Exploring city image: residents’ versus tourists’ perceptions

Fabio Cassia (Department of Business Administration, University of Verona, Verona, Italy)
Vania Vigolo (Department of Business Administration, University of Verona, Verona, Italy)
Marta Maria Ugolini (Department of Business Administration, University of Verona, Verona, Italy)
Rossella Baratta (Dipartimento di Economia Aziendale, Universita degli Studi di Verona, Verona, Italy)

The TQM Journal

ISSN: 1754-2731

Publication date: 13 August 2018

Abstract

Purpose

City image has been defined as the sum of beliefs, ideas and impressions people hold regarding a city. While abundant literature has explored city image from tourists’ perspectives, few studies have explored residents’ perceptions, and even fewer have compared city image as perceived by tourists and residents. In addition, very few studies have compared tourists’ and residents’ perceptions of city image in small- to medium-sized destinations. Considering these research gaps, the purpose of this paper is to address city image in a medium-sized destination, Verona, in northern Italy with three specific objectives: to examine residents’ perceptions of the city of Verona’s image; to examine tourists’ perceptions of the city of Verona’s image and to compare the perceptions of the two groups.

Design/methodology/approach

The research was conducted through questionnaires collected among residents and tourists in Verona. Questionnaires were based on a multi-item scale addressing four dimensions of the city image.

Findings

The findings show that residents and tourists hold similar perceptions of city image regarding services and leisure, security and entertainment. The only significant difference in city image concerns the municipal facilities. Specifically, residents are more critical than tourists about this dimension of city image.

Practical implications

The research provides useful implications for policy makers and destination management organisations, and shows some strengths and weaknesses of Verona.

Originality/value

The study addresses the image of a medium-sized city that is typical in the Italian context, thus enhancing knowledge about city image. In addition, by testing and enhancing a scale previously used only to measure residents’ perceptions, the study provides a common measurement instrument to compare tourists’ and residents’ perceptions.

Keywords

Citation

Cassia, F., Vigolo, V., Ugolini, M. and Baratta, R. (2018), "Exploring city image: residents’ versus tourists’ perceptions", The TQM Journal, Vol. 30 No. 5, pp. 476-489. https://doi.org/10.1108/TQM-11-2017-0161

Download as .RIS

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited


1. Introduction

A positive and distinctive city image is the first step towards successful city branding (Buhalis, 2000; Merrilees et al., 2012; Paskaleva-Shapira, 2007). City image can be described as the set of beliefs, ideas and impressions people hold regarding a city (Kotler, 1997). This concept has received widespread attention in tourism studies and particularly from the perspective of external stakeholders, such as tourists (e.g. Beerli and Martin, 2004; Byon and Zhang, 2010; Cherifi et al., 2014; Chi and Qu, 2008; Mak, 2017). In fact, the destination image held by tourists is widely recognised as a determinant of tourist satisfaction with the destination and revisit intention (Kim and Lee, 2015; Papadimitriou, Apostolopoulou and Kaplanidou, 2015; Stylidis, 2016). Less attention has been devoted to city image from an internal stakeholders’ perspective (Martini and Buffa, 2015). Nevertheless, in recent years several scholars have emphasised the importance of assessing the image residents hold of the place where they live (e.g. Gilboa et al., 2015; Stylidis, 2016; Stylidis et al., 2015; Zenker and Rütter, 2014). Residents’ perceptions are important because a positive city image can support tourism development and affect the overall tourist experience (Stylidis et al., 2014). Even fewer studies have compared tourists’ and residents’ perceptions with regard to city image. However, an integrated analysis approach is required to promote city branding and facilitate the sustainable development of cities in the long term (Crouch and Ritchie, 1999). From this perspective, a competitive and successful destination is the one that combines the well-being of all its stakeholders—tourists, businesses and local residents (Paskaleva-Shapira, 2007).

