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This paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3) What should be the future research trends in Airbnb?

This paper uses the systematic literature review (SLR) with a well-defined protocol, research strategy and methods to answer the research questions.

The review revealed that while Airbnb plays a significant role as the platform provider, the stakeholders influencing the experiences are multifaceted. Hosts, guests, local communities and even regulatory bodies all contribute to shaping the overall Airbnb Experience ecosystem. Hosts, in particular, have a crucial role in curating and delivering unique experiences, which significantly impacts the quality and authenticity of the offerings. On the question of whether Airbnb offers an authentic travel experience, the review uncovered mixed findings. For examples, some studies emphasized the potential for Airbnb to provide authentic and local experiences, allowing travelers to engage with the community and cultural aspects of a destination. However, other studies raised concerns about the commodification and standardization of experiences, leading to a potential loss of authenticity.

This paper is different from previous SLR where previous research systematically reviewed; motivations to use and choose Airbnb, institutionalization of Airbnb, stakeholders of Airbnb. This paper addresses authentic experience as a factor that influences activity participation.

This paper explores how Airbnb hosts' experiences with and responses to the coronavirus disease 2019 (COVID-19) health crisis may differ according to their motivations to host and to the type and spatial layout of their Airbnb accommodation. Based on these insights, the paper reflects on the lessons that are learned for the future of short-term rentals.

This is a qualitative multi-method small-scale case study, which relies on in-depth interviews and a focus group discussion carried out with a group of hosts affiliated to the Airbnb Host Community in Aarhus, Denmark. Informed by an interpretivist approach, the study aims to make sense of people's subjective experiences with hosting on the Airbnb platform, and how they have continued and adapted their hospitality practices during the pandemic.

Participants' adaptive practices vary according to their motivations to host and the type of accommodation that they rent out. Although all hosts in this study now implement more intensive cleaning practices, hosts who stay with their guests onsite tend to take stricter preventative measures to avoid contamination and transmission of the virus in their social interactions with guests. On the contrary, hosts who rent out their entire properties and have minimal contact with their guests found themselves less affected by the pandemic's impacts and have had a continued demand for their properties.

The COVID-19 pandemic has unevenly affected Airbnb hosts. Hosts who share their homes with guests require different adaptations to their daily behaviour and cleaning practices at home than hosts who do not stay with their guests and rent out entire properties. However, unlike professional hosts who largely or solely rely on Airbnb for their income, occasional home-sharing hosts tend to be more flexible in coping with cancelled or fewer bookings.

This study provides novel insights into the uneven impact of the COVID-19 pandemic on participants in the platform economies of tourism. It contributes to existing literature on the impacts of the pandemic on Airbnb's operations by showing how hosts' adaptive practices are informed by their subjective living conditions and the type of accommodation they can offer their guests.

This paper aims to explore the components of a negative memorable Airbnb experience.

Two studies of North American and British nationals were conducted online using an open-ended survey questionnaire with photo-elicitation via Amazon Mechanical Turk (MTurk). The grounded theory was used to analyse the collected data.

The findings of the current study are destination-specific and generalisation is limited. In addition, this study gathered data using an open-ended survey questionnaire with visual images (photo-elicitation technique) in MTurk. Moreover, the study participants were mainly Westerners.

Airbnb could provide hosts with a service quality checklist to warrant quality assurance across listings. Hosts must be informed, guided and monitored so that service quality standards are fulfilled. In addition, hosts should be incentivised to write an honest and accurate description of their listing.

Airbnb can provide hosts with a service quality checklist to ensure standardisation and quality assurance across listings. Hosts must be informed, guided and monitored so that service quality standards are fulfilled. In addition, hosts might benefit from training or workshops on the role of hosting and service quality management.

This is one of the first studies to explore the components of a negative memorable experience in the context of Airbnb.

