Kong Bingxian， Shi Xiao,3*， Yang Feng

1. School of Management, University of Science and Technology of China, Hefei 230026, China;2. International Institute of Finance, University of Science and Technology of China, Hefei 230601, China;3. School of Management and Engineering，Capital University of Economics and Business. Beijing 100070，China

Abstract: Nowadays, the tourism industry is characterized by ever-increasing competition, and social media is the main way we get information in the information age. As an important branch of tourism, rural tourism industry is of great significance to economy and culture in China. Since rural tourism is an important part of tourism development and the current research on rural tourism is still insufficient, this paper puts forward the following two research questions. First, which quality of rural tourism information in social media will affect tourists’ perception of destination image? Second, whether tourists’ perception of the destination image will affect tourists’ rural tourism intention?Based on the previous literature, we select relevant concepts and items about information quality, the destination image and travel intention to form a questionnaire to investigate people’s travel behavior.A total of 177 respondents completed our survey, and it has been proved that there are significant positive correlations among rural tourism information quality, destination images and travel intention. The results based on empirical analysis indicate that the qualities are positively relating with the perception of the destination image are informativeness, value-added, amount of information, accessibility and source credibility, and have a significant impact on travel intention eventually. This study not only examines the role of rural tourism information quality in social media on tourists’ travel intention from the theoretical perspective,but also proposes a marketing strategies for governments and practitioners of rural tourism to attract more tourists by improving the information quality in social media from the practical implications.

Keywords: rural tourism;social media;information quality;destination image;travel intention

1 Introduction

Rural tourism, as a part of tourism industry, refers to activities that take place at the countryside. Major cultural and heritage attractions (e.g., handicrafts, cultural amenities) play a pivotal role in rural tourism industry and enabling communities to increase their income[1]. In 2019, the total number of rural tourism tourists in China was 3.09 billion, and the total revenue of rural tourism was 1.81 trillion yuan, accounts for a large proportion in the tourism industry[2]. Tourism is a popular activity in modern life and has made a significant contribution to the economic development in recent years[3]. Developing rural tourism contributes to accelerating rural economic transformation and realizing industrial prosperity.The reason why rural tourism has developed on such a scale is due to the fact that it allows people to relax under the high pressure of life, so that tourists can take vacations, enjoy sightseeing, join leisure activities. The development of rural tourism puts forward higher requirements to the destination image, relevant departments need to develop effective marketing plans and strategies to enhance destination images[4].

Along with the rapid growth of the information technology, people’s daily lives have been dramatically changed. Social media platforms allow users to release information and interact with each other[5].Existing studies have discussed the impact of various information in social media[6，7]. Scholars around the world have conducted research on the subject of information quality, which is an important branch of the research field of social media.In the tourism industry, social media can offer a platform for tourists to search tourism information, share travelling experiences, find tourism destination, and make tourism plans. Therefore, social media is considered as an important information source for tourists[8].Compared with traditional communication channels, people now regard social media as a more trustworthy information source when choosing products and services.In January 2021,the number of social media users has reached 4.2 billion and increased by more than 13% in the past year. On average, Chinese people spend 5 hours and 22 minutes online every day. Rural tourism industry is showing a trend of prosperity and innovation with the help of the convenience of social media platforms.Therefore, social media plays an important role in increasing the tourists’ willingness to travel.

Under the development of social media, tourism practitioners of remote rural areas could disseminate tourism information without time and space restrictions.Social media is often considered as an important information source for tourists in the context of rural tourism in practice[8], tourists could depend on all kinds of social media platforms to collect information for rural tourism.For example, travel information publishing platforms represented by Ctrip and Qunar, self-media video platforms represented by Tiktok, real-time sharing platforms represented by Weibo and Oasis,high-aggregation youth culture platforms represented by Bilibili and Zhihu, daily social interaction platforms represented by WeChat and QQ.In the context of the prosperity of social media, tourists can get the latest information more quickly and conveniently, such as discount information and event information, which attract them more willingly to visit rural tourism destinations.

Currently,the application of high technology in tourism is pretty extensive, “Internet + tourism” is very popular in the information age. A series of products such as intelligent explanation machines and 3D smart electronic devices have integrated technological factors to provide convenience for tourists’ travel, but their basic business model is still traditional tourism. Traditional rural tourism ignored the promotion in social media. Although practitioners are now increasingly realizing the importance of social media for the development of rural tourism, they have limited knowledge about how to use it. Specifically,the use of social media can also be reflected in the way of information promotion and the way tourists obtain information before the tourist event. Making full use of the social media to display rural tourism information is an important breakthrough in the development of rural tourism.

Past studies[9]have envisaged that rural tourism development could increase the quality of life for local residents through increased job opportunities and household income. Rural tourism can not only show tourists the beautiful natural scenery, but also show local customs and folk culture. With the help of rural tourism, the cultural self-confidence of the nation can be strengthened and excellent traditional culture can be spread.So rural tourism is important for government of rural areas to improve residents’ livelihood and promote the local culture, and the practitioners of rural areas can get more profit under the development of rural tourism. Based on the importance of rural tourism, we explore the impact of online social media information on offline tourism behavior decision-making.

