Destination Reputation Management: The Divergent Role of Tourists’ Word of Mouth in Urban China

Abstract

This study reveals the influence of word of mouth on destination reputation from the perspective of tourists’ reputation judgment and explores the differentiating effect of judgment dimensions on the degree of consistency between word of mouth and reputation based on multinomial logistic regression analysis, aiming to advance the theoretical exploration of the complex relationship between word of mouth and reputation. This study finds that (1) tourists weigh word-of-mouth information that is identical or different from their views to make reputation judgments, and destination reputation is a systematic emergent outcome of word-of-mouth information that is recursively weighed and judged by tourists in the process of dissemination. (2) Tourists judge the reputation of a destination based on different dimensions, including scenic spots, local food, history and culture, natural environment, social atmosphere, activities and events, and facilities and services. (3) Tourists’ reputation judgment dimensions have a differentiating effect on the influence of word of mouth on destination reputation; that is, there are interpersonal differences in the influence of word of mouth information on destination reputation by tourists based on different dimensions. This paper provides a new perspective and approach to the study of the relationship between word of mouth and destination reputation, which can contribute to destination reputation management and marketing efforts.

1. Introduction

Destination reputation management is one of the keys to sustainable destination brand development. A destination with a good reputation can maximize its attractiveness to tourists and expand its economic benefits, which will be conducive to the healthy development of the destination brand [1]. Due to shared memories and information communication among tourists, managing the reputation of a destination is an essential operational and strategic activity [2,3]. However, the relationship between word of mouth and reputation has always been an unresolved issue in theory and practice, with a complex process from individual judgment to collective emergence, and influenced by many factors. Most of the existing destination management practices use marketing tools such as filming destination promotional videos, selecting spokespersons, and placing advertisements to build a good destination reputation [4,5] to enhance the competitiveness of the destination [6], attract external investment [7] and maintain tourist loyalty [8,9]. The impact of user-generated content, especially word of mouth, on the destination’s reputation, cannot be ignored [10]. Therefore, it is urgent to reveal the important role of word of mouth in the evaluation of tourists’ reputation, to explore which factors and in what ways influence the role of word of mouth in the evaluation of tourists’ destination reputation, to promote theoretical research on the complex mechanism of the interaction between word of mouth and destination reputation, and to provide practical references for destination reputation management and marketing.

Destination reputation sometimes overlaps with destination image while maintaining certain differences [11]. Destination image can be defined as the overall impression that the traveler has of the destination or the traveler’s mental picture of the destination [12]. It is most important that the destination image formation starts before visiting the destination and is further developed through and after visiting [13]. On the contrary, the destination reputation is usually formed by the public and stakeholders based on identity, brand, image, and information obtained from different sources. This means that destination reputation is influenced more by external information, whether marketing information or word-of-mouth information.

Word of mouth is verbal, person-to-person communication about a brand, product, or service between a recipient and a noncommercial communicator [14]. Research has focused on the content of information formed during word-of-mouth communication, i.e., the impact of word-of-mouth information on tourists’ decision-making, perceived processing, and brand evaluation [15,16,17]. Compared to marketing messages consciously placed by destination management organizations, word-of-mouth information is derived from tourists’ existing travel experiences and is more readily accepted by other tourists or the public [18]. However, it is also difficult to manage and respond to because of its high degree of uncertainty [19,20]. Although the importance of word of mouth in reputation management has been recognized by both academia and industry, much of the research has been conducted on the subject of tourists’ experiences [21,22]. The importance of word of mouth in reputation management has received attention from academics and the industry, but most of the existing research has been conducted at the group level of tourists [23]. However, it has not been possible to answer the question of the mechanism by which the complex word-of-mouth information at the individual tourist level affects the reputation of a destination. In particular, when tourists receive word-of-mouth information that contradicts their perceptions of a destination’s reputation, opinions from others may not only serve as new information but also as a form of peer pressure to influence tourists’ judgments of a destination’s reputation [24]. Therefore, word-of-mouth information has an important role to play in tourists’ perceptions of a destination’s reputation.

Reputation is a multilevel concept that can be used to describe countries, regions, companies, and individuals [25]. In the field of marketing, reputation is a set of values attributed to a company that are inferred from its past behavior [26]. It is an intangible asset that has been developed over time and is validated by the market [27]. Most of the studies on destination reputation follow the definition of corporate reputation. For example, Marinao Artigas et al. (2015) define tourism destination reputation as “the aggregation of consumers’ perceived representations and evaluations of the past behavior and performance of a tourism destination over time” [28]. Darwish and Burns [11], using the Delphi method based on empirical research, define destination reputation as:

The public and stakeholders’ evaluation of the destination formed from their own experience of the place and/or collected from a variety of sources, including word of mouth, print, digital, and broadcast media. (p. 156)

in other words, destination reputation is an assessment of the holistic nature of a destination based on both direct personal experience and information collection, including word of mouth. Although studies continue to recognize the strong link between word of mouth and reputation, the relationship between the two remains underexplored in the existing research.

