Submitted by Sara Ribeiro (sara.ribeiro@ucb.br) on 2018-06-18T18:32:50Z No. of bitstreams: 1 JulianaLucenadoNascimentoDissertacao2018.pdf: 1777586 bytes, checksum: e530293eedf2c74e9f8e10c8bb3803b4 (MD5) / Approved for entry into archive by Sara Ribeiro (sara.ribeiro@ucb.br) on 2018-06-18T18:37:29Z (GMT) No. of bitstreams: 1 JulianaLucenadoNascimentoDissertacao2018.pdf: 1777586 bytes, checksum: e530293eedf2c74e9f8e10c8bb3803b4 (MD5) / Made available in DSpace on 2018-06-18T18:37:29Z (GMT). No. of bitstreams: 1 JulianaLucenadoNascimentoDissertacao2018.pdf: 1777586 bytes, checksum: e530293eedf2c74e9f8e10c8bb3803b4 (MD5) Previous issue date: 2018-02-26 / The purpose of this study is to bring information about Airbnb, more precisely, about its effects on the hotel and real estate markets in New York City. Using panel data and simultaneous equations models, the study showed a series of relationships between the platform and the hotel and real estate markets and also between the platform and socioeconomic variables. The main results found in the study show that there is a positive association between supply and demand for Airbnb and hotel offers. More precisely, neighborhoods with a 1% higher offer of hotels are associated with an offer and demand of 0,104% and 0,155% deviation standard, respectively. In the real estate analysis, the results suggest that districts with 1% higher Airbnb offerings are associated with long-term rents 0,04% higher and neighborhoods where the average price of the platform is 1% higher have a long-term rental price level 0,5% higher. In addition, neighborhoods where the average platform price is 1% higher are associated with a 1,038% lower long-term rental property offer. / O propósito desse trabalho é trazer informações a respeito do Airbnb, mais precisamente, sobre seus efeitos nos mercados hoteleiro e imobiliário na cidade de Nova York. Utilizando dados em painel e modelos de equações simultâneas, o trabalho mostrou uma série de relações entre a plataforma e os mercados hoteleiro e imobiliário e também entre a plataforma e variáveis socioeconômicas. Os principais resultados encontrados no trabalho mostram que há uma associação positiva entre a oferta e a demanda por Airbnb e oferta de hotéis. Mais precisamente, bairros com uma oferta 1% superior de hotéis estão associados a uma oferta e demanda 0,104% e 0,155% desvio-padrão maiores, respectivamente. Na análise imobiliária, os resultados sugerem que bairros com oferta 1% superior de Airbnb estão associados a aluguéis de longo prazo 0,04% superiores e bairros onde o preço médio da plataforma é 1% superior apresentam nível de preços de aluguel de longo prazo 0,5% superiores. Além disso, bairros onde o preço médio da plataforma é 1% superior estão associados a uma oferta de imóveis de aluguel de longo prazo 1,038% menor.

The main purpose of this degree project is to reveal the Airbnb customer’s preferences and quantify the impact of non-market factors on the market price of tourist accommodation in Berlin, Germany. The data retrieved from Airbnb listings, publicly available on Inside Airbnb (2017), was supplemented on indicator of sharing economy accommodation using machine learning method in order to distinguish between amateur and business-running professional hosts. The main aim is to examine the consumers’ preferences and quantify the marginal effect of "real sharing economy" accommodation and other key variables on market price. This is accomplished by model approach using hedonic pricing method, which is used to estimate the economic value of particular attribute. Surprisingly, our data indicates the negative impact of sharing economy indicator on price. The set of motivations of consumers, which determine their valuation of Airbnb listings, was identified. The trade-off between encompass and parsimony of the set was desired in order to build an effective model. Calculation of proportion of explained variance showed that the price is affected mainly by number of accommodated persons, degree of privacy, number of bedrooms, cancellation policy, distance from the city centre and sharing economy indicator in decreasing order.

Submitted by Edson Wu (edson_wu1991@hotmail.com) on 2016-05-09T21:45:41Z No. of bitstreams: 1 Dissertation - V20160422.pdf: 3700609 bytes, checksum: fd4bc7b83bbddb6dc18e2b24154d988f (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2016-05-19T19:50:27Z (GMT) No. of bitstreams: 1 Dissertation - V20160422.pdf: 3700609 bytes, checksum: fd4bc7b83bbddb6dc18e2b24154d988f (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-06-06T13:41:31Z (GMT) No. of bitstreams: 1 Dissertation - V20160422.pdf: 3700609 bytes, checksum: fd4bc7b83bbddb6dc18e2b24154d988f (MD5) / Made available in DSpace on 2016-06-06T13:43:11Z (GMT). No. of bitstreams: 1 Dissertation - V20160422.pdf: 3700609 bytes, checksum: fd4bc7b83bbddb6dc18e2b24154d988f (MD5) Previous issue date: 2016-03-30 / Peer-to-peer markets are highly uncertain environments due to the constant presence of shocks. As a consequence, sellers have to constantly adjust to these shocks. Dynamic Pricing is hard, especially for non-professional sellers. We study it in an accommodation rental marketplace, Airbnb. With scraped data from its website, we: 1) describe pricing patterns consistent with learning; 2) estimate a demand model and use it to simulate a dynamic pricing model. We simulate it under three scenarios: a) with learning; b) without learning; c) with full information. We have found that information is an important feature concerning rental markets. Furthermore, we have found that learning is important for hosts to improve their profits.

