Variables that affect the purchase intention of Peruvian gastronomy

1. Introduction

According to Khan et al., (2012), Fishbein & Ajzen (1975), purchase intention is the individual and subjective decision that consumers make towards a brand, product or service which has been selected by them after a certain level of evaluation. Additionally, Huy & Svein (2012) affirm that it is essential to analyze the purchase intention of goods and services offered by a company, since marketing managers are involved to analyzing it with the aim of predicting sales, estimating the demand for their products and services, segmenting the market and designing promotional strategies.

Similarly, Madahi and Sukati (2012) point out that purchase intention is an increasingly critical element for studies on consumer behavior; consumers will decline in their purchase based on their evaluation and appreciation of the product or service bought. According to Keller (2001), the purchase intention can be affected by many external factors; however, the ultimate decision between accepting or rejecting a product or service will depend on the purchase intention of the consumer.

The general objective of the present investigation is analyze the association of purchase intention of Peruvian gastronomy with country image of Peru, gastronomy’s product image, familiarity with Peru and gastronomy’s product familiarity variables. In addition, specific objectives are following:

I.Analyze the association of the country image of Peru with the gastronomy’s product image.

II.Analyze the association of the country image of Peru with the purchase intention of Peruvian gastronomy.

III.Analyze the association of the gastronomy’s product image with the purchase intention of Peruvian gastronomy.

IV.Analyze the association of familiarity with Peru with the purchase intention of Peruvian gastronomy.

V.Analyze the association of gastronomy’s product familiarity with the purchase intention of Peruvian gastronomy.

VI.Analyze the effect of country image of Peru, gastronomy’s product image, familiarity with Peru, gastronomy’s product familiarity with the purchase intention of Peruvian gastronomy.

2. Literature Review

It's analyzed the main models that explain the relationship between the variable purchase intention with image country, image product, country familiarity and product familiarity variables.

Han - Construct Summary (1989) proposed a model that researched the variables that influence the consumer purchase intention, identifying as main variables: country image and product familiarity. Han concluded that when the consumers doesn’t have knowledge of a specific product; the image country of this product impacts on the consumers purchase intention through their perceptions and beliefs relative to the product.

In addition, Han - Halo Effect (1990) developed a new model that analyzed the consumer’s perception of product quality through evaluation of the product's country of origin. His model studied the impact of this evaluation on their purchase intention. The main finding was that the country of origin may affect the perception of product's quality; and it influences the consumer purchase intention. However, country image isn’t the unique variable that can impact on the perception of product's quality.

Other perspective was researched by Hong and Wyer (1989) who proposed a model that demonstrated that the information relating to product's country of origin generates more awareness in knowing information regarding the other attributes of the product by the consumers. Subsequently, the information of product's country of origin stimuli the final evaluation of the product. However, the analysis of this model doesn’t allow to conclude when it is wise to promote product's country of origin.

In contrast, Roth and Romeo (1992) studied a model integrating the country image and product image, with purchase intention. They defined country image in terms of four dimensions, which are evaluated at the same time when the consumer analyze a specific product. This lets determining when it is advisable to promote the product's country of origin and when not, it allows prioritization of the dimensions of the country image that require greater care.

In addition, Papadopoulos and Heslop (2000) presented the model based on Roth and Romero (1992) research, however, it focused on a multi-country study. Consequently, they were able to study the influence of product's country of origin on the consumer purchase intention. Similarly, Lin and Kao (2004) developed a model based on Roth and Romeo (1992). However, they model analyzed the relation of the variables concerning to the brand and country image and its influence on the consumer purchase intention. They found that the country of origin impacts positively the intention purchase of consumer.

On the other hand, Long Yi and Chun-Shuo (2006) suggested a model that studied the effect of the country and product image, the degree of product's entailment and knowledge on the consumer purchase intention. They main finding was that product's knowledge and entailment moderate the final impact that the country of origin has on consumer purchase intention. Although this model studied in greater depth variables concerning to the product; it doesn't test the brand effect on consumer intention of purchase.

