7218 THS- Manage Tourism And Hospitality Information Assessment Answer

Introduction

The hospitality and tourism industry is one of the major business concepts for maintaining the profit graph of a significant organisation. The hospitality service provided by an individual hotel is one of the other key challenges for maintaining the enhancement in the consumer graph (Reyes-Menendez et al., 2020). Basically, the networking reviews of a particular brand are the potential key factor for the brand. This academic research literature review is totally based on online reviews in the hospitality and tourism industry. This literature review maintains the basic guidelines of the significance of online reviews, major issues along with the provided solutions by the researchers.

Discussion

Researched Pieces of Information

Majorly used networking methods to know the primary details about any significant hotels or lodges in a trip destination are known as the online reviews of the hotel as well as the lodge. Basically, online reviews promote the hospitality experienced by consumers. A numeric count of research already found that online reviews majorly have a positive impact on the hotel’s brand image to maintain the primary consumer base. Secondly, the overviews of the hotels have positively enhanced the bookings of hotels and maintained the primary decisions on prior demand. On the other side, negative reviews totally damage the consumer's attention to the particular hotel (Amatulli, De Angelis and Stoppani, 2019). Few study research has created the general characteristics of Online Reviewers. Basically, a group of genuine reviewers always maintains to share their actual experience on the hospitality provided by the hotels. Whereas some paid reviewers always maintain a positive image of the hotels in the review section of the hotels. The positive and majorly used information in online reviews is one of the crucial key components in the hospitality and tourism industry (Gour, Aggarwal and Erdem, 2021). The innovative researchers have highlighted the positive along with the prior demand for online reviews in the Hospitality and Tourism industry.

The Significance of Online Reviews

The increasing along in the demanding networking business world has a positive impact on the primary data such as information about real-life examples. Crucially the online reviews of a particular hotel as well as a lodge always create the positive as well as the negative image of the brand. The consumers of the Hotels always use to maintain the feedback in networking websites that advertises the hotels. A particular percentage of positive feedback such as affirmative reviews always use to maintain the enhancement of the consumer graph of the hotel. Basically, online reviews create the brand images along with it has the potential to damage the brand image (Park, Sutherland and Lee, 2021). The innovative ways of hospitality to the consumers always create a positive side of the particular brand. The studies of Park, Sutherland and Lee, (2021), addressed that, maintaining the brand image is one of the major key concepts to maintain the profit graph. The influence of previous consumers is always crucial and demanding for the upcoming consumers. Whereas the paid reviews of the hotel also maintain a positive graph to seek the attention of upcoming consumers. Basically, an analytical graph report directed that a 10% growth in positive reviews always creates a minimum percentile of 4-5% in hotel bookings.

The Central Issues

Current networking business worlds have several central issues that appear in online reviews in the hospitality and tourism industry. All the central issues are structured below in tabular format.

Insights on online Reviews in the Hospitality and Tourism Industry

The previous research study reports have already mentioned a numeric number of innovative insights on the addressed topic of online reviews in the hospitality and tourism industry. Basically, few studies have continuously maintained the affirmative impact on the consumer buying approach such as the booking of the hotels. One positive review enhances the initial chance of booking the brand (Cheng et al., 2019). The innovative researchers have also found the primary intention of making the fake image to the upcoming consumer by using paid reviewers. Whereas the negative reviews totally create damage in the networking image of hotels. On the other hand, the paid reviewers maintain positive reviews to create a positive image of the particular hotels. The previous researchers demandingly identified the manipulation of the reviewers to create an affirmative brand image for the consumer. The explored data of previous researchers shows the massive insights of online reviews in this potential business sector. The insights are maintaining consumer purchasing behaviour, creating a positive brand image for the consumer, and influencing the consumer base by advertising through the networked media (Reyes-Menendez et al., 2020). Overall the previous research shows the importance of online reviews in the hospitality and tourism industry. It has the initial potential to enhance the profitable business graph.

The Likely Solutions Addressed by Researchers

The researchers have already demonstrated a numeric count of solutions to mitigate the critical issues to maintain the business graph. The several recommended solutions are stated below in tabular format.

The Identified Issues of Understanding

Several genuine issues are addressed in the tabular format below

Conclusion

This entire researched literature review concluded that the key challenges of maintaining the brand image are one of the demanding challenges for the organisation. Online reviews in the hospitality and tourism industry create a positive brand image for significant brands. This researched literature review is proposed to address the authentic reviews along with the potential challenges. The unresolved identified issues are also addressed to find out the authenticity and trust of the significant brand.

Critical Reflection

Used artificial intelligence tools to assist

Assistance with editing and ensuring grammatical accuracy when producing this literature review, I used a computer program called Grammarly. Grammarly is an AI-powered writing helper that offers in-the-moment corrections for spelling, grammar, and punctuation mistakes as well as formatting ideas. It improves the text's overall clarity and coherence by pointing out any problems that might have gone unnoticed during the authoring process. I was able to raise the content's quality and make sure that the thoughts and ideas were communicated clearly. This tool assisted me in adhering to grammar rules and maintaining a consistent writing style, resulting in a more polished and expert presentation of the content. The use of Grammarly to serve as an artificial tool in the literature review process improved the text's readability and accuracy, which in turn improved readers' comprehension and interest.

