The study of tourist behavior examines the psychological and behavioral processes involved in tourist decision-making and the influencing factors. The earliest research on tourist behavior can be traced back to the population migration theory proposed by E.G. Ravenstein in the 19th century, followed by the “push-pull” theory [6]. When applied to tourist behavior, the “push-pull theory” can be described as a comprehensive decision made by tourists based on three factors: their travel motivation, the attractiveness of the destination, and the costs incurred in pursuing their travel plans. At that time, the push-pull theory was widely used in tourism research, but it did not systematically summarize and categorize the deeper influencing factors and mechanisms of tourist behavior. Subsequently, a theory studying rational consumer behavior emerged in the field of marketing: the Theory of Planned Behavior (TPB) [7], which originated from the Theory of Reasoned Action (TRA) jointly proposed by Ajzen and Fishbein. TRA argues that a person’s behavioral intentions directly determine their behavior and are controlled by individual will, influenced only by personal “behavioral attitudes” and external “subjective norms.” Ajzen, however, argues that behavioral intentions are not entirely influenced by personal attitudes nor entirely by external subjective norms, but are often the result of both [8]. Therefore, to better predict behavior that is not entirely under the control of will, this theory adds the variable of “perceived control of behavior,” thus forming a new theory, namely the “Theory of Planned Behavior.”

The TPB theory comprises three structural levels [9][10]. The first level is Behavior Intention, reflecting an individual’s tendency to engage in a specific behavior, which often largely determines actual behavior. The second level consists of three major factors influencing Behavior Intention: Attitude refers to an individual’s positive or negative feelings about engaging in a specific behavior, representing a relatively stable stance; Subjective Norm refers to the social pressure an individual or group exerts when making behavioral decisions, i.e., the perceived expectations of others, social norms, behavioral standards, and internal behavioral guidelines that conform to these norms; and Perceived Bahavioral Control refers to an individual’s ability to control their own behavior. The third level consists of beliefs that influence attitude, norm, and perceived bahavioral control, representing specific influencing factors. These three structural levels of the TPB theory, analyzing from superficial to profound, reveal the deep-seated factors influencing behavioral decisions, thus forming the entire theoretical framework. The specific details of this theory are illustrated in Figure 1Figure 1.

Figure 1. Theoretical model of planned behavior.

This study focuses on middle school students in Shaoxing City. Since this group consists of minors, their independent decision-making ability differs significantly from general adult tourists [11]. They are subject to stronger external supervision and resource constraints. Therefore, this paper expands the traditional TPB model by mapping specific influencing factors to the three core TPB constructs:

Attitude toward the Behavior: “Travel Motivation” (A) and “Destination Image” (B) are conceptualized as the primary drivers forming the students’ positive or negative toward participating in a study tour. Attitude Subjective Norm: “Information Sources” (C), specifically the opinions of influential groups (parents, teachers, peers), constitute the social pressure to participate. Subjective Norm Perceived Behavioral Control (PBC): “Self-compliance” (D) and “Behavioral Feasibility” (E) are mapped to. Since students lack full autonomy, their ability to perform the behavior depends heavily on their obedience to authority (compliance) and external constraints like safety and cost (feasibility). Perceived Behavioral Control Based on this theoretical framework (see Figure 2Figure 2), the following hypotheses are proposed for empirical testing:

H1: Travel Motivation and Destination Image have a significant positive correlation with the behavioral intention to choose a study tour destination.

H2: Information Sources (Subjective Norms) have a significant positive correlation with behavioral intention.

H3: Self-compliance negatively acts as a control variable; however, higher alignment with authority figures (parents/teachers) correlates with positive behavioral intention.

H4: Behavioral Feasibility (Safety and Cost) serves as a decisive constraint; lower feasibility (e.g., high cost or low safety) significantly reduces behavioral intention.

Figure 2. Tourist behavior TPB model.

