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The purpose of this paper is to assess the impact of sociopolitical instability on the peer-to-peer market for tourist accommodation.

The author studies for the case of Barcelona the impacts of the events occurring in the past months of 2017, which consisted of a terrorist attack and the calling for a referendum on the independence of Catalonia, by fitting a fixed effects regression model to a data panel of Airbnb listings, using New York and Paris as a control group.

The results show that, after controlling for individual and time effects, listing reviews and revenues fall in the last quarter of 2017 and do not recover until the second quarter of the next year, in spite of a notable effort to decrease prices in the same period. They also indicate that peer-to-peer hosts react fast to demand shocks and as those from traditional markets.

This is the first study to evaluate the impact of terrorism or political uncertainty in the peer-to-peer market and the first to evaluate their combined effect in any market.

This study aims to focus on peer-to-peer accommodation services in the sharing economy. Adopting construal level theory as the theoretical foundation, this study investigates the main and interaction effects of social and spatial distances on guest loyalty toward peer-to-peer accommodation.

This study uses a secondary source of online observational data archived on Xiaozhu, a leading peer-to-peer accommodation sharing platform in China. It consists of 2,612 observations of 1,304 unique travelers who stayed at 559 listings managed by 281 hosts in four major metropolitan areas of China over four years from August 2012 to August 2016. Non-linear binary choice panel models of probability regressions were used to estimate the effects of psychological distances (social and spatial) between hosts and guests on the likelihood of repeat purchase. The software used for the econometric analyses is STATA 14.

The results indicate that social distance negatively affects guest loyalty toward the listing hosts, while spatial distance has a positive influence on guest loyalty. The results also show significant interactions between the two psychological distance dimensions in influencing loyalty. The findings provide important insight into the influences of psychological distances on travelers’ repeat purchase behavior toward peer-to-peer accommodation providers.

This study contributes to the literature by providing empirical evidence that supports the importance of psychological distances in forming a loyal relationship between hosts and guests in the peer-to-peer accommodation sector of the sharing economy.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

The purpose of this paper is to investigate investor behavior in the market of peer-to-peer lending, which is an alternative form of finance, from the liquidity perspective.

Liquidity metrics and regressions are used to identify the trend of the market and the variables that significantly impact the successful resale, selling time and discount rate in the secondary market. Structural break analysis is used to examine the impact of COVID on the market.

There is a high demand for performing loans that are sold quickly; however, the discount rate is also high, which reflects the price of liquidity. Based on the results obtained from regressions, the main factors that impact the investors’ decisions are discount rate, borrower’s country, principal and the month passed after loan origination. Furthermore, it can be concluded that the pandemic has led to a structural break in March 2020, and investors have started to liquidate their claims.

This paper’s purpose is to add to the research that examines the secondary market in social lending. It also contributes to the understanding of an investor’s decision and behavior, which are key parts of the segment’s long-term sustainability from the demand perspective. The comprehensive understanding of a lender’s behavior is also essential for supervisory authorities and other participants of the financial market.

Previous studies mostly focused on credit risk aspects, whereas this paper contributes to the modest research of liquidity features. The added value of this paper is further supported by the use of a large European secondary market data set, including more than 5 million transactions, covering an 18-month horizon. Moreover, the market’s sensitivity is analyzed in the case of an external shock. In the beginning of 2020, the COVID outbreak caused an economic shutdown in many European countries. The paper examines how these uncertain economic conditions impact the secondary market.

This study aims to identify institutional work mechanisms that public actors employ in market shaping.

The paper uses an abductive theorizing process, combining a literature review with an empirical exploration of three different market-shaping contexts.

The study identifies 20 granular mechanisms of institutional work that market-shaping public actors employ. These mechanisms are all potentially employable in creating, maintaining or disrupting markets. Institutional work vis-à-vis individual institutions may differ in direction from the institutional work vis-à-vis the market system. Public actors are not a homogeneous group but may have different values and support competing institutional logics even when operating in the same market.

The empirical data were limited to three cases in three small open economies. Data collected from other markets and with other methods would provide more rigorous insight into market-shaping public actors.

The findings revealed institutional work mechanisms that public actors can use to shape markets. Companies wanting to engage public actors in market shaping should be aware of the values and institutional logics that influence market-shaping public actors.

The paper unites and expands on the scattered knowledge regarding institutional work in market shaping. It illuminates and dissects the role of public actors in market shaping, challenging the reactive stance that is often assigned to them. The study provides a better understanding of how conflicting market views affect markets. It also brings insights into the interplay between market-shaping actions and the multiple levels of market systems.

From the perspective of two-sided review systems, this study aims to investigate how guests’ prior reputation influences their subsequent satisfaction on Airbnb.

This study applied a conceptual framework based on social capital theory to explain the effect of guests’ reputation decided by hosts’ prior evaluations on their subsequent satisfaction. The authors collected 96,204 guest reviews posted for 17,325 properties on Airbnb and used the review polarity to measure guest satisfaction. All historical evaluations generated by hosts for each guest were collected and treated as a proxy of guest reputation. Ordinary least squares regressions were conducted to estimate the effect of guests’ reputation on their subsequent satisfaction.

Results show that guests whose historical evaluations have higher valences or larger variations tend to be more satisfied in their subsequent bookings. However, the number of reviews that guests received from hosts in the past does not influence their subsequent satisfaction.

This study provides new insights into the hospitality literature by identifying the influencing factors of guest satisfaction on peer-to-peer rental platforms from the perspective of two-sided review systems. Results also present practical implications to property owners and website designers to gain a deeper understanding of the determinants of guest satisfaction and the consequences of social interactions between hosts and guests.

