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The study aims to probe into university instructors' reactions to adopting the remote online learning model brought by the coronavirus disease 2019 (COVID-19) pandemic. The study investigates the instructors' perspectives, in the humanities and science classes, on the effectiveness of the emergency remote teaching (ERT) compared to face-to-face teaching.

The data for the study were compiled from the responses of 127 instructors representing two private universities in middle and northern Jordan. The sample included 66 faculty members in the humanities and 61 in the sciences. The instructors' responses were elicited through a Likert-type questionnaire consisting of 20 items.

The present study's findings have shown that online instruction is becoming more common despite the presence of some major challenges facing instructors. The results showed that the e-learning system seems to better suit the humanities courses compared to the sciences courses. The findings also showed that faculty members in the humanities are more satisfied with the effectiveness of the assessment tools utilized in the online courses than their colleagues in the sciences. In addition, humanities e-courses seem to provide a more interactive learning environment than e-courses in the sciences.

More training for instructors on how to design online course syllabi to ensure effective delivery is needed. Instructors need to develop ways to encourage students to interact in virtual e-classes to the same level as the on-ground classes. Instructors also need to adopt the “blended learning” system as a transitional stage before switching completely to online learning.

Different studies have investigated how COVID-19 has impacted education. The current study brings to light the perspectives of the Jordanian teaching staff on transitioning to ERT during the COVID-19 crisis taking into account the differences between humanities and sciences classes.

This study aims to depict and probe into the building tension, stress and depression to which Jordanian university students have been vulnerable after the compulsory shift to online learning and their prolonged use of digital tools.

The researchers used a five-construct questionnaire, namely, use of digital tools in e-learning, sleeping habits, social interaction, psychological reactions and academic performance, to elicit the responses of university students in Jordan concerning the psychological impact of COVID-19’s e-learning digital tools on their well-being. In total, 775 university-level students representing Jordanian public and private universities were asked to fill in the questionnaire, and their responses were statistically analyzed.

The results showed that the prolonged use of digital tools, lack of face-to-face interaction and heavy load of assignments have led to anxiety, change of sleeping habit, distraction and a stress-building environment, perhaps resulting in depression. This was aggravated by COVID-19’s strict regulatory measures of social distancing, lockdowns, health threats and eroding family income. The prolonged and escalating social, psychological, loss of affection and worsening economic conditions have increased the number of psychological disorders and a drop in students’ academic performance.

This study is useful for educational leaders and policymakers, providing guidance and insights on how higher education institutions can support students’ mental health and psychological well-being, especially in times of crisis. Consequently, the higher education sector should be prepared to function more efficiently and effectively in future emergency situations.

While different studies have investigated the impact of COVID-19 on the education sector globally, little attention has been given to developing countries in the Middle East. By focusing on the Jordanian example, the present study will fill a gap in the research endeavors addressing the prolonged use of e-learning digital tools.

The purpose of this paper is investigate the dynamic linkages among industrial energy use, industrial value added, financial development (FD) and trade openness, in case of India. The study covers the annual frequency data on both aggregate and disaggregate variables for the period 1971–2016.

The autoregressive distributed lag bounds testing approach is applied to examine the long-run relation among variables under consideration. Also, Johansen and Juselius (1990) and vector error-correction mechanism results confirm the result of cointegration. Furthermore, non-linear relationship in the model is also tested.

It has been found that there exists long-run relationship among variables. Long-run estimates show that increasing FD leads to more energy uses. Hence, FD should be directed in such a way that it incentivises firms to invest in energy-efficient technology. Furthermore, it is also found that study supports the evidence of conservative hypothesis, which supports that the energy conservation policy should be adopted in the industrial sector. Energy efficiency programme needs to be designed very carefully to achieve a higher level of energy efficiency. This leads to a sustainable growth and low carbon emission.

This paper examines the recent trend in Indian industrial energy consumption and does a comprehensive analysis using a robust econometric method. We have developed a lucid model to examine the deriving factors of industrial energy consumption.

The purpose of this paper is to analyze the effect of economic growth, international trade and energy consumption on the global carbon dioxide (CO₂) emissions, in the case of top CO₂ emitters, namely, USA, Japan, Canada, Iran, Saudi Arabia, UK, Australia, Italy, France and Spain using the annual data from 1971 to 2013.

For this purpose, the time series, data technique is applied. Unit root test with structural break and the bounds testing approach for cointegration in the presence of structural break is tested. Finally, a vector error correction model for the Granger causality test is applied to detect the direction of causality. The authors have used the techniques that will help in examining the structural break in the time series data.