Much of the early research on the relationship between word of mouth and reputation emerged in the field of marketing, where studies explored how companies could gain more positive word of mouth and benefit from reputation building. Subsequent studies have continued to identify the positive contribution of word of mouth to corporate reputation [29,30]. This has revealed the impact of users’ perceived reputation on satisfaction and loyalty through the acquisition of word-of-mouth information [31,32]. It has also been argued that word of mouth and reputation are causal. When a company has a high reputation, users are more likely to interact and post positive word-of-mouth messages [33]. In recent years, with the development of social media platforms, more and more studies have confirmed the impact of word of mouth on reputation. Studies have classified word of mouth into positive word of mouth (PWOM) and negative word of mouth (NWOM), both of which have been found to significantly influence corporate reputation [34]. It has also been argued that reputation is very fragile and is more vulnerable to negative word of mouth [35]. Shinta Rahmani et al. (2021) experimentally explored the attitudes and behavioral intentions of users in contradictory scenarios of good reputation and negative word-of-mouth combinations and found that a good reputation can reduce the bad effects of negative word of mouth [36]. In addition, it has also been found that the effect of word of mouth on reputation is influenced by culture [37] and emotional experience [38]. In the tourism field, the contribution of word of mouth to destination reputation has been rarely studied. Some studies have equated word-of-mouth information collections about specific destinations in a particular information channel with reputation, identifying and assessing destination reputation through data analysis of online reviews [39,40]. However, not all word-of-mouth information can be trusted and adopted by tourists in the face of complex and heterogeneous user-generated content and opinions [41]. Some studies have taken tourists as their subjects and concluded that familiarity plays an important role in the process of tourists’ assessment of destination reputation [28]. The familiarity of tourists with a destination can be established through the word-of-mouth information search process [42,43]. Good word of mouth not only creates a positive image of a destination but also raises awareness of the destination among those unfamiliar with it [44]. Thus, it remains to be explored which word-of-mouth information there is and how it contributes to the destination reputation assessment process for tourists.

In summary, the impact of word-of-mouth information on destination reputation has received attention from both academia and industry, but how word-of-mouth information affects tourists’ reputation assessment is still an ambiguous issue. Especially when both positive and negative word-of-mouth information are present, how tourists judge a destination’s reputation is an unresolved question.

First, we identify the complex situations in which tourists judge the reputation of a destination and reveal the dimensions of destination reputation and its association with word-of-mouth information. Then, we use reputation word-of-mouth consistency to characterize the extent to which tourists are influenced by word-of-mouth information, and explore the differential effects of word-of-mouth information on tourists’ reputation of a destination in different contexts. Finally, a multinomial logistic regression model is constructed to reveal the factors influencing the differential effects of word-of-mouth information on tourists’ destination reputation judgments.

2. Data Sources and Research Methods

2.1. Data Sources

In order to explore the impact of word-of-mouth information on tourists’ evaluation of destination reputation, researchers first explored the consistency of word-of-mouth information and reputation evaluation dimensions and then revealed the influencing factors that affect the consistency of word-of-mouth information and reputation evaluation. This study thus proposes these three hypotheses:

Hypothesis 1. 

Tourists evaluate destination reputation based on different dimensions.

Hypothesis 2. 

There are inconsistencies in the reputation and WOM information of the destination.

Hypothesis 3. 

There are factors that affect the effect of word-of-mouth information on tourists’ reputation judgement.

Researchers used a questionnaire to collect data for the study. Taking into account the impact of differences in socioeconomic levels in different regions, researchers distributed questionnaires in typical cities representing the seven geographic regions of China to make the survey sample representative. The cities representing north China, east China, central China, northwest China, northeast China, southwest China and south China are Beijing, Shanghai, Wuhan, Xi’an, Changchun, Kunming, and Guangzhou, respectively. The survey period was from November 2018 to January 2020, when the distribution was unfortunately stopped with the onset of the COVID-19 outbreak. Even so, a total of 1760 questionnaires were distributed, and 1240 valid questionnaires were collected, with a response rate of 70.45%. Researchers distributed questionnaires to visitors and citizens at travel hubs, such as airports and high-speed rail stations. After confirming that respondents had had sufficient time to check in, a survey was conducted through a person-to-person direct interview. There was no opinion lead in the interview. The sample characteristics are shown in

Table 1. Sample characteristics.

Variables	Indicators	Percentage	Variables	Indicators	Percentage
Gender	Male	51.5	Career	Business unit staff	12.2
	Women	46.9		Teachers	6.8
	Not filled	1.6		Students	20.3
Marital Status	Married	49.1		Civil Service	3.3
	Unmarried	48.1		Corporate personnel	28.1
	Not filled	2.8		Private company owner	4.4
Age	Under 18 years old	2.2		Service industry personnel	3.9
	18–27	43.2		Freelancer	10.7
	28–37	30.1		Retirees	2.3
	38–47	12.7		Other	5.4
	48–57	6.6		Not filled	2.7
	58–67	2.0	Monthly income	Less than 1500	3.0
	Over 67 years old	1.3		1500–4500	19.0
	Not filled	1.9		4500–9000	34.1
Education level	Junior high school and below	4.1		9000–35,000	19.7
	High School	12.1		35,000–55,000	1.6
	University	66.9		Greater than 55,000	1.5
	Graduate Students	15.0		No income	15.8
	Not filled	1.9		Not filled	5.3

.

