Country-of-Origin Scale (COO-Para) | PsychScales

{n “title”: “Country-of-Origin Scale (COO-Para)”,n “content”: “

1. Abstract

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The Country-of-Origin Scale (commonly designated in psychometric and consumer marketing literature as COO-Para) is an influential, multi-tiered psychometric measurement instrument developed by Ravi Parameswaran and R. Mohan Pisharodi (1992, 1994). Formulated to address critical conceptual and methodological limitations in early international marketing research—most notably the pervasive reliance on single-item indicators and unidimensional constructs of “made-in” labeling—the COO-Para framework models country image as a complex, multidimensional cognitive hierarchy. The instrument distinctly separates general macro-level attitudes toward a foreign nation from mid-level generalized perceptions of products manufactured in that country, as well as concrete, micro-level product-specific evaluations.

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Initially operationalized in 1992 as a 24-item instrument across six oblique latent dimensions, the scale was expanded and refined in 1994 into a 35-item, eight-factor structural model. The structural inventory comprises three core conceptual domains: General Country Attitudes (GCA), assessing perceived national competence, socio-cultural similarity, and global political engagement; General Product Attitudes (GPA), evaluating cross-category product attributes including positive quality, negative attributes (defect proneness), and marketing/distribution capabilities; and Specific Product Attitudes (SPA), an adaptable facet capturing category-contingent performance criteria (such as automotive engineering or consumer electronics reliability). Items are administered via a standardized 10-point semantic differential and Likert-type scale format (anchored from 1 = “Not at all appropriate / Strongly disagree” to 10 = “Most appropriate / Strongly agree”). Across empirical validation studies spanning multiple consumer product categories (e.g., automobiles, blenders) and country profiles (e.g., Germany, South Korea), the scale demonstrated robust construct validity, stable confirmatory factor structures, and internal consistency coefficients ranging from $\alpha = 0.586$ to $\alpha = 0.943$. The COO-Para remains an foundational benchmark for research in international consumer psychology, cross-cultural brand equity, and multinational product positioning.

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2. Keywords

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Country-of-origin effect, COO-Para, consumer psychology, General Country Attitudes, General Product Attitudes, Specific Product Attitudes, cognitive halo effect, summary construct model, psychometric validation, cross-national marketing, brand origin perception, multi-attribute attitude model

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3. Authors

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The Country-of-Origin Scale was conceptualized, operationalized, and psychometrically validated by scholars in international marketing and consumer research at Oakland University:

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• Ravi Parameswaran, Ph.D.: Professor Emeritus of Marketing, Department of Management and Marketing, School of Business Administration, Oakland University, Rochester, Michigan, United States. Dr. Parameswaran has published extensively in the fields of global marketing strategy, international trade perceptions, consumer stereotyping, and quantitative measurement in business research.

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• R. Mohan Pisharodi, Ph.D.: Professor Emeritus of Marketing, Department of Management and Marketing, School of Business Administration, Oakland University, Rochester, Michigan, United States. Dr. Pisharodi’s research centers on supply chain logistics, international buyer behavior, quantitative structural equation modeling, and consumer information processing.

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Correspondence regarding the original developmental studies was historically coordinated through the Department of Management and Marketing, School of Business Administration, Oakland University, Rochester, MI 48309-4401, USA.

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4. Purpose

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For several decades, academic inquiries into the country-of-origin (COO) phenomenon suffered from what psychometricians termed the “unidimensional fallacy.” Early paradigms typically presented participants with a single “Made in [Country]” prompt or measured country image through generic, unstandardized evaluative adjectives (e.g., “good/bad” or “high quality/low quality”). These reductionist methodologies failed to capture the cognitive richness of consumer national schemas, conflated high-level socio-political beliefs with manufacturing competence, and could not account for cross-category discrepancies—such as why consumers might view a nation as exceptionally competent at building complex mechanical goods but deficient in food production or fashion design.

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The primary purpose of the COO-Para instrument is to deliver a theoretically grounded, psychometrically robust, and diagnostic measurement system capable of isolating how distinct layers of country image interact to influence product judgments. Specifically, the scale was created to accomplish three foundational objectives:

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• Hierarchical Disentanglement: To structurally separate an individual’s macro perceptions of a nation’s people, political stance, and economic advancement (GCA) from their aggregate beliefs about products originating from that nation (GPA), and from tangible evaluations of a designated product category (SPA).

