Introduction

As argued by Buhalis (2000), a tourism destination can be defined as “amalgam of tourism products and services, which are consumed under the brand name of the destination” (p. 98). This definition seems very appropriate, since it allows approaching destinations simultaneously from both market sides –supply and demand. From supply side, destination is a well-defined geographical territory which is promoted as a unique entity, with a political and normative framework for tourism marketing and planning (Buhalis, 2000). It adopts distinct spatial scales, as resorts, cities, regions, countries or even supranational territories (Hall, 2010). Moreover, destination’s stakeholders can benefit from a common destination brand developed under the umbrella of a destination management organization (DMO). From demand side, as stated by Buhalis (2000), de Araújo et al. (2019) and Cardoso et al. (2019a), a destination is a perceptual concept, being interpreted subjectively by the consumers. In addition, the subjectivity of these perceptions depends “on their travel itinerary, cultural background, purpose of visit, educational level and past experience” (Buhalis, 2000, p. 97). Furthermore, tourism destinations can be considered from different criteria: (1) public versus corporate destinations; (2) ranging from very small to very large territories (e.g., local attractions, villages, cities, regions, countries, or even supranational entities) (Cardoso et al., 2019a); (3) and related to different tourist motivations and products (De Araújo et al., 2019; Dias, 2018): cultural tourism, sun & sea, rural, wellness health, sports, nature, religious, medical, food tourism (Cardoso et al., 2019b) among many other.

Recent studies have focused on some variables that influence the choices of tourists considering the geographical context, such as geographical tourist context and other neighbouring tourists, advocated by Cano Guervos et al. (2018) or the role of destinations resources defended by Chekalina, Fuchs and Lexhagen (2018). However, Beritelli et al. (2017) states that “travel decision research still struggles to explain a large portion of the variance in travel choices” (p.1). Actually, facing the myriad of destination brand names existing in all over the world, on the one hand, and the immeasurable number of tourists making their own destination choices, on the other, the following cutting edge question arises: what are the more valuable destination brands for tourists from a certain region of the globe?

Most of studies addressing the issue of brand equity for tourism destinations do not allow to answer the last question, since they are focused primarily on a given destination or on a small set of destinations. In fact, a more realistic research setting that integrates the free choice of respondents (any respondent can freely consider any destination that have in mind) is a very complex task and therefore almost always avoided by the researchers. Even so, considering that all destinations are competing in the national and international markets, to address the issue of customer-based brand equity for tourism destinations (CBBE-TD) in the context of free destinations choice is a tempting challenge but enormous. Studies carried out by Dias and Cardoso (2017) and Cardoso et al. (2019a) shed some light on this complex matter, allowing to understand why in a given context a person enunciates, for instance, “U.K.”, while in another context he/she enunciates “England”.  Thus, starting from the concepts of dream and favourite destination proposed by Cardoso et al. (2019a), the present study maps the Indian tourists’ brands spatial scales, adopting the top-of-mind approach. The present study aimed at understanding the attractiveness of domestic and international destination brands for Indian tourists, by mapping their Dream and Favourite Destinations, both domestic and worldwide.

 

Theoretical Perspective

The spatial multidimensionality of destination brand concept

Comparing destination brands with the brands for manufactured products, at least four important features become evident, making destination branding a complex matter: (1) Being destination brands a subset of place brands (Ashworth & Kavaratzis, 2010; Gnoth, 2002; Hudson & Ritchie, 2009; Pike, 2005), they can adopt very diverse spatial scales, ranging from local to supranational territories (Figure 1). For example, India, Maharashtra and Jaipur, despite their distinct scales, all they are tourism destinations; (2) Destination brands can be formal (registered brands, trademarks) or informal (overall image), that is, destination brands can be owned by administrative entities and governed by a DMO or they can be just toponymical names used to designate a place that tourists usually visit. Both formal and informal brands interact with each other over time (Hall, 2010).

Figure 1: Architecture of place brands model

Source: Adapted from Hall (2010).