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<p dir="ltr">In the dynamic landscape of digital platforms, which includes various e-commerce and online review platforms, reputation systems play a fascinating role in shaping consumer behavior and influencing market outcomes. Seller-level reputation badges and individual recognition interventions, such as status badges and exemplar reviews, serve as important tools for enhancing trust and guiding customer decisions. Despite the prevalent use of customer reviews and ratings, the additional value provided by these reputation mechanisms warrants comprehensive investigation. This dissertation delves into the multifaceted impacts of seller-level reputation badges and exemplar reviews on consumer behavior and platform performance through two distinct essays.</p><p dir="ltr">In the first essay, we utilize a distinctive panel dataset from Airbnb to estimate the comprehensive effects of the seller reputation badge on both individual sellers and the overall platform. This study diverges from existing research that predominantly examines the influence of product-level reputation badges on individual sellers. By employing a difference-in-differences methodology and an exogenously determined schedule of updating the Superhost badge status, we find a substantial positive impact of the Superhost badge system on the bookings for Airbnb sellers and the platform. Additionally, we employ counterfactual estimators to uncover evidence of temporal dynamics in the badge system's positive effects. Our findings from counterfactual estimators indicate that the influence of the Superhost badge intensifies considerably within the initial weeks following its implementation, after which it reaches a state of equilibrium. Moreover, our analysis suggests that the Superhost badge exerts a more significant positive effect on the bookings of properties managed by hosts with multiple listings than those with a single property. These observations underscore the significant value of instituting a seller reputation badge system, even for online platforms with customer review mechanisms.</p><p dir="ltr">In a related analysis, the second essay investigates the strategies employed by online review platforms, which often involve targeted interventions such as status badges and exemplar reviews, to enhance user contribution to the platform's review system. However, a minority of individuals receive these interventions, and limited research exists on how reviews written by such intervention recipients result in second-order effects on nonrecipients' contributions. In this study, we leverage a quasi-experimental framework on a leading Asian review platform to evaluate the impact of exemplar reviews on users' review-writing behavior. We utilize a combination of econometric methods and natural language processing techniques to show an increase in the quantity and quality of user contributions following exposure to exemplar reviews. We also observe that users adapt their writing styles in response to exemplar reviews. Importantly, the effect of an exemplar review is moderated by the user's review-writing experience. Specifically, our findings reveal that less experienced reviewers, as opposed to their more seasoned counterparts, tend to increase their review volume and length upon reading exemplar reviews. However, they need more progress regarding review readability and perceived helpfulness. Further investigation indicates that reviews by users exposed to exemplar content gradually exhibit increasing homogeneity over time in terms of length, sentiment, readability, and topic diversity, suggesting a self-herding behavior that has not been previously documented in the literature on user-generated content. These insights provide valuable practical implications for platform managers on effectively utilizing reward programs to enhance the sustainability of their review platforms.</p>

The thesis focuses on professional and didactical points of view on digitalization in high school social science education. The aim of the thesis is to create a series of lessons for high schools (grammar schools) based on research on digitalization, which is supposed to aid students in better orientation at the labour market. At the same time, the didactical part is designed to be used and adapted by teachers interested in the topic. The theoretical part presents the professional background of the prepared lessons including key words, corresponding arguments and the general work basis of the author. Professional topics are transformed into a form didactically appropriate at the chosen level of secondary education (grammar schools). The practical part consists of a series of lessons focusing on changes in the labour market related to digitalization and technology development. Individual lessons are dedicated to online sharing economy platforms such as Uber and Airbnb, which change the concept of work in today's society and determine new working conditions of employees. The professional background of the prepared series of lessons defines the key terms and points to the historical context of work development in individual chapters; furthermore, it focuses on the following topics: the meaning of work...

