Destination Image, Sport Event Image, and Intention to Recommend–Model Inventory

1. Abstract

The Destination Image, Sport Event Image, and Intention to Recommend—Model Inventory (Hautbois, Liu, & Djaballah, 2023) is a comprehensive psychometric assessment instrument developed to evaluate sports spectators’ multidimensional cognitive and affective appraisals of host destination cities, their perceptions of sporting event brand equity, immediate visitor satisfaction, and behavioral intentions regarding word-of-mouth recommendations. Constructed within the empirical context of major international sports competitions—specifically tested during the UEFA Euro 2016 tournament across medium-scale host cities in France—the scale addresses a critical intersection between sports management, destination marketing, and consumer psychology. The initial measurement development process was grounded in an extensive multidisciplinary literature review, generating a preliminary item pool of 36 indicators adapted from foundational frameworks in tourism destination branding (e.g., Echtner & Ritchie, 1993) and sport event consumer behavior (e.g., Hallmann & Breuer, 2010). Following systematic expert content review, semantic refinement, and psychometric pruning, the final inventory settled on a robust 30-item architecture spanning multiple distinct subscales: affective city image, tourism atmosphere, tourism infrastructure, tourism attractions, event atmosphere, event quality, tourist satisfaction, and event recommendation.

Psychometric evaluations demonstrate excellent empirical validity and reliability. Exploratory factor analysis (EFA) with principal component extraction identified a five-factor structure for the 19 destination image indicators explaining 65.023% of total variance, alongside a two-factor structure for the 9 sport event image items. Confirmatory factor analysis (CFA) cross-validated the global measurement model, yielding robust goodness-of-fit indices (χ² = 113.354, df = 38, p < .01, χ²/df = 2.983, Normed Fit Index [NFI] = .943, Comparative Fit Index [CFI] = .960, and Root Mean Square Error of Approximation [RMSEA] = .078) following the deletion of problematic low-loading items. Convergent validity was established across all latent constructs, with Composite Reliability (CR) exceeding .70 and Average Variance Extracted (AVE) values surpassing the .50 benchmark. Discriminant validity met the rigorous criteria established by Fornell and Larcker (1981), with all squared inter-construct correlations falling below their respective AVE estimates. Internal consistency reliability across all domains proved exemplary, displaying Cronbach’s alpha values consistently exceeding the .70 threshold. Available in French and English, the inventory represents a vital operational tool for researchers examining destination brand equity, event leveraging, and spectator post-consumption behavioral loyalty.

2. Keywords

Destination Image, Sport Event Image, Intention to Recommend, Mega-Sporting Events, Event Satisfaction, Consumer Behavior, Tourism Infrastructure, Affective Destination Image, Confirmatory Factor Analysis, Structural Equation Modeling, Sports Tourism, Brand Equity, Word-of-Mouth Intentions, Host City Branding, Psychometrics

3. Authors

The Destination Image, Sport Event Image, and Intention to Recommend—Model Inventory was conceptualized and empirically validated by a team of leading scholars in sports management, economics, and tourism marketing:

• Christopher Hautbois, Ph.D. — Affiliated with the Université Paris-Saclay, Complexité, Innovations, Activités Motrices et Sportives (CIAMS), Orsay, France. Dr. Hautbois specializes in sports marketing, municipal sports policies, destination branding, and the territorial impact of sporting events.
• Dongfeng Liu, Ph.D. (Corresponding Author) — Affiliated with the School of Economics and Management at Shanghai University of Sport, Shanghai, China (Postal Code: 200438; Email: [email protected]). Dr. Liu’s research focuses on sport event tourism, mega-event legacy, consumer perceptions, and destination economic development.
• Mathieu Djaballah, Ph.D. — Affiliated with the Université Paris-Saclay, CIAMS, Orsay, France. Dr. Djaballah’s scholarship investigates the governance of major sport events, organizational dynamics in public sport services, and consumer evaluative judgments.

4. Purpose

Major and mega-sporting events, such as the Olympic Games, the FIFA World Cup, and the UEFA European Championship, are globally recognized as catalytic instruments for regional economic transformation, public infrastructure modernization, and place branding. However, hosting such tournaments demands substantial capital allocation from regional and national public authorities. Consequently, municipal stakeholders, event organizing committees, and academic researchers increasingly require standardized, psychometrically validated instruments to quantify how effectively host cities leverage these events to foster durable, positive consumer attitudes, visitor satisfaction, and long-term tourism loyalty.

