Hotels Pricing at Travel Search Engines

2011 ◽  
Vol 1 (4) ◽  
pp. 64-74
Author(s):  
Anastasios A. Economides ◽  
Antonia Kontaratou
Keyword(s):  
Data Analysis ◽  
Web 2.0 ◽  
Search Engine ◽  
Search Engines ◽  
Information Sources ◽  
Descriptive Statistics ◽  
Tourism Destinations ◽  
Price Analysis

Web 2.0 applications have been increasingly recognized as important information sources for consumers, including the domain of tourism. In the center of the travelers’ interest is the use of these applications in order to compare and choose hotels for their accommodation at various tourism destinations. It is important to investigate the issues related to the presence of the hotels on some of the most dominant tourism search engines and to the prices that they present. This paper compares the search engines and determines whether the cheapest and to the most complete one can be discovered. This paper focuses on analyzing the hotel prices presented on their official websites and on the following eight tourism search engines: Booking.com, Expedia.com, Hotelclub.com, Hotels.com, Orbitz.com, Priceline.com, Travelocity.com, and Venere.com. The data analysis, by the use of the descriptive statistics, showed that only 23% of the hotels examined are found at all the search engines. Furthermore, the price analysis showed that there are differences among the search engines. Although some search engines statistically give lower prices, there is not a single search engine that always gives the lowest price for every hotel.

Hotels Pricing at Travel Search Engines

2013 ◽  
pp. 295-305
Author(s):  
Anastasios A. Economides ◽  
Antonia Kontaratou
Keyword(s):  
Data Analysis ◽  
Web 2.0 ◽  
Search Engine ◽  
Search Engines ◽  
Information Sources ◽  
Descriptive Statistics ◽  
Tourism Destinations ◽  
Price Analysis

Web 2.0 applications have been increasingly recognized as important information sources for consumers, including the domain of tourism. In the center of the travelers’ interest is the use of these applications in order to compare and choose hotels for their accommodation at various tourism destinations. It is important to investigate the issues related to the presence of the hotels on some of the most dominant tourism search engines and to the prices that they present. This paper compares the search engines and determines whether the cheapest and to the most complete one can be discovered. This paper focuses on analyzing the hotel prices presented on their official websites and on the following eight tourism search engines: Booking.com, Expedia.com, Hotelclub.com, Hotels.com, Orbitz.com, Priceline.com, Travelocity.com, and Venere.com. The data analysis, by the use of the descriptive statistics, showed that only 23% of the hotels examined are found at all the search engines. Furthermore, the price analysis showed that there are differences among the search engines. Although some search engines statistically give lower prices, there is not a single search engine that always gives the lowest price for every hotel.

The Externalities of Search 2.0: The Emerging Privacy Threats when the Drive for the Perfect Search Engine meets Web 2.0

First Monday ◽  
2008 ◽  
Author(s):  
Michael Zimmer
Keyword(s):  
Web 2.0 ◽  
Search Engine ◽  
Search Engines ◽  
Information Seeking ◽  
Web Search ◽  
Personal Information ◽  
Informational Privacy ◽  
Capture Process ◽  
Privacy Threats ◽  
Intellectual Activities

Web search engines have emerged as a ubiquitous and vital tool for the successful navigation of the growing online informational sphere. As Google puts it, the goal is to "organize the world's information and make it universally accessible and useful" and to create the "perfect search engine" that provides only intuitive, personalized, and relevant results. Meanwhile, the so-called Web 2.0 phenomenon has blossomed based, largely, on the faith in the power of the networked masses to capture, process, and mashup one's personal information flows in order to make them more useful, social, and meaningful. The (inevitable) combining of Google's suite of information-seeking products with Web 2.0 infrastructures -- what I call Search 2.0 -- intends to capture the best of both technical systems for the touted benefit of users. By capturing the information flowing across Web 2.0, search engines can better predict users' needs and wants, and deliver more relevant and meaningful results. While intended to enhance mobility in the online sphere, this paper argues that the drive for Search 2.0 necessarily requires the widespread monitoring and aggregation of a users' online personal and intellectual activities, bringing with it particular externalities, such as threats to informational privacy while online.

