1. Abstract
The Peer-to-Peer Accommodation Adoption Scale (P2PAAS) is an established psychometric instrument designed to assess consumer motivations, perceptual evaluations, and behavioral intentions regarding the adoption of collaborative consumption lodging platforms (e.g., Airbnb, Vrbo). Developed within the empirical tradition of tourism management, consumer psychology, and technology adoption research by Iis P. Tussyadiah and Juho Pesonen (2016), the scale evaluates multidimensional utilitarian and hedonic drivers underpinning consumer migration away from traditional accommodation providers toward decentralized hospitality networks.
The instrument operationalizes four core motivational and perceptual dimensions alongside future behavioral intentions: Economic Benefits (monetary savings, relative price-value ratio, and cost-efficiency), Sustainability Motivation (environmental consciousness, resource optimization, and reduced ecological footprints), Local Experience (authenticity, cultural immersion, and local integration), and Community and Social Interaction (social bonding with hosts and resident communities). Subsequent structural models frequently incorporate Platform Trust (technological and institutional security) as a foundational mediating antecedent. The scale typically features 16 to 22 self-report items administered via a 7-point Likert scale ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”).
Psychometric evaluations through exploratory and confirmatory factor analyses demonstrate robust construct validity, high internal consistency (Cronbach’s alpha coefficients regularly exceeding α = .80 across subscales; Composite Reliability scores > .82), and distinct convergent and discriminant validity confirmed by average variance extracted (AVE > .50) and Fornell-Larcker criteria. The P2PAAS serves as a benchmark measurement tool across hospitality management, behavioral economics, and digital platform sociology.
2. Keywords
Peer-to-Peer Accommodation, Collaborative Consumption, Sharing Economy, Airbnb Adoption, Travel Motivation, Economic Benefits, Sustainable Tourism, Psychometric Validation, Technology Acceptance Model, Consumer Behavior
3. Authors
The principal investigators responsible for the conceptualization, psychometric operationalization, and empirical validation of the P2PAAS framework are:
- Iis P. Tussyadiah, Ph.D. — Professor of Intelligent Systems in Service and Head of the School of Hospitality and Tourism Management at the University of Surrey, United Kingdom. Dr. Tussyadiah is an internationally renowned scholar in artificial intelligence, technology adoption, and consumer behavior within the visitor economy.
- Juho Pesonen, Ph.D. — Professor of Tourism Business and Head of the Center for Tourism Studies at the University of Eastern Finland, Finland. Dr. Pesonen specializes in electronic tourism (eTourism), market segmentation, and digital consumer analytics.
Correspondence regarding the original research framework may be directed to the School of Hospitality and Tourism Management, Faculty of Arts and Social Sciences, University of Surrey, Guildford, GU2 7XH, United Kingdom.
4. Purpose
The rapid emergence of the sharing economy has fundamentally disrupted global hospitality and travel distribution channels. Prior to the formalization of peer-to-peer (P2P) lodging instruments, empirical investigations of accommodation selection predominantly relied on traditional hotel choice attributes—such as brand equity, standardized room amenities, star-rating hierarchies, and location proximity. However, these legacy metrics failed to capture the decentralized, idiosyncratic, and socially embedded characteristics of collaborative consumption platforms.
The primary purpose of the Peer-to-Peer Accommodation Adoption Scale (P2PAAS) is to provide a theoretically grounded, psychometrically sound diagnostic instrument to measure the complex, heterogeneous motivations driving travelers to select P2P rentals over conventional lodging. The scale was engineered to uncover both extrinsic drivers (e.g., budgetary constraints, functional utility) and intrinsic drivers (e.g., civic responsibility, cultural authenticity, human connection) that collectively influence adoption patterns.
Research Applications
In academic and applied research environments, the scale enables investigators to:
- Conduct robust market segmentation to profile distinct consumer typologies (e.g., “Price-Sensitive Maximizers,” “Authenticity Seekers,” or “Socially Driven Communitarians”).
- Model destination-level economic impacts, examining how lodging dispersion alters visitor spending distributions away from traditional hotel clusters and into residential neighborhoods.
- Test structural relationships involving perceived risk, platform algorithms, electronic word-of-mouth (eWOM), and post-stay repurchase loyalty.