负面的难忘体验：北美及英国Airbnb住客视角分析

在本文中, 我们探讨负面难忘的Airbnb体验的组成部分。

两项研究针对北美和英国居民的展开, 并使用亚马逊土耳其机器人（Amazon Mechanical Turk）来通过匿名调查问卷的方式在线进行照片提取。 采用扎根理论对收集到的数据进行了分析。

这项研究确定了负面令人难忘的Airbnb体验的三个最常见的组成部分：肮脏和恶劣的房间条件；恶劣的, 欺骗性的和粗鲁的主人行为；以及糟糕的客户服务。调查结果支持研究表明Airbnb的服务质量是不可预测的。

目前研究的结果是基于特定目的地的, 并且其概括性是有限的。 此外, 这项研究收集数据使用匿名调查问卷的MTurk视觉图像（照片提取技术）。 此外, 研究参与者主要是西方人。

爱彼迎可以为业主提供服务质量清单, 以保证整个列表款项的质量。 房主必须得到通知、指导和监测, 以便满足服务质量标准。 此外, 应该鼓励房主写一个诚实和准确的房源描述。

此研究在探索在Airbnb的背景下负面难忘体验的组成部分中处于领先地位。

爱彼迎, 记忆, 负面的难忘体验, 服务质量, 共享经济

研究论文

Experiencias negativas memorables: Perspectivas de los huéspedes de Airbnb de Norteamérica y Gran Bretaña

En este documento, exploramos los componentes de una experiencia negativa y memorable de las aerobombas.

Se realizaron dos estudios de ciudadanos norteamericanos y británicos en línea utilizando un cuestionario de encuesta abierto con foto-elicitación a través de Amazon Mechanical Turk. Se utilizó la teoría fundamentada para analizar los datos recogidos.

Este estudio identificó los tres componentes más comunes de las experiencias memorables negativas de las Airbnb: condiciones sucias y pobres de la habitación; comportamiento malo, engañoso y grosero del anfitrión; y un pobre servicio al cliente. Los resultados apoyan los estudios que indican que la calidad del servicio de Airbnb es impredecible.

Los hallazgos del estudio actual son específicos para cada destino y la generalización es limitada. Además, este estudio recopiló datos mediante un cuestionario de encuesta abierto con imágenes visuales (técnica de fotoelicitación) en MTurk. Además, los participantes del estudio eran principalmente occidentales.

Airbnb podría proporcionar a los anfitriones una lista de control de calidad del servicio para garantizar la calidad de los listados. Los anfitriones deben ser informados, guiados y monitoreados para que se cumplan los estándares de calidad del servicio. Además, se debería incentivar a los anfitriones para que escriban una descripción honesta y precisa de su listado.

Este es uno de los primeros estudios que explora los componentes de una experiencia negativa y memorable en el contexto de Airbnb.

Calidad de servicio, Memoria, Airbnb, Economía de compartir, Experiencia negativa memorable

Trabajo de investigación

This paper aims to examine the types of user misbehaviours in the sharing economy (SE) context. SE offers a fruitful study setting due to the scope of potential misbehaviour and the expanded role of consumers.

The study drew on online archival data from the AirbnbHell.com website, where people share their stories about their Airbnb-related negative experiences. The authors reviewed 405 hosts’, guests’ and neighbours’ stories and coded the identified forms of misbehaviours into categories. The typology thus developed was validated in the context of the Uber Rides service.

User misbehaviours in the SE context can be distinguished based on the domain in which the user role is violated and the nature of violated norms. These two conceptual distinctions delineate a four-fold typology of user misbehaviours: illegal, unprofessional, unbefitting and uncivil behaviours.

The trustworthiness of the stories could not be assessed.

The presented typology can be used as a mapping tool that facilitates detection of the full scope of misbehaviours and as a managerial tool that provides ideas for effective management of misbehaviours that correspond to each category.

The paper presents the first empirically derived comprehensive typology of user misbehaviours in SE settings. This typology enables classification of a broad set of misbehaviours, including previously overlooked unprofessional behaviours carried out by peer-service providers. The study also puts forward a revised definition of consumer misbehaviours that encompasses the impact of misbehaviours on parties not directly involved in the SE-mediated exchange.

