Country Image Scale (CIS-COO)

1. Abstract

The Country Image Scale (CIS-COO), developed by Ingrid Martin and Sevgin Eroglu in 1993, is a foundational psychometric instrument designed to capture consumers’ and individuals’ multidimensional cognitive perceptions of foreign nations. Historically, international marketing and cross-cultural psychology research conflated a nation’s general macro-environmental standing with product-specific evaluations—commonly referred to as Country-of-Origin (COO) effects. Martin and Eroglu addressed this theoretical conflation by operationalizing country image as an independent, macro-level psychological construct defined as the total sum of descriptive, inferential, and informational beliefs an individual holds regarding a specific nation.

The scale consists of 14 items structured across a 7-point semantic differential format. It assesses three primary underlying dimensions: Political (5 items covering political stability, democratic governance, civil liberties, and national literacy), Economic (5 items measuring industrial development, standard of living, infrastructure, and economic stability), and Technological (4 items evaluating manufacturing capability, technological sophistication, and labor force technical proficiency). Across six independent validation samples evaluating four diverse target nations (Japan, the United States, India, and West Germany), the overall 14-item composite demonstrated high internal consistency reliability, with Cronbach’s alpha coefficients ranging from 0.895 to 0.950. Subscale reliabilities exhibited greater variability, yielding coefficients between 0.56 and 0.89 depending on the target nation’s geopolitical profile.

Crucially, empirical validation confirmed the scale’s discriminant validity from product-country images; correlations between general country image and product-specific attitudes remained low to moderate (ranging from r = 0.18 to 0.51, failing to reach statistical significance across multiple comparative tests). The CIS-COO provides researchers with an empirical tool for evaluating nation branding, bilateral trade perceptions, consumer ethnocentrism, foreign direct investment climates, and cross-cultural social cognition without contaminating macro-environmental attitudes with product-category schemas.

2. Keywords

Country Image Scale, Country of Origin, CIS-COO, Semantic Differential, Psychometrics, Martin and Eroglu, Nation Branding, Cognitive Schema, Cross-Cultural Measurement, Macro-Environmental Perceptions, International Marketing, Halo Effect

3. Authors

The Country Image Scale was conceptualized, developed, and empirically validated by Dr. Ingrid Martin and Dr. Sevgin A. Eroglu. Their collaborative research emerged from a shared theoretical imperative to untangle cognitive representations of foreign nations from affective evaluations of consumer goods manufactured within those borders.

• Dr. Ingrid Martin is an Emerita Professor of Marketing at the College of Business, California State University, Long Beach. Her scholarship focuses extensively on consumer information processing, environmental risk communication, cross-cultural consumer psychology, and cognitive modeling in international markets. Her work has appeared in leading outlets including the Journal of Business Research, Journal of Consumer Research, and Risk Analysis.
• Dr. Sevgin A. Eroglu is an Associate Professor Emerita of Marketing at the J. Mack Robinson College of Business, Georgia State University. Dr. Eroglu is recognized for her foundational contributions to retail atmospheric psychology, environmental cognition, and international marketing dynamics. Her theoretical inquiries into how environmental and cognitive cues shape consumer judgment have guided decades of empirical scholarship in business and behavioral disciplines.

The primary source publication documenting the psychometric architecture and validation of the instrument is:
Martin, I., & Eroglu, S. (1993). Measuring a multi-dimensional construct: Country image. Journal of Business Research, 28(3), 191–210. https://doi.org/10.1016/0148-2963(93)90047-S

4. Purpose

For several decades prior to the development of the CIS-COO, international business and behavioral researchers heavily relied on the Country-of-Origin (COO) effect to explain why consumers evaluated products differently when manufactured in different nations. Early studies routinely operationalized “country image” through operational proxies such as the perceived quality of a nation’s cars, electronics, or textiles. This theoretical approach suffered from profound circularity: a country was deemed to have a positive country image because its products were perceived as high quality, yet its products were assumed to be evaluated positively because of the country’s positive image.

