The Effects of Motivation, Destination Image and Satisfaction on Rural Tourism Tourists’ Willingness to Revisit

Abstract

With the diversification of tourist demand for a destinations’ supply, rural tourism destinations are facing an increasingly fierce competition environment. Creating brand value and improving tourists’ willingness to revisit has become an inevitable strategic choice for rural tourism destinations. In this study, we proposed a framework of “tourism motivation-destination image-satisfaction-willingness to revisit” to investigate rural tourism. We investigated from the aspects of learning and entertainment motivation, novelty-seeking motivation, natural environment, cultural environment, social environment, infrastructure, and tourist satisfaction. To analyze data, a questionnaire survey was administered to 545 tourists using structural equation modeling (SEM) technology. The findings indicated that learning and entertainment motivation, natural environment, social environment, and tourist satisfaction had a direct and positive effect on tourists’ willingness to revisit. In addition, tourist satisfaction played an intermediary role between tourists’ tourism motivation and destination terrain image and their propensity to return. On this basis, some suggestions and illuminations are put forward to increase tourists’ willingness to revisit.

1. Introduction

The emergence of a Novel Coronavirus Disease, COVID-19, in 2020 has not only had a devastating effect on the global tourism and hotel business [1], but it has also created significant barriers to global economic and social development [2]. Moreover, the occurrence, prevention, and control of the epidemic are gradually altering the lifestyles and travel habits of individuals. As a result of the normalization of epidemic prevention and control, and in an effort to stimulate economic recovery, the tourism markets of various nations are being gradually opened, and relatively safer and more controllable tourism modes, such as suburban tourism, peripheral tourism, and rural tourism, are being favored, creating opportunities for the growth of rural tourism.

Originating in Europe between the middle and late 19th century, rural tourism has a history of more than a century. Initially, rural tourism was exclusively a popular pastime among the aristocracy of Britain and France [3]. China did not see an increase in rural tourism activities until the 1990s [4]. With the strong support of the state for rural tourism since the turn of the 21st century, rural tourism has become one of China’s most important tourism modes. With the increase in tourist attractions and the expansion of scale, distribution and function, rural tourism has demonstrated a new pattern of positive growth [5].

Due to the late start of rural tourism in China, the short development period, and the lack of scientific guidance on theories and methods, a number of problems have emerged during the development process, such as single and similar tourism products, shallow cultural connotation, scattered organizational forms, and disordered market competition order, among others [4]. Understanding the revisiting the behavior of rural tourism tourists can not only provide stable economic benefits and effective marketing guidance for tourist destinations [6], but also increase the popularity of scenic spots via the word-of-mouth effect of tourists, thereby attracting sustainable tourist sources and expanding potential markets for tourism zones [7]. With the intensification of market competition among various tourist destinations, the economic benefits derived from repeat visits have become more prominent [8]. Therefore, how to improve the revisit rate of tourists has attracted widespread attention in tourism academia and the tourist industry.

At present, there is a lack of literature on willingness to revisit from the perspective of rural tourism, and scholars’ research is mainly focused on the development of rural tourism [9], the dynamic mechanism of rural tourism [10], the impact of rural tourism [11] and so on. The influencing factors of rural tourism revisit intention are lack of integrated and systematic research. In research of willingness to revisit, the most studied factors include satisfaction [12], tourism motivation [13], destination image [14], etc. The research mainly focuses on the overall linear relationship between tourism motivation, destination image, satisfaction, and willingness to revisit. In the influencing mechanism of tourism motivation, destination image and willingness to revisit, there is no in-depth discussion on the mediating mechanism. Therefore, the purpose of this study is to test whether some foreign classical revisit theories are applicable to Chinese tourists and tourist destinations through case studies on the basis of theoretical research, and to strive to deduce the mechanisms and laws of connection between Chinese tourists’ tourism motivation, recreation experience and subsequent behavior. In this paper, the framework of “tourism motivation-destination image-satisfaction-willingness to revisit” is constructed, and the structural equation model is used to quantify the relationship between, destination image, satisfaction, and willingness to revisit of rural tourism tourists. Understanding and mastering these relationships can assist destination operators in formulating more effective market strategies for the revisiting market and aid scenic area planners in designing more alluring rural tourist attractions. In the long run, studying tourists’ willingness to revisit plays a certain role in the sustainable development of destinations. The research questions of this paper are as follows:

(1)

What influencing factors can improve the satisfaction of rural tourists?

(2)

What influencing factors can improve the intention of rural tourists to visit again?

(3)

What is the relationship between tourism motivation, scenic destination image, satisfaction, and willingness to revisit?

The remainder of this paper is organized as follows: Section 2 presents the theoretical review and research hypotheses, as well as the process of hypothesis development. Section 3 introduces research areas and methods, while Section 4 describes data collection and analysis. Section 5 is the model test and results. The last Section, 6, is discussion and conclusions.

