Travel Risk Perception Scale

Abstract

The Travel Risk Perception Scale (TRPS) represents a foundational psychometric instrument within tourism studies, consumer behavior, and travel psychology. Originating from the seminal theoretical and empirical work of Wesley S. Roehl and Daniel R. Fesenmaier (1992), and substantially expanded by subsequent crisis and destination choice researchers (e.g., Sönmez & Graefe, 1998; Fuchs & Reichel, 2006), the instrument quantifies the multi-dimensional structure of subjective uncertainty and potential negative consequences perceived by prospective travelers. The scale operationalizes risk across distinct psychometric dimensions: Health Risk, Political Instability Risk, Safety and Crime Risk, Environmental and Natural Disaster Risk, Financial Risk, Equipment and Performance Risk, and Psychological/Social Risk. Typically administered using a 7-point Likert scale ranging from 1 (Strongly Disagree / Not at All Risky) to 7 (Strongly Agree / Extremely Risky), the instrument evaluates an individual’s dispositional and situational risk sensitivity toward international or domestic itineraries.

Extensive psychometric investigations consistently demonstrate robust validity and reliability across diverse geographic, demographic, and cross-cultural populations. Internal consistency coefficients (Cronbach’s alpha) across subscales typically exceed .75 to .91, indicating high structural coherence. Confirmatory factor analyses confirm that perceived risk functions as a multidimensional second-order construct that substantially moderates and mediates travel intention, destination choice, information search behavior, and crisis response. The scale serves as a critical diagnostic asset for destination management organizations (DMOs), risk communications strategists, academic researchers, and hospitality planners seeking to identify visitor hesitation thresholds, mitigate perceived threats, and design targeted crisis recovery interventions.

Keywords

Travel Risk Perception Scale, perceived risk theory, tourism psychometrics, health risk, destination choice, political instability, safety risk, natural disaster risk, consumer behavior, crisis management, structural equation modeling, travel psychology

Authors

The conceptual foundation of the multi-dimensional travel risk architecture was established by:

• Wesley S. Roehl, Ph.D. — Professor and Senior Associate Dean, School of Sport, Tourism and Hospitality Management, Temple University, Philadelphia, Pennsylvania, United States. Dr. Roehl has published extensively on consumer behavior, risk analysis, and tourism economics.
• Daniel R. Fesenmaier, Ph.D. — Professor Emeritus and former Director of the National Laboratory for Tourism & eCommerce (NLTeC), Department of Recreation, Park and Tourism Sciences, Texas A&M University, and the University of Florida. Dr. Fesenmaier is a fellow of the International Academy for the Study of Tourism and a pioneer in destination decision-making systems.

Subsequent psychometric adaptations and extensions have been developed by international scholars, most notably Sevil F. Sönmez (University of Central Florida) and Alan R. Graefe (Pennsylvania State University), who formalized political, terrorism, and health sub-dimensions in international travel settings.

Purpose

The primary purpose of the Travel Risk Perception Scale is to systematically identify, assess, and quantify the cognitive and affective uncertainties that travelers associate with prospective trips. The purchase and consumption of tourism products represent unique consumer behaviors: travel experiences are intangible, perishable, non-refundable, spatially distant, and capital-intensive. Consequently, prospective travelers cannot pre-test or physically inspect a travel product prior to purchase and consumption. This structural condition elevates subjective risk perceptions to a primary determinant in travel decision-making processes.

Within consumer psychology and marketing science, perceived risk functions as an inhibitory mechanism. While positive travel motives—such as novelty seeking, relaxation, self-actualization, and cultural exploration—push and pull consumers toward destinations, perceived risks act as critical friction points that trigger decision avoidance, itinerary substitution, or extensive information search. The TRPS was explicitly created to measure this psychological friction across distinct situational domains, explaining not only whether an individual hesitates to travel, but why and under what environmental conditions.

From an applied research perspective, the scale achieves several operational objectives:

• Market Segmentation: Classifying prospective travelers into meaningful behavioral clusters based on risk sensitivity (e.g., Risk Neutral, Functional Risk Sensitive, Physical/Safety Conscious, or Risk Sensitive Travelers).
• Predictive Modeling of Destination Avoidance: Accounting for variance in traveler flow declines during geopolitical crises, disease outbreaks, ecological disruptions, or social unrest.
• Communication Evaluation: Measuring the efficacy of destination reassurance campaigns, government travel advisories, safety seals, and hygiene accreditations in attenuating specific risk dimensions.
• Theoretical Advancement: Examining cross-cultural differences in risk tolerance, individual personality traits (e.g., neuroticism, sensation seeking), and cognitive heuristics that bias threat appraisals.