However, Wang and Yang (2008) proposed a model that studied the impact of brand personality and the country of origin on the consumer purchase intention. They concluded that the brand personality and product's country of origin produce combined effect that favor the consumer purchase intention. In addition, Khan, Ghauri and Majeed (2012) analyzed the impact of product’s country of origin on the consumer purchase intention. They main discovery was that the impact of the product's brand on the consumer intention of purchase is directly and determined by the brand components: brand awareness, past experiences of the brand, and the association between brand awareness, and past experiences of the brand.

Xianguo, Yang & Wang (2012) evaluated the influence of the country image on the perception of product quality; and the impact of ethnocentrism and customer animosity on such association. They concluded that ethnocentrism impacts positively on the consumer purchase intention of national products, unlike, with imported products. A new viewpoint was presented by Guina and Giraldi (2012) who appraised the impact of product's country image and familiarity with the country of origin of the product on the consumer purchase intention. The authors concluded that the country familiarity impacts positively on the country image, and consumer purchase intention.

Correspondingly, Sinrungtam (2013) analyzed the effect of product's country of origin on the consumer's purchase intention. Additionally, the author studied in depth the country of origin developing six dimensions to study it, and concluded that four of the dimensions that form country of origin impact directly on consumer purchase intention; while the country of assembly and country of design dimensions are not associate with the consumer purchase intention. Similarly, Ortiz (2014) studied the association between the product's country of origin and brand personality; as in besides, its impact on the consumer purchase intention. His results specified that country of origin image has a direct and significant impact on the brand personality; and this interaction has a positive effect on consumer purchase intention.

On the other hand, Liu and Guo (2016) studied the effect of product's access, satisfaction, reputation and familiarity on consumer purchase intention. Their results showed that both product's familiarity and access don't directly impact on the consumer purchase intention; highlighting that both variables indirectly impact consumer purchase intention through product's trust and social benefit variables.

A critical finding in the review of the literature is the scarcity of studies on the consumer’s purchase intention for agricultural and gastronomic products from emerging countries. Additionally, country's familiarity was studied in the model, such variable have not been analyzed in the literature frequently. As a result, the following are the hypotheses (see figure 1):

Hypothesis 1 (H1): The better the country image of Peru is, the better the gastronomy's product image is.

Numerous researchers have analyzed the relationship between country image and product image. Nevertheless, other researchers have associated these two variables with others in their studies, as Nagashima (1970); Narayana (1981); Agarwal and Sikri (1996); Roth and Romeo (1992); Martin and Eroglu (1993); and Kotler and Gertner (2012).

Hypothesis 2 (H2): The better the country image of Peru is, the higher the intent to purchase gastronomy will be.

Various authors researched the association between the country image and consumer purchase intention. However, others have studied the relationship between both variables with others in their research, as Han - Construct Summary (1989); Hong and Wyer (1989); Roth and Romeo (1992); Papadopoulos and Heslop (2000); Long-Yi and Chun-Shuo (2006); Wang and Yang (2008); Xianguo, Jing, and Da Xia (2012).

Hypothesis 3 (H3): The better the gastronomy´s product image is, the higher the intent to purchase gastronomy will be.

According to the review of the literature, several authors analyzed the correlation between product image and consumer purchase intention. Nevertheless, other authors have researched both variables with others in their studies, such as Han - Halo Effect (1990); Roth and Romeo (1992); Papadopoulos and Heslop (2000) ; Long-Yi and Chun-Shuo (2006).

Hypothesis 4 (H4): The better the country familiarity with Peru variable is, the higher the intent to purchase gastronomy will be.

According to the review of the literature, Guina and Giraldi (2012) and Roth and Romeo (1992) researched the country familiarity and consumer purchase intention with other variables in their analysis.

