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1 – 10 of over 2000The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing…
Abstract
Purpose
The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing tourism destination in the United States.
Design/methodology/approach
Culture reflecting consuming behaviour of low-context innovators and high-context imitators is measured by the price elasticity of demand (PED). Hotel brand reflecting guests’ hotel class is measured by the income elasticity of demand. Autoregressive distributed lag has been conducted on the Smith Travel Research data in 33 years (1989–2022) to determine the relationship among hotel brand, culture and life cycles.
Findings
Skilled labour is the key to make hotels grow. Therefore, increase room rates when hotels possess skilled professionals and decrease room rates when hotels have no skilled professionals. During the rejuvenation in Myrtle Beach (1999–2003), hoteliers increased room rates for innovators due to skilled professionals to increase revenue. Otherwise, a decrease in room rates due to lack of skilled professionals would lead to increase revenue.
Research limitations/implications
(1) Although Myrtle Beach is one of the fastest growing tourism destinations in the US, it has a relatively small geographic area relative to the country. (2) Data cover over one tourist life cycle, so the time span is relatively short. Hoteliers can forecast the number of guests in different culture by changing room rates.
Practical implications
To optimize revenue, hoteliers can select skilled labour in professional design hotel brands which could make an increase in demand for leisure transient guests no matter what room rates increase after COVID-19 pandemic.
Social implications
The study has considered the applied ethical processes regarding revenue management that would maximize both revenue and customer satisfaction when it set up an increase in room rates to compensate for professional hotel room design or it decreases room rates for low-income imitators in exploration and development.
Originality/value
This research highlights that (1) skilled design in the luxury hotel brand is the key for the hotel growth and (2) there is a steady state of the growth model in the destination life cycle.
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Mona Yaghoubi and Reza Yaghoubi
This study aims to show the difference between the two types of oil price volatility resulting from either increases or decreases in oil prices and find evidence of the…
Abstract
Purpose
This study aims to show the difference between the two types of oil price volatility resulting from either increases or decreases in oil prices and find evidence of the differential effect of oil price volatility on firms' environmental initiatives.
Design/methodology/approach
This paper examines how volatility in crude oil prices affect corporate environmental responsibility among US firms (excluding oil and gas producers) between 2002 and 2020, with a particular focus on the differential impact of oil price volatility.
Findings
The authors find that a one standard deviation increase in oil volatility resulting from positive changes in oil prices corresponds to a 12.7% decrease in environmental score, while the same increase in volatility from negative changes in oil prices leads to a 5.5% decrease in environmental score. Financial constraints are identified as a potential channel through which oil price volatility influences environmental activities. Specifically, a one standard deviation increase in oil volatility from positive price changes leads to an 18% decrease in environmental score for firms with high financial constraints, compared to an 8% decrease for firms with low financial constraints.
Originality/value
This study builds on the research of Phan et al. (2021) and Maghyereh and Abdoh (2020). Pan et al. reveal a negative association between oil price uncertainty and corporate social responsibility in the oil and gas sector, yet they overlook 1) the asymmetric impacts of oil price changes and sectoral disparities. Moreover, 2) their inclusion of a year-fixed effect undermines their findings’ reliability, as the oil price volatility variable remains constant across all firm-year observations, and including a year-fixed effect diminishes its explanatory power.
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Yunqi Fan, Guanglei Hu and Xiaoxue Chen
This study aims to examine whether mandatory audit partner rotation is associated with future stock price crash risk.
Abstract
Purpose
This study aims to examine whether mandatory audit partner rotation is associated with future stock price crash risk.
Design/methodology/approach
This study makes use of a regulatory change from the Ministry of Finance of China and the China Securities Regulation Commission, which requires mandatory rotation of audit partners since 2004, as a natural experiment to establish causality and applies a difference-in-difference research design.
Findings
Audit partner rotation leads to a significant decrease in future stock price crash risk in the departing partner’s final year of tenure preceding mandatory rotation, consistent with peer monitoring argument of mandatory rotation. Inconsistent with other arguments, including client-specific knowledge, fresh perspective and auditor independence, no significant effect takes a place in the incoming partner’s first year of tenure following mandatory rotation. Mechanism analysis documents that mandatory audit partner rotation reduces stock price crash risk by improving audit quality and constraining managerial empire building.
Originality/value
The results shed new light on the capital market consequence of mandatory audit partner rotation and the cause of stock price crash risk.