For example, the informal portrayal of such informal destinations like Himalaya, Caribe, and Baltic Countries can be influenced by the strategies of the national states related to these territories; (3) Each tourism product influence in a specific way the configuration of the spatial scale of destinations and their administrative borders. For example, mountain destinations are often large regional spaces without well-defined borders (e.g., Alps, Pyrenees or Himalaya), while city tourism or shopping tourism take place at urban destinations; other types of tourism (e.g., religious, cultural or adventure tourism) are routes crossing long distances in the territories (e.g., Route 66 in the USA, or Kedarnath in India); (4) Differently from the branding of common products or services, the focalization of visual identity in logos or other visual signs is not so effective in the case of destination branding. Who among tourists that visit Paris or London knows the logos of these city brands?

 

Understanding and consolidating destination brand choices

 The pre-trip anticipation is a crucial moment, since it determines the experience in situ. Before deciding where to go, each tourist/s consider distinct alternatives (Decrop, 2010; Um & Crompton, 1990), and the likelihood of a given destination being considered as a possible choice depends on tourist’s knowledge and beliefs (Martins, 2015), and also on more subjective elements such as emotions, attitudes and images of destinations (Um & Crompton, 1990) and previous experiences (De Araujo et al., 2019; Cardoso et al., 2019a). Consequently, the likeliness of a destination being the tourist’s final choice depends on its relative brand equity, when compared with its competitors (Dias & Cardoso, 2017).

As a second step, the experience at destination is a kind of “test of reality”, since it provides cognitive and emotional elements to confirm or revise previous expectations, based on the pre-visit image of the destination, that was formed under the influence of organic and/or induced sources or agents (Gartner, 1994). This “test of reality” originates the consumer’s satisfaction or dissatisfaction, which in turn determines the level of consumer’s loyalty. This way, the experience at the destination is the main factor determining the post-trip destination image, judgements regarding destination quality, and future intentions of visit and/or recommendation. That is, in this case, as argued by Gretzel et al. (2018), the experience lived in destination becomes the key concept.

Aiming to focus on the role of destination brand equity into the destination choice process, Dias and Cardoso (2017) and Cardoso et al. (2019a), supported by Um and Crompton (1990) and Decrop (2010) proposed the Destination Brand Choice Integrative (BDCI) model (Figure 2), describing destination choices as a flowchart based on a funnel selection. The BDCI model integrates two parallel but almost isolated research traditions: the studies of brand equity assessment (Aaker, 1991; 1996; Keller, 1993; Konecnik & Gartner, 2007), and the studies of destination choice (Um & Crompton, 1990; Decrop, 2010).

Figure 2: Destination brand choice integrative model (DBCI model)

Source: Cardoso et al. (2019a)

The DBCI model integrates Keller’s (1993) construct of customer-based brand equity for tourism destinations (CBBE-TD) and the multi-steps destination choice process flowchart proposed by Decrop (2010). As shown in the Figure 2, CBBE-TD includes the following dimensions: destination brand awareness (DBA), perceived quality (PG), destination image (DI) and destination loyalty (DL). In turn, the destination choice flowchart is composed of four sequential stages: consideration, evaluation, constraints, choice and post-visit re-evaluation. According to the DBCI model, in each stage of destination choice flowchart the components of the CBBE-TD have a determinant influence:

• Consideration stage: The leading role is played by DBA at this stage. It reflects the salience of a destination brand in the tourists’ mind (Aaker, 1996). There are two different empirical approaches to assess DBA: free recall and recognition. DBA plays a crucial role at the first stage of destination choice, since only destinations with high level of awareness can be considered in a future choice.
• Evaluation stage: Destinations included in the awareness set are then submitted to the scrutiny of DI and PQ. Concerning DI, it is the starting point for the purchase decision and for brand loyalty (Aaker, 1991) and it embraces all the brand associations existing in tourists’ mind. According to Keller (1993), these associations correspond to attributes, benefits and attitudes. Attributes consist of what a tourist thinks the destination brand is or has to offer and what is involved in its purchase or consumption. Benefits are the personal values consumers associate to the brand. Attitudes towards destination brand are tourists’ overall evaluations of the destination brand and have a crucial role in the destination choice. Regarding PQ, it refers to the customers’ overall perception of quality of products or services in comparison with the rivalry offering (Aaker, 1991). When the intangible attributes acquire high predominance, as it is the case in tourism, the quality assessment depends almost exclusively on perceived quality. According to the DBCI model, both DI and PQ determine how a given destination can fail or win at the evaluation stage. Only destinations highly scored in these both dimensions can progress to the next step.
• Dealing with constraints: At this stage, when final decision has to be made, consumers have to deal with constraints. According to Oliver (1997, 1999) and Blut et al. (2007), the ability to overcome inertia and to achieve the repeated purchase, even if it is necessary to overcome constraints, reflects the consumers’ action loyalty. However, DL goes beyond the action loyalty and repeated purchase, since loyalty has also cognitive, affective and conative dimensions (Oliver, 1997, 1999). Cognitive loyalty occurs whenever a brand appears first in the consumers’ mind as their first choice. Affective loyalty consists of a favourable attitude towards a particular brand, and it is an outcome of the consumer’s satisfaction. Conative loyalty expresses the consumer’s commitment with a future purchase, but without conclusive fulfilment, being usually expressed as recommendation to friends and relatives or positive word-of-mouth.
• Post-visit re-evaluation: There is a causal relationship between tourists’ satisfaction at destination, perceived quality, positive image and loyalty. Consequently, DBCI model (Figure 2) includes a post-visit re-evaluation stage, where visited destinations are sorted in three distinct sets: favourite set, if the experience in situ was enjoyable; deception set, if the experience was frustrating; and trivial set, if the experience generated neutral or ambivalent feelings.

Dream versus favourite destinations’ perceptions

In order to differentiate the structural perceptions of the two categories of destination (favourites versus dream), Cardoso et al. (2019a) argued that destinations included in both dream set and favourite set are relatively strong destination brands since they have high CBBE-TD ratings, i.e., top-of-mind awareness, high perceived quality, positive image and strong loyalty. However, they are distinct in one crucial aspect: the existence or the lack of personal experience at the destination. Although dream destinations are rooted in the tourist imaginary, being generated by organic and/or induced sources of influence, they have high brand salience and correspond to the ideal preferences of consumers; in turn, as argued by Dias and Cardoso (2017), favourite destinations refer to those places that have already been visited and have aroused positive emotions on tourists, and still remain in their minds as memorable experiences.

Dream destinations are highly desirable places deserving to be visited someday in the future, rooted in the collective imaginary and built on discourse (Cherifi et al. 2014) or on shared images by the cinema and/or literature (Best, 2006). Moreover, they reflect tourists’ behavioural intentions towards future experiences, and therefore they are elaborated in the framework of the prospective memory (Graf & Uttl, 2011; McFarland & Glisky, 2012). However, they are connected to the episodic system of memory, more specifically they are part of what Atance and O’Neill (2001) designated as episodic future thinking – an ability to project the self forward in time to pre-experience an event.

Favourite destinations, in turn, refers to a place the tourist has already visited and considers the best destination for a specific type of travel (De Araújo et al., 2019; Cardoso et al. 2019b; Dias & Cardoso, 2017), being rooted on the tourist’s retrospective memory (Cardoso et al., 2019a). In fact, it’s worthy to stress that favourite destinations are specific for each type of travel, since for different types of tourism (for instance, cruise, nautical, religious, cultural, rural, shopping, mountain or sport) and depending on tourist’s previous experiences and motivations. Moreover, favourite destinations are deeply grounded on the autobiographical (retrospective) memory, as they are related to previous behaviours and associated with memorable experiences (Tung & Ritchie, 2011). More precisely, they are associated with the semantic memory system, which is broadly defined as our knowledge of the world (Atance & O’Neill, 2001).

Research aims and hypothesis

 As states Cardoso et al. (2019a, p. 83), the “comparative analysis of Dream and Favourite Destinations has the specific merit of focusing on an important, but never examined, issue in tourism studies: the dynamics of autonoetic consciousness during the destination choice process”. Tulving (1985, p. 1) defined autonoetic consciousness as “the kind of consciousness that mediates an individual’s awareness of his/her existence and identity in subjective time extending from the personal past through the present to the personal future”. Tourists’ autonoetic consciousness allow them to develop intentions regarding places to visit in the future, and also allow them to make trade-offs between their retrospective and prospective memories. Also known as “memory of the future” (McDaniel & Einstein, 2000), prospective memory embraces all cognitive processes involved in the formation and execution of future intentions (McFarland & Glisky, 2012). This double focus of autonoetic consciousness (past versus future) is never studied in tourism destination choice.

