Search results

1 – 6 of 6
Per page
102050
Citations:
Loading...
Article
Publication date: 9 January 2017

Adam Pawlicz and Tomasz Napierala

This study aims to measure the effect on prices through the differing characteristics and attributes of hotels.

2218

Abstract

Purpose

This study aims to measure the effect on prices through the differing characteristics and attributes of hotels.

Design/methodology/approach

A hedonic price model (HPM) was adopted to estimate the impact of various site and situational factors on hotel prices in Warsaw, Poland. To better understand room rates not explained by HPM, spatial analysis of residuals was used. Datasets regarding prices from three different online travel agents (OTAs) and star ratings, either official or provided by OTAs, were investigated.

Findings

A significant impact on hotel prices by star rating has been confirmed. Every additional star allows the hotel to set approximately 25 to 36 per cent higher prices, which is in line with previous studies. Moreover, two factors indicated a high but still underestimated theoretical hotel prices: location within the city centre and proximity to the international airport.

Practical implications

The results of this study suggest that hoteliers should use a spatial analysis of room rates offered by the competing enterprises. Moreover, managers are expected to verify their price tactics and policies according to the geographical determinants of hotel prices investigated.

Originality/value

The uniqueness of the study is highlighted by comparison of HPMs based on data from different OTAs, analysing differences in HPMs based on star ratings provided by OTAs and official systems and spatial analysis of residuals of estimated HPMs. Moreover, this study is among the first to examine the usage of HPM in the hospitality industry in East-Central Europe.

Details

International Journal of Contemporary Hospitality Management, vol. 29 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 15 May 2023

Catherine Prentice and Adam Pawlicz

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the…

1161

Abstract

Purpose

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the literature.

Design/methodology/approach

To address the research aims, this study conducted a systematic literature review and content analysis of all relevant articles. Following the review, the methodological sections of the selected papers were examined to identify the characteristics and limitations of all data sources used in the papers.

Findings

This study revealed several limitations of the use of three major data sources, namely, web scraping with self-made bots, inside Airbnb and AirDNA, for sharing economy research. The review shows that the majority of the selected papers did not acknowledge any limitations, nor did they discuss the quality of the data sources.

Research limitations/implications

The findings of this paper can serve as guidelines for selecting appropriate data sources for research into the sharing economy and cautions researchers to address the limitations of the data sources used.

Originality/value

To the best of the authors’ knowledge, this is the first study that explores the advantages and limitations of data sources used in short-term rental market research.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Book part
Publication date: 14 October 2019

Sameer Mathur and Ashish Dubey

This paper identifies and models the effect of eight attributes that influence hotel room rents in India. These attributes are conceptually grouped into three factors: (1) site…

Abstract

This paper identifies and models the effect of eight attributes that influence hotel room rents in India. These attributes are conceptually grouped into three factors: (1) site factors including the presence or absence of a “swimming pool,” “free breakfast,” and the “hotel capacity”; (2) situational factors including, “distance from the airport,” “weekend/weekday,” “city population,” “cost of living”; and (3) a reputation factor indicated by “star rating.” Our regression model uses secondary data collected from a hotel booking website for 570 hotels across 18 cities of India. The results indicate that six out of these eight variables namely, presence of swimming pool, free breakfast, hotel capacity, distance from the airport, city population, and hotel star rating have a significant impact on hotel room rents in India.

Details

Advances in Hospitality and Leisure
Type: Book
ISBN: 978-1-83867-956-9

Keywords

Article
Publication date: 5 October 2020

Isaac Cliford Queku, Seth Gyedu and Emmanuel Carsamer

The purpose of the paper is to investigate the causal relationships and speed of adjustment of stock prices to changes in macroeconomic information (MEI) in Ghana from 1996 to…

491

Abstract

Purpose

The purpose of the paper is to investigate the causal relationships and speed of adjustment of stock prices to changes in macroeconomic information (MEI) in Ghana from 1996 to 2018 using monthly data. The paper seeks to conduct the investigation at individual MEI level rather than the composite MEI.

Design/methodology/approach

Quantitative approach was used in this paper. Monthly data span of 1996–2018 was used. The delay and half-life technique was used to determine the speed with which the information resulting from the changes in the macroeconomic are evident in the stock price. Thereafter, Toda–Yamamoto Granger no-causality approach was used to examine the causal relationship amongst variables.