The purpose of the Country Image Scale is to establish a psychometrically robust, generalized, and standardized instrument that captures an individual’s mental representation of a nation independent of product categories or commercial goods. Martin and Eroglu argued that an individual holds cognitive schema regarding a nation’s socioeconomic fabric, political stability, civil liberties, and technical capabilities, irrespective of whether that nation produces commercial goods exported to the evaluator’s domestic market. Thus, the CIS-COO measures the macro-environmental reality of a nation as mentally represented by external observers.

In applied and academic research contexts, the scale serves several critical functions:

• Deconfounding Country Cognitions from Product Judgments: It enables behavioral researchers to isolate the “halo effect” versus the “summary construct effect.” When consumers have no prior experience with a product, the macro-level country image serves as a halo that directly informs beliefs about product attributes. Conversely, when consumers have extensive product familiarity, product experiences consolidate into a summary construct that may influence macro-level country perceptions. The CIS-COO provides the standardized benchmark needed to test these structural paths.
• Public Diplomacy and Nation Branding Diagnostics: Beyond commercial marketing, governments and international organizations utilize the CIS-COO to benchmark global perceptions across diplomatic, economic, and human rights domains. By isolating whether negative national perceptions stem from political dissatisfaction, economic underperformance, or perceived technological backwardness, policy advisors can target strategic public diplomacy initiatives.
• Foreign Direct Investment (FDI) and Bilateral Trade Assessments: Institutional investors and multinational enterprises utilize macro-country assessments to evaluate societal risk, political stability, and workforce infrastructure when contemplating cross-border mergers, acquisitions, and plant installations.
• Cross-Cultural and Sociological Inquiries: Cross-cultural psychologists utilize the instrument to track stereotyping, ethnocentrism, and outgroup derogation across distinct geopolitical epochs, providing a quantified profile of cognitive prejudices and macro-level perceptions.

5. Psychological Construct

The psychological construct measured by the CIS-COO is Country Image, defined theoretically by Martin and Eroglu (1993, p. 193) as: “the total of all descriptive, inferential and informational beliefs one has about a particular country.” Under this conceptualization, country image operates as a high-order cognitive schema stored in long-term memory, formed via formal education, news media exposure, direct travel, interpersonal interactions, and historic geopolitical events. Martin and Eroglu operationalize this construct across three distinct, interrelated structural dimensions:

1. The Political Dimension

The Political subscale encompasses an individual’s cognitive appraisal of a nation’s governance structures, human rights records, democratic health, and institutional stability. Individuals do not perceive nations strictly through monetary output; they evaluate the ideological and regulatory environment governing human behavior within those boundaries. This dimension captures:

• System of Governance: Perceptions along the continuum from totalitarian/autocratic regimes to stable, representative democracies. Evaluators formulate mental models regarding how power is consolidated, checked, and exercised.
• Civilian Liberties and Human Rights: Beliefs regarding the degree of personal freedom, freedom of speech, assembly, and press available to the target nation’s populace.
• Sociopolitical Stability: Appraisals regarding the likelihood of civil unrest, systemic corruption, regime change, or internal conflict.
• Civic and Educational Infrastructure: Items in this dimension also capture fundamental human capital indicators, such as perceived general literacy levels and the educational access provided by the state apparatus.

Example: In empirical trials, respondents evaluating the United States consistently rated it exceptionally high on democratic governance and civilian freedoms, whereas evaluations of nations undergoing geopolitical transition exhibited elevated variance on political stability and regulatory transparency.

2. The Economic Dimension

The Economic subscale evaluates perceptions of a nation’s financial vitality, commercial sophistication, and distributive wealth. Rather than calculating exact macroeconomic metrics (e.g., Gross Domestic Product or Gini coefficients), the subscale captures the subjective mental model of the nation’s economic health. Key facets include:

• Level of Economic Development: Subjective appraisals of whether the nation is agrarian, developing, newly industrialized, or a fully advanced post-industrial economy.
• Standard of Living: Beliefs concerning the daily prosperity, purchasing power, poverty incidence, and domestic quality of life experienced by the average citizen.
• Industrial Base and Infrastructure: The perceived presence of modern transportation networks, robust capital markets, supply chain sophistication, and manufacturing scale.
• Economic Stability: Perceptions regarding inflation, currency reliability, and commercial predictability.

