The Role of Social Media in Shaping Brand Equity for Historical Tourism Destinations

Abstract

In the post-pandemic era, tourism is recovering and historical and cultural scenic spots are highly favored but face serious homogenization and fierce competition. It is clear to both the industry and in academia that brand image building through social media is the key to relieving the situation; however, existing studies are mostly undertaken from the perspective of branding, often ignoring the use of brand equity theory in evaluating the brand image of such scenic spots. Based on the social media perspective, this study proposes and validates a set of brand image assessment frameworks for historical and cultural scenic spots centered on brand awareness, satisfaction, and reputation, which provides a scientific basis for scenic spot branding. The study constructs a multidimensional index system, utilizes the fuzzy optimal inferiority method and the TOPSIS hybrid evaluation model, and takes six historical and cultural scenic spots in Xi’an, China, as samples for quantitative and qualitative evaluation. By analyzing the rankings of these scenic spots, this study provides suggestions on how to publicize and shape brand images on social media platforms. These suggestions can enhance scenic spots’ competitiveness, leading to increased tourist flow, improved economic benefits, and enhanced cultural preservation efforts. This, in turn, contributes to the long-term, sustainable development of historical tourism destinations, addressing socio-economic and cultural challenges in a more targeted manner.

1. Introduction

Driven by economic recovery and economic growth in the post-pandemic era, the tourism industry has gradually shown a recovery in recent years. Taking China as an example, according to statistics, in 2023, the number of domestic trips reached 4.89 billion, realizing a remarkable growth of 93.3% over the previous year [1]. The trend continued in 2024, with domestic trips in the first three quarters totaling 4.237 billion, up 15.3% year on year. At the same time, the total expenditure of domestic Chinese tourists on tourism activities also reached 4.35 trillion yuan, up 17.9% year on year. At present, with the continuous improvement of social living standards and the growing demand for leisure travel, the cultural tourism market is generally showing a trend of diversification, personalization, and quality [2].

In China, during the May Day holiday in 2024, historical and cultural scenic spots were significantly favored as the preferred destinations for many tourists. According to Tencent Big Data, the heat of traffic at cultural heritage scenic spots during the May Day holiday achieved a year-on-year increase of 6.7%. This trend shows that the competition between cities is no longer limited to economic strength, infrastructure construction, and other traditional hard power categories, but is increasingly deepening into urban culture, brand image, and other soft power competitions [3]. The importance of historical and cultural attractions as concentrated carriers of regional culture and heritage is self-evident. For a city, the development and promotion of historical and cultural attractions are not only important requirements for the protection and inheritance of cultural heritage; they are also key initiatives for shaping and improving the city’s image and enhancing the soft power of urban culture [4].

However, historical and cultural scenic spots also face many challenges, such as homogenized competition, the overexploitation of cultural resources, and a uniform tourist experience in the process of development, which have led to a somewhat ambiguous positioning of scenic spots’ brand image. In the context of this study, “brand image” is mainly from the perspective of consumers. Brand image is a set of associations and perceptions expressed by consumers about a brand, reflecting the perception and impression of the brand in consumers’ minds [5]. For historical and cultural scenic spots, brand image includes consumers’ overall perception of the scenic spot’s cultural heritage, scenic features, service quality, and tour experience, which comes from consumers’ personal tour experience, word-of-mouth on social media, and all kinds of promotional materials. Further, “brand equity” refers to the market advantage and value added for the scenic spot due to consumers’ perceptions, attitudes, and behavioral tendencies towards the brand, which is reflected in the increase of tourist flow and the enhancement of tourist loyalty, as well as the enhancement of the scenic spot’s premium ability in the market [6]. In brand communication, brand image is defined as “a set of unique associations that a brand strategist seeks to create or maintain”. Brand image, as a name or iconic symbol used to clearly differentiate corporate entities, product lines, and services, is a key strategic cornerstone for building and maintaining a long-term competitive advantage [7]. In today’s increasingly competitive tourism market, branding has gradually become a core element in the marketing strategy of tourist attractions. This shift means that the focus of competition in the tourism industry has transitioned from relying solely on natural or human-centered tourism resources to a new stage of branding and influence diffusion. With the widespread popularity of social media, tourists are more inclined to share and post their travel experiences and impressions, a phenomenon that provides unprecedented promotional opportunities for scenic spots [8]. At the same time, many tourist attractions have adopted diversified strategies to actively build and strengthen their brand image by enriching the content of tourism products, improving service details, enhancing interaction with tourists, and innovatively showcasing and promoting the attractions’ unique charm [9]. For example, social media platforms such as Little Red Book and Weibo play an important role in promoting historical and cultural scenic spots.

The development of historic and cultural sites is increasingly inseparable from brand building and brand management. In this process, tourists play a crucial triple-role: the receiver of the brand, the practitioner of the experience, and the disseminator of word-of-mouth. When tourists visit a scenic area, if the actual experience and the scenic area match the conveyed brand image—that is, if it is “true to its name”—they will often give a positive subjective evaluation and, through the “word-of-mouth” effect, recommend the scenic area to friends and relatives [10]. This kind of real feedback based on personal experience can not only effectively enhance the popularity of the scenic spot, but also, more importantly, it can profoundly influence the travel decision-making process of potential tourists [11]. Compared with the information provided by traditional marketing channels, word-of-mouth recommendations among tourists are often regarded as a more credible and persuasive source of information, which has a more direct and significant effect on stimulating people’s interest and willingness to visit. For scenic spots, tourists’ evaluations of tourism brand culture and their sharing through social media and other channels have become one of the important indicators for measuring the competitiveness of scenic spots, which plays an important role in promoting the scenic spots’ brand image enhancement, market share expansion, and sustainable development [12]. Therefore, optimizing social media to differentiate the brand image of historical and cultural scenic spots has become the focus of attention for many scenic spots in seeking breakthroughs and to enhance their attractiveness.