Moreover, these two destination categories (dream versus favourite) express distinct meanings of brand loyalty: when a person evokes a toponymical name as dream destination, he/she just expresses his/her cognitive and affective loyalty towards that destination (that is, a favourable attitude and a positive feelings); however, when a person designates a destination as favourite, he/she goes beyond cognitive and affective loyalty, since it also means conative loyalty and (in many cases) action loyalty. In other words, when one says: “X is my favourite destination”, it also means: “I recommend X”.

The first attempts to compare and distinguish dream and favourite destinations were undertaken by Dias and Cardoso (2017), Cardoso et al. (2019a), Cardoso et al. (2019b) and Araujo et al. (2019). These studies found out significant differences between dream and favourite destinations in following dimensions:

1. Distance between tourists’ place of residence and evoked destinations:
Dream destinations are located too far away from the tourists’ place of residence, mostly in other continents; while favourite destinations consist of domestic destinations or foreign destinations located in neighbouring countries. As referred above, due to constraints of money or time, or both, dream destinations have a very low likelihood to be chosen in the near future. To visit these psychologically desirable but economically inaccessible destinations, one has to book long-haul or ultra-long-haul flights, that are more expensive and requiring longer trips. It’s not surprising that around 85% – 90% of all international arrivals worldwide are intracontinental (corresponding to short-haul or medium-haul flights), against a too small part of international tourist flows that are related to intercontinental, long-haul flights (UNWTO, 2018).
Drawing on the existing evidence, the following hypotheses are formulated:

H_1a: Indian tourists’ favourite destinations are located not too far away from their place of residence (in their state of residence or in neighbouring countries).

H_1b: Indian tourists’ dream destinations are far away from their place of residence, in other continents, and located mostly in Europe or America.

2. The spatial scale used to categorize destinations:
Most of dream destinations are very strong and globalized brands, such as influential countries or famous cities that achieved high cognitive salience in the people’s mind in all over the world. In turn, favourite destinations are chosen among all destination individual already visited, and consequently they are experience-specific and depend on several personal factors such as tourist personal profile, motivation to a specific kind of tourism (cultural, mountain, religious, etc.) and personal experience (portfolio of visited destinations), etc. Due to these circumstances, favourite destinations have higher likeliness of adopting more diverse spatial scales: local, regional, national or supranational destinations. For example, favourite beach destinations are expected to entail the local scale; while favourite mountain destinations are likely regional territories; however, favourite cruise destinations are supposedly supranational regions. On the basis of already existing empirical evidence (Dias & Cardoso, 2017; Cardoso et al., 2019a; de Araujo et al., 2019), it is expected that the country brand categories appear more frequently associated with dream destinations than with favourite ones; likewise, the local and regional brand categories are more characteristic of favourite destinations that of dream ones.

That understanding leads to the following hypotheses:

H_2a: Dream destinations of Indian tourists are mostly shaped as country brands.

H_2b: Favourite destinations correspond more frequently to urban/local and regional or provincial place brands.

 

