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Due to population ageing, the European Union (EU) has adopted active ageing as a guiding principle in labour and retirement policies. Among the strategies for active ageing, age-friendly workplaces play a crucial role. This study compares age-friendly human resource (HR) practices in the Baltic and Nordic countries. The latter are pioneers in active ageing, and as the employment rate of older employees in the Baltics is like that in the Nordic countries, we may assume equally age-friendly workplaces in both regions.

We used the latest CRANET survey data (2021–2022) from 1,452 large firms in seven countries and constructed the fuzzy logic model on age-friendliness at the workplace.

Despite a high employment rate of older individuals in the Baltics, HR practices in these countries fall short of being age-friendly compared to their Nordic counterparts. Larger firms in the Nordic countries excel in every studied aspect, but deficiencies in the Baltics are primarily attributed to the absence of employer-provided health and pension schemes. The usage of early retirement is more frequent in the Nordic countries; however, its conceptualisation as an age-friendly HR practice deserves closer examination. Our findings suggest that the success of active ageing in employment has translated into age-friendly HR practices in larger organisations in the Nordics, but not in the Baltics. It is likely that high employment of older individuals in Estonia, Latvia and Lithuania is a result of the relative income poverty rate.

Our model represents one of the few attempts to utilise fuzzy logic methodology for studying human resource practices and their quantitative evaluation, especially concerning age-friendly workplaces.

Data breaches in the US healthcare sector have more than tripled in the last decade across all states. However, to this day, no established framework ranks all states from most to least at risk for healthcare data breaches. This gap has led to a lack of proper risk identification and understanding of cyber environments at state levels.

Based on the security action cycle, the National Institute of Standards and Technology (NIST) cybersecurity framework, the risk-planning model, and the multicriteria decision-making (MCDM) literature, the paper offers an integrated multicriteria framework for prioritization in cybersecurity to address this lack and other prioritization issues in risk management in the field. The study used historical breach data between 2015 and 2021.

The findings showed that California, Texas, New York, Florida, Indiana, Pennsylvania, Massachusetts, Minnesota, Ohio, and Georgia are the states most at risk for healthcare data breaches.

The findings highlight each US state faces a different level of healthcare risk. The findings are informative for patients, crucial for privacy officers in understanding the nuances of their risk environment, and important for policy-makers who must grasp the grave disconnect between existing issues and legislative practices. Furthermore, the study suggests an association between positioning state risk and such factors as population and wealth, both avenues for future research.

Theoretically, the paper offers an integrated framework, whose basis in established security models in both academia and industry practice enables utilizing it in various prioritization scenarios in the field of cybersecurity. It further emphasizes the importance of risk identification and brings attention to different healthcare cybersecurity environments among the different US states.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

Cesspits are the means for each house to dispose of wastewater in the Bani Kinanah District (BKD) of Jordan, which creates severe environmental complications. This research aimed to find a suitable site for a wastewater treatment plant (WWTP) in BKD.

Geographic Information System (GIS)-based multicriteria decision analysis (MCDA) was used for an optimal site selection for a sewage treatment plant. Several datasets were obtained to prepare the maps of the criteria influencing the choice of the most suitable site for the WWTP. The analytic hierarchy process was used to apply the weights for each factor.

Five classes of suitability were generated: 0.23% very high suitability, 8.49% high suitability, 47.12% moderate suitability, 37.67% low suitability and 6.49% very low suitability. According to Analytical Hierarchy Process (AHP) results, the elevations, slope and groundwater depth have high importance; where their weights 21%, 19% and 17%, respectively. The most suitable site for establishing a WWTP was found in the northern part of the study area, where it is characterized by relatively low elevations (−90 to −93 m), low slope (0–2.5 %), distance from groundwater level (47–82 m) and the space is sufficient for building the plant (25328 m², 8861 m² and 8586 m²).

This research is limited by the availability of data.

The research is invaluable for decision makers involved in urban planning.

Wastewater treatment plants are essential for communities with limited resources such as Jordan. It has also profound impacts on the surrounding environment.

