Outcomes of entrepreneurship education in China: A customer experience management perspective

Journal of Business Research 103 (2019) 338–347

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Outcomes of entrepreneurship education in China: A customer experience management perspective☆ Xinhua Doua, Xiajing Zhua,

⁎,1

a b

T

, Jason Q. Zhangb,1, Jie Wanga,1

Jiangnan University, China Loyola University Maryland, USA

ARTICLE INFO

ABSTRACT

Keywords: Entrepreneurship education Service goods Customer experience Entrepreneurship attitude & intention Customer experience management

Although important to business and economic development, entrepreneurship education has offered its customers (i.e., students) mixed experiences. While some prior studies find entrepreneurship education to have a positive effect on entrepreneurial attitude or activities, others report the opposite, suggesting the need to consider environmental factors. Drawing on the nascent research on customer experience management, this study treats entrepreneurship education as a service product and advocates that service providers take a “touchpoint journey view” in that the providers should manage or influence all touchpoints in the environment—some touchpoints are internal to the providers, while others may be external. This perspective leads to a comprehensive conceptual model that identifies ten student-resource touchpoints across three areas: a) curricular b) regulatory environment, and c) social environment resources. With a unique sample of students who are systematically exposed to all three types of resources through a pilot entrepreneurship program, this study finds empirical evidence to support the proposed model. These findings offer pertinent implications to entrepreneurship education design (e.g., totality of various touchpoints). In addition, with the rising influence of the Chinese economy, this study also represents a meaningful step toward a better understanding of consumers' service goods experience in this strategically important market.

1. Introduction As entrepreneurial activities are found to be an important antecedent of economic competiveness and innovation capacity (e.g., Galindo & Méndez, 2014; Pagano, Petrucci, & Bocconcelli, 2018; Rotger, Gørtz, & Storey, 2012), many developed economies have invested heavily in entrepreneurship education at universities (e.g., Brush, Bruin, & Welter, 2009; Katz, 2003). China, as a fast-growing economy, has firmly embraced the importance of entrepreneurship education and actually made it a national priority. Since 2014, the Chinese government has proposed a nation-wide strategic initiative to stimulate entrepreneurship and innovation in order to fuel continued economic growth. At the center of this initiative, Chinese educational institutions, particularly universities, have developed and implemented many innovative systems (e.g., efforts beyond regular curricular designs) to deliver entrepreneurship education (MyCOS, 2018). Such education aims to promote young people's entrepreneurial competency and, more importantly, their attitude toward and intention of

entrepreneurial career choices. Entrepreneurship education, however, has offered its customers (i.e., students) very mixed experience (Walter, Parboteeah, & Walter, 2013). Specifically, while some prior studies reveal that entrepreneurship education fosters entrepreneurial attitude, intention or behavior through enhanced entrepreneurial interest and competency (e.g., Bae, Qian, Miao, & Fiet, 2014; Kuratko, 2005; Martin, McNally, & Kay, 2013), others find rather the opposite—a negative effect of entrepreneurship education (e.g., Oosterbeek, van Praag, & Ijsselstein, 2010; von Graevenitz, Harhoff, & Weber, 2010). This discouraging effect occurs arguably because students going through entrepreneurship education become more realistic about their ability and resource limitations in obtaining success. These mixed effects suggest that there may be other environmental factors that impact the overall effect of entrepreneurship education. To address the above gap, the objective of this research is three-fold. First, treating entrepreneurship education as a service product and students as its customers, we take a customer experience perspective in

This study was supported by the Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (KYCX17_1475). Corresponding author. E-mail address: [email protected] (X. Zhu). 1 All authors contributed equally to the paper. ☆ ⁎

https://doi.org/10.1016/j.jbusres.2019.01.058

Available online 07 February 2019 0148-2963/ © 2019 Elsevier Inc. All rights reserved.