The results reveal that their exists a long-run relationship between CO₂ emissions and its determinants in the USA, Canada, Iran, Saudi Arabia, the UK, Australia, Italy, France and Spain, energy consumption is the main determinant of carbon dioxide (CO₂) emissions in the long run and for direction of causality, the authors found bidirectional causality in the long run between energy consumption and CO₂ emissions in the USA, Canada, Iran, Saudi Arabia and the UK, and Granger causality running in opposite direction in the case of Australia from CO₂ emissions to energy consumption was analyzed. In terms of growth-trade-pollution nexus (USA, Canada, Iran and France) hold one-way causality running from economic growth and trade openness to CO₂ emissions (IV) the environmental Kuznets curve hypothesis is validated only for the USA. Robust policy implications can be derived from this study. First, without harming the economy, these countries can reduce the use of energy consumption for lower pollution. Second, the amount of trade should be decreased to lower the emissions because the authors find that an increase in trade does Granger cause to CO₂ emissions in the long run.

There has been no study that investigated the relationship between CO₂ emissions, real income, consumption of energy and international trade in the environmental Kuznets relation for the top CO₂ emitter’s countries over the period of 1971–2013. The authors did a comparative study of the empirical finding among these nations.

Because of growing energy consumption and increasing absolute CO₂ emissions, the recent calibrations about the environmental sustainability across the globe have mandated to achieve the minimal energy consumption through employing energy-efficient technology. This study aims to estimate linkage between simple measure of energy efficiency indicator that is reciprocal of energy intensity and total factor productivity (TFP) in case of Indian paper industry for 21 major states. In addition, the study incorporates the other control variables like labour productivity, capital utilization and structure of paper industry to scrutinize their likely impact on energy efficiency performance of the industry.

To derive the plausible estimates of TFP, the study applies the much celebrated Levinsohn and Petrin (2003) methodology. Using the regional level data for the period 2001-2013, the study employs instrumental variable-generalized method of moments (GMM-IV) technique to examine the nature of relationship among the variables involved in the analysis.

An elementary examination of energy intensity shows that not all states are equally energy intensive. States like Goa, Rajasthan, Jharkhand and Tamil Nadu are less energy intensive, whereas Uttar Pradesh, Kerala, Chhattisgarh, Assam and Punjab are most energy-intensive states on the basis of their state averages over the whole study period. The results estimated through GMM-IV show that increasing level of TFP is associated with lower level of energy per unit of output. Along this better skills and capacity utilization are also found to have positive impact on energy efficiency performance of industry. However, the potential heterogeneity within the structure of industry itself is found responsible for its higher energy intensity.

States should ensure and undertake substantial investment projects in the research and development of energy-efficient technology and that targeted allocations could be reinforced for more fruitful results. Factors aiming at improving the labour productivity should be given extra emphasis together with capital deepening and widening, needed for energy conservation and environmental sustainability. Given the dependence of structure of paper industry on the multitude of factors like regional inequality, economic growth, industrial structure and the resource endowment together with the issues of fragmented sizes, poor infrastructure and availability and affordability of raw materials etc., states should actively promote the coordination and cooperation among themselves to reap the benefits of technological advancements through technological spill overs. In addition, owing to their respective state autonomies, state governments should set their own energy saving targets by taking into account the respective potentials and opportunities for the different industries. Despite the requirement of energy-efficient innovations, however, the cons of technological advancements and the legal frameworks on the employment structure and distributional status should be taken care of before their adoption and execution.

To the best of our knowledge, this is the first study that empirically examines the linkage between energy efficiency and TFP in case of Indian paper industry. The application of improved methods like Levinsohn and Petrin (2003) to derive the TFP measure and the use of GMM-IV to account for potential econometric problems like that of endogeneity will again add to the novelty of study.

The purpose of this paper is to benchmark the energy use of Indian iron and steel industry. For this purpose, the authors have estimated a production frontier to know the best performing states. Further, the energy-saving targets are estimated to lie below the benchmark level for those states. Panel data for this purpose are extracted from the Annual Survey of Industry (an official database from the government of India) for 19 major steel-producing states over the period from 2004–2005 to 2013–2014.

