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1
RĂBOJ, Daniela. "The Impact of Airbnb Platforms on the Romanian Real Estate Market." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Horticulture 76, no. 2 (2019): 245. http://dx.doi.org/10.15835/buasvmcn-hort:2019.0036.
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Airbnb or other similar platforms have evolved greatly in recent years and managed to change the perception of accommodation, in the same manner as Uber has changed the perception of public transport. Renting for tourism purposes, through Airbnb type platforms, has a direct impact on investors, state institutions, real estate markets and so on. The purpose of this paper is to analyze the effect of Airbnb type platforms on the Romanian real estate market and to describe the difficulties encountered in evaluating the properties that produce hotel rental income. These analyzes are intended in order to highlight an empirical perspective on this trend. The study consisted of a thorough online research, that took also into consideration legislation in force. In this paper I have presented a series of assessments of the impact on the market value of residential properties in Romania, which the properties listed for rent on Airbnb, seem to have.
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Tatsi, Foteini, Fotios Tatsis, Nikolaos Mylonidis, and Kostas Karamanis. "Assessing the impact of sharing economy on Greece’s hospitality sector: Perspectives from hoteliers and hosts." Journal of Infrastructure, Policy and Development 9, no. 1 (2025): 10383. https://doi.org/10.24294/jipd10383.
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The expansion of short-term rental platforms like Airbnb and HomeAway has reshaped the hospitality sector, introducing competitive pressures for traditional hotels and influencing local communities in Greece. This study examines perceptions among 343 hoteliers and 277 Airbnb hosts across Greece, focusing on economic, competitive, and social impacts of Airbnb-type accommodations. This cross-sectional study used structured questionnaires to assess views on Airbnb’s contribution to tourism, competition, and economic performance. Results reveal significant differences in perceptions: hoteliers expressed concerns about increased competition and regulatory inequalities, often viewing Airbnb as a mixed or negative influence on local tourism. In contrast, Airbnb hosts perceived their accommodations as beneficial for tourism growth and local economic support. Key areas of divergence included perceived competitive pressures, impact on overnight stays, and pricing strategies, with Airbnb hosts reporting more frequent economic benefits. These findings emphasize the need for a balanced regulatory approach to ensure fair competition and sustainable growth in Greece’s tourism sector. By comparing the perspectives of traditional and alternative accommodation providers, this study provides insights for policymakers seeking to address evolving challenges in the Greek hospitality landscape.
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Ni Tara, Kou Dan. "The impact of COVID-19 on sharing economy in Singapore: Role of customer’s perceived risk." BCP Business & Management 38 (March 2, 2023): 2204–23. http://dx.doi.org/10.54691/bcpbm.v38i.4081.
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The unprecedented COVID-19 pandemic has had a significant impact on the tourism industry. Previous research has studied the perspective of Airbnb hosts, but rarely mentioned the effect on consumer choice. As consumer choices may be driven by their risk perceptions, how COVID-19 may influence is not well-understood. This paper aims to investigate how COVID-19 may change consumer risk perception on different Airbnb listings, and such an impact on risk perception may affect their choices and overall business performance. The paper utilizes large-scale data about customer reviews and listing characteristics from Airbnb Singapore in the years 2019-2021, using NLP techniques to analyze, and extract the change in tourists’ risk perception before and after the outbreak of COVID-19 in Singapore. Comparing the topical content from customer reviews, we find that customers tend to perceive their experience more significantly on cleanliness-related issues since the outbreak of COVID-19. Furthermore, sentiment Analysis is performed to classify customer reviews into positive and negative, respectively, such that all listings are classified according to their valence in the perceived cleanliness. We show that the number of bookings and revenues of listings perceived as clean and not clean by the customers has diverged since the pandemic, i.e., the listings that are perceived clean would receive more bookings and thus accrue more revenues than those that are perceived as not clean. Overall, the research results would provide insight for Airbnb hosts and platforms to manage listings in the post-pandemic era, especially on how to manage and communicate cleanliness-related risks.
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Parantika, Asep, and RR Cindy Diana Nadia Lolita. "Psychological Effect of Customers to The Re-Purchase Decision of AirBNB Accommodation Facilities in Jakarta." Media Wisata 19, no. 2 (2021): 146–53. http://dx.doi.org/10.36276/mws.v19i2.116.
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Attitude repurchase decision influenced by other three components, which are stay experience. This article aims to discover the psychological effect of customers’ service on the re-purchase decision of AirBNB accommodation facilities in Jakarta. The research uses quantitative analysis. The data collection technique used is questionnaire circulation and literature reviews. The result shows that there are three components influencing respondents to reuse AirBNB services, which are Motivation, Perception, and, Users Review, and Price Sensitivity. Every component provides each influence in determining the repurchase decision of Air bnb. Service psychology holds a great impact on the AirBNB repurchase decision. Other components such as motivation, perception, and attitude play significant roles in the decision and greatly impacted the customers, as well as other factors such as stay experience, guest review and price sensitivity.
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Esparza Rodríguez, Saúl Alfonso, and Jaime Apolinar Martínez Arroyo. "Department location: Factor for Airbnb user’s valuation perception." Mercados y Negocios, no. 40 (July 5, 2019): 23–42. http://dx.doi.org/10.32870/myn.v0i40.7361.
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The objective is to analyze the impact of the location in the quality perception of customers. Data was obtained from the stars-based valuation of Airbnb website, considering a standardized option of accommodation just apartments of one room up to two guest maximum, with an average cost of USD 50 per night and located in four cities: New York and Miami in USA, and Mexico City and Cancun in Mexico, using a chi-square analysis to identify if there is a difference in quality perception considering if the destination place have beach or not. The results showed than departments located in New York had the most significant difference in valuation of quality of hosts.
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Kang, Minhyung. "Factors Affecting a Listing's Popularity on Airbnb." Jeju National University Tourism, Business, and Economic Research Institute 43, no. 2 (2023): 1–24. http://dx.doi.org/10.24907/jtir.2023.43.2.1.
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This study aims to understand the factors that influence the popularity of listings on Airbnb. For this purpose, data on the attributes of hosts (who are service providers), the attributes of listings (which are the core facilities of the Airbnb service), and the content of reviews (which represent the existing customers' perceptions of their experience) were obtained from Inside Airbnb, a non-for-profit data site related to Airbnb. To develop the research hypotheses, the effects of the five sub-dimensions of the SERVQUAL model, perceived value, and review sentiment on the popularity of a listing were examined. The popularity of a listing was measured by the number of new reviews, and since it is a count variable and has a skewed distribution, it was analyzed through Poisson regression. The results showed that all five dimensions of the service quality model have a positive impact on the popularity of Airbnb listings, and perceived value, which is important in the Airbnb context, also has a significant positive impact. However, the positive and negative sentiments in reviews did not yield the expected results. Our findings have academic contributions in the form of a new theoretical framework, a new dependent variable, and the application of a longitudinal research method. Additionally, they also have practical implications for the management of Airbnb listings.
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Garau-Vadell, Joan B., Desiderio Gutiérrez-Taño, and Ricardo Díaz-Armas. "Residents’ Support for P2P Accommodation in Mass Tourism Destinations." Journal of Travel Research 58, no. 4 (2018): 549–65. http://dx.doi.org/10.1177/0047287518767067.
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Recently, the sharing economy has made a disruptive incursion into the tourism industry. Companies like Airbnb or Wimdu have successfully developed platforms that grant access to accommodation in private homes. However, it seems that conflicts with locals have arisen in different destinations. This study provides an explanatory model to show how the perception of the impacts of the activity influences residents’ attitudes and support. The model was examined using a sample of 1,088 residents in Tenerife (Spain). Results confirm that resident support is directly and positively affected by their perception of the social and cultural impacts, and especially by the economic impacts. It has not been possible to prove the influence of their perception of environmental impacts. Evidence has been gained that perceptions strongly depend on whether locals benefit personally from the activity, and to a lesser extent on their attitude toward the sharing economy and on the state of the local economy.
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Li, Jiemei. "How Do Information Quality, E-service Quality, And System Quality Enhance Customer Satisfaction for Airbnb?" International Journal of Education and Humanities 13, no. 2 (2024): 29–45. http://dx.doi.org/10.54097/knn3fq40.