In existing studies, most scholars have explored the factors affecting the development of attraction brands from a branding perspective, and brand personality and brand image have been the focus of many scholars. Usakli and Baloglu [13] surveyed 382 visitors to Las Vegas and found that visitors attributed brand personality traits to five dimensions of the destination: vitality, sophistication, competence, modernity, and sincerity. Hosany, et al. [14] investigated the relationship between destination image and destination personality and made a significant contribution to the understanding of brand image and brand personality in the context of tourism destinations. Ruiz, et al. [15] investigated the relationship between destination image and destination personality in building a competitive brand personality in tourism marketing by using text mining and tourist-driven approaches. Xie, Hu, Wu, Shan, Li and Shen [4] found that currently sustainability issues affect tourist behavior and the competitiveness of destination brand images. A comprehensive literature review using the Scopus database identified means to address these issues, including local community involvement, competitive markets, etc. Kladou, et al. [16] assessed the contribution of commonly used symbolic elements, i.e., destination name, logo, and slogan, to the establishment of a destination brand image for a scenic area and concluded that scenic destinations need to prioritize branding efforts. However, existing studies have neglected the examination of the brand images of historic and cultural scenic areas based on brand equity theory. Despite the fact that numerous scholars have conducted research on scenic branding from different perspectives, there are still significant shortcomings in the integration of social media. Many studies have overly relied on traditional questionnaires, field interviews, etc., in the process of data collection and analysis [17,18]. This approach is not only time-consuming and labor-intensive; it is also difficult to comprehensively capture the real-time feedback and diverse behavioral patterns of tourists on social media. Social media platforms such as Xiaohongshu, Weibo, and Dianping contain rich information about tourists, including their sharing of travel experiences, expressions of emotional tendencies, and instant evaluations of scenic brands, etc. However, existing studies have failed to fully explore these data resources, resulting in a lack of in-depth understanding of the actual situation of scenic brands in social media communication. Brand awareness and brand reputation are important components of brand equity. Brand awareness refers to the extent to which a brand is known and understood by the public, also known as “brand recognition”, which reflects the degree of understanding and familiarity with the brand. Brand reputation refers to the extent to which a brand has gained public trust, support, and approval. Meanwhile, brand satisfaction reflects consumers’ overall evaluation of a brand’s products or services. This evaluation is based on consumers’ individual needs and expectations and is compared with their actual experience of the brand’s products or services. Brand satisfaction increases when a product or service meets or exceeds consumer expectations. Conversely, if the product or service does not meet expectations, brand satisfaction may decrease.

Based on the above background, this study aims to address the following key issues: How to construct a set of scientific, comprehensive, and practical evaluation index systems for the brand equity of historical and cultural scenic spots based on social media big data and using a multi-criteria decision analysis method to accurately assess scenic spots’ brand equity and provide effective strategies for scenic spots’ brand construction. In view of this, this study is dedicated to proposing and validating a framework for evaluating the brand image of historical and cultural scenic spots from the perspectives of brand image construction and social media. Specifically, we first carefully constructed a set of multi-dimensional indicator systems covering the three core aspects of brand awareness, brand satisfaction, and the brand reputation of historical and cultural scenic spots. Then, we adopted a hybrid evaluation model combining the fuzzy best–worst method and TOPSIS to conduct a comprehensive and in-depth analysis of the brand image of historical and cultural scenic spots. During this study, we used a combination of quantitative and qualitative evaluations to conduct a systematic ranking and evaluation analysis using six famous historical and cultural scenic spots in Xi’an, China, as empirical objects. To this end, through an in-depth analysis of the evaluation and ranking results of the historical and cultural scenic spots, we provide reference value suggestions on how to promote and shape the brand image on social media platforms more effectively.

The main innovations and contributions of this study are as follows: first, a multidimensional index system applicable to the brand image evaluation of historical and cultural scenic spots was constructed by combining brand equity theory (BET) with social media analysis; second, the fuzzy BWM–TOPSIS method is applied to solve the problem of coexisting subjectivity and uncertainty in scenic spot brand image evaluation by quantifying social media data; finally, six historical and cultural scenic spots in Xi’an, China, are used as empirical objects to reveal the key role social media plays in brand image formation and to provide targeted management suggestions.

This paper is structured as follows: Section 2 introduces a framework for the brand image evaluation of historical and cultural scenic spots from a social media perspective; Section 3 presents a ranking study using six historical and cultural scenic spots in Xi’an, China; Section 4 discusses and analyzes the evaluation and ranking results; the final section summarizes the entire study and provides an outlook for future research.

2. Methodology

2.1. Research Framework

To achieve an effective assessment of the brand image of historical and cultural sites from a social media perspective, this study constructs a systematic research framework, the specific details of which are shown in Figure 1. The framework mainly consists of five interrelated steps. First, we extensively refer to the existing, relevant literature on the evaluation of sorting categories, from which we extract and establish four core index design principles, thus laying a solid theoretical foundation for subsequent work. Second, based on professional standards and analysis of the literature review, we carefully select a set of indicators applicable to the assessment of historical and cultural scenic spot brands. This process ensures the credibility and applicability of the selected indicators. Immediately after this process, based on the results of the previous two steps, we further clarify the three first-level indicators and the corresponding six second-level indicators for this study. We then construct a set of scientific and reasonable evaluation and ranking methods. The method innovatively combines fuzzy BWM for numerical transformation and TOPSIS for ranking, thus achieving a quantitative assessment of the brand image of historical and cultural scenic spots. Finally, we select a real case for empirical study and, applying the above method, the ranking results of historical and cultural scenic spots are derived, discussed, and analyzed in depth.

2.2. Theoretical Foundations

2.2.1. Triangular Fuzzy Number

In 1965, Professor Zadeh proposed fuzzy set theory [19]. The fuzzy set theory, as an extension of classical set theory, can help decision makers to solve practical problems in uncertain environments. Triangular fuzzy number refers to a fuzzy set on a given domain, and for any $x\in U$, there is a number $u\left(x\right)\in \left[0,1\right]$ corresponding to it, where $u\left(x\right)$ is called the degree of membership of the pair, known as the membership function. The closer the degree of membership $u\left(x\right)$ is to 1, the higher the degree of membership; meanwhile, the closer the degree of membership $u\left(x\right)$ is to 0, the lower the degree of membership. Referring to the degree of affiliation $u\left(x\right)$, each element in the domain of discourse can be mapped onto a real number in the interval [0, 1]. The triangular fuzzy number is defined below.

The fuzzy number can be represented by $\left(l,m,u\right)$, where $0\le l\le m\le u\le 1$, and the affiliation function can be expressed with the Equation (1):

$$u_M\left(x\right)=\left\{\begin{array}{c}0,\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}x<l\\ {\displaystyle \frac{x-l}{m-l}},\hspace{1em}\hspace{1em}l<x<m\\ {\displaystyle \frac{u-x}{u-m}},\hspace{1em}\hspace{1em}m<x<u\\ 0,\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}x>u\end{array}\right.$$

(1)

Then, $M$ is said to be a triangular fuzzy number and, if $l=m=u$, then $M$ is an exact number. In the decision-making process, $l$ means that the expert gives the most pessimistic value (i.e., the lower bound of the triangular fuzzy number), $m$ means that the expert gives the value that he or she thinks is most likely, and $u$ means that the expert gives the most optimistic value (i.e., the upper bound of the triangular fuzzy number).

Professor Zadeh introduced linguistic variables in 1975 [19] to evaluate quantitative issues with qualitative criteria in order to make people’s evaluations more realistic. Linguistic variables are converted into triangular fuzzy numbers for calculation. The specific conversion rules are shown in

Table 1. Transformation rules of the linguistic variables of decision makers.

