Customer perceptions of Japanese foods in Italy

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54

JEF157_proof ■ 16 August 2018 ■ 1/10

Journal of Ethnic Foods xx (2018) 1e10

Contents lists available at ScienceDirect

Journal of Ethnic Foods journal homepage: http://journalofethnicfoods.net

Review article

Customer perceptions of Japanese foods in Italy Q7

Rosa M. Fanelli*, Angela Di Nocera

Q1


degli Studi del Molise, Italy Department of Economics, Universita

a r t i c l e i n f o

a b s t r a c t

Article history: Received 27 June 2018 Received in revised form 23 July 2018 Accepted 25 July 2018 Available online xxx

As we all know, online consumer reviews have come to substitute more traditional forms of restaurant criticism. In this article, we examine the significance of TheFork for the reputation of Japanese restaurants in Italy. Data were extracted from the websites of restaurants associated with TheFork. A total of 675 online reviews were analyzed. The study focused on statistical inquiry using principal component analysis and analysis of variance to answer the following research question: Does a statistically significant relationship exist between the attributes of Japanese restaurants and reviewer profiles? The results highlighted two elements, which were successfully constructed: the reviewer's profile and the attributes of Japanese restaurants. © 2018 Korea Food Research Institute. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Consumer attitudes Consumer profiles Ethnic food Japanese restaurant attributes Online review websites Statistic tests

1. Introduction With the increase of tourism and international trade, the role of ethnicity in the world has become more important not only in business and consumer behavior but also in food culture and the food industry [56]. In Italy, in particular during the recession, the rapid increase of the migrant population, which now equals 5 million inhabitants [over 8.2% of the total population, with a prevalence of those from Romania (22%), Albania (10%), and Morocco (9%)], has caused changes in dietary patterns and lifestyles. Italians increasingly appreciate ethnic and international food (Fondazione Leone) [7,13,18,25,41]. Moreover, the presence of numerous restaurants managed by foreign entrepreneurs makes it easier to sample ethnic cuisine in Italy[34]. Indeed, there are many restaurants, which specialize in foreign cuisine: In the last year, their number increased from 2000 to 4000. The most numerous are Chinese restaurants, followed by Japanese and other oriental restaurants (e.g., Vietnamese and Korean), but even restaurants that prepare kebabs are increasing and are growing in popularity in Italy. The proliferation of ethnic food restaurants follows the migratory flows of the various ethnic groups in different cities. In Milan, Turin, and Venice, many Chinese and Egyptian restaurants have arisen; in Florence, there are a number of Iranian restaurants; and in Palermo,

* Corresponding author. E-mail address: [email protected] (R.M. Fanelli).

a number of restaurants from Tunisia have been set up. In some countries such as France, the Netherlands, and the United States, ethnic restaurants, generally characterized by their small size and moderate prices, are usually frequented by a resident clientele in the immediate vicinity who often follow the same routine both regarding the day of the week they dine out and the dishes they consume [24]. This definition can be used for the Italian case as prices and quality of services are more or less the same. As this study shows, there is no great variation between one city (Rome) and another (Milan) and also within the menus of individual, allinclusive restaurants. The success of Japanese cuisine in Italy is partly due to the trend toward healthy, sustainable, and fresh food. Japanese cuisine is characteristically fresh and simple because it is traditionally based on nutrition from natural ingredients. The nutritious qualities of Japanese food are largely due to the geography of Japan. Japan consists of four main islands and thousands of smaller ones and is surrounded by the sea; there is always seasonal fresh seafood available, and most Japanese cuisine is seafood based [63]. Rice is also abundant in Japan and therefore is another staple ingredient in Japanese cuisine. Short-grain rice (often called sushi rice) has especially played a huge part in Japanese culture and is the best choice for rice puddings and rice cakes. Rice is also prevalent in Japanese drinking culture, with the rice-based alcohol sake. Unlike other ethnic foods, Japanese food has a refreshing and delicate flavor that comes from the absence of heavy spices and a lightness that results from an extremely low use of dairy products and fat. Some people believe that tasty food requires the use of unhealthy

https://doi.org/10.1016/j.jef.2018.07.001 2352-6181/© 2018 Korea Food Research Institute. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 2/10

2

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

ingredients, but Japanese cuisine makes an exception to this common belief as it is both tasty and healthy. In the light of the aforementioned information, the purpose of this study is to analyze the online review websites to highlight the relationship between the attributes of Japanese restaurants and the profile of consumers who have used and reviewed them. Several studies have argued that online reviews represent a key source of information for consumers [17,30,42,70]. In addition to reviews posted on specific restaurant websites, sites such as Yelp, Urban Spoon, and TripAdvisor host thousands of reviews of various restaurants, providing consumers and guests with opportunities to rate their experiences of services and products, leave comments, and inform others. In this study, through the analysis of the reviews of Japanese restaurants, we will seek to answer the research question: Does a statistically significant relationship exist between the attributes of Japanese restaurants and reviewer's profiles? To this aim, an analysis of the customers who frequently visit foreign restaurants in Italy and the reasons for their choice is very important. The analysis reported in the following sections is based on literature review, on surveys already carried out, and mainly on TripAdvisor reviews [66]. Several studies have highlighted that the voluntary online review is becoming an important information source for customers to learn about products or services and to assist them in making purchase decisions [6,20,32]. Others searches, conducted by the content analysis method, have shown that most of the reviews generated by users are true [21,52,77]). The article has the potential to contribute to debate on the complex relationships between food service quality (cuisine, service, and atmosphere), restaurant image, customer-perceived value, and customer satisfaction. After the introduction, the work aims to provide an analysis of the main determinants that drive consumers toward ethnic cuisine (part 2); set out the methodology of analysis (part 3); show the results (part 4); and, finally, give discussions and some summary considerations (part 5). 2. Consumer attitudes toward ethnic food: a literature review Consumer attitudes toward or perceptions of ethnic food have become more positive when we consider the popularity of ethnic foods and the increasing availability of restaurants managed by foreigners in Italy. The Italian restaurant has 320,391 firms (activity code 56), divided into 149,085 bars and 168,289 restaurants of various types. Table 1 shows that Lombardia and Lazio are the first two Italian regions for the presence of both active restaurants and restaurants managed by foreigners. These data explain sufficiently how the diffusion of restaurants depends more on demographic variables (the resident population) than on economic variables (income, consumption, consumption propensity, etc.). This does not mean, however, that both the demographic and the economic variables have not had a joint impact on the setting up of restaurants. By focusing on ethnic restaurants, Fig. 1 highlights that in Italy, for every thousand residents, there are just over three restaurants managed by foreigners. On one hand, the regions that highlight a greater percentage are in the order the Valle d'Aosta (5.23), Liguria (4.70), and Abruzzo (3.94). On the other hand, those that register a minor presence are Basilicata (2.37), Sicilia (2.47), and Lombardia (2.63). However, there are other factors that require a more in-depth analysis that can lead to preference of ethnic foods, such as traveling to foreign countries, the requests of increasingly demanding consumers in terms of variety of food, and the exploratory and playful attitude especially of young people toward food.