Hypothesis 5 (H5): The better the gastronomy product familiarity is, the higher the intent to purchase gastronomy will be.

Han - Construct Summary (1989); Han - Halo Effect (1990) and Lin and Kao (2004) studied the association between product familiarity and consumer intention to purchase, with other variables in their researchers. Particularly, Roth and Romeo (1992) made a short comment of products familiarity and its association in the consumer purchase intention, however, they didn't study it in their model.

Hypothesis 6 (H6): The country image of Peru, the gastronomy´s product image, the country familiarity with Peru and the gastronomy´s product familiarity used together have a significant impact on the intent to purchase gastronomy.

Han - Construct Summary (1989); Han - Halo Effect (1990); Hong and Wyer (1989); Papadopoulos and Heslop (2000); Lin and Kao (2004); Long-Yi and Chun-Shuo (2006); Wang and Yang (2008); Xianguo, Jing, and Da Xia (2012); Khan Ghauri and Majeed (2012) and Sinrungtam (2013) studied the association between the following variables country image, product image, country familiarity and product familiarity with the consumer purchase intention, with other variables in their studies.

3. Method

A descriptive confirmatory study was carried out studying the variables analyzed in the literature review. It is possible to conclude their associations (Kumar, 2000). It was used a qualitative method to collect the primary information and the survey technique was performed. Additionally, a structured questionnaire of closed questions was formed organized into five sections; adapting the questionnaire designed by Roth and Romeo (1992).

Two samples were studied for data collection, each sample was formed by countries with different levels of familiarity with Peruvian gastronomy. The first sample was acquiesced of undergraduate and postgraduate students from the United States (U.S.) whose familiarity with Peru is high; while the second sample was acquiesced by undergraduate and postgraduate students of France whose familiarity with Peru is low, based on the research of Verbeke and Vackier (2004).

It was selected a non-probabilistic sampling for convenience, according to Douglas and Craig (2007), this sampling is suitable in international marketing research, given the time and money limitations and restricted access to the population analyzed, see table 1.

The selection of the components of country image of Peru and gastronomy’s product image were based on the items of the country image and product image analyzed in the review of the literature. The items studied by Roth and Romeo (1992): prestige, design, innovation and manpower were used, while country familiarity, product familiarity and consumer purchase intention were measured through a single item.

The interval method was performed to measure the various categories of response by consumers to the items analyzed. For this reason, the semantic differential scale was useful as a measurement scale based on response categories ordered on a seven-point scale. It’s represented the degree of acceptance, preference or agreement with each of the items studied, given their simplicity, speed of application and tabulation of results (Kineear & Taylor, 1999).

Preliminary Analysis

Table 2 shows the statistical reliability for country image of Peru and the gastronomy’s product image scales. The individual corrected item-total correlations and the total value of Cronbach’s alpha are extensively satisfactory according to Nunnally (1967).

Tables 3, 4, 5 and 6 shows the outcomes of dimensionality for the country image of Peru and the gastronomy’s product image. The first factor of the Principal Component Analysis (PCA) explains much more variance than the second, and this more than the third; additionally, the first factor of the PCA is the unique that has an eigenvalue greater than one, in both cases. As a result, both scales are one-dimensional (Carmines & Zeller, 1979).

Table 7 shows ANOVA test of equal means for France and U.S. samples, it was made for each analyzed variable, results indicates that the null hypothesis of equal means isn’t accepted in any case based on F values, since p <0.000 in all the studied variables. Similarly, Turkey test was carried out in order to analyze the homogeneous subsets of samples. Table 6 shows that the mean of French sample is significantly less than the mean of the U.S. sample for Peru country image, familiarity with Peru, and purchase intention of Peruvian gastronomy. Specially, for the gastronomy product image and familiarity with gastronomy; samples of USA and France determine a homogeneous group.

4. Conclusions

It was analyzed the peer correlation of the country image of Peru with the gastronomy’s product image. Additionally, it was studied each of the four variables researched with the purchase intention of Peruvian gastronomy, through bivariate analysis.