From the present study, it can be concluded that GIS is essential in urban utility establishment, like urban domestic wastewater treatment site selection. Although the study area has adequate potential areas for establishing WWTP, further assessment of flood vulnerability, wastewater amount quantification, population growth and urban expansion must be seriously considered before implementation.

This paper delves into cross-border E-business, unraveling its intricate dynamics and forecasting its future trajectory.

This paper projects the prospective market size of cross-border E-business in China for the year 2023 using the GM (1,1) gray forecasting model. Furthermore, to enhance the analysis, the paper attempts to simulate and forecast the size of China’s cross-border E-business sector using the GM (1,3) gray model. This extended model considers not only the historical trends of cross-border E-business but also the growth patterns of GDP and the digital economy.

The forecast indicates a market size of 18,760 to 18,934 billion RMB in 2023, aligning with the consistent growth observed in previous years. This suggests a sustained positive trajectory for cross-border E-business.

Cross-border e-commerce critically shapes China’s global integration and traditional industry development. The research in this paper provides insights beyond statistical trends, contributing to a nuanced understanding of the pivotal role played by cross-border e-commerce in shaping China’s economic future.

The presence of green spaces plays a vital role in promoting urban sustainability. Urban green parks (UGPs) help create sustainable cities while providing fundamental ecological functions. However, rapid urbanization has destroyed crucial green areas in Ranchi City, endangering inhabitants’ health. This study aims to locate current UGPs and predict future UGP sites in Ranchi City, Jharkhand.

It uses geographic information system (GIS) and analytical hierarchical process (AHP) to evaluate potential UGP sites. It involves the active participation of urban communities to ensure that the UGPs are designed to meet dweller’s needs. The site suitability assessment is based on several parameters, including the normalized difference vegetation index (NDVI), land use and land cover (LULC), population distribution, PM 2.5 levels and the Urban Heat Island (UHI) effect. The integration of these factors enables an evaluation of potential UGP’s sites.

The findings of this research reveal that 54.39% of the evaluated areas are unsuitable, 15.55% are less suitable, 12.76% are moderately suitable, 11.52% are highly suitable and 5.78% are very highly suitable for UGPs site selection. These results emphasize that the middle and outer regions of Ranchi City are the most favorable locations for establishing UGPs. The NDVI is the most important element in UGP site appropriateness, followed by LULC, population distribution, PM 2.5 levels and the UHI effect.

This study improves the process of integrating AHP and GIS, and UGPs site selection maps help urban planners and decision-makers make better choices for Ranchi City’s sustainability and greenness.

The purpose of this study is to analyze the challenges encountered by international nongovernmental organizations (INGOs) operating in armed conflicts within the Democratic Republic of the Congo (DRC) and the Central African Republic (CAR). Through a 20-month fieldwork analysis, this research maps logistical risks and highlights key obstacles on the ground for successful humanitarian deployments in dynamically changing and complex environments. The study brings together academics and practitioners, providing practical and concrete recommendations for nongovernmental organizations (NGOs) to focus on in the conflict zones studied.

Using a mixed-methods approach that combines qualitative and quantitative methods, this research provides valuable insights into the challenges faced by INGOs in conflict zones. After collecting data from the field, including interviews with key stakeholders and on-the-ground observations, the data analysis uses software tools such as Text Analysis Markup System analyzer and Macbeth. By adhering to ethical principles and incorporating a reflexive analysis, the study sheds light on the multidimensional nature of successful humanitarian deployments.

The primary risk in all armed conflict zones, including the DRC and CAR, is insecurity. However, to achieve a successful humanitarian deployment in such contexts, a multidimensional approach is required. This involves first securing the acceptance of local communities and conflict parties, which can be achieved through a deep understanding of both political and customary structures, with a focus on respecting key engagement leaders. Sustainability also plays a crucial role, and NGOs must maintain a secure stock of energy and provide greater initiative for on-the-ground managers to meet the expressed needs of beneficiary populations and involve them from the planning stage onwards. Finally, effective communication, cooperation and collaboration with United Nations Office for the Coordination of Humanitarian Affairs are essential to overcome procurement, technical and security risks, particularly during the initial deployment phases.

