June 24, 2024

This paper uses structural equation model to test the research hypotheses. RMSEA is a more important indicator in the model fit evaluation system, as can be seen from Table 8, the RMSEA value is 0.027, which meets the fit criteria. Among the absolute fit index, value-added fit index and parsimonious fit index statistics, all of them meet the acceptable criteria of the model except PGFI. At the degree of freedom of 20, the chi-square value of model fitness is equal to 25.290, and the significance probability value is 0.191 > 0.05, indicating that the theoretical model of this paper can fit well with the survey data, and the convergence validity of the model is quite good, which can be used to test the research hypothesis.

Table 8 Key indicators for model fitness tests.

The results of the tests of the model hypotheses are shown in Table 9. The standardized path coefficients of behavioral attitude, perceived behavioral control, and subjective norm on behavioral intentions all reached significant levels, so hypotheses H1, H2, and H3 were valid. Meanwhile, the standardized path coefficients of behavioral intention on actual behavior also reached a significant level, hypothesis H5 was valid. But the standardized path coefficients of perceived behavioral control on actual behavior did not pass the test of data, so hypothesis H4a was not valid.

Table 9 Results of model hypothesis testing.

We further test hypothesis H4b by mediating effects: consumers’ relevant perceived control behavior can influence actual purchase behavior through the mediating variable behavioral intention. Zhang et al.37 proposed that the conditions for testing the mediating effect are as followed: (1) regressing the independent variable on the dependent variable with a significant coefficient a, which is a prerequisite for the mediating effect; (2) regressing the independent variable on the mediating variable with a significant coefficient b, which means there is an effect of the independent variable on the mediating variable; (3) after controlling for the mediating variables and regressing the independent and mediating variables on the dependent variable simultaneously, the resulting regression coefficient c of the mediating variable on the dependent variable is significant, while the regression coefficient d of the independent variable on the dependent variable is insignificant, or the effect size is significantly reduced relative to c. The presence of mediating effect is determined when the above three conditions are met simultaneously. The coefficient d is used to determine whether the mediating effect is partially mediated (d is significant) or fully mediated (d is not significant). In this paper, all the observed variables involved in perceived behavioral control, behavioral intention, and actual behavior were averaged and centered, and then used SPSS 25.0 to analyze “dependent variable to independent variable”, “mediator variable to independent variable”, “dependent variable to independent variable and mediator variable”. Finally, the existence and the type of mediating utility were judged based on the significance of the regression coefficients, and the results are shown in Table 10.

Table 10 Regression equations to test the mediating effect of behavioral intention as a function of perceived behavioral control and actual behavior.

The results indicated that perceived behavioral control indirectly influences actual behavior through the mediating variable of behavioral intention. The calculated contribution of the mediating effect to the total effect was 49.12%, and the mediating effect explained 24.4% of the variance variance of the dependent variable.

Xian et al.38 concluded that individual characteristics such as gender and age have significant effects on green consumption behavior. Due to this, this paper constructed a multicluster model based on gender, age, income, and education to analyze the psychology attributions of different types of consumers’ new energy hybrid vehicle purchase behavior. We hope the results will suggest corresponding policy insights for the effective promotion of new energy vehicles.

As can be seen from Table 11, the RMSEA values for each characteristic met the criterion of < 0.05. Among the absolute fit, value-added fit and parsimonious fit statistics, all of the individual characteristics met the acceptable criteria of the model, except for the PGFI for education (0.492) and the NFI for age (0.868), which did not meet the criteria. This indicates that the theoretical model for the different individual characteristics in this paper fits well with the survey data, and the convergence validity of the multi-group model is quite good and can be used to test the research hypothesis. In this paper, the hypotheses of this paper are tested one by one through a comparative analysis of the multi-cluster models of individual consumer characteristics. The results are shown in Table 12.

Table 11 Summary table of the overall model fitness test for the multi group structural model.
Table 12 Comparative analysis of multiple cohort models based on individual consumer characteristics.

In terms of significance level, the model tests for consumers with different individual characteristics satisfy hypotheses H1, H2, H3, and H5. The magnitude of the effect coefficients shows that compared to male, low-educated, low-income, low-transportation-consuming, and youth consumers (β = 0.274, 0.294, 0.301, 0.305, 0.301), females, highly educated, high transport consumption, high income, middle-aged consumers (β = 0.363, 0.317, 0.326, 0.313, 0.356) had a greater degree of influence of subjective norms on behavioral intentions. This may be because, when buying a new energy hybrid vehicle, these consumer groups are extremely externally focused and are more impacted by social groups than by elements like consumer behavioral control and vehicle perception. For instance, middle-aged, high-consumption consumers frequently must choose their own consumption habits based on the same circle of groups as their own due to their position or employment requirements. He et al.39 discovered that low-income groups were more receptive to and interested in incentives than other groups, and that persons with higher education levels tended to advocate the purchase of hybrid automobiles40. Also, men are more logical than women, who are more likely to be driven to buy eco-friendly products41. Female consumers, on the other hand, are more interested in premium or recently introduced products and are more fashion aware. In comparison to conventional vehicles, modern energy hybrid vehicles are newer in terms of configuration and performance. Customers will be more likely to select to buy new energy hybrid cars, indicating a stronger desire to buy, if doing so will increase their sense of superiority over other community members and make them feel better about themselves. For extroverted buyers, a sense of social acceptance or moral superiority dominates their impression of the value of a new energy hybrid vehicle.

The influence of behavioral attitudes (β = 0.469, 0.445, 0.526, 0.442, 0.438) on behavioral intentions was significantly higher for male, low education, low transportation consumption, low income, and youth consumers than the influence of subjective norms (β = 0.274, 0.294, 0.301, 0.305, 0.301) on behavioral intentions. It’s possible that buying a new energy hybrid car is an expensive proposition for young consumers, the majority of whom are still in school. As a result, they will be more focused on the cost effectiveness of the vehicle when considering making the purchase. Consumers with low income, low education levels, and low levels of transportation spending will prioritize determining if the advantages of purchasing a new energy hybrid automobile outweigh those of using public transit. Men are more logical while shopping, thus they will consider the cost-effectiveness of significant outlays on cars. As a result, these buyers are incredibly introspective and have a tendency to follow their hearts while looking for a hybrid car. As opposed to outside expectations or interference, they prefer to follow their hearts and concentrate on whether a product’s performance is consistent with their own. For instance, this consumer segment is concerned with the product’s pricing. Consumers who are more reserved tend to value new energy hybrid vehicles more due to economic considerations.

Although the effects of perceived behavioral control on behavioral intention were all significant, its coefficient of influence on behavioral intention was lower than that of behavioral attitude and subjective norm. This may be due to the high recognition of new energy hybrid cars in life. On April 18, 2016, in order to better distinguish and identify new energy hybrid cars and implement differentiated traffic management, China launched a special number plate for new energy hybrid cars. New energy license plate in the color of green as the main color, reflecting the “green environmental protection” implication. And new energy hybrid car number plate to increase the special logo, the logo as a whole to green as the background color, meaning electric, new energy, green circle in the right side of the electric plug pattern, the left side of the colorful part and the English letter “E” (Electricity) similar. Therefore, most of the people can quickly identify the new energy hybrid cars. Consumers’ perception of the role of new energy vehicles in environmental management is biased42. In addition, none of the perceived behavioral controls for different individual characteristics had a significant effect on actual behavior, but behavioral intention still had a significant positive effect on actual behavior.


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