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The Impact of User-Generated Content on Intention to Select a Travel Destination, Dissertation – Methodology Example

Pages: 11

Words: 3137

Dissertation - Methodology

Introduction

This chapter justifies the methodology the researcher will use to investigate the phenomenon and use primary and secondary data. The researcher will refer to the study’s objectives and aim, explaining why the researcher designed it. The components used to ensure reliability and validity, as well as the questionnaire design and way of analyzing the results and discussion of the research findings.

Aims and objectives

This study will investigate TripAdvisor reviews and how it influences the UGC travel customers’ decision-making process about attraction sites. The researcher will investigate how the number of positive reviews affects tourist decision-making. The researcher aims to gather data by assessing the picture, their quality, and the wording of the review and if or not that correlates to users’ decision when selecting their attraction sites to book. In this study, there is a need to focus on several listings on TripAdvisor.

Research Philosophy

The researcher aims to use a research-based approach in this study by constructing information based on the respondent’s state. The constructivism philosophy is reflected in this study through a systematic review of the social phenomenon so that the researcher uses an inductive method to generalize findings. The researcher uses this philosophy of constructivism to gather facts through close observation and measurement using the quantitative method to help conclude and reflect on the objectivity of the existing realities. By understanding behavior, the researcher can reinforce the complexity of the participant’s views and narrow them down to find meaning.

The researcher will also use post-positivism to investigate users’ decision-making process after viewing negative and positive comments on TripAdvisor and booking attraction sites… the reduction of ideas from the respondents will be by testing hypotheses and refuting or supporting existing theories about acceptable marketing mechanisms using technological tools.

Research Approach

Primary and Secondary Data Research

The researcher will collect both primary and secondary data in this research. The secondary data is from document analysis and reviews of previous ratings and research studies. However, the questionnaire’s primary exercise will generate the primary data for the study. The researcher gathered data from the self-administer questionnaire by selecting the target participants using stratified sampling.

The total number of responses that the researcher target is at least one thousand per month in the three years. The researcher will extract the data or Google into an excel file for analysis using the SPSS software. The statistical test will be vital in deriving the quantitative data. Quantitative data from the SPSS software allows the researcher to manipulate the data by running several statistical tests such as the Mann-Whitney-U test, correlation, and chi-square to analyze relations and trends among the variables. Taecharungroj and Mathayomchan (2019, p. 550-560) state that the SPSS software is vital for social scientists since it helps them design methods to test hypotheses and handle complex statistical problems.

Wang and Kirilenko (2021, p. 294) write that the chi-square and Pearson correlations tests are vital statistical methods to test the existence of a relationship between variables or two groups. Lee et al. (2022, p. 347-364) write that these tests offer acceptable levels and rate of significance determined by a 0.05 probability that indicates a lack of a significant relationship or a 1 indicating a relationship. A result above 5% indicates no significance between variables. P values result when testing a null hypothesis indicates that the researcher should reject it since the results show the implicitly meaningless level of acceptance of that hypothesis, whether the null or alternative hypothesis.

The chi-square test statistically analyzes the significance levels and predefines the hypothesis based on the results of the tests that have been rejected or accepted. Data analysis and the questionnaire results should be precise and cleaned depending on themes. Thus, the researcher should code the data to ensure responses fit pre-existing patterns and valid research areas.

Quantitative Method

This study uses a quantitative research design to collect data. According to Ganzaroli et al. (2021, p. 2044), web-based and social media are critical in offering information and content to tourists. These people rely on the contribution, opinions, and information that sharers leave on each of their destinations and formulate the basis of the places they will visit, the activities they will do while there, and sometimes, the duration of their stays. It is thus vital that the content and information on the Trip Advisor application is accurate, timely, and serves the purpose of the viewers. Fitchett and Hoogendoorn (2019, p. 91-109) explain that marketing significantly influences information uptake and decision-making in the touring sector. The travel blogs and reviews left on these web pages are thus vital in information gathering for traveling clients. The information on attractions, destinations, activities, services, and products is essential and should have adequate information, images, and descriptions to help the tourists make their decisions.