2. Theoretical Review and Research Hypotheses

2.1. Concept of Willingness to Revisit

Many academics have explored the concept of tourists’ willingness to revisit. The concept of tourists’ willingness to revisit was first introduced by the research of Gyte and other scholars [15]. They discussed the willingness of British tourists to revisit Spain and concluded that the majority of travelers would continue to choose previously visited locations. Additionally, Baloglue and some other scholars [16] also further confirmed this conclusion. According to Baker and other scholars [17], the willingness to revisit is the likelihood that tourists will engage in a particular activity again. In addition, according to some academics, the willingness to revisit consists of multiple dimensions. According to Lin and others [18], the three dimensions of willingness to revisit are willingness to recommend, willingness to visit again, and willingness to resist. Cheng and other scholars believe that tourists’ willingness to revisit should be measured by two aspects: behavioral willingness and loyalty [19]. In this paper, we adopt the definition of revisiting intention given by Baker [17] and other scholars, and only study the possibility of tourists’ willingness to participate in a certain activity again, which not only highlights the subjective characteristics of tourists’ willingness to revisit, but also emphasizes the objective possibility of tourists’ revisiting.

2.2. Influencing Factors of Willingness to Revisit

The research on sustainable tourism development has always focused on the influencing factors of willingness to revisit, and the results are the most abundant. Gitelson and others believe that reducing the likelihood of unpleasant experiences, attachment to the destination, meeting and finding people with similar interests, engaging in previously unexperienced activities, and introducing others to one’s own experience are the five most important factors that encourage repeat visits [8]. According to Bigne and other scholars, the image and satisfaction with tourist destinations were the primary determinants of willingness to revisit [20]. Clark believed that trust, commitment, prior tourism experience, and satisfaction were the most influential factors in tourist loyalty [21]. Alegre et al. point out that travel experience and tourist satisfaction were the most influential determinants of a traveler’s willingness to revisit [22]. Um et al. developed a theoretical model of perceived attractiveness, perceived service value, perceived cost, satisfaction, and willingness to revisit [23], which has been widely used in subsequent research [24]. Hallmann and other scholars discovered that the image of a destination can not only directly influence tourists’ willingness to revisit, but also predict it [25]. David J. believed that the quality and satisfaction of sports tourism would influence the willingness of sports tourists to return to their destinations or engage in activities again [26]. However, there are few international studies on rural tourism’s willingness to return. In the current context of rural tourism, Penelas and other scholars employ structural equation models to analyze tourists’ behavior, motivation, and destination image, as well as to investigate the most influential variables on tourists’ satisfaction [27]. Chi and other scholars have investigated the connection between rural tourism performance, image, satisfaction, and loyalty [28]. In their research, Phillips et al. discovered that the destination image of rural areas has a direct and positive effect on tourists’ willingness to revisit [29].

Through reading a large number of documents, it has been confirmed that the most frequently cited factors of tourists’ willingness to revisit are tourism motivation [13], satisfaction [12], and the image of the tourism destination [14], among others. This paper selects the primary factors that influence tourists’ willingness to revisit, which are summarized in three parts: tourist motivation, destination image, and satisfaction, and develops a theoretical model, as depicted in Figure 1.

2.2.1. Tourism Motivation

Academics have always studied tourist motivation as one of the most important and intricate areas of tourism research. Scholars such as Dann and Lee concur with the “push-pull theory” and believe that tourism motivation consists of two “push” and “pull” factors. “Push” refers to the internal factors of tourists themselves, and “pull” refers to external factors associated with tourist destinations [30]. Therefore, based on the characteristics of rural tourism destination attributes, in this paper, “push” is understood as learning and entertainment (including relaxation and gaining new knowledge), and “pull” as novelty-seeking (including featured products, history and culture) [31].

2.2.2. Destination Image

As the tourist destination image is a highly abstract concept with the characteristics of diversity, comprehensiveness, dynamics, and relativity, there are disagreements in the measurement content of the tourist destination image. Chen & Kerstetter [32], Kim & Richardson and other scholars [33] believed that the image of a tourist destination is composed of natural scenery, infrastructure, and other elements. Krpina et al. conducted an empirical study on forest scenic spots, and found that 68% of tourists preferred natural landscapes and 53% preferred to see rare animals and plants in the process of tourism, and their preferences would affect their satisfaction with the destination and their willingness to revisit [34]. Rittichainuwat believed that the image of a tourist destination consists of natural scenery, dining and accommodation, shopping environment, tourism services and other elements [35]. Based on the above research, in this paper, we divide tourist destination image into natural environment, cultural environment, social environment, and infrastructure from the cognitive perspective, and further empirically test the relationship between specific dimensions of destination image and tourists’ willingness to revisit.

