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Cited by 264Sharing Economy and PlatformsDigital Marketing and Social MediaDiverse Aspects of Tourism Research

When guests trust hosts for their words: Host description and trust in sharing economy

Tussyadiah, Iis P., Park, Sangwon·2018·Tourism Management
DOI 10.1016/j.tourman.2018.02.002
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Abstract

Abstract In order to better understand the dynamics of user behavior in the sharing economy platform, a multi-stage study was conducted on how Airbnb hosts articulate themselves online and how consumers respond to different host self-presentation patterns. First, using text mining techniques on a large dataset consisting descriptions of Airbnb hosts in 14 major cities in the United States, two patterns of host self-presentation were identified. Hosts generally present themselves online as (1) a well-traveled individual, eager to meet new people or (2) an individual of a certain profession. This contributes to the conceptualization of profile as promise framework for online self-presentation in mixed-mode interactions involving peer-to-peer accommodation platform. Second, consumers respond to the two host self-presentation strategies differently, demonstrating higher levels of perceived trustworthiness in and intention to book from well-traveled hosts. This has direct strategic implications for effective self-marketing of “amateur” tourism players as well as for the role of residents as resources in tourism destinations.

AI snapshot

Written from the paper’s full text.

TL;DR

This two-study paper uses text mining of 31,119 Airbnb host descriptions from 14 US cities to identify two host self-presentation patterns—"Travelers" and "Workers"—and then tests consumer responses to them. Consumers reported higher perceived trustworthiness and booking intention for "Travelers" than for "Workers," with a hybrid persona performing between the two.

Key findings

  • Study 1 identified two broad host self-presentation patterns: Persona 1 "Travelers" (well-traveled, eager to meet new people) and Persona 2 "Workers" (identifying with a profession); the 2-cluster solution had higher accuracy than the 4-cluster solution.
  • In Study 2, "Travelers" hosts received higher ratings than "Workers" hosts on trust in platform (M = 3.90 vs. 3.79, t = 2.02, p < 0.05), integrity (M = 4.02 vs. 3.94, t = 1.96, p < 0.05), benevolence (M = 4.23 vs. 3.51, t = 14.69, p < 0.001), ability (M = 4.39 vs. 3.97, t = 9.07, p < 0.001), and trusting intention (M = 4.26 vs. 3.99, t = 4.52, p < 0.001).
  • An additional study compared "Travelers," "Workers," and a "Hybrid" persona; significant differences appeared for benevolence (F = 125.84, p < 0.001), ability (F = 52.25, p < 0.001), and trusting intention (F = 11.61, p < 0.001). "Travelers" showed the highest perceptions, followed by "Hybrid" and "Workers"; post-hoc Duncan tests found ability and trusting intention did not differ statistically between "Hybrid" and "Workers," while "Travelers" differed statistically from both.
  • Pilot testing confirmed the stimuli: classification accuracy was 92% for New York and Chicago and 94% for Austin, with Fleiss' Kappa values of .69, .70, and .75 (p < 0.001).

Methods

  • Study 1 analyzed 31,119 Airbnb host descriptions from 14 major US cities obtained from InsideAirbnb.com (2015), excluding hosts with more than one listing. Text was pre-processed with Stanford POS tagger (tokenization, stop-word removal, POS tagging, lemmatization) and analyzed in KH Coder using hierarchical cluster analysis (Ward's criterion, Jaccard coefficient) and word co-occurrence networks.
  • Study 2 included a pilot test (N = 301) and a main between-subjects experiment (N = 800) via Amazon Mechanical Turk with US residents and approval rating above 98%; respondents rated trusting beliefs (ability, benevolence, integrity), trust in platform, and booking intention on 5-point scales. Analysis used PLS, confirmatory factor analysis, AVE, Cronbach's alpha, composite reliability, and t-tests.
  • An additional study (N = 279) compared a "Hybrid" persona with "Travelers" and "Workers" using identical procedures and ANOVA with Duncan post-hoc tests.

Limitations

  • Stated: the study did not consider other host-profile cues such as pictures, reviews, and other identifiers; it did not vary the length of host descriptions; and booking intention was measured independently of property characteristics, assuming the property matched consumer criteria.
  • Evident: the experimental samples were US-based Amazon Mechanical Turk respondents with high approval ratings, and booking intention was hypothetical rather than actual booking behavior; the host descriptions came from single-listing hosts in selected US cities, limiting generalization to professional hosts or other markets.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.tourman.2018.02.002

Cites

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Statistics

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Claims the paper makes

0 of 19 cited sources checked · 0 supported · 0 flagged

  • Findingown data
    § 3.1. Study 1: Host self-presentation patterns

    The 2-cluster solution appears to have higher accuracy in terms of self-presentation patterns than the 4-cluster solution.