La presente investigación tiene como finalidad evidenciar los cambios originados por la incursión de Airbnb en los servicios de la industria de alojamiento. La metodología usada fue la revisión bibliográfica de libros, tesis, artículos científicos y publicaciones de fuentes académicas. Acerca del tema investigado, la información encontrada evidencia que los hoteles han reaccionado realizando segmentación y especialización en un tipo específico de turista y han añadido valor en los servicios a través de experiencias que buscan quedar grabadas en los recuerdos de los turistas. Respecto a Airbnb, las investigaciones encontradas evidencian que actualmente está creciendo de manera acelerada por el uso de la economía colaborativa, la cual se basa en compartir la creación, producción, distribución y consumo de bienes y servicios entre diferentes personas y empresas haciendo uso de los avances tecnológicos como medio para realizar transacciones. También, a la creciente tendencia por parte de los millennials que son la población que hace mayor uso de Airbnb y esto se relaciona al hecho de la valoración de precios accesible, conocer la cultura local y obtener una mayor información del lugar que se visita. En conclusión, actualmente los hoteles han implementado estrategias que buscan reducir los cambios generados por los nuevos modelos de negocio como Airbnb, usando la segmentación y especialización en un tipo de turista, realizando inversiones en modelos de economía híbrida, paquetes y promociones de servicios que incluyen el hospedaje, alquiler de habitaciones por horas, inversión en mayor tecnología y apertura de hoteles económicos. / The current investigation aims to show the changes caused by Airbnb's incursion into the services of the hospitality industry. The methodology used was the bibliographic review of books, theses, scientific articles and publications from academic sources. Regarding the investigated topic, the found information shows that hotels have reacted by segmentation and specialization in a specific type of tourist and have added value in services through experiences that seek to be recorded in the memories of tourists. Regarding Airbnb, the investigations found show that it is currently growing at an accelerated rate due to the use of the collaborative economy, which is based on sharing the creation, production, distribution and consumption of goods and services between different people and companies making use of the technological advances as a means to carry out transactions. Also, to the growing trend of millennials who are the population that makes the most use of Airbnb and this is related to the fact of accessible price valuation, knowing the local culture and obtaining more information about the place that is visited. In conclusion, hotels have currently implemented strategies that seek to reduce the changes generated by new business models such as Airbnb, using segmentation and specialization in a type of tourist, making investments in hybrid economy models, packages and promotions of services that include lodging, renting rooms by the hour, investing in more technology and opening cheap hotels. / Trabajo de investigación

This master's thesis is about the success of sharing economy in the accommodation segment in Prague. The thesis is based on theories conceptualizing sharing economy as a result of social and value change, not only as technological one. Using online review data, the user experience of shared accommodation via Airbnb and traditional via Booking are compared. Analysis is conducted with focus on users' satisfied needs and fulfilled values. For processing the data, text mining techniques (topic modelling and sentiment analysis) were employed. The major result is that in Prague the models of sharing economy accommodation meets the growing need in society to fulfil post-material values in the market much better than the models of traditional accommodation (hotels, hostels, boarding houses). In their experiences, Airbnb users reflect social and emotional values more often, even though most sharing economy accommodations in Prague do not involve any physical sharing with the host. The thesis thus brings a unique perspective on the Airbnb phenomenon in the Czech context and contributes to the discussion of why the market share of the sharing economy in the accommodation segment in Prague has been growing, while traditional models stagnated.

La presente investigación tuvo como objetivo analizar el impacto que generó el ingreso de Airbnb al mercado limeño en el sector hotelero a través de las 3 métricas más importantes para la evaluación económica de dicho sector como son los ratios de Tarifa Promedio Diaria (ADR), Tasa de Ocupación (OCC), Rentabilidad por Habitación Disponible (RevPAR). Esta investigación mixta se realizó con fines informativos y con miras a brindar un sustento válido a la industria hotelera para que pueda revisar el comportamiento de Airbnb y viceversa. Para la realización de la investigación, el primer paso fue la búsqueda, clasificación y análisis de las principales teorías de diferentes autores y temas relacionadas con nuestro tema. Seguidamente se realizó un análisis cuantitativo con la recopilación de data de la industria hotelera, de la oferta de Airbnb y de las variables de control para potenciar el modelo. Se determinó que la mejor manera de comprobar nuestra hipótesis de si el mercado hotelero fue afectado por el ingreso de Airbnb en Lima, es realizando una lectura conjunta del resultado de como la oferta de Airbnb afecta individualmente a cada uno de los ratios antes mencionados. De esta manera, complementamos la lectura del análisis cuantitativo con entrevistas realizadas a dos personas encargadas de tomar decisiones en el sector hotelero. La conclusión del análisis mixto concluyó que la hipótesis general se rechaza, es decir, que Airbnb no tiene un efecto negativo significante en el mercado hotelero. / The objective of this research was to analyze the impact generated by the Airbnb’s entry into the Lima market in the hotel sector through the 3 most important metrics for the economic evaluation in the sector, such as the Average Daily Rate (ADR), Rate Occupancy (OCC), Profitability per Available Room (RevPAR). This mixed research was made for informational purposes and for providing valid support to the hotel industry so that it can review Airbnb's behavior and reverse. To carry out the research, the first step was the search, classification and analysis of the main theories of different authors and topics related to our topic. Then, we made the quantitative analysis with the researched data from the hotel industry, Airbnb's offer and control variables to enhance the model. It was determined that the best way to check our hypothesis of whether the hotel market was affected by the entry of Airbnb in Lima, making a joint reading of the result of how the Airbnb offer individually affects each of the aforementioned ratios. In this way, it complements the reading of the quantitative analysis with interviews with two decision-makers in the hotel sector. The conclusion of the mixed analysis concluded that the general hypothesis is rejected, that is, that Airbnb does not have a significant negative effect on the hotel market. / Tesis