Table 1 Active restaurants and restaurants managed by foreigners in Italy. Regions

Lombardia Lazio Campania Veneto Emilia-Romagna Toscana Piemonte Sicilia Puglia Liguria Calabria Sardegna Marche Abruzzo Friuli-Venezia Giulia Trentino-Alto Adige Umbria Basilicata Molise Valle d'Aosta Italia

Active restaurants

Restaurants managed by foreigners

N.

%

N.

%

49375 34528 29911 25671 24788 21410 23575 20004 18677 11967 10150 10451 8398 8363 7133 5757 4579 2652 1875 1127 320391

15.41 10.78 9.34 8.01 7.74 6.68 7.36 6.24 5.83 3.74 3.17 3.26 2.62 2.61 2.23 1.80 1.43 0.83 0.59 0.35 100

26336 21517 17103 14734 14703 14461 13991 12504 11115 7354 6011 5974 5605 5208 4078 3246 2902 1349 1104 664 189959

13.86 11.33 9.00 7.76 7.74 7.61 7.37 6.58 5.85 3.87 3.16 3.14 2.95 2.74 2.15 1.71 1.53 0.71 0.58 0.35 100

Source: [14].

Several studies [12,46,48,58,71,72,] have established some influencing factors on the increase of ethnic foods, such as extrinsic factors (growing international trade, globalization, migration, and tourism), psychological factors (the desire for healthier diets, flavor, and adventure), and sociocultural factors related to changes in lifestyle and values. Some ethnic foods are perceived as healthy because they include low-calorie items (low in fats and oils) and plenty of vegetables [4]. As consumers have become more interested in healthy eating, more restaurants have begun using healthy food strategies in their menus. Nowadays, restaurants often present Asian foods as “healthy” menu items. A common example is the promotion of Asian menu items as a healthy option in fast food restaurants. For example, McDonald's offers an Asian salad, which displays the nutritional information of the item. It seems that ethnic restaurant consumers perceive some ethnic foods as healthy, and this positive perception of ethnic food may be regarded as one of the influencing factors when a consumer decides to visit an ethnic restaurant [49]. Previous studies have examined the important factors for satisfied consumers choosing Chinese restaurants, such as “food and environment,” “service and courtesy,” “price and value,” and “location, advertising, and promotion.” [55]. Other important attributes for consumer satisfaction in Chinese restaurants are food quality (especially taste) and service quality (especially service reliability), along with dining atmosphere, food authenticity, and fair pricing [43]. Several factors can affect consumer satisfaction: “employee services and atmosphere” (including employee friendliness, level of service, and atmosphere); “food quality and dining environment” (including good food quality, consistent food quality, and reasonable pricing); and “physical attributes” (including good location, convenient parking, and convenient operating hours) [33,44,68,73,78]. Compared to Chinese restaurants, there are few studies [16,35,47,53,59,67,69] focusing on Japanese cuisine and consumer behavior, so another aim of this study is to fill this gap. The common Italian image of Japanese cuisine is that seasoning is used lightly, the natural flavor of the ingredients is emphasized, and a traditional menu composition is common [2,15,28,29]. Others positive aspects of the traditional Japanese diet are that it has high fiber content and is low in calories and cholesterol. The Japanese foods, characterized with low salt, soy beans, fish,

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 3/10

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

Basilicata Sicilia Lombardia Puglia Campania Veneto Trentino Alto Adige Calabria Italy Piemonte Umbria Emilia Romagna Friuli Venezia Giulia Molise Sardegna Marche Lazio Toscana Abruzzo Liguria Valle d'Aosta

3

2.37 2.47 2.63 2.74 2.93 3.00 3.05 3.06 3.14 3.19 3.26 3.30 3.34 3.56 3.61 3.64 3.65 3.86 3.94 4.70 5.23

Fig. 1. Number of restaurants managed by foreigners/per 1000 residents. Source: [14].

seaweed, and probably also green vegetables, are candidates for chronic noncommunicable disease prevention [8,60,75,76]. 3. Materials and methods 3.1. Data sources The analysis was carried out using reviews written by 675 consumers using TheFork (an app belonging to TripAdvisor) to evaluate their perception of Japanese food and restaurants. The first factor of the analysis includes the profile of consumers. Consumers who go to Japanese restaurants are classified by TripAdvisor, with the system of the “Star badge”, on the basis of the number of written reviews, into four profiles: gastronomist (n. of reviews
10), connoisseur (4  n. of reviews 9), gourmand (2  n. of reviews 4), and not classified. This system gives users the ability to check which reviewers are more experienced and therefore more reliable. Moreover, the larger the number of postings, the more accurate the overall evaluation [10]. The second factor concerns the city in which a restaurant is located. In this case, two regional capitals were chosen because they show the highest number of ethnic restaurants: Milan and Rome (Table 1). The reasons for the utilization of data from TheFork are threefold. First, TheFork is the leading online restaurant reservation platform in Europe. Part of the TripAdvisor Media Group since May 2014, TheFork has 40,000 restaurants present in 12 countries with around 12 million reviews, 14 million average monthly visits, and more than 7 million app downloads. With this app, each restaurant allows people to read menus in advance, see the prices of dishes, and view any promotions. For each booking, customers receive gift credits called “yums” that allow consumers to receive discounts on future bookings [66]. Second, for consumers, TripAdvisor represents one of the most widely investigated restaurant review websites. It has been chosen as the website for data collection by numerous researchers over the years [11,30,61,62,79,80]. Third, TheFork facilitates the filtering of consumers because they are classified on the basis of the criteria reported previously

into four profiles (gourmand, gastronomist, connoisseur, and not classified). This classification makes the website particularly suitable for our analysis. Restaurants in TheFork were selected for data collection by a two-step process. In the first step, a total of 40 Japanese restaurants associated with TheFork located in two cities (Milan and Rome) in regions with the highest presence of ethnic restaurants (Lombardia and Lazio) were chosen. In the second step, a total of 675 reviews, written in January 2018, were extrapolated. More precisely, from each of the 40 restaurants, the online review responses were formatted according to the location of the restaurant in excel sheets, and the names of the restaurants were transformed into codes to protect the confidential business figures. 3.2. Data collection, research method, and hypotheses In February 2018, a total of 675 reviews posted between 1 and 31 January 2018 by consumers who used the TheFork discount to go to a Japanese restaurant were filtered according to the 40 ethnic restaurants selected in the first step of the analysis. For each restaurant, the following factors were considered: ensign, city, average price, date of posting, gender, consumer profile type (gourmand, gastronomist, connoisseur, and not classified), the average score for the three attributes for Japanese restaurants (cuisine, service, and atmosphere), and the text of the review. For the quantitative analysis, 10 variables were used (average price, the number of consumers for each profile type and for gender, and the average score for the three aspects used to evaluate ethnic restaurants) Table 2. STATA programmer (Stata 12.32, software package created in 1985 by Stata Corp) was used to perform statistical analysis of the data collected from the websites of 40 restaurants associated with TheFork. To measure the relationship between the profiles of TheFork users and the score given for the three attributes of Japanese restaurants, descriptive statistics, principal component analysis (PCA), and one-way analysis of variance (ANOVA) were performed. In the first step, with the assistance of descriptive statistics, the most important characteristics of the Japanese restaurants and of