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understanding the outcomes of entrepreneurship education (e.g., Homburg, Jozić, & Kuehnl, 2017; Lemon & Verhoef, 2016). Drawing on the nascent literature of customer experience management, we argue that entrepreneurship education providers (i.e., universities) need to take a “journey” view in designing educational experience (Voorhees et al., 2017). More specifically, university-based curricular and extracurricular offerings represent only one type of student-resource touchpoints in students' journeys of experiencing entrepreneurship. Two other types of environmental resources, namely regulatory environment resources (e.g., entrepreneurship-friendly public policies) (Walter & Block, 2016) and social environment resources (e.g., entrepreneur mentorship) (Eesley & Wang, 2017) may all come into play to influence students' overall experience. While both regulatory and social environment resources are external to educational institutions, education programs can purposely integrate and align external student-resource touchpoints to expand and enhance “customers' journeys and thus customer experience in their related environments” (Homburg et al., 2017, p. 389). This “alliance orientation” is the central view to customer experience management (Homburg et al., 2017), which represents a response to earlier research's call of placing universities at the center of integrating external resources in order to create an effective and more holistic experience for young entrepreneurs (Jansen, Zande, Brinkkemper, Stam, & Varma, 2015). Second, through extensive literature review, we propose a comprehensive conceptual model that identifies ten student-resource touchpoints in three separate areas: a) curricular and extracurricular resources, b) regulatory environment resources, and c) social environment resources. All would be meaningful in shaping students' experiences with entrepreneurship education. Thirdly, we empirically test this conceptual model with a unique field study in which a sample of university students participated in a pilot entrepreneurship program that gave them systematic and institutionalized access to all three types of resources (i.e., curricular/extracurricular, regulatory, and social resources). This unique sample allows us to assess the outcomes of conventional curricular/extracurricular factors, in conjunction with environmental factors, simultaneously. With data from this pilot field study, we show that when other environmental resources are organically integrated into entrepreneurship education, curricular and extracurricular offerings have positive effects in forming students' entrepreneurial attitudes. In addition, though some prior research points out that the supervisory nature of government regulations and policies may restrict people's entrepreneurial desire (Hwang & Powell, 2005), we find that university entrepreneurship programs can play a positive role in helping students explore the regulatory environment, thus reducing their cognitive barriers in understanding rules and policies. In addition, students may become more cognizant of entrepreneurship-friendly policies and government funding opportunities, all positively shaping their entrepreneurial attitude. In fact, our sample shows that perceived support from the regulatory environment is the most important factor in shaping entrepreneurial attitude, highlighting the role of public policy makers in fostering entrepreneurial activities (e.g., Schwarz, Wdowiak, Breitenecker, & Kuntaric, 2009; Stel, Storey, & Thurik, 2007). Lastly, our data supports the role of social resources on entrepreneurship education experience, supporting research from other countries (e.g., Eesley & Wang, 2017; Kenney & Goe, 2004; Roach & Sauermann, 2015). This study aims to make several important contributions. First, we add to the ongoing debate on the effect of entrepreneurship education (e.g., Oosterbeek et al., 2010; von Graevenitz et al., 2010; Walter et al., 2013; Walter & Dohse, 2012) by showing a Chinese case that entrepreneurship curricular/extracurricular resources help develop young people's entrepreneurial attitude and intention. Additionally, different from earlier studies that tend to focus on entrepreneurship curriculum (e.g., Athayde, 2009; Peterman & Kennedy, 2003; Sánchez, 2013; Souitaris, Zerbinati, & Al-Laham, 2007) or instructional design (Eesley