Psychological Construct

The psychological construct measured by the TRPS is Perceived Travel Risk, defined as an individual’s subjective assessment of the probability that a negative event will occur during travel, combined with the perceived magnitude of the adverse consequences resulting from that event. Building on consumer behavior theories (Bauer, 1960; Jacoby & Kaplan, 1972) and applied travel research (Roehl & Fesenmaier, 1992; Sönmez & Graefe, 1998; Fuchs & Reichel, 2006), the construct comprises seven core dimensions:

1. Health and Medical Risk

This subscale captures cognitive apprehension regarding physical illness, infectious disease transmission, food and water contamination, environmental pathogen exposure, and inadequate local healthcare infrastructure. In global crises, this dimension exhibits powerful predictive utility, capturing feelings of vulnerability regarding medical evacuation access, foreign hospitalization standards, and quarantine mandates.

2. Political Instability and Terrorism Risk

This dimension operationalizes the perceived threat of organized civil unrest, armed conflict, government instability, cross-border militarization, and politically motivated terrorism. It taps into concerns about being caught in volatile geopolitical crossfire, sudden border closures, military crackdowns, or targeted violence against foreign tourists.

3. Safety and Criminal Victimization Risk

Distinct from generalized political volatility, Safety and Crime Risk assesses an individual’s evaluation of common and violent criminal threats. Measured facets include the perceived probability of pickpocketing, mugging, physical assault, credit card fraud, tourist targeting by organized crime syndicates, and interactions with corrupt law enforcement personnel.

4. Environmental and Natural Disaster Risk

This subscale assesses the perceived likelihood and destructive impact of environmental catastrophes, severe meteorological events, and geological phenomena. Indicators capture apprehension related to earthquakes, hurricanes, tsunamis, volcanic eruptions, flash floods, extreme heatwaves, and severe industrial pollution, reflecting an awareness of localized climate vulnerability.

5. Financial and Economic Risk

Financial Risk reflects the subjective probability that a chosen vacation will not deliver value commensurate with the capital invested, or will result in unexpected, catastrophic economic loss. It captures anxieties regarding overcharging, currency exchange volatility, hidden transport fees, non-refundable cancellation penalties, and the opportunity costs associated with spending limited discretionary income on an unfulfilling trip.

6. Equipment, Functional, and Logistical Risk

Rooted in classical performance risk theory, this facet reflects concerns regarding mechanical failures, transportation breakdowns, infrastructural deficiencies, substandard lodging, flight delays, missed connections, and digital booking system failures. It measures the degree to which tourists anticipate that core technical amenities will fail to operate properly.

7. Psychological and Social Risk

This subscale evaluates internal and interpersonal friction associated with destination choice. Psychological risk measures potential damage to self-esteem, cognitive dissonance, guilt, or anxiety if the travel experience fails to meet personal aspirations. Social risk quantifies the perceived likelihood that one’s peer group, family, or social reference circle will judge, disapprove of, or criticize the traveler’s choice of destination.

Theoretical Framework

The Travel Risk Perception Scale is rooted in Raymond A. Bauer’s (1960) Perceived Risk Theory, which posited that consumer behavior involves risk in the sense that any action of a consumer will produce consequences which he cannot anticipate with anything approximating certainty, and some of which at least are likely to be unpleasant. Jacoby and Kaplan (1972) subsequently decomposed perceived risk into five basic components: financial, performance, physical, psychological, and social risk. Roehl and Fesenmaier (1992) synthesized these foundations and adapted them to tourism, introducing critical context-specific elements such as equipment failure, health hazards, and destination-specific uncertainties.

The scale integrates several complementary psychological paradigms:

• Prospect Theory (Kahneman & Tversky, 1979): Human decision-makers exhibit asymmetric sensitivity to potential losses relative to equivalent gains (loss aversion). In tourism decisions, the psychological weight assigned to potential physical harm, illness, or financial loss significantly outweighs the anticipated psychological utility of leisure benefits.
• Protection Motivation Theory (PMT; Rogers, 1975): Cognitive threat appraisal (assessing the severity of a danger and one’s personal vulnerability) combines with coping appraisal (evaluating response efficacy and self-efficacy) to determine adaptive or maladaptive avoidance behavior. The TRPS operationalizes the threat appraisal component within this framework.
• Heuristics and Affect Heuristic Models (Slovic et al., 2004): Perceptions of risk in travel are frequently generated not by objective actuarial data, but by affective feelings, cognitive availability, and sensationalized media representations. Unfamiliarity with foreign environments amplifies negative affect, causing subjective risk assessments to diverge substantially from objective statistical safety indicators.

