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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.

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 examine the effect of proximity and spatial dependence on the house price index for the nascent market Dar es Salaam, Tanzania. Despite the ongoing housing market transactions, there is no single house price index that takes into account proximity and spatial dependence. The proximity considerations in question are proximal to arterial roads, public hospitals, an airport and food markets. Previous studies on sub-Saharan Africa have focused on the ordinary least squares (OLS)-based hedonic model for the index and ignored spatial and proximity considerations.

Using the OLS and spatial econometric approach, the paper tests for the significance of the two effects – proximity and spatial dependence in the hedonic price model with year dummy variables from 2010 to 2019. The paper then compares the three indices in the following configurations: without the two effects, with proximity factors only, and with both effects, i.e. proximity and spatial dependence.

The inclusion of proximity factors and spatial dependence – spatial autocorrelation – seems to improve the hedonic price model but does not significantly improve the house price index. However, further research should be called for on account of the nascent nature of the market.

The paper brings new knowledge by demonstrating that it may not be necessary to take into account proximity factors and spatial dependence for the Dar es Salaam house price index.

Urban mobility has substantially evolved in several western countries, shifting from interest in road expansion strategies to cater motorized movement to the emphasis on sustainable mobility. This is, however, not the case in several developing countries that still try to accommodate vehicular flows in inner historic cities. This paper aims at providing an assessment framework that helps in evaluating the effect of streetscape development on the walking and cycling environment in historic contexts.

This research follows a two-phase methodology. Phase 1 is the investigation of the literature review including the streetscape design, Sustainable Development Goals (SDGs) and indicators for the assessment of walking and cycling environment. This phase results in developing a set of indicators for the assessment. Phase 2 is the case study including, methods, steps and results of the assessment based on the output of Phase 1. This phase concludes with a discussion on the challenges and recommendations for the enhancement.

The streetscape development in Afrang was insufficient and negatively affected the walking and cycling environment. It was motorized-oriented, instead of enhancing green mobility. The interventions led to more crowds, safety risks and less pleasant experience. Moreover, the car users' experience was enhanced initially; however, the traffic situation did not persist. A sustainable urban mobility approach is necessary to be implemented with consideration to the global level and the relation to SDGs.

There is a gap in tackling the research problem both within the context of Port Said in particular and Egyptian context in general. Local authorities need a clear structured methodology to follow in the development of the streetscape. The assessment indicators gathered can be the basis for evaluating future plans.

The purpose of this paper is to explain the effects of innovation, specialisation, qualifications and sectoral structure on the resilience of German regions (municipal level) facing the Great Recession in 2008/2009.

To calculate the effects of various variables on the resilience of German regions against the Great Recession, the authors use quantile regressions. To measure resilience, the authors create a number of indexes representing different parts of the economy: resistance performance index, recovery performance index, shift-share resistance index, shift-share recovery index, manufacturing resistance index, manufacturing recovery index, service resistance index and service recovery index.

The results of this study confirm that locations with employment growth before the crisis and with a good industry structure show better employment dynamics during and after the crisis. The authors find evidence for positive relationship between innovativeness, qualification, the share of the service sector, specialisation and resistance. The authors obtain positive results for related variety and both resistance and recovery. The share of the manufacturing sector only shows a positive relationship with recovery.

The authors expand the existing literature in three aspects: First, instead of using regions as observation units, the authors conduct the analyses on the basis of municipalities and their surroundings. By doing so, the authors reduce the modifiable area unit problem because the authors do not rely on regions defined for administrative reasons. Second, the authors apply quantile regressions to detect nonlinear effects. Third, in addition to the resilience of the whole economy, the authors also study the resilience of the manufacturing and service sectors separately and examine the resilience of the local shift effect.

Abuja, the capital city of Nigeria, is one of the fastest growing capital cities in sub-Saharan Africa. Recently, the city is experiencing an alarming rate of burglary and violent crimes, while the city planning management frameworks lacks adequate and effective crime mapping, monitoring and management techniques necessary for achieving liveable and safe environment for habitation despite its grandiose spatial planning and aesthetically appealing architectural design as a modern city. Based on police crime records (2007–2018) and geospatial analysis, this paper aims to provide adequate understanding on the interplay of land use configuration and burglary crime formation in residential neighbourhoods of Abuja, Nigeria.