    “the 2-cluster solution appears to have higher accuracy in terms of self-presentation patterns than the 4-cluster solution”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.
  • Findingown data
    § Highlights

    Two self-presentation patterns were found from Airbnb host profiles.

    “Two self-presentation patterns were found from Airbnb host profiles.”
    • Also stated in: § ABSTRACT · plain
      “two patterns of host self-presentation were identified.”
    • Also stated in: § [Please insert Table 1 and 2 about here] · boosted
      “Therefore, it can be concluded that peer-to-peer accommodation hosts present themselves online following two broad patterns, which can be presented into two host personae”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.
  • Findingown data
    § Cluster 1: Workers

    Ability was higher for Persona 1 'Travelers' (M=4.39) than for Persona 2 'Workers' (M=3.97), t=9.07, p<0.001.

    “| Ability | 4.39 | 3.97 | 9.07*** |”
    • Also stated in: § Cluster 1: Workers · plain
      “Note: the responses have been obtained by a 5-point scale ranging from 1 (strongly disagree or extremely unlikely) to 5 (strongly agree or extremely likely); * p &lt; 0.05, *** p &lt; 0.001”
    Quote in the paperNot a substantial claim
  • Findingown data
    § [Please insert Table 4 about here]

    All indicator reliability (loadings) are over the cut-off of 0.70.

    “It is found that all of indicator reliability (or loadings) are over the cut-off of 0.70.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Cluster 1: Workers

    Benevolence was higher for Persona 1 'Travelers' (M=4.23) than for Persona 2 'Workers' (M=3.51), t=14.69, p<0.001.

    “| Benevolence | 4.23 | 3.51 | 14.69*** |”
    • Also stated in: § Cluster 1: Workers · plain
      “Note: the responses have been obtained by a 5-point scale ranging from 1 (strongly disagree or extremely unlikely) to 5 (strongly agree or extremely likely); * p &lt; 0.05, *** p &lt; 0.001”
    Quote in the paperSubstantial claim
  • The quote only partly states this claim. 3
  • May combine two claims. 21
  • Classified as probably not a substantial claim. 23

  • The quote only partly states this claim.

    Findingnone given
    § Highlights

    Consumers' intention to book was higher for well-traveled hosts than for hosts of the other persona.

    “Consumers' booking intention was higher for well-traveled hosts.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Amazon Mechanical Turk users residing in the United States are representative of prospective guests of peer-to-peer accommodation.
    • Rests on an assumption: Prospective guests' responses to written host descriptions in a survey reflect their real-world trust and booking intentions.
    • Rests on an assumption: The three cities (New York, Chicago, Austin) are representative of major US cities for host self-presentation.

  • May combine two claims.

    Findingown data
    § ABSTRACT

    Hosts generally present themselves online as either a well-traveled individual eager to meet new people or an individual of a certain profession.

    “Hosts generally present themselves online as (1) a well-traveled individual, eager to meet new people or (2) an individual of a certain profession.”
    • Also stated in: § Highlights · plain
      “Hosts present themselves as well-traveled or those with certain professions.”
    • Also stated in: § [Please insert Table 1 and 2 about here] · plain
      “host descriptions in one cluster are dominated by themes related to their love for travel and meeting new people, while those in the other cluster by themes associated with host professions.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § 3.1. Study 1: Host self-presentation patterns

    Only a small fraction of reviews in the documents (less than 1% of the data) does not belong to any of the clusters.

    “Only a small fraction of reviews in the documents (less than 1% of the data) does not belong to any of the clusters.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

  • The quote only partly states this claim.

    Findingnone given
    § Highlights

    Consumers demonstrated higher levels of perceived trustworthiness in well-traveled hosts than in hosts of the other persona.

    “Consumers demonstrated higher trust in well-traveled hosts.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Amazon Mechanical Turk users residing in the United States are representative of prospective guests of peer-to-peer accommodation.
    • Rests on an assumption: Prospective guests' responses to written host descriptions in a survey reflect their real-world trust and booking intentions.
    • Rests on an assumption: The three cities (New York, Chicago, Austin) are representative of major US cities for host self-presentation.

  • May combine two claims.