The researcher will use a survey design of a selected city to select TripAdvisor reviews and evaluate how the rating influence consumerism in term of choice of destination. The researcher will select a convenient city for them, sample several attraction sites, products, and services rated on TripAdvisor, and evaluate how the reviews’ positivity, neutrality, and negativity affect their business. Taecharungroj and Mathayomchan (2019, p. 568) assert that the aim is to use a numeric description of the attitudes, trends, and opinions among the population under study. The quantitative output will help the researcher in coming up with generalized that the people who rely on TripAdvisor can use to make informed business decisions whether they are business owners or users and tourists.

Fitchett and Hoogendoorn (2019, p. 91-109) state that the clients favor pictures followed by brief descriptions instead of lengthy write up with fewer pictures. As a result, the picture is more helpful in telling the story and explaining a destination and the services than length descriptions.

Research Questionnaire

The researcher will use a closed questionnaire with sixteen questions divided into three sections. The first section collects the necessary data about the participants, such as their age, place of residence, gender, frequency, level of education, name of the attraction site, how many reviews the facility has, and the bookings per annum. This section of the questionnaire had a nominal binary scale; thus, the categories of the section that the participants responded to are based on that scale. The possible answers are coded as no—1, yes-2, and none of the two-3. Gender and age had ranges; thus, the range can be coded on a scale of one to five. The gender scale of one to three, where one denotes female, two denotes male, and 3, the person does not identify as either of the genders. The second section defines the frequency of several facility, product, and destination bookings and the number of positive, neutral, and negative reviews. The length questionnaire is also cost-effective and helps quickly collect all necessary data. All parts of the questionnaire are coded, and the data will be analyzed depending on them to show correlation, range, frequency, agreeability, and other critical factors in the questionnaire using both the Likert and nominal binary scales. The researcher is interested in the importance of ratings from the Likert scale to measure the importance.

Measurement Items

The methodology the researcher users to analyze the impact of online reputations, comments, and reviews on TripAdvisor on influencing tourist destinations will be quantitative. The information gathered will be from the TripAdvisor web page and portal. The researcher will manually extract the review using SPSS statistical analysis to enable the researcher to index the specific ratings and words that negatively and positively impact the client’s decision-making process.

After extracting all the relevant data, the researcher used quantitative techniques to evaluate the frequency of positive and negative ratings, the correlation between ratings by eWoMs, and the number of tourists booking a destination. The analysis is through SPSS’s second version of statistical software. The nominal variable depends on the openness of responses, noncoding, and processing using the software.

Variables

Place Nationality Gender Month
The researcher will rank attractions by generating ratings of opinions and how they receive tourists. The researcher will define the approximation regarding socio-demographics profiling of tourists visiting the places and the importance of TripAdvisor marketing in that city. The researcher will compare the percentage of women and men giving negative or positive reviews. The researcher will analyze seasons in a year when the greatest online reviews are generated from TripAdvisor and correlate the investigation with seasonality in that city.
Year Title Reviews Valuation
The researcher will chart the decline or growth of eWoMs generated annually in the years between 2021-2023 The researcher will investigate the initial image or concepts that people use to judge their destinations and if they base it on the negative, neutral, and positive reviews users leave on TripAdvisor. The researcher will measure satisfaction on a scale of 0-5 on selected attraction sites, services, and destinations and quantify if the variable represents the booking rates depending on seasonality. Using a Likert scale, the researcher will calculate eWoMs, opinions, and reviews based on the online reputation users leave on TripAdvisor. The ranking of restaurants, hotels, and travel destinations will determine the frequency of words such as bad, lousy, terrible, normal, excellent, and good, affecting the rate at which you book the places or services.

The table below shows an analysis of other conglomerates with similar comments, reviews, and opinions wording.

Sampling technique

This study will sample participants with reviews and comments on TripAdvisor eWoM, OTRs, and TGC as information resources for tourists and people in the hospitality industry. The OTRs on the websites will be measured to ascertain the users’ impression of attraction, quality of services, products, and activities in a destination.