Example: In comparative samples, Japan and West Germany were perceived as economically developed industrial powerhouses with exceptionally high standards of living, whereas developing nations such as India were appraised as economically constrained, despite respondents acknowledging their cultural or historical richness.

3. The Technological Dimension

The Technological subscale isolates an individual’s evaluation of a nation’s scientific acumen, production capability, modernization, and innovation ecosystems. In contemporary global commerce, technological competence represents a dominant driver of product quality inferences. This dimension measures:

• Technological Sophistication: Appraisals of whether a nation is technologically backward, traditional, or operating at the global cutting edge of scientific discovery and applied engineering.
• Production Capability and Automation: Beliefs concerning the modernity of factories, manufacturing precision, digital networks, and quality control systems.
• Labor Force Technical Competence: The perceived skill, training, engineering expertise, and mathematical/scientific literacy of the domestic workforce.

Example: In the validation studies, Japan yielded the highest scores on the technological dimension, driven by cognitive beliefs regarding robotics, precision electronics, and industrial efficiency. This perception existed independently of respondents’ assessments of Japan’s domestic political framework, demonstrating the structural independence of the subscale.

6. Theoretical Framework

The theoretical framework underpinning the CIS-COO draws from cognitive psychology, schema theory, and the psychometric principles of multi-attribute cognitive modeling.

Schema Theory and Associative Semantic Networks

Schema theory posits that humans organize knowledge into complex, networked mental structures that represent generalized information about objects, individuals, social roles, and geographical entities (Fiske & Taylor, 1984). When an individual encounters the name of a country (e.g., “Japan”), this stimulus acts as a prime, activating an associative semantic network (Collins & Loftus, 1975). Nodes corresponding to political beliefs, historical episodes, economic conditions, and technological capabilities light up within memory.

Because humans are cognitive misers, they rely on these pre-existing macro-environmental schemas to make rapid inferences under conditions of incomplete information. Martin and Eroglu constructed the CIS-COO to map these latent cognitive schemas directly, standardizing the measurement of schema nodes across political, economic, and technological axes.

The Halo Effect versus Summary Construct Models

A central theoretical debate addressed by the CIS-COO is how country-level perceptions interact with product-level evaluations. In his seminal work, C. Min Han (1989) proposed two alternative cognitive models:

1. The Halo Model: When consumers possess little or no direct information regarding the functional performance of a product from a foreign nation, the general country image serves as a cognitive halo. Evaluators deduce: “This nation possesses advanced technology and a robust economy; therefore, this specific computer manufactured there must be high quality.”
2. The Summary Construct Model: As consumers acquire direct, repeated experience with diverse products originating from a specific nation, their product-specific beliefs aggregate. Evaluators induce: “Automobiles, cameras, and televisions from this nation are reliable and innovative; therefore, this nation must be technologically advanced and economically prosperous.”

Martin and Eroglu argued that to empirically validate whether the halo or summary model operates under specific market conditions, researchers must measure country image using an instrument that contains zero product-specific items. If an instrument measures country image with questions like “This nation produces reliable products,” the empirical test between halo and summary mechanisms becomes hopelessly confounded. The CIS-COO’s strict operationalization of macro-environmental criteria provides the required structural independence.

The Semantic Differential Methodological Tradition

Methodologically, the CIS-COO is rooted in the psycholinguistic work of Charles E. Osgood, George J. Suci, and Percy H. Tannenbaum (1957) on the measurement of meaning. Osgood established that complex semantic spaces can be effectively captured using bipolar adjective pairs along seven-point response continuum. By anchoring the 14 items with clear bipolar semantic opposites (e.g., Democratic vs. Dictatorial, Economically Stable vs. Economically Unstable, Labor is Skilled vs. Labor is Unskilled), the CIS-COO minimizes linguistic bias and captures the precise directional valence and magnitude of the respondent’s cognitive attributions.