Linguistic Terms	Membership Function
Equally important (EI)	(1, 1, 1)
Weakly important (WI)	(2/3, 1, 3/2)
Fairly important (FI)	(3/2, 2, 5/2)
Very important (VI)	(5/2, 3, 7/2)
Absolutely important (AI)	(7/2, 4, 9/2)

.

2.2.2. Fuzzy BWM

As the latest multi-indicator decision method, Professor Rezaei proposed the best–worst method in 2015 [20], and, since its introduction, BWM has demonstrated a strong potential for application in many fields due to its unique decision logic and efficient arithmetic mechanism [21,22]. By selecting the best and worst indicators from all indicators and comparing them with other indicators, this method obtains the priority of the best indicators to other indicators and the priority of other indicators to the worst indicators, builds a nonlinear programming model, and finally determines the weights of the indicators [23]. In evaluating the brand image of historical and cultural scenic spots, fuzzy BWM has significant advantages in dealing with the multi-indicator decision problem. Compared with other methods, it can effectively reduce the subjective judgment bias. At the same time, since some indicators in the brand image evaluation of scenic spots are difficult to quantify precisely, fuzzy BWM can more accurately reflect the relative importance of the indicators, thus providing a more reliable weighting basis for brand image evaluation.

Step 1: Defining decision indicators

A system of evaluation indicators is established based on the object of study, with values that reflect the performance of different alternatives.

This is very important for the proper evaluation of alternatives. Assuming that there are n indicators, it can be expressed as $\left\{c_1,c_2,\dots ,c_n\right\}$.

Step 2: Choosing the best and worst indicators

The best indicator ($c_B$) is the most important indicator in the indicator system according to the decision maker, and the worst indicator ($c_W$) is the least important indicator according to the decision maker.

Step 3: Determining the fuzzy preference of the optimal indicator over other indicators

Determining the fuzzy preference is a very important step in fuzzy BWM, where the optimal indicator $c_B$ is compared pairwise with other indicators. With the linguistic variables listed in Table 1, the fuzzy optimal–other vector can be obtained with Equation (2):

$${\tilde{A}}_B=({\tilde{a}}_{B1},{\tilde{a}}_{B2},\dots ,{\tilde{a}}_{Bn})$$

(2)

${\tilde{a}}_{Bj}$ denotes the fuzzy preference of the optimal indicator $c_j(j=1,2,\dots n)$ for indicator $c_B$, where ${\tilde{a}}_{BB}=\left(1,1,1\right)$.

Step 4: Determining the fuzzy preference of other indicators over the worst indicator

In the same way as the previous step, the fuzzy preference of the decision maker is converted into triangular fuzzy numbers through the linguistic variables and conversion rules listed in Table 1, and the fuzzy other–worst vector is obtained with the Equation (3):

$${\tilde{A}}_W=({\tilde{a}}_{1W},{\tilde{a}}_{2W},\dots ,{\tilde{a}}_{nW})$$

(3)

${\tilde{a}}_{jW}$ denotes the fuzzy preference of indicator $c_j(j=1,2,\dots n)$ over the worst indicator $c_W$ pair, where ${\tilde{a}}_{WW}=\left(1,1,1\right)$.

Step 5: Determining the optimal fuzzy weights $\left({\tilde{w}}_1^{*},{\tilde{w}}_2^{*},\dots ,{\tilde{w}}_n^{*}\right)$.

For each fuzzy pair ${\tilde{w}}_B/{\tilde{w}}_j$ and ${\tilde{w}}_j/{\tilde{w}}_W$, the optimal fuzzy weights for each indicator are obtained when ${\tilde{w}}_B/{\tilde{w}}_j={\tilde{a}}_{Bj}$ and ${\tilde{w}}_j/{\tilde{w}}_W={\tilde{a}}_{jW}$. In order to satisfy all the conditions of $j$, it is necessary to minimize the maximum absolute difference between all $\left|{\displaystyle \frac{{\tilde{w}}_B}{{\tilde{w}}_j}}-{\tilde{a}}_{Bj}\right|$ and $\left|{\displaystyle \frac{{\tilde{w}}_j}{{\tilde{w}}_W}}-{\tilde{a}}_{jW}\right|$ containing $j$. Therefore, we need to build the following model with extremely large and small values using Equation (4):

$$\begin{array}{l}\min {\max }_j\left\{\left|{\displaystyle \frac{{\tilde{w}}_B}{{\tilde{w}}_j}}-{\tilde{a}}_{Bj}\right|,\left|{\displaystyle \frac{{\tilde{w}}_j}{{\tilde{w}}_W}}-{\tilde{a}}_{jW}\right|\right\}\\ s.t.\left\{\begin{array}{c}{\displaystyle {\sum }_{j=1}^{n}R({\tilde{w}}_j)}=1\\ l_k^w\le m_k^w\le u_k^w\\ 0\le l_j^w\\ j=1,2,\dots ,n\end{array}\right.\end{array}$$

(4)

where ${\tilde{w}}_B=\left(l_B^W,m_B^W,u_B^W\right)$, ${\tilde{w}}_j=\left(l_j^W,m_j^W,u_j^W\right)$, ${\tilde{w}}_W=\left(l_W^W,m_W^W,u_W^W\right)$, ${\tilde{a}}_{Bj}=\left(l_{Bj},m_{Bj},u_{Bj}\right)$ and ${\tilde{a}}_{jW}=\left(l_{jW},m_{jW},u_{jW}\right)$.

The above model can be converted into a non-linear constrained optimization problem with Equation (5):

$$\begin{array}{l}\min {\zeta }^{*}\\ s.t.\left\{\begin{array}{c}\left|{\displaystyle \frac{(l_B^W,m_B^W,u_B^W)}{(l_j^W,m_j^W,u_j^W)}}-\left(l_{Bj},m_{Bj},u_{Bj}\right)\right|\le (k^{*},k^{*},k^{*})\\ \left|{\displaystyle \frac{(l_j^W,m_j^W,u_j^W)}{(l_W^W,m_W^W,u_W^W)}}-\left(l_{jW},m_{jW},u_{jW}\right)\right|\le (k^{*},k^{*},k^{*})\\ {\displaystyle {\sum }_{j=1}^{n}R({\tilde{w}}_j)}=1\\ \begin{array}{l}{l}_k^w\le m_k^w\le u_k^w\\ 0\le l_j^w\\ j=1,2,\dots ,n\end{array}\end{array}\right.\end{array}$$

(5)

Calculating Equation (5), the optimal fuzzy weights $(w_1^{*},w_2^{*},\dots ,w_n^{*})$ can be obtained.

