Energy Economy
Sabah mohammed ridha Faisal; Taghi Ebrahimi salari; Mozhgan Bahmani
Abstract
Renewable energies play an important role in converting clean energy and reducing carbon emissions. Therefore, it is necessary to understand the trends and factors affecting the distribution of renewable energies and inequality between countries. Therefore, the aim of the current research is to compare ...
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Renewable energies play an important role in converting clean energy and reducing carbon emissions. Therefore, it is necessary to understand the trends and factors affecting the distribution of renewable energies and inequality between countries. Therefore, the aim of the current research is to compare the factors affecting the consumption of renewable energy in industrialized and developing societies with the new approach of panel momentary quantile regression (MMQREG) during the period of 1990-2022. The results showed that different factors have different effects on the development of clean energy in developed and developing countries. The results show that energy consumption, financial development, and carbon emissions reduce the consumption of renewable energy in developed countries. While energy consumption and financial development help the development of clean energy in developing countries. However, economic growth increases the development of clean energy in developed countries, but in developing countries, it causes a decrease in the development of green energy. In addition, the results showed that increasing globalization increases the consumption of green energy in both groups of countries. Therefore, in order to achieve the goals of carbon neutrality and sustainable development, the authorities of developed and developing countries should consider factors appropriate to each society for the development of clean energy.
Energy Economy
Meysam Pashayi; saleh Ghavidel Doostkouei; Masoud Sofimajidpour; Mahmood Mahmoodzadeh
Abstract
This study aims to analyze the growth trajectory of artificial intelligence (AI) technology and assess its impact on energy consumption in the United States, with the intention of deriving implications for Iran. To measure the level of AI development, two proxy indicators were employed: the number of ...
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This study aims to analyze the growth trajectory of artificial intelligence (AI) technology and assess its impact on energy consumption in the United States, with the intention of deriving implications for Iran. To measure the level of AI development, two proxy indicators were employed: the number of AI-related patents and the share of AI patents in total registered patents. A logistic growth function was used to model the technology growth, given its suitability for describing saturating growth patterns. The findings indicate that both indicators exhibit rapid growth, with the midpoint of growth estimated to occur in 2024 for both cases. The saturation level for the number of patents is projected around 2050, while the saturation for the share of AI patents is anticipated by 2060. Subsequently, using two forecasting scenarios, the impact of AI growth on energy consumption was examined. The results of energy demand modeling, using a structural time series model, reveal that AI-related variables have a positive and significant effect on energy consumption. These findings offer valuable insights for AI investment strategies in Iran and highlight that the expansion of data centers and related infrastructure—currently in its early stages in Iran—could substantially increase energy demand.
Energy Economy
Meysam Pashaee; Masoud Soufimajidpour; saleh Ghavidel Doostkouei; Mahmood Mahmoodzadeh
Abstract
This study examines the impact of artificial intelligence on energy consumption and carbon dioxide emissions in the United States over the period 1976 to 2020. Given the potential for nonlinear relationships and varying effects of artificial intelligence under different economic conditions, a Smooth ...
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This study examines the impact of artificial intelligence on energy consumption and carbon dioxide emissions in the United States over the period 1976 to 2020. Given the potential for nonlinear relationships and varying effects of artificial intelligence under different economic conditions, a Smooth Transition Regression model with a logistic transition function (LSTR) was employed. In this model, the degree of economic openness is considered as a threshold variable to investigate whether the effect of artificial intelligence on environmental variables differs across various levels of economic openness. The estimation results indicate that the relationship between artificial intelligence and both energy consumption and carbon dioxide is threshold-dependent and contingent on economic openness. At the threshold level of openness (approximately 23%), a significant change in the intensity of the effect is observed. In particular, when the degree of economic openness exceeds this level, artificial intelligence has a decreasing effect on carbon dioxide emissions, while its effect on energy consumption initially increases and then tends to stabilize. These findings suggest that integration into the global economy and trade openness can act as mediators in the impact of new technologies. Additionally, control variables such as per capita income and urbanization have significant positive effects on increasing energy consumption and pollution. Based on these results, it is recommended that policymakers, in promoting artificial intelligence development, take economic openness into account and simultaneously focus on advancing clean technologies, technology transfer, and smart environmental policies.