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 4/10

4

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

Table 2 Drivers for the analysis of Japanese restaurants. Drivers City Average price (Eur) TheFork's reviewer profile

Gender Reviews of Consumers with TheFork discount (January 2018)

Variable

Unit

Milan Rome Average price Gourmand Gastronomist Connoisseur Not classified Male Female Cuisine

1 2 Eur Number Number Number Number Number Number Voting (average value)

Service Atmosphere

Voting (average value) Voting (average value)

Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork.

the consumers' profiles were identified. To be more specific, we calculated the minimum and the maximum values, the mean, the deviation standard, and the variation coefficient. In the second step, the PCA was used to construct the new components affecting the 675 reviewer's opinion on the attributes of 40 Japanese restaurants selected. The PCA was carried out based on a matrix with a size of 40 (restaurants) by 10 (variables) with the broad purpose to summarize data so that the interdependencies among observed variables and components can be easily interpreted and understood. In the last step of the quantitative analysis, the new components, identified with PCA which affected reviewer evaluation of the attributes of the Japanese restaurants, were tested using one-way ANOVA. In particular, this parametric test known as ANOVA calculated the ratio between the variance among the groups' distributions (divided by the freedom degree) and the variance within each group distribution (divided by the freedom degree). In other words, ANOVA evaluated whether the differences of the mean values of the different groups are statistically significant or not. ANOVA used F statistic to test if the three groups had the same mean. The null hypothesis for an ANOVA was that there was no significant difference among the groups. The alternative hypothesis assumed that there was at least one significant difference among the groups. The F-ratio and the associated probability value (p value) must then be calculated. In general, if the p value associated with the F is smaller than 0.05, then the null hypothesis is rejected and the alternative hypothesis is supported. If the null hypothesis is rejected, one concludes that the means of all the groups are not equal. Bartlett's test, instead, was used to test if the three groups had equal variances. The Bartlett's test statistic is designed to test for equality of variances across groups against the alternative that variances are unequal for at least two groups. The null hypothesis was that the three group variances were equal. The alternative hypothesis was the group variances were not all equal. This means that at least one is not equal to the others. The hypotheses of Bartlett's test are defined as follows:

H0 Ha

s21 ¼ s22 ¼ ... ¼ s2k s2i s s2j for at least one pair (i,j).

In this study, with the application of the ANOVA, we tried to answer the research question: Does a statistically significant relationship exist between the attributes of ethnic restaurants (cuisine, service, and atmosphere) and the customer satisfaction of the four profile types for reviewers (gourmand, gastronomist, and connoisseur, and not classified)? The independent variables were the attributes (cuisine, service, and atmosphere), and the dependent variables were the four profile types for users (gourmand, gastronomist, connoisseur, and not classified). The two hypotheses formulated were as follows: H0: There is no statistically significant relationship between the evaluation of the attributes of Japanese restaurants and the profiles of reviewers. H1: There is a statistically significant relationship between the evaluation of the attributes of Japanese restaurants and the profiles of reviewers. Instead, for the qualitative analysis, the most frequently occurring words and phrases to express a positive and/or negative appreciation on the cuisine, service, and atmosphere of Japanese foods and restaurants were considered. 4. Results 4.1. Quantitative analysis Fig. 2 shows the total number of reviewers (675) for the month of January 2018, the profile and the gender of TheFork reviewers, and the cities where the 40 Japanese restaurants are located. Specifically, they are summarized across the four profile types: gourmand, gastronomist, connoisseur, and not classified; the gender (male and female), as well as across the two cities Milan and Rome. Of the 675 reviewers selected, 57.8% (N. ¼ 390) were male, and 42.2% (N. ¼ 285) were female. To obtain the main factor of the results of statistical analysis, it is necessary to analyze the main component, or better known as PCA. PCA is a preliminary analysis to be used in the continued analysis of a series of analyses in a study. In principle, the use of PCA is formed from new factors that have random properties, and then the data can be interpreted according to the factors or components that are formed. In reducing the number of variables, a factor analysis process is needed to create a set of new variables or factors that replace a number of variables from the previous data. With the first stage of analysis, descriptive statistics were used to observe the distribution of the data and to measure the similarity/dissimilarity between the variables. Table 3 provides the minimum and maximum values, average, standard deviation, and coefficient of variation. The coefficient of variation, calculated as the ratio between standard deviation and mean, highlighted, with values closer to 0, the homogeneity and disparities, with values greater than 1, between the Japanese restaurants based on the values assumed by the 10 variables considered. On the one hand, the biggest difference between restaurants is in the number of gourmand reviewers (1.04). On the other hand, greater similarity between the same restaurants relates to the evaluation of the atmosphere (0.09) and the service (0.09). The average price to eat in one of the Japanese restaurants was 30.15 Euro, with a minimum of 20 Euro (8 restaurants) to a maximum of 90 Euro (only one restaurant). The male and the female scores, not considered for the ANOVA, ranged respectively from 1 to 37 and 0 to 35. For the ANOVA, instead, the three attributes of Japanese restaurants as the independent variables and the four consumers' profiles as the dependent variables were considered. Table 3 reports the scores for all variables, but for the analysis, we are more interested in the characteristics of Japanese restaurants and consumers profiles.

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 5/10

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

5

Fig. 2. Selected TheFork reviewers of Japanese restaurants, profile type, gender, and city (January, 2018). Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork.

The scores for the three independent variables, cuisine, service and atmosphere, ranged respectively from 5.3 to 10, from 6.7 to 10, and from 6.9 to 10, with a mean of 8.65, 8.72, and 8.36. The dependent variables gourmand, gastronomist, connoisseur, and nonclassified scores ranged respectively from 0 to 25, from 0 to 12, from 0 to 13, and from 0 to 24. With the second step of the analysis, the simple correlation matrix in pairs was used to verify the congruence of the method to the aim of the research and at the same time to discard from the analysis some starting variables showing too weak correlations. In this case, in verifying correlations between the variables selected, only pairs of variables that had an absolute value of the correlation index equal to or greater than 0.50 were considered. These couples were 16 out of a possible 55 (29%). Attention was therefore focused on strong correlations. They are represented by pairs of indices with positive sign (highlighted in bold). As expected, the strongest and positive correlations are between the reviewer's profile and the gender and between the attributes of Japanese restaurants (cuisine, service, and atmosphere). On the one hand, regarding the reviewer's profile, the males are more correlated with the gourmand's profile than females, whereas the females are more correlated with the profile of the gastronomist and the connoisseur. The results explained that female customers were more likely to visit Japanese restaurants. On the other hand, there is the highest correlation between the service and the atmosphere with respect to the correlation between cuisine and atmosphere. This means that although food and service quality should always be

Table 3 Descriptive statistics of the variables selected (year 2018). Variable

Mean

Average price 30.15 Gourmand 4.60 Gastronomist 3.88 Connoisseur 3.33 Not classified 5.08 Male 9.75 Female 7.13 Cuisine 8.65 Service 8,72 Atmosphere 8.36

