scholarly journals Holiday Rentals in Cultural Tourism Destinations: A Comparison of Booking.com-Based Daily Rate Estimation for Seville and Porto

Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 157
Author(s):  
Miguel Ángel Solano-Sánchez ◽  
José António C. Santos ◽  
Margarida Custódio Santos ◽  
Manuel Ángel Fernández-Gámez
Keyword(s):  
Cultural Tourism ◽  
Sharing Economy ◽  
Model Application ◽  
Rate Estimation ◽  
Daily Rate ◽  
Two Cities ◽  
Multiple Variables ◽  
Tourism Destinations ◽  
Using Data

Multiple variables determine holiday rentals’ price composition in cultural tourism destinations. This study sought, first, to test a model including the variables with the greatest impact on tourism accommodations’ prices in these destinations and, second, to demonstrate the proposed model’s applicability to cultural city destinations by identifying the adaptations needed to apply it to different contexts. Two cities were selected for the model application—Seville in Spain and Porto in Portugal—both of which are located in different countries and are well-known cultural tourism destinations. The data were extracted from Booking.com because this accommodations platform has adapted its offer to the sharing economy, becoming one of the most important players in the market, and because research on holiday rentals using data from Booking.com is scarce. The results show that the variables used are relevant and highlight the adaptations necessary for specific cultural tourism destinations, thereby indicating that the model can be applied to all cultural tourism destinations. The proposed approach can help holiday rental managers select the correct tools for determining their accommodation units’ daily rates according to their product and marketing context’s characteristics.

Motivations and attitudes toward domestic tourism in Saudi Arabia

2019 ◽  
Vol 9 (1) ◽  
pp. 27-37
Author(s):  
Mourad Mansour ◽  
Alhassan G Mumuni
Keyword(s):  
Saudi Arabia ◽  
Local Environment ◽  
Domestic Environment ◽  
Domestic Tourism ◽  
Tourism Destinations ◽  
Tourism Information ◽  
The Government ◽  
Using Data ◽  
Tourism Organization ◽  
Self Administered Questionnaire

AbstractBeginning with the establishment of a Supreme Commission for Tourism and Antiquities’ (SCTA) in 2000, there have been official attempts by the government of Saudi Arabia to encourage domestic tourism in order to tap into the huge amounts that Saudis spend annually on vacations. This paper examines the motivations and attitudes of consumers toward tourism destinations and activities within the country (domestic tourism). Using data collected through a structured self-administered questionnaire, the study finds that familiarity and trust of the local environment, perceptions of the safer domestic environment, and limitations imposed by respondents’ vacation timing are the primary motives for choosing to spend their vacations locally, while lack of quality domestic tourist sites and services (including entertainment facilities), lack of tourism information, insufficient tourism organization services, and the harsh local environmental conditions during summer are factors that ‘push’ people from spending the vacations locally. Attitudes toward domestic tourism are generally negative, although there are significant differences in attitudes between respondents who prefer domestic destinations and those who prefer to travel out of Kingdom. Implications of the findings are outlined and discussed.

scholarly journals “P3”: an adaptive modeling tool for post-COVID-19 restart of surgical services

JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Divya Joshi ◽  
Ali Jalali ◽  
Todd Whipple ◽  
Mohamed Rehman ◽  
Luis M Ahumada
Keyword(s):  
Data Warehouse ◽  
Predictive Analytics ◽  
Surgical Patient ◽  
Protective Equipment ◽  
Operating Room Personnel ◽  
Surgical Services ◽  
Multiple Variable ◽  
Multiple Variables ◽  
Using Data ◽  
User Friendly

Abstract Objective To develop a predictive analytics tool that would help evaluate different scenarios and multiple variables for clearance of surgical patient backlog during the COVID-19 pandemic. Materials and Methods Using data from 27 866 cases (May 1 2018–May 1 2020) stored in the Johns Hopkins All Children’s data warehouse and inputs from 30 operations-based variables, we built mathematical models for (1) time to clear the case backlog (2), utilization of personal protective equipment (PPE), and (3) assessment of overtime needs. Results The tool enabled us to predict desired variables, including number of days to clear the patient backlog, PPE needed, staff/overtime needed, and cost for different backlog reduction scenarios. Conclusions Predictive analytics, machine learning, and multiple variable inputs coupled with nimble scenario-creation and a user-friendly visualization helped us to determine the most effective deployment of operating room personnel. Operating rooms worldwide can use this tool to overcome patient backlog safely.

