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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 purpose of this paper is to investigate the potential effects of the so-called sharing economy on growing city tourism as well as on urban property markets.

Official statistical data and a geo-information system (GIS) are used on a small scale in order to identify concentration processes among overnight visitors and the potential concomitant conflicts with other interest groups.

Currently, the effects of the sharing economy on housing markets and city tourism are barely measurable and are limited to a few central locations. However, a growing demand can be discerned in housing-like accommodation concepts which can be operated via booking platforms. As there is likely to be strong future growth in this area, continuous market observation (monitoring) is urgently advised.

Official statistics only allow an analysis of overnight guests staying with larger accommodation providers. Booking platforms for holiday homes and other temporary accommodation options have such little interest in data transparency that the overall phenomenon of city tourism can be addressed only in part.

Associating various data within the GIS enables municipal administrators and urban planners to identify potential sources of conflict within the property markets in good time and effectively counteract these where possible.

Increases in property prices directly attributable to growing city tourism may lead to the displacement of less financially secure members of the established population as well as businesses.

The sharing economy is a relatively new research topic which will become increasingly important in future. The identification of potential sources of conflict due to tourist accommodation has therefore not yet been comprehensively carried out on a small scale.

The purposes of the present study were to analyse: (1) if there is a hierarchical relationship between cognitive dimension (attention) and emotional dimension (enthusiasm); (2) to what extent the cognitive and emotional dimensions of the customer engagement (CE) affect loyalty to consumer brands in traditional settings and in social media; and (3) if involvement moderates the relationships between cognitive and emotional dimensions of CE and between each CE dimension and the two kinds of loyalties (offline and social media).

The authors applied structural equation model on a sample of 272 passengers of main airlines operating the domestic Argentinian market in 2018. The authors also used multigroup analysis to combine involvement as a moderator variable.

Cognitive dimensions of engagement (attention) had a direct and positive effect on the emotional engagement (measured by enthusiasm). Capturing the attention of passengers is key to maintaining their loyalty both in offline and online environments, especially if they are lowly involved with brands.

The present study suggests and tests a model for the consequences of CE as a multidimensional construct in a specific service context.

Following the attitude formation approach and the hierarchy of effect of advertising theory, this study researched the dynamic of relationship between cognitive and emotional dimensions of CE. The results contribute on the line of considering CE as a process, including stages that consumers go through until they achieve the engagement with the brand. The results offer evidence of the specific impact of each CE dimension on loyalty at two environments (offline and social media).

本研究有以下三個目標：

(1) 、探討認知維度 (注意) 與情緒維度 (熱忱) 之間是否存在著一個等級關係;

(2) 、瞭解顧客契合的認知維度和情緒維度、分別在傳統的設置裡，以及在社交媒體內，影響消費者品牌忠誠的程度;和.

(3) 、研究參與會否調節顧客契合的認知維度和情緒維度之間的關係;再者，參與會否調節顧客契合每個維度與兩類忠誠 (即離線和社交媒體) 之間的關係。

我們以結構方程模型，分析一個涵蓋於2018年在阿根廷國內市場營運的主要航空公司272名乘客的樣本，我們亦以多組分析，把參與作為調節變數，合併在一起。

研究結果顯示，顧客契合的認知維度對情緒維度 (以熱忱來計量) 有直接和積極的影響。研究結果亦顯示，若要在離線、以及在網絡環境下維持乘客的忠誠，最重要的是公司需取得他們的注意，特別是當他們談及品牌時是卑微的。

本研究為瞭解在一個特定服務業的背景裡，顧客契合、作為多元的構建會帶來的結果，建議並測試了一個模型。

研究人員使用態度形成的理念和廣告的階層效果理論，去探討顧客契合的認知維度與情緒維度之間的關係的動態。研究的貢獻、在於視顧客契合為一個過程，而這個過程，包括了消費者若要與品牌齧合所需經過的階段。另外，研究結果為每個顧客契合，在離線和社交媒體兩個環境裡，對忠誠所產生特定的影響提供了證據。

Hotels are immersed in a very competitive environment and hoteliers have to plan and redesign their strategies to stay in the hospitality industry while faced with a steady rise in competition. Hoteliers can employ horizontal differentiation strategies and pricing decisions to gain a competitive advantage over their competitors. The goal of our work is to analyse the effect of pricing and horizontal differentiation strategy of a hotel on its online reputation and to analyse if the hotel location and agglomeration of competitors moderates their relationship with online reputation.

