Academic literature on the topic 'User Generated Content (UGC)'

UGC has become an important part of traveling both for the companies and for the travellers themselves. The topic is currently at its forefront of research, which makes the area of study even more relevant. Followed by the development of social media in the corporate world and especially its major part in the everyday life of Generation Y. The competition has become tougher among the destinations since social media, a positive online image has, therefore, become essential on these platforms due to the new ways of obtaining information in a previsiting setting. Instagram is an attractive platform for generation Y and the main channel for tourist to publish their visual word-of-mouth experience after a travel. The concept has its own name called, UGC which together with the consumers perceptions of it has been studied in this thesis. The purpose of the study was to see a comparison between the differences of perceived -usefulness, - credibility and -authenticity based on DMOC and UGC. Moreover, how the participants respond concerning the intention to visit Vienna based on an illustrated destination image of UGC or DMOC. The conceptual S-O-R-model was implemented to illustrate how the input of destination image, became a process of perceptions and outcome of intentions belongs together like a common thread. A quantitative study approach was applied with the strategy of Experimental vignette methodology (EVM), to formulate and illustrated the experiment also, to obtain empirical data which later was analyzed and defined the result. Additionally, the study found that there is no significant difference between USG and DMOC in perceived -usefulness, -credibility, and visiting intention. However, findings of perceived authenticity of the destination image demonstrated that UGC communicates a more positive destination image compared to the DMOC regarding perceived authenticity. Moreover, the practical contributions of this study suggest in accordance with previous studies DMO to cooperate with the users and in that way combine UGC with DMOC in the destination presentation.

Background: Throughout recent years, the amounts of competitions on Instagram have increased and is now a popular marketing tool for companies to use. The strong competition in digital marketing has led to the need for brands to effectively utilize this marketing strategy. However, what motivates users to participate is a subject that lacks previous research. Hence, the question of what motivates the users to participate remains. Purpose: The purpose of this study is, therefore, to explore the motivational factors for women in the ages between 16-25, which leads to participation in contests on Instagram. Further, this research additionally aims to proceed with the knowledge of UGC and partly investigate how companies can use the appeared motivational factors when designing and formulating contests.  Method: For this qualitative study, 15 interviews were conducted, using a phenomenological interview approach.  Conclusion: The main conclusion from the analysis was that several motivational factors were discovered that had not earlier been presented in previous research, the most significant one being the social aspects. Furthermore, the size of the prize and the non-motivational factors proved to be of importance for the users. Secondly, factors relating to entertainment, aesthetics and the desire to win were proved to be of high importance as well. Lastly, several managerial applications have also been discovered that could help businesses when forming contests on Instagram.

Background: The modern day era of the Internet gave birth to the growing phenomenon of Internet memes (IM), a type of online user generated content (UGC) (Gangadharbatla, 2008). Now marketers have begun researching the relationship between UGC and consumer based brand equity (CBBE) (Christodoulides et.al, 2012; Rachna and Khajuria, 2017). The problem discussion presents the issue of the diminishing control of brand equity due to the rise of UGC and lack of research on how to manage its influence (Morrison et al., 2013). Leading to the purpose of this thesis, which is to determine the impact Internet memes have on consumer based brand equity. Literature: The review presents two leading contributors to the field, Aaker’s (1991) framework on the different dimensions of CBBE and Keller’s (1993) definition of the concept. In addition recent studies on UGC and brand equity provided the basis for hypothesis development. Method: This thesis assumed a deductive research approach, developing the hypothesis from current literature in the field. A quantitative study, that utilized an explanatory research approach, because it best suited the experimental design. As for the data collection method, surveys were considered (Saunders et al., 2016), which the authors designed as a self-completion questionnaire and pre-tested (Bryman and Bell, 2015). Convenience sampling was chosen to select participants (Hernon, 2004). Construct and content validity was used along with homogeneity and stability to control reliability and measure the quality of research instruments (Bryman and Bell, 2015). SPSS version 25 was used to conduct all statistical analyses. Results: Four hypotheses were developed, to measure the effect of the independent variable IM on each of the four CBBE dimensions. To summarize, three of the hypothesis (H1, H3 and H4) were rejected as the difference in the means are not significant enough and can be explained by chance. The effect on brand association (H2) was however found to be significant therefore H2 was accepted.

