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A Classification of Arabic Grammar Rules for Writing Skills Instruction of Persian-Speaking Learners
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
Among the challenges of language acquisition, developing writing proficiency is widely acknowledged as particularly demanding. Learners must not only select appropriate vocabulary but also use it effectively within a specific context. However, the emphasis on writing skill development should not solely lie in memorizing grammatical rules. Rather, grammar should serve as a tool to facilitate clear and effective communication of ideas. Consequently, prioritizing and strategically selecting essential grammar rules for instruction can significantly enhance and expedite the acquisition of writing skills. This research employs a descriptive-analytical method and utilizes a questionnaire to investigate the potential effects of streamlining Arabic grammar instruction on facilitating and accelerating the development of writing skills in Arabic among Persian undergraduate students majoring in Arabic Language and Literature. To achieve this objective, the study employed a researcher-designed questionnaire distributed among a sample of 16 Arabic language teachers and experts. This instrument aimed to identify the relative importance of Arabic grammar components across three proficiency levels: beginner, intermediate, and advanced. Informed by expert opinion, the research proposes a tiered approach to Arabic grammar instruction. At the beginner level, priority is given to mastering structural order and interrogative particles. The intermediate level focuses on relative nouns, causative constructions, and the mood system. Finally, advanced learners concentrate on verbal mode and aspects. Additionally, the findings highlight the experts' emphasis on introducing similar Arabic and Persian grammar rules in the early stages of education, and Arabic-specific rules at higher levels.
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
The increasing ubiquity and impact of audiovisual content has turned it into one of the primary objects of study in a number of disciplines in humanities, including Translation Studies. In the recent decade, audiovisual translation (AVT) has been a thriving research focus in many parts of the world. This article aims at mapping AVT in the context of Iran by reviewing the published Persian AVT research worldwide. The article is organized into two parts: the first part provides an overview of the main research articles, delineating the main research trends in AVT research in Iran. The second part presents and discusses research gaps and areas that merit further scholarly attention by academia. The article concludes that research on the topic in Iran is still in a fairly early stage, with the studies focusing mainly on dubbing and subtitling of audiovisual products. Furthermore, areas such as accessibility and inclusion, in particular, voice-over and game localization are grossly under-researched. To fill the gap, certain areas are highlighted and recommended for future research.
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
The intricate connection between teacher support, academic burnout, grit, and psychological wellbeing is a compelling area of research that has recently garnered second language (L2) education researchers' attention. This study aims to investigate such complex relationships with undergraduate English-major students in Iran. To this end, a sample of 318 undergraduate English-major students from various universities in Iran was selected through convenience sampling. The data were analyzed using IBM SPSS version 26 for descriptive statistics and correlation analysis, while LISREL software was employed for Confirmatory Factor Analysis (CFA) to validate the measurement models. The findings revealed that teacher support showed a positive and significant correlation with students' L2 grit and L2 psychological wellbeing while demonstrating a negative and significant correlation with students' L2 academic burnout. Furthermore, the simple linear regression analysis indicated that teacher support significantly predicted a 13% increase in students' grit and psychological wellbeing and a 0.03% in academic burnout. This suggests that measures to reduce the academic burnout of students in higher education should be prioritized in second language education through positive teacher support and positive psychology. The study provides valuable insights and recommendations for English language teachers, students, and policymakers and outlines future research directions.
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
Pre-service teacher education programs play a pivotal role in the formation and evolution of teachers' identities, wherein both formal and hidden curriculums exert significant influences (Beauchamp and Thomas, 2009). This qualitative study delves into the development of Language Teacher Identities (LTIs) among student teachers at Farhangian University, with a particular focus on the reformed curriculum.A qualitative research method was used. A total of 27 female student teachers shared their experiences through individual and focus group interviews. Thematic analysis was used for analyzing the interviews. The findings revealed mismatches between the student teachers’ envisioned identities and the curriculum’s expected identity, leading to feelings of cognitive unpreparedness. The study also highlighted the significant roles of both formal and hidden curriculums in shaping teacher identity, with both positive and negative changes observed in cognitive, social, and emotional aspects. The implications drawn from the study’s findings provide insights into curriculum design and teacher education programs, offering guidance on how to effectively support the construction of teacher identity and raise student teachers’ awareness of this transformative process.