Some studies have highlighted the existence of different perceived city images according to different groups of stakeholders. For example, Stylidis et al. (2016) suggested that residents tend to have more positive perceptions than tourists do, while Stylidis et al. (2017) maintain that tourists hold more favourable perceptions than residents. Conversely, other scholars have found similar opinions regarding city image between residents and tourists (e.g. Ryan and Aicken, 2010).

Regarding the context of analysis, most research about city image has focused on big cities (e.g. Anholt, 2006; Gilboa et al., 2015). Some other studies comparing residents’ and visitors’ perceptions have focused on the place image at a regional level (e.g. Ryan and Aicken, 2010) or at a country level (e.g. Henkel et al., 2006), while others have compared visitors’ and non-visitors’ perceptions rather than residents’ and tourists’ points of view (e.g. Choi et al., 2011). Very few studies have devoted their attention to small- and middle-sized urban destinations. For these cities, the interaction between residents and tourists is even stronger than in big destinations (Den Dekker and Tabbers, 2012), and therefore it is important to closely monitor residents’ vs tourists’ perceptions to guarantee adequate community support for tourism development. In this regard, Gilboa et al. (2015) explicitly emphasise the need to assess the image of small- to medium-sized cities, and not just major capital cities.

This study addresses these gaps in the literature by comparing residents’ and tourists’ perceptions in a medium-sized city located in the north of Italy—the city of Verona. In particular, the aim of this study is to: to examine tourists’ perceptions of the city of Verona’s image; to examine residents’ perceptions of the city of Verona’s image; and to compare the perceptions of the two groups by identifying similarities and significant differences.

From a methodological point of view, this study adopts a quantitative approach based on a structured questionnaire submitted to a sample of residents and tourists. Specifically, the study contributes to the literature about city image by testing and developing a common scale to measure both residents’ and tourists’ city image perceptions, rather than using a different scale for each group following Gilboa et al. (2015).

Overall, the findings provide important insights both for city planning and city marketing.

The paper is organised as follows: Section 2 provides the theoretical background for the study, the methodology is described in Section 3, and results are presented in Section 4, while conclusions, implications and limitations of the research are listed in Section 5.

2. Theoretical background

City image is a mental picture that may depend both on objective knowledge about the services and facilities provided by a city, and on more emotional and affective components (Baloglu and Brinberg, 1997; San Martín and Del Bosque, 2008; Stylidis et al., 2017). Two main streams of research can be identified regarding city image—one focusing on external stakeholders, especially tourists (e.g. Boo et al., 2009; Heung and Quf, 2000), and the other focusing on internal stakeholders, such as residents or local businesses (Merrilees et al., 2009, 2012; Ramkissoon and Nunkoo, 2011). Very few studies have attempted to combine the two perspectives (e.g. Ahmed, 1991; Jutla, 2000; Ryan and Aicken, 2010; Stylidis et al., 2017), emphasising the need to consider the perceptions of diverse groups of stakeholders (both internal and external) when assessing city image. City image may have concrete consequences regarding attitudes and behaviours of both residents and tourists (Gilboa et al., 2015; Jaffe and Nebenzahl, 2006; Kotler, 1997). Therefore, understanding city image is important from a city management or marketing perspective because it enables the identification of a city’s strengths and weaknesses (Luque-Martínez et al., 2007) and the consequent correction of the more problematic aspects to improve the overall city image. In fact, a positive destination image translates into positive tourists’ attitudes and behaviours (Aksu et al., 2009; Byon and Zhang, 2010; Chi and Qu, 2008; Phillips and Jang, 2008; Stylidis et al., 2015, 2017), thus increasing the destination’s overall competitiveness (Pike and Ryan, 2004).

