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This study aims to examine the impact of oil consumption on carbon dioxide (CO₂) emissions and total factor productivity (TFP) in highly oil-consuming countries of the world from 1995 to 2019.

For this purpose, fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied.

FMOLS and DOLS models reveal that oil consumption, human capital, population, trade openness and nonrenewable energy have a significant positive effect on CO₂ emissions. While information and communication technology (ICT), as proxied by mobile and natural resources, has a significant negative effect on CO₂ emissions. In the case of TFP, oil consumption, ICT and natural resources have a significant positive effect on the TFP. On the other hand, trade openness, population, human capital and nonrenewable energy have a significant negative effect on TFP. The results of this study can help to provide policy recommendations to reduce CO₂ emissions in studied highly oil-consuming countries of the world.

Due to the threat to sustainable development, climate change has become a major topic for debate around the world. The influence of oil consumption on CO₂ emission and TFP is less known in the available literature. Another significance of this study is that many researchers considered aggregate energy consumption to study this relationship, but the authors have studied the effect of energy consumption, particularly from oil in the top oil-consuming countries, which is a significant shortcoming of the present research.

The paper investigates the effects of climate change along with ecological and carbon footprint on rice crop production in India during 1982–2016.

The autoregressive distributed lag (ARDL), canonical cointegration regression (CCR) and fully modified ordinary least square (FMOLS) models are used in the paper.

A long-run relationship is found between climate change and rice production in India. Results report that ecological footprint and carbon footprint spur long-term rice production. While rainfall boosts rice crop productivity in the short term, it has a negative long-term impact. Further, the findings of ARDL models are validated by other cointegration models, i.e., the FMOLS and CCR models.

This study provides insights into the role of ecological footprint and carbon footprint along with climate variables in relation to rice production.

In the literature, the effects of ecological and carbon footprint on rice production are missing. Therefore, this is the first study to empirically examine the impact of climate change along with ecological footprint and carbon footprint on rice production in India.

The paper aims to examine the effects of floods on economic growth in India from 1980 to 2019, taking into account the role of foreign direct investment (FDI) inflows and foreign aid.

The study uses augmented Dickey–Fuller (ADF) and Phillip–Perron (PP) tests to determine the stationarity of the variables. Several models, including autoregressive distributed lag (ARDL), fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS) and canonical cointegration regression (CCR), are used to examine the impact of floods on economic growth.

The bounds test determines the long-term relationship between floods, FDI inflows, economic growth and foreign aid. According to the ARDL and FMOLS models, floods have a negative long-term and short-term impact on India’s economic growth. Furthermore, FDI inflows and foreign aid are beneficial to economic growth. The findings of the ARDL and FMOLS models are confirmed by the DOLS and CCR models. Granger causality establishes a unidirectional causality that extends from floods to economic growth. Further diagnostic tests show that the estimates are free of heteroskedasticity, serial correlation and parameter instability.

Indian government needs to invest more in research and development on flood management techniques. Institutional strengthening is also required to implement pre- and post-flood prevention measures properly. Sound disaster financing strategy and proper water bodies management should be prioritised. Foreign investment opportunities should be encouraged by strengthening international relations.

This is the first time-series study that analysed the effects of floods on economic growth in India. Moreover, the paper contributes to floods literature by applying several econometric models for robustness check.

The case was devised using secondary sources of data collection from annual reports, sustainability reports and the Hindustan Petroleum Corporation Limited (HPCL) website. These documents provided insights into the HPCL’s sustainability initiatives, financial performance and disclosure practices. Other data were obtained through the websites of the relevant businesses/sectors.

In March 2022, Pushp Kumar Joshi, chairman and managing director of HPCL, contemplates the oil giant’s sustainability strategy amid challenges. Despite a 38% revenue increase in financial year 2021–2022, profits dropped because of reduced refinery capacity. HPCL, a major player in India’s oil and gas industry, recognized the need to align with climate goals and changing consumer expectations. Joshi emphasized stakeholder engagement, carbon mitigation, technology adoption and transparent environmental, social and governance (ESG) reporting. A materiality assessment highlighted key issues like gender diversity, air quality and the low-carbon transition. Joshi grapples with balancing profitability and sustainability amid stakeholder pressure and market fluctuations, seeking advice from the sustainability team for the future.

This can potentially be a case study for a business management course, particularly focusing on sustainability, corporate social responsibility and strategic decision-making. It could be used at both the undergraduate and graduate levels in courses related to business administration, sustainability management, corporate strategy, environmental management or stakeholder engagement. The case could be analyzed to discuss the challenges and opportunities faced by a company like HPCL in balancing profitability and sustainability, developing effective sustainability strategies, integrating ESG considerations and managing stakeholder expectations.

Teaching notes are available for educators only.

The discourse on global value chains (GVC) is undergoing a transformation in terms of its conceptualisation, theorisation and pragmatic applications. Today, the production systems have become more complex as global economic order continues to witness marked geo-economic manoeuvring. Thus, the direction of discourse on GVC ought to move from mere theoretical propositions toward becoming more evidence based. There have been recent studies that have used the governance and upgrading propositions by Gary Gereffi and others to seek quantitative evidence. This study aims to decipher the quantitative discourse on GVC and to set the emerging and future research agenda.

Through a systematic literature review, the authors first analyse the quantitative studies on GVC carried out during the last two decades. The authors then outline a future research agenda and examine a few relevant modelling techniques that could potentially be used to solicit newer evidence in GVC research.

The authors categorise the quantitative discourse on GVC into three crucial themes, namely, GVC framework, GVC participation and position, environmental aspects and regionalisation in GVC. The most commonly used quantitative techniques are gravity model, panel data estimation, structural decomposition analysis and computable general equilibrium modelling.

