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This study aims to examine the reuse of plastic and fly ash (FA) to improve the soil and achieve sustainable development goals.

Sand from the Anzali port was reinforced with Geopet (GP) and stabilized with FA plus 3% sodium hydroxide. The GP was placed in FA-stabilized soil and the California bearing ratio (CBR), and unconfined compressive strength (UCS) tests were performed on samples at the optimum moisture content.

The results showed that the improvement in the optimum CBR was 174.9%. The UCS increased 15.25% and 48.65% in soil reinforced with three layers of GP plus 15% FA over those containing 10% and 5% FA, respectively. Additionally, the current analysis used response surface methodology (RSM) to investigate the impact of FA percentage, GP layers and their interaction on CBR. The results highlight the efficacy of the used RSM model, as evidenced by the significantly low p-value (<0.0001).

This demonstrates the suitability and effectiveness of RSM for evaluating CBR in this scientific study.

This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations of these models in handling temporal information in financial time series.

Employing a robust methodological framework, the study systematically compares a range of Transformer models, including first-generation and advanced iterations like Informer, Autoformer, and PatchTST, against benchmark models (HAR, NBEATSx, NHITS, and TimesNet). The evaluation encompasses 80 different stocks, four error metrics, four statistical tests, and three robustness tests designed to reflect diverse market conditions and data availability scenarios.

The research uncovers that while first-generation Transformer models, like TFT, underperform in financial forecasting, second-generation models like Informer, Autoformer, and PatchTST demonstrate remarkable efficacy, especially in scenarios characterized by limited historical data and market volatility. The study also highlights the nuanced performance of these models across different forecasting horizons and error metrics, showcasing their potential as robust tools in financial forecasting, which contradicts the findings of Zeng et al. (2023)

This paper contributes to the financial forecasting literature by providing a comprehensive analysis of the applicability of Transformer-based models in this domain. It offers new insights into the capabilities of these models, especially their adaptability to different market conditions and forecasting requirements, challenging the existing skepticism created by Zeng et al. (2023) about their utility in financial forecasting.

Recognising the literature of a field is vital for advancement in that field. Yet, there has not been a systematic analysis of recent publications published in the Journal of Hospitality and Tourism Insights (JHTI). Therefore, this research aims to do a bibliometric analysis of articles published in JHTI during the previous five years.

This study used bibliometric techniques and indicators to analyse JHTI publications from 2018 to 2022. The data utilised in the study were obtained from Scopus and subsequently subjected to analysis through the Bibliometrix software.

The findings show good collaboration between the production components (country, institution and author) in JHTI. The co-occurrence analysis of keywords comprises five clusters; the co-citation analysis comprises six; and a group of articles connected with psychological aspects and areas such as motivation, attitude, customer engagement, place attachment and behavioural intention was the most remarkable cluster. Sharing economy, destination marketing, destination image and some, to an extent, social media and revenue management are just a few of the niche themes that have the potential to come up.

This study will be helpful as a roadmap for researchers in different fields who are interested in such studies, as well as for editorial board members and those who work in JHTI.

Scholars and practitioners may benefit the most from this research by obtaining insight into the development of JHTI's research and the areas of the hospitality and tourism industries that need more study.

The current study is both necessary and valuable because it is the first to provide insight into the effectiveness and intellectual framework of the hospitality and tourism literature selected by the JHTI.

This study aims to provide a framework for the interaction of blockchain technology, the audit process and International Financial Reporting Standards (IFRS).

This study was conducted in three phases. In the first phase, a meta-synthesis method was used until 2020. Out of 87 papers, a total number of 15 were selected, and 72 were excluded after an initial screening. In the second phase, 11 interviews were held with experts with sufficient experience and expertise in blockchain technology, accounting and auditing. These interviews were held between 2020 and 2021. The sampling was purposive (targeted) in type, along with snowball sampling. In the third phase, a combination of questionnaire-based method and the fuzzy Delphi method was used. The research population for this phase consisted of accounting professors, members of the Iranian Association of Certified Public Accountants and accounting and technology professionals. Following the selection of the Delphi panel, 35 questionnaires were collected between 2021 and 2022 for analysis.