& Wang, 2017), we advocate a customer experience view. That is, an entrepreneurship program needs to collaborate with external environmental resources to enhance customers' entire journey experience and thus the outcomes. Entrepreneurship classes are important. In fact, their mere existence is important to signaling the desirability of entrepreneurship (Walter et al., 2013). But as our study shows, regulatory and social environment factors also matter. Many of these factors should be deliberately woven into entrepreneurship programs (e.g., mentorship; access to capital through alumni networks). Lastly, our conceptual model maps out ten student-resource touchpoints to offer directions for innovative entrepreneurship program design—an area interesting to service experience researchers, curriculum designers, public policy makers, and entrepreneurial communities alike. In the following sections, we first review relevant literature, and develop our conceptual model. We then describe our data, analysis methods, and findings. Finally, we discuss implications and directions for future work. 2. Conceptual framework 2.1. Customer experience management Customer experience is an emerging marketing concept that is important to both theory and practice (Lemon & Verhoef, 2016). Abbott (1955, p. 40) stated “what people really desire are not products but satisfying experiences.” Subsequently, in 1998, Pine and Gilmore's seminal article on the experience economy elevated interest in customer experience as an important source of product/service success (Pine II & Gilmore, 1998). Since then, a growing body of research has informed the development of the concept, including, for example, customer satisfaction and loyalty (e.g., Zeithaml, 1988), service quality (e.g., Parasuraman, Zeithaml, & Berry, 1988), customer relationship management (e.g., Bolton, Lemon, & Verhoef, 2004), customer centricity (e.g., Sheth, Sisodia, & Sharma, 2000), and customer engagement (e.g., Kumar, Andrew Petersen, & Leone, 2010). Recently, the customer experience concept was also brought to the studies of Chinese consumers (e.g., Jiang, Luk, & Cardinali, 2018). For the purposes of this research, we follow Lemon and Verhoef (2016) and define customer experience as a customer/student's journey with a service provider over his/her entire journey. That is, the totality of a customer's experience with an education program across multiple touchpoints. Homburg et al. (2017) found that firms that had a “touchpoint journey orientation” emphasized managing or influencing all touchpoints in the environment—some touchpoints are internal to the firms; while others may be external (Nambisan & Watt, 2011). This view provides a useful framework to design an effective entrepreneurship education program that considers students' points of interaction with three types of resources: curricular/extracurricular, regulatory, and social resources. In terms of the level of control (Lemon & Verhoef, 2016), curricular/extracurricular touchpoints are managed/owned by universities. The latter two types of student-resource touchpoints can be influenced/facilitated by universities. Below, we discuss them separately. 2.2. University entrepreneurship curricular/extracurricular resources It is now very common to find university level entrepreneurship curriculum. In fact, prior research suggests that many developed countries have heavily invested in entrepreneurship education at universities (e.g., Brush et al., 2009; Katz, 2003). This investment of educational resources is based on the realization that successful entrepreneurs tend to have certain dispositions, skills, and competencies (Rauch, Frese, & Utsch, 2005; Unger, Rauch, Frese, & Rosenbusch, 2011). Clearly, education plays an important role in developing individuals' skills and competencies (Kuratko, 2005). Some research also suggests that education may even influence individuals' dispositions by 339

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signaling social acceptability or desirability of entrepreneurship activities (Walter & Block, 2016). Recent meta-analysis in this area (e.g., Bae et al., 2014; Martin et al., 2013) shows increased scholarly attention to entrepreneurship education and its outcomes. In examining student experience or the effectiveness of entrepreneurship education, many prior studies have looked at specific curricular or extracurricular offerings, including lectures (Boyles, 2012; Oosterbeek et al., 2010), pitch competitions (Lüthje & Franke, 2002), student associations (Menzies & Paradi, 2003; Moen & Kolvereid, 1997; Trivedi, 2017) and career guidance/services (Du & Wang, 2015; Walter & Block, 2016). All of the above resources, curricular or extracurricular, constitute university-owned touchpoints that shape students' entrepreneurship education experience. More specifically, university lectures about entrepreneurship focus primarily on raising awareness about entrepreneurship by teaching students various aspects of starting and running a business (e.g., Oosterbeek et al., 2010). Common themes include developing knowledge and skills that increase the likelihood of starting a business and success of entrepreneurs (e.g., Boyles, 2012), identifying and stimulating entrepreneurial drive (Gibb, 2008; Glaub & Frese, 2011), and preparing business proposals as well as creating new ventures (Rasmussen, Moen, & Gulbrandsen, 2006). Various prior studies, across a broad variety of contexts and countries, have found that entrepreneurship lectures are valuable to students (e.g., Athayde, 2009; Peterman & Kennedy, 2003; Sánchez, 2013; Souitaris et al., 2007; Walter et al., 2013; Walter & Dohse, 2012). We expect Chinese college students are no exception. Other than formal curriculum, university entrepreneurship education may also involve other extracurricular offerings or touchpoints from the perspective of customer experience. Two most common types of such offerings are business idea pitch competitions and student associations with an entrepreneurship spirit (Lüthje & Franke, 2002; Menzies & Paradi, 2003; Trivedi, 2017). These university-based extracurricular offerings allow students to apply their knowledge and skills acquired from entrepreneurship lectures (Neck & Greene, 2011), as in the case of pitch competitions, and to get inspiration and encouragement from peer groups (Coduras, Urbano, Rojas, & Martínez, 2008), as in the case of student associations. As a result, students are likely to find these offerings to be valuable. Lastly, career guidance and services offer students guidelines with a long term vision for career planning. These guidelines may help students realize their entrepreneurial potential (Eesley & Wang, 2017). Liñán and Chen (2009) pointed out that the entrepreneurial attitude not only means that one likes or dislikes entrepreneurial activities, but also includes one's evaluative considerations. For instance, one examines the advantages/disadvantages to being an entrepreneur. Thus, career guidance and services serve as an important resource to influence student experience. In light of the above, university-owned entrepreneurship education resources, curricular or extracurricular, may work together to increase students' entrepreneurial self-efficacy, and thus influence students' perception and preference of being an entrepreneur, or their entrepreneurial attitude (Autio et al., 2001; Autio et al., 2012). We therefore hypothesize the following.