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• Cross-National Diagnostic Rigor: To facilitate direct, empirically standardized comparisons between nations with contrasting industrial, developmental, and geopolitical reputations (for example, highly developed economies versus rapidly industrializing newly industrialized countries).

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• Strategic Marketing Utility: To equip multinational corporations, export promotion agencies, and brand strategists with a diagnostic profiling tool capable of identifying whether a product’s market resistance stems from high-level socio-cultural biases, generalized manufacturing skepticism, or category-specific functional deficits.

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In applied consumer psychology and international business research, the COO-Para instrument serves as a core diagnostic tool in experimental designs testing brand-origin congruency, global supply chain transparency, international brand equity dilution, and consumer ethnocentrism. By measuring separate dimensions, investigators can assess whether targeted promotional interventions should seek to alter broad country perceptions or address specific engineering characteristics.

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5. Psychological Construct

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The psychological construct underlying the COO-Para inventory rests on a multi-tiered, hierarchical model of cognitive structure and social stereotyping. The instrument conceptualizes national image as a cognitive network organized into three interconnected tiers comprising eight distinct sub-dimensions:

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Tier 1: General Country Attitudes (GCA)

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General Country Attitudes capture an individual’s macro-level socio-political, economic, and cultural schemata regarding a foreign nation, independent of any immediate product interaction. In the expanded 1994 operationalization, this tier consists of three distinct latent factors:

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• Country Competence (GCA-COMP): Measures cognitive appraisals of a nation’s technical sophistication, industrial modernization, workforce education, economic stability, and scientific standards. For example, respondents evaluate whether citizens of the target nation possess advanced engineering capabilities, high work ethics, and reliable institutional systems.

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• Perceived Similarity (GCA-SIM): Assesses subjective cultural, social, and psychological proximity between the consumer’s home country and the target nation. Grounded in social identity theory, this dimension determines whether individuals view the target country’s cultural values, lifestyle, and social standards as compatible with or alien to their own.

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• Global Political & Economic Engagement (GCA-ENG): Evaluates perceptions of the nation’s participation in international affairs, democratic governance, economic openness, and bilateral diplomatic cooperation. This facet captures whether the foreign country is seen as a responsible global citizen or a protectionist/adversarial state.

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Tier 2: General Product Attitudes (GPA)

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General Product Attitudes represent the mid-level cognitive layer reflecting an individual’s aggregate beliefs about goods and manufacturing outputs originating from the target nation, abstracted across product classes. This tier encompasses three factors:

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• Positive Product Quality (GPA-POS): Captures overarching perceptions of product excellence, prestige, aesthetic refinement, craftsmanship, and enduring performance characteristics across all goods produced by the nation.

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• Negative Product Attributes (GPA-NEG): Explicitly measures perceived liabilities, such as defect rates, unreliability, cheap assembly, high maintenance requirements, and rapid obsolescence. Psychometrically, Parameswaran and Pisharodi established that negative product evaluations do not merely represent the mathematical inverse of positive quality, but form a partially distinct cognitive dimension governed by loss aversion and negativity bias.

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• Distribution and Promotion Capabilities (GPA-DIST): Evaluates consumer beliefs regarding the foreign nation’s commercial sophistication, product availability, dealer network reach, advertising truthfulness, and after-sales service reliability in the domestic marketplace.

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Tier 3: Specific Product Attitudes (SPA)

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Specific Product Attitudes represent the micro-level layer of the construct, operationalizing consumer evaluations of a concrete, designated product category originating from the country in question. Because evaluative criteria naturally vary by engineering complexity and usage context, the SPA tier adapts its indicator items to the category under investigation while preserving consistent latent properties:

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• SPA – High-Involvement / Complex Engineering Goods (e.g., Automobiles): Evaluates category-critical performance attributes such as mechanical reliability, crash safety, fuel economy, advanced electronics, acceleration, and trade-in value.

