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This study aims to identify the trend in the financial performance of renewable energy companies and to outline the renewable energy policies impacting their performance. The study is conducted on major renewable energy companies of India and US for the study period of 2015-2019. The financial performance of these companies is analyzed by using ret...
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... They concluded that algorithms can be used to predict stock prices based on their coefficients of determination [72]. Rastogi et al. (2020) used machine learning techniques to analyze the trend in the financial performance of large renewable energy companies in India and the United States using return on equity (ROE). As a result of the study, it was concluded that the performance of companies in the renewable sector is largely affected by government policies [73]. ...
... Rastogi et al. (2020) used machine learning techniques to analyze the trend in the financial performance of large renewable energy companies in India and the United States using return on equity (ROE). As a result of the study, it was concluded that the performance of companies in the renewable sector is largely affected by government policies [73]. ...
Energy has been a key driver of change globally. As a developing country, Türkiye's increasing energy demand and consumption highlight the growing importance of efficient and sustainable energy management for its future. This study aims to determine the variables of the financial performance of 12 energy companies. Three different models are created with the return on assets, return on equity, and net profit margin as financial performance indicators of 12 firms. 12 financial ratios are used as input variables as determinants of financial performance. In the analysis, 37 quarterly data between 2014Q4-2023Q4 are used as the sample period. In machine learning, 17 different algorithms are considered in the selection of the appropriate model. The findings indicate that the Bagged Tree algorithm achieved successful outcomes for the ROA target variable, the Boosted Tree model demonstrated effective performance for the ROE model, and the Linear SVM algorithm yielded favorable results for the NPM model. According to the result obtained by the LIME method, Liquidity Ratio and Cash Ratio affect the ROA, ROE, and NPM models positively, while inventory turnover affects the models negatively.
... Renewable energy is often referred to as "classical" Renewable Energy Sources (RES) which are generated from such sources as wind power, solar energy, and waterpower but in daily life, some products have the potential to be used as renewable energy are consumed within the manufacturing sector as long as there is a component with high energy potential and through the recycling process they could be used as a source of "renewable energy (Petronijevic et al., 2020). The motivation behind the switch to alternative sources of energy such as renewable energy is majorly the environmental crises all over the world such as the exhaustion of fossil fuels, global warming, and pollution-driven numerous health hazards (Rastogi et al., 2020). ...
The present paper investigates the impact of Green Manufacturing Practices (GMP) on the Learning and Growth (LGE) of consumer goods manufacturing companies listed in Nigeria. The study utilized Green Product Design (GPD), Green Supply Chain Management (GSM), Green Efficient Processes (GEP), Green Renewable Energy (GRE), and End-of-life Product Management (EPM) as constructs for green manufacturing practices on learning and growth efficiency of consumer goods manufacturing companies listed in Nigeria. A survey research design was adopted for this study the consumer goods manufacturing companies listed in Nigeria made up the population of this study. The sample size of 228 was determined using Taro Yamane’s formula and randomly selected. A 5-point Likert Scale questionnaire was employed for data collection. The validity of the instrument of data collected was premised on the vast experience of the managers and the reliability of the data was done using the Cronbach Alpha Coefficient Technique which produced between 0.767 and 0.966 results. Statistical Package for Social Sciences (SPSS) version 22.0 was used to analyze and test the multiple regression. Descriptive and inferential (multiple regression) statistics were used to analyze the data at a 5% significance level. The findings indicate that green manufacturing practices variables (GPD, GSM, GEP, GRE, and EPM) had a positive significant effect on learning and growth efficiency (Adj.R2 = 0.440, F(6,217) = 35.001, p < 0.05) indicating that a unit increase in GMPs will enhance the LGE of consumer goods manufacturing companies listed in Nigeria. These findings should be of major interest to the Management of the consumer goods manufacturing companies listed in Nigeria. They suggest that they need to make informed strategic decisions about green initiatives and prioritize investments in them, while Government policymakers develop or refine regulatory frameworks that encourage green manufacturing practices in the manufacturing industry. This investigation provides original empirical evidence on the effect of green manufacturing practices on the learning and growth efficiency of consumer goods manufacturing companies listed in Nigeria.