Residents’ perceptions, even if less investigated by the previous literature (Stylidis, 2016), play a likewise significant role in residents’ attitudes towards tourism, their intention to recommend the destination (Bigne et al., 2005; Stylidis et al., 2017) and their support of further tourism development (Ramkissoon and Nunkoo, 2011; Stylidis, 2016). In this regard, the involvement of residents as part of the tourism planning process is a necessary condition for the sustainable development of a destination in the long term (Nunkoo and Ramkissoon, 2012; Stylidis, 2016). Besides residents representing an important intangible component of the overall tourist experience (Stylidis et al., 2015), Gallarza et al. (2002) emphasised the “active role” of residents, who have their own image of the city where they live. Such image should be investigated in comparison with tourists’ city image (Sternquist Witter, 1985). In addition, an examination of residents’ city image can help policy makers to understand how to improve their quality of life and welfare (Luque-Martínez et al., 2007).

Studies comparing tourists’ and residents’ perceptions of city image have arrived at different conclusions. Some scholars highlight the existence of different city images according to the considered group of stakeholders. For example, Jutla (2000) examined the image of Shimla (India) as perceived by tourists and residents. The study revealed that tourists’ image of the city was based on the natural and cultural landscapes, whereas residents’ image was based on their familiarity with the city. In addition, some residents ascribed negative aspects of city image such as congestion, over-development, water shortage and the high cost of living to the presence of tourists. Similarly, Zenker and Beckmann (2013) compared internal with external stakeholder perceptions of the city of Hamburg, Germany, and identified different perceptions between the two groups and the existence of stereotypes held by non-residents. In fact, a higher familiarity with a place can be related to a more positive city image (Baloglu, 2001). More recently, Papadimitriou, Kaplanidou and Apostolopoulou (2015) addressed the city image of Patras (an urban Greek destination) and found significant differences in city image perceptions among residents, past tourists and prospective tourists. Specifically, for residents, overall image perceptions were influenced mainly by cognitive components of destination image. Moreover, other scholars argued that residents may hold a more positive city image than tourists because of more accurate perceptions of their own city and their stronger level of place attachment (Stylidis et al., 2016). However, recent research has shown that tourists tend to have more positive perceptions of city image than residents do. For example, in their study conducted in the resort city of Eilat, Israel, Stylidis et al. (2017) found that tourists retain more favourable perceptions than residents because they may be influenced more by the affective component than by the cognitive component of destination image, thus corroborating the findings of Papadimitriou, Kaplanidou and Apostolopoulou (2015).

Finally, other scholars did not find differences in perceptions between internal and external stakeholders. For example, in their study about the image of the island of Waiheke, New Zealand, Ryan and Aicken (2010) described an overall high congruency between perceptions of the two groups of respondents, even though some tourists criticised the island development.

Besides the contrasting results found in the literature and the adoption of different perspectives when studying city image, scholars tend to agree that city image is a multi-dimensional construct. For example, according to Echtner and Ritchie (1991), destination image is the result not only of the perceptions of single destination attributes, but also of holistic impressions, that is, the overall impressions of the destination (e.g. atmosphere). Holistic impressions can be based both on common traits (such as accommodation and infrastructure) and unique destination features. Moreover, Echtner and Ritchie (1991) distinguished between the functional and psychological elements of destination image. Functional characteristics are based on physical characteristics and are directly observable or measureable, whereas psychological characteristics concern feelings and cannot be directly measured (Echtner and Ritchie, 1991). Each of these components can be based on traits common to all destinations, as well as to unique features, set along a functional–psychological continuum. Similarly, other scholars have suggested considering both cognitive and affective image dimensions (e.g. Baloglu and McCleary, 1999; Pike, 2009; Qu et al. 2011).

Examples of other dimensions that compose the destination image include landscape and surroundings, natural resources, attractions, shopping facilities (Baloglu and McCleary, 1999), infrastructures (Beerli and Martin, 2004), social interaction (Crompton et al., 1992), overall convenience or price, accommodation and food, culture and climate (Heung and Quf, 2000). In a large-scale international study not specifically aimed at tourists, Anholt (2006) and Anholt-GfK (2015) developed a city brand index by including six dimensions of city image: presence (i.e. international status and standing); place (i.e. outdoors and transport); prerequisites (i.e. basic necessities and public amenities); people (i.e. friendliness and cultural diversity); pulse (i.e. interesting events and activities) and potential (i.e. economic and educational opportunities). The 50 cities considered by Anholt-GfK (2015) are capital cities and well-known destinations, such as London, Paris, New York and Rome, whereas small- and medium-sized cities were not considered.