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This research study delves into the dynamic interplay between information quality, service quality, e-service quality, customer satisfaction, repurchase intention, and customer loyalty within the Airbnb platform, offering significant insights and practical implications for the sharing economy and online platforms. Utilizing a quantitative research approach, the study examines the complex relationships among these factors, drawing on empirical evidence to enhance our understanding of consumer behavior in the context of Airbnb. The study's findings reveal a significant positive correlation between information quality and customer satisfaction, highlighting the pivotal role of clear, accurate, and reliable information in influencing consumer perceptions and trust. Similarly, both service quality and e-service quality are found to have substantial positive relationships with customer satisfaction, underscoring the importance of high-quality service delivery in both physical and digital realms. Furthermore, the research identifies a strong positive association between customer loyalty and repurchase intention, suggesting that loyal customers are more likely to continue using Airbnb services in the future. These insights have profound implications for Airbnb and similar platforms in the sharing economy, suggesting that prioritizing information transparency, user-friendly interface design, quality customer service, and loyalty programs can significantly enhance user experiences, foster trust, and ensure steadfast consumer loyalty. The practical applications of this study advise platforms like Airbnb to focus on improving the accuracy and transparency of information, investing in intuitive and error-free user interfaces, offering efficient customer service, and implementing loyalty programs to cultivate long-term customer relationships and promote repeat business. The study also discusses the limitations encountered, including the constraints of a quantitative approach that may not fully capture the breadth of customer experiences and viewpoints, the sample size which might not accurately reflect the diversity of Airbnb's customer base, and the reliance on online data collection that may exclude certain segments of the population. These limitations suggest avenues for future research, emphasizing the need for incorporating qualitative methodologies, expanding the sample size for greater generalizability, and diversifying data collection methods to include a broader spectrum of user experiences. In conclusion, this research contributes to the existing body of knowledge by empirically demonstrating the crucial impact of information quality, service quality, and e-service quality on customer satisfaction, loyalty, and repurchase intentions in the Airbnb context. It offers valuable recommendations for enhancing service delivery and customer experience in the sharing economy, highlighting the strategic importance of building and maintaining customer loyalty for the sustained success of platforms like Airbnb.
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Wang, Zhao, and Aron Culotta. "When Do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception Using Individual Treatment Effect Estimation." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7233–40. http://dx.doi.org/10.1609/aaai.v33i01.33017233.
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Studies across many disciplines have shown that lexical choice can affect audience perception. For example, how users describe themselves in a social media profile can affect their perceived socio-economic status. However, we lack general methods for estimating the causal effect of lexical choice on the perception of a specific sentence. While randomized controlled trials may provide good estimates, they do not scale to the potentially millions of comparisons necessary to consider all lexical choices. Instead, in this paper, we first offer two classes of methods to estimate the effect on perception of changing one word to another in a given sentence. The first class of algorithms builds upon quasi-experimental designs to estimate individual treatment effects from observational data. The second class treats treatment effect estimation as a classification problem. We conduct experiments with three data sources (Yelp, Twitter, and Airbnb), finding that the algorithmic estimates align well with those produced by randomized-control trials. Additionally, we find that it is possible to transfer treatment effect classifiers across domains and still maintain high accuracy.
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Zamani, Efpraxia D., Jyoti Choudrie, George Katechos, and Yaping Yin. "Trust in the sharing economy: the AirBnB case." Industrial Management & Data Systems 119, no. 9 (2019): 1947–68. http://dx.doi.org/10.1108/imds-04-2019-0207.
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Purpose The purpose of this paper is to examine sharing economy online marketplaces with the aim of understanding how trust perceptions form and get communicated through sharing economy platforms. Design/methodology/approach The authors build on online user comments and reviews as aggregated by independent third-party websites, and apply a qualitative analysis. Findings The findings show that the quantity of information and communication are important drivers towards building trust perceptions, while an overall lack of interaction between users and the marketplace provider intensifies perceived risks. Originality/value The authors validated the importance of trust and the authors have illustrated that the critical conditions that hinder trust formation are information asymmetry as well as the lack of interaction. What is also an interesting implication is that the impact of both of these can be exacerbated when there is a perceived lack of support among users and between them and the marketplace operator.
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Lee, Sanghyun, Sounman Hong, Won-Yong Shin, and Bong Gyou Lee. "The Experiences of Layoff Survivors: Navigating Organizational Justice in Times of Crisis." Sustainability 15, no. 24 (2023): 16717. http://dx.doi.org/10.3390/su152416717.
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This study explores the impact of COVID-19 layoffs on surviving employees’ perceptions at Airbnb, a key player in the hospitality industry, during the global pandemic. The crisis brought organizational justice into sharp focus, raising questions about fairness, employee satisfaction, and trust in management. Utilizing an interpretivist approach, we conducted fifteen semi-structured interviews with Airbnb employees who survived the layoffs. Accompanied by a comprehensive literature review, our analysis delved into the challenges these employees encountered. The thematic analysis uncovered insights into organizational justice dimensions—distributive, procedural, interactive, and informational—and their role in shaping fairness perceptions and employee outcomes. Findings reveal that despite challenging circumstances, empathetic and proactive practices like regular check-ins and transparent communication significantly helped maintain fairness perceptions among survivors. This counters the common belief that layoffs invariably diminish justice perceptions. Our study demonstrates that negative impacts can be effectively mitigated through thoughtful organizational practices. In conclusion, the research underscores the importance of organizational justice during crisis-induced layoffs. It advocates for maintaining fairness and transparency to preserve employee trust and satisfaction, which are vital for organizational resilience and sustainability. This study enriches the literature on organizational justice and crisis management, providing valuable insights for businesses in similar situations.
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Hany B. Moussa, Mohamed, Mohamed Tawfeek Essawy,, Fabio Naselli, and Islam Momtaz Mohamed. "Perceptions of Using Private Dwellings at Gamaleyah as Airbnb Rent Listings in Old Historic Cairo." ATHENS JOURNAL OF TOURISM 8, no. 1 (2021): 55–74. http://dx.doi.org/10.30958/ajt.8-1-4.
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The social movement renowned as the "sharing economy" is becoming increasingly noticeable in online peer-to-peer platforms recently. One of these platforms is Airbnb; an accommodation marketplace that offers access to alternative accommodation. These platforms have a mega important socio-economic impact on tourist destinations. Old Cairo historic area encounters a lot of historical, heritage, and cultural features and folklores. Many owners of private homes in the area use them to accommodate guests and visitors to the area. Unfortunately, this is taking place under no organization or control by the Ministry of Tourism (MoT) since Egyptian accommodation regulations do not include a classification for such rent places. However, the area is well known among tourists and visitors and is included in downtown tours organized by tour operators and guides. This paper discusses the idea of using these homes as rent listings using the Airbnb platform among the executives of Historical Cairo Development Project (HCDP), Ministry of Tourism (MoT), and Egyptian Tourism Federation (ETF) as well as academics heading Heritage programs in Egyptian, Bahrain, and British Universities. This paper is devoted to revealing the differences in these perceptions among guests, professional practitioners, and academics, and officials "executives" of the government. Results indicate that all parties are in line with the idea and they recommended a change of regulations for that purpose. Keywords: Airbnb platform, old Cairo, hospitality regulations, architectural heritage, local community welfare, functioning model
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Alrawadieh, Zaid, Daniel Guttentag, Merve Aydogan Cifci, and Gurel Cetin. "Budget and midrange hotel managers’ perceptions of and responses to Airbnb." International Journal of Contemporary Hospitality Management 32, no. 2 (2020): 588–604. http://dx.doi.org/10.1108/ijchm-01-2019-0015.
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Purpose The purpose of this paper is to examine the degree to which budget and mid-range hoteliers perceive Airbnb as a threat, and the extent to which they are actively responding to the peer-to-peer accommodation business model. Design/methodology/approach The study draws on qualitative data collected through 19 semi-structured interviews with budget and midrange hotel managers in Istanbul, Turkey, covering how they view Airbnb and have responded to Airbnb’s rise. Findings The results suggest that the managers believed they were losing some business to Airbnb, yet they generally neither perceive Airbnb as a serious threat nor were they generally taking concrete strategic measures to respond to Airbnb. Regulatory lobbying against Airbnb and exploiting Airbnb as a new distribution platform were the most common responses, and cutting rate also was commonly seen as a potential competitive strategy. Originality/value The study responds to calls by several scholars for more research addressing the strategies adopted by traditional lodging facilities to protect their market share from Airbnb. This study does so with a specific focus on the budget and midrange hotel segments, which some studies suggest may be particularly vulnerable to Airbnb competition. Also, the limited research addressing Airbnb’s perceived impacts on traditional lodging has been conducted in mature economies, so the topic remains largely neglected in maturing economies like Turkey.
