Navigating the future of brand experience: insights from bibliometric analysis Open Access

The difficulties companies face in differentiating their products and services have led them to offer disparate experiences to protect their profit margins and guard against price erosion (Pine and Gilmore, 1999). In this context, consumers’ interactions with brands are evaluated by academics and marketers in terms of how well multiple elements of a brand (e.g. products, employees and physical and online stores) evoke sensory, emotional, intellectual and behavioral responses of consumers as competitive advantages (Brakus et al., 2009).

Discussions on the relationship between experience and brands began in the 1950s, when Gardner and Levy (1955) described brand image as a complex system of symbols influenced by individuals’ direct experiences with products. However, not until the pioneering work of Holbrook and Hirschman (1982) was the brand experience (BE) concept fully recognized as a key element for marketers when providing experiential services, such as leisure activities (Holbrook et al., 1984).

Regarding the roots of BE, Khan and Rahman (2015) argue that this concept was first raised by Ortmeyer and Huber (1991), who proposed that BE moderates the negative impact of promotions. However, the concept of BE achieved significant academic recognition in 2009, largely attributed to the seminal work of Brakus, Schmitt and Zarantonello. In their influential study, they defined BE as “those subjective and internal responses of the consumer (sensations, feelings and cognitions), along with behavioral responses evoked by brand-related stimuli” (Brakus et al., 2009, p. 53). The authors contended that consumers are not only influenced by the functional attributes of a brand but also by the experiential aspects associated with its design, identity, packaging, communications and marketing environments. In addition, they suggested that when consumers have intense and solid experiences with a brand, positive results can be expected in their attitudes, satisfaction and loyalty.

Zarantonello et al. (2007) and Brakus et al. (2009) made the most important proposals for a scale to measure BE. Brakus et al. (2009) proposed a scale with four dimensions, defined as follows:

1. sensory (i.e. the impact of brands on the five senses);

2. affective (i.e. the wide variety of affective responses brands generate, such as feelings and sensations);

3. intellectual (i.e. the ability of brands to cause consumers to think); and

4. behavioral (i.e. the behavioral nature of the experience, including items related to lifestyle and actions).

Since Brakus et al.’s (2009) seminal article, BE has attracted the attention of researchers in multiple marketing-related domains, including innovative BE (Lin, 2015), brand relationship experience (Merrilees, 2016), corporate BE (Shamim et al., 2016) and online BE (Morgan-Thomas and Veloutsou, 2013). However, despite these significant outputs, few studies have analyzed the evolution of BE research through a longitudinal bibliometric lens.

The research gap this study addresses is twofold. First, while numerous studies have explored various dimensions of BE, there is a lack of comprehensive, longitudinal bibliometric analyses that map the development and trends in BE research over an extended period. Existing studies often cover shorter timeframes and smaller data sets, limiting their ability to capture the full evolution of the BE construct and its implications over time (Appendix A. Supplementary material). For instance, Zha et al. (2020) covered a period from 2002 to 2018 with only 136 articles, which is insufficient for a thorough longitudinal analysis. Similarly, Nguyen and Trinh (2022) reviewed 226 documents spanning from 1987 to 2021 but did not include the critical period affected by the COVID-19 pandemic, which has had profound effects on consumer behavior and brand interactions.

Second, the rapid advancements in technology and the changing landscape due to the COVID-19 pandemic have introduced new variables that significantly impact BE. Previous bibliometric studies have not fully incorporated these recent developments, thereby limiting their relevance to contemporary marketing challenges and opportunities. There is a pressing need to update the research agenda to reflect these changes and to provide a more current and comprehensive understanding of BE. The absence of bibliometric studies on BE has hindered the development and establishment of a future BE-focused research agenda (Zha et al., 2020). In addition, due to the complexity of consumption contexts based on artificial intelligence (AI), virtual reality (VR) and automation, multiple investigations have called for a new understanding of consumers’ experiences with brands and the state of this research stream (Puntoni et al., 2021).

Motivated by this research gap, this investigation has three main objectives:

1. to improve understanding of the scientific contributions made by prior BE research;

2. to identify salient topics and current BE research trends; and

3. to provide a research agenda for the future of BE.

We adopted a bibliometric approach, analyzing BE-focused production published up to the end of 2023, based on Donthu et al.’s (2021) step-by-step guidelines for conducting bibliometric analysis.

The present paper contributes to the BE-focused literature in several ways. First, we use the longest time span possible for bibliometric analysis of the academic production on BE (1981–2023). Second, this study is the first to examine the period 2020–2023, which was affected by the COVID-19 pandemic. Taken together, this work updates BE agendas and future lines of research that, naturally, had not accounted for COVID-19 and technological advancements such as AI and virtual, augmented or extended reality. To achieve these aims, the following research questions (RQs) guided our investigation and are addressed consecutively through bibliometric analysis:

This research is organized as follows. Section 2 provides a detailed description of the bibliometric work developed. Section 3 presents the results of the analyses. Section 4 proposes a research agenda and discusses future lines of research. Finally, Section 5 presents the conclusions, and Section 6 discusses the limitations of our study.