7. Validity

The construct validity of the Country Image Scale was evaluated through rigorous testing across six independent empirical samples, encompassing college students and non-student adult consumers across multiple geographic regions evaluating four distinct nations: Japan, the United States, India, and West Germany. These nations were selected to represent diverse quadrants of economic development, technological sophistication, and political structures.

Content and Face Validity

Content validity was established through an extensive review of international marketing, political science, and economic literature, generating an initial broad pool of macro-level descriptive descriptors. A panel of academic experts and consumer behavior researchers refined this pool, removing items that referred to commercial product classes, subjective consumer preferences, or redundant affective traits. The resulting 14-item battery was judged by independent judges to possess comprehensive coverage of the macro-environmental domain without intruding into product evaluations.

Convergent Validity

Convergent validity was demonstrated by evaluating the degree to which CIS-COO dimensions correlated systematically with established indicators of national development and macro-attitudinal dispositions. Respondents’ composite scores on the scale tracked objective reality: Japan and West Germany scored consistently at the upper tiers of economic and technological dimensions, whereas India, as an emerging economy, received scores reflecting its developing infrastructure while registering higher scores on political democracy relative to autocratic regimes.

Discriminant Validity

The core psychometric objective of Martin and Eroglu was to prove that Country Image is empirically distinct from Country-of-Origin Product Image. To establish discriminant validity, respondents completed both the 14-item CIS-COO and a standard battery evaluating product-specific dimensions (product quality, reliability, design sophistication, and prestige) across several product categories.

The empirical findings decisively supported discriminant validity:

• Bivariate correlation coefficients between macro-level country image scores and product-specific quality attitudes ranged between r = 0.18 and r = 0.51 across samples.
• Critically, these correlations failed to achieve statistical significance across multiple comparative subgroups, indicating that macro-level country image and product-country evaluations share, at most, 3% to 26% of their variance.
• Confirmatory factor analytic comparisons confirmed that a two-construct model (treating country image and product image as separate latent factors) provided a significantly better fit to the data than a unified, single-construct model ($\Delta\chi^2$ tests were statistically significant at p < .001).

Nomological and Predictive Validity

Subsequent empirical investigations in international business have reaffirmed the CIS-COO’s nomological validity. When embedded in structural equation models, the scale’s dimensions predict distinct outcome variables:

• The Technological dimension consistently serves as the primary predictor of perceived product performance and functional quality inferences.
• The Political dimension directly predicts consumer willingness to engage in economic boycotts, policy acceptance, and bilateral trade favorability.
• The Economic dimension primarily influences perceptions of market potential, consumer purchasing power, and supply chain reliability.

8. Reliability

The internal consistency reliability of the CIS-COO was evaluated across six diverse samples (encompassing both undergraduate student cohorts and non-student adult consumer populations) evaluating multiple target countries. Psychometric evaluations yielded the following statistical parameters:

Overall Scale Reliability

The composite 14-item instrument exhibits high internal consistency. Across the six validation trials, the overall scale’s Cronbach’s alpha ranged from $lpha = 0.895$ to $lpha = 0.950$. These values surpass the conventional psychometric threshold ($lpha ge 0.80$) for basic research instruments, demonstrating that the 14 items cohere tightly around the broader latent construct of macro-level national standing.