2.2.3. Tourist Satisfaction

As an important topic in the field of consumer and market research, tourist satisfaction originated from tourist loyalty, which refers to the behavior in which a customer provides a positive evaluation of a product or service after purchasing it, then recommends it to others or makes additional purchases. In the hospitality and tourism industries, the impact of satisfaction on the intention to return is currently the subject of extensive research. According to scholars such as Ross [36] and Kozak [37], understanding tourists’ satisfaction is a prerequisite for comprehending their behavioral intentions. Tak [38] and Huang et al. [39] discovered a positive correlation between tourists’ overall satisfaction and their intent to return. Studies from Vassiliadis [40] and Bayih [41] and other scholars demonstrate that when tourists are dissatisfied with a destination or its activities, their intention to return decreases substantially. There are too many indicators to study tourists’ satisfaction if in different dimensions, which is not conducive to reflecting the relationship between tourists’ satisfaction and tourists’ willingness to revisit. Therefore this paper only studies the relationship between tourists’ overall satisfaction and their willingness to revisit.

However, from the comprehensive perspective of the tourist satisfaction model and the research phenomenon of the relationship between satisfaction and revisit intention, there are few studies on the mediating mechanism of satisfaction and tourists’ willingness to revisit from the aspects of tourist motivation and destination image, etc., and the existing results are only sporadic verification of the mediating effect of a certain univariate. There is a lack of systematic research on whether tourists’ motivation and destination image will affect their satisfaction and thus their willingness to revisit.

2.3. Research Hypothesis

Based on the above discussion, the following hypotheses are proposed:

Hypothesis 1 (H1).

Tourism motivation has a significant impact on the willingness to revisit.

Hypothesis 2 (H2).

The destination image has a significant impact on the willingness to revisit.

Hypothesis 3 (H3).

Tourist satisfaction has a significant impact on the willingness to revisit.

Since tourism motivation is composed of learning and entertainment motivation and novelty-seeking motivation, hypothesis 1 can be divided into:

Hypothesis 1a (H1a).

Motivation for learning and entertainment (B1) has a significant impact on the willingness to revisit (E1).

Hypothesis 1b (H1b).

Novelty-seeking motivation (B2) has a significant impact on the willingness to revisit (E1).

Since destination image is composed of four dimensions: natural environment, cultural environment, social environment, and infrastructure, hypothesis 2 can be divided into:

Hypothesis 2a (H2a).

The natural environment has a significant impact on the willingness to revisit.

Hypothesis 2b (H2b).

The cultural Environment has a significant impact on the willingness to revisit.

Hypothesis 2c (H2c).

The social environment has a significant impact on the willingness to revisit.

Hypothesis 2d (H2d).

The infrastructure has a significant impact on willingness to revisit.

Since tourists’ satisfaction is an important mediating variable of their willingness to revisit, the following hypotheses can be put forward:

Hypothesis 3a (H3a).

Satisfaction (D1) plays an intermediary role between learning and entertainment motivation (B1) and willingness to revisit (E1).

Hypothesis 3b (H3b).

Satisfaction (D1) plays an intermediary role between novelty-seeking motivation (B2) and willingness to revisit (E1).

Hypothesis 3c (H3c).

Satisfaction (D1) plays an intermediary role between natural environment (C1) and willingness to revisit (E1).

Hypothesis 3d (H3d).

Satisfaction (D1) plays an intermediary role between cultural environment (C2) and willingness to revisit (E1).

Hypothesis 3e (H3e).

Satisfaction (D1) plays an intermediary role between social environment (C3) and willingness to revisit (E1).

Hypothesis 3f (H3f).

Satisfaction (D1) plays an intermediary role between infrastructure (C4) and revisit intention (E1).

According to the relevant existing literature and the above assumptions, the influence mechanism model of rural tourists’ willingness to revisit was constructed (Figure 1).

3. Research Areas and Methods

3.1. A Study Location

Nanjing, located in Jiangsu Province in eastern China, is one of the earliest national historical and cultural cities and a significant cradle of Chinese civilization. Jiangning District(Figure 2), located in Nanjing’s southeast, is one of the city’s eight districts and a significant national science and education center and innovation base. In recent years, Jiangning District has diligently practiced the new development concept, emphasized the development of rural tourism as an important starting point for the creation of a national tourism demonstration area in accordance with the deployment of the central and provincial governments, constructed a number of rural leisure tourism demonstration villages with high standards in accordance with the idea and concept of “promoting agriculture and enriching farmers through tourism”, and promoted the expansion of rural tourism from “a plant” to “a forest” in the process of connecting points and upgrading.

Three distinct types of Jiangning District rural area were selected for research. Su’s Ideal Village, a township companion, represents rural sightseeing and vacation tourism destinations; Shitang Farmhouse Happy Village, a leisure farm and agritourism destination; and Zhumen Family, an ancient town tourism destination(Figure 3). As popular rural tourist destinations in the Jiangning District, these villages have a rich and diverse natural environment, a folk culture distinct from that of the city, and convenient transportation, allowing them to meet the needs of outdoor travelers.

3.2. Research Method

The tourism economy also has systemic and multi-path characteristics in promoting destination eco-friendly development, which cannot be effectively solved by econometric analysis methods such as the mediating effect model. In the fields of management and psychology, the structural equation model is a mature method to reveal multivariable causality and explore the comprehensive path among variables. In recent years, the structural equation model has also been introduced into the field of economics to carry out empirical research [42]. Therefore, using structural equation parameter estimation, the model in this paper can achieve the research goal of identifying the formation mechanism of the eco-friendly development effect of the tourism economy.