Bibliometric analysis allows researchers to examine large volumes of data about the evolution of scientific production in a specific subject area (Donthu et al., 2021). This includes the exploration of emerging trends in a concept/phenomenon, patterns of collaboration, the impact of articles and journals and the intellectual framework of specific areas in the existing literature (Donthu et al., 2020, 2021). This method uses an objective approach to undertake advanced analysis based on mathematical and statistical techniques. In a two-stage approach, our bibliometric procedures started with a performance analysis using bibliographic data to assess researchers’ influence and productivity (Podsakoff et al., 2008). Second, through scientific mapping, we identified the structural and cognitive elements of particular domains (Cobo et al., 2011) related to the BE phenomenon.

The analytical tools used in this study were the VOSviewer and Bibliometrix R software. The VOSviewer software uses specific algorithms to identify keywords in published material and subsequently applies the visualization of similarities (VOS) mapping technique to create bibliometric maps/landscapes (Van Eck et al., 2010). These bibliographic maps are presented in multiple forms to identify the attributes of the contents of research articles. The Bibliometrix R software creates diagrams showing the degree of development (density) and the relevance (centrality) of specific topics.

Bibliometric analysis is based on descriptive indicators and network analyses. First, understanding the volume of scientific output/total articles produced over a specific time period allows for an assessment of how active a topic is in a research field. Second, co-citation analysis is based on the idea that authors cited in the same article have addressed similar or related topics (Boyack and Klavans, 2010). A co-citation matrix (i.e. a clustering technique based on the VOSviewer software) groups articles with close relationships (Waltman and Van Eck, 2012). Third, topic mapping analysis provides evidence of issues hidden in the bibliographic materials being studied (Yan et al., 2012). This analysis constructs a map from a similarity matrix based on a co-occurrence matrix of items (i.e. topics).

The bibliometric analysis of this study was undertaken using data from the Scopus database. Scopus is considered to be one of the most reliable and complete sources of information about scientific publications (Harzing and Alakangas, 2016). The unit of analysis was the journal article because it is the unit most often used in bibliometric studies, particularly in the areas of business and management (see Donthu et al., 2021).

The search query used in the database was “brand experience.” Subsequently, the relevant filters, typology and cut-off year were applied to identify the scientific production. The search returned 778 documents published from 1981 to December 31, 2023. The database provided information about the authors, country of affiliation, title, abstract, keywords, journal and publication date. Next, the data were cleaned to correct incomplete records and generate a thesaurus for the VOSviewer software to allow it to homogenize keywords in singular and plural forms and to address the orthographic differences between British and US English (see the sequential process and techniques used in Figure 1). Although a bibliometric analysis does not follow the same pattern as a literature review, it is necessary to complement the analytical interpretation with certain guidelines from a systematic literature review. According to Paul and Criado (2020), systematic literature reviews should identify and synthesize relevant literature to compare and contrast the findings of prior studies in a domain.

In the three decades from 1981, when the first BE-related article was indexed in Scopus, production was limited, with 45 articles appearing between 1981 and 2010 (5.81% of the total). From 2011, production increased, ranging from 16 articles published in 2011 to 95 articles published in 2021 – a cumulative total of 774 articles between 1981 and 2023. Addressing RQ1, Figure 2 shows the evolution of BE-related production and citations received per year over the period 1981–2023. Although production systematically increased (with some exceptions, i.e. 2012, 2015 and 2018), the total volume of citations per year has been asymmetrical. For example, Brakus et al. (2009), who developed a BE scale, received 2,334 citations out of the 3,009 citations of the 6 articles published that year. Similarly, Tynan et al. (2010) developed a theoretical framework of types of value and identified processes of value creation in the context of luxury brands, which aroused sufficient interest to attract 560 citations of the 1,493 received by the 10 articles published that year.

Parallelly, the emergence of some topics, such as tourism, triggered new BE-related research. For the first time, some studies (e.g. Woodside et al., 2007) discussed BE in the context of converting destinations (Bologna and Florence) into iconic brands. Woodside et al. (2007) was one of five articles published in 2007, accumulating 138 citations.

The articles produced by Schmitt seeded the development of experiential marketing and the BE research stream (Schmitt, 1999, 2000, 2003). Schmitt’s collaborations with Brakus and Zarantonello (Brakus et al., 2009; Zarantonello et al., 2007; Zarantonello and Schmitt, 2010) have had a wide impact, as they made important intellectual contributions. Schmitt’s contributions were evident in Brakus et al. (2009), who based their BE proposals on Schmitt (1999). Specifically, the four dimensions of BE proposed by Brakus et al. (2009) (affective, intellectual, sensory and behavioral) were based on dimensions Schmitt (1999) proposed: acting, feeling, thinking and relating.

