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Background: When managed effectively, oil wealth can drive economic development and improve wellbeing. Conversely, as has been the experience in Ogoniland in the Niger Delta, the presence of the oil industry can lead to environmental degradation and social and economic vulnerabilities with negative impacts on health and wellbeing. Few studies have explored the experiences and perceptions of these impacts among residents of host communities themselves. Methods: This qualitative study explored Ogoni residents' experiences and perceptions of oil-industry related economic exclusion and associated impacts on health and wellbeing. In-depth interviews with 22 participants from four Local Government Areas (LGAs) were analyzed with open (inductive) coding. Guided by constructivist philosophy, interpretation of emerging themes was informed by the concept of social exclusion which recognizes that multi-dimensional processes can deprive individuals or groups of resources, rights, goods, and services, thus limiting broader societal participation. Results: Findings highlight the exclusionary impacts of the oil industry at the intersection of i) damaged livelihoods and family income, that increased economic vulnerability and reduced participants' ability to meet basic needs including ability to pay for healthcare; ii) lack of progress on environmental remediation and non-transparent benefit sharing schemes that exacerbate economic displacement and contribute to ongoing exposures to air and water pollution; and iii) insufficient of investment in economic development and essential health services, limiting employment opportunities and ability to access adequate healthcare. Conclusion: Addressing these issues requires integrated policy interventions focusing on equitable resource distribution, environmental restoration, and inclusive economic development to promote sustainable community resilience. [ABSTRACT FROM AUTHOR]

Occupational accidents occur in many sectors in Türkiye every year. In this study, which aims to evaluate occupational accidents occurring in the oil sector, accident estimation was made using artificial neural networks. Data on 2210 work accidents that occurred between 2020 and 2023 in a company operating in the oil sector were used. In this study; Artificial neural network modeling was done with monthly accident data. In the study, Multilayer Perceptron Artificial Neural Networks (MLPANN) and Radial Basis Function Artificial Neural Networks (RBFANN), which are feed-forward networks, were used. 70% of the data is divided as training data and 30% as test data. As a result of the analysis; An 84.1% correct classification rate was obtained with the MLPANN method, and an 86.4% correct classification rate was obtained with the RBFANN method. It can be said that the RBFANN method performs more successfully than the MLPANN method. lt is suggested to use the methods in order to estimate the occupational accidents . [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The control room is a critical work environment where optimal performance is essential to minimize errors. Lighting is one of the key environmental factors influencing the performance of control room operators. Inadequate sleep quality and job stress also significantly impact job performance. Poor sleep quality, eye fatigue, inappropriate lighting, and occupational stress can lead to errors and decreased accuracy in work. Objectives: The present study aims to determine the correlation between lighting intensity, eye fatigue, occupational stress, and sleep quality among control room operators at the Abadan Refinery. The study was conducted in 2022. Methods: This cross-sectional descriptive-analytical study was conducted on 190 control room operators at the Abadan Refinery in 2022. A lux meter device was used to evaluate the intensity of lighting. Standard Pittsburgh sleep quality, eye fatigue, and Occupational Stress questionnaires were also administered. The results were analyzed using SPSS software. Results: The average light intensity of the work surface was 347.95 ± 147.34 lux. The mean and standard deviation of job stress score and sleep quality were 155.42 ± 9.18 and 9.38 ± 1.62, respectively. The average eye fatigue score was 5.09 ± 0.821 in people without glasses and 4.47 ± 0.828 in people with glasses. A significant correlation was found between brightness intensity and visual fatigue (ρ = 0.201, P = 0.029). The correlation between eye fatigue and sleep quality score was also significant (ρ = 0.225, P = 0.002). However, no significant correlation was observed between lighting intensity and sleep quality (ρ = - 0.005, P = 0.946). The correlation between the overall score of occupational stress and sleep quality was statistically significant (r = - 0.148, P = 0.042). Conclusions: The results showed a significant correlation between lighting intensity and the factors of sleep quality and eye fatigue. Additionally, there was a significant correlation between eye fatigue and sleep quality, as well as between occupational stress and sleep quality. Therefore, it is suggested that planning to minimize job stress, and improve lighting and sleep quality for gas refinery control room personnel should be designed and implemented by the authorities. [ABSTRACT FROM AUTHOR]