Step 6: Performing fuzzy weight defuzzification

The weights calculated in the fuzzy BWM are triangular fuzzy numbers, which are very different from those of the traditional BWM; thus, we need to defuzzify the fuzzy weights of the metrics based on the linguistic variables of the decision maker and transform them into clear values. The fuzzy weight values are transformed into precise weight values using graded mean integration (graded mean integration representation). The method can be described with Equation (6):

$$R({\tilde{a}}_j)={\displaystyle \frac{l_i+4m_i+u_i}{6}}$$

(6)

Step 7: Calculating the consistency ratio

The consistency test is performed on the calculated results, and the consistency test coefficients (CIs) corresponding to different worst language variables ${\tilde{a}}_{BW}$ are shown in

Table 2. Consistency index (CI) for fuzzy BWM.

Linguistic Terms	Equally Important (EI)	Weakly Important (WI)	Fairly Important (FI)	Very Important (VI)	Absolutely Important (AI)
${\tilde{a}}_{BW}$	(1, 1, 1)	(2/3, 1, 3/2)	(3/2, 2, 5/2)	(5/2, 3, 7/2)	(7/2, 4, 9/2)
CI	3.00	3.80	5.29	6.69	8.04

.

$$CR={\displaystyle \frac{{\zeta }^{*}}{CI}}$$

(7)

The lower the CI, the higher the consistency of the comparison results.

2.2.3. TOPSIS

As a classic method in the field of multi-criteria decision making, the TOPSIS algorithm has been widely used in many disciplines and practical application scenarios, and its theory and application have been continuously developed and improved [24,25]. The main advantage of the TOPSIS algorithm is that it calculates the distance between each program and the positive and negative ideal solutions for obtaining a comprehensive evaluation score, which can effectively solve the problem of multi-indicator decision making and comprehensively reflect the differences between programs. In addition, its calculation process is relatively simple and clear, and the results are intuitive and easy to understand, which can clearly show the strengths and weaknesses of each scenic spot in terms of brand image construction and facilitate scenic spot managers to make targeted improvements. The steps of the TOPSIS algorithm are outlined below.

(1) Construction of the standardization matrix: The evaluation matrix X is standardized by the square and normalization method to obtain the standardized matrix Z. The numerical calculation method of the indicators in the standardized matrix Z is given below. The steps of the TOPSIS algorithm can be represented with Equation (8):

$$z_{ij}={\displaystyle \raisebox{1ex}{$x_{ij}$}\!\left/ \!\raisebox{-1ex}{$\sqrt{{\displaystyle \sum _{i=1}^m{x}_{ij}^2}}$}\right.}$$

(8)

(2) Construction of the weighted standardization matrix: According to the entropy weight method, calculated weights and standardized matrix are multiplied to obtain the standardized matrix U, and it is calculated with Equation (9):

$$\begin{array}{l}{u}_{ij}=W_j\times z_{ij}\\ U=\left[\begin{array}{ccc}{u}_{11}& \dots & u_{1n}\\ \dots & \dots & \dots \\ u_{m1}& \dots & u_{mn}\end{array}\right]\end{array}$$

(9)

(3) Calculation of the positive and negative ideal solutions $U^{+} \mathrm{and} U^{-}$ is performed for each indicator, and the test equations are calculated with (10) and (11):

$$U^{+}=(u_1^{+},u_2^{+},\dots ,u_n^{+})=\left\{\max u_{ij}\right|i=1,2,\dots ,m\}$$

(10)

$$U^{-}=(u_1^{-},u_2^{-},\dots ,u_n^{-})=\left\{\min u_{ij}\right|i=1,2,\dots ,m\}$$

(11)

(4) Calculation of the distance between each evaluation index and the positive and negative ideal solutions is performed, and the calculation formulas can be expressed with Equations (12) and (13):

$$D_i^{+}=\sqrt{{\displaystyle \sum _{j=1}^n{(u_j^{+}-u_{ij})}^2}}$$

(12)

$$D_i^{-}=\sqrt{{\displaystyle \sum _{j=1}^n{(u_j^{-}-u_{ij})}^2}}$$

(13)

(5) Calculation of the comprehensive score index of each index: Through the calculation of the Euclidean distance that can be derived from the evaluation of the relative closeness of the object, the comprehensive evaluation of the programmed score can be performed. The higher the value, the better the programmed score; the lower the value, the worse the programmed score. The formula for calculating the comprehensive score index can be presented with Equation (14):

$$C_i={\displaystyle \frac{D_i^{-}}{D_i^{+}-D_i^{-}}}$$

(14)

2.3. Evaluation Process

2.3.1. Principles for the Design of Indicators

(1) The dominant principle of quantitative analysis indicators

A scenic area brand culture system is a multi-dimensional, multi-level, complex system, which includes brand history, cultural connotation, market influence, visitor satisfaction, and other aspects. Therefore, when constructing an evaluation system for a scenic area brand, it should adhere to quantitative analysis as the dominant principle and strive to reflect the whole picture of the system objectively and realistically. Quantitative analysis can provide a more reliable basis for evaluating objective content due to its clear and accurate standards. Specifically, through quantitative indicators such as brand awareness index, tourist satisfaction score, market share, etc., quantitative methods can effectively enhance the objectivity of the evaluation and reduce the bias caused by subjective assumptions. The application of this principle not only helps to improve the accuracy of the evaluation; it also provides data support for the subsequent development of the brand strategy.

(2) The principle of combining science and applicability

In designing an evaluation index system for a scenic brand culture, we must strictly follow the scientific connotation of brand science to ensure that the indicators can scientifically and reasonably reflect the core value of the scenic brand. This requires that we select indicators, weight distribution, and the standard setting for evaluation, etc., based on the theoretical foundation of brand science, rigorous logical reasoning, and scientific evidence. At the same time, in order to have a wide range of applicability and practical value, the design of the indicator system must also consider applicability and popularity, not only for vertically comparing the changes in scenic spot brands at different points in time, but also for horizontally comparing the differences between different scenic spot brands. In addition, the design of indicators should also consider the availability and convenience of data and make use of the existing statistical data and easily collected data as much as possible, to ensure the operability and practicability of the evaluation system.

(3) Principle of operability

When selecting evaluation indicators, in addition to considering whether they meet the requirements of comprehensive evaluation, it is also necessary to focus on data support and the operability of indicators. The selection of indicators should be concise and clear, and neither too cumbersome and complex nor too simple and crude, to ensure that indicators are logical and avoid overlap and conflict. At the same time, the collection and calculation of data should be simple and straightforward, and the calculation methods used should be concise, to ensure the efficiency and accuracy of the evaluation process. The implementation of this principle will help to reduce the complexity of the evaluation work, improve the efficiency of the evaluation, and provide strong support for continuous improvement in the brand culture of the scenic spot.