In reference to RQ2 (i.e. which academics produced the most articles over the period), Table 1 is led by Khan and Rahman, who coauthored most of the BE-focused articles. Among these articles, they proposed a scale to measure hotel BEs (Khan and Rahman, 2017), publishing in journals such as the Journal of Product and Brand Management, the Journal of Retailing and Consumer Services and the International Journal of Contemporary Hospitality Management. The 1,720 authors (among whom only 82 are sole authors) contributing to the 774 articles retrieved were affiliated with universities from 82 countries – predominantly from the USA, accounting for 22.70% of the total output, succeeded by India (14.49%), China (10.80%), the United Kingdom (8.43%), South Korea (8.16%), Australia (5.66%), Taiwan (5.53%), Malaysia (5.01%) and Germany (3.68%).

A further comparison of the most cited authors and the most published authors (Table 1) revealed that authors’ productivity was not directly related to the number of citations they received. Specifically, the most prolific authors, for example, Khan (18) and Rahman (10), are not among the three most cited. Thus, it can be deduced that other variables converge on the impact of BE-related research, such as journal type, type of coverage (open access) and the article’s innovation and value.

In reference to RQ3, the multidisciplinary nature of the BE-focused studies ensured that the 774 articles appeared in a wide variety of journals (n = 325) dedicated to diverse topics (i.e. marketing, consumer behavior, brands, sales, banking and tourism). The 10 journals that featured the most BE-focused articles published 7 or more, comprising 26.23% of the total number (Table 2). Of the four journals with the highest production, two specifically focus on brand management (Journal of Product and Brand Management and Journal of Brand Management), one is positioned in the same line but from a general business perspective (Journal of Business Research), and one focuses on consumer behavior (Journal of Retailing and Consumer Services).

A second metric used to show the impact of BE papers on the scientific community is performance analysis. Using this indicator changes Table 2’s order. For example, the Journal of Brand Management (1,841) has more citations than the Journal of Product and Brand Management (1,401), which published more BE-related articles.

The articles with the greatest impact in terms of the number of citations (RQ4) are identified in Table 3, highlighting the articles that proposed novel theoretical and conceptual frameworks. For example, Brakus et al. (2009), with 2,334 citations, is considered a pioneer contribution due to the BE scale development. Tynan et al. (2010) have been frequently cited (560); their article developed a theoretical framework of four types of value for luxury brands and identified value co-creation processes involving luxury brand owners, their customers and members of their respective networks through cocreating the BE. Gensler et al. (2013), with 543 citations, developed a framework that analyzed the impact of social media on brand management; they argued that consumers contribute to brand success when they create brand-based stories on social media and share them.

These investigations marked a direction for work undertaken in subsequent studies and bracketed a period of five years (2009–2013) in which there was a clear rebound of research activity on BE In this period, several works were published that laid the foundations for future research into BE and had a considerable impact on the literature, as evidenced by the fact that 8 of the 10 most cited BE-focused articles were published during those years.

Among these articles, in addition to the three mentioned above, other important contributions were made by Stokburger-Sauer et al. (2012), who tested an integrative theoretical framework to analyze the antecedents of consumer–brand identification. Boo et al. (2009) examined BE in the context of the tourist industry and created a destination brand model using customer-based brand equity models. Völckner and Sattler (2006) concluded that the fit between the parent brand and an extension product is key to the success of a brand extension, with the parent BE playing a minor role. Iglesias et al. (2011) documented direct and indirect relationships between BE and trust. Kandampully et al. (2015) provided a framework to extend the understanding of the antecedents and consequences of customer loyalty, highlighting the need for more empirical evidence of BE’s impact on customer loyalty. Morgan-Thomas and Veloutsou (2013) integrated a dual theoretical perspective from information systems and marketing research to develop a model for online BE. Ramaswamy and Ozcan (2016) provided an integrative framework for understanding brand value co-creation in a digitalized world through intensive actions of co-creational BEs.

In addition to calculating the total number of citations per article, it is illustrative to identify the number of citations they receive per year (see Table 3). Using the latter metric leads to changes in the order of the most cited articles. For example, Kandampully et al. (2015) was the eighth most cited paper in the period analyzed but fifth when ranking the number of citations per year.

As to RQ5, co-citation analysis detects relationships between authors (e.g. based on topics, subjects or country of origin) and displays them visually in co-citation groups. This analysis is based on the proposal that journal articles and frequently cited researchers may be examining similar related ideas. Co-citation occurs when two articles receive a citation from a third work. Figure 3 depicts the three clusters resulting from the co-citation analysis by author.