With a sample of 264 hotels from Paris, an empirical study is developed that aims to analyse, using regression techniques, the impact of price, differentiation, location and competitive environment on online ratings given by consumers in the hospitality context.

The paper provides empirical evidence of how a good location improves the online reputation of a company and how pricing strategies should take into account the location and number of competitors since a good location allows premium prices to be valued positively by consumers while an inappropriate location can produce the opposite effect. Depending on location, the number of competitors can intensify or reduce the effect of price on online reputation. Finally, online reputation only benefits from horizontal differentiation strategies when the degree of agglomeration is low.

This work provides insights about how hotels can strengthen their online reputation through pricing and differentiation strategies, incorporating elements of their environment such as location and competition in this decision-making process.

酒店處於一個競爭非常激烈的經營環境中，營運者要面對競爭日益加劇的挑戰，在這情況下，他們必須計劃並重新設計其策略，以在酒店服務業中仍能繼續其業務。營運者可採用水平分化策略和定價決策，以取得比同業更大的競爭優勢。本研究旨在分析，若酒店採用價格及水平差異之策略，這對它們的網上聲譽會起什麽效應；研究亦探討酒店所處的位置及競爭者的凝聚會否減弱其與網上聲譽的關係。

研究樣本為來自巴黎264間酒店。研究人員採用實驗研究法，透過迴歸分析法，去分析在酒店服務的背景下，價格、差異化、地點和競爭環境如何影響消費者所給予的網上評分。

本文提供了經驗性證據，證明良好的地點會改善公司的網絡聲譽； 同時，亦證明釐定價格策略時，經營者應考慮競爭者的位置和數目，這是因為良好的地點會讓消費者正面評價溢價，而不合適的地點則會導致相反的效應。根據所在的地點，消費者的數目能增強或減弱價格對網絡聲譽的影響。最後，本文也證明了網絡聲譽只會在凝聚程度低的情況下才會受惠於水平分化策略。

本研究提供啟示，使我們更明瞭酒店如何能透過價格及差異化策略，同時亦透過把它們的環境元素如地點和競爭等納入決策程序中，來強化網絡聲譽。

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

The purpose of this qualitative study is to explore well-being experiences of international business travellers (IBTs) and contribute to our understanding of personal and job characteristics as antecedents of ill- or well-being.

The authors’ insights are based on semi-structured in-depth interviews with 32 IBTs assigned to various destinations ranging from single-country travel to global operation. Participants in this study represent a range of traveller personas (regarding demographics, type of work, travel patterns). Thematic analysis is used to reveal new insights.

The authors’ analysis revealed trip-load (i.e. workload, control, organisational support) and intensity of travel (i.e. frequency, duration and quality) as job characteristics that sit on an energy stimulation continuum, driving work-related outcomes such as stress and burnout or health and well-being. Energy draining and boosting processes are moderated by cognitive flexibility and behavioural characteristics.

Findings represent a framework for managing IBT well-being via adjustments in job and travel characteristics, plus guidance for training and development to help IBTs self-manage.

The insights within this paper contribute to the conversation around how to enhance well-being for IBTs and frequent flyers. The study intends to offer direction as to which specific job, psychological and behavioural characteristics to focus on, introducing a novel framework for understanding and avoiding serious consequences associated with international mobility such as increased stress, burnout and ill-health.