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Global crises have become increasingly recurrent events that jeopardize public-private partnerships (PPPs). In this context, the purpose of this paper is to expose the PPP-crisis research agenda by combining bibliometric and network analyses.

The PPP literature associated with global crises between the 2008 global financial crisis and 2022 was analyzed in three stages: (1) paper selection and screening for the inclusion/exclusion of articles relevant to this research, (2) semantic network development for examining thematic relationships among selected papers by considering the co-occurrence of keywords within the chosen studies and (3) calculation of network metrics for analysis.

The paper identified six research avenues for the PPP-crisis agenda: public interest, relational governance, risk management, user-pay PPPs, crisis management and financial performance. The PPP-crisis literature has spread significantly in the last five years driven by the case study approaches on a national or regional basis. Conversely, non-crisis periods generate room to strengthen user-pay PPPs and relational governance. The pandemic and post-pandemic times shared the priorities of the 2008 financial crisis but also strengthened the management of the risks and the structural drivers of the global crisis.

This study demonstrates that during global crisis periods, the public interest and financial performance gain relevance in a detriment of structural solutions to social legitimacy erosion of PPPs because of the urgency of giving tools to the public and private sectors to tackle the financial issues, which steer future issues for PPPs.

The missing travel time data for roads is a common problem encountered by traffic management departments. Tensor decomposition, as one of the most widely used method for completing missing traffic data, plays a significant role in the intelligent transportation system (ITS). However, existing methods of tensor decomposition focus on the global data structure, resulting in relatively low accuracy in fibrosis missing scenarios. Therefore, this paper aims to propose a novel tensor decomposition model which further considers the local spatiotemporal similarity for fibrosis missing to improve travel time completion accuracy.

The proposed model can aggregate road sections with similar physical attributes by spatial clustering, and then it calculates the temporal association of road sections by the dynamic longest common subsequence. A similarity relationship matrix in the temporal dimension is constructed and incorporated into the tensor completion model, which can enhance the local spatiotemporal relationship of the missing parts of the fibrosis type.

The experiment shows that this method is superior and robust. Compared with other baseline models, this method has the smallest error and maintains good completion results despite high missing rates.

This model has higher accuracy for the fibrosis missing and performs good convergence effects in the case of the high missing rate.

The purpose of this paper is to investigate the functionality and effectiveness of the Carbon Risk Real Estate Monitor (CRREM tool). The aim of the project, supported by the European Union’s Horizon 2020 research and innovation program, was to develop a broadly accepted tool that provides investors and other stakeholders with a sound basis for the assessment of stranding risks.

The tool calculates the annual carbon emissions (baseline emissions) of a given asset or portfolio and assesses the stranding risks, by making use of science-based decarbonisation pathways. To account for ongoing climate change, the tool considers the effects of grid decarbonisation, as well as the development of heating and cooling-degree days.

The paper provides property-specific carbon emission pathways, as well as valuable insight into state-of-the-art carbon risk assessment and management measures and thereby paves the way towards a low-carbon building stock. Further selected risk indicators at the asset (e.g. costs of greenhouse gas emissions) and aggregated levels (e.g. Carbon Value at Risk) are considered.

The approach described in this paper can serve as a model for the realisation of an enhanced tool with respect to other countries, leading to a globally applicable instrument for assessing stranding risks in the commercial real estate sector.

The real estate industry is endangered by the downside risks of climate change, leading to potential monetary losses and write-downs. Accordingly, this approach enables stakeholders to assess the exposure of their assets to stranding risks, based on energy and emission data.

The CRREM tool reduces investor uncertainty and offers a viable basis for investment decision-making with regard to stranding risks and retrofit planning.

The approach pioneers a way to provide investors with a profound stranding risk assessment based on science-based decarbonisation pathways.

In the literature there are numerous tests that compare the accuracy of automated valuation models (AVMs). These models first train themselves with price data and property characteristics, then they are tested by measuring their ability to predict prices. Most of them compare the effectiveness of traditional econometric models against the use of machine learning algorithms. Although the latter seem to offer better performance, there is not yet a complete survey of the literature to confirm the hypothesis.