The blue cluster (1) includes the authors who wrote about the relationships between engagement and experience. In particular, Brodie (176 co-citations), Hollebeek (454 co-citations) and Khan (329 co-citations) addressed the theoretical bases of engagement (Brodie et al., 2011); the interfaces of engagement in business-to-business settings (Hollebeek, 2019); the development of scales to measure engagement in social media contexts (Hollebeek et al., 2014); and the effect of BE on millennial consumers’ engagement (Khan et al., 2021). Kumar’s (239) works pursued the same line of research, focusing on the relationships between engagement and experience (Kumar and Kaushik, 2020).

The red cluster (2) contains the authors with a greater number of co-citations who wrote about BE’s origins and foundations. Holbrook (470) and Hirschman (180) were the first to lay the foundations for research into the consumption of experiential products/services (Holbrook and Hirschman, 1982; Holbrook et al., 1984). Also included in this cluster are seminal works by Brakus (611), Schmitt (1,299) and Zarantonello (844) (Brakus et al., 2009; Schmitt, 1999; Zarantonello and Schmitt, 2010).

The green cluster (3) houses, first, the authors who used partial least squares structural equation modeling in consumer behavior-related studies. Highlighted here are Hair (506), Ringle (382), Sarstedt (334) and Henseler (139) (Hair et al., 2012). Second, this cluster features authors who examined BE and the tourism industry, among them Ekinci (112), Baloglu (54) and Hosany (51) (Ekinci and Hosany, 2006).

To address RQ6 using co-word analysis, a map was created that identified the most important topics in BE-focused research and their interrelationships. This technique identifies the core content of a publication and establishes that words frequently shown together are thematically linked. The words used in the co-word analysis were “author keywords,” “article titles” and “abstracts” (e.g. Donthu et al., 2020). Co-word analysis helps researchers better understand thematic clusters (Chang et al., 2015) and offers insights into potential future research.

The VOSviewer text mining algorithms identified 13,313 BE-related terms. For use in the analysis, the terms had to appear at least six times. The software then selected, by default, 60% of the most important terms and displayed them in different colored clusters based on their co-occurrence in the same article. Greater co-occurrence implies a stronger relationship and identification with the cluster. The sphere’s diameter shows the frequency of use of the term.

Figure 4 shows the four clusters that emerged following the co-word analysis and affinity grouping. The purple cluster predominantly focuses on themes pertinent to the tourism industry that are fundamentally linked to the tourism experience. This is evident through keywords such as “destination brand experience” (frequency: 48), “tourist” (46), “destination” (28), “tourist destination” (26) and “visitor” (25). Within this cluster, noteworthy studies are included, with many pioneering this theme. For instance, a destination branding model was designed (Boo et al., 2009), and the conceptualization of “destination brand experience” was addressed (Barnes et al., 2014), as well as how it serves to build tourist trust (Torres-Moraga and Barra, 2023). The impact of BE at the destination in promoting it was explored (Srivastava et al., 2022), the role of BE at the destination was analyzed (Kumar and Kaushik, 2018) and those arguing for the differential perception of a branded destination were highlighted (Singh and Mehraj, 2019).

The mustard cluster focuses on the evolution and interactivity of BE and consumer engagement, social media and online brands. Identified with terms such as “content” (37) and “social media platform” (25), this group underscores studies by Morgan-Thomas and Veloutsou (2013), Gensler et al. (2013), Lee and Jeong (2014) and Jafari et al. (2016). Furthermore, another group emerges around “Instagram” (15), “Facebook” (38), “young consumer” (9) and “millennial” (8), including notable works on millennials’ loyalty and their limited engagement in social networks (Fernandes and Inverneiro, 2021) and how BE dimensions affect millennial consumers’ engagement (Khan et al., 2021).

The blue cluster comprises other constructs related to BE and various facets of brand management, emphasizing how these interact with consumer perception and experience. Key constructs include “brand love” (72), “brand satisfaction” (31), “brand management” (28), “brand awareness” (23) and “brand communication” (9). Salient studies in this context are those by Schmitt (2012), Ding and Tseng (2015) and Nikhashemi et al. (2019). Consumers’ emotional bonding is also evident in this cluster with key terms like “customer experience” (18), “customer satisfaction” (10) and “consumer perception” (9), with standout authors such as Schmitt (1999), Pine and Gilmore (1999), Carù and Cova (2003) and Ebrahim et al. (2016). Another reference term in this cluster is “structural equation modeling” (56), referring to many studies that have developed and applied this statistical methodology (e.g. Hair et al., 2012).

