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This paper aims to examine the existence of the ripple effect from Amsterdam to the housing markets of other regions in The Netherlands. It identifies which regional housing markets are influenced by house price movements in Amsterdam.

The paper considers the ripple effect as a lead-lag effect and a long-run convergence between the Amsterdam and regional house prices. Using the real house prices for second-hand owner-occupied dwellings from 1995q1 to 2016q2, the paper adopts the Toda–Yamamoto Granger Causality approach to study the lead-lag effects. It uses the autoregressive distributed lags (ARDL)-Bounds cointegration techniques to examine the long-run convergence between the regional and the Amsterdam house prices. The paper controls for house price fundamentals to eliminate possible confounding effects of common shocks.

The cumulative evidence suggests that Amsterdam house prices have influence on (or ripple to) all the Dutch regions, except one. In particular, the Granger Causality test concludes that a lead-lag effect of house prices exists from Amsterdam to all the regions, apart from Zeeland. The cointegration test shows evidence of a long-convergence between Amsterdam house prices and six regions: Friesland, Groningen, Limburg, Overijssel, Utrecht and Zuid-Holland.

The paper adopts an econometric approach to examine the Amsterdam ripple effect. More sophisticated economic models that consider the asymmetric properties of house prices and the patterns of interregional socio-economic activities into the modelling approach are recommended for further investigation.

This paper focuses on The Netherlands for which the ripple effect has not yet been researched to the authors’ knowledge. Given the substantial wealth effects associated with house price changes that may shape economic activity through consumption, evidence for ripples may be helpful to policy makers for uncovering trends that have implications for the entire economy. Moreover, the analysis controls for common house price fundamentals which most previous papers ignored.

This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).

The research methodology employed technical procedures based on bibliographic and exploratory analyses. A traditional investigation was carried out using the Scopus, ScienceDirect and Web of Science databases. The papers selection and classification took place in three steps considering only studies in English language and published in electronic journals (from 2008 to 2022). The investigation led up to the selection of 46 publications (10 presenting literature reviews and 36 proposing CSMs).

The findings showed that CSMs are usually formulated using Financial Analysis, Machine Learning, Statistical Techniques, Operational Research and Data Mining Algorithms. The main databases used by the researchers were banks and the University of California, Irvine. The analyses identified 48 methods used by CSMs, the main ones being: Logistic Regression (13%), Naive Bayes (10%) and Artificial Neural Networks (7%). The authors conclude that advances in credit score studies will require new hybrid approaches capable of integrating Big Data and Deep Learning algorithms into CSMs. These algorithms should have practical issues considered consider practical issues for improving the level of adaptation and performance demanded for the CSMs.

The results of this study might provide considerable practical implications for the application of CSMs. As it was aimed to demonstrate the application of optimisation methods, it is highly considerable that legal and ethical issues should be better adapted to CSMs. It is also suggested improvement of studies focused on micro and small companies for sales in instalment plans and commercial credit through the improvement or new CSMs.

The economic reality surrounding credit granting has made risk management a complex decision-making issue increasingly supported by CSMs. Therefore, this paper satisfies an important gap in the literature to present an analysis of recent advances in optimisation methods applied to CSMs. The main contribution of this paper consists of presenting the evolution of the state of the art and future trends in studies aimed at proposing better CSMs.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

The purpose of this stud is to analyze the financialization effect on oil prices.

This study applied the technique of multibreak point analysis with Bai and Perron test plus VAR methodology.

Findings revealed that there was no effect on oil prices.

To the best of the author’s knowledge, this is the first paper combining the multibreakpoint analysis with VAR for the period analyzed in the present work.

Existence of working poverty reduces the effectiveness of the strategy of “increasing employment to reduce poverty”. Developed countries are already concerned about it but insufficient attention has been made by developing countries. Focusing on developing countries this study identifies (1) the effects of trade openness (TO) on working poverty and (2) whether the working poverty trap exists or not in developing countries. Both objectives are also analyzed for three subsamples of low income, lower-middle income and upper-middle income developing countries.

Panel data for 98 developing countries over the period of 2000–2016 have been collected for the study. Fixed effect and GMM methods are applied for static and dynamic analysis, respectively.

The study finds that TO significantly reduces working poverty rate (WPR) (mainly driven up by upper-middle income developing countries). The positive association between WPR with its previous year's rate proves the existence of working poverty trap.

