This research aims to verify the mismatches between the tourists’ and residents’ perceptions and satisfaction regarding the tourism destination attributes and provides a list of priorities for public organisations and Destination Management Organisation managers.
The authors combined the importance-performance-analysis and the analysis of Penalty-reward contrast, Impact Range Satisfaction and Impact Asymmetry (IAA). Data were collected from residents and tourists in Santa Maria da Feira, Portugal.
Results revealed the accumulated effect of each attribute to improve overall satisfaction with the destination and enhance the tourism destination’s image and attractiveness as a place to visit and to live. It can help develop tourism destinations from the placemaking perspective. IAA results showed some attributes dissatisfiers. It is an alert to city managers since they are the basic conditions for the destination.
The theoretical implications build the society-centric tourism development approach. For the destinations, it means focusing on serving different consumers’ profiles and understanding that part of the market target lives in the city or nearby; they are “staycationers.”
The findings also represent insights into building a two-tier destination brand architecture for internal and external consumers.
Understanding the residents as leisure consumers helps public city managers improve the quality of life in society.
The theoretical implications build the society-centric tourism development approach. For the destinations, it means focusing on serving different consumers’ profiles and understanding that part of the market target lives in the city or nearby; they are “staycationers.” The findings also represent insights into building a two-tier destination brand architecture for internal and external consumers.
1. Introduction
More and more places are using destination branding (as one type of place branding) to target tourists and inhabitants for touristic purposes, highlighting tourist attractions and experiences and positioning the place in the tourism market (Escobar-Farfán et al., 2024). However, satisfying both target groups is difficult, as they often share different perceptions and conceptions about the destination. Destination tourism competitiveness has increased, and understanding of what constitutes effective tourism development has evolved to be more society-centric (Costa et al., 2025). Consequently, decision-makers must create destination image-building strategies that cater to the diverse needs of various target groups. This requires an even-handed strategy reconciling external and internal priorities to create a brand architecture beyond the tourist gaze to encompass residents as key stakeholders (Zelenskaya and Elkanova, 2021).
A destination image comprises a set of beliefs, ideas and impressions that a person creates about a place, and it is shaped by various cognitive and affective components (Bigné et al., 2001; Stepchenkova and Mills, 2010; Kock et al., 2016). It contributes to the destination’s brand and significantly influences consumer behaviour throughout the tourism experience, including the pre-visit phase (destination selection process), during the visit (modification of the image through experience and satisfaction) and post-visit (potential revisits and recommendations of the destination) (Gallarza et al., 2002; Beerli and Martin, 2004).
Despite the destination image being usually considered only from the visitor’s perspective, nowadays, it is essential to consider it from a resident standpoint as they are significant promoters of the destination image (Gorji et al., 2023). Residents providing hospitality and tourism receptivity contribute to a destination’s branding, and are also internal tourism consumers due to the rise of staycation (Stylidis, 2020). In staycation, residents stay in their city instead of travelling to another destination and use this time to enjoy the local environment, making trips to places within a radius of 50 miles from their homes (Yesawich, 2010). Often, staycationers stay in a hotel to explore the urban or rural areas around their city (Cvelbar et al., 2021).
Nevertheless, residents as leisure consumers and destination branding creators are not a priority in the agenda of tourism decision-makers nor the literature (Braun et al., 2013), despite their growing importance in the economy, especially in small non-costal tourism destinations (James et al., 2017; Stylidis, 2020). However, it can be advantageous to rethink the destination considering the tourists’ and residents’ perspectives jointly. Residents can help to promote a destination (Chen and Rahman, 2018), boost its branding (Chan and Marafa, 2016; Zenker et al., 2017) and stimulate local tourism firms, particularly in the low season, through staycation (Stylidis, 2020). Also, destinations can use the tourism infrastructure to improve the leisure offered to residents and enhance the quality of life.
Our study assumes that we must rethink tourism development and destination branding from the perspective of residents and visitors, aligning tourism competitiveness with placemaking and recent views, such as Destination well-being and Beyond GDP approach (Dwyer, 2022; Dwyer, 2023). To achieve this, we must understand the decision-making priorities and provide insights helpful to an integrative destination management approach that supports a two-tier destination brand architecture for internal and external consumers. To contribute to this topic, we propose to define the priorities based on two visions of the tourism destination’s perceived image. Our study had two objectives:
To verify the mismatches between tourists’ and residents’ perceptions and satisfaction regarding the tourism destination attributes.
To identify the priorities for tourism decision-makers to improve the perceived image of the tourism destination, considering tourists’ and residents’ perspectives jointly.
Our research contributes towards understanding residents as tourism consumers and contributors to destination branding, a necessary topic nowadays. We followed the theoretical line of society-centric tourism development (Chim-Miki et al., 2023) to examine tourism destinations as places to live and visit, while providing insights for managers to develop integrative destination brand architecture. Our study has also methodological implications, highlighting different tools for local decision-makers to satisfy the profiles of both tourists and residents. Finally, by focusing on the city of Santa Maria de Feira in mainland Portugal, we provide practical implications for public organisations and Destination Management Organisation (DMO) managers that can be helpful for other tourism places.
2. Tourism destination image and its effects
2.1 Evaluation of tourism destination attributes and their effects
A tourism destination is a set of tourism facilities and services composed of attributes to meet the needs of tourists (Hu and Ritchie, 1993; Gorji et al., 2023). These attributes contribute to creating a set of sub-brands that shape local destination brand architecture. Zelenskaya and Elkanova (2021) highlight that a place has more than one brand, including tourism attractions, gastronomic brands, event brands and corporate or product brands.
A tourist’s global experience is influenced by the dimensions of the services and the place that defines the destination image (Kock et al., 2016). Destinations must develop their intrinsic characteristics to create products, services and infrastructures that promote the desire to visit and to guarantee a positive and memorable experience for all visitors and residents (Murphy et al., 2000). Destinations have intrinsic attributes, such as climate, nature, culture and tradition (Laws, 1995), technological, cultural, economic, political-legal factors and natural space (Murphy et al., 2000). Furthermore, destinations must present services and facilities to promote tourism, such as hotels, transport, entertainment activities (Laws, 1995), travel, catering, entertainment, accommodation and shopping (Murphy et al., 2000). Combining these attributes produces the destination’s visitor experience that impacts the destination image (Kock et al., 2016) and brand (Braun et al., 2013), central aspects for cities guarantee market share (Bigné et al., 2001).
The literature offers several models with different attributes to evaluate destination competitiveness that closely relate to the destination image. For example, Crouch and Ritchie (1999) proposed a holistic model based on comparative and competitive advantages. The first advantage is the destination resources found on endogenous assets, such as human, historical and cultural resources. The second advantage is linked to the ability to use the assets efficiently and effectively, considering the maintenance of the resource in the medium and long term. These authors’ proposals also include other fundamental attributes, namely support factors and resources, i.e. elements that can stabilize the success of tourism; central resources and attractions (these are the primary elements of the image of the tourism destination); tourism destination management; the policy, strategy, planning and development of the destination and the qualifying determinants that consist of programs and management processes.
