Sharing Economy Services Research Articles

The Motivation Factors for Chinese Female Tourists to Participate in ‘Pin’ Themed Afternoon Tea at Luxury Hotels in Macau from the Sharing Economy Perspective and Self-Determination Theory

ABSTRACT The sharing economy has changed the consumption pattern of hospitality services. This study explored a new situation under the sharing economy service – the “Pin” afternoon tea (a form of group purchases) – and determined consumers’ motivations for participation. Qualitative research was conducted in the context of the sharing economy theory and self-determination theory. The results of interviews with 11 Chinese female tourists revealed nine motivation factors in five main dimensions (financial benefits, social benefits, sustainability, enjoyment, and novelty) of “Pin” afternoon teas: cost saving, product scarcity, expanding the circle of friends, social status, environmental consciousness, enjoying the processes, enjoying the foods, enjoying the environment, and experiencing new things. This study contributes to hospitality research by indicating how a niche market (Chinese female tourists) is motivated by a new sharing economy model (the “Pin” afternoon tea). Knowing these motivations may help the hospitality industry formulate appropriate strategies to speed tourism recovery.

Research on Customer Sharing Economy Service Development Pattern and Countermeasures

Research on Customer Sharing Economy Service Development Pattern and Countermeasures

Trust dynamics in sharing economy services during a crisis: A comparison between Airbnb and Uber

AbstractThis study investigates trust dynamics in sharing economy services during the COVID‐19 crisis, comparing Airbnb and Uber as prominent representatives of accommodation and transportation services in tourism. Guided by two research questions, the study first explores the antecedents and mechanisms of trust creation on these platforms and then examines how the global pandemic affected trust in these services. The findings reveal that structural assurance, privacy protection, and social influence (only for Uber) are key antecedents of trust. Trust, in turn, significantly influences perceived usefulness and the intention to use both platforms. The results also show that perceived risk, heightened by COVID‐19 concerns, negatively moderates the relationship between trust and usage intention. Comparing the two platforms, Airbnb exhibited higher levels of structural assurance, perceived usefulness, social influence, and usage intentions than Uber. Theoretically, this study advances knowledge by integrating technology acceptance literature with trust‐focused insights from tourism research. Practically, the findings guide sharing economy platforms in enhancing user trust and intention, particularly during crises.

What is Problem in Sharing Economy Service Ecosystem? Reviewing the Role of Trust in Loyalty

What is Problem in Sharing Economy Service Ecosystem? Reviewing the Role of Trust in Loyalty

Exploring the role of the service provider in sharing economy services

PurposeThis paper aims to investigate the role of the service provider in determining customer satisfaction in sharing economy services. The authors sought to examine how the intrinsic and extrinsic cues along with their interactions influence customer satisfaction.Design/methodology/approachThis research uses a mixed-methods design to test the hypotheses. Study 1 uses secondary data from Inside Airbnb. Study 2 uses a 2 × 2 × 2 between-subject experimental design.FindingsBoth studies support the confirmation bias perspective over the expectancy-confirmation perspective in explaining the interplay among different cues in determining customer satisfaction. In the context of Airbnb, in the absence of a Superhost badge, if hosts adopt a reactive communication style, physical presence has a greater impact on customer satisfaction compared to virtual presence.Originality/valueThis study extends the services marketing literature and cue utilization theory by investigating the dynamic interactions among multiple intrinsic and extrinsic service cues. It shed new light on how a combination of these cues may become additive or redundant in determining customer satisfaction. This study contributes to the services marketing literature by addressing the interactive nature of sharing economy services and the neglected role of service providers.

Cybersecurity threats in tourism and hospitality: perspectives from tourists engaging with sharing economy services

ABSTRACT In recent years, the number of cyber-attacks has increased significantly, affecting various business sectors, including tourism and hospitality. However, research on cybersecurity in tourism remained scarce. The current study aims at investigating cybersecurity threats from tourists’ perspectives while using sharing economy services. Using snowball sampling method and considering the ‘real experience of cybercrime’ as inclusion criterion, a total number of 14 in-depth interviews with tourists from different parts of the world were conducted online and data were analysed thematically through the lens of Protection Motivation Theory. The findings uncovered the heightened susceptibility of both tourists and sharing economy services to an array of cyber-attacks, encompassing side jacking, Point-of-sale attacks, insecure transactions, personal data breaches, phishing, etc. These multifarious threat vectors significantly complicate effective responses. In line with PMT, several themes, including threat appraisal, coping appraisal (perceived efficacy, response efficacy and response costs), self-protection and behavioural decision-making, have emerged. The results further indicate that high vulnerability attributes to tourists unfamiliarity and restricted cognizance of destination-specific elements such as regulatory framework, financial systems and technological infrastructure. Tourists’ reactions to cybercrimes exhibit variability contingent upon the typologies of threats or attacks, contextual factors, prevailing conditions and their geographic disposition during the occurrence.

