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This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology.

Data analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness.

This study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance.

This study does not use a primary database, but uses secondary data from official sources that can be accessed by the public.

The paper includes implications for the development of intelligent technology based on big data and also requires policy innovation.

Sustainable tourism development.

This study finds the expansion of new theory competitiveness of ecotourism destinations.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

This study aims to examine the impact of the beginning of the Russia–Ukraine war and the Wagner Group’s attempted military coup against Putin’s regime on the European defense sector, consisting of weapons manufacturers.

The authors use the event study methodology to quantify the impact. That is, the authors assume that markets are efficient, and abnormal stock returns around the event dates capture the magnitudes of the impacts of the two events studied on European defense sector companies. The authors use the capital asset pricing model and two different multifactor models to estimate expected stock returns, which serve as the benchmark necessary to obtain abnormal returns.

The start of the war on February 24, 2022, when the Russian forces invaded Ukraine, was followed by high positive abnormal returns of up to 12% in the next few days. The results are particularly strong if multiple factors are used to control for the risk of the defense stocks. Conversely, the authors find a negative impact of the rebellion initiated by the mercenary Wagner Group’s chief, Yevgeny Prigozhin, on June 23, 2023, on the abnormal returns of defense industry stocks on the first trading day after the event.

To the best of the authors’ knowledge, this is the first study of the impact of the Russia–Ukraine war on the defense sector. Furthermore, this is the first study to measure the financial implications of the military coup initiated by the Wagner Group. The findings contribute to a rapidly growing literature on the financial implications of military conflicts around the world.

The aim of this research is to understand the relationship between cultural buildings, economic powers and social justice and equality in architecture and how this relationship has evolved over the last hundred years. This research seeks to identify architectural and urban elements that enhance social justice and equality to inform architectural and urban designs and public policies.

The author explores the relationship between case studies of museums, cultural centers and libraries, and economic powers between 1920 and 2020 in Stockholm, Sweden. The author conducts a historical analysis and combines it with statistical and geographically referenced information in a Geographic Information System, archival data and in situ observations of selected buildings in the city. The author leverages the median income of household data from Statistics Sweden, with the geographical location of main public buildings and the headquarters of main companies operating in Sweden.

This analysis presents a gradual commercialization of cultural buildings in terms of location, inner layout and management, and the parallel filtering and transforming of the role of users. The author assesses how these cultural buildings gradually conformed to a system in the city and engaged with the market from a more local and national level to global networks. Findings show a cluster of large public buildings in the center of Stockholm, the largest global companies' headquarters and high-income median households. Results show that large shares of the low-income population now live far away from these buildings and the increasing commercialization of cultural space and inequalities.

This research provides a novel image of urban inequalities in Stockholm focusing on cultural buildings and their relationship with economic powers over the last hundred years. Cultural buildings could be a tool to support equality and stronger democracy beyond their primary use. Public cultural buildings offer a compromise between generating revenue for the private sector while catering to the needs and interests of large numbers of people. Therefore, policymakers should consider emphasizing the construction of more engaging public cultural buildings in more distributed locations.

The application of circular building adaptability (CBA) in adaptive reuse becomes an effective action for resource efficiency, long-lasting usability of the built environment and the sped-up transition to a circular economy (CE). This paper aims to explore to which extent CBA-related strategies are applied in adaptive reuse projects, considering enablers and obstacles.

A stepwise theory-practice-oriented approach was followed. Multiple-case studies of five circular adaptive reuse projects in The Netherlands were investigated, using archival research and in-depth interviews. A cross-case analysis of the findings was deductively conducted, to find and replicate common patterns.

The study revealed that configuration flexibility, product dismantlability and material reversibility were applied across the case studies, whereas functional convertibility and building maintainability were less applied. Low cost of material reuse, collaboration among team members and organisational motivation were frequently observed enabling factors. Lack of information, technical complexities, lack of circularity expertise and infeasibility of innovative circular solutions were frequently observed obstacles to applying CBA.

This paper provides practitioners with a set of CBA strategies that have been applied in the real world, facilitating the application of CBA in future adaptive reuse projects. Moreover, this set of strategies provides policymakers with tools for developing supportive regulations or amending existing regulations for facilitating CE through adaptive reuse.