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• SPA – Low-to-Moderate Involvement Consumer Durables (e.g., Small Appliances / Blenders): Evaluates category-specific operational features including motor longevity, blade sharpness, ease of cleaning, noise levels, and compact counter design.

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This tripartite structural hierarchy ensures that investigators do not treat an individual’s admiration for a nation’s technical infrastructure (GCA) as synonymous with a willingness to endorse its household appliances or industrial machinery (SPA).

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6. Theoretical Framework

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The COO-Para scale is anchored in foundational principles of cognitive psychology, attitude theory, and consumer information processing. In particular, the instrument synthesizes three theoretical paradigms:

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1. The Cognitive Halo versus Summary Construct Model

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In consumer cognitive architecture, country-of-origin cues function through two distinct information-processing mechanisms, as formalized by Min Han (1989):

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• The Halo Model: When consumers possess little direct personal experience or factual knowledge about a nation’s specific products, their broad national image (GCA) functions as an inferential cognitive “halo.” This halo directly shapes general product beliefs (GPA), which subsequently color specific product assessments (SPA) and purchase intent.

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• The Summary Construct Model: As consumers acquire direct experiential familiarity with branded goods from a given country over time, they summarize their concrete evaluations of those products (SPA) into higher-order general product attitudes (GPA) and, ultimately, adjust their overarching country image (GCA).

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By establishing distinct operationalizations for GCA, GPA, and SPA, Parameswaran and Pisharodi created the first psychometric tool capable of empirically testing whether consumers are operating under a halo mechanism, a summary mechanism, or a recursive hybrid processing model.

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2. Fishbein’s Multi-Attribute Attitude Model

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The operational structure of the scale is directly grounded in Fishbein and Ajzen’s multi-attribute attitude model. Under this framework, an overall attitude toward an attitude object is a mathematical function of the strength of an individual’s salient cognitive beliefs about the object’s attributes weighted by the evaluative aspect of those attributes. Parameswaran and Pisharodi argued that general country perceptions serve as external informational belief anchors that modulate the subjective weights consumers assign to specific product attributes.

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3. Categorization and Schema Theory

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Drawing on Eleanor Rosch’s prototype theory and schema theories of cognitive categorization, the COO-Para models a country’s name as a central categorical cue that activates associative nodes in memory. If a country is categorized within an individual’s schema as “technologically advanced” or “industrially disciplined” (e.g., Germany), positive manufacturing expectations are automatically retrieved. Conversely, if a country is categorized as “developing” or “untested” (as was the case for South Korea during the scale’s early developmental window), non-compensatory heuristics may trigger heightened perceived risk.

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7. Validity

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The psychometric validity of the COO-Para has been rigorously established across multiple empirical phases utilizing cross-national samples, divergent product categories, and structural equation modeling (SEM).

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Construct and Convergent Validity

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Convergent validity was evaluated by assessing the statistical significance and magnitude of factor loadings within confirmatory factor analytic models. In Parameswaran and Pisharodi’s (1994) validation across American consumer evaluations of German and South Korean products (automobiles and blenders):

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• Standardized lambda ($\lambda$) coefficients for items loading on their designated latent factors were overwhelmingly large and statistically significant ($p < 0.001$), with the majority exceeding the$0.65$ threshold.

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• Average Variance Extracted (AVE) estimates across the latent dimensions consistently supported convergence, with higher-order factors demonstrating strong shared variance among their respective measurement indicators.

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Discriminant Validity

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Discriminant validity was established via nested-model comparisons in LISREL. For each pair of latent constructs (e.g., GCA-Competence versus GPA-Positive Quality), the correlation parameter ($\phi$) was constrained to unity ($1.00$). In every pairwise comparison, the unconstrained model yielded a statistically significant improvement in chi-square ($\Delta \chi^2$, $p < 0.001$) over the constrained model. This verified that even closely related constructs—such as general nation competence and generalized product quality—represent distinct psychological concepts in consumer memory rather than redundant re-phrasings.

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Predictive and Criterion-Related Validity

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Predictive validity was verified by entering GCA, GPA, and SPA factors into structural equations predicting consumers’ actual brand evaluations, perceived product value, and behavioral purchase intentions:

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• In both categories (automobiles and blenders), the intermediate GPA and micro SPA dimensions mediated the relationship between macro GCA and final purchase preference.