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Guizi, Alan, Zélia Breda, and Rui Costa. "How are overtourism and host–guest relationships portrayed by the Portuguese print media?" International Journal of Tourism Cities 6, no. 1 (2020): 215–32. http://dx.doi.org/10.1108/ijtc-06-2019-0081.
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Purpose The purpose of this paper is to understand the main perceived impacts of overtourism in Portugal and the reactions of tourism stakeholders in the main Portuguese cities, especially the host. Design/methodology/approach This study uses a qualitative approach, based on the analysis of news published in Portuguese newspapers between March 2018 and March 2019, applying Bardin’s (2011) content analysis and matching with the theory as proposed by Laville and Dionne (1999). Findings The study reveals that the main perceived impacts are the evictions and transformation of old residence into short-term rentals (e.g. Airbnb) and small hotels, besides other impacts such as garbage in the streets, gentrification, loss of security and others. Research limitations/implications The study considered the period of one year, being a limitation of analysis for contexts within that period, as well as the possible partiality of how the context of overtourism is dealt by newspapers. Practical implications This study seeks to understand the context of overtourism and its perception by the hosts and aims to present a basis of tourism planning for public and private sector stakeholders, in order to provide a better visit experience to the tourist, without losing the hosts’ quality of life. Originality/value Studies using newspapers as sources of data are rare. The newspapers are considered local witnesses; therefore, they bear important information for several purposes, not just for tourism but for other realities or contexts.
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Petruzzi, Marina A., Gabriela S. Marques, Manuel do Carmo, and Antonia Correia. "Airbnb and neighbourhoods: an exploratory study." International Journal of Tourism Cities 6, no. 1 (2020): 72–89. http://dx.doi.org/10.1108/ijtc-08-2019-0119.
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Purpose This study aims to identify residents’ perceptions of the impacts of Airbnb through an exploratory study that accounts for 94 residents in Lisbon, Portugal, in neighbourhoods with a high number of accommodations listed on the Airbnb platform. Design/methodology/approach A quantitative research was conducted. A questionnaire was designed and administered within the selected neighbourhoods. Factor analysis using the principal component methods is used to reduce the items evaluated. Findings The study reveals that residents have perceptions of both agreement and disagreement towards the impacts of the sharing economy in economic, environmental and sociocultural aspects. Positively perceived impacts refer to interactions with tourists, natural preservation and increase in business and job opportunities. Conversely, the growth of rent prices, the increase in noise issues, the change in the local culture and the threat of losing authenticity and traditions are the dimensions that may lead to negatively perceived impacts towards Airbnb. Research limitations/implications In spite of being the largest network for sharing accommodation, Airbnb is not the only one. Research on individual perceptions analyses the understandings of each person, which can be built and shaped by the context. In spite of the potential of the Likert scale, qualitative research should be added to enrich future studies. Practical implications This study identified several challenges for Airbnb and other sharing platforms, including residents’ concerns over noise, the threat of losing identity, changes in the local culture and rise in rent prices. Originality/value The study is dedicated to analyzing the host community residents and identifying their perceptions of impacts of the sharing economy. The use of residents’ perceptions provides useful insights that may be considered when planning, developing and implementing local policies.
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Misra, P., and W. Takeuchi. "ASSESSING POPULATION SENSITIVITY TO URBAN AIR POLLUTION USING GOOGLE TRENDS AND REMOTE SENSING DATASETS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W11 (February 14, 2020): 93–100. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w11-93-2020.
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Abstract. This study demonstrates relationship between remote sensing satellite retrieved fien aerosol concentration and web-based search volumes of air quality related keywords. People’s perception of urban air pollution can verify policy effectiveness and gauge acceptability of policies. As a serious health issue in Asian cities, population may express concern or uncertainty for air pollution risk by performing search on the web to seek answers. A ‘social sensing’ approach that monitors such search queries, may assess people’ perception about air pollution as a risk. We hypothesize that trend and volume of searches show impact of air pollution on general population. The objectives of this research are to identify those atmospheric conditions under which relative search volume (RSV) obtained from Google Trends shows correlation with measured fine aerosol concentration, and to compare search volume sensitivity to rise in aerosol concentration in seven Asian megacities. We considered weekly relative search volumes from Google Trends (GT) for a four year period from January, 2015 to December, 2018 representing diverse PM2.5 concentrations. Search volumes for keywords corresponding to perception of air quality (‘air pollution’) and health effects (‘cough’ and ‘asthma’) were considered. To represent PM2.5 we used fine aerosol indicator developed in an earlier research. The results suggest that tendency to search for ‘air pollution’ and ‘cough’ occurs when AirRGB R is in excess and temperature is below the baseline values. Consistent with this, in cities with high baseline concentrations, sensitivity to rise in AirRGB R is also comparatively lower. The result of this study can used as an indirect measure of awareness in the form of perception and sensitivity of population to air quality. Such an analysis could be useful for forecasting health risks specially in cities lacking dedicated services.
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Al Sadat Zyed, Zafirah, Mun Yee Yong, and Peter Aning Tedong. "Public users’ perception of Airbnb in Malaysia: should we regulate?" Property Management 38, no. 5 (2020): 627–42. http://dx.doi.org/10.1108/pm-09-2019-0050.
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PurposeDrawing from available literature and several case studies, this research aims to determine the criteria to be considered in shaping a framework regulating Airbnb. This paper will identify the regulatory frameworks of Airbnb from an international perspective and investigate the public perception on the criteria to be considered in shaping the framework regulating Airbnb. The criteria needed to be considered to regulate Airbnb are suggested accordingly.Design/methodology/approachA quantitative approach based on central tendency statistics was adopted in this research. Questionnaires were administered to the public to investigate the public's opinion on the criteria to be considered to regulate Airbnb. Finally, the criteria to be considered to regulate Airbnb will be determined. By using the mean analysis, this paper will tease out the ranking of the criteria that should be prioritized in shaping the Airbnb regulatory framework.FindingsThe results indicated that the criteria of “permits and safety” and “housing rules enforcement” outweigh the other “taxes” and “rule enforcement” criteria and shall be prioritized by the local authorities during the formation of Airbnb regulations in Malaysia.Originality/valueThis paper provides valuable pointers for policymakers before the expansion of Airbnb and before it becomes more difficult to regulate.
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Mwangi, Evah N., Nyabisi Mengo, and Louise Ngugi. "The Influence of Guest Perception in the Selection of Air Bed and Breakfast in Nakuru County." Journal of Science, Innovation and Creativity 3, no. 2 (2024): 1–8. http://dx.doi.org/10.58721/jsic.v3i2.724.
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This study was conducted to investigate the influence of guest perception in the selection of Airbnb in Nakuru County, Kenya. This study was anchored on expectancy disconfirmation theory. The study employed a cross-sectional descriptive research design and adopted purposive random sampling to gather data from a sample size and use of 104 respondents, from the questionnaires that were found valid. These respondents were the people who frequently patronize Airbnb. According to the study results, there is a linear relationship between guest perception and choice of Airbnb and it was examined using the regression analysis. The model indicated that guest perception could explain about 38.4 % of the variance in the choice of Airbnb. The correlation results showed that there is the existence of a statistically linear positive relationship between guest perception and choice of Airbnb (r=0.239, p=<0.05). This implies that a significant majority of the respondents were influenced by guest perception to select Airbnb, authentic experience, service quality, and guest satisfaction had a bigger influence on the development of guest perception. Guest perception relevancy in hospitality management evolves from the recognition that, customer sentiments are vital when it comes to expenditures on services rendered. Quality has been used as the critical key determinant that influences hospitality industry performance, but basic elements remained the same or as they were during the traditional times.
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Lee, Sanghyun, Sounman Hong, and Bong Gyou Lee. "Is There a Right Way to Lay Off Employees in Times of Crisis?: The Role of Organizational Justice in the Case of Airbnb." Sustainability 15, no. 5 (2023): 4690. http://dx.doi.org/10.3390/su15054690.
