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The purpose of this paper is to investigate the influence of the external environment on the strategic thinking dimensions in Malaysia and Palestine on the banking sector.

This paper focuses on dynamism and complexity in political and economic external environments. This study uses qualitative methodology through a comparative case study method. Purposive sampling was used to collect data from in-depth semistructured interviews with 33 bank executives from Malaysia and 17 from Palestine.

The findings revealed that the banking sector in both Malaysia and Palestine shared five common strategic thinking dimensions, including vision, creativity, conceptual thinking, futurism and opportunity. However, a sixth dimension, intent-focused, was unique to Palestinian bank executives. This study indicates that Palestine’s financial strategic thinking environment is more dynamic and complex than Malaysia’s. Additionally, the study highlights the significant influence of both microenvironments (such as types of banks) and the macroenvironment (such as political and economic situations). These findings hold important implications for decision-makers in the banking sector of both countries.

As with many studies, this study has some limitations. First, the analysis examines only the turbulent and stable environment in the two countries by using a qualitative approach which enables the analysis of thoughts and actions and exposes the beliefs, perceptions, mental maps and structures of belief in their perceptions (Cavana et al., 2001). As such, the results are limited to a particular time, date and geographical location; thus, opinions and perceptions might be altered due to changes in the external political and economic environment. The second limitation of this work is that the case study might not be appropriate for generalization (Stake, 1978). Finally, the limited number of female participants in Palestine shows a high level of inequality compared to Malaysian participants.

This study explores the implication of uncertain environments at the national level on executives’ cognition and actions, links the micro- and macro-environment of the banking industry to a theoretical perspective and develops a conceptual circular model to show the effect of macro environments on bank performance. The findings offer practical contributions to the current literature, providing insights for executives to navigate a dynamic and complex banking industry.

This study fills the literature gap by exploring how strategic thinking dimensions triggered by macro- and micro-environments impact banking sector performance in Malaysia and Palestine.

The paper positions social and technological innovation as pivotal counterforces to conservative resistance against change, particularly in light of the recurrent economic and technological upheavals characterizing the present shape of capitalism.

The research adopts a qualitative methodology, rooted in a comparative case study approach, offering a critical retrospective analysis of societal disruptions and transformations. Central to this methodological framework is the construct of sensemaking, which is characterized as the process by which collective entities retrospectively develop plausible narratives that rationalize their experiences. The approach is informed by the dynamics of socio-ecological systems, which are understood to undergo cyclical phases of growth, stabilization, collapse, and regeneration.

The study shows evidence that resilience and adaptability are more authentically gauged by socio-technological responses to cyclical disruptions and recoveries. It delineates sensemaking as a crucial socioecological mechanism through which elicitation emerges and societies and organizations navigate these cycles, forging shared narratives from collective experiences that are driven by plausibility rather than mere accuracy.

The research calls for the development of policies that synthesize disruptive innovations with strategies for social cohesion. Such policies must ensure the protection of the socioeconomic texture from implicit structural precariousness arising from innovation. The ability to integrate and institutionalize change is emphasized as crucial, demanding a synergy between innovative creativity, new normative frameworks, and the preservation of fundamental societal values.

The paper challenges reductionist technological interpretations of societal changes, advocating for a holistic perspective that accounts for the redistributive and elicitation roles as vital to the evolution of socio-economic systems. The value of this research lies in its comprehensive framing of these transformations, underscoring the importance of a multi-faceted understanding in the effective management of socioeconomic change.

The primary purpose of this study is to explore the effect of technical changes on provincial-level income inequality in Vietnam. The authors also investigate whether the quality of institutions and human capital level moderate this relationship.

This research applies the fixed-effect and random-effect models on a balanced panel data set of 63 Vietnamese provinces/cities from 2010 to 2020.

The study’s empirical results show that technical improvement has a nonlinear influence on income disparity in Vietnamese localities. When the local level of technology is limited, technological change can mitigate income disparity. However, as local technological levels increase, inequality tends to rise. Moreover, the study also reveals that the quality of a province’s institutions and the level of human resources are factors that moderate the correlation between technological change and income inequality. For provinces with better institutional quality and/or better human resources, inequality tends to decline under the impact of technological change.

The results of this study suggest that while encouraging technology advancement, localities should also ensure sustainable development, reduce income inequality and focus on improving institutional quality and human resources development.

There are increasing concerns about the impact of technical change on inequality in income distribution; however, empirical evidence on this relationship in developing countries remains scarce. This study is among the few attempts to examine this issue at the provincial level of a developing country considering the moderation effect of institutional quality and human capital level.

Increased trapped heat in the atmosphere leads to global warming and economic activity is the primary culprit. This study proposes the nonlinear impact of economic activity on cooling degree days to develop a climate Kuznets curve (CKC). Further, this study explores the moderating role of higher education and renewable energy in diminishing the climate-altering effects of economic activity.

All the selected BRICS economies range from 1992 to 2020. The CKC analysis uses a distribution and outlier robust panel quantile autoregressive distributed lagged model.

Results confirmed a U-shaped CKC, controlling for population density, renewable energy, tertiary education enrollment and innovation. The moderating role of renewable energy and education can be exploited to tackle the progressively expanding climate challenges. Hence, education and renewable energy intervention can help in reducing CKC-based global warming.

This study highlighted the incorporation of climate change mitigating curriculum in education, so that the upcoming economic agents are well equipped to reduce global warming which must be addressed globally.

This study is instrumental in developing the climate change-based economic activity Kuznets curve and assessing the potential of higher education and renewable energy policy intervention.