In this study, the textual content in positive/negative reputation judgment reasons and positive/negative word-of-mouth messages were dimensionally classified by three-level manual coding. The manual coding followed a bottom-up refinement logic, and the coding results were consistently endorsed by the three authors. Based on the premise hypothesis of this study that the degree of consistency in judging bases when destination reputation and word of mouth are the same or different is influenced differently by factors from within and outside the individual, a multinomial logistic regression approach was used to explore the influence of multiple factors on the dependent variable at multiple value levels. Logistic regression models require few assumptions about the variables and ultimately provide results in the form of probability of event occurrence. The model parameters are estimated using the maximum likelihood estimation method, which provides the results in the form of the probability of occurrence of an event relative to the reference event [45]. The model parameters are estimated by maximum likelihood estimation. Let the degree of consistency between reputation judgments and word-of-mouth information be $\mathrm{Y}=\left({\mathrm{y}}_1,{\mathrm{y}}_2,\dots \dots ,{\mathrm{y}}_{\mathrm{n}}\right)$, the influence factor $\mathrm{X}=\left({\mathrm{x}}_1,{\mathrm{x}}_2,\dots \dots ,{\mathrm{x}}_{\mathrm{n}}\right)$, P be the response probability of the model, and the multinomial logistic regression model of the response is as follows:

$${\mathrm{y}}_{\mathrm{i}}=\ln \left(\frac{{\mathrm{P}}_1}{{\mathrm{P}}_{\mathrm{m}}}\right)={\mathsf{\beta }}_0+\sum _{\mathrm{j}=\mathrm{i}}^{\mathrm{n}}{\mathsf{\beta }}_{\mathrm{j}}{\mathrm{X}}_{\mathrm{j}}$$

(1)

where ${\mathrm{P}}_1$ is the event ${\mathrm{y}}_{\mathrm{i}}$ the probability of occurrence of ($1\le \mathrm{i}<\mathrm{m}$), $\mathrm{a}$ is the reference event, ${\mathrm{y}}_{\mathrm{m}}$ the probability of occurrence, and ${\mathrm{P}}_1+{\mathrm{p}}_2+\dots +{\mathrm{p}}_{\mathrm{m}}=1$. In addition, when ${\mathrm{X}}_{\mathrm{j}}$ is a non-control, it takes the value of 1, and when it is a control, it takes the value of 0. The study was analyzed by multinomial logistic regression using SPSS 23.0.

2.2. Research Results and Analysis

2.2.1. Tourist Destination Reputation Judgment Dimensions and Disagreements

There are differences in the tourist destinations with good/bad reputations as judged by tourists based on their own experiences, thus leading to disagreement in the reputation of tourist destinations. Of the 153 destination cities or regions mentioned by tourists, 59 of them appear in both the positive and the negative reputation lists, and 47 destinations appear on only one of the lists. Destination reputation (Gi) and poor reputation (Bi) were calculated based on the number of mentions of the cities in positive or negative tourism destinations, using the following formula:

$${\mathrm{G}}_{\mathrm{i}}=\frac{{\mathrm{G}}_{{\mathrm{m}}_{\mathrm{i}}}}{\mathrm{M}}$$

(2)

$${\mathrm{B}}_{\mathrm{i}}=\frac{{\mathrm{B}}_{{\mathrm{m}}_{\mathrm{i}}}}{\mathrm{M}}$$

(3)

where $\mathrm{M}$ denotes the total number of tourists who participated in the destination reputation judgment, which is 1240 in this study, ${\mathrm{G}}_{{\mathrm{m}}_{\mathrm{i}}}$ is the positive reputation mention rate, i.e., the place mentioned by tourists, $\mathrm{i}$ appearing as a positive reputation destination is the negative reputation mention rate, i.e., the number of times the place mentioned by tourists appear among the negative reputation destinations. The reputation of the 31 tourist destinations ranked in the top 20% of total mentions (the sum of all positive and negative reputation mentions) were counted (Figure 1). We found a clear divergence in the reputation of several high-profile tourist destinations. Taking Beijing as an example, a total of 152 tourists judged Beijing’s destination reputation, with the ratio of positive reputation judgments to negative reputation judgments close to 6:4, producing a great divergence in judgments. In contrast, Lijiang’s destination reputation was mainly judged negatively, and Chengdu’s destination reputation was mainly judged positively, both having less divergence in judgments.

The disagreement of tourist destination reputation judgments is also manifested in the reputation judgment dimensions. The dimensional division of the reasons for positive and negative reputation judgments by tourists was conducted by means of three-level manual coding. Seven dimensions were extracted: scenic spots, local food and drink, history and culture, natural environment, social atmosphere, activities and events, and facilities and services, and the proportion of terms used for each dimension was calculated (

Table 2. Examples of words and number ratios for the dimension of destination reputation judgment.