More specifically,we raise the following two research questions: ① What are the information qualities of rural tourism in social media? How does social media information affect tourists’ perceived image of rural tourism destination? ② How does tourists’ perceived image of rural tourism destination influence the tourists’ travel intention?In general, we aim to provide suggestions for government and practitioners of rural tourism to increase tourists’ rural tourism intention by using social media platforms to activate rural tourism industries.It is important and urgent to solve these questions as they also concern the interests of tourists and rural residents, so our research will be very meaningful.

A total of 199 questionnaires were collected through questionnaire surveys, and 177 valid questionnaires were screened for empirical analysis.We used the SmartPLS 2.0 for data analysis, which is a typical structural equation modeling method based on partial least squares (PLS),it is an appropriate statistical program for validating an exploratory multipath model with latent variables.

Based on the information age and the background of rural revitalization, the development of rural tourism is of great strategic significance, so our research is very valuable. This article provides tourism managers with suggestions for improving their marketing efforts by exploring the influence mechanism of rural tourism information quality in social media on tourists’ travel intention, thereby increasing the rural tourism intention and promoting the development of the rural tourism industry.

This article is organized as follows.Section 2 provides theoretical backgrounds of rural tourism, social media, information quality, destination image, and related theory based on the literature review. Section 3 proposes research models and hypotheses, which explores the relationships among information quality, destination image and travel intention. Section 4 explains the research method and data analysis. Section 5 discusses the results and highlights implications. Section 6 makes a summary of full text, points out limitations and future research.

2 Literature review

2.1 Theoretical background

2.1.1 Rural tourism

In the past few decades, tourism experienced tremendous growth as tourists are seeking for places to relax and release their stress[10]. With that, rural tourism has attracted increased attention from governments, non-governmental organization (NGO), and industry practitioners because it plays a significant role in leading economy activities and helps increase community income[11]. Rural tourism can be considered as a sustainable activity and serves as a basis for sustainable and renewable energy promotion[12].

In academic research, there can be found different definitions of rural tourism,an accepted view is rural tourism refers to activity that takes place in the countryside, it is an activity which is a part of the rural structure and activities that use local resources.Broadly speaking, rural tourism has been defined by the OECD as spending the holidays in the countryside (WTO, 2002). Rural tourism is different from other types of tourism because their main attraction to tourists is the environment of the tourism destination. In order to attract tourists, rural tourism emphasizes natural scenery, appreciation and protection of the environment in its tourism activities[13].

Considering the rural tourism(Table 1), researchers usually explore destination development strategies[1], tourism impacts[9,11],the development trend[12], and development aspirations[13]. Regarding the tourists’ perception and behavior, existing studies investigate tourists’ travel intention[3,14,15], travel motivation[5], travel plans[16], tourism information search and process[17,18].

Table 1. Literature review on rural tourism.

Table 2. Wang and Strong’s[31] conceptual framework of information qualities.

However, there is still a lack of literature that considers the effect of online rural tourism information on tourists’ destination perception and travel intention.Therefore, we put focus on rural tourism and take the role of social media into account to consider the relationship among rural tourism information quality, the destination image and tourists’ travel intention from the perspective of stimulus-organism-response paradigm to fill this research gap.

2.1.2 Social media information qualities in rural tourism

Rural tourism is a type of products and services in which tourists are highly engaged. They may spend a lot of time searching for information before traveling to ensure the satisfaction of travel[19]. Searching for information is to consult various information sources before making a travel decision[17].Many studies have pointed out the positive impact of tourism information on the travel intention[20].

Due to the rise of online users, there are many types of online information sources that a person could reach easily.Among all the information sources, the impact of social media is the main focus[24]. The influence of social media on the tourism industry is increasing, it has been supported that social media is a primary information source for tourists when they search for online tourism information[32].Social media is an internet-based application, its content is publicly available and created by users rather than marketers or suppliers[33], include business users and institutional users.

A variety of studies on information qualities from the consumers’ perspective have been conducted, our classification of social media information qualities mainly refers to Wang and Strong’s[31]conceptual framework of information qualities. They categorized information qualities into four dimensions of quality (i.e., intrinsic, contextual, representational, and accessibility qualities), illustrated in Table 2. Many scholars have adopted this framework to investigate the phenomena related to consumers.

Table 3. Measurement scale and literature sources.

Klein[34]analyzed the contextual quality of information in the World Wide Web, Knight and Burn[35]developed metrics for information retrieval from World wide web based on Wang and Strong[31]. Agarwal and Yiliyasi[36]and Emamjome et al[37]reorganized this conceptual framework of IQ in the context of social media. As such, the literature review of existing research shows that Wang and Strong’s framework of information qualities[31]is appropriate for information from social media.Pipino et al[38]used this framework to map IQ dimensions into subjective and objective. Kahn et al[39]recategorized this conceptual framework as Product-Service-Performance (PSP) model. Therefore, Wang and Strong’s information qualities framework[31]is suitable for consumers who search and use information for their products and services.