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
Over the past decades, research on language teacher engagement in action research (AR) has received a surge of interest. However, little research is available on how teachers’ experience contribute to their development of agency and professional performances through their participation in an AR program. Accordingly, this study explored the role of experience in five novice and five experienced language teachers’ development of agency and practice before, during, and after their engagement in an action research engagement program (AREP). To this end, we collected data via semi-structured interviews, reflective journals, and classroom observations. The findings revealed that novice and experienced teachers’ development of their agency and professional practice undergo similar trajectories. Moreover, the study argues that although experience affects teacher-researchers’ agentive role and performances, novice and experienced teachers go through similar paths as they engage in AR. However, the novice teachers became more oriented towards reflection-in-action during and after their engagement in AREP. Moreover, the novice teachers chose more AR tools and drew more on their AR experience which, in turn, facilitated their professional growth through tool transformation. We conclude the paper with implications for teacher education to better understand the role of AR in teachers’ agency development and professionalism.
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
Metaverse is a space that includes the real world and virtual worlds in which people use a digital and virtual representation called an avatar to be present. Metaverse is considered as the major media of commercial advertising in the future and it will play a fundamental role in terms of audience attraction and society awareness. By adopting semiotics approach, this research analyzes the preparation of the subject and the formation of the avatar in Metaverse commercials. Ten commercial advertisements of prominent brands are chosen as statistical sample, and the virtual world of Hyundai brand on Roblox is examined as the case study because of its diverse activities. Descriptive-analytical method is carried out relying on participatory observation, in a way that the researcher experiences the field, and seeks to answer two questions: 1) What kind of discourse is applied to Subject and Object interactions? 2) What is the procedure of conversion of real body to ideal body? Results show that Subject of Metaverse should be considered as a Being-actor who continuously finds itself in a lack of meaning due to Becoming-centered situation and is called to action and achieves meaning as a result of the action. Besides, the avatar could be considered as Ideal-otherness while the dialogue between physical and virtual body is possible through the third body, which is the Imaginary body, which is the main base of sensory-perceptual receptions and leads the actions of the subject.
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
This research is aimed to capture EFL teachers’ use of technology in Task-Based Language Teaching (TBLT) by focusing on the variety and intensity of tasks in teaching reading. Driven by the survey research, the data were collected from 71 teachers of English as a Foreign Language (EFL) in Indonesia and analyzed descriptively. The findings show that the EFL teachers perceived that the use of technology in TBLT in teaching reading is important and it can enhance students' language learning experiences. Technology offers engaging materials and activities that aid reading comprehension. Furthermore, EFL teachers' use of various tasks and resources may indicate a need for continuing professional development to improve digital literacy skills and pedagogical strategies of English teachers in EFL context. Although the findings of this survey give an insight into the data of English teachers’ use of technology in TBLT in terms of variety and intensity in teaching reading, this survey has its limitations with regard to the numbers of participants. This research highlights the dynamic relationship among technology, TBLT, and reading instruction in the EFL context, and suggests the need for continued research and exploration of best practices in this area. The current study succeeded in adding new empirical studies related to the variety and intensity in pre-reading, whilst-reading and post-reading activities of EFL teachers enacting teaching reading with the use of TBLT.
Volume 0, Issue 0 (Articles accepted at the time of publication 2024)
Abstract
Semiotics, with its phenomenological turn, provides the basis for re-projecting lost dimensions of meaning such as presence, perceptual-sensory flow, and the body. French semiotician Eric Landowski also proposes linguistic systems of adaptation and coincidence in a different way from Grimas. The Resāle-y-Mūmūsīyāh by Ehsan Abdipour, in which the linguistic actions of the actors create an interactive situation in which we witness the transformation of discursive spaces into each other and one event into another. These successive becomings are formed in the context of language and through perceptual-sensory and bodily processes. The issue is how the process of generating meaning in the context of language and the processes of transition from language to discourse are realized. In this research, the mechanisms of meaning production are investigated from the perspective of Landofsky's phenomenology in the context of adaptation, coincidence, programmatic and persuasive linguistic systems. Also, the phenomenological manifestations of the body are examined and analyzed by relying on the linguistic and discourse systems of this story. The aim of the research is to apply Landowski's phenomenological model in analyzing the linguistic structures of the story. The research question is also how does the main character of the story live in the world and which linguistic and discursive systems are seen in this story? The result shows that the systems of planning and persuasion force the main character of the story to accept certain requirements, but the systems of adaptation and coincidence create a lived experience for her.