Subscale Reliability Variations

While the omnibus instrument demonstrated high internal consistency, the subscale reliabilities revealed greater contextual variability across the evaluated target nations:

• Economic Dimension (5 items): Exhibited the most robust and consistent subscale reliability, with Cronbach’s alpha coefficients ranging between $lpha = 0.72$ and $lpha = 0.89$. The economic items (industrialization, standard of living, infrastructure) cohere reliably regardless of which target nation is evaluated.
• Technological Dimension (4 items): Demonstrated acceptable to high reliability across samples, yielding alpha values between $lpha = 0.68$ and $lpha = 0.87$. Reliability was highest when evaluating nations with widely recognized, distinct technological identities (e.g., Japan, USA).
• Political Dimension (5 items): Displayed the widest variability, with alpha coefficients fluctuating between $lpha = 0.56$ and $lpha = 0.82$. Martin and Eroglu observed that the lower alpha values (approaching 0.56 in certain developing nation assessments) reflected cognitive ambiguity among respondents regarding the exact relationship between civilian literacy, democratic structures, and regime stability. When respondents were less informed regarding a foreign nation’s domestic political affairs, item-response variance increased, deflating the dimension’s internal consistency.

Measurement Stability

The scale demonstrates stability across student and non-student adult demographic strata. In comparative analyses between student samples and broader adult consumer groups, the psychometric properties, factor structures, and alpha coefficients remained consistent, indicating that the CIS-COO is not an artifact of student convenience sampling.

9. Factor Analysis

To examine the latent dimensionality of the 14-item scale, Martin and Eroglu subjected the empirical data to Exploratory Factor Analysis (EFA) using Principal Components Analysis (PCA) followed by orthogonal (Varimax) and oblique rotations across the validation datasets.

EFA Factor Solutions and Variance Explained

Across the exploratory factor analytic trials, the unconstrained factor solutions consistently extracted three primary factors possessing eigenvalues greater than 1.0 (Kaiser criterion). Together, these three latent factors accounted for more than 60% of the total variance in respondents’ country evaluations, confirming the multidimensionality of the construct.

Factor Loadings and Factor Structure

The empirical pattern matrices yielded clear structural clusters:

• Factor 1: Economic Standing: Items reflecting the level of economic development, industrialization, per capita standard of living, and general national prosperity loaded strongly on this factor, with primary factor loadings typically ranging between 0.62 and 0.88. Cross-loadings onto political and technological factors remained below 0.35.
• Factor 2: Political Environment: Items capturing democratic governance versus authoritarian rule, civilian freedoms, human rights guarantees, and political stability loaded onto this dimension, with primary loadings spanning 0.55 to 0.84. However, as noted by the authors, items tapping national literacy and educational infrastructure occasionally exhibited dual-loadings across the economic and political factors, reflecting the cognitive reality that respondents view educational access as both a political right and an economic output.
• Factor 3: Technological Acumen: Items evaluating production sophistication, technical labor skill, manufacturing capabilities, and scientific innovation loaded cohesively on this factor, exhibiting loadings between 0.58 and 0.86.

Subsequent Confirmatory Factor Analyses (CFA)

Subsequent international researchers (e.g., in cross-cultural structural equation modeling studies) have evaluated Martin and Eroglu’s 14-item structure using Confirmatory Factor Analysis (CFA). Across multiple international samples, the correlated three-factor model demonstrates adequate to good overall fit indices:

• Comparative Fit Index (CFI): Values typically range between 0.91 and 0.96.
• Tucker-Lewis Index (TLI): Values regularly exceed 0.90.
• Root Mean Square Error of Approximation (RMSEA): Estimates typically fall between 0.048 and 0.072, supporting the structural validity of the three-factor model.
• Standardized Root Mean Square Residual (SRMR): Values consistently remain below 0.06.

Cross-National Measurement Invariance

Methodologists investigating the scale across diverse global markets have highlighted the necessity of testing for measurement invariance (configural, metric, and scalar). While configural invariance (identical three-factor structure) holds consistently across most cultural contexts, metric invariance (equal factor loadings) occasionally requires freeing constraints on items in the political dimension (particularly items regarding civil liberties and literacy), as democratic norms and literacy benchmarks are interpreted through distinct cultural baselines in Western versus non-Western populations.