On the basis of the previous research about information qualities, we selected information qualities related to tourists search information for rural tourism from social media, such as informativeness[40], value-added[41], novelty[1], amount of information[41], accessibility[41]and source credibility[42]. What’s more, Kim et al[32]divided information qualities into content (i.e., systematic) and non-content (i.e., heuristic) qualities drawing on the HSM (Heuristic-systematic model) in the context of tourism, which is regarded as a representative example of the prominent persuasion theories related to consumer information proposed by Chaiken[43].

Heuristic-systematic model (HSM)[43]postulates that people can be persuaded through two basic ways: heuristic and systematic processes. The heuristic-systematic model (HSM) of information processing proposes that variations in the nature of persuasion outcomes depend on distinguishing the systematic (information quality) and heuristic processing (informational and normative social influence) of information[44]. While systematic processing entails a comprehensive and analytic examination of judgment-relevant information, heuristic information processing needs minimal cognitive effort to reach conclusions based on the least effort principle of the model (HSM), relying on heuristics or non-content cues[41].

Referring to HSM and division of tourism information quality from Kim et al[41], we considered heuristic cues as non-content quality and systematic as non-content quality. In our framework of rural tourism information quality, content qualities consists of informativeness, value-added and novelty, non-content qualities consists of amount of information, accessibility and source credibility.

2.1.3 Rural tourism destination image

The image is a construct that is widely applied in marketing and behavioral sciences to represent people’s perceptions of products, objects, behaviors and events driven by beliefs, feelings, and impressions[45]. In the research of the tourism destination, the image has been given various definitions. Most researchers agree that the destination image is a set of individual impressions, ideas, expectations and emotional thoughts towards a specific place.

Since 1970s, the concept of the perceived destination image has been widely applied in the field of tourism research[14].The tourism destination is central to the tourism industry,and its destination image is critical to destination positioning and destination selection process[46].The destination image has been described as being composed of both cognitive and affective components[47].

The cognitive image expresses the sum of beliefs and knowledge, reflecting evaluations of the perceived attributes of the destination[46]. The affective image refers to the emotional responses or appraisals of the individual, reflecting the tourist’s feelings towards the destination[48].

Gartner[47]proposed the destination image formation theory, which suggests that cognitive and affective images represent individuals’ subjective associations or perceptions related to a destination’s characteristics, and conative destination image is the action step: how one acts on the information and how they feel about a destination, represents a behavioral component implying future action and intention (e.g., intention to visit the destination). This theory explains the cognitive component influences both the affective and conative components, and the affective component influences the conative component as well.

2.1.4 Travel intention

Intention is something that we want and plan to do[15]. An individual’s travel intention plays an important role in his traveling destination choosing process. Both tourism researchers and professionals in tourism industry have studied on how travel intention was formed and changed, in order to arouse the intention for traveling and enjoy the benefit of the tourism economy[49].

2.2 Stimulus-organism-response paradigm

In today’s world, the social media have become an indispensable part of consumers’ lives and have great influence on their behavior. Stimulus-organism-response (SOR) paradigm is an effective view that explains the impact of online information on individual behavior, and provides theoretical foundations to understand how consumers react to social media environment[50]. SOR model suggests that environmental stimuli generates a cognitive or emotional reaction, which in turn drives consumer’s behavioral response[51].

This model was initially adopted to study consumer behavior, recently, various studies used this model to explore the technological environment cues. Study conducted by Hu et al[52]used SOR model to study the link between website features and consumers’ purchase intention in the context of online shopping environment. They referred peers’ qualities and website features as “stimulus”, experimental shopping values as “organism”, and “response” is considered as users’ purchase intention. Likewise, Al-Qudah[50]used SOR model to study the impact of content quality and brand interactivity on purchase intention via mediation of brand awareness.In our research, we treat rural tourism information in social media as “stimulus”, tourists’ perception of the rural tourism destination image as “organism” which consists of cognitive image (i.e. cognitive reaction) and affective image (i.e. emotional reaction), and consider “response” as tourists’ travel intention. Hence, we propose the research model “information quality-destination image-travel intention” eventually.

In order to better understand “Stimulus” of SOR, we classified information quality into content and non-content. We treat content information qualities as systematic cues and non-content information qualities as the heuristic cues according to HSM.The “Organism” in SOR theory includes cognitive and affective reaction, and the “Response” could reflect conative reaction. Based on the SOR and HSM, we develop the research model considering the cognitive and affective destination image under the context of rural tourism.

3 Research model and hypotheses

The abundant literature has elaborated related theories in detail, provided a theoretical basis for the deeper research of this article, and has important reference significance for the hypotheses of this research and the establishment of the model.

3.1 Information quality and destination image

Information quality is of great significance to information acquirers, in the information literature, information quality is one major dimension for evaluating the success of information systems[53]. This article aims to study the impact of information quality on travel intention via mediation of the destination image, on the basis of the discussions of Mehrabian and Russell’s SOR paradigm.

The user’s impression of any product or service is formed by processing various information sources.Many studies suggest that high quality information in social media allow users to get a better understanding about a particular product or service, get support and become able to make better decisions[41]. So, the information will affect the user’s impression,the impression is the tourist’s perception of the destination image in the context of rural tourism.