Regarding city image dimensions to emerge from studies focusing on residents’ perceptions, Merrilees et al. (2009) assessed the image of the Gold Coast city in Australia, and identified dimensions such as business creativity, shopping, nature, cultural activities, social bonding, safety, clean environment, sun and surf brand personality. The authors further emphasised the importance of studying residents’ perceptions of city image by showing that different perceptions of city image exist even among residents of the same city, for example, high-income vs low-income residents.

Ramkissoon and Nunkoo (2011) explored city image among residents in Port Luis, Mauritius, and proposed four image dimensions: social attributes, transport attributes, government services attributes and shopping. Meanwhile, Stylidis (2016) conducted a study among residents of Kavala (an urban destination in Greece) and classified the following dimensions: community services, physical appearance, social environment and entertainment services. In a recent study conducted among the residents of Eilat, Israel, Stylidis (2018) identified natural environment, amenities, attractions, accessibility and social environment as city image dimensions. As synthesised by Ramkissoon and Nunkoo (2011), studies focusing on residents propose dimensions such as nature, recreational activities, shopping, restaurants, business creativity, social capital, social relations and bonding, cultural tolerance, interaction and cultural activities, thus often overlapping with destination image dimensions. However, some studies include image dimensions that are particularly relevant for residents but would not be appropriate for tourists. In this regard, Zenker et al. (2013) conducted a study among the residents of the 15 largest German cities and identified city image features that particularly pertain to residents, namely job opportunities and cost efficiency. These features are closely linked to aspects such as cost of living, the housing market and the availability of apartments and houses.

From a methodological perspective, a few studies adopted a qualitative approach (e.g. Laaksonen et al., 2006; Ryan and Cave, 2005). For example, in their study about city image Ryan and Aicken (2010) implemented a qualitative approach using open-ended questions to identify the image attributes of the island of Waiheke, New Zealand, according to residents and visitors. In addition, Zenker and Beckmann (2013) conducted in-depth interviews and an online survey with open-ended questions to assess the city image of Hamburg. However, despite these exceptions, most research comparing residents’ and tourists’ perceptions has adopted a quantitative approach. For example, Gilboa et al. (2015) compared the images of three cities (Rome, Trieste and Jerusalem) using different city dimensions for residents and tourists. The authors found that residents’ overall perception of city image comprised four dimensions (municipal facilities, leisure, security and public services), while tourists’ overall perception of city image comprised five dimensions (caring, tourism and recreation, security, public services, and leisure and entertainment). In a different study, Stylidis et al. (2017) focused on the cognitive and affective dimensions of the destination image of Eilat, Israel, and used the same measures for tourists and residents. The cognitive dimensions of city image included natural environment, amenities, social environment and attractions, while the affective dimensions included extreme affective states, for example, boring or exciting and sleepy or lively.

To conclude, while some city image dimensions are necessarily more relevant for one group of stakeholders than for another (e.g. attractions for tourists or job opportunities for residents), there is a need to explore residents’ and tourists’ perceptions of city image further with a common measure that can compare city image between groups. Different perspectives must be considered by city planners and city marketers, since gaps and divergences in the perceptions of a city can lead to conflicts between residents and tourists (Stylidis et al., 2015) and this can in turn affect the overall sustainability of a tourist destination (Byrd et al., 2009; Stylidis et al., 2017).

Based on these considerations, this study intends not only to assess tourists’ and residents’ perceived city image, but also to compare and jointly analyse both images since different stakeholders can perceive the same city differently, according to their own filter or lens (Merrilees et al., 2012; Stylidis et al., 2015, 2017).

According to this theoretical background, the following null hypothesis will be tested:

H0.

