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The aim of the research is to reveal information with regard to being a digital nomad as a family. Within this brief, the aim is to provide information regarding the reasons for choosing the digital nomad lifestyle of families, the female and male thoughts regarding the experience, destination selection factors and the difficulties and conveniences of digital nomadism for family aspects.

The data were obtained through a semi-structured interview questionnaire with a British digital nomad family, individually from the wife and husband, using a qualitative research design in the scope of the phenomenological research.

It was determined that having a better lifestyle, being willing to spend more time with family and traveling with them were the reasons for becoming a digital nomad. The opinions of the woman and man are in parallel. While the main features of being a digital nomad are freedom and flexibility, having time to spend with family is also important. Factors for choosing a destination as a nomad were access to nature, quality of life, cost of living, quality of the food, climate, proximity to other families who are nomads and interest in nonschool education. As a family, they meet their needs and wants, such as going to a local shop or staying in a rented house, but prefer to use restaurants and other facilities if their stay is short. Although having children motivates digital nomadism, it has been determined that families prefer to stay in a fixed place as nomads since it is not appropriate for children over a certain age to travel frequently.

The study provides detailed information regarding a family experience with digital nomadism through a case study.

Artificial intelligence is one of the most significant and active fields of study in the last few years. Artificial intelligence-derived robotic technologies known as chatbots are gaining interest from both academic and industry sectors. By analyzing the development and patterns of research on the chatbot phenomena within the tourism field, this study seeks to develop a theoretical framework for the interaction between chatbots and tourism.

The Web of Science (WoS) database’s 33 articles on chatbots related to travel and hospitality were examined between 2019 and 2024 using VOSviewer software for bibliometric and thematic content analysis.

Research on chatbots for tourism and hospitality appears to be in its early stages. The factors influencing tourists' intentions to use chatbots have been thoroughly researched; the attitudes, perceptions and behavioral intentions of destinations, travel agencies and restaurant patrons regarding chatbots were examined, and it was found that the quantitative research approach was dominant. In addition, the majority of the studies are based on a particular theory or model.

This is one of the first attempts to directly comprehend and depict the interconnected structures of studies on the interaction between chatbots and tourism through the use of network analysis. Furthermore, the study’s findings can offer academics a comprehensive viewpoint and a reference manual for more accurate assessment and oversight of the chatbot-tourism interaction. Regarding the lack of research on the topic and the fragmented structure of the studies that exist, it is imperative to provide both a comprehensive overview and a roadmap for future investigations into the usage of chatbots in the travel and hospitality sector.

This study examines the impact of raising the ceiling value of Electronic Commerce Custom Declarations (ECCD) on Turkey's export performance processed via ECCD during the COVID-19 period.

This paper examines the impact of the pandemic conditions on Cross-Border Electronic Commerce (ECCD) exports from Turkey to 47 countries over 42 months before and during the pandemic. An empirical analysis using the Pooled Mean Group (PMG) and Mean Group (MG), Panel Autoregressive Distributed Lag (ARDL) approach was conducted to identify the factors affecting export flows.

The findings suggest that raising the ceiling of the ECCD trade is a vital factor in increasing exports. and this result is robust after controlling for pandemic conditions. On the other hand, although the COVID-19 shock mitigates the export volume of ECCD in the short run, it changes by reversal and increases the export level in the long run. Additionally, the number of COVID-19 cases and deaths in Turkey have a significant and negative impact on export flows in the short run, while they have a positive and significant effect in the long run.

The results of this study have practical implications for policymakers, emphasizing the potential and significance of Cross-Border E-Commerce (CBEC) trade.

The study is a pioneering effort in the literature of CBEC to explore how changes in the upper limit on customs declarations can affect export flows, taking into account the impact of the COVID-19 pandemic.

The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for megaprojects and their stakeholders.

The framework was initially developed by conducting a comprehensive literature review to obtain extensive knowledge about disruption management and megaprojects. Focus group discussion (FGD) sessions with the participation of the construction practitioners were then organized to validate and strengthen the findings of the literature review. Consequently, 17 selection factors were identified and categorized as requirement, ability and outcome. Lastly, the most convenient DA methods for megaprojects were identified by performing integrated fuzzy analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) analysis. Additionally, consistency analysis was also conducted to verify the reliability of the results.

The results revealed that the measured mile method is the most appropriate DA method for megaprojects. In case the measured mile method cannot be adopted due to various technical and contractual reasons, the decision-makers are proposed to consider program analysis, work or trade sampling, earned value analysis and control chart method, respectively. Second, the selection factors such as “Comprehensible analysis procedure,” “Existing knowledge and experience about a particular DA method,” “Ability to resolve greater number of disruption events,” “Ability to resolve complex disruption events,” “Ability to exclude factors that are not under the owner's responsibility” and “General acceptance by practitioners, courts, and arbitration, etc.” were given the top priority by the experts, highlighting the critical aspects of the DA methods.