Other prominent models in the literature offer a systemic view of attributes of tourism destinations, such as those of Dwyer and Kim (2003) and Heath (2003). Even though they are created for tourism competitiveness, they also cover aspects of image and, consequently, these attributes help boost destination branding and placemaking (Custódio et al., 2018). Dwyer and Kim (2003) pointed out that local conditions at a destination positively or negatively influence competitiveness. The destination attributes in their model are divided into four dimensions: resources (endogenous, inherited, created and supported), factors of context conditions, demand conditions and destination management. In turn, Heath (2003) discussed the validity of these models from the perspective of underdeveloped countries due to the need for more focus on driver conditions, such as key drivers of success (people) and vital links (e.g. communication and information management).
The Organisation for Economic Cooperation and Development (OECD) highlighted the need for a general measurement framework for analysing tourism destinations. The OECD promoted a study to generate a common framework of key indicators organised around four categories, namely:
Indicators to measure the performance and impacts of tourism;
Indicators to monitor the destination’s capacity to offer competitive and quality tourism services;
Indicators to monitor the destination attractiveness; and
Indicators to describe policy responses and economic opportunities (Dupeyras and Maccallum, 2013).
The OECD framework facilitates monitoring the performance of elements constituting the destination image while providing insights for managing destination branding. This branding is shaped by various associations consumers form based on their experiences through interactions with the place, its communication, values, behaviours, design and overall culture (Zenker and Beckmann, 2012).
2.2 Destination image and its effects on residents
Recent research reinforced that destination satisfaction is influenced by tourist experiences and destination image (Li et al., 2021; Akroush et al., 2016). The destination’s image, competitiveness and attractiveness are intrinsically related since the performance of the destination’s competitiveness attributes impacts the perceived image and the destination branding. It is essential to highlight that a destination’s perceived image effects both tourist and resident satisfactions, generating double benefits: attractiveness and loyalty to the destination (Chen and Rahman, 2018; Afshardoost and Eshaghi, 2020; Yoon and Uysal, 2005) and place attachment (Azevedo et al., 2013).
Residents are stakeholders in cities and their tourism development; therefore, understanding their perceptions is fundamental for elaborating policy proposals that can promote sustainable tourism (Scalabrini and Remoaldo, 2022; Chim-Miki et al., 2019). Citizens interact with each other and with visitors, creating the social atmosphere of the place that, combined with the physical environment, produces the tourist experience (Braun et al., 2013; Chan and Marafa, 2016); therefore, residents are essential to building the destination image and branding (Bassols and Leicht, 2020).
Tourism destination attributes and their perceived image are also evaluated by residents who participate in festivals, fairs and events and consume tourism attractions in their leisure time (Costa et al., 2024; Chim-Miki et al., 2019). The emergence of the staycation phenomenon through several crises, such as global economic recession, climate and sustainability crisis, COVID-19, created a relevant market and further accentuated this tourism modality (Cvelbar et al., 2021; Kay and Wang, 2010). As such, staycation consumption still needs to be addressed by tourism firms and scholars (Zhang et al., 2022). With the growth of short-distance trips and holidays in the place where people live, a staycation can be a potential market helpful to minimise the seasonality problems (Cvelbar et al., 2021; Zhang et al., 2022) and improve leisure options for citizens (Moon and Chan, 2022).
Destination satisfaction is achieved when consumers think that their experience at the destination is equal to or greater than their previous expectations (Prayag, 2009), thus equating to the destination’s image or brand. This satisfaction is directly associated with destination loyalty as it leads to consumers becoming more likely to go back to relishing the same products or services and suggesting them to other people (Chi and Qu, 2008). However, tools for evaluating destinations based on their attributes generally is focused on tourists (Añaña et al., 2018), while the resident’s perspective is typically considered in assessing the societal impacts of tourism from a competitiveness standpoint (Aguiar-Barbosa and Chim-Miki, 2022; Dwyer, 2022), or residents’ attitudes towards tourists and resident participation in tourism planning (Zenker et al., 2017). Literature, therefore, tends to adopt distinct perspectives, acknowledging the existence of different objectives among visitors and residents. Nevertheless, some intersections simultaneously shape the destination as they consume it, contributing to its image and branding (Bassols and Leicht, 2020; Zenker et al., 2017).
There is a specific overlap when residents are regarded as leisure consumers, similar to visitors (Lobo et al., 2023; Costa et al., 2024). Consequently, understanding the importance of destination attributes from the different perspectives of consumers, tourists and residents becomes vital for public organisations and DMO managers to improve the destination image and branding (Bassols and Leicht, 2020). It can help them to conduct a Society-centric tourism development, which, according to Chim-Miki et al. (2023), occurs when tourism becomes a vector to attend to the visitor and community, contributing to social problems, quality of life and creating a destination to visit and live in. Based on the literature review, Figure 1 presents a synthesis of attributes that affect tourists’ and residents’ perceived image of tourism.
Tourism destination attributes affecting the perceived image
Source: Authors’ own work
Tourism destination attributes affecting the perceived image
Source: Authors’ own work
3. Methodology
3.1 Method of analysis
This study uses four quantitative methods following the indications of Karimi and Boley (2022) to analyse in the contexts of asymmetrical relationships: the Importance-Performance-Analysis (IPA) matrix, together with other techniques, namely, Service Quality Gap Analysis based on Penalty-Reward Contrast Analysis (PRCA) and Impact Asymmetry Analysis (IAA):
3.1.1 The Importance-Performance analysis.
It was created by Martilla and James (1977). It is a two-axial matrix that can support the decision-making process towards a more efficient application of resources. The IPA matrix has four quadrants that indicate the prioritisation of resources to generate better satisfaction with the analysed product or service (Figure 2).
IPA matrix – importance–performance analysis
Source: Adapted from O’Leary and Deegan (2005)
3.1.2 Service quality gap analysis based on Penalty-Reward contrast analysis.
Based on two independent IPA analyses of residents and visitors, we calculated the gap score for each attribute using the difference between the mean for importance and performance. We used an independent sample t-test to compare the two groups’ means and determine whether statistical evidence shows they differ significantly. Afterwards, we generate an Accumulated I-P Gap summarising the dissatisfaction of residents and visitors to provide a list of public city manager priorities considering the two perspectives. The satisfaction score with the attributes was recoded into two dummy variables. Considering that our questionnaire used a five-point Likert scale to measure penalty indices, we converted the lowest satisfaction recordings (1 and 2) to 1 and all other recordings to 0 to create the first set. The second set measured the reward indices by converting the highest ratings (4 and 5) to 1 and all other recordings to 0 (Mikulić and Prebežac, 2008; Karimi and Boley, 2022). That means when attributing satisfaction is above a specific reference value, the reward dummy variable (X1pos) is greater than zero and the penalty dummy variable (X1neg) equals zero. If satisfaction with the attribute is below the standard, the penalty dummy variable (X1neg) is less than zero and X1pos is equal to zero. If the satisfaction equals reference, X1pos and X1neg are equal to zero. In this way, we get two regression coefficients for a single independent variable: a coefficient when satisfaction with the attribute is less than the reference value and another when it is more significant, using the following equation:
In which ATn is the satisfaction with the attribute n.
