Of products and tourism destinations: An integrative, cross-national study of place image

JBR-08543; No of Pages 9 Journal of Business Research xxx (2015) xxx–xxx

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Journal of Business Research

Of products and tourism destinations: An integrative, cross-national study of place image Statia Elliot a,⁎, Nicolas Papadopoulos b,1 a b

School of Hospitality, Food and Tourism Management, University of Guelph, Guelph, Ontario, Canada N1G 2W1 Sprott School of Business, Carleton University, Ottawa, Ontario, Canada K1S 5B6

a r t i c l e

i n f o

Article history: Received 1 April 2013 Received in revised form 1 June 2014 Accepted 1 October 2014 Available online xxxx Keywords: Product-country image Tourism destination image

a b s t r a c t Despite recognition that places have images, and that images influence consumers (Rojas-Mendez, 2013), place image research has been challenged by a lack of breadth. Studies are generally limited to the perspective of one field of study, mainly Product-Country Image (PCI) or Tourism Destination Image (TDI), measure the images of individual places without reference to a comparative perspective, and rarely consider the influence of a broader gestalt perception of place (Zeugner-Roth & Zabkar, 2015). To explore the multi-dimensional nature of place image and its influence on buyer behavior, this study adopts an interdisciplinary approach by incorporating product, country, and tourism variables simultaneously. An integrated model is empirically tested in two countries using four target countries in each case, resulting in eight model tests. Results reveal how the subcomponents of place image are related: cognitive country image has the greatest influence on product evaluations; affective country image has the greatest influence on destination evaluations; and notably, product beliefs influence tourism receptivity, supporting the hypothesized cross-over effect from PCI to TDI. © 2015 Elsevier Inc. All rights reserved.

1. Introduction The power of image as an intangible cue to influence buyer behavior has long been recognized by marketers and market researchers (Dichter, 1985). Its use for geographically defined places, more broadly termed place branding or marketing, is the most macro level application to date. In recent years, the amount of research and practice in the place branding field has intensified (Gertner, 2011). Conceptually, a positive place brand is claimed to create and sustain wealth (Anholt, 2003), and in practice, place cues are commonly used in advertising (Papadopoulos, El Banna, Murphy, and Rojas-Mendez, 2012). The importance of place branding research is reflected in the range of fields that study the phenomenon; most notably, studies are found in marketing (Fetscherin, 2010), tourism (Herstein, 2012), and public diplomacy (Gertner, 2011). For consumers, particularly in developed countries where both the incidence of international travel and the availability of foreign goods continue to grow, the associations that come to mind for any given place are likely to reflect an array of dimensions, from tourism to technology (Rojas-Mendez, 2013). However, most studies are still undertaken within the context of one subject domain, for one place at a time, limiting the contribution of extant research to place image theory and the generalizability of findings. As well, place ⁎ Corresponding author. Tel.: +1 519 824 4120x53970. E-mail addresses: [email protected] (S. Elliot), [email protected] (N. Papadopoulos). 1 Tel.: +1 613 520 2600x2382.

branding studies are predominantly qualitative, lacking testable models or hypotheses (Gertner, 2011). More narrowly focused, yet encouragingly substantial and expansive, is the body of empirical theory-based place image research in two related sub-fields: Product-country image (PCI) and tourism destination image (TDI). Both fields focus on relationships between place image and buyer behavior, for product evaluations and purchase in the PCI context and for destination evaluations and choice in TDI. Nevertheless, despite their common interests in place image and buyer behavior, contributions to international marketing and place branding, and private and public audience cross-overs, research empirically connecting the two is very limited. Images are mental schemata that reflect a complex web of associations of both cognitive and affective components stored in memory (Hawkins, Best, and Coney, 2001). Consistent with this definition, the overall image of a place will influence how its products and destinations are viewed—and its manifestations as a producer and a tourism destination may also interact with each other. The suggestion that place-related behavior is influenced by affective as well as cognitive factors is supported by research both in tourism (e.g., Papadopoulos, Elliot, and De Nisco, 2013) and in product-related research fields such as ethnocentrism (e.g., Shimp and Sharma, 1987) and animosity (e.g., Klein, Ettenson, and Morris, 1998). PCI studies have shown that country image influences evaluations of that country's products, sometimes referred to as a halo effect (Han, 1989), most applicable when consumers are unfamiliar with foreign products. Verlegh and Steenkamp's (1999) meta-analysis of 41 empirical PCI studies found the average effect size

http://dx.doi.org/10.1016/j.jbusres.2015.08.031 0148-2963/© 2015 Elsevier Inc. All rights reserved.

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

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S. Elliot, N. Papadopoulos / Journal of Business Research xxx (2015) xxx–xxx

