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Measuring a multi-dimensional construct: Country image
J BUSN RES 1993:28:191-210
Measuring a Multi-Dimensional Country Image
191
Construct:
Ingrid M. Martin University of Southern California
Sevgin Eroglu Georgia State University
This study presents the procedures and results obtained in developing a scale to measure the multi-dimensional construct of country image. This effort intends to serve two purposes. First, it is likely to explicate many aspects of how product evaluations are affected by country image and, therefore, has theoretical as well as managerial implications. Second, a valid operational measure may help resolve some of the methodological and conceptual issues raised in the area of country of origin effects research. Tests of internal reliability and validity were conducted across different countries and samples to assess the strength of the final 14-item scale. The results imply that constructs used in international marketing research are scalable and that they can meet precise measurement criteria.
Introduction The growing literature on country image and country of origin effects to date has indicated that industrial and consumer buyers develop stereotypical images of countries and/or their products, which subsequently affect their purchase decisions (see Baughn and Yaprak, 1991, for a review). More specifically, a recent study by Han (1989) identified two major functions for country image effects. First, buyers can use country image in product evaluations when they are unable to detect the true quality of a country’s products before purchase (halo function). As such, country image indirectly affects brand attitudes through inferential beliefs. Second, as buyers become more familiar with a country’s products, country image may help them summarize their product beliefs and directly affect their brand attitudes (summary function). In this capacity, the country image is found to stimulate buyers to think more extensively about other product information as well (Hong and Wyer, 1989). The above findings have important practical and theoretical implications. From a managerial perspective, international marketers and public policy makers alike
Address correspondence to Ingrid M. Martin, Department of Marketing, tration, University of Southern California, Los Angeles, CA 90089-1421.
Journal of Business Research 28, 191-210 (1993) 0 1993 Elsevier Science Publishing Co., Inc. 655 Avenue of the Americas, New York, NY 10010
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need to understand country images within the context of their own offerings and those of their competition. Research has shown, for example, that consumers’ negative product evaluations based on country images constitute significant market barriers for companies from less developed countries (Schooler et al., 1987). The image that consumers hold of South Africa where major boycotts have managed to shut down the market for certain goods and services serves as an extreme example of this. Similarly, Johansson and Nebenzahl (1984) have found that multi-national firms with foreign manufacturing operations may risk potential loss in brand image depending on the country image of the sourcing country. Factors affecting country image also are instrumental for the positioning strategies of firms that compete in their domestic markets against foreign competitors (Hooley et al., 1988). In sum, international managers need to assess the extent to which relevant country images are favorable or unfavorable, if and how they affect product quality perceptions and purchase decisions, and how they can be used to develop effective marketing strategies. From a theoretical standpoint researchers in the area of country image effects have become increasingly sensitive to its theoretical and methodological dimensions (e.g., Bilkey and Nes, 1982; Jaffe and Nebenzahl, 1984; Parameswaran and Yaprak, 1987). In their review of the country of origin literature, Baughn and Yaprak (1991) conclude that these studies have contributed to international marketing research by increasing concerns about the psychometric properties of cross-national measures such as country image in the following ways. Presently, the measures used in the country of origin research stream are subject to the same criticisms that are directed at research in cross-cultural consumer behavior; namely, the shortage of valid and reliable measuring instruments (Davis et al., 1981). Our literature survey to date indicates that there is no validated scale for measuring country image per se. Furthermore, those that are currently being used to tap country image effects seem questionable for two reasons. First, from a conceptual perspective most of the scales presently used do not clearly distinguish between the image objects; that is, whether it is country image or product image that is being measured. The widely used Nagashima (1970, 1977) scale is a case in point. The scale that is designed to measure the image of products with a foreign country of origin includes items that also may capture country image. A valid scale, however, requires a precise delineation of the construct’s domain. If product attitudes are of interest, then the final scale should reflect measurement of product-specific attributes (e.g., reliable/unreliable, expensive/inexpensive). If, on the other hand, country image is being measured, the scale items should capture advanced/technically backward, coscountry-relevant attributes (c.g., technically mopolitan/ethnocentric). An accurate scale of country image needs to clearly specify the construct’s domain and to be exact concerning what is included as well as what is excluded from the definition. The second issue concerns the low reliability ratings of the existing scales used in country image studies. Several researchers reported poor reliabilities in their efforts to validate some of the popular scales used in country of origin research by Jaffe (e.g., Narayana, 1981; Cattin et al., 1982). Their findings were supported and Nebenzahl (1984) who concluded that existing image scales not only have low reliability but also are not tested for internal consistency and stability.
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These measurement concerns present several problems for researchers. In the event that conflicting measures are obtained, as pointed out by Bilkey and Nes (1982) in their review of the country of origin research, the researcher is not sure if the discrepancy is due to actual differences in country or product image or to different measures. As yet, there is no validated instrument available to assess country image without tapping into the image of products from the respective country. The basic tenet of the country of origin research is that one’s country image is reflected in higher evaluations of products originating in that country. It is difficult to assess the extent and nature of country image impact on product evaluations without an accurate instrument to measure it. The objective of the present study is to describe the development and evaluation of a multiple-item country image scale to help fill the need for better measures in this area. In sum, there are two distinct reasons for examining and developing a measure for country image. First, this effort is likely to explicate many aspects of how product attributes and evaluations are affected by the images that consumers have about their country of origin. This should have an impact on both the managerial and theoretical issues discussed previously. Second, a valid operational measure may help resolve some of the methodological and conceptual issues raised in the area of country image research. In the following pages, we first define the country image construct and identify its relevant dimensions from a review of the literature. Next, we discuss the procedure used to generate scale items and establish the content validity of the construct. This is followed by a discussion on assessing internal consistency and item stability as well as the validation techniques used to fine tune the scale. Finally, a discussion is presented on the relevancy of the final scale to both managers and academicians.
Methodology Defining
the Construct
and Identifying
Dimensions
The critical first step in the development of the scale is to specify the domain of the construct of country image. This involves a comprehensive review of the literature related to country of origin as well as country image studies (e.g., Baughn and Yaprak, 1991; Bilkey and Nes, 1982; Cattin et al., 1982; Dornoff et al., 1974; Gaedeke, 1973; Hafhill, 1980; Han, 1989; Han and Terpstra, 1988; Hong and Wyer, 1989; Johansson et al., 1985; Johansson and Moinpour, 1977; Nagashima, 1970; 1977; Narayana, 1981; Parameswaran and Yaprak, 1987). The review also included the literature on scale development and related issues in both the psychology and marketing methodology areas (e.g., Campbell and Fiske, 1959; Churchill, 1979; Frazier, 1983; Jaffe and Nebenzahl, 1984; Malhotra, 1981; Nagashima, 1970; 1977; Nunnally, 1978; Osgood et al., 19.57; Peter, 1979; 1981; Peter and Churchill, 1986; Wee, 1986; Wish et al., 1972; Zinkhan and Muderrisoglu, 1982). On the basis of the literature in these areas as well as discussions undertaken with international faculty and students, a conceptual definition was developed for the domain of the country image construct. Accordingly, country image was defined as the total of all descriptive, inferential and informational beliefs one has about a particular country.
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Again, it should be noted that this is completely different from one’s attitudes toward products from a certain country. One’s country image can develop as a result of a direct experience with the country, such as traveling to the country. Alternatively, it can be influenced by outside sources of information, such as advertising or word of mouth communications. Last, it could be affected by inferences (correct or incorrect) based on past experience such as opinions gained from using products originating in that particular country. In order to operationalize the definition, it was necessary to determine the relevant underlying dimensions of this construct. Country image has been consistently identified as a multi-dimensional concept (e.g., Jaffe and Nebenzahl, 1984; Johansson and Moinpour, 1977; Han, 1989). Several analytic and multi-dimensional scaling studies have indirectly implied some dimensions of country image across various countries (Johansson and Moinpour, 1977; Johansson et al., 1985; Wish et al., 1972). Along with the above studies, an interdisciplinary review of the literature (e.g., international business, political sciences, economics, sociology) resulted in the identification of four relevant dimensions. These four dimensions used to define the construct’s domain are (1) political, (2) economic, (3) technological, and (4) social desirability. The first three dimensions are self-explanatory and the fourth dimension, social desirability, includes such factors as quality of life, standard of living, and level of urbanization. Interestingly, the literature did not indicate culture or cultural familiarity as an underlying dimension of the country image construct. The format selected to measure country image in this study is the semantic differential scale. The theoretical rationale for using the semantic differential scale has been detailed by Osgood et al. (1957) as well as Churchill (1979). The most commonly used device for measuring images of such concepts as brands or products, stores, political candidates, countries, institutions, or ideas is the semantic differential scale. Using this scale device the researcher can measure, assess, and compare the image of a concept or object with that of similar topics (Alreck and Settle, 1985). In addition, the semantic differential has enjoyed a great acceptance and relevance in marketing research that is unmatched by any other scaling procedure (Malhotra, 1981). A two-phase procedure was used to generate the initial item pool. First, a short questionnaire was developed to derive a pool of phrases and adjectives that describe the image one has of any country. This instrument was administered to students and faculty on two midwestern university campuses. The sample provided adjectives, through free association, that were then combined with the second group based on their usage frequency. The second phase involved a focus group with eight doctoral students from various international backgrounds. During the 2-hour session the participants discussed their beliefs and impressions of various countries ranging from Nigeria to France to Korea to Yugoslavia. Once both sets of items were pooled together, all duplicated items as well as items that were country-specific were deleted. The result was a total of 60 bipolar word pairs. The next step involved reducing the number of items to a usable subset with the aid of five expert judges (three doctoral students and two faculty members in international-related fields). The judges were provided with the definition of country image and were instructed to evaluate the 60 bipolar word pairs in terms of their
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compatibility with the given definition as well as making suggestions for better wording of the items. An example of the instruction form is included in Appendix A. The judges were asked to rate the bipolar word pairs using the following scale: (1) clearly representative of a country’s image, (2) somewhat representative of a country’s image, and (3) not at all representative of a country’s image. This procedure involved an independent evaluation by the five judges. Average interjudge agreement and reliability was obtained for 29 of the 60 bipolar word pairs. The Holsti procedure (1969) was used to determine an average interjudge agreement of .848 and a reliability of .965. These 29 items were combined to form the initial scale that was then tested (see Appendix B for the initial 29-item scale).