Finally, the red cluster reveals an innovative convergence between technology and marketing, where augmented reality (AR) and VR emerge as key tools in the evolution of BE. Predominant terms such as “opportunity” (53), “virtual reality” (30), “success” (30), “innovation” (14) and “investment” (12) illustrate this trend. In studies such as that by Park and Lim (2023), the experience of fashion in the metaverse is explored, showing how these virtual environments can open new consumer interactions with brands. Similarly, Kim et al.’s (2023) research emphasizes how immersive and interactive experiences provided by AR not only change consumer perception but also enhance brand loyalty. In addition, this cluster encompasses the conceptual bases of BE, perceived through terms such as “literature review” (21), “marketing literature” (18) and “theoretical framework” (10). These terms appear in early conceptual studies that formalized experiential marketing (Schmitt, 1999) and BE as a construct (Brakus et al., 2009).

The research topics identified in the clusters evolved differently over time. For a more detailed analysis, the production time frame (1981–2023) was divided into three to reflect changes in trends/topics that marked new BE-focused research.

The predominance of each topic can be seen in the strategic diagram provided by the Bibliometrix R software. The diagram has two axes (see Figure 4). The first depicts the degree of development (density), and the second, the degree of relevance (centrality): “Density measures the internal strength of the keywords or thematic network, while centrality refers to the degree of interaction between different networks” (Rojas-Lamorena et al., 2022, p. 1070). Crossing the axes creates four quadrants that group the themes into four categories:

1. niche themes;

2. motor themes;

3. emerging or declining themes; and

4. basic and transversal themes.

In the design of the strategic diagram, the authors’ keywords were used as indicators of the article’s content (Zhang et al., 2016).

Figure 5 depicts the analysis of the first period, the longest, from 1981 to 2010. Production in this period was limited to 45 articles (23.58% of the citations). This period saw the publication of pioneering works on the conceptualization of BE and theoretical frameworks to underpin the concept (Brakus et al., 2009; Tynan et al., 2010) and the first article to refer to BE (Arndt and May, 1981). Arndt and May (1981) developed a conceptual model to explain the interaction effects of internal (BE) and external (word-of-mouth and advertising) sources of information on consumers’ brand choices. Their work is included in the motor themes group, with a high degree of importance (centrality) and a high degree of development (density) in the “advertising” cluster.

Other motor theme works featured in this period (1981–2010) and cluster. For example, Ortmeyer and Huber (1991) first proposed that BE moderates the negative impact of promotions. Cliffe and Motion (2005) described how sponsorship can be used as a fundamental driver of brand strategies to create a BE for customers and to add value to brands through their functional (e.g. performance) and nonfunctional (e.g. emotional and social) values. Phillips and McQuarrie (2010) examined how the esthetic properties of brand advertisements can evoke various types of engagement and argued that the use of grotesque images can lead to narrative transportation, which can persuade customers through intensified BE.

The “brand image” cluster in this period appears in the basic issues quadrant, and although it has high importance (centrality), its development (density) is medium–low. This cluster includes notable works. Boo et al. (2009) addressed the construct of destination BE and designed a tourist destination brand model using customer-based models of brand equity. Rindell et al. (2010) proposed a tool to track how past consumer experiences can influence the corporate brand image perceived by current consumers. Works followed multiple themes; for example, Schembri (2009) examined brand subcultures and argued that consumers are an integral part of the co-creation of BE.

Figure 6 depicts the strategic diagram for the second period (2011–2016). In just half the time of the previous period, production was 3.4 times greater, representing 20.03% of the works published. The most important works published in this period were those of Schmitt (2012), who identified the main constructs of the brand in relation to consumer psychology; Stokburger-Sauer et al. (2012), who tested an integrative theoretical framework of the antecedents of consumer–brand identification; and Iglesias et al. (2011), who analyzed the direct and indirect relationships between BE and trust.

The Bibliometrix clustering process identified “online brand experience” as a basic theme with low development (density) and high relevance (centrality). For example, Morgan-Thomas and Veloutsou (2013) integrated marketing and information systems research to develop a model of online BE. Among other studies, Lee and Jeong (2014) examined online BE in the hotel sector and argued that both the congruence of self-image and the congruence of online–offline brand image importantly influence customers’ online BEs and their trust in hotel brands. Loyalty, considered one of the most important factors for the success of companies, was among the topics discussed in this period (see Jafari et al., 2016).

Another basic theme with high relevance (centrality) and low density (development) was “social media.” The creation and management of brands through online media have been little researched but have gradually gained attention in the literature. A reference work in this period was Gensler et al. (2013), who provided a framework for the analysis of the impact of social media on brand management. Similarly, Sloan et al. (2015) examined how consumer–brand relationships are formed by the communications that occur between consumers. They argued that knowledge sharing has an important influence on prepurchase decision-making and is a mechanism for building trust and sharing BEs. Other works (e.g. Tafesse, 2016) created an experiential model of consumer engagement in the context of Facebook brand pages, while Presi et al. (2016) explored how brand selfies posted on social media contribute to BE. Further studies described the interrelationship between brand personality and tourism services and the satisfaction resulting from destination BE (Bhattachary and Dutta, 2016).