One of the main challenges in the treatment of industrial wastewater is the removal of oil-in-water emulsions, which are stable and therefore difficult to treat. Bacterial cellulose (BC) has structural characteristics that make it an ideal filtration membrane. Several research projects are underway to develop new materials, both biotechnological and traditional, for use in filter beds. The study examined the potential of a BC membrane filtration system for treating oily industrial wastewaters, an underexplored biomaterial in wastewater treatment. The results demonstrated that BC is highly effective at removing oily contaminants (~99%), reducing the colour and particulate matter of wastewater, as well as eliminating nearly the entire microbiological load (~99%). SEM, MEV, FTIR, XRD, and TGA confirmed the presence of oil in the interior of the membrane after filtration, characteristic peaks of its chemical composition, and a 40% reduction in crystallinity. TGA revealed an increase from three (pre-filtration) to five (post-filtration) stages of thermal degradation, indicating the retention of the contaminant in the BC. The mechanical tests demonstrated that the membrane has a tensile strength of 72.13 ± 8.22 MPa and tolerated elongation of up to 21.11 ± 4.81% prior to tearing. The BC membrane also exhibited excellent flexibility, as it could be folded >100 times at the same point without exhibiting signs of tearing. The BC surpasses traditional methods, such as activated charcoal and effluent treatment stations, in the removal of emulsified oils. The findings demonstrate that BC is promising for the treatment of industrial wastewaters, which is a field that requires continual technological innovations to mitigate the environmental impacts of the oil industry. [ABSTRACT FROM AUTHOR]

Abstract Background When managed effectively, oil wealth can drive economic development and improve wellbeing. Conversely, as has been the experience in Ogoniland in the Niger Delta, the presence of the oil industry can lead to environmental degradation and social and economic vulnerabilities with negative impacts on health and wellbeing. Few studies have explored the experiences and perceptions of these impacts among residents of host communities themselves. Methods This qualitative study explored Ogoni residents’ experiences and perceptions of oil-industry related economic exclusion and associated impacts on health and wellbeing. In-depth interviews with 22 participants from four Local Government Areas (LGAs) were analyzed with open (inductive) coding. Guided by constructivist philosophy, interpretation of emerging themes was informed by the concept of social exclusion which recognizes that multi-dimensional processes can deprive individuals or groups of resources, rights, goods, and services, thus limiting broader societal participation. Results Findings highlight the exclusionary impacts of the oil industry at the intersection of i) damaged livelihoods and family income, that increased economic vulnerability and reduced participants’ ability to meet basic needs including ability to pay for healthcare; ii) lack of progress on environmental remediation and non-transparent benefit sharing schemes that exacerbate economic displacement and contribute to ongoing exposures to air and water pollution; and iii) insufficient of investment in economic development and essential health services, limiting employment opportunities and ability to access adequate healthcare. Conclusion Addressing these issues requires integrated policy interventions focusing on equitable resource distribution, environmental restoration, and inclusive economic development to promote sustainable community resilience.