Three-Level Coding	Secondary Codes	Level 1 Code Example	Positive Judgment Ratio	Negative Judgment Ratio
Scenic spots	Number of attractions	Many tourist attractions, attractions with characteristics, scenic spots with reasonable design Too few attractions, poor attractions, over development of scenic spots	4.62%	3.17%
	Quality of attractions
	Management level
Local Food	Food Culture	Good food, dining features, fresh ingredients and snacks Monotonous diet, poor food quality, food not to taste special dishes, unique food culture, unhygienic food, poor sterilization over-promotion, small selectivity	7.88%	1.95%
	Flavor Ingredients
	Sanitary conditions
	Price Marketing
History and Culture	Ethnic customs	Cultural heritage, cultural characteristics, ethnic culture, long history, no cultural flavor, lack of local culture	9.33%	2.15%
	Social atmosphere
Natural Environment	Historical heritage	Good natural scenery, good climate, and green trees Severe haze, poor water quality, unsuitable climate, stifling heat	31.77%	14.31%
	Climatic conditions
Social atmosphere	Landscaping	Friendly citizens, high-quality, open and tolerant, and welcoming residents Rip-off, xenophobic thinking, poor quality, feeling unsafe	30.86%	48.00%
	City Folkways
Activity Events	Business atmosphere	Activities with special features, recreational programs and entertainment venues Inconvenient self-drive tours, homogenization of activities, activities without highlights	4.85%	13.18%
	Leisure activities
Facility Services	Consumer Price	Good infrastructure, many direct flights, good city infrastructure Traffic congestion, backward facilities, poor accommodation, pollution	10.69%	17.24%
	Supporting facilities

). It was found that there were differences in the number of descriptive words for each dimension between the tourists making positive reputation judgments and when they made negative destination reputation judgments. The social climate dimension was an important dimension for tourists’ judgment in both positive and negative reputation judgments, with more than 30% of the lexical items concerning the social climate of the destination. In addition, the natural environment dimension was more important in the positive than the negative reputation judgments of tourist destinations, while the infrastructure dimension and the activity event dimension were more important in the negative than the positive reputation judgments of tourist destinations. In other words, the disagreement in tourist destination reputation judgments is not only over the outcome of reputation judgments, but it also concerns the dimensions of reputation judgments. In short, there are differences in the importance of the dimensions in the positive and negative reputation judgments of the destination by tourists.

2.2.2. Consistency between Tourists’ Destination Reputation Judgments and Word of Mouth

Tourists judge destination reputation by weighing the differences in word-of-mouth information that agrees with or differs from their own views. The results of the questionnaire show that 89.86% of the respondents filled in at least one positive word- of-mouth message from others when they thought a destination had a positive reputation, i.e., the same word-of-mouth message. On the other hand, 53.98% of the respondents filled in at least one negative word-of-mouth message from others, i.e., a different word-of-mouth opinion. When respondents perceived a destination as having a negative reputation, 79.85% of respondents filled in at least one negative word-of-mouth message from others, i.e., the same word-of-mouth message. However, only 64.49% of respondents filled in at least one positive word-of-mouth message from others, i.e., a different word-of-mouth opinion. In other words, tourists’ destination reputation judgments are more often influenced by the same in each case, the respondent followed word of mouth, but word-of-mouth information that is different from their own opinion still entered into the weighing process of their personal word-of-mouth judgments. This phenomenon was more pronounced in negative reputation judgments.

In addition, the dimensional consistency of reputation judgment and word-of-mouth information also affects the results of tourists’ reputation judgment. Based on the dimensions of tourists’ reputation judgment, the dimensional coding of word-of-mouth information was conducted, and the ratio of the number of mentions of each dimension to the total number of mentions was calculated to draw a radar plot of the ratio of reputation judgment to word-of-mouth information (Figure 2). The positive reputation judgment dimensions are in high agreement with the same word of mouth, especially the information of the facility service dimension in the positive word of mouth further supports the tourists’ judgment of the positive reputation of the destination. At this point, since the facility service and event dimensions are not important dimensions in tourists’ reputation judgment, the dissimilar word of mouth focusing on them has less influence on the positive reputation judgment. The negative reputation judgment dimension has a higher degree of agreement with the same word of mouth and a lower degree of agreement with dissimilar word of mouth. In other words, the opinions from others further corroborate the negative judgments of tourists about the destination, and, despite providing a lot of information about the natural environment, history, and culture that are attractive for tourism, it is still not enough to change the negative reputation judgments of tourists about the destination.