of country image to be 0.39, considered a medium to large effect on product evaluations. TDI studies, by contrast, do not typically disaggregate a construct for country image, often mixing together country items (e.g. security) and product items (e.g. attractions) as part of a destination image construct. They do show, however, that TDI influences destination selection (Goodrich, 1978) and traveler satisfaction (Bigne, Sanchez, and Sanchez, 2001), as evidence of an image-to-behavior effect. However, while each of the PCI and TDI fields has been studied extensively, the interaction between the product- and destination-related images, and between them and the overall image of a place, remains uncertain. The dearth of research in this area reflects the broad scope of the phenomenon under observation, and represents a fundamental research gap that impedes the cross-pollination of ideas between the two fields and the development of a holistic understanding of the image concept. The present study aims to address this gap through an interdisciplinary approach that incorporates country, product, and destination image variables in a single integrative model, enabling the examination of image effects simultaneously within each of the product and tourism domains as well as the interactions between the two. The model examines cross-over effects between the constructs in two ways: i. Drawing from evidence that suggests country image influences evaluations of that country's products, it postulates whether this influence might extend further from product evaluations to receptivity to that country as a tourism destination; and, vice-versa, ii. Drawing from evidence that suggests country image influences evaluations of that country as a tourism destination, it postulates whether this influence might extend further from destination evaluations to receptivity to products from that country. In other words, the model examines whether consumers' positive associations with a country, as in the case of, for example, French quality of life, may engender, first, positive beliefs about French products (e.g., refined wines, high fashion) and tourism destinations (e.g., Paris, Côte d'Azur), as well as, second, cross-over effects between the two, both direct (e.g., wines to rural agri-tourism and vice-versa) and indirect (e.g., upscale tourism to upscale products and vice-versa). Like the halo effect, such influences may not be product- or place-specific but reflect a general extension of positive or negative associations from image to beliefs to behavior. The focus of the research is on an extensive empirical test of the integrative model, carried out in two countries and for the images of four target countries, resulting in a total of eight tests to assess the model's cross-country applicability. The overall research goal is to contribute to marketing theory an effective approach to examining and identifying place image that encompasses both products associated with the place and the tourism image of the place itself. Through this process, image dimensions can be examined and identified both at the general country level as well as specifically with regards to products and tourism. The following sections focus on the theoretical background of the study, including an overview of relevant research and description of the model; the study's methodology; presentation and discussion of the main findings; and conclusions, limitations, and implications for research and practice. 2. Theoretical background 2.1. Overview of past research From the early work of Boulding (1956), image has been considered a significant predictor of human behavior that influences thoughts, feelings, and actions. In particular, marketing research confirms its strong influence on consumer behavior in a number of contexts, including store image (Thang and Tan, 2003), brand image (Aaker and Joachimsthaler, 2000), and corporate image (Stuart, 1999). Concerning specifically place image, the phenomenon has been studied most extensively within the sub-fields of TDI, in the tourism literature, and PCI

(also commonly referred to as “country of origin” or “brand origin”), in international marketing. One distinguishing characteristic between research in these two fields has been that TDI considers any level of place, from nations to regions or specific cities or villages, whereas PCI tends to focus predominantly on the country level. Collectively, place image is acknowledged as a significant factor not only in tourism destination selection (Beerli and Martin, 2004) but more broadly in foreign product evaluation (Papadopoulos and Heslop, 2002). In the PCI context, country image can be defined as the “overall perception consumers form of products from a particular country, based on their prior perceptions of the country's production and marketing strengths and weaknesses” (Roth and Romeo, 1992:480). Though an early PCI study (Papadopoulos and Heslop, 1986) found a correlation between travel and product evaluations, this potential relationship has been largely ignored by both the TDI and PCI streams, with only a small handful of exceptions which are themselves limited for various reasons in terms of usefulness and/or relevance. For example, Mossberg and Kleppe (2005) identify substantial overlap between the concepts of country image and destination image, and conceptualize an integrated model, but never test it empirically. Heslop, Nadeau, O'Reilly, and Luk (2005) incorporate country-level constructs from PCI within a TDI model, but do not include product measures. Most recently, Zeugner-Roth and Zabkar (2015) assess the influence of country image and destination image on consumer decisions, but again, omit independent product measures. As a result, there is no extant research combining measures of general country, product, and tourism image except for two studies that are limited in scope (range of relationships and tests) and/or country applications (Elliot, Papadopoulos, and Kim, 2011; Elliot, Papadopoulos, and Szamosi, 2013) and produced inconclusive results for the PCI–TDI cross-over effect. The present research extends existing knowledge by testing more relationships than any previous study, and expanding the empirical test cross-nationally by using two sample and four target countries, all of which makes it possible to assess the PCI–TDI cross-over effects more conclusively. Results tell us more about the influence of a place's product beliefs on its tourism beliefs, and vice-versa, contributing to place image theory and to marketing practice. 2.2. Model development In order to explore how consumer perceptions of place might influence attitudes about products and destinations simultaneously, an integrated model is proposed to incorporate constructs to measure both tourism and product related consumption behavior patterns. The cornerstone relationships of place image theory that are adopted in this study are three-fold: (i). Country image affects beliefs. The rationale for this is both intuitive and theory-based: Images are mental schemata, and since schemata are arranged hierarchically in the mind (Nejad and Winsler, 2000), it follows that a country's overall image might influence how consumers view it as a destination and producer, and that the latter two may interact. Additionally, both PCI (Orbaiz and Papadopoulos, 2003) and TDI (Baloglu and McCleary, 1999; Beerli and Martin, 2004) distinguish between cognitive, tangible image cues (i.e. quality, wealth, education, technology), and the affective, or emotional components of place image (i.e. pleasant, friendly, trustworthy, safe). Thus, relationships are modeled from two country image constructs—cognitive and affective—to product and destination beliefs. (ii). Familiarity affects beliefs. From the early study of place image, the influence of familiarity, meaning knowledge of and/or experience with a destination (Gunn, 1972), and foreign products (i.e. use, ease to find) has been considered (Papadopoulos et al., 1988). This relationship has since been confirmed in both the TDI (Baloglu, 2001) and PCI (Orbaiz and Papadopoulos, 2003) fields,

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

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in the context of, respectively, tourism and products. Thus, relationships are modeled from both product and destination familiarity to product and destination beliefs. (iii). Beliefs affect behavioral intent, or receptivity. The broader term receptivity is used to incorporate not only the consumers' willingness to buy or travel but also his/her overall assessment of places as producers (i.e. open to imports, ownership pride) and tourism destinations (i.e. ideal country, good destination). Again, this relationship has been confirmed by various studies in both TDI (Beerli and Martin, 2004) and PCI (Heslop, Papadopoulos, Dowdles, Wall, and Compeau, 2004). Thus, relationships are modeled from product and destination beliefs to product and destination receptivity. Of particular interest here are the interactions between the two streams, namely, consumer attitudes about products, on the one hand, and destinations, on the other, rather than the relationships within each stream. Model constructs were selected from among those that have been proven in earlier studies, resulting in four types of constructs, with two specific constructs in each case, measured indirectly through multiple indicators: Country Image (cognitive and affective) and Beliefs, Familiarity, and Receptivity (each for products and destinations). Specific measures are listed in Table 3. Combining the known relationships within each of TDI and PCI, with the cross-over relationships that are the unique focus of the integrated model, results in the conceptualization that is presented in Fig. 1. In total the model posits 21 hypothesized relationships between and among the eight constructs, as listed in Table 1.

