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This study aims to explore the spatial externalities of apartment vacancy rates on housing rent by considering multiple vacancy durations.

This research uses smart meter data to measure unobservable vacant houses. This study made a significant contribution by applying building-level smart meter data to housing market analysis. It examined whether vacancy duration significantly affected apartment rent and whether the relationship between apartment rent and vacancy rate differed depending on the level of housing rent.

The primary finding indicates that there is a significant negative correlation between apartment rent and vacancy duration. Considering the spatial externalities of apartment vacancy rates, the apartment vacancy rates of surrounding buildings did not show any statistical significance. Moreover, quantile regression results indicate that although the bottom 10% of apartment rent levels showed a negative correlation with all vacancy durations, the top 10% showed no statistical significance related to vacancies.

This study measures the extent of spatial externalities that can differentiate taxation based on housing vacancies.

The findings indicate that landlords have asymmetric information about their buildings compared with the surrounding buildings, and the extent to which price adjusts for long-term vacancies differs depending on the level of apartment rent.

The aim of this research is to explore the relationship between destination supply-side factors, visitor demand-side factors and the role of local government authorities in supporting the drive tourism market with effective interventions. A mixed methods approach was used to gather qualitative data from 14 destination stakeholders, which informed the development of a survey of 397 drive tourists to the Atherton Tablelands, in the far north of Australia. The findings identified stakeholder concerns about fragmented regional promotions by different regional entities, weakened destination branding and infrastructure needs. Drive tourist surveys indicated that although the destination provides a competitive tourism experience, there were concerns about the availability of information. This research highlights the danger of destination disunity, and the theoretical and practical contributions of the learning destination concept to understanding the importance of destination-wide, stakeholder collaboration, although it may be difficult to implement.

The purpose of this paper is to study the influence mechanism of different levels of social capital (Structure holes–local network attributes and indirect ties–global network attributes) and organizational culture on the creativity of key inventors, and the role of organizational culture between social capital and creativity.

The paper tested the hypotheses with a sample of patent data accumulated from 46 firms in Chinese electronic information and automobile sectors. Negative binomial regression was used to explore the factors influencing the creativity of key inventors.

The paper discovers that structural holes are valuable social capital for the creativity of key inventors and very important in firms with a collective and conservative culture. Moreover, it also locates that key inventor are more creative in firms with an individualistic and competitive culture than those in firms with a collective and conservative culture.

This study emphasizes the influence of social capital on creativity and contributes to R&D management. It highlights structural holes are certainly important to key inventors in a collective and conservative culture, thus contradicting preceding studies that locate structural holes useful solely in an individualistic culture. This finding broadens our knowledge of the benefits of this network structure. Also, this debate challenges several basic views on structural holes currently.

This study aims to explore the consumer perceptions of cognition and intention to visit pilot zone of international medical tourism as emerging, developed medical tourism destinations.

Using a survey-based quantitative method, based on a survey of 439 tourists who have cross-border travel experience, the partial least squares approach was performed to test the hypotheses.

The results show that internal factors had a stronger influence on destination image compared to external factors. Among different factors, preferential policies had the greatest impact on intention to visit. Perceived quality had a stronger effect on intention to visit than preference. Geographical distance had a varied effect, with those furthest away in Northeast China showing greater intention to visit compared to closer regions.

This study explores the impact of multidimensional destination perception on medical tourists’ behavioural intention in emerging destinations by integrating the push-pull theory and theory of planned behaviour and tests how geographical distance affects intention to visit emerging destinations. Using China international medical tourism pilot area as a typical case of medical tourism emerging destinations for empirical analysis. This research offers guidance for branding and marketing strategies, contributes to a deeper understanding of medical tourists’ destination choices, enriches the theoretical explanation of emerging destination choice in medical tourism and provides valuable insights for destination recovery.

Tehran’s health-care system is growing, yet it lacks emergency planning procedures. The premise of this study is that the urban environment around a hospital is just as robust as the hospital itself. This study aims to look at hospital resilience in an urban setting to see where it may be improved to keep the hospital operational during a disaster.

The urban resilience (UR) of Amir-Alam Hospital was analyzed in this study using a customized version of the United Nations Office for Disaster Risk Reduction’s City Resilience Profiling Tool. The 34 indications were broken down into five categories.