Standard deviation Min Max Coefficient of variance 12.70 4.80 3.68 3.21 4.91 7.70 7.02 0.92 0.81 0.79

20 0 0 0 0 1 0 5.3 6.7 6.9

90 25 12 13 24 37 35 10 10 10

0.42 1.04 0.95 0.96 0.97 0.79 0.98 0.11 0.09 0.09

Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork.

at an exceptional level, a pleasing atmosphere may contribute to a greater level of overall satisfaction and subsequent behavior in the food service industry. Regarding the negative correlations, the average price is negatively correlated with the reviewer's profile and shows weak correlations with the attributes of Japanese restaurants. In this study, the average price is a variable that had a low influence on the opinions of the consumers on the aspects of the Japanese restaurant because the reviewers go to these restaurants with TheFork's discount (Table 4). With the third step of the analysis, PCA was used to construct the new factors affecting reviewer evaluation of Japanese restaurants. The first step in PCA is to search for eigenvalue and eigenvector values. The eigenvalue and eigenvector are shown in Table 5, Fig. 3, and Table 6. Based on the Kaiser Criterion theory, all components having an eigenvalue less than one (<1) will be aborted, and an eigenvalue greater than or equal to one (
1) will be maintained [5]. The eigenvalue measures how much variation of the observed variables is explained by factors. Any factor with an eigenvalue greater than or equal to one (
1) explains more variance than a single observed variable. Table 5 displays the total variance explained by the 10 principal components extracted, but attention was focused on the first two components because their eigenvalues are greater than one. The value of the third component is very close under one, and it explains 8.72% of the total variance. The cumulative percentage of variance explained by the first two components was 72.34% of the total variance (marked in bold). Another method used for component extraction was the analysis of the Scree plot [38]. This one is a subjective method that requires the researcher judgment. According to this criterion, the significant components are disposed like a cliff, having a big slope, whereas the trivial components are disposed at the base of the cliff. Fig. 3 shows that starting with the third component, the slope of the curve is quite small, and these factors could be excluded from the model. The second step in PCA is to allocate each variable of origin into the factor according to the loading value. Based on the eigenvalue that has value greater than one (>1), two components Component 1 and Component 2 will be used.

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

6

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

Table 4 Correlation between the reviewer's profile and the attributes of Japanese restaurants.

AVE P GOU GAS CON NOC M F CUIS SERV ATM

AVE P

GOU

GAS

CON

NOC

M

F

CUIS

SERV

ATM

1 0.09 0.20 0.10 0.08 0.14 0.12 0.45 0.21 0.44

1 0.59 0.76 0.77 0.91 0.88 0.38 0.28 0.14

1 0.70 0.44 0.69 0.80 0.15 0.27 0.10

1 0.63 0.83 0.88 0.32 0.37 0.24

1 0.88 0.78 0.29 0.19 0.02

1 0.88 0.38 0.37 0.18

1 0.27 0.23 0.04

1 0.36 0.52

1 0.64

1

Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork. AVE P, average price; ATM, atmosphere; CUIS, cuisine; CON, connoisseur; F, female; GAS, gastronomist; GOU, gourmand; M, male; NOC, not classified; SERV, service.

Table 5 Principal component analysis/correlation and the total variance explained. Component Eigenvalue Difference Comp1 Comp2 Comp3 Comp4 Comp5 Comp6 Comp7 Comp8 Comp9 Comp10

5.21 2.02 0.87 0.74 0.42 0.29 0.20 0.18 0.07 0.00

3.19 1.15 0.14 0.31 0.13 0.09 0.02 0.11 0.07 0.00

Percentage of variance

Cumulative percentage

52.10 20.24 8.72 7.36 4.22 2.9 1.95 1.77 0.71 0.02

52.10 72.34 81.06 88.42 92.64 95.54 97.49 99.27 99.98 100.00

Table 6 Rotated component matrix.

Source Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork.

Variable

Comp1

Comp2

Average price Gourmand Gastronomist Connoisseur Not classified Male Female Cuisine Service Atmosphere

0.11 0.40 0.33 0.39 0.35 0.42 0.41 0.21 0.20 0.13

0.43 0.12 0.10 0.06 0.19 0.10 0.20 0.42 0.41 0.60

Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork.

factor loadings ranging from 0.41 to 0.60. The items in Component 2 were the attributes of Japanese restaurants (mainly the atmosphere) and the average price. Two new principal factors were successfully constructed using PCA and identified as the factors affecting reviewer evaluation. Table 7 shows the new factors and percentage of variance explained for each of them. The first factor shows the highest percentage of variance explained when it was extracted. When the first factor, reviewer's profile before and after attending to Japanese restaurants, was extracted, then 52.10% of the variance would be explained. The two new factors that affect reviewer evaluation of the attributes of the Japanese restaurants were tested using one-way ANOVA [27]. Reviewers were divided into three groups based on the three attributes of the Japanese restaurants (cuisine, service, and atmosphere), with the aim of verifying if and how the scores change in the four-consumer profile types. The dependent variable consists of the same four profiles (gourmand, gastronomist, connoisseur, and not classified), and the independent variables consist of the average reviewers who evaluate the three aspects of Japanese restaurants (cuisine, service, and atmosphere) Table 8. The variable average price was due to the low correlation with other variable analysis (Table 4) and was excluded by the analysis. A p value of less than 0.05 was required for significance. The results of the variance analysis showed that the variable scores all

1

Eigenvalues 2 3

4

5

Table 6 shows the rotated factor matrix, which contains the loadings of every variable on the retained components. A rotation is a linear transformation that was performed on the initial factor solution for the purpose of making an easier interpretation. The most common rotation method is orthogonal varimax [40], which is provided by the programmer utilized STATA 12. To make the interpretation of the meaning of every factor, the variables that had the greatest loadings on a factor were analyzed in terms of their similarity regarding the measured construct. After this interpretation, the principal components could be labeled according to their relevant meaning. Component 1 comprised six positive items with factor loadings ranging from 0.33 to 0.42. The items in Component 1 were the gender and the profile of reviewers (mainly the male and the gourmand). Component 2 comprised of four positive items with

Table 7 Denomination of the new factors with the percentage of variance.

0

1 2 3 Q5 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 6/10

0

2

4 6 Component numbers

8

10

Fig. 3. The Scree plot after PCA. Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork. PCA, principal component analysis.

Factor 1 Factor 2

Reviewer's profile The aspects of Japanese restaurants and average price

52.10 20.24

Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork.

