Entrepreneurial creativity refers to the ability of individuals to produce and implement innovative ideas regarding products and services in early or mature enterprises to establish new enterprises, plan the development direction of enterprises, and produce new services and products (Amabile, 1997). It is original and novel and requires entrepreneurs to find a new thinking system from existing achievements, to better explore and find the connection between divergent aspects, and creatively find new business opportunities (Zhan et al., 2020). Entrepreneurial creativity is not only the key driving force of entrepreneurial intention but also the core element for enterprises to improve their competitive strength (Olufunso, 2010). As a special group, green entrepreneurs should maintain vigilance to protect the environment, pay attention to the environmental development problems that other entrepreneurs do not realize, use innovative thinking to find and identify business opportunities, open up the entrepreneurial market, and employ flexible creative thinking to solve environmental problems. Studies have shown that college students’ entrepreneurial creativity has a positive impact on entrepreneurial intention (Zampetakis, 2008). Compared to students with average creativity, those with higher creativity are better able to break the inherent thinking of problems. Thus, they are more likely to show positive entrepreneurial spirit (Liang et al., 2019), higher green entrepreneurial willingness (Jiang et al., 2020), and the possibility of implementing green entrepreneurial behavior. Therefore, entrepreneurial creativity has an important impact on college students’ green entrepreneurial intention.

The related connotation of self-continuity was mentioned by the philosopher Parfit (1971), who pointed out that an individual’s past experience will affect the past self and eventually become a part of self-identity; the individual’s view of the future self will also affect the present self. Therefore, as an individual identifies the past, present, and future selves as one self in the time dimension, it becomes a continuous self. Ersner-Hershfield et al. (2009) put forward the connotation of future self-continuity and believed that its essence refers to the closeness of the individual’s perception of the present and future selves, by focusing on a person’s feelings and views of the present and future selves. Hershfield (2011) summarized the characteristics of future self-continuity as vividness, similarity, and positivity. The psychological and behavioral aspects of entrepreneurs are impacted by the consistency of their future self-continuity. The higher the degree of psychological connection between the future and the present selves, the more the individual is able to adhere to the present decision (Ersner-Hershfield et al., 2009) in the future choice. The individual can also come into a positive emotional state to make efforts for future decisions. In addition, some researchers have shown that future self-continuity is an entrepreneurial trait of start-ups. Individuals with high future self-continuity are likely to accept uncertain entrepreneurial environment and adhere to entrepreneurship in the future environment than others (Zeng and Ouyang, 2020).

Entrepreneurial cognition refers to the cognitive structure of individuals in the process of creating new enterprises and identifying and evaluating market opportunities (Smith et al., 2009). Green cognition refers to the process of individual understanding and understanding of the green concept and psychological experience of undertaking green problems through the integration of green knowledge and skills accumulated by individuals (Jiang et al., 2020). The existing literature shows that green cognition is positively correlated with green entrepreneurial intention. The stronger the entrepreneur’s green cognition, the more likely the person will have green entrepreneurial intention and exhibit various green entrepreneurial behaviors. Entrepreneurs with high green awareness are better than ordinary entrepreneurs in terms of environmental awareness. Green entrepreneurs pay more attention to whether entrepreneurial behavior and decision-making have a negative impact on the environment. Therefore, when they start a business, they look for and identify green business opportunities. However, entrepreneurs with good green cognition can identify potential green entrepreneurial interests and green ideas and implement and solve the problems of a green economy (Jiang et al., 2020). Thus, college students’ cognition of green entrepreneurship, including their understanding of green concepts, cognition of environmental problems, and the ability to identify green entrepreneurial opportunities, may affect their green entrepreneurial intention.

Entrepreneurship culture refers to beliefs, attitudes, and values related to entrepreneurial activities in a specific region or country (Linan et al., 2020). Different modes of entrepreneurship reflect the variations in cultural modes in many countries and the entrepreneurship culture advocated by the regions where the entrepreneurs live (Capelleras et al., 2019). Social and cultural norms affect individuals’ entrepreneurial intention. Some researchers point out that if a country or region encourages entrepreneurship and shows cultural respect for the identity of entrepreneurs, and if individuals can actively feel the entrepreneurial spirit of struggle, innovation, and risk-taking, then they are more willing to try entrepreneurship, which can promote individual entrepreneurial intention (Spencer and Gomez, 2004). Green entrepreneurial culture with social support can affect entrepreneurs’ green entrepreneurial spirit and entrepreneurial quality (Alwakid et al., 2020). By actively developing green entrepreneurial culture, beliefs, and norms, a country and society can better convey the entrepreneurial development direction to entrepreneurs, which directly or indirectly affects the choice of individual entrepreneurial direction (Diaz-Casero et al., 2012). The promotion of green entrepreneurial culture is guided by social norms and policies. Therefore, the green entrepreneurial intention of college students is promoted, when the country, colleges, and universities actively advocate a green entrepreneurship culture.