The results showed that in line with the interaction of blockchain technology, audit process and IFRS, 52 indicators were confirmed in eight components. Moreover, “Verifiability,” “Timeliness” and “Predictive value” were the most influential factors, respectively, according to the conceptual model. In addition, higher average scores of experts’ views were related to “Transparency audit reports” and “Increasing the quality of the auditor’s judgment”, respectively.

Blockchain is a complex subject, and there has been very little published research on the intersection of IFRS and blockchain technology. It is crucial for the audit profession and technology professionals to focus on the interaction of blockchain technology with the qualitative characteristics of information. This is an area that has not been thoroughly researched yet. The interaction of blockchain technology, improvements in the audit process and adherence to IFRS is a significant development in accounting and auditing.

Climate change has led to a rise in the frequency, intensity and scope of droughts, posing significant implications for businesses. This study examines the impact of local community drought levels on audit pricing. Additionally, it explores the moderating effects of high-tech industries, auditor busyness and the level of local community concern regarding the drought crisis.

This study employs a mixed-methods approach to rigorously test the research hypotheses. The quantitative phase of the study utilizes a sample of 1,278 firm-year observations from Iran’s capital market. For the analysis of the quantitative data, ordinary least squares regression with clustered robust standard errors is used. Additionally, this research supplements its quantitative findings with qualitative evidence obtained through semi-structured interviews with 19 Iranian audit partners.

The results suggest that firms operating in provinces facing severe droughts experience notably higher audit fees. Furthermore, the positive relationship between drought and audit fees is weakened when auditors are busy, local community concern regarding the drought crisis is high or the firm operates within high-tech industries. These findings are supported by a range of robustness checks and qualitative evidence gathered from the field.

This research contributes to the growing literature on climate change by examining the influence of local community drought levels on audit pricing within an Iranian context. Additionally, our study sheds light on how high-tech industries, auditor workload and the level of local community concern regarding the drought crisis moderate the relationship between drought and audit fees. Importantly, our study pioneers in providing mixed-methods evidence of the association between drought severity and audit fees.

This research contributes to the existing literature on the connection between trust and investment activities by exploring the effect of trust in the retirement system on dwelling investments.

This study utilizes data including 28 OECD countries from 2009 to 2020, and employs panel fixed effects and GMM estimators.

The analysis reveals a negative relationship between trust in the retirement system and investment in dwellings. Notably, this is found to be more evident in countries that promote neo-liberalized welfare systems.

The implications of our results are particularly relevant for policymakers and international construction firms.

The primary contribution of this paper extends the “trust–pension investment behavior” nexus. We explore whether individuals with diminished trust in the retirement system consider investing in the property market as an alternative means to safeguard their financial well-being during retirement.

The purpose of this study is to comprehensively analyze the research article retractions in social sciences over the past decade (2014–2023).

The study used scientometric methods to evaluate the prevalence, patterns and factors contributing to social sciences article retractions. Bibliographic data of retracted articles were collected from the Retraction Watch Database under an agreement signed with the database. Further, citations of the retracted articles were collected from Scopus and Google Scholar. The analysis encompasses performance assessment and citation-based analysis to reveal the trend of retraction and scrutinize the impact of retracted articles.

Over the past decade, article retractions have shown dynamic trends, with notable fluctuations in recent years. Further, investigating the time taken for article retraction reveals the urgency of addressing issues identified soon after publication. Scientific misconduct and publication-related concerns emerge as primary factors leading to retractions. Countries such as Russia, the USA, China and publishers such as Elsevier and Taylor and Francis led in the retractions of social science articles. A significant portion of retracted works had garnered academic attention prior to retraction and even after retraction.

This study can contribute to a better understanding among scholars and stakeholders of the trends and reasons for retractions of research articles in the social sciences.

This paper aims to investigate the relationship between the proprietary costs of financial reporting and the comparability of financial statements with the interactive role of information asymmetry.

Data were selected from the information of all the listed companies on the Tehran stock exchange from 2011 to 2021, based on 781 observations. A multiple regression model is used to analyze data.

Results convey a significant relationship between proprietary costs of financial reporting and comparability of financial statements. Furthermore, information asymmetry has a significant impact on the relationship between proprietary costs of financial reporting and the comparability of financial statements.

Unlike previous studies, this study applies future dependent variables and the residual of dependent and independent variables in the additional analyses, which support the primary hypotheses.