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 7/10

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

7

Table 8 Score (average value), mean, standard deviation, and significance values of the variable for reviewer profiles. Predictor

Profiles

Voting (average value) Cuisine

Service

Atmosphere

Gourmand Gastronomist Connoisseur Not classified Gourmand Gastronomist Connoisseur Not classified Gourmand Gastronomist Connoisseur Not classified

Descriptive statistics

Total

Bartlett's test for equal variance

N

Media

Standard deviation

SS

DF

MS

F

Prob > F

184 155 133 203 184 155 133 203 184 155 133 203

4.6 3.875 3.325 5.075 4.6 3.875 3.325 5.075 4.6 3.875 3.325 5.075

4.80 3.68 3.21 4.91 4.80 3.68 3.21 4.91 4.80 3.68 3.21 4.91

899.6 528.375 400.775 940.775 899.6 528.375 400.775 940.775 899.6 528.375 400.775 940.775

39 39 39 39 39 39 39 39 39 39 39 39

23.06 13.55 10.28 24.12 23.06 13.55 10.28 24.12 23.06 13.55 10.28 24.12

6.80 1.82 2.59 2.99 0.81 1.04 0.97 0.81 1.64 1.28 2.23 2.22

0.0001 0.0990 0.0214 0.0103 0.6857 0.4681 0.5353 0.6795 0.1492 0.3032 0.0480 0.0492

c2 (8) (7) (8) (8) (6) (7) (7) (7) (9) (8) (6) (9)

54.261 65.923 58.068 7.9112 16.4135 9.6089 6.7876 18.6464 4.8118 8.8094 6.3018 5.1143

Prob >c2 0.711 0.473 0.669 0.442 0.012 0.212 0.451 0.6795 0.1492 0.3032 0.3900 0.824

Source: Data refers to 675 reviewers of the 40 Japanese restaurants associated with TheFork.

differ in the four profile types (Table 8). The most obvious result is that the cuisine attribute presents the highest value for all fourconsumer profile types when compared to the other two attributes. The service attribute, on the other hand, records the highest value for the gastronomist profile. Finally, the atmosphere attribute shows the highest value for the connoisseur. For the first group, we can accept the hypothesis (H1) of equal means (p < 0.05) for the three profiles (gourmand, connoisseur, and not classified) related to the attribute cuisine, but not the hypothesis of equal variance (p > 0.05), and reject the hypothesis (H0) for the gastronomist (p > 0.05). For the second group, for the four profiles related to service, we can reject the hypothesis (H1) of equal means (p > 0.05) and of equal variance for three profiles (connoisseur, not classified, and gastronomist) and reject the hypothesis (H0) of equal variance for the profile of gourmand. Finally, for the third group, we can accept the hypothesis (H1) of equal means (p < 0.05) for two profiles (connoisseur and not classified) and reject the hypothesis (H0) of equal means (p > 0.05) for the other two profiles (gastronomist and not classified) and for equal variance for the four profiles considered. According to the literature, food quality, service quality, and atmosphere are the most important restaurant attributes that affect customers' overall dining satisfaction and postdining behavioral intentions [43]. The results are in accordance with previous empirical studies [23,43,54,64], supporting the conclusion that there is a statistically significant relationship between the attribute of cuisine (food quality, healthy ingredients, presentation, health options, taste, freshness, variety, and temperature) and the customer satisfaction of three types of consumer (gourmand, not classified, and connoisseur). Quality of food has consistently been shown as one of the core attributes that customers consider when deciding on a restaurant [50]. The importance of service quality, instead, has increased only in recent years, and restaurants should develop a system that will both evaluate service performance as well as improve service delivery. However, the results of the analysis show that this aspect of Japanese restaurants is important only for the gastronomist profile. The definition of quality service may vary depending on a person, on experience with Japanese foods, and on the situation. At the end, the different atmospheric factors (lighting, music, temperature, scent, smell, and furnishings) can be characterized as the ability to create an image that will support and influence customer behavior [36]. The atmosphere of a restaurant can have a significant impact on the perceptions of the overall quality of the service encounter. The analysis indicated that there was a

relationship between atmosphere and customer satisfaction for the profiles of connoisseurs and not classified. 4.2. Qualitative analysis The large variety of online reviews and opinions from customers of Japanese restaurants allows us to highlight the three different attributes (cuisine, service, and atmosphere) that affect customer satisfaction. Customer satisfaction, identified as the distinction between the assumed quality of service and the customer's involvement or feelings after having experienced the service, depends on several components such as the quality of the food, price, personnel, atmosphere, and other local factors (e.g., parking convenience and location near the center of the city or near public transport) that may influence service quality [3]. For all three attributes of the evaluated Japanese restaurants, positive reviews rather than negative ones prevailed. Starting from the cuisine-target reviews, these included many positive and repetitive descriptions such as “tastes good”, “spicy taste”, “healthy”, and “menu rich and intuitive”. Almost 82% of the reviewers considered (552) gave a positive description of Japanese

Table 9 Repetitive descriptions of Japanese restaurant cuisine and food. Positive descriptions

N.

%

Tasted good Spicy taste Healthy Menu rich and intuitive

70 58 54 50

12.7 10.5 9.8 9.1

Original and surprising recipes A great choice of items

48 45

8.7 8.2

The quality of the food is good

40

7.2

The food is tasty and flavorful

37

6.7

Excellent quality of ingredients

34

6.2

Dishes prepared with care 27 4.9 Excellent quality fish 20 3.6 Elegant dishes 18 3.3 Delicate flavors 15 2.7 Excellent wines 14 2.5 Excellent presentation of dishes 12 2.2 Good sauces 7 1.3 Successful combinations 3 0.5 Total 552 100

Negative descriptions

N.

%

Cold dishes Small portions Expensive Different expectations Flavors not sought Price quality ratio not really exciting High price without yum Very little Japanese cuisine Price not suitable for quality Raw fish

25 20 19 16

20.3 16.3 15.4 13.0

12 10

9.8 8.1

8

6.5

6

4.9

5

4.1

2

1.6

123 100

Source: Phrases descriptions extrapolated from the online review websites.

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 8/10

8

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

cuisine and food. On the other hand, only 123 reviewers (18%) gave a negative description: Recurrent were “cold dishes”, “small portions”, “expensive”, and “different expectations” (Table 9). The results that the food presentation impacts the appetite of the customer and their perception of food quality are in accordance with previous studies [50,54,64]. However, dishes offered with sustainable and healthy ingredients will most likely have a positive effect on the customer's perceived assessment of the restaurant experience [37]. The taste was defined as an essential value that explained the quality and freshness of raw ingredients used to prepare the dishes (e.g., fresh fish and real Japanese spices). Consumers were looking for the true flavors of Japanese cuisine which were not always found in recipes modified to meet Western tastes and in dishes that are sometimes a bit too sapid for the addition of aromas and glutamate. In the two cities, “sushi/sashimi”, “tartare”, “nido roll”, “deluxe gyoza”, “tataki”, “kaisekiryori”, “yakitori”, “tonkatsu”, “shabu-shabu”, “soba”, and “udon” were the most common answers for favorite Japanese food. These dishes evoke classic Japanese cuisine. Great attention is also paid to the service, emphasizing positive aspects such as punctuality and friendliness and kindness of managers, and the negative ones, among which slowness of service was most frequent and less frequent was the degree of difficulty in understanding staff who did not speak perfect Italian. Servicetarget reviews included positive descriptions (almost 82%) such as “friendly and attentive service”, “reasonable waiting time”, and “friendly staff”. However, the negative descriptions (18%) included “very slow service”, “rude waiter”, and “only passable service” (Table 10). Finally, atmosphere-target reviews included positive descriptions (77%) such as “restaurant well-looked after”, “restaurant clean”, and “restaurant chic”, whereas negative descriptions (23%) included phrases such as “small restaurant” “very simple restaurant”, “dark restaurant”, and so on (Table 11).