This study provides an illustration of the uncommon practice of conducting collaborative research in humanitarian settings amidst two neighboring areas of armed conflict. The authors identified 268 common risk factors across eight categories during five deployment phases. To analyze these risks based on criticality and NGO responsiveness, the authors used a multicriteria method. This approach allowed the authors to validate unanimous judgments, resulting in valuable insights and concrete recommendations.

Overtourism has been identified as a significant global problem with numbers of negative externalities. The purpose of this paper is to contribute to the establishment of a standard that objectively measures the extent of tourism to produce a dynamic ranking of selected European settlements, as there is a lack of studies using sophisticated statistical methods to analyse secondary data on overtourism.

The 28 selected sites, studied according to their involvement in overtourism, were ranked using multi-criteria decision-Mmaking Methods between 2014 and 2023. Rankings were calculated by VIKOR, TOPSIS and MMOORA, and an aggregate ranking was created by using the cross-entropy optimization. Additionally, the annual changes in the rankings were presented graphically using principal component analysis on a two-dimensional space, referred to as the “sites' space.” Finally, the sites were clustered into three distinct groups based on their level of overtourism: less, medium and more. This was achieved through the use of the K-means algorithm.

Following the onset of the pandemic in 2020, there was a notable decline in overtourism. However, following the year 2021, the numbers began to rise once more, and by 2022, they had returned to their pre-pandemic levels. Among the methods, MMOORA demonstrated the most effective performance in comparison to the optimal ranking.

The applied methods with novel rank aggregation could also shed light on the most relevant indicators to overtourism. These included the number of nights spent in paid accommodation per population, the number of overnight visits per population and the number of air passengers.

This study proposes a guided tool for cybersecurity risk assessment tailored for nongovernmental organizations (NGOs), enabling them to comply with cybersecurity policies despite limitations in security awareness, funding and expertise.

A digital transformation is indispensable for ensuring the sustainable operation of NGOs. Embracing a digital manifesto necessitates an awareness of cybersecurity risks, highlighting the critical need for a robust cybersecurity risk assessment methodology. Initial research phases revealed significant shortages in security awareness, funding and expertise. Consequently, this study introduces an intuitive approach tailored specifically for NGOs, supported by a customized tool designed to address their unique requirements. The NIST cybersecurity risk assessment framework and National Cyber-security Authority (NCA) were adopted to define the risk assessment approach. The efficacy of this approach is evaluated qualitatively through a case study involving three NGOs in Saudi Arabia, aimed at assessing their capability to utilize the tool effectively. Following the implementation, a Likert-scale survey gauged satisfaction among NGOs regarding the tool’s utility.

Results from the case study indicate high satisfaction, affirming its alignment with their operational needs and enhancement of compliance with NCA controls. Furthermore, the use of the tool enhances the awareness of NCA’s cybercity requirements and controls.

Based on theoretical and empirical grounds, this research proposes a novel design of security assessment framework tailored for NGO requirements and supported by initiative tool enabling complying with cybersecurity policies and enhances the awareness of cybersecurity controls.

This article introduces the Special Issue on Sustainable Management of Heritage Buildings in long-term perspective.

It starts by reviewing the gaps in knowledge and practice which led to the creation and implementation of the research project SyMBoL—Sustainable Management of Heritage Buildings in long-term perspective funded by the Norwegian Research Council over the 2018–2022 period. The SyMBoL project is the motivation at the base of this special issue.

The editorial paper briefly presents the main outcomes of SyMBoL. It then reviews the contributions to the Special Issue, focussing on the connection or differentiation with SyMBoL and on multidisciplinary findings that address some of the initial referred gaps.

The article shortly summarizes topics related to sustainable preservation of heritage buildings in time of reduced resources, energy crisis and impacts of natural hazards and global warming. Finally, it highlights future research directions targeted to overcome, or partially mitigate, the above-mentioned challenges, for example, taking advantage of no sestructive techniques interoperability, heritage building information modelling and digital twin models, and machine learning and risk assessment algorithms.