(4) Principle of typicality

In view of the extensive content of brand evaluation, while striving for comprehensiveness, the indicator design must also pay attention to typicality and highlight the key points. The selection of evaluation indicators should be representative and truly and accurately reflective of the core characteristics and comprehensive advantages of the scenic brand culture. By selecting the most typical indicators, the accuracy and effectiveness of the evaluation can be effectively enhanced. In addition, when setting up the indicators of the evaluation system, distributing the weights among the indicators, and dividing the evaluation criteria, experts in the field should be invited to participate, and their considerable professional knowledge and practical experience should be used to ensure the scientific, rational, and authoritative nature of the evaluation system. The application of this principle can help improve the practicality and implementation of the evaluation system and provide a strong guarantee for the improvement and development of the brand culture of scenic spots.

2.3.2. Basis for Indicator Design

(1) Professional standard basis

The basis of professional standards is the foundation and guideline for the design of indicators. When constructing the evaluation system, it should first refer to the professional standards in related fields at home and abroad, such as GB/T29187-2012 [26], “Brand Evaluation Brand Value Evaluation Requirements”. These professional standards usually contain several dimensions and key elements of the brand culture evaluation of scenic spots, providing clear guidance and a framework for indicator design [4]. Following professional standards can ensure that the indicator design meets the industry requirements and best practices, and enhances the authority and credibility of the evaluation system.

(2) Literature and theoretical basis

Literature and theoretical basis support indicator design: In the process of forming the indicator design, the literature and research results in related fields should be widely consulted to understand the latest theories, methods, and cases of the brand culture evaluation of scenic spots. The external performance of the brand includes product logo, product image, product price, etc. People’s early understanding of a brand is relatively simple, i.e., its name and logo distinguish it from other competitor brands, but the deeper meaning of a brand is that it is a carrier of culture. The existing literature measures brands according to three dimensions: brand awareness, satisfaction, and reputation [6,16,18]. Therefore, this study also follows these dimensions.

2.3.3. Construction of the Primary Indicator System

Operators can pass the corporate culture and business philosophy to consumers and receive recognition from consumers through their brand, which also makes the brand have a deeper meaning. The brand is not only closely related to the scenic spot but also has a close relationship with its consumers, and the brand can build trust among its consumers and estimate the number of consumers that favor the brand, resulting in a higher willingness to buy as well as an increase in price tolerance. Brand awareness, reputation, and satisfaction in brand theory are important indicators for assessing brand image and market performance.

Brand awareness refers to the extent to which a scenic spot’s brand is known and understood by the public; it is also known as brand recognition. It reflects the degree of public understanding and familiarity with the brand of the scenic spot. A scenic spot brand with high brand awareness means that its name, characteristics, location, and other information have been widely disseminated and can quickly attract the attention of tourists. Improvement in brand awareness helps tourists to have a sense of familiarity with the scenic spot brand, which, in turn, can create a good feeling and lay a solid foundation for the subsequent travel experience. At the same time, brand awareness is also an important prerequisite for tourists in generating trust, support, and praise, as a highly visible brand often means greater reliability and professionalism. Word-of-mouth communication, as an important means of information transfer, plays a significant role in enhancing the brand awareness of the scenic area.

Brand reputation refers to the extent to which the scenic brand has gained public trust, support, and praise. It reflects the public’s positive evaluation of the overall image of the scenic spot brand and is an important part of brand attitude. A scenic spot brand with a high reputation usually means that its service quality, tour experience, safety, and security are excellent and can win wide recognition and praise from tourists. The enhancement of reputation helps to strengthen tourists’ loyalty to the scenic spot brand, promote word-of-mouth communication, and stimulate the growth of scenic spot traffic.

Brand satisfaction, on the other hand, refers to the extent to which tourists’ needs and expectations are met by the brand products or services of the scenic spot, e.g., tour experience, service quality, facilities, and equipment, after visiting the scenic spot. It is an important index for measuring the market performance of the scenic spot brand and the level of tourist satisfaction. A scenic spot brand with a high level of satisfaction means that it can fully meet the expectations and needs of tourists and provide high-quality visitor experiences and services. An improvement in satisfaction helps to enhance tourists’ trust and loyalty to the scenic spot brand, encourage tourists’ return visits and word-of-mouth advertisement, and promote the long-term development of the scenic spot brand.

2.3.4. Construction of a System of Secondary Indicators

The secondary indicators for these three areas are listed below.

(1) Brand awareness

Brand impression: Brand impression refers to the quality of tourists’ initial impressions and memories of the scenic spot brand. Brand impression reflects the uniqueness and recognition of the scenic spot brand in the minds of tourists. A brand with high impression can stand out among many scenic spots and leave a deep impression on tourists.

Brand recognition: Brand recognition refers to the ability of tourists to accurately identify and distinguish the brand of the scenic spot. Brand recognition is an important part of brand awareness, reflecting the degree to which tourists are familiar with the brand name, logo, slogan, and other elements of the scenic spot. A highly recognizable brand helps tourists to quickly find and identify the scenic spot from a large amount of information.

(2) Brand satisfaction

Soft satisfaction: Soft satisfaction refers to the degree of tourists’ satisfaction with the non-material services provided by the scenic spot (e.g., service attitude and scenic entertainment atmosphere). Soft satisfaction reflects the performance of the scenic spot in terms of service, including the friendliness, professionalism, and responsiveness of the staff, as well as the cultural atmosphere of the scenic spot and the guided tour service. These factors directly affect tourists’ experiences and satisfaction [27].

Hard satisfaction: Hard satisfaction refers to the degree of tourists’ satisfaction with the hardware facilities, e.g., ease of navigation, for traveling to the scenic spot. It reflects the scenic spot’s investment in and maintenance of hardware facilities. A scenic spot with high hard satisfaction usually has perfect facilities and equipment, good cleanliness, and safety, and can provide tourists with a comfortable and safe visiting environment.

(3) Brand reputation

Brand identity: Brand identity refers to the degree of recognition of the scenic spot brand by tourists, including affirmation of its quality, value, characteristics, and other aspects. Brand awareness reflects tourists’ overall evaluation of the scenic brand. A brand with high recognition usually means that it has high quality and value and can meet the expectations and needs of tourists.

Brand trust: Brand trust refers to the degree of tourists’ trust in the scenic spot brand, including their trust in its honesty, safety, service quality, and other aspects. Brand trust is the core component of brand reputation, which reflects the degree of tourists’ trust in the scenic spot’s brand. A brand with a high level of trust usually means that it has a good record of honest operation, perfect safety measures, and high service quality, and can win the full trust and support of tourists.

In summary, the indicator system that we have constructed is shown in

Table 3. Scenic spot brand culture index system.

Tier 1 Indicators	Secondary Indicators
Brand awareness	Brand recognition
	Brand impression
Brand reputation	Brand identity
	Brand trust
Brand satisfaction	Soft satisfaction
	Hard satisfaction

.