5. Discussion and conclusions The article demonstrated that the evaluation of the key attributes of the Japanese restaurants associated with TheFork varies across consumers' profiles. The findings of the study highlight that on the one hand, the attribute of food quality (tasted good, spicy taste, healthy, menu rich, and intuitive) had a significant influence and relationship with customer satisfaction and customer behavior intention of fourconsumer profile types (gastronomist, connoisseur, gourmand, and not classified) when compared to the other two attributes.

Table 10 Repetitive descriptions on Japanese restaurant service. Positive

N.

%

Friendly and attentive service 120 21.7 Reasonable waiting times 95 17.2 Friendly staff 72 13.0 Attentive and courteous service 60 10.8 Fast service 50 9.0 Efficient service 43 7.8 Polite waiters 37 6.7 Impeccable service 25 4.5 Sober service 19 3.4 Accommodating service 14 2.5 Amazing service 10 1.8 The waiters speak Italian well 8 1.4 Total 553 100

Negative

N.

%

Very slow service Rude waiter Only passable service Long waiting times Awful service

41 34 26 14 7

33.6 27.9 21.3 11.5 5.7

122 100

Source: Phrases of descriptions extrapolated from the online review websites.

Table 11 Repetitive descriptions of Japanese restaurant atmosphere. Positive

N.

%

Restaurant well-looked 80 15.4 after Premise restaurant clean 79 15.2 Restaurant chic 74 14.2 Relaxing atmosphere 48 9.2 Nice music 37 7.1 Tastefully furnished 35 6.7 Informal restaurant 33 6.3 Pleasant atmosphere 30 5.8 Well-laid tables 28 5.4 Intimate restaurant 25 4.8 Silent restaurant 20 3.8 Calm environment 14 2.7 Subtle music 12 2.3 Relaxing atmosphere 6 1.2 Total 521 100

Negative

N.

%

Small restaurant

36

23.4

Very simple restaurant Dark restaurant Minimal atmosphere Restaurant cold Noisy restaurant Restaurant full Smelt of fried food Huge spray of flowers Restaurant frequented by VIPs

31 18 16 14 12 10 8 6 3

20.1 11.7 10.4 9.1 7.8 6.5 5.2 3.9 1.9

154 100

Source: Phrases descriptions extrapolated from the online review websites.

These results were in accordance with those of the previous literature [1,22,23,43,50,64]. On the other hand, the service quality (friendly and attentive service, reasonable waiting times, fast service, and polite waiters) recorded the highest value for the gastronomist profile and the atmosphere (restaurant well-looked after, premise restaurant clean, restaurant chic, and relaxing atmosphere) for the connoisseur. In this case, the logical consequence was that the importance of service quality has only increased in recent years, and therefore, restaurants should develop a system that will both evaluate service performance as well as improve service delivery [57]. The results showed that the evaluation of quality service depends on a person, the restaurant experience (consumers' profile), and the situation. Atmosphere, instead, can be seen as the ability of the surrounding environment to create an image that will support and influence customer behavior. The analysis showed that there was a relationship between the attribute of atmosphere and the customer satisfaction of the profile types “connoisseur” and “not classified”. However, on these two attributes, in literature, a few studies have been conducted, [43,50] so another aim of this article was to fill this gap. This article further with the indication, extrapolated from the online written tests, of the relationship between the quality attributes of Japanese restaurants and the motivation that had stimulated consumers to visit this type of ethnic restaurants could help the Japanese restaurant operators to understand the wants and the needs of the customers. It is very important to provide an appropriate approach for Japanese operators, associated with TheFork, and thereby assist restaurateurs in developing strategies that would best attract this market. Owing to the surprising growth in Italy, during this financial crisis, the number of ethnic restaurants increased from 2000 to 4000, and the industry has met its biggest challenge in years. Competition between ethnic restaurants has become extremely aggressive, and businesses are focused on attaining the highest revenue possible to remain profitable. As the ethnic food market becomes more competitive, customers' decisions are based on impressions regarding attributes of Japanese restaurants. Based on the results of qualitative analysis, Japanese restaurant operators should develop more creative and innovative system to improve food and service quality. For example, if the restaurant is frequented by Italian consumers, it is very important that the foreigner operators improve the Italian language. In addition, for the physical environment, restaurant operators must pay more attention to the cleanliness of the place and to the pleasing atmosphere. However, the results highlight that

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

JEF157_proof ■ 16 August 2018 ■ 9/10

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

Q2

there were many different factors that influenced customer and dining satisfaction in the food service. The research indicated that on the one hand, the most positive influential atmospheric factors in Japanese restaurants were restaurant's cleanliness, restaurant chic, relaxing atmosphere, nice music, tastefully furnished, and so on, and on the other hand, negative descriptions were related to small restaurant, very simple restaurant, dark restaurant, and smell of fried food (Table 10). In accordance with other previous studies researched [9,57], there were upscale restaurant characteristics that had most impact on customers' emotional behavior and responses. The analysis carried out also seems to indicate that the characteristics of a restaurant have a different importance for each consumer profile. For example, those who rarely or occasionally publish a review mainly look at the quality of food; whereas gastronomists, who count a greater number of judgments and therefore appear more competent, observe and evaluate with attention also other aspects, starting from the characteristics of the servicedpunctuality and attention but also good knowledge of the Italian language by the staffdup to atmosphere of the room, of which the refinement or the intimate character is appreciated. However, our results are different from those of Weiss et al.’s research, who found that customer satisfaction with food quality and atmosphere was the only significant attribute influencing return intention, without satisfaction of service quality [74]. We found that satisfaction with service quality is the strongest influencing factor mainly for the gastronomist profile. Accordingly, restaurant managers should improve the quality of the restaurant in those three dimensions and pay more attention to food quality to respond to the needs of all consumers' profiles. For improving satisfaction of food quality, managers can work hard on food taste, food variety, visual appeal, and food nutrition. Service quality training of employees should be effective because it can hold employees' enthusiasm to treat consumers warmly. Meanwhile, attendants' appearance is also important. To improve satisfaction of the atmosphere, the facility should be consistent with the atmosphere. When customers are addicted to it, they will likely revisit. Conflicts of interest The authors declare no conflicts of interest. Uncited reference

Q6

[19], [26], [31], [39], [45], [51], [65]. Acknowledgments

Q3

Authors are grateful for online reviews generated by consumers who used the TheFork discount to go to Japanese restaurants. Appendix A. Supplementary data Supplementary data related to this article can be found at https://doi.org/10.1016/j.jef.2018.07.001. References [1] Barber N and Scarcelli J. Enhancing the assessment of tangible service quality through the creation of a cleanliness measurement scale. Meas Serv Qual 2010;20(1):46e69. [2] Barer-Stein T. You eat what you are: people, culture and food traditions. Toronto: Firefly Books; 1999.