“Look me in the eye, customer”: How do face-to-face interactions in peer-to-peer sharing economy services affect customers’ misbehavior concealment intentions?

Customer misbehavior poses a major risk in the sharing economy. For example, property damage to shared accommodations imposes burdens on both sharing platforms and hosts, especially if misbehaving guests purposefully, not coincidentally conceal, or fail to report damages. Such misbehavior might be facilitated by remote listing management and the lack of face-to-face interactions between hosts and guests. Therefore, this study investigated the effects of host–guest interaction modes (face-to-face, online-only) and frequency on guests’ misbehavior concealment intentions. Social identification and irritation emerged as bright- and dark side mediators, respectively. Guests who interacted face-to-face (vs. online-only) with hosts exhibited weaker intentions to conceal their misbehavior due to increased social identification. Platforms can elicit social identification by engaging guests in virtual communities. However, when face-to-face interactions become excessive, guests experience irritation and are more likely to conceal their misbehavior. These insights offer practical implications for both peer-to-peer sharing platforms and hosts.

Blacklisting Based Anonymous Authentication Scheme for Sharing Economy

Authentication and blacklisting mechanisms have a key role for service providers to deliver the service to correct users through digital channels. Nevertheless, there always have been concerns about privacy of the users against such mechanisms. The conditional anonymity concept is proposed as a remedy to these concerns. A recent approach in the literature for conditional anonymity is blacklistable anonymous credentials, which allows service providers to blacklist users for an authentication session without identifying the user. In this paper, we improve user anonymity in conditionally anonymous schemes using two complementary mechanisms. First, we define whitelisting property for blacklistable anonymous credentials and give a construction of this scheme. The whitelisting property can be used to unlink an honestly behaved authentication session from the user. Second, we propose an extension of this scheme for a particular use case, sharing economy services. This scheme allows a service provider to blacklist a user only if the user have not returned the shared asset in due time. We benchmark the performance of our schemes by comparing them with the rival schemes. Our experiments show that both of our scheme have comparable performance to previous works.

Signals that sharing economy service providers should send out: The case of codementor

A sharing economy is an economy that enables individuals to share their assets with or provide services to those in need through online platforms. Information asymmetry prevents consumers from effectively choosing the best service provider for their needs. Therefore, service providers should offer high-quality signals to address this problem. Unlike other studies, which have focused on platforms for sharing tangible assets (e.g., houses), in this study, we focused on platforms for sharing intangible assets (e.g., knowledge). Specifically, we adopted signaling theory to develop a research model for determining the internal and external signals that service providers should provide on their platforms to attract customers. Public data were collected from the Codementor platform by using Python web scraping. After rigorous data processing, the data obtained from 612 service providers were analyzed to identify key signals. Four crucial internal signals were identified: availability of follower information, availability of reviews, free trial, and service cost. In addition, two crucial external signals were identified: number of projects accomplished and endorsements from other websites related to mentor performance. Overall, our findings expand the application of signaling theory to intangible asset transactions and enable service providers to identify the essential signals that they should provide on their sharing economy platforms to increase the number of consumers interested in their services.

Ekonomija dijeljenja

This paper focuses on the two most prevalent and economically significant services of the sharing economy: accommodation and transport. Its primary objective is to compare these two crucial sectors in terms of user perspective and their perceived service quality. Given that these platforms operate similarly, this study aims to determine if there are unique aspects that require different approaches or areas that need to be improved. This is crucial for making these platforms function better and provide a better experience for users. The quality of service was analysed through technical and social categories. The goal was to determine whether and how the aforementioned service quality categories affect user behaviour and whether there are differences in the ranking of service quality categories from the users’ perspective, depending on the individual sector of the sharing economy. On a sample of 327 respondents, SEM analysis was used to show that the technical and social categories of service quality positively and directly influence the behavioural intentions of users in the sharing economy in both the accommodation and transport sectors. The findings also revealed that, for the users of the sharing economy service in the accommodation sector, the social category of service quality is more important than the technical category, while for the users of the sharing economy services in the transport sector, the technical category of service quality is more important than the social one.

