The factors influencing university students’ participation in social welfare activities

Main Article Content

Qi Chen

Min Zhang

Cite this article:  Chen, Q., & Zhang, M. (2023). The factors influencing university students’ participation in social welfare activities. Social Behavior and Personality: An international journal, 51(11), e12713.


Abstract
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Social public welfare practice is an important way to realize the goal of practical education in colleges and universities. Through a survey of 439 university students in Beijing, the results in this study showed that university students’ intention to participate in social public welfare practice was influenced by perceived value, behavioral attitude, and perceived behavioral control, and was not affected by subjective norms. Behavioral attitude and perceived behavioral control played a mediating role between perceived value and intention to participate. These findings extend the research perspective to the field of social welfare and have the potential to promote the development of social welfare practice activities for university students.

Article Highlights

  • Behavioral attitudes and perceived behavioral control were found to affect the willingness of college students to participate in social public welfare practice.
  • Subjective norms did not affect the willingness of college students to participate in social welfare practice.
  • Perceived value had both direct and indirect impacts on college students’ willingness to participate in social welfare practice.

Many colleges and universities worldwide have incorporated participation in social welfare practice into student credit management, and social welfare activities have become an important form of social practice for students. A certain social value is highlighted in cultivating this practice and it is an effective way to spread core socialist values (Z. Liu, 2018). In China, the activities range from volunteer teaching in remote mountainous areas to public welfare activities at social welfare institutions. However, university students’ social welfare practice comes with problems. For example, some students participate only to receive credits, and negative news about social welfare in society may affect their willingness to participate to some extent. Therefore, it is necessary to strengthen theoretical understanding of university students’ willingness to participate in social welfare practice to offer better practical guidance for these students in their engagement in social welfare activities.

Academic research has been conducted to examine social welfare practice involving new media users (Q. Yang, 2020), enterprise employees (C. Liu & Chi, 2019), townsfolk (F. Liu et al., 2015), and youth groups (Tan, 2019). With the development of internet technology, new fields of public welfare research have emerged, and scholars have conducted studies on public entrepreneurship (Lan, 2021), volunteering in the tourism industry (Zhou et al., 2020), charity games initiated by public welfare organizations (Y. Yang, 2021), and online public welfare (H. Li et al., 2019). In studies on university students’ willingness to participate in social welfare practice, researchers have relied on different theories, perspectives, and methods. Some have followed the theory of planned behavior (J. Li et al., 2019) or grounded theory (Ng et al., 2019), while others have examined students’ internal needs and external pressure (Su & Wu, 2019), or conducted research from the perspective of social support (M. Zhang et al., 2021), and the sense of social welfare as manifested in the emotion of being willing to participate in public interest activities, such as conserving resources and caring for public property and the environment (Zheng, 2021).

There is an abundance of existing research on social welfare, but studies with university student participants are still rare. In addition, the focus of research on university students’ public welfare behavior has been mainly on qualitative and theoretical analysis, and there are insufficient results from quantitative research. From the perspective of cognition, in this study we discussed the mechanism of the formation of university students’ willingness to participate in social public welfare practice, which has theoretical significance and practical value for improving the effect of practical education and enhancing the sustainable development of university students’ social public welfare activities.

University Students’ Willingness to Participate in Social Welfare Practice

The theory of planned behavior (Ajzen, 1991) is a model in which the behavior of individuals is successfully predicted and explained (Nie et al., 2020). It has been widely used for over 20 years. According to this theory, the stronger the perceived behavioral control, the greater is the probability of individual behavior occurring. Behavior intention is determined by behavior attitude, subjective norms, and perceived behavioral control (Deng & Chen, 2022). For university students, school and the family are important environments, and parents, relatives, and classmates have an important impact on them. Accordingly, we formed the following hypothesis:
Hypothesis 1: Subjective norms will have a positive impact on university students’ willingness to engage in social public welfare behaviors.
 
Behavioral attitude refers to the positive or negative feeling related to certain behavior and the attitude formed after the conceptualization of the evaluation of this specific behavior (Ajzen, 1991). The willingness of university students to participate in social welfare activities is based on their understanding of these activities. University students who have a thorough understanding of social public welfare and think that participating in social practice is necessary and meaningful are more willing to engage in social public welfare practice (Su & Wu, 2019). Therefore, we proposed the following hypothesis:
Hypothesis 2: A positive behavioral attitude will have a positive impact on university students’ willingness to participate in social welfare practice.
 