A lot of information qualities have been determined in the previous literature. Kim et al[41]chose seven qualities in the context of tourism, and they identified tourism information quality into two categories (i.e., content and non-content qualities) according to the HSM of information processing[43], content qualities include valued-added, relevancy, timeliness, completeness, and interestingness; non-content qualities include the amount of information and web page designs.Based on HSM, we treat content information qualities as the systematic cues and non-content information qualities as the heuristic cues to evaluate the impact of different information qualities on tourists’ perception of the destination image.

In the literature, content quality is defined as individual’s perception regarding completeness, accuracy, timeliness and relevance of information related with brand in the social media page of the brand[54]. In addition, a large number of studies have shown that content quality is a necessary environmental clue for consumer behaviors[55]. Non-content quality is regarded as heuristic cues of information processing by Kim et al[32]based on HSM, and Fu et al[52]point out that consumers not only care about the intrinsic quality of information content (systematic cues) but also take the heuristic cues into consideration in their decisions in the social commerce context. Exist research show that people often agree or disagree with a message primarily on the basis of their reactions to non-content cues. Moreover, we classified the destination image into the cognitive image and affective image according to many scholars’ definitions and measurements[56,57].

In light of the above arguments, we propose following hypotheses:

H1Content qualities of rural tourism information in social media are positively associated with the cognitive image of rural tourism destination.

H2Content qualities of rural tourism information in social media are positively associated with the affective image of rural tourism destination.

H3Non-content qualities of rural tourism information in social media are positively associated with the cognitive image of rural tourism destination.

H4Non-content qualities of rural tourism information in social media are positively associated with the affective image of rural tourism destination.

3.1.1 Content quality and destination image

Referring to the qualities Kim et al[41]chose, we combine completeness,timeliness and relevance into informativeness according to the items of measuring informativeness[40], which is complete, timely and relevant. Informativeness is a perceptual construct, it refers to peoples’ overall perceptions regarding the information quality related characteristics of information[58]. Thus, the following hypotheses are offered:

H1aInformativeness of rural tourism information in social media is positively associated with the cognitive image of rural tourism destination.

H2aInformativeness of rural tourism information in social media is positively associated with the affective image of rural tourism destination.

Second quality we considered into content quality is value-added,it refers to the degree to which the information consumer obtains a benefit by using the information, information with this quality could give you a competitive edge and add value to your operation[31]. Value-added of information plays an important role in tourists’ formation of destination image[41]. Thus, we hypothesize the following:

H1bValue-added of rural tourism information in social media is positively associated with the cognitive image of rural tourism destination.

H2bValue-added of rural tourism information in social media is positively associated with the affective image of rural tourism destination.

Novelty of content refers to the degree to which information is considered new[59].It is the opposite of familiarity. Although it is not included as one of the original content qualities of information in Kim et al’s[41]research framework, we consider novelty as one factor that can belong to the content quality of information in our research.Since seeking novelty is an important motivation for many tourists to travel, if tourists think that the information provided is new, they may start constructing the image and incorporating this information into the image[52]. Hence, the hypotheses below are proposed:

H1cNovelty of rural tourism information in social media is positively associated with the cognitive image of the rural tourism destination.

H2cNovelty of rural tourism information in social media is positively associated with the affective image of the rural tourism destination.

To sum up briefly, regarding the content quality of information, this study considers three qualities (i.e., informativeness, value-added and novelty) as influencing factors on the tourists’ rural tourism destination image formation.

3.1.2 Non-content quality and destination image

According to previous articles, we chose three qualities as non-content quality of rural tourism information, which are amount of information, accessibility and source credibility.

Amount of information refers to the extent of the quantity or amount of information is available or appropriate[31]. In the context of tourism, Kim et al[41]proposed operational definition for the amount of information as the degree to which the quantity or amount of available tourism information about destination provided through social media is appropriate.Gartner[47]argued that the amount of information received by an individual influences the formation of the cognitive component of the image. Baloglu and McCleary[48]provided empirical evidence that the appropriate amount of information has a positive impact on the cognitive destination image formation.What is more, we propose an amount of information has positive impact on affective image in the context of rural tourism.The amount of rural tourism information in social media is still small, and there is often a lack of public experience-style information that can bring more intuitive emotional feelings to tourists, for instance, personal blogs and rural tourism documentary is still insufficient.So tourists will find it difficult to have emotional resonance, which is not conducive to the perception of the affective image. On the contrary, if the amount of information in the social media platform increases, it will bring tourists more information about rural tourism, such as travel strategies, local customs, and online reviews. As the amount of information increases, it may bring more forms of information presentation such as texts, pictures, and videos, which will make it easier for tourists to enhance their perception of the affective image of the rural tourism destination.Therefore, the following hypotheses are offered:

H3aAmount of rural tourism information in social media is positively associated with the cognitive image of rural tourism destination.

H4aAmount of rural tourism information in social media is positively associated with the affective image of rural tourism destination.