1) Questionnaire Structure

This study conducts an empirical investigation using a questionnaire survey, analyzing the collected data to draw relevant conclusions. The questionnaire consists of three parts. The first part covers demographic variables, including basic information about the respondents, excluding private information. The second part is a screening question: “Which of the following study tour destinations would you most like to visit?” This question aims to elicit respondents’ behavioral intentions regarding destination selection. Since there is currently no clear and unified standard for classifying tourist destinations in academia, this paper, based on existing literature, categorizes the dominant types of tourism resources in study tour destinations into six main categories: natural ecological landscape areas, cultural and historical site landscape areas, historical building landscape areas, distinctive folk custom landscape areas, cultural and artistic landscape areas, and modern urban landscape areas [12]. The third part is the main body of the questionnaire, consisting of four questions. Each question corresponds to a core variable in the third level of the constructed model: travel motivation, destination image, information source, self-compliance, and behavioral feasibility. The questionnaire design employs a five-point Likert scale.

2) Influencing factors

Based on the construction of the TPB theoretical model and after referring to relevant domestic and foreign literature, the questionnaire items are summarized as shown in Table 1.

Table 1. Description of questionnaire factors and items.

This study collected data using questionnaires, targeting middle and high school students in Shaoxing City. Questionnaires were distributed through a combination of online and offline methods. Offline distribution was primarily done directly at popular tourist attractions such as Lu Xun’s Former Residence, Chen Garden, and Shaoxing Oriental Landscape Park. Online distribution included electronic questionnaires through student social media groups and WeChat Moments. Parental consent was sought during questionnaire distribution. The questionnaires were distributed on January 10, 2022. Due to the Lunar New Year holiday, the high visitor volume at tourist attractions facilitated distribution. A total of 205 questionnaires were collected. After deleting invalid questionnaires (those completed in less than 20 seconds), 181 valid questionnaires were obtained, resulting in an effective response rate of 88%.

The basic information includes three parts: gender, grade, and family income. The distribution of the data is obtained through SPSS frequency analysis. The frequency and percentage of the three qualitative items are shown in Table 2.

Table 2. Demographic information.

Table 2 shows that among the 181 respondents, 71 were male (39.23%) and 110 were female (60.77%). In terms of grade, high school students constituted the majority (68.51%), while junior high school students accounted for 31.49%. The larger number of high school students compared to junior high school students helps ensure the quality of the questionnaire, as high school students generally have stronger comprehension abilities. The majority of respondents’ families had an average income between 5000 and 10,000 yuan (44.2%), followed by those with an income above 10,000 yuan (43.09%). Those with an income below 5000 yuan accounted for a smaller proportion (12.71%), indicating that the number of low-income families is currently small, consistent with the current level of economic development.

The reliability test mainly analyzes the credibility of the questionnaire, that is, the degree of consistency and agreement among the indicators. The alpha statistic, also known as the Cronbach’s alpha, is used to measure the reliability of the questionnaire. As shown in Table 3, the reliability coefficient is 0.868. Since this study is a practical inquiry type, an alpha coefficient greater than 0.7 is acceptable, indicating that the reliability of this study is relatively high.

Table 3. Questionnaire reliability analysis.

This study used factor analysis to measure the construct validity of the questionnaire. As shown in Table 4, the KMO value was 0.826. KMO (Kaiser-Meyer-Olkin) is an indicator used to compare correlation coefficients between variables and can determine whether the data is suitable for factor analysis. The KMO value in this study was higher than 0.8, indicating that the questionnaire has high validity. Simultaneously, the p-value corresponding to the Bartlett’s sphericity was less than 0.05, indicating that the questionnaire data passed the Bartlett’s sphericity test and that the questionnaire has high validity, making it very suitable for factor analysis.

Table 4. Questionnaire factor analysis.

1) Correlation Analysis

Correlation analysis is used to study the degree of association between data. It can determine whether the correlation is positive or negative, and the strength of the association. Data is imported into SPSS software and subjected to bivariate Pearson correlation analysis, where * indicates P < 0.05 and ** indicates P < 0.01. The presence of * indicates a correlation between the data.