activities, including for example, local politics, control of corruption, entrepreneurs' roles/status in the society, policies and regulations, and public funding (e.g., Lim, Morse, Mitchell, & Seawright, 2010; Rotger et al., 2012; van Praag & Versloot, 2007; Walter & Block, 2016). Not enough attention, however, has been paid to the consideration of how to formally integrate these external factors into university-based entrepreneurship education in order to enhance overall student experience. In the context of university entrepreneurship education, we focus on two regulatory environment resources: entrepreneurship-friendly policies and government funding opportunities that can be integrated into the journey design of entrepreneurship education. Entrepreneurshipfriendly policies are linked to the creation of a fruitful environment and atmosphere for entrepreneurs (Hart, 2003). Such policies encourage people to participate in entrepreneurial activities and increase the survival rate of start-ups. Many Chinese universities work closely with public policy makers to create school-based incubators, preferential policies for college entrepreneurs (e.g., tax breaks and reduced fees), and coaching services on new business regulations. Likewise, public funding opportunities or availability is found to be linked to people's participation in entrepreneurial activities (Autio et al., 2012). In China, such monetary support can take the form of either government-backed funding programs (e.g., low-interest loans or equity funds) or subsidies (e.g., medical insurance subsidies). These types of resources are often distributed through or facilitated by university-based entrepreneurship education programs. When universities cooperate with regulatory environment resources and bring students to close contact with entrepreneurship-friendly policies and public funding opportunities, such student-resource interactions will enhance the students' journey experience (e.g., from learning to doing) in entrepreneurship education. We thus hypothesize: H2. Regulatory environment resources, manifested in a) entrepreneurship-friendly policies, and b) government funding opportunities, are perceived to be valuable in forming students' entrepreneurial attitude. 2.4. Social environment resources Earlier studies have found ample evidence to show that the decision to start a business is a social one (e.g., Burt, 1995; Dobrev & Barnett, 2005; Qin & Estrin, 2015; Shu, Ren, & Zheng, 2018). Research has shown that a person's willingness to become an entrepreneur is positively related to his/her exposure to entrepreneurship through those around him/her (Nanda & Sørensen, 2010). Thus, working with experienced entrepreneurs and successful alumni, who have themselves engaged in entrepreneurial activities (Lerner & Malmendier, 2013; Nanda & Sørensen, 2010), would affect how students experience entrepreneurship education. After reviewing relevant literature and considering the context of university entrepreneurship education, we choose to focus on four types of social environment resources that potentially can be built into university ecosystem for enhanced student experience: entrepreneurial experience/knowledge sharing (Collins, Smith, & Hannon, 2006; Johannisson, Landstrom, & Rosenberg, 1998; Mwasalwiba, 2010), b) entrepreneurial mentorship (Mwasalwiba, 2010; Robinson & Haynes, 1991), c) alumni funding opportunities (Lerner & Malmendier, 2013), and d) social network capital (Eesley & Wang, 2017). We briefly discuss them in order. University students typically lack first-hand experience in starting a business. This lack of experience or real world skills is cited as the most important barrier to entrepreneurial activities (Eesley & Wang, 2017). Universities, with their alumni networks and connections to business communities, can bring experienced individuals to campus to facilitate the exchange of entrepreneurial knowledge and experience (Bennett, 2006). In China, through establishing entrepreneur/executive clubs and