Accessibility refers to the degree to which customers can easily find information or services provided by online information resources[18],in the context of tourism, accessibility is the degree to which tourists can easily access and use online tourism information sources[42]. Research shows tourism social media with this quality can enhance the usability and perceived usefulness of the technologies, so that it will encourage them to process the information to form both cognitive and affective destination images. Therefore, we hypothesize that:

H3bAccessibility of rural tourism information in social media is positively associated with the cognitive image of rural tourism destination.

H4bAccessibility of rural tourism information in social media is positively associated with the affective image of rural tourism destination.

Source credibility refers to the perception of the message source’s reputation by the message receiver, and does not reflect the message itself[52]. This quality has been regarded as heuristic processing, source credibility of online reviews positively affects argument quality[40]. It has been confirmed that source credibility of informational messages has a positive effect on potential users’ perceived usefulness of information technology acceptance[42]. Hence, the following hypotheses are offered:

H3cSource credibility of social media is positively associated with the cognitive image of rural tourism destination.

H4cSource credibility of social media is positively associated with the affective image of rural tourism destination.

3.2 Destination image and travel intention

On the basis of Gartner’s destination image formation theory[47], the conative component of destination image represents tourists’ active consideration of a place as a potential travel destination[47]. So, we could regard the cognative image as travel intention, and we argue that the interrelationship among the cognitive image, affective image and travel intention still hold in the context of rural tourism. In accordance with the foregoing, we propose the following hypothesis:

H5The cognitive image is positively associated with the affective image of a destination.

Destination image is an important element that affects personal travel intention[14]. According to Gartner[47], the interrelationship of cognitive and affective image components eventually determines the predisposition for visiting a destination. The destination image consists of a subjective interpretation of a destination made by an individual which influences tourist behavior[61]. An individual’s travel intention to visit a specific place is strongly connected with the destination image in that person’s mind[15].Therefore, to fully understand travel intent, the destination image is a key issue that should be analyzed. Hence, leading to the sixth hypothesis of this research:

H6Destination image is positively associated with the tourists’ travel intention of rural areas.

The cognitive component of the image attributes involves the scenery, climate, accommodation facilities, restaurants, and historical and cultural attractions. All these can induce an individual to visit a specific destination.Moreover, Klenosky[62]have shown that before tourists make their travel decision, they formulate a more positive affective destination image when the destination-related emotions match their motives and the benefits pursued. Therefore, we hypothesize that:

H6aThe cognitive image is positively associated with the tourists’ travel intention of rural areas.

H6bThe affective image is positively associated with the tourists’ travel intention of rural areas.

Based on the above concepts and hypotheses, the research framework of this article was derived and is presented in Figure 1.

Figure 1. Research framework.

4 Research method

4.1 Measures

To validate research model,the tool of collecting data used in this study was a questionnaire. To expedite the data collection process, we developed a survey,and all constructs,except for the subjects’ demographic variables, were measured on a five-point Likert-type scale(from 1 strongly disagree to 5 strongly agree).

All constructs in our survey were measured using multi-item scales. In order to ensure the validity of the content, the measurement items used in this article are mainly from the previous research (shown in Table 3).

After the preliminary design of the questionnaire survey, 17 students were found to do a pre-survey to test the readability and ease of understanding of the questionnaire.

A total of 12 items was adopted into informativeness, value-added and novelty. There are three items were adapted to illustrate amount of rural tourism information, accessibility and source credibility respectively.Twelve items for the cognitive image and four items for the affective image were adopted, among them, the cognitive image is divided into attractive, community, and comfort.Three items are used to express the concept of travel intention.All of the items are presented in the appendix.

4.2 Data collection

This data is distributed using the platform of the questionnaire star.A total of 199 questionnaires were collected, 177 valid questionnaires were screened out as usable survey responses for the empirical analysis after rigorous questionnaire validity screening.All the respondents are tourists who are keen on travelling but have no rural travel experiences, and the most important way for them to obtain information is social media. The respondents to this valid questionnaire were distributed in 26 provinces, so, the questionnaire sample is geographically dispersed and has a typical representative.

The analysis begins with the demographics of respondents, depicted in Table 4.45.76 % (n=81) of the survey respondents were male and 54.24 % (n=96) of the survey respondents were female. 92.09 % (n=163) of respondents were aged in their 18～40. In addition, 94.35 % (n=167) of respondents have Bachelor’s degree or above. The samples collected in this study have good representativeness.

Table 4. Demographic characteristics (n=177).

There are 93 students, accounting for 52.54% of the survey respondents.Zhang et al[63]use binary logistics regression to analyze and summarize the focus of rural tourism. It is concluded that people with higher education levels are more willing to travel to rural areas. It is concluded that people with higher education levels are more willing to travel to rural areas. At the same time, because students have more free time, they are more willing to go on rural tourism. Overall, the sample groups collected in this research meet the main consumer groups of rural tourism in this conclusion.

4.3 Data analysis

4.3.1 Measurement model

IBM SPSS Statistics 20.0 and SmartPLS 3.0 were used for our data analysis. We used the partial least squares (PLS) method, because it is an appropriate statistical procedure to validate an exploratory multipath model with latent variables, even under conditions of non-normality and small number of samples,PLS can be used to confirm the validity of an instrument’s constructs and assess the structural relationship among constructs[64]. It has following advantages. First, it is suitable for verifying some hypotheses that have not been proved in the existing literature, and it is also used to verify exploratory and complex theoretical models, such as the relationship between information quality in social media and tourists’ perception of rural tourism destination image.Second,it is suitable to deal with second-order constitutive variables, such as the cognitive image in this study.