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• The model successfully discriminated between high-equity origin countries (Germany) and emerging origin countries (South Korea), capturing significant mean differences in perceived negative attributes ($t$-test values significant at $p < 0.001$) and technical competence.

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8. Reliability

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The internal consistency reliability of the COO-Para scale has been extensively documented across its initial 1992 formulation and expanded 1994 architecture. Reliability parameters have been computed across distinct country origins (e.g., Germany vs. Korea) and varying product classes (e.g., complex durables vs. small household appliances).

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Internal Consistency Coefficients (Cronbach’s Alpha)

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In the empirical assessments conducted by Parameswaran and Pisharodi (1994), Cronbach’s alpha ($\alpha$) coefficients across the latent subscales demonstrated acceptable-to-excellent internal consistency:

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• General Country Attitudes (GCA):n
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  • Country Competence: $\alpha = 0.85$ to $0.91$

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  • Similarity: $\alpha = 0.72$ to $0.81$

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  • Global Engagement: $\alpha = 0.68$ to $0.77$

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• General Product Attitudes (GPA):n
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  • Positive Product Quality: $\alpha = 0.84$ to $0.92$

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  • Negative Product Attributes: $\alpha = 0.76$ to $0.86$

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  • Distribution and Promotion: $\alpha = 0.69$ to $0.78$

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• Specific Product Attitudes (SPA):n
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  • Automobile Specific Attributes: $\alpha = 0.88$ to $0.94$

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  • Blender Specific Attributes: $\alpha = 0.74$ to $0.85$

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Across the complete spectrum of subscales and product-country pairings, composite factor reliability coefficients ranged between 0.586 and 0.943. Marginal reliabilities ($\alpha < 0.70$) occurred primarily within the distribution/promotion facet when applied to lesser-known foreign industries where consumer knowledge was ambiguous. Composite Reliability (CR) values calculated within confirmatory structural models consistently confirmed robust scale stability.

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9. Factor Analysis

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The structural composition of the COO-Para scale was developed through exploratory factor analysis (EFA) and validated via confirmatory factor analysis (CFA) using covariance structural equation modeling.

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Historical Structural Evolution: 1992 vs. 1994 Models

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The scale progressed through two primary structural iterations:

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• The 1992 Baseline Model (24 Items, 6 Factors): Derived using principal component analysis with varimax and oblimin rotations. Extracted factors included: GCA1 (Country Competence, 5 items), GCA2 (Similarity, 3 items), GPA1 (Negative Product Attributes, 5 items), GPA2 (Distribution and Promotion, 4 items), GPA3 (Positive Product Quality, 3 items), and SPA (Automobile Specifics, 4 items).

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• The 1994 Expanded Model (35 Items, 8 Factors): Expanded to integrate global engagement, refined product attributes, and dual-category cross-validation (automobiles and blenders), finalizing an eight-factor oblique latent structure.

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Confirmatory Factor Analysis (CFA) Fit Statistics

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In the 1994 structural validation using maximum likelihood estimation in LISREL, the eight-factor measurement model was contrasted against alternative nested models (including a single-factor general country/product model and a two-factor uncorrelated model):

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Standardized item loadings across latent factors were substantial, with EFA pattern matrix coefficients and CFA lambda paths regularly spanning between $0.62$ and $0.91$, confirming strong construct definitions without severe cross-loadings.

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10. Instrument / Measurement Tool

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The COO-Para is structured as a multidimensional, self-administered survey questionnaire designed for paper-and-pencil or modern computerized/online administration:

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• Instrument Type: Standardized multi-item self-report rating inventory.

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• Target Population: Adult consumers, corporate purchasing managers, business students, and international trade analysts evaluating foreign products and country reputations.

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• Administration Format: Individual or group administration; self-paced; average completion time ranges from 12 to 18 minutes depending on the number of focal nations examined.

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• Item Count:n
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  • 1992 Short Form: 24 items across 6 subscales.

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  • 1994 Comprehensive Form: 35 items across 8 subscales (including category-specific adaptation).