Purifying the Scale Items The determination of how many items to have in a multi-dimensional scale is a difficult problem. On the one hand, a multi-dimensional construct can be factorially complex enough to require more than a single-item component to accurately capture the concept. On the other hand, if too many items are included in the questionnaire, then problems of fatigue and boredom may arise. Other scales in the literature (e.g., Malhotra, 1981; Lundstrom and Lamont, 1976; Nagashima, 1970; 1977; Zaichkowsky, 1985) were found to be shorter than the 29-item original scale. Therefore, it was decided that as we continued to purify the scale we also would allow for the deletion of scale items, if deemed necessary. The reduction of the number of items in the scale was done through a commonly used procedure (e.g., Lundstrom and Lamont, 1976; Malhotra, 1981; Wee, 1986) that required further data collection using the 29-item scale. The sample used for this purpose included 200 undergraduate and graduate students in the Colleges of Business Administration and Communication Arts and Sciences on a midwestern university campus. It is considered appropriate and common to use students as subjects in scale developments in both marketing and psychology (e.g., Malhotra, 1981; Osgood et al., 1957; Zaichkowsky, 1985). A pre-test was conducted to determine which country would be best to use in the initial test of the scale. The country of Japan was found to be a good candidate because of its high familiarity among the subjects. The data were analyzed for internal consistency. Given the multi-dimensional nature of the scale, though, it is not very meaningful to estimate an overall measure of internal consistency (Peter, 1979). Therefore, first the coefficient alpha was computed for each subset of scale items that made up a certain factor. The result was a 21-item scale with item-total correlations ranging between .23 and .58. Internal consistency for the scale was then tested by checking the reliability coefficient alphas, which ranged from .77 to .81. These values were deemed reasonable when compared with others obtained in the marketing studies previously mentioned as well as the evaluation guidelines suggested by Peter (1979). Nunnally (1978) argues that increasing reliability beyond .8 is unnecessary because at that level correlations are attenuated very little by measurement error. Principal component analysis was used to determine which variables had high intraset correlations and low interset correlations for the country of Japan. This methodology is common for exploratory scale development and it uncovered three of the four factors that had been identified in the literature. Principal component
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Table 1. Correlations
Between Social Desirability
and the Other Three Factors of
Country Image
Level of economic
development
Political
Economic
,344
.I3 (.065)
._51 (.0001)
(.ml)
.49 (.OWl)
.32 (.0001)
.20 (.0058)
.18 (.OllO)
.22 (.002)
.18 (.0116)
.Sl (.WOl)
.04 (.614)
.02 (.83)
.15 (.036)
(.Wl) Level of per capita
Size of middle
Existence
income
class
of a welfare
system
Level of unemployment
,581
.Ol (.93)
Note; Numbers
in parentheses
are probability
values
for the respective
Technological
correlations.
analysis with varimax rotation yielded three distinct and independent factors: (1) political, (2) economic, and (3) technological. This provided supportive evidence of construct validity for the scale. The social desirability component did not emerge as a significant factor. The literature postulates that this factor is described by such items as quality of life, standard of living, and level of urbanization. It was hypothesized that such items could have been captured in the three other factors of economic, political, and technological aspects. For example, it could be argued that some of the items that fall in the economic dimension (e.g., level of standard of living, stability of economic environment, level of labor costs) all are very similar to the items in the social desirability component. Similarly, level of urbanization very well may have been captured in the technological dimension with such items as level of industrialization and level of technological research. Based on these findings and reasoning, we decided to conduct another set of tests to determine if social desirability was truly captured by the three factors. The next step was to identify the items in the scale that could be components of the social desirability factor. These items were then correlated with the three factors both as an individual factor of social desirability and as individual components of the hypothesized factor. The five items identified included level of economic development, level of per capita income, size of middle class, existence of a welfare system, and level of unemployment. First, the five items were individually correlated with the three factors and the results can be seen in Table 1. The items with the highest correlations to one or more of the factors included level of economic development, level of per capita income, size of middle class, and existence of a welfare system. The last item, level of unemployment, correlated only moderately with any of the technological factors (r = .15, p < .04). The second step in the analysis involved regressing each of the social desirability items on each factor. The result was an adjusted R2 of .40, .44, and .34 for the political, economic, and technological factors, respectively. This, along with the moderately high correlations of the social desirability items, provided evidence that this factor was indeed captured in the three factors. One last test was conducted
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to ensure this point. The five social desirability items were combined into a factor that was correlated with each of the other three factors. The result was moderate and highly significant correlations between that factor and the political, economic, and technological dimensions (r = .43, p < .OOOl; r = .50, p < .OOOl; r = .28, p < .OOl, respectively). Based on these findings and the above reasoning, it was concluded that the social desirability component was captured by the three emergent dimensions. Next, by using the criterion of meaningfulness recommended by Gorsuch (1983), items that had factor loadings less than .30 or that loaded highly on more than one factor were deleted, resulting in a scale with 14 items. The items that were removed from the scale suggest that either these items did not explain a significant amount of variation in the data or that these items were unique. The reliability coefficient alphas for the three factors ranged from .56 to .71. The overall Cronbach’s alpha for the new 1Qitem scale was found to be .95. Given these highly satisfactory results, the scale was then tested using the 14 bipolar word pairs.
Testing the Revised Scale The revised scale, (Appendix C), which consisted of 14 items, was tested to determine if it was a reliable and valid measurement. This was necessary for two reasons (Nunnally, 1978). First, the revised instrument was considerably shorter than the original version. Second, determining if the scale provided consistent results when different countries were used as image objects was necessary. If the scale held up across various countries, then it could be considered a stable instrument (Churchill, 1979). This phase of scale testing included a new group of 230 undergraduate students from 2 midwestern universities. The use of large samples during this phase of scale construction is recommended by Nunnally (1978). At least 10 times as many subjects as items should be used to ensure that the reported coefficients are not inflated. In this phase, the United States was the image object. Confirmatory factor analysis was used on the 1Citem scale with varimax rotation as the factors were deemed independent. This resulted in the same three factors emerging, as previously mentioned. The majority of the item-to-total correlations for each of the items was above .40, supporting the premise that they all relate to the single country image construct. The Cronbach’s alpha for the entire scale was calculated at .925. Additionally, the correlation between split halves was calculated and found to be .78. The newly identified component scales are shown in Table 2 with factor loadings ranging between .30 and .78. The first factor contains five items that were related to the overall political climate and characteristics of a country, in this instance the United States. The second factor had five items that were related to the economic environment of a country. The last set had four items that addressed the technological aspects and characteristics of a country. The majority of the item-to-total correlations of these three factors were above .40. The high item-to-total correlations were also reflected in the low determinant of the correlation matrix of .0095. This measure shows little, if any, variability in the factors. The second column of Table 2 displays, for each item, a Cronbach’s alpha computed from the other items in the scale, ranging between .81 and .84.
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Table 2. Component
and S. Eroglu
Scale Items Item-to-Total Correlation
Description: Factor One: Political Dimension Democratic versus dictatorial system Capitalist versus communist system Civilian versus military system Pro-western versus pro-communist Free market versus centrally planned
Alpha if Item Deleted
.713 ,612 ,631 ,708 ,573
.812 .x20 .818 .813 ,823
Factor Two: Economic Dimension Level of standard of living Stability of economic environment Quality of products Existence of a welfare system Level of labor costs
,535 ,443 ,359 ,278 ,414
,825 ,831 ,836 ,842 ,834
Factor Three: Technological Dimension Level of industrialization Level of technological research Level of literacy Mass produced versus handcrafted products
,429 ,247 ,381 ,285
.832 .H4l .H3S ,840
Total
Scale Reliability
Coefficient
system
,925
Construct Validation The term construct validity is the degree to which a measure assesses the construct it is purported to describe. This means the measure only can be assessed indirectly as the construct (i.e., country image) is not observable (Peter, 1981). For example, in this study country image was theoretically hypothesized to have four dimensions. This hypothesis was derived from an evaluation of the interdisciplinary literature on country image. The results of the factor analysis and further tests provided significant support for three, not four, underlying dimensions. It was argued earlier that the lack of the fourth dimension, social desirability, may be due to the fact that it falls within the other three factors of country image and not as a separate dimension. This was empirically verified using the social desirability items in the original 29-item scale. The next step was to hypothesize that country image has three underlying dimensions as identified in the factor analysis and that these three dimensions fit the theoretical dimensions suggested by the literature. This fit could be interpreted as supportive evidence of construct validity (Peter, 1981). More substantive evidence of construct validity was then obtained via an examination of the content validity and discriminant validity. Construct validity concerns the adequacy of the domain of observables relating to a construct and can be tested by analyzing how item scores correlate with each other (Churchill, 1979; Nunnally, 1978). To do this, the lbitem scale was further tested by collecting data using two other countries as image objects. The countries of India and West Germany were chosen for this purpose mainly because pre-tests showed these countries to be different with respect to at least two of the three underlying dimensions of country image (economic and technological). The scale
Measuring
a Multi-Dimensional Table 3. Evaluation
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Construct of Construct
Validity
of Country
199
Image for India Item-to-Total Correlation
Squared Multiple Correlation
s59 ,485 ,482 ,345 ,324
,455 .448 .401 ,435 ,390
Factor Two: Economic Dimension Level of standard of living Stability of economic environment Quality of products Existence of a welfare system Level of labor costs
,756 ,718 ,589 ,593 ,552
.710 .706 ,528 .477 ,624
Factor Three: Technological Dimension Level of industrialization Level of technological research Level of literacy Mass produced versus handcrafted products
,734 .709 .686 ,724
,721 ,528 .540 .527
Description: Factor One: Political Dimension Democratic versus dictatorial system Capitalist versus communist system Civilian versus military system Pro-western versus pro-communist Free market versus centrally planned
Total scale reliability
coefficient
system
.895
was then administered to a new group of 160 students. There were 80 students who rated West Germany and 80 who rated India for country image. The analysis gave highly satisfactory results (Tables 3 and 4). For both West Germany and India, the three previously obtained (political, economic, and technological) factors emerged as a result of confirmatory factor analysis using varimax rotation. The factor loadings varied between .52 and .85 for both countries. The item-to-total correlations for the majority of the items in the scale were all greater than 55 and .65 for India and West Germany, respectively. These favorable correlations also were reflected in the very low determinants of the correlation matrices of .00036 and .000055, for India and West Germany, respectively. The squared multiple correlations obtained provide an index of the relative extent to which each scale item contributes to capturing country image. This can be seen where the majority of the squared multiple correlations were above .52 for India and .69 for West Germany. In addition, the Cronbach’s alphas for each dimension were checked and were found in the range from .686 to .887 for the country of India and from .581 to .761 for West Germany. This provided added credence to support the conclusion that all the image items measure one singly underlying construct, country image. Once this was established, the scale had to be tested further for content and discriminant validity. Content validity concerns the degree of representativeness of the items to the construct. Open-ended interviews with representative respondents (Churchill, 1979) as well as expert judgments (Green and Tull, 1978) are deemed appropriate procedures for checking scale content. In this case, generation of the initial item pool employed both of these methods. Furthermore, the final scale was again
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Table 4. Evaluation
of Construct
Validity
of Country
and S. Eroglu
Image for West Germany Item-to-Total Correlation
Squared Multiple Correlation
.778 ,786 ,755 .743
,757 ,784 ,783 .750 .730
Factor Two: Economic Dimension Level of standard of living Stability of economic environment Quality of products Existence of a welfare system Level of labor costs
,721 ,663 ,664 ,636 .555
,812 ,796 ,356 ,561 .444
Factor Three: Technological Dimension Level of industrialization Level of technological research Level of literacy Mass produced versus handcrafted products
,524 .649 .747 .44v
,465 ,687 .710 .693
Description: Factor One: Political Dimension Democratic versus dictatorial system Capitalist versus communist system Civilian versus military system Pro-western versus pro-communist Free market versus centrally planned
Total
Scale Reliability
Coefficient
.73s system
,928
examined independently by the initial group of judges for scale content and wording. Discriminant validity needed to be established as the domain of the construct is multi-dimensional (Campbell and Fiske, 1959). Discriminant validity exists to the extent that one can empirically differentiate the construct from other similar constructs and can indicate what is unrelated to the construct. Therefore, it was necessary to test whether the new country image scale was significantly different from the previously used Nagashima scale (1970, 1977). The Nagashima scale (Appendix D) consists of 20 bipolar items measured on a 7-point scale. It is frequently used in international marketing research (e.g., Han and Terpstra, 1988; Han, 1989; Narayana, 1981) and attempts to measure the image of products with foreign country of origin, which, in turn is purported to reflect one’s country image (Bilkey and Nes, 1982). In order to make the comparison between the country image scale and that of Nagashima, several steps were taken. First, a new group of 158 students was used to rate West Germany (n = 79) and India (n = 79) with the Nagashima instrument. Because discriminant validity requires that the two constructs do not correlate highly with each other (e.g., Bagozzi, 1982; Campbell and Fiske, 1959; Peter, 1981) correlations were calculated between each of the three dimensions of the country image scale and the Nagashima scale for both India and West Germany (Table 5). The correlations for each of the dimensions and the Nagashima scale were low to moderate and non-significant for all the dimensions across both countries. Having both countries tested across the two different scales using different student samples, we found that there was discriminant validity between the country image scale and
Measuring a Multi-Dimensional TABLE 5. Evaluation
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Construct of Discriminant
Validity of Country Image for West Germany
and India West Political
Economic
dimension
dimension
Technological
dimension
Note: Numbers in parentheses
Germany
India
.18
.43
(.68)
C.29)
.41
.28
632)
t.501
.51 C.19)
.34 C-191
are probability values for the respective correlations
the product image scale developed by Nagashima (1970). This verifies the hypothesis that the new country image scale is unique and not simply a reflection of other variables (Peter and Churchill, 1981).