Then, we conducted two separate multiple regression analyses based on the two sets of dummy variables as independent variables and overall satisfaction as the dependent variable. The results were used in two different ways. First, to generate the matrix of classification of attributes according to magnitude penalty and reward coefficients, that is, mandatory, one-dimensional, attractive and neutral attributes (Matzler and Sauerwein, 2002).
3.1.3 Impact range satisfaction analysis.
We determined the Range of Impact on Customer Satisfaction (RICS) by the sum of the absolute values of penalty and reward indices associated with each attribute. Next, we measured the attribute’s potential for generating satisfaction (Satisfaction Generating Potential – SGP) and dissatisfaction (Dissatisfaction Generating Potential- DGP) through the following equations:
In which:ri is the reward index for attribute I; pi is the penalty index for attribute I; RICSi indicates the range of impacts on overall customer satisfaction measured by summing the penalty and reward indices.
3.1.4 Impact Asymmetry Analysis (IAA).
Finally, we performed the IAA that is:
We adopted the Mikulić and Prebežac (2008) categories to IA magnitude: frustraters (IA≤−0.7); dissatisfiers (−0.7 < IA≤−0.2); hybrids (−0.2 < IA <0.2); satisfiers (0.2 ≤ IA <0.7); and delighters (IA ≥0.7).
3.2 Context of analysis
Santa Maria da Feira is a non-coastal small city in the north of mainland Portugal, located in the Metropolitan Area of Porto city. It is close to Porto airport (about 45 kilometres), which constitutes an added value in accessibility and proximity to major motorways. Santa Maria da Feira offers a range of tourism assets, from natural to built environment, providing a rich and diverse array of elements at the heart of its tourism offer. Tourism flow has been growing, despite the number of overnight stays still needs to improve to match the national average (INE, 2019). However, demographically, the city has shown a population decrease and an increase in the ageing of its inhabitants (Pordata, 2019).
Thus, we chose study this city because of three cumulative conditions:
The population ageing index is growing in the city and in the region (Pordata, 2019), which can increase Staycation and become a source of economic development.
On the other side, it demands improved quality of life and leisure offered to the current population and can be a strategy to attract new residents to reduce the population loss.
The municipality has invested in tourism and shows an annual increase in the tourist flow; however, with an overnight stay below the country average (1.8–2.7 nights).
The tourism resources and the positive perception of the city’s image as a destination can be an attraction source for tourists and new residents; besides, it contributes to maintaining the current ones.
3.3 Data collection
The data collection was through a questionnaire. We included filter questions to guarantee the pertinence of the sample. To residents, the filter question is whether a Santa Maria da Feira resident was. To tourists, the filter question is whether the respondent has visited this municipality at least once in the last three years. The questionnaires had questions related to demographic data and to assessing the destination’s attributes. We used statements considering the categorisation and indicators based on the theoretical sources shown in Figure 1. A five-point Likert scale evaluated each item regarding the indicator’s importance for the perceived destination image (1-nothing important and 5-extremely important). At the same time, the respondent evaluated the indicator’s performance in Santa Maria da Feira (1-very Dissatisfied and 5-very Satisfied). One question assesses the overall satisfaction with the destination. Previously, we conducted a pretest phase with three tourism professors and five students to establish content validity.
We opted for an online questionnaire via the LimeSurvey platform during the summer of 2022. This choice of data collection is particularly suited compared to on-site methods. As the respondents may complete the questionnaire after visiting Santa Maria da Feira, the online collection is more convenient and effective than the on-site collection. We selected Portugal’s most popular social media platforms for our promotion, targeting tourist groups on social media, including the Facebook pages of Portuguese DMOs and tourism organisations. We also promoted resident groups and social organisations on Facebook. On Instagram, the strategy was to send private messages to people who shared photos of Santa Maria da Feira.
4. Results
4.1 Participant profile
We collected 175 valid questionnaires, that is, those who attended the filter questions, and it was adequately filled out, 71 tourists and 104 residents. This sample size satisfied the conditions of Churchill (1979), with at least five respondents per scale item. We used SPSS software for data analysis. Although this sample cannot be considered representative of the city (e.g. in terms of size, gender, age and income), it can still serve as a valuable first step in addressing our research question. Table 1 presents some demographic characteristics of the total sample.
Sociodemographic characteristics of the sample
| Characteristic | N | Frequency (%) |
|---|---|---|
| Gender | ||
| Female | 115 | 65.7 |
| Male | 60 | 34.3 |
| Age (years) | ||
| 18–34 | 135 | 77.1 |
| 35–54 | 34 | 19.4 |
| >55 | 6 | 3.4 |
| Income level (€) | ||
| Until 850 | 125 | 71.4 |
| 851–1350 | 32 | 18.3 |
| 1351–2000 | 15 | 8.6 |
| >2001 | 3 | 1.7 |
| Occupation | ||
| Elementary | 19 | 10.8 |
| Secondary | 32 | 18.2 |
| College | 84 | 48.0 |
| Graduate | 40 | 23.0 |
Note(s): n = 175
The tourists’ questionnaire included the motivation for visiting Santa Maria da Feira and the duration. The results indicated that 62.5% had already visited the destination more than six times, 25% visited between 2 and 3 times, 10.7% visited only once and one respondent had already visited more than four times. 72% visited on a trip with friends or family, and more than half of the respondents went for leisure, recreation and vacation (55.4%).
4.2 Importance-Performance analysis
The Importance-Performance Analysis results for the perceived image attributes by tourists revealed a concentration of factors in the matrix, mainly in two quadrants. In general, the destination presented a good Importance-Performance ratio (I-P). Only five items were plotted in Quadrant 1, indicating that tourism public officers and DMO managers should prioritise improvements related to the supply of natural resources for tourism and tourism infrastructure, increasing the diversity of the tourism offer, facilitating resources and price competitiveness. On the other hand, public city managers undergo unnecessary investments (Q4) in general infrastructure, management and communication, according to the tourists’ analysis (Figure 3).
Importance-performance Matrix of destination image attributes by the tourists’ perception
Source: Authors’ own work
Importance-performance Matrix of destination image attributes by the tourists’ perception
Source: Authors’ own work
In Quadrant 2, attributes that meet a good degree of satisfaction, the tourists considered the heritage, history and cultural resources, events, quality of entertainment, health, hygiene, safety, protection, quality of services, accessibility to the destination and hospitality. From the tourist’s perspective, there are items of low importance for the perceived image of the destination, which they also pointed out as low performance in the municipality (Q3). These attributes were air, land and port transport infrastructure, purchase offer, entrepreneurship, labour market and ICT readiness, investment climate, international openness, travel and tourism sector prioritisation and environmental sustainability (Figure 3).