Perceived behavioral control refers to an individual’s perceived difficulty with engaging in a specific behavior. It refers to individuals’ knowledge of their own resources and expectations (Ajzen, 1991). Students’ perceived behavioral control when participating in social public welfare practice is mainly reflected in two aspects: ability assessment and condition assessment. Ability assessment comprises individuals’ subjective evaluation and cognition of their ability to execute specific behaviors and refers to the degree of confidence they have in completing the behavior. The higher the level of cognition of their own ability, the more faith individuals have and the more they can persist (J. Zhang et al., 2011). Individual behavior is also affected by external control, so that condition assessment includes other opportunities, resources, and control conditions. When individuals feel that currently having more resources and opportunities than were previously available reduces the obstacles encountered, their perceived behavioral control over willingness to engage in a behavior becomes stronger (Nie et al., 2020). Consequently, we formulated the following hypothesis:
Hypothesis 3: Perceived behavioral control will have a positive impact on university students’ willingness to participate in social welfare practice.
 
Although the theory of planned behavior has become one of the most widely used in social and behavioral science settings (Marta et al., 2014), Ajzen (2020) questioned whether its variables are sufficient to fully explain individual behavior and intentions. Thus, J. Zhang et al. (2011) sought to combine other theories and introduce new variables to improve the interpretability of the theory. In this research we added the variable of perceived value to improve the interpretability of the theory of planned behavior.
 
According to the perceived value model, the path of individual needs and meanings should follow the logic and structure of a cognitive hierarchy. The cognitive level is mainly composed of five levels: physiological needs, safety needs, social needs, respect needs, and self-realization needs, which result in different human behaviors and psychological states. Humans generally have a need for balance and harmony. When people experience imbalance and disharmony in their cognition, psychological tension and anxiety are induced, thereby promoting the cognitive structure to transform toward a balanced and harmonious direction. This process has been described as cognitive hierarchy → cognitive balance → perceived value → behavioral intention (F. Yang & Zheng, 2021). Individuals’ perception of the value of a behavior determines their will to engage in that behavior (Marta et al., 2014). Social welfare practice itself is a planned behavior, and before individuals decide whether to participate, they often consider or weigh the values associated with it. University students’ perception of the value of social welfare practice is reflected in the opportunities it provides to exercise their abilities and manifest their personal values. In addition, some scholars have proposed that the level of perceived value can affect behavioral attitudes (Ren & Liu, 2008; F. Yang & Zheng, 2021). In other fields of research, studies have suggested that perceived value positively affects subjective norms (B. Liu et al., 2021) and that subjective norms play a mediating role in the relationship between perceived value and behavioral intention (Xue et al., 2016). In their empirical research on the impact of perceived value on green food purchase intention, Xue et al. (2016) pointed out that perceived value does not have a direct impact on perceived behavioral control and that perceived behavioral control acts as a mediator between perceived value and behavioral intention. Because of the particularity of social public welfare, in reality, the greater the benefits and the higher the value that university students expect from social public welfare practice, the more often they stimulate their own potential to participate in social public welfare activities. Therefore, our aim in this study was to further explore the relationship between perception of the value of the activities and willingness to participate in the setting of university students’ social welfare practice. Thus, we put forward the following hypotheses:
Hypothesis 4: Perceived value will have a positive impact on university students’ willingness to participate in social welfare practice.
Hypothesis 5: Perceived value will have a positive impact on university students’ attitude toward social welfare practice.
Hypothesis 6: Perceived value will have a positive impact on the subjective norms of social public welfare among university students.
Hypothesis 7: Perceived value will have a positive impact on the perceived behavioral control of university students.
Hypothesis 8: Behavioral attitude will play a mediating role in the relationship between the perceived value and social public welfare participation intention of university students.
Hypothesis 9: Subjective norms will play a mediating role in the relationship between the perceived value and social public welfare participation intention of university students.
Hypothesis 10: Perceived behavioral control will play a mediating role in the relationship between the perceived value and social public welfare participation intention of university students.

Theoretical Model

The theory of planned behavior and the perceived value model show theoretical homology, and both are an expansion and extension of rational behavior theory. In this research we integrated these two theories to gain stronger explanatory power. The integrated mechanism model of university students’ willingness to participate in social welfare practice is represented in Figure 1.