Conclusions Countries evoke different product images in consumers’ minds. However, because country of origin effects vary across countries, samples, and products, the results of this stream of research seem to lack consistency and generalizability. Among the suggestions made to advance the state of the art in the country of origin literature is more emphasis on measurement of the relevant constructs such as country image (e.g., Jaffe and Nebenzahl, 1984; Cattin et al., 1982; Han, 1989). To this end the present study was designed to develop and validate a multipleitem scale for measuring the construct of country image as distinct from product immge. The procedures recommended by Churchill’s (1979) paradigm for developing better measures were followed to capture the concept of country image. The resulting 16item semantic differential scale was developed by using 4 different data sets with students from 2 midwestern universities. Following a series of procedures for item generation, expert judges were used to select those items with high content validity. The reliability of the scale was established by the use of various indicators across different countries as well as the scale’s construct and discriminant validities. The present instrument is intended to be useful for practitioners and researchers alike. From a practical perspective, there are situations where a quantitative yardstick on country image may be necessary for managers. In marketing a country in a competitive industry such as tourism, it would be useful to have a baseline rating of the target market’s opinion of the country to be promoted. Similarly, when trying to attract foreign investment into a country, public and private promoters would benefit from information on the perceptions that the concerned parties have about a certain country. Under these and other similar situations, when the “product” is a country, choosing the most appropriate marketing strategy largely depends on the type of image held by the target ,market. An example that we are now faced with is the dramatic change in eastern Europe. With the radical change in the political, economic, and technological base of countries such as Poland, Romania, and Hungary, how will the perceptions that Westerners hold of these countries affect their ability to compete in the world market?
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These countries should be interested in determining exactly what their respective country image is with the Western world so that negative perceptions can be changed to allow them to better compete in the marketplace. This same concept can be applied to the changes occurring in western Europe as they face 1992. The perception that they are a solid economic and political block is critical for the success of their push to merge into a United States of Europe. The country image scale can provide a quantitative yardstick for these countries to determine the perception of other countries. This information then can be used to adapt persuasive communication campaigns to provide others with the “correct” image. If the image is positive, this should be stressed in an attempt to market the country’s products and services. The practical importance for marketers is that a favorable country image can be used to sell inferior products only temporarily. For example, country image can act as an information cue for consumers. This cue combines with an array of information cues, both intrinsic and extrinsic to the product, to aid the consumer in evaluating the product. This implies that there must be a match between country image and the image that one has of a country’s products (Bilkey and Nes, 1982). The theoretical interests of the scale development project are several. First, country image has three, not four, underlying dimensions. Past literature as well as research has asserted that social desirability is an underlying dimension of country image, but based on extensive testing, it was determined that social desirability is captured by the three factors of economic, political, and technological aspects. Second, researchers would benefit from a validated instrument specifically designed to measure country image. The scale would contribute to designing studies that are more explanatory and/or predictive in nature rather than purely descriptive. For example, the present scale would be applicable to determine if consumers’ evaluations of products from a country are consistent with their overall image of that country. The scale also would help to explain how consumers develop the country stereotypes they have by examining the scores for each of their dimensions. Additionally, the country image scale could be used to understand if and how different countries (as perceived by consumers) are likely to affect consumers’ evaluations of different product classes. Another possible application of the scale would be to categorize consumers into several image segments (e.g., low, medium, high) on their individual image scores for a single country. Alternatively, consumer segments could be identified based on their image scores across countries. It should be emphasized that this scale is strictly aimed at measuring one’s image of a country and should not be used to assess image of or attitudes toward products from a country. With respect to limitations of this scale, during the development and validation of the scale only a few countries were used. Further tests need to be carried out by using other countries as well as non-student samples to verify the stability and the validity of the scale. Along with the above, it should be further investigated as to whether social desirability continues to bc a component of the three factors identified and verified in this study. Future research could look at the ability to use measures of country image to predict the probability of purchase behavior; that is, what are the stereotypes that consumers have for countries that rank as planned economies with low standards of living and low literacy and level of industrialization? The next interesting issue is to determine if the stereotypes that form our country image also impact our probability of buying a certain product from that country.
Measuring a Multi-Dimensional
Appendix
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Construct
203
A
Judge Evaluation Form JUDGE
EVALUATION
FORM
Thank you for agreeing to participate as a judge in this scaling project. This is a crucial step in the development of an accurate scale of any concept. On the following pages there are 60 word/phrases that are generated to represent the concept of Country Image. In this study, for the purposes of scale development, the definition of country image is: One’s impressions of a country is based on a set of perceived ratings of the country along various dimensions. These dimensions include economic, social, cultural, geographical, technological and political characteristics which reflect a perception of that particular country. Your task is to judge each of the bipolar words/phrases as to how well they represent the concept of Country Image as defined above. Each set of bipolar words/phrases should be rated using the following scale: a. Clearly representative of a country’s image. b. Somewhat representative of a country’s image. c. Not representative of a country’s image. Only one of the above choices that best represents your opinion of the bipolar words/phrases and its ability to reflect the concept of Country Image, should be circled. The following example illustrates the task of selecting representative concepts of Country Image.
Introverted People
1. Extroverted People
a. Clearly representative of a country’s image.
b. Somewhat a country’s
rep. of image
Clearly representative of a country’s image.
Not rep. of a country’s image
Advanced Economy
2. Backward Economy @
@
b. Somewhat a country’s
rep. of image.
c. Not rep. of a country’s image
Please remember that this is a weeding out process. It is important that you realize that most or all may seem to clearly represent the concept. However, we are interested in the fine distinctions between the a, b, c categories.
204
Appendix
J BUSN RES 1993:28:191-210
I. M. Martin and S. Eroglu
B Original
29-Item
Country
Image
Scale
Country
Image
Scale
This is a survey to find out what a person thinks about a certain country. To measure this, we will ask you to rate the country that appears at the top of the page against a series of descriptors by placing a check (J) on the scale from one to seven that best reflects your judgment. There are no right or wrong answers. We are only interested in how YOU perceive the country. Consider the following example: By placing a check (J) in the middle, it would mean that you feel that the country that appears at the top of the page is neither pro-Western or pro-Communist. pro-Western
--: (I)
~. -. J: -. -: (2)’ (3)’ (4) (5)’ (6)
However, if you feel that the country the scale in the following manner: pro-Western
J: (1)
Please
_: (I)
pro-Communist (7)
pro-Western
you would
pro-Communist
pro-Communist
you would
-: -. -. ~. -. J. (2) (3) ’ (4)’ (5) ’ (6)
__: (7)
mark the scale in this
pro-Communist
ask if you have any questions. (Country Name) economically
1) economically developed
(1):(2):(3):(4):(5):(h):(7): underdeveloped
2) democratic system
~. ~. -. -. -. ~. _. (1)’ (2)’ (3)’ (4)’ (5)’ (6)’ (7)’
dictatorial system
3) civilian government
~. -. -. -. ~. -.(I)’ -.(2)’ (3)’ (4)’ (5)’ (6)’ (7)’ . -. . -. . -. . -. ~. . _. . -.
military government
4) extended family 5) large population 6) high per capita income
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-. -. -. -. -. ~. ~. (I)’ (2)’ (3)’ (4)’ (5)’ (6). (7)’ (I)’
mark
(2):(3):(4):0:(h):(7):
Or, if you feel that it is slightly manner: pro-Western
is extremely
-:
(2)’
(3)’
(4)’
(5)’
(6)’
(7)’
nuclear family small population low per capita income
Measuring
a Multi-Dimensional
7) exporter industrial products
J BUSN RES 1993:28:191-210
Construct
of -.(1)’ -.(2)’ -.(3)’
-. -. -. -. (4)’ (5)’ (6)’ (7)’
importer industrial products
-. -. -. (5)’ (6)’ (7)’
centrally planned
8) free market system
~.(1)’ -.(2)’ -.(3)’ -.(4)’
9) culturally diverse
_. -. -. ~. -. ~. (4)’ (5)’ (6)’ (7)’ -.(1)’ (2)’ (3)’
10) stable economic environment
-.(1)’ -.-. (2)’
11) exporter of agricultural products
-.(1)’
12) existence of a large middle class
-.(1)’ -.-. (2)’
13) large land mass 14) high level of technological research
-.(1)’
(3)’
_.-. (4)’
(5)’
-. -. (6)’ (7)’
_. -. -. _. -. -. (2)’ (3)’ (4)’ (5)’ (6). (7)’
(3)’
-.-. -. -. (4) * (5)’ (6)’ (7)’
_. -. -. _. -. ~. (2)’ (3)’ (4)’ (5)’ (6)’ (7)’
-. -. ~. _. -. ~. _. (1)’ (2)’ (3)’ (4)’ (5)’ (6)’ (7)’ -. -. -. -. (4)’ (5) * (6)’ (7)’
of
system
culturally uniform unstable economic environment importer of agricultural products existence of a small middle class small land mass low level of technological research
15) mass produced products
-.(1)’ ~.(2)’ -.(3)’
16) high literacy rates
-. -. -. -.(1)’ -.(2)’ -.(3)’ -.(41’ (5)’ (6)’ (7)’
17) exporter of raw materials
-.(1)’ -.-. (2)’
(3)’
18) pro-Western
-.(1)’ -.-. (2)’
(4)’ (3)’ -.-.