The degree of consistency between the same/different reputation judgment basis and the word of mouth of different tourists was counted, i.e., the number of words that belong to the same dimension of reputation judgment basis and word of mouth, forming four indicators of consistency of the same word of mouth and consistency of different word of mouth in positive reputation judgment, and consistency of the same word of mouth and consistency of different word of mouth in negative reputation judgment, respectively. Since the respondents filled in no more than three-word phrases as the reasons for their reputation judgments, the consistency indicators were all given a range of 0–3. The mean and standard deviation of the four consistency indicators were counted and analyzed by ANOVA (

Table 3. The degree of consistency between reputation and word of mouth in different combinations.

	Positive Reputation		Negative Reputation
	Average Value	Standard Deviation	Average Value	Standard Deviation
Same word-of-mouth consistency	0.81	0.93	1.03	1.00
Different word-of-mouth consistency	0.45	0.79	0.35	0.68
Total	0.63	0.88	0.69	0.92

), and it was found that both positive or negative reputation judgments (F = 6.546, p = 0.011 < 0.05) and similar or dissimilar word of mouth (F = 383.798, p = 0.000 < 0.05) had an effect on the degree of consistency, and there was an interaction between the two (F = 36.352, p = 0.000 < 0.05). The results indicate that tourists tend to adopt word-of-mouth information that shares their views. In particular, negative word-of-mouth information not only influenced tourists’ negative reputation judgments as identical word-of-mouth information but also influenced tourists’ positive reputation judgments relatively more as dissimilar word-of-mouth information.

The same word-of-mouth consistency is higher than dissimilar word-of-mouth consistency, while word-of-mouth information that is contrary to the tourists’ opinion, although obtained by the tourist, does not become a key basis for their destination reputation judgments. However, dissimilar word-of-mouth consistency is higher in positive reputation judgments than in negative reputation judgments, i.e., tourists weigh negative word-of-mouth information more heavily in making positive destination reputation judgments. At the same time, tourists are more likely to adopt word-of-mouth information that shares their views when making negative reputation judgments than positive ones. In other words, compared to positive word-of-mouth information, negative word-of-mouth information not only motivates tourists to make negative reputation judgments but also influences them to make positive reputation judgments about the destination.

As a result, divergent destination reputations influence others’ reputation judgments through word-of-mouth communication. Tourists weigh the inconsistent word-of-mouth information and judge the reputation of a destination on the basis of judgmental dimensions with different importance. Destination reputation is the result of a recursive system of personal judgment and word-of-mouth transmission among individuals.

2.3. Factors Influencing the Consistency of Destination Reputation Judgments and Word of Mouth

2.3.1. Variable Selection and Treatment

Based on the existing studies and the scenario of this study, the multinomial logistic regression model of the influence of different factors on the degree of consistency between reputation and word of mouth was constructed (

Table 4. Variable definitions.

Type	Variables	Assignment	Type	Variables	Assignment
Dependent variable	Reputation and reputation consistency degree	High = 1	Personal Characteristics	Gender	Male = 1
		Medium = 2			Female = 2
		Low = 3		Marital Status	Married = 1
Reputation Judgment Dimension	Local Food	Yes = 1			Unmarried = 2
		None = 2		Age	<30 years old = 1
	History and Culture	Yes = 1			30–50 years old = 2
		None = 2			>50 years old = 3
	Natural Environment	Yes = 1			Two or more times = 1
		None = 2	Number of visits		Once = 2
	Social atmosphere	Yes = 1			No visit = 2
		None = 2	Length of stay		Greater than 7 days = 1
	Activity Events	Yes = 1			Less than 7 days = 2
		None = 2			Did not stay = 3
	Facility Services	Yes = 1	Physical Distance		<1000 km = 1
		None = 2			1000–2000 km = 2
	Scenic spots	Yes = 1			>2000 km = 3
		None = 2	Do you have any friends or relatives		Yes = 1
Word of mouth characteristics	Reference to others	All references = 1			None = 2
		Partial reference = 2
		No reference = 3
	Number of WOM	More = 1
		Less = 2

).

The dependent variable of the model is the consistency degree of reputation and word of mouth, which is counted by the number of consistent dimensions of word of mouth and reputation. A score of zero is determined as low consistency, one to two as medium consistency, and three and above is classified as high consistency.

The independent variables of this model are reputation judgment dimension, word- of-mouth characteristics, personal characteristics, number of visits, length of stay, physical distance, friends and relatives. The dimensions of reputation judgment were transformed into six dummy variables, i.e., when a respondent mentioned the word of a dimension, the dimension took the value of “yes” and vice versa. Word-of-mouth characteristics refer to the amount and credibility of word-of-mouth information. Personal characteristics include gender, marital status, and age. The number of visits refers to whether the respondent has visited the destination he or she filled in. The length of stay refers to the length of time the respondent stayed at the destination he or she indicated. The presence or absence of friends and relatives refers to whether the respondent has friends and relatives living permanently in the destination they filled in. Physical distance is the spherical distance between the city (destination) filled in by the respondent and his or her permanent residence (source) calculated by ArcGIS.

Since the multiscore logistic regression model could not allow for missing values, some of the incomplete questionnaire data were deleted, and finally, 1626 sample data were obtained for model construction. Among them, 789 sample data about positive reputation destinations were used to construct the positive reputation consistency model; 837 sample data about negative reputation destinations were used to construct the negative reputation consistency model. All sample data were used to construct the overall consistency model.