    Findingown data
    § [Please insert Table 1 and 2 about here]

    Some top words in Persona 2 ('Workers') reveal personal characteristics of the host, such as gender, age, and marital status, implying a higher degree of self-disclosure.

    “Some top words reveal the personal characteristics of the host, such as gender ('male,' 'man'), age ('mid,' 'twenty'), marital status ('wife'), etc., implying a higher degree of self-disclosure.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § Cluster 1: Workers

    In the word co-occurrence network for New York, NY, the Workers cluster had 55 nodes, 49 edges, and density .032.

    “Figure 3. Word co-occurrence network: New York, NY”
    • Also stated in: § Cluster 1: Workers · plain
      “Nodes = 55; Edges = 49; Density = .032”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing). May combine two claims.

    Findingown data
    § Cluster 1: Travelers

    In the word co-occurrence network for Chicago, IL, the Travelers cluster had 28 nodes, 24 edges, and density .063.

    “Figure 2. Word co-occurrence networks: Chicago, IL”
    • Also stated in: § Cluster 1: Workers · plain
      “Nodes = 28; Edges = 24; Density = .063”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 3.2.3. Additional study: A new persona

    The mean values of all three variables (benevolence, ability, trusting intention) of Persona 1 'Travelers' are statistically different from those of both Persona 3 'Hybrid' and Persona 2 'Workers'.

    “the mean values of all three variables of Persona 1: 'Travelers' are statistically different to those of both Persona 3: 'Hybrid' and Persona 2: 'Workers.'”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning
    § [Please insert Table 1 and 2 about here]

    Additional clusters in the 4-cluster solutions are derivatives of the two personae and do not demonstrate different patterns of self-presentation strategies.

    “additional clusters in the 4-cluster solutions are derivatives of the two personae (e.g., 'Workers' with niche professions such as doctors, bankers, and lawyers), but do not demonstrate different patterns of self-presentation strategies.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

  • May combine two claims.

    Findingown data
    § 3.2.3. Additional study: A new persona

    Consumers who read the description of Persona 1 'Travelers' tend to show the highest perception of benevolence, ability, and booking intention, followed by those who engaged with Persona 3 'Hybrid' and Persona 2 'Workers' hosts.

    “Consumers who read the description of Persona 1: 'Travelers' tend to show the highest perception of benevolence, ability, and booking intention, followed by those who have engaged with Persona 3: 'Hybrid' and Persona 2: 'Workers' hosts.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § Cluster 1: Travelers

    In the word co-occurrence network for Chicago, IL, the Workers cluster had 53 nodes, 39 edges, and density .028.

    “Figure 2. Word co-occurrence networks: Chicago, IL”
    • Also stated in: § Cluster 1: Workers · plain
      “Nodes = 53; Edges = 39; Density = .028”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § Cluster 1: Workers

    In the word co-occurrence network for New York, NY, the Travelers cluster had 30 nodes, 25 edges, and density .057.

    “Figure 3. Word co-occurrence network: New York, NY”
    • Also stated in: § Cluster 1: Workers · plain
      “Nodes = 30; Edges = 25; Density = .057”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 3.2.1. Pilot test: Confirmation of host personae

    In the pilot test, the majority of respondents classified host descriptions correctly into the two personae, with average accuracy 92% for New York and Chicago and 94% for Austin.

    “As presented in Table 3, the majority of respondents classified host descriptions correctly into the two personae. On average, the accuracy is 92% of for New York and Chicago and 94% for Austin.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § [Please insert Table 1 and 2 about here]

    Host descriptions in one cluster are dominated by themes related to love for travel and meeting new people, while those in the other cluster are dominated by themes associated with host professions.

    “host descriptions in one cluster are dominated by themes related to their love for travel and meeting new people, while those in the other cluster by themes associated with host professions.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § References

    In the word co-occurrence network for Austin, TX, the Travelers cluster had 34 nodes, 36 edges, and density .057.

    “Figure 1. Word co-occurrence networks: Austin, TX”
    • Also stated in: § Cluster 1: Travelers · plain
      “Nodes = 34; Edges = 36; Density = .057”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § 2.1. Online self-Presentation in mixed-mode interactions

    Online profiles are crafted to allow the audience to expect that future face-to-face interaction will take place with someone that does not differ fundamentally from the person represented by the profile.

    “Ellison, Hancock and Toma (2011), in this vein, suggest 'profile as promise' framework, asserting that online profiles are crafted to allow audience to have an expectation that 'future face-to-face interaction will take place with someone that does not differ fundamentally from the person represented by the profile' (p. 12).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Ellison, Hancock and Toma (2011)

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationcitation
    § 2.2. Trust within digital platforms

    Trusting hosts means expecting hosts to act in accordance with the persona they portray through their profile description as well as their reputation.

