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This study aims to revisit the empirical debate about the asymmetric relationship between oil prices, energy consumption, CO₂ emissions and economic growth in a panel of 184 countries from 1981 to 2020.

A relatively new research method, the PVAR system GMM, is applied.

The outcome of the PVAR system GMM model at the group level in the study suggests that oil prices exert a positive but statistically insignificant effect on economic growth. Energy consumption is inversely related to economic growth but statistically significant, and the correlation between CO₂ emissions and economic growth is negative but statistically insignificant. The Granger causality test indicates that oil prices, CO₂ emissions, oil rents, energy consumption and savings jointly Granger-cause economic growth. A unidirectional causality runs from energy consumption, savings and economic growth to oil prices. At countries’ income grouping levels, oil prices, oil rent, CO₂ emissions, energy consumption and savings jointly Granger-cause economic growth for the high-income and upper-middle-income countries groups only, while those variables did not jointly Granger-cause economic growth for the low-income and lower-middle-income countries groups. The modulus emanating from the eigenvalue stability condition with the roots of the companion matrix indicates that the model is stable. The results support the asymmetric impacts of oil prices on economic growth and aid policy formulation, particularly the cross-country disparities regarding the nexus between oil prices and growth.

From a methodological perspective, to the best of the author’s knowledge, the study is the first attempt to use the PVAR system GMM and such a large sample group of 184 economies in the post-COVID-19 era to examine the impacts of oil prices on countries’ growth while controlling for other crucial variables, which is noteworthy. Two, using the World Bank categorisation of countries according to income groups, the study adds another layer of contribution to the literature by decomposing the 184 sample economies into four income groups: high-income, low-income, upper-middle-income and lower-middle-income groups to investigate the potential for asymmetric effects of oil prices on growth, the first of its kind in the post-COVID-19 period.

With revolutions in the telecommunication sector having led to wide unprecedented consequences in all facets of human life, this paper aims to examine the relationship between cell phone tower base stations (CPTBSs) and residential property prices within the City of Johannesburg (CoJ), South Africa.

The authors align their work with global literature and assess how the impact of CPTBSs influences residential property values in South Africa. The authors use a semi-log hedonic pricing model to test the hypothesis that proximity of CPTBSs to residential properties does not account for any variation in residential property prices.

The results show a significant impact that proximity of CPTBS has on residential property sale prices. However, the impact of CTPBSs’ proximity on residential property prices depends on their distance from the residential properties. The closer a residential property is to the CTPBS, the greater the impact that the CTPBS will have on the selling price of the residential property.

With international studies offering mixed findings on the impact of CPTBSs on residential property values, there is limited research on their impact in South Africa. The findings of this study offer crucial insights for the real estate practitioners, property owners, telecommunications companies and the public, providing a nuanced understanding of the relationship between CPTBSs and property values. This research helps property owners understand the effects of CPTBSs on their properties, and it assists property valuers in gauging the impact of CPTBSs on property values.

The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

The purpose of this study is to examine the effects of the Odd-Even Road Rationing Policy (RRP) on housing prices in Jakarta, Indonesia. It aims to evaluate the net effect of the RRP on housing prices.

The study uses the monocentric model and employs the difference-in-differences (DD) method. Annual neighborhood-level housing price data is analyzed to assess the impact of the RRP on housing prices. Additionally, propensity score matching is used to address potential biases resulting from non-random policy assignments.

The results demonstrate that houses located within the RRP-restricted area experience a decrease in price that is relative to those in the control group. The findings indicate a decrease in housing prices ranging from 7.59% to 14.7% within the RRP-restricted area. This suggests that the positive impacts resulting from the RRP have not fully compensated for the restricted accessibility experienced by individuals who have limited behavioral changes. The study also confirms the significance of commuting costs in individuals' location decisions, aligning with predictions from urban economics models.

This study contributes to the literature by providing insights into the effects of a RRP on housing prices. It expands understanding beyond the immediate effects on traffic conditions and air pollution, which previous studies have primarily focused on. Furthermore, to the best of the authors’ knowledge, this research will be the first conducted to identify the impacts of RRP on housing prices in Indonesia.

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。

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with the aim of elucidating the underlying economic principles governing this dynamic interplay.

Using monthly data of China, the authors use the asymmetry nonlinear autoregressive distributed lag (NARDL) model to test for nonlinearity in the relationship between land supply price and urban housing prices.

The empirical results confirm the existence of an asymmetric relationship between land supply price and urban housing prices. The authors find that land supply price has a positive and statistically significant impact on urban housing prices when land supply is increasing. Policymakers should strive to strike a balance between safeguarding residents’ housing rights and maintaining market stability.

Although the asymmetric effect of land supply price has been identified as a significant contributor in this study, it is important to note that the research primarily relies on time series data and focuses on analysis at the national level. Although time series data offer a macroscopic perspective of overall trends within a country, they fail to adequately showcase the structural variations among different cities.

To ensure a stable housing market and meet residents’ housing needs, policymakers must reexamine current land policies. Solely relying on restricting land supply to control housing prices may yield counterproductive results. Instead, increasing land supply could be a more viable option. By rationally adjusting land supply prices, the government can not only mitigate excessive growth in housing prices but also foster the healthy development of the housing market.

First, the authors have comprehensively evaluated the impact of land supply prices in China on urban housing sales prices, examining whether they play a facilitating or mitigating role in the fluctuation of these prices. Second, departing from traditional linear analytical frameworks, the authors have explored the possibility of a nonlinear relationship existing between land supply prices and urban housing sales prices in China. Finally, using an advanced NARDL model, the authors have delved deeper into the asymmetric effects of land supply prices on urban housing sales prices in China.

The purpose of this study is to investigate the relationship between tourism development and urban housing prices in Chinese cities. Specifically, the study aimed to explore whether there is a relationship between the two variables in tourist and non-tourist cities and whether there is a non-linear relationship between them.

In this study, the entropy method was used to construct the China City Tourism Development Index, which provides a more comprehensive measure of the level of tourism development in different cities. In total, 45 major cities in China were studied using the panel data approach for the period of 2011 to 2019.

The empirical analysis conducted for this study found that tourism development affects urban house prices, and that there is an inverted U-shaped relationship. However, this varies across cities, with house prices in tourist cities tending to be more influenced by tourism development than non-tourist cities. Also, foreign direct investment, population size, fixed asset investment and disposable income per capita were found to have an impact on house prices in both tourism and non-tourism cities.

There are significant differences in tourism development and urban house prices in different cities in China. This study considers these differences when examining the impact of tourism on house prices in 45 major cities in China by dividing the sample cities into tourist and non-tourist cities.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

The purpose of this study is to discover what attributes of casino buffet restaurants are the most important for customers’ willingness to pay (WTP).

Choice-based conjoint analysis was used in this study to test seven attributes: food, price/value, real price, service, atmosphere, the number of reviews and user-generated star ratings. Sawtooth Software was used to do the conjoint analysis, and a series of significance t-tests were run to determine the significance of each attribute on WTP with Statistical Package for the Social Sciences (SPSS).

Based on a survey of 483 respondents who had visited a buffet at a casino within the last two years, this study found that food is ranked as the most significant attribute of a casino buffet restaurant, followed by real price and service quality.

Theoretically, this work is the first to the authors’ knowledge to apply the antecedents of behavioral intention to willingness-to-pay for niche restaurants. Practically, the results of this study will help casino buffet operators as they re-open after COVID-19. Future studies could collect data in the post-pandemic environment and examine WTP at casino buffets in different geographic locations.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.