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The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

This study aims to examine the predictive power of childhood adversity and severity of positive symptoms on suicidality, controlling for selected sociodemographics factors, among hospitalized patients diagnosed with schizophrenia in Jordan.

This study used a descriptive-explorative design. The study was conducted at two major psychiatric hospitals in Jordan. The targeted sample was 66 patients diagnosed with schizophrenia. Data was collected using a structured format in the period February–April 2024.

A two-step multiple hierarchical regression analysis was conducted. In the first model, childhood adversity and the severity of positive symptoms were entered. In the second model, sociodemographic variables were entered. The analysis revealed that the first model (F = 5.35, p = 0.007) was statistically significant. The second model (F = 717, p < 0.001) was statistically significant. Furthermore, the analysis revealed that childhood adversity was not a significant predictor for suicidality. However, positive symptoms and patients’ demographics (age, number of hospitalizations and length of being diagnosed with schizophrenia) were significant predictors of suicidality. The analysis revealed that childhood adversity was not a significant predictor of suicidality. However, positive symptoms and patients’ demographics (age, number of hospitalizations and length of being diagnosed with schizophrenia) were significant predictors of suicidality.

One limitation of this study is related to the sample and the setting where there were only 66 patients recruited from governmental hospitals within inpatient wards. Thus, the upcoming studies should include more participants from private hospitals and different hospital settings including outpatient and emergency departments.

The research provides empirical insights that positive symptoms, age hospitalization and schizophrenia diagnosis length were significant predictors of suicidality. At the same time, childhood adversity was not a significant predictor of suicidality.

The current research contributes to expanding mental health studies. Moreover, this study enlarges the body of knowledge in the academic world and clinical settings. It supports the disciplines of psychology, mental health and social sciences by increasing knowledge of the complicated relationships among childhood adversity, positive symptoms and suicidality.

This paper fulfills an identified need to study childhood adversity with comorbid psychiatric disorders such as schizophrenia, as well as psychiatric mental health covariates.

The aim of this study is to critically examine the transparency and reporting practice of Environmental, Social, and Governance (ESG) controversies within the pharmaceutical and textile industry. Based on the four core dimensions of transparency, we explore which reporting medium is most frequently chosen for the disclosure of negative ESG contributions, the nature and information content of the disclosed incidents and how voluntary adherence to sustainability reporting standards and independent assurances affect the reporting.

We use conceptual content analysis and employ a counter-accounting approach to analyse the disclosure of 190 ESG controversies in 104 corporate reports from the pharmaceutical and textile industries, covering a three-year period from 2018–2020.

The very large majority of controversies are reported only once in the legal proceedings section of the annual report, but not again in the sustainability report, where it would be necessary to provide a balanced picture. Moreover, companies tend to disclose only those controversies that are either associated with high media attention or are expected to be related to litigation, resulting in 26 per cent of controversies not being disclosed at all. The overall quality of disclosure is unsatisfactory and in need of improvement, but comparably higher in the pharmaceutical industry than in the textile industry. Interestingly, neither the application of sustainability reporting standards nor independent assurance seems to positively impact the disclosure behaviour.

Our paper provides new insights into the shortcomings of current ESG controversy disclosures by revealing patterns of selective reporting practices and the strategic framing of issues. In addition, it contributes to the debates on corporate cherry-picking in the adoption of sustainability reporting guidelines and on the effectiveness of external assurance of sustainability reports. Based on the findings, it offers important implications for practitioners, in particular management, policy makers, rating agencies and assurance providers.

The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic.

Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets.

Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map.

Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.

Emotional intelligence (EI) and self-concept (SC) play a very important role in one’s life. The purpose of this paper is to investigate the SC and EI of tribal and nontribal university students.

The research used a quantitative approach, 100 nontribal (50 male and 50 female) and 100 tribal (50 male and 50 female) students were selected by nonprobability sampling method. The Bangla version of the self-concept questionnaire (Beck et al., 2001) and the emotional intelligence questionnaire (Hyde et al., 2002) were used to measure the SC and EI of students. Pearson correlation, t-test and post hoc tests were used for statistical analysis.

The findings of this study showed that the tribal and nontribal students differ significantly on the measure of SC and EI (p < 0.01). Although nontribal students showed higher SC than tribal students, tribal students showed a higher level of EI than nontribal students. The results also showed that gender significantly affects SC and EI (p < 0.01). Males have higher SC and EI than females. Furthermore, the study revealed that socioeconomic status differs significantly in the case of SC. Finally, the result also showed a significant positive correlation (r = 0.245, p < 0.01) between SC and EI.

The results of the research are only based on the students of one university besides the sample size is limited.

This research allowed the authors to determine the practical implications. The findings suggest that there is a significant difference in SC and EI between tribal and nontribal students, with nontribal students showing higher levels of SC. This implies that interventions and programs aimed at enhancing SC may be particularly beneficial for tribal students. The study also reveals that there are significant differences in SC and EI between tribal and nontribal adolescent boys and girls. This highlights the importance of considering gender differences when designing interventions to improve SC and EI among tribal and nontribal students. Moreover, educators, parents and policymakers can use these findings to develop targeted interventions and strategies to enhance SC among tribal students, with the aim of improving their overall well-being, academic achievements and success in life.

This paper adds to the literature on the SC and EI of tribal and nontribal university students by describing the difference in levels and a significant correlation. This paper obtains an innovative statistical approach to develop the findings so that information can be used in the future.