Table 5 shows that travel motivation, destination imagery, information source opinions, self-compliance, and behavioral feasibility all passed the P-test, indicating that these items are correlated with the intention to participate in study tours. Hypotheses H1, H2, and H3 were verified. It can be seen that travel motivation and destination imagery have a high correlation with behavioral intention, indicating that travel motivation and destination imagery are influencing factors on middle school students’ intention to participate in study tours. While the other items show correlation, the correlation coefficients are not significant.

Table 5. Correlation analysis of factors influencing middle school students’ intention to study tours.

As shown in Table 6, there is a significant negative correlation between the average monthly income of middle school students’ families and their travel intentions. That is, students from families with lower incomes are more likely to choose not to participate or choose destinations with relatively lower travel costs when faced with high travel expenses. Therefore, the monthly income level of the family is a limiting factor in behavioral decisions. On the other hand, students from families with higher monthly incomes are not significantly affected by the cost.

Table 6. Correlation analysis of middle school students’ families’ average income level and tourism behavior intentions.

**. The correlation is significant above 0.01 (two-tailed).

2) Descriptive Analysis

The survey data was imported into SPSS software for descriptive analysis of the self-compliance factor, resulting in Table 7. The values in the table, such as the mean, median, and standard deviation, describe the self-compliance of middle school students. The table shows that the standard deviation for each item is relatively large. Because middle school students are in adolescence, some students exhibit strong rebellious emotions, while others do not. This complex emotional state of the middle school student group leads to a large dispersion in the overall data. Since the standard deviations of the items in the table are relatively close, the average value can be directly analyzed. Data analysis reveals that the students’ level of compliance and trust in information sources, from strongest to weakest, is: parents, teachers, friends, and classmates.

Table 7. Descriptive analysis of middle school students’ self-compliance.

Importing the behavioral feasibility data into SPSS software and performing descriptive analysis yielded Table 8. For behavioral feasibility, the dispersion of all items was relatively high, reflecting varying degrees of importance students placed on travel costs and safety. The standard deviation of safety was smaller than that of travel costs, and analysis of the mean and median clearly shows that most middle school students have concerns about safety, with the majority agreeing that study tours must be conducted on a safe basis. Based on the descriptive analysis of behavioral feasibility and the survey results, it is evident that a large proportion of middle school students fully agree that they would not participate in study tours if the destination has unsafe factors. This directly demonstrates that safety factors directly influence the final actual behavior. Therefore, hypothesis H4 is valid.

Table 8. Descriptive analysis of the feasibility of middle school students’ behaviors.

Based on the well-developed TPB theory and referencing relevant research findings both domestically and internationally, this study expands upon the theory to address the characteristics of middle school students in Shaoxing City, constructing a model of influencing factors in their study tour behavior decisions. An empirical study using questionnaires categorizes the influencing factors according to the dimensions of TPB theory, exploring the correlations and other characteristics among the influencing factors in each dimension, and drawing conclusions with theoretical value and practical guiding significance.

First, in the process of middle school students in Shaoxing City choosing study tour destinations, there are five main influencing factors: travel motivation, destination image, opinions of relevant groups, personal compliance, and behavioral feasibility. Among these, travel motivation and destination image have a significant impact on the intention to choose a travel destination, while personal compliance and behavioral feasibility directly affect actual behavior. Meanwhile, self-compliance and behavioral feasibility, functioning as perceived behavioral controls, are critical constraints. Although this study measured intentions, according to TPB logic, these strong constraints (e.g., parental disapproval or safety concerns) are likely to behavioral intention directly predict and limit actual behavior, even if the student has high willpower. Therefore, when developing study tour products, we should design them more from the perspective of user needs to stimulate the travel motivation of potential tourists.

Secondly, the sources of information regarding subjective norms are the opinions of relevant groups, as well as the internet and travel agency platforms. Subjective norms have a significant impact on tourists’ behavioral intentions. Surveys have found that because middle school students lack a certain level of independence, parents’ opinions have the greatest influence on their behavioral intentions when making decisions, followed by school teachers and classmates. Therefore, the needs of relevant groups should be fully considered in the development and promotion of study tour products.