Volume 0, Issue 0 (ARTICLES IN PRESS 2024)
Abstract
Rural handwoven carpet weavers, particularly in the context of handmade silk carpet production, grapple with significant challenges concerning recognizing all stakeholders and establishing timely connections. These challenges have a substantial impact on the adoption of innovation in carpet production and the overall enhancement of productivity. This research was conducted to scrutinize the communication network of carpet weavers within the Knowledge and Innovation System (KIS) of handmade silk carpet production in rural areas. Data were gathered through interviews with 270 rural households in Zanjan province, specifically in the Tarom, Khodabandeh, and Zanjan counties, utilizing a structured questionnaire. Social Network Analysis (SNA) in UCINET was employed to examine the interactions among these actors, and graphical representations were created using Net Draw. The results revealed that the network's density varied across different levels, showing weakness in some cases, moderate strength in others, and strong connections in select instances. The connections of carpet weaving families with other actors within the KIS were predominantly localized. Among these families, those utilizing the home-based wage production method exhibited the most extensive interactions. The individuals designated as "FMs" (likely referring to family members) and "WNVKRs" (possibly local experts) demonstrated the highest degree of connection and influence within the network of weavers' interactions
Volume 0, Issue 0 (ARTICLES IN PRESS 2024)
Abstract
This study aimed to increase the vase life of cut rose flowers by improving the regulation of Programmed Cell Death (PCD). Experiments were carried out on cut rose (Rosa hybrida cv. Dolce vita+) flowers under either physical treatment of Static Magnetic Field (SMF; 15 and 25 mT) for 3 hours, or chemical treatments of silver nano particle (Nano-Ag; 5 and 10 ppm), 6-Benzyladenine (BA; 25 and 50 mg L-1), 1% sucrose, and combinations of 5 and 10 ppm nano-Ag with 3 and 6% sucrose. Results showed that a 15 mT-SMF significantly increased vase life up to 25 days, compared to the controls and to all chemical treatments. Among the chemicals, 5 ppm Nano-Ag and 1% (w/v) sucrose increased vase life to 23 and 18 days, respectively. The smallest decline in fresh weight was observed in the 15 mT-SMF physical treatment. Markedly, the 15 mT-SMF treatment led to the least reduction in Chlorophyll (Chl) content. On the 17th day of the applied different treatments, both Water Uptake (WU) and Relative Fresh Weight (RFW) showed an inverse significant relationship with PCD in cut rose flowers, verifying there markable delayed PCD which is favored the market. As a whole, the most effective induced treatments (15 mT-SMF, 5 ppm Nano-Ag, and 1% Sucrose) are suggested to be promising for enhancing postharvest quality and prolonged vase life of cut rose flowers.
Volume 0, Issue 0 (ARTICLES IN PRESS 2024)
Abstract
The Ministry of Agriculture Jihad in Iran implemented contract farming (CF) for wheat in 2021 to address marketing issues. This study compares agricultural sustainability for farmers participating in and not participating in CF. Agricultural sustainability was assessed by applying a combined index approach that considers economic, social, and environmental dimensions. The required data came from 620 wheat farmers in Golestan province, sampled using the multi-stage randomization technique. The data were evaluated using exploratory factor analysis (EFA) and clustering methods. The findings indicated a significant difference in the performance of economic and environmental sustainability dimensions between two groups of wheat farmers. For the participants, 14.2% were deemed unsustainable, 47.7% were considered partially sustainable, and 38.1% were classified as sustainable. For non-participants, the figures were 38.7%, 47.7%, and 13.5%, respectively. Therefore, it is suggested to provide more opportunities for participation in this program and expand it to other key crops. Additionally, authorities should provide more information about the benefits of the CF plan.
Volume 0, Issue 0 (ARTICLES IN PRESS 2024)
Abstract
Extension field staff is the group of people who are responsible for managing activities related to agricultural information dissemination and farming community is the recipient or audience of that knowledge by implementing this knowledge on farm, farming community may enhance their farm productivity and uplift socio-economic situation. The Present study was based on primary data, collected from agricultural extension field staff (EFS) using interview schedule in cotton belt of Punjab province. Three hundred and fifty-nine (359) extension field staff workers were selected from population of five hundred and forty (540) by using Cochran sampling technique. Moreover, Borich needs assessment model was implied to prioritize the training needs of EFS about climate adaptation. Study found that majority of the EFS seek trainings in specific areas regarding climate variability including; skills to use meteorological instrument, ability to comprehend early warning system, serving and mapping of climatic variability areas, management of ICT tools for weather forecasting, disaster management skills, and integrated soil management skills by acquiring these competencies they can effectively and efficiently work for minimizing the consequences of climate variability on cotton crop. There was significant positive correlation of 0.608 between specialization and possessed competencies regarding climate adaptation which shows that specialized extension staff possessed competencies regarding climate adaptation. On the basis of findings study suggests that the training needs of the extension field workers should be assessed regularly regarding various latest techniques and technologies. Training sessions regarding climate variability adaptation should be arranged for extension workers of cotton belt.