The reason behind choosing this tool

Due to its established track record as a dependable AI-powered writing helper, Grammarly was my choice for the tool for this discussion. By offering insightful tips for grammar, spelling, punctuation, and style corrections, Grammarly is renowned for its capacity to improve the quality of writing. In my role as a language model, I work to respond to users' questions in a precise and comprehensible manner, and Grammarly helps me to do that. I may use Grammarly to make sure that none of my comments contain typos or typical grammatical problems, resulting in a more polished and expert presentation of data. My writing is more readable and understandable for people overall because to the tool's in-context suggestions, which also help me have a consistent writing voice and follow grammar rules. Because they may expect more precise and logical answers to their queries, this improves the user experience.

Rise of artificial intelligence and its Benefits and Consequences

The emergence of artificial intelligence (AI) brings intriguing opportunities and potential concerns for those studying tourism and hospitality and for future professionals. Various facets of the industry, including client care and personalization as well as data analysis and revenue management, have already begun to change as a result of AI. The ability of AI to improve client experiences is one of the most important advantages it has for the travel and hospitality industries. Chatbots and virtual assistants powered by AI can respond quickly and personally to client enquiries, increasing engagement and happiness. Additionally, AI systems can examine big data sets to find trends and patterns, assisting organisations in making defensible judgements and streamlining their processes. However, there are some issues with the AI integration as well. Since hospitality is based on personalised experiences, it will be vital for future professionals to strike an equilibrium between the usage of AI and preserving human engagement. As client data is a major component of artificial intelligence systems, ensuring data security and privacy will also be of utmost importance.

It will be crucial for students to stay current on the most recent advancements in AI and its uses in the travel and hospitality industries. Future professionals' biggest issue will be embracing AI as a tool for creativity and efficiency while maintaining the human touch in the workplace. In conclusion, the future of the tourism and hospitality sector will surely be shaped by understanding and utilising AI's potential, making it an exciting and dynamic topic to research and contribute to as an aspiring and future professional.

Reference list

Amatulli, C., De Angelis, M., & Stoppani, A. (2019). Analyzing online reviews in hospitality: data-driven opportunities for predicting the sharing of negative emotional content. Current Issues in Tourism, 22(15), 1904-1917. https://doi.org/10.1080/13683500.2019.1594723

Cheng, X., Fu, S., Sun, J., Bilgihan, A., & Okumus, F. (2019). An investigation on online reviews in sharing economy driven hospitality platforms: A viewpoint of trust. Tourism Management, 71, 366-377. https://doi.org/10.1016/j.tourman.2018.10.020

D’Acunto, D., Tuan, A., Dalli, D., Viglia, G., & Okumus, F. (2020). Do consumers care about CSR in their online reviews? An empirical analysis. International Journal of Hospitality Management, 85, 102342. https://doi.org/10.1016/j.ijhm.2019.102342

Gour, A., Aggarwal, S., & Erdem, M. (2021). Reading between the lines: analyzing online reviews by using a multi-method Web-analytics approach. International Journal of Contemporary Hospitality Management, 33(2), 490-512. https://doi.org/10.1108/IJCHM-07-2020-0760

Jain, P. K., Pamula, R., & Srivastava, G. (2021). A systematic literature review on machine learning applications for consumer sentiment analysis using online reviews. Computer science review, 41, 100413. https://doi.org/10.1016/j.cosrev.2021.100413

Park, C. W., Sutherland, I., & Lee, S. K. (2021). Effects of online reviews, trust, and picture-superiority on intention to purchase restaurant services. Journal of Hospitality and Tourism Management, 47, 228-236. https://doi.org/10.1016/j.jhtm.2021.03.007

Park, E., Kang, J., Choi, D., & Han, J. (2020). Understanding customers' hotel revisiting behaviour: a sentiment analysis of online feedback reviews. Current Issues in Tourism, 23(5), 605-611. https://doi.org/10.1080/13683500.2018.1549025

Reyes-Menendez, A., Correia, M. B., Matos, N., & Adap, C. (2020). Understanding online consumer behavior and eWOM strategies for sustainable business management in the tourism industry. Sustainability, 12(21), 8972. https://doi.org/10.3390/su12218972

Sánchez-Franco, M. J., Navarro-García, A., & Rondán-Cataluña, F. J. (2019). A naive Bayes strategy for classifying customer satisfaction: A study based on online reviews of hospitality services. Journal of Business Research, 101, 499-506. https://doi.org/10.1016/j.jbusres.2018.12.051

Seo, K. H., & Lee, J. H. (2021). The emergence of service robots at restaurants: Integrating trust, perceived risk, and satisfaction. Sustainability, 13(8), 4431. https://doi.org/10.3390/su13084431

Sutherland, I., Sim, Y., Lee, S. K., Byun, J., & Kiatkawsin, K. (2020). Topic modeling of online accommodation reviews via latent dirichlet allocation. Sustainability, 12(5), 1821. https://doi.org/10.3390/su12051821

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