Research Methodology

Data collection

Data collection was part of a larger scale, qualitative surveys that was carried out in the framework of the Favourite Destinations Worldwide project – http://favouritedestinations.com/en/ – a purpose developed online multilingual platform that was conceived to assess destination brands from all of over the world, using an unstructured questionnaire with open-end questions. Three Indian researchers, members of the research team, were responsible for the data collection in India, which took place during the second semester of 2018. To collected textual dream and favourite perceptions, we adopted the top- of-mind approach that refers to a brand or specific product being first in customers’ minds (Buyunitri & Putri, 2016; Šerić et al., 2016).  The technique applied to access the top-of-mind was the free recall technique, such as Cardoso et al. (2019a) and similar studies that mapped destinations perceptions (Stepchenkova & Li, 2013; Stepchenkova & Morrison, 2008). Free recall is a mental process that allows one to collect information from memory, since the memory has the ability to create important associations and the ability to unite associative representations to evoke them at a later date (Ofen, Yu, & Chen, 2016). The Dream Destination construct was operationalised through the following question: “Bearing in mind all tourism destinations existing all over the world, please indicate your dream destination in general”. This instruction was accompanied by the following note: “The expression «Dream Destination» refers to destinations that you did not visit but desire and hope to visit someday”. Concerning Favourite Destination, the questionnaire included a two-step approach: (1) First, each respondent was invited to indicate the type (of types) of tourism he/she prefer (respondent could choose one or more items from a list of 15 tourism products – e.g., seaside, cultural, gastronomic, shopping, etc.); (2) Then, the following statement was presented: “Please indicate your Favourite Destination for this type of tourism”. Each respondent could choose a Favourite Destination for each chosen tourism product. This was accompanied by the note: “The expression «Favourite Destination» refers to destinations you have already visited and loved the most”.

It’s crucial to note that the questionnaire did not restrict the destination choice to any specific geographical or administrative category, such as city, region, country, island, etc. The lack of geographic cues was meant to avoid influencing respondents’ free recall. Moreover, the exact wording of questionnaire questions was based on the literature on prospective and retrospective memories (Atance & O’Neill, 2001). In this context, when respondents should evoke their top-of-mind favourite destinations, they had to invoke previous experiences in those destinations, and their choice was clearly based on their retrospective memory. Likewise, when respondents should evoke their top-of-mind dream destinations, they were expected to project themselves forward in time to pre-experience the event of travelling to such place.

All the three Indian team-mates used the same tutorial of guidelines for data collection, including specific requirements for sampling and advices about the importance of a one-to-one approach, in order to avoid spreading the questionnaire through social media and to diversify the sample, aiming to ensure a satisfactory level of control and sample representativeness.

 

Data analysis procedures

To obtain the Indian tourists’ brand special scales, the data were mapped considering two theoretical models, favourite and dream destinations choice of DBCI model proposed by Cardoso et al. (2019a) and then the Indian perceptions’ were mapped in tourist’s brands special scales based on Brand architecture issues of place brands model developed by Hall (2010) (Figure 3).

Figure 3: Theoretical model of analysis procedures

 

 

The 2^nd and 3^rd steps of Hall model were performed in two steps, the first one comprised the categorization of evoked information concerning the destinations into two distinct variables:

• Variable “distance of destination”, with four categories: (1) located in the respondent’s state; (2) in another Indian state; (3) in neighbouring country; (4) in another continent.
• Variable “spatial scale”, with five categories: (1) urban/local; (2) sub-regional; (3) regional (4) national; (5) supranational or continental.

The second step was the use of statistical procedures using SPSS.24, assessing the frequencies of destinations and testing the hypotheses using the non-parametric test of chi-square.

Table 1 shows the sample’s distribution regarding geographical location and gender. The total amount of responses was 736, but 39 were invalidated due to lack of necessary information or not appropriate content. The 697 valid responses count for 2.921 top-of-mind evoked destinations (697 dream destinations and 2.224 favourite destinations).

 

Table 1: Sample description

Variable	N	%		Variable	N	%
State of residence				Gender
Delhi	224	33,1		Male	390	56
Maharashtra	198	28,4		Female	307	44
Himachal Pradesh	28	4,1
Karnataka	25	3,5		Age
Gujarat	24	3,4		From 18 to 25	153	22
Punjab	23	3,3		From 26 to 35	160	23
Haryana	23	3,3		From 36 to 45	181	26
Madhya Pradesh	20	2,9		From 46 to 55	119	17
Uttarakhand	14	2,0		More than 56	84	12
Kerala	14	2,0
Bengal	13	1,9		Mother tongue
Uttar Pradesh	13	1,9		Hindi	291	41,9
Odisha	11	1,6		Marathi	205	29,0
Bhubaneswar	11	1,6		Punjabi	22	3,3
Rajasthan	10	1,2		Kannada	21	3,1
Tamil Nadu	9	1,0		Malayalam	20	2,9
Bihar	9	1,0		Gujarati	25	4,0
Andhra Pradesh	8	1,0		Bengali	31	3,9
Jammu	8	1,1		Urdu	22	3,0
Jharkhand	7	1,0		Tamil	18	3,0
Other states	5	0,7		Odiya	16	2,0
Total	697	100		Other languages	26	4,0