... These investments facilitate India's shift towards clean energy, curbing carbon emissions and fostering rural employment. Emerging as a key player in India's renewable energy sector, Greenko entices investors eyeing sustainable ventures with promising growth prospects (Rastogi et al., 2020). ...
Sustainable finance and investment (SFI) have risen in prominence due to growing environmental concerns and heightened societal awareness. This study examines the shift from conventional financial models to SFI, with a focus on integrating environmental, social, and governance (ESG) factors into investment decisions. Conducting an extensive literature review, the research explores the core principles, methodologies, and impacts of SFI compared to traditional finance. Using qualitative research methods, it analyzes financial sector concepts, theories, and practical applications drawing from secondary data sources such as academic literature and reputable online platforms. The goals of this study encompass comprehending how ESG factors influence SFI strategies, assessing the related advantages and obstacles, examining empirical data, and pinpointing future research paths. The study's findings contrast traditional finance with SFI across several dimensions, encompassing focus, decision criteria, risk management, long-term outlook, and investment offerings. The study highlights how sustainable finance plays a crucial role in promoting economic growth, preserving the environment, and enhancing social welfare. Ultimately, this research emphasizes the pivotal role of SFI in shaping a more resilient, equitable, and sustainable future for financial markets and society as a whole.
... Through joint operations, organizations can gain a strategic competitive advantage. This is possible because collaboration provides enterprises with both tangible and intangible benefits by allowing knowledge and resources to be shared (Jha and Singh 2019;Rastogi et al. 2020). Supply-chain partners must focus on various elements to ensure performance (Hassan et al. 2019;Sahebi et al. 2019). ...
... Many researchers have looked at both qualitative and quantitative measures of SC performance. Efficiency, flexibility, responsiveness, and quality are four major RESC performance categories researchers suggest (Abidi et al. 2020;Maestrini et al. 2017;R. Rastogi et al. 2020;Um et al. 2017). According to (Athari and Ardehali 2016), supply chain efficiency/effectiveness are essential criteria to include in the performance measurement framework. (Fernando et al. 2018) Included ''agility'' as a specific criterion for evaluating RESC performance. Coordinated supply chain activities among supply chain partners im ...
... According to the above content, a comprehensive literature review helped identify unique properties of RESC, such as agility (Aseffe et al. 2021;Wee et al. 2012), sustainability (Manning & Soon 2016), quality & safety (Herrera et al. 2020;Wee et al. 2012), consumer service and investments (R. Rastogi et al. 2020;Tsai & Tung 2017), supply chain efficiency (Mustikaningsih 2019), and coordination among the partners of chain (Mustikaningsih 2019;Sarkar & Seo 2021) as main criteria of RESC performance. Table 3 summarizes the RESC's performance assessment criteria. ...
Any renewable energy supply chain's (RESC) performance measurement system comprises complex interconnected indicators. Hence, this research aims to propose an integrated RESC performance measurement framework containing all the performance measurement criteria and their indicators. This study identified six critical performance criteria through a combined expert opinion and literature review. RESC performance criteria and indicators are prioritized herein using the neutrosophic enhanced best-worst method (NE-BWM) that considers decision-makers (DM) opinions' confidence rating levels. The top five indicators, i.e., ''supply chain management cost,'' ''energy quality to consumers,'' ''reverse logistics,'' ''product quality,'' and ''information sharing,'' and three critical performance criteria, i.e., ''quality,'' ''supply chain efficiency,'' and ''service to the customer,'' were identified. Findings point to the need for proper coordination/collaboration among RESC partners. Information sharing is a critical component of improving supply chain coordination/collaboration. Experts' subjective inputs in demography are a significant limitation of this study. The NE-BWM results proposed that the top 10 indicators provided 90% of the weightage. According to this accuracy, the primary contribution of the research is the presentation of a comprehensive framework that will help to make the current RESC of emerging economics.
... Through joint operations, organizations can gain a strategic competitive advantage. This is possible because collaboration provides enterprises with both tangible and intangible benefits by allowing knowledge and resources to be shared (Jha and Singh 2019;Rastogi et al. 2020). Supply-chain partners must focus on various elements to ensure performance (Hassan et al. 2019;Sahebi et al. 2019). ...