2.4. Scenic Spot Ranking Based on Fuzzy BWM–TOPSIS

In the process of comprehensively evaluating the brand image of historical and cultural scenic spots, the scientific and reasonable determination of the weights of each evaluation index is an important condition for ensuring the accuracy of the evaluation results. Therefore, experts who have long been engaged in the fields of scenic spot management, tourism planning, and brand research are invited to apply the fuzzy linguistic variables in Section 2.2.1 to carefully evaluate the importance of each evaluation index based on their professional knowledge and practical experience. Then, the weight coefficients of each indicator are finally calculated according to the fuzzy best–worst method (fuzzy BWM) described in Section 2.2.2.

After obtaining the weights of each indicator, we enter the practical application of the TOPSIS algorithm. Quantifying each secondary indicator is a crucial step. Through quantification, we can transform abstract brand image and market performance into concrete and comparable data, so as to make a more accurate and objective evaluation for the management and development of scenic spots. In exploring how to quantify the secondary indicators of the scenic spot brand evaluation index system, we cannot ignore the important role played by social media platforms such as Xiaohongshu, Weibo, and Dianping.

With its unique community atmosphere and content form, Xiaohongshu has become the preferred platform for an increasing number of young people to obtain travel information and share travel experiences. For scenic spots, indicators such as the number of notes, likes, comments, and emotional tendencies on Xiaohongshu can intuitively reflect the level of interest, satisfaction, and brand awareness of tourists towards scenic spots. Microblogging, as a social media practice with a large user base, is characterized by fast information dissemination and wide coverage, which makes it an important lens through which to measure the brand awareness and reputation of scenic spots. The number of mentions, retweets, comments, and likes on Weibo not only reflects the exposure and influence of the scenic spot brand; they also reflect the degree of tourists’ recognition of and trust in the brand. In addition, the sentiment analysis on Weibo can dig deeper into the real feelings of tourists towards the scenic spot and provide valuable feedback for the scenic spot. As a platform focusing on local life services, Dianping, with its rich user evaluation and rating system, provides scenic spots with a powerful tool for quantifying soft and hard satisfaction.

(1) The way to quantify brand impression: the number of social media reviews

Brand impression is an important indicator for measuring the quality of tourists’ initial impressions and memories of a scenic area’s brand. In the digital era, the social media online evaluation platform has become an important channel through which tourists obtain information about scenic spots and form brand impressions. The higher the number of social media reviews, the higher the attention received by the scenic brand and the deeper the impression formed by tourists about the brand. Therefore, the number of reviews can be used as an important reference for measuring brand impression.

(2) Quantification of soft satisfaction: word-of-mouth score

Soft satisfaction is an important indicator to measure the degree of tourists’ satisfaction with the intangible services of the scenic spot. As a comprehensive evaluation of tourists’ overall experience of the scenic spot, a word-of-mouth score can reflect tourists’ satisfaction with the scenic spot’s soft service in the process of touring. The higher the internet word-of-mouth (IWOM) score, the higher the satisfaction tourists feel with the soft services of the scenic spot.

(3) Hard satisfaction quantification method: facility ratings

Hard satisfaction is an important indicator for measuring tourists’ satisfaction with the hardware facilities of scenic spots. Navigation and location service applications such as Gaode (https://www.gaode.com/) not only provide scenic area navigation and location information; they also often contain tourists’ evaluations and ratings of scenic areas. Among them, the evaluation and rating of the hardware facilities of the scenic area can reflect the satisfaction of tourists with the hard services of the scenic area. The higher the rating, the higher the satisfaction tourists feel with the hardware facilities of the scenic area.

(4) Way to quantify brand recognition: amount of brand publicity of scenic spot on social media

Brand recognition is an important indicator that measures the ability of tourists to accurately recognize and distinguish scenic spot brands. On social media platforms, such as Weibo, the number and frequency of scenic spot brand mentions can reflect its popularity and recognition. Therefore, the number of microblogs can be used as an effective indicator to quantify brand recognition. The higher the number of microblogs, the higher the exposure and visibility of the scenic spot brand on social media and, thus, the higher the level of recognition among tourists.

(5) Brand identity quantification: number of social media likes

Brand identity is an important indicator for measuring the degree of recognition of tourists toward the scenic spot brand. On social media platforms, such as Weibo, tourists’ liking behavior towards the scenic spot brand can reflect their degree of recognition and love for the brand. Therefore, the number of social media likes can be used as an effective indicator to quantify brand recognition. The higher the number of likes, the higher the tourists’ recognition of the scenic spot brand.

(6) Way to quantify brand trust: social media brand emotion

Brand trust is an important indicator for measuring the degree of tourists’ trust in the scenic brand. On social media platforms, tourists’ comments on and emotional attitudes towards scenic spot brands can reflect their level of trust in these brands. Therefore, extracting sentiment trends in microblogs through sentiment analysis techniques can be an effective method to quantify brand trust. The higher the proportion of positive emotional tendencies, or the more positive the average value of emotional tendencies, the higher the tourists’ trust in the scenic brand.

3. Implementation and Results

3.1. Case Context

As one of the four ancient capitals of civilizations around the world, Xi’an, China, occupies an important place in the history of China and even in the world. As the ancient capital of 13 dynasties in ancient China, Xi’an possesses profound historical and cultural connotations and rich cultural resources. The historical and cultural scenic spots in Xi’an not only have a deep historical connotation but also have an important cultural value. Meanwhile, as a famous historical and cultural city, Xi’an enjoys wide popularity and influence both at home and abroad. Therefore, we chose six famous historical and cultural scenic spots in Xi’an as research cases: Sui Daxing Tang Chang’an City Mingde Gate Ruins Park, Temple of Heaven Ruins Park, Xi’an Municipal Museum, Yanming Lake, China Tang Garden, and Dahan Shanglin Garden (Du Ling). The distribution of these six historical and cultural scenic spots is relatively centralized, which helps to exclude the interference of some additional factors, such as climatic differences and any differences in custom brought about by diverse geographic locations.

3.2. Identification of Criteria

Brand impression was measured by the number of social media reviews, word-of-mouth scores (reflecting soft satisfaction), facility scores (reflecting hard satisfaction), the number of social media campaigns quantifying brand awareness, the number of likes measuring brand advocacy, and the results of microblog sentiment analysis assessing brand trust. The specific data are as shown in

Table 4. Data results.

	Brand Impression	Soft Satisfaction	Hard Satisfaction	Brand Recognition	Brand Identity	Brand Trust
Sui Daxing Tang Chang’an City Mingde Gate Ruins Park	0	0.3	1	0	0	1
Temple of Heaven Ruins Park	0.012	1	0.8	0.761	0.734	0.662
Xi’an Municipal Museum	1	1	1	1	0.296	0.404
Yanming Lake	0.039	1	1	0.234	0.560	0.874
China Tang Garden	0.295	1	0.8	0.060	1	0
Dahan Shanglin Garden (Du Ling)	0.026	0	0	0.930	0.178	0.542

(the first five secondary indicators have been normalized to exclude experimental evaluation errors due to inconsistencies in the data scale levels).