Table 1 Tourism and product country image hypothesized relationships. H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12 H13 H14 H15 H16 H17 H18

3. Methodology

H19

3.1. Country selection

H20

To effectively satisfy the theoretical objective, the study is conceptualized to involve empirical testing in two countries, South Korea and Canada, with regards to the images of four countries, of which three

H21

A country's cognitive image is positively related to that country's affective image. A country's cognitive image is positively related to beliefs about that country's products. A country's cognitive image is positively related to beliefs about that country as a travel destination. A country's affective image is positively related to beliefs about that country's products. A country's affective image is positively related to beliefs about that country as a travel destination. A country's affective image is positively related to receptivity toward that country's products. A country's affective image is positively related to receptivity toward that country as a travel destination. Beliefs about a country's products are positively related to receptivity toward that country's products. Beliefs about a country's products are positively related to receptivity toward that country as a travel destination. Beliefs about a country as a travel destination are positively related to receptivity toward that country's products. Beliefs about a country as a travel destination are positively related to receptivity toward that country as a travel destination. Consumer's familiarity with a country's products is positively related to their beliefs about that country's products. Consumer's familiarity with a country's products is positively related to their beliefs about that country as a travel destination. Consumer's familiarity with a country's products is positively related to receptivity toward that country's products. Consumer's familiarity with a country's products is positively related to receptivity toward that country as a travel destination. Consumer's familiarity of a country as a travel destination is positively related to their beliefs about that country's products. Consumer's familiarity of a country as a travel destination is positively related to their beliefs about that country as a travel destination. Consumer's familiarity of a country as a travel destination is positively related to receptivity toward that country's products. Consumer's familiarity of a country as a travel destination is positively related to receptivity toward that country as a travel destination. Consumer's familiarity of a country as a travel destination is positively related to their affective image of that country. Consumer's familiarity with a country's products is positively related to their affective image of that country.

Fig. 1. Integrated model of place image.

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

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(U.S., Japan, and Australia) are common to enable comparisons, and the fourth is the other of the two sampled countries (South Korea in Canada and Canada in South Korea). This configuration makes it possible to test the model across eight different country dyads so as to enhance the generalizability of the findings. The sampled and target countries are in line with suggestions from the literature concerning the need for both diversity and similarity for effective comparative research (see Craig and Douglas, 2005; Malhotra, Agarwal, and Peterson, 1996; Sekaran, 1983). The sampling locations provide a diverse view of developed/developing and Western/Asian consumers from two countries that have close trade and tourism links, and that are important and yet different internationally from the product (mostly South Korea) and tourism (mostly Canada) perspectives. The three comparator countries selected provide the best possible set for a study of both travel and product images from the standpoint of the two sample countries. The U.S. and Japan have a major global presence in products, unlike Canada and Australia; Canada, Australia, and the U.S. are primarily Anglo-Saxon countries with many differences but also comparable tourism attractions; the U.S. is the prime short-haul destination for Canadians and long-haul destination for South Koreans, while Japan holds the equivalent but reverse position as an important overseas destination for South Korea (short-haul) and Canada (long-haul); the countries enable within-sample comparisons between Western (U.S., Canada, Australia) and Asian (Japan, South Korea) product origins and travel destinations; and the identified countries are known to respondents to varying degrees, which is desired in order to provide the insights sought. 3.2. Data collection The study uses a structured self-administered questionnaire, developed in English and translated to Korean using back-translation to ensure equivalency (Brisles, 1970; Craig and Douglas, 2001). It consists of a set of standard demographics questions and three main sections intended to evaluate the test countries, their products, and their tourism characteristics, respectively with 8, 10, and 8 items each (26 items total for each target country; see Table 3). Scale items proven in past research are used where appropriate, selected based on a thorough review of both the TDI and PCI literatures, and new constructs are built using proven variables for both PCI measures (e.g. from Orbaiz and Papadopoulos, 2003; Hauble, 1996), and TDI measures (e.g. from Echtner and Ritchie, 1991; Baloglu and McCleary, 1999; Bigne et al., 2001). Seven-point bipolar adjective scales are used for the measures. The fieldwork used an intercept of adults attending major travel shows in South Korea and Canada (with attendance of over 80,000and 20,000 visitors, respectively). Trained interviewers, working under the direct supervision of the researchers, approached show visitors randomly to explain the purpose of the study and provided those who agreed to participate with a copy of the questionnaire, which they could fill out at specifically set tables. After discarding incomplete questionnaires, the total sample sizes are n = 307 for Canada and n = 349 for South Korea. The demographic profiles of the realized samples indicate that both are representative of the active consumer population in the respective countries; in other words, the respondents tend to be urban consumers, younger in age, better educated, and with higher incomes than the respective overall population norms. The South Korean sample consists of 48% males, with 73% of the total having university education. The average household size is 4 persons, and average annual household income, converted from Won to Canadian dollars for comparison, is fairly representative of the active consumer population at approximately $34,000. The sample is younger than the population on average, but a substantive proportion of 39% is 30 years and older. The Canadian sample also consists of 48% males, with over 70% having at least some college or university, a mode of 2–3 in household size, and medians of annual household income and age of $75,000 and 40 years, respectively.

