacles to the financing and development of mines, including iron ore mines. If this obstacle is removed or shortened, the entry of financial resources into this industry will increase. The more efficient the mines are, the easier it will be to finance them. Profit is one of the most basic elements of financial statements that has always been taken into consideration and is referred to as a measure to evaluate the continuity of activity and efficiency. The laws need to be reviewed with a comprehensive view in line with the development of the country's mines. In revising the laws, attention should be paid to strengthening the monitoring of mineral activities and licenses in the Mining Law and its executive regulations. According to the findings, the effectiveness of the Ministry of Health in financing iron ore mines has been low so far. Therefore, this important organization should take measures to have a greater impact on this market. The technical and financial empowerment of the geological organization in order to prepare, produce, and publish accurate and reliable geological information can improve the financing of iron ore mines. پژوهش‌های داخلی با اذعان به وجود کسری منابع مالی در حوزۀ معدن، راه‌حل را در استفاده از ابزار جدید یافته‌اند. اما باوجودِ ابزارهای متنوع، همچنان حوزۀ معدن دچار کمبود منابع مالی است. بنابراین، نگارنده در این پژوهش قصد دارد با درنظر گرفتن پیشنیۀ نظری و تجربی داخلی و خارجی، راهکاری جامع با هدف رفع مشکل کمبود منابع مالی معادن سنگ آهن ارائه دهد، به‌شکلی که با اجرای الگوی پیشنهادی مشکلات تأمین مالی معادن سنگ آهن مرتفع شود. بدین منظور، نگارنده در این پژوهش ابتدا با مطالعۀ اسناد موجود و انجام مصاحبه با افراد مطلع، ازطریقِ تحلیل مضمون، مضامین اصلی را استخراج کرده است. مضامین اصلی عبارت‌اند از: 48 مضمون پایه، 10 مضمون سازمان‌دهنده و 3 مضمون فراگیر. سپس مدل مفهومی الگوی تأمین مالی معادن را در سه سطح ابعاد، مؤلفه‌ها و شاخص‌ها به دست آورده است. در این مرحله، خبرگان مصاحبه‌شده با نمونه‌گیری هدف‌مند و گلولۀ برفی انتخاب شدند. سپس این مدل مفهومی با راهکارهای بهبود شاخص‌های شناسایی‌شده و استفاده از پرسش‌نامه برای نظرسنجی در اختیار خبرگان گذاشته شده است. خبرگان با نمونه‌گیری هدف‌مند از بین خبرگان صنعت معادن سنگ آهن و خبرگان تأمین مالی در بازار سرمایه و شبکۀ بانکی و متخصصان حقوقی انتخاب شدند. پاسخ‌های آن‌ها به روش تحلیل عاملی تأییدی بررسی شد. درنهایت، مدل مفهومی و راهکارهای حاصل از مطالعات این پژوهش تأیید شد. مهم‌ترین راهکارها در راستای رفع کسری بودجه، تعدیل سیاست‌های بانک مرکزی، مدیریت ریسک، افزایش بازده صنعت، بهبود قوانین و مقررات و کاراتر کردن نهادها ارائه شده است.

https://amf.ui.ac.ir/article_28329_e2c60cf572249bf24535962e93efeefc.pdf

دانشگاه اصفهان مدیریت دارایی و تامین مالی 2383-1189 12 2 2024 06 21 Impact of Sanction Shock on Iran's Stock Market Index اثر شوک تحریم بر شاخص بازار سرمایه ایران. 113 126 28620 10.22108/amf.2024.141380.1880 FA رضا تهرانی استاد، گروه مهندسی مالی، دانشکدۀ حسابداری و علوم مالی، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران محمود مختاربند استادیار، گروه اقتصاد، دانشکدۀ اقتصاد و علوم سیاسی، دانشگاه شهید بهشتی، تهران، ایران منال العبوده دانشجوی دکتری، گروه مهندسی مالی، دانشکدۀ حسابداری و علوم مالی، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران Journal Article 2024 05 05 The imposition of Western economic sanctions against Iran has had varying effects on the country's financial markets, with the capital market being one of the sectors not immune to the shockwaves of these sanctions. Given the pivotal role of sanctions in shaping Iran's economic fluctuations, this study aimed to examine the effects of sanctions on the state of the Iranian capital market using a structural macroeconomic econometric model. Unlike previous research, this study accounted for the non-linear, intensity-dependent nature of the sanctions' impact, rather than assuming a constant effect. The research methodology employed an Auto-Regressive Distributed Lag (ARDL) model, considering datasets with both annual and seasonal frequencies over a 30-year period from 1991 to 2021. The findings of the optimal model indicated that the sanctions index had a negative and statistically significant effect on the behavior of the Iranian capital market. تحمیل تحریم‎‌های اقتصادی غرب علیه ایران آثار متفاوتی بر بازارهای مختلف مالی داشته است و بازار سرمایه در ایران نیز یکی از بازارهایی بوده که از شوک تحریم بی تأثیر نبوده است. ازآن‎‌جایی‌که تحریم‎‌ها عاملی کلیدی در توضیح نوسانات اقتصادی ایران هستند، هدف این مقاله بررسی آثار تحریم در قالب الگویی اقتصادسنجی کلان ساختاری بر وضعیت بازار سرمایه در ایران است. برخلاف سایر پژوهش‌های انجام‌شده، نحوۀ اثرگذاری تحریم به‌صورت غیرفازی در این پژوهش لحاظ نشده و مطابق با شدت تحریم‎‌ها تغییر می‎‌کند. روش پژوهش نیز خود رگرسیون با وقفه‎‌های توزیعی با در نظر گرفتن داده‎‌های با تواتر زمانی متفاوت است که داده‎‌های استفاده‌شده برای دورۀ سی‌ساله برخی با تواتر سالانه و برخی با تواتر فصلی از سال‌های 1370 تا 1400 است. نتایج الگوی بهینه نشان می‎‌دهد که شاخص تحریم تأثیر منفی و معنادار بر رفتار بازار سرمایه دارد.

https://amf.ui.ac.ir/article_28620_de01514eda170e62bd105ff8b9b20dce.pdf