Abstract:PurposeThe successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex… Show more
“…This could be due to the high initial investment and benefits over an extended period. The result parallels the earlier study of (Guru et al, 2023; Kapoor et al, 2014; Tapaninen et al, 2009), where OBS does not influence the usage of sustainable energy technology. Kapoor et al (2014), (Khan et al (2022) reviewed the literature systematically on innovation attributes of DOI theory and found that OBS does not influence solar energy adoption.…”
Section: Resultssupporting
confidence: 90%
“…This could be due to the high initial investment and benefits over an extended period. The result parallels the earlier study of (Guru et al, 2023;Tapaninen et al, 2009),…”
Environmental deterioration and climate change are the key issues nowadays that hinder sustainable development, and the consumption of fossil fuel‐based energy sources significantly contributes to the issues. To achieve Sustainable Development Goal‐7 concerning sustainable and clean energy development, deploying non‐conventional energy sources is crucial. Solar energy is considered a significantly clean and sustainable energy source among renewable energy sources. Therefore, the present study attempted to investigate the key factors affecting the adoption of non‐residential Rooftop Solar Photovoltaic (RSPV) systems in Chandigarh, India. The researchers used a descriptive research design to examine the current phenomena. The current study is premised on the perceptions of the users of the non‐residential RSPV system. The data was acquired through a self‐administered survey questionnaire. A complete response from 207 participants was used for analysis purposes. The researchers have used the Partial Least Square‐Structural Equation Modeling strategy to estimate measurement and structural models. The study found that nodal agencies and environmental organizations are crucial in disseminating information and motivations concerning RSPV adoption. The study revealed that the environmental concerns of the users, compatibility, environmental benefits, the immediacy of reward, and trialability were found to be significant drivers of the diffusion and adoption of non‐residential RSPV systems. The study concluded that a paucity of financial incentives and high upfront expenses had been significant blockades to the diffusion and adoption of non‐residential RSPV.
“…This could be due to the high initial investment and benefits over an extended period. The result parallels the earlier study of (Guru et al, 2023; Kapoor et al, 2014; Tapaninen et al, 2009), where OBS does not influence the usage of sustainable energy technology. Kapoor et al (2014), (Khan et al (2022) reviewed the literature systematically on innovation attributes of DOI theory and found that OBS does not influence solar energy adoption.…”
Section: Resultssupporting
confidence: 90%
“…This could be due to the high initial investment and benefits over an extended period. The result parallels the earlier study of (Guru et al, 2023;Tapaninen et al, 2009),…”
Environmental deterioration and climate change are the key issues nowadays that hinder sustainable development, and the consumption of fossil fuel‐based energy sources significantly contributes to the issues. To achieve Sustainable Development Goal‐7 concerning sustainable and clean energy development, deploying non‐conventional energy sources is crucial. Solar energy is considered a significantly clean and sustainable energy source among renewable energy sources. Therefore, the present study attempted to investigate the key factors affecting the adoption of non‐residential Rooftop Solar Photovoltaic (RSPV) systems in Chandigarh, India. The researchers used a descriptive research design to examine the current phenomena. The current study is premised on the perceptions of the users of the non‐residential RSPV system. The data was acquired through a self‐administered survey questionnaire. A complete response from 207 participants was used for analysis purposes. The researchers have used the Partial Least Square‐Structural Equation Modeling strategy to estimate measurement and structural models. The study found that nodal agencies and environmental organizations are crucial in disseminating information and motivations concerning RSPV adoption. The study revealed that the environmental concerns of the users, compatibility, environmental benefits, the immediacy of reward, and trialability were found to be significant drivers of the diffusion and adoption of non‐residential RSPV systems. The study concluded that a paucity of financial incentives and high upfront expenses had been significant blockades to the diffusion and adoption of non‐residential RSPV.
“…Industrial agglomeration is widespread worldwide. The challenges brought by the global supply chain disruption during the COVID-19 epidemic also led governments to attach importance to industry integration and agglomeration, thus promoting the industry’s resistance to external shocks (Guru et al 2023 ; Wang et al 2023 ). From existing literature, research on IC mainly focuses on discussing its positive and negative external impacts.…”
Industrial co-agglomeration (IC) plays a pivotal role in the development of local and adjacent green energy efficiency across 284 Chinese cities, encompassing both resource-based and non-resource-based urban centers. Based on the panel data of 284 cities in China from 2005 to 2020, this study employs spatial econometric methods to empirically assess the influence of IC and its spillover effects on green energy efficiency, employing a spatial Durbin model. Additionally, the study categorizes the 284 Chinese cities into resource-based and non-resource-based categories, utilizing spatial econometric methods to delve into the heterogeneity of their effects and spillover impacts. The key findings are as follows: (1) The average green energy efficiency across the 284 Chinese cities from 2005 to 2020 stands at 0.5834. The trend in IC indicates growth and concentration towards the central areas, increasing from 2.7396 in 2005 to 2.7658 in 2020. (2) The IC, with a coefficient of 0.0918, promotes the local green energy efficiency. (3) There are spillover effects of local IC on the green energy efficiency in adjacent areas with a coefficient of 0.2550 and an Indirect Effect of 0.4567. (4) In resource-based cities, IC positively impacts local green energy efficiency with a coefficient of 0.1056 but negatively affects green energy efficiency in adjacent areas with a coefficient of −0.1368. In non-resource-based cities, IC enhances green energy efficiency in adjacent cities with a coefficient of 0.1335. Consequently, the study offers pertinent policy recommendations aimed at improving energy efficiency in light of these findings.
“…Moreover, several studies reported analytical frameworks on the LNG importation portfolio to investigate the optimal strategies [ [21] , [22] , [23] , [24] ]. For producing companies, early market assessments facilitate deciding and planning production capacities, selling portfolios, and delivery plans [ [25] , [26] , [27] ]. The uncertainties associated with energy markets and the increased competition motivated researchers to investigate and assess optimal LNG export strategies [ [28] , [29] , [30] ].…”
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