... Many researchers have looked at both qualitative and quantitative measures of SC performance. Efficiency, flexibility, responsiveness, and quality are four major RESC performance categories researchers suggest (Abidi et al. 2020;Maestrini et al. 2017;R. Rastogi et al. 2020;Um et al. 2017). According to (Athari and Ardehali 2016), supply chain efficiency/effectiveness are essential criteria to include in the performance measurement framework. (Fernando et al. 2018) Included ''agility'' as a specific criterion for evaluating RESC performance. Coordinated supply chain activities among supply chain partners im ...
... According to the above content, a comprehensive literature review helped identify unique properties of RESC, such as agility (Aseffe et al. 2021;Wee et al. 2012), sustainability (Manning & Soon 2016), quality & safety (Herrera et al. 2020;Wee et al. 2012), consumer service and investments (R. Rastogi et al. 2020;Tsai & Tung 2017), supply chain efficiency (Mustikaningsih 2019), and coordination among the partners of chain (Mustikaningsih 2019;Sarkar & Seo 2021) as main criteria of RESC performance. Table 3 summarizes the RESC's performance assessment criteria. ...
Any renewable energy supply chain's (RESC) performance measurement system comprises complex interconnected indicators. Hence, this research aims to propose an integrated RESC performance measurement framework containing all the performance measurement criteria and their indicators. This study identified six critical performance criteria through a combined expert opinion and literature review. RESC performance criteria and indicators are prioritized herein using the neutrosophic enhanced best-worst method (NE-BWM) that considers decision-makers (DM) opinions' confidence rating levels. The top five indicators, i.e., ''supply chain management cost,'' ''energy quality to consumers,'' ''reverse logistics,'' ''product quality,'' and ''information sharing,'' and three critical performance criteria, i.e., ''quality,'' ''supply chain efficiency,'' and ''service to the customer,'' were identified. Findings point to the need for proper coordination/collabo-ration among RESC partners. Information sharing is a critical component of improving supply chain coordination/col-laboration. Experts' subjective inputs in demography are a significant limitation of this study. The NE-BWM results proposed that the top 10 indicators provided 90% of the weightage. According to this accuracy, the primary contribution of the research is the presentation of a comprehensive framework that will help to make the current RESC of emerging economics.
... The importance of renewable energy rest in addressing global clean energy (Lowitzsch et al., 2020;Yan et al., 2020) and environmental challenges (Zafar et al., 2020;Yan et al., 2020). The existing literature on renewable energy has focused on diverse but salient research areas like the convergence of renewable energy (Bhattacharya et al., 2018;Saba and Ngepah, 2022), adoption of renewable energy technologies (Makki and Mosly, 2020), impact on firm performance (Rastogi et al., 2020), renewable energy development (Huang and Liu, 2017;Gómez-Muñoz and Porta-Gándara, 2002), etc. The different nations have made efforts and policies related to energy conservation and clean energy and, as a result, have gained different levels of outcome (Bhattacharya et al., 2018;Makki and Mosly, 2020). ...
... The fourth contribution of the work lies in applying gap statistic as a robust method to form clusters. The papers (Gómez-Muñoz and Porta-Gándara, 2002;Rastogi et al., 2020) apply the Elbow method for clustering, which only calculates the Euclidean distance; the silhouette method that provides the average linkage without considering the variance, maximum and minimum differences, etc. However, the gap statistic does not average out the function, retains the k-means function, and compares the intra-cluster variations for different k levels. ...
... Considering firm-level studies, firms practicing sustainable development and endeavoring climate change strategies are achieving far better accounting performance than non-practicing firms (Michalisin and Stinchfield, 2010). Rastogi et al. (2020) uncover that net profit margin is the important driving factor of return on equity in Indian renewable energy companies, while no specific single driver for the United States renewable energy companies. ...
The study explores the resemblance of the countries based on renewable energy consumption (% of total energy consumption). A simplistic clustering approach is applied to implement the segmentation using the gap statistic method. The paper deals with the comparability of countries from the perspective of income level and geographical distribution. The clustering-based results reveal that the values of most mean clusters representing major economies have deteriorated over the past few years. The High and Upper-middle income countries are found to be not following sustainable practices, while Low and Lower-middle income countries are relying much on renewable energy consumption. The outcome is also presented as clusters for geographical distribution and a cross-section distribution of Income level-Region for all economies sampled. The study may assist in policy-making in the wake of the global clean energy transition.