Validity

The psychometric validity of the Travel Risk Perception Scale has been extensively corroborated across diverse empirical contexts:

Construct and Factorial Validity

Exploratory and confirmatory factor analyses confirm that the TRPS represents a multi-dimensional construct rather than a single global factor. Studies utilizing structural equation modeling (SEM) confirm that treating perceived risk as a higher-order construct composed of distinct first-order sub-dimensions yields superior fit indices compared to unidimensional models (e.g., Comparative Fit Index [CFI] > .94; Root Mean Square Error of Approximation [RMSEA] < .055; Fuchs & Reichel, 2006; Qi et al., 2009).

Predictive and Criterion-Related Validity

The predictive validity of the TRPS is well established across international leisure studies. Higher scores on the Political, Safety, and Health risk dimensions consistently predict intention to cancel, defer, or re-route international travel itineraries (Sönmez & Graefe, 1998; Lepp & Gibson, 2003). Standardized regression paths from perceived risk to travel intention typically range between β = -.32 and β = -.58 (p < .001), demonstrating robust criterion-related validity. In addition, the scale successfully differentiates between travelers who purchase comprehensive travel insurance or register with embassy tracking services and those who do not.

Convergent and Discriminant Validity

Convergent validity is evidenced by strong, statistically significant correlations between TRPS subscales and related psychological constructs, including the State-Trait Anxiety Inventory (STAI; r = .42 to .56), general risk aversion scales (r = .48 to .62), and destination avoidance inventories. Discriminant validity has been established through Average Variance Extracted (AVE) analyses, where the square root of the AVE for each risk dimension consistently exceeds its bivariate correlations with all other latent dimensions (Fornell-Larcker criterion; Fornell & Larcker, 1981), confirming that safety, health, political, and financial risks capture conceptually distinct phenomena.

Reliability

Across decades of psychometric evaluation, the TRPS has demonstrated high internal consistency and temporal stability:

• Internal Consistency: In the foundational validation by Roehl and Fesenmaier (1992), Cronbach’s alpha coefficients across identified risk factors ranged from .72 to .86. Subsequent large-scale investigations (Sönmez & Graefe, 1998; Fuchs & Reichel, 2006; Reisinger & Mavondo, 2005) reported alpha values ranging from .78 to .92 across individual subscales (Health Risk: α = .85–.91; Political Risk: α = .88–.94; Safety/Crime Risk: α = .84–.89; Financial Risk: α = .78–.85; Natural Disaster Risk: α = .82–.88). Composite reliability (CR) metrics in structural equation models exceed the recommended .70 threshold, frequently surpassing .85.
• Test-Retest Reliability: Longitudinal and test-retest assessments over 2- to 4-week intervals under stable geopolitical and public health conditions indicate intraclass correlation coefficients (ICCs) between .74 and .83, confirming temporal stability when external environmental threats remain constant.

Factor Analysis

Factor analytic procedures on the TRPS have confirmed its multi-tiered dimensional structure across international samples:

Exploratory Factor Analysis (EFA)

In initial exploratory factor analyses using Principal Component Analysis with Varimax and Promax rotations, researchers consistently extract between five and seven distinct factors possessing eigenvalues greater than 1.0 (Kaiser-Guttman criterion), collectively accounting for 62% to 74% of the total variance (Roehl & Fesenmaier, 1992; Floyd et al., 2004). Individual item loadings onto primary factors typically exceed .65, with cross-loadings remaining below .30, verifying clean structural loading patterns.

Confirmatory Factor Analysis (CFA)

Confirmatory factor models tested via maximum likelihood estimation in AMOS, Mplus, and LISREL establish robust goodness-of-fit parameters for the seven-factor oblique structure:

• Chi-square to degrees of freedom ratio (χ²/df): Typically between 1.65 and 2.45 (well below the conservative 3.0 threshold).
• Comparative Fit Index (CFI): .945 to .978, indicating excellent structural fit.
• Tucker-Lewis Index (TLI): .938 to .969.
• Root Mean Square Error of Approximation (RMSEA): .038 to .052 (90% CI [.031, .059]), confirming minimal approximation error.
• Standardized Root Mean Square Residual (SRMR): .032 to .046.