The authors employed a radial and non-radial (slack-based measure) variant of the data envelopment analysis (DEA) to estimate the production frontier. Particularly, slack-based measures (SBMs) developed by Tone (2001) are used to get a more comprehensive measure of energy efficiency along with technical efficiency. Variable returns to scale technology is specified to accommodate market imperfection and heterogeneity across states. Four inputs (capital, labour, energy and material) and a single output are conceptualised for the production process to accommodate input substitution. The relative position of each state in terms of the level of energy efficiency is then identified.

The authors started by examining energy-output ratio. The average level of energy intensity shows declining trends over the period of time. States like Bihar, Jharkhand, Gujarat and Uttarakhand remain stagnant in the energy intensity level. SBM of energy efficiency shows an overall average energy saving potential of 8 per cent without reducing average output level. Considerable heterogeneity exists among states in terms of the energy efficiency scores. Further, the authors calculated scale efficiency (SE) which shows the overall average level of SE is 0.91; hence, the scale of operation is not optimal and needs to adjusted to enhance energy efficiency.

The authors demonstrate the empirical application of DEA with SBM to energy use performance. This is the first study that benchmarks Indian states in terms of the consumption of energy input to produce iron and steel by applying DEA.

This paper aims to measure the state-level energy efficiency in Indian paper industry and simultaneously explain inter-state variation in efficiency by inefficiency effect model. Three variables, labor productivity, capital intensity and structure of paper industry, are included in inefficiency effect model to assess the likely impact on energy efficiency.

Sub-vector input distance function is derived through neo-classical production function which provides measures to estimate energy efficiency. Assuming a translog production function specification, energy efficiency is estimated by using Battese and Coelli (1995) stochastic frontier analysis (SFA). The authors also estimated four other SFA models, and energy efficiency from all the models is compared for robustness checking.

The results show the existence of a vast potential to improve energy efficiency. Inefficiency effect model reported a positive impact of structure of the industry and capital intensity on energy efficiency performance, while labor productivity does not have any significant impact on energy efficiency. There exists considerable energy efficiency variation among states. Uttarakhand, Punjab and Orissa are the best performing states while Rajasthan, Jharkhand and Goa have worst energy efficiency performance based on average efficiency. The ranks assigned to states according to inefficiency effects model are found contrary to the simple measure of energy efficiency, i.e. energy intensity. Thus, energy intensity may not always be a good proxy for underlying energy efficiency and need to be compared with a comprehensive possible measure.

To the best of the authors’ knowledge, this is the first study which measures energy efficiency of Indian paper industry through stochastic frontier model using region-level data. Instead of relying on traditional energy efficiency indicators (energy-output ratio), total-factor energy efficiency approach is used to conduct the empirical exercise. Deviations from the frontier because of factors beyond the scope of producers are also incorporated into analysis to portray the magnitude of random factors in influencing the efficiency performance.

The present study empirically examines the impact of coronavirus disease 2019 (COVID-19) and policy uncertainty on stock prices in India during the COVID-19 pandemic.

To this end, the authors use the daily data by applying the autoregressive distributed lag (ARDL) model, which tests the short- and long-run relationship between stock price and its covariates.

The study finds that increased uncertainty has adverse short- and long-run effects on stock prices, while the vaccine index has favorable effects on stock market recovery.

From investors' perspectives, volatility in the Indian stock market has negative repercussions. Therefore, to protect investors' sentiments, policymakers should be concerned about the uncertainty induced by the COVID-19 pandemic and similar other uncertainty prevailing in the financial markets.

This study used the news-based COVID-19 index and vaccine index to measure recent pandemic-induced uncertainty. The result carries some policy implications for an emerging economy like India.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0244

Due to the Coronavirus 2019 (COVID-19) pandemic, education has been disrupted right from kindergarten to University. Globally, states are advocating for online learning. The COVID-19 pandemic had led to the closure of universities and it was not clear how long this would last. e-Learning was crucial. Lecturers were asked to complete their syllabuses and continue to teach and administer tests remotely. So far, there is a dearth of information on how Kenya’s higher education responded to the pandemic through online learning. This qualitative study utilized online platforms (zoom and Skype) for interviews. This study employed a constructivist approach to explore the faculty officials’ perception of online learning in Kenya’s institutions of higher education. Approximately 45 faculty officials from public universities were involved in this study. The study was carried out in three public universities in Western Kenya. The participants argued that online education was beneficial and primarily promoted online research and enabled them to connect with other practitioners in the global community. There were challenges associated with online learning for instance unreliable internet. This study’s results are hoped to inform the ministry of education and higher learning policies on making online effective and efficient to both the students and the lecturers. This will also be a fairer spring-ball for Kenya toward the realization of Vision 2030.