(5)’ -.(6)’ -: (7)
pro-Communist
19) high labor costs
-.(1)’ ~._. (2)’
(4)’ (3)’ -.-.
(5)’ -.6
low labor costs
20) existence of a welfare system
-.(1)’ -.-. (2)’
(4)’ (3)’ -._.
(5)’ -.(6)’ -: (7)
of 21) production high quality products
-.(1)’ -.-. (2)’
(3)’
-._. (4)’
(5)’
-. -. (6)’ (7)’
production low quality products
22) high standard of living
-. -. ~. -.-. (1)’ (2)’ (3)‘ (4)’
(5)’
~. -. (6)’ (7)’
low standard of living
23) stable political environment
-.(1). ~.(2)’ -.(3)’
-._. (4)’
(5)’
-. -. (6)’ (7)’
-: (7)
-. ~. -. -. (4)’ (5)’ (6)’ (7)’
handcrafted products low literacy rates importer of raw materials
lack of a welfare system
unstable political environment
of
205
206
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I. M. Martin
and S. Eroglu
24) large social class differences
--: (1)
---: ~. (2) (3)‘(4):(5):
~. ~. (6)’ (7)’
small social class differences
25) exporter of consumer products
-: (1)
-.
_. _. (6)’ (7).
importer consumer products
26) capitalist system
-: (1)
-: -. ~. ~. _. _. (2) (3)’ (4)’ (5)’ (6)‘ (7)’
27) high population inmigration rate
-: (1)
-: -. -. ~. (2) (3) ’ (4)’ (9’
~. (6)
28) predominantly industrialized
-: (1)
-. -: (2)’ (3)
(4):(5):
(6):(7):
predominantly non-industrialized
29) high unemployment rate
_: (1)
_: _: (2) (3)
-: --: (4) (5)
_: (6)
low unemployment rate
Appendix
(2)’
-: (3)
-: _: (4) (5)
of
communist system
_. . 6’)
_: (7)
high population out-migration rate
C
Revised
II-Item
Country
Image Scale Country
Image
Scale
This is a survey to find out what a person thinks about a certain country. To measure this, we will ask you to rate the country that appears at the top of the page against a series of descriptors by placing a check (J) on the scale from one to seven that best reflects your judgment. There are no right or wrong answers. We are only interested in how YOU perceive the country. Consider the following example: By placing a check (J) in the middle, it would mean that you feel that the country that appears at the top of the page is neither pro-Western or pro-Communist. pro-Western
-: (1)
-: -: (2) (3)
J: _: (4) (5)
However, if you feel that the country the scale in the following manner: pro-Western
is extremely
J. (1).(2):(3):(4):&q:(7).
Or, if you feel that it is slightly manner:
_: (6)
pro-Communist
_: (7)
pro-Communist
pro-Western
.
you would
you would
mark
pro-Communist
mark the scale in this
Measuring
a Multi-Dimensional
pro-Western
Please
J BUSN RES 1993:28:191-210
Construct
J.
207
pro-Communist
o:(2):(3):(4):(5):(6).(7):
ask if you have any questions.
(Country Name) 1) economically developed
-: (1)
-: -: (2) (3)
--: _: (4) (5)
_: (6)
-: (7)
economically underdeveloped
2) democratic system
-: (1)
-: -: (2) (3)
_: _: (4) (5)
-:
-: (7)
dictatorial system
3) mass produced products
_: (1)
_: _: (2) (3)
-: -: (4) (5)
-: (6)
-: (7)
handcrafted products
. -. -. (6)’ 6’)’
military government
4) civilian government
(1)’
(2)’
(3)’
(4)’
0’
(6)
5) predominantly industrialized
-: (1)
-: -: (2) (3)
_: _: (4) (5)
_: (6)
-: (7)
predominantly non-industrialized
6) high labor costs
-: (1)
-: -: (2) (3)
-: -: (4) (5)
-: (6)
-: (7)
low labor costs
7) high literacy rates
-: (1)
-: -: (2) (3)
_: _: (4) (5)
-: (6)
-: (7)
low literacy rates
8) free market system
_: (1)
_: _: (2) (3)
-: -: (4) (5)
-: (6)
-: (7)
centrally planned
9) existence of welfare system
-: (1)
-: -: (2) (3)
_: _: (4) (5)
-: (6)
-: (7)
lack of a welfare system
10) stable economic environment
-. ~. -. -. -. -. -. (1)’ (2)’ (3)’ (4)’ (5)’ (6)’ (7)’
11) exporter of agricultural products
-: (1)
-: -: (2) (3)
12) production of high quality products
-: (1)
-. -. ~. -: ~. _. (2)’ (3)’ (4)’ (5)’ (6)’ (7)
13) high standard of living
-: (1)
-: -: (2) (3)
O’(5)’
14) high level of technological research
-: (1)
(2)’
(4)’
u)’
_: -: (4) (5)
(5)’
-: (6)
unstable economic environment
-: (7)
(6)’
0’
(6)’
(7)’
system
importer of agricultural products production IOW quality products .
low standard of living
f
low level of technological research
of
208
J BUSN RES 1993:28:191-210
Appendix
I. M. Martin and S. Eroglu
D
The Nagashima
Product
Image
Scale
(Country Name) 1) Expensive
-: (I)
-: -: (2) (3)
_. --: (4)’ (5)
2) Reasonably Priced
-: (I)
-: -: (2) (3)
--: ~. ~. -: (4) (5)’ (6)’ (7)
3) Reliable
-: (I)
~. ~. -: _: (2)’ (3)’ (4) (5)
4) Luxury
_: (6)
-: (7)
Inexpensive
Unreasonably Priced
-. -: (6)’ (7)
Unreliable
items
Necessary
Items
(1):(2):(3):(4):(5):(h):(7): 5) Heavy Industry Products 6) Careful and meticulous workmanship 7) Technically Advanced
-: (1)
-: -: (4) (5)
-: -: (2) (3)
(2).
(I)’ .
(3)’ .
(4)’ .
(5)’ .
-: (6)
-: (7)
. -. -. . (6)’ (7)
Not so careful meticulous workmanship
.
:
Technically Backward
:
Hand
.
Mostly
.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(I)’
(2)’
(3)’
(4)’
(5)’
(6)’
(7)
8) Mass Produced 9) World Wide Distribution
. (1)
. (2)
. (3)
. (4)
.. -. (5)
Light Manufacturing Products
(6)
. -. (7)
Domestic
Distribution .
10) Inventive
Made
Imitative
(1):(2):(3):(4):(5):(6):(7). 11) Pride of ownership 12) Much Advertising
-:
-:
(1)
(2)
-: (3)
. (1)
-: (4)
(3)
(7)
(5)
(6)
: -: (7)
-: -: (4) (5)
-: (6)
(4)
-: (1)
-: -: (2) (3)
14) Large choice of size & model
-: (1)
~. ~. -: -: (2)’ (3)’ (4) (5)
16) Clever use of color
(I)’
_:
(6)
.
13) Recognizable brand names
15) More concerned-. with outward appearance
_:
(5)
. (2)
_:
Not much pride of ownership Little Advertising Unrecognizable brand names
-: (7)
Limited choice of size & model
~. -: (6)’ (7)
-: -. -. ~. ~. ~. (2)’ (3)‘ (4)’ (5)’ (6)’ (7)
More concerned with performance .
(1):(2):(3):(4):(5):(6):(7).
Not clever use of color
Measuring
a Multi-Dimensional
17) More for young people
J BUSN RES 1993:28:191-210
Construct
(1):
_: -. -. ~. -. -. (2)’ (3) ’ (4)’ (5) ’ (6)’ (7)
209
More for old people
18) More for men
-. -.-. -. -. . _: _: (1) (2) (3)’ (4)’ (5)’ (6)’ (7)
More for women
19) Upper class
._____: _: -: -: -: -: -: (1) (2) (3) (4) (5) (6) (7)
Lower class
20) Exclusive
. -.-. . . -. . _: _. . -.-. . (1) (2) (3) (4) (5) (6) (7)
Common
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Green, P., and Tull, D. S., Research for Marketing Decisions, Prentice-Hall, Cliffs, NJ. 1978.
Han, C. M., Country Image: 26 (May 1989): 222-229.
Halo or Summary
Construct?
Journal Countries.
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to Cross National
Dornoff, R. J., Tankersley, C. B., and White, G. P. Consumers’ Perceptions Akron Business and Economic Review 5 (Summer 1974): 26-29.
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Hillsdale, Englewood
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Journal of Marketing Research
Han, C. M., and Terpstra, V., Country of Origin: Effects for Uni-National and Bi-National Products. Journal of International Business Studies 16 (Summer 1988): 235-256. Holsti, 0. R., Content Analysis for the Social Sciences and Humanities, Publishing, Reading, MA. 1969.
Addison-Wesley
Hong, S., and Wyer, R. S., Effects of Country of Origin and Product Attribute Information on Product Evaluation. Journal of Consumer Research 16 (1989): 175-187.
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Hooley, G., Shipley, D., and Krieger, N., A Method for Modeling of Country of Origin. Znternational Marketing Review (Autumn
and S. Eroglu
Consumers’ Perceptions 1988): 67-76.
Jaffe, E. D., and Nebenzahl, I. D., Alternative Questionnaire Formats for Country Studies. Journal of Marketing Research 21 (November 1984): 463-471.
Image
Johansson, J. K., and Moinpour, R., Objective and Perceived Similarity of Pacific Countries. Columbia Journal of World Business 12 (4) (Winter 1977): 65-76.
Rim
Johansson, J. K., Douglas, S. P., and Nonaka, I., Assessing the Impact of Country of Origin on Product Evaluations: A New Methodological Perspective. Journal of Marketing Research 22 (November 1985): 373-381. Lundstrom, W. J., and Lamont, L. M., The Development of a Scale to Measure Discontent. Journal of Murketing Reseurch 13 (November 1976): 373-381. Malhotra. N., A Scale to Measure Self-concepts, Journal of Marketing Research 18 (November
Person-concepts, 1981): 456-464.
Nagashima, A., A Comparison of Japanese and U.S. Attitudes Journal of Marketing 34 (July 1970): 68-74. Nagashima, nessmen.