 

 

Results and findings

Indian dream destination’s perceptions results

Table 2 presents the top 30 dream destinations of Indian tourists, accounting for 73.6% of all distribution. In the top 10 of more desirable destinations for a future experience appear seven country brands (Switzerland, U.S.A., Australia, Dubai, Japan, Germany and New Zealand), two city brands (Paris and London) and one continental brand (Europe). It’s worthy to note that in the top 30 there are just two regional brands: Jammu & Kashmir and Goa.

 

Table 2: Top 30 dream destinations of Indian tourists (weigh value = 73.6%)

Rank	Destination	N	%	Rank	Destination	N	%	Rank	Destination	N	%
1	Switzerland	72	10,3	11	Las Vegas	18	2,5	21	Rome	9	1,3
2	U.S.A.	50	7,1	12	Singapore	16	2,3	22	Spain	9	1,3
3	Europe	35	5,0	13	Jammu & Kashmir	15	2,1	23	Brazil	7	1,0
4	Paris	34	4,8	14	Thailand	12	1,7	24	Goa	7	1,0
5	Australia	29	4,2	15	France	10	1,5	25	Greece	7	1,0
6	London	25	3,6	16	Egypt	9	1,3	26	New York	7	1,0
7	Dubai	24	3,4	17	India	9	1,3	27	Venice	7	1,0
8	Japan	19	3,1	18	Italy	9	1,3	28	China	6	0,8
9	Germany	19	2,7	19	Malaysia	9	1,3	29	Ecuador	6	0,8
10	New Zealand	19	2,7	20	Maldives	9	1,3	30	Ireland	6	0,8

 

The top 30 favourite destinations of Indian tourists (Table 3) accounts for 54.4% of all distribution. Compared this last ranking with the previous one, it presents a diametrically opposite scenario: eight destinations in the top 10 favourite destinations are domestic brands, and Goa, Mumbai and Kerala stand out clearly as the most favourite destinations for Indian tourists. Moreover, in the ranking of Indians’ favourite destinations there are many other domestic destinations, although some foreign destination brands are also represented in the list, namely: Dubai, USA, Maldives, Paris, Singapore, Switzerland, Australia, Japan, London and Bali.

 

Table 3: Top 30 favourite destinations of Indian tourists (weigh value = 54.4%)

Top 10	N	%		Top 11 – 20	N	%		Top 21 – 30	N	%
Goa	175	7,9		Jammu & Kashmir	37	1,6		Bangalore	19	0,9
Mumbai	121	5,5		Pune	34	1,5		Mahabaleshwar	19	0,9
Kerala	117	5,3		Himalaya	26	1,2		Australia	18	0,8
India	85	3,8		Uttara hand	26	1,2		Andaman/Nicobar	16	0,7
Dubai	60	2,7		U.S.A.	25	1,1		Japan	16	0,7
Rajasthan	54	2,4		Maldives	23	1,1		London	16	0,7
Delhi	53	2,4		Paris	23	1,1		Maharashtra	16	0,7
Thailand	45	2,0		Singapore	23	1,1		Ajanta & Ellora	15	0,7
Himachal Pradesh	39	1,8		Switzerland	22	1,0		Bali	15	0,7
Hyderabad	37	1,6		Jaipur	20	0,9		Chennai	15	0,7

 

 

Bearing in mind that respondents were asked to identify their favourite destination for specific tourism products, Table 4 presents a segmentation of the top 10 favourite destinations for each of these products.