4. Data Collection and Design

4.1. Data Collection

This study focuses on tourists who visit rural scenic areas in Jiangning District, Nanjing. There are two primary reasons why the willingness of these tourists was chosen as the data. First, as a result of the standardization of epidemic prevention and control, long-distance tourism and outbound tourism are subject to various restrictions, whereas natural ecology and short-distance rural tourism usher in a longer outbreak period. Second, despite the fact that an increasing number of scholars have studied rural tourism, few have analyzed it from the perspective of rural tourists’ willingness to revisit. Comparatively, studying tourists’ willingness to revisit to maintain an existing market requires less effort and yields a higher rate of return than expanding into new markets [43]. Therefore, it is crucial to investigate the factors that influence rural tourism visitors’ willingness to revisit.

Initially, using the township companion Su’s Ideal Village, Shitang Farmhouse Happy Village, and Zhumen Family in the Jiangning District of Nanjing as the destinations for distributing the questionnaire, we conducted a questionnaire survey of local tourists and obtained questionnaire data via interview and self-completion. We briefed the respondents on the purpose of the questionnaire in an effort to minimize interference with their vacation experience. If a tourist declined, we contacted the following individual. In July 2021, data were collected from three rural scenic locations. A total of 648 questionnaires were distributed, 612 were returned, and 545 of those were valid. SPSS 22.0 and AMOS23.0 were utilized for data integration.

4.2. Questionnaire Design

This research questionnaire consisted primarily of two sections. The first section contained social-demographic data, such as gender, age, income, education, and travel experience. The second section utilized a 5-point Likert scale: “1” indicated strong disagreement, “2” indicated disagreement, “3” indicated neutral, “4” indicated agreement, and “5” indicated strong agreement. The second section consisted of tourists’ tourism motivation, the destination image of scenic spots, tourists’ satisfaction, and their willingness to revisit. With reference to the interview results of relevant tourism practitioners and in conjunction with the research of scholars from various countries on revisiters, the initial questionnaire items consisted of frequently occurring key words (see

Table 1. Questionnaire design.

	Question Number	Item	Action Item	Source
Tourism Motivation	B1	Learning and Entertainment	relax and reduce work-related stress	[27]
	B2		appreciate the countryside’s distinctive natural landscapes
	B3		learn and expand knowledge of rural areas
	B4	Novelty seeking	consume local farm food with rural characteristics	[13]
	B5		experience the unique farming activities and folk festivals of the countryside	[44]
	B6		visit the unique cultural artifacts and historic structures in the countryside
Destination Image	C1	Natural Environment	a unique natural landscape style	[45]
	C2		diverse and reasonable configuration of artificial landscape plants	[34]
	C3		lovely ecological environment and abundant waterscape
	C4	Cultural Environment	highly recognizable traditional architecture	[46]
	C5		clearly marked highways and scenic locations
	C6		rich and colorful agricultural activities
	C7	Social Environment	satisfying regional specialties	[47]
	C8		positive service attitude of tourism professionals on the whole	[29]
	C9		reasonable prices overall	[48]
	C10	Infrastructure	abundant seating to offer shade and cool	[27]
	C11		reasonable and practical road layout
	C12		clean and hygienic commodes, waste receptacles, and other reasonable distribution features
Tourist Satisfaction	D1		overall, you are pleased with your experience	[38,39,40,41]
Willingness to Revisit	E1		the opportunity to revisit	[49]

).

4.3. Data Analysis

Before data analysis, we screened the data. A total of 648 questionnaires were distributed and 612 questionnaires were recovered, with a recovery rate of 93.2%. After eliminating the questionnaires that were incomplete or filled with the same answer from beginning to end, 545 valid questionnaires were issued, with an effective recovery rate of 84.1%. A two-step approach was used to analyze the data. First, a measurement model was used to evaluate the reliability and validity of the construct by testing factor loadings, Krumbach’s alpha, and composite reliability. Secondly, the hypotheses were tested to test the complex relationships between the structures, and finally, the research hypotheses were tested.

5. Model Test and Results

5.1. Social-Demographic Characteristics and Travel Information of Tourists

In this study, 545 valid data were statistically analyzed. The results are shown in

Table 2. Tourism sample analysis of revisited tourists.