 

Table/Figure

Figure 1. Formation Mechanism Model of University Students’ Willingness to Participate in Social Welfare Practice

Method

Participants

Undergraduate students at universities in Beijing, China, took part in the study. There are 17 undergraduate universities in the Beijing region, mainly divided into four types: comprehensive undergraduate universities under government supervision, science and engineering universities under government supervision, specialized undergraduate universities under government supervision, and private undergraduate universities. Researchers have compiled and calculated data obtained from the official websites of various schools in Beijing and found that the number of undergraduate students in 2022 was 289,918. We selected one university from each of the four types described above for sampling. The planned sample size was 500 students. The ratio of men to women was basically balanced, as was the balance across grades, although there were 172 freshmen, which was slightly more than other grades, accounting for 34.4% of the total.

Procedure

We obtained informed consent from the participants and received approved from the relevant university ethics committee before beginning the study. Participants were asked to respond to all items in the five dimensions based on their true thoughts. We conducted screening of the completed surveys for incomplete responses, short time for completion, and a high rate of identical answers in the survey. Finally, we collected 439 valid survey forms for analysis.

Measures

We used scales that had previously been developed and shown to have good reliability and validity with a Chinese sample. A 5-point Likert scale was used to rate the items, ranging from 1 = strongly disagree to 5 = strongly agree. The survey had five dimensions, each with three items (see Table 1).

Table 1. Scale Design

Table/Figure

Data Analysis

In the analysis we used structural equation modeling (SEM). First, we performed a confirmatory factor analysis (CFA) to assess the measurement model, and then SEM analysis was performed with bootstrapping estimation to measure the fit and path coefficients of the research framework. We also conducted a validity and reliability analysis and hypothesis testing of the sample data.

Results

Reliability and Validity Test

Reliability refers to the degree of consistency of the results obtained with one method; it is evaluated using Cronbach’s alpha coefficient. In general, higher reliability values indicate higher quality of the design of survey items. The Cronbach’s alphas were .94, .95, .94, .98, and .90, for subjective norms, behavioral attitude, perceived behavioral control, perceived value, and participation intention dimensions, respectively, which are all higher than the threshold of .70, suggesting that the internal consistency of each dimension and the reliability of the survey was good (Ajzen, 2020).

Validity refers to the accuracy of a scale, focusing on whether the scale can truly detect the target to be measured. All items of the scale used in this study were adopted from existing scales and were compiled in combination with expert interviews, guaranteeing good content validity.

According to Fornell and Larcker (1981), average variance extracted (AVE) values greater than .50 and composite reliability (CR) values greater than .70 indicate a good level of validity of the sample data. After model correction, in our study all pathways had standardized factor loading coefficients above .60, squared multiple correlation values above .30, AVE values above .50, and CR values above .70. This shows that the modified model had ideal intrinsic quality, good stability, and good reliability and convergent validity. The results are shown in Table 2.

When the square root of AVE is greater than the correlation coefficient between one construct and the remaining constructs, there is good discriminant validity between constructs (Fornell & Larcker, 1981: Nunnally, 1978). In this study the square roots of AVE in each construct were greater than the correlation coefficients with the other constructs, indicating good discriminant validity between constructs. As shown in Table 3, the study model had good discriminant validity.

Table 2. Reliability and Validity Test of the Scale

Table/Figure

Note. SMC = squared multiple correlation; CR = composite reliability; AVE = average variance extracted.

Table 3. Differential Validity Test of the Latent Variables 

Table/Figure

Note. Cronbach’s alpha values are shown in parentheses on the diagonal.

Structural Equation Modeling

The research reviewed in this study indicated that SEM is an effective method for studying behavioral intention. SEM explains the causal relationship and degree of influence between endogenous and exogenous variables. The structural model is presented below.

Table/Figure
Figure 2. Structural Model
Note. PV = perceived value; PI = participation intention; BA = behavioral attitude; SN = subjective norms; PBC = perceived behavioral control.

Model Fit Test

After the reliability and validity tests, we conducted maximum likelihood estimation with Amos software. The results shown in Table 4 demonstrate that the overall fit of the model was good, so further analysis could be performed.

Table 4. Test of Model Fit

Table/Figure

Note. SRMR = standardized root mean square residual; RMSEA = root mean square error of approximation; IFI = incremental fit index; CFI = comparative fit index; TLI = Tucker–Lewis index; GFI = goodness-of-fit index; PGFI = parsimonious goodness-of-fit index; Acceptable = fit is within the reference value range. The acceptable threshold for the chi-squared test (χ2) was set at < 5.0, following Wheaton et al. (1977).