Volume 0, Issue 0 (ARTICLES IN PRESS 2024)
Abstract
As new venture establishment has become a vital source of economic evolution and indispensable expediter for local development in current years, the ecosystem approach is considered as one of the practical solutions for reducing the gap between the economies of developed and developing regions. The concept of rural entrepreneurship ecosystems has attracted significant attention among practitioners, policymakers, and researchers during the past decade. However, the research concerning rural entrepreneurship ecosystem has been largely focused on empirics from developed regions. In order to explain the drivers of rural entrepreneurship ecosystem in a developing region, in this study, the data was collected from 103 rural entrepreneurship practitioners through a survey in northern area of Iran. The data was then analyzed using the exploratory factor analysis method. The research team considered the rural entrepreneurship ecosystem supporters in three pillars: policy-making, institution, and society. According to the results of exploratory factor analysis, each triple supporter pillar of the rural entrepreneurship ecosystem was divided into two components. The components extracted from the policy pillar included "rules and regulations" and "infrastructure." The components extracted from the institutional pillar included "networking and informing" as well as "services and support." In addition, "tendencies and characteristics of the people" and "financial participation" were assumed as the society components. These results were discussed and provided agenda for future practical and professional works.
Volume 0, Issue 0 (ARTICLES IN PRESS 2024)
Abstract
The effectiveness and return on investment (ROI) of agricultural training programs have always been among the most significant challenges for experts and managers in agricultural extension and development. Based on this, the main objective of the present study was to evaluate the effectiveness of beekeeping training courses using the ROI technique. This study is an applied and quasi-experimental research conducted by collecting data in two phases (before and after the training course). The data collection tool was a semi-structured, researcher-made questionnaire. Additionally, the ROI calculation was carried out through a nine-step process, enabling the assessment of ROI for both participants of the beekeeping training courses and the Agricultural Research, Education, and Extension Organization. In this process, along with tangible and/or monetary effects, intangible and non-monetary impacts were also quantified. The findings of this study indicated that, on average, beekeeping training courses had a 1302% return on investment for participants. Furthermore, these courses yielded an average ROI of 770% for the Agricultural Research, Education, and Extension Organization. The results provide strong evidence supporting the enhancement and expansion of beekeeping training courses and similar programs conducted by the organization. Moreover, this study and its findings serve as a starting point for further research on evaluating the impacts of agricultural training programs, ultimately supporting decision-making and investment development in training farmers and agricultural beneficiaries.
Volume 0, Issue 0 (in press 2024)
Abstract
Buried concrete tanks serve as critical components of public and military infrastructure, where structural damage can trigger severe social, security, and environmental crises. Consequently, designing these tanks to withstand shock loads from explosions is of paramount importance. Additionally, the behavior of layered clay soils under such loading conditions requires detailed examination. This study investigates the influence of burial depth on the performance of concrete tanks subjected to explosive loads in layered clay soils. The analysis was conducted using AUTODYN and FLAC 2D finite element software. Concrete tanks buried at depths of 3, 6, 8, and 10 meters were analyzed under surface explosions generated by 50, 100, and 200 kg of TNT, with defined pressure and distance parameters. The soil properties, structural characteristics, and internal fluid pressure were incorporated into the model. Results indicate that increasing the burial depth significantly reduces the displacement of the tank roof and floor due to the dissipation of explosion energy in the surrounding soil. For instance, with a 50 kg TNT charge, increasing the burial depth from 3 meters to 6, 8, and 10 meters resulted in roof displacement reductions of 54%, 70%, and 78%, respectively. These findings demonstrate the critical role of burial depth in enhancing structural resilience against explosive loads and mitigating damage.
Volume 0, Issue 0 (Articles accepted for Publication 2024)
Abstract
Aim and Introduction
Achieving sustained and long-term economic growth necessitates the optimal allocation and utilization of resources at the national level. This goal relies heavily on the existence of efficient financial markets, particularly well-functioning and extensive capital markets. Numerous macroeconomic variables can influence the level of risk associated with shareholder rights, corporate cash flows, and adjusted discount rates. Additionally, changes in economic conditions can alter both the quantity and nature of investment opportunities.
However, establishing a fixed and consistent relationship between macroeconomic variables and stock price indices remains challenging. The complex and dynamic nature of financial markets makes it difficult to identify a method that accurately reflects economic conditions and captures the most critical influencing variables. Therefore, this study employs machine learning models to identify the key macroeconomic factors affecting stock price indices.
Methodology
Feature selection is one of the most common and crucial techniques in data preprocessing and serves as an essential component of machine learning. This study employs feature selection models to identify the most relevant predictors of the stock price index. The models utilized include the random forest method and regularized linear regression. To examine the nature of the relationships between variables, the jointness method was applied. Additionally, the mutual information analysis was conducted to assess the influence of key variables over different decades, enabling a deeper understanding of how the impact of macroeconomic factors on stock prices has evolved over time.