9

[3] Bateson J and Hoffman K. Managing service marketing. Boston: Dryden press; 2000. [4] Block G, Mandel R and Gold E. On food frequency questionnaires: the contribution of open-ended questions and questions on ethnic foods. Epidemiol 2004;15:216e22. [5] Braeken J and van Assen MALM. An empirical Kaiser criterion. Psychol Meth 2017;22(3):450e66. [6] Burgess S, Sellitto C, Cox C and Buultjens J. Trust perceptions of online travel information by different content creators: Some social and legal implications. Inf Syst Front 2011;13:221e35. [7] Censis. Ricette italiane di integrazione. 2015. [8] Chan YC, Suzuki M and Yamamoto S. Dietary, anthropometric, hematological and biochemical assessment of the nutritional status of centenarians and elderly people in Okinawa, Japan. J Am Coll Nutr 1997;16(3):229e35. [9] Chang K. The impact of perceived physical environments on customers' satisfaction and return intentions. 2000 J Prof Serv Market 2000;21(2):75e85. https://doi.org/10.1300/J090v21n02_06. [10] Chen Y, Fay S and Wang Q. Marketing implications of online consumer product reviews. 2003 Bus Week 2003;7150:1e36. [11] Chua AYK and Banerjee S. Reliability of reviews on the internet: the case of trip advisor. Lect Notes Eng Comput Sci 2013;1:453e7. [12] Clemes MD, Gan C and Sriwongrat C. Consumers' choice factors of an upscale ethnic restaurant. J Food Prod Market 2013;19(Issue 5). [13] Colombo E, Navarini G and Semi G. I contorni del cibo etnico. 2008. In: Neresini F and Rettore V, editors. Cito, vultura, identita. Roma: Carocci; 2008. p. 78e96. [14] Coop, FIPE, Confocommercio, Unioncamere, Infocamere, Camere di Commercio, 2014. [15] Cwiertka KJ. From ethnic to hip: circuits of Japanese cuisine in Europe. 2006 Food Foodw 2006;13(4):241e72. https://doi.org/10.1080/074097105909 31294. [16] Czarniecka-Skubina E and Nowak D. Japanese cuisine in Poland: attitudes and behaviour among Polish consumers. Int J Consum Stud 2014;38(1):62e8. [17] Dabholkar PA. Factors influencing consumer choice of a “rating web site”: an experimental investigation of an online interactive decision aid. J Market Theor Pract 2006;14(4):259e73. [18] De Rose A and Strozza S. Rapporto sulla popolazione. Bologna: Il Mulino; 2015. [19] De Winter JCF, Dodou D and Wieringa PA. Exploratory factor analysis with small sample sizes. Multivariate Behav Res 2009;44:147e81. [20] Decker R and Trusov M. Estimating aggregate consumer preferences from online product reviews. Int J Res Market 2010;27:293e307. [21] Dellarocas C. The digitization of word of mouth: promise and challenges of online feedback mechanisms. Manag Sci 2003;49:1407e24. [22] DeLuco D and Cremer M. Consumers' perceptions of hospital food and dietary services. J Am Diet Assoc 1990;90(12):1711e5. [23] Delwiche J. The impact of perceptual interactions on perceived flavor. Food Qual Prefer 2004;15(2):137e46. https://doi.org/10.1016/S0950-3293(03) 00041-7. [24] Finkelstein J. Dining out. A sociology of modern manners. Cambridge, Polity Press. In: Trad. It.: Andare a pranzo fuori. Sociologia delle buone maniere. Bologna: Il Mulino; 1992. [25] Moressa Fondazione Leone. L’influsso della cucina etnica sulle abitudini alimentari degli italiani. Mestre: VE; 2012. [26] Food & Wine. Gruppo editoriale l’Espresso Spa. 2009. Roma. [27] Green SB and Salkind NJ. Using SPSS for windows and macintosh: analyzing and understanding data. 5th ed. Upper Saddle River, NJ: Pearson Education, Inc; 2010. [28] Gu N, Lee K, Kim S and Lee S. Food culture in the world. Paju: Kyomunsa; 2006. [29] Ha A. American’s perceived image of Asian foods: analyzing the importanceperformance of image attributes. Master thesis. West Lafayette: Purdue University; 2006. [30] Henning-Thurau T, Malthouse EC, Friege C, Gensler S, Lobschat L, Rangaswamy AB and Skiera B. The impact of new media on customer relationships. J Serv Res 2010;13(3):311e30. [31] Hoerl AF and Kennard RW. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 1970;12:55e67. [32] Hu N, Liu L and Zhang JJ. Do online reviews affect product sales? The role of reviewer characteristics and temporal effects. Inf Technol Manag 2008;9: 201e14. [33] Ingerson S and Kim AK. Exploring the value of an ethnic restaurant experience: a consumer perspective towards Korean restaurants. Tour Recreat Res 2016;41(2):199e212. [34] Istat. Dati statistici sull’immigrazione in Italia. 2014. Roma. [35] Jang S, HA A and Silkes CA. Perceived attributes of Asian foods: from the perspective of the American customers. Int J Hospit Manag 2009;28(1): 63e70. [36] Jeong E and Jang S. Restaurant experiences triggering positive electronic word-of-mouth (eWOM) motivations. Int J Hospit Manag 2010. https:// doi.org/10.1016/j.ijhm.2010.08.005. In Press, Corrected Proof. Q4 [37] Johns N and Tyas P. Use of service quality gap theory to differentiate between foodservice outlets. Serv Ind J 1996;16(3):321e46. [38] Jolliffe IT. Principal component analysis. New York: Springer; 2002.