A., A Comparative Made-In Product Image Journul of Marketing 41 (July 1977): 95-100.
Narayana, C., International 31-35. Nunnally,
Consumer
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Foreign
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Japanese
Busi-
Aggregate Images of American and Japanese Products: Implications on Marketing. Columbia Journal of World Business 16 (2) (Summer 1981):
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Osgood, C. E., Succi, G. J., and Tannenbaum, University of Illinois Press, Champaign-Urbana,
New York.
1978.
P. M., The Measurement IL. 1057.
Parameswaran, R.. and Yaprak, A., A Cross-National Comparison Measures. Journal of lnternutional Business Studies 15 (Winter
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Peter, J. P., Reliability: A Review of Psychometric Basics and Recent Journal of Marketing Research 16 (February 1979): 6-17.
Marketing
Peter. J. P., Construct Validity: A Review of Basic Issues and Marketing of Marketing Research, May, 133-45, 1981.
Practices,
Research Practices. Journal
Peter, J. P., and Churchill, G. A., Relationships Among Research Design Choices and Psychometric Properties of Rating Scales: A Meta-Analysis. Journul of Marketing Research 18 (May 1986): 133-141. Schooler, C., Wildt, A., and Jones, J., Strategy Development for Manufactured Exports of Third World Countries to Developed Countries. Journal of Global Marketing 1 (l-2) (1987): 53-67. Wee, C. H., Shopping Area Image: Its Factor Analytic Structure and Relationships with Shopping Trips and Expenditure Behavior. Advances in Consumer Research Proceedings 14 (1986): 48-52. Wish, M., Deutsch, M., and Biener, L., Differences in Perceived Similarity of Nations, in Multidimensional Scaling: Theory and Application in the Behavioral Sciences. A.K. Romney. ed., Seminar Press, New York. 1972. Zaichkowsky, J. L., Measuring the Involvement 12 (December 1985): 341-352.
Construct.
Journal of Consumer Research
Zinkhan, G. M., and Muderrisoglu, A., Involvement, Familiarity, Cognitive Differentiation, and Advertising Recall: A Test of Convergent and Discriminant Validity. Advances in Consumer Reseurch Proceedings 10 (1982): 356-361.
Measuring a Multi-Dimensional Country Image
191
Construct:
Ingrid M. Martin University of Southern California
Sevgin Eroglu Georgia State University
This study presents the procedures and results obtained in developing a scale to measure the multi-dimensional construct of country image. This effort intends to serve two purposes. First, it is likely to explicate many aspects of how product evaluations are affected by country image and, therefore, has theoretical as well as managerial implications. Second, a valid operational measure may help resolve some of the methodological and conceptual issues raised in the area of country of origin effects research. Tests of internal reliability and validity were conducted across different countries and samples to assess the strength of the final 14-item scale. The results imply that constructs used in international marketing research are scalable and that they can meet precise measurement criteria.
Introduction The growing literature on country image and country of origin effects to date has indicated that industrial and consumer buyers develop stereotypical images of countries and/or their products, which subsequently affect their purchase decisions (see Baughn and Yaprak, 1991, for a review). More specifically, a recent study by Han (1989) identified two major functions for country image effects. First, buyers can use country image in product evaluations when they are unable to detect the true quality of a country’s products before purchase (halo function). As such, country image indirectly affects brand attitudes through inferential beliefs. Second, as buyers become more familiar with a country’s products, country image may help them summarize their product beliefs and directly affect their brand attitudes (summary function). In this capacity, the country image is found to stimulate buyers to think more extensively about other product information as well (Hong and Wyer, 1989). The above findings have important practical and theoretical implications. From a managerial perspective, international marketers and public policy makers alike
Address correspondence to Ingrid M. Martin, Department of Marketing, tration, University of Southern California, Los Angeles, CA 90089-1421.
Journal of Business Research 28, 191-210 (1993) 0 1993 Elsevier Science Publishing Co., Inc. 655 Avenue of the Americas, New York, NY 10010
Act-301,
School of Business
Adminis-
0148-2963/93/$6.OCl
192
J BUSN RES 1993:28:191-210
I. M. Martin
and S. Eroglu
need to understand country images within the context of their own offerings and those of their competition. Research has shown, for example, that consumers’ negative product evaluations based on country images constitute significant market barriers for companies from less developed countries (Schooler et al., 1987). The image that consumers hold of South Africa where major boycotts have managed to shut down the market for certain goods and services serves as an extreme example of this. Similarly, Johansson and Nebenzahl (1984) have found that multi-national firms with foreign manufacturing operations may risk potential loss in brand image depending on the country image of the sourcing country. Factors affecting country image also are instrumental for the positioning strategies of firms that compete in their domestic markets against foreign competitors (Hooley et al., 1988). In sum, international managers need to assess the extent to which relevant country images are favorable or unfavorable, if and how they affect product quality perceptions and purchase decisions, and how they can be used to develop effective marketing strategies. From a theoretical standpoint researchers in the area of country image effects have become increasingly sensitive to its theoretical and methodological dimensions (e.g., Bilkey and Nes, 1982; Jaffe and Nebenzahl, 1984; Parameswaran and Yaprak, 1987). In their review of the country of origin literature, Baughn and Yaprak (1991) conclude that these studies have contributed to international marketing research by increasing concerns about the psychometric properties of cross-national measures such as country image in the following ways. Presently, the measures used in the country of origin research stream are subject to the same criticisms that are directed at research in cross-cultural consumer behavior; namely, the shortage of valid and reliable measuring instruments (Davis et al., 1981). Our literature survey to date indicates that there is no validated scale for measuring country image per se. Furthermore, those that are currently being used to tap country image effects seem questionable for two reasons. First, from a conceptual perspective most of the scales presently used do not clearly distinguish between the image objects; that is, whether it is country image or product image that is being measured. The widely used Nagashima (1970, 1977) scale is a case in point. The scale that is designed to measure the image of products with a foreign country of origin includes items that also may capture country image. A valid scale, however, requires a precise delineation of the construct’s domain. If product attitudes are of interest, then the final scale should reflect measurement of product-specific attributes (e.g., reliable/unreliable, expensive/inexpensive). If, on the other hand, country image is being measured, the scale items should capture advanced/technically backward, coscountry-relevant attributes (c.g., technically mopolitan/ethnocentric). An accurate scale of country image needs to clearly specify the construct’s domain and to be exact concerning what is included as well as what is excluded from the definition. The second issue concerns the low reliability ratings of the existing scales used in country image studies. Several researchers reported poor reliabilities in their efforts to validate some of the popular scales used in country of origin research by Jaffe (e.g., Narayana, 1981; Cattin et al., 1982). Their findings were supported and Nebenzahl (1984) who concluded that existing image scales not only have low reliability but also are not tested for internal consistency and stability.
Measuring
a Multi-Dimensional
J BUSN RES 1993:28:191-210
Construct
193
These measurement concerns present several problems for researchers. In the event that conflicting measures are obtained, as pointed out by Bilkey and Nes (1982) in their review of the country of origin research, the researcher is not sure if the discrepancy is due to actual differences in country or product image or to different measures. As yet, there is no validated instrument available to assess country image without tapping into the image of products from the respective country. The basic tenet of the country of origin research is that one’s country image is reflected in higher evaluations of products originating in that country. It is difficult to assess the extent and nature of country image impact on product evaluations without an accurate instrument to measure it. The objective of the present study is to describe the development and evaluation of a multiple-item country image scale to help fill the need for better measures in this area. In sum, there are two distinct reasons for examining and developing a measure for country image. First, this effort is likely to explicate many aspects of how product attributes and evaluations are affected by the images that consumers have about their country of origin. This should have an impact on both the managerial and theoretical issues discussed previously. Second, a valid operational measure may help resolve some of the methodological and conceptual issues raised in the area of country image research. In the following pages, we first define the country image construct and identify its relevant dimensions from a review of the literature. Next, we discuss the procedure used to generate scale items and establish the content validity of the construct. This is followed by a discussion on assessing internal consistency and item stability as well as the validation techniques used to fine tune the scale. Finally, a discussion is presented on the relevancy of the final scale to both managers and academicians.
Methodology Defining
the Construct
and Identifying
Dimensions
The critical first step in the development of the scale is to specify the domain of the construct of country image. This involves a comprehensive review of the literature related to country of origin as well as country image studies (e.g., Baughn and Yaprak, 1991; Bilkey and Nes, 1982; Cattin et al., 1982; Dornoff et al., 1974; Gaedeke, 1973; Hafhill, 1980; Han, 1989; Han and Terpstra, 1988; Hong and Wyer, 1989; Johansson et al., 1985; Johansson and Moinpour, 1977; Nagashima, 1970; 1977; Narayana, 1981; Parameswaran and Yaprak, 1987). The review also included the literature on scale development and related issues in both the psychology and marketing methodology areas (e.g., Campbell and Fiske, 1959; Churchill, 1979; Frazier, 1983; Jaffe and Nebenzahl, 1984; Malhotra, 1981; Nagashima, 1970; 1977; Nunnally, 1978; Osgood et al., 19.57; Peter, 1979; 1981; Peter and Churchill, 1986; Wee, 1986; Wish et al., 1972; Zinkhan and Muderrisoglu, 1982). On the basis of the literature in these areas as well as discussions undertaken with international faculty and students, a conceptual definition was developed for the domain of the country image construct. Accordingly, country image was defined as the total of all descriptive, inferential and informational beliefs one has about a particular country.