The relevance of the research is justified by the rapid development of the oil industry, which requires constant improvement of methods and equipment to increase extraction efficiency and reduce environmental impact. The aim of this study is to enhance the current engineering aspects of drilling in the Altyguyi field while considering increased productivity and reduced environmental impact. Among the methods used, it is necessary to mention the synthesis method, abstraction method, generalization method, induction method, deduction method, classification method, and others. This study examines the technological aspects of operating wells in the Altyguyi gas-condensate field. Extensive laboratory and industrial research on the properties and composition of oil, gas, and condensate was conducted to properly implement the dual completion technology for gas extraction from one formation and oil extraction from another formation in a single well. By implementing advanced drilling methods, including horizontal and multi-hole drilling, as well as using modern drilling fluids, it was possible to improve well productivity and reduce drilling time. As a result of technology optimization, the overall efficiency of the oil and gas extraction process in the field has been increased, confirming the significance of innovation implementation for improving results in the oil industry. These enhancements not only increased drilling safety and efficiency, but also reduced the negative impact on the environment, emphasizing the importance of integrating modern technologies with environmental considerations in the oil extraction process. This research makes a significant contribution to the development of more efficient and environmentally sustainable drilling methods in oil fields, contributing to increased oil extraction productivity and reduced environmental impact

Companies are increasingly leveraging their research and development (R&D) functions, utilizing the diverse knowledge dispersed across global networks of emerging and developed markets. This research stream emphasizes not only knowledge acquisition but also the utilization and development of new products. Knowledge and its components can play a fundamental role in the successful execution of R&D activities. This study aims to investigate the role of knowledge management components on R&D activities in the oil industry. Initially, a conceptual model and research hypotheses were developed through a review of the theoretical literature and previous studies. To test the research hypotheses, the statistical population consisted of managers and experts from an active company in the oil industry, numbering approximately 135 individuals. Based on Cochran's formula, the sample size was determined to be 100 individuals, and questionnaires were distributed among them. The questions in this questionnaire were adapted from reliable sources, and their validity and reliability were confirmed. Given the non-normal distribution of the data, Partial Least Squares (PLS) and SmartPLS 2 software were used for statistical analyses. Based on the significance values related to the hypotheses, all four were confirmed. The impact levels of knowledge creation, application, exchange, and retention on R&D activities were 0.884, 0.905, 0.748, and 0.625, respectively. Therefore, the most significant recommendation of this research is to focus on teamwork, where knowledge exchange occurs, fostering creativity and innovation, thereby enhancing the success of R&D activities. [ABSTRACT FROM AUTHOR]

The relevance of the research is justified by the rapid development of the oil industry, which requires constant improvement of methods and equipment to increase extraction efficiency and reduce environmental impact. The aim of this study is to enhance the current engineering aspects of drilling in the Altyguyi field while considering increased productivity and reduced environmental impact. Among the methods used, it is necessary to mention the synthesis method, abstraction method, generalization method, induction method, deduction method, classification method, and others. This study examines the technological aspects of operating wells in the Altyguyi gas-condensate field. Extensive laboratory and industrial research on the properties and composition of oil, gas, and condensate was conducted to properly implement the dual completion technology for gas extraction from one formation and oil extraction from another formation in a single well. By implementing advanced drilling methods, including horizontal and multi-hole drilling, as well as using modern drilling fluids, it was possible to improve well productivity and reduce drilling time. As a result of technology optimization, the overall efficiency of the oil and gas extraction process in the field has been increased, confirming the significance of innovation implementation for improving results in the oil industry. These enhancements not only increased drilling safety and efficiency, but also reduced the negative impact on the environment, emphasizing the importance of integrating modern technologies with environmental considerations in the oil extraction process. This research makes a significant contribution to the development of more efficient and environmentally sustainable drilling methods in oil fields, contributing to increased oil extraction productivity and reduced environmental impact. [ABSTRACT FROM AUTHOR]