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The COVID-19 pandemic has negatively affected the tourism and services sector. Using the example of Airbnb’s recent layoff of 25% of its workforce, we focused on the role of organizational justice in mitigating the negative psychological impacts of layoffs. Based on a unique survey of Airbnb employees who survived the layoffs, as well as those who left, we employed an ordinary least squares regression to show that employees’ perceptions of organizational justice were positively related to their job satisfaction and trust in management, while being negatively related to their emotional exhaustion and cynicism. We discovered the crucial importance of interactional justice (i.e., interpersonal and informational justice). The respect, dignity, and politeness shown by management (i.e., interpersonal justice), as well as truthful and adequate communication about the procedure (i.e., informational justice) were pivotal to successfully conducting layoffs, especially during unprecedented economic uncertainty.
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Sandhu, Namrata, and Dilpreet Singh. "Gender Contamination in Indian Automobile Advertisements." Paradigm 21, no. 2 (2017): 139–55. http://dx.doi.org/10.1177/0971890717736212.
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Datsun Go surely and boldly disturbed the prevailing gender order in automobile advertisements by airing a series of ‘women only’ automobile advertisements on Indian television channels. This study uncovers the phenomenological response of men to this supposed gender contamination of a male-gendered product. The study captures the change in participants’ construction of gender identity meanings of the car and its purchase probability in response to exposure to differently gendered advertisements of the car. Results indicate the significant impact of gender signals in advertisements on the viewers’ perception of the gender identity meanings of the car. The study also provides evidence of male acceptance of gender bending in automobiles. Managerial implications and theoretical contributions are discussed.
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Ganapati, I. Dewa Gede, Tatan Sukwika, and Yohanes Sulistyadi. "Analisis Dampak Platform Peer-To-Peer Airbnb Terhadap Usaha Perhotelan Konvensional di Provinsi Bali." Jurnal Kepariwisataan: Destinasi, Hospitalitas dan Perjalanan 5, no. 1 (2021): 34–47. http://dx.doi.org/10.34013/jk.v5i1.340.
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The sharing economy platforms in the accommodation, such as Airbnb, gain more public attention. Several hoteliers in Indonesia have complained about the unequal playing of the field due to the alleged tax violations. Some studies on the impact of Airbnb have been discussed in various countries, but this subject has not been widely conducted in Indonesia. This study aims to determine the impact of Airbnb on the conventional hotel industry in Bali and how the conventional hotel’s response to compete with Airbnb. This research was conducted using qualitative research. Data was collected through interviews and secondary data collection. Interviews were conducted with representatives of hoteliers, Airbnb owners, and hospitality associations in Bali. Using forecasting analysis, this study finds that the presence of Airbnb in Bali has an impact on the occupancy rate of conventional hotels in Bali. However, there doesn't a significant impact from Airbnb regarding the hospitality revenue. Meanwhile, conventional hoteliers generally do not make particular efforts to compete with Airbnb. This research implies for the managerial side of hotels and public programs and policies, especially for the Government of Bali in the future to pay attention to consumer protection to provide equal action between conventional hotel and Airbnb owners.
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Lee, Carmen Kar Hang, Ying Kei Tse, Minhao Zhang, and Jie Ma. "Analysing online reviews to investigate customer behaviour in the sharing economy." Information Technology & People 33, no. 3 (2019): 945–61. http://dx.doi.org/10.1108/itp-10-2018-0475.
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Purpose The purpose of this paper is to investigate attributes that influence Airbnb customer experience by analysing online reviews from users staying in London. It presents a text mining approach to identify a set of broad themes from the textual reviews. It aims to highlight the customers’ changing perception of good quality of accommodations. Design/methodology/approach This paper analyses 169,666 reviews posted by Airbnb users who stayed in London from 2011 to 2015. Hierarchical clustering algorithms are used to group similar words into clusters based on their co-occurrence. Longitudinal analysis and seasonal analysis are conducted for a more coherent understanding of the Airbnb customer behaviour. Findings This paper provides empirical insights about how Airbnb users’ mindset of good quality of accommodations changes over a five-year timespan and in different seasons. While there are common attributes considered important throughout the years, exclusive attributes are discovered in particular years and seasons. Research limitations/implications This paper is confined to Airbnb experiences in London. Researchers are encouraged to apply the proposed methodology to investigate Airbnb experiences in other cities and detect any change in customer perception of quality stay. Practical implications This paper offers implications for the prioritisation of customer concerns to design and improve services offerings and for alignment of services with customer expectations in the sharing economy. Originality/value This paper fulfils an identified need to examine the change in customer expectation across the timespan and seasons in the case of Airbnb. It also contributes by illustrating how big data can be used to uncover key attributes that facilitate the engagement with the sharing economy.
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Tumbali, Mary Vida L. "IMPACT OF AIRBNB ON PHILIPPINE ACCOMMODATION SECTOR: A QUANTITATIVE APPROACH." Journal of Tourism, Hospitality and Environment Management 5, no. 21 (2020): 74–88. http://dx.doi.org/10.35631/jthem.521005.
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The study aimed at scrutinizing the impact of Airbnb on the Philippine hotel accommodation sector with regards to occupancy rates and the number of tourist arrivals. The more extensive point was to make a functional contribution to the current discussions and issues around the sharing accommodation, in particular Airbnb platform, from an ethnically diverse country standpoint. This study used a quantitative explanatory approach, and a secondary data sampling technique was adopted. Statistics from the Philippines were obtained from the DOT library while Airbnb data was purchased from AirDNA last September-November 2019. Secondary data collected were analyzed through SPSS. The study measured the relationship between Airbnb occupancy rates and tourist arrival. Moreover, to test whether Airbnb is directly competing with the lower category of hotel in terms of occupancy rates, the correlational examination was taken into account. Pearson R coefficient was utilized followed by a regression analysis to come up with a model. The findings inferred that it is Airbnb that has most influenced the activity of the tourism industry sector most especially under the accommodation sector and apparently set up to be a threat to the budget traditional providers. The result of the examination required for a business reaction for the traditional providers on the best way to team up with Airbnb to give better accommodation preferences for the increasing number of travelers in the country.
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Poon, Ka Yin, and Wei-Jue Huang. "Past experience, traveler personality and tripographics on intention to use Airbnb." International Journal of Contemporary Hospitality Management 29, no. 9 (2017): 2425–43. http://dx.doi.org/10.1108/ijchm-10-2016-0599.
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Purpose This study aims to identify the individual and trip characteristics that are associated with intention to use peer-to-peer accommodation, including past experience (users vs non-users), accommodation preferences, traveler personality and tripographic variables. Design/methodology/approach To compare Airbnb users and non-users, quantitative research was conducted to test for group differences. A questionnaire was designed and administered face-to-face in major tourist areas. Quota sampling was used to ensure comparable samples of Airbnb users and non-users. Findings While Airbnb users and non-users expressed few differences in their demographics and perceived importance of accommodation attributes, the two groups vary in their perception of Airbnb and evaluation of Airbnb compared to hotels, suggesting some positive and negative changes after experiencing Airbnb. Respondents who were more allocentric were more likely to use Airbnb. Hotels were preferred for traveling with family as well as shorter trips, while Airbnb was preferred for traveling with friends as well as longer trips. Practical implications This study identified several challenges for Airbnb and other sharing platforms, including consumers’ security concerns, potential decrease in the likelihood of repeat usage and low likelihood of using Airbnb when traveling with family. Originality/value While previous studies focused more on existing customers of peer-to-peer accommodation, this study compared users and non-users and identified key differences in their perceptions. The use of traveler personality and tripographic variables to examine intention to use Airbnb provides a unique perspective to consider Airbnb as an “allocentric destination” and the type of trips that are more compatible with the Airbnb experience.
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Fu, Zhehao, Hongying Zhu, and Fengming Pan. "Evaluating the Impact of Airbnb on Social Equality." Highlights in Business, Economics and Management 19 (November 2, 2023): 352–67. http://dx.doi.org/10.54097/hbem.v19i.11933.