When Information is Missing: Booking Decisions in Peer-To-Peer Accommodation

ABSTRACTGiven the limited tourist capacity for each listing and the frequent introduction of new properties, booking decisions in peer-to-peer accommodations inherently involve uncertainty due to incomplete information available to tourists. However, the psychological mechanism underlying customers’ booking decisions in such accommodations remains unclear. This study confirms that the presence of inference stimuli can enhance tourists’ booking intentions for a property without essential information. Furthermore, this study finds that tourists’ decision confidence mediates the effect of inference stimuli on booking intention, while customers’ information processing styles moderate the relationship. These results generate new insights to understand customers’ booking decisions under uncertainty in sharing economy services and provide strategies to mitigate uncertainty for listings with incomplete information, ultimately boosting accommodation bookings.

Collaborative Consumption in an Emerging Market: What Motivates Consumers to Adopt It under Economic and Political Uncertainty?

This study presents a consumption model tailored for emerging markets beyond BRICS, which considers the advantages of a sharing economy service and its impact on user behavioral intention. Moreover, it integrates moderating variables to enhance the understanding of consumer behavior toward adopting collaborative consumption services, making two significant contributions to the existing literature. By drawing data from 270 customers from Chile and utilizing variance-based structural equation modeling along with partial least squares techniques that use SmartPLS, the research findings highlight that convenience and enjoyment play the most pivotal roles in influencing consumer behavioral intention. Additionally, the study reveals that gender significantly moderates the relationship between convenience and purchase intention. Overall, this research sheds light on the potential of sharing economy services in emerging markets, providing valuable insights into consumer preferences and behavior, which can prove beneficial for businesses and policymakers alike.

Customer misbehavior and service providers’ risk perception in the sharing economy

Sharing economy (SE) service providers (e.g., home-sharing hosts) are regularly faced with customer misbehavior, either directly via their own experiences or indirectly via the experiences of other providers. In our study, we demonstrate that this increases providers’ perceived risk and, ultimately, their intention to quit sharing. Based on a comprehensive framework, we identify several boundary conditions for providers’ risk processing. We tested our model utilizing a sample of 1,312 owners of European holiday homes. Regarding sharing platforms’ management, our results offer insights for reducing provider turnover by selectively encouraging providers to share experiences with each other and by increasing service providers’ enjoyment in sharing. We performed an additional multigroup analysis to examine the role of providers’ places of residence, which reveals important differences. For example, it appears that risk-related information acquired in face-to-face interactions has a greater impact on perceived risk than information from indirect exchanges (e.g., online forums).

$\mathrm{W}^{2}$Parking: A Data-Driven Win-Win Contract Parking Sharing Mechanism Under Both Supply and Demand Uncertainties

With the rapid growth of the number of private vehicles, searching for accessible parking spaces becomes intractable for drivers, especially during high-demand hours. In recent years, we are witnessing a number of sharing economy services. Contract parking sharing, as an innovative sharing economy mode, has the potential to alleviate the difficult parking issue and make full use of the urban parking resources. However, the uncertainties of both drivers' parking demand and owners' sharing supply make it challenging to achieve efficient sharing. Thanks to IoT technology, many current parking lots now record vehicles' fine-grained parking data for billing purposes. Leveraging these fine-grained parking data, we exploit available contract parking spaces to share them with drivers that have temporary parking demand. Specifically, we propose <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathrm{W^{2}}$</tex-math></inline-formula> Parking, a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</u> in- <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</u> in contract <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">parking</u> sharing system, which includes two key components: (i) an idle time prediction model to estimate available periods of parking spaces and (ii) a parking sharing model to schedule temporary users to have access to these available parking spaces under both demand and supply uncertainties using dynamic programming combined with a 2-approximation algorithm with performance-bound guarantees. we evaluate our system on seven-month real-world parking data from 368 parking lots with 14,704 parking spaces. Extensive experimental results show that our <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathrm{W^{2}}$</tex-math></inline-formula> Parking achieves more than 90% of accuracy in parking time prediction, and the utilization rate of contract parking spaces is improved by 35%

The Short- and Long-Term Impacts of COVID-19 Pandemic on the Sharing Economy: Distinguishing Between “Symptomatic” and “Asymptomatic” Platforms