The primary purpose of the Destination Image, Sport Event Image, and Intention to Recommend—Model Inventory is to provide a psychometrically rigorous, holistic framework that quantifies how sports spectators perceive both the physical and emotional attributes of host cities, how those perceptions interact with their appraisals of the event itself, and how these joint cognitive-affective evaluations shape behavioral intentions. Historically, measurement tools within sport management often isolated the sports event experience (e.g., stadium servicescape, athletic drama, operational logistics) from the geographical and cultural milieu in which the tournament was embedded. Conversely, traditional destination marketing scales frequently overlooked the dynamic, high-arousal environment characteristic of temporary, high-profile sporting competitions. This inventory bridges that conceptual gap by unifying place perception and event brand equity into an integrated structural measurement paradigm.

In applied research and organizational contexts, this instrument serves multiple distinct purposes:

• Quantifying Image Spillover and Synergies: The inventory permits researchers and event strategists to dissect the reciprocal image transfer (or “co-branding spillover”) that transpires between the sporting competition brand equity and the municipal brand equity of the host territory.
• Diagnostic Benchmarking for Host Municipalities: Medium-scale and emerging urban centers frequently struggle to stand out alongside primary global metropolises. This inventory affords municipal marketing directorates a diagnostic tool to evaluate specific structural dimensions (such as public transit accessibility, hotel hospitality, tourist attractions, and civic ambiance) that drive or hinder spectator satisfaction.
• Predictive Modeling of Post-Consumption Word-of-Mouth: Word-of-mouth (WOM) and electronic word-of-mouth (eWOM) recommendations are among the most influential behavioral outcomes determining subsequent tourism inflows. The scale operationalizes intention to recommend as a distinct endogenous criterion variable, enabling structural path modeling that identifies which specific experiential levers (e.g., event quality vs. urban atmosphere) exert the strongest direct and indirect effects on consumer advocacy.
• Longitudinal and Cross-City Comparative Analysis: Because the tool separates stable infrastructure dimensions from volatile affective responses, it can be deployed longitudinally across pre-event, in-event, and post-event phases to evaluate enduring brand legacy impacts, or cross-sectionally across multiple host cities to benchmark operational performance.

5. Psychological Construct

The theoretical architecture of the inventory is grounded in multi-attribute attitude theory, environmental psychology, and consumer brand equity models. Consumer evaluations of multi-faceted leisure experiences are conceptualized not as unidimensional impressions, but as hierarchical, multi-tiered constellations comprising cognitive assessments, affective sentiments, cumulative satisfaction appraisals, and conative behavioral loyalty. The inventory structures these phenomena into distinct, interconnected psychological constructs:

Destination Image Dimensions

Destination image has long been defined in consumer psychology as the sum of beliefs, ideas, and impressions that an individual holds regarding a geographic entity. The inventory delineates this macro-construct into four empirical dimensions:

• Affective City Image: Reflects the respondent’s emotional and sensory valence toward the host city. Rooted in Russell’s (1980) circumplex model of affect, this construct assesses whether the urban environment is perceived as pleasant, stimulating, welcoming, vibrant, or relaxing. Rather than measuring objective urban facts, it measures the emotional resonance evoked by the destination’s social fabric.
• Tourism Atmosphere: Pertains to the intangible, ambient qualities of the host location during the staging of the tournament. This includes street vitality, local resident hospitality, celebratory public energy, safety, and the cultural festivity that permeates public squares, fan zones, and commercial districts.
• Tourism Infrastructure: Represents the functional, tangible cognitive sub-dimension of destination image. It evaluates the perceived adequacy, convenience, efficiency, and cleanliness of public transportation networks, commercial accommodation, pedestrian connectivity, retail services, and informational accessibility throughout the host municipality.
• Tourism Attractions: Captures the cognitive appraisal of the city’s leisure portfolio, historical landmarks, architectural heritage, cultural venues, gastronomy, and scenic landmarks. It measures the extent to which the host destination provides a compelling, independent tourism value proposition beyond the athletic tournament itself.