3.3. Determination of Criteria Weights

Based on the established evaluation index system, the fuzzy BWM method was used to obtain the weight of each expert regarding the index.

In this study, five experts were invited to form an expert group, denoted as DM1, DM2, and DM3. The expert group identified brand trust (c4) and brand awareness (c1) as the best and worst indicators, respectively, and ranked them against other indicators, resulting in pairwise comparison matrices as shown in

Table 5. Fuzzy linguistic preferences for best and worst indicators.

	Brand Recognition	Brand Impression	Brand Identity	Brand Trust	Soft Satisfaction	Hard Satisfaction
Best metric	AI	VI	VI	EI	WI	FI
Worst metric	EI	WI	FI	AI	AI	AI

and

Table 6. Fuzzy number preferences for the best and worst indicators.

	Brand Recognition	Brand Impression	Brand Identity	Brand Trust	Soft Satisfaction	Hard Satisfaction
Best metric	(7/2, 4, 9/2)	(5/2, 3, 7/2)	(5/2, 3, 7/2)	(1, 1, 1)	(2/3, 1, 3/2)	(3/2, 2, 5/2)
Worst metric	(1, 1, 1)	(2/3, 1, 3/2)	(3/2, 2, 5/2)	(7/2, 4, 9/2)	(7/2, 4, 9/2)	(7/2, 4, 9/2)

.

By substituting in Equation (5), the result of the calculation is obtained as follows:

$W=(0.08, 0.10, 0.11, 0.29, 0.21, 0.22)$, $CR=0.028$. This CR value is less than 0.1. It passes the consistency test and confirms that the results are reliable.

3.4. Ranking

Combined with the obtained scenic spot brand data and indicator weights, the TOPSIS algorithm is utilized to obtain the ranking results as shown in

Table 7. TOPSIS evaluation calculations.

Scenic Spots	Relative Closeness	Sorting Results
Sui Daxing Tang Chang’an City Mingde Gate Ruins Park	0.2	6
Temple of Heaven Ruins Park	0.55	2
Xi’an Municipal Museum	0.67	1
Yanming Lake	0.41	5
China Tang Garden	0.47	4
Dahan Shanglin Garden (Du Ling)	0.52	3

.

The sorting results show that there is a significant difference in the relative proximity of brand image construction among the historical and cultural scenic spots. Xi’an Municipal Museum, Tiantan Ruins Park, and Dahan Shanglin Yuan (Du Ling) ranked in the top three, indicating that they have achieved remarkable results in terms of historical and cultural heritage and brand image construction. The China Tang Yuan and Yanming Lake Recreation Park, on the other hand, scored slightly lower but was still competitive. In contrast, Sui Daxing Tang Chang’an City Mingdemen Ruins Park scored only 0.2, with the lowest ranking. In the ranking of scenic spots in this study, Xi’an Museum scored the highest. This is due to its excellent performance in many aspects: infrastructure, i.e., modern exhibition technology combined with intelligent guides and convenient facilities to enhance visitor satisfaction; digital marketing, with the help of platforms such as Xiaohongshu and Jieyin in achieving high exposure and strong interaction with creative content to enhance brand awareness; historical depth, i.e., a rich and valuable collection of cultural relics with thematic exhibitions and cultural lectures to deepen the connection to the objects and to establish an authoritative image. In contrast, some scenic spots have advantages in historical resources, but they have outdated infrastructure and weak digital marketing. Xi’an Museum stood out in the brand image evaluation due to its comprehensive efforts across multiple dimensions.

4. Discussion

Considering the increasingly fierce competition in the tourism market at present, the construction of scenic cultural brands has become a key factor in the development of scenic spots. From the above information, we can infer that it is of great significance to construct scenic spot cultural brands with multiple dimensions. We carefully analyze multiple dimensions to explore the ways to accurately achieve the efficient construction of scenic spot cultural brands that meet the constantly evolving needs of tourists.

At the level of analyzing the brand impression measurement, we suggest digging deeper into the cultural and historical associations of scenic spots, organizing professional teams to study cultural, historical, and religious attractions, and combining ancient legends, famous anecdotes, and landscapes to enrich the brand heritage. At the same time, we suggest collecting the descriptive vocabulary of tourists, potential tourists, and residents, analyzing character traits, and determining brand personality. We also extensively study cases of successful applications of brand personality in countries and cities to learn from successful experiences and to compare cultural brand impressions of the same type of scenic spots to discover the competitive differentiation points in terms of the form of cultural displays, visitor experience programs, etc., with the aim of creating a unique cultural brand image and clear market positioning.

In soft satisfaction, it is necessary to pay attention to the excavation of intangible advantages and brand experience enhancement. On one hand, given the complexity of competition among scenic areas, the intangible aspects are crucial, and a professional team should be organized to thoroughly analyze the unique intangible qualities of the scenic area, such as the local cultural atmosphere and customs, etc., incorporating the human-centered qualities of the residents’ warmth and hospitality into the brand positioning, and shaping a brand image of warmth and friendliness. On the other hand, to enhance the brand experience, tourism brand experience is the cumulative experience of tourists across their entire journey, with multiple contact points, from the tourists’ plan to go to the scenic area after acquiring information about it, to the tour process of service, to the end of the tour after the feedback stage. A comprehensive combination of various aspects is necessary for the optimization of the brand-related stimulus factors, such as the official website, design of brochures (it is important to adopt a unique visual style), improvement in the guided tour signs in the scenic area, and the improved quality of service personnel.

In terms of hard infrastructure and service experience, the concept of art transportation can be borrowed, and the transportation facilities in the scenic area can be formed into a cultural dissemination carrier, such as displaying local artworks on sightseeing buses and organizing small-scale cultural activities, so as to enhance the cultural experience of tourists on the way to the sightseeing area. In terms of the application of technology, the introduction of artificial intelligence, augmented reality, and other advanced technologies can be actively introduced to provide tourists with virtual previews of scenic areas, intelligent guides, and other services, keeping pace with contemporary trends and meeting the demand of tourists for technology-centered experiences. At the same time, hard satisfaction attaches great importance to health and safety issues. Hard infrastructure should strictly implement health and epidemic/pandemic-prevention measures, have high-quality safety and security facilities, and convey safety initiatives to visitors in a timely and clear manner, to enhance their sense of security.

To build unique brand recognition, it is necessary to make full use of social media and diversified cultural strategies. Social media has become an important marketing tool in the cultural services market, and scenic spots’ managers can take advantage of its high interactivity and user participation to display the scenic spot’s unique cultural content, such as publishing the scenic spot’s historical and cultural stories, short videos of folklore activities, etc., on social platforms, to attract tourists’ attention and enhance brand exposure. In terms of cultural strategy, the scenic spot can draw from the idea of city branding to explore its own unique cultural resources: if the scenic spot has a unique food culture, it can be positioned as a “food culture scenic spot”; advertising could focus on historical moments or art trends, such as publicizing the architectural and art styles of a certain historical period; tours could carry out cultural gamification activities and design a cultural treasure hunt route, such that tourists can gain a deeper understanding of the scenic spot’s culture during the tour. Through these initiatives, the unique cultural brand image of the scenic spot could be formed to deepen visitors’ recognition of the scenic spot brand, thus strengthening brand loyalty.