Study of H1: The better the country image of Peru is, the better the gastronomy’s product image is.

In the sample of France, country image of Peru is directly and non-significantly correlated with the gastronomy´s product image (r=+0.106; p=0.272). In contrast, in the U.S. sample, the correlation is direct and significant; the country image of Peru is significantly correlated to the gastronomy´s product image (r=+0.324; p=0.001), at 5% level of significance; see table 8. This outcome of the empirical part confirms what was studied in the literature concerning the relationship between the country image and the product image researched by Nagashima (1970), Narayana (1981), Agarwal and Sikri (1996), Roth and Romeo (1992); and Martin and Eroglu (1993).

Study of H2: The better the country image of Peru is, the higher the intent to purchase gastronomy will be. In the sample of France, there is a positive and significant relation of the country image of Peru with the intent to purchase gastronomy (r=+0.334; p=0.000), at 5% level of significance. Similarly, in the sample of U.S., the association of the country image of Peru with the intent to purchase gastronomy is direct and significant (r=+0.489; p=0.000), at 5% level of significance; see table 9. This empirical result validates what has been analyzed in the literature, relative to the association between the country image and the consumer intention to purchase, as studied by Roth & Romeo (1992); Papadopoulos & Heslop (2000); Lin & Kao (2004); Long-Yi & Chun-Shuo (2006); Wang & Yang (2008); Xianguo, Yang & Wang (2012); Khan, Ghauri & Majeed (2012) and Sinrungtam (2013), see table 9.

Study of H3: The better the gastronomy´s product image is, the higher the intent to purchase gastronomy will be. In the sample of France, it was found a positive and significant correlation between the gastronomy’s product image of Peru and the intention to purchase gastronomy from Peru (r=+0.259; p=0.007), at 5% level of significance. Similarly, in the case of the US sample, the correlation between the gastronomy’s product image of Peru and the intent to purchase gastronomy from Peru is positive and significant (r=+0.471; p=0.000), at 5% level of significance; see table 10. This finding in the empirical part corroborates what has been researched in the literature, concerning the existence of an association between the product’s image and the purchase intention, as can be observed in Han - Construct Summary (1989); Roth and Romeo (1992); Papadopoulos and Heslop (2000); Long-Yi and Chun-Shuo (2006).

Study of H4: The better the country familiarity with Peru variable is, the higher the intent to purchase gastronomy will be. In France sample, the correlation between country familiarity with Peru and the purchase intention of gastronomy is positive and significant (r=0.111; p=0.250), at 5% level of significance. Similarly, in the case of the US sample, the correlation between the country familiarity with Peru and the purchase intention of gastronomy is positive and significant, (r=0.511; p=0.000), at 5% level of significance; see table 11. This insight in the empirical part represents scientific contribution, since there aren’t studies that incorporate an association between the country familiarity with the consumer's purchase intention. Specially, the model of Roth and Romeo (1992) is the unique research that mentions country familiarity, but doesn’t include this variable in its study.

Study of H5: The better the gastronomy product familiarity is, the higher the intent to purchase gastronomy will be. In the sample from France, it was found that the correlation between the familiarity gastronomy product of Peru and the purchase intention of gastronomy from Peru is positive and not significant (r=0.155; p=0.107). In contrast, in the U.S. sample, the correlation was found to be positive and significant (r=0.599; p=0.000), at 5% level of significance; see table 12. This finding in the empirical part corroborates what has been studied in the literature, as Han - Construct Summary (1989); Han – Halo Effect (1990); Roth and Romeo (1992); Lin and Kao (2004).

Study of H6: The country image of Peru, the gastronomy´s product image, the country familiarity with Peru and the gastronomy´s product familiarity used together have a significant effect on the intent to purchase gastronomy.