General topic in this paper is the role of oil industry in global economy and the result of changing oil prices on economic variables in Azerbaijan. The major aim is to analyze the effects of crude oil price changes on Azerbaijan economy in order to measure how changes in oil prices affect its basic economic variables. At the beginning, a general outlook on oil industry will be given and the main oil exporting economies will be analized. However, main focus will be on the structure of Azerbaijan’s economy and it will examine the example of Azerbaijan as a transition economy where oil and gas production and exports have steadily increased from the mid ‘90s. Many critical oil and gas extraction projects have been implemented; while the oil and gas sector's dominance in the economy poses a number of threats to the balanced development of the country's economy. It will show how the economy of Azerbaijan was affected after the oil crisis, such as other developing countries that mainly depending on oil and petroleum products. For this purpose, VEC Model has been applied, consdering Azerbaijan Statistic Data and analized the effects of oil price fluctuations on its economic variables parallel with the oil industry. The main findings indicate that Azerbaijan's economy is strongly dependent on resource exports, which produce high growth rates when commodity prices are favorable, but end up with lower macroeconomic performance when global oil prices fall. It is clear that the main income of Azerbaijan comes from oil and oil products, so the export of oil will have a high impact on the saving level of the population. At the time of high revenues come from export and the low exchange rate of the foreign currency in Azerbaijan has also led to the low cost of imported goods. As well demonstrated in the research, Azerbaijan economy has been widely exposed to major crude oil price distortions. It can be said that in order to avoid increasing overdependence on oil earnings, diversifying the economy should be a top priority.

The production of petroleum substances has a long historical tradition in Iran. Glance (1970) reported that the "first man‐made oil well was dug" in the ancient city of Susa (present‐day Shush), about 40 km northwest of Ahwaz, in 500 BC during the reign of the Achaemenid emperor Darius I. Writing in the fifth century BC, Herodotus described petroleum production near a place called Ardericca, probably present‐day Masjed Soleyman, located 210 furlongs from Susa (Lees, 1950). The petroleum substances produced included bitumen which was used in construction and the waterproofing of ships. Sorkhabi (2005) detailed the petroleum history in Iran during ancient and medieval times. The modern quest for oil in Iran dates from the second half of the 19th century. From a historical perspective, this modern period can be divided into six distinct phases: (i) The early years, 1872–1900; (ii) The Anglo‐Persian years, 1901–1932; (iii) The Anglo‐Iranian Years and Nationalization, 1933–1953; (iv) The second Pahlavi years, 1954–1978 including the rise of OPEC; (v) The Islamic Revolution and Iran‐Iraq War, 1979–1989; and (vi) Buyback Contracts and US Sanctions, 1990–Present. The search for oil was singularly unsuccessful during the first of these phases and the early years of the second phase. However, after a difficult six‐year exploration campaign, oil in commercial quantities was struck in the early hours of 26 May, 1908 at Maidan‐e Naftun, which in later years achieved world fame as the Masjed Soleyman oil field. Since then, more than 120 oil and gas field discoveries have been made in Iran's onshore areas and its territorial waters in the Persian Gulf. The story of oil has always been an emotive and politically charged issue in Iran and has been the focus of great national interest and debate for over a century. Certainly, the discovery in 1908 marked a milestone in Iran's 20th century history: it ushered in a new era – an era not only of progress and prosperity, but also of social and political upheaval and turmoil that has not yet ended (Ala, 2007). In this paper, important events in each of the historical phases identified above are briefly reviewed. Emphasis is placed on the emergence of the modern petroleum industry in Iran, and the early phases are covered in particular detail. [ABSTRACT FROM AUTHOR]

This paper determines the impact of Brent oil shocks on the price of shares of companies from the oil, agricultural and food industries that includes the period of the COVID-19 pandemic. For this purpose, they use a quantile regression approach and compare its findings with a standard Ordinary Least Squares (OLS) regression model. Moreover, in this research they use quantile regression, which enables them to analyze different quantiles of share prices of companies from the oil industry, the agricultural industry, and the food industry. They observe three different periods - a period of recession, a normal period and a period of expansion. Finally, empirical evaluations using quantile regression and OLS models show us that shocks from the oil market are more pronounced in companies from the oil industry compared to companies from the agricultural and food industries. The findings of this research provide important information for investors, economic policy makers, and other parties. [ABSTRACT FROM AUTHOR]