scholarly journals What Do You Need to Know to Use a Search Engine? Why We Still Need to Teach Research Skills

AI Magazine ◽  
2015 ◽  
Vol 36 (4) ◽  
pp. 61-70 ◽  
Author(s):  
Daniel M. Russell
Keyword(s):  
Search Engine ◽  
User Interfaces ◽  
Search Engines ◽  
Question Answering ◽  
Information Sources ◽  
The Internet ◽  
Depth Of Processing ◽  
Simple Fact ◽  
Front End ◽  
Question Answering Systems

For the vast majority of queries (for example, navigation, simple fact lookup, and others), search engines do extremely well. Their ability to quickly provide answers to queries is a remarkable testament to the power of many of the fundamental methods of AI. They also highlight many of the issues that are common to sophisticated AI question-answering systems. It has become clear that people think of search programs in ways that are very different from traditional information sources. Rapid and ready-at-hand access, depth of processing, and the way they enable people to offload some ordinary memory tasks suggest that search engines have become more of a cognitive amplifier than a simple repository or front-end to the Internet. Like all sophisticated tools, people still need to learn how to use them. Although search engines are superb at finding and presenting information—up to and including extracting complex relations and making simple inferences—knowing how to frame questions and evaluate their results for accuracy and credibility remains an ongoing challenge. Some questions are still deep and complex, and still require knowledge on the part of the search user to work through to a successful answer. And the fact that the underlying information content, user interfaces, and capabilities are all in a continual state of change means that searchers need to continually update their knowledge of what these programs can (and cannot) do.

scholarly journals Assessing the Level of Popularity of European Stag Tourism Destinations

2016 ◽  
Vol 35 (3) ◽  
pp. 15-29 ◽  
Author(s):  
Grzegorz Iwanicki ◽  
Anna Dłużewska ◽  
Melanie Smith Kay
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Primary Objective ◽  
Continental Scale ◽  
Travel Agencies ◽  
Academic Publications ◽  
Tourism Destinations ◽  
Engine Method

Abstract The primary objective of this article is to determine the degree of popularity of stag tourism destinations in Europe. Research was based on the search engine method, involving an analysis of the highest positioned offers of travel agencies in the most commonly used search engines in Europe (Google, Bing, Yahoo). The analysis divided the studied cities into four categories in terms of popularity. Conducting the said analysis is strongly justified, because academic publications have so far not provided studies which have determined the degree of popularity of stag destinations on a continental scale.

Social Media as Information Sources and Their Influence on the Destination Image

2018 ◽  
pp. 265-283 ◽  
Author(s):  
María Pilar Martínez-Ruiz ◽  
Isabel Llodrá-Riera ◽  
Ana Isabel Jiménez-Zarco
Keyword(s):  
Social Media ◽  
Web 2.0 ◽  
Information Sources ◽  
Destination Image ◽  
User Generated Content ◽  
Destination Marketing ◽  
Tourist Destination ◽  
Travel And Tourism ◽  
Tourism Destinations ◽  
Travel Decisions

Tourists use social media to share their experiences and obtain information about travel and tourism destinations. Information shared by tourists is different than information published by destination marketing organizations (DMOs) in the sense that it does not include formal messages and photographs. Some researchers have proven that user-generated content (UGC) through social media exerts an influence on the perceived image of a tourist destination and the motivations for visiting it. Tourists and travelers tend to use a combination of official and unofficial information to make travel decisions. Nowadays, there are still plenty of opportunities to advance destination image research using social media. With these ideas in mind, this chapter aims to review different types of Web 2.0 platforms and discuss their influence on destination image formation and sustainability perception.