H1. University entrepreneurship curricular/extracurricular resources, manifested in a) lectures, b) pitch competitions, c) student associations, and d) career guidance/service, are perceived to be valuable in forming students' entrepreneurial attitude. 2.3. Regulatory environment resources Public policies can have a substantial impact on the development of entrepreneurship activities (e.g., Brush et al., 2009; Katz, 2003; Yoon, Kim, Buisson, & Phillips, 2018). Prior studies have found many regulatory environment factors that are linked to entrepreneurship 340

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customer experience management, the design of this education service expanded customers/students' journeys beyond institution/university owned resources (i.e., curricular/extracurricular offerings) (Lemon & Verhoef, 2016). The expanded journey included points of interaction with government-backed resources such as training on innovation and entrepreneurship policies, local government-backed incubators, simplified policies and fee/tax structures for college entrepreneurs, and government funding opportunities. Though many of the above resources are existing ones, this program aligned students' curricular/ extracurricular activities with regulatory environment resources by bringing many resources to university campus and by requiring students' exposure to, and involvement with, such resources. Likewise, in the area of social environment resources, each student throughout his/her entire university career, was paired up with an entrepreneurial mentor—either an entrepreneur or high level business executive connected to the university's surrounding communities. Every student in this pilot program was paired-up, again, by the design of the program. The involved entrepreneurial mentors and their contacts, supported many angel funds, crowd-funding platforms, business idea pitch competitions, and various outreach activities. In the area of curricular/extracurricular design, all students were required to take entrepreneurship and career planning classes. All were also required to take part in university/government supported business idea pitch competitions. Performance in these competitions would be evaluated when students were considered for academic awards and scholarships. The structural design of this pilot entrepreneurship education program ensured students' access to all three types of resources that we considered in this paper. The mindset (and efforts) of this program to align students' experiences with the resources from beyond the control of the university is at the very heart of customer experience management—the alliance orientation (Homburg et al., 2017). As such, this unique program offers us an ideal context to gather data and empirically test our proposed model of entrepreneurship education. After all, respondents' evaluations of resources are most meaningful and reliable when respondents are actually exposed to the resources and have access to them. We administered a survey to students who were enrolled in the above pilot program. Four hundred sixty-five students took part in the survey, with an effective sample of 417 (89.68% response rate). The sample comprised of 184 (44.10%) male students and 233 (55.90%) female students, with a mean participant age of 20.81 years. Table 1 presents more information on sample descriptive statistics.

advisory boards, many entrepreneurship education programs aim to involve high impact individuals to share their experience/knowledge with students, closing the experience gap in this area. Entrepreneurial mentorship is related to entrepreneurial experience sharing, but mentorship is more involved and hands-on (Tan & Ng, 2006). Research has found that experienced mentors could be the most important social influence on an individual's career choice of starting a business (Boyd & Vozikis, 1994). Alumni with entrepreneurial backgrounds often provide direct counseling to students and help them identify the value of their business ideas (Lerner & Malmendier, 2013). Further, industry mentors may share their thoughts and opinions with students and help eliminate information barriers (Eesley & Wang, 2017). Alumni funding opportunities represent a major source of angel capital in college entrepreneurship (Lerner & Malmendier, 2013). Such funding may directly lower the financial barrier for college students to start their businesses (Shane & Cable, 2002; Wang, 2016). In addition, entrepreneur alumni may help students to identify and secure more sources of capital through their social networks (Wang, 2016). Eesley and Wang (2017) also note that entrepreneur alumni may have more financial management experience. Transfer of such experience to college students may also help them close financial gaps. An entrepreneur's social network capital is found to be related to entrepreneurial activities (Kenney & Goe, 2004). A network of entrepreneurs and related people facilitates the exchange of ideas, opportunities, and knowledge. Such exchange is found to be beneficial not only to college entrepreneurs but also to established entrepreneurs who may be running businesses (Elert, Andersson, & Wennberg, 2015). Effective dissemination of information, after all, benefits everyone involved in the social network (Qin & Estrin, 2015). To sum up, as universities are often at the center of alumni-based social systems, universities are at a unique position to bring together various social environment resources and expand students' entrepreneurship education journey to touchpoints rooted in extended social connections. In light of the above, we hypothesize that H3. Social environment resources, manifested in a) entrepreneurial experience/knowledge sharing, b) entrepreneurial mentorship, c) alumni funding opportunities, and d) social network capital, are perceived to be valuable in forming students' entrepreneurial attitude. 2.5. Entrepreneurial attitude and intention The theory of planned behavior (Ajzen, 1991) suggests that one's intention to perform a given behavior is the result of one's attitude toward the behavior—the more favorable one's attitude toward a behavior, the higher his/her intention toward that behavior. In light of this, one's entrepreneurial attitude is expected to lead to his/her entrepreneurial intention, leading to H4. Fig. 1 summarizes all the hypothesized relationships.