The study's outcome is subject to selected time, countries and methods. Future research should use more improve methods and should identify the channels through which TO could affect working poverty.

Middle income and upper-middle income developing countries should increase TO to reduce the working poverty. Low income developing countries that have the highest working poverty should search the way to derive beneficial effects of trade on working poverty.

Working poverty is not only a developed country issue rather it is a global phenomenon. Hence, it is expected that the study will raise the social consciousness about this phenomenon in developing countries too.

The study fulfills the gaps of identifying the effects of TO on working poverty and existence of in-work poverty trap in developing countries.

Sports leagues have stood out in the entertainment industry due to their great economic value and cultural impact. This is the case of the American sports leagues, with emphasis on the National Basketball Association (NBA), whose largest Latin American market lies on Brazil. The aforementioned league’s audience is constantly growing, a fact that can be partially explained by the encouragement provided for its viewers to interact through social media, in a phenomenon called social TV. Accordingly, the aim of the present study is to investigate how social TV works as a means for Brazilian fans to coproduce their NBA broadcasting enjoyment through social media interactions.

The authors conducted a netnography on the community of fans engaged in Twitter hashtag #NBAnaESPN, which was released by ESPN to promote audience integration during NBA games' broadcasting.

A theorization about the role played by social TV in the way fan culture articulates through social media to enjoy broadcasting media products was herein presented. The findings of this study have evidenced three categories concerning the role played by television broadcasting, social media and the fandom in NBA consumption by Brazilian fans. Based on these findings, the authors got to the conclusion that social TV establishes a mediatized environment where fan culture can be articulated through social media to enable interactions about television broadcasting.

The study was limited to members of the Brazilian NBA audience who engage in the official social media of the league’s broadcasting.

The study heads toward a theoretical generalization based on the research results.

This paper aims to explore smokefree prison policy, from the perspective of people in custody in Scotland.

In total, 77 people in custody in Scotland were interviewed in the period leading up to implementation of a nationwide prison smokefree policy. Data were thematically analysed to identify the diversity of views and experiences.

Participants described a widespread awareness in prisons of plans to implement a smokefree policy from 30 November 2018. Opinions about smokefree prisons varied among participants based on perceptions of the fairness, and anticipated positive and negative consequences of removing tobacco from prisons. At the time of the interviews, people in custody were responding to the impending smokefree policy, either by proactively preparing for the smokefree rule change or by deploying avoidance strategies. Participants described opportunities and challenges for implementing smokefree policy in prisons across three main themes: the role of smoking in prison, prison smoking cessation services and motivations for quitting smoking among people in custody.

This study exploring smokefree prisons from the perspectives of people in custody has several novel features which extend the evidence base. The findings highlight measures for jurisdictions to consider when planning to prohibit smoking in their prisons in the future. These include the need for evidence-based smoking cessation support in advance of smokefree policy, effective communication campaigns, consideration of broader structural determinants of health in prison and ongoing measures to reduce rates of return to smoking post release.

Stakeholder capitalism (SC) advocates that organisations should focus on creating long-term value for all key stakeholders rather than maximising short-term profits for shareholders. This paper aims to explore whether and how business organisations have applied stakeholder capitalism principles (SCPs) during the COVID-19 pandemic and how these efforts were communicated in integrated reports.

This study is based on the content analysis of the text extracted from the integrated reports of 22 companies categorised as excellent in the 2020 EY Excellence in Integrated Reporting Award 2020. The research material consisted of paragraphs that reflected how the company observed the SCPs in practice.

The stakeholder responsibility principle was the most represented by the examined companies, followed by the principles of continuous creation, stakeholder engagement and stakeholder cooperation. The COVID-19 pandemic has propelled the necessity of implementing innovative solutions to counteract the virus's spread. It has also spurred the need for two-way digitalised communication between the executives and stakeholders. The new situation also required collaborative approaches in the forms of partnerships, joint initiatives and programmes to ensure employee safety and help communities recover from the social and economic impacts of the pandemic.

This study links SC with integrated reporting (IR) and contributes to the literature by providing new insights into how SCPs have been applied during the COVID-19 pandemic. This discussion suggests that whereas these principles determine how the companies must act to satisfy stakeholders expectations, integrating reporting may help develop a report that is stakeholder-oriented and which responds to their information needs.