Comparison Shopping Behaviour in Online Environments

2010 ◽  
pp. 119-133
Author(s):  
Carla Ruiz Mafé ◽  
Silvia Sanz Blas
Keyword(s):  
Data Analysis ◽  
Search Engine ◽  
Search Engines ◽  
Online Purchases ◽  
Information Tools ◽  
Comparison Shopping ◽  
Factors Influencing ◽  
Shopping Behaviour ◽  
Key Drivers ◽  
Willingness To Use

The aim of this chapter is to analyse antecedents of search engines use as prepurchase information tools. Firstly, there is a literature review of the factors influencing search engines use in online purchases. Then, there is an empirical analysis of a sample of 650 Spanish E-shoppers. Logistical regression is used to analyse the influence of demographics, surfing behaviour and purchase motivations on willingness to use search engines for E-shopping. Data analysis shows that experience as Internet user and as Internet shopper are negative key drivers of search engine use. Most of the utilitarian shopping motivations analyzed predict comparison shopping behaviour. Demographics are not determinant variables in the use of search engines in online purchases. This research enables companies to know the factors that potentially affect search engine use in E-shopping decisions and the importance of using search engines in their communication campaigns.

What does Google recommend when you want to compare insurance offerings?

2019 ◽  
Vol 71 (3) ◽  
pp. 310-324
Author(s):  
Dirk Lewandowski ◽  
Sebastian Sünkler
Keyword(s):  
Data Analysis ◽  
Empirical Study ◽  
Search Engine ◽  
Search Engines ◽  
Large Scale ◽  
Insurance Companies ◽  
Content Type ◽  
Search Queries ◽  
Large Scale Analysis ◽  
Search Engine Result

Purpose The purpose of this paper is to describe a new method to improve the analysis of search engine results by considering the provider level as well as the domain level. This approach is tested by conducting a study using queries on the topic of insurance comparisons. Design/methodology/approach The authors conducted an empirical study that analyses the results of search queries aimed at comparing insurance companies. The authors used a self-developed software system that automatically queries commercial search engines and automatically extracts the content of the returned result pages for further data analysis. The data analysis was carried out using the KNIME Analytics Platform. Findings Google’s top search results are served by only a few providers that frequently appear in these results. The authors show that some providers operate several domains on the same topic and that these domains appear for the same queries in the result lists. Research limitations/implications The authors demonstrate the feasibility of this approach and draw conclusions for further investigations from the empirical study. However, the study is a limited use case based on a limited number of search queries. Originality/value The proposed method allows large-scale analysis of the composition of the top results from commercial search engines. It allows using valid empirical data to determine what users actually see on the search engine result pages.

Hubungan Dinamika Kelompok dan Keberdayaan Peternak dengan Keberhasilan Program Kelompok Peternak Sapi Potong

2019 ◽  
Vol 2 (5) ◽  
pp. 603
Author(s):  
Muhammad Romadhon ◽  
Amiruddin Saleh
Keyword(s):  
Data Analysis ◽  
Correlation Coefficient ◽  
Group Dynamics ◽  
Descriptive Statistics ◽  
Statistic Analysis ◽  
Group Approach ◽  
The People ◽  
The Government ◽  
People Group ◽  
Cattle Farmer

