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The impact of photo verification service on sales performance in the peer-to-peer economy: Moderating role of customer uncertainty

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Abstract

The innovative service of photo verification is now offered by major home-sharing platforms. It remains unclear, however, whether and how a peer provider’s adoption of the platform’s photo verification service influences the provider’s sales performance. We draw on the theory of motivated information management to argue that verified photos are a crucial visual and experiential cue to reduce customer uncertainty regarding the properties and peer providers. We collect observational data from a leading home-sharing platform in China and utilize the propensity score matching method to account for endogeneity. Our results show that after adopting photo verification service, peer providers benefited from an improved sales performance in terms of revenue and rent days. The positive effect is stronger for properties with a source of greater uncertainty: (1) properties that lack certification and (2) properties with fewer customer reviews.

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... Finally, several recent studies concentrated on the role of photos as a performance determinant. Ma et al. (2022) found that verified photos had a larger positive effect on the performance of properties that lacked certification and those with fewer customer reviews. According to He et al. (2023), the booking rate was boosted by a background photo that featured a living room and showed more interior elements, while bedroom photos tended to decrease it. ...
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Millions of tourists have used Airbnb accommodations, and Airbnb is frequently discussed in terms of its current or future impacts on hotels. The purpose of this research was to investigate such impacts by determining the extent to which Airbnb is used as a hotel substitute and to examine how Airbnb guests expect their accommodations to perform relative to hotels. Together, these analyses were intended to provide empirical insight into Airbnb’s status as a disruptive innovation. The study involved an online survey of over 800 tourists who had used Airbnb within the previous year. Nearly two-thirds had used Airbnb as a hotel substitute. When considering traditional hotel attributes (e.g., cleanliness and comfort), Airbnb was generally expected to outperform budget hotels/motels, underperform upscale hotels, and have mixed outcomes versus mid-range hotels, signalling some – but not complete – consistency with the concept of disruptive innovation. Numerous practical and theoretical implications are discussed.
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‘Sharing economy’ platforms such as Airbnb have recently flourished in the tourism industry. The prominent appearance of sellers' photos on these platforms motivated our study. We suggest that the presence of these photos can have a significant impact on guests' decision making. Specifically, we contend that guests infer the host's trustworthiness from these photos, and that their choice is affected by this inference. In an empirical analysis of Airbnb's data and a controlled experiment, we found that the more trustworthy the host is perceived to be from her photo, the higher the price of the listing and the probability of its being chosen. We also find that a host's reputation, communicated by her online review scores, has no effect on listing price or likelihood of consumer booking. We further demonstrate that if review scores are varied experimentally, they affect guests' decisions, but the role of the host's photo remains significant.
Article
This paper presents an eight-firm study, conducted from the service-dominant logic perspective, which makes a contribution regarding knowledge of the anatomy of value propositions and service innovation. The paper suggests that value propositions are configurations of several different practices and resources. The paper finds that ten common practices, organized in three main aggregates, constitute and fulfill value propositions: i.e. provision practices, representational practices, and management and organizational practices. Moreover, the paper suggests that service innovation can be equated with the creation of new value propositions by means of developing existing or creating new practices and/or resources, or by means of integrating practices and resources in new ways. It identifies four types of service innovation (adaptation, resource-based innovation, practice-based innovation, and combinative innovation) and three types of service innovation processes (practice-based, resource-based, and combinative). The key managerial insight provided by the paper is that service innovation must be conducted and value propositions must be evaluated from the perspective of the customers’ value creation, the service that the customer experiences. Successful service innovation is not only contingent on having the right resources, established methods and practices for integrating these resources into attractive value propositions are also needed.
Article
The relationship between uncertainty and information has long been at the forefront of the social scientific study of human behavior. The last decade has seen increased attention among communication scholars to the information-management process. The result has been significant widening of ideological lenses and an impressive growth of knowledge. However, a review of the literature shows that there is the need for a framework that integrates and extends these efforts. We advance the theory of motivated information-management to fill that need. The theory proposes a 3-phase process of information-management in interpersonal encounters, emphasizes the role of efficacy, and brings attention to the interactive nature of information-management in this context. We explicate the theory's propositional structure and present a graphical model intended to capture some of the overarching principles detailed in that structure.
Article
Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp’s rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5% to 9% increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant’s average rating is affected by the number of reviews and whether the reviewers are certified as “elite” by Yelp, but is unaffected by the size of the reviewers’ Yelp friends network.
Professional photograph service
  • Airbnb
Airbnb (2020). Professional photograph service. https://zh.airbnb.com/d/pro-photograph y?_set_bev_on_new_domain=1599439189_NDVkYjliY2RiYzFk (accessed in September 2020).
Seeking interpersonal information over the internet: An application of the theory of motivated information management to internet use
  • Tokunaga
How much is an image worth? Airbnb property demand analytics leveraging a scalable image classification algorithm
  • S Zhang
  • D Lee
  • P V Singh
  • K Srinivasan
Zhang, S., Lee, D., Singh, P. V., & Srinivasan, K. (2017). How much is an image worth? Airbnb property demand analytics leveraging a scalable image classification algorithm. Available at SSRN: https://ssrn.com/abstract=2976021 or https://doi.or g/10.2139/ssrn.2976021.
To stop fraud, Airbnb to verify all housing listings
  • M Kan
Kan, M. (2019). To stop fraud, Airbnb to verify all housing listings. https://sea.pcmag. com/news/34834/to-stop-fraud-airbnb-to-verify-all-housing-listings-sort-of (accessed in September 2020).
Reviews, reputation, and revenue: The case of Yelp.com. Harvard Business School Working Paper
  • M Luca
Can lower-quality images lead to greater demand on Airbnb? Working paper
  • Zhang