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Digital technology can benefit the oil and gas sector by increasing hydrocarbon recovery, ensuring safety throughout the corporate ecosystem, and improving operational reliability. This study addresses the oil and gas supply chain digital transformation tendencies as well as the Norwegian petroleum refining company Equinor's initiatives. The main objective is to explore the opportunities for digitalisation in the oil and gas industry as well as the state of the industry's digital strategy more generally. The findings support the industry's major players continuing to invest in their collaborative ecosystem by partnering with their suppliers and start-ups and sharing with them a platform where data that can help them improve their economic position can easily be shared. It is recommended that they should develop a digital strategy roadmap, as in the case of Equinor, as a matter of priority. Supporting innovation and technology adoption through continued investment and the hiring of qualified experts is also of critical importance. It is also important to improve the digital skills of employees and spread a digital culture throughout the company so that they can protect themselves against future cyberattacks or other potential risks. On a global level, the successful implementation of a digital solution will reshape market dynamics (in terms of supply, demand, and investment) as well as the way energy networks are managed. [ABSTRACT FROM AUTHOR]

This analysis explores the complicated relationship between oil price fluctuations, the oil industry's finances, and the resulting increase or decrease in carbon emissions. Oil price changes have far-reaching effects on the global economy because of its dependence on fossil fuels; therefore, understanding these patterns is essential for effective policymaking and long-term energy planning. The study uses a dataset built from secondary data collected in China over 15 years, starting in 2008 and ending in 2022. This information comes from a wide range of authoritative places, including public records, trade journals, university studies, and the records of international organizations, and provides a solid foundation for study. Oil prices on a global and national scale, oil sector financial performance indicators (such as revenues, earnings, and investment levels), and carbon emission statistics are all significant factors under investigation. As one of the world's largest oil consumers, China has been singled out in this study to allow for a more comprehensive analysis of reactions within this crucial subset of the energy industry. To understand the complex interplay between oil price shocks, the financial dynamics of the oil sector, and carbon emissions, the research utilizes statistical and econometric methods, most notably time-series analysis and regression models. The results are meant to shed light on how oil price shocks consistently affect the monetary aspects of the oil business and, by extension, the patterns in carbon emissions. This study helps us understand these vital interrelationships more completely and nuancedly. [ABSTRACT FROM AUTHOR]

The paper presents data on the complex processing of large-tonnage waste from oil and gas industry and chemical production, as well the methods of their utilization and processing.The data was collected at the industrial sites of the plants in Western Kazakhstan.During the work, there were studied data on the chemical composition of the waste, properties of the experimental compositions, material structure, and peculiarities of the technological processes of recycling. When processing the data, there were used such physical-chemical and mechanical methods as X-ray structure, mass and IR spectroscopy, radiometric analysis of the experimental samples. The paper provides data on thermodynamic calculations for chemical reactions of interaction between components of the compositions.It is established that the reaction of interaction of petroleum sulphur with sludge monochromate in the production of polymer concrete significantly reduces their toxicity. On the basis of researching data on the composition and properties of wastes and semi-finished products evidence about the possibility to recycle them into goods with positive ecological and economic effect has been obtained.The given data on practical methods of complex processing and waste recycling (on the example of Western Kazakhstan), allow systematically solving the problem of solid waste management, realizing the basic ecological principle “waste to income” and may be suitable for similar enterprises in other developing countries.

This paper determines the impact of Brent oil shocks on the price of shares of companies from the oil, agricultural and food industries that includes the period of the COVID-19 pandemic. For this purpose, they use a quantile regression approach and compare its findings with a standard Ordinary Least Squares (OLS) regression model. Moreover, in this research they use quantile regression, which enables them to analyze different quantiles of share prices of companies from the oil industry, the agricultural industry, and the food industry. They observe three different periods - a period of recession, a normal period and a period of expansion. Finally, empirical evaluations using quantile regression and OLS models show us that shocks from the oil market are more pronounced in companies from the oil industry compared to companies from the agricultural and food industries. The findings of this research provide important information for investors, economic policy makers, and other parties.