The result revealed that the hospital’s UR score was 51.75 out of 100, indicating medium resilience. The results of this study enable the decision-makers to determine what measures they may take to improve the hospital’s resilience in terms of its surrounding urban context.

The originality of this research is based on the surrounding urban environment’s resilience as an integral part of hospital resilience.

The study aims to devise a comprehensive evaluation model (CEM) for evaluating spatial equity in the layout of elderly service facilities (ESFs) to address the inequity in the layout of ESFs within city center communities characterized by limited land resources and a dense elderly population.

The CEM incorporates a suite of analytical tools, including accessibility assessment, Lorenz curve and Gini coefficient evaluations and spatial autocorrelation analysis. Utilizing this model, the study scrutinized the distributional equity of three distinct categories of ESFs in the city center of Xi’an and proposed targeted optimization strategies.

The findings reveal that (1) there are disparities in ESFs’ accessibility among different categories and communities, manifesting a distinct center (high) and periphery (low) distribution pattern; (2) there exists inequality in ESFs distribution, with nearly 50% of older adults accessing only 18% of elderly services, and these inequalities are more pronounced in urban areas with lower accessibility, and (3) approximately 14.7% of communities experience a supply-demand disequilibrium, with demand surpassing supply as a predominant issue in the ongoing development of ESFs.

The CEM formulated in this study offers policymakers, urban planners and service providers a scientific foundation and guidance for decision-making or policy amendment by promptly assessing and pinpointing areas of spatial inequity in ESFs and identifying deficiencies in their development.

This study aims to explore the good crowding effect among Indian domestic travellers during the COVID-19 pandemic in the context of the city destination. This study uses the framework of social motivation theory to achieve the objective.

This study adopted a qualitative research design by taking the case of Shimla, Himachal Pradesh. Using purposive sampling, semi-structured interviews were conducted with 37 respondents, and themes were drawn manually.

The analysis found four themes that create a good crowding effect among domestic tourists, namely, convenience and price; familiarity and place attachment; social affiliation; and safety. The themes indicated that despite the pandemic, and constant occurrences of new variants, Indian domestic tourists’ on-site attitude towards crowding was favourable.

Firstly, the good crowding effect during the pandemic could have been better understood using empirical data. Secondly, the results cannot be generalized, specifically for developed economies.

This study offers practical implications to destination managers and local administrative bodies for whom achieving sustainability in urban tourism has always been concerning. These include developing infrastructural facilities, encouraging cultural activities in city centres and improving the perception of safety to sustain the good crowding effect.

The affective dimension involved in making a travelling decision played a significant role in the post-pandemic phase. While suppliers needed survival, tourists needed social affiliation and escape from the mandated home isolation due to multiple phases of COVID-19 lockdown in India. This study adds value to society by emphasising that the need for social affiliation among travellers remains intact, and the tourism industry should embrace this transformation.

While most of the pandemic-related studies criticised crowd and tourists’ crowd averting behaviour, this study reported that the good crowding effect could also be an outcome owing to different factors. Therefore, this study offers distinctive nuance of tourists’ behaviour in the post-COVID-19 phase, allowing destination managers and tourism stakeholders to re-think their strategies.

The world over is becoming urbanized, and people are migrating to cities in large numbers in search of opportunities. The increased urbanization has posed challenges such as congestion, rising crime, and growing urban poverty. The governments respond by providing amenities such as schools, hospitals, and housing to meet to increase in demand for these facilities. However, there is a need for the provision of facilities that meets the expectations of the people, particularly on the proximity of amenities and bundles of utility-bearing housing characteristics. In an attempt to address the challenge mentioned, the study estimated the hedonic characteristics influencing the willingness to accept and willingness to pay for housing facilities in the Eastern Cape Province, South Africa. Using a multiple linear regression model and artificial neural network, the study found out that properties with a bathroom, garage and large floor size have a higher value compared to properties without these facilities.When making decisions to acquire a property, buyers consider the availability of discounts and the prevailing property price. Overall, willingness to pay and accept decisions are mainly determined by location and the price at which homogeneous neighborhood properties were sold. Therefore, the study recommends that urban town planners and other housing authorities prioritize the construction of properties with larger floor areas, parking bays, and bathrooms using a cost-effective mechanism that makes the properties affordable to residents.

The sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.

Informational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.

Findings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.

This work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.