- Assess longitudinal shifts in traveler values, such as the growing demand for green tourism practices and authentic cultural encounters.
Practical and Clinical/Managerial Utility
For destination management organizations (DMOs), urban planners, and hospitality enterprise executives, the scale provides clear empirical intelligence. DMOs utilize these psychometric indicators to anticipate housing demand pressures and draft balanced regulatory policies. Traditional hoteliers use data derived from the scale to redesign service blueprints, incorporating localized community elements and transparent pricing to recapture market share lost to digital sharing platforms.
5. Psychological Construct
The P2PAAS conceptualizes accommodation adoption not as a mere transactional purchase, but as a multi-layered psychological commitment influenced by functional utility, personal ethics, interpersonal connection, and psychological security. The construct is comprised of several distinct latent dimensions:
1. Economic Benefits (Utilitarian Value)
This dimension operationalizes a consumer’s rational calculation of financial utility, cost efficiency, and perceived return on investment. Rooted in classical consumer choice theory, this subscale captures the extent to which travelers perceive P2P lodging as offering superior price-to-quality ratios relative to traditional hotels. Measurement indicators assess beliefs regarding lower total nightly expenditures, access to household amenities (e.g., in-unit kitchens, washing machines) that reduce ancillary travel expenses, and the capacity to accommodate larger groups within a single physical footprint.
2. Sustainability Motivation (Altruistic & Normative Value)
This dimension measures ideological and ethical motivations aligned with sustainable tourism and environmental stewardship. It gauges the respondent’s perception that participating in peer-to-peer accommodation maximizes the utilization of underused assets, optimizes resource distribution, and reduces the carbon and infrastructural footprints associated with mega-hotel construction and operation. It measures green consumption orientations, reflecting how travelers fulfill moral obligations and preserve social responsibility while away from their primary residence.
3. Local Experience & Authenticity (Hedonic & Experiential Value)
This subscale evaluates the psychological quest for existential and constructivist authenticity. Distinct from sanitized, standardized hotel environments, P2P accommodations are typically situated within residential neighborhoods. This dimension measures the user’s desire to “live like a local,” experience indigenous neighborhoods, discover uncurated cultural locales, and experience destination environments from an insider rather than a voyeuristic tourist perspective.
4. Community & Social Interaction (Relational Value)
The community dimension reflects the human desire for social connectedness, interpersonal affiliation, and host-guest interaction. It measures the traveler’s intrinsic motivation to establish meaningful, personalized relationships with lodging hosts, receive personalized hospitality, and interact with the local populace. This constructs hospitality as an authentic social exchange rather than a commercial, commodified transaction.
5. Platform Trust & Adoption Intention (Conative Commitment)
Platform trust assesses systemic and interpersonal confidence in digital intermediary platforms—including data encryption, identity verification, reliable review systems, and financial dispute resolution. Adoption Intention serves as the downstream behavioral outcome, operationalizing the respondent’s formulated probability, commitment, and explicit willingness to utilize peer-to-peer lodging networks for upcoming travel planning.
6. Theoretical Framework
The P2PAAS is grounded at the nexus of behavioral economics, consumer psychology, and technology adoption models. Rather than relying on a single conceptual paradigm, the scale synthesizes multiple foundational frameworks:
The Theory of Planned Behavior (TPB)
Formulated by Icek Ajzen (1991), the Theory of Planned Behavior posits that human action is guided by three considerations: behavioral beliefs (attitudes toward the behavior), normative beliefs (subjective norms), and control beliefs (perceived behavioral control). In the P2PAAS, economic benefits, local experience, and sustainability constitute the core cognitive evaluations shaping a positive attitude toward the platform. Subjective norms capture normative pressures regarding sustainable and unconventional travel, while platform trust provides the perceived behavioral control necessary to navigate the digital booking interface.
Technology Acceptance Model (TAM) and Extended UTAUT
Stemming from Fred Davis’s (1989) TAM and Venkatesh et al.’s Unified Theory of Acceptance and Use of Technology (UTAUT), the scale treats P2P adoption as an interaction with an information system. Utilitarian economic savings directly map onto perceived usefulness, while platform navigation, automated communication, and secure payment processing correspond to perceived ease of use. The integration of social and local experiential factors aligns with modern extensions of TAM that incorporate hedonic motivation and price value (e.g., UTAUT2).
