Influence of social media in travel decision making

Abstract

This paper explores the significant impact of social media on travel decision-making processes. With the rapid proliferation of social media platforms, individuals now have access to an extensive array of user-generated content and peer recommendations that greatly influence their travel choices. This study seeks to analyze the ways in which social media platforms shape perceptions, preferences, and decisions related to travel. The research delves into the mechanisms through which social media exerts its influence on travel decisions. It investigates how travelers use platforms like Instagram, Face book, Twitter, and travel-focused review sites to gather information, exchange experiences, and connect with other travelers. Furthermore, the study examines the role of influencers and content creators in shaping travel aspirations and choices. The interactive nature of social media platforms, including the ability to seek real-time advice and engage with travel-related content, adds a layer of immediacy and personalization to the decision-making process. The research on the influence of social media in travel decision making holds significant importance for several key stakeholders, including travelers, the travel industry, and researchers. Understanding the impact of social media on travel decisions empowers travelers to make more informed choices. By recognizing the role of social media, individuals can better navigate the vast array of travel information available and make decisions that align with their preferences and interests. Travelers can use the insights gained from this research to enhance their travel planning processes. They can identify reliable sources of information, seek real-time recommendations, and learn how to effectively engage with content and communities on social media to optimize their travel experiences. Applying the "Weighted Aggregated Sum Product Assessment (WASPAS)" method, those making decisions are able to evaluate possibilities based on a wide range of parameters. It involves providing criteria weights, determining scores for every potential and summing the results to determine the most suitable option. From the result Destination A is in first rank where as Destination E is lower rank.