Entrepreneurship education refers to the national education system that provides entrepreneurship-related education for students, which allows them to identify entrepreneurial opportunities and possess entrepreneurial skills (Kuratko, 2005). The level of entrepreneurship education is positively correlated with entrepreneurial intention (Mark, 2012). Thus, it is an important determinant of students’ entrepreneurial intentions (Agu et al., 2021). Green entrepreneurship education refers to the cultivation of entrepreneurs with environmental and economic values, thus emphasizing the concept and practice orientation of green entrepreneurship. College students with basic knowledge of green entrepreneurship are more willing to participate in green entrepreneurship activities (Yi, 2020). It may be because they are gradually able to learn green knowledge and entrepreneurial skills in the diversified green entrepreneurship education organized by the school. Green entrepreneurship education can further stimulate the construction of college students’ cognition of green entrepreneurship and encourage them to deal better with the possible problems faced in the process of green entrepreneurship in the future, so as to enhance their green entrepreneurial intention. Therefore, green entrepreneurship education is also an important factor that affects college students’ green entrepreneurship.

Financial support mainly refers to subsidies, loan discounts, tax incentives, and other financial support for actively carrying out green entrepreneurship activities. Owing to the special orientation of “environmental values,” green entrepreneurship needs more financial support than other forms of entrepreneurship (Welter, 2011). Financial support is inevitable for the normal operation of the project (Xu et al., 2020). In particular, green entrepreneurship requires more green technology and financial support is the basic guarantee for green entrepreneurs. When college students realize that there is a lack of financial support or funds, they rather delay starting or wanting to start a business (Braun and Sieger, 2021). However, the implementation of financial policies by the state, government, colleges, and universities, make them more willing to accept financial support and avail of more entrepreneurial resources and opportunities. The fundamental function of financial support is to provide effective material guarantees to reduce the uncertainties caused by technology and market risks at the initial stage or in the process of entrepreneurship, to enhance their confidence and enthusiasm in entrepreneurship (Pergelova and Angulo-Ruiz, 2014; Xu et al., 2020). Therefore, venture capital support is more conducive to stimulating the practice of green entrepreneurship among college students and has an important impact on their green entrepreneurial intention.

Chia and Liang (2016) developed a scale for entrepreneurial creativity, which included 12 items. Each item was rated on a 5-point Likert scale with the options (1 = “very much disagree” to 5 = “very much agree”). In this study, the scale showed good reliability (Cronbach’s alpha = 0.930). The items of the measurement scale were revised include (“I can plan innovative entrepreneurial activities;” “I can plan entrepreneurial activities with my characteristics;” “I can plan stimulating entrepreneurial activities;” “Entrepreneurial activities that I plan are ingenious;” “Entrepreneurial activities that I plan are unique;” “Entrepreneurial activities that I plan are to guide the market;” “I understand customers’ needs;” “I adapt practices flexibly to the changes;” “I consider preferences in the consumer market;” “Entrepreneurial activities that I plan are to meet customers’ goals;” “Entrepreneurial activities that I plan can be adapted to different situations;” “Entrepreneurial activities that I plan are recognized in the consumer market”).

Future self-continuity was measured on a 10 items scale adapted from Sokol and Serper (2020). It is divided into three structures: the similarity questions (Question 1–4; e.g., “How similar are you now to what you will be like 10 years from now?” “How similar are your beliefs now to what they will be like 10 years from now?” “How similar is your personality now to what it will be like 10 years from now?” “How similar are your values now to what they will be like 10 years from now?”) are answered on a 5 - point Likert scale (1 = “completely different” to 5 = “exactly the same”), the vividness questions (Questions 5–7; “How vividly can you imagine what you will be like in 10 years from now?” “How vividly can you imagine what you will look like in 10 years from now?” “How vividly can you imagine what your family relationships will be like in 10 years from now?”), and positive affect questions (Questions 8–10; “Do you like what you will be like 10 years from now?” “Do you like what your personality will probably be like 10 years from now?” “Do you like what your actions will probably be like 10 years from now?”), and the 5-point Likert scale is used to answer (1 = “not at all” to 5 = “perfectly”). The average score of each future self-continuity questionnaire item was used to obtain the total score of the future self-continuity questionnaire (ranging from 1 to 5). The higher the score, the higher the future self-continuity level. This scale has been widely used in previous studies and has good reliability, with a Cronbach’s alpha of 0.921.

Jiang et al. (2020) compiled the scale of green cognition, which has six items (“I can recognize new venture opportunities in environmental protection industries;” “I frequently identify ideas that can be converted into new products or services in environmental protection industries;” “I generally lack green ideas that may materialize into profitable enterprises;” “I frequently identify opportunities to start up new businesses in environmental protection industries;” “I enjoy thinking about new ways of doing green businesses;” “I thought of many ideas for new green activities in the past month”). The third question is the reverse. The responses for the questions were based on a 5-point Likert scale (1 = “very disagree” to 5 = “very agree”) and with a Cronbach’s alpha of 0.828.