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This research paper aims to investigate the development and impact of Airbnb on social, economic, and cultural dimensions, with a focus on its negative impacts on social equality and gentrification. The paper argues that Airbnb gentrifies local communities through the creation of short-term rent gaps, leading to rising housing prices, displacement of long-term users, and social injustice. Using data retrieved from the website of the UK government and Insideairbnb, this study examines the relationship between Airbnb and the well-being of London residents using linear regression. The results show a close correlation between Airbnb and rising housing prices, a fair correlation with decreasing greenery, transportation, and average income levels, and no significant correlation with average life expectancies. The correlation between these variables highlights the negative externalities associated with social justice that have arisen from Airbnb's proliferation. Considering that the growth of Airbnb in London has led to negative consequences for residents' well-being, policymakers should mitigate these impacts while monitoring Airbnb's growth to promote social justice and equitable outcomes for all residents.
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Liu, Xinran, Yuxuan She, and Meihan Liu. "The Impact of Spatial and Locational Characteristics on Airbnb Prices in London." Advances in Economics, Management and Political Sciences 69, no. 1 (2024): 238–46. http://dx.doi.org/10.54254/2754-1169/69/20231439.
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This research delves into the intricate relationship between spatial and locational attributes and Airbnb pricing in London. Utilizing data encompassing Airbnb listings in London collected over one year concluding on December 10, 2022, and employing advanced geospatial statistical techniques, including a geographically weighted regression (GWR) model equipped with ten select explanatory variables, this study reveals multifaceted spatial patterns underlying Airbnb pricing. The study underscores the paramount significance of dissecting the multifaceted determinants of Airbnb pricing, encompassing property characteristics, location-specific variables, host-related attributes, and customer feedback. Through empirical analyses, this research illuminates pronounced spatial heterogeneity within Airbnb pricing, with notable variations discerned across different room types. Interpretation of model coefficients reveals the multifaceted influence of factors, such as proximity to subway stations, volume of customer reviews, and specific scores, on pricing dynamics. Additionally, the GWR model exposes significant spatial variations in the impact of location and neighborhood-related variables on pricing, with particularly marked effects in the realms of entire homes and private rooms. This study aims to illustrate the intricate interplay between spatial and locational characteristics and Airbnb pricing dynamics, offering invaluable insights for researchers and industry practitioners.
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Kilian, Melanie A., Markus Kattenbeck, Matthias Ferstl, Bernd Ludwig, and Florian Alt. "Towards task-sensitive assistance in public spaces." Aslib Journal of Information Management 71, no. 3 (2019): 344–67. http://dx.doi.org/10.1108/ajim-07-2018-0179.
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Purpose Performing tasks in public spaces can be demanding due to task complexity. Systems that can keep track of the current task state may help their users to successfully fulfill a task. These systems, however, require major implementation effort. The purpose of this paper is to investigate if and how a mobile information assistant which has only basic task-tracking capabilities can support users by employing a least effort approach. This means, we are interested in whether such a system is able to have an impact on the way a workflow in public space is perceived. Design/methodology/approach The authors implement and test AIRBOT, a mobile chatbot application that can assist air passengers in successfully boarding a plane. The authors apply a three-tier approach and, first, conduct expert and passenger interviews to understand the workflow and the information needs occurring therein; second, the authors implement a mobile chatbot application providing minimum task-tracking capabilities to support travelers by providing boarding-relevant information in a proactive manner. Finally, the authors evaluate this application by means of an in situ study (n = 101 passengers) at a major European airport. Findings The authors provide evidence that basic task-tracking capabilities are sufficient to affect the users’ task perception. AIRBOT is able to decrease the perceived workload airport services impose on users. It has a negative impact on satisfaction with non-personalized information offered by the airport, though. Originality/value The study shows that the number of features is not the most important means to successfully provide assistance in public space workflows. The study can, moreover, serve as a blueprint to design task-based assistants for other contexts.
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Zouni, Georgia, Ioannis Katsanakis, Athanasios Athanasiadis, and Myrsini Sofia Nika. "The Impact of Antecedents on Airbnb Listing Prices: Evidence from Greece." Studia Periegetica 46, no. 2 (2024): 81–96. https://doi.org/10.58683/sp.1994.
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The study investigates varied effects that price antecedents have on Airbnb listings. Using data on 31705 listings from four major Greek regions (Athens, Thessaloniki, Crete, and the South Aegean), which appeared on Airbnb in December 2022 and were recorded by Inside Airbnb, the authors apply statistical tests and regression analysis to identify key pricing determinants. The results confirm the existence of evident differences in prices depending on external variables, such as the listing’s region, and internal listing qualities and host attributes. The findings offer valuable insights that individual hosts, professional listing administrators, and policymakers can use to adjust pricing strategies and regulations to changes taking place in the dynamic Airbnb market in Greece.
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Stollery, Aubrey, and Soo Hyun Jun. "The antecedents of perceived value in the Airbnb context." Asia Pacific Journal of Innovation and Entrepreneurship 11, no. 3 (2017): 391–404. http://dx.doi.org/10.1108/apjie-12-2017-040.
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Purpose This study aims to examine the antecedents of perceived value in the Airbnb context using the variables of perceived benefits (i.e. monetary saving, hedonic benefit, novelty and social interaction) and perceived risks (i.e. performance, physical, psychological and time). Design/methodology/approach The study population was Airbnb users in South Korea. This study applied a survey research method using a questionnaire. A link to the survey was sent via e-mail to panel members of a multinational research company. Findings The results revealed the positive influence of monetary saving, hedonic benefit and novelty on perceived value and the negative influence of psychological risk on perceived value. Research limitations/implications The results of this study, which identified the specific factors that influence Airbnb users’ perception of value, can assist Airbnb managers and Airbnb hosts in developing appropriate marketing plans and strategies to enhance the value of their offerings. Originality/value This study provided empirical support to the inclusion of affective factors and risk in determining perceived value. Moreover, while previous Airbnb studies focused on consumers from Western countries (e.g. USA and Canada), this study used a sample of South Korean consumers.
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Hur, Dongkeun, Seonjin Lee, and Hany Kim. "The Impact of Airbnb on Long-Term Rental Markets in San Francisco: A Geospatial Analysis Using Multiscale Geographically Weighted Regression." ISPRS International Journal of Geo-Information 13, no. 9 (2024): 298. http://dx.doi.org/10.3390/ijgi13090298.
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The rapid proliferation of peer-to-peer short-term vacation rentals has sparked a debate regarding their impact on housing markets. This study further investigates this issue by examining the effect of Airbnb on relative rent costs in San Francisco. The research addresses a critical gap in understanding whether Airbnb financially burdens local renters within different income groups. The authors also differentiated the effect of Airbnb accommodations with different levels of commercialization by categorizing Airbnb listings based on their level of commercialization. Using the multiscale geographically weighted regression technique, this study also considered spatial variations in the relationship between short- and long-term rental markets. The findings indicate that the density of Airbnb only affects the relative rent of renters with a yearly household income between USD 50,000 and USD 75,000. Furthermore, the density of Airbnb listings from more commercialized hosts that own between three and eleven showed a positive relationship with the relative rent cost. This study highlighted the variability in the impact of Airbnb on the local community by income group, listing characteristic, and geographic region. This finding underscores the need for differentiated regulation toward peer-to-peer accommodations, as the impact on rent affordability varies by host commercialization level and renter income group.
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Aslan, Ahmet Suvar, and Ebru Harman Aslan. "The Impact of Airbnb on Urban Transformation The Case of Beyoğlu, Istanbul." Kent Akademisi 18, no. 3 (2025): 1780–804. https://doi.org/10.35674/kent.1562319.
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Short-term rentals (STR) attract more capital into specific neighborhoods, usually those close to the center or those in arty and cultural areas via Airbnb. This research explores the impact of Airbnb on the gentrification processes in Beyoğlu, Istanbul's internationally best known and leading desirable urban area. This study aims to analyze the new layer that the STR adds to the gentrification processes in historic settlements that are already subject to gentrification. In the study, we used a mixed method. We accessed quantitative data on Airbnb in Beyoğlu, Istanbul through Inside Airbnb. In the qualitative part of the dataset, we used semi-structured in-depth interviews with relevant actors. Our findings show that STRs in Beyoğlu add a new layer to the existing gentrification process. Although this layer reduced its impact during the curfews caused by the Covid-19 pandemic, it became more effective with the normalization process. We provide evidence of an increase in change values in the study area due to Airbnb and the rapid airbnbification of dwellings in some parts of Beyoğlu, especially in the Galata district. These findings suggest that STR platforms threaten the housing stock in Beyoğlu, Istanbul. We contend that, in an uncontrolled or newly regulated system, Airbnb and comparable STR services essentially add a new layer to transformation processes in neighborhoods already experiencing gentrification.