Findings
The study analyzed the impact of selected macroeconomic variables on stock price indices, focusing on the Tehran Stock Exchange. The findings from the Random Forest (RF) and Regularized Linear Regression (RLR) models indicate that exchange rates, financial development, inflation, economic growth, trade openness, and global uncertainty significantly influence Iran’s stock price index. The results demonstrate that global uncertainty, interest rates, and trade openness exert negative effects on stock prices, whereas the other variables positively influence stock prices.
The jointness method was employed to analyze the relationships between these variables, further confirming their significance. Moreover, the Mutual Information method was used to examine how the influence of these key variables varied across different decades.
Discussion and Conclusion
Among the variables examined, exchange rates, financial development, inflation, economic growth, trade openness, and global uncertainty emerged as the most significant factors influencing Iran’s stock price index. This finding is not surprising, given Iran’s historical experience with significant exchange rate fluctuations and persistent inflationary pressures. Global uncertainty has consistently influenced domestic markets in Iran due to political and economic instability. Previous research has highlighted the complex relationship between exchange rate fluctuations and stock price indices (Ratanapakorn & Sharma, 2007). Scholars have argued that the relationship between stock prices and exchange rates can significantly affect monetary and fiscal policy, as a recessionary stock market can reduce overall demand and impact broader economic performance.
Extensive research has also investigated the relationship between inflation and stock prices, identifying inflation as a significant factor affecting stock indices
(Boudoukh & Richardson, 1993; Fama & Schwert, 1977; Jaffe & Mandelker, 1976) . While some studies have reported a positive correlation between inflation and stock prices, others have found a negative relationship.
Moreover, trade openness has been recognized as a key factor influencing stock market fluctuations. Open economies are more vulnerable to external shocks due to increased global risk-sharing among markets. Although some studies have not found conclusive evidence of a direct effect between trade openness and stock prices, trade openness remains one of the influential factors (Nickmansh, 2016).
Stock prices reflect the present value of future cash flows, which are subject to two main effects: cash flow changes driven by increased production and interest rates, which serve as a discount factor. Stock prices tend to decline when expected cash flows decrease or interest rates rise. The level of actual economic activity directly influences cash flows, as higher economic activity generally leads to increased cash flow. Among the various indicators used to predict commodity markets, real Gross Domestic Product (GDP) is considered the most comprehensive measure of economic activity (Yuhasin, 2011; Christopher et al., 2006).
mouseout="msoCommentHide('_com_1')" onmouseover="msoCommentShow('_anchor_1','_com_1')">Finally, global uncertainty plays a significant role in shaping the internal economic environment of countries, making it an important global macroeconomic variable that influences the performance of publicly traded companies on the stock exchange.
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Volume 0, Issue 0 (Articles accepted for Publication 2024)
Abstract
Aim and Introduction
Over the past few decades, the housing market has experienced recurrent boom-and-bust cycles and considerable price volatility. A significant portion of this volatility can be attributed to speculative activities. Speculators often purchase properties with the expectation of future price increases, which contributes to the formation of housing price bubble. These bubbles not only destabilize the economy but also lead to serious social consequences. As such, policymakers have consistently focused on identifying the determinants of speculative behavior and housing market bubbles. One of the government’s regulatory instruments in this domain is the transfer tax, intended to influence trader behavior and mitigate housing price bubbles. This study investigates the effect of transfer tax policies on the housing price bubble in Shiraz city.
Methodology
This research employs an Agent-Based Model (ABM) to simulate the dynamic processes of the housing market and analyze the contributing factors to price bubble formation. The model incorporates four key agents active in the housing market: sellers, buyers (including both personal-consumption and speculative buyers), developers, and real estate agencies. Data and statistics up to the beginning of 1401 (2022) were incorporated into the model to forecast housing prices in Shiraz through 1409 (2030).
Three scenarios were tested by varying the proportion of speculative buyers—30%, 50%, and 70%—and applying different transfer tax rates of 1% and 5%. The simulation explores how these variables influence the magnitude and growth of the housing price bubble under different market conditions.
Results and Discussion
The findings reveal that, regardless of the proportion of speculative buyers, the implementation of transfer taxes can reduce the housing price bubble in Shiraz. However, the extent of this effect varies with market conditions. These results align with prior studies, such as Chen (2017) and Izadkhasthi et al. (2018), which found that transfer taxes can mitigate housing price volatility.