The recent meeting of G-20 world leaders, held in New Delhi, in 2023, highlighted that the physical effect of climate change has considerable macro-economic costs at the national and global levels and they have also pledged to accelerate the clean, sustainable and inclusive energy transition along a variety of pathways. Climate change could pose various emerging risks to the firm’s operational and financial activities, specifically for those which are belonging to the energy sector. Thus, this study aims to investigate the impact of climate risks on the financial performance of select energy companies from G-20 countries.

The study considered 48 energy companies from G-20 countries as the sample for the period of 2017 to 2021. To measure the climate change-related physical risks, the study has considered the ND-GAIN climate vulnerability score and the firm’s financial performance has been measured by return on assets, return on equity, return on capital used and price-to-book ratio. To examine the impact of climate risks on the financial performance of the sample companies, the authors have used pooled ordinary least squares (OLS) and fixed/random effect regression analysis and required data diagnosis tests are also performed.

The empirical results suggested that climate risks negatively impacted the financial performance of the sample companies. The market performances of the firms are also being impacted by the physical climate change. The results of panel data regression analysis also confirmed the robustness of the empirical results derived from the pooled OLS analysis suggesting that firms that operated in a less climate-risky country, financially performed better than the firms that operated in a more climate-risky country.

The paper has significant practical implications like it could be helpful for the policymakers, investors, suppliers, researchers and other stakeholders in developing deeper insights about the impact of climate risks on the energy sectors from an international perspective. This study may also help the policymakers in developing policies for the management of climate risk for the energy sector.

This study adds insights to the existing literature in the area of climate risks and firm’s financial performance. Moreover, this may be the first study that attempts to evaluate the impact of climate risks on the financial performance of select energy companies from the G-20’s perspective.

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.

This research examines the transformative impact of the “Great Reset” on organisational theory through the thematic network analysis of managerial responses from Germany, France, and Spain, emphasising the importance of technological integration, remote working, and resilience.

Questionnaire responses from managers in Germany, France, and Spain were examined using thematic network analysis to understand remote working, digital transformation, and organisational resilience.

Managers highlighted the pivotal role of technology in reshaping future work systems, especially in telecommuting and digitising business procedures. This transformation requires upskilling, shifts in management approaches, and a modernised employee assessment structure.

This study offers practical insights into implementing the Great Reset framework and explains its impact on technological progress, managerial strategies, and organisational resilience.

The significance of this research lies in providing an understanding of how economic conditions, including financial development, informal economic activities and economic uncertainty, influence carbon emissions and tries to offer valuable insights for policymakers to promote sustainable development.

The Panel-ARDL method is employed for a group of 30 developing countries from 1990 to 2018. This study analyzes the data obtained from the World bank, International Monetary Fund and World Uncertainty databases.

Based on the empirical results of the extended model, an increase in GDP and energy intensity is associated with an 83 and 14% increase in carbon emissions, respectively. Conversely, a 1% increase in financial development and economic uncertainty is linked to significant decrease in carbon emissions (about 47 and 23%, respectively). Finally, an increase in the informal economy can lead to a negligible yet significant decrease in carbon emissions. These results reveal that financial development plays an effective role in reducing CO₂ emissions. Moreover, while economic uncertainty and informal economy are among unfavorable economic conditions, they contribute in CO₂ reduction.

Therefore, fostering financial development and addressing economic uncertainty are crucial for mitigating carbon emissions, while the impact of informal economy on emissions, though present, is relatively negligible. Accordingly, policies to control uncertainty and reduce the informal economy should be accompanied by environmental policies to avoid increase in emissions.

The originality of this paper lies in its focus on fundamental changes in the economic environment such as financial development, economic uncertainty, and informal activities as determinants of carbon emissions. This perspective opens up new avenues for understanding the intricate relationship between carbon emissions and economic factors, offering unique insights previously unexplored in the literature.

This paper aims to examine the long-run relationship between stock market development and Nigerian economic growth from 1980 to 2020.

Market capitalization, number of listed companies, total value traded ratio and turnover ratio are used. An autoregressive distributed lag model is used for the analysis.

The market capitalization ratio and turnover ratio have positively significant links with economic growth. The number of listed companies has a negative and non-significant impact on economic growth. Total value traded ratio has a negatively significant link with economic growth in the short run. The positive but insignificant relationship between traded value ratio and turnover ratio in the long run growth means that the Nigerian stock market is growth inducing and on the right track as stock market liquidity drives growth.

The government and Security Exchange Commission should increase the market liquidity level by improving the trading infrastructure. The government and regulatory authorities should improve and effectively implement the existing policies that would ensure stock market growth. This facilitates the investors’ speed to purchase and sell shares. The Securities and Exchange Commission should reduce transaction costs to encourage active trading activities. The market should be diversified with investment instruments such as derivatives, futures and swap options which would limit the adverse effect of listed companies in the market. To increase the stock market liquidity, the Security and Exchange Commission should apply moral suasion to bring private companies that have met certain financial thresholds to convert to public companies. Government should improve on the legislation to encourage more private companies to list on the stock exchange.

The study findings add value in that stock market development has a positive impact on economic growth in Nigeria.

With the intensification of market competition, there is a growing demand for weak signal identification and evolutionary analysis for enterprise foresight. For decades, many scholars have conducted relevant research. However, the existing research only cuts in from a single angle and lacks a systematic and comprehensive overview. In this paper, the authors summarize the articles related to weak signal recognition and evolutionary analysis, in an attempt to make contributions to relevant research.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. Framework comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.

The research results show that it is necessary to improve the automation level in the process of weak signal recognition and analysis and transfer valuable human resources to the decision-making stage. In addition, it is necessary to coordinate multiple types of data sources, expand research subfields and optimize weak signal recognition and interpretation methods, with a view to expanding weak signal future research, making theoretical and practical contributions to enterprise foresight, and providing reference for the government to establish weak signal technology monitoring, evaluation and early warning mechanisms.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. It comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.