Sport Event Image Dimensions

Sport event image encompasses the symbolic, functional, and experiential associations linked to the tournament brand in the consumer’s memory network. The inventory conceptualizes event image across two foundational operational pillars:

• Event Quality: Reflects the functional and operational excellence of the sporting spectacle. This comprises venue modernity, spectator viewing angles, audiovisual presentations, digital integration, scheduling precision, ticketing logistics, security protocols, and the athletic standard of the competition.
• Event Atmosphere: Captures the collective emotional contagion, fan camaraderie, acoustic energy, competitive tension, and celebratory fervor inside the competition stadium. This experiential dimension addresses the hedonic, emotional arousal derived from co-present spectator interaction.

Tourist Satisfaction

Tourist satisfaction is conceptualized through the lens of Oliver’s (1980) expectancy-disconfirmation theory. It measures the spectator’s cumulative psychological state resulting from the overall consumption encounter. It assesses whether the holistic visit met or exceeded prior expectations, eliciting a cognitive-affective summary state of pleasure, value congruence, and personal fulfillment regarding the trip to the host locality.

Event Recommendation

Event recommendation represents the conative, behavioral intention dimension within the classic hierarchy of effects model (Cognition → Affect → Conation). It measures the active propensity of spectators to disseminate positive interpersonal word-of-mouth, advocate for the event among peers, and encourage future attendance at subsequent editions of the mega-event or follow-up visits to the host destination.

6. Theoretical Framework

The Destination Image, Sport Event Image, and Intention to Recommend—Model Inventory is underpinned by three foundational paradigms in cognitive psychology, marketing, and sociology: Associative Network Theory, Cognitive-Affective-Conative Hierarchy, and Co-Branding / Spillover Theory.

Associative Network Theory of Memory

According to John Anderson’s (1983) ACT* model of human cognition and Kevin Lane Keller’s (1993) customer-based brand equity (CBBE) framework, human memory consists of an associative network of nodes interconnected by informational links. When applied to sports tourism, the host city and the sporting event represent two distinct conceptual nodes in the consumer’s cognitive memory bank. Prior to the event, each node possesses its own pre-existing informational associations (e.g., historical reputation, perceived safety, brand prestige). When an individual attends a mega-sporting event staged within a specific host city, simultaneous activation of these memory nodes establishes new associative neural pathways, causing attributes from one node to “spread” and color evaluations of the other.

Cognitive-Affective-Conative Attitude Theory

The inventory operationalizes the tri-component model of attitudes articulated by Fishbein and Ajzen (1975). In this progression, cognitive beliefs serve as the foundational perceptual input:

1. Cognitive Appraisal: Spectators first evaluate tangible operational characteristics—such as transportation infrastructure, physical attractions, and event operational quality.
2. Affective Response: These cognitive evaluations inform emotional and atmospheric appraisals, synthesizing into feelings of pleasure, excitement, and overall tourist satisfaction.
3. Conative Intentions: Positive affective states subsequently induce behavioral loyalty, manifested as the intention to recommend the event and destination to prospective travelers.

By mapping each item cluster to this sequence, the inventory allows researchers to evaluate whether structural infrastructure failures inhibit affective enjoyment, and whether hedonic stadium atmosphere can overcome deficits in civic urban services.

Brand Spillover and Co-Branding Dynamics

Mega-sporting events function as mega-event alliances or co-branding arrangements between the organizing governing body (e.g., UEFA, IOC) and the host municipal government. Signaling theory indicates that consumers use perceived brand quality in one domain to infer unobservable attributes in another. For medium-scale host cities with limited international visibility, hosting a world-class tournament serves as an institutional endorsement of modern infrastructure and urban safety. Conversely, exceptional urban hospitality and tourism heritage enhance the contextual perceived value of the sporting competition. The inventory’s structural framework models these reciprocal dynamics empirically.

7. Validity

The psychometric validity of the instrument was rigorously evaluated during its initial validation study involving international and domestic stadium spectators attending matches during the UEFA Euro 2016 tournament across regional host cities in France. The authors implemented a comprehensive multi-phase validation protocol encompassing content validity, construct validity, convergent validity, and discriminant validity.