    “This infers that trusting hosts means expecting hosts to act in accordance with the persona they portray through their profile description as well as their reputation.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Luhmann, 1979

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation
    § 2.2. Trust within digital platforms

    The dimensions of trustworthiness (competence/ability, benevolence, and integrity) can be adapted to measure online trust, where the object of trust is a person or a technology-deploying organization.

    “these dimensions of trustworthiness (also referred to as trusting beliefs) can be adapted to measure online trust, where the object of trust is a person or a technology-deploying organization.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites McKnight, Choudhury and Kacmar (2002a; 2002b)

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § 2.2. Trust within digital platforms

    Trusting beliefs lead to trusting intentions.

    “Studies also found that trusting beliefs lead to trusting intentions.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites McKnight et al., (2002a; 2002b)

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning
    § 3.2.1. Pilot test: Confirmation of host personae

    The pilot test was carefully designed to minimize confounding effects derived from survey and/or response errors.

    “We carefully designed the study to minimize confounding effects that can be derived from survey and/or response errors.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Amazon Mechanical Turk users residing in the United States are representative of prospective guests of peer-to-peer accommodation.
    • Rests on an assumption: Prospective guests' responses to written host descriptions in a survey reflect their real-world trust and booking intentions.

  • May combine two claims. The quote only partly states this claim.

    Interpretationown data
    § 4. Conclusion and implications

    The first cluster of host descriptions portrays a well-traveled individual eager to meet new people and show the destination, indicating a strategy to appear knowledgeable and empathetic, emphasizing desirability and low self-disclosure.

    “This pattern indicates an underlying strategy for peer-to-peer accommodation hosts to portray themselves as a host with knowledge about the 'ins and outs' of the destination and expansive experience of traveling, allowing them to understand and feel empathetic toward fellow travelers (i.e., guests).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Study design and conductnone given
    § 4. Conclusion and implications

    The stimuli used to solicit consumers' booking intention were made independent from the property characteristics.

    “the stimuli used to solicit consumers' booking intention were made independent from the property characteristics, assuming that the property matches consumer's criteria.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The property matches consumer's criteria in the stimuli used to solicit booking intention.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning
    § 4. Conclusion and implications

    The fact that hosts have experienced similar situations as prospective guests gives a new meaning to renting from peer travelers.

    “It can be suggested that the fact that hosts have experienced similar situations as the prospective guests (i.e., visiting new destinations, finding accommodation, etc.) gives a new meaning to renting from (and staying with) peer travelers.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § 4. Conclusion and implications

    The second cluster of host descriptions contains more personal information, particularly highlighting profession, representing higher self-disclosure and projecting self as regular individuals.

    “In the second cluster, host descriptions contain more personal information, particularly highlighting their profession, representing a higher degree of self-disclosure. It is suggested that because profession can be a main source of personal identity, these hosts are projecting self as regular individuals.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § [Please insert Table 1 and 2 about here]

    Work has long been considered a principal source of identity to many, and a majority of American workers get a sense of self-identity from their job.

    “Since work has long been considered a principal source of identity to many (Fryers, 2006), and that a majority of American workers get a sense of selfidentity from their job (Gallup, 2014)”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Fryers, 2006 source

      Not checked in the free run.

    • cites Gallup, 2014

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data
    § 4. Conclusion and implications

    Consumers trust a 'well-traveled' host more than a 'designer/doctor/lawyer' host, implying that communicating hosting-related information carries more 'promise' than personal information.

    “As evident in the results from Study 2, consumers trust a 'well-traveled' host more than a 'designer/doctor/lawyer' host, implying that communicating hosting-related information carries more 'promise' than personal information.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation
    § 4. Conclusion and implications

    This study reinforces the framework of offline modalities.

    “Indeed, this study reinforces the framework of offline modalities (e.g., Ellison et al., 2006; 2011; Gibbs et al., 2006).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Ellison et al., 2006 source

      Not checked in the free run.

    • cites Ellison et al., 2011

      Not checked in the free run.

    • cites Gibbs et al., 2006 source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductcitation
    § 3.2.1. Pilot test: Confirmation of host personae

    All host names were changed into names that score 5 (neutral in sentiments) on a valence scale of 1-9 to reduce possible sentiment bias resulting from host names.

