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This paper aims to formulate a hedonic pricing model for Japanese rice wine, sake, via hierarchical Bayesian modeling estimated using an efficient Markov chain Monte Carlo (MCMC) method. Using the estimated model, the authors examine how producing regions, rice breeds and taste characteristics affect sake prices.

The datasets in the estimation consist of cross-sectional observations of 403 sake brands, which include sake prices, taste indicators, premium categories, rice breeds and regional dummy variables. Data were retrieved from Rakuten, Japan’s largest online shopping site. The authors used the Bayesian estimation of the hedonic pricing model and used an ancillarity–sufficiency interweaving strategy to improve the sampling efficiency of MCMC.

The estimation results indicate that Japanese consumers value sweeter sake more, and the price of sake reflects the cost of rice preprocessing only for the most-expensive category of sake. No distinctive differences were identified among rice breeds or producing regions in the hedonic pricing model.

To the best of the authors’ knowledge, this study is the first to estimate a hedonic pricing model of sake, despite the rich literature on alcoholic beverages. The findings may contribute new insights into consumer preference and proper pricing for sake breweries and distributors venturing into the e-commerce market.

This paper examines rent determinants and their relationship with commercial office property rents.

The method adopted in this study differs from that of previous studies on this topic. Firstly, based on the survey of the viewpoints of experts, Relative Importance Index (RII) analysis was used to identify rent determinants and to rank and ensure their relevance and validity in the Sri Lankan context. Secondly, sampling of data related to 115 office properties collected from property tenants and landlords located within the central built-up area of Colombo City was conducted using a multi-methods approach to carry out an objective hedonic analysis of office rents.

This research utilizes RII and hedonic models to provide insights into determinants and relationships. Both analyses confirm that the three top drivers of commercial office rent are distance from the major town center, availability of parking space and the condition of the property. In addition to these three factors, hedonic models reveal that the age of the property and the availability of a conference hall also play a relevant role in explaining office rents. Given the disparities in the findings of the two methods, further examination was able to confirm that factors such as distance from the major town center, parking availability, age of the property, presence of a conference hall, building condition, floor size, business type and type of building are likely to influence commercial office rent. These findings reflect elements such as the quality, newness and better facilities of different office properties.

This systematic study and analysis of office rent for the guidance of real estate investors can support sound investment decisions, potentially leading to more financially sound property development, reduced public debt levels and improved public-private financing. Further, the research findings offer valuable insights to real estate investors, developers and planners regarding location decisions for office development quality enhancements in future office developments.

This research provides fresh insights into the local scale office market, an area where limited evidence currently exists. Further, the methodology adopted provides evidence that hedonic analysis, supported by a multi-method approach, can mitigate the subjective judgments made by professionals.

TikTok social media app has become one of the most popular forms of leisure and entertainment activities, but how hedonic consumption experiences (comprising fantasy, escapism, enjoyment, role projection, sensory, arousal and emotional involvement) of the TikTok app determine users' intention to use the app and its resulting impact on the actual usage behavior remains limited in the information systems literature, especially featuring the hedonic consumption perspective in entertainment industry.

This study employs uses & gratification theory to answer the “why” via predicting the role of hedonic consumption experiences that serve as gratifications to trigger technology acceptance behavior (especially, in form of users' behavioral intention to use the TikTok app and its further impact on usage behavior). This study utilizes the partial least squares-structural equation modeling approach to perform data analyses on 258 TikTok app users.

Our results provide a strong support such that users' playful consumption experiences (i.e. escapism, role projection, arousal, sensory experience and enjoyment) positively influence their intention to use the TikTok app and its resultant effect on users' actual usage of the app. In contrast, fantasy and emotional involvement fail to influence users' intention to use the TikTok app.

To the best of our knowledge, our investigation is one of the first studies to apply the hedonic consumption experiences as potential gratifications that derive users' intention and its subsequent influence on the actual usage of the TikTok app. Our study results would assist marketing and brand managers to redefine approaches and tactics to create effective strategies that implement essential determinants to increase behavioral intention among entertainment service providers.

The paper aims to empirically test a framework to predict the desire and intention to engage with an elective health-care procedure and implement a methodology to test the anticipated positive and negative emotions in hedonic adaptation to an elective procedure.