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Rizka Amalia Nugrahapsari, Abdul Muis Hasibuan and Tanti Novianti
This study aims to investigate the factors influencing the citrus trade in Indonesia, the effects of tariff and non-tariff policies on the industry and the welfare of producers…
Abstract
Purpose
This study aims to investigate the factors influencing the citrus trade in Indonesia, the effects of tariff and non-tariff policies on the industry and the welfare of producers and consumers.
Design/methodology/approach
The research used annual series data from 1991 to 2021 and employed inferential, simulation, and descriptive analyses. The two-stage least squares (2SLS) of 19 simultaneous equations were used to estimate parameters.
Findings
The results indicate that free trade policies and restrictions have influenced the citrus industry, leading to a reduction in Indonesian citrus imports, and increased consumer and producer prices. However, eliminating import tariff policies on citrus from China and import restrictions increased producer surplus while decreasing consumer surplus, government revenue, and total welfare. Therefore, trade policies should be combined with non-trade policies such as citrus region development policies and advancing cultivation technology.
Originality/value
This study provides empirical evidence for the Indonesian government to formulate effective citrus trade and development policies. It emphasizes the importance of carefully considering the impact of trade policy on the citrus industry and the need to implement non-trade policies such as citrus zone development policies and advancing cultivation technology to benefit both producers and consumers.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0148
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Abdulmuttalip Pilatin, Ali Hepşen and Onur Kayran
This study aims to reveal whether social capital has an effect on the housing price index in Turkey, which is a developing country. The research was carried out by using the data…
Abstract
Purpose
This study aims to reveal whether social capital has an effect on the housing price index in Turkey, which is a developing country. The research was carried out by using the data on the basis of 81 provinces of Turkey in a 12-year period covering the years 2007–2018.
Design/methodology/approach
The data were subjected to panel data regression analysis and the related models were tested using the Driscoll-Kraay (1998) Estimator.
Findings
According to the results of the analysis, it was understood that there is a negative and significant relationship between social capital (SC1) and the housing price index. The results were corroborated by susceptibility testing. As the level of social capital rises in the provinces in Turkey, the manipulative and opportunistic behavior tendencies of individual and corporate house sellers decrease. These results support the principal–agent theory and theory of moral hazard, which constitute the theoretical background of the study.
Originality/value
No study has been found in the literature on the effect of social capital on housing prices. This situation constitutes the main motivation source of the study and shows its originality.
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Wan-Hsiu Cheng, Shih-Chieh Chiu, Chia-Yueh Yen and Fu-Chang Yeh
This study aims to explore the relationship between house prices and time-on-market (TOM) in Silicon Valley. Previous findings have been inconclusive due to variations in property…
Abstract
Purpose
This study aims to explore the relationship between house prices and time-on-market (TOM) in Silicon Valley. Previous findings have been inconclusive due to variations in property characteristics. This paper highlights the discrepancy between listing and selling prices and identifies differences among housing types such as condominiums, detached houses and townhouses based on housing orientations and customer groups. Additionally, this study considers the impact of the COVID-19 pandemic and the Fed’s interest rate policies on the housing market.
Design/methodology/approach
The authors analyze 63,853 transactions from the Bay East Board of Realtors’ Multiple Listing Service during 2018 to 2022. The study uses a multiple-stage methodology, including a nonlinear hedonic pricing model, search theory and two-stage least squares method to address concerns relating to endogeneity.
Findings
The Silicon Valley housing market shows resilience, with low-end properties giving buyers more bargaining power without significant price drops. High-end properties, on the other hand, attract more attention over time, leading to aggressive bidding and higher final sale prices. The pandemic, despite reducing housing supply, did not dampen demand, leading to price surges. Post-COVID, price correlations with TOM changed, indicating a more cautious buyer approach toward high premiums. The Fed’s stringent monetary policies post-2022 intensified these effects, with longer listing times leading to greater price disparities due to financial pressures on buyers and shifting dynamics in buyer interest.
Practical implications
Results reveal a nonlinear positive correlation between TOM and the price formation process, indicating that the longer a listed property is on the market, the greater the price changes. For low-end properties, TOM becomes significantly negative, while for high-end properties, the coefficient becomes significantly positive, with effects and magnitudes varying by type of dwelling. Moreover, external environmental factors, especially those leading to financial strain, can significantly impact the housing market.
Originality/value
The experience of Silicon Valley is valuable for cities using it as a development model. The demand for talent in the tech industry will stimulate the housing market, especially as the housing supply will not improve in the short term. It is important for government entities to plan for this proactively.