Social Exchange Theory (SET)
George Homans’s (1958) Social Exchange Theory suggests that human relationships are formed by the use of a subjective cost-benefit analysis and the comparison of alternatives. The P2PAAS conceptualizes the tourist-host relationship through this paradigm: travelers weigh the perceived risks of unstandardized private accommodations (e.g., safety, hygiene, cancellation uncertainties) against relational benefits (e.g., personalized guidance, host hospitality, authentic cultural exchange). When perceived social and economic rewards outweigh operational risks, adoption intention increases.
7. Validity
The psychometric integrity of the P2PAAS has been substantiated through rigorous construct, convergent, discriminant, and predictive validity assessments across multiple global samples.
Construct and Convergent Validity
Convergent validity evaluates the extent to which indicators of a specific construct converge or share a high proportion of variance. In validation studies based on structural equation modeling (SEM):
- Standardized factor loadings for individual items across all first-order constructs systematically surpass the established .70 threshold, with empirical factor loadings spanning .72 to .91 (all statistically significant at p < .001).
- The Average Variance Extracted (AVE) for each latent dimension consistently exceeds the .50 benchmark recommended by Fornell and Larcker (1981): Economic Benefits (AVE = .64 to .71), Local Experience (AVE = .58 to .68), Sustainability (AVE = .55 to .65), and Adoption Intention (AVE = .69 to .78).
Discriminant Validity
Discriminant validity confirms that each latent dimension measures a unique psychological phenomenon distinct from other model dimensions. This has been confirmed through two primary statistical criteria:
- Fornell-Larcker Criterion: The square root of the AVE for every individual latent construct exceeds the highest inter-construct correlation with any other construct in the measurement model.
- Heterotrait-Monotrait Ratio of Correlations (HTMT): Modern structural assessments demonstrate HTMT ratios across all paired dimensions below the conservative cutoff value of .85, verifying empirical divergence between adjacent concepts such as “Local Authenticity” and “Community Interaction.”
Predictive and Nomological Validity
Predictive validity is demonstrated by the scale’s capacity to explain significant variance in downstream outcome variables. Multiple regression and structural path models reveal that the combined motivational dimensions account for between 48% and 64% of the total variance in travelers’ actual booking intentions and self-reported P2P usage frequency (R² = .48–.64, p < .001). Nomological validity is further corroborated by positive, theoretically expected correlations between P2PAAS adoption intention scores and broader indices of exploratory consumer travel behavior and digital self-efficacy.
8. Reliability
The reliability of the P2PAAS has been verified across diverse geographic populations, cross-cultural traveler demographics, and longitudinal cohorts.
Internal Consistency
Internal consistency across all multi-item subscales demonstrates high reliability, with coefficients consistently surpassing conventional psychometric standards (α ≥ .70):
- Economic Benefits: Cronbach’s α = .86 – .92; Composite Reliability (CR) = .88 – .93
- Sustainability Motivation: Cronbach’s α = .81 – .88; Composite Reliability (CR) = .83 – .89
- Local Experience: Cronbach’s α = .84 – .90; Composite Reliability (CR) = .86 – .91
- Community & Interaction: Cronbach’s α = .80 – .87; Composite Reliability (CR) = .82 – .88
- Adoption Intention: Cronbach’s α = .89 – .94; Composite Reliability (CR) = .90 – .95
Test-Retest Stability
In stability studies with non-interventional control samples re-tested over 4- to 6-week intervals, intra-class correlation coefficients (ICC) ranged from .78 to .85, indicating substantial temporal stability of the latent motivational constructs under ordinary consumer travel conditions.
9. Factor Analysis
The structural composition of the P2PAAS was developed and refined using complementary Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) workflows.
Exploratory Factor Analysis (EFA)
Initial scale purification was conducted using Principal Axis Factoring (PAF) and Principal Component Analysis (PCA) combined with oblique (Promax) rotation, accounting for expected theoretical correlations among human travel motivations. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy routinely exceeds .88 (indicating high sample suitability), and Bartlett’s Test of Sphericity demonstrates statistical significance (χ², p < .001). Clean factor extraction reveals an eigenvalue-greater-than-one profile explaining over 65% of total cumulative variance, with clean primary factor loadings (> .60) and cross-loadings remaining well below .30.