The environmental, social, and economic challenges associated with the massive activities of the oil and gas industry require analysis and evaluation of companies' sustainability priorities. Evaluating the environmental performance of oil companies requires the application of strict mathematical tools and models that provide rigorous results. Multi-criteria decision-making (MCDM) is a rigorous tool that evaluates the performance and practices of oil and sustainable energy companies. However, classical multi-criteria decision analysis has problems related to inconsistency because of the subjective nature of pairwise comparisons. This study responded to the literature call by utilizing the weight fuzzy judgment method (WFJM) to determine the weight coefficients of criteria with zero consistency. Such a method employed criteria values and expert judgment for decision-making to create a bridge between the mathematical approach and the human approach. This study aims to develop a solid decision support system by evaluating and benchmarking 11 companies utilizing the fuzzy judgment method based on fuzzy theory and the VIekriterijumsko KOmpromisno Rangiranje (VIKOR) method to determine sustainability priorities for oil and gas companies. The oil companies' criteria were efficiently weighted by the fuzzy judgment method, and the organizational capabilities represented the greatest weight value of 0.128, whilst the low-weight criteria were the high costs of technologies at 0.080. Besides, the benchmarking results for oil companies revealed that COM 8 was the best, whilst COM 11 was the worst. The fuzzy judgment technique is a unique approach to solving complicated decision-making problems, and its influence can be significant. Furthermore, this method can be applied in sectors other than energy, including banking, medical services, and engineering, where decision-making is not straightforward and requires a systematic approach. [Display omitted] • We developed a novel method called the weight fuzzy judgment method (WJSM). • This study arised the decision matrix based on 9 main criteria and 11 alternatives. • This study evaluated oil and gas companies' sustainability behaviors. • A comparison analysis was conducted between WJSM and BWM methods. [ABSTRACT FROM AUTHOR]

Despite a multi-decade decrease in cardiovascular disease, geographic disparities have widened, with excess mortality concentrated within the United States (U.S.) South. Petroleum production and refining, a major contributor to climate change, is concentrated within the U.S. South and emits multiple classes of atherogenic pollutants. We investigated whether residential exposure to oil refineries could explain variation in self-reported coronary heart disease (CHD) prevalence among adults in southern states for the year 2018, where the majority of oil refinery activity occurs (Alabama, Mississippi, Louisiana, Arkansas, Texas, New Mexico, and Oklahoma). We examined census tract-level association between oil refineries and CHD prevalence. We used a double matching method to adjust for measured and unmeasured spatial confounders: one-to-n distance matching and one-to-one generalized propensity score matching. Exposure metrics were constructed based on proximity to refineries, activities of refineries, and wind speed/direction. For all census tracts within 10 km of refineries, self-reported CHD prevalence ranged from 1.2% to 17.6%. Compared to census tracts located at ≥5 km and <10 km, one standard deviation increase in the exposure within 5 km of refineries was associated with a 0.33 (95% confidence interval: 0.04, 0.63) percentage point increase in the prevalence. A total of 1119.0 (123.5, 2114.2) prevalent cases or 1.6% (0.2, 3.1) of CHD prevalence in areas within 5 km from refineries were potentially explained by exposure to oil refineries. At the census tract-level, the prevalence of CHD explained by exposure to oil refineries ranged from 0.02% (0.00, 0.05) to 47.4% (5.2, 89.5). Thus, although we cannot rule out potential confounding by other personal risk factors, CHD prevalence was found to be higher in populations living nearer to oil refineries, which may suggest that exposure to oil refineries can increase CHD risk, warranting further investigation. • Association of oil refineries with coronary heart disease (CHD) was examined. • We found positive association in seven states of the southern U.S. • The prevalence of CHD explained ranged from 0.02% to 47.4%. • Residents living nearer to oil refineries may have a higher risk of CHD. • Oil refineries may explain small area variation in the risk of CHD. [ABSTRACT FROM AUTHOR]