Third, the feasibility of this study encompasses two aspects: economic issues such as travel costs and safety issues. Safety is paramount, having a decisive influence on whether middle school students will actually participate in study tours, and is the most crucial consideration throughout the entire process. Therefore, safety is the primary prerequisite for conducting study tours; only on this basis can study tour products and activities be designed and implemented to meet the needs of tourists.

Fourth, travel expenses, as a factor in the feasibility of travel, significantly influence both the intention and actual behavior of tourists. Family income levels greatly restrict middle school students’ freedom to choose travel destinations, and can even directly affect their eligibility to participate in study tours. However, study tours are a special form of education, and students should all enjoy this right. Therefore, relevant government departments, schools, and tourism enterprises should work together to address the financial burden on middle school students participating in study tours.

1) Develop study tour destinations with greater market potential based on students’ interests.

Research analysis reveals a correlation between middle school students’ perceptions of tourist destinations and their destination selection intentions. Therefore, tourism destination management departments should develop tourism products that better meet market demands, starting from the perspective of tourist needs. Data on tourist motivations and destination perceptions show that middle school students place significant emphasis on natural ecological environments, recreational facilities, and cultural customs.

Therefore, when creating new tourist destinations, the needs of students should be fully considered and the tourism resources of the destinations should be screened. Some regions have resources with inherent educational value, such as Lu Xun’s former residence in Shaoxing. “Following the textbook to tour Shaoxing” is an educational tourism product derived from Shaoxing as a famous historical and cultural city. The specific details of the design need to be tailored to local conditions to create educational tourism destinations that are rich in their own characteristics and meet the needs of tourists.

2) Emphasize the promotion of parent schools.

The research results show a significant correlation between information sources on study tour destinations and middle school students’ destination selection intentions. Descriptive statistical analysis of various information sources reveals that middle school students highly value the opinions of parents, teachers, and relatives; they are more likely to choose destinations recommended by these individuals. However, due to the relatively short history of study tours, awareness among students, parents, and even schools is still low. Therefore, destinations need to fully utilize media platforms such as Weibo, WeChat, Douyin, and Xiaohongshu, as well as online travel agencies (OTAs) like Ctrip, Mafengwo, and Lvmama, and traditional travel agencies to popularize study tours among these groups, thereby generating travel motivation and demand, and ultimately driving destination selection behavior.

For tourism businesses, it is crucial to leverage the roles of parents and schools. Only by gaining their approval can they generate positive word-of-mouth among students through experiential trial activities. Since parents are often dispersed and difficult to reach, tourism businesses can first establish friendly cooperative relationships with schools, securing their support by offering discounts on tickets and transportation. The schools can then help promote the program to parents, thereby increasing their enthusiasm and acceptance of study tours for their children.

3) Strengthen security measures

Based on the descriptive analysis of behavioral feasibility, safety issues have a decisive impact on whether middle school students will actually participate in study tours, making it the most primary consideration throughout the entire process. Therefore, the Ministry of Education and tourism authorities should strengthen cooperation, establishing a dedicated task force for safety precautions to regulate all aspects of work at tourist destinations using industry standards. Schools should conduct risk assessments and develop emergency plans before activities. Study tour destinations should ensure safety during the reception process, paying particular attention to the safety of transportation, catering, and facilities.

4) Provide tourism expense subsidies

As a special form of education, study tours are a right that every student should have from the perspective of educational equity. However, the cost of travel, as a factor in the feasibility of the behavior, greatly influences the intention and actual behavior of travel. Family income level greatly restricts middle school students’ freedom to choose travel destinations, and may even directly affect their eligibility to participate in study tours.

Economic issues can be addressed through joint efforts from relevant national departments, schools, and tourism enterprises. At the national level, policies should be introduced to encourage low-income families to participate, including special subsidies for study tours. This would increase parents’ enthusiasm for study tours, allowing students to participate with parental support. Schools should fully implement relevant policies issued by the Ministry of Education, effectively promoting study tours and providing subsidies to participating students. Tourism enterprises, as the profit-makers in the entire tourism activity, should assume social responsibility and respond to government policy calls by reducing the cost of participating in study tours through student discounts. By addressing funding issues from all levels of society, the feasibility of participating in study tours can be improved.