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The application of circular building adaptability (CBA) in adaptive reuse becomes an effective action for resource efficiency, long-lasting usability of the built environment and the sped-up transition to a circular economy (CE). This paper aims to explore to which extent CBA-related strategies are applied in adaptive reuse projects, considering enablers and obstacles.

A stepwise theory-practice-oriented approach was followed. Multiple-case studies of five circular adaptive reuse projects in The Netherlands were investigated, using archival research and in-depth interviews. A cross-case analysis of the findings was deductively conducted, to find and replicate common patterns.

The study revealed that configuration flexibility, product dismantlability and material reversibility were applied across the case studies, whereas functional convertibility and building maintainability were less applied. Low cost of material reuse, collaboration among team members and organisational motivation were frequently observed enabling factors. Lack of information, technical complexities, lack of circularity expertise and infeasibility of innovative circular solutions were frequently observed obstacles to applying CBA.

This paper provides practitioners with a set of CBA strategies that have been applied in the real world, facilitating the application of CBA in future adaptive reuse projects. Moreover, this set of strategies provides policymakers with tools for developing supportive regulations or amending existing regulations for facilitating CE through adaptive reuse.

This study provides empirical evidence on the application of CBA in different real-life contexts. It provides scholars and practitioners with a starting point for further developing guiding or decision-making tools for CBA in adaptive reuse.

This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City.

The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117.

The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City.

Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost.

The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam.

This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy.

This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.

This study is based on the consumer purchase intention (CPI) in real estate. The purpose of this study is to investigate the link between CPI and preferred individual investment capacity in buying real estate properties. This study investigates if commonly known factors of CPI such as attitude, social power or subjective norms, perceived behavior power or control, location, surrounding environment and socialization can influence a consumer’s preferred investment amount when buying a house, either for own use or for rental purpose.

A total of 334 respondents participated in this study. The survey data was analyzed using factor analysis technique, ordinary least square technique and Poisson pseudo maximum likelihood technique.

This study finds that location, surrounding environment, property/construction papers, roads, mosque/temple and fire services significantly influence the preferred investment amount of a real estate investor.

This study suggests that a link exists between CPI and real estate investment decision through factors such as location, surrounding environment, legal documentation and communication facility. These identified CPI factors require serious consideration by the real estate developers and their financing partners.

Network coverage is crucial for the adoption of advanced Smart Home applications. The commonly used log-based path loss model is not able to accurately estimate WiFi signal strength in different houses, as it does not fully consider the impact of building morphology. To better describe the propagation of WiFi signals and achieve higher estimation accuracy, this paper studies the basic building morphology characteristics of houses.

A new path loss model based on a decision tree was proposed after measuring the WiFi signal strength passing through multiple housing units. Three types of regression models were tested and compared.

The findings demonstrate that the log-based path loss model fits small houses well, while the newly proposed nonlinear path loss model performs better in large houses (area larger than 125 m2 and area-to-perimeter ratio larger than 2.5). The impact of building design on path loss has been proven and specifically quantified in the model.

Proposed an improved model to estimate indoor network coverage. Quantify the impacts of building morphology on indoor WiFi signal strength. Improve WiFi signal strength estimation to support Smart Home applications.

Hotels provide high-quality guest experiences to generate perceived value for money (PVM), positively influencing word-of-mouth (WOM) and electronic word-of-mouth (eWOM) communication. This study aims to (1) verify the impacts of the perceived quality by the guests about their experiences in hotels on their PVM; (2) inspect the influence of guests' perception of hotel prices on PVM; (3) examine the impacts of guest PVM on their hotel experiences on WOM and eWOM and (4) investigate the consequences of the hotel guests' behavioural engagement on social networking sites (HGBE-SNS) on eWOM.

This quantitative and descriptive study consists of a survey with 371 guests who evaluated their experiences at three hotels in Brazil. PLS-SEM tested the hypothetical model that resorted to the stimulus-organism-response theory (S-O-R), proposed by Mehrabian and Russell (1974). Cluster Analysis compared the PVM, WOM and eWOM of groups of hotel guests with different levels of social media engagement.