Fraud abroad

2019 ◽  
Vol 13 (2) ◽  
pp. 249-275
Author(s):  
Jake David Hoskins ◽  
Ryan Leick
Keyword(s):  
Sharing Economy ◽  
Gdp Per Capita ◽  
Content Type ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Level Of Economic Development ◽  
Per Capita ◽  
Using Data ◽  
Developed Nations

Purpose This study aims to investigate a sharing economy context, where vacation rental units that are owned and operated by individuals throughout the world are rented out through a common website: vrbo.com. It is posited that gross domestic product (GDP) per capita, a common indicator of the level of economic development of a nation, will impact the likelihood that prospective travelers will choose to book accommodations in the sharing economy channel (vs traditional hotels). The role of online customer reviews in this process is investigated as well, building upon a significant body of extant research which shows their level of customer decision influence. Design/methodology/approach An empirical analysis is conducted using data from the website Vacation Rentals By Owner on 1,940 rental listings across 97 countries. Findings GDP per capita serves as risk deterrent to prospective travelers, making the sharing economy an acceptable alternative to traditional hotels for the average traveler. It is also found that the total number of online customer reviews (OCR volume) is a signal of popularity to prospective travelers, while the average star rating of those online customer reviews (OCR valence) is instead a signal of accommodation quality. Originality/value This study adds to a growing agenda of research investigating the effect of online customer reviews on consumer decisions, with a particularly focus on the burgeoning sharing economy. The findings help to explain when the sharing economy may serve as a stronger disruptive threat to incumbent offerings. It also provides the following key insights for managers: sharing economy rental units in developed nations are more successful in driving booking activity, managers should look to promote volume of online customer reviews and positive online customer reviews are particularly influential for sharing economy rental booking rates in less developed nations.

Localization of Tourism Destinations' Websites

2018 ◽  
pp. 132-154 ◽  
Author(s):  
Emanuele Mele ◽  
Lorenzo Cantoni
Keyword(s):  
Online Communication ◽  
Cultural Tourism ◽  
Tourism Industry ◽  
Cultural Translation ◽  
Cultural Backgrounds ◽  
Political Borders ◽  
Tourism Destinations ◽  
At Home

The globalization of the tourism industry has been made possible thanks to ICTs. From a communication viewpoint, Internet does not know political borders, but still experiences linguistic and cultural ones. This situation requires that publishers provide both a linguistic and a cultural translation of their messages. Only caring for such a comprehensive “localization” will ensure being understandable and attractive for people with different cultural backgrounds. The chapter analyzes (1) the reasons why localization in tourism online communication is needed (with a focus on tourism destinations and cultural tourism); (2) the main needed activities to provide it. It also discusses (3) different practices and strategies (presenting a few cases), as well as (4) the issue of how much localization is needed, and when it may become counter-productive, making the destination too much similar to one's own experience at home.

Social Media Analytics

2022 ◽  
pp. 385-410
Author(s):  
Časlav Kalinić ◽  
Miroslav D. Vujičić
Keyword(s):  
Social Media ◽  
Big Data ◽  
Cultural Tourism ◽  
Social Media Analytics ◽  
Online Platforms ◽  
New Information ◽  
People Participation ◽  
Management And Development ◽  
Social Media Platforms ◽  
Tourism Destinations

The rise of social media allowed greater people participation online. Platforms such as Facebook, Twitter, Instagram, or TikTok enable visitors to share their thoughts, opinions, photos, locations. All those interactions create a vast amount of data. Social media analytics, as a way of application of big data, can provide excellent insights and create new information for stakeholders involved in the management and development of cultural tourism destinations. This chapter advocates for the employment of the big data concept through social media analytics that can contribute to the management of visitors in cultural tourism destinations. In this chapter, the authors highlight the principles of big data and review the most influential social media platforms – Facebook, Twitter, Instagram, and TikTok. On that basis, they disclose opportunities for the management and marketing of cultural tourism destinations.

Prospect of Promoting Sikkim as a Smart Tourism Destination

2022 ◽  
pp. 326-345
Author(s):  
Supriya Dam
Keyword(s):  
Economic Growth ◽  
Smart City ◽  
Financial Support ◽  
The State ◽  
Tourism Destination ◽  
Essential Ingredient ◽  
North Eastern ◽  
Two Cities ◽  
Tourism Destinations ◽  
Smart Tourism

Since 2006, Sikkim progressively switching to a full-fledged tourism-centred state having declared it a predominant industry as an engine for its economic growth. The state accounted for the highest influx of foreign tourists amongst the eight north eastern states of India during the last 20 years or so. The smart city mission was commissioned by government of India as a centrally sponsored scheme destined to provide financial support for the allotted cities to the extent of INR. 100 Crore per city per year spanning over five years. Studies suggest that induction of smart city concept will act as precursor for growth of smart tourism destinations (STDs) across the country. The STD as a concept revolves around “6A's,” an essential ingredient for promoting smart tourism in destinations. Incidentally, two cities in Sikkim have been enlisted amongst the top 100 cities in India for promoting smart city, instrumental in promoting STD in tourism-driven states. The chapter delves into the concept of smart city as an antecedent for promoting STD along with conditions with respect to Sikkim.

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