There is no significant difference between residents’ and tourists’ perceptions of the city image of Verona.

3. Methodology

This study focused on a middle-sized destination situated in Northeast Italy—Verona. The choice of this city was consistent with the purpose of filling the knowledge gap highlighted in the previous sections of the paper, that is, the need to study the city image of small- and middle-sized urban destinations. Verona is the second largest municipality of the Veneto region, after Venice, with a population of nearly 260,000 inhabitants (ISTAT, 2016). Verona has been designated as a World Heritage Site by UNESCO, and tourism is a well-developed industry there: in 2016, Verona recorded 1,725,908 arrivals and 3,618,193 overnight stays, and tourism flows increased by more than 77.66 per cent from 2006 to 2016 (U.O. Sistema Statistico Regionale, Regione Veneto, 2016).

To test the research hypothesis a quantitative research design was used. Data collection took place from January to March 2017 and was based on non-probabilistic sampling. This choice was guided by the difficulty of drawing a probabilistic sample of the tourists that visit Verona. More specifically, convenience sampling based on respondents’ easy accessibility, availability at a given time and willingness to participate was used (Etikan et al., 2016). In fact, the respondents were approached, and for the majority directly interviewed, at the weekends during waiting times outside the main attractions of Verona, where both tourists and residents can be found. In addition, the opportunity was given of self-administering the questionnaire through a link to a web-based version of the survey. The final sample was composed of 380 residents of Verona and 167 tourists, leading to an overall sample of 457 individuals. The sizes of the two groups had not been defined a priori but resulted spontaneously from the sampling process (all people that were approached by interviewers and who agreed to participate were included in the samples). However, the analysis technique (t-test) used in this paper takes into account the standard error of the estimates of the means for each group. Therefore, the different sample sizes were not a concern.

The questionnaire included multiple-item measures of the city image dimensions and questions related to the demographic profile of the respondents, beyond some space for free comments. To grasp city image perceptions, the multiple-item measures developed by Gilboa et al. (2015) to register residents’ perceived city image along with dimensions (Municipal facilities, Leisure, Security and Public services) were used. A few adaptations were introduced to make the items more relevant for tourists as well. For example, the original item “Tourism facilities (restaurant, parks)” was expanded into “Tourism facilities (accommodation, restaurant, parks)”. Similarly, the item “Easy to communicate with municipality officials” was expanded into “Easy to communicate with municipality officials, local police, etc.”. All 18 items included by Gilboa et al.’s (2015) residents’ scale were retained (see below list). Like Gilboa et al.’s (2015) study, respondents were asked to rate their level of agreement on seven-point Likert scales, with 1 and 7, respectively, meaning high disagreement and high agreement with each statement.

Items used and grouped according to Gilboa et al.’s (2015) city image scale are as follows.

Scale items:

  1. Factor I—municipal facilities:

    • a tolerable level of air pollution;

    • well lighted at night;

    • good public transportation;

    • care for elderly people;

    • well-maintained streets and sidewalks; and

    • easy communication with municipality officials, local police, etc.

  2. Factor II—leisure:

    • tourism facilities (accommodation, restaurants, parks, etc.);

    • close to major cities;

    • close to main motorways;

    • discos and night clubs; and

    • youth clubs (scouts, etc.).

  3. Factor III—security:

    • quiet;

    • safe;

    • a low crime rate; and

    • not crowded.

  4. Factor IV—public services:

    • enough bank and postal branches;

    • enough shops; and

    • enough hospitals and health care facilities.

For each of the two subsamples (residents and tourists) data were first analysed through an exploratory factor analysis (EFA) followed by a confirmatory factor analysis (CFA) to assess scale validity and reliability. Subsequently, residents’ and tourists’ city image perceptions were compared through t-tests.