3.2. Measures All measures used in this study were adapted from existing scales. Unless otherwise specified, all items were measured on 7-point Likert scales anchored by “Strongly Disagree (1)” and “Strongly Agree (7)”. All the items were first translated from English to Chinese and then translated back to English to ensure accuracy in item definition. In addition, before the survey's formal launch, we conducted pretests and expert interviews to determine the accuracy of the items. A complete list of measurement items appear in Appendix 1.

H4. Students' entrepreneurial attitude positively influences their entrepreneurial intention. 3. Methods

3.3. Outcome measures

3.1. Data

3.3.1. Entrepreneurial attitude Entrepreneurial attitude measures students' perception and preference toward being an entrepreneur (Autio et al., 2012; Liñán & Chen, 2009). We included three items for this construct: “Being an entrepreneur implies more advantages than disadvantages to me”; “Being an entrepreneur would entail great satisfaction for me”; “A career as an entrepreneur is attractive for me”, following the study by Liñán and Chen (2009). We averaged all the items to form a composite measure (composite reliability = 0.844).

We collected our data from a unique field study in which a large public university in Southeastern China has designed and implemented a pilot entrepreneurship education program that offered students access to all three types of resources, i.e., curricular/extracurricular, regulatory, and social resources. Different from many other universities or programs, this entrepreneurship education program integrated and institutionalized student access to external resources by the design of the program and explicit structural requirements. From the perspective of 341

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Lectures 0.783 Pitch Competitions

0.793 Perceived Value of University-Owned Resources

0.834 Student Associations 0.861

0.280

Career Guidance/Service Entrepreneurship-Friendly Policies

0.876 0.881

Government Funding Opportunities

0.823

Entrepreneurial Intention

0.886 0.892 0.830

Alumni Funding Opportunities

Entrepreneurial Attitude

0.246

Entrepreneurial Experience/Knowledge Sharing Entrepreneurial Mentorship

Perceived Value of 0.302 Regulatory Environment Resources

Perceived Value of Social Environment Resources

0.829

Social Network Capital

Fig. 1. Entrepreneurial education: student-resource touchpoints and outcomes.

3.3.2. Entrepreneurial intention Three items, based on previous research (Chen, Greene, & Crick, 1998; Liñán & Chen, 2009), were used to measure the students' intention of becoming an entrepreneur, including “My professional goal is to become an entrepreneur”, “I will start a business no matter what difficulties I meet”, and “I am very likely to start my own business in the next five years.” We averaged all the items to form a composite measure (composite reliability = 0.830).

above 0.7; b) the average of variance extracted (AVE) should be above 50%; and c) the composite reliability should be above 0.6, and preferably above 0.7 (Byrne, 2001; Fornell & Larcker, 1981; Hair, Black, Babin, & Anderson, 2013). The results of CFA showed that the standardized regression weights of 35 items in our research ranged from 0.654 to 0.873. Most of the values were above 0.7. The AVE of all 10 factors were ranging from 50.68% to 71.81% — all above 50%. In addition, the values of composite reliability demonstrated a high degree of consistency and reliability for all the included measures, ranging from 0.755 to 0.884. Table 2 presents finer details on factor loading, AVE, and reliability statistics.