Proponents of transfer taxes argue that speculative activities drive housing price bubbles and that such taxes increase transaction costs, thereby reducing speculative trading and contributing to market stability. For instance, with a 70% speculative buyer share and a 5% tax rate, the housing price bubble decreased by approximately 25% between 1401 and 1409. In contrast, a 1% tax rate under the same market conditions led to a 22% reduction in the bubble. However, when only 30% of buyers were speculative, the tax had a comparatively more minor effect, indicating that the efficacy of the tax diminishes when fewer speculators are present.
Conclusion
The results suggest that increasing the transfer tax rate does not necessarily reduce the housing price bubble. In scenarios with 30%, 40%, and 50% speculative buyer presence, higher average tax rates did not result in a significant reduction in the housing bubble and, in some cases, slightly intensified it. This supports earlier warnings in financial economics literature—such as those by Schwert and Seguin (1993) – that excessive transaction taxes may deter informed traders, who play a vital role in maintaining market efficiency and price stability. Similarly, Friedman (1953) emphasized the stabilizing role of rational traders in financial markets.
According to the simulation results, Article 59 of Iran’s Direct Taxes Law, which stipulates a 5% transfer tax, may help reduce housing bubbles in Shiraz and potentially nationwide. However, the optimal tax rate should be adaptive and context-specific, considering the varying proportions of speculative and non-speculative market participants. Therefore, the government is advised to collect comprehensive data on the structure of the housing market, assess the share of speculative transactions, and adjust tax rates accordingly.
Moreover, since the transfer tax only applies to documented transactions, many informal or contract-based transactions—particularly those occurring prior to property completion—escape taxation. In such cases, builders may sell properties through promissory notes or undocumented agreements, which are difficult to track and tax. As a result, it is recommended that the government strengthen monitoring mechanisms for such transactions. This includes identifying and intercepting units exchanged informally or without official documentation to ensure both effective taxation and bubble control.
Volume 0, Issue 0 (Articles accepted for Publication 2024)
Abstract
Aim and Introduction
One of the most critical criteria for assessing the development of the digital economy is financial deepening. Most analysts agree that financial deepening can accelerate economic growth. Economic policy orientations are increasingly aligned with the objectives of financial deepening, underscoring its growing significance. The digital economy is characterized by its large scale, rapid development, and strong connectivity—factors that demand more accurate and efficient financial support.
Financial deepening refers to the multi-dimensional strategy for establishing a market-oriented, multi-level financial system to foster economic growth. This approach includes the expansion and development of financial markets, the creation of innovative financial products and services, the reform of financial institutions, and the strengthening of financial supervision. The digital economy today extends beyond the realms of electronics, communication, and information industries, and has deeply integrated with the traditional economy. It no longer represents merely a part of the economy but increasingly defines it as a whole. Given its potential for growth and high profitability, the digital economy and its associated industries require substantial financial support.
Financial deepening enhances the stock of liquid assets, expands financing channels, and directs capital flows toward competitive, high-yield digital sectors—thereby promoting their rapid development. Financial institutions are increasingly supporting emerging industries through targeted credit policies and are actively facilitating the digital transformation of traditional sectors. Furthermore, regional financial deepening improves the accessibility of financial intermediaries—such as banks and venture capital firms—to real-time corporate information. This reduces financing constraints, broadens financing channels, lowers capital costs, and provides firms with more diverse financial options.
For digital economy enterprises, financial deepening improves resource allocation efficiency through the integration of advanced technologies such as big data. It enables the effective investment of funds in critical areas of the digital economy, thereby fostering its development. As the digital economy expands, it becomes essential to manage the associated financial risks. Financial deepening addresses these concerns by reinforcing the financial market infrastructure, enhancing the regulatory environment, and adopting comprehensive risk management strategies to ensure the sector's sustainable and healthy growth.
Moreover, financial deepening spurs innovation in digital payment systems, digital currencies, financial technologies, and other related fields, resulting in more efficient and accessible financial services that underpin digital economy growth. Overall, financial deepening plays an important role in reducing financial constraints, enhancing resource allocation, managing financial risks, and providing vital financial services to support the robust and sustainable development of the digital economy.
Methodology
This study employs a random dynamic panel model using the Spatial Generalized Method of Moments—Dynamic Panel Data (SGMM-DPD-SDM) framework with two-stage Arellano-Bond estimation and random dynamic coefficients. To evaluate the effects of financial deepening, economic openness, government size, and economic growth on digital economy development in MENA countries, spatial econometric techniques are applied. In this model, the development of the digital economy is the key dependent variable.
