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This study aims to convey lessons learned from two sustainability initiatives at Norway’s largest university. This contributes to knowledge-based discussions of how future, sustainable higher education institutions (HEIs) infrastructures should be envisioned and planned if the fundamental uncertainty of the future development of learning, researching and teaching is acknowledged.

This study was submitted on 24 January 2023 and revised on 14 September 2023. HEIs, particularly when they are engaged in research activities, have a considerable environmental footprint. At the same time, HEIs are the main producers and disseminators of knowledge about environmental challenges and their employees have a high awareness of the urgent need to mitigate climate change and biodiversity loss. In this study, the gap between knowledge and environmental performance is addressed as a question of infrastructural change, which is explored in two case studies.

The first case study presents limitations of ambitious, top-down sustainability planning for HEI infrastructures: support from employees and political support are central for this strategy to succeed, but both could not be secured in the case presented leading to an abandonment of all sustainability ambitions. The second case study exposes important limitations of a circular approach: regulatory and legal barriers were found against a rapid and radical circular transformation, but also more fundamental factors such as the rationality of an institutional response to uncertainty by rapid cycles of discarding the old and investing in new equipment and facilities.

Being based on qualitative methods, the case studies do not claim representativity for HEIs worldwide or even in Norway. Many of the factors described are contingent on their specific context. The goal, instead, is to contribute to learning by presenting an in-depth and context-sensitive report on obstacles encountered in two major sustainability initiatives.

Research reporting on sustainability initiatives too often focuses descriptively on the plans or reports the successes while downplaying problems and failures. This study deviates from this widespread practice by analysing reasons for failure informed by a theoretical frame (infrastructural change). Moreover, the juxtaposition of two cases within the same context shows the strengths and weaknesses of different approaches to infrastructural change particularly clearly.

The entrepreneurial process often cannot be explained by a single entrepreneurial theory. Instead, it is more likely the result of the interaction between various entrepreneurial behavior patterns and different environmental conditions. However, existing research has frequently overlooked the complexity inherent in the entrepreneurial phenomenon. Building on a configurational perspective, this study aims to examine how new ventures can use different behavioral configurations to achieve high performance amid various uncertain environments.

Based on the survey data from 143 new start-ups in China’s software industry, this study uses fuzzy-set qualitative comparative analysis (fsQCA).

This study jointly considers multiple entrepreneurial behaviors − causation, effectuation and entrepreneurial bricolage and different types of environmental uncertainty − state uncertainty, effect uncertainty and response uncertainty. The findings reveal three behavioral configurations for high/nonhigh new venture performance.

This study expands previous insights into the relationship between entrepreneurial behaviors and new venture performance from the perspective of configurational theory. Moreover, it offers new insights into the types of uncertainty, further refining our understanding of the uncertainties inherent in entrepreneurial activities.

This study aims to explore the intricate relationship between uncertainty indicators and volatility of commodity futures, with a specific focus on agriculture and energy sectors.

The authors analyse the volatility of Indian agriculture and energy futures using the GARCH-MIDAS model, taking into account different types of uncertainty factors. The evaluation of out-sample predictive capability involves the application of out-sample R-squared test and computation of various loss functions.

The research outcomes underscore the significant impact of diverse uncertainty factors such as domestic economic policy uncertainty (EPU), global EPU (GEPU), US EPU and geopolitical risk (GPR) on long-run volatility of Indian energy and agriculture (agri) futures. Additionally, the study demonstrates that GPR exhibits superior predictive capability for crude oil futures volatility, while domestic EPU stands out as an effective predictor for agri futures, particularly castor seed and guar gum.

The study offers practical implications for market participants and policymakers to adopt a comprehensive perspective, incorporating diverse uncertainty factors, for informed decision-making and effective risk management in commodity markets.

The research makes an inaugural attempt to examine the impact of domestic and global uncertainty indicators on modelling and predicting volatility in energy and agri futures. The distinctive feature of considering an emerging market also adds a novel dimension to the research landscape.