Disruption claims in megaprojects are very critical for the contractors to compensate for the losses stemming from disruption events. Although the effective use of DA methods maximizes the accuracy and reliability of disruption claims, decision-makers can barely implement these methods adequately since past studies neglect to present extensive knowledge about the most convenient DA methods for megaprojects. Thus, developing a decision support framework for the selection of DA methods, this study is the earliest attempt that examines the mechanisms and inherent differences of DA methods. Additionally, owing to the robustness and versatility of this research approach, the research approach could be replicated also for future studies focusing on other project-based industries since disruption is also a challenging issue for many other industries.

The metaverse offers great potential for creating a new educational environment with unique experiences. Currently, it has been integrated into many stages of education, including classroom study aids, clinical skill interaction and image training simulators, thanks to a new generation of Internet applications. This paper aims to provide a comprehensive systematic review using bibliometric analysis on the metaverse in health education and analyze the trends and patterns of research output within the field.

The paper conducts bibliometric analysis and follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure a rigorous and transparent review process. Specifically, this article identifies research questions, develops a data-collection strategy and establishes a screening approach that includes determining relevant keywords and applying inclusion and exclusion criteria.

A bibliometric analysis is conducted comprising 231 studies from 145 scientific journals to assess the trends, patterns and collaboration networks in research on the use of metaverse technology in health education. This paper provides insights into the research themes, publication trends and countries leading in this field, which can guide future research in this field.

The use of metaverse technology in health education has gained momentum in recent years. Despite this interest, comprehensive studies to review and analyze the existing literature on this topic systematically are lacking. In response, this paper provides a systematic review that explores the potential role of the metaverse in health education. By considering the current research, key trends, research hotspots and opportunities for future investigations are identified. The findings not only shed light on the current state of research but also offer guidance for advancing this exciting field.

The purpose of this research is to conduct a theoretical prediction study exploring the effectiveness of different content marketing strategies in expanding the second-hand market for fashion brands, comparing the costs and risks involved in these strategies in practice.

First, the expert interview method is employed to extract the content marketing strategies of the fashion second-hand market. Then, a descriptive space that is able to identify various fashion brand images is established. Then, experts' perceptions of the relationships between content marketing strategies and fashion brand image dimensions are obtained through a subjective evaluation procedure. Data of semantic evaluation were quantified and analyzed using the fuzzy logic method.

When fashion brands expand to the second-hand market, they not only need to focus on improving the individual differentiation of products but also give priority to the quality of products and services and the overall customer experience. Exploring the “social impact strategy” will become an important direction for the development of fashion brands in the future.

The research methodology employed herein exhibits a noteworthy degree of novelty. This study introduces a pioneering theoretical prediction approach utilizing fuzzy logic, marking the inaugural exploration of this emerging and captivating dimension within the context of the study. Simultaneously, the study provides comparative results among content marketing strategies for expanding the fashion second-hand market, offering guidance for market expansion.

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.

The primary objective of this study is to investigate the application of blockchain technology (BCT) in the agri-food supply chain, focusing on traceability and food safety.

The study employed a semi-structured interview method with representatives from the cherry supply chain to evaluate their awareness and acceptance of BCT's impact. Additionally, the analytic hierarchy process (AHP) was utilized to determine digital investment priorities in supply chain strategies. By applying the supply chain operations reference (SCOR) model framework to the cherry supply chain, the study aimed to address the question “Which process model is suitable for implementing BCT in the agri-food supply chain?”

The global agri-food supply chains are characterized by significant food losses, escalating prices along the chain, and food safety risks. Concurrently, consumer concerns regarding food safety, quality and transparency are on the rise. BCT, with its ability to ensure data integrity, immutability, and seamless tracking of chain movements, presents immense potential as a secure infrastructure in the agri-food supply chain traceability.

The developed analytic framework and the study's findings can be adapted to different sectors and different sub-sectors within agri-food supply chains.

The present study focused on examining the effect of treated wastewater (TWW) on soil chemical properties. Also, efforts were made to compare the soil chemical properties under TWW irrigation with that under groundwater (GW).

During the years 2021 and 2022, surface and subsurface soil samples were randomly collected in triplicate by using an auger fortnightly at two depths (20 and 40 cm) from the selected spot areas to represent the different types of irrigation water sources: TWW and GW. Samples of the GW and the TWW were collected for analysis.

This study examines the impact of TWW on soil characteristics and the surrounding environment. TWW use enhances soil organic matter, nutrient availability and salt redistribution, while reducing calcium carbonate accumulation in the topsoil. However, it negatively affects soil pH, electrical conductivity and sodium adsorption ratio, although remaining within acceptable limits. Generally, irrigating with TWW improves most soil chemical properties compared to GW.

In general, almost all of the soil’s chemical properties were improved by irrigating with TWW rather than GW. Following that, wastewater is used to irrigate the soil. Additionally, the application of gypsum to control the K/Na and Ca/Na ratios should be considered under long-term TWW and GW usage in this study area in order to control the salt accumulation as well as prevent soil conversion to saline-sodic soil in the future. However, more research is needed to thoroughly investigate the long-term effects of using TWW on soil properties as well as heavy metal accumulation in soil.