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This paper aims to investigate the impact of climate change news on the dynamics of US stock indices.

The empirical basis of the study was 3,209 news articles. Sentiment analysis was performed by a pre-trained bidirectional FinBERT neural network. Thematic modeling is based on the neural network, BERTopic.

The results show that news sentiment can influence the dynamics of stock indices. In addition, five main news topics (finance and politics natural disasters and consequences industrial sector and Innovations activism and culture coronavirus pandemic) were identified, which showed a significant impact on the financial market.

First, we extend the theoretical concepts. This study applies signaling theory and overreaction theory to the US stock market in the context of climate change. Second, in addition to the news sentiment, the impact of major news topics on US stock market returns is examined. Third, we examine the impact of sentimental and thematic news variables on US stock market indicators of economic sectors. Previous works reveal the impact of climate change news on specific sectors of the economy. This paper includes stock indices of the economic sectors most related to the topic of climate change. Fourth, the research methodology consists of modern algorithms. An advanced textual analysis method for sentiment classification is applied: a pre-trained bidirectional FinBERT neural network. Modern thematic modeling is carried out using a model based on the neural network, BERTopic. The most extensive topics are “finance and politics of climate change” and “natural disasters and consequences.”

This paper aims to examine the effect of contractual factors and noncontractual factors on tax avoidance (TA).

The sample comprises 400 firm-year observations of 67 companies listed on the HDAX during the period 2008–2017. The generalized least square panel regression is applied.

The study results confirm a significant effect of long-term chief executive officer (CEO) compensation incentives and CEO attributes on TA. Findings exhibit a significant impact of foreign CEO on TA, whereas an insider CEO mitigates TA. The results hold for several robustness tests, with lag effective tax rate as dependent variable and with splitting foreign CEO into European and non-European origin.

First, the sample is limited to 400 firm-year observations and to the German context. For shareholders, the study provides first evidence on relationships between the geographical and internal versus external labor market for CEOs and TA. For researchers, the findings underline the importance of integrating behavioral approaches like place attachment theory and the rooting theory in the theory of TA.

To the best of the authors’ knowledge, this is the first study to examine the impact of both contractual determinants and behavioral determinants on TA in the German context as an emerged economy with a dualistic corporate governance. This study contributes to the existing literature regarding the scientific debates about the impact of CEOs and CEO attributes on TA. It also analyses the balance between the place attachment theory and the rooting theory in the face of the compensation outcomes of agency theory.

This paper empirically investigates the effect of the coronavirus pandemic (COVID-19) on the Indian financial market and firm betas, perhaps the first paper to do so. The results will be helpful for investors tracking betas during future the coronavirus waves.

A conditional capital asset pricing model (CAPM) and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model is used to estimate time-varying daily betas of the 50 largest Indian stocks spread across 16 industries over five years (Nov 2017 to May 2021), including the two waves of COVID-19 in India.

The results show that the betas increased during the COVID wave-1 (2020) but not during COVID wave-2 (2021). Moreover, the increase is more pronounced for consumer goods, infrastructure, insurance and information technology, unlike energy (oil and gas, power and mining) industries. Further, there are positive abnormal residual returns during the COVID waves. The results will be helpful for investors tracking betas during future COVID-19 waves.

This is perhaps the first paper to study the firm betas in light of the COVID-19 pandemic.

The purpose of this paper is to examine the effect of economic policy uncertainty (EPU) of China on investment opportunities in five ASEAN economies.

This paper employs advanced empirical approaches, such as Multivariate DCC-GARCH and Continuous Wavelet Transform (CWT) to test the research objective. The period of analysis involved monthly data from 2003 until 2019.

This paper provides evidence where the Malaysian stock market to be the least exposed to risks emanating from Chinese EPU, followed by Singapore, the Philippines, Thailand and Indonesia. Results for investment opportunities based on time horizon suggest, for a short-term holding period, investors are better off investing in Singapore and Indonesia, while, for medium-term holding periods, all ASEAN markets appear lucrative except for the Philippines.

From a managerial perspective, the outcome or findings of this study are expected to aid the retail and institutional investors in designing better strategies on diversifying a stock portfolio with different holding periods.

Theoretically, the findings of this study contribute fresh insights into an emerging strand of literature focusing on the transmission of regional policy. Methodologically as well, this study is a novel venture to the best of authors' knowledge.

This paper aims to investigate the moderating role of government policy interventions amid the early spread of novel coronavirus (COVID-19) (January–May 2020) on the investor sentiment and stock returns relationship.

This paper uses panel data from a sample of 53 countries to examine the impact of investor sentiment, measured by the financial and economic attitudes revealed by the search (FEARS) index (Da et al., 2015) on the stock return.

The moderating role of government policy response indices with the FEARS index on the global stock returns is further explored. This paper finds that government policy responses have a moderating role in the sentiment and stock returns relationship. The effect holds true even when countries are split based on five classifications, i.e. cultural distance, health standard, government effectiveness, social well-being and financial development. The results are robust to an alternative measure of pandemic search intensity, quantile regression and two measures of stock market activity, i.e. conditional volatility and exchange traded fund returns.