AbstractOur study presents a systematic literature review on the repercussions of the COVID-19 pandemic on the different types of sharing economy platforms and the sharing economy phenomenon in its entirety. Our literature review helps understand how the characteristics of different services of the sharing economy combine with contingent factors, such as government-mandated lockdowns, changed consumer behaviors, and people’s fear of contagion, to determine the magnitude of the impact of COVID-19 on the sharing economy both in the short run and in the long run. By examining these factors, we distinguish between sharing economy services/platforms that were (and possibly will be) negatively impacted by the COVID-19 pandemic (referred to as “symptomatic” platforms) and those that were not (and possibly will not be) impacted at all or even benefit (referred to as “asymptomatic” platforms). We then propose a new framework that combines traditional dimensions of sharing economy with a dimension resulting from the COVID-19 pandemic, i.e., the level of physical interaction required to deliver the sharing economy service. Building upon the extant literature, the framework helps better understand how the sharing economy will evolve after the pandemic. It also helps identify important research gaps that both academics and practitioners working on the field of sharing economy should address in the near future.

Examining sharing economy operations: A process perspective

<scp>Examining sharing economy operations</scp>: A <scp>process perspective</scp>

Exploring the Over-Time Variation in Customer Concerns on Sharing Economy Services

The sharing economy represented by Airbnb has evolved rapidly. It is particularly important to identify and understand how consumer concerns change over time. As a result, this study employs structural topic modelling using room type and time as covariates to extract topics from 896,658 Airbnb reviews in London and to observe the variation in the prevalence of topics over time. The findings show that the topic proportion changed relatively sharply in the early years of Airbnb (2010-2013) and during the COVID-19 pandemic (2020-2022), but relatively smoothly in the middle period (2014-2019). This research also discovered that the proportion of topics on customers' special experiences has been decreasing while the proportion of topics on their overall experience has been increasing. This shift could be attributed to an increase in the number of professional hosts, which has accelerated the standardisation of the Airbnb service.

Multi‐sided? Operation mode of sharing economy enterprises

AbstractTurning to the theoretical methods of two‐sided markets, we analyze the operation mode selection of the sharing economy. Considering the interactions of the operating enterprise, resource suppliers (basic service providers), value‐added service providers, and consumers, we show that the selection of one‐sided mode, two‐sided mode, or multi‐sided mode depends on enterprise service quality, pricing power and cross‐group externalities of sharing economy service, utility evaluation and access cost of the value‐added service. Further, we give a theoretical explanation of the operation mode evolution in China's online car‐hailing market and put forward two specific multi‐sided platform development paths.

Interpersonal versus institutional trust: consumers' trust to sharing services and its impact on continuance intention

The influence of trust on consumers' sharing intentions is an essential topic in electronic commerce. However, research on interpersonal trust is very scarce. Therefore, this paper explores the impact of interpersonal trust on consumers' continuance intentions to use sharing economy services. Another research question of this paper is how the impact of this trust differs by the service platforms, which offer different products to share (pet, car, and accommodation). For this purpose, we conducted an online survey on 252 users from three separate sharing platforms. Findings reveal that trust in peer and trust in product play a significant role in consumers' continuance intentions regardless of platforms. Findings also show that disposition to trust indirectly affects the continuance intention of two platforms, which offer pet or car sharing. We found that trust in product affects continuance intention for car sharing. We also found that the effect of trust in peer on continuance intention for pet sharing platform is relatively strong. Revisiting the concept and measurement of trust in the context of sharing economy, this paper is regarded as an important contribution to an underexplored area.

New Frontiers of Entrepreneurial Opportunities and Startups: An Analytical Perspective

The entrepreneurial landscape has been fast changing as new prospects for entrepreneurs in a variety of industries emerge. The emergence of advanced technologies such as artificial intelligence, blockchain, and the Internet of Things has opened up new possibilities for startups to create innovative solutions that disrupt traditional industries. With many companies concentrating on environmentally and socially conscious business models, social and environmental issues have also emerged as significant drivers of entrepreneurship in addition to technology. With platforms for freelance labor and sharing economy services, the growth of the gig economy has also opened up new options for entrepreneurs. With more female and minority entrepreneurs entering the market, the startup ecosystem has also become more diverse. The rise of alternative financing methods like crowdfunding and peer-to-peer lending has increased access to capital as well. However, there are still many difficulties that startups must overcome, such as stiff competition, legal restrictions, and hiring difficulties. Despite this, startups continue to push the envelope of innovation and develop fresh goods and services that will help to shape the course of the company.