In turn, the Importance-Performance Analysis results for the attributes of the destination image perceived by residents revealed a greater concentration of factors in Quadrants Q2 and Q3 of the matrix, which means that residents also considered an excellent I-P ratio in the destinations. Five items were indicated for concentration efforts (Q1), and three overlapped with the tourists’ points of view (Natural resources and climate, tourism infrastructure and price competitiveness). Residents also indicated that public tourism officers and DMO managers must pay more attention to environmental sustainability and destination accessibility. In contrast, all items with high importance and good performance (Q2) shown by residents coincide with some of those pointed out by tourists: Heritage, history and cultural resources, Protection and safety, Health and hygiene, Quality of services and hospitality. However, from the tourists’ perspective, there are more items in Q2 (Figure 4).
Importance-performance Matrix of destination image attributes by the residents’ perception
Source: Authors’ own work
Importance-performance Matrix of destination image attributes by the residents’ perception
Source: Authors’ own work
From the resident’s point of view, the most significant number of image attributes was in Quadrant 3, which had low importance on the perceived destination image and low performance in the municipality. Of these items, eight coincide with the results obtained from the tourists’ perspective: air, land and port transport infrastructure, the offer for purchases, entrepreneurship, preparation of the job market, the investment atmosphere, international openness and the prioritisation of the travel and tourism sector. However, residents also include Enabling Resources and Destination Marketing. The attributes that residents considered with possible over-attention (Q4) in the destination of Santa Maria da Feira were generally infrastructure, management and communication, special events and ICT readiness. The first two coincide with the tourists’ opinions (Figure 4).
We observed the pairing of some interests and divergence in others from the tourists’ and residents’ points of view. However, the student’s t-test results for the two independent samples showed no significant differences in the average between the two groups. Test-t considered the Importance of Performance attributes as independent variables and the Global Image as a dependent variable. We found significant differences among means only in the importance of Natural resources (p-value = 0.036) and climate and the Performance of Heritage, History and Cultural Resources (p-value = 0.047). The other attribute, the p-value of the Test-t, is above 0.05. Thus, we sum the I-P gaps from residents and visitors to create an accumulated result that ranks the dissatisfaction Gaps. The most significant discrepancies between the importance and performance provide a list of priorities for tourism public officers and DMO managers considering both viewpoints, residents and visitors (Table 2).
I-P gaps of destination image components from the residents and visitors’ perspectives
| Residents | Visitors | Gap I-P Accumulated | Importance t-test | Performance t-test | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Code | Variable | I | P | I-P GAP | I | P | I-P GAP | Rank | t | p | t | p | |
| Endogenous resources | |||||||||||||
| END1 | Natural resources and climate | 4.30 | 3.50 | 0.80 | 4.32 | 3.82 | 0.50 | 1.30 | 3ª | 0.086 | 0.931 | 2.115 | 0.036 |
| END2 | Heritage. history. and cultural resources | 4.52 | 4.30 | 0.22 | 4.27 | 4.29 | −0.02 | 0.20 | 20ª | −2.003 | 0.047 | −0.114 | 0.909 |
| Created resources | |||||||||||||
| CRE1 | Tourism infrastructures | 4.39 | 3.66 | 0.73 | 4.17 | 3.82 | 0.35 | 1.08 | 6ª | −1.728 | 0.086 | 1.163 | 0.247 |
| CRE2 | Air transportation infrastructure | 3.73 | 2.18 | 1.55 | 3.45 | 2.23 | 1.22 | 2.77 | 1ª | −1.591 | 0.113 | 0.223 | 0.824 |
| CRE3 | Land and port infrastructure | 4.11 | 3.23 | 0.88 | 3.98 | 3.10 | 0.88 | 1.76 | 2ª | −0.787 | 0.432 | −0.753 | 0.453 |
| CRE4 | Diversity of the tourism offer | 4.45 | 3.79 | 0.66 | 4.30 | 3.72 | 0.58 | 1.24 | 4ª | −1.212 | 0.227 | −0.454 | 0.650 |
| CRE5 | Shopping | 2.63 | 2.68 | −0.06 | 2.57 | 2.34 | 0.23 | 0.17 | 21ª | −0.274 | 0.785 | −1.780 | 0.077 |
| CRE6 | Quality of entertainment | 4.23 | 3.82 | 0.41 | 4.29 | 3.89 | 0.40 | 0.81 | 11ª | 0.447 | 0.655 | 0.506 | 0.613 |
| CRE7 | Special events | 4.21 | 4.38 | −0.17 | 4.16 | 4.32 | −0.16 | −0.33 | 23ª | −0.389 | 0.698 | −0.376 | 0.707 |
| Supporting factors | |||||||||||||
| SUP1 | General infrastructure | 4.29 | 3.96 | 0.33 | 4.14 | 3.83 | 0.31 | 0.64 | 13ª | −1.178 | 0.241 | −1.053 | 0.294 |
| SUP2 | Security and safe | 4.59 | 4.25 | 0.34 | 4.46 | 4.22 | 0.24 | 0.58 | 16ª | −1.208 | 0.229 | −0.263 | 0.793 |
| SUP3 | Health and hygiene | 4.66 | 4.27 | 0.39 | 4.50 | 4.30 | 0.20 | 0.59 | 15ª | −1.518 | 0.132 | 0.249 | 0.804 |
| SUP4 | Quality of services | 4.63 | 4.09 | 0.54 | 4.43 | 4.14 | 0.29 | 0.83 | 10ª | −1.727 | 0.086 | 0.380 | 0.705 |
| SUP5 | Facilitating resources | 4.20 | 3.77 | 0.43 | 4.15 | 3.79 | 0.36 | 0.79 | 12ª | −0.331 | 0.741 | 0.190 | 0.850 |
| SUP6 | Preparedness of the labour-market | 3.63 | 3.68 | −0.06 | 3.64 | 3.67 | −0.03 | −0.09 | 22ª | 0.083 | 0.934 | −0.082 | 0.935 |
| SUP7 | Accessibility to the destination | 4.45 | 3.84 | 0.61 | 4.32 | 3.90 | 0.42 | 1.03 | 7ª | −1.061 | 0.290 | 0.412 | 0.681 |
| SUP8 | Hospitality | 4.54 | 4.23 | 0.31 | 4.50 | 4.32 | 0.18 | 0.49 | 18ª | −0.353 | 0.724 | 0.752 | 0.453 |
| SUP9 | Management and communication | 4.21 | 3.98 | 0.23 | 4.04 | 3.86 | 0.18 | 0.41 | 19ª | −1.258 | 0.210 | −0.846 | 0.399 |
| SUP10 | ICT readiness | 4.20 | 3.95 | 0.25 | 4.08 | 3.78 | 0.30 | 0.55 | 17ª | −0.843 | 0.401 | −1.156 | 0.249 |
| Strategic areas | |||||||||||||
| STR1 | Entrepreneurship level | 4.05 | 3.70 | 0.35 | 3.83 | 3.54 | 0.29 | 0.64 | 13ª | −1.296 | 0.197 | −1.035 | 0.302 |
| STR2 | Marketing of the destination | 4.09 | 3.55 | 0.54 | 3.83 | 3.56 | 0.27 | 0.81 | 11ª | −1.712 | 0.089 | 0.034 | 0.973 |
| STR3 | Investment context | 3.75 | 3.39 | 0.36 | 3.63 | 3.41 | 0.22 | 0.58 | 16ª | −0.697 | 0.487 | 0.086 | 0.932 |
| STR4 | Travel and tourism prioritization industry | 3.89 | 3.46 | 0.43 | 3.76 | 3.33 | 0.43 | 0.86 | 9ª | −0.929 | 0.354 | −0.878 | 0.381 |
| STR5 | International openness | 3.98 | 3.64 | 0.34 | 3.91 | 3.65 | 0.26 | 0.60 | 14ª | −0.500 | 0.618 | 0.035 | 0.972 |
| STR6 | Price competitiveness | 4.32 | 3.84 | 0.48 | 4.14 | 3.60 | 0.54 | 1.02 | 8ª | −1.410 | 0.160 | −1.699 | 0.091 |
| STR7 | Environmental sustainability | 4.32 | 3.77 | 0.55 | 4.10 | 3.54 | 0.56 | 1.11 | 5ª | −1.590 | 0.114 | −1.629 | 0.105 |
Our results indicated that although the destination is considered to have good accessibility due to its proximity to an airport of another significant tourism destination and access to main roads, this is not the perceived image by tourists and residents. Attributes related to accessibility were the highest I-P Gaps. The results suggested that tourism public officers and DMO managers should analyse the flights’ offers and frequency. Another item both groups pointed out as a gap was related to the leisure offer based on natural resources. The municipality should invest in creating leisure opportunities by exploring its natural areas and in periods appropriate to the local weather. This component will also influence the variable in fourth place in the priorities ranking, that is, improvements in the diversity of the tourism offer. The fifth item was environmental sustainability, which is also linked to offering leisure activities in natural areas. Other items and their ranking of priorities can be seen in Table 2.