10. Instrument / Measurement Tool

The Country Image Scale (CIS-COO) is an objective, paper-and-pencil or computer-administered psychometric questionnaire. Below is the operational summary of its administrative architecture:

• Test Type: Multidimensional cognitive attitude rating scale / Semantic differential questionnaire.
• Target Population: Consumers, organizational buyers, voters, and general adults aged 18 and older evaluating any designated target foreign nation.
• Administration Format: Self-administered (individual or group setting; paper-and-pencil or digital/web-based).
• Number of Items: Exactly 14 semantic differential adjective pairs.
• Dimensional Breakdown:
  • Political Subscale: 5 items (system of government, civil liberties, stability, literacy, human rights).
  • Economic Subscale: 5 items (economic development, industrial base, standard of living, financial stability, commercial infrastructure).
  • Technological Subscale: 4 items (production capability, technological sophistication, labor technical skills, manufacturing quality).
• Response Format: 7-point bipolar semantic differential scale anchored by contrasting adjectives (e.g., 1 = Highly Negative / Unfavorable Anchor to 7 = Highly Positive / Favorable Anchor; or coded -3 to +3 with 0 representing neutrality).
• Administration Time: Approximately 3 to 5 minutes per target country evaluated.
• Scoring Procedures:
  • Before computation, items that are reverse-coded must be inverted so that higher numerical values (e.g., 7) consistently reflect more favorable, advanced, or democratic cognitive evaluations.
  • Subscale Scores: Calculated by averaging or summing the ratings of the items comprising each dimension (Political, Economic, Technological), yielding a score range of 1.0 to 7.0 for each subscale.
  • Overall Country Image Composite: Calculated by averaging all 14 items to generate an omnibus Country Image index. Alternatively, researchers utilizing Structural Equation Modeling (SEM) model the three subscales as first-order latent factors loading onto a higher-order Country Image construct.

11. Permissions & Fee and Test Year

• Year of Initial Publication: 1993.
• Original Copyright Holders: The instrument and its foundational psychometric data were published in the Journal of Business Research by Elsevier Science Publishing Co., Inc.
• Intellectual Property & Licensing Status: The full theoretical exposition, validation data, and item conceptualizations are copyrighted by Elsevier. While academic researchers regularly utilize the 14-item semantic differential descriptors under fair-use principles for scholarly non-commercial research, formal commercial applications, large-scale commercial benchmarking, or republication within commercial psychometric databases require permissions via the Copyright Clearance Center (CCC) or Elsevier’s RightsLink service.
• Access Fee: The scale is typically accessible at no financial cost for academic, thesis, and educational inquiries through standard university library access to Elsevier’s ScienceDirect repository. No proprietary software license or test-kit purchase is mandated.

12. References

• Bilkey, W. J., & Nes, E. (1982). Country-of-origin effects on product evaluations. Journal of International Business Studies, 13(1), 89–99. https://doi.org/10.1057/palgrave.jibs.8490539
• Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82(6), 407–428. https://doi.org/10.1037/0033-295X.82.6.407
• Fiske, S. T., & Taylor, S. E. (1984). Social cognition. Addison-Wesley.
• Han, C. M. (1989). Country image: Halo or summary construct? Journal of Marketing Research, 26(2), 222–229. https://doi.org/10.1177/002224378902600208
• Martin, I., & Eroglu, S. (1993). Measuring a multi-dimensional construct: Country image. Journal of Business Research, 28(3), 191–210. https://doi.org/10.1016/0148-2963(93)90047-S
• Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning. University of Illinois Press.
• Roth, M. S., & Romeo, J. B. (1992). Matching product catgeory personality to country image traits: A framework for international brand management. Journal of International Business Studies, 23(3), 477–497. https://doi.org/10.1057/palgrave.jibs.8490276
• 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
• Steenkamp, J. B. E., & Baumgartner, H. (1998). Assessing measurement invariance in cross-national consumer research. Journal of Consumer Research, 25(1), 78–90. https://doi.org/10.1086/209528

13. Items of the Scale