Model Hypothesis Testing

The path relationship of each latent variable was tested based on the previous model of the formation mechanism of university students’ willingness to participate in social welfare practice. At the same time, the model we constructed in this study combined the theory of planned behavior with the perceived value model to construct a model to better predict and explain university students’ intention to participate in social welfare practice and its formation process. The results are shown in Table 5.

Influence of Subjective Norms on the Willingness to Participate

The result for the test of the effect of subjective norms on university students’ willingness to participate in social public welfare practice was not significant. Thus, Hypothesis 1 was not supported. This result shows that the attitude toward social welfare of people around the university students did not affect the willingness of these students to participate in social welfare practice, and that the students decided by themselves whether to participate.

Influence of Behavioral Attitude on Willingness to Participate

There was a significant positive correlation of behavioral attitude with university students’ willingness to participate in social welfare practice. Thus, Hypothesis 2 was supported.

Influence of Perceived Behavioral Control on Willingness to Participate

There was a significant positive correlation of perceived behavioral control with university students’ willingness to participate in social welfare practice. Therefore, Hypothesis 3 was supported. The results indicate that the level of university students’ cognition of their ability to participate in social welfare had an impact on their willingness to participate. University students’ level of cognition of factors such as ability and time availability to engage in social welfare practice constrained their willingness to participate in these activities.

Influence of Perceived Value on Willingness to Participate, Behavioral Attitudes, Subjective Norms, and Perceived Behavioral Control

There was a significant positive correlation between perceived value and university students’ willingness to participate in social welfare practice. Thus, Hypothesis 4 was supported. The results indicate that social welfare activities that gave university students a sense of gain and value had a positive impact on their willingness to participate in social welfare practice. University students paid greater attention to improving their abilities and increasing their experience than to making like-minded friends when taking part in social welfare activities. In addition, there were significant positive correlations between university students’ perceived value and their attitude, subjective norms, and perceived behavior control in relation to social welfare activities. Thus, Hypotheses 5, 6, and 7 were supported. Among these, perceived value had the greatest influence on students’ behavioral attitude. These results indicate that the greater the benefits social welfare practice can bring for the students, the higher is their expectation of the value of participation in social welfare practice, the stronger is their sense of identity with social welfare, and, thus, the more positive is their attitude toward it. Moreover, perceived value had a positive reinforcing effect on subjective norms and perceived behavioral control.

Table 5. Results of the Model Hypothesis Testing

Table/Figure
Note. CR = composite reliability; SN = subjective norms; PI = participation intention; BA = behavioral attitude; PBC = perceived behavioral control; PV = perceived value.

Mediation Effects Test

We used bootstrapping analysis with 5,000 repeated samples and 95% confidence intervals (CIs) to test the mediating role of behavioral attitude and perceived behavioral control in the relationship between perceived value and willingness to participate. A mediation effect is significant if the CI does not include zero. From Table 6, it can be seen that the effect of subjective norms as a mediator between perceived value and willingness to participate was nonsignificant; thus, Hypothesis 9 was not supported. However, behavioral attitude and perceived behavioral control both played a significant mediating role between perceived value and willingness to participate, supporting Hypotheses 8 and 10. In comparison, behavioral attitude had a more significant mediating effect than did perceived behavioral control.

Table 6. Results of Mediation Effects Testing

Table/Figure

Note. PV = perceived value; BA = behavioral attitude; PI = participation intention; SN = subjective norms; PBC = perceived behavioral control; CI = confidence interval; LL = lower limit; UL = upper limit.

Discussion

Theoretical Implications

Our results show that behavioral attitudes and perceived behavioral control are associated with university students’ willingness to participate in social welfare practice, whereas subjective norms are not. The finding that subjective norms do not influence willingness to participate in social welfare activities contrasts with the conclusions of relevant research conducted by other scholars (M. Zhang et al., 2021). The reason behind the lack of influence of subjective norms may be that social public welfare practice is not yet universal throughout China, and university students living on university campuses feel either no or little pressure and expectations from family, friends, and other important people around them to participate in social welfare activities. As a result, they lack sufficient pressure and motivation to increase their willingness to participate in these activities.