4.3.2 Common method bias

Considering that only questionnaire survey method was used to collect data in this study, common method bias is likely to occur[65], which will be detrimental to the effectiveness of data analysis. In order to control the common method bias, the following methods were used in this study. First, anonymous assessment is adopted in the questionnaire design to protect the anonymity of respondents and reduce their speculation on the purpose of measurement. Secondly, Harman mono-factor analysis was adopted according to the study of Podsakoff et al[65].The results show that four principal components extracted from the measurement model can explain 68.9% of the variance. The first component explains 46.8% of the variance, within the acceptable 50% variance range[66]. The results did not show that there was a single factor that explained majority of variances among all items, indicating that there were no serious problems related to common biases in the data sample, and the test passed.

4.3.3 Measurement model

When measuring the measurement model, we mainly test the reliability and validity of the model. Reliability refers to the degree of internal consistency among the items of each variable, and validity refers to the degree to which the items of the measurement variable can accurately measure the construct, including convergent validity and discriminant validity.

For this study, to ensure the reliability of this research, internal consistency was used, measured with Cronbach’s alpha and composite reliability (CR) scores. As given in Table s 4,Cronbach’s alpha and CR values of all constructs were greater than 0.70[67], which ensures the internal reliability of items in this study.

Table 5. Factor loading and descriptive statistics (n=177).

[Note] ①=Composite Reliability; ②=Average Variance Extracted.

To ensure the validity of latent variables, we assessed both convergent and discriminant validities. First, convergent validity was assessed by examining both the average variance extracted (AVE) scores and the factor loadings of the indicators related to each construct. A confirmatory factor analysis was adopted to compute the factor loadings. Table 5 shows that AVE values ranged from 0.587 to 0.862, which are well above the threshold value of 0.5[68]. The factor loadings ranged from 0.71 to 0.95, and all of them were statistically significant and larger than 0.7[68].

Discriminant validity was assessed by comparing the square root of the AVE for each construct against the inter-construct correlations[67]. As shown in Table 6, all the diagonal elements, which are the square root of AVE, between 0.766 and 0.928, exceed the inter-construct correlations, thereby satisfying the discriminant validity.

Next, we analyzed the construct-related HTMT ratio. As shown in Table 7, the HTMT matrix values were all lower than the threshold of 0.85[69], which proved the strong discriminant validity. The above test results show that the model in this study satisfies the discriminant validity.In addition, we done cross-loading shown in Table 8. Fornell-Larcker criterion Loading exceed cross-loadings[70], and discriminant validity is appropriate.

Since the cognitive image is a second-order reflective variable, this study uses SmartPLS to test it. According to Chin et al[71], the path between the first-order variable and the second-order variable is established, and the first-order variable is replaced by the generated latent variable score as the item of the second-order variable, thereby describing the second-order variable. The indicators loading indicates the contribution to the second-order construct through its weight[72].The result is shown in Figure 2, which shows that the first-order variable can reflect and describe the second-order variable.

Figure 2. PLS results of second-order reflective variable-cognitive image.

Note: Rectangle represent second-order (cognitive image). Ellipses represent first-order factors(attract, community and comfort).The reflective models were analyzed in the PLS model simultaneously with the entire structural model. The numbers in brackets are the loading of the indicators. All weighs are significant at thep<0.001 level.

4.3.4 Structural model

In an empirical analysis, the test of the structural model is an important statistical method to test the relationship between variables. To test the hypotheses, we measured the explained variance (R2) of the dependent and mediating variables, path coefficients (β), and their levels of significance (t-values) to assess the significance of the hypothesized relationships.

Results of the hypotheses testing summarized in Figure 3 and Table 9 show that nine hypothesized paths in our research model are supported, which are H1a, H2a, H2b, H3a, H3c, H4a, H4b, H5,and H6b. The model results explain the variance of 23.8% of tourists’ cognitive image perception of the rural tourism destination, 28.7% of tourists’ affective image perception of the rural tourism destination, and 24.2% of tourists’ intention of the rural tourism.

Table 9. Structural model testing-hypotheses testing.

Figure 3. Result of hypotheses analysis.

Table 6. Correlation matrix (n=177).

Table 7. Heterotrait-Monotrait ration (n=177).

Table 8. Item loadings and cross-loadings analysis (n=177).

Note: Bold italics represent the square root of average variance extracted while the other entries represent the correlations.

[Note]*p≤0.05,**p≤0.01,***p≤0.001.

First, for the role of information quality,informativeness was significantly associated with both cognitive (β=0.270,p<0.005) and affective images (β=0.194,p<0.05), supporting H1a and H2a. Value-added was found to be significantly related to the affective image (β=0.315,p<0.005), supporting H2b. However, the relationship between value- added and the cognitive image (i.e., H1b) were not supported.Similarly, significant relationships were not observed between novelty and cognitive images and between novelty and affective images (H1c and H2c are not supported).