In summary, both samples comprise respondents who are likely to reflect the views of consumers knowledgeable about and with interest in travel and product imports, thereby comprising a good base for the study. 4. Analysis and findings 4.1. Measurement model validity Factor Analysis was used to assess the degree to which responses are consistent across the items within each of the exploratory factor constructs. As a first step, Cronbach's alpha (a lower bound for reliability, as noted, among others, by Sijtsma, 2009) measures convergent validity. Individually, all alphas except one (CA-AU Product Familiarity, 0.518) are near 0.60 or higher, reaching 0.884 for SK-JP Product Beliefs, but all aggregate scores are above the minimum threshold of 0.60, which is commonly accepted in the case of predictor tests (Malhotra, 2002; Shay and Baack, 2004; Sood and Nasu, 1995); in light of the multiple models and measures comprising this study, the validity of the constructs is considered adequate. Discriminant validity is measured by estimating the correlations between the latent variables, supported if correlations are not greater than 0.85, considered “excessively high” by Kline (2005:73). The correlations are acceptable and suggest discriminant validity (Table 2) with only a few exceptions. These include four instances where correlations are high (Cognitive Image with Affective Image, SK-CA 0.89 and CA-AU 0.92; Destination Beliefs with Destination Receptivity, SK-AU 0.92; and Product Beliefs with Product Receptivity, SK-CA), and two where they are borderline at 0.85 (Destination Beliefs with Destination Receptivity SK-US; Product Beliefs with Product Receptivity CA-US). In cases of high correlation, collapsing constructs was considered, but not done, since the separation allows for the exploration of the hypothesized relationships and is grounded in extant theory. Furthermore, no more than one high correlation per model exists for all but one model (SK-CA has two), and all correlations are positive, except for Product Familiarity, which displays negative correlations in half the models. In sum, there is sufficient and adequate validity, but the correlations are noted as they may influence subsequent modeling. The variance explained in each country model is also included in Table 2, with an acceptable range from 56.3% to 67.2%. Next, a hierarchical approach toward building a final model is followed using Confirmatory Factor Analysis (CFA) for each of the eight sample-target country combinations. This process required several iterations, because the models would not converge to an admissible solution when all 21 hypothesized relationships were included (see Fig. 2). To derive one “best” model that fit for each case, six paths were dropped, all of which are measurable through reduced formula equations, produced by LISREL for each exogenous to endogenous construct path. By eliminating paths, a generalizable model with reasonable fit for the eight cases was found. 4.2. Measurement model reliability Table 3 presents the standardized path coefficients for all sampletarget country models, with estimates of measurement error in brackets. The CFA reliability was evaluated through assessing composite construct reliability (CCR), generally considered acceptable when values are N 0.60 (Bagozzi and Yi, 1988). The construct validity meets the criterion for all the South Korea models, and two of the four Canada models (Table 3). Marginally below are the Cognitive Country Image construct in two cases (CCR = 0.54; 0.58) and Product Receptivity in two cases (CCR = 0.52; 0.56). Table 3 also includes the R2 values averaged across the eight models, as a measure of the explained variance, and the model fit statistics (χ2/d.f., RMSEA, CFI). For Product Receptivity, two country models, SK-US and CA-US, would not converge when open to imports was included as a measure.

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

S. Elliot, N. Papadopoulos / Journal of Business Research xxx (2015) xxx–xxx

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Table 2 Summary of correlations of independent variables. Correlations1 between

SK-US

SK-JP

SK-AU

SK-CA

CA-US

CA-JP

CA-AU

CA-SK

CI2-Cognitive Image CI-Affective Image CI-Product Beliefs CI-Destination Beliefs CI-Product Familiarity CI-Destination Receptivity CI-Product Receptivity DestBeliefs-DestReceptivity ProdBeliefs-ProdReceptivity Cumulative variance explained (%)

1.00 .48a .62a .40a .21a .48a .47a .85a .71a 61.2

1.00 .53a .58a .48a .19a .48a .60a .82a .47a 59.1

1.00 .80a .56a .47a −.06 .54a .46a .92a .73a 56.3

1.00 .89a .54a .49a −.20a .56a .57a .74a .90a 63.0

1.00 .81a .59a .37a .40a .58a .61a .77a .85a 63.2

1.00 .80a .41a .33a .37a .32a .45a .63a .80a 67.2

1.00 .92a .50a .43a −.09 .48a .49a .75a .41a 63.8

1.00 .81a .55a .31a .16b .44a .42a .64a .44a 65.4

1 2 a b

LISREL path analysis using maximum likelihood. CI = cognitive country image. p N 0.01 (2-tailed). p N 0.05 (2-tailed).

This reflects what would seem to be an interesting consumer dilemma for South Koreans and Canadians alike. While both are willing to buy American goods, and are proud to own them, they are less receptive to more imports, perhaps due to the high level of imports the U.S. already holds within both countries relative to other foreign importers. For Destination Receptivity, the three items willing to travel, good tourism destination, and ideal country were not predicted to load together as a measure of Destination Receptivity but they do, in fact, perform well as a final dependent measure within the model. In summary, while the 26 variables' performance varies across the eight models, overall they represent a good set of measures with broad applicability that can be used in order to identify unique strengths and weaknesses. Turning to the measures of fit shown in Table 3, the normed chisquared statistic (χ2/d.f.) is less than 5.0 and closer to 2.0, ranging from 2.72 to 3.51, suggesting that the model is a good fit with the data (Bollen, 1989). The RMSEA scores are all around 0.80, which suggests reasonable error of approximation (Kline, 2005:139). Lastly, the