Content and Face Validity

Initial content validity was established through an exhaustive deductive review of foundational literature in tourism destination modeling (e.g., Baloglu & McCleary, 1999; Echtner & Ritchie, 1993) and sport event management (e.g., Hallmann & Breuer, 2010; Kaplanidou & Vogt, 2007). An initial pool of 36 prospective items was reviewed by a panel of academic experts specializing in sports marketing and psychometric survey design. The panel assessed item clarity, theoretical alignment, linguistic neutrality across both French and English translations, and face validity. Substandard, double-barreled, or ambiguous indicators were revised or eliminated prior to field administration.

Construct and Convergent Validity

Construct validity was demonstrated through exploratory and confirmatory factor modeling. Convergent validity, which gauges the degree to which individual indicators effectively converge upon their shared latent construct, was systematically appraised through two statistical criteria:

• Composite Reliability (CR): Every latent construct demonstrated a Composite Reliability coefficient substantially higher than the widely accepted psychometric threshold of .70 (Bagozzi & Yi, 1988), indicating that the indicators consistently represent their latent targets.
• Average Variance Extracted (AVE): The Average Variance Extracted for each latent dimension exceeded the recommended benchmark of .50 (Fornell & Larcker, 1981). This establishes that each latent construct accounted for more than 50% of the variance observed across its assigned measurement items, rather than being dominated by random measurement error.

Discriminant Validity

Discriminant validity confirms that each latent dimension represents a psychologically distinct construct that is not empirically redundant with other dimensions in the structural system. The researchers applied the stringent Fornell–Larcker criterion, which dictates that the squared inter-construct correlation (φ²) between any pair of latent constructs must be strictly lower than the Average Variance Extracted (AVE) of each individual construct.

Statistical testing confirmed that this condition was satisfied across all model pairs. Even between the two most highly correlated latent dimensions—Event Image and Event Recommendation, which displayed a Pearson correlation of r = .831 (squared correlation = .691)—the respective AVE values remained higher than this shared variance figure. This outcome statistically confirms that spectator perceptions of the event’s brand identity remain conceptually and empirically differentiated from their conative willingness to recommend attendance to others.

8. Reliability

Reliability refers to the internal consistency, stability, and repeatability of a psychometric instrument. The Destination Image, Sport Event Image, and Intention to Recommend—Model Inventory was subjected to rigorous internal consistency assessments across all latent dimensions.

Internal Consistency Reliability

Internal consistency was calculated utilizing Cronbach’s alpha (α) for each extracted subscale. In psychometric research, values of α ≥ .70 reflect acceptable reliability, α ≥ .80 indicate good reliability, and α ≥ .90 indicate excellent internal consistency (Nunnally & Bernstein, 1994). In the validation study by Hautbois, Liu, and Djaballah (2023), every latent factor exceeded the standard .70 cut-off, confirming that items within each factor measure a homogeneous psychological construct.

Furthermore, Composite Reliability (CR) scores calculated within the structural equation modeling framework provided additional proof of internal consistency without relying on the assumption of tau-equivalence (which assumes equal item factor loadings). The calculated CR parameters across destination image dimensions (affective city image, tourism atmosphere, tourism infrastructure, tourism attractions), event image dimensions (event quality, event atmosphere), tourist satisfaction, and event recommendation all surpassed .70, demonstrating that the measurement model exhibits strong internal coherence across its subscales.

Measurement Invariance and Multilingual Equivalence

The survey instrument was made available to stadium spectators in both French and English to accommodate international sports travelers and domestic attendees. Semantic equivalence was maintained through standard forward-and-back translation procedures. Cross-language item performance demonstrated consistent factor loading patterns, indicating that the cognitive interpretation of the subscales remained invariant across different linguistic groups.

9. Factor Analysis

The underlying factor structure of the inventory was determined using a rigorous two-step statistical procedure: Exploratory Factor Analysis (EFA) to discover the underlying dimensionality of newly combined indicator sets, followed by Confirmatory Factor Analysis (CFA) within a structural equation modeling environment to test model fit.