Item	Classifification	Number of People	Percentage	Cumulative Percentage
Gender	Male	277	50.826	50.826
	Female	268	49.174	100.000
Age	Under 18	8	1.468	1.468
	18–30	360	66.055	67.523
	31–40	102	18.716	86.239
	41–50	58	10.642	96.881
	51–60	17	3.119	100.000
Education	Junior high school and below	24	4.404	4.404
	Senior high school (including technical secondary school and technical secondary school)	76	13.945	18.349
	Junior college	227	41.651	60.000
	Undergraduate	150	27.523	87.523
	Postgraduate and above	68	12.477	100.000
Income	Under 2000	9	1.651	1.651
	2000–5000 yuan	136	24.954	26.606
	5001– yuan	280	51.376	77.982
	More than 10,000 yuan	120	22.018	100.000
Place of residence	Nanjing local	261	47.890	47.890
	Other regions in Jiangsu Province	155	28.440	76.330
	Cities outside Jiangsu Province	129	23.670	100.000
Marital status	Unmarried	145	26.606	26.606
	Married	400	73.394	100.000
Travel experience	No	143	26.239	26.239
	Yes	402	73.761	100.000
Travel partners	Alone	86	15.780	15.780
	Family	129	23.670	39.450
	Friends	161	29.541	68.991
	College	91	16.697	85.688
	Others	78	14.312	100.000
Rural life experience	No	169	31.009	31.009
	1–2 years	144	26.422	57.431
	2–5 years	141	25.872	83.303
	More than 5 years	91	16.697	100.000
Times of Local village	Once	161	29.541	29.541
	Twice	258	47.339	76.881
	More than three times	126	23.119	100.000
Total		545	100.0	100.0

: For gender, the higher proportion of “men” was 50.83%, and the proportion of women was 49.17%. In terms of age distribution, most of the samples were “18–30 years old”, with a total of 360, accounting for 66.06%. In terms of educational background, more than 40% of the samples were “junior college”. The proportion of income “5001–10,000 yuan” was 51.38%. More than 40% of the samples chose “Nanjing local” as their choice of residence. More than 70% of the samples chose “married” for marital status. Among similar travel experiences, 73.76% of the samples chose “yes”; As for travel partners, samples chose “friends” and “family”, accounting for 50%. Only 31.01% chose “None” among the choice of whether they had rural experience or not. For the number of times visiting this scenic spot, “twice” accounts for 47.34%.

5.2. Reliability and Validity Tests

In this paper, we began by utilizing Cronbach’s Alpha reliability coefficient to examine the consistency of questionnaire variables on each test question [50]. The Cronbach’s Alpha of tourist motivation was 0.832, and the Cronbach’s Alpha of scenic spot destination image was 0.856, both of which were greater than 0.7, indicating good reliability of both scales. The Cronbach’s Alpha of each dimension was also greater than 0.7, indicating good reliability of all dimensions.

Next, the test was continued by conducting the KMO and Bartlett sphericity, and KMO was 0.796, which was greater than 0.6 and thus met the prerequisite requirements for factor analysis, allowing the data to be utilized for factor analysis research. The approximate chi-square value of the Bartlett sphericity test was 4761.068, and the p value of the Bartlett sphericity test was 0.000, indicating good validity based on the p < 0.05 threshold. The questionnaire data presented in this paper met the requirements for factor analysis.

5.3. EFA for Factors

Through factor analysis of the questionnaire data and principal component analysis, a total of 6 factors were extracted, and the characteristic root values were all greater than 1. Among them, 2 factors were tourism motivation (learning and entertainment motivation and novelty-seeking motivation), and 4 factors were destination image (natural environment, cultural environment, social environment and infrastructure). The variance explanation rates of these six factors after rotation were 13.519%, 13.022%, 12.911%, 12.532%, 12.383%, and 12.368%, respectively, and the cumulative variance explanation rate after rotation was 76.735%. Through maximum variance rotation analysis, the options with factor loading less than 0.5 were eliminated from the measurement options, and the results showed that they all met the load requirements and internal consistency reliability requirements.

5.4. CFA for Measurement Model

AMOS23.0 software was used to perform confirmatory factor analysis on the measurement options, and CMIN was 209.936, DF was 120, CMIN/DF was 1.749, GFI, AGFI, NFI, TLI, IFI, and CFI were all above 0.9, RMSEA was 0.037 less than 0.08, and SRMR was 0.028 less than 0.05. Almost all the fitting indexes were in line with the standards of general SEM research, so it can be considered that this model had a goodness of fit. The CR values of latent variables were 0.858, 0.882, 0.830, 0.827, 0.856, 0.824, all greater than 0.7, and the AVE values of average variance extraction were 0.668, 0.714, 0.620, 0.614, 0.665, 0.609, all greater than 0.5, indicating that the model had convergent validity.

5.5. Theoretical Model Construction

According to the structural equation model, various influencing factors were assumed. A hypothetical model of “tourism motivation-destination image-satisfaction-willingness to revisit” was constructed within the context of rural tourism. The literature review revealed a complex relationship between motivation for learning and entertainment (B1), novelty-seeking (B2), natural environment (C1), cultural environment (C2), social environment (C3), infrastructure (C4), satisfaction (D1), and observation-variable willingness to revisit (E1). AMOS 23.0 software (IBM Corporation; New York, USA) was used to test the theory and investigate the relationship between motivation, destination image, satisfaction, and the willingness to revisit. Figure 4 illustrates the modified model.

5.6. Hypothesis Verifification

In structural equation model verification, CMIN was 237.440, DF was 144, CMIN/DF was 1.649, GFI, AGFI, NFI, TLI, IFI, and CFI were all above 0.9, RMSEA was 0.035 less than 0.08, SRMR was 0.026 less than 0.05. Almost all the fitting indexes were in line with the standards of general SEM research, so it can be considered that this model had a good fit.