 

                                                   Frequency          Percentage                 

Old Town                                                                                         1158                              28.9

Promenade                                                                                        308                               7.7

Banús Harbor                                                                                  1553                               38.7

Avenida Del Mar Promenade                                                        350                                8.8

Alameda Park                                                                                   203                                5.1

Constitución Park                                                                              48                                 1.2

La Cañada Shopping Center                                                               25                                  6.2

Venus–Bajadilla Beach                                                                    48                                 1.2

Cabopino Beach                                                                                90                                  2.2

Total                                                                                                 4009                               100

 

The researcher will distribute the tourist destinations, hotels, and restaurants section to ensure fair random stratified sampling. The researcher will focus on hundred destinations and attraction sites, hundred services, and hundred products that these providers offer to the tourists and evaluate how negative, neutral, or positive reviews affect the selection of that destination. To select this accurate sample, the research will categorize data collection from restaurants, attraction sites, and hotels and the services they offer at each place, including transfers and social and tourist activities. The data or a specific city will be selected, and the analysis will help the researcher understand people’s perceptions when picking tourist destinations based on the city’s available resources. The period that the researcher will analyze is between 2021 and 2023.

According to Ali et al. (2021, p.100892), TripAdvisor receives over three hundred million comments and reviews between 2021 and 2023 for the city. The manual verification that the researcher did indicates that the reviews with corresponding responses were about a third of the total reviews. The reviews the researcher found accurate, or the geographical area description, were about two hundred. Many of these people who left comments and reviews about various destinations they visited in the city were done while they were still in that location—the eWoMs were more accurate, especially those accompanied by view pictures and videos to elaborate the points.

There were also over thirty thousand opinions where people debated and discussed various services and destinations, with some rating the services as exquisite and others who did not like them so much. In such a case, the research focused on the independent reviews and comments in the discussion posts as these give tourists an accurate depiction of what they are likely to find depending on what they are looking for and the items they have on their to-do list.

After specifying the parameter or sampling, the researcher extracted data and comments or TripAdvisor and encoded them directly in tables. Since the study is quantitative and does not focus so much on perception but its level, the researcher built a tool to estimate how much weight each of the online reputations, opinions, comments, and eWoMs carried about a product, service, or destination. The variable the researcher considered for the TripAdvisor web page is the manual extraction of ratings, the comment base measured on the IBM SPSS statistics version 2 model.

Methodology design

Figure 1: Methodology design

Source: (Researcher, 2023)

Sampling Pilot Test

The pilot sampling will test for possible errors and help the researcher modify the questionnaire to ensure clarity and enhance understanding of all the questionnaires, perfect language, and responses. TripAdvisor content is user generated based on their viewpoint. Users may also find it more useful to upload pictures to manifest their liking or dislike of an item or service.

Validity and Reliability

Validity ensures accuracy in research so that the outcome represents reality. The accuracy of the data collection guarantees that the participants give accurate responses. To ensure the respondents understood what whey asked of them, the researcher peer-reviewed the questionnaire, which Taecharungroj and Mathayomchan (2019, p. 568) state ensures the language was easy to understand and that the exercise was manageable for the participants. The researcher also connected the questions to the objectives and aim of the study to ensure relevance and applicability.

Reliability refers to the consistency of the data found. The researcher uses observation, all document analysis of secondary data sources, and the questionnaire to ensure data triangulation and saturation. They will exhaust all the facts and gather all the necessary information. The researcher was transparent in representing the outcome and reporting on all the findings from the data.

Data Collection

The researcher will begin the data collection in March 2023 and mail the questionnaire to TripAdvisor users and attraction sites on the application. Data collection will take two weeks to allow respondents adequate time to mail them back.

Ethical considerations

At the beginning of the questionnaire, the researcher asked the participants to read the exercise’s nature and purpose. No names or specific ages could be used to identify the respondents. Participation in the exercise was voluntary, and there was no pressure or coercion. The participants were free to ask for clarification and leave at any stage of the filling process. The researcher gave the research tool to peers to ensure all information was neutral and not offensive or unfriendly to the participants.