4. Findings

4.1 Respondents’ profile

The final sample included 380 residents and 167 tourists. The subsample of residents was composed mainly of women (62 per cent) and the average age was 39 years, with a minimum of 16 and a maximum of 87 years. Regarding occupation status, 29 per cent were students, 27 per cent were employees, 12 per cent were self-employed, 10 per cent were retired, 3 per cent were managers, 3 per cent were unemployed, 1 per cent performed household work and 2 per cent performed other jobs. The high number of students was not surprising since Verona hosts a university with about 25,000 students. The majority of residents (48 per cent) defined their income to be in the average range, followed by those who declared that their income covered their costs (23 per cent), those who defined their level of income as lower than average (12 per cent) and those who defined their income as much higher than the average (1 per cent).

The subsample of tourists included more women (53 per cent) than men (47 per cent). The average age was 38 years, with a minimum of 14 and a maximum of 76 years. The majority of respondents were employees (35 per cent), followed by those who were self-employed (22 per cent), students (15 per cent), managers (8 per cent), performed other jobs (8 per cent), retired (4 per cent), performed household work (2 per cent) and unemployed (2 per cent). Regarding perceived income level, 46 per cent of tourists defined their income in the average range, 20 per cent declared that their income covered their costs, 7 per cent defined their level of income as lower than average, 3 per cent as higher than average and 2 per cent as much higher than the average. Most tourists (72 per cent) were in Verona for leisure motives.

4.2 Measurement validation

Before comparing city image perceptions between residents and tourists, measurement validity and reliability were assessed through EFA followed by CFA for each of the two groups (residents and tourists).

First, EFA with Varimax rotation was run through PASW Statistics software, using the principal components method to extract the factors. This analysis freely allows the grouping of items into factors (Worthington and Whittaker, 2006). Both the Kaiser–Meyer–Olkin and Barlett’s test of sphericity were satisfactory for both subsamples, thus supporting the appropriateness of factor analysis. After a first round of analysis, the items “Low air pollution” and “Safe” were excluded because of high cross loadings. The final rotated Varimax solutions yielded four factors, as expected, but some items loaded on factors that were different from those highlighted by Gilboa et al. (2015). We then ran a CFA through AMOS software to assess the reliability and validity of the measures. The overall goodness of fit was satisfactory for both subsamples (Bagozzi and Yi, 2012) with χ2=164.37, df=90 (p<0.01); χ2/df=1.82; CFI=0.96; RMSEA=0.04, pclose >0.10; and SRMR =0.03 for the residents’ subsample; and χ2=150.20, df=90 (p<0.01); χ2/df=1.66; CFI=0.93; RMSEA =0.06, pclose >0.10; and SRMR =0.05 for the tourists’ subsample.

The final constructs and items resulting from the factor analyses, highlighting some differences compared with the initial measures (Items used and grouped according to Gilboa et al.’s (2015) city image scale, list above) are shown in the below list. In fact, the first factor combines most of the items that composed the “Public services” and “Leisure” dimensions in the original scale developed by Gilboa et al. (2015). Therefore, for this study it was labelled “Services and leisure”. The second and third factors are consistent with the original scales (except for the two items that were dropped through the factor analyses) and were labelled accordingly, “Security” (Factor 2) and “Municipal facilities” (Factor 3). The last factor was composed of two items that in the original scale were included in the leisure dimension. Since these items refer to specific diversion activities, Factor 4 was labelled “Entertainment”.

Scale items:

  1. Factor I—services and leisure:

    • near major cities;

    • near major highways;

    • tourism facilities;

    • enough medical facilities;

    • enough shops; and

    • enough bank and post-office branches.

  2. Factor II—security:

    • a low crime rate;

    • quiet; and

    • not crowded.

  3. Factor III—municipal facilities:

    • well-maintained streets and sidewalks;

    • good public transportation;

    • caring for older people;

    • easy to communicate with municipality officials; and

    • well lit at night.

  4. Factor IV—entertainment:

    • discos and night clubs; and

    • youth clubs.