The selection of explanatory variables—namely financial deepening, economic openness, government size, and economic growth—is grounded in theoretical foundations. The inclusion of the lagged dependent variable in the model introduces autocorrelation between the explanatory variables and the error term, violating one of the classical assumptions of panel models. Consequently, the use of ordinary least squares methods in fixed and random effects models would yield biased and inconsistent estimates. Therefore, dynamic panel data techniques are employed to ensure robustness.
Findings
The results indicate that financial deepening significantly enhances digital economy development. Additionally, its spatial effects reveal that financial deepening in one country positively influences neighboring countries. According to the spatial lag estimation, the digital development of a given country is affected by the weighted average of digital development levels in neighboring countries, with an estimated effect of 0.82.
The estimated coefficients for economic growth, government size, and economic openness are all positive and statistically significant, confirming their direct contribution to digital development. Moreover, these variables exhibit spatial spillover effects, further validating the presence of regional interdependencies. All spatial proximity-related variables are statistically significant, underscoring the importance of spatial and regional dynamics in understanding the influence of these factors on digital development.
Discussion and Conclusion
To promote financial deepening and foster the growth of the digital economy, the following recommendations are proposed based on the research findings:
Gradual reforms in the financial system should be pursued, with an emphasis on improving the efficiency and quality of financial services through the establishment of a sound regulatory framework. Strengthening the capacity of financial services for the real economy and encouraging traditional financial institutions to enhance their service offerings will ensure robust financial support. Simplifying approval processes for digital economy enterprises and lowering funding thresholds are also crucial for enabling the rapid development of this dynamic sector.
Encouraging innovation in financial products and services tailored to the needs of the digital economy—such as those based on e-commerce platforms and blockchain technologies—will drive further progress. Additionally, promoting direct financing through the gradual liberalization of capital markets and increasing their share in the financial system can significantly stimulate economic growth.
Welcoming foreign investment and facilitating the entry of international financial institutions will bring in much-needed capital and advanced financial technologies. These measures will not only enrich the financial ecosystem but also accelerate the digital transformation process across the MENA region
One of the most critical criteria for assessing the development of the digital economy is financial deepening. Most analysts agree that financial deepening can accelerate economic growth. Economic policy orientations are increasingly aligned with the objectives of financial deepening, underscoring its growing significance. The digital economy is characterized by its large scale, rapid development, and strong connectivity—factors that demand more accurate and efficient financial support.
Financial deepening refers to the multi-dimensional strategy for establishing a market-oriented, multi-level financial system to foster economic growth. This approach includes the expansion and development of financial markets, the creation of innovative financial products and services, the reform of financial institutions, and the strengthening of financial supervision. The digital economy today extends beyond the realms of electronics, communication, and information industries, and has deeply integrated with the traditional economy. It no longer represents merely a part of the economy but increasingly defines it as a whole. Given its potential for growth and high profitability, the digital economy and its associated industries require substantial financial support.
Financial deepening enhances the stock of liquid assets, expands financing channels, and directs capital flows toward competitive, high-yield digital sectors—thereby promoting their rapid development. Financial institutions are increasingly supporting emerging industries through targeted credit policies and are actively facilitating the digital transformation of traditional sectors. Furthermore, regional financial deepening improves the accessibility of financial intermediaries—such as banks and venture capital firms—to real-time corporate information. This reduces financing constraints, broadens financing channels, lowers capital costs, and provides firms with more diverse financial options.
For digital economy enterprises, financial deepening improves resource allocation efficiency through the integration of advanced technologies such as big data. It enables the effective investment of funds in critical areas of the digital economy, thereby fostering its development. As the digital economy expands, it becomes essential to manage the associated financial risks. Financial deepening addresses these concerns by reinforcing the financial market infrastructure, enhancing the regulatory environment, and adopting comprehensive risk management strategies to ensure the sector's sustainable and healthy growth.
Moreover, financial deepening spurs innovation in digital payment systems, digital currencies, financial technologies, and other related fields, resulting in more efficient and accessible financial services that underpin digital economy growth. Overall, financial deepening plays an important role in reducing financial constraints, enhancing resource allocation, managing financial risks, and providing vital financial services to support the robust and sustainable development of the digital economy.
Methodology
This study employs a random dynamic panel model using the Spatial Generalized Method of Moments—Dynamic Panel Data (SGMM-DPD-SDM) framework with two-stage Arellano-Bond estimation and random dynamic coefficients. To evaluate the effects of financial deepening, economic openness, government size, and economic growth on digital economy development in MENA countries, spatial econometric techniques are applied. In this model, the development of the digital economy is the key dependent variable.