... This is one of the most widely used unsupervised machine learning algorithms and can be implemented using different software (KNIME, MATLAB Spectral, Python, R, etc.). This type of analysis has already been used in the field of industry, e.g., Gkotsis et al. (2018) and Rastogui et al. (2020). The k-means 2 cluster analysis technique 3 is a multivariate technique that groups the cases of a data set (variables) according to the similarities between them. ...
Business innovation is fundamental for sustained economic growth at the regional level. Knowing the common characteristics of innovative companies and their location is essential to carry out appropriate economic policies. To this end, we have carried out a double analysis: one grouping of companies according to characteristics and another by geolocation. This study focused on one of Spain’s 17 autonomous communities, the Comunitat Valenciana, a region characterised by significant industrial diversity. Our results show, among other things, that size is not a differentiating factor when it comes to innovation, and that there is a positive relationship between physical clustering and productivity.
... The most common types of climate investments are in sustainable agriculture, sustainable transportation, energy efficiency, and renewable energy (Mahat et al., 2019). Investments in renewable energy, including solar and wind power, have been proven to perform well with low risk (Rastogi et al., 2020). Energy efficiency investments, such as building retrofits, have also been found to have strong performance and low risk (Mikulić et al., 2021). ...
This research article seeks to provide a comprehensive review of climate investing and anticipated future developments by using bibliometric study. Climate investing is a well-researched subject of study, and the massive increase in publications in recent years indicate the breadth and depth of the topic. Affiliation statistics show that the majority of research is centered in the USA, Australia and the UK, offering up new possibilities for climate investing research in developing countries. The authors examined 1091 articles related to climate investing from the Scopus database since 1971, using the bibliometric review technique to provide numerous viewpoints from previous climate investing studies associated with carbon offsetting, green bonds, impact investing, sustainable stock indices, climate-themed funds, ESG screening, divestment from fossil fuels, climate-aligned funds, and climate-smart agribusiness and suggests future study directions. This research may be helpful to policy makers, particularly those from developing nations, in understanding the challenges of climate investing.
... Changes in government regulation and collective bargaining policy have emerged as common factors that determine the future of the company. Tariff rates and policies for renewable energy companies must be designed to encourage companies to increase their investment in clean energy production (Rastogi et al., 2020). ...
The aim of this research is to analyze the differences in the performance of renewable energy companies before and after the Initial Public Offering (IPO). This research uses Paired Sample T-test as a data analysis method. The population in this study is a renewable energy company that conducts an IPO on the Indonesia Stock Exchange with a total of 3 companies. The sampling technique in this study uses purposive sampling and gets 2 samples. The results of this research indicate that there is no significant difference in the performance of renewable energy companies before and after the IPO. This could be due to the high initial investment costs in the renewable energy industry, the Government's low attention and utilization of renewable energy and the quality of management. Keywords: Renewable Energy Companies; Performance; Initial Public Offering.
... In this context, for green energy investment companies that want to prefer this method to focus on cost efficiency would be appropriate. The importance of financial effectiveness for developing green energy investment projects was emphasized in the literature by different researchers (Schabek 2020;Rastogi et al. 2020). ...
The purpose of this study is to provide a hybrid group decision-making approach to evaluate fintech-based financial alternatives for green energy investment projects. First, the multidimensional factors of due diligence for fintech-based financing alternatives of green energy investment projects are identified. In this regard, the balanced scorecard perspectives are considered. Next, consensus-based group decision-making analysis is performed. Second, impact-relation directions for fintech-based financing alternatives of green energy investment projects are defined. For this purpose, the spherical fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is applied. The novelty of this study is its proposal of a new outlook to due diligence of fintech-project financing for renewable energy investments by using the group and integrated decision-making approaches with spherical fuzzy DEMATEL. The findings indicate that customer expectations are the most essential factor for the revenue sharing and rewarding models. Additionally, this study identified that organizational competency plays the most important role with respect to the peer-to-business debt model. In contrast, the conclusion was reached that financial returns have the greatest importance for the equity sharing model.