    “following Dodds et al.'s (2011) hedonometrics study, all host names were changed into names that score 5 (i.e., neutral in sentiments) on a valence scale of 1 - 9: Neil for male and Marjorie for female.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Dodds et al.'s (2011) source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § 4. Conclusion and implications

    Adding statements that project resourcefulness (e.g., knowledge about the city and neighborhood) can be effective in inducing perceived ability, which shapes overall trustworthiness.

    “it can be suggested for peer-to-peer accommodation hosts that adding statements that project their resourcefulness (e.g., knowledge about the city and neighborhood) can be effective in inducing perceived ability, which shapes the overall trustworthiness.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning
    § 3.2.1. Pilot test: Confirmation of host personae

    Three types of questionnaires were developed for three separate cities (New York, Chicago, Austin) to manage bias related with the context of a specific destination.

    “First, in order to manage bias related with the context of a specific destination, three types of questionnaires were developed for three separate cities: New York in NY, Chicago in IL, and Austin in TX.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The three cities (New York, Chicago, Austin) are representative of major US cities for host self-presentation.

  • Classified as probably not a substantial claim.

    Premisecitation
    § 4. Conclusion and implications

    Profiles serve as a psychological contract between hosts and prospective guests, in that hosts promise aspects of the self that they believe are feasible during future service delivery.

    “According to the 'profile as promise' framework (Ellison et al., 2011), profiles serve as a psychological contract between hosts and prospective guests, in that hosts promise aspects of the self that they believe are feasible during future service delivery.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Ellison et al., 2011

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given
    § 3.2.1. Pilot test: Confirmation of host personae

    Respondents were randomly assigned to answer one of the three questionnaires.

    “Respondents were randomly assigned to answer one of the three questionnaires.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data
    § 4. Conclusion and implications

    The source of the significant difference in perceived trustworthiness is the host's travel experience and eagerness to meet new people instead of information related to profession as personal identity and information related to hosting competence.

    “the source of the significant difference in perceived trustworthiness is the host's travel experience and eagerness to meet new people instead of information related to hosting of profession as personal identity and information related to hosting competence.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning
    § 4. Conclusion and implications

    The identification of these two patterns implies opportunities to assess if one is more effective in bringing about consumer trust than the other.

    “the identification of these two patterns implies opportunities to assess if one is more effective in bringing about consumer trust than the other.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Ellison et al., 2006 source

      Not checked in the free run.

    • cites Gibbs et al., 2006 source

      Not checked in the free run.

    • cites Labrecque et al., 2011 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning
    § [Please insert Table 4 about here]

    The factor loadings on the corresponding constructs are much higher than the ones on other principal constructs, which confirms the discriminant validity.

    “This implies that the factor loadings on the corresponding constructs are much higher than the ones on other principal constructs, which confirms the discriminant validity.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data
    § 4. Conclusion and implications

    The hybrid persona seems to perform better than Persona 2 'Workers' in terms of benevolence, ability, and trusting intention, while Persona 1 'Travelers' still shows the highest scores.

    “The results suggest that while Persona 1: 'Travelers' still shows the highest scores in terms of benevolence, ability, and trusting intention, the hybrid persona seems to perform better than the Persona 2: 'Workers.'”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Interpretationown data
    § [Please insert Table 1 and 2 about here]

    Persona 1 ('Travelers') consists of hosts who personify themselves as well-traveled individuals who are eager to meet new people.

    “Persona 1, referred to as 'Travelers' herein for simplification, consisting of hosts who personify themselves as welltraveled individuals who are eager to meet new people”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § [Please insert Table 1 and 2 about here]

    Persona 2 ('Workers') consists of hosts who identify themselves as working professionals.

    “Persona 2, called 'Workers' herein, consisting of hosts who identify themselves as working professionals.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

  • May combine two claims.

    Interpretationown data
    § [Please insert Table 4 about here]

    The measurements for each construct are validated and reliable in acceptable levels.

    “Accordingly, it can be confirmed that the measurements for each construct are validated and reliable in acceptable levels.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § [Please insert Table 4 about here]

    The variables explain the indicators more than the error variances, which confirms the convergent validity.

    “This implies that the variables explain the indicators more than the error variances, which confirms the convergent validity.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data
    § Cluster 1: Workers

    The reliability of the host persona stimuli, measured by Fleiss' Kappa, was .69 for New York, .70 for Chicago, and .75 for Austin (all p < .001).