All tests comparing regression analysis and AVMs machine learning on the same data set have been identified. The scores obtained in terms of accuracy were then compared with each other.

Machine learning models are more accurate than traditional regression analysis in their ability to predict value. Nevertheless, many authors point out as their limit their black box nature and their poor inferential abilities.

AVMs machine learning offers a huge advantage for all real estate operators who know and can use them. Their use in public policy or litigation can be critical.

According to the author, this is the first systematic review that collects all the articles produced on the subject done comparing the results obtained.

The purpose of this paper is to shed light on the state-of-the-art about sustainable tourism. Despite the significant growth of publications exploring sustainable tourism, the debate on the relationship between tourism and sustainability remains open. In addition, the sector faces the challenge of the 2030 Agenda, as the authors have not yet managed to curb environmental degradation and social disparities. This research needs to be comprehensively addressed to inform future steps and to identify sustainable tourism practices that will advance the goals of this action plan.

This study applies a mixed methodology, using a bibliometric analysis performed by VOSviewer and SciMat software of 311 articles from the Web of Science. In addition, it includes an in-depth analysis of trending research topics in the field during 2019 and 2020.

After 20 years of research on sustainable tourism, there is still significant dispersion of studied topics, frameworks and applications. The results show the evolution of research towards the study and measurement of sustainable change, social and cultural aspects and the development of responsible governance models.

New stakeholder relationships models require a methodological and technological framework. Further progress in sustainable tourism guided by the 2030 Agenda demands the establishment of worldwide recognised measurement indicators and policy frameworks.

With a mixed methodological approach and a special focus on the sustainable development goals (SDGs), this paper provides a “state-of-the-art” update to sustainability research in tourism. The results obtained have been associated with their contribution to achieving SDGs.

尽管探索可持续旅游业的出版物大幅增长, 但关于旅游业和可持续性之间关系的辩论仍然没有结束。此外, 该部门还面临着2030年议程的挑战, 因为我们还没有设法遏制环境退化和社会差异。这项研究需要全面解决, 以便为未来的步骤提供信息, 并确定可持续旅游的做法, 以推进本行动计划的目标。

本研究采用混合方法, 通过VOSviewer和SciMat软件对来自科学网的311篇文章进行文献计量分析。此外, 它还包括对2019年和2020年期间该领域的趋势性研究课题的深入分析。

经过20年的可持续旅游研究, 所研究的课题框架和应用仍然存在很大的分散性。我们的结果显示, 研究朝着研究和测量可持续变化、社会和文化方面以及发展负责任的治理模式的方向发展。

新的利益相关者关系模型需要一个方法学和技术框架。在2030年议程的指导下, 可持续旅游业的进一步发展需要建立世界公认的测量指标和政策框架。

通过混合方法和对可持续发展目标（SDGs）的特别关注, 本文为旅游业的可持续性研究提供了 “最先进 “的更新。获得的结果与他们对实现可持续发展目标的贡献有关。

A pesar del importante crecimiento de las publicaciones que exploran el turismo sostenible, el debate sobre la relación entre turismo y sostenibilidad sigue abierto. Además, el sector se enfrenta al reto de la Agenda 2030, ya que aún no se ha conseguido frenar la degradación medioambiental y las disparidades sociales. Esta investigación debe abordarse de forma exhaustiva para informar de los pasos futuros e identificar las prácticas de turismo sostenible que harán avanzar los objetivos de este plan de acción.

Este estudio aplica una metodología mixta, utilizando un análisis bibliométrico realizado por el software VOSviewer y SciMat con 311 artículos de la Web of Science. Además, incluye un análisis en profundidad de los temas de investigación de tendencia en el campo durante 2019 y 2020.

Después de 20 años de investigación sobre el turismo sostenible, sigue habiendo una importante dispersión de los marcos temáticos estudiados y de las aplicaciones. Nuestros resultados muestran la evolución de la investigación hacia el estudio y la medición del cambio sostenible, los aspectos sociales y culturales y el desarrollo de modelos de gobernanza responsable.

Los nuevos modelos de relaciones con los grupos de interés requieren un marco metodológico y tecnológico. Los nuevos avances en el turismo sostenible guiados por la Agenda 2030 exigen el establecimiento de indicadores de medición y marcos políticos reconocidos a nivel mundial.