Comparative Fit Index (CFI) is greater than 0.90 for all tests, again suggesting reasonably good fit (Kline, 2005:140). 4.3. Model invariance test To test for model invariance and determine the cross-cultural applicability of the constructs, multi-group structural equation modeling is used (Steenkemp and Baumgartner, 1998). Consideration is given primarily to assessing configural invariance to identify whether the measurement model can be conceptualized in the same pattern across countries. A comparison of the statistical significance of the difference in Goodness of Fit between the constrained and unconstrained models suggests that the model is, in fact, invariant. Through constraining loadings in the null hypothesis test, the model appears to also be partial metric invariant. The Full Information Maximum Likelihood method is used to fit the model to the two multivariate data sets. The evaluation scores for the U.S. are presented in Table 4. The tests assess the null hypothesis (H0),

Fig. 2. Final integrated model of place image.

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

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Table 3 Measurement model variable loadings by construct1.1 South Korea n = 349

Canada n = 307

Ave R2

U.S.

JA

AU

CA

U.S.

JA

AU

SK

Cognitive Country Image Quality of life Wealth Technology level Education CCR2

.56(.69) .54(.70) .53(.72) .63(.61) .65

.59(.66) .52(.73) .51(.74) .60(.64) .64

.67(.55) .54(.71) .54(.71) .69(.52) .70

.60(.64) .51(.74) .63(.60) .72(.48) .71

.53(.72) .29(.91) .46(.78) .60(.64) .54

.54(.71) .39(.84) .66(.57) .82(.33) .70

.62(.62) .34(.88) .38(.86) .64(.59) .58

.74(.46) .48(.76) .50(.75) .69(.52) .69

.37 .22 .28 .46

Affective Country Image Pleasant Friendly Safety Trustworthy CCR

.58(.67) .62(61) .62(.62) .83(.32) .76

.74(.45) .64(.59) .51(.74) .71(.50) .75

.67(.55) .63(.60) .71(.50) .71(.49) .78

.75(.43) .61(.63) .65(.57) .74(.46) .78

.65(.57) .73(.46) .65(.58) .78(.39) .80

.68(.4) .77(.41) .81(.35) .84(.30) .87

.70(.51) .72(.48) .79(.38) .81(.35) .85

.71(.49) .61(.63) .73(.47) .78(.39) .80

.47 .45 .47 .60

Product Beliefs Quality Workmanship Innovativeness Value for money CCR

.71(.50) .68(.54) .74(.45) .81(.35) .82

.70(.51) 73(.46) .83(.31) .78(.39) .85

.65(.57) .60(.64) .67(.55) .64(.59) .74

.61(.63) .76(.43) .68(.54) .66(.56) .77

.71(.50) .70(.51) .59(.65) .77(.41) .79

.70(.51) .72(.47) .66(.57) .78(.39) .81

.61(.63) .70(.50) .65(.57) .73(.47) .77

.70(.52) .79(37) .65(.57) .68(.54) .80

.45 .51 .47 .54

Destination Beliefs Appealing scenery Quality attractions Range activities Value for money CCR

.74(.45) .79(.37) .86(.26) .59(.65) .84

.75(.44) .81(.35) .85(.27) .38(.85) .80

.76(.42) .79(.37) .86(27) .55(.70) .83

.75(.44) .78(.39) .77(.40) .51(.74) .80

.69(52) .74(45) .82(.32) .76(.46) .84

.73(.47) .77(.41) .84(.29) .53(.72) .81

.65(.48) .84(.30) .88(.23) .71(.50) .86

.75(.43) .87(.25) .87(.24) .73(.46) .88

.53 .64 .72 .37

Product Familiarity Use Ease to find Satisfaction CCR

.38(.86) .33(.89) .96(.07) .61

.68(.53) .76(.43) .65(.57) .74

.79(.38) .66(.57) .46(.79) .68

.74(.45) .72(.48) .40(.84) .66

.62(.62) .35(.88) .72(.48) .59

.69(.52) .44(.80) .78(.40) .68

.86(.26) .57(.68) .27(.93) .61

.80(.36) .59(.65) .40(.84) .63

.50 .33 .39

.30(.91)

.22(.95)

.32(.90)

.46(.79)

.50(.75)

na

.82(.33)

.46(.79)

.23 .64

Product Receptivity Open to imports Willing to buy Ownership pride CCR

na .87(.25) .50(.75) .65

.53(.72) .70(.51) .59(.66) .64

.35(.86) .82(.31) .71(.51) .62

.47(.78) .74(.46) .54(.71) .61

na .71(.50) .46(.78) .52

.46(.79) .88(.23) .45(.80) .64

.52(.73) .65(.58) .47(.77) .56

.49(.76) .76(.43) .55(.70) .63

.24 .59 .29

Destination Receptivity Willing to travel Ideal country Good destination CCR

.56(.69) .53(.72) 79(.37) .67

.78(.39) .58(.66) .73(47) .74

.73(.47) .58(.67) .69(.53) .71

.58(.67) .72(.48) .82(.29) .76

.68(.54) .65(.58) .80(.36) .75

.68(.54) .65(.58) .80(.36) .75

.71(.49) .66(.56) .81(.34) .77

.62(.61) .83(.31) .90(.19) .83

.44 .45 .66

3.32 .082 .92

3.16 .079 .93

2.72 .070 .93

2.74 .071 .94

3.51 .091 .92

3.03 .081 .93

3.77 .095 .91

3.39 .088 .93

Destination Familiarity Coun. knowledge CCR

Model fit χ2/d.f. RMSEA CFI 1 2

Standardized path coefficients (estimates of measurement error). Composite Construct Reliability (CCR) = (∑standardized loadings)2 / (∑standardized loadings)2 + ∑εj where εj is the measurement error.