The sample period of this study encompasses the early spread phase (January–May 2020) of the novel COVID-19 spread.

This paper provides some early evidence on whether the government policy interventions are helpful to mitigate the impact of investor sentiment on the stock market. The paper also helps to shed better insights on the role of different country characteristics for the sentiment and stock return relationship.

This study examines herding behaviour in commodity markets amid two major global upheavals: the Russo–Ukraine conflict and the COVID-19 pandemic.

By analysing 18 commodity futures worldwide, the study examines herding trends in metals, livestock, energy and grains sectors. The applied methodology combines static and dynamic approaches by incorporating cross-sectional absolute deviations (CSAD) and a time-varying parameter (TVP) regression model extended by Markov Chain Monte Carlo (MCMC) sampling to adequately reflect the complexity of herding behaviour in different market scenarios.

Our results show clear differences in herd behaviour during these crises. The Russia–Ukraine war led to relatively subdued herding behaviour in commodities, suggesting a limited impact of geopolitical turmoil on collective market behaviour. In stark contrast, the outbreak of the COVID-19 pandemic significantly amplified herding behaviour, particularly in the energy and livestock sectors.

This discrepancy emphasises the different impact of a health crisis versus a geopolitical conflict on market dynamics. This study makes an important contribution to the existing literature as it is one of the first studies to contrast herding behaviour in commodity markets during these two crises. Our results show that not all crises produce comparable market reactions, which underlines the importance of the crisis context when analysing financial market behaviour.

The purpose of this paper is to address the inefficiency in resource allocation for disaster relief procurement operations. It presents a holistic and reconfigurable procurement auctions‐based framework which includes the announcement construction, bid construction and bid evaluation phases.

The holistic framework is developed in a way that auctioneers and bidders compete amongst each other in multiple rounds of the procurement auction. Humanitarian organization in disaster locations are considered as auctioneers (buyers) and suppliers are considered as bidders.

Unique system parameters (e.g. announcement options, priority of items, bidder strategies, etc.) are introduced to represent the disaster relief environment in a practical way. The framework is verified by simulation and optimization techniques using the system characteristics of the disaster relief environment as an input. Based on the parameters and their values, behavioural changes of auctioneers and suppliers are observed.

Combining the three phases of procurement auctions is unique both in the auction literature and in the disaster relief research, and it helps the humanitarian organizations supply the immediate and long‐term requirements in the disaster location more efficiently.

The purpose of this paper is to address the inefficiency problems in procurement operations in disaster relief logistics which are mainly due to the lack of coordination among less organized suppliers and partnerships. Such problems lead to poor responsiveness and hinder timely procurement of required goods.

An auction‐based framework for procurement of goods, which is suitable for a single coordinating platform in disaster relief logistics, is proposed. Integer programming formulations are used in auctioning operations. A simulation model that generates problem instances is used to evaluate and tune system‐level design parameters.

Design parameters greatly affect the behaviour and responsiveness of the system and the performance of the auction‐based framework in different problem instances. Combinations of those parameters may allow suppliers with limited capacities to become more involved in the bidding process. In addition, the procurement shares of bidders may change substantially with different values of the parameters.

Even though the presented framework is inspired from real‐life applications, it is not implemented in real‐life disaster relief operations. The goodness of fit for the framework would best be evaluated by a real disaster case. In addition, transportation scheduling and vehicle routing considerations and budgeting issues are not considered in the framework.

This paper presents an auction‐based framework for less organized suppliers of goods and their partnerships, such as local humanitarian organizations, private companies, and standby partners. The presented framework offers a background for coordination during disaster relief operations which provides opportunities to act as a set of organized entities. This background also helps those entities coordinate their efforts to enhance the capabilities of local governments and NGOs.

The purpose of this paper is to investigate the use of freight containers to store relief items instead of operating a permanent warehouse building.

A mathematical model is developed to determine the location and quantity of containers as well as the type and amount of relief supplies to store in order to investigate the practicality of using freight containers for storage. The model is tested using earthquake risk data, estimates of population under risk, and the distances between cities. An experimental study is performed using Turkish Prime Ministry Disaster and Emergency Management Presidency (abbreviated as AFAD in Turkish) data for total number of relief supplies.

Considering the earthquake risk of possible locations, the results of the study indicate the target locations for containers. The idea of using containers as storage facilities helped beneficiaries to be reached within a short distance and in an efficient way.

The presented model is not implemented in real life disaster relief operations even if it is tested with real earthquake risk, demand and distance data.

To apply this model in practice, the container locations within cities should be determined and managerial operations such as maintenance, environmental, and security planning have to be considered.

This study presents the first analysis of three sub-topics’ intersection: warehousing, pre-positioning in disaster relief, and containerization. To the best of authors’ knowledge, containers have not been considered for storage of relief items in humanitarian logistics before.