4.3 Mean values and t-tests

To obtain an overview of how tourists and residents perceive city image, the mean value for each item was examined. The three items that registered the higher scores in the tourist subsample were: presence of shops, location near major highways and availability of tourism facilities. In the resident subsample, the three items that obtained the highest scores were location near major highways, location near major cities, and presence of shops. Hence, for both subsamples, items belonging to the services and leisure dimension received the highest scores. Although tourists revealed positive perceptions of the general maintenance of streets and sidewalks, residents were quite critical in this regard and assigned the lowest score to this item. In addition, both tourists and residents tended to perceive Verona as a crowded city. The findings for all items are summarised in Table I.

To compare perceptions of residents with perceptions of tourists, t-tests for the mean values of each dimension were conducted. Overall, the mean values for the four factors show that both tourists and residents hold quite a positive perception of the city image. In particular, services and leisure obtained the highest score among tourists, followed by municipal facilities, security and entertainment. Residents, as well, assigned the highest score to services and leisure, followed by entertainment, security and municipal facilities.

The results of the t-tests show that no significant differences emerged between the perceptions of the two groups of respondents with regard to services and leisure, security and entertainment (p>0.05). Therefore, for these three dimensions of city image, the findings support the null hypothesis, H0, according to which there is no significant difference between residents’ and tourists’ perceptions of the city image of Verona. However, tourists rated the city’s municipal facilities significantly higher than residents did (p<0.001). For this specific dimension, the findings indicate a rejection of H0, and therefore the alternative must be accepted:

H1.

There is a significant difference between residents’ and tourists’ perceptions of the city image of Verona (Table II).

5. Conclusions and implications

The purpose of the study was to assess the city image of Verona both as a city in which to live and as a tourist destination, and to compare city images held by residents and tourists. The results contribute to advancing available knowledge (Merrilees et al., 2012; Stylidis et al., 2015, 2017) by reconciling studies that have advocated either the existence or non-existence of differences in the city image perceived by residents and tourists. In fact, our findings highlight that differences exist for only one of the four dimensions of city image, that is, municipal facilities. For all other dimensions, residents and tourists showed similar perceptions. This applies also to the specific city image attributes: the subsamples demonstrated similar perceptions for 12 of the 16 attributes measured in this study. For example, both tourists and residents tended to perceive Verona as quite a crowded city. This result is interesting because it suggests that long-term efforts for the deseasonalisation and decentralisation of tourist flows may be able to simultaneously improve both tourists’ and residents’ perceptions.

The only significant difference between subsamples emerged for municipal facilities, for which tourists revealed more favourable perceptions than residents. In line with the previous literature (Stylidis et al., 2017), the lower ratings reported by residents could be explained by the fact that residents tend to be more critical of city attributes about which they have objective knowledge, whereas tourists focus more on emotional and affective dimensions. In fact, residents tend to have more accurate perceptions of city attributes than do tourists because they have greater experience of the city. In detail, residents were critical of the general maintenance of streets and sidewalks and the lack of possibility for communicating with municipality officials.

The findings of this study also contribute to enriching knowledge about the measurement of city image. While the majority of available studies have supported the use of distinct scales to grasp residents’ and tourists’ perceptions (e.g. Gilboa et al., 2015), this study has used one single scale for both residents and tourists.

Practical implications for city planners, destination management organisations and city marketers can be derived from the results of the research by considering the four dimensions of the city image and their 16 attributes. First, an effective deseasonalisation or decentralisation strategy could be implemented to minimise the weak point related to city congestion. In fact, respondents’ perceptions about crowdedness suggest that, without any intervention, tourism development may be close to reaching unsustainability. Therefore, while tourism represents a valuable resource for Verona from an economic point of view, the social and environmental impacts on residents’ quality of life may be close to unsustainability. In addition, the standard of some facilities such as streets, sidewalks and public transport should be addressed by municipal authorities and consequently improved to ensure residents’ welfare and quality of life. Second, since services and leisure obtained the highest scores among respondents and thus represent a strong point for the city image, city marketers could emphasise this aspect when promoting Verona as a tourist destination. Finally, the findings show that both residents and tourists do not hold a high opinion of the city’s ability to care for older people. Given that population ageing is a major demographic trend (United Nations, 2015), especially in developed countries, and that older people represent an increasingly attractive segment for the tourism industry (Vigolo, 2017), city planners and DMOs should strive to improve facilities for older individuals, thus responding to the needs of both residents and tourists.