The ranking in Table 2 does not mean that there are attributes of the perceived destination image by residents and tourists that tourism public officers, DMO managers and local firms should not consider. All attributes have a degree of importance, but our results indicated which points managers should focus their efforts on first. One component that stands out at the bottom of the priority list is special events. This result reflects a tourism development policy conducted by the municipal government for some years to create a destination branding related to cultural events. Our findings suggested that maybe the investment in the city event agenda achieved a sufficient level, and, currently, tourism public officers and DMO managers should focus on developing other tourism products. The pairing of key variables for tourists and residents highlights the importance of understanding residents as consumers of the tourism offer. This result aligns with Scalabrini and Remoaldo’s (2022) argument that recognising residents’ role is fundamental for developing effective tourism policy proposals. Additionally, it confirms that visitors and residents contribute to creating a destination’s image (Chen and Rahman, 2018), which can significantly impact destination branding (Chan and Marafa, 2016; Zenker et al., 2017). This finding supports Braun et al.'s (2013) assertion that residents play a crucial role in destination branding.
The results from the IPA Quadrants revealed that variables across the four factors are distributed within the matrix without adhering to a consistent pattern by dimension. This finding suggests that the weights assigned to the variables are not prioritised by resource type, which contrasts with the recommendations in established competitiveness models, such as those proposed by Crouch and Ritchie (1999), Dwyer and Kim (2003), and Heath (2003). Although this is a preliminary finding, it may indicate the need to restructure tourism destination competitiveness frameworks and provide insights for developing a different and more complex brand architecture.
Assuming that there is no statistically significant difference between the average evaluation of residents and visitors according to the Test t results, we performed the analysis of Penalty-Reward Contrast (PRCA), the Impact Range Satisfaction (IRSA) and the Impact Asymmetry (IAA) using the entire database.
4.3 Penalty-Reward contrast analysis
According to the PRCA results plotted in the scatter plot, the mandatory attributes have a penalty coefficient significantly higher than the reward coefficient (Figure 5). That means that overall satisfaction is influenced by items in this quadrant when satisfaction with the attribute is below the average level, but is not influenced when it is above. The mandatory variables are CRE3, CRE4, STR1 and SUP2. That means that public tourism officers and DMO managers must improve the infrastructure to access the destination by land or port, incentivise the diversity of tourism offers and improve the city’s entrepreneurial level, security and safety.
Classification of attributes by magnitude penalty and reward coefficients
Source: Authors’ own work
Classification of attributes by magnitude penalty and reward coefficients
Source: Authors’ own work
The attractive attributes present the reward coefficient with a magnitude significantly higher than the penalty coefficient. Therefore, the variables in this quadrant impact the overall results when satisfaction with the attribute is above the average level of satisfaction. Still, it is not influenced when it is below. Only three attributes are in this Quadrant: END1, STR4 and SUP7. These results showed that access to destinations, natural resources and the prioritisation of the tourism sector work as attractors to the perceived image (Figure 5).
Unidimensional attributes present the penalty coefficient with a magnitude close to the reward coefficient. In this case, overall satisfaction is influenced by the level of satisfaction with the attribute when it is above or below the average. END2, CRE2, STR3, STR5, STR6, SUP5, SUP8, SUP9 and SUP10 are Unidimensional attributes (Figure 5). These variables represent the basic components that the visitors hope to find in every city, such as cultural and historical resources, access by air transportation, price competitiveness, facilitating resources, hospitality and international openness. Also, as unidimensional attributes of overall satisfaction, some variables are related to economic development, such as investment context, city management, communication and ICT readiness.
There are also neutral attributes, which do not influence overall satisfaction, regardless of their performance. PRCA results indicated CRE1, CRE5, CRE6, CRE7, STR2, STR7, SUP1, SUP3, SU4, SUP6. Results indicated that most of the attributes are neutral. That means tourism and general infrastructures, shopping, entertainment, events, destination marketing, health and hygiene, quality of services and preparedness of workers are considered basic attributes (Figure 5). They are comparative advantages that neutrally influence overall satisfaction, although they are essential to the destination image and tourism offer. Table 3 presents the indices of Penalty and Reward, which means how much the attribute impacts satisfaction or dissatisfaction.