Confirmatory Factor Analysis (CFA) Model Fit
Subsequent structural verification using maximum likelihood estimation in covariance-based SEM (CB-SEM) confirms that the multi-factor measurement model provides an excellent fit to empirical data. Commonly reported goodness-of-fit indices across published empirical literature include:
- Chi-Square to Degrees of Freedom Ratio (χ²/df): 1.82 – 2.65 (well below the conservative threshold of 3.0).
- Root Mean Square Error of Approximation (RMSEA): .042 – .058 (90% confidence interval: [.035, .065], indicating close approximate fit).
- Comparative Fit Index (CFI): .945 – .978 (surpassing the recommended .95 benchmark).
- Tucker-Lewis Index (TLI): .938 – .971.
- Standardized Root Mean Square Residual (SRMR): .035 – .049 (indicating minimal residual discrepancy).
10. Instrument / Measurement Tool
- Instrument Designation: Peer-to-Peer Accommodation Adoption Scale (P2PAAS)
- Diagnostic Classification: Psychometric Self-Report Behavioral Motivation and Intention Inventory
- Measurement Paradigm: Multi-attribute cognitive and affective assessment based on Likert psychometrics
- Item Count: 16 to 22 core manifest items (depending on whether Platform Trust is embedded or analyzed as an antecedent variable)
- Administration Format: Standardized paper-and-pencil or self-administered Computer-Assisted Web Interview (CAWI)
- Estimated Administration Duration: 5 to 8 minutes
- Response Modality: 7-Point Likert-Type Rating Scale:
- 1 = Strongly Disagree
- 2 = Disagree
- 3 = Somewhat Disagree
- 4 = Neutral (Neither Agree nor Disagree)
- 5 = Somewhat Agree
- 6 = Agree
- 7 = Strongly Agree
- Scoring and Computational Procedures:
- Subscale-specific scores are derived by calculating the unweighted arithmetic mean of the items loading onto each respective dimension.
- Alternatively, latent variable scores can be calculated using standardized factor score coefficients extracted from Confirmatory Factor Analysis (CFA).
- No reverse-coded items are present in the standard original index, simplifying survey administration and data processing.
- Higher mean subscale scores reflect elevated motivational prioritization within that specific functional or experiential domain.
11. Permissions & Fee and Test Year
The foundational research detailing the development and validation of the Peer-to-Peer Accommodation Adoption Scale was published in 2015–2016 by Dr. Iis P. Tussyadiah and Dr. Juho Pesonen in leading academic outlets, notably the Journal of Travel Research.
The scale items, theoretical frameworks, and psychometric structures are protected under standard academic copyright laws held by the original authors and the corresponding journal publishers (SAGE Publications). However, under scholarly fair-use conventions, the instrument may be utilized freely without licensing fees by academic researchers, doctoral candidates, and educators for non-commercial scientific research, provided that formal citation of the original source articles is explicitly documented.
Commercial enterprises, market intelligence agencies, or private hospitality analytics firms intending to integrate the scale into proprietary business software, fee-based consumer surveys, or commercial consulting frameworks must seek formal permission and clear licensing terms with the copyright holders and publishers.
12. References
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
- Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597–606. https://doi.org/10.1086/222355
- Tussyadiah, I. P. (2015). An exploratory study on drivers and deterrents of collaborative consumption in travel. In I. Tussyadiah & A. Inversini (Eds.), Information and Communication Technologies in Tourism 2015 (pp. 347–359). Springer. https://doi.org/10.1007/978-3-319-14343-9_26
- Tussyadiah, I. P., & Pesonen, J. (2016). Impacts of peer-to-peer accommodation use on travel patterns. Journal of Travel Research, 55(8), 1022–1040. https://doi.org/10.1177/0047287515608505
- Tussyadiah, I. P., & Pesonen, J. (2018). Drivers and barriers of peer-to-peer accommodation adoption. Journal of Travel & Tourism Marketing, 35(6), 703–717. https://doi.org/10.1080/10548408.2017.1410952
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540