The selection of explanatory variables—namely financial deepening, economic openness, government size, and economic growth—is grounded in theoretical foundations. The inclusion of the lagged dependent variable in the model introduces autocorrelation between the explanatory variables and the error term, violating one of the classical assumptions of panel models. Consequently, the use of ordinary least squares methods in fixed and random effects models would yield biased and inconsistent estimates. Therefore, dynamic panel data techniques are employed to ensure robustness.
Findings
The results indicate that financial deepening significantly enhances digital economy development. Additionally, its spatial effects reveal that financial deepening in one country positively influences neighboring countries. According to the spatial lag estimation, the digital development of a given country is affected by the weighted average of digital development levels in neighboring countries, with an estimated effect of 0.82.
The estimated coefficients for economic growth, government size, and economic openness are all positive and statistically significant, confirming their direct contribution to digital development. Moreover, these variables exhibit spatial spillover effects, further validating the presence of regional interdependencies. All spatial proximity-related variables are statistically significant, underscoring the importance of spatial and regional dynamics in understanding the influence of these factors on digital development.
Discussion and Conclusion
To promote financial deepening and foster the growth of the digital economy, the following recommendations are proposed based on the research findings:
Gradual reforms in the financial system should be pursued, with an emphasis on improving the efficiency and quality of financial services through the establishment of a sound regulatory framework. Strengthening the capacity of financial services for the real economy and encouraging traditional financial institutions to enhance their service offerings will ensure robust financial support. Simplifying approval processes for digital economy enterprises and lowering funding thresholds are also crucial for enabling the rapid development of this dynamic sector.
Encouraging innovation in financial products and services tailored to the needs of the digital economy—such as those based on e-commerce platforms and blockchain technologies—will drive further progress. Additionally, promoting direct financing through the gradual liberalization of capital markets and increasing their share in the financial system can significantly stimulate economic growth.
Welcoming foreign investment and facilitating the entry of international financial institutions will bring in much-needed capital and advanced financial technologies. These measures will not only enrich the financial ecosystem but also accelerate the digital transformation process across the MENA region
Volume 0, Issue 2 (8-2011)
Abstract
A bench scale aerobic sequencing batch reactor (SBR) was evaluated in terms of its potential to treat synthetic dairy wastewater. The 2-l plexiglass bioreactor was supplied with oxygen via a fine bubble air diffuser, fed with synthetic dairy wastewater under various operational conditions. To analyze the process, three significant independent variables — influent chemical oxygen demand (COD), mixed liquor volatile suspended solids (MLVSS), and aeration time — were assessed. Three dependent process and quality parameters (as process responses) were also evaluated: total COD removal efficiency, sludge volume index (SVI) and final pH. The experiments were based on a central composite design (CCD) and analyzed using response surface methodology (RSM). The treatment was limited to the following concentration regimes: COD (1000, 3000 and 5000 mg/l), MLVSS (3000, 5000 and 7000 mg/l) and aeration time (2, 10 and 18 h). Maximum COD removal efficiency (of 96.5%) was obtained for an influent with the following characteristics: CODin: 3000 mg/l, MLVSS 5000 mg/l, and aeration time of 18 h. The study demonstrated the capability of aerobic SBRs for high COD removal from dairy industrial wastewater. Easy operation, low cost, and minimal sludge bulking condition were some of advantages of the SBR system as an option for biological treatment of medium-strength industrial wastewater. The present study provides valuable information about relationships between quality and process parameters for different values of operating variables.
Volume 1, Issue 1 (3-2013)
Abstract
In order to determine effects of chicken and cattle manures in culture of Chlorococcum, an experiment was designed in six treatments including; 0.1, 0.4, 0.8 g/l of chicken manure and 0.1, 0.4, 0.8 g/l of cattle manure as completely randomize design with three replicates for 28 days. Results showed that the mean maximum density (87.1 × 105 cell/ml), specific growth rate (0.054 day-1), algal dry biomass (0.644 g/l), and chlorophyll a (9.42 mg/l) were obtained with 0.8 mg/l chicken manure. In order to compare performance of these manures with other culture media, second experiment with five treatments including; BBM (control) (Bold’s Basal Medium), BBM + soil extract, 0.8 g/l chicken manure, 0.8 g/l cattle manure and mixture of all treatment (BBM, BBM + soil extract, chicken manure and cattle manure) was designed as completely randomize design with three replicates for 15 days. Comparative results showed that BBM + soil extract had highest algal density (11.6 x 106 cells/ml), highest algal dry biomass (0.81 mg/ml), maximum SGR (0.13 /day), highest chlorophyll a (10.15 mg/l) and minimum doubling time (4.97 days). In conclusion, performance of BBM + soil extract was better in terms of biomass and growth parameters of Chlorococcum.