Results of IRSA and IAA
| Attribute | Penalty indices | Reward indices | RICS | Satisfaction Generating Potential (SGP) | Dissatisfaction generating Potential (DGP) | Impact asymmetry | Factora |
|---|---|---|---|---|---|---|---|
| END1 | −0.052 | 0.082 | 0.13 | 0.62 | 0.39 | 0.22 | Satisfier |
| END2 | 0.064 | 0.025 | 0.09 | 0.28 | 0.72 | −0.44 | Dissatisfier |
| CRE1 | −0.088 | −0.063 | 0.15 | 0.42 | 0.58 | −0.17 | Hybrid |
| CRE2 | 0.091 | 0.217 | 0.31 | 0.70 | 0.29 | 0.41 | Satisfier |
| CRE3 | −0.022 | 0.008 | 0.03 | 0.28 | 0.74 | −0.46 | Dissatisfier |
| CRE4 | −0.006 | −0.010 | 0.02 | 0.59 | 0.36 | 0.24 | Satisfier |
| CRE5 | −0.092 | −0.077 | 0.17 | 0.45 | 0.54 | −0.09 | Hybrid |
| CRE6 | −0.174 | −0.089 | 0.26 | 0.34 | 0.66 | −0.33 | Dissatisfier |
| CRE7 | −0.054 | −0.025 | 0.08 | 0.31 | 0.69 | −0.38 | Dissatisfier |
| SUP1 | −0.284 | −0.364 | 0.65 | 0.56 | 0.44 | 0.12 | Hybrid |
| SUP2 | 0.016 | −0.012 | 0.03 | 0.44 | 0.59 | −0.15 | Hybrid |
| SUP3 | −0.143 | −0.239 | 0.38 | 0.63 | 0.38 | 0.25 | Satisfier |
| SUP4 | −0.053 | −0.045 | 0.10 | 0.46 | 0.55 | −0.09 | Hybrid |
| SUP5 | 0.042 | 0.046 | 0.09 | 0.52 | 0.48 | 0.04 | Hybrid |
| SUP6 | −0.135 | −0.051 | 0.19 | 0.28 | 0.72 | −0.45 | Dissatisfier |
| SUP7 | −0.066 | 0.006 | 0.07 | 0.08 | 0.91 | −0.83 | Frustrater |
| SUP8 | 0.113 | 0.049 | 0.16 | 0.30 | 0.70 | −0.40 | Dissatisfier |
| SUP9 | 0.067 | 0.060 | 0.13 | 0.47 | 0.53 | −0.05 | Hybrid |
| SUP10 | 0.077 | 0.061 | 0.14 | 0.44 | 0.55 | −0.11 | Hybrid |
| STR1 | −0.039 | −0.015 | 0.05 | 0.27 | 0.73 | −0.46 | Dissatisfier |
| STR2 | −0.071 | −0.117 | 0.19 | 0.62 | 0.38 | 0.24 | Satisfier |
| STR3 | 0.111 | 0.134 | 0.25 | 0.55 | 0.45 | 0.09 | Hybrid |
| STR4 | −0.054 | 0.019 | 0.07 | 0.27 | 0.74 | −0.47 | Dissatisfier |
| STR5 | −0.015 | 0.045 | 0.06 | 0.75 | 0.25 | 0.50 | Satisfier |
| STR6 | 0.059 | 0.057 | 0.12 | 0.50 | 0.51 | −0.01 | Hybrid |
| STR7 | −0.184 | −0.200 | 0.38 | 0.52 | 0.48 | 0.04 | Hybrid |
Note(s): aFrustraters (IA≤−0.7); dissatisfiers (−0.7 < IA≤−0.2); hybrids (−0.2 < IA <0.2); satisfiers (0.2 ≤ IA <0.7); and delighters (IA ≥0.7)
4.4 Impact range satisfaction analysis and impact asymmetry analysis
The RICS scores integrated with IAA revealed other outcomes: 23.1% of attributes are satisfiers (6 attributes), 30.8% are dissatisfiers (8 attributes), 3.8% are frustraters (1 attribute) and 42.3% are hybrid (11 attributes). These results confirmed the previous analyses but complemented them since they showed how much each attribute can generate a change in satisfaction if the tourism public officers and DMO managers improve them, and the impact on dissatisfaction if they reduce performance (Table 3).
There were no delighters’ attributes among the results, which indicates that the tourism public officers and DMO managers need to rethink the destination strategies to improve the city to enchant tourists and residents. According to IA results, more attributes impact dissatisfaction than satisfaction; thus, destination management should carefully analyse them.
It is important to note that SUP8 (Hospitality) has the highest Penalty index coefficient (0.113) among the dissatisfactors’ group of attributes. Hospitality has a Dissatisfaction Generating Potential (DGP) of 0.70 and a Satisfaction Generating Potential (SGP) of 0.30. Despite it being a unidimensional attribute according to the classification of magnitudes of Penalty and Reward coefficients, changes in the hospitality level, both positive and negative, will impact more dissatisfaction than satisfaction.
Among satisfactors’ attributes, CRE2 (Air transportation infrastructure) presented the highest reward index coefficient. Then it should be a priority for tourism public officers and DMO managers since for each unit of increase or decrease in satisfaction with the attribute, overall satisfaction with the destination changes by 0.217 (reward) and 0.091 (penalty), and this attribute has a Satisfaction Generating Potential (SGP) of 0.90.
Likewise, the matrix of classification of attributes by magnitude Penalty and Reward coefficients shows many unidimensional and neutral attributes; the Impact Range Satisfaction Analysis (IRSA) and IAA confirmed these results. Most attributes were classified as hybrid; that is, they had similar coefficients of SGP and DGP. Although these attributes are not attractors or mandatory, tourism public officers and DMO managers should look at them carefully since the modifications in the performance of these attributes will produce similar changes in satisfaction and dissatisfaction with the destination. Furthermore, one of the hybrids is also mandatory: SUP2 (Security and Safe) presented a Reward index coefficient (−0.012) with SGP of 0,44 and a Penalty index coefficient (0.016) with DGP of 0,59.
5. Discussion
This study extensively analysed the effects of destination attributes on overall satisfaction with the city according to tourists’ and residents’ perceptions to provide insights to decision-makers. Despite our study having a practical view with findings applied to Santa Maria da Feira city, it presented a set of methodologies to help tourism public officers and DMO managers conduct tourism developments to satisfy the residents without losing tourist attraction capacity.
Our study showed scholars, tourism public officers and DMO managers four ways to assess the destination attributes that can be applied to many tourism products from distinct perspectives. Although our sample revealed no statistically significant difference between the means of the two groups, they have different priorities that put the decision-makers at a crossroads. Thus, our findings provided points to Santa Maria da Feira city, concentrating on improving the tourism destination image and developing a two-tier destination brand architecture for internal and external consumers (Figure 6). These results build upon Zelenskaya and Elkanova’s (2021) assumption that a place can encompass multiple brands, including tourism attractions, gastronomic, event and corporate or product brands.
Most mismatches are attributed to the residents’ daily experiences, for example, health and hygiene, general infrastructure, management and communication, security and safety, land and port infrastructure and special events. This result may be because tourists must stay longer at the destination to feel dissatisfied with some city attributes. These discrepancies were found by other studies using these tools (e.g. Karimi and Boley, 2022) and confirm the importance of using more than one analysis technique if there are asymmetric relationships.