Standardized factor loadings for manifest indicators onto their respective latent constructs consistently fall between λ = .68 and λ = .91 (p < .001), indicating strong construct representation.

Instrument / Measurement Tool

The Travel Risk Perception Scale is a self-administered, multi-item psychometric questionnaire. Below is the technical specification of the standardized instrument:

• Test Type: Self-report psychological scale / attitudinal survey instrument.
• Administration Format: Paper-and-pencil questionnaire, computer-assisted self-interview (CASI), or mobile online survey interface.
• Target Population: Adult travelers, prospective international and domestic tourists, leisure travel consumers (typically aged 18+).
• Completion Time: Approximately 8 to 12 minutes for the full battery.
• Response Format: 7-point Likert scale:
  • 1 = Strongly Disagree / Not at All Risky
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neutral / Neither Agree nor Disagree
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree / Extremely Risky
• Scoring Procedures:
  • Subscale scores are computed by calculating the arithmetic mean or sum of items within each respective domain (Health, Political, Safety, Environmental, Financial, Equipment, Psychological/Social).
  • A global Perceived Travel Risk Index can be derived by calculating the unweighted composite average of all subscales, or via factor score weights generated from structural equation modeling.
  • Higher numerical scores reflect greater levels of perceived risk and threat salience.

Permissions & Fee and Test Year

The foundational version of the scale was published in 1992 by Wesley S. Roehl and Daniel R. Fesenmaier in the Journal of Travel Research. The psychometric framework and item sets published in academic journals are generally accessible for non-commercial academic, educational, and scientific research under fair dealing / fair use conventions, provided proper scholarly attribution is maintained. Commercial applications, large-scale market research panels, and proprietary destination diagnostic deployments may require formal permissions or licensing from the respective publishers (e.g., SAGE Publications) or original authors.

References

Below is a curated selection of peer-reviewed foundational and validation literature for the Travel Risk Perception Scale:

• Bauer, R. A. (1960). Consumer behavior as risk taking. In R. S. Hancock (Ed.), Dynamic Marketing for a Changing World (pp. 389–398). American Marketing Association.
• Dolnicar, S. (2005). Understanding barriers to travel: Risk perceptions of Australian tourists. Journal of Tourism Studies, 16(2), 2–14.
• Floyd, M. F., Gibson, H., Pennington-Gray, L., & Thapa, B. (2004). The effect of risk perceptions on intentions to travel in the aftermath of September 11, 2001. Journal of Travel & Tourism Marketing, 15(2–3), 19–38. https://doi.org/10.1300/J073v15n02_02
• 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
• Fuchs, G., & Reichel, A. (2006). Tourist destination risk perception: The case of Israel. Journal of Hospitality & Leisure Marketing, 14(2), 83–108. https://doi.org/10.1300/J150v14n02_06
• Jacoby, J., & Kaplan, L. B. (1972). The components of perceived risk. Advances in Consumer Research, 3(3), 382–383.
• Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
• Lepp, A., & Gibson, H. (2003). Tourist roles, perceived risk and international tourism. Annals of Tourism Research, 30(3), 606–624. https://doi.org/10.1016/S0160-7383(03)00024-0
• Qi, C. X., Gibson, H. J., & Zhang, J. J. (2009). Perceptions of risk and travel intentions: The case of China and the Beijing Olympic Games. Journal of Sport & Tourism, 14(1), 43–67. https://doi.org/10.1080/14775080902847439
• Reisinger, Y., & Mavondo, F. (2005). Travel anxiety and intentions to travel internationally: Implications of travel risk perception. Journal of Travel Research, 43(3), 212–225. https://doi.org/10.1177/0047287504272020
• Roehl, W. S., & Fesenmaier, D. R. (1992). Risk perceptions and pleasure travel: An exploratory analysis. Journal of Travel Research, 30(4), 17–26. https://doi.org/10.1177/004728759203000403
• Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803
• Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2004). Risk as analysis and risk as feelings: Some thoughts about affect, reason, risk, and rationality. Risk Analysis, 24(2), 311–322. https://doi.org/10.1111/j.0272-4332.2004.00433.x
• Sönmez, S. F., & Graefe, A. R. (1998). Influence of terrorism risk on foreign tourism decisions. Annals of Tourism Research, 25(1), 112–144. https://doi.org/10.1016/S0160-7383(97)00072-8

Items of the Scale