Perceived quality by hotel guests positively impacts PVM. Perceived price negatively influences PVM. PVM had a positive and robust impact on WOM. PVM impacts and explains weakly eWOM. In contrast, HGBE-SNS affects and better explains eWOM than PVM.

This unprecedented investigation concomitantly exhibits the relationships between perceived quality, price, PVM, WOM, eWOM and HGBE-SNS. Hotels must offer high perceived quality experiences to influence PVM and WOM positively. PVM is unable to stimulate eWOM strongly. HGBE-SNS is pivotal for guests to share their hotel experiences through eWOM. This study suggests marketing strategies for hospitality companies to amplify customer engagement on SNS.

Hotels offer high-quality guest experiences to positively impact their emotions, satisfaction, perceived value, word-of-mouth (WOM) and electronic word-of-mouth (eWOM). This study aims to investigate the impacts of the quality perceived by hotel guests on their positive emotions, negative emotions, perceived value and satisfaction; verify the impacts of the price on perceived value and satisfaction; examine the impacts of satisfaction on WOM and eWOM; and test the moderating effect of hotel guests’ behavioural engagement on social networking sites (HGBE-SNS) on the relationship between satisfaction and eWOM.

This survey included 371 guests who assessed their experiences at three Brazilian hotels. Structural equation modelling tested the hypothetical model supported by the stimulus-organism-response (S-O-R) theory (Mehrabian and Russell, 1974).

The quality perceived by hotel guests (stimulus) positively impacts perceived value, positive emotions and satisfaction and negatively affects negative emotions (organism). Price (stimulus) negatively impacts perceived value but does not affect satisfaction. Perceived value positively impacts satisfaction. Satisfaction positively impacts WOM and eWOM (responses). The HGBE-SNS moderates the relationship between satisfaction and eWOM.

To the best of the authors’ knowledge, this study is the first that simultaneously demonstrates the relationships between perceived quality, price, perceived value, positive and negative emotions, satisfaction, WOM, eWOM and HGBE-SNS. Hotels must offer their guests high-quality services to positively impact’ perceived value, positive emotions, satisfaction and WOM. Low prices boost the perceived value but do not directly increase guest satisfaction. Satisfied hotel guests share their experiences via WOM, but high HGBE-SNS is crucial to boost eWOM.

Los hoteles ofrecen experiencias de alta calidad a sus huéspedes para influir positivamente en sus emociones, satisfacción, valor percibido, boca a boca (WOM) y boca a boca electrónico (eWOM). Este estudio tiene como objetivo a) investigar el impacto de la calidad percibida por los huéspedes del hotel en sus emociones positivas, emociones negativas, valor percibido y satisfacción; b) verificar el impacto del precio en el valor percibido y la satisfacción; c) examinar el impacto de la satisfacción en el WOM y eWOM; d) probar el efecto moderador del compromiso conductual de los huéspedes del hotel en las redes sociales (HGBE-SNS) en la relación entre satisfacción y eWOM.

En esta encuesta participaron 371 huéspedes que evaluaron sus experiencias en tres hoteles brasileños. La modelización de ecuaciones estructurales puso a prueba el modelo hipotético apoyado en la teoría estímulo-organismo-respuesta (S-O-R) (Mehrabian y Russell, 1974).

La calidad percibida por los clientes del hotel (estímulo) influye positivamente en el valor percibido, las emociones positivas y la satisfacción, y negativamente en las emociones negativas (organismo). El precio (estímulo) afecta negativamente al valor percibido, pero no a la satisfacción. El valor percibido afecta positivamente a la satisfacción. La satisfacción afecta positivamente al WOM y al eWOM (respuestas). El HGBE-SNS modera la relación entre satisfacción y eWOM.