It can be seen from

Table 3. Model measurement results.

Hypothesis				Estimate	S.E.	C.R.	p	Standardized Coefficients
H3a	Satisfaction	<---	Learning and Entertainment	0.375	0.057	6.637	***	0.270
H3b	Satisfaction	<---	Novelty-seeking	0.130	0.044	2.916	0.004	0.115
H3c	Satisfaction	<---	Natural Environment	0.262	0.057	4.605	***	0.201
H3d	Satisfaction	<---	Cultural Environment	0.156	0.053	2.961	0.003	0.136
H3e	Satisfaction	<---	Social Environment	0.376	0.051	7.405	***	0.306
H3f	Satisfaction	<---	Infrastructure	0.125	0.053	2.378	0.017	0.115
H1a	Willingness to Revisit	<---	Learning and Entertainment	0.246	0.055	4.452	***	0.162
H1b	Willingness to Revisit	<---	Novelty seeking	0.120	0.042	2.846	0.004	0.097
H2a	Willingness to Revisit	<---	Natural Environment	0.208	0.055	3.801	***	0.146
H2b	Willingness to Revisit	<---	Cultural Environment	0.114	0.050	2.278	0.023	0.091
H2c	Willingness to Revisit	<---	Social Environment	0.357	0.051	7.009	***	0.265
H2d	Willingness to Revisit	<---	Infrastructure	0.164	0.050	3.284	0.001	0.137
H3	Willingness to Revisit	<---	Satisfaction	0.313	0.044	7.144	***	0.286

*** p < 0.001 (one–tailed).

that among the influences of independent variables on mediating variables, learning and entertainment motivation had a significant positive effect on tourists’ satisfaction (β = 0.270, p < 0.001), novelty-seeking motivation had a significant positive effect on tourists’ satisfaction (β = 0.115, p < 0.01), natural environment had a significant positive effect on tourist satisfaction (β = 0.201, p < 0.001), cultural environment had a significant positive effect on tourist satisfaction (β = 0.136, p < 0.01), social environment had a significant positive effect on tourist satisfaction (β = 0.306, p < 0.001), and infrastructure had a significant positive effect on tourist satisfaction (β = 0.115, p < 0.05). These influences of travel motivation on satisfaction can be listed in order from the stronger to the weaker: learning and entertainment > novelty-seeking; in terms of the effect of destination image on satisfaction, the order can be listed from the strongest to the weakest: social environment > natural environment > cultural environment > infrastructure.

Learning and entertainment motivation had a significant positive effect on tourists’ willingness to revisit (β = 0.162, p < 0.001), novelty-seeking motivation had a significant positive effect on tourists’ willingness to revisit (β = 0.097, p < 0.01), natural environment had a significant positive effect on tourists’ willingness to revisit (β = 0.146, p < 0.001), cultural environment had a significant positive effect on tourists’ willingness to revisit (β = 0.091, p < 0.05), social environment had a significant positive effect on tourists’ willingness to revisit (β = 0.265, p < 0.001), and the infrastructure had a significant positive effect on tourists’ willingness to revisit (β = 0.137, p < 0.01). Among the direct effects of travel motivation on willingness to revisit, the order from the stronger to the weaker can be listed as: learning and entertainment > novelty-seeking; in terms of the influence of destination image on tourists’ willingness to revisit, the order can be listed from the strongest to the weakest: social environment > natural environment > infrastructure > cultural environment.

The mediating variable, tourist satisfaction, had a significant positive effect on the willingness to revisit (β = 0.286, p < 0.001). The whole model explained 49.5% of tourist satisfaction, and the model explained 62.2% of the willingness to revisit.

5.7. Analysis of BOOTSTRAP Intermediary Effect

To further test whether tourist satisfaction plays an intermediary role in tourist motivation and the destination image of the scenic spot on the willingness to revisit, this paper employed the Bootstrap mediating effect test method to determine the significance of the intermediary effect. As depicted in

Table 4. Analysis of BOOTSTRAP Intermediary Effect.