Finally, Figure 7 depicts the strategic diagram of the third reference period (2017–2023). In this period, scientific production soared, reaching 74.16% of the total. The cluster “destination brand experience” emerged as a basic topic with moderate development (density) and high relevance (centrality). The latter reflects its growing importance and influence on related studies, suggesting deeper integration with other research themes.

Among the significant works in this cluster was that by Kumar and Kaushik (2018), who examined the role of BE in destinations and how its dimensions affect tourists’ trust in and loyalty toward destination brands. The impact of destination BE on tourists’ behavioral intentions was also addressed by Singh and Mehraj (2019), who concluded that BE dimensions contribute to tourists’ satisfaction, word of mouth and revisit intentions. Rodrigues et al. (2021) obtained similar results, showing that destination BE influences brand attitude and can increase tourists’ loyalty toward destinations. Other studies examined BEs on tourism destination websites and social media (e.g. Jiménez-Barreto et al., 2020), showing that online BEs also influence brand credibility and users’ behavioral intentions.

Another cluster that appeared as a basic theme during this period was “sensory brand experience”. Its notable centrality indicates that this theme acts as an interdisciplinary nexus, integrating with and impacting various study areas within marketing. Moreover, its moderate density reveals a strong cohesion among studies within the cluster, demonstrating that research on “sensory brand experience” is building a robust body of knowledge. Studies were undertaken to try to measure the incipient topic of sensory experience (e.g. Gao and Lan, 2020). A noteworthy study by Iglesias et al. (2019) investigated the effects of sensory BE on brand equity through customer engagement and satisfaction. Castillo-Villar and Villasante-Arellano (2020) argued that multisensory BE positively influences customer satisfaction and brand loyalty. Another work from this period and cluster was by Farzin et al. (2021), who showed that sensory BE influences brand equity.

The “social media” theme was established as basic in the period 2011–2016, with great relevance (centrality) but poor development (density), then became a motor theme during 2017–2023, with medium development and relevance. Beig and Khan (2018) continued this research stream in the second period, arguing that two marketing activities on Facebook (content sharing and interaction) positively impact BEs. Guede and Filipe (2019) proposed that BE on social media is the most important direct predictor of the quality of customer–brand relationships and brand loyalty. More recently, Marmat (2021) proposed a conceptual model to enhance BE within the social media context.

In this period, the “fashion metaverse” cluster emerged for the first time. Its low centrality suggests that it is in the initial stages of integration with broader research themes. However, its high density reflects a highly specialized and concentrated area, with closely related studies focusing on the metaverse applied to fashion. This pattern indicates a growing interest in and deep development within this specific niche, projecting significant potential. Another relevant niche theme is “extended reality.” Its moderate centrality suggests that it is starting to establish meaningful connections with other research themes, while its high density reveals a highly specialized and focused field with deeply interconnected research. This pattern reflects the intensive development and maturation of this theme within its own domain, indicating an area of study with a solid foundation and considerable potential to influence future directions in marketing and technology.

In the realm of fashion in the metaverse and extended reality, recent works, such as those by Park and Chun (2023), stand out. They explored how fashion transcends its decorative function, becoming a game in digital media and influencing both fashion marketing and social media culture. Park and Lim (2023) investigated the adoption of the metaverse by fashion brands, proposing a theoretical framework to understand how various strategies in the metaverse affect brand value. Jeon (2023a) focused on conceptualizing and measuring BE on extended reality platforms. Finally, Jeon (2023b) analyzed how different avatars reflect varied BEs and their influence on purchase intentions, highlighting the importance of BE in extended reality as a mediating factor.

To provide an overall view of the study results on BE-focused production, including identification of the predominant related topics, a tabulated summary is presented in Table 4.

By analyzing the insights from the bibliometric analysis, we underline four imminent BE-related topics (i.e. technology, tourism, luxury and corporate social responsibility [CSR]), representing a research agenda for scholars interested in the present and future BE domain (see Table 5). The following sections discuss the new trends and topics observed in this study into the evolution of BE:

Almost all future BE studies will be conditioned by the implementation of technology. The groundbreaking technological innovations that have emerged over the last few years, such as AI, AR and VR, have been insufficiently addressed in the BE literature. While recent studies have explored BE’s role in AR (Butt et al., 2024), VR (Song et al., 2021; Kim et al., 2023) and the Internet of Things (Hoffman and Novak, 2018), multiple aspects related to the preceding, actual and after stages of consumer experiences with multiple technological touchpoints remain unknown. One aspect is how brands should deal with third parties delivering BEs (e.g. technological providers) without compromising consumers’ relationships with brands. This question is particularly important for companies managing BEs at different touchpoints and journey stages (i.e. omnichannel experiences, Gahler et al., 2022). Further, growing interest in new approaches related to human–technology interactions (Hoffman and Novak, 2018) calls for shifting the understanding of consumers’ experiential responses from a human-centric to an interaction-centric perspective. That is, future BE research should also analyze the role (i.e. the agency and communal contributions) of consumers and technology within the interaction, combined with measuring consumers’ experiential responses (e.g. sensory, affective, intellectual and behavioral).