The researcher took several steps to protect the identity of the restaurants, holes, and attraction sites included in this study. These places were coded to ensure the data did not affect their tourism activities. The researcher also kept the participants’ identities anonymous by excluding any personal data that could be used to identify them. The online questionnaire was confidential and conducted anonymously; thus, the respondents’ answers could not be linked to them. The step also excluded the possibility that their provided data could be misused.

Data Analysis

The researcher will gather data online using the closed questionnaire and use statistical code to copy and analyze it on SPSS software. The primary data will allow statistical testing to measure the results’ accuracy and describe the outcome using descriptive methods such as frequencies and tabulation. This explanation will explain the relationship between eWoMs on TripAdvisor and the type of reviews that users leave on it.

SPSS analysis and statistical method for quantitative data

SPSS analysis and statistical method for quantitative data

The gender representation of the respondents indicates majority were females ranging at 63.8%, while 35.4% of reviewers were male. These reviews form the primary data that the researcher will discuss; thus, it is vital to understand the gender specificity and what kind of reviews the males and females are likely to leave on TripAdvisor.

Age distribution

Age distribution

The participant’s ages ranged from below 20 t 0 above 41. Most of the reviews were from people between 20-25. Those below 20 years commented the least, with the age group between the ages of 25-30 years having a substantial number of comments. The ages of 30-40 have a review rate of 4%, while the review rate goes up to 6%.

Correlation through clustering by word similarity

Figure 4: Correlation through clustering by word similarity

The researcher observed a high correlation between booking and attraction sites with specific words that denote positive reviews. Geographical areas rated 6-denoting excellent services, sites, and products, with higher ratings of booking than those with negative words such as lousy and bad.

Education level

The level of education determines the amount of meaningful review. The researcher focused on reviews that could be translated into English.36.2% of the reviews had post-education, 31.5% had tertiary education, and 2.3% had no formal education. The positive review goes up based on the shortage of stay and the level of education. Participants with low education levels had more negative reviews, while the average level had more positive reviews, and the reviewers with high education levels had many neutral reviews. The lengthier the comment, the more detail there was and use of words that the researcher used to clarify a review as positive or negative. The lengthy negative and positive reviews thus fell under the neutral category. The lengthy review also described the product, destination site, or service in extensive detail and thus was generally more objective. The short responses were easy to classify as positive or negative, as the reviewers used these keywords to explain their perception of the places.

Reference List

Ali, T., Marc, B., Omar, B., Soulaimane, K. and Larbi, S., 2021. Exploring destination’s negative e-reputation using aspect-based sentiment analysis approach: case of Marrakech destination on TripAdvisor. Tourism Management Perspectives40, p.100892.

Fitchett, J.M. and Hoogendoorn, G., 2019. Exploring the climate sensitivity of tourists to South Africa through TripAdvisor reviews. South African Geographical Journal= Suid-Afrikaanse Geografiese Tydskrif101(1), pp.91-109.

Ganzaroli, A., De Noni, I. and Bonera, M., 2021. The influence of foreigners’ buzzing on TripAdvisor ranking of restaurants in Venice: Implications for the sustainability of over-touristed heritage cities. Current Issues in Tourism24(14), pp.2044-2058.

Lee, J., Benjamin, S. and Childs, M., 2022. Unpacking the emotions behind TripAdvisor travel reviews The case study of Gatlinburg, Tennessee. International Journal of Hospitality & Tourism Administration23(2), pp.347-364.

Taecharungroj, V. and Mathayomchan, B., 2019. Analysing TripAdvisor reviews of tourist attractions in Phuket, Thailand. Tourism Management75, pp.550-568.

Wang, L. and Kirilenko, A.P., 2021. Do tourists from different countries interpret travel experiences with the same feeling? Sentiment analysis of TripAdvisor reviews. In Information and Communication Technologies in Tourism 2021: Proceedings of the ENTER 2021 eTourism Conference, January 19–22, 2021(pp. 294-301). Springer International Publishing.

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