In equation 1, the dependent variable is the intent to purchase gastronomy from Peru and the independent variables are gastronomy’s product familiarity, country familiarity with Peru, country image of Peru and gastronomy’s product image. All these variables have a quantitative nature and form the regression equation; it was used the intro method. The purpose of this regression was identify which independent variables are significant in the intent to purchase gastronomy from Peru. In consequence, the null hypothesis to test was: Ho: β1=β2=β3=β4=0.

Equation 1: Regression equation of H6.

𝐼𝑛𝑡𝑒𝑛𝑡 𝑡𝑜 𝑝𝑢𝑟𝑐ℎ𝑎𝑠𝑒 𝑔𝑎𝑠𝑡𝑟𝑜𝑛𝑜𝑚𝑦 𝑓𝑟𝑜𝑚 𝑃𝑒𝑟𝑢= 𝐶𝑜𝑛𝑠𝑡𝑎𝑛𝑡+ 𝛽1 ∗ 𝐺𝑎𝑠𝑡𝑟𝑜𝑛𝑜𝑚𝑦′𝑠 𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑓𝑎𝑚𝑖𝑙𝑖𝑎𝑟𝑖𝑡𝑦+ 𝛽2 ∗𝐶𝑜𝑢𝑛𝑡𝑟𝑦 𝑓𝑎𝑚𝑖𝑙𝑖𝑎𝑟𝑖𝑎𝑡𝑦 𝑤𝑖𝑡ℎ 𝑃𝑒𝑟𝑢+ 𝛽3 ∗ 𝐶𝑜𝑢𝑛𝑡𝑟𝑦 𝑖𝑚𝑎𝑔𝑒 𝑜𝑓 𝑃𝑒𝑟𝑢+ 𝛽4 ∗𝐺𝑎𝑠𝑡𝑟𝑜𝑛𝑜𝑚𝑦′𝑠 𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑖𝑚𝑎𝑔𝑒+ 𝑒𝑟𝑟𝑜𝑟.

Where:

𝛽1 = 𝑅𝑒𝑔𝑟𝑒𝑠𝑠𝑖𝑜𝑛 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 𝑜𝑓 𝑔𝑎𝑠𝑡𝑟𝑜𝑛𝑜𝑚𝑦′𝑠 𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑓𝑎𝑚𝑖𝑙𝑖𝑎𝑟𝑖𝑡𝑦 ,

𝛽2 = 𝑅𝑒𝑔𝑟𝑒𝑠𝑠𝑖𝑜𝑛 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑟𝑦 𝑓𝑎𝑚𝑖𝑙𝑖𝑎𝑟𝑖𝑎𝑡𝑦 𝑤𝑖𝑡ℎ 𝑃𝑒𝑟𝑢,

𝛽3 = 𝑅𝑒𝑔𝑟𝑒𝑠𝑠𝑖𝑜𝑛 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑟𝑦 𝑖𝑚𝑎𝑔𝑒 𝑜𝑓 𝑃𝑒𝑟𝑢,

𝛽2 = 𝑅𝑒𝑔𝑟𝑒𝑠𝑠𝑖𝑜𝑛 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 𝑜𝑓 𝑔𝑎𝑠𝑡𝑟𝑜𝑛𝑜𝑚𝑦′𝑠 𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑖𝑚𝑎𝑔𝑒.

As a preliminary analysis to test H6, it was identified the presence of extreme cases or outliers. The outcomes presented that there isn’t residue with standardized value lower than -3 or higher than +3 in both samples. Additionally, it was identified that no factor variance inflation was greater than 5, and the condition indexes were all under 30. Therefore, there isn’t multincollinearity in the regression variables for both samples.

Table 13 presents the regression results for the sample of France, it’s identified that R squared corrected is 0.139. Additionally, table 14 shows that the amount of variance explained by the regression model for the sample of France is significant (p=0.001). In consequence, it is not accept the null hypothesis (Ho: β1=β2=β3=β4=0). It means that all beta coefficients of the regression equation are not zero.