that the model is identical across sample countries (South Korea and Canada), and the alternative hypothesis test (H1), that the model is not identical. The H0 model fit, the Root Mean Square Error of Approximation (RMSEA) = 0.083, indicates a good fit of the “equal” or “identical” model to the data. To compare the results of the null and alternative hypotheses, H0 and H1, the Chi-square difference, shown in Table 4, supports the null hypothesis, meaning that the cross validation of the model is supported

by the two-country data. The test was repeated for Japan and Australia, and while stable, results were inferior for the unconstrained models, suggesting partial invariance, which is reasonable. 4.4. The structural model To test the study hypotheses, the structural parameters produced by SEM for each country-of-interest model are assessed in terms of their

Table 4 Cross-country hypothesis test of model invariance. US model 2

Alternative (Halt): χ Unconstrained Null (Hnull): χ2 Constrained

χ2

d.f.

χ2/d.f.

RMSEA

Δχ2

1892.92⁎ 2082.59⁎

564 579

3.356 3.597

0.091 0.083

Δχ2(15) = 189.67

⁎ p b 0.01.

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

S. Elliot, N. Papadopoulos / Journal of Business Research xxx (2015) xxx–xxx

significance. Table 5 includes the standardized path coefficients for all models and summarizes the number that are significant and the level of support for each hypothesis. In most instances, the hypothesized relationships are confirmed for some models, but not all. In such cases, individual parameter estimates and significance levels are scrutinized in terms of scale and direction, and consideration is given to the reduced form equation results. Two additional hypotheses, H22 and H23, not included in the original model but tested through reduced form equations, are presented because of their significance. Of the 23 relationships, 16 are supported either strongly (9/S), moderately (2/M), or weakly (5/W), and 7 are not supported (N). To begin, as the model posits, Cognitive Country Image is positively related to three constructs: Affective Country Image, Product Beliefs and Destination Beliefs. While consistent with accepted theory that country image affects beliefs, the integrated model distinguishes affect strength by product and destination beliefs. Cognitive Country Image is positively related to Affective Country Image in all eight models, and is significant in six, strongly supporting H1. Cognitive Country Image is positively related to beliefs about its products in seven of eight models, and is significant in four, and Cognitive Country Image is positively related to beliefs about it as a destination in five of eight models, and is significant in three. Thus, H2 is moderately supported, and H3 is weakly supported. Next, the model posits that Affective Country Image is positively related to four constructs: Beliefs and Receptivity for each of Products and Destinations. In both samples, the relationship from country affect to Beliefs is weaker than it is to Receptivity. As well, the influence of affect is weaker on the product than on the destination side of the model, in contrast to the influence of cognitive country image. Affective Country Image is positively related to Product Beliefs in five of eight models, yet is significant in only two (one of which is negative), not supporting H4. Affective Country Image is positively related to Destination Beliefs in five of eight models, and is significant in three (one of which is negative), weakly supporting H5. By contrast, Affective Country Image is positively related to Product Receptivity in all models, and is

7

significant in four, and positively related to Destination Receptivity in all models, being significant in all. These results support H6 (moderately) and H7 (strongly). Turning to Product Beliefs, the model posits that it is positively related to two constructs: Product Receptivity and Destination Receptivity. Product Beliefs is positively and significantly related to Product Receptivity in all models, strongly supporting H8 and confirming past PCI research that, generally, beliefs affect behavioral intent. Similarly, Product Beliefs is positively related to Destination Receptivity in all models, and significant in six. Importantly, therefore, H9, the cross-over influence of product beliefs on destination receptivity, tested cross-nationally in this study, is strongly supported. Destination Beliefs has a similar relationship to Destination Receptivity and Product Receptivity, but the cross-over effect is weaker in this direction. Destination Beliefs is positively related to Product Receptivity in five of eight models, and significant in three. Thus, H10 is weakly supported. On the other hand, Destination Beliefs is positively and significantly related to Destination Receptivity in all models, strongly supporting H11. For Product Familiarity, the model posits that it is positively related to five constructs: Product and Destination Beliefs, Product and Destination Receptivity, and Affective Country Image. Only two of these relationships are strongly supported. Product Familiarity is positively and significantly related to both Product Beliefs and Product Receptivity in six models, strongly supporting H12 and H14. Two additional hypotheses, Product Familiarity to Destination Beliefs and to Destination Receptivity, are positively related in five and six of eight models respectively, but significantly related in just two. Thus, H13 and H15 are weakly supported, suggesting some additional influence from the product to destination side of the model. Lastly, Product Familiarity is positively and significantly related to Affective Country Image in only one model, not supporting H21. Similarly, the model posits that Destination Familiarity is positively related to the same five constructs as its product-side equivalent. However, in this case none of these relationships are supported. Even

Table 5 Path Coefficients for all hypothesized relationships, by model1. South Korea models (n = 349)

Canada Models (n = 307)

Sig.

