The purpose of this study is to analyze the competitive relationships among the four major Global Distribution Systems (GDSs), which are representative reservation systems in the tourism industry by using niche theory. To that end, niche theory, which presents the three core concepts of niche breadth, niche overlap, and niche superiority, was combined with gratification in the uses to apply the gratification niche analysis technique. Based on an extensive literature review, four factors (core functions, system functions, service functions, and additional functions) to measure user satisfaction levels by function with GDSs were extracted. Online/offline questionnaire surveys were conducted with travel agencies’ airline counter staffs who had experience using all four GDSs, and in total, 324 copies of the questionnaire were used in the analysis. The analysis results confirmed that Sabre had a competitive edge in general over the other three GDSs, while TOPAS (Amadeus) and Galileo had a comparative competitive edge in certain functions. This study suggested concrete implications that can help individual GDSs in terms of their development of functions or the establishment of marketing strategies by verifying user satisfaction by the function of individual GDSs.

This study aimed to derive tourism motives and constraint factors that have changed or are newly applicable after COVID-19, and to identify the influencing relationships between these factors and complex aspects of tourism behavior intentions. For this purpose, the Push-Pull-Mooring model was used. To achieve the purpose of this study, prior literature and empirical studies were used to derive the primary measurement items through the primarily derived PPM model-based factors, and an online questionnaire survey was conducted with consumers who had had experience of overseas travel within the past two years. In total, 322 copies of the questionnaire were used for analysis. Through factor analyses, five push factors, four pull factors, and four mooring factors were derived. To understand tourism behavior intentions, each of the travel resumption times, preferred destination types, and preferred accommodation types were divided into three to conduct multinomial logistic regression analysis. The influence relationships between variables were verified to identify the changes in tourism behavior intentions caused by COVID-19, and the results indicated that some items of the PPM factors had significant influencing relationships with travel resumption times and preferred accommodation types. The preferred destination types were found to have significant influencing relationships with some items of the push/pull factors that were not found to have any influencing relationships with the mooring factors. This study is meaningful in that it presented motives and constraint factors for tourism behaviors from a new perspective based on changes in the tourism environment due to COVID-19, and the application of the PPM model and travel behavior is expected to be applied to diverse tourist behavior studies hereafter to achieve theoretical extensions.

Online guided tours have become an essential form of non-contact tourism, yet the experiential attributes shaping participants’ digital tour experiences remain underexplored. This study aims to identify the core experiential dimensions of online guided tours by analyzing user-generated review data and interpreting the findings through the experience economy framework. A dataset of 1506 participant reviews was collected from major online guided tour platforms and analyzed using text mining techniques, including TF-IDF and Latent Dirichlet Allocation (LDA). The results reveal the following seven experiential attributes: entertainment, education, esthetics, escapism, presence, interactivity, and digital environment. These findings indicate that online guided tours extend beyond traditional 4E experience dimensions, incorporating digitally mediated elements such as real-time communication and platform-driven immersion. The proposed “4E + 3D Model” captures the hybrid nature of digital tourism experiences, combining classic experiential factors with technology-enabled components. This study contributes to tourism experience research by empirically validating an expanded experiential structure suitable for digital contexts. It also demonstrates the value of user-generated review analysis for deriving authentic experiential insights. The results provide practical implications for enhancing online guided tour design, emphasizing real-time interactivity, digital esthetics, and system stability to improve participant experiences in virtual tourism settings.