2.3.2. Model Fit Test

The overall model fit test was a likelihood ratio test of whether all the biased regression coefficients of the independent variables in the model were zero (

Table 5. Model likelihood ratio test.

		Overall Consistency		Positive Reputation Consistency		Negative Reputation Consistency
Type	Factor	Likelihood Value	Cardinality (Significance)	Likelihood Value	Cardinality (Significance)	Likelihood Value	Cardinality (Significance)
	intercept distance	2838.19	0	1312.32	0	1477.97	0
Reputation Dimension	Local Food	2842.82	4.63 *(0.099)	1321.96	9.64 ** (0.008)	1479.3	1.34 (0.512)
	History and Culture	2844.55	6.36 ** (0.042)	1324.54	12.22 *** (0.002)	1480.66	2.70 (0.26)
	Natural Environment	2905.35	67.15 *** (0.000)	1350.81	38.49 *** (0.000)	1532.05	54.09 *** (0.000)
	Social atmosphere	3046.15	207.95 *** (0.000)	1445.1	132.78 *** (0.000)	1572.72	94.76 *** (0.000)
	Activity Events	2875.98	37.78 *** (0.000)	1338.52	26.20 *** (0.000)	1488.19	10.22 *** (0.006)
	Facility Services	2905.07	66.88 *** (0.000)	1349.12	36.80 *** (0.000)	1515.34	37.37 *** (0.000)
	Scenic spots	2841.91	3.72 (0.156)	1322.48	10.16 *** (0.006)	1484.81	6.84 ** (0.033)
Word of mouth characteristics	Number of Word of Mouth	2838.77	0.57 (0.751)	1312.4	0.08 (0.961)	1481.02	3.05 (0.218)
	Reference to others	2843.11	4.92 (0.296)	1318.34	6.02 (0.198)	1482.78	4.81 (0.308)
Personal Characteristics	Gender	2842.49	4.30 (0.117)	1314.15	1.83 (0.401)	1482.60	4.63 *(0.099)
	Married and unmarried	2838.86	0.67 (0.715)	1313.63	1.31 (0.519)	1478.85	0.88 (0.645)
	Age	2844.55	6.35 (0.174)	1318.58	6.25 (0.181)	1479.75	1.78 (0.777)
Other factors	Number of visits	2842.21	4.02 (0.134)	1319.56	7.24 (0.027)	1478.26	0.29 (0.865)
	Length of stay	2843.39	5.20 * (0.074)	1315.58	3.25 (0.197)	1479.19	1.23 (0.542)
	Distance	2848.5	10.31 ** (0.036)	1317.88	5.55 (0.235)	1483.77	5.80 (0.215)
	Do you have any friends or relatives	2839.87	1.68 (0.432)	1313.38	1.06 (0.588)	1478.35	0.39 (0.824)

Note: *** represents p < 0.001; ** represents p < 0.05; * represents p < 0.1.

). The fit results showed that the two-fold log likelihood value of the overall consistency model decreased from 3160.304 to 2811.032 with a significance level of p = 0.000; the twofold log likelihood value of the positive reputation consistency model decreased from 1559.787 to 1306.856 with a significance level of p = 0.000; and the two-fold log likelihood value of the negative reputation consistency model decreased from 1641.896 to 1460.027 with a significance level of p = 0.000. This indicates that the null hypothesis that all coefficients of the independent variables are zero can be rejected, and the model fits better, regardless of whether tourists make positive or negative reputation judgments of the destination.

However, there are differences in the role of different influencing factors in tourists’ positive and negative reputation judgments. Overall, the dimensions by which tourists judge reputation are important factors influencing the consistency of their reputation through word of mouth. Tourists are more likely to refer to others’ opinions when judging dimensions such as social atmosphere, natural environment, facilities and services, and activity events, regardless of whether they are making a positive or negative reputation judgment. The influence of the local food and historical culture dimensions on the consistency of negative reputation was not significant. This may be due to the highly individualized eating habits or travel preferences of tourists, the importance of personal experiences in dimensions such as local food and drink over others’ opinions and the difficulty for tourists to easily identify and internalize others’ negative opinions. The effect of word-of-mouth characteristics on tourist reputation judgments and word-of-mouth consistency was not significant, while the effects of factors such as length of stay and distance between two places reached significant levels. This further indicates that the content of word-of-mouth information and tourists’ travel experiences have a more important role in their destination reputation judgments than the amount of word-of-mouth information tourists obtain. Among the personal traits of tourists, only the gender factor reached a significant level of influence in the consistency of negative reputation.

2.3.3. Results of Parameter Estimation

Based on the parameter estimation results of the three models (

Table 6. Model parameter estimation results.