The methods used for the purpose of data collection includes; field survey, Block Environmental Inventory, while inferential statistics and Geographic Information System tools was used for data analysis. The analysis established that Lagos, Nsukka and Enugu Streets are hotspots; while Chief Palace street, Ladoke Akintola and Oka-Akoko streets were found to be cold spots.

This study, however, established the applicability of crime pattern, opportunity theory and routine activity theory in understanding the rising burglary crime events in the study areas and the link between physical characteristics of street block typology and burglary crime pattern. The results of the analysis has in a way affirmed the positions of the theories, while disagreed with them in cases where the results indicated contrary outcome.

This paper concluded with inference drawn from the results that supported mixed-use development but with built-in crime prevention through environmental design strategies as effective burglary crime prevention mechanisms that contribute to crime rate reduction.

This paper examines the post-COVID-19 travel intentions to Kenya among Hong Kong outbound travelers using the theory of planned behavior (TPB) over three different time horizons of 1, 5, and 10 years.

An extension was made by including two new constructs of perceived destination image and travel constraints. A cross-sectional sample of Hongkongers was surveyed. Data were collected using a self-administrated bilingual (English and Chinese) online survey. Exploratory factor analysis, linear regression and mediation analysis were conducted to test the research model.

The findings from 216 Hongkongers reveal that different combinations of the four constructs, namely, perceived behavioral control, attitude, subjective norms, and destination image, share a positive effect on individuals' travel intention to Kenya over the three different time horizons. Travel constraints act as a significant negative mediator on the four constructs in predicting travel intention to Kenya among Hongkongers.

The results provide useful insight to Kenya's destination marketing organization (DMO) and Hong Kong outbound travel agencies to integrate prominent elements into marketing strategies to arouse travel intention and expand their business prospects, which will also accelerate tourism recovery in the post-pandemic era.

By integrating two extended variables into the TPB model, this study makes a contribution by overcoming the deficiency of the original theory.

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.

This study investigated consumers’ willingness to pay (WTP) for a local, organic chicken breed “Taphao Thong-Kasetsart” and the drivers that shape consumers’ WTP across different meat preferences in Thailand.

Face-to-face interviewing was used to collect data at food-service outlets in Bangkok and Nakhon Pathom provinces, Thailand. Data analysis used the double-bounded dichotomous choice model across different consumers’ meat preferences for preferred chicken and non-preferred chicken consumers.

The results showed that there were different WTP amounts for local organic chicken across consumers’ meat preferences, with a higher WTP among non-preferred chicken consumers. This indicated that local organic chicken may attract more consumers in the alternative market. Consumers’ values and attitudes to taste drove chicken-preferred consumers to pay a premium for local organic chicken; health concerns mattered for non-preferred chicken consumers. These findings should provide useful information for food marketing campaigns based on consumers’ preferences.

The study contributed to understanding consumer heterogeneous preferences toward WTP for local organic chicken. The findings indicated that analyzing WTP across different meat preferences highlighted more effective marketing strategies to achieve the premium that consumers would pay. These strategies could help farmers to enlarge their local organic market share, leading to increased revenue and farmers’ well-being.

The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention from investors, policy makers and researchers. This study investigates neural networks for composite property price index forecasting from ten major Chinese cities for the period of July 2005–April 2021.

The goal is to build simple and accurate neural network models that contribute to pure technical forecasts of composite property prices. To facilitate the analysis, the authors consider different model settings across algorithms, delays, hidden neurons and data spitting ratios.

The authors arrive at a pretty simple neural network with six delays and three hidden neurons, which generates rather stable performance of average relative root mean square errors across the ten cities below 1% for the training, validation and testing phases.

Results here could be utilized on a standalone basis or combined with fundamental forecasts to help form perspectives of composite property price trends and conduct policy analysis.