Two studies in USA and Australia (N = 1,200) confirmed the psychometric properties of the key constructs under the chemical peel condition. Two further studies in the USA and Australia (N = 1,100) explored the research question and hypotheses in the adapted model of goal-directed behaviour under the Botox condition. A survey was self-administered to online panels who had previously engaged in such elective procedures.

The findings highlighted the pragmatic implications for communication and activation strategies to safeguard consumer interests and retain their loyalty.

From the authors’ best understanding, neither a methodology nor a theoretical framework exists to explore hedonic adaptation to recurring engagement with elective health care. A methodology and theoretical framework will highlight the mood states and factors that predict desire and intention to engage. This can advance the research on hedonic adaptation and decision-making and offer pragmatic suggestions for communication and activation strategies to safeguard consumer interests and retain their loyalty.

The purpose of this study is to examine the influence of key hotel attributes on the room rates of selected hotels in the Greater Gaborone Region, Botswana.

Using hedonic pricing analysis, the effect of eight attributes collected from 80 standard double rooms on Booking.com in the area was analysed using quantile regression.

The estimated results from quantile regression suggested the importance of the 10th quantile as the best predictor of hotel room price distribution. Overall, the presence of a fitness centre and the availability of meeting and conference facilities were positively significant for the lowest- and premium-priced hotels, respectively.

The study advanced the literature in hedonic pricing models by confirming the applicability of hotel room rate attribute research in unexplored environments.

Hotel managers should be aware of the influence of key attributes, such as meeting and conference space availability and locational factors, on the pricing decisions of room rates in the Greater Gaborone Region. The study also presented opportunities for business-to-business marketing between hotel and tour operators in the region.

The study is one of the few that uses quantile regression in the hedonic pricing analysis of hotel room rates.

No study to date has addressed the construct of event tourist experience value and there is no well-accepted value measurement method. This study aims to examine the underlying dimensions of event tourist experience value from a holistic perspective.

The research process consists of two steps. First, the dimensions of event tourist experience value are investigated by using grounded theory and content analysis of travel blogs. The second step is to explore and verify the scale of event tourist experience value.

The items show that event tourist experience value can be comprehensively understood from three dimensions: functional value (functional factors); hedonic value (relaxation, escape, restoration and interaction); and symbolic value (social prestige, belonging and self-transcendence).

The findings are useful indicators explaining events attendance, and can help event organizers and destination managers to better understand the needs of tourists and design event experiences in a more sophisticated way.

This work integrates a series of varied events to suggest a holistic view of event tourist experience value, which provides a theoretical basis for other scholars to compare and monitor findings in this field.

This study aims to explore image-based visual price determinants (image features and visual aesthetic perception) and how image features affect Airbnb listing price on a sharing accommodation platform.

The study uses an SOR model and a hedonic price model to examine the connections between the characteristics of image features, visual aesthetic perception and Airbnb listing prices. The model is then examined by an econometric model using data from Insideairbnb.com.

Empirical results revealed that image features have a significant positive effect on visual aesthetic perception, visual aesthetic perception has a significant positive effect on Airbnb listing price and visual aesthetic perception has a significant mediating effect between image features and Airbnb listing price.

This study contributes to the relationship and effect mechanism among image features, visual aesthetic perception and Airbnb listing price and has some implications for both property operators and the sharing accommodation platform.

本研究探讨了基于图像的视觉价格决定因素（图像特征和视觉美学感知）以及图像特征如何影响共享住宿平台Airbnb价格。

本研究采用SOR模型和hedonic价格模型来检验图像特征特征、视觉美感与Airbnb房源价格之间的关系。然后使用Insideairbnb.com上的数据, 通过计量经济学模型对该模型进行检验。

实证结果显示：1）图像特征对视觉美学感知有显著的正向影响; 2）视觉美学感知对Airbnb价格有显著的正向影响; 3）视觉美学感知在图像特征和Airbnb价格之间有显著的中介效应。

本研究有助于探讨图像特征、视觉美学感知和Airbnb价格之间的关系和影响机制, 对房源经营者和共享住宿平台都有一定的借鉴意义。

Este estudio explora los determinantes visuales del precio basados en las imágenes (características de las imágenes y percepción estética visual) y cómo afectan las características de las imágenes al precio de los anuncios de Airbnb en una plataforma de alojamiento compartido.

El estudio emplea un modelo SOR y un modelo de precios hedónicos para examinar las conexiones entre las características de los rasgos de la imagen, la percepción estética visual y los precios de Airbnb. A continuación, se examina el modelo mediante un modelo econométrico utilizando datos de Insideairbnb.com.