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Again, it should be noted that this is completely different from one’s attitudes toward products from a certain country. One’s country image can develop as a result of a direct experience with the country, such as traveling to the country. Alternatively, it can be influenced by outside sources of information, such as advertising or word of mouth communications. Last, it could be affected by inferences (correct or incorrect) based on past experience such as opinions gained from using products originating in that particular country. In order to operationalize the definition, it was necessary to determine the relevant underlying dimensions of this construct. Country image has been consistently identified as a multi-dimensional concept (e.g., Jaffe and Nebenzahl, 1984; Johansson and Moinpour, 1977; Han, 1989). Several analytic and multi-dimensional scaling studies have indirectly implied some dimensions of country image across various countries (Johansson and Moinpour, 1977; Johansson et al., 1985; Wish et al., 1972). Along with the above studies, an interdisciplinary review of the literature (e.g., international business, political sciences, economics, sociology) resulted in the identification of four relevant dimensions. These four dimensions used to define the construct’s domain are (1) political, (2) economic, (3) technological, and (4) social desirability. The first three dimensions are self-explanatory and the fourth dimension, social desirability, includes such factors as quality of life, standard of living, and level of urbanization. Interestingly, the literature did not indicate culture or cultural familiarity as an underlying dimension of the country image construct. The format selected to measure country image in this study is the semantic differential scale. The theoretical rationale for using the semantic differential scale has been detailed by Osgood et al. (1957) as well as Churchill (1979). The most commonly used device for measuring images of such concepts as brands or products, stores, political candidates, countries, institutions, or ideas is the semantic differential scale. Using this scale device the researcher can measure, assess, and compare the image of a concept or object with that of similar topics (Alreck and Settle, 1985). In addition, the semantic differential has enjoyed a great acceptance and relevance in marketing research that is unmatched by any other scaling procedure (Malhotra, 1981). A two-phase procedure was used to generate the initial item pool. First, a short questionnaire was developed to derive a pool of phrases and adjectives that describe the image one has of any country. This instrument was administered to students and faculty on two midwestern university campuses. The sample provided adjectives, through free association, that were then combined with the second group based on their usage frequency. The second phase involved a focus group with eight doctoral students from various international backgrounds. During the 2-hour session the participants discussed their beliefs and impressions of various countries ranging from Nigeria to France to Korea to Yugoslavia. Once both sets of items were pooled together, all duplicated items as well as items that were country-specific were deleted. The result was a total of 60 bipolar word pairs. The next step involved reducing the number of items to a usable subset with the aid of five expert judges (three doctoral students and two faculty members in international-related fields). The judges were provided with the definition of country image and were instructed to evaluate the 60 bipolar word pairs in terms of their
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compatibility with the given definition as well as making suggestions for better wording of the items. An example of the instruction form is included in Appendix A. The judges were asked to rate the bipolar word pairs using the following scale: (1) clearly representative of a country’s image, (2) somewhat representative of a country’s image, and (3) not at all representative of a country’s image. This procedure involved an independent evaluation by the five judges. Average interjudge agreement and reliability was obtained for 29 of the 60 bipolar word pairs. The Holsti procedure (1969) was used to determine an average interjudge agreement of .848 and a reliability of .965. These 29 items were combined to form the initial scale that was then tested (see Appendix B for the initial 29-item scale).
Purifying the Scale Items The determination of how many items to have in a multi-dimensional scale is a difficult problem. On the one hand, a multi-dimensional construct can be factorially complex enough to require more than a single-item component to accurately capture the concept. On the other hand, if too many items are included in the questionnaire, then problems of fatigue and boredom may arise. Other scales in the literature (e.g., Malhotra, 1981; Lundstrom and Lamont, 1976; Nagashima, 1970; 1977; Zaichkowsky, 1985) were found to be shorter than the 29-item original scale. Therefore, it was decided that as we continued to purify the scale we also would allow for the deletion of scale items, if deemed necessary. The reduction of the number of items in the scale was done through a commonly used procedure (e.g., Lundstrom and Lamont, 1976; Malhotra, 1981; Wee, 1986) that required further data collection using the 29-item scale. The sample used for this purpose included 200 undergraduate and graduate students in the Colleges of Business Administration and Communication Arts and Sciences on a midwestern university campus. It is considered appropriate and common to use students as subjects in scale developments in both marketing and psychology (e.g., Malhotra, 1981; Osgood et al., 1957; Zaichkowsky, 1985). A pre-test was conducted to determine which country would be best to use in the initial test of the scale. The country of Japan was found to be a good candidate because of its high familiarity among the subjects. The data were analyzed for internal consistency. Given the multi-dimensional nature of the scale, though, it is not very meaningful to estimate an overall measure of internal consistency (Peter, 1979). Therefore, first the coefficient alpha was computed for each subset of scale items that made up a certain factor. The result was a 21-item scale with item-total correlations ranging between .23 and .58. Internal consistency for the scale was then tested by checking the reliability coefficient alphas, which ranged from .77 to .81. These values were deemed reasonable when compared with others obtained in the marketing studies previously mentioned as well as the evaluation guidelines suggested by Peter (1979). Nunnally (1978) argues that increasing reliability beyond .8 is unnecessary because at that level correlations are attenuated very little by measurement error. Principal component analysis was used to determine which variables had high intraset correlations and low interset correlations for the country of Japan. This methodology is common for exploratory scale development and it uncovered three of the four factors that had been identified in the literature. Principal component
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Table 1. Correlations
Between Social Desirability
and the Other Three Factors of
Country Image
Level of economic
development
Political
Economic
,344
.I3 (.065)
._51 (.0001)
(.ml)
.49 (.OWl)
.32 (.0001)
.20 (.0058)
.18 (.OllO)
.22 (.002)
.18 (.0116)
.Sl (.WOl)
.04 (.614)
.02 (.83)
.15 (.036)
(.Wl) Level of per capita
Size of middle
Existence
income
class
of a welfare
system
Level of unemployment
,581
.Ol (.93)
Note; Numbers
in parentheses
are probability
values
for the respective
Technological
correlations.
analysis with varimax rotation yielded three distinct and independent factors: (1) political, (2) economic, and (3) technological. This provided supportive evidence of construct validity for the scale. The social desirability component did not emerge as a significant factor. The literature postulates that this factor is described by such items as quality of life, standard of living, and level of urbanization. It was hypothesized that such items could have been captured in the three other factors of economic, political, and technological aspects. For example, it could be argued that some of the items that fall in the economic dimension (e.g., level of standard of living, stability of economic environment, level of labor costs) all are very similar to the items in the social desirability component. Similarly, level of urbanization very well may have been captured in the technological dimension with such items as level of industrialization and level of technological research. Based on these findings and reasoning, we decided to conduct another set of tests to determine if social desirability was truly captured by the three factors. The next step was to identify the items in the scale that could be components of the social desirability factor. These items were then correlated with the three factors both as an individual factor of social desirability and as individual components of the hypothesized factor. The five items identified included level of economic development, level of per capita income, size of middle class, existence of a welfare system, and level of unemployment. First, the five items were individually correlated with the three factors and the results can be seen in Table 1. The items with the highest correlations to one or more of the factors included level of economic development, level of per capita income, size of middle class, and existence of a welfare system. The last item, level of unemployment, correlated only moderately with any of the technological factors (r = .15, p < .04). The second step in the analysis involved regressing each of the social desirability items on each factor. The result was an adjusted R2 of .40, .44, and .34 for the political, economic, and technological factors, respectively. This, along with the moderately high correlations of the social desirability items, provided evidence that this factor was indeed captured in the three factors. One last test was conducted
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to ensure this point. The five social desirability items were combined into a factor that was correlated with each of the other three factors. The result was moderate and highly significant correlations between that factor and the political, economic, and technological dimensions (r = .43, p < .OOOl; r = .50, p < .OOOl; r = .28, p < .OOl, respectively). Based on these findings and the above reasoning, it was concluded that the social desirability component was captured by the three emergent dimensions. Next, by using the criterion of meaningfulness recommended by Gorsuch (1983), items that had factor loadings less than .30 or that loaded highly on more than one factor were deleted, resulting in a scale with 14 items. The items that were removed from the scale suggest that either these items did not explain a significant amount of variation in the data or that these items were unique. The reliability coefficient alphas for the three factors ranged from .56 to .71. The overall Cronbach’s alpha for the new 1Qitem scale was found to be .95. Given these highly satisfactory results, the scale was then tested using the 14 bipolar word pairs.
Testing the Revised Scale The revised scale, (Appendix C), which consisted of 14 items, was tested to determine if it was a reliable and valid measurement. This was necessary for two reasons (Nunnally, 1978). First, the revised instrument was considerably shorter than the original version. Second, determining if the scale provided consistent results when different countries were used as image objects was necessary. If the scale held up across various countries, then it could be considered a stable instrument (Churchill, 1979). This phase of scale testing included a new group of 230 undergraduate students from 2 midwestern universities. The use of large samples during this phase of scale construction is recommended by Nunnally (1978). At least 10 times as many subjects as items should be used to ensure that the reported coefficients are not inflated. In this phase, the United States was the image object. Confirmatory factor analysis was used on the 1Citem scale with varimax rotation as the factors were deemed independent. This resulted in the same three factors emerging, as previously mentioned. The majority of the item-to-total correlations for each of the items was above .40, supporting the premise that they all relate to the single country image construct. The Cronbach’s alpha for the entire scale was calculated at .925. Additionally, the correlation between split halves was calculated and found to be .78. The newly identified component scales are shown in Table 2 with factor loadings ranging between .30 and .78. The first factor contains five items that were related to the overall political climate and characteristics of a country, in this instance the United States. The second factor had five items that were related to the economic environment of a country. The last set had four items that addressed the technological aspects and characteristics of a country. The majority of the item-to-total correlations of these three factors were above .40. The high item-to-total correlations were also reflected in the low determinant of the correlation matrix of .0095. This measure shows little, if any, variability in the factors. The second column of Table 2 displays, for each item, a Cronbach’s alpha computed from the other items in the scale, ranging between .81 and .84.
