The globalization of markets since the 80's has enhanced the urgency of research on the impact of country-of-origin image (CO) in cross-national consumer behavior. A rich harvest of such studies has consequently been generated. Prior weaknesses in such studies, such as poor handling of a complex construct, single cue studies and lack of methodological rigor, are being addressed. This study is in the genre of such research where the nature and dimensionality of the CO construct is examined using confirmatory factor analysis. Findings suggest that the theorized structure needs modification. Critical reviews on country-of-origin (CO) studies have identified several major inadequacies which have thus far prevented a definitive identification of the precise nature of the impact of CO in influencing purchase behavior. How complex is the construct? In other words, what is its dimensionality? The focus of this study is a rigorous examination of the nature of the country-of-origin construct and a confirmation of the scales that have been developed to measure it. The relative importance of country and general product image (GCA, GPA) cues in shaping purchase behavior is not entirely clear based on past research.
Johansson, Douglas, and Nonaka (1985) claimed that the CO effect, as a result of single cue studies, may be overstated and that its effects may be contaminated by the effect of other cues. Heslop, Liefeld and Wall (1987) stated that the CO effect gained in strength with product complexity, increased risk, and decreased purchase frequency. Bilkey and Nes (1982) reported that a negative CO image was not overcome by a well known brand name. An extensive literature search was conducted in the design of the questionnaire that was used in this study. Data were gathered from the adult population of a large midwestern metropolitan area which is highly heterogenous in terms of ethnic composition. These people represented the then current and potential users of automobiles -- both domestic and foreign. In order to adequately capture the ethnic flavor of the metropolitan area, relevant ethnic associations were contacted, membership lists acquired and representative samples selected therefrom.
Blank questionnaires were hand delivered to the selected respondents and completed questionnaires were collected within the next two weeks. In order to achieve a high response rate, the president/committee members of these associations were approached and requested to encourage their members to participate. A total of 678 completed and useable questionnaires were returned from the 1025 that were originally placed, a 66% response rate. A second objective of the statistical analysis presented in this paper was to respecify the measurement model (if necessary) through an understanding of the dimensionality of the three concepts of interest. Maximum likelihood estimation procedures available in the statistical package LISREL 7 (Joreskog and Sorbom 1989) were used for the application of the full information method. The covariances in the input data set were tested against the covariances expected as the result of the a priori specified model. When the parameters of the model are estimated through the method of maximum likelihood (an option in LISREL), the differences between the relationships reflected in the data and those specified by theory are tested using a chi-square statistic.
The chi-square statistic tests the overall fit of the model to data, smaller values of the statistic typically representing better fit. Oblique centroid multiple groups factor analysis (MGRP) available in the statistical package ITAN (Gerbing and Hunter 1988) was used for the application of the limited information method. The process of model respecification described in this paper was strongly driven by theory. In other words, model respecification based purely on data (and possessing no theoretical rationale) was avoided. The initial model (Figure 1) consisted of three constructs (unobservable variables): GCA, GPA, and SPA, and 40 indicators (observable variables). GCA was measured using 12 indicators, GPA by 18 indicators, and SPA through 10 indicators. The indicators of goodness-of-fit obtained through the analysis of the model using LISREL 7 indicated a very poor fit (Table 2). The poor fit was also reflected in large standardized residuals and modification indices. Similarly, the inter-item correlations generated by ITAN indicated the three constructs were being measured using indicators which lacked internal consistency.