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Thackway, William Thomas, Matthew Kok Ming Ng, Chyi-Lin Lee, Vivien Shi, and Christopher James Pettit. "Spatial Variability of the ‘Airbnb Effect’: A Spatially Explicit Analysis of Airbnb’s Impact on Housing Prices in Sydney." ISPRS International Journal of Geo-Information 11, no. 1 (2022): 65. http://dx.doi.org/10.3390/ijgi11010065.
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Over the last decade, the emergence and significant growth of home-sharing platforms, such as Airbnb, has coincided with rising housing unaffordability in many global cities. It is in this context that we look to empirically assess the impact of Airbnb on housing prices in Sydney—one of the least affordable cities in the world. Employing a hedonic property valuation model, our results indicate that Airbnb’s overall effect is positive. A 1% increase in Airbnb density is associated with approximately a 2% increase in property sales price. However, recognizing that Airbnb’s effect is geographically uneven and given the fragmented nature of Sydney’s housing market, we also employ a GWR to account for the spatial variation in Airbnb activity. The findings confirm that Airbnb’s influence on housing prices is varied across the city. Sydney’s northern beaches and parts of western Sydney experience a statistically significant value uplift attributable to Airbnb activity. However, traditional tourist locations focused around Sydney’s CBD and the eastern suburbs experience insignificant or negative property price impacts. The results highlight the need for policymakers to consider local Airbnb and housing market contexts when deciding the appropriate level and design of Airbnb regulation.
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Mhlanga, Oswald. "The innovation-employment nexus: an analysis of the impact of Airbnb on hotel employment." Journal of Hospitality and Tourism Technology 11, no. 3 (2020): 407–23. http://dx.doi.org/10.1108/jhtt-09-2019-0111.
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Purpose The purpose of this paper is to examine the impacts of Airbnb on hotel employment. Design/methodology/approach A triple-difference regression framework was used to compare changes in hotel employment in three cities in South Africa where Airbnb started operating relative to cities without this home-sharing platform. Data on hotel employment was drawn from the survey on hotel service conducted by Smith Travel Research whereas the data on Airbnb’s listings was drawn from the Airbnb’s homepage for the period between July 2015 and December 2018. The analysis was restricted to 792 hotels. Findings Although prior studies have showed that Airbnb has an adverse impact on hotel performances, the findings show that total hotel employment expanded after the entry of Airbnb, accompanied by a marked relative shift towards self-employment. Airbnb supply negatively affected permanent employment, which was compensated by increase in temporary employment and self-employment. While the paper finds no evidence of adverse employment impacts, the hourly earnings declined for hotel employees were compensated by increase in income among self-employed Airbnb hosts. Although these findings might be contradictory to the general conjecture, such evidence calls for a comprehensive investigation of Airbnb’s overall economic impact. Research limitations/implications First, the study was based on the impact of Airbnb on hotel employment in South Africa. Caution is therefore required when generalising the findings of this study in other geographic areas. Second, some variables that may affect employment have not been included in this study because of the unavailability of data. Practical implications The results show that the sharing economy plays an important role in solving the unemployment problem, particularly in South Africa, where there is a high rate of unemployment. More practical implications are further discussed. Originality/value To the best of author’s knowledge, this paper provides the first systematic evidence of the impact of Airbnb on labour market outcomes in the hotel industry in South Africa.
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Zhu, Haiting. "Airbnb’s Growth Changes Residential Property Prices in Adelaide." Journal of Sustainable Urbanization Planning and Progress 6, no. 1 (2022): 6–22. http://dx.doi.org/10.26789/jsupp.2022.01.002.
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In this research, the impact of Airbnb on residential property prices in Adelaide is assessed. Many previous European and American research have connected short-term rental, Airbnb and property market and made conclusion that short-term rentals (STR) are increasing housing prices and rents. However, there is no research about Airbnb and its effects on residential property prices in Adelaide. This research aims to fit this gap and makes Plan SA know more about Airbnb’s effects. This research used multiple linear regression model to examine the Airbnb activity’s effects on housing prices in Greater Adelaide during a specific time period before COVID-19. This regression model has been utilised in 3 Airbnb hotspot suburbs, Adelaide, North Adelaide and Glenelg and 3 adjected suburbs with few Airbnb listings, Thebarton, Prospect and Glengowrie in Greater Adelaide; different results in these 3 pairs suburbs has been employed to understand Airbnb’s different effects in housing prices. According to the results of regression model in different suburbs, Airbnb hotspot areas, have higher R squares and unpopular areas have smaller R squares. Considering coefficients in Airbnb hotspot areas, the number of Airbnb listings can increase housing prices and Airbnb daily can decrease housing prices. However, in unpopular Airbnb areas, R square and sample size are too small to make correlation between Airbnb and housing prices. The further study should enlarge the size of sample to verify whether there is a correlation between Airbnb and residential property prices in Airbnb unpopular areas.
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Mody, Makarand, and Lydia Hanks. "Consumption Authenticity in the Accommodations Industry: The Keys to Brand Love and Brand Loyalty for Hotels and Airbnb." Journal of Travel Research 59, no. 1 (2019): 173–89. http://dx.doi.org/10.1177/0047287519826233.
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Airbnb has gained popularity as an alternative to hotels, with the authenticity of the consumption experience being a critical differentiating factor. However, the hospitality and tourism literature has not fully explored how Airbnb and traditional hotel brands are facilitating authentic travel experiences and the impact of these experiences on brand love and brand loyalty. In this study, we explore three elements of consumption authenticity and examine their how they interact in the context of an accommodation brand. Second, we compare the components of consumption authenticity across hotels and Airbnb, and examine their relative impact on brand love for these two segments of the accommodations industry. We found that hotels and Airbnb draw upon different sources of authenticity to create brand-loving customers. Our results indicated that Airbnb leverages brand, existential, and intrapersonal authenticity in creating brand-loving and brand-loyal customers, while hotels utilize only brand authenticity. Thus, the keys to creating customers who love and are loyal to the brand differ between hotels and Airbnb. Implications for theory and practice are discussed, and areas of future research are identified.
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HERTE, Elena, and Alina BADULESCU. "RESEARCH ON THE DISTRIBUTION OF AIRBNB ACCOMMODATION IN MAJOR EUROPEAN DESTINATIONS." ANNALS OF THE UNIVERSITY OF ORADEA. ECONOMIC SCIENCES 32, no. 1 (2023): 154–64. http://dx.doi.org/10.47535/1991auoes32(1)011.
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The Airbnb platform, one of the most popular platforms of its kind, is present worldwide, with a variety of accommodations, depending on the type of accommodation it offers (single room, whole apartment, etc.). In this article, we set out to analyse the spatial allocation of accommodation and the density of Airbnb listings in comparison with hotel establishments in Europe. For the spatial analysis of Airbnb accommodations we used data from the Inside Airbnb website and QGIS, an application used for geographic information systems (GIS) that supports visualization, editing, and analysis of geospatial data. In this way, we created a geospatial database that helped us better understand the dynamics of each location. After analysing the data we concluded that a consequence of the concentration of Airbnb accommodation is that life in these areas has become more expensive and more crowded for locals. Airbnb accommodation has caused inconvenience not only to hotel owners but also to locals. In addition, Airbnb is having a strong impact on the rental market by increasing rental prices. Another trend that can be seen from the distribution of Airbnb accommodation is that in cities with a seafront location, accommodation is located close to beaches and most accommodation is of the entire home/apartment type. Differences in the frequency of use and prices of listings highlight the geographical inequality in the benefits and impact of Airbnb’s activity. The Airbnb offer is not a uniform segment of tourist accommodation and its effects on destinations are important and should therefore be analysed in relation to the territorial context.
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Zeng, Gengyuan, Ningning Huo, and Xinhe Zhang. "Research on Different Factors Affecting Airbnb Housing Prices." Advances in Economics, Management and Political Sciences 202, no. 1 (2025): 37–49. https://doi.org/10.54254/2754-1169/2024.25061.
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To study the different factors affecting Airbnb housing prices, this research uses the data from the Airbnb platform and evaluates key determinants influencing listing prices on the Airbnb website. The study employs exploratory data analysis (EDA) and linear regression analysis to analyze the impact of these variables on Airbnb housing prices. The research finding reveals that accommodations, bedrooms, and beds have a significant correlation with housing prices. Insights coming out of this research are able to provide valuable perspectives to Airbnb hosts and its housing rental business. It is suggested that focusing on these factors will enhance Airbnbs pricing strategies and its overall market performance.