Perceived value influences university students’ willingness to participate in social welfare practice in both direct and indirect ways. Most of the existing research (M. Li & Chen, 2020; Su & Wu, 2019) has been focused on the direct impact via the path of perceived value and participation intention. In this study we empirically analyzed the indirect impact via the paths of perceived value, behavioral attitude, participation intention, and of perceived value, perceived behavioral control, and participation intention. We found that behavioral attitudes play a more important mediating role between perceived value and willingness to participate than do either participation intention or perceived behavioral control, indicating that university students’ understanding of and identification with social welfare practices is the most influential of these factors on their willingness to participate in social welfare activities.

We found that perceived value had a significant positive impact on subjective norms, perceived behavioral control, and, most prominently, behavioral attitudes. Previous researchers concentrated on the impact of perceived value on behavioral attitudes and subjective norms, and there have been few studies on the impact of perceived value on perceived behavioral control (B. Liu et al., 2021). In our study we have shown through empirical research that perceived value has a significant positive impact on perceived behavioral control. That is, we have shown that the greater the benefits and the higher the value that university students expect from social public welfare practice, the more often they stimulate their own potential to participate in these activities.

Practical Implications

In cultivating the willingness of university students to participate in social welfare practices, staff at universities should pay greater attention to the impact of perceived value and behavioral attitudes. They should also carry out targeted public welfare activities based on college students' public welfare experiences, as well as their behavior and attitude toward public welfare activities, to strengthen these two aspects.

Limitations and Future Research Directions

From the perspective of the survey sample, our focus in this study was on undergraduate students. Further verification is needed to determine if the research conclusions are applicable to other user groups. In the future, the survey sample range could be expanded to improve the robustness of the research conclusions based on our model. In addition, the impact of other factors, such as public role models and public education, on university students’ willingness to participate in social welfare could be explored in future work.

 

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes50(2), 179–211.
 
Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324.
 
Deng, P., & Chen, B. (2022). Empirical analysis of the factors influencing health care tourism intention under the influence of COVID-19 [In Chinese]. Journal of Kunming University of Science and Technology (Social Science Edition), 22(5), 112–122.
 
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research18(1), 39–50.
 
Lan, L. (2021). Youth development in the perspective of public entrepreneurship [In Chinese]. Journal of Youth Social Science, 40(1), 19–26.
 
Li, H., Zhang, H., & Zhang, C. (2019). Research on the influencing factors and generating mechanisms of online public welfare’s social identity [In Chinese]. Management Review, 31(1), 268–278.
 
Li, J., Fang, J., & Chen, M. (2019). Research on the influence of university public welfare education on university students’ public welfare behavior intention: Empirical analysis based on the theory of planned behavior [In Chinese]. Exploration of Higher Education, 4, 124–128.
 
Li, M., & Chen, K. (2020). Empirical analysis of farmers’ willingness and behavior in relation to green agriculture production [In Chinese]. Journal of Huazhong Agricultural University (Social Sciences Edition), 4, 10–19 + 173–174.
 
Liu, B., Wu, X., & Xu, Y. (2021). Research on the factors influencing individual cognitive willingness to protect privacy information [In Chinese]. Journal of Modern Information, 41(3), 60–68.
 
Liu, C., & Chi, G. (2019). Research on the process mechanism of employee volunteer behavior: A dynamic perspective based on “motivation–behavior–result” [In Chinese]. Human Resources Development of China, 36(1), 138–151.
 
Liu, F., Lu, W., & Zhang, X. (2015). The volunteering behavior of urban Chinese citizens and the impact of cultural capital: An empirical research based on survey data from 27 cities in China [In Chinese]. Journal of Tsinghua University (Philosophy and Social Sciences), 30(2), 37–47.
 
Liu, J. (2017). Analysis of the influence of entrepreneurship education on college students’ willingness to start a business based on the theory of planned behavior [In Chinese]. Exploration of Higher Education, 5, 117–122.
 
Liu, Z. (2018). The unity of knowledge and action: The key to the cultivation of university students’ public welfare spirit [In Chinese]. People’s Forum, 25, 128–129.
 
Marta, E., Manzi, C., Pozzi, M., & Vignoles, V. L. (2014). Identity and the theory of planned behavior: Predicting maintenance of volunteering after three years. The Journal of Social Psychology, 154(3), 198–207.
 
Ng, J. C. Y., Zhao, S., & Tan, Q. (2019). Study on the sustainability of volunteer behavior of university students [In Chinese]. Contemporary Youth Studies, 6, 33–39.
 