Comparatively, the set of methods showed that some attributes in the IPA appeared to have good performance since they had the smallest accumulated I-P gaps. However, among these attributes, according to the IAA results, are two dissatisfiers: 1) Heritage, history, cultural resources, and 2) special events. These represent leisure activities to residents and visitors and, therefore, have double importance on the overall image of Santa Maria da Feira city. They can improve tourism competitiveness and attract visitor flows (Dwyer and Kim, 2003), staycations (James et al., 2017; Stylidis, 2020) and placemaking (Custódio et al., 2018). Our results align with previous studies that showed that cultural resources are not attractive enough for residents because they are part of daily life, or the cultural offer is not addressed (Costa et al., 2024). Based on these findings, destination managers must address the residents’ demand for urban and cultural leisure opportunities to make the city more competitive (Costa et al., 2024).
On the other hand, among the attributes with the highest I-P gaps, considered with low performance, the IAA showed satisfiers: Air transportation, Natural resources, climate and Diversity of the tourism offer. These are attributes that tourism public officers and DMO managers of Santa Maria da Feira city need to improve to achieve better satisfaction among visitors; besides, they will significantly impact the city’s overall image. At the same time, these attributes enhance the quality of life and attract people to live in the city, as previously pointed out by Kim and Perdue (2011) and Pike and Page (2014); therefore, it helps to minimise population loss.
The elevated number of attributes with medium values of I-P gaps but classified as a hybrid by the IAA results is an alert to public organisations and DMO managers of the analysed city, since these attributes impact satisfaction and dissatisfaction. These relate to primary conditions such as infrastructures, security, ICT, communication, destination management, Preparedness of the Labour market, Investment context, Environmental Sustainability and price competitiveness. Public organisations and DMO managers sometimes focus more on tourism offers, attractions and marketing and leave the primary conditions in the background. The literature recognised this assumption since these variables are in all tourism competitiveness models (e.g. Crouch and Ritchie, 1999; Ritchie and Crouch, 2003; Heath, 2003; Dwyer and Kim, 2003; Dupeyras and Maccallum, 2013).
The coefficients of reward and penalty provide the impact of each attribute on satisfaction or dissatisfaction and can help predict the effects of tourism, public officers and managers’ efforts. This mix of methods generated a priority ranking to improve tourism destinations’ competitiveness and help build society-centric tourism development, a current tourism perspective highlighted by Chim-Miki et al. (2023). Also, it is a way to rethink destination branding with a more comprehensive architecture, as indicated by Zelenskaya and Elkanova (2021), creating sub-brands.
Our findings indicate that seven items should be the priority of the public organisations and DMO managers. The manager’s order of attention must consider the attributes classified as frustrated or dissatisfier and, at the same time, attractor or mandatory. Furthermore, the magnitude of the accumulated I-P Gap should also be considered. Then, based on our results, for the analyzed destination, the hierarchical priority list is SUP7 (Accessibility to the destination), CRE3 (Land and port infrastructure), STR4 (Travel and Tourism Prioritization Industry), STR1 (Entrepreneurship level), END1 (Natural resources and climate), CRE4 (Diversity of the tourism offer), SUP2 (Security and Safe).
5.1 Theoretical implications
The theoretical implications of our study align with rethinking the management of the tourism destination from the residents’ perspective. We not only looked at tourism’s positive and negative impacts on the residents’ daily lives, but also at how tourism can improve the well-being of residents as leisure consumers. Despite our sample being small and specific to a Portuguese city, our study supports a rethinking of the tourism approach that is also focused on citizens, thus providing insights to other cities.
We focused on including residents as consumers of the leisure offered side-by-side with tourists. Thus, we considered their perception of the destination image and their role in place-making. For destinations, this means focusing on serving different consumer profiles and recognising that part of the target market lives in or near the city – they are “staycationers”. In addition, our study showed that meeting the attributes from a twofold view can bring greater satisfaction to residents and tourists. It will impact loyalty to the destination, as previous literature indicated (Chi and Qu, 2008). Our results supported Stylidis (2020) and Zenker et al. (2017), who claimed that it gradually becomes difficult to draw a line between residents and tourists for two reasons: tourists are transforming into temporary residents, and residents act as “tourists” in their city, visiting attractions and events. Based on our study, our primary goal is to highlight that destinations should not draw a line between residents and tourists. Instead, tourism destinations must rethink their priorities, considering that both are tourist consumers. This way, public organisations and DMO managers will achieve efficiency in city management as a tourism destination and improve social value creation.
In synthesis, our study has theoretical implications for using destination image attributes, taking into account the perspectives of different stakeholders to support the development of an integrative destination management approach. This approach would feature a multi-tiered destination brand architecture catering to internal and external consumers, including residents, staycationers and tourists. Zenker and Beckmann (2012) suggest that the consumer experience encompasses place interaction, communication, values, behaviour, the overall offer and culture, all of which shape branding and the destination image. Additionally, our findings have implications for developing tourism destinations through a placemaking lens – viewing it as creating quality places where people can live, work, play, visit and learn.
5.2 Practical implications
Our results generated a double practical implication. First, it presents a methodology to take the tourism public officers and DMO managers from the crossroads between serving the residents and the tourists, satisfying both. While their focus is often on destination branding aimed at attracting tourists, it is equally important to consider residents for two key reasons: first, they are active consumers of leisure within the destination; second, tourism development that prioritises societal well-being is the most effective way to generate long-term social value. We provided a priority order of action that makes the investment decision and public policies for the sector more assertive in the analysed city, which can serve as insights into other cities. Second, the findings offer a diagnosis of the city of Santa Maria da Feira that can support the municipality’s decisions to maintain its growing flow of tourism and match tourist spending and stay in the destination with the national average. Table 4 synthesises the improvements suggested based on our set of results.
