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Extant research suggests that consumers value the pursuit, attainment and retention of income security and financial well-being (FWB). The authors aim to expand the relevant literature by examining how consumers' psychosocial characteristics affect and are affected by the pursuit of those objectives.

The authors utilize partial least squares structural equation modeling (PLS-SEM) to evaluate the authors' hypotheses based on a sample of USA and Canadian consumers (n = 619).

The authors' PLS-SEM results provide support for the authors' hypotheses, indicating that individuals' insecure attachments – anxious and avoidant – relate negatively to their income security and FWB. The authors' results also show that these two desirable states relate positively to individuals' undesirable state of social loneliness.

The authors' methodology and findings illuminate the positioning of psychosocial factors as antecedents to and outcomes of income security and FWB. This research also provides a basis for understanding the linear vs curvilinear influences of income security on an individual’s social life.

In the present empirical study, the authors present a rare empirical examination of individuals' income security and FWB as outcomes of their psychosocial profile vis-à-vis insecure attachments. Drawing on established psychometric scales, this study expands the consumer psychology and FWB literature, showing significant linkages between insecure attachments, income security, FWB and social loneliness.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

Since crude oil is crucial to the nation's economic growth, crude oil futures are closely related to many other markets. Accurate forecasting can offer investors trustworthy guidance. Numerous studies have begun to consider creating new metrics from social networks to improve forecasting models in light of their rapid development. To improve the forecasting of crude oil futures, the authors suggest an integrated model that combines investor sentiment and attention.

This study first creates investor attention variables using Baidu search indices and investor sentiment variables for medium sulfur crude oil (SC) futures by collecting comments from financial forums. The authors feed the price series into the NeuralProphet model to generate a new feature set using the output subsequences and predicted values. Next, the authors use the CatBoost model to extract additional features from the new feature set and perform multi-step predictions. Finally, the authors explain the model using Shapley additive explanations (SHAP) values and examine the direction and magnitude of each variable's influence.

The authors conduct forecasting experiments for SC futures one, two and three days in advance to evaluate the effectiveness of the proposed model. The empirical results show that the model is a reliable and effective tool for predicting, and including investor sentiment and attention variables in the model enhances its predictive power.

The data analyzed in this paper span from 2018 through 2022, and the forecast objectives only apply to futures prices for those years. If the authors alter the sample data, the experimental process must be repeated, and the outcomes will differ. Additionally, because crude oil has financial characteristics, its price is influenced by various external circumstances, including global epidemics and adjustments in political and economic policies. Future studies could consider these factors in models to forecast crude oil futures price volatility.

In conclusion, the proposed integrated model provides effective multistep forecasts for SC futures, and the findings will offer crucial practical guidance for policymakers and investors. This study also considers other relevant markets, such as stocks and exchange rates, to increase the forecast precision of the model. Furthermore, the model proposed in this paper, which combines investor factors, confirms the predictive ability of investor sentiment. Regulators can utilize these findings to improve their ability to predict market risks based on changes in investor sentiment. Future research can improve predictive effectiveness by considering the inclusion of macro events and further model optimization. Additionally, this model can be adapted to forecast other financial markets, such as stock markets and other futures products.

The authors propose a novel integrated model that considers investor factors to enhance the accuracy of crude oil futures forecasting. This method can also be applied to other financial markets to improve their forecasting efficiency.

Autism spectrum conditions (ASC) and borderline personality disorder (BPD) have overlapping symptom profiles. Dialectical behaviour therapy (DBT) is an established treatment for self-harm and BPD, but little research has investigated the outcomes of DBT for ASC populations. This exploratory service evaluation aims to investigate the outcomes of a comprehensive DBT programme for adolescents with a diagnosis of emerging BPD and a co-occurring ASC diagnosis as compared to those without an ASC diagnosis.

Differences from the start to end of treatment in the frequency of self-harming behaviours, BPD symptoms, emotion dysregulation, depression, anxiety, the number of A&E attendances and inpatient bed days, education and work status, and treatment non-completion rates were analysed for those with an ASC diagnosis, and compared between those with an ASC diagnosis and those without.

Significant medium to large reductions in self-harming behaviours, BPD symptoms, emotion dysregulation and inpatient bed days were found for those with an ASC diagnosis by the end of treatment. There were no significant differences between those with an ASC and those without in any outcome or in non-completion rates. These findings indicate that DBT may be a useful treatment model for those with an ASC diagnosis, though all results are preliminary and require replication.

To the best of the authors’ knowledge, this is the first study to report the outcomes of a comprehensive DBT programme for adolescents with an ASC diagnosis, and to compare the changes in outcomes between those with a diagnosis and those without.

In this article, we highlight ways in which disability critical race theory (DisCrit) (Annamma et al., 2013), inclusive education and community-based participatory research (CBPR) can be used within professional development schools (PDS) to provide students with disabilities with more access to inclusive classrooms. At a grade 4–6 elementary school, we developed a model of a critical PDS to promote inclusive education and facilitate the transition of students of color with disabilities from self-contained to inclusive classrooms. We conducted semi-structured interviews and used action plan meetings with school administrators, teachers, professionals and students with disabilities and their parents to assess the impact of our critical PDS model. Findings suggest this model had a positive impact on administrators’ and teachers’ critical consciousness, ideological and instructional practices, students of color with disabilities’ social, academic and personal outcomes, as well as a schoolwide culture of inclusion and social justice. This study can inform tailored professional development efforts to improve educators’ inclusive practices.

We conducted semi-structured interviews and used action plan meetings with school administrators, teachers, professionals and students with disabilities and their parents to assess the impact of our critical PDS model.