Energy Economy
amirreza alborz; mahmood ahmadisharif; mahmood hashemi
Abstract
1- INTRODUCTIONOil and natural energies are important tools in global economic financial policies and the process based on income generation and progress based on it. In this context, oil and oil derivatives play a fundamental role in the economic infrastructure of countries that produce this precious ...
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1- INTRODUCTIONOil and natural energies are important tools in global economic financial policies and the process based on income generation and progress based on it. In this context, oil and oil derivatives play a fundamental role in the economic infrastructure of countries that produce this precious substance. Iran's economy has been mainly based on oil since many years ago, especially from the 1350s onwards. In Iran, first of all, as an energy source, oil has evolved the life and economy of the country's people and caused economic growth and development, secondly, the income from oil has led to advancement and progress in all economic and social pillars. In other words, oil has been the factor of national prestige and the driving engine of economic, social and cultural growth and development of the country. 2- THEORETICAL FRAMEWORKThe issue of changes in the business model and adaptation to the current market conditions is a fundamental and vital issue, and blockchain is an up-to-date structure in various businesses; It is in different sizes and in different patterns. Blockchain is a data distribution of database based on the community of millions of sharing points, in which data is recorded and modified simultaneously, which can be used by using this open, free and at the same time complex platform. Dealing with financial, scientific and information exchanges. blockchain technology can be considered a network that has a function like a database, but is not centralized and is not controlled by an institution or organization. The information stored in the blockchain has some differences with the information stored in the database. Information in the blockchain is stored in blocks. This information can be anything and is not limited to transactions. Each block has a "hash" in addition to the information stored in it. Hash is a set of characters that special algorithms are used to create. 3- METHODOLOGYIn the petroleum industry, blockchains are shared or distributed data structures that can securely store digital transactions without using a central point. Most importantly, blockchain enables the automatic execution of smart contracts in peer-to-peer (P2P) networks. They can be thought of as databases that allow multiple users to make changes to the ledger simultaneously, which can lead to multiple versions of the chain. Instead of the ledger being managed by a trusted center, each individual network member has a copy of the chain of records and agrees on the valid state of the ledger. The precise method of achieving consensus is an ongoing area of research and may vary across a wide range of application domains. New transactions are cryptographically linked to previous transactions, which makes blockchain networks flexible and secure. Each network user can self-check whether transactions are valid, which provides transparency and reliable, tamper-proof records. 4- RESULTS & DISCUSSIONThe purpose of this research is to identify the international trade structures of oil derivatives using blockchain technology. In this regard, first by reviewing the verbal evidence of the research and identifying the concepts, we proceed to the open coding process, then the components of the axial coding paradigm including causal conditions, main phenomenon, strategies, background, intervening conditions and consequences are separated and based on categories. Subsets are proposed and finally linked according to selective coding.First, in open coding, the data are broken into separate parts, carefully examined to obtain similarities and differences, and questions about the phenomena that the data indicate. , are raised. Open coding is a part of the analysis that clearly deals with the naming (conceptualization) and categorization of the phenomena through careful examination of the data. Therefore, it can be said that there are two main steps in open coding, which are: conceptualization and categorization. 5- CONCLUSIONS & SUGGESTIONSThe investigation showed that the causal conditions include the complexity of the industry - ambiguity and uncertainty in situations, rapid technological developments - integration of technologically oriented companies with companies in this industry - changing competition conditions – necessi,ty and strategic importance.The central phenomenon includes the use of blockchain technology in international trade (petroleum derivatives), market monitoring, competitors monitoring, industry monitoring, company monitoring, document and law monitoring, creating an intelligent information system, industry interactions and exchanges, insurance matters and work contracts.Background conditions include national conditions (growth of social awareness in the oil and gas industry, domestic capacity and capabilities of the country), international conditions (imitating similar successful fields, forming a consortium to join technologies similar), organizational conditions (structural dimensions - globalization culture, technological culture, awareness). Intervention conditions include internal organizational conditions (structural factors - managerial factors - individual factors) and external conditions (economic conditions - political conditions).