Summary of results and indication of strategic action
| Cod | Attribute | IPA GAP | PRCA/IAA | Strategic action |
|---|---|---|---|---|
| Endogenous resources | ||||
| END1 | Natural resources and climate | 1.30 (3ª) | Attraction Satisfier | Improve the offer of leisure in natural areas to tourists and residents |
| END2 | Heritage, history, and cultural resources | 0.20 (20ª) | Unidimensional Dissatisfier | create campaigns for residents to develop a sense of pride and knowledge about local history, heritage, and culture, and incentivize residents to frequent cultural attractions |
| Created resources | ||||
| CRE2 | Air transportation infrastructure | 2.77 (1ª) | Unidimensional Satisfier | Negotiate with airlines to offer more flights to the region |
| CRE3 | Land and port infrastructure | 1.76 (2ª) | Mandatory Dissatisfier | Prioritize the improvements in access to the city by land infrastructure |
| CRE4 | Diversity of the tourism offer | 1.24 (4ª) | Mandatory Satisfier | Create and prioritize programs to stimulate city entrepreneurs to innovate in tourism |
| CRE1 | Tourism infrastructures | 1.08 (6ª) | Neutral Hybrid | Continuously provide a good tourism infrastructure to be used by tourists and residents |
| CRE6 | Quality of entertainment | 0.81 (11ª) | Neutral Dissatisfier | Incentive the entrepreneurs to improve the city’s entertainment quality with leisure offers to both residents and visitors |
| CRE5 | Shopping | 0.17 (21ª) | Neutral Hybrid | Create public policies to attract new businesses to maintain the shopping offer in the city |
| CRE7 | Special events | −0.33 (23ª) | Neutral Dissatisfier | Rethinking the city’s events calendar as attractive for staycations to reduce the seasonality of tourism flow |
| Supporting factors | ||||
| SUP7 | Accessibility to the destination | 1.03 (7ª) | Attraction Frustrater | Negotiate with airlines to offer more flights to the region and with land transportation companies |
| SUP4 | Quality of services | 0.83 (10ª) | Neutral Hybrid | Promote training for tourism workers and entrepreneurs in partnership with tourism associations and educational institutions to improve the quality of services |
| SUP5 | Facilitating resources | 0.79 (12ª) | Unidimensional Hybrid | Improve the facilitating resources in the city |
| SUP1 | General infrastructure | 0.64 (13ª) | Neutral Hybrid | Keep up the good offer of general infrastructure |
| SUP3 | Health and hygiene | 0.59 (15ª) | Neutral Satisfier | Keep up the good work on security and health and hygiene |
| SUP2 | Security and safe | 0.58 (16ª) | Mandatory Hybrid | Prioritize the improvements in security and safe in the city |
| SUP10 | ICT readiness | 0.55 (17ª) | Unidimensional Hybrid | Create programs and policies to improve the ICT among tourism firms |
| SUP8 | Hospitality | 0.49 (18ª) | Unidimensional Dissatisfier | Create campaigns for residents, tourism workers, and entrepreneurs to improve hospitality in the city |
| SUP9 | Management and communication | 0.41 (19ª) | Unidimensional Hybrid | The city council should improve communication and management |
| SUP6 | Preparedness of the labour-market | −0.09 (22ª) | Neutral Hybrid | Promote training for tourism workers and entrepreneurs in partnership with tourism associations and educational institutions |
| Strategic areas | ||||
| STR7 | Environmental sustainability | 1.11 (5ª) | Neutral Hybrid | Create networks and programs to foster eco-innovation adoptions |
| STR6 | Price competitiveness | 1.02 (8ª) | Unidimensional Hybrid | Monitor price competitiveness in comparison with similar destinations |
| STR4 | Travel and tourism prioritization industry | 0.86 (9ª) | Attraction Dissatisfier | Create public policies to prioritize the travel and tourism sector |
| STR2 | Marketing of the destination | 0.81 (11ª) | Neutral Satisfier | Create a marketing destination toward both consumers: tourists and staycationers |
| STR1 | Entrepreneurship level | 0.64 (13ª) | Mandatory Dissatisfier | Create programs and policies to foster entrepreneurship among residents, as well as policies to attract outside entrepreneurs |
| STR5 | International openness | 0.60 (14ª) | Unidimensional Satisfier | Maintain policies of international openness |
| STR3 | Investment context | 0.58 (16ª) | Unidimensional Hybrid | Create policies to foster business context and attract outside investors |
5.3 Limitations and further research
The main research limitation was the sample size of residents and visitors. Also, the number of destination image components was restricted due to the difficulty of participants answering long questionnaires, which is another limitation of this study. We suggest further research using large samples and various destinations to confirm our results and provide the generalisation of findings. Also, more studies with different samples are needed to understand cities as tourism destinations for residents and tourists to create integrative management models and new directions for place-making. Moreover, using the same techniques in different destinations, like the sun and sea, urban or rural areas and low-density territories, would be necessary.
Although our sample restriction, the results outlined some implications for further academic research in urban tourism and practice in the management of touristic cities. The dissatisfied and hybrid attributes are basic variables in urban tourism. These results may mean that if city dwellers do not satisfy their leisure needs, tourism attractions may also be insufficient to improve the length of stay for tourists. Researchers have focused more on studying innovations for tourism destinations, and the basic conditions of competitiveness models are in the background. However, we need to recover this research focus as it remains the minimum necessary condition for developing touristic cities from the perspective of placemaking. An analysis of urban tourism and the city’s overall image from the residents’ viewpoint can help to recuperate this research line.
6. Conclusions
This research had two objectives:
to verify the mismatches between tourists’ and residents’ perceptions and satisfaction regarding the tourism destination components; and
to identify the priorities for tourism decision-makers to improve the tourism destination-perceived image considering residents’ and visitors’ perspectives jointly.
First, the study considered the importance and performance of destination components, verifying the existence of discrepancies between the tourists’ and residents’ perceptions. Second, it provided an integrated viewpoint to verify the effects of satisfaction with destination attributes on the overall satisfaction with the city. We applied our analysis in the Portuguese city of Santa Maria da Feira, providing a theoretical view and practical insights for this municipality. Our research indicated a priority ranking to decision-makers of Santa Maria da Feira city, which can guide them in improving the tourism destination-perceived image. The results of the IPA Matrix (Importance-Performance Analysis) showed some differences between the two views, residents and tourists. However, there are some overlaps between the point of view of residents and tourists regarding the importance and satisfaction with the destination attributes. Our results became more robust as we used three techniques: the PRCA, Impact Range Satisfaction Analysis (IRSA) and IAA. They provided the effects of each attribute on the satisfaction with the destination competitiveness from residents’ and tourists’ perspectives for the analysed city.
The IPA analysis, the Test t, and the comparison between I-P Gaps verified if there is a difference in the priorities of destination’s attributes to improve its perceived image from the perspective of the resident and the visitor. We concluded that tourism public officers and DMO managers of Santa Maria da Feira city should consider the differences pointed out by the IPA results from a complementary perspective since the Test t de student showed significant differences only in two groups.
From this research, we highlight that gaps between importance and performance from both perspectives must be estimated by the tourism public officers and DMO managers and added to create a prioritisation list for sectoral development that serves both external and internal tourists. This way, city managers can create destination branding with a double architecture, a strategy that considers visitors’ and residents’ needs and preferences. This approach can significantly improve the tourism destination’s image and attractiveness as a place to visit and live, enhancing placemaking. Murphy et al. (2000) pointed out that the global experience at the destination includes the dimensions of services and space. We suggest that each place explores its intrinsic characteristics to create products that generate resident satisfaction and tourists’ desire to visit. In this way, tourism can contribute to economic development and help minimise social problems, such as this municipality’s decreasing population, since the overall destination image contributes to the city’s attractiveness and place-making. The attributes of infrastructure, leisure, environment, primary conditions and business context produce a tourism destination and guarantee market share, as Bigné et al. (2001) claimed. If this set of attributes is towards both visitors and residents, it creates a society-centric tourism development (Chim-Miki et al., 2023) and a two-tier destination brand architecture (Zelenskaya and Elkanova, 2021; Braun et al., 2013).
The study was funded by the PRR – Plano de Recuperação e Resiliência and by the NextGenerationEU funds at Universidade de Aveiro, through the scope of the Agenda Business Innovation “ATT Agenda Mobilizadora Acelerar e Transformar o Turismo” (Project no. 47 with the application C645192610-00000060). The authors also thank the Productivity Grant N° 307536/2021–1 of the Brazilian National Council for Scientific and Technological Development.