		Overall Consistency		Positive Reputation Consistency		Negative Reputation Consistency
		High (Control = Low)	Medium (Control = Low)	High (Control = Low)	Medium (Control = Low)	High (Control = Low)	Medium (Control = Low)
intercept distance		−4.36 ***	−1.44 ***	−2.29 ***	−2.29 ***	−4.78 ***	−1.28 ***
Consider local food	Control = None	−0.56 *	0	−0.76 **	0.28	0.42	−0.16
Consider the history and culture	Control = None	−0.72 **	−0.08	−1.19 ***	0.09	0.98	0.64
Consider the natural environment	Control = None	1.25 ***	0.91 ***	0.84 ***	1.21 ***	2.01 ***	1.12 ***
Consider the social atmosphere	Control = None	2.56 ***	1.51 ***	2.55 ***	1.94 ***	2.76 ***	1.17 ***
Consider the event	Control = None	0.98 ***	0.95 ***	1.18 ***	1.44 ***	0.75 ***	0.57 ***
Consider facility services	Control = None	1.42 ***	1.01 ***	1 ***	1.32 ***	1.64 ***	0.74 ***
Consider scenic spots	Control = None	0.3	0.42 *	−0.52	0.7 **	1.24 ***	0.45
High number of word-of-mouth	Contrast = less	0.04	−0.07	0.11	0.02	0.41 *	0.05
All references to others	Contrast = no reference	−0.03	0.02	−0.22	−0.35	0.26	0.31
Partial reference to others	Contrast = no reference	0.33 *	0.06	0.39	0.02	0.36	0.04
Multiple Visits	Comparison = No visit	0.25	−0.01	−0.24	−0.14	0.68 **	0.3
One visit	Comparison = No visit	0.08	0.15	−0.74 *	0.13	0.5 *	0.24
Long-term stay	Contrast = No stay	0.53 **	0.19	0.59 *	0.34	0.19	−0.12
Proximity of two locations	Contrast = Far	−0.03	0.18	−0.39	0.24	0.06	0.07
Medium distance between the two locations	Contrast = Far	−0.48 **	−0.09	−0.55 *	−0.03	−0.5 *	−0.14
Have a friend or relative	Control = None	0.02	−0.16	0.22	−0.04	−0.08	−0.15
Male	Control = Female	−0.23	−0.25 **	0.2	−0.12	−0.48 **	−0.29 *
Married	Control = Unmarried	−0.01	−0.08	0.25	−0.12	−0.22	−0.01
Youth groups	Control = Elderly	1.16 ***	0.34	1.84 ***	0.28	0.88 *	0.52
Middle-aged group	Control = Elderly	0.86 ***	0.1	1.24 **	0	0.73 *	0.27

Note: *** represents p < 0.001; ** represents p < 0.05; * represents p < 0.1.

), the strength and direction of the effect of different levels of each factor on low consistency of reputation word of mouth compared to low consistency of reputation word of mouth were further explored.

The results show that the influential factors of reputation word-of-mouth consistency include reputation dimensions, length of stay, distance, and age. Tourists are affected by word-of-mouth information to different degrees when they evaluate the destination’s reputation according to different dimensions; for example, tourists are less influenced by word-of-mouth information when they judge the reputation of the destination based on local food. Meanwhile, tourists who have visited the destination two or more times were more likely to show content consistent with others’ word-of-mouth information when making negative reputation judgments, while tourists who had stayed for longer than seven days were more likely to show content consistent with others’ word-of-mouth information when making positive reputation judgments. Visitors living within a moderate distance of the destination were less likely to be influenced by word-of-mouth information when making destination reputation judgments than visitors who were residing far away from the location. Male tourists were less influenced by word-of-mouth information when making destination reputation judgments compared to female tourists. Younger and middle-aged groups were more influenced by word-of-mouth information when making destination reputation judgments compared to elderly groups.

3. Conclusions

3.1. Conclusions and Discussion

This study reflects on the role of word of mouth in the reputation judgment of tourist destinations by the degree of consistency between tourist reputation judgment and word-of-mouth information. This study provides new research ideas and methods to explore the role of word of mouth in tourism destination reputation judgment, which is useful to destination reputation management. The following three conclusions were obtained from this study:

First, destination reputation emerges from the recursive process of tourists’ weighting of judgments in the word-of-mouth communication process. This study first reveals the phenomenon that different tourists have different opinions on the reputation of the same destination. The results showed that more than 37 percent of the 151 destinations mentioned by respondents had inconsistent reputations, while the most divergent destinations included Lijiang, Dali and Sanya. The inconsistency between word-of-mouth information and tourist reputation evaluation shows that tourists do not accept word-of-mouth information in its entirety but rather the process of screening and weighing it according to their views and perspectives. This finding could explain why WOM has intensified the contingency of organizational reputation [46]. Compared to positive reputation destination judgments, tourists are more likely to be influenced by word-of-mouth information when making negative reputation destination judgments, exhibiting a higher degree of reputational word-of-mouth consistency. Existing research has identified WOM as an antecedent of reputation [47], but previous work has not looked further into how word of mouth plays a role in reputation. This study further deepens the theoretical explanation of how heterogeneous word-of-mouth information emerges as destination reputation by classifying word of mouth into identical word of mouth and dissimilar word of mouth—based on the similarities and differences between tourists’ reputation judgment results and word-of-mouth valence—and discovers the emergence process of a spiral intertwined system in which tourism destination reputation constantly generates and resolves disagreements in the process of word-of-mouth information dissemination. It has been argued that word-of-mouth validity (positive or negative word of mouth) is an important factor influencing tourists’ perception and adoption of word-of-mouth information [28]. However, the difference in tourists’ attention to each dimension of information further affects the formation of a destination’s reputation.