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Wikanatha Sagita, Putu Agus, and I. Made Kusuma Negara. "PENGARUH HARGA DAN FAKTOR PSIKOLOGIS TERHADAP KEPUTUSAN PEMESANAN AKOMODASI MELALUI ONLINE TRAVEL AGENT." Jurnal IPTA 10, no. 1 (2022): 83. http://dx.doi.org/10.24843/ipta.2022.v10.i01.p09.
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This study aims to identify the effect of price and psychological factors on accommodation booking decisions through the Airbnb application. Data collection in this research was carried out by observation, interview, questionnaire and literature study techniques. The data analysis technique used is descriptive quantitative analysis and multiple linear regression analysis. The results of this study are expected to reveal whether tourists who book accommodation through Airbnb are merely motivated by the desire to get accommodation at a low price. Are psychological factors consisting of variables of motivation, perception, learning, and attitudes related to the desire of tourists to learn new things such as knowing the lives of local people also influence tourists in booking accommodation via Airbnb. The results of this study are independent variables consisting of price variables (X1), perception variables (X3), learning variables (X4), attitude variables (X5) significantly influence the dependent variable, namely the accommodation booking variable (Y). Whereas the motivation variable (X2) which is related to the trend indicator of the use of technology to book accommodations anywhere and anytime has no significant effect in booking accommodations through Airbnb's Online Travel Agent.
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Obrč, Polona, and Boštjan Kerbler. "The Impact of Airbnb on Long-Term Rental Housing: The Case of Ljubljana." Critical Housing Analysis 8, no. 1 (2021): 150–58. http://dx.doi.org/10.13060/23362839.2021.8.1.531.
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Airbnb has become a fixture in the development of global cities. It especially impacts cities’ residential characteristics. The company works with the concept of the sharing economy, the essence of which is the exchange of services or goods between individuals who set the rules of operation without generating profits, but together generate more revenue. It insists that it does not represent a form of direct competition with other urban accommodation services and that it merely seeks to expand the tourism market. Nonetheless, this article proceeds from the assumption that Airbnb is influencing and transforming the housing market of the cities it operates in. It focuses on Ljubljana, which until 2019 had a record number of international arrivals and overnight stays. The findings confirm that short-term Airbnb rentals have affected the long-term rental market in Ljubljana. They also show that a very large share of rentals through Airbnb take place in the grey economy. However, the analysis of cases from selected European cities showed that, in addition to the drawbacks described, Airbnb also has positive effects on the development of cities. It is therefore necessary to accept and adapt appropriately to this global phenomenon through specific measures, such as those proposed in the conclusion for Ljubljana.
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Önder, Irem, Christian Weismayer, and Ulrich Gunter. "Spatial price dependencies between the traditional accommodation sector and the sharing economy." Tourism Economics 25, no. 8 (2018): 1150–66. http://dx.doi.org/10.1177/1354816618805860.
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The emergence of peer-to-peer (P2P) accommodation (e.g. Airbnb) has steadily increased the pressure on the traditional accommodation sector. Although Airbnb listings are perceived as being more affordable than hotels, this has not yet been conclusively demonstrated. Therefore, the aim of this study is to investigate whether significant price dependencies exist between the Airbnb and traditional accommodation sectors and to analyze the underlying pricing strategies. For this purpose, the Estonian capital city of Tallinn is used as a case example. Airbnb data, prices and locations of hotels in Tallinn, as well as spatial information such as distance to points of interest (POIs), and so on, are used in hedonic price regression models. The results show that Airbnb pricing positively depends on characteristics of the listing and the number of POIs within an optimal 650 m radius, which is obtained from a simulation study. Also, prices of hotels and of other Airbnb listings within the same radius positively impact Airbnb listing prices. Finally, Airbnb accommodations are shown to indeed be the more affordable alternative.
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Zhang, Zhihua, and Rachel J. C. Chen. "Assessing Airbnb Logistics in Cities: Geographic Information System and Convenience Theory." Sustainability 11, no. 9 (2019): 2462. http://dx.doi.org/10.3390/su11092462.
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City managers and planners seek insights into Airbnb logistics in cities for the purposes of effective lodging management. This requires managers and planners to gain a holistic understanding of Airbnb geographic dynamics, which has drawn limited attention in the literature. To fill this gap, this paper explored Airbnb supply and logistics in three cities (New York City, Los Angeles, and Chicago) through the lenses of geographic clustering and location convenience. We explored the spatial allocations of Airbnb supply in cities and investigated Airbnb’s influencing factors at the census tract level, utilizing spatial regression models. The results showed that (1) the spatial distribution of Airbnb supply in all three cities has a clear center-peripheral pattern, indicating that Airbnb allocations predominate in the central area of the city; (2) the number of housing units and points of interest (POI) have an influential impact on Airbnb supply for three cities; (3) the proportion of youth population and employment has a positive effect on Airbnb supply in NYC and Chicago, but not in LA, while the distance to the city center negatively affects Airbnb supply in LA and Chicago, but not in NYC; (4) the income has a mixed effect on Airbnb supply in three cities, while the proportion of African Americans and education level has only a positive effect on Airbnb supply in NYC; and (5) rent is not associated with Airbnb supply for all three cities, which indicates that the Airbnb explosion may not contribute to rent increases in cities.
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Jiao, Junfeng, and Shunhua Bai. "Cities reshaped by Airbnb: A case study in New York City, Chicago, and Los Angeles." Environment and Planning A: Economy and Space 52, no. 1 (2019): 10–13. http://dx.doi.org/10.1177/0308518x19853275.
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In the last 10 years, Airbnb has rapidly grown from a simple, online bed and breakfast operation to a leading global hospitality service provider. Scholars have been using different spatial analysis tools to study its potential impacts on cities. To better understand Airbnb’s impact this featured graphic applied a cartogram processing tool to reshape census tracts based on Airbnb listing intensity in three major US cities (New York City, Chicago, and Los Angeles). Results showed that different cities have different patterns of Airbnb listings. Census tracts in New York City became completely unrecognizable after the analysis, which indicted a highly skewed Airbnb distribution in the city. Compared with New York City, we saw less and least deformation in Chicago and Los Angeles, respectively, where Airbnb was more evenly distributed. The results showed that Airbnb listings were very evenly distributed in the large US cities. Airbnb would impose completely different impacts on different neighborhoods based on their locations.
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Hübscher, Marcus, Juana Schulze, Felix zur Lage, and Johannes Ringel. "The impact of Airbnb on a non-touristic city. A Case study of short-term rentals in Santa Cruz de Tenerife (Spain)." Erdkunde 74, no. 3 (2020): 191–204. http://dx.doi.org/10.3112/erdkunde.2020.03.03.
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Short-term rentals such as Airbnb have become a persistent element of today’s urbanism around the globe. The impacts are manifold and differ depending on the context. In cities with a traditionally smaller accommodation market, the impacts might be particularly strong, as Airbnb contributes to ongoing touristification processes. Despite that, small and medium-sized cities have not been in the centre of research so far. This paper focuses on Santa Cruz de Tenerife as a medium-sized Spanish city. Although embedded in the touristic region of the Canary Islands, Santa Cruz is not a tourist city per se but still relies on touristification strategies. This paper aims to expand the knowledge of Airbnb’s spatial patterns in this type of city. The use of data collected from web scraping and geographic information systems (GIS) demonstrates that Airbnb has opened up new tourism markets outside of the centrally established tourist accommodations. It also shows that the price gap between Airbnb and the housing rental market is broadest in neighbourhoods that had not experienced tourism before Airbnb entered the market. In the centre the highest prices and the smallest units are identified, but two peripheral quarters stand out. Anaga Mountains, a natural and rural space, has the highest numbers of Airbnb listings per capita. Suroeste, a suburban quarter, shows the highest growth rates on the rental market, which implies a linkage between Airbnb and suburbanization processes.
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Bao, Helen X. H., and Saul Shah. "The Impact of Home Sharing on Residential Real Estate Markets." Journal of Risk and Financial Management 13, no. 8 (2020): 161. http://dx.doi.org/10.3390/jrfm13080161.