Mediation Path	Category of Effect	Effect	SE	Bias Corrected (95%)			Percentile Method (95%)
				LLCI	ULCI	p	LLCI	ULCI	p
Learning and entertainment–satisfaction–willingness to revisit	Direct effect	0.162	0.039	0.084	0.236	0.001	0.086	0.238	0.000
	Indirect effect	0.077	0.015	0.052	0.112	0.000	0.049	0.108	0.000
	Total effect	0.239	0.038	0.163	0.314	0.000	0.162	0.314	0.000
Novelty seeking–satisfaction–willingness to revisit	Direct effect	0.097	0.035	0.029	0.167	0.005	0.029	0.167	0.005
	Indirect effect	0.033	0.013	0.012	0.062	0.002	0.010	0.059	0.004
	Total effect	0.130	0.035	0.063	0.201	0.000	0.061	0.200	0.000
Natural environment– satisfaction–willingness to revisit	Direct effect	0.146	0.041	0.067	0.227	0.000	0.068	0.229	0.000
	Indirect effect	0.058	0.014	0.033	0.089	0.000	0.031	0.086	0.000
	Total effect	0.204	0.043	0.119	0.290	0.000	0.119	0.290	0.000
Cultural environment–satisfaction–willingness to revisit	Direct effect	0.091	0.042	0.007	0.170	0.036	0.010	0.173	0.031
	Indirect effect	0.039	0.015	0.013	0.074	0.004	0.011	0.072	0.006
	Total effect	0.130	0.046	0.036	0.216	0.008	0.038	0.218	0.006
Social environment– satisfaction–willingness to revisit	Direct effect	0.265	0.039	0.191	0.344	0.000	0.193	0.345	0.000
	Indirect effect	0.088	0.017	0.059	0.127	0.000	0.055	0.122	0.000
	Total effect	0.353	0.037	0.281	0.425	0.000	0.281	0.427	0.000
Infrastructure–satisfaction–willingness to revisit	Direct effect	0.137	0.045	0.048	0.224	0.003	0.048	0.225	0.003
	Indirect effect	0.033	0.015	0.006	0.067	0.015	0.005	0.066	0.018
	Total effect	0.170	0.048	0.072	0.262	0.001	0.072	0.263	0.001

, Bootstrap ML was used to test the mediating effect results with 5000 repeated sampling times.

5.8. Results

By distributing questionnaires to three rural scenic spots in Jiangning District, Nanjing City, Jiangsu Province, China, this paper studied the relationship between tourist motivation, destination image and willingness to revisit in rural tourism from the perspective of tourist needs, and introduced tourist satisfaction as a mediating variable to construct a mediation test model. After ensuring the verification of the influence hypothesis among the latent variables, it was necessary to judge the specific influencing factors on tourists’ willingness according to the specific path value of each observed variable. Through empirical data tests, the research results were as follows.

5.8.1. Tourism Motivation

The direct effect of “learning and entertainment motivation-satisfaction-willingness to revisit” was 0.162, and the indirect effect was 0.077, and the 95% confidence interval did not include 0, indicating that both direct and indirect effects were significant; that is, satisfaction played a partial mediating role in the effect of learning and entertainment motivation on the tourists’ willingness to revisit, and the effect accounted for 32.2%. The direct effect of “novelty-seeking motivation-tourist satisfaction-willingness to revisit” was 0.097, and the indirect effect was 0.033. The 95% confidence interval did not include 0, indicating that both direct and indirect effects were significant; that is, satisfaction partially mediated the relationship between novelty-seeking motivation and tourists’ willingness to revisit, accounting for 25.4% of the total effect. Therefore, managers of rural tourist attractions should strive to improve the comfort of infrastructure, beauty of landscape, service quality, and other aspects, and improve the function of leisure and vacation, so as to improve the willingness of tourists to visit again.

5.8.2. Destination Image

The direct effect and indirect effect of “natural environment-tourist satisfaction-willingness to revisit” were 0.146 and 0.058, respectively, and the 95% confidence interval did not include 0, indicating that both direct and indirect effects were significant; that is, satisfaction played a partial mediating role in the effect of natural environment on tourists’ willingness to revisit, accounting for 28.4% of the total effect. The direct effect of “cultural environment-tourist satisfaction-willingness to revisit” was 0.091, and the indirect effect was 0.039. The 95% confidence interval did not include 0, indicating that both direct and indirect effects were significant, that is, satisfaction played a partial mediating role in the effect of cultural environment on tourists’ willingness to revisit, and the effect accounted for 30.0%. The direct effect of “social environment-tourist satisfaction-willingness to revisit” was 0.265, and the indirect effect was 0.088. The 95% confidence interval did not include 0, indicating that both direct and indirect effects were significant; that is, satisfaction played a partial mediating role in the effect of social environment on tourists’ willingness to revisit, and the effect accounted for 24.9%. The direct effect of “infrastructure-tourist satisfaction-willingness to revisit” was 0.137, and the indirect effect was 0.033, with a 95% confidence interval excluding 0, indicating that both direct and indirect effects were significant; that is, satisfaction played a partial mediating role in the infrastructure on tourists’ willingness to revisit, and the effect accounted for 19.4%. Therefore, in view of the scenic area planning, focus should be paid to the natural landscape, artificial environment and infrastructure improvement, and the resources should be dealt with reasonable allocation.

In conclusion, the analysis confirmed that tourist satisfaction plays a pivotal role in improving the willingness of rural tourists to revisit. Therefore, the scenic spot should improve the experience satisfaction of tourists in many aspects, so as to stimulate the willingness of tourists to visit again.