Hyp

Path

US

JP

AU

CA

US

JP

AU

SK

#

supp.23

H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H223 H233

CogCI–AffCI CogCI–ProdBel CogCI–DestBel AffCI–ProdBel AffCI–DestBel AffCI–ProdRec AffCI–DestRec ProdBel–ProdRec ProdBel–DestRec DestBel–ProdRec DestBel–DestRec ProdFam–ProdBel ProdFam–DestBel ProdFam–ProdRec ProdFam–DestRec DestFam–ProdBel DestFam–DestBel DestFam–ProdRec DestFam–DestRec DestFam–AffCI ProdFam–AffCI CogCI–ProdRec CogCI–DestRec RMSEA

0.75 0.56⁎ 0.58 0.05 −0.02 0.29⁎ 0.19⁎ 0.66⁎ 0.27⁎

1.07 0.48⁎ 0.57⁎ 0.05 0.02 0.70⁎ 0.31⁎ 0.33⁎ 0.23⁎

0.82⁎ 0.77⁎ 0.25 −0.21 0.21 0.17⁎ 0.30⁎ 0.63⁎

0.93⁎ 0.40 −0.25 0.25 0.77 0.05 0.17⁎ 0.89⁎ 0.15⁎

0.87⁎ −0.31 −0.42 0.93⁎ 0.81⁎ 0.01 0.20⁎ 0.87⁎ .025⁎

0.06 0.60⁎ 0.51⁎ −0.03 −0.81 −0.33 0.20 0.71⁎ 2.80 1.69 1.40 −1.35 0.96 0.10 .078

0.37 0.26⁎ 0.59⁎ 0.25⁎

0.72⁎ 0.04 −0.12 0.21 0.56⁎ 0.09 0.17⁎ 0.81⁎ 0.21⁎ 0.11⁎ 0.49⁎ 0.51⁎ 0.56⁎ 0.49⁎ 0.21⁎

0.99⁎ 10.55 2.39⁎ −10.3 −1.95 0.40⁎ 0.24⁎ 0.33⁎

−0.10 0.65⁎ 0.41⁎ 0.00 0.27⁎

0.94⁎ 2.25⁎ 1.89⁎ −1.82⁎ −1.73⁎ 0.03 0.20⁎ 0.83⁎ 0.21⁎ 0.23⁎ 0.57⁎

−0.42 0.64 −0.29 0.09 0.23 −0.15⁎ 0.53⁎ 0.45⁎

—– —– —– —– —– 0.22⁎ 0.26⁎ 0.30⁎

6 4 3 2 3 4 8 8 6 3 8 6 2 6 2 0 2 0 0 0 2 7 6

S M W N W M S S S W S S W S W N N N N N N S S

.086

.078

0.11 0.09 0.24 0.49 0.67 0.75 0.0 0.55⁎ 0.68⁎ .076

−.070 −0.06 0.81⁎ 0.16⁎ −0.06 0.09 −0.15 −0.15 −0.57⁎ 0.06 −0.11 0.72 −0.29 0.50⁎ 0.54⁎ .066

−0.10 0.62⁎ 0.29⁎ 0.01 0.26⁎ 0.05 0.07 −0.33 0.10 −0.11 0.27 0.02 0.56⁎ 0.54⁎ .066

0.11 0.28⁎ 0.59⁎ 0.34 −0.01 0.10⁎ 0.03 −0.01 0.12 0.02 0.05 0.0 0.0 0.72⁎ 0.56 .088

0.02 0.45⁎ 0.30⁎ 0.11 0.37⁎ 0.18 −0.34 0.31 −0.30 −0.15 −0.28 0.14 0.45⁎ 0.43⁎ .081

⁎ Statistically significant path at p N 0.05 level. 1 Standardized coefficients. 2 Strong, Moderate, Weak, No support. 3 Not included in the original model, but additionally tested through reduced form equations: H22: A country's cognitive image is positively related to receptivity toward that country's products. H23: A country's cognitive image is positively related to receptivity toward that country as a travel destination.

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

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S. Elliot, N. Papadopoulos / Journal of Business Research xxx (2015) xxx–xxx

the path from Destination Familiarity to Destination Beliefs, though positive in five of eight models, is only significant in two (one of which is negative). H16 through H20 are not supported. Thus, the proposition that familiarity affects beliefs only holds on the product side of the model, not the destination side. Unfortunately, contributing to this result may be the relatively poor performance of Destination Familiarity, the one single-item construct of the model. The final results of the hypothesis testing are summarized in Fig. 2, which shows the paths that were supported strongly and moderately or weakly, and those that were not supported. Overall, these findings can be deemed satisfactory since a complex model, tested in two countries with four target origins in each, resulted in support for 70% of the hypothesized paths. 5. Discussion of the model results Looking more closely at the relationships in Fig. 2, it is evident that country image has a significant influence on consumers' beliefs and their receptivity to goods and travel. The two additional paths not tested in previous models (Elliot et al., 2011; Elliot et al., 2013) from Cognitive Country Image show a significant influence on Product Receptivity and Destination Receptivity in seven and six cases respectively, all positive, thus strongly supporting both relationships (H22 and H23 in Table 5). The cognitive components of country image prove particularly strong, in that they also have a strong influence on Affective Country Image, and a partial influence on Product and Destination Beliefs. On the other hand, the findings concerning the influence of Affective Country Image are in line with findings in other related research (e.g., Klein et al., 1998), which suggests that affect is linked to receptivity directly and not necessarily through Beliefs. Overall, viewed from the product vs. destination perspective, Cognitive Country Image appears to have a stronger influence on the product side of the model while Affective Country Image has a stronger influence on the destination side. Product Beliefs is also an influential construct, with significant relationships to not only Product Receptivity but to Destination Receptivity. This supports the cross-over hypothesis, that what one believes about a country's products will not only influence their receptivity to that country's goods but also their receptivity toward it as a travel destination. Though weak, Product Familiarity also has some influence on Destination Beliefs and Receptivity. The reverse, however, does not hold: Destination Familiarity does not influence the product side of the model at all, nor does it even influence Destination Beliefs. Also, unlike the strong influence of Product Beliefs on Destination Receptivity, Destination Beliefs has only a weak influence on Product Receptivity. This suggests that consumers, as marketers well know, can be rather savvy. For example, if one feels that a place is able to produce a wide range of desirable products, one is likely to also feel that such a place offers good accommodations and attractions, a good range of tourism activities, and good value for money, as well as good “scenery” or “culture” depending on the destination. All of these are characteristics of a well-developed and broadbased tourism destination, like the U.S. On the other hand, a country's natural endowments, which add to its range of tourism offerings, may not necessarily mean that the country also is an able producer of quality products. Still, the fact that H10 was in the right direction in five cases, and significantly so in three, suggests that a cross-over relationship from destination to product is also likely, though less pronounced. In summary, the weight of the evidence indicates that the product side of the model has a stronger influence on the destination side of the model than the reverse. 6. Conclusions and implications A consumer today shops the global market almost as commonly as today's researcher references it. Consumers in North America, Asia, and points between have access to a range of foreign products, no longer