Second, for the non-content qualities, amount of information was significantly associated with both cognitive (β=0.177,p<0.05) and affective images (β=0.223,p<0.05), supporting H3a and H4a. Source credibility was significantly associated with the cognitive image (β=0.215,p<0.01), and accessibility was related to the affective image (β=0.163,p<0.05), supporting H3c and H4b, respectively. In addition, we could not find a significant relationship between accessibility and the cognitive image (i.e., H3b) and the relationship between source credibility and the affective image (i.e., H4c), respectively.

As expected,the cognitive component of the destination image was significantly associated with the affective component of the destination image (β=0.551,p<0.001), supporting H5. The affective component of the destination image was also significantly associated with travel intention (β=0.458,p<0.001), supporting H6b. But the relationship between the cognitive component of the destination image and travel intention (i.e., H6a) were not supported.

5 Discussion

5.1 Discussion of result

This research shows the relationship between the information quality of rural tourism in social media and the formation of destination images. The results suggest that some aspects of the content qualities and non-content qualities of tourism information in social media are positively correlated with different types of destination images.

Firstly, we focus on H1 and H2.All content qualities of rural tourism information will affect either the cognitive image or the affective image except for novelty of information.This is a plausible result as the information displayed on the social media platform is already the latest recommendation after the system is refreshed. At the same time, with the development of innovation, it is no longer rare for tourists to have access to novel information.The informativeness of information has a significant impact on both cognitive and affective images.This result shows that informativeness of rural tourism information in social media is related to the potential tourists’ information processing, and it plays an important role in forming the destination image.However, value-added information is only significantly related to the formation of the affective image, and isn’t to cognitive information. This is also a reasonable result beyond assumptions.Because the value-added information is reflected in the extent to which tourists benefit from the information, such as providing aiding in planning rural tourism plans.Tourists can get relevant emotional feelings about rural tourism due to gaining benefits, but these benefits may not necessarily related to the cognitive image.Therefore, value-added information can help tourists form the affective component of the destination image, rather than being related to the cognitive image.

Secondly, we focus on H3 and H4. In the non-content qualities of information quality,it can be seen that the all of these information qualities have correlation with cognitive image or emotional image.Among them, the amount of information is related to the formation of cognitive and affective images. The items selected for measurement amount of information are large, sufficient, and appropriate, the higher score of the amount of information means information allows tourists to perceive the sum of beliefs and knowledge (i.e.cognitive image) and the better feeling (i.e.affective image) of rural tourism.Therefore, it is reasonable that amount of information in rural tourism is significantly related to the image formation of rural tourism destination.Accessibility of information is only related to the formation of the affective image, but not significantly related to the formation of the cognitive image. More convenient information acquisition can make the information processing more efficient, they can form more positive emotional feelings about that, but information with this quality may not necessarily enable tourists to have an overall belief and improve the knowledge evaluation of the destination. Source credibility is not related to the formation of affective image, it is only related to the formation of cognitive image. Although we initially believed that source credibility is related to the formation of cognitive image and affective image, we also tend to think that the correlation between source credibility and the cognitive image is more significant. Because the source credibility is only related to the social media publisher,If the platform has high credibility, and is professional in rural tourism related fields, then tourists will think that the information description in the platform is more real,which is helpful for tourists to form a more specific cognitive image.

The significant impact of cognitive image on affective image has been verified. In the correlation between destination image and tourism intention, the significant impact of the affective image on tourists’ rural tourism intention has also been verified, which is in line with the previous hypotheses.However, the cognitive image has no significant impact on the rural tourism intention. This may be attribute to the particularity of the rural tourism industry. Today’s rural tourism operations are more diversified, and some rural tourism focuses on specialized products and services to attract tourists to travel.Therefore, these destinations may not be able to obtain high scores at the cognitive image,but they can still enable tourists to generate higher travel intention, as a result, there is no significant correlation between the cognitive image and rural tourism intention.This conclusion is also corroborated by the conclusion drawn by Kim et al[41].The cognitive image is more significantly associated with the affective image than the conative image. The indirect process of the cognitive-affective-conative destination image formation is found to be more accountable than the direct process of cognitive-conative destination image formation because a person develops various intentions for their behaviors based on not only cognitive but also affective factors. And the influence of the cognitive component on the conative dimension is higher when mediated by the affective component[61].This result implies that it is necessary to understand the role of various aspects of information in social media on both cognitive and affective images to provide tourists with effective tourism information in social media.

5.2 Implications

Rural tourism promotes economic development and is an important part of the tourism industry.However, scholars have limited research on this filed, and the theoretical research on information quality of rural tourism, rural tourism destination and rural tourism intention is not sufficient. The practical process of rural tourism marketing lacks corresponding theoretical support, and it is difficult to explore the future development of rural tourism under the information age. This article studies the formation mechanism of tourists’ travel intention, and provides scientific and reasonable suggestions for the rural tourism industry to realize more potential tourists.