By analyzing at the level of brand identity, scenic spots’ managers should follow the concept of environmental protection throughout their operations, such as adopting solar energy facilities and promoting garbage classification in order to attract eco-conscious tourists. The digital environment should be used to showcase the scenic spot’s four seasons and special activities through social media, and artificial intelligence should be utilized to analyze tourists’ preferences, customize personalized itinerary recommendations, enhance interaction with tourists, and improve brand awareness. The accessibility and inclusiveness of scenic spots should be enhanced by improving barrier-free facilities, providing multi-language services, respecting the customs of tourists from different cultural backgrounds, and shaping an inclusive and friendly brand image. For focusing on cultural exchanges and authenticity, tourists should be convinced to participate in traditional handicraft production and folklore celebrations to win the recognition and trust of tourists and to successfully shape the scenic spot’s cultural brand.

At the level of brand trust, by establishing loyalty toward cultural institutions based on brand loyalty, which comprises attitudes and behavioral loyalty and is reflected in tourists’ willingness to revisit and recommend, the scenic area can collect feedback from tourists through questionnaires and online comments [28], analyze the factors affecting loyalty, and continuously optimize the service and experience, such as creating personalized tour routes and providing exclusive member benefits to enhance the satisfaction of tourists. By keeping up with market trends and paying attention to new developments in the tourism industry, such as emerging tourism modes and popular tourism elements, we can win the trust of tourists with sincere, professional, and continuous high-quality experiences and establish a trustworthy cultural brand image for each scenic spot.

Enhancing the brand equity of historical and cultural scenic spots through social media-based strategies can attract more tourists in a sustainable way. The increased tourist flow not only stimulates local economic growth but also provides more financial resources for the protection and maintenance of historical and cultural heritages. For example, with improved brand awareness and satisfaction, scenic spots can charge reasonable entrance fees or develop culture-related products, and the revenue can be used for heritage restoration and preservation. Moreover, the emphasis on brand reputation can promote better service quality and cultural experience in scenic spots. This attracts tourists with a high-quality and sustainable tourism concept, which is conducive to the long-term development of the tourism industry. From a social perspective, by shaping a unique brand image, scenic spots’ managers can enhance local residents’ sense of identity and pride, promoting community participation in tourism development. This integrated approach, which combines economic, cultural, and social aspects, is essential for the sustainable development of historical tourism destinations in the face of increasing competition and changing market demands.

Although social media data provide a novel perspective for assessing the brand image of historical and cultural sites, there are significant limitations. On one hand, there are demographic biases in the data, and users of different ages, genders, and geographical regions exhibit large differences in their activity and behavior patterns across platforms, making it difficult for single-platform data to represent the viewpoints of all tourists. On the other hand, the phenomenon of false interactions is common, and behaviors such as brushing comments and buying likes result in distorted feedback regarding brand image, which affects the accuracy of the evaluation. Therefore, more considerations need to be added in the application.

5. Conclusions and Future Research

In the post-pandemic era, tourism has gradually recovered, and historical and cultural scenic spots have become popular destinations for domestic tourists, but they are also caught in the predicament of serious homogenization and fierce competition. In response to this situation, the formation of a unique brand image with the help of social media has become an important way to enhance the competitiveness of scenic spots, as recognized by the industry and in academia. However, most current studies are conducted from the perspective of branding, often ignoring the important value of brand equity theory in the evaluation and practical application of the brand image of historical and cultural scenic spots. This study aims to fill this gap by constructing a set of innovative frameworks for evaluating the brand image of historical and cultural scenic spots from the perspective of social media. The framework takes brand awareness, satisfaction, and reputation as core dimensions, integrates brand equity theory, and builds a theoretical foundation for the scenic spot to scientifically shape its brand image. At the same time, the study constructs a multi-dimensional index system and applies the fuzzy Best–Worst method and TOPSIS hybrid evaluation model to quantitatively and qualitatively evaluate six historical and cultural scenic spots in Xi’an, China, which effectively verifies the validity and applicability of the evaluation framework.

From the point of view of practical application, the results of this research are of great significance to the brand building of historical and cultural scenic spots. Taking the scenic spots participating in this evaluation as examples, for those scenic spots with high brand awareness but needing to improve satisfaction, the focus should be on optimizing service details and perfecting hardware facilities so as to improve tourists’ experience and to realize the all-round improvement of brand image. For scenic spots with low reputation, it is necessary to deeply excavate the cultural associations of the place, actively carry out cultural activities, and reshape the brand in tourists’ minds. In terms of academic value, this study enriches theories and methods in the field of brand image evaluation and provides a new perspective and model for subsequent research. Its innovation lies in the close integration of social media and brand equity theory, which overcomes the limitations of traditional research in this area.

Looking ahead, the continuous development of social media will bring more opportunities and challenges to the brand image formation of historical and cultural scenic spots, and scenic spots’ managers must attach great importance to the role of social media. The evaluation framework and indicator system proposed in this study are not only applicable to historical and cultural scenic spots; they can also provide useful references for the brand image evaluation of other types of scenic spots. In future studies, the scope can be further expanded to include more scenic spots of different types and geographical regions, so as to reveal the laws and trends of brand image formation in a more comprehensive way.

The methodology used in this study has some limitations. In the process of determining the weights of indicators using the fuzzy best–worst method (fuzzy BWM), the subjective judgment of experts plays a key role. Due to the different knowledge backgrounds, practical experiences, and personal preferences of different experts, their judgments on the importance of indicators may differ significantly, which may further affect the accuracy of weight determination. To improve this situation, the introduction of a more diverse evaluation language for comprehensively and accurately measuring expert opinions can be considered, thus reducing the bias caused by subjective factors. In addition, the method selected in this paper also has limitations in application, and, in the future, we should actively explore the application of other sorting methods in the evaluation of scenic area brand image, in-depth comparison of the advantages and disadvantages of different methods, and the sorting strategy that is most suitable for research in this field, so as to provide a richer and more accurate theoretical and technological support for the evaluation and improvement of scenic area brand image. Additionally, future research can further investigate the relative importance of brand trust and satisfaction as the core dimensions of brand equity and establish a dynamic brand equity evaluation model based on social media, as well as exploring the various effects of different dimensions on the brand building of historical and cultural scenic spots. Finally, future research will further deepen the research on the relationship between brand equity theory and destination branding, and explore the innovative strategies of different types of destination branding through interdisciplinary integration and the application of new technologies, so as to better support the sustainable development of the tourism industry.