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Table 2. Component
and S. Eroglu
Scale Items Item-to-Total Correlation
Description: Factor One: Political Dimension Democratic versus dictatorial system Capitalist versus communist system Civilian versus military system Pro-western versus pro-communist Free market versus centrally planned
Alpha if Item Deleted
.713 ,612 ,631 ,708 ,573
.812 .x20 .818 .813 ,823
Factor Two: Economic Dimension Level of standard of living Stability of economic environment Quality of products Existence of a welfare system Level of labor costs
,535 ,443 ,359 ,278 ,414
,825 ,831 ,836 ,842 ,834
Factor Three: Technological Dimension Level of industrialization Level of technological research Level of literacy Mass produced versus handcrafted products
,429 ,247 ,381 ,285
.832 .H4l .H3S ,840
Total
Scale Reliability
Coefficient
system
,925
Construct Validation The term construct validity is the degree to which a measure assesses the construct it is purported to describe. This means the measure only can be assessed indirectly as the construct (i.e., country image) is not observable (Peter, 1981). For example, in this study country image was theoretically hypothesized to have four dimensions. This hypothesis was derived from an evaluation of the interdisciplinary literature on country image. The results of the factor analysis and further tests provided significant support for three, not four, underlying dimensions. It was argued earlier that the lack of the fourth dimension, social desirability, may be due to the fact that it falls within the other three factors of country image and not as a separate dimension. This was empirically verified using the social desirability items in the original 29-item scale. The next step was to hypothesize that country image has three underlying dimensions as identified in the factor analysis and that these three dimensions fit the theoretical dimensions suggested by the literature. This fit could be interpreted as supportive evidence of construct validity (Peter, 1981). More substantive evidence of construct validity was then obtained via an examination of the content validity and discriminant validity. Construct validity concerns the adequacy of the domain of observables relating to a construct and can be tested by analyzing how item scores correlate with each other (Churchill, 1979; Nunnally, 1978). To do this, the lbitem scale was further tested by collecting data using two other countries as image objects. The countries of India and West Germany were chosen for this purpose mainly because pre-tests showed these countries to be different with respect to at least two of the three underlying dimensions of country image (economic and technological). The scale
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Construct of Construct
Validity
of Country
199
Image for India Item-to-Total Correlation
Squared Multiple Correlation
s59 ,485 ,482 ,345 ,324
,455 .448 .401 ,435 ,390
Factor Two: Economic Dimension Level of standard of living Stability of economic environment Quality of products Existence of a welfare system Level of labor costs
,756 ,718 ,589 ,593 ,552
.710 .706 ,528 .477 ,624
Factor Three: Technological Dimension Level of industrialization Level of technological research Level of literacy Mass produced versus handcrafted products
,734 .709 .686 ,724
,721 ,528 .540 .527
Description: Factor One: Political Dimension Democratic versus dictatorial system Capitalist versus communist system Civilian versus military system Pro-western versus pro-communist Free market versus centrally planned
Total scale reliability
coefficient
system
.895
was then administered to a new group of 160 students. There were 80 students who rated West Germany and 80 who rated India for country image. The analysis gave highly satisfactory results (Tables 3 and 4). For both West Germany and India, the three previously obtained (political, economic, and technological) factors emerged as a result of confirmatory factor analysis using varimax rotation. The factor loadings varied between .52 and .85 for both countries. The item-to-total correlations for the majority of the items in the scale were all greater than 55 and .65 for India and West Germany, respectively. These favorable correlations also were reflected in the very low determinants of the correlation matrices of .00036 and .000055, for India and West Germany, respectively. The squared multiple correlations obtained provide an index of the relative extent to which each scale item contributes to capturing country image. This can be seen where the majority of the squared multiple correlations were above .52 for India and .69 for West Germany. In addition, the Cronbach’s alphas for each dimension were checked and were found in the range from .686 to .887 for the country of India and from .581 to .761 for West Germany. This provided added credence to support the conclusion that all the image items measure one singly underlying construct, country image. Once this was established, the scale had to be tested further for content and discriminant validity. Content validity concerns the degree of representativeness of the items to the construct. Open-ended interviews with representative respondents (Churchill, 1979) as well as expert judgments (Green and Tull, 1978) are deemed appropriate procedures for checking scale content. In this case, generation of the initial item pool employed both of these methods. Furthermore, the final scale was again
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Table 4. Evaluation
of Construct
Validity
of Country
and S. Eroglu
Image for West Germany Item-to-Total Correlation
Squared Multiple Correlation
.778 ,786 ,755 .743
,757 ,784 ,783 .750 .730
Factor Two: Economic Dimension Level of standard of living Stability of economic environment Quality of products Existence of a welfare system Level of labor costs
,721 ,663 ,664 ,636 .555
,812 ,796 ,356 ,561 .444
Factor Three: Technological Dimension Level of industrialization Level of technological research Level of literacy Mass produced versus handcrafted products
,524 .649 .747 .44v
,465 ,687 .710 .693
Description: Factor One: Political Dimension Democratic versus dictatorial system Capitalist versus communist system Civilian versus military system Pro-western versus pro-communist Free market versus centrally planned
Total
Scale Reliability
Coefficient
.73s system
,928
examined independently by the initial group of judges for scale content and wording. Discriminant validity needed to be established as the domain of the construct is multi-dimensional (Campbell and Fiske, 1959). Discriminant validity exists to the extent that one can empirically differentiate the construct from other similar constructs and can indicate what is unrelated to the construct. Therefore, it was necessary to test whether the new country image scale was significantly different from the previously used Nagashima scale (1970, 1977). The Nagashima scale (Appendix D) consists of 20 bipolar items measured on a 7-point scale. It is frequently used in international marketing research (e.g., Han and Terpstra, 1988; Han, 1989; Narayana, 1981) and attempts to measure the image of products with foreign country of origin, which, in turn is purported to reflect one’s country image (Bilkey and Nes, 1982). In order to make the comparison between the country image scale and that of Nagashima, several steps were taken. First, a new group of 158 students was used to rate West Germany (n = 79) and India (n = 79) with the Nagashima instrument. Because discriminant validity requires that the two constructs do not correlate highly with each other (e.g., Bagozzi, 1982; Campbell and Fiske, 1959; Peter, 1981) correlations were calculated between each of the three dimensions of the country image scale and the Nagashima scale for both India and West Germany (Table 5). The correlations for each of the dimensions and the Nagashima scale were low to moderate and non-significant for all the dimensions across both countries. Having both countries tested across the two different scales using different student samples, we found that there was discriminant validity between the country image scale and
Measuring a Multi-Dimensional TABLE 5. Evaluation
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Construct of Discriminant
Validity of Country Image for West Germany
and India West Political
Economic
dimension
dimension
Technological
dimension
Note: Numbers in parentheses
Germany
India
.18
.43
(.68)
C.29)
.41
.28
632)
t.501
.51 C.19)
.34 C-191
are probability values for the respective correlations
the product image scale developed by Nagashima (1970). This verifies the hypothesis that the new country image scale is unique and not simply a reflection of other variables (Peter and Churchill, 1981).
Conclusions Countries evoke different product images in consumers’ minds. However, because country of origin effects vary across countries, samples, and products, the results of this stream of research seem to lack consistency and generalizability. Among the suggestions made to advance the state of the art in the country of origin literature is more emphasis on measurement of the relevant constructs such as country image (e.g., Jaffe and Nebenzahl, 1984; Cattin et al., 1982; Han, 1989). To this end the present study was designed to develop and validate a multipleitem scale for measuring the construct of country image as distinct from product immge. The procedures recommended by Churchill’s (1979) paradigm for developing better measures were followed to capture the concept of country image. The resulting 16item semantic differential scale was developed by using 4 different data sets with students from 2 midwestern universities. Following a series of procedures for item generation, expert judges were used to select those items with high content validity. The reliability of the scale was established by the use of various indicators across different countries as well as the scale’s construct and discriminant validities. The present instrument is intended to be useful for practitioners and researchers alike. From a practical perspective, there are situations where a quantitative yardstick on country image may be necessary for managers. In marketing a country in a competitive industry such as tourism, it would be useful to have a baseline rating of the target market’s opinion of the country to be promoted. Similarly, when trying to attract foreign investment into a country, public and private promoters would benefit from information on the perceptions that the concerned parties have about a certain country. Under these and other similar situations, when the “product” is a country, choosing the most appropriate marketing strategy largely depends on the type of image held by the target ,market. An example that we are now faced with is the dramatic change in eastern Europe. With the radical change in the political, economic, and technological base of countries such as Poland, Romania, and Hungary, how will the perceptions that Westerners hold of these countries affect their ability to compete in the world market?
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These countries should be interested in determining exactly what their respective country image is with the Western world so that negative perceptions can be changed to allow them to better compete in the marketplace. This same concept can be applied to the changes occurring in western Europe as they face 1992. The perception that they are a solid economic and political block is critical for the success of their push to merge into a United States of Europe. The country image scale can provide a quantitative yardstick for these countries to determine the perception of other countries. This information then can be used to adapt persuasive communication campaigns to provide others with the “correct” image. If the image is positive, this should be stressed in an attempt to market the country’s products and services. The practical importance for marketers is that a favorable country image can be used to sell inferior products only temporarily. For example, country image can act as an information cue for consumers. This cue combines with an array of information cues, both intrinsic and extrinsic to the product, to aid the consumer in evaluating the product. This implies that there must be a match between country image and the image that one has of a country’s products (Bilkey and Nes, 1982). The theoretical interests of the scale development project are several. First, country image has three, not four, underlying dimensions. Past literature as well as research has asserted that social desirability is an underlying dimension of country image, but based on extensive testing, it was determined that social desirability is captured by the three factors of economic, political, and technological aspects. Second, researchers would benefit from a validated instrument specifically designed to measure country image. The scale would contribute to designing studies that are more explanatory and/or predictive in nature rather than purely descriptive. For example, the present scale would be applicable to determine if consumers’ evaluations of products from a country are consistent with their overall image of that country. The scale also would help to explain how consumers develop the country stereotypes they have by examining the scores for each of their dimensions. Additionally, the country image scale could be used to understand if and how different countries (as perceived by consumers) are likely to affect consumers’ evaluations of different product classes. Another possible application of the scale would be to categorize consumers into several image segments (e.g., low, medium, high) on their individual image scores for a single country. Alternatively, consumer segments could be identified based on their image scores across countries. It should be emphasized that this scale is strictly aimed at measuring one’s image of a country and should not be used to assess image of or attitudes toward products from a country. With respect to limitations of this scale, during the development and validation of the scale only a few countries were used. Further tests need to be carried out by using other countries as well as non-student samples to verify the stability and the validity of the scale. Along with the above, it should be further investigated as to whether social desirability continues to bc a component of the three factors identified and verified in this study. Future research could look at the ability to use measures of country image to predict the probability of purchase behavior; that is, what are the stereotypes that consumers have for countries that rank as planned economies with low standards of living and low literacy and level of industrialization? The next interesting issue is to determine if the stereotypes that form our country image also impact our probability of buying a certain product from that country.
Measuring a Multi-Dimensional
Appendix
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Construct
203
A
Judge Evaluation Form JUDGE
EVALUATION
FORM
Thank you for agreeing to participate as a judge in this scaling project. This is a crucial step in the development of an accurate scale of any concept. On the following pages there are 60 word/phrases that are generated to represent the concept of Country Image. In this study, for the purposes of scale development, the definition of country image is: One’s impressions of a country is based on a set of perceived ratings of the country along various dimensions. These dimensions include economic, social, cultural, geographical, technological and political characteristics which reflect a perception of that particular country. Your task is to judge each of the bipolar words/phrases as to how well they represent the concept of Country Image as defined above. Each set of bipolar words/phrases should be rated using the following scale: a. Clearly representative of a country’s image. b. Somewhat representative of a country’s image. c. Not representative of a country’s image. Only one of the above choices that best represents your opinion of the bipolar words/phrases and its ability to reflect the concept of Country Image, should be circled. The following example illustrates the task of selecting representative concepts of Country Image.
Introverted People
1. Extroverted People
a. Clearly representative of a country’s image.
b. Somewhat a country’s
rep. of image
Clearly representative of a country’s image.
Not rep. of a country’s image
Advanced Economy
2. Backward Economy @
@
b. Somewhat a country’s
rep. of image.
c. Not rep. of a country’s image
Please remember that this is a weeding out process. It is important that you realize that most or all may seem to clearly represent the concept. However, we are interested in the fine distinctions between the a, b, c categories.