5.2.1 Theoreticalimplications

This study advances the theoretic development in the stream of rural tourism research. To sum up, this study contributes to the literature in at least three ways. First, our study contributes to the understanding of rural tourism information quality in social media based on Wang and Strong’s information quality framework[31]in the context of tourism destination. The feasibility of the information qualities applied in the present study has been analyzed from both theoretical and empirical perspectives.Second, we also found that rural tourism information quality can be recategorized as content qualities (i.e., informativeness, value-added, and novelty) and non-content qualities (i.e., amount of information, accessibility and source credibility) based on Chaiken’s heuristic-systematic model (HSM)[43]. Therefore, this study seeks to investigate empirically how the content and non-content information qualities of rural tourism in social media influence tourists’ destination image formation. Third, this study contributes to the literature regarding the destination image formation process.Most of the extant studies have confined themselves to conceptual studies without any empirical validation in the context of social media,but our study fills this research gap by assessing Chinese tourists’ rural tourism destination image formation in social media. As mentioned, this study also contributes to the literature on the Stimulus-Organism-Response (SOR) paradigm in the context of tourists’ travel intention.

This article is exploratory in nature and thus does not test or confirm a proposed theory.Our contributions are as follows:① Refine rural tourism information quality in social media, and make up for the insufficiency of rural tourism research; ② Validate the relationships between the information quality and destination image in the context of rural tourism, and identify which information quality in social media are significant impact on tourists’ perception of rural tourism destination image; ③ Expand the destination image theory to rural tourism destinations, and explore the influence of the destination image on travel intention.

5.2.2 Practical implications

This research highlights the relationship between tourism information quality factors in social media and destination image formation and will provide a strong practical basis for research on the role of information of social media in the tourism industry. The results suggest that different information qualities in social media are positively associated with different types of destination images. Among the six qualities selected in this paper, the qualities that have a significant impact on the perception of destination image are informativeness, value-added, amount of information and source credibility. Among them, the impact of informativeness, amount of information and source credibility on cognitive image is significantly positive; the influence of informativeness, value-added, the amount of information, and accessibility have a significant positive correlation with the affective image. In the rural tourism industry, these five qualities should be paid more attention.

From the perspective of improving five qualities above, relevant practitioners can make the following efforts. On the one hand, for social media platform managers, they should release rural tourism information on time and completely. The content of information can include the description of the introduction of tourism projects and tourists’ experience to ensure the relevant, completeness of the information. they also should provide information about travel routes, local weather and accommodation conditions to increase value-added of information to facilitate tourists’ tour planning.On the other hand, leaders in tourism companies are suggested to publish information on multiple platforms, such as local government official media, travel websites, etc. to improve the accessibility and amount of information. The government could build a rural tourism information shared database and establish dynamic data monitoring and early warning mechanisms to guarantee the healthy development of the tourism industry.

Our research results also show that the affective image of rural tourism destinations has a positive influence on the travel intention, so we can increase tourists’ travel intention from the perspective of improving the affective image. We can improve the affective image by enhancing the cognitive image considering that the cognitive image is positively associated with affective image.In the scenery,practitioners should protect historical cultural heritages, build buildings with the antique architectural style, protect cultural monuments, sell local cuisines, organize folk performances, and design delicate handicrafts.In terms of community, the management committee should create a kind atmosphere among local residents, keep tourists a simple and relaxed lifestyle, advocate residents to inherit traditional folk customs.On the environment, we should do a good job of sorting garbages, enhance rural residents’ environmental protection awareness and beautify the rural tourism environment. Through the above methods, rural tourism practitioners can enable tourists to obtain a better affective image from good products and services.

6 Conclusions and future researches

This study explores the quality of rural tourism information in social media and further analyses the effect of information quality on tourists’ perceived destination image and travel intention. The rural tourism information quality is depicted from two perspectives: content qualities (informativeness, value-added, novelty) and non-content qualities (amount of information, accessibility, source credibility). By deepening tourists’ information processing in social media platforms, this study strengthens the understanding of tourists’ rural travel intention.

This article still has some limitations, and we provide some directions for future research.Firstly, respondents may have vague definitions and boundaries of rural tourism.We did not conduct research on specific forms of rural tourism, such as hiking, fruit picking activities, visit the former residences of celebrities and so on.The future research can specify forms so as to segment the categories and make it easier to propose management strategies. Secondly, we did not interview for a specific rural tourist destination. The future study can contact the local government to get the latest development trend and new policies in the research, and put forward constructive opinions. Thirdly, this paper focuses on the Mainland China. In the subsequent research work, scholars can study the differences of tourist’s behaviors from other countries and regions, and compare the differences between different cities.

Acknowledgments

Financial support from the National Natural Science Foundation of China (71991464/71991460, 71631006 and 71921001) are gratefully acknowledged.

Conflictofinterest

The authors declare no conflict of interest.

Authorinformation

KongBingxianInternational Institute of Finance, School of Management, University of Science and Technology of China.

ShiXiaoInternational Institute of Finance, School of Management, University of Science and Technology of China； School of Management and Engineering， Capital University of Economics and Business.

YangFengInternational Institute of Finance, School of Management, University of Science and Technology of China.