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This paper explores the effects of home-sharing platforms in general and Airbnb in particular on rental rates at a neighbourhood level. Using consumer-facing Airbnb data from ten neighbourhoods located within large metropolitan areas in the U.S. between 2013–2017, as well as rental data from the American online real estate database company, Zillow, this paper examines the relationship between Airbnb penetration and rental rates. The results indicate that the relationship is not as unanimous as once thought. Viewing the relationship at an aggregate level, an approach used by many researchers in the past, hides the complexities of the underlying effects. Instead, Airbnb’s impact on rental rates depends on a neighbourhood’s individual characteristics. This study also urges policy makers to create tailor-made solutions that help curb the negative impacts associated with the platform whilst still harnessing its economic benefits.
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Zhang, Zhihua, and Rachel J. C. Fu. "Accommodation Experience in the Sharing Economy: A Comparative Study of Airbnb Online Reviews." Sustainability 12, no. 24 (2020): 10500. http://dx.doi.org/10.3390/su122410500.
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Current research investigating the accommodation experience in the sharing economy in China is limited, especially from a cross-cultural perspective. To fill this gap, this study examined the accommodation experience of Airbnb guests using text-mining techniques and compared the accommodation experience perception between two culturally different groups: domestic Chinese and foreign English-speaking Airbnb guests. The results showed that the two groups shared eight common dimensions, including “Convenience/Location”, “Amenities”, “Feel at home”, “Check-in/out”, “Experience”, “Availability/Transportation”, “Host”, and “Style/Decoration”. However, there are differences in the relative importance of each dimension of accommodation experience between the domestic and foreign Airbnb guests. For example, the foreign guests more often mentioned homeliness, location/convenience, and availability/transportation, while the domestic guests showed greater interest in check-in procedures and style/decoration. Additionally, the two groups have several unique dimensions. The dimensions unique to foreign guests are “Recommendation” and “Booking flexibility”, while the dimensions unique to domestic guests are “Revisit” and “Cleanliness”. This study provides both theoretical and practical implications for peer-to-peer accommodation hosts and platforms. For example, Airbnb hosts can improve the satisfaction of Airbnb guests by improving several common extracted topics (e.g., amenities quality and host response) and the fact that foreign guests care more about homeliness, while domestic guests pay more attention to the check-in process and house design and decoration.
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Oskam, Jeroen A. "Eiffel Tower and Big Ben, or 'off the beaten track'? Centripetal demand in Airbnb." Hospitality & Society 10, no. 2 (2020): 127–55. http://dx.doi.org/10.1386/hosp_00017_1.
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Abstract In the light of the debate on the growth of visitor numbers to city destinations and the sociocultural footprint of urban tourists, the spatial distribution of urban vacation rentals is a key question: does 'sharing', as Airbnb has claimed, spread visitors to peripheral neighbourhoods and contribute to decreasing the congestion in traditional tourist hotspots? Or does it, on the contrary, worsen this congestion problem, with its consequences for the perception of tourism by residents, in traditional tourist centres? This article analyses the spatial concentration of Airbnb listings in 26 European cities in terms of a distance decay from a central point. Besides the concentration of the offer, it studies the decay of business performance according to the distance from the city centre. The study finds an exponential decay for the number of listings. There is a strong effect on financial performance and a more limited effect on rental performance. While several single city studies show that Airbnb, instead of spreading tourism to neighbourhoods, led to greater concentration, these findings show that these were not incidental excesses but a common development pattern for Airbnb. Implications are that the authenticity sought by Airbnb users is not the same as the search for an unspoilt neighbourhood life. Furthermore, it means that benevolent policies towards urban vacation rentals, aimed at spreading tourism, are based on a false assumption.
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Lee, Seunghwan, Min Jung Kim, and Dae-Young Kim. "The Effect of Airbnb Users’ Regret on Dissatisfaction and Negative Behavioral Intention." International Journal of Environmental Research and Public Health 20, no. 1 (2022): 2. http://dx.doi.org/10.3390/ijerph20010002.
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As the most successful platform for peer-based accommodation sharing, Airbnb has transformed the lodging industry into something much more affordable and accessible for travelers on a budget. Compared to a hotel stay, however, its variability of facility and service has created guests’ negative emotions such as regret and dissatisfaction. These emotions may cause stress, which negatively affect mental health. Therefore, we explore the factors that influence Airbnb guests’ regret, and investigate the relationship between their regret, dissatisfaction, and negative behavioral intention. Structural equation model is utilized on a total of 456 U.S. consumers to examine the relationship among Airbnb users’ responses. The findings indicate that price perception influences regret and dissatisfaction the most. The study also reveals that regret has a positive correlation with dissatisfaction, while does not have an influence on switching intention and negative word of mouth. Based on the result, theoretical and managerial implications are discussed.
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Li, J., and F. Biljecki. "THE IMPLEMENTATION OF BIG DATA ANALYSIS IN REGULATING ONLINE SHORT-TERM RENTAL BUSINESS: A CASE OF AIRBNB IN BEIJING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W9 (September 30, 2019): 79–86. http://dx.doi.org/10.5194/isprs-annals-iv-4-w9-79-2019.
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Abstract. With the fast expansion and controversial impacts of short-term rental platforms such as Airbnb, many cities have called for regulating this new business model. This research aims to establish an approach to understand the impact of Airbnb (and similar services) through big data analysis and provide insights potentially useful for its regulation. The paper reveals how Airbnb is influencing Beijing’s neighbourhood housing prices through machine learning and GIS. Machine learning models are developed to analyse the relationship between Airbnb activities in a neighbourhood and prevailing housing prices. The model of the best fit is then used to analyse the neighbourhood price sensitivity in view of increasing Airbnb activities. The results show that the sensitivity is variable: there are neighbourhoods that are likely to be more price sensitive to Airbnb activities, but also neighbourhoods that are likely to be price robust. Finally, the paper gives policy recommendations for regulating short-term rental businesses based on neighbourhood’s price sensitivity.
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Yang, Jiayi. "Impacts of COVID-19 on the Hospitality Industry: Case Study of Airbnbs Response and Market Exit." Advances in Economics, Management and Political Sciences 42, no. 1 (2023): 124–29. http://dx.doi.org/10.54254/2754-1169/42/20232093.
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This paper investigates the impact of the COVID-19 pandemic on the hospitality industry, with a specific focus on Airbnb as a case study. Through an in-depth analysis, this paper uncovers the disruptions and transformations experienced by the hospitality industry due to COVID-19. Examining the case of Airbnb sheds light on the complexities and vulnerabilities inherent in the sharing economy model. The study showcases the unique challenges Airbnb faces in the Chinese context and evaluates the effectiveness of the strategies employed to sustain operations. It provides valuable insights into Airbnbs decision-making processes and gives alternative solutions that could be helpful. By combining the findings from this case study, this paper offers practical assessments and recommendations for the future development of the hospitality industry. In conclusion, this paper provides a comprehensive examination of the impact of COVID-19 on the hospitality industry through the lens of Airbnb.
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Medina-Hernandez, Vivian Constanza, Estela Marine-Roig, and Berta Ferrer-Rosell. "Accommodation sharing: a look beyond Airbnb’s literature." International Journal of Culture, Tourism and Hospitality Research 14, no. 1 (2020): 21–33. http://dx.doi.org/10.1108/ijcthr-07-2019-0130.
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Purpose Airbnb is the peer-to-peer (P2P) accommodation platform that has attracted researchers’ attention during the past decade. The purpose of this paper attempts to illustrate the scarce research on P2P accommodation platforms other than Airbnb and to highlight the research gaps concerning these platforms. Design/methodology/approach This study starts by presenting a literature review on Airbnb based on several review papers about P2P accommodation sharing and conducts a quantitative comparative analysis between existing literature on Airbnb and other P2P accommodation platforms in Web of Science (WoS) using a keyword search. Findings Findings suggest that the literature regarding P2P accommodation platforms other than Airbnb is limited and that little is known about their possible impact on the collaborative tourism ecosystem. The analysis also suggests further research on P2P accommodation platforms to move on from an Airbnb-centric view and include other types of P2P accommodation platforms. Originality/value This paper compares the most common topics studied regarding Airbnb and other P2P accommodation platforms, highlighting the existence of other for-profit and non-profit accommodation platforms. It proposes new lines of research on different types of platforms such as the niche P2P accommodation platforms.