Los resultados empíricos revelan que 1) las características de la imagen tienen un efecto positivo significativo sobre la percepción estética visual, 2) la percepción estética visual tiene un efecto positivo significativo sobre el precio de los anuncios de Airbnb, y 3) la percepción estética visual tiene un efecto mediador significativo entre las características de la imagen y el precio de los anuncios de Airbnb.

Este estudio contribuye al mecanismo de relación y efecto entre las características de la imagen, la percepción estética visual y el precio del anuncio de Airbnb, y tiene algunas implicaciones tanto para los operadores inmobiliarios como para la plataforma de alojamiento compartido.

The purpose of the study is to examine the efficiency of linear, nonlinear and artificial neural networks (ANNs), in predicting property prices.

The present study uses a dataset of 1,468 real estate transactions from 2020 to 2022, obtained from the Department of Property Taxes of Republic of Kosovo. Beginning with a fundamental linear regression model, the study tackles the question of overlooked nonlinearity, employing a similar strategy like Peterson and Flanagan (2009) and McCluskey et al. (2012), whereby ANN's predictions are incorporated as an additional regressor within the ordinary least squares (OLS) model.

The research findings underscore the superior fit of semi-log and double-log models over the OLS model, while the ANN model shows moderate performance, contrary to the conventional conviction of ANN's superior predictive power. This is notably divergent from the prevailing belief about ANN's superior predictive power, shedding light on the potential overestimation of ANN's efficacy.

The study accentuates the importance of embracing diverse models in property price prediction, debunking the notion of the ubiquitous applicability of ANN models. The research outcomes carry substantial ramifications for both scholars and professionals engaged in property valuation.

Distinctively, this research pioneers the comparative analysis of diverse models, including ANN, in the setting of a developing country's capital, hence providing a fresh perspective to their effectiveness in property price prediction.

This study aims to examine the impact of “space-as-a-service” (SAAS) provision on office rents in the UK and quantify premia to office rents.

Using hedonic modelling techniques the authors are able to quantify the impact of a number of SAAS features on office rents in the City of London using CoStar data. The authors control for the quality of the buildings by focussing on five-star buildings, rated by CoStar, as these buildings are more likely to incorporate SAAS features.

Using data on 317 transactions in 37 City of London Office buildings over the period 1 November 2004–15 July 2020, the authors find that tenant exclusive mobile applications (MAPPS) and a public terrace or rooftop command a rent premium of around £13 and £6.5 per sq. ft per annum, respectively. However, other SAAS features such as conferencing facilities, on-site fitness centre and touch down space have no significant impact on office rents. The impact of exclusive MAPPS varies with size of net lettable area.

The SAAS real estate model is an emerging trend in the office market. As it grows in importance more research questions will have to be investigated. The present study raises awareness of the need to specify SAAS features and form a rating system that will facilitate future research on the subject.

The conclusion from the present investigation is that only two SAAS features have a positive impact on office (tenant exclusive mobile apps and a public terrace or rooftop), which suggest that these two features may form the basis of any future SAAS rating system. These two SAAS components should carry more weight in valuations and pricing.

To the best of the authors’ knowledge, this is the first study that attempts to quantify the impact of SAAS features on office rents.

The emergence of virtual reality (VR) has the potential to revolutionize various industries, including tourism, as it delivers a simulated environment that closely emulates real-life experiences. Therefore, this study aims to explore how the factors, i.e. enjoyment, emotional involvement, flow state, perceived privacy risk, physical risk and cost, influence the customers’ intention to use VR for tourism.

This study integrates the technology acceptance model, hedonic consumption theory with other factors, including cognitive response, authenticity, perceived privacy risk, perceived physical risk, perceived cost and perceived presence. Partial least squares structural equation modelling approach was used to test the proposed research model.

The finding based on the sample of 252 respondents revealed that authenticity is the most influential factor impacting behavior intention followed by perceived cost, attitude, cognitive response and enjoyment. Also, the study supported the moderating impact of personal innovativeness between attitude and behavioral intention to use VR for tourism.

The findings of the study offers practical implications for service providers, site managers, destination marketers, tourist organizations and policymaker to develop more effective strategies for offering VR services for tourism.

This study enriches the current understanding of VR adoption in context of tourism with empirical evidences.