This study is a novel attempt that analyzes the effect of guests’ reputation on their satisfaction with subsequent bookings based on two-sided review systems on peer-to-peer rental platforms. Thus, this study provides a starting point for investigating how two-sided review systems affect use behavior on peer-to-peer rental platforms.

The purpose of this paper is to compare customer perceptions of hotel and peer-to-peer (e.g. Airbnb) accommodation advantages and disadvantages and examine their influence on customer satisfaction and repurchase intentions. The advantages of each accommodation type are conceptualized through perceived travel experience authenticity, whereas the disadvantages are evaluated through the risks associated with staying at each accommodation type, including product performance risk, time/convenience risk and safety and security risk.

A cross-sectional survey was designed and disseminated to gather the data necessary to fulfill the study objectives. A total of 391 usable responses were collected for a multi-group analysis of the structural model designed to test the proposed relationships.

The multi-group comparison revealed similarities between the peer-to-peer (Airbnb) and hotel guest structural models. Model testing revealed a strong positive relationship between satisfaction and repurchase intention. Perceived authenticity was identified as a statistically significant satisfaction predictor for both accommodation types. Time/convenience and product performance risks were found to be insignificant predictors of guest satisfaction, while safety and security risk appeared to be statistically significant only in the Airbnb sample.

This study’s recruited sample represented a higher concentration of younger travelers, and, therefore, might only be generalized to the corresponding US traveler group population. Additionally, samples recruited via Amazon’s MTurk may be subject to self-selection bias as any other non-probability samples. Consequently, further research with a larger and more diverse sample is recommended.

It is recommended for both hotels and Airbnb to strengthen the authenticity of their accommodation offerings to provide a better guest experience and increase consumer satisfaction.

To develop the authenticity component, Airbnb hosts and hotels may offer local experiences to their customers, where guests would be able to engage with the community and to see and feel how the city lives. Such partnerships may not only improve the traveler experiences but also support the local community and strengthen the ties between local businesses.

This study contributes to the literature by advancing understanding of peer-to-peer (Airbnb) versus hotel accommodation consumer preferences. This study offers relevant theoretical constructs for assessing both accommodation types’ advantages and disadvantages.

This study aims to testify the effects of green marketing on peer-to-peer (P2P) accommodation consumers’ repurchase intention and positive word-of-mouth (WOM) towards P2P accommodation platforms through the mediation of trust and consumer identification.

A questionnaire survey was applied to collect data from a sample of 488 consumers in China who had used P2P accommodation platforms in the past six months. Partial least squares structural equation modelling was used to analyse the data.

The study found that consumers’ perception of green marketing orientation of P2P accommodation platforms significantly increased consumer trust in the platform and consumer identification with the platform, which in turn each positively influenced repurchase intention and positive WOM to the platform. Furthermore, consumer trust had a positive effect on consumer identification and both trust and identification mediated the relationship between green marketing and repurchase intention and that between green marketing and positive WOM.

The findings of this study provide P2P accommodation platform operators with important insights to apply green marketing and focus on consumer trust and identification in sustaining their business and coping with the intense market competition.

This study contributes to better understanding of the impact of green business practices on consumers in sharing economy and offers practical implications on sustainable P2P accommodation practices.

The purpose of this study is to formulate the most probable future scenario for the use of blockchain technology within the next 5–10 years in the electricity sector based on today’s experts’ views.

An international, two-stage Delphi study with 20 projections is used.

According to the experts, blockchain applications will be primarily based on permissioned or consortium blockchains. Blockchain-based applications will integrate Internet of Things devices in the power grid, manage the e-mobility infrastructure, automate billing and direct payment and issue certificates regarding the origin of electricity. Blockchain solutions are expected to play an important big role in fostering peer-to-peer trading in microgrids, further democratizing and decentralizing the energy sector. New regulatory frameworks become necessary.

The Delphi study’s scope is rather broad than narrow and detailed. Further studies should focus on partial scenarios.

Electricity market participants should build blockchain-based competences and collaborate in current pilot projects.

Blockchain technology will further decentralize the energy sector and probably reduce transaction costs.

Despite the assumed importance of blockchain technology, no coherent foresight study on its use and implications exists yet. This study closes this research gap.

Peer-to-peer (P2P) lending facilitates direct online lending and aims to provide financial inclusion and investment returns. Lender goals range from for-profit to pro-social and objective information is limited, which highlights the need to examine heuristics.

This study examines 1,347 lending decisions by finance students on a mock P2P site. Testimonials were used to randomly condition the financially literate lenders towards for-profit or pro-social decision-making. Each investor evaluated three loans. The three loan applications were identical except for a female or male headshot (vs an icon) and random reports of 50% funding for the female or male loan in 3 days (vs 11 days for opposite gender and 7 for icon). Previous research surveys students on a mock platform (Gonzalez, 2020) and reports similar heuristics and lifelike decisions in student and general population samples (Gonzalez and Komarova, 2014).

Lenders randomly conditioned towards pro-social lending state lower trust in borrowers. However, pro-social investors state lower risk in P2P lending and higher financial literacy. Second, pro-social investors are more confident when lending to borrowers highly trusted by other lenders, especially if the popular loan applicant is female. Third, pro-social conditioning increases lending to male applicants when the popular loan applicant is female. Fourth, pro-social investors who have experienced financial trauma have greater confidence in bad loan recovery.

This is the first study of heuristics in pro-social vs for-profit P2P lending. In addition, it shows that testimonials can effectively condition lending goals and affect trust and risk perceptions.