Our purpose is to explore how culture’s impact on investment is depending on uncertainty levels.

This study investigates the interplay between national culture, uncertainty, and corporate investment decisions. Focusing on the uncertainty avoidance dimension (HUA) from Hofstede’s culture framework and utilizing the World Uncertainty Index (WUI) as a measure of uncertainty, this research explores how culture’s impact on investment is depending on uncertainty levels.

Our results reveal that high HUA countries lower long-term investment during periods of heightened uncertainty, particularly in riskier investments like R&D, rather than capital expenditure. This relation is more pronounced for smaller firms. The findings suggest that HUA is associated with less risk taking, primarily when uncertainty is high. Furthermore, we demonstrate that the interaction between HUA and uncertainty exerts more significant and consistent effects on corporate investment than other cultural dimensions, religion, and various formal institutions, contrary to prevailing literature.

This study looks at the relationship between national culture and corporate investment under ambiguity, and what are the implications for risk taking. If national culture is related to riskier investments, such as R&D, relative to safer investments, like capital expenditure this would imply that risk taking is explaining the relationship between national culture and corporate investment. This relation should be clear during uncertain times. This is the first study to include the moderating effects of the level of uncertainty on the relation between national culture and corporate investment (or financial decisions in general).

This paper aims to focus on exploring and understanding the practice of analyzing the determinants of the Moroccan Dirham by foreign exchange professionals in trading rooms in the context of transitioning to a more flexible regime initiated by Moroccan authorities. The objective of this study is to highlight how foreign exchange operators analyze the determinants of the Moroccan Dirham in the context of exchange rate liberalization, focusing primarily on qualitative data rather than quantitative data.

Therefore, this paper opted for a methodological approach using interview surveys to understand the underlying behavior of Moroccan foreign exchange operators, conducting a content analysis. This paper targeted six foreign exchange operators from nine Moroccan banks authorized as market makers by Bank Al-Maghrib.

The results indicate that the fluctuations of the Moroccan Dirham are closely linked to two main factors: the analysis of the EUR/USD exchange rate and market liquidity analysis. Furthermore, content analysis revealed five essential aspects regarding the practice of analyzing the determinants of the Dirham: “Dirham determinants,” “complementarity between technical analysis and fundamental analysis,” “trends and reversals,” “utility of macroeconomic models” and “psychological factors.”

Certainly, this methodology allows for exploring and understanding the underlying behavior of currency operators but inherently generates a certain degree of subjectivity that can affect the research validity. Indeed, the subjectivity can arise from the responses of the currency operators themselves. They may present the phenomenon coherently or selectively choose the elements they remember to respond to. On the other hand, the validity of this type of research relies on the researcher's ability to cultivate empathy throughout the knowledge creation process. The empathetic stance adopted in this study proved to be complex due to the uniqueness of operators and interaction, sometimes making it challenging to combine empathy, respect and critical thinking (Olivier De Sardan, 2004). Furthermore, the researcher is often faced with an interpretation bias, which can manifest not only during the coding of collected data but also during the analysis of the constructed content. To mitigate this interpretation bias, this paper subjected the collected data to a double coding procedure.

This study aims to narrow the gap in opinions between academics and practitioners by providing a practical overview for change novices.

This study is the pioneering inquiry exploring the process of determining the Moroccan dirham within the transition to a flexible exchange rate regime, using an exploratory methodological approach.

This paper aims to identify the key drivers of US sustainable stock price movements in both the short and long term, deploying a rich collection of variables corresponding to green finance, investor attention and sentiment, market fear and uncertainty, macroeconomic variables, common market risk factors, commodity markets and the carbon emission market.

The empirical analysis is based on two main methodologies. First, the elastic net penalized regression is utilized to select the factors most influential on the price formation of sustainable stocks. Second, short- and long-run dynamics of the chosen factors are examined using the dynamic simulations of the autoregressive distributed lag (DYNARDL) model.