limited to French wine, Italian fashion, and German cars. We now have access to an international potpourri, and consume global culture, products, and scenery on- and off-line, through music, movies, or the news media. This expansive exposure creates innumerable associations in the consumer's mind that blend together to create metamorphic images of place. Tourism and product research can no longer measure image independently, as if each is influenced solely by the images crafted by the marketers of one organization. It is hoped that the development of an integrated model of place image will contribute to place branding efforts in many settings, applied to many situations, to enhance TDI and PCI theory, and to further researchers' and practitioners' understanding of place, product and tourism destination relationships. The systematic and analytical approach of studying a mix of place image components helps a place to identify its most unique attributes, its assets, and its vulnerabilities, as dominant associations emerge. The associations identified in this study reveal an interesting picture of how the general country, product, and tourism components of place image are related. Considering the resulting paths for PCI, from country image to beliefs to receptivity, confirms the findings of earlier studies within the PCI field, while the equivalent path for TDI confirms the value of the cross-disciplinary exchange of ideas and contributes in its own right to the TDI literature. By simultaneously testing PCI and TDI cross-nationally, the similarities and differences of each path are notable. Notably, cognitive country image has greater influence on the product side of the model, affective country image has greater influence on the destination side, familiarity only influences product beliefs and behaviors, and affect has a greater influence directly on receptivity than through the beliefs construct. Complex studies of causal relationships involving multiple variables, while informationally rich, can also be fraught with limitations. Evaluations were at a global level of products and destinations (i.e., without specifying particular product categories, seasons, or brands) and used the product “origin” term broadly (i.e., without reference to countryof-manufacture vs. -design, or other such hybrid configurations). Relationships may vary at the micro level of specific products, brands, or places, and are worthy of future investigation. Practitioners can benefit substantively from the findings of the model. First, exporters of products made in Canada and South Korea will find the results of interest when preparing strategies to enter the other's market. For example, promoting Canada's affective strength (trustworthiness) and product strength (workmanship) can positively influence receptivity to Canada as a tourism destination. The comparison of one country's image to that of competitors helps international marketers to better position their products (e.g. Japanese innovativeness; U.S. product value; Korean workmanship). The country selections provide for comparison to economic leaders, such as Japan and the U.S., as well as Australia, considered a middle-power nation like Canada. The results can guide exporters to determine whether a global marketing and product distribution strategy will be effective, or whether attitudes toward their country's products necessitate a more local strategy. An understanding of place image helps direct decisions related to branding, packaging, advertising, retail distribution, and sourcing. South Koreans, for example, are willing to buy American goods, but they are not able to easily find them in comparison to Japanese goods. The pattern of relationships can also guide strategy development at a more macro level. Cognitive image associations influence foreign consumers' beliefs of a country's products, whereas affective image associations influence receptivity to those products. The pattern for travel destination perceptions, by contrast, is weaker from cognitive image associations to beliefs about a country as a travel destination, and stronger from the country's affective image associations to beliefs and receptivity to travel there. The influence of familiarity is also different across the paths. Knowledge of a foreign destination does not affect consumers' perceptions of a country's products, either directly or indirectly. And while consumer familiarity with foreign products does not directly affect perceptions

Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031

S. Elliot, N. Papadopoulos / Journal of Business Research xxx (2015) xxx–xxx

of a country as a travel destination (Product Familiarity → Destination Beliefs not significant), the former does influence destination receptivity indirectly through product beliefs (Product Familiarity → Product Beliefs → Destination Receptivity). In other words, a consumer who is familiar with a country's products will evaluate that country's products more positively, and will also be more receptive to the idea of travelling there. It is consumer beliefs that exhibit the stronger cross-over effects than familiarity, particularly in the direction from product beliefs to destination receptivity. The influence of destination beliefs on the receptivity to that country's products, though weaker, is still evident. Public policy makers, particularly at the national level, can benefit from the assessment of cognitive and affective image dimensions, to delineate not only a country's attributes of quality but also the symbolic and emotional aspects of country image, thereby capturing a deeper meaning of “place”. From these associations, a country must find its je ne sais quoi to symbolize and make its image globally competitive (e.g., the role played by the Statue of Liberty for the U.S. or the red maple leaf for Canada). Whatever a country's strengths may be, the process of developing place branding strategies that require integration across sectors can be compared to the development of a corporate brand incorporating various sub-brands. The common dimension of a place's corporate image would be the cognitive elements (quality of life, technology, education, wealth) that influence both product and travel paths. Affective image associations play a “corporate” role as well, with greater influence on the travel than the product sub-sector. Because the cross-over effect is stronger from the product to travel side than viceversa, the corporate place brand should first and foremost strengthen its cognitive country elements. The fundamental contribution of the study is the empirical support found for the proposed integrative model, which enables an exploration and understanding of the relationships between product and destination beliefs and behaviors. The model provides a starting framework for analysis of any place of interest, contributes to the theoretical foundations of place image, and helps to enhance practitioners' understanding of how product and tourism images interact.

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Please cite this article as: Elliot, S., & Papadopoulos, N., Of products and tourism destinations: An integrative, cross-national study of place image, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.08.031