With the increase of environmental concerns in recent years and the prevalence of such issues, which originate mainly from large industries and manufacturing plants, green supply chain management (GSCM) issues have been given special attention among researchers. GSCM is a group of management applications integrating supply chain management with criteria related to environment and supplier selection with the purpose of reducing environmental pollution caused by processes involved in a company supply chain. In this research the main contributions is to draw a decision-making structure addressing the applicability of the green supplier selection (GSS) and order allocation (OA) problem in an Iranian Oil refinery company. A combination of Cloud-PROMETHEE along with using GBWM was taken into account for GSS as the first phase and MCGP method for OA as the second phase, in order to solve the GSSOA problem. The proposed technique lets the vagueness and uncertainty of experts' judgments be obtained by assisting uncertain linguistic variable derived from the cloud model. Furthermore, the group best-worst method (GBWM) obtains the optimal criteria weights by forming a nonlinear programing model and the prioritizing of nominated suppliers is established using the PROMETHEE method with the possibility to pick a distinct preference function for each criterion and draw a graph of supplier preferences. At last, MCGP method was applied considering with the possibility of multi-choice aspiration levels (MCAL) for each goal. The suggested model illustrated with actual figures in an oil refinery to provide insight to decision-makers of green supplier selection and order allocation. To do so, initially nine criteria have been derived after vast research on literature and experts' opinions. Then the suppliers was successfully evaluated with considering uncertainties and randomness in a group of decision maker judgments. The order allocation was also completed by minimizing total cost and delays and maximizing purchase using results of supplier ranking in the first phase. Results have shown that the supplier with better ranking in GSS is preferred in allocating orders. A sensitivity analysis then performed and confirmed that the suggested method is highly stable against different changes in the data. The proposed method was also compared with the basic MCGDM cloud model and the method is approved. Finally, managerial implications and conclusions for additional researches are demonstrated. • A novel MADM model entitled CLOUD-PROMETHEE model is introduced. • This model is a combination of uncertainty concerns and MADM methods. • A real study in an Oil refinery was solved and numerical data was provided. • Uncertain linguistic variables were utilized in data collection from experts. • Sensitivity analysis was conducted to illustrate the applicability of model. [ABSTRACT FROM AUTHOR]

The growing global awareness of social and environmental issues has led investors to prioritize sustainable investments. This study examines the relationship between ten Islamic and conventional sector indices, which include stocks screened for environmental, social, and governance (ESG) factors, across three energy-related fields: renewable energy, energy efficiency, and oil equipment and services. Using a quantile cross-spectral approach, this research finds a high level of long-term synchronization among all energy-related sectors and indices. However, as markets shift from bearish to bullish, the current relationship between energy-related sectors and Islamic and conventional indices weakens. To support the findings in this research and investigate potential financial implications, this investigation applies a causality-in-quantiles approach. The research in this study shows a bidirectional causal relationship between conventional and Islamic indices, particularly in the energy efficiency sector during bearish market conditions. At lower tails, ESG market indices are found to cause renewable energy products, suggesting a hedging mechanism. The findings of this study assert that investments that do not possess any ESG shortcomings are imperative for effectively bolstering renewable energy companies and fostering opportunities for energy efficiency. These conclusions hold considerable ramifications for energy policymakers as they strive to devise more robust financial mechanisms that can provide substantial support to the burgeoning green sector. [Display omitted] • Nexus of three heterogenous energy-connected areas and sectoral investments studied. • Considerable dependence of budding health care-related investments on renewables. • Distinguished coherence of conventional financials stocks on all energy companies. • The renewable energy sector could benefit from ESG investments. • Shariah indices are more associated with renewables industries. [ABSTRACT FROM AUTHOR]