Exploratory Factor Analysis (EFA)

Principal Component Analysis (PCA) with orthogonal/oblique rotations was conducted separately on the destination image and sport event image indicator pools to examine their underlying factor structures:

• Destination Image Factor Structure: Following the iterative deletion of cross-loading and weakly performing items, 19 indicators assessing destination image loaded cleanly onto five distinct factors with eigenvalues greater than 1.0. These five factors collectively explained 65.023% of the total variance, demonstrating a highly satisfactory capture of the destination image domain. The factors reflected affective city image, tourism atmosphere, tourism infrastructure, tourism attractions, and destination amenities.
• Sport Event Image Factor Structure: The 9 indicators assessing sport event image resolved cleanly into two primary factors with eigenvalues exceeding 1.0, accounting for substantial variance and dividing into Event Atmosphere and Event Quality.

Confirmatory Factor Analysis (CFA) and Model Pruning

Following initial exploratory modeling, a global Confirmatory Factor Analysis was conducted using maximum likelihood estimation to test the structural integrity of the integrated measurement model. In the initial full CFA run, the goodness-of-fit was acceptable; however, detailed inspection of factor loadings revealed that items related to price-value perception (pricing) and one specific item measuring tourist satisfaction demonstrated standardized factor loadings below the established .60 threshold.

In accordance with psychometric purification standards (Hair et al., 2010), these low-performing items were systematically excised, and the CFA model was re-estimated. The resulting refined measurement model showed marked improvements in overall goodness-of-fit, displaying exceptional statistical metrics:

• Chi-Square (χ²): 113.354
• Degrees of Freedom (df): 38
• Significance Level: p < .01
• Normed Chi-Square (χ²/df): 2.983 (comfortably below the standard ≤ 3.0 or ≤ 5.0 cut-offs indicating good fit)
• Normed Fit Index (NFI): .943 (exceeding the ≥ .90 threshold)
• Comparative Fit Index (CFI): .960 (exceeding the rigorous ≥ .95 standard for superior fit)
• Root Mean Square Error of Approximation (RMSEA): .078 (within the acceptable threshold of ≤ .08)

All remaining standardized factor loadings in the pruned model were statistically significant (p < .001) and exceeded .60, confirming strong structural validity.

10. Instrument / Measurement Tool

The operational specifications of the Destination Image, Sport Event Image, and Intention to Recommend—Model Inventory are outlined below:

• Test Type: Original psychometric inventory / multi-construct self-report questionnaire.
• Administration Format: Paper-and-pencil stadium intercept survey; adaptable for digital mobile survey administration via QR codes or post-event online distribution.
• Item Count: 30 items in the comprehensive empirical model (pruned from a 36-item exploratory pool).
• Response Format: Multi-point Likert scale (typically a 5-point or 7-point scale anchored from 1 = Strongly Disagree to 5/7 = Strongly Agree; affective image subscales may employ semantic differential anchors such as Unpleasant—Pleasant, Boring—Exciting, Stressful—Relaxing).
• Target Population: Human adults (≥ 18 years), including young adults (18–29), individuals in their thirties (30–39), and middle-aged/older adults (≥ 40) attending live sports competitions. Applicable to both local residents and traveling domestic/international tourists.
• Languages Available: English, French (empirically validated in both languages).
• Administration Time: Approximately 8 to 12 minutes to complete all sections.
• Scoring Guidelines: Subscale scores are calculated by averaging the numerical responses of the retained items within each verified dimension. No reverse-scored items are present in the final validated model. Higher composite scores represent more favorable destination perceptions, superior perceived event operational quality, higher satisfaction, and stronger word-of-mouth recommendation intentions.

11. Permissions & Fee and Test Year

• Test Year: 2023 (developed from research conducted during and following the UEFA Euro 2016 tournament).
• Copyright & Ownership: Christopher Hautbois, Dongfeng Liu, and Mathieu Djaballah. Published by Cognizant Communication Corporation in Event Management.
• Fee: Free of charge for non-commercial academic research, pedagogical use, and non-profit scientific inquiry.
• Permissions Information: Researchers wishing to utilize, reproduce, translate, or adapt the inventory for scholarly or commercial empirical studies must contact the corresponding author, Dr. Dongfeng Liu ([email protected]), or contact the journal publisher (Cognizant Communication Corporation) for formal permissions.

12. References

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13. Items of the Scale