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This paper aims to provide a reliable statistical model for time-series prices of short-stay accommodation and overnight stays in a eurozone country.

Exploiting the unit root feature, the cointegrated vector autoregressive model solves the problem of misspecification. Subsequently, variables are modelled for a long-run equilibrium with included deterministic variables.

The empirical results confirmed that overnight stays for foreign tourists were positively associated with the prices of short-stay accommodation.

The major limitation lies in the data vector and its time horizon; its extension could provide a more specific view.

Findings can assist practitioners and hotel executives by providing the information and rationale for adopting seasonal volatility pricing. Structural breaks in price time-series have practical implications for setting seasonal-pricing schemes. Tourists could benefit either from greater price stability or from differentiated seasonal prices, which are important in the promotion of the price attractiveness of the tourist destination.

The originality of the paper lies in the applied unit root econometrics for tourism price time-series modelling and the prediction of short-stay accommodation prices.

The purpose of this paper is to map the service quality (SQ) of Airbnb, to provide additional insight for such top player of short-stay accommodation in the sharing economy context.

A mixed-method approach is used in two phases. In the qualitative phase, 112,138 online review comments of Airbnb guests were analyzed to generate the service attributes. In the quantitative phase, an online survey (n = 814) was conducted to calculate the performance and importance values of extracted attributes to plot them in an Importance-Performance Analysis (IPA) matrix.

A holistic image of the Airbnb extracted service attributes was presented through the IPA plot. Four types of SQ strategies were proposed, considering the actions priority. “Price reasonability” was the most important service attribute of Airbnb for guests, whereas “Check-in flexibility” was the best performed one.

The results shed light on the most relevant SQ attributes of Airbnb and proposed suitable strategies that can prioritize relevant stakeholders’ actions and decisions. The study significantly contributes to all decision makers involved in the short-stay accommodation sharing industry to further understand and develop SQ.

This research, using a comprehensive hybrid method, opens a lens to see more clearly the positioning of different attributes of Airbnb service from importance and performance viewpoints. As a contribution, the SQ of Airbnb was mapped by conducting an IPA for the first time in the literature.

The swift and wide‐ranging changes that present‐day society is undergoing are leading to an increasing personalization in consumer behaviour patterns. These are increasingly less well explained by socio‐demographic and economic criteria. This effect seems to be particularly well reflected in tourism. As one of the chief characteristics of this market is its heterogeneity, there is a need to include other variables, such as lifestyle, in order to segment it more adequately. This would permit a greater depth of knowledge of the variables influencing tourist behaviours, rendering them accessible to businesses, which could thus better satisfy tourists’ needs and wants by matching the services they offer more efficiently to them. Defines the construct “lifestyle” based on the activities, interests and opinions approach. Offers in addition certain innovations of scholarly interest, but also of practical use for business. Although this variable is not a brand‐new concept, it is still being actively researched.

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.

Although networked hospitality businesses as Airbnb are a recent phenomenon, a rapid growth has made them a serious competitor for the hospitality industry with important consequences for tourism and for tourist destinations. The purpose of this paper is to analyse the nature of the phenomenon, its potential further development in the next five years and the impact this developments will have on tourism, on hotels and on city destinations.

A literature study, combined with scenario workshops and a Delphi panel, were used to map current trends and uncertainties. With this input, future scenarios were elaborated using the Global Business Network (“scenario cross”) method.

Network platforms as Airbnb are often classified under something called the “Sharing Economy”, a denomination that obscures their true nature. Airbnb is a challenging innovation to which traditional hospitality will have to respond. Its impact has at the same time led to a call for regulatory policies. The definition of these policies and the evolution of tourism are variables that determine future scenarios. Attempts to ban the phenomenon mean a disincentive to innovation and protect oligopolistic markets; more receptive policies may have the desired results if tourism grows moderately but in booming destinations they may lead to a harmful commercialization.

Until now, Airbnb has been described in conceptual studies about the so-called “Sharing economy”, or more recently in empirical studies about isolated effects of holiday rentals. This paper contextualizes the evolution of networked hospitality and seeks to synthesize the sum of its impacts, thus enabling businesses and local governments to define positions and strategies.

The understanding of the factors that influence the selection of accommodation by guests is an important issue for international accommodation providers. The purpose of this research is to gain a greater understanding not only of the factors that influence the selection of motel accommodation by guests, but also of when and under which situations these factors become trigger points for decision making, focusing in particular on the influence that the length of stay has on the trigger points that impacted the selection process.

To undertake this research, five focus groups were conducted, involving participants who had previous experience in staying in motel accommodation either for business, on vacation or a combination of the two. Participants were selected and invited from a large variety of occupations and backgrounds.

Three levels of trigger points were identified for different lengths of stay. For overnight stays requirements were “minimalist”, convenience being the prime trigger point, and visitors felt they could tolerate most situations. For stays of two‐four nights there were certain requirements, “essentials”, that provided the necessary requirements for sleeping, eating and relaxation, while for stays longer than four nights, additional requirements that enhanced the stay, “enhancers”, were sought, raising the provision of the “essentials” to a higher level of sophistication and comfort.

This research, although conducted in New Zealand and in a specific part of a market, illustrates how complex the process of accommodation selection is by guests and in particular how the trigger points for selection change with the length of stay. It indicates how the physical facilities provided need to be tailored to the market in relation to the length of the visitor's stay.