The findings of this study suggest this model had a positive impact on administrators’ and teachers’ critical consciousness, ideological and instructional practices, students of color with disabilities’ social, academic and personal outcomes, as well as a schoolwide culture of inclusion and social justice.

This study can inform tailored professional development efforts aiming to improve educators’ inclusive practices.

We developed a model of a critical PDS to promote inclusive education and facilitate the transition of students of color with disabilities from self-contained to inclusive classrooms.

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.

The aim of this paper is to evaluate empirically the impact of oil price fluctuations on the relationship between banking sector development and economic growth in oil-importing MENA countries.

The study used the newly developed panel autoregressive distributed lagged (ARDL) approach in order to address any potential endogeneity between research variables.

The empirical results show a unidirectional causality in the long run from oil price to both economic growth and banking sector development for oil-importing countries. Also, banking sector development not only leads directly to economic growth but also can play a moderator role in the oil price—economic growth nexus.

The study has two principal limitations. On the one hand, this study was conducted in a relatively limited sample of countries. On the other hand, the study did not consider others indicators for banking sector development and others macroeconomic variables.

The results found have imperative implications for banks' managers, regulators and researchers. Bank managers should be more concerned with the negative repercussions of oil price fluctuations on the development of their banks. The regulatory authorities must emphasize policies and strategies to further strengthen their banking sector in order to alleviate the negative influence of oil price shocks on economic growth. Researchers focused on finance-growth nexus must take into account the potential influence of oil price shocks.

The developed conceptual model allows examining to what extent the oil price fluctuations might affect the relationship between economic growth and banking sector development. This effect is neither evaluated nor clarified in the relevant literature.

With the growth and profound influence of technology on our life, it is important to address the ethical issues inherent to the development and deployment of technology. Researchers and practitioners submit the need to inspect: how technology and ethics interact, how ethical principles regulate technology and what could be the probable future course of action to execute techno-ethical practices in a socio-technical discourse effectively. To address the thoughts related to techno-ethics, the authors of the present study conducted exploratory research to understand the trend and relevance of technology ethics since its inception.

The study collected over 679 documents for the period 1990–2022 from the Scopus database. A quantitative approach of bibliometric analysis was conducted to study the pattern of authorship, publications, citations, prominent journals and contributors in the subject area. VOS viewer software was utilized to visualize and map academic performance in techno-ethics.

The findings revealed that the concept of techno-ethics is an emerging field and requires more investigation to harness its relevance with everchanging technology development. The data revealed substantial growth in the field of techno-ethics in humanities, social science and management domain in the last two decades. Also, most of the prominent cited references and documents in the database tend to cover the theme of Artificial Intelligence, Big data, computer ethics, morality, decision-making, IT ethics, human rights, responsibility and privacy.

The article provides a comprehensive overview of scientific production and main research trends in techno-ethics until 2022. The study is a pioneer in expanding the academic productivity and performance of embedding ethics in technology.

This paper contributes to the literature as follows. First, it examines if option and stock compensations raise creditor's risk, and which one is more important than the other. Second, it explores if CEO's compensation interacts with CEO overconfidence to raise creditor's risk. Third, it investigates how banks use different loan terms to alleviate their credit risk.

This study used advanced regression analysis and use of generalized methods of moment methodology.

The results show that option compensation is more important than stock compensation in raising credit risk; option compensation interacts with CEO overconfidence, giving rise to a much higher credit risk; and covenant usage is more important than other loan contract terms in mitigating credit risk given that covenant use could not be substituted away by using other loan contract terms such as increasing interest rate, reducing principal or shortening loan duration. This paper has practical implications for credit markets.

The main implication is that hand-collect data are available up to 2010.

It informs creditors the potential sources of loan risk emanating from option rather than stock incentives; it informs creditors that option incentive interacts with CEO overconfidence rendering the credit risk bigger than expected, and it informs creditors the importance of using covenants vis-à-vis other loan contract terms for mitigating compensation and overconfidence risk.

Banks are alerted to the risk due to the interaction between overconfidence and compensations, implying that overconfident managers remunerated with options compensations are more risky than overconfident managers who are not remunerated as such.

This paper is original: (1) The authors show that option compensation is more risky than stock compensation from viewpoint of creditors. This has not been assessed. (2) Interaction between managerial compensation and managerial overconfidence has not been assessed before. (3) Use of different loan contract terms to alleviate risk from overconfident managers (who are prone to over investment but who are innovative according to the literature) has not been evaluated.

Manufacturing firms must embrace smart technologies and develop complex leadership approaches to achieve sustainability. Using the dynamic capability theory, this paper aims to examine the influence of the adoption of industry 4.0 technologies (AT) and paradoxical leadership (PL) on corporate sustainable performance (CSP) of manufacturing small-medium enterprises (SMEs) in Malaysia. Moreover, organisational ambidexterity (OA) is a mediator and strategic flexibility (SF) is a moderator in the study.

The study is a cross-sectional, quantitative study design that collected 395 usable responses through a simple random sampling technique and a close-ended structured questionnaire. Structural equation modelling (SEM) procedures were followed to analyse the data.

The statistical outcome implies that the AT significantly influence CSP and OA and mediate with CSP in the presence of OA. Moreover, PL shows a significant impact on OA, is insignificant on CSP and mediates with OA and CSP. The authors found a significant association between OA and CSP; however, SF did not provide evidence of a moderate effect.

The findings of this study clarify the role that organisational capabilities (OA, AT, PL and SF) play in fostering sustainability. The authors suggest incorporating SMEs from different geographies in other sectors by applying diverse methodologies and relevant constructs.

The result injects new perspectives into policy, managerial and individual levels. Installing OA, AT, PL and SF makes SMEs sustainable.

The empirical validation of the influence of OA and AT on CSP and the interaction of PL and SF enriches the organisational and entrepreneurial literature.