 

Table 4: Top 10 favourite brand destinations for different segments of tourist experiences

Top 10	%		Top 10	%		Top 10	%		Top 10	%
Seaside (N = 269)			Cultural (N = 204)			Mountain (N = 181)			Religious (N=142)
Goa	40,5		Rajasthan	12,7		Himalaya	10,6		India	9,2
Kerala	6,3		India	10,8		Jammu/Kashmir	7,3		Thailand *	6,3
Maldives *	5,6		Ajanta & Ellora	4,4		Himachal Pradesh	6,6		Vaishno Devi	5,6
Mumbai	5,2		Jaipur	3,9		Manali	6,0		Shirdi	4,9
Konkan	2,6		Ajanta Caves	3,4		Uttarakhand	6,0		Bodhgaya	4,2
Australia	2,2		Kerala	2,9		Switzerland *	5,3		Char Dham	2,8
Bali *	2,2		Maharashtra	2,5		Mahabaleshwar	3,3		Tirupati	2,8
Ganapatipule	2,2		Himachal Pradesh	2,0		Shimla	3,3		Diksh Bhumi	2,1
Andaman/Nicobar	1,9		Pune	2,0		Ladakh	2,6		Ellora Caves	2,1
Miami *	1,5		Egypt *	1,5		Leh	2,6		Gaya	2,1
Total	70,2		Total	46,1		Total	53,6		Total	42,1
City tourism (N=137)			Ecotourism (N=115)			Shopping (N=103)			Business (N=91)
Mumbai	17,5		Kerala	19,0		Dubai *	24,3		Mumbai	22,0
Delhi	10,9		Mahabaleshwar	6,0		Mumbai	14,6		Pune	5,5
New York *	5,8		Himachal Pradesh	4,3		Delhi	11,7		U.S.A. *	5,5
Hyderabad	5,1		Switzerland *	4,3		Thailand *	6,8		Bangalore	4,4
Paris *	5,1		Lonar Lake	3,4		London *	5,8		Chennai	4,4
Bangalore	4,4		Jammu/Kashmir	2,6		Paris *	5,8		Delhi	4,4
Dubai *	3,6		North East India	2,6		Pune	5,8		Dubai *	4,4
Chandigarh	2,9		Tadoba Nat. Park	2,6		Hyderabad	2,9		Germany *	4,4
Jaipur	2,9		Africa *	1,7		Bangkok	1,9		Himachal Pradesh	3,3
Pune	2,9		Ajanta	1,7		Chandigarh	1,9		Singapore *	3,3
Total	61,1		Total	48,2		Total	81,5		Total	61,6
Gastronomy (N=72)			Rural tourism (N=72)			Wellness (N=70)			Sport (N=58)
Hyderabad	16,7		Assam	5,6		Kerala	42,9		England *	9,5
India	8,3		Maharashtra	5,6		India	7,1		London *	9,5
Italy *	8,3		Rajasthan	5,6		Igatpuri	5,4		Australia *	7,1
Kerala	5,6		Hemalkasa	4,2		Haridwar	3,6		Pune	7,1
Kolhapur	5,6		India	4,2		Lavasa	3,6		China *	4,8
France *	4,2		Punjab	4,2		New Zealand *	3,6		Goa	4,8
Mumbai	4,2		Sri Lanka	4,2		Alleppey	1,8		Sunderban	4,8
Spain *	4,2		Andaman/ Nicobar	2,8		Bali *	1,8		U.S.A. *	4,8
Amritsar	2,8		Bihar	2,8		Bhutan *	1,8		Bali *	2,4
Delhi	2,8		Gujarat	2,8		China *	1,8		Brazil *	2,4
Total	62,7		Total	42,0		Total	73,4		Total	57,2

* Foreign destinations

An overall appreciation of the favourite destinations ranked at the top 10 of all these 12 product-based destinations allows to highlight the following findings:

• There is a clear predominance of domestic (Indian) destinations brands among the favourite destinations;
• Most of the favourite destinations are regional or local/city brands;
• Domestic destinations are most frequently associated with the following specific products: cultural tourism, rural tourism, mountain tourism, ecotourism, religious tourism, coastal tourism and health and wellness tourism;
• However, there is no clear predominance of domestic destinations when it concerns the following four products: urban tourism, gastronomic tourism, shopping tourism and business tourism;
• Finally, regarding sport destinations brands, the favourite tourist destinations are predominantly located abroad.

 

Summing up, it comes evident that there is a sharp differentiation between dream destinations and favourite destinations in terms of their special scales (Hypothesis 2_(a-b)) and distance from respondents’ place of residence (Hypothesis 1_(a-b)).