This paper contributes to the GVC discourse in two ways. Firstly, the authors argue that the theoretical frameworks within the GVC discourse should be complemented by evidence-based quantitative studies. Secondly, the authors suggest potential modelling techniques that can be used on the emerging and future research agenda.

The purpose of this paper is to identify and examine the most important factors that could predict the Saudi customer’s continued intention towards adoption of mobile banking.

The proposed conceptual model was based on the technology acceptance model (TAM) and task-technology fit (TTF) model. This is also expanded by considering two additional factors: perceived privacy and perceived security. By using a self-administered questionnaire, the data were collected from a convenience sample of Saudi banking customers from different parts of Saudi Arabia.

The main results based on structural equation modelling analyses supported the impact of perceived privacy, perceived security, perceived usefulness and TTF on the customers’ continued intention to use mobile banking.

The moderation influence of the demographic factors (i.e. age, gender, income level, educational level) was not tested. The data were also collected using a self-report questionnaire; however, it would be more accurate to utilise more statistics from the bank database about the users of m-banking.

This study represents a worthy attempt to test such novel technology (m-banking) in the KSA where there is a scarcity of literature. A considerable theoretical contribution was also made by integrating the TTF model with the TAM in addition to consider privacy and security in one single model. Moreover, considering both perceived privacy and security in the current model creates an accurate picture about the adoption of m-banking especially as there are a limited number of m-banking studies that have considered privacy and security alongside the TTF model and TAM in the same model.

This study presents the impact of Economic Policy Uncertainty (EPU)-induced Trade Supply Chain Vulnerability (TSCV) on the Small and Medium-Sized Enterprises (SMEs) in India by leveraging the World Bank Enterprise Survey data for 2014 and 2022. Applying econometric techniques, it examines firm size’ influence on productivity and trade participation, providing insights for enhancing SME resilience and trade participation amid uncertainty.

The econometric techniques focus on export participation, along with variables such as total exports, firm size, productivity, and capital intensity. It addresses crucial factors such as the direct import of intermediate goods and foreign ownership. Utilizing the Cobb-Douglas production function, the study estimates Total Factor Productivity, mitigating endogeneity and multicollinearity through a two-stage process. Besides, the study uses a case study of North Indian SMEs engaged in manufacturing activities and their adoption of mitigation strategies to combat unprecedented EPU.

Results reveal that EPU-induced TSCV reduces exports, impacting employment and firm size. Increased productivity, driven by technological adoption, correlates with improved export performance. The study highlights the negative impact of TSCV on trade participation, particularly for smaller Indian firms. Moreover, SMEs implement cost-based, supplier-based, and inventory-based strategies more than technology-based and risk-based strategies.

Policy recommendations include promoting increased imports and inward foreign direct investment to enhance small firms’ trade integration during economic uncertainty. Tailored support for smaller firms, considering their limited capacity, is crucial. Encouraging small firms to engage in international trade and adopting diverse SC mitigation strategies associated with policy uncertainty are vital considerations.

This study explores the impact of EPU-induced TSCV on Indian SMEs’ trade dynamics, offering nuanced insights for policymakers to enhance SME resilience amid uncertainty. The econometric analysis unveils patterns in export behavior, productivity, and factors influencing trade participation during economic uncertainty.

The surge in internet usage has generated widespread speculation and optimism regarding its potential impact on the accessibility to financial services. The aim of this study is to investigate the effect of internet penetration on the accessibility of banking services in developed and developing countries.

Panel data regression methods are used to estimate the impact of internet penetration on accessibility to banking services in a sample of 74 countries from Global Findex survey waves of 2011, 2014, 2017 and 2021. To mitigate potential issues related to heteroscedasticity, autocorrelation and cross-sectional dependence, the study has implemented cluster robust standard errors testing. Furthermore, as a sensitivity check, the sample has been segregated into developed and developing country groups.

The study finds a significant positive correlation between internet penetration and banking access in full sample. Subsample analysis reveals that this relationship is statistically significant in developed countries, but not in developing ones, despite being positive. The research discusses the implications of these findings for both country groups.

Research to date has largely investigated the link between information and communication technology (ICT) and financial inclusion, often treating internet penetration as one component of ICT, which obscures its individual influence. This study, however, isolates internet penetration to specifically analyze its distinct effects on banking accessibility across developed and developing countries.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

The extraction of relevant knowledge from data is called knowledge discovery (KD). The KD process requires a large amount of data and it must be reliable before mining. Complexity is not only in deriving knowledge from data but also in improving system performance with a psycho-cognitive approach. KD demands a high level of human cognition and mental activity to generate and retrieve knowledge. Therefore, this study aims to explain how psychological knowledge is involved in KD.

By understanding the cognitive processes that lead to knowledge production, KD can be improved through interventions that target psychological processes, such as attention, learning and memory. In addition, psycho-cognitive approaches can help us to better grasp the process of KD and the factors that influence its effectiveness. The study attempted to correlate interdependence by interpreting cognitive approaches to KD from a psychological perspective. The authors of this paper draw on both primary and secondary literary warrants to empirically prove psychological bending in KD.

Understanding the psychological aspects of data and KD can identify the development of tools, process and environments that support individual and teams in making sense of data and extracting valuable knowledge. The study also finds that interdisciplinary collaboration, bringing together expertise in psychology, data science and domain specific knowledge fosters effective KD processes.

The KD system cannot function well and will not be able to achieve its full potential without psycho-cognitive foundation. It was found that KD in the KD system is influenced by human cognition. The authors made a contribution to KD by fusing psycho-cognitive approaches with data-driven technology and machine learning.