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• Response Scale: Standardized 10-point interval rating format (anchored from 1 = “Not at all appropriate / Completely disagree” to 10 = “Most appropriate / Completely agree”). The 10-point spread was specifically selected to optimize variance and minimize midpoint clustering in cross-national consumer evaluations.

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• Scoring and Computational Rules:n
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  • Subscale scores are computed by calculating the arithmetic mean of items assigned to each factor.

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  • Items belonging to the Negative Product Attributes (GPA-NEG) factor are either maintained as an independent negative valence score (recommended for diagnostic profiling) or reverse-coded ($11 – X$) when compiling an aggregate GPA index.

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  • Higher scores on GCA, GPA-POS, GPA-DIST, and SPA denote favorable consumer evaluations, while elevated scores on unreversed GPA-NEG denote heightened consumer perception of product defect risks.

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  • Researchers examining specific target goods must adapt the Specific Product Attitudes (SPA) module to mirror the primary evaluative criteria of the target category while holding GCA and GPA batteries invariant.

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11. Permissions & Fee and Test Year

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The developmental foundations and structural properties of the COO-Para were introduced across two seminal journal publications:

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• 1992: Initial six-factor scale published in the Journal of the Academy of Marketing Science (Spring 1992, Vol. 20, No. 2, pp. 169–179).

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• 1994: Refined and expanded eight-factor structural model published in the Journal of Advertising (March 1994, Vol. 23, No. 1, pp. 43–56).

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• Copyright and Access Permissions: The scale items, empirical factor matrices, and theoretical frameworks were published in scholarly peer-reviewed journals owned by academic societies. The copyright is held by the respective publishers (the American Academy of Advertising / Taylor & Francis for the Journal of Advertising, and Springer Nature / Academy of Marketing Science for the Journal of the Academy of Marketing Science).

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• Commercial and Research Licensing: Non-commercial academic research, pedagogical use, and dissertation investigations may utilize and cite the scale’s operational framework under standard fair-use academic research conventions, provided comprehensive bibliographic attribution is accorded to Parameswaran and Pisharodi. Commercial market research organizations and corporate entities seeking proprietary deployment or inclusion in commercial diagnostic toolkits must contact the respective journal publishers or original authors for licensing clearance.

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12. References

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• Bilkey, W. J., & Nes, E. (1982). Country-of-origin effects on product evaluations. Journal of International Business Studies, 13(1), 89–100. https://doi.org/10.1057/palgrave.jibs.8490539

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• Cohen, J. B., & Basu, K. (1987). Alternative models of categorization: Toward a contingent processing framework. Journal of Consumer Research, 13(4), 455–472. https://doi.org/10.1086/209082

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• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.

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• 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

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• Han, C. M. (1989). Country image: Halo or summary construct? Journal of Marketing Research, 26(2), 222–229. https://doi.org/10.1177/002224378902600208

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• Parameswaran, R., & Pisharodi, R. M. (1992). Country-of-origin effects: An alternative approach to measuring dual-level constructs. In V. L. Crittenden (Ed.), Developments in Marketing Science: Proceedings of the Academy of Marketing Science (Vol. 15, pp. 248–252). Springer. https://doi.org/10.1007/978-3-319-13248-8_52

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• Parameswaran, R., & Pisharodi, R. M. (1994). Facets of country-of-origin image: An empirical assessment. Journal of Advertising, 23(1), 43–56. https://doi.org/10.1080/00913367.1994.10673430

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• Pisharodi, R. M., & Parameswaran, R. (1992). Confirmatory factor analysis of a country-of-origin scale. Journal of the Academy of Marketing Science, 20(2), 169–179. https://doi.org/10.1007/BF02723457

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• Roth, M. S., & Romeo, J. B. (1992). Matching product category and country image perceptions: A framework for managing country-of-origin effects. Journal of International Business Studies, 23(3), 477–497. https://doi.org/10.1057/palgrave.jibs.8490276

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• Schooler, R. D. (1965). Product bias in the Central American Common Market. Journal of Marketing Research, 2(4), 394–397. https://doi.org/10.1177/002224376500200407

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13. Items of the Scale