L'objectiu d'aquesta investigació consisteix en determinar si el contingut generat pels usuaris en llocs webs relacionats amb la indústria de l'allotjament valida els sistemes de classificació de qualsevol establiment i plataforma d'allotjament per crear un sistema internacional de classificació d'hotels que pugui servir també per categoritzar qualsevol tipus d'allotjament. Aquesta memòria presenta el treball dut a terme a través de la descàrrega i l'anàlisi de prop de quaranta milions de ressenyes sobre hotels de tot el món descarregades des de TripAdvisor i Booking.com. D’una banda, s’analitza les valoracions dels usuaris sobre establiments d'allotjament per comparar les seves puntuacions i determinar que la posició que ocupen els hotels en el rànquing està molt relacionada entre TripAdvisor i Booking.com. De l'altra, la investigació consisteix en l'anàlisi dels sistemes de classificació d'hotels, demostrant que hi ha una relació entre les valoracions dels usuaris i les categories d'hotels a tot el món, de tal manera que les categories es poden predir a partir del contingut generat pels usuaris a internet, entre d'altres paràmetres. Finalment, a través de tècniques d'aprenentatge automàtic, es crea un model per classificar els establiments d'allotjament siguin tradicionals o plataformes d'allotjament col·laboratiu, com ara Airbnb, per a què convergeixin els diferents sistemes de classificació de tot el món.<br>El objetivo de esta investigación consiste en determinar si el contenido generado por los usuarios en webs relacionadas con la industria del alojamiento valida los sistemas de clasificación de cualquierestablecimiento y plataforma de alojamiento para crear un sistema internacional de clasificación de hoteles que pueda servir también para categorizar cualquier tipo de alojamiento. Esta memoria presenta el trabajo llevado a cabo a través de la descarga y el análisis de cerca de cuarenta millones de reseñas sobre hoteles de todo el mundo descargadas desde TripAdvisor y Booking.com. Por un lado, esta investigación se centra en analizar la información brindada por los usuarios con sus valoraciones sobre establecimientos de alojamiento para comparar sus puntuaciones y determinar que la posición que ocupan los hoteles en el ranking está muy relacionada entre TripAdvisor y Booking.com. Por el otro, la investigación consiste en el análisis de los sistemas de clasificación de hoteles, demostrando que existe una relación entre las valoraciones de los usuarios y las categorías de hoteles en todo el mundo, de tal manera que las categorías se pueden predecir a partir del contenido generado por los usuarios en internet, entre otros parámetros. Finalmente, a través de técnicas de aprendizaje automático, esta tesis crea un modelo que permite clasificar los establecimientos de alojamiento ya sean tradicionales o plataformas de alojamiento colaborativo, como Airbnb, para que converjan los diferentes sistemas de clasificación de todo el mundo.<br>The aim of this research is to determine whether online User-Generated Content (UGC) about the lodging industry validates the ranking system of any accommodation property or platform in order to create an international hotel classification system that may also serve to categorize any type of accommodation. This thesis presents the work carried out following the collection and analysis of nearly 40 million reviews of hotels worldwide downloaded from TripAdvisor and Booking.com. On the one hand, this research focuses on the analysis of information provided by users, and specifically their reviews of accommodation properties, to compare their scores and to determine whether the position of a hotel in both ranking systems is closely related. On the other hand, the research consists of the analysis of hotel classification systems. It demonstrates that although international classification systems are not unified, there is a relationship between users’ ratings and hotel categories worldwide. Consequently, categories can be predicted from UGC on the Internet, among other parameters. Finally, through machine learning, this thesis creates a model that allows accommodation properties, whether on traditional or collaborative hosting platforms (e.g., Airbnb), to be classified in such a way that different classification systems worldwide are consistent.