Table 15 indicates which regression coefficients are significant to explain the intent to purchase gastronomy from Peru, it allows contrast the null hypothesis, Ho: β1=β2=β3=β4=0; for the sample of France. The results indicate that the null hypothesis isn’t accepted for the country image of Peru variable (p = 0.001). As a result, country image of Peru is a significant variable to explain the purchase intention of Peruvian gastronomy. Moreover, the relationship of this variable with the purchase intention of Peruvian gastronomy is direct, since it was found that β4> 0 (B4=0.304). In contrast, gastronomy’s product familiarity (p=0.617), familiarity with Peru (p=0.369) and gastronomy’s product image (p=0.055) aren’t significant variables to explain the purchase intention of Peruvian gastronomy.

Table 16 presents the regression results for the sample of U.S., it’s identified that R squared corrected is 0.445. Additionally, table 16 shows that the amount of variance explained by the regression model for the sample of U.S. is significant (p=0.000). Therefore, it isn’t accept the null hypothesis (Ho: β1=β2=β3=β4=0). It means that all beta coefficients of the regression equation are not zero.

Table 18 indicates which regression coefficients are significant to explain the intent to purchase gastronomy from Peru, it allows contrast the null hypothesis, Ho: β1=β2=β3=β4=0; for the sample of France. The results indicate that the null hypothesis isn’t accepted for gastronomy’s product familiarity variable (p=0.000) and country image of Peru (p=0.008). As a result, gastronomy’s product familiarity and country image of Peru are significant variables to explain the purchase intention of Peruvian gastronomy. Moreover, the relationship of these variables with the purchase intention of Peruvian gastronomy is direct, since it was found that β1> 0 (B1=0.357) and β3> 0 (B3=0.008). In contrast, familiarity with Peru (p=0.251) and gastronomy’s product image (p=0.089) aren’t significant variables to explain the purchase intention of Peruvian gastronomy.

In the table 19, summary of the H6, it can be seen that all correlations are positive. However, there are differences between the variables that are significant and those that are not significant to explain the intent to purchase gastronomy; from one sample to the other. When the four variables are studied together to explain the purchase intention of Peruvian gastronomy, it was found that country image of Peru is significant for both samples. As a result, gastronomy’s product image, familiarity with Peru and gastronomy product familiarity are not significant for both samples.

5. Discussion

Regarding the H1, according to the review of the literature, several researchers were found a positive and significant relationship between the country image variables and the product image. The results obtained in this research partially confirm this relationship; according to the results, the image of Peru affects the image of Peru's gastronomy product when the consumer has high familiarity with Peru, but not when the consumer has low familiarity with Peru. As a result, there is a partial acceptance of the H1.

Relative to H2, studies which analyzed to the association between country image and the purchase intention were carried out in several researchers, and therefore, is the country image is the variable used with greater frequency in the literature of the purchase intention of the consumer. According to the results of the empirical part, the H2 should be widely accepted in cases when the consumer has high familiarity with Peru, as well as, in cases when the consumer has low familiarity with Peru. Therefore, there is wide acceptance of H2.

Analyzing the H3; a low presence of the product image variable associated to the intention to purchase was observed in the review of the literature, in comparison with to the country image variable. The results widely confirm this association, according to the results, the gastronomy product image of Peru affects the purchase intention of Peruvian gastronomy when the consumer has high or low familiarity with Peru. Therefore, there is a wide acceptance of H3.

Similarly, studying the H4, it was found that Peru familiarity affects purchase intention of Peruvian gastronomy when the consumer has high familiarity with Peru; and when the consumer has low familiarity with Peru. In consequence, it is concluded that there is a wide acceptance of the H4, which constitutes an important contribution to the academy, since the familiarity of the country, has not been associated by the literature with the consumer's purchase intention.