Con un enfoque metodológico mixto centrado especialmente en los Objetivos de Desarrollo Sostenible (ODS), este trabajo proporciona una actualización del “estado del arte” a la investigación de la sostenibilidad en el turismo. Los resultados obtenidos se han asociado con la consecución de los ODS.

Many employers experiment with virtual working modes for project-based work. Virtual internships are one such mode that is gaining increasing popularity worldwide, particularly e-internships that require remote working with employers. However, little is known about the extent to which e-internships present learning opportunities to such e-interns.

The current study examined mentoring experiences among a cross-sectional sample of 158 e-interns working for different companies. Data were collected using an online survey in two data collection rounds.

The length of the e-internships did not increase mentoring satisfaction, but the likelihood of e-interns having a mentor was higher the longer the e-internships. Mentoring was offered irrespective of working hours per week. Mentoring increased reported skill development, particularly in relation to their communication skills and their ability to think strategically about problems. In addition, mentored e-interns were more likely to have opportunities to cooperate with and help others. They likewise had opportunities to share information, knowledge and experiences.

The study recruited interns from various countries. Potentially relevant cultural differences were not explored as part of this study.

The results demonstrate that the benefits of mentoring observed in relation to traditional internships can be fostered in e-internships. E-internships represent an opportunity for managers and employees, regardless of company size, to become mentors. E-internships thus represent another work-integrated as well as work-applied learning and skill development opportunity that creates additional options for many interns and organisations alike.

The evidence suggests that mentoring is becoming a regularly available feature for virtual and temporary workers such as e-interns, many of which are hired for short-term projects. As remote working has become a standard practice, e-internships are on the rise – and worthy of further study in order to promote best practices.

In Kenya, gaps exist in health service provision to slum residents, especially service availability and access to quality care. There is also little information on the health status of people living in slums other than in Nairobi. The purpose of this paper is to generate evidence for use in designing interventions to improve health services in four mid-sized slums in Embu, Nyeri and Thika, Kenya.

A cross-sectional survey of clients receiving services in health facilities was conducted in the targeted slums. Data were collected through face-to-face interviews. Factor scores were generated using the Rasch model; simple and multivariate logistic regression analyses were done using the R statistical software.

Overall, 81 per cent of the 203 participants reported being satisfied with health services. Most clients (89 per cent) reported that health facility staff greeted them warmly; 82 per cent said their consultation was private. The facility type, waiting time and client experience with service providers determined their satisfaction (p < 0.05).

Healthcare managers can improve client satisfaction levels by understanding the client flow in their facilities and addressing causes of client dissatisfaction, such as long waiting times, while at the same time promoting facilitating factors.

The authors use latent variable modelling to compute client satisfaction scores, which were dichotomised into two categories and fitted into a logistic regression model to identify factors that influence client satisfaction. Health facility clients in the four slums are satisfied with services and have confidence the providers will serve them in a friendly and professional manner that promotes respect and quality care. The paper recommend healthcare managers in similar settings carry out client flow analysis and institute remedial measures to address long waiting times. Qualitative studies are recommended to determine the reasons behind the high satisfaction levels reported in this study.

This article explores memory work and storytelling as an organising tool through family histories, offering theoretical and methodological implications and extending existing conceptualisations of memory work as a feminist method. This approach is termed as impressionist memory work.

To illustrate impressionistic memory work in action, the article presents two family histories set during Second World War and invite the reader to engage in the “undoing” of these stories and dominant ways of knowing through storytelling. This method challenges the taken-for-granted roles, plots and detail of family histories to uncover the obscured or silenced stories within, together with feminine, affective and embodied subjectivities, marginalisation and social inequalities.

This study argues that impressionistic memory work as a feminist method can challenge the silencing and gendering of experiences in co-constructed and co-interpreted narratives (both formal and informal ones).

This study shows that engagement with impressionistic memory work can challenge taken-for-granted stories with prominent male actors and masculine narratives to reveal the female actors and feminine narratives within. This approach will offer a more inclusive perspective on family histories and deeper engagement with the marginalised or neglected actors and aspects of our histories.