However, this study is not free from limitations. The first major shortcoming concerns the fact that the questionnaire did not address residents’ and tourists’ attitudes and behaviours, but rather just their perceptions about the city image. Hence, we must rely on the prior literature to claim that a positive image translates into positive behaviours towards the city itself. Second, only Italian tourists participated in the research, since the period of the data collection was rather unfavourable for the presence of foreign tourists. Further research should incorporate the perceptions of foreign tourists, who constitute a relevant part of Verona tourism flows. In addition, this study measured only functional dimensions of city image. Future studies could attempt to develop a common scale that includes both functional and affective dimensions of city image relevant to both residents and tourists. Moreover, the use of a non-probabilistic sampling technique may represent a limitation to the generalisability of the findings. Future studies may overcome this limitation by adopting probabilistic sampling methods, such as stratified sampling. Other perspectives could also be considered, such as those of tourism businesses and local authorities. Finally, the research could be broadened to other small- to medium-scale cities, which constitute the vast majority in the Italian setting.

Descriptive statistics for city image items

Tourists Residents
Items Mean SD Mean SD
Services and leisure
Near major cities 5.84 1.137 5.90 1.081
Near major highways 6.03 1.166 6.19 0.919
Tourism facilities 5.91 1.200 5.85 1.118
Enough medical facilities 5.24 1.264 5.61 1.274
Enough shopsa 6.04 1.174 5.87 1.241
Enough bank and post-office branches 5.06 1.323 5.16 1.451
Security
A low crime rate 4.57 1.305 4.52 1.418
Quiet 5.30 1.287 5.29 1.359
Not crowded 4.05 1.680 4.03 1.594
Municipal facilities
Well-maintained streets and sidewalksa 4.88 1.505 3.79 1.673
Good public transportationa 4.60 1.502 4.28 1.665
Caring for older peoplea 4.21 1.182 4.31 1.355
Easy to communicate with municipality officials 4.27 1.375 4.07 1.449
Well lit at night 5.07 1.301 4.92 1.383
Entertainment
Discos and night clubs 4.64 1.454 4.79 1.532
Youth clubs 4.65 1.265 4.62 1.465

Note: aItems for which residents’ and tourists’ mean values differed at the 0.05 level of significance based on t- tests

Differences in image dimensions between tourists and residents

Tourists Residents
Mean SD Mean SD Mean difference t df
Services and leisure 5.71 0.920 5.76 0.879 −0.04655 −0.562 545
Security 4.63 1.128 4.61 1.129 0.02727 0.26 545
Municipal facilities 4.67 0.984 4.27 1.056 0.39642 4.125* 545
Entertainment 4.63 1.255 4.69 1.343 −0.05055 −0.401 545

Note: *p<0.001

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Corresponding author

Vania Vigolo is the corresponding author and can be contacted at: vania.vigolo@univr.it

About the authors

Fabio Cassia, PhD in Marketing, is Researcher at the Department of Business Administration, University of Verona, Italy. His research interests are related to business-to-business marketing and branding, services marketing, international business.

Vania Vigolo, PhD in Marketing, is Researcher at the Department of Business Administration, University of Verona, Italy. Her research interests include services marketing, with a focus on tourism and hospitality, and branding strategies.

Marta Maria Ugolini, PhD in Business Administration, is Full Professor at the Department of Business Administration, University of Verona, Italy. Her research interests include service marketing and management, especially in the tourism and health care industries.

Rossella Baratta is PhD Student in Management at the Department of Business Administration, University of Verona, Italy. Her research interests include sustainability in tourism and destination management.