This paper aims to investigate the roles of different types of customer value in influencing in customer evaluations of Airbnb. In particular, this study empirically tests the roles of four value dimensions in shaping existing Airbnb users’ attitudes and future behavioral intentions along with the effects of tripographic characteristics on users’ post-purchase evaluative judgments.

This study adopted a multi-study approach to test the hypotheses. In Study 1, theoretical relationships between constructs were proposed and empirically analyzed; and in Study 2, a different sample was used to validate the hypothesized model and enhance the external validity of the findings. After completing both studies, the two samples were combined to test for the moderating effects of several key tripographic factors among Airbnb users.

This study found that price value, emotional value, quality value and social value were critical factors exerting differential effects on customers’ evaluations of Airbnb. Further analysis of group differences revealed that Airbnb customers’ value perceptions differed significantly depending on the length of stay, group size and number of previous trips. The number of previous trips also had a significant moderating effect on the relationship between social value and attitudes.

The findings of this study contribute to the literature on Airbnb by presenting a comprehensive assessment of the differential effects of value components in evaluating Airbnb experiences with the consideration of tripographic characteristics. While supporting the importance of emotional, social, quality and price value to Airbnb guests, the results also show that Airbnb seems to appeal particularly to visitors who stay longer, travel with large groups and have used the platform several times in the past.

The findings of this study provide important insight into which customer values contribute to users’ attitudes and consequent favorable behaviors. More importantly, this study emphasized the importance of understanding the moderating effects of tripographic characteristics in the relationships between customer values and existing users’ evaluative judgment of Airbnb experiences.

This paper aims to empirically analyze tourists' length of stay in Istanbul, an important cultural destination. The objective of the study is twofold: (1) uncovering the qualitative difference between one-night visitors and longer stay visitors and (2) for those visitors staying longer at the tourism destination, investigating the key determinants of length of stay.

This research was carried out using a self-administered questionnaire distributed to international tourists who were about to leave the destination. To perform the analysis, we applied a two-step approach: first, we opted for classical binary logit to investigate the tourists' group membership (one-night vs longer stays); second, we applied a zero-truncated Poisson model for uncovering the drivers of length of stay for longer stay visitors.

The results confirmed the structural difference between the two visitor subgroups. Moreover, we found a positive impact of cultural attributes on tourists' length of stay.

The findings provide useful information for destination managers and planners, highlighting the importance of designing different tourism policies in light of tourists' heterogeneity. Moreover, the results confirmed the importance of the preservation and promotion of cultural attributes, given that these are a key factor in determining the success of a destination.

The importance and originality of this study are that it explores the impact of cultural/heritage attributes of the destination on tourists' length of stay. Moreover, it sheds light on the qualitative difference between short- and long-stay visitors.

This study intends to decompose the tourist choice process into two stages (decision to take a holiday and tourist expenditure), and to propose and test various expectations on the dimensions which explain the above decisions.

In order to simultaneously model the two decisions, we use a system of equations based on the Heckit model.

The dimensions affecting the decision to go on holiday are income, household size, education, size of the city of origin and opinion of going on holiday. The determinant factors influencing the level of expenditure are distance between origin and destination, type of accommodation, income, household size, age, marital status and length of stay. An important finding of this analysis is the differentiated effect of a given dimension on each decision.

The lack of information on some explanatory dimensions. Joint modelling. The spending decision should be modelled jointly with the decision to go on holiday due to the dependency between them.

The promotion of destinations should be developed with special attention paid to some faraway markets of origin, due to the expected propensity for these tourists to spend longer periods at the destination. The specialisation of destinations in terms of accommodation type and length of stay. The design of holiday packages should be adapted to the needs of the tourists identified, as they represent the most profitable tourist profiles.

The particular findings, and the research and practical implications proposed show the relevance of the topic analysed. Also, these aspects are backed by a sample of 3,781 individuals, which assures the robustness of the results.

Co-existing health conditions and frequent hospital usage are pervasive in homeless populations. Without a home to be discharged to, appropriate discharge care and treatment compliance are difficult. The Medical Respite Centre (MRC) model has gained traction in the USA, but other international examples are scant. The purpose of this paper is to address this void, presenting findings from an evaluation of The Cottage, a small short-stay respite facility for people experiencing homelessness attached to an inner-city hospital in Melbourne, Australia.

This mixed methods study uses case studies, qualitative interview data and hospital administrative data for clients admitted to The Cottage in 2015. Hospital inpatient admissions and emergency department presentations were compared for the 12-month period pre- and post-The Cottage.

Clients had multiple health conditions, often compounded by social isolation and homelessness or precarious housing. Qualitative data and case studies illustrate how The Cottage couples medical care and support in a home-like environment. The average stay was 8.8 days. There was a 7 per cent reduction in the number of unplanned inpatient days in the 12-months post support.

The paper has some limitations including small sample size, data from one hospital only and lack of information on other services accessed by clients (e.g. housing support) limit attribution of causality.

MRCs provide a safe environment for individuals to recuperate at a much lower cost than inpatient admissions.

There is limited evidence on the MRC model of care outside of the USA, and the findings demonstrate the benefits of even shorter-term respite post-discharge for people who are homeless.