Destination brand identity: challenges, opportunities, and future research agenda

Figures & data

Figure 1. Research protocol on bibliometric analysis.

Source: Own elaboration based on Page and Moher (2017).

Figure 2. Evolution of published articles.

Source: Own elaboration (2023).

Table 1. General citation structure.

Numbers of citations	TA	% of 268	TC	% of 10,011	TC/TA
>201 citations	11	3.73%	4,332	43.27%	393.82
151–200 citations	3	1.02%	508	5.07%	169.33
101–150 citations	6	2.03%	753	7.52%	125.50
51–100 citations	16	5.42%	1,131	11.30%	70.69
11–50 citations	115	38.98%	2,790	27.87%	24.26
1–10 citations	116	39.32%	497	4.96%	4.28
0 citations	28	9.49%	0	0.00%	0.00
Total	295	100.00%	10,011	100.00%	33.94

Source: Own elaboration (2023). Note: TA = Total number of articles; TC = Total number of citations; TC/TA = Average Citations per Article.

Figure 3. Map of affiliated articles.

Source: Own elaboration (2023).

Figure 4. Longitudinal evolution thematic map.

Source: SciMAT. (Cobo et al., 2012).

Figure 5. Strategic diagram based on the number of documents.

Source: SciMAT. (Cobo et al., 2012).

Table 2. Summary of implications and research agenda.

Theme A: Brand identity in the tourist destination

Establish a consensus on a general definition of destination identity. Identify the main elements that make up the destination identity. Establish an appropriate brand identity theory to approach destination branding.

Theme B: Communications and digital technologies

Establish which online social networks are the most appropriate to communicate the destination brand identity. Expand to other information technologies like neuromarketing, artificial intelligence, and big data to create and communicate tourist destinations. Embrace and adapt to the rapid advancement of digital technology and innovation in communication tactics caused by COVID-19.

Theme C: Co-creation of destination brand identity

Inclusion of multiple stakeholders to ensure a more complete representation of perspectives and experiences in forming the destination’s brand identity. Coordinate and analyze complex and multiple stakeholder interactions. Development of appropriate evaluation metrics to measure the success of co-creating the destination’s brand identity.

Theme D: Place branding

Study the co-creation of destination identity. Apply the theory of service-dominant logic in this line of research. Establish the differences and similarities between place, destination, nation, and city. Examine the effects of using terms in a similar or differential way

Theme E: Cultural identity

Develop a definition and measurement of the essence of the destination culture. Examine tourist perception and sustainable cultural preservation. Propose an interdisciplinary approach and holistic understanding that allows us to capture the richness and diversity of a destination’s culture wholly and accurately.

Theme F: Sustainable destination

Integrate brand identity and sustainable practices caused by COVID-19. Design of brand strategies to promote sustainability. Challenges in aligning brand objectives with sustainable practices. Inclusion of multiple stakeholders to ensure that sustainable destination brand identities are genuinely inclusive and beneficial for all actors involved.

Theme G: The dimensionality of destination identity

Determine common dimensions of destination brand identity. How do destination brand identity dimensions differ from one study to another? Why are they proposed differently? Study antecedents and consequences of destination identity

Theme H: Satisfaction/tourist wellbeing

Enhancing the distinctive identity of the place to highlight the identity and promise of the place. Continuous evaluation of tourist satisfaction to understand and improve the visitor experience.

Source: Own elaboration.

Page, M. J., & Moher, D. (2017). Evaluations of the uptake and impact of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement and extensions: A scoping review. Systematic Reviews, 6(1), 263. https://doi.org/10.1186/s13643-017-0663-8

 PubMedGoogle Scholar

Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2012). SciMAT: A new science mapping analysis software tool. Journal of the American Society for Information Science and Technology, 63(8), 1609–1630. https://doi.org/10.1002/asi.22688

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