This study provides empirical evidence on the application of CBA in different real-life contexts. It provides scholars and practitioners with a starting point for further developing guiding or decision-making tools for CBA in adaptive reuse.

With the aim of monitoring the existing regulations that are applicable to community of owners facing delinquency, in view of the importance of this issue for the achievement of the Urban Agenda, the present study aims to analyse the most stringent and controversial measures available for the community of owners facing delinquency from a comparative perspective.

The present work addresses the recent legislative amendments that have taken place at national level in this field in several countries and analyses to what extent they have addressed the delinquency problem faced by community of owners.

The current paper shows that, in the end, legal certainty, the prospective legal and economic effects on mortgage lending and constitutional concerns are the underlying reasons behind the reluctance to implement some stringent measures to face delinquency. It also shows that recent amendments concerning alternative dispute resolution mechanisms are a missed opportunity.

Community of owners plays a key role in cities for the achievement of the Urban Agenda, so the periodical contributions from co-owners are paramount to the proper implementation of urban regeneration, energy efficiency and accessibility policies. To this end, the paper analyses existing regulations that are applicable to community of owners facing delinquency, which may increase in the coming years due to the current socioeconomic context.

This paper builds on existing research and goes one step further by addressing the recent legislative amendments that have taken place recently at national level in this field. These measures may serve as an inspiration to other EU legal systems.

This study delves into the nuanced implications of short-sale constraints on stock prices within the context of stock market efficiency. While existing research has explored this relationship, inconsistencies persist in their findings. The purpose of this study is to conduct a comprehensive review of literature to elucidate the reasons behind these disparities.

A systematic review of existing theoretical and empirical studies was conducted following the PRISMA method. The analysis centered on discerning the factors contributing to the divergence in projected stock prices due to these constraints. Key areas explored included assumptions related to expectations homogeneity, revisions, information uncertainty, trading motivations and fluctuations in supply and demand of risky assets.

The review uncovered multifaceted reasons for the disparities in findings regarding the influence of short-sale constraints on stock prices. Variations in assumptions related to market expectations, coupled with fluctuations in perceived information uncertainty and trading motivations, were identified as pivotal factors contributing to differing projections. Empirical evidence disparities stemmed from the use of proxies for short-sale constraints, varied sample periods, market structure nuances, regulatory changes and the presence of option trading.

This study emphasizes the significance of not oversimplifying the impact of short-sale constraints on stock prices. It highlights the need to understand these effects within the broader context of market structure and methodological considerations. By delineating the intricate interplay of factors affecting stock prices under short-sale constraints, this review provides a nuanced perspective, contributing to a more comprehensive understanding in the field.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

Over the last decade, investments in green energy companies have witnessed noticeable growth rates. However, the glacial pace of the world economic restoration due to COVID-19 pandemic placed a high degree of uncertainty over this market. Therefore, this study investigates the short- and long-term relationships between COVID-19 new cases and WilderHill New Energy Global Innovation Index (NEX) using daily data over the period from January 23, 2020 to February 1, 2023.

The authors utilize an autoregressive distributed lag bounds testing estimation technique.

The results show a significant positive impact of COVID-19 new cases on the returns of NEX index in the short run, whereas it has a significant negative impact in the long run. It is also found that the S&P Global Clean Energy Index has a significant positive impact on the returns of NEX index. Although oil has an influential effect on stock returns, the results show insignificant impact.

Governments have the chance to flip this trend by including investment in green energy in their economic growth stimulation policies. Governments should highlight the fundamental advantages of investing in this type of energy such as creating job vacancies while reducing emissions and promoting innovation.

First, as far as the authors are aware, the authors are the first to examine the effect of oil prices on clean energy stocks during COVID-19. Second, the authors contribute to studies on the relationship between oil prices and renewable energy. Third, the authors add to the emerging strand of literature on the impact of COVID-19 on various sectors of the economy. Fourth, the findings of the paper can add to the growing literature on sustainable development goals, in specific the papers related to energy sustainability.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.