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Hao Li and Changhui Cao
This paper investigates the buy online and pick up in-store cooperation (BOPSC) of online and offline retailers. Specifically, this study solves the following questions: (1) What…
Abstract
Purpose
This paper investigates the buy online and pick up in-store cooperation (BOPSC) of online and offline retailers. Specifically, this study solves the following questions: (1) What is the impact of BOPSC on their optimal price and sales volume of products? (2) When should an online retailer and an offline retailer conduct the BOPSC strategy with each other?
Design/methodology/approach
The paper first establishes two game models to explore the equilibriums of online and offline retailers in non-BOPSC and BOPSC. Then the condition for online and offline retailers to implement BOPSC strategy are determined. Furthermore, the applicability of the BOPSC strategy is enhanced by incorporating numerical analysis.
Findings
The study’s findings reveal that BOPSC strategy will not always beneficial to online and offline retailers, which depends on the total cost of online shopping and the product valuation of consumers. BOPSC strategy leads to the increase of prices and online orders, and the demand of offline retailer is eroded. Moreover, BOPS cooperation between different retailers is easier to achieve than omni-channel integration strategy. When the convenience difference between offline shopping and BOPSC pick-up is moderate, the effectiveness of BOPSC strategy can be improved.
Originality/value
This study has the following two main contributions: Firstly, the authors investigate the effects of BOPSC strategy on the prices of online and offline retailers. The study results show that the BOPSC strategy alleviates price competition and promotes a win–win situation between online retailers and offline retailers. Secondly, this paper mainly studies the cooperative behavior between online and offline retailers and reveals the optimal conditions for online and offline retailers to adopt BOPSC strategy. It can help small- and medium-sized online and offline retailers to choose suitable products for BOPSC strategy, so as to achieve the purpose of increasing profit.
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This study aims to analyse the effect of competition on retail fuel prices in a small European Union (EU) country with high market concentration.
Abstract
Purpose
This study aims to analyse the effect of competition on retail fuel prices in a small European Union (EU) country with high market concentration.
Design/methodology/approach
The researchers use a panel data set to estimate a fuel price equation that includes supply and demand factors as well as time-fixed effects.
Findings
The study finds that more competitors in the local market decrease prices, whereas the high market share of oligopoly brands does not condition this effect. Additionally, independent brands set lower prices than wholesalers, and gas stations located near the borders of almost all neighbouring countries are associated with higher prices.
Research limitations/implications
The study suggests that Slovenia’s retail fuel market maintains competitive pricing despite high oligopolistic shares because of historical regulatory influences that shaped firm behaviour and pricing strategies, along with geographical and economic factors such as Slovenia’s role as a transit country. External competitive pressures from neighbouring countries and high levels of traffic, combined with the remnants of regulatory structures, help prevent market abuses and keep fuel prices lower than in other EU countries.
Practical implications
It also indicates that policy should encourage fiercer competition in the local market by increasing the density of gas stations, especially from independent brands.
Originality/value
These findings may be associated with specific country characteristics. This paper introduces unique findings that shed light on the impact of a small market on competition, with a particular focus on highlighting the effect of oligopolistic brands.
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Yanwen Tan, Ruixue Yue, Liru Chen, Congxi Li and Kevin Z. Chen
This paper aims to examine whether China's grain price support policy has distorted the grain market price.
Abstract
Purpose
This paper aims to examine whether China's grain price support policy has distorted the grain market price.
Design/methodology/approach
The time-varying differences-in-differences (DID) model is used to study the impact of support policies on grain prices, and it is combined with the event study method to explore the dynamic effects of price support policy. Panel data model is used to study the effect of the price support policy on price formation for national grain market prices. In addition, we apply the smooth transformation (STR) model to verify whether there is a distortion in the transmission of grain prices among different markets in China and from the international market to China’s market.
Findings
China’s grain price support policy plays a significant role in rising grain market prices, weakens the decisive role of the market mechanism in the formation of grain prices, hinders the spatial transmission of market price signals and decreases the effect of price transmission from the world market to China’s market.
Research limitations/implications
In order to ensure both the stability of grain production as well as the market stability, and also to ensure that intervention policies do not distort the food market, the minimum purchase price of grain and market regulation policies should be adjusted as follows: (1) price support policy should be shifted to an income support policy and (2) reasonably determine the scale of reserves and implement a grain minimum purchase price policy in limited areas.
Originality/value
Our findings are relevant for understanding the effect of China's grain price support policies on the implementation regions and the price transmission effect, which provide reference experience for developing countries to implement food price policies.
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Narvada Gopy-Ramdhany and Boopen Seetanah
Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign…
Abstract
Purpose
Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.
Design/methodology/approach
Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.
Findings
The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.
Originality/value
Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.
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