    “Table 3. Reliability of stimuli: Percent agreement and Fleiss' Kappa”
    • Also stated in: § Cluster 1: Workers · plain
      “| Fleiss' Kappa | .69 *** | .70 *** | .75 *** |”
    • Also stated in: § Cluster 1: Workers · plain
      “Note: *** p &lt; .001”
    Quote in the paperSubstantial claim
41 of 41

  • The paper relies on this without support.

    The two host personae identified by the cluster analysis are the only relevant self-presentation patterns for Airbnb hosts.

    “additional clusters in the 4-cluster solutions are derivatives of the two personae (e.g., 'Workers' with niche professions such as doctors, bankers, and lawyers), but do not demonstrate different patterns of self-presentation strategies.”

  • The paper relies on this without support.

    Amazon Mechanical Turk users residing in the United States are representative of prospective guests of peer-to-peer accommodation.

    “The questionnaire was distributed via Amazon Mechanical Turk (AMT), targeting users residing in the United States.”

  • The paper relies on this without support.

    Prospective guests' responses to written host descriptions in a survey reflect their real-world trust and booking intentions.

    “Actual host descriptions, one from each cluster, were randomly selected from the dataset and presented in a randomized order as stimuli in within-subject experimental design”

  • The paper relies on this without support.

    The three cities (New York, Chicago, Austin) are representative of major US cities for host self-presentation.

    “three types of questionnaires were developed for three separate cities: New York in NY, Chicago in IL, and Austin in TX.”

  • The paper relies on this without support.

    It is largely unknown if individual hosts employ self-marketing strategies to achieve being considered trustworthy.

    “it is largely unknown if individual hosts employ self-marketing strategies to achieve this outcome.”

  • The authors state this as an assumption.

    The property matches consumer's criteria in the stimuli used to solicit booking intention.

    “assuming that the property matches consumer's criteria.”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Personal characteristics and behaviors influence how trustworthy individuals are seen to be within sharing economy platforms.

    “Personal characteristics (for example, personal innovativeness; see Wang &amp; Jeong, 2018) and behaviors (for example, how users portray themselves in a platform; see Tussyadiah &amp; Park, 2018) influence how trustworthy individuals are seen to be within sharing economy platforms.”

    From Building trust in the sharing economy: Current approaches and future considerations (2021) · cites this paper as Tussyadiah & Park, 2018

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Integrity reliability falls below the stated cutoff

    Minor

    The methods specify a 0.80 cutoff for Cronbach's alpha and composite reliability, but Table 6 reports a Cronbach's alpha of 0.75 for Integrity while the text concludes that the measurements have acceptable reliability.

  • Table 6 diagonal is identified as both AVE and square root of AVE

    Minor

    The text says Table 6 presents square roots of AVEs, whereas the table note calls its diagonal values AVE scores. Those are different quantities.

2 of 2

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. Higuchi, 2017, A two-step approach to quantitative content analysis: KH coder tutorial using anne of Green gables (Part II), Ritsumeikan Social Sciences Review, 53, 137
  2. Li, 2015, Agent behavior in the sharing economy: Evidence from Airbnb, SSRN Electronic Journal
  3. Raban, 2009, Self-presentation and the value of information in Q&A websites, Journal of the Association for Information Science and Technology, 60, 2465

Cited by

Sorted by citations

Related

Authors
Tussyadiah, I. P., & Park, S.
Affiliations
  • University of Surrey (GB)
  • Hong Kong Polytechnic University (HK)
Corresponding author
Tussyadiah, Iis P.
ORCID
Venue
Tourism Management
Publisher
Elsevier BV
Published
2018-08
Volume
67
Pages
261-272
ISSN
0261-5177 (ISSN-L)
DOI
10.1016/j.tourman.2018.02.002
OpenAlex
W2786061594
Semantic Scholar
c056331fdda761390418be0950a2e8d1de1bd91f
Cited by
264
References
83
Citations by year
2026: 21 · 2025: 25 · 2024: 33 · 2023: 33 · 2022: 46 · 2021: 43 · 2020: 31 · 2019: 30 · 2018: 2
FWCI
47.49
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Tourism Management (publishedVersion)
  • Surrey Research Insight Open Access (The University of Surrey) (submittedVersion)
  • PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Marketing › Sharing Economy and Platforms
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
  • Social Sciences › Sociology and Political Science › Diverse Aspects of Tourism Research
Keywords
sharing economy, Airbnb hosts, online self-presentation, perceived trustworthiness, booking intention, self-promotion

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-08.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-08.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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