Similarly, it is foreseeable that BE research will proliferate with new technologies related to the metaverse and AI (Ho and Chow, 2023). The value and meaning a brand creates in the consumer’s mind and the experiential responses evoked by new technologies are topics yet to be developed. Notably, brand–consumer relationships are based on interactions with algorithms (e.g. automated processes) with minimal human intervention (Grabarczyk and Pokropski, 2016). Therefore, future research should determine the effects of AI on consumer–brand interactions, such as virtual representatives of brands. This technological development, and others yet to emerge in the near future (e.g. BEs in spatial computing devices such as Apple Vison Pro), presents opportunities to redesign the consumer experience with online brands.

Topics related to BE and tourism were present in all periods analyzed, and it is likely they will continue to be important in the coming years, with a particular emphasis on the technology–tourism nexus. That is, as the range of AI-based technology available to serve consumers in the hospitality and tourism industry increases, multiple research projects will respond to how companies’ and destinations’ BEs can maintain their relevance through the use of immersive VR (Yu et al., 2024), AR (Barhorst et al., 2023) and mixed reality (Pillai et al., 2022) experiences. Relationships with AI-based technology such as chatbots (Ku, 2023) or interactions with robots in hotel services (Tung and Tse, 2023) will equally feature on the future agenda. In the physical context, destination BE has emerged as a strong topic, with studies on its influence in forming tourist trust (Torres-Moraga and Barra, 2023) and behavior (Tang et al., 2023).

BE is an important concept for many companies in the luxury goods and services industry. Exclusive access, personalization and relationships with vendors and employees characterize the industry and shape BE and how it is perceived (Harris and de Chernatony, 2001). The topic of luxury was present in all periods (De Kerviler and Rodriguez, 2019; Tynan et al., 2010) and, consequently, is expected to continue to feature. The emergence of new technologies, such as AR, will foster the continued importance of this topic (Javornik et al., 2021). Analysis has begun into robotic services in some luxury establishments, such as hotels (Tung and Tse, 2023), but not enough research has been conducted to determine whether they enhance BEs. Similarly, the exploration of luxury BEs in the metaverse warrants further investigation (Jiang et al., 2023).

CSR will continue to be part of the global business transformation agenda. Due to social pressure, public and private organizations have focused on developing CSR in recent decades; companies now seek to meet their objectives more sustainably. This new approach will foster research into topics that advocate CSR activities, for example, sustainability and energy efficiency and how they influence BE (Kushwah and Srivastava, 2023), and other related branding constructs such as brand loyalty (Khan and Fatma, 2019), brand image (Hennigs et al., 2017) and brand engagement (Tsou et al., 2022).

BE represents a complex and dynamic research topic and one of the most relevant constructs in marketing research (Khan and Rahman, 2015). Despite its relevance, longitudinal knowledge about its evolution and current status is limited and fragmented.

Although numerous studies have explored various dimensions of brand equity, there is a notable lack of comprehensive, longitudinal bibliometric analyses that map the development and trends in BE research over an extended period. Existing studies often cover shorter timeframes and smaller data sets, limiting their ability to capture the full evolution of the BE construct and its implications over time. For instance, Zha et al. (2020) analyzed the period from 2002 to 2018 with only 136 articles, which is insufficient for a thorough longitudinal analysis. Similarly, Nguyen and Trinh (2022) reviewed 142 documents spanning from 1987 to 2021 but did not include the critical period affected by the COVID-19 pandemic, which has profoundly impacted consumer behavior and brand interactions.

In addition, the rapid technological advancements and the changing landscape due to the COVID-19 pandemic have introduced new variables that significantly impact BE. Previous bibliometric studies have not fully incorporated these recent developments, thereby limiting their relevance to contemporary marketing challenges and opportunities. There is an urgent need to update the research agenda to reflect these changes and to provide a more current and comprehensive understanding of BE. The absence of recent bibliometric studies on BE has hindered the development and consolidation of a future BE-focused research agenda (Zha et al., 2020). Furthermore, due to the complexity of consumption contexts based on AI, VR and automation, multiple investigations have called for a new understanding of consumers’ experiences with brands and the current state of this research stream (Puntoni et al., 2021).