With respect to the results of H5, a low presence of the product familiarity variable related to the intention to purchase was identified in the review of the literature, in comparison with country image, and product image variables. The results partially confirm this relationship; the familiarity with gastronomy product of Peru affects the purchase intention of gastronomy from Peru, when familiarity with the consumer has high familiarity with Peru; in contrast, when the consumer has low familiarity with Peru. Therefore, there is partially acceptance of H5.

Finally, regarding H6, when the bivariate analysis is carried out and then the multivariate analysis, it is possible to study the effect of the four variables simultaneously in the purchase intention. The results present that the behavior of the four variables studied changes for each sample; specially, it was found that Peru country image is significant associated with the intention to purchase of Peruvian gastronomy, for both samples. In consequence, H6 is partially accepted.

6 Limitations

The reliability of the results is low since the size of each of the samples is reduced due to budgetary and time constraints. Additionally, the small sample size doesn't allow a study by gender, age and socio-economic level of the consumers to determine the existence of differences in their purchase intention based on these variables. Similarly, the results obtained are not extrapolated to the universe since the sampling method used was convenience sampling (non-probabilistic method).

Furthermore, the sample used was composed by master's students from universities in the two countries where the research was conducted (France and U.S.). However, they didn't represent the universe, they have postgraduate studies and labor experience. As a result, they have greater international exposure as well as a higher cultural level that allows them to have a better knowledge of Peru and its gastronomy.

On the other hand, it wasn’t possible to use structural equations to perform the validation of the model because only two variables used in the research were constructs (country image and product image) composed of four dimensions. While the other three variables (country familiarity, product familiarity and purchase intention) were one-dimensional.

Finally, four identical items (Innovation, Design, Prestige and Handmade Design) were studied in order to measure the country and product image, according to the methodology proposed by Roth and Romeo (1992). Nevertheless, the multidimensional country image construct could have been used.

References

Tables

Table 1. Technical sheet of the study carried out

Table 2: Reliability results for the multi-item scales

Country image of Peru scale, Cronbach’s 𝜶 = 0.866 Peruvian gastronomy’s product image scale, Cronbach’s 𝜶 = 0.874 Corrected Item-Total Correlation

Alpha if Item Deleted Innovativeness 0.699 0.841 0.670 0.862 Design 0.697 0.839 0.753 0.829 Prestige 0.805 0.791 0.810 0.806 Workmanship 0.686 0.842 0.689 0.855 Source: Own elaboration

Alpha if Item Deleted

Corrected Item-Total Correlation

Table 3: Dimensionality results for Peru Country Image scale

Component Initial Eigenvalue Total % of Variance Cumulative % 1 2.876 71.894 71.894 2 0.492 12.300 84.195 3 0.381 9.537 93.731 4 0.251 6.269 100 Source: Own elaboration

Table 4: Component Matrix (1 component extracted)

Item Component 1 Innovativeness Peru 0.832 Design Peru 0.834 Prestige Peru 0.901 Workmanship Peru 0.823 Source: Own elaboration. Extraction Method: Principal Component Analysis

Table 5: Dimensionality results for Gastronomy Product Image scale

Component Initial Eigenvalue Total % of Variance Cumulative % 1 2 3 4

72.661 84.519 94.065 100.000 Source: Own elaboration

2.906 0.474 0.382 0.237

72.661 11.858 9.546 5.935

Table 6: Component Matrix (1 component extracted)

Item Component 1 Innovativeness Gastronomy 0.809 Design Gastronomy 0.869 Prestige Gastronomy 0.903 Workmanship Gastronomy 0.825 Source: Own elaboration. Extraction Method: Principal Component Analysis.