Este estudio es el primero que demuestra simultáneamente las relaciones entre calidad percibida, precio, valor percibido, emociones positivas y negativas, satisfacción, WOM, eWOM y HGBE-SNS. Los hoteles deben ofrecer a sus clientes servicios de alta calidad para influir positivamente en el valor percibido, las emociones positivas, la satisfacción y el WOM. Los precios bajos aumentan el valor percibido pero no incrementan directamente la satisfacción de los huéspedes. Los huéspedes satisfechos comparten sus experiencias a través del WOM, pero un alto nivel de HGBE-SNS es crucial para impulsar el eWOM.

酒店提供高质量的宾客体验, 对宾客的情绪、满意度、感知价值、口碑（WOM）和电子口碑（eWOM）产生积极影响。本研究旨在 a) 调查酒店客人感知到的质量对其积极情绪、消极情绪、感知价值和满意度的影响; b) 验证价格对感知价值和满意度的影响; c) 检验满意度对 WOM 和电子口碑的影响; d) 检验酒店客人在社交网站上的行为参与（HGBE-SNS）对满意度和电子口碑之间关系的调节作用。

本次调查包括 371 位客人, 他们对自己在巴西三家酒店的入住体验进行了评估。结构方程模型检验了由刺激-组织-反应（S-O-R）理论（Mehrabian 和 Russell, 1974 年）支持的假设模型。

酒店客人感知到的质量（刺激因素）对感知价值、积极情绪和满意度有积极影响, 而对消极情绪（有机体）有消极影响。价格（刺激因素）对感知价值有负面影响, 但不影响满意度。感知价值对满意度有积极影响。满意度对 WOM 和 eWOM（反应）产生积极影响。HGBE-SNS 可调节满意度与网络口碑之间的关系。

本研究首次同时展示了感知质量、价格、感知价值、积极和消极情绪、满意度、WOM、eWOM 和 HGBE-SNS 之间的关系。酒店必须为客人提供高质量的服务, 才能对 “感知价值"、"积极情绪"、"满意度 “和 “WOM “产生积极影响。低价会提升感知价值, 但不会直接提高客人满意度。满意的酒店客人会通过 WOM 分享他们的体验, 但高 HGBE-SNS 对促进 eWOM 至关重要。

This study aims to investigate the relationship between market share and rent levels to understand the supply structure in the Japanese private rental housing market.

The study calculates the municipal-level market share of a dominant rental housing operator in Japan and ascertained the overall market rent and the dominant operator’s rent premium at the municipal level by using a major web portal’s listing data of rental houses.

The study shows that, as market share increased, overall market rent tends to decrease, and analyzed by market share, there is no significant difference between the rent of the dominant operator and the overall market rent.

The results of the study suggest that dominant operators may have lowered the rent of their own property to prioritize filling vacancies, which, in turn, causes the overall level of market rent to decline. This is an outcome of rental housing operators’ strategy to maximize long-term rental income under sublease contracts with individual owners, which ensures stable rental income for owners regardless of the occupation status of the apartments.

Previous research on regional monopolies in mortgage sales and brokerage businesses in the USA implies that rental housing operators in a position of great influence over the market can control and keep the market rents at high levels, that is, at large costs for consumers. The findings of the study are novel in showing the inverse relationship in the Japanese private rental market.

This study aims to explore the impact of decentralized long-term rental apartments on the value of in-community housing from two perspectives of housing price and rent.

This study uses the hedonic model to identify the factors affecting the housing value, and the influence of distributed long-rented apartments on the housing value in the community is analyzed from two aspects of housing price and rent by using the ordinary least square method and propensity score matching method.

The primary finding indicates that decentralized long-term rental apartments increase housing prices while decreasing general rental housing rents in the community, with the average degree of increase ranging from 0.93% to 2.59% and the average degree of decrease ranging from 2.23% to 4.34%. According to additional research, the prices of houses within communities rise by 0.042% for every 1% increase in the share of decentralized long-term rentals, while the rents for other types of rental property fall by 0.162%.

The government can regulate the housing market by regulating the access and layout of distributed long-rent apartments.

The findings of this study indicate that the existence and share of distributed long-rent apartments have a heterogeneous impact on the housing price and rent in the community, respectively.

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 aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM).

The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices.

The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18.

This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.