To contextualize this research gap, it is useful to review previous bibliometric studies on BE. Zha et al. (2020), using the Web of Science database, covered the period from 2002 to 2018 with 136 articles, aiming to reconceptualize BE and present a future research framework by identifying core and peripheral knowledge sources. Through a bibliometric analysis, they identified four emerging areas: customer experience, consumer–brand relationship, sensory BE and online BE and proposed a '2 × 2’ research matrix for future studies, emphasizing firm-based, social constructionist, embodiment and virtuality approaches. Conversely, Nguyen and Trinh (2022), using the Scopus database, reviewed the period from 1987 to 2021 with 142 articles, aiming to synthesize research trends on the distribution of 'other customer perception’ on BE and suggest future research directions. Through a systematic review combined with bibliometric analysis, they identified three groups of research topics, emphasized the role of social interactions in BE and the potential of mindfulness in consumer behavior and highlighted the importance of online experiences and Generation Z’s shopping behavior post-COVID-19.

These studies underscore the necessity for more comprehensive and updated analyses that consider recent technological impacts and the effects of the pandemic. This study aims to fill that gap, providing a more holistic understanding of BE and its evolving nature and suggesting a research agenda that incorporates these contemporary developments to ensure its relevance and applicability in the field of modern marketing.

In this endeavor, this paper presents a detailed bibliometric analysis of 774 BE-related articles published over the period 1981–2023. The findings of our bibliometric analysis contribute by expanding knowledge about scientific production, evolution and main salient topics in BE academic literature and proposing a future research agenda with implications for a wide range of organizations.

First, the results indicated that BE research is increasing, especially between 2017 and 2023, representing 74.16% of the published articles, according to the Scopus database used in the bibliometric analysis. This finding reveals that the proliferation of BE research is recent.

Second, as part of the motor themes resulting from the bibliometric analysis, conceptual themes regarding BE and their links with campaigns, promotions, sponsorships and advertisements were prevalent at the beginning of the periods analyzed. Subsequently, social media and online brand relationships emerged as basic and motor themes between 2017 and 2023, in which most research focused on the creation of experiences, the impact of brand management on BE and the role of consumers as cocreators of brand content on social media. Most recent research on BE expanded into new areas, such as tourism, fashion, luxury, banking and sports, and recently examined emerging technologies, such as AR and VR.

Third, of the 325 journals that published articles on the BE, the 10 most productive accommodate 26.23% of the output. The most productive were the Journal of Business Research, the Journal of Retailing and Consumer Services, the Journal of Product and Brand Management, the Journal of Brand Management, Sustainability and the Asia Pacific Journal of Marketing and Logistics.

Fourth, the articles that made the most significant impact regarding citations appeared in the period 2011–2016, represented by seminal articles developing the BE scale. The co-citation analysis showed that journal articles that addressed similar topics were regularly cited. This was also tested in the analysis of co-citations by the authors, which reached the same conclusion – i.e. authors examining similar topics (such as social media) tended to cite each other. Moreover, the articles’ longevity, innovation value, methodology and open access influenced the volume of citations.

Finally, the key insights of this paper are synthesized in a research agenda with a delimitation of multiple areas on BE that are proposed as the future of this construct. The research agenda proposes that immersive technologies will be transversal axes in future BE investigations. Other topics considered as future pivotal themes in BE literature are the role of AI, AR, VR, mixed reality and the metaverse (see Table 6). As tourism is a recurring and widespread topic in BE literature, we anticipate the rise of blended tourism and immersive technology in the near future. In addition, research will likely be conducted on social media, luxury, and how BE can be quantified and conveyed in omnichannel contexts. In addition, we note that consumers’ interest in companies’ CSR activities could lead to the emergence of sustainability-related themes interrelated with BE in the near future.

As with any other bibliometric study, various limitations arise that should be considered in future research. First, the choice of a single data source inherently introduces a level of uniformity to the analysis. In our study, Scopus was selected due to its reputation as a comprehensive and multidisciplinary database, known for its coverage of high-impact journals (Harzing and Alakangas, 2016). However, for a broad understanding and validation of findings, future bibliometric research on BE should incorporate multiple data sources such as WoS, Google Scholar and CrossRef, allowing for triangulation of results.

Second, our analysis focused solely on articles published in peer-reviewed journals to ensure consistency and reliability of the data. Consequently, other forms of scholarly output such as conference papers, reviews, books or book chapters were excluded from consideration. Nevertheless, it remains worthwhile for future studies to explore the inclusion of these alternative sources, albeit with caution due to the potential duplication of data. In addition, assessing the extent to which content from these sources later appears in journal articles could offer valuable insights into the scholarly landscape of BE research

This study was supported by the Andalucian Research, Development and Innovation Plan (Plan Andaluz de Investigación, Desarrollo e Innovación) PAIDI 2020 (Grant: P20_00457) and by the Spanish Ministry of Education, Culture and Sport (Ministerio de Educación, Cultura y Deporte del Gobierno de España) (Grant: FPU20/00235).

The supplementary materials for this article can be found online.