A group approach having an excess because its scope broader, and in accordance with communal culture of the people. Group dynamics and independency farmers become a yardstick to judge whether the programs the government (the course of development) involving group cattle farmers cut is sustainable or not, so that it can be evaluated for sustainability the next. The purpose of research are (1) analyze group dynamics formed in the group spr mega jaya, (2) analyzed levels of independency of farmers in the farmers spr mega jaya, (3) analyze relations group dynamics and independency of farmers with the success kejar farmers spr mega jaya. Data analysis of analysis descriptive statistics (a frequency, the percentage, on the average), and statistic analysis inferential by test a correlation coefficient rank the spearman. The research results show that group dynamics spr mega jaya tends in category high, and independency of farmers spr mega jaya tends in category enough, while test relations shows that there is a positive connection welfare between group dynamics the cattle farmer and independency of farmers with the success kejar cattle farmers cut. This means that the more dynamic group spr mega jaya and independency of felt farmers high, so the success of the program group farmers who reached the higher.Keywords: group dynamics, independency of groups, sekolah peternakan rakyatABSTRAKPendekatan kelompok memiliki kelebihan karena cakupannya yang lebih luas, dan sesuai dengan budaya masyarakat komunal. Dinamika kelompok dan keberdayaan peternak menjadi tolok ukur untuk menilai apakah program pemerintah (program pembangunan) yang melibatkan kelompok peternak sapi potong bersifat sustainable atau tidak, sehingga dapat dievaluasi untuk keberlanjutan program selanjutnya. Tujuan dari penelitian adalah (1) menganalisis dinamika kelompok yang terbentuk dalam kelompok SPR Mega Jaya, (2) menganalisis tingkat keberdayaan peternak pada kelompok peternak SPR Mega Jaya, (3) menganalisis hubungan dinamika kelompok dan keberdayaan peternak dengan keberhasilan program kelompok peternak SPR Mega Jaya. Analisis data berupa analisis statistik deskriptif (frekuensi, persentase, rata-rata), dan analisis statistik inferensial dengan uji koefisien korelasi rank Spearman. Hasil penelitian menunjukkan bahwa dinamika kelompok SPR Mega Jaya cenderung pada kategori tinggi, dan keberdayaan peternak SPR Mega Jaya cenderung pada kategori cukup, sedangkan uji hubungan menunjukkan bahwa terdapat hubungan positif signifikan antara dinamika kelompok peternak dan keberdayaan peternak dengan keberhasilan program kelompok peternak sapi potong. Hal ini berarti bahwa semakin dinamis kelompok SPR Mega Jaya dan keberdayaan yang dirasakan peternak tinggi, maka keberhasilan program kelompok peternak yang tercapai semakin tinggi.Kata kunci: dinamika kelompok, keberdayaan kelompok, sekolah peternakan rakyat

Uji Kesukaan Es Krim Kefir Labu Kuning

2017 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Amanda Kania Diandini
Keyword(s):  
Diabetes Mellitus ◽  
Data Analysis ◽  
Experimental Method ◽  
Skim Milk ◽  
Ice Cream ◽  
Artificial Sweetener ◽  
Value Analysis ◽  
Nutrient Value ◽  
Bioactive Content ◽  
Price Analysis

The safe ice cream which is consumed by Diabetes Mellitus sufferers is made by subtituting skim milk, cream and sugar with kefir, pure pumpkin, cornstarch, vegetable oil, and artificial sweetener special gor Diabetes Mellitus. Kefir is known can decrease (blood sugar) because of its bioactive content. The aim of this research is knowing predilection level test to ice cream pumpkin kefir. This research is conducted with experimental method. The data analysis includes predilection test, nutrient value analysis, and price analysis. Ice cream pumpkin kefir that is liked most are from texture side, the cheapest price, and also the highest fiber content exists in balance 578 with the ratio of kefir and pumpkin 50%:50%. Ice cream pumpkin kefir that is liked most from colour side exists in balance 236 with the ratio of kefir and pure pumpkin 70%:30%. Ice cream pumpkin kefir that is liked most from taste side and aroma exists in balance 522 with the ratio between kefir and pure pumpkin 80%:20%.

scholarly journals The Matter of Chance: Auditing Web Search Results Related to the 2020 U.S. Presidential Primary Elections Across Six Search Engines

2021 ◽  
pp. 089443932110068
Author(s):  
Aleksandra Urman ◽  
Mykola Makhortykh ◽  
Roberto Ulloa
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Large Scale ◽  
Web Search ◽  
Primary Elections ◽  
Virtual Agents ◽  
Search Results ◽  
Presidential Primary ◽  
Large Scale Analysis ◽  
Algorithmic Information

We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default—that is nonpersonalized—conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale analysis of algorithmic information curation in a controlled environment. Specifically, we look at the text search results for “us elections,” “donald trump,” “joe biden,” “bernie sanders” queries on Google, Baidu, Bing, DuckDuckGo, Yahoo, and Yandex, during the 2020 primaries. Our findings indicate substantial differences in the search results between search engines and multiple discrepancies within the results generated for different agents using the same search engine. It highlights that whether users see certain information is decided by chance due to the inherent randomization of search results. We also find that some search engines prioritize different categories of information sources with respect to specific candidates. These observations demonstrate that algorithmic curation of political information can create information inequalities between the search engine users even under nonpersonalized conditions. Such inequalities are particularly troubling considering that search results are highly trusted by the public and can shift the opinions of undecided voters as demonstrated by previous research.

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