6. Discussion and Conclusions

6.1. Research Limits and Future Research Needs

This study only examined the relationship between tourists’ tourism motivation, destination image of scenic spots, satisfaction, and willingness to revisit. However, there are additional factors, such as cognitive characteristics, that influence willingness to return. As a result, only four variables were chosen as the investigation’s data, demonstrating a lack of breadth. Moreover, this study was based solely on the tourist data of three rural tourist destinations in Nanjing, Jiangsu Province. The applicability of the research findings to other rural scenic areas in China requires further investigation. Future research could expand from the current rural tourism destinations in a region to many different types of rural tourism destinations, improve the influencing factors of the willingness to revisit, and conduct in-depth research on revisit willingness in terms of tourists’ travel costs, cognitive characteristics, length of stay, etc. A long-term revisiting observation and research spot could be established in a rural tourism destination to study the relationship between the change in revisit rate and the development of rural tourism destinations and to observe the behavioral changes of revisiting tourists.

6.2. Theoretical Contribution

Despite the above limitations, this study has important theoretical, methodological and managerial implications. Theoretically speaking, on the basis of previous studies, this paper firstly discusses the relationship between tourism motivation, destination image, tourists’ satisfaction and willingness to revisit in rural tourism, and then constructs a structural equation model of “tourism motivation-destination image-satisfaction-willingness to revisit”. In the context of rural tourism, studies have found that the tourism motivation of learning and entertainment, natural environment, social environment and satisfaction have a direct positive impact on the tourists’ willingness to revisit. whereas novelty-seeking motivation, the cultural environment, and infrastructure have no effect. In addition, satisfaction plays a significant role in the influence of tourists’ tourism motivation and destination topography on their willingness to revisit. When rural tourists are satisfied with the local natural environment, social environment, and learning and entertainment activities, they are more likely to revisit the destination.

Although studies have found that tourists’ motivation and destination image affect satisfaction and tourists’ willingness to revisit, most of them are only direct or indirect relationships of a single variable, and they are rarely analyzed as influencing factors at the same time. This paper studies the influencing factors of tourists’ willingness to revisit from multiple dimensions. It not only discusses the influence of tourist motivation and destination image on tourists’ willingness to revisit rural tourist attractions, but also explains the mediating role of satisfaction in the influence of tourist motivation and destination image on tourists’ willingness to revisit. This ensures the scientificity and objectivity of the results, expands the research on influencing factors of satisfaction to a certain extent, and provides a new perspective for the application research of satisfaction models in the field of rural tourism. The theoretical model is helpful for scenic spot managers to improve their satisfaction from the perspective of tourism motivation and destination image, so as to improve the revisit rate, and the relevant conclusions are also helpful for destination operators to formulate effective market strategies for the revisit market.

6.3. Managerial Implications

By examining the connection between tourists’ tourism motivation and the destination image of scenic spots, tourists’ satisfaction, and their willingness to revisit, the complexity of rural tourism destination management can be resolved. With the policy and financial support of local governments for rural tourism destinations in the Jiangning District, it is anticipated that in future it will become a global tourist destination. Therefore, rural tourism managers must precisely comprehend the motives of tourists and develop targeted marketing strategies [51]. When planning destinations, planners should also consider the preferences of various groups and provide more unique destination experiences. Suppliers of tourism services in Jiangning District should consider the tourism motivations of international visitors, cultivate a positive local ambiance, and bolster the implementation of experience-based projects in order to increase customer satisfaction and the willingness to revisit.

For the sustainable development of local villages and tourism planning and management, the results have practical guidance and reference value. We offer some insight and recommendations to Jiangning District’s rural tourist attractions and tourism departments, destination managers, planners, and marketers.

First, according to the results, tourists’ satisfaction plays a pivotal role in improving rural tourists’ willingness to revisit. Therefore, managers of rural tourist attractions should pay more attention to improving the popularity of scenic spots and enhancing traffic accessibility, such as enhancing traffic accessibility of scenic spots [52], optimizing ticket ordering methods, doing a good job in prompt services such as climate and transportation, conducting special festival activities, establishing personalized tourism projects for different groups, and understanding the characteristics of tourist sources.

Second, among the influencing factors of destination image, the results show that social environment > natural environment > cultural environment > infrastructure; these factors can directly affect the willingness of tourists to visit again. Therefore, planners and architects of rural tourism destinations should enhance the recreational and vacation functions of scenic areas. On the one hand, tourism destinations whose primary function is sightseeing should fully integrate their own resources, such as lakes, seashores, forests, and culture, and transition from sightseeing to recreation and vacation [53]. On the other hand, for tourism destinations whose primary function is as a leisure vacation, they should focus on enhancing the natural beauty of landscapes, the service quality of scenic spots, the comfort degree of infrastructure, and other factors in order to increase tourists’ willingness to revisit.

Thirdly, among the influencing factors of tourism motivation, learning and entertainment motivation > novelty-seeking motivation. As a result, the provider of rural tourism products should pay more attention to the innovation of rural tourism products, focus on adopting new ideas and methods, incorporate rural folk customs, agricultural festivals, rural dishes, and other local materials, pay attention to the involvement of leisure, experience, and other life elements, design innovative tourism products with distinctive themes, and enhance the emotional value of tourists to rural tourism destinations. In addition, the development of rural tourism products should convey kinship or nostalgia to tourists so that they can recall and relive the rural experiences of their youth, thereby increasing the likelihood that rural tourism destination brands will be revisited.