This study aims to bridge the gaps in the extant literature on memorable tourism experiences (MTEs) and Airbnb by exploring the sources of negative memorable Airbnb experiences among Finnish guests.

This study used a qualitative approach and used data collected through semi-structured interviews. The sampling criteria for selecting participants were that they must be Finnish nationals who had booked and stayed in an Airbnb accommodation within the past 36 months. The participants were selected using a criteria-based snowball sampling technique. A qualitative empirical study was conducted using self-structured interviews that were completed by 18 Finnish tourists who had stayed at an Airbnb property in the past three years.

Three main sources constitute the conceptual framework of a negative memorable Airbnb experience: unclean accommodations, unpleasant host behaviour and poor customer service.

Airbnb management should make efforts to reduce guests’ negative experiences. This goal can be achieved by developing service-quality-management policies and strategies that are standardised, clear and universally applicable to all hosts. In addition, Airbnb management should recruit qualified customer service personnel and equip them with service recovery skills through training and control mechanisms. Such training should focus on upgrading their ability to handle complaints.

This study responds to the need to examine negative incidents that are a part of MTEs and the sources of negative memories. The originality of this study includes the extension of the existing literature on MTEs and Airbnb, as a conceptual framework of negative memorable Airbnb experiences that comprises three main components: unclean rooms, unpleasant host behaviour and poor customer service has been proposed.

This qualitative study aims to explore the activities that guests perform while staying in Airbnbs, emotions associated with these experiences and the components of memorable Airbnb experiences.

An empirical study of a qualitative nature was conducted using a self-administered open-ended questionnaire among tourists who had stayed in an Airbnb in the past three years. Data were collected using two different sources for triangulation purposes, referred to as Studies 1 and 2.

Many respondents reported conducting similar activities while at home and while staying in an Airbnb, supporting Burch’s (1969) spill-over theory. Travellers mostly recalled mundane activities, such as cooking. The results suggest that the spill-over effect is more prevalent in the Airbnb context than in other accommodation types, as one often travels from one’s own home to another’s home. Respondents associated their Airbnb experience with the positive emotion of joy. Respondents mentioned numerous reasons for having felt joy during their Airbnb experiences, such as sharing the trip with travel companions and spending time with friends.

Airbnb should clearly define host’s tasks and responsibilities, hosts should treat guests in a friendly manner, which includes resolving any problems they face in relation to the rental property.

This paper proposes a new conceptual framework for a memorable Airbnb experience, which comprises several components: socialising and bonding with friends and family members, location, the host’s hospitality, a homely feeling, home amenities and negative experiences (the poor condition of the room and a dishonest host).

Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.

A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.

Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.

This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

This study aims to explain why online reviews in Airbnb are skewed toward positive ratings. The authors examine customer perceptions of the service quality of an Airbnb stay as a relevant antecedent of whether customers leave an online review of that Airbnb stay. To this end, the authors test the hypothesis that the relationship between service quality and leaving an online review is linear and positive.

To test the hypothesis, the authors rely on primary survey data from 177 Airbnb customers combined with secondary data coming from their personal online Airbnb accounts. The authors conducted a binary logistic regression analysis to test the hypothesis.

The results show that customers’ service quality perceptions are positively and linearly related to leaving an online review of an Airbnb stay. In other words, satisfied customers are more likely to leave a review after an Airbnb stay than those who are dissatisfied.

The study is original in two respects. First, it reconsiders the role of customer experiences in explaining online customer reviews. In doing so, it empirically shows that the conventional wisdom of a U-shaped relationship between customer experiences and online reviewing does not hold in the context of the sharing economy. Second, by relying on primary survey data, the authors reveal the risk of dissatisfied customers creating an underreporting bias in online reviews, which ultimately make online reviews of Airbnb skewed toward positive ratings.