The entrepreneurship culture scale has been widely used in research (Diaz-Casero et al., 2012), with a total of 5 items (“In my country/region, the national culture is highly supportive of individual success achieved through own personal efforts;” “In my country/region, the national culture emphasizes self-sufficiency, autonomy, and personal initiative;” “In my country/region, the national culture encourages entrepreneurial risk-taking;” “In my country/region, the national culture encourages creativity and innovativeness;” “In my country/region, the national culture emphasizes the responsibility that the individual (rather than the collective) has in managing his or her own life”). The score of each item ranges from 1 (very disagree) to 5 (very agree), and has shown good reliability with a Cronbach’s alpha of 0.930.

The Walter and Block (2016) scale was used in entrepreneurship education, with a total of 4 items (“My school education helped me develop my sense of initiative—a sort of entrepreneurial attitude;” “My school education helped me to better understand the role of entrepreneurs in society;” “My school education made me interested to become an entrepreneur;” “My school education gave me skills and know-how that enable me to run a business”). The responses were based on a 5-point Likert scale which ranged from 1 (very disagree) to 5 (very agree). In this study, the Cronbach’s alpha was 0.726.

The financial support scale was compiled by Wu and Mao (2020), and there were five items in total. The fourth question was related to the competition intensity of local financial institutions, which had nothing to do with this study; so, it was deleted. Finally, four questions were included in this study (“There are alternative finance sources for student entrepreneurs;” “Low-interest loans offered by banks are accessible;” “Start-up funds offered by the school/government are accessible;” “A variety of loan guarantee options are available”). The score of each item ranged from 1 (very disagree) to 5 (very agree). In this study, the Cronbach’s alpha was 0.873.

The green entrepreneurial intention scale is a 6-item scale compiled by Wang et al. (2016). The six questions are (“I will do anything to become a green entrepreneur;” “My professional goal is to become a green entrepreneur;” “I will make every effort to establish and operate my own green business;” “I am seriously considering starting a green business;” “I am determined to become a professional green business manager;” “I am committed to developing my green business into a high-growth enterprise”). Each item is scored on a 5-point Likert scale and used to answer the questions (1 = “very disagree” to 5 = “very agree”). In this study, the green entrepreneurial intention scale had good reliability (Cronbach’s alpha = 0.778). All these items are shown in Table 1.

The calibration of variables refers to the process of collective membership of grouping the condition variables (entrepreneurial creativity, future self-continuity, green cognition, entrepreneurship culture, entrepreneurship education, financial support) and the outcome variable (green entrepreneurial intention), which transforms the original data of the condition and outcome variables into a fuzzy set membership score of 0–1. Three critical values need to be set: the fully in point, crossover point, and fully out point (Ragin, 2008). In this study, the data were calibrated according to the standard proposed by Fiss (2011): 75% (fully in), 50% (crossover point), and 25% (fully out). First, the percentile of the data was calculated using SPSS, and the thresholds of the fully in point, the crossover point, and the fully out point were set to the 75th, 50th, and 25th percentiles of each variable, respectively. The calibration anchors for each variable are listed in Table 2. Furthermore, the calibration function in fs/QCA3.0, was used to calibrate each variable, with each variable set after calibration belonging to 0∼1.

If the necessary condition is included in the truth table analysis, it may be eliminated by parsimonious solution. The consistency threshold of the necessity analysis is 0.9. If the condition variable exceeds 0.9, it indicates that the condition variable constitutes a necessary condition. When an outcome occurs, a condition always exists (when the condition is missing, the outcome cannot occur). Then, the explanatory power of this condition variable on the outcome variable is stronger than that of the other condition variables. Table 3 shows the necessity analysis results for college students’ high green entrepreneurial intention. Because the consistency of each condition is not higher than 0.9, there is no need for separate conditions for high green entrepreneurial intention.

The fuzzy set truth table algorithm of the fsQCA software is used to select the outcome and condition variables of the model, and the truth table is generated automatically. Furthermore, the consistency threshold and case threshold of the variables must be set. Variable consistency refers to the probability that the combination of condition variables has a decisive explanatory power on the outcome variable. The higher the threshold, the higher the explanatory probability. A consistency threshold of 0.8 indicates a good and robust subset relation (Fiss, 2011; Bell et al., 2014; Campbell et al., 2016). Case coverage refers to the number of cases that can be covered by a specific condition variable, a combination of variables, or the number of acceptable cases. The larger the value, the more cases in which the condition variable can lead to key results. In general, the case threshold is set to 1 (Ragin, 2008; Hernandez-Perlines et al., 2016). In addition, we need to review the proportional reduction in inconsistency (PRI) to reduce the contradictory configurations. If it was less than 0.7, the outcome variable was set to 0. Finally, based on fs/QCA3.0, three types of solutions were obtained: complex, intermediate, and parsimonious. The intermediate solution reflects the easy counterfactuals (consistent with theory or substantive knowledge), while the parsimonious solution reflects difficult counterfactuals (inconsistent with theory or substantive knowledge). The existence of both intermediate and parsimonious solutions can determine the core conditions.