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

JEF157_proof ■ 16 August 2018 ■ 10/10

10

R.M. Fanelli, A. Di Nocera / Journal of Ethnic Foods xx (2018) 1e10

[39] Jung S and Takane Y. Regularized exploratory factor analysis. In: Shigemasu K, Okada A, Imaizumi T and Hoshino T, editors. New trends in psychometrics. Tokyo: University Academic Press; 2008. p. 141e9. [40] Kaiser HF. The varimax criterion for analytic rotation in factor analysis. Psychometrika 1958;23:187e200.
, Mondi Migranti, n. 3/2008. Franco [41] Leonini L. (a cura di). Consumi e Identita Angeli; 2009. €tz O, Risselada H and Stephen AT. [42] Libai B, Bolton R, Bügel MS, De Ruyter K, Go Customer-to-customer interactions: broadening the scope of word of mouth research. J Serv Res 2010;13(3). 267-28. [43] Liu Y and Jang S. Perceptions of Chinese restaurants in the U.S.: What affects customer satisfaction and behavioral intentions? Int J Hospit Manag 2009;28(3):338e48. https://doi.org/10.1016/j.ijhm.2008.10.008. [44] Maa JE, Qub H, Njiteb D and Chena S. Western and Asian customers’ perception towards Chinese restaurants in the United States. J Od Qual Assur Hospit Tourism 2001;12:121e39. [45] MacCallum RC and Austin JT. Applications of structural equation modeling in psychological research. Annu Rev Psychol 2000;51:201e26. [46] Mascarello G, Pinto A, Marcolin S, Crovato S and Ravarotto L. Ethnic food consumption: habits and risk perception in Italy. J Food Saf 2017;37(4). [47] Matsusaki MH and Stokes JW. The Japanese restaurant industry, hotel and restaurant. Adm Q 1971;12(3):53e60. [48] Miles S and Frewer LJ. Investigating specific concerns about different food hazards. Food Qual Prefer 2001;12:47e61. [49] Mintel. Ethnic restaurants - US - March 2012. London: Mintel Group Ltd; 2012. [50] Namkung Y and Jang S. Does food quality really matter in restaurants? Its impact on customer satisfaction and behavioral intentions. 2007 J Hospit Tourism Res 2007;31(3):387e409. https://doi.org/10.1177/ 1096348007299924. [51] Nunnally JC. Psychometric theory. 2nd ed. New York: McGraw-Hill; 1978. [52] O’Connor P. Managing a Hotel’s Image on TripAdvisor. J Hospit Market Manag 2010;19:754e72. [53] Park SB, Jang J and Ok CM. Analyzing Twitter to explore perceptions of Asian restaurants. 2016 J Hospit Tourism Technol 2016;7(4):405e42. [54] Peri C. The universe of food quality. Food Qual Prefer 2006;17(1e2):3e8. https://doi.org/10.1016/j.foodqual.2005.03.002. [55] Qu H. Determinant factors and choice intention for Chinese restaurant dining: a multivariate approach. J Restaur Foodserv Mark 1997;2:35e49. [56] Rossiter JR and Chan AM. Ethnicity in business and consumer behavior. J Bus Res 2004;42:127e34. [57] Ryu K and Han H. Influence of the quality of food, service, and physical environment on customer satisfaction and behavioral intention in quickcasual restaurants: moderating role of perceived price. J Hospit Tourism Res 2010;34(3):310e29. https://doi.org/10.1177/1096348009350624. [58] Saba A. Food, people and society: a European perspective of consumers’ food choices. In: Frewer L, Risvik E and Schifferstein H, editors. Cross-cultural differences in food choice. Berlin: Springer; 2001. p. 233e45. [59] Sato Y and Parry ME. The influence of the Japanese tea ceremony on Japanese restaurant hospitality. J Consum Market 2015;32(7):520e9. [60] Sho H. History and characteristics of Okinawan longevity food. Asia Pac J Clin Nutr 2001;10(2):159e64. [61] Simeon MI, Buonincontri P, Cinquegrani F and Martone A. Exploring tourists’ cultural experiences in Naples through online reviews. J Hospit Tourism Technol 2017;8(Issue 2):220e38. [62] Snehasish B, Alton YK and Chua AYK. In search of patterns among travellers' hotel ratings in TripAdvisor. Tourism Manag 2016;53:125e31. [63] Sobko T, Marcus C, Govoni M and Kamiya S. Dietary nitrate in Japanese traditional foods lowers diastolic blood pressure in healthy volunteers. Nitric Oxide 2010;22(2):136e40. https://doi.org/10.1016/j.niox.2009.10.007.

[64] Sulek JM and Hensley RL. The relative importance of food, atmosphere, and fairness of wait. Cornell Hotel Restaur Adm Q 2004;45(3):235e47. https:// doi.org/10.1177/0010880404265345. [65] Tabachnick BG and Fidell LS. Using multivariate statistics. 4th ed. Boston: Allyn and Bacon; 2001. [66] TheFork. Company profile. 2017. Available from: http://about.thefork.com. [67] Thienhirun S and Chung S. Influence of list of values on customer needs, satisfaction, and return intention in ethnic restaurants. J Hospit Market Manag 2017;26(8):868e88. [68] Tian RG. Cultural awareness of the consumers at a Chinese restaurant: an anthropological descriptive analysis. J Food Prod Market 2001;7(Issue 1e2): 111e30. [69] Tierney RK. Consuming sumo wrestlers: taste, commensality, and authenticity in Japanese food. Food, Cult Soc 2016;19(4):637e53. [70] Van Doorn J, Lemon KN, Mittal V, Nass S, Pick D, Pirner P and Verhoef PC. Customer engagement behavior: theoretical foundations and research directions. J Serv Res 2010;13(3):253e66. [71] Verbeke W and Viaene J. Ethical challenges for livestock production: meeting consumer concerns about meat safety and animal welfare. J Agric Environ Ethics 2000;12:141e5. [72] Verbeke W and Lopez GP. Ethnic food attitudes and behaviour among Belgians and Hispanics living in Belgium. Br Food J 2005;107:823e40. [73] Verbeke W and Poquiviqui G. Ethnic food attitudes and behaviour among Belgians and Hispanics living in Belgium. B Food J 2005;107(No. 11):823e40. [74] Weiss R, Feinstein AH and Dalbor M. Customer satisfaction of theme restaurant attributes and their influence on return intent. J Foodserv Bus Res 2005;7:23e41. [75] Willcox DC, Scapagnini G and Willcox BJ. Healthy aging diets other than the Mediterranean: a focus on the Okinawan diet. Mech Ageing Dev 2014;136: 148e62. [76] Yamori Y, Miura A and Taira K. Implications from and for food cultures for cardiovascular diseases: Japanese food, particularly Okinawan diets. Asia Pac J Clin Nutr 2001;10(2):144e5. [77] Yang Z and Fang X. Online service quality dimensions and their relationships with satisfaction: a content analysis of customer reviews of securities brokerage services. Int J Serv Ind Manag 2004;15(3):302e26. [78] Yinghua L and Soo Cheong (Shawn) J. Perceptions of Chinese restaurants in the U.S.: What affects customer satisfaction and behavioral intentions? Int J Hospit Manag 2009;28(3):338e48. [79] Zhang L and Hanks L. Online reviews: The effect of cosmopolitanism, incidental similarity, and dispersion on consumer attitudes toward ethnic restaurants. Int J Hospit Manag 2018;68:115e23. [80] Zhang Z, Ye Q, Law R and Li Y. The impact of e-word-of-mouth on the online popularity of restaurants: A comparison of consumer reviews and editor reviews. Int J Hospit Manag 2010;29(94):694e700.

Rosa Maria Fanelli graduated in Economics and Social Sciences, received her Master's Degree and a Ph.D. in Agricultural Economics and Policy. From 1 November 2002, she is a confirmed researcher for the disciplinary sector 07/A1 - Economia e Estimo Rurale at the Department of Economics of the Universit
a degli Studi del Molise. At the same Department she deals with agro-industrial Economics and in particular of statistical methodologies for sector analysis and is Professor of Economics of Agro-industrial companies and of Economics and Management of the agri-food system.

Angela Di Nocera graduated in Economics and Social Science, reveived Ph.D in Agricultural Economics and Policy. She is Technical officer at the Department of Economics
degli Studi del Molise. of the Universita

Please cite this article in press as: Fanelli RM, Di Nocera A, Customer perceptions of Japanese foods in Italy, Journal of Ethnic Foods (2018), https://doi.org/10.1016/j.jef.2018.07.001

50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98