Second, the heterogeneity of word of mouth influence on destination reputation comes from the results of different tourists’ judgments of destinations based on different dimensions. The dimensions of tourists’ destination reputation judgment can be divided into seven dimensions: scenic spots, local food and drink, history and culture, natural environment, social atmosphere, activities and events, and facilities and services. Tourists judge destination reputation based on different dimensions, and the core dimensions differ between positive and negative reputation judgments. When tourists judge a positive reputation, they mainly rely on the social atmosphere and natural environment dimensions; when they judge a negative reputation, they mainly rely on the social atmosphere and facilities and services dimensions. WOM is widely recognized as a noncommercial source of information that has a more persuasive effect [48]. This study further found that different dimensions of word-of-mouth information have different effects on tourist reputation evaluation. Tourists are more likely to be influenced by word-of-mouth information that is consistent with their opinions when they judge the reputation of a destination. Dissimilar word-of-mouth messages, especially those that are not related to the core dimensions of tourists’ reputation judgments, have only a weak effect on destination reputation judgments. Studies of online hotel reviews also find that tourists discriminate between the credibility of extremely positive review information rather than directly trusting and adopting positive word-of-mouth information [41]. Thus, this finding is a further advancement of recent studies on the adoption of word-of-mouth information by tourists and provides a new perspective to reveal the formation of destination reputation under the intersection of word-of-mouth information and judgmental dimensions.

Third, many factors affect the role of word-of-mouth information in the evaluation of destination reputation. A recent study reveals that tie strength, valence, degree of influence, trust message quality, and source credibility of WOM have a positive impact on reputation [49]. This study focuses on the dimensions of reputation evaluation and finds that the role of word-of-mouth information is different when tourists make reputation evaluations according to different dimensions. For example, when tourists judge reputation based on local food, history and culture, and scenic spots, they focus more on personal experience and are less influenced by word-of-mouth information from others. When tourists judge the reputation of a destination based on the local atmosphere and natural scenery, word of mouth has a more important impact on the outcome of the reputation judgment because of its comprehensive and rich information sources. At the same time, tourists’ travel experience and personal factors also moderate the influence of word of mouth on a destination’s reputation to a certain extent. On the one hand, tourists’ travel experience is the process of confirming or disproving the destination’s reputation information. The more extreme positive or negative word-of-mouth information obtained by tourists before the tour will tend to become more objective and rational during the travel experience. On the other hand, as tourists age, their exposure to word-of-mouth information decreases, and female tourists are more likely to be influenced by word-of-mouth information than male tourists. It has also been found that internal information, such as information in tourists’ memory and familiarity with the destination, are important factors influencing their destination reputation judgments compared to word-of-mouth information from external sources [42]. This study further found that a number of factors influence the degree of consistency between reputation and word of mouth and may contribute to the final destination reputation judgment by influencing tourists’ adoption of word-of-mouth information. However, this finding needs to be further explored.

3.2. Limitations and Future Directions

Unlike previous studies that focused on the impact of positive or negative word-of-mouth information on destination reputation, this study focuses on the complex scenarios where word-of-mouth information is consistent or inconsistent with reputation evaluation and to find the factors that affect the evaluation of destination reputation. This approach is an exploration and innovation in research perspective and methodology. However, there are still two limitations to this study.

First, our study adopted the method of asking respondents to fill in positive reputation or negative reputation cities independently, which can better evoke the memory scenario and help respondents to fill in their true feelings accurately. However, it is undeniable that different tourist destinations differ in many aspects—such as natural landscape, history and culture, and infrastructure. Subsequently, we can explore the spatial and temporal evolution patterns and influencing factors of their destination reputation influenced by word-of-mouth information for a typical tourist destination and consider the influence of the time factor. Second, we did not pay particular attention to word-of-mouth information channels. Nowadays, digital platforms and social media have quickly become one of the most important methods of communication for individuals [50]. More and more tourists get word-of-mouth information through the Internet rather than via face-to-face communication. This study does not focus on the sources and communication channels of word-of-mouth information. Further studies can explore the role of e-WOM in reputation evaluation. Third, destination reputation management is an important work for the sustainable development of destinations, which needs the joint efforts of local communities, governments, and tourism organizations. This study explores the influencing factors of reputation evaluation from the perspective of tourists, which is helpful to optimize marketing information and respond to negative word-of-mouth information in time. Subsequent research can further explore how the destination reputation is formed under the intervention of organizational management.