Of 32 candidate variables, the elastic net chooses US renewable energy, European sustainable stock market, EU ETS emission allowances, public attention to sustainable finance, gold and European renewable energy as the most contributing factors to the price behavior of sustainable stocks. The DYNARDL estimation results reveal that US renewable energy, European sustainable stock market and EU ETS emission allowances are important determinants in the short and long term, while public attention (European renewable energy) tends to affect sustainable stock prices only in the short (long) run.

The corresponding short- and long-run effects of US renewable energy, EU ETS emission allowances and European sustainable stocks on US sustainable stock prices should induce policymakers to keep the price behavior of these factors under systematic review. The formulation of policy measures could serve to safeguard the sustainable stock market from the price vagaries in these influential markets.

Relevant literature often focuses on the reaction of sustainable stocks to mainstream assets and risk proxies, limiting analysis to a few factors and providing an incomplete understanding of the drivers behind sustainable stock prices. More comprehensive research is needed due to the lack of studies on the determinants of sustainable stock prices and the growing global demand for these investments. This paper aims to address this gap by examining the potential explanatory power of 32 candidate factors representing key players in the global economic and financial landscape.

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

This study aims to investigate the dynamic relationships between profitability, credit risk, liquidity risk and capital in Indonesian banking industry.

The authors use a panel vector autoregression model that incorporates macroeconomic variables: growth, interest rate, foreign exchange. The analysis is based on a monthly panel data set of 88 banks spanning from January 2012 to September 2021, which comprises 10,296 bank-month observations.

Our key findings highlight (i) permanent credit cost and liquidity cost pass through practices, (ii) complementary function of liquidity and capital, (iii) earning management motivated asset write off and (iv) credit risk-liquidity risk neutrality. In addition, the authors observe that the banks demonstrated resilience to macroeconomic shocks.

Our study have shown some interesting dynamic patterns of fundamentals; nevertheless, unified theoretical underpinning of the process is still unavailable. This should be an important future reasearch avenue.

The study brings significant implications for regulatory and supervisory practices aimed at enhancing the financial stability of banks.

We conduct estimation of Indonesian banks system in dynamic perspective and perform impulses responses.

This study aims to examine the potential of Sharia status as ex ante information to signal the quality of an issuing firm by improving the decision-making process of potential investors when assessing initial public offerings (IPOs) in an environment where information asymmetry is pronounced. Potential investors face challenges in evaluating and determining the true value of IPO issues, which inherently influences their decision-making. Consequently, this results in pronounced price fluctuations in IPO shares, leading to higher underpricing.

This study uses a sample of 350 IPOs listed on the Kuala Lumpur Stock Exchange (KLSE) between 2004 and 2021 to examine the signaling role of Sharia-compliance status. A three-model approach is used to ensure that the study's objectives are met. The first model investigates the effect of Sharia status on underpricing to determine whether the main beneficiary of such a signal is the investor or the issuer. The second model examines the effect of Sharia status on investor demand to determine if such a signal influences prospective investors' investment decision-making processes. The third model inspects the effect of Sharia status on investor divergence of beliefs to measure the signal's ability to reduce information asymmetry within the Malaysian IPO market.

The Malaysian IPO market relies heavily on the fixed-price mechanism, which exacerbates high information asymmetry, affecting potential investors' behavior, asset price formation and return generation on the first day of listing. The study results indicate that Sharia status does not have any signaling role in the Malaysian IPO market. This is because investors in the Malaysian market are driven by ex ante information that helps unveil relevant information that leads to capital gains. Furthermore, most new issues in the Malaysian IPO market fall under Sharia status, diluting the relevance of such information for prospective investors in determining profitable investments.

The findings highlight the challenges faced by issuing firms in estimating market demand due to limited premarket insights and the difficulties prospective investors face in identifying the quality of issuing firms. Efforts to provide more information on investor demand can reduce uncertainty and facilitate more informed decision-making.

This research stands as one of the pioneering efforts to provide an empirical explanation of the potential signaling influence of Sharia status in an emerging IPO market.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.