204
Appendix
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B Original
29-Item
Country
Image
Scale
Country
Image
Scale
This is a survey to find out what a person thinks about a certain country. To measure this, we will ask you to rate the country that appears at the top of the page against a series of descriptors by placing a check (J) on the scale from one to seven that best reflects your judgment. There are no right or wrong answers. We are only interested in how YOU perceive the country. Consider the following example: By placing a check (J) in the middle, it would mean that you feel that the country that appears at the top of the page is neither pro-Western or pro-Communist. pro-Western
--: (I)
~. -. J: -. -: (2)’ (3)’ (4) (5)’ (6)
However, if you feel that the country the scale in the following manner: pro-Western
J: (1)
Please
_: (I)
pro-Communist (7)
pro-Western
you would
pro-Communist
pro-Communist
you would
-: -. -. ~. -. J. (2) (3) ’ (4)’ (5) ’ (6)
__: (7)
mark the scale in this
pro-Communist
ask if you have any questions. (Country Name) economically
1) economically developed
(1):(2):(3):(4):(5):(h):(7): underdeveloped
2) democratic system
~. ~. -. -. -. ~. _. (1)’ (2)’ (3)’ (4)’ (5)’ (6)’ (7)’
dictatorial system
3) civilian government
~. -. -. -. ~. -.(I)’ -.(2)’ (3)’ (4)’ (5)’ (6)’ (7)’ . -. . -. . -. . -. ~. . _. . -.
military government
4) extended family 5) large population 6) high per capita income
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-. -. -. -. -. ~. ~. (I)’ (2)’ (3)’ (4)’ (5)’ (6). (7)’ (I)’
mark
(2):(3):(4):0:(h):(7):
Or, if you feel that it is slightly manner: pro-Western
is extremely
-:
(2)’
(3)’
(4)’
(5)’
(6)’
(7)’
nuclear family small population low per capita income
Measuring
a Multi-Dimensional
7) exporter industrial products
J BUSN RES 1993:28:191-210
Construct
of -.(1)’ -.(2)’ -.(3)’
-. -. -. -. (4)’ (5)’ (6)’ (7)’
importer industrial products
-. -. -. (5)’ (6)’ (7)’
centrally planned
8) free market system
~.(1)’ -.(2)’ -.(3)’ -.(4)’
9) culturally diverse
_. -. -. ~. -. ~. (4)’ (5)’ (6)’ (7)’ -.(1)’ (2)’ (3)’
10) stable economic environment
-.(1)’ -.-. (2)’
11) exporter of agricultural products
-.(1)’
12) existence of a large middle class
-.(1)’ -.-. (2)’
13) large land mass 14) high level of technological research
-.(1)’
(3)’
_.-. (4)’
(5)’
-. -. (6)’ (7)’
_. -. -. _. -. -. (2)’ (3)’ (4)’ (5)’ (6). (7)’
(3)’
-.-. -. -. (4) * (5)’ (6)’ (7)’
_. -. -. _. -. ~. (2)’ (3)’ (4)’ (5)’ (6)’ (7)’
-. -. ~. _. -. ~. _. (1)’ (2)’ (3)’ (4)’ (5)’ (6)’ (7)’ -. -. -. -. (4)’ (5) * (6)’ (7)’
of
system
culturally uniform unstable economic environment importer of agricultural products existence of a small middle class small land mass low level of technological research
15) mass produced products
-.(1)’ ~.(2)’ -.(3)’
16) high literacy rates
-. -. -. -.(1)’ -.(2)’ -.(3)’ -.(41’ (5)’ (6)’ (7)’
17) exporter of raw materials
-.(1)’ -.-. (2)’
(3)’
18) pro-Western
-.(1)’ -.-. (2)’
(4)’ (3)’ -.-.
(5)’ -.(6)’ -: (7)
pro-Communist
19) high labor costs
-.(1)’ ~._. (2)’
(4)’ (3)’ -.-.
(5)’ -.6
low labor costs
20) existence of a welfare system
-.(1)’ -.-. (2)’
(4)’ (3)’ -._.
(5)’ -.(6)’ -: (7)
of 21) production high quality products
-.(1)’ -.-. (2)’
(3)’
-._. (4)’
(5)’
-. -. (6)’ (7)’
production low quality products
22) high standard of living
-. -. ~. -.-. (1)’ (2)’ (3)‘ (4)’
(5)’
~. -. (6)’ (7)’
low standard of living
23) stable political environment
-.(1). ~.(2)’ -.(3)’
-._. (4)’
(5)’
-. -. (6)’ (7)’
-: (7)
-. ~. -. -. (4)’ (5)’ (6)’ (7)’
handcrafted products low literacy rates importer of raw materials
lack of a welfare system
unstable political environment
of
205
206
J BUSN RES 1993:28:191-210
I. M. Martin
and S. Eroglu
24) large social class differences
--: (1)
---: ~. (2) (3)‘(4):(5):
~. ~. (6)’ (7)’
small social class differences
25) exporter of consumer products
-: (1)
-.
_. _. (6)’ (7).
importer consumer products
26) capitalist system
-: (1)
-: -. ~. ~. _. _. (2) (3)’ (4)’ (5)’ (6)‘ (7)’
27) high population inmigration rate
-: (1)
-: -. -. ~. (2) (3) ’ (4)’ (9’
~. (6)
28) predominantly industrialized
-: (1)
-. -: (2)’ (3)
(4):(5):
(6):(7):
predominantly non-industrialized
29) high unemployment rate
_: (1)
_: _: (2) (3)
-: --: (4) (5)
_: (6)
low unemployment rate
Appendix
(2)’
-: (3)
-: _: (4) (5)
of
communist system
_. . 6’)
_: (7)
high population out-migration rate
C
Revised
II-Item
Country
Image Scale Country
Image
Scale
This is a survey to find out what a person thinks about a certain country. To measure this, we will ask you to rate the country that appears at the top of the page against a series of descriptors by placing a check (J) on the scale from one to seven that best reflects your judgment. There are no right or wrong answers. We are only interested in how YOU perceive the country. Consider the following example: By placing a check (J) in the middle, it would mean that you feel that the country that appears at the top of the page is neither pro-Western or pro-Communist. pro-Western
-: (1)
-: -: (2) (3)
J: _: (4) (5)
However, if you feel that the country the scale in the following manner: pro-Western
is extremely
J. (1).(2):(3):(4):&q:(7).
Or, if you feel that it is slightly manner:
_: (6)
pro-Communist
_: (7)
pro-Communist
pro-Western
.
you would
you would
mark
pro-Communist
mark the scale in this
Measuring
a Multi-Dimensional
pro-Western
Please
J BUSN RES 1993:28:191-210
Construct
J.
207
pro-Communist
o:(2):(3):(4):(5):(6).(7):
ask if you have any questions.
(Country Name) 1) economically developed
-: (1)
-: -: (2) (3)
--: _: (4) (5)
_: (6)
-: (7)
economically underdeveloped
2) democratic system
-: (1)
-: -: (2) (3)
_: _: (4) (5)
-:
-: (7)
dictatorial system
3) mass produced products
_: (1)
_: _: (2) (3)
-: -: (4) (5)
-: (6)
-: (7)
handcrafted products
. -. -. (6)’ 6’)’
military government
4) civilian government
(1)’
(2)’
(3)’
(4)’
0’
(6)
5) predominantly industrialized
-: (1)
-: -: (2) (3)
_: _: (4) (5)
_: (6)
-: (7)
predominantly non-industrialized
6) high labor costs
-: (1)
-: -: (2) (3)
-: -: (4) (5)
-: (6)
-: (7)
low labor costs
7) high literacy rates
-: (1)
-: -: (2) (3)
_: _: (4) (5)
-: (6)
-: (7)
low literacy rates
8) free market system
_: (1)
_: _: (2) (3)
-: -: (4) (5)
-: (6)
-: (7)
centrally planned
9) existence of welfare system
-: (1)
-: -: (2) (3)
_: _: (4) (5)
-: (6)
-: (7)
lack of a welfare system
10) stable economic environment
-. ~. -. -. -. -. -. (1)’ (2)’ (3)’ (4)’ (5)’ (6)’ (7)’
11) exporter of agricultural products
-: (1)
-: -: (2) (3)
12) production of high quality products
-: (1)
-. -. ~. -: ~. _. (2)’ (3)’ (4)’ (5)’ (6)’ (7)
13) high standard of living
-: (1)
-: -: (2) (3)
O’(5)’
14) high level of technological research
-: (1)
(2)’
(4)’
u)’
_: -: (4) (5)
(5)’
-: (6)
unstable economic environment
-: (7)
(6)’
0’
(6)’
(7)’
system
importer of agricultural products production IOW quality products .
low standard of living
f
low level of technological research
of
208
J BUSN RES 1993:28:191-210
Appendix
I. M. Martin and S. Eroglu
D
The Nagashima
Product
Image
Scale
(Country Name) 1) Expensive
-: (I)
-: -: (2) (3)
_. --: (4)’ (5)
2) Reasonably Priced
-: (I)
-: -: (2) (3)
--: ~. ~. -: (4) (5)’ (6)’ (7)
3) Reliable
-: (I)
~. ~. -: _: (2)’ (3)’ (4) (5)
4) Luxury
_: (6)
-: (7)
Inexpensive
Unreasonably Priced
-. -: (6)’ (7)
Unreliable
items
Necessary
Items
(1):(2):(3):(4):(5):(h):(7): 5) Heavy Industry Products 6) Careful and meticulous workmanship 7) Technically Advanced
-: (1)
-: -: (4) (5)
-: -: (2) (3)
(2).
(I)’ .
(3)’ .
(4)’ .
(5)’ .
-: (6)
-: (7)
. -. -. . (6)’ (7)
Not so careful meticulous workmanship
.
:
Technically Backward
:
Hand
.
Mostly
.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(I)’
(2)’
(3)’
(4)’
(5)’
(6)’
(7)
8) Mass Produced 9) World Wide Distribution
. (1)
. (2)
. (3)
. (4)
.. -. (5)
Light Manufacturing Products
(6)
. -. (7)
Domestic
Distribution .
10) Inventive
Made
Imitative
(1):(2):(3):(4):(5):(6):(7). 11) Pride of ownership 12) Much Advertising
-:
-:
(1)
(2)
-: (3)
. (1)
-: (4)
(3)
(7)
(5)
(6)
: -: (7)
-: -: (4) (5)
-: (6)
(4)
-: (1)
-: -: (2) (3)
14) Large choice of size & model
-: (1)
~. ~. -: -: (2)’ (3)’ (4) (5)
16) Clever use of color
(I)’
_:
(6)
.
13) Recognizable brand names
15) More concerned-. with outward appearance
_:
(5)
. (2)
_:
Not much pride of ownership Little Advertising Unrecognizable brand names
-: (7)
Limited choice of size & model
~. -: (6)’ (7)
-: -. -. ~. ~. ~. (2)’ (3)‘ (4)’ (5)’ (6)’ (7)
More concerned with performance .
(1):(2):(3):(4):(5):(6):(7).
Not clever use of color
Measuring
a Multi-Dimensional
17) More for young people
J BUSN RES 1993:28:191-210
Construct
(1):
_: -. -. ~. -. -. (2)’ (3) ’ (4)’ (5) ’ (6)’ (7)
209
More for old people
18) More for men
-. -.-. -. -. . _: _: (1) (2) (3)’ (4)’ (5)’ (6)’ (7)
More for women
19) Upper class
._____: _: -: -: -: -: -: (1) (2) (3) (4) (5) (6) (7)
Lower class
20) Exclusive
. -.-. . . -. . _: _. . -.-. . (1) (2) (3) (4) (5) (6) (7)
Common
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