Connections between scientific research and education in the field of tourism and leisure in the Czech Republic

Studnička, Petr; Plzáková, Lucie

doi:10.54055/ejtr.v15i.259

Cited by 3 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The application of big data analysis is not only connected with the positive business effects like finding new ways how to market the business or how to improve the current marketing strategy but as well with the need for more qualified employees involved in the data analysis processes, which can lead to workplace instability (Weaver, 2021) or increase in the difference between the researchers and practitioners perception of the revenue management in its perspectives (Ivanov et al, 2021;Studnička and Plzáková, 2017). As proposed by Ivanov et al (2021), the research-practice gap is caused by the low transferability of the knowledge within the revenue management research and the lack of detailed and understandable methodology description.…”

Section: Introductionmentioning

confidence: 99%

Understanding customer's online booking intentions using hotel big data analysis

Chalupa

Petříček

2022

Journal of Vacation Marketing

View full text Add to dashboard Cite

The presented article focuses on the issue of customer segmentation in the hospitality industry and its use for price optimisation. To identify the market segments article uses the Two-Step cluster analysis. The analysis was based on the seven variables (length of stay, average room rate, distribution channel, reservation day, day of arrival, lead time and payment conditions). Six clusters were identified as following segments: Corporates, Early Bird Bookers, Last Minute Bookers, Product Seekers, Values Seekers and Last Minute Bookers. To optimise the price for these segments, article works with the coefficient of price elasticity of demand for the presented market segments. The price elasticity of demand is measured by the log-log regression analysis. Data were colected from the four-star hotel in Prague, Czech Republic and analysis is based on more than 9000 transactions. Last minute bookers segment was the only one with the positive coefficient of price elasticity and has the lowest value of lead time (9,27 in average). Product seekers have the highest coefficient of price elasticity (−3,413) and highest average room rate (3573 CZK in average). Early bird bookers, Long time stayers, Corporates and Value seekers was identified as pricely inelastic.

show abstract

Section: Introductionmentioning

confidence: 99%

Understanding customer's online booking intentions using hotel big data analysis

Chalupa

Petříček

2022

Journal of Vacation Marketing

View full text Add to dashboard Cite

show abstract

The Use of Business Process Management in Hotel Direct Sales Improvement

Chalupa¹,

Petříček²,

Ulrych³

2021

TEM Journal

View full text Add to dashboard Cite

This article deals with Business Process Modelling and Reengineering use in the hospitality industry, focusing on the improvement of direct telephone sales by application of the CRM system. After modelling the current state of the selected process using ARIS methodology, the same process was remodelled for the application of the CRM system. This application shortened the whole process (mainly the number of activities needed to prosecute) and allowed the front-office employee to be more clients oriented. The automation of labour-intensive processes can reduce the number of human-caused errors and improve the convertibility and reservation request and their overall value.

show abstract

Job requirements in the hospitality industry: Technical or general skills? The dilemma for academic education

Varra

Scioni

Grassini³

et al. 2021

EJTR

View full text Add to dashboard Cite

This paper identifies the professional profiles of graduates for job positions in the accommodation sector, in particular, whether specific skills of the position or skills related to the tourism sector are preferred. A conjoint design is applied, which presents the more realistic context of asking respondents to evaluate potential “product” profiles. Managers of accommodation facilities expressed their preferences on four hypothetical profiles of candidates for five job positions: receptionist, administrative clerk, human resources professional, web marketing specialist, revenue manager. Six attributes (academic degree and level, among others) are used to describe the candidate profiles. The data were analysed through a multinomial logit model and an ordinary least squares regression model that highlighted the preferred characteristics of the candidates for the considered job positions. The main findings show that recruitment in accommodation facilities looks at specialized skills and academic programmes appropriate for the specific job positions. Knowledge of the desired characteristics of graduates, which could affect a possible recruitment, is important for designing effective academic curricula.

show abstract

Connections between scientific research and education in the field of tourism and leisure in the Czech Republic

Cited by 3 publications

References 0 publications

Understanding customer's online booking intentions using hotel big data analysis

Understanding customer's online booking intentions using hotel big data analysis

The Use of Business Process Management in Hotel Direct Sales Improvement

Job requirements in the hospitality industry: Technical or general skills? The dilemma for academic education

Contact Info

Product

Resources

About