As it is shown in the Table 5, dream destinations are mostly located far away in other continents, clearly confirming the Hypothesis 1_(a-b). Moreover, 89.7% of toponymical names evoked as dream destination correspond to international destination brands, located out of India. In contrast, just 38.8% of favourite destinations are located abroad.

 

Table 5: Distance categorization of evoked destinations

	The evoked destination is located at:
Type of destinations	Home’s state	Another Indian state	Neighbouring country	Another continent
Dream	0,4%	10,0%	14,2%	75,3%
Favourite	17,2%	43,9%	18,0%	20,9%

Chi square = 791.48; p <0,001

 

Based on the architecture of Hall’s (2010) place branding model, it is also evident a sharp differentiation between dream and favourite destinations regarding the spatial scale of destinations.

Figure 4: Spatial scales of Indians’ dream and favourite destinations

Source: authors’ elaboration based on research findings

Figure 4 and Table 6 present clear evidence confirming the Hypothesis 2 (a-b) regarding the geographic scales used to categorize dream and favourite destinations: the former are predominantly related to country brands, in turn the latter are mostly local/city brands.

 

Table 6: Geographic scale of the destination

	Local	Sub-regional	Regional	National	Supranational
Dream destinations (%)	24.6	0.2	13.1	54.9	7.1
Favourite destinations (%)	43.3	3.7	31.1	19.6	2.2

Chi-square = 947.43; p <0.001

 

Discussion and conclusion

 The convergence and integration of two research issues (destination choice and customer-based brand equity for tourism destinations) into one more global approach can be a useful and heuristic solution to go further in the knowledge of tourists’ destination preferences, on one hand, and to develop a monitoring system to assess the attractiveness of tourism destinations in a comparative setting, on the other. However, the referred integration requires a deep changing of the way to assess the CBBE-TD construct: instead of studying destination brand equity in isolation, focussing the research on a given tourism destination (or on a small set of destinations) chosen a priori by the researcher, the research focus should be how to grasp the mental processes through which destinations brands are chosen by consumers, according to their own criteria.

Changing the focus of research and asking tourists to inform their own preferred destinations (in terms of their favourite and dream destinations) and not limiting them to a specific geographic category or to a defined spatial scale, the task becomes a complex challenge that only can be approached using free-recall technics in the data collection. In counterpart, the benefits of this new approach largely compensate the enhanced effort to deal with the complexity of data collecting and processing a huge amount of semantic material. Actually, using dream and favourite destinations as triggers to assess the stronger destination brands for a given nationality of tourists (as it is the case of Indian tourists), it becomes possible to measure and mapping the comparative attractiveness of destination competing in the world market, using the brand equity construct; moreover, it allows to shed light on the structural differences in the imagery processing of destination images related to different kinds of tourist experiences.

Findings confirm previous studies (Dias & Cardoso, 2017; Cardoso et al., 2019a) regarding some basic structural differences between dream and favourite destinations, as two desirable and strong brand categories, namely:

• Dream Destination are mostly located too far away from tourists’ home (just 10.4% of Indian respondents located their dream destination in the domestic market) and, even more significantly, 75.3% of dream destinations require long-haul flights since they are located in Europe and Americas. In turn, as it was expected, favourite destinations are predominantly domestic destinations (around 60%), and just 20.9% of them are located in other continents
• Dream Destination are mostly related to the country brand category (54.9% of Indian respondents evoked countries as their dream destinations, and 24.6% referred local/city destinations; in turn, the regional scale corresponds just to 13.1%). In turn, geographic scales of favourite destinations are predominantly related to local and regional levels (74.3%), and just 19.6% of favourite destinations correspond to countries’ names.

Although this study presents an evident limitation related to the representativeness of the sample, this research presents a new methodology to map tourists’ brands spatial scales, a useful tool since, DMOs that are interested in monitoring the attractiveness of their own destinations can adopt the DBCI model and the proposed methodological tool as a useful framework for assessing brand equity for all competing destinations. In such comparative setting, they will achieve a better understanding of the outcomes of their own branding policy.