Findings

The paper revealed that although the market adjustment to MEI has improved, the speed is till slow. The exchange rate exhibited the slowest speed in respect of the market reaction while the market reaction to money supply was the fastest. Toda–Yamamoto Granger no-causality estimation also revealed a bi-directional causality between MEI (gross domestic product, interest rate and money supply) and stock price and uni-directional relationship flowing from MEI (the exchange rate and foreign direct investment) to stock price. The paper also found no causality between inflation and stock price.

Research limitations/implications

The findings although revealed improved level of market efficiency in comparison with the earlier data, the speed of adjustment is still undesirable. Rigorous approach should be adopted for the implementation of major reforms such as alternative market so as to increase the number of share listing and to increase the scope of investors' participation to enhancing trading volume and marketability and ultimately speed up information diffusion.

Practical implications

The practical implication of the low level of information processing rate of Ghana Stock Exchange (averagely more than a month) is that astute investors and market analysts could employ MEI to outperform the market prior to their infusion onto the stock market.

Originality/value

This study is one of the few studies in the Ghanaian literature that has extended the investigation of the speed of adjustment beyond composite or aggregate macroeconomic level estimation to estimation at individual variable level. This contribution is very relevant since each macroeconomic variable has unique characteristics and require specific policy framework, it is important to consider the speed of adjustment from the perspective of each of the individual variables.

Details

International Journal of Emerging Markets, vol. 17 no. 1
Type: Research Article
ISSN: 1746-8809

Keywords

Open Access
Article
Publication date: 25 October 2022

Andrea Valenzuela-Ortiz, Jorge Chica-Olmo and José-Alberto Castañeda

This research investigates the effect of accessibility to points of tourist interest (buffer) and direct and indirect spatial spillover effects of agglomeration economies on…

3150

Abstract

Purpose

This research investigates the effect of accessibility to points of tourist interest (buffer) and direct and indirect spatial spillover effects of agglomeration economies on tourism industry revenues in Spain.

Design/methodology/approach

Data were collected from the Bureau van Dijk's (BvD) Orbis global database. The data were analysed using a spatial econometric model and the Cobb–Douglas production function.

Findings

This study reveals that hotels located inside the buffer zone of points of tourist interest achieve better economic outcomes than hotels located outside the buffer. Furthermore, the results show that there is a direct and indirect spatial spillover effect in the hotel industry.

Practical implications

The results provide valuable information for identifying areas where the agglomeration of hotels will produce a spillover effect on hotel revenue and the area of influence of location characteristics. This information is relevant for hotels already established in a destination or when seeking a location for a new hotel.

Social implications

The results of this study can help city planners in influencing the distribution of hotels to fit desired patterns and improve an area's spatial beauty.

Originality/value

The paper provides insights into how investment, structural characteristics, reputation and location affect hotel revenue.

Details

European Journal of Management and Business Economics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2444-8451

Keywords

Article
Publication date: 12 September 2020

Chun-Min Kuo, Wen-Yuan Chen, Chin-Yao Tseng and Chang Ting Kao

This paper develops a smart system based on the concept of Industry 4.0 to prevent customer dissatisfaction. The value of this prevention system is that it enables hoteliers to…

765

Abstract

Purpose

This paper develops a smart system based on the concept of Industry 4.0 to prevent customer dissatisfaction. The value of this prevention system is that it enables hoteliers to interact with customers by understanding what they like/dislike from their behaviors via data analysis. Therefore, this system helps hoteliers to enhance service quality by predicting service issues.

Design/methodology/approach

The system, named the dissatisfaction identification system (DIS), is developed. A total of 127 service items were examined by a hotel manager who preset the threshold values for the measurement of service quality. A big data set for the questionnaire survey is statistically generated by a pseudorandom number generator and 10,000 mock data sets are taken as input for comparison.

Findings

The results indicated that 36 out of 127 service items are identified as service issues for the participating hotel. Examples include customer code number 01d, “Space of parking lot is adequate” in the safety management category, and number 05a, “A hotel's service time meets my needs” in the front office service category. The items identified require improvement action plans for preventing customer dissatisfaction.

Originality/value

This paper offers a new perspective paper emphasizing customer dissatisfaction using a big data-driven technology system. The DIS, prevention system, is developed to aid hotels by enhancing their relationships with customers using a data-driven approach.

Details

Industrial Management & Data Systems, vol. 121 no. 6
Type: Research Article
ISSN: 0263-5577

Keywords

1 – 6 of 6
Per page
102050