The purpose of this paper is to describe how the growing presence of Airbnb rentals, resulting partly from tourists’ increasing desire for transformative travel experiences, is ironically much more transformative for the host communities than the tourists themselves.

This paper provides a conceptual analysis linking the motivations of Airbnb guests with the impacts of Airbnb on host communities. It uses an experience economy lens, and is based on a review of the academic literature and of media stories related to Airbnb.

Many tourists are increasingly seeking transformative travel experiences, and Airbnb commonly will be appealing to such tourists. However, the capacity of Airbnb lodging to independently foster personal transformation is questionable. On the other hand, there is little doubt that Airbnb and its guests are producing significant transformations in host communities.

This paper contributes toward understandings of Airbnb and its impacts on destinations around the world. It, for the first time, links Airbnb guests’ travel motivations with Airbnb’s community impacts, and in doing so demonstrates parallels with past critiques of alternative tourism. This paper is also one of the first to examine Airbnb from the perspective of the experience economy.

This study aims to provide a cutting-edge evaluation of the sharing economy's impact within the realm of tourism and hospitality. The primary objectives guiding this research are as follows: to uncover the prevalent discussions and debates within the tourism and hospitality sector concerning the implications and effects of the sharing economy on urban destinations; and to analyse how scholarly inquiries and empirical investigations have contributed to a comprehensive comprehension of the intricate theoretical foundations and practical intricacies inherent in the sharing economy. This exploration takes place within the extensive expanse of existing literature.

The study used the non-conventional method for data mining. An artificial intelligence (AI) tool called www.dimensions.ai was used to mine data between the year 2002 and 2021. After which the data was analysed, using Citespace software that assisted in building themes for answering the research questions.

The sharing economy has multifaceted implications for rural and urban destinations. For instance, the findings demonstrated that emotional solidarity fosters community bonds between tourists and residents, enhancing authenticity. While, management firms optimise short-term rentals, boosting revenue and occupancy rates despite capped at 20%. It further demonstrated that the sharing economy disrupts traditional accommodations, especially hotels, impacting rural and urban destinations differently based on location and regulatory flexibility. Technological advancements would shape the digital future, transforming the resource in sharing and connectivity in urban settings.

Management firms or agents significantly enhance property facilities, revenue and occupancy rates. Properties managed by professionals perform better in terms of revenue and occupancy; furthermore, traditional accommodations need innovative strategies to compete with sharing economy platforms. Policymakers must consider location-specific regulations to balance sharing economy impacts. Embracing technological advancements ensures urban destinations stay relevant and competitive.

Emotional solidarity fosters bonds between residents and tourists, contributing to a sense of community. Management firms contribute to local economies and stability. However, Airbnb's impact on traditional accommodations raises concerns about the effect on residents and communities.

The study incorporates classical sociology theory to understand emotional solidarity and extends the concept of moral economy to guide economic behaviour in the sharing economy. The analysis also underscores the influence of technological trends such as mobile technology, Internet of Things, AI and blockchain on sharing practices in reshaping existing theoretical frameworks in the sharing atmosphere. Furthermore, the co-creation of value theory highlights collaborative interactions between hosts and guests, shaping the sharing economy experience. Consumer segmentation and choice theories shed light on sharing economy dynamics. Institutional and location-based theories provide insights into regulatory and location-specific impacts.

This research contributes by comprehensively exploring the multifaceted implications of the sharing economy on a tourist destination. It delves into emotional solidarity, management firm roles and location-specific impacts, enriching the understanding of the sharing economy's effects. The application of co-creation of value theory and examination of platform technologies offer fresh perspectives on value creation and user engagement. The study's focus on practical dimensions guides stakeholders in optimising the benefits and addressing challenges posed by the sharing economy in urban contexts. The exploration of moral economy and its relevance to the sharing economy provides a novel perspective, while the examination of technological influences on sharing practices contributes to understanding the digital future of the sharing economy.