Table 7: Descriptive ANOVA results for the comparison of means

Item F p Turkey post hoc comparison Peru Country Image 60.653 0.000 𝜇𝐹𝑟𝑎𝑛𝑐𝑒< 𝜇𝑈𝑆𝐴

Gastronomy product Image 21. 288 0.000 𝜇𝐹𝑟𝑎𝑛𝑐𝑒= 𝜇𝑈𝑆𝐴 Familiarity with country Peru 197.703 0.000 𝜇𝐹𝑟𝑎𝑛𝑐𝑒< 𝜇𝑈𝑆𝐴 Familiarity with product Gastronomy 12.316 0.000 𝜇𝐹𝑟𝑎𝑛𝑐𝑒= 𝜇𝑈𝑆𝐴 Purchase intention (Peru Gastronomy) 126.934 0.000 𝜇𝐹𝑟𝑎𝑛𝑐𝑒< 𝜇𝑈𝑆𝐴 Source: Own elaboration

Table 8: Summary of the H1

Sample from France Sample from U.S. Sample from France

Sample from U.S.

Direction and intensity of the correlation P values Country image of Peru Gastronomy’s product image

0.106 0.324* 0.272 0.001**

Source: Own elaboration. *Highest correlation. **Significant correlation at 5%.

Table 9: Summary of the H2

Sample from France Sample from U.S. Sample from France Sample from U.S. Direction and intensity of the correlation P value Country image of Peru Purchase intention of Peruvian gastronomy

0.334

0.489*

0.000**

0.000**

Source: Own elaboration. * Highest correlation. **Significant correlation at 5%.

Table 10: Summary of the H3

Sample from France

Sample from U.S. Direction and intensity of the correlation P value Gastronomy’s product image Purchase intention of Peruvian gastronomy

Sample from U.S.

Sample from France

0.259 0.471* 0.007** 0.000**

Source: Own elaboration. *Highest correlation. **Significant correlation at 5%.

Table 11: Summary of the H4

Sample from France Sample from U.S. Sample from France

Sample from U.S.

Direction and intensity of the correlation P value Familiarity with Peru Purchase intention of Peruvian gastronomy

0.111 0.511* 0.250** 0.000**

Source: Own elaboration. *Highest correlation. **Significant correlation at 5%.

Table 12: Summary of the H5

Sample from France Sample from U.S. Sample from France Sample from U.S. Direction and intensity of the correlation P value Gastronomy’s product familiarity Purchase intention of Peruvian gastronomy

0.155 0.599* 0.107 0.000**

Source: Own elaboration. *Highest correlation. **Significant correlation at 5%.

Table 13. Summary multiple regression model of purchase intent for gastronomy for sample of France.

Source: Own elaboration

Table 14. Breakdown of the sum of squares of the regression for the intent to purchase gastronomy for Sample of France.

Total 262.807 108 Source: Own elaboration

Table 15. Significance of the regression coefficients for the intent to purchase gastronomy for Sample of France

Gastronomy´s product image 0.046 0.024 0.201 1.938 0.055 Source: Own elaboration

Table 16. Summary multiple regression model of the intent to purchase gastronomy for sample of U.S.

1 0.682 0.466 0.445 1.670 Source: Own elaboration

Table 17: Breakdown of the sum of squares regression of the intent to purchase gastronomy for the sample of U.S.

Model Sum squares Df Media square F Sig. Regression 252.938 4 63.235 22.662 0.000

Residual 290.199 104 2.790

Total 543.138 108 Source: Own elaboration

Table 18. Significance of the regression coefficient effect for the intent to purchase gastronomy (Sample of U.S.)

Gastronomy´s product image 0.042 0.025 0.153 1.718 0.089 Source: Own elaboration

Table 19: Summary of the H6

Country image of Peru Gastronomy’s product image Familiarity with Peru Gastronomy’s product familiarity

Franc

Franc

Franc

Franc

U.S.

U.S.

U.S.

U.S.

e

e

e

e

0.001* 0.008* 0.055 0.089 0.369 0.251 0.617 0 . 001 Source: Own elaboration. * Significant.

VIII Figures

Figure 1. Diagram of proposed hypotheses

Source: Own elaboration based on adaptation of Roth and Romeo (1992)