Nie, J., Zheng, C., Zeng, P., Zhou, B., Lei, L., & Wang, P. (2020). Using the theory of planned behavior and the role of social image to understand mobile English learning check-in behavior. Computers & Education, 156, Article 103942.
 
Nunnally, J. C. (1978). Psychometric theory. McGraw Hill.
 
Ren, J., & Liu, W. (2008). A discussion of the problem of volunteer failure in nongovernmental organizations in China [In Chinese]. Journal of Inner Mongolia University (Philosophy and Social Sciences), 2, 44–48.
 
Su, Y., & Wu, H. (2019). University students’ public welfare behavior orientation and its influencing factors [In Chinese]. Contemporary Youth Studies, 6, 53–57.
 
Tan, J. (2019). The development direction of youth volunteer service in China: Review and outlook on the youth volunteer service in the past 70 years in China [In Chinese]. Journal of Youth Social Science, 38(2), 102–108.
 
Wheaton, B., Muthén, B., Alwin, D. F., & Summers, G. F. (1977). Assessing reliability and stability in panel models. Sociological Methodology, 8(1), 84–136.
 
Xue, Y., Bai, X., & Hu, Y. (2016). An empirical study on the impact of perceived value and expected regret on green food purchase intention [In Chinese]. Soft Science, 30(11), 131–135.
 
Yang, F., & Zheng, X. (2021). The impact of ecological compensation methods on farmers’ green production behavior from the perspective of value perception [In Chinese]. China Population, Resources and Environment, 31(4), 164–171.
 
Yang, Q. (2020). Research on new media users’ network public welfare behavioral intention and its influencing factors (Master’s thesis) [In Chinese]. Wuhan University.
 
Yang, Y. (2021). Why are young people keen on online public welfare games? Motivation analysis from a cognitive perspective [In Chinese]. China Youth Study, 10, 70–77.
 
Zhang, J., Liu, T., & Liu, W. (2011). Analysis of the factors influencing citizens’ charitable donation behavior based on the theory of planned behavior: Taking the data of Liaoning Province as an example [In Chinese]. Soft Science, 25(8), 71–77.
 
Zhang, M., Wang, J., & Chen, R. (2021). Research on the factors influencing youth volunteer service behavior from the perspective of social support [In Chinese]. Journal of Guangdong Youth Vocational College, 35(2), 104–112.
 
Zheng, T. (2021). Moral licensing effect after public welfare behavior of university students with different emotion of public welfare (Master’s thesis) [In Chinese]. Shanghai Normal University.
 
Zhou, Y., Mei, Q., & Hou, B. (2020). Influencing factors of tourism volunteer service behavior based on grounded theory [In Chinese]. Tourism Tribune, 35(9), 74–89.

Table/Figure

Figure 1. Formation Mechanism Model of University Students’ Willingness to Participate in Social Welfare Practice


Table 1. Scale Design

Table/Figure

Table 2. Reliability and Validity Test of the Scale

Table/Figure

Note. SMC = squared multiple correlation; CR = composite reliability; AVE = average variance extracted.


Table 3. Differential Validity Test of the Latent Variables 

Table/Figure

Note. Cronbach’s alpha values are shown in parentheses on the diagonal.


Table/Figure
Figure 2. Structural Model
Note. PV = perceived value; PI = participation intention; BA = behavioral attitude; SN = subjective norms; PBC = perceived behavioral control.

Table 4. Test of Model Fit

Table/Figure

Note. SRMR = standardized root mean square residual; RMSEA = root mean square error of approximation; IFI = incremental fit index; CFI = comparative fit index; TLI = Tucker–Lewis index; GFI = goodness-of-fit index; PGFI = parsimonious goodness-of-fit index; Acceptable = fit is within the reference value range. The acceptable threshold for the chi-squared test (χ2) was set at < 5.0, following Wheaton et al. (1977).


Table 5. Results of the Model Hypothesis Testing

Table/Figure
Note. CR = composite reliability; SN = subjective norms; PI = participation intention; BA = behavioral attitude; PBC = perceived behavioral control; PV = perceived value.

Table 6. Results of Mediation Effects Testing

Table/Figure

Note. PV = perceived value; BA = behavioral attitude; PI = participation intention; SN = subjective norms; PBC = perceived behavioral control; CI = confidence interval; LL = lower limit; UL = upper limit.


Qi Chen, School of Marxism, Beijing Jiaotong University, No. 18, Jiaoda East Road, Haidian District, Beijing, People’s Republic of China. Email: [email protected]

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