4. Results 4.1. Confirmatory factor analysis Before we fit the data to our conceptual model using Structural Equation Modeling (SEM), the psychometric properties of our items were evaluated through a comprehensive confirmatory factor analysis (CFA) by using SPSS Amos 22. Following previous research, we used the following criteria for goodness-of-fit: a) the standardized regression weight (factor loading) values should be above 0.5 and preferably

4.2. Model development In searching for the best-fit model, we used chi-square tests and goodness-in-fit indices to guide model development. A smaller chisquare value indicates a better model fit. But chi-square tests are quite sensitive to sample size. Thus, we also considered several goodness-in-

Table 1 Sample summary statistics. Gender Year

Family income ($/year)

Male Female 1 2 3 4 < 8800 8800–17,600 17,600–26,400 26,400–35,200 35,200–44,000 44,000–52,000 > 52,800

184 233 38 200 146 33 109 165 76 29 17 7 14

44.10% 55.90% 9.10% 48.00% 35.00% 7.90% 26.10% 39.60% 18.20% 7.00% 4.10% 1.70% 3.40%

Level of education (father)

Level of education (mother)

Age

342

Primary school Middle school High school Associate degree College Graduate school Primary school Middle school High school Associate degree College Graduate school Average

29 135 116 58 70 9 61 140 108 59 45 4 20.81

7.00% 32.40% 27.80% 13.90% 16.80% 2.10% 14.60% 33.60% 25.90% 14.10% 10.80% 1.00% /

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Table 2 Measurement model statistics. Second-order factors

First-order factors

Items

Standardized regression weight

Regression weight

Perceived value of university entrepreneurship curricular or extracurricular resources

Lectures

Lv1 Lv2

0.861 0.864

Lv3 Pitch competitions

Student associations

Career guidance/ service Perceived value of regulatory environment resources

Entrepreneurship friendly policies

Government funding opportunities

Perceived value of social environment resources

Entrepreneurial experience/ knowledge sharing

Entrepreneurial mentorship

Alumni funding opportunities

Social network capital

S.E.

t-Value

AVE

Composite reliability

1 0.921

0.046

0.709

0.758

0.048

Cv1 Cv2

0.755 0.786

1 0.971

20.168 (< 0.01) 15.871 (< 0.01)

66.35%

0.855

0.066

59.25%

0.814

Cv3

0.768

1.055

0.073

Av1

0.764

0.977

0.066

57.46%

0.802

Av2

0.726

0.958

0.068

Av3 Cv1 Cv2

0.783 0.771 0.788

1 1 0.980

0.061

64.48%

0.845

Cv3

0.848

1.116

0.065

Pv1 Pv2

0.717 0.721

1 1.077

0.079

56.48%

0.838

Pv3

0.739

1.167

0.084

Pv4

0.824

1.216

0.080

Fv1 Fv2

0.873 0.871

1 0.929

0.042

71.81%

0.884

Fv3

0.796

0.886

0.045

Ev1 Ev2

0.697 0.751

1 1.066

0.082

50.68%

0.755

Ev3

0.686

0.939

0.078

Mv1 Mv2

0.776 0.749

1 0.939

0.064

14.712 (< 0.01) 13.897 (< 0.01)

55.48%

0.789

Mv3

0.708

0.968

0.070

Ov1 Ov2

0.820 0.846

1 0.942

0.052

18.034 (< 0.01) 14.177 (< 0.01)

61.55%

0.826

Ov3

0.677

0.750

0.053

Nv1 Nv2

0.654 0.808

1 1.149

0.084

13.754 (< 0.01)

59.67%

0.854

14.737 (< 0.01) 14.472 (< 0.01) 14.847 (< 0.01) 14.163 (< 0.01) 16.098 (< 0.01) 17.220 (< 0.01) 13.568 (< 0.01) 13.871 (< 0.01) 15.277 (< 0.01) 22.347 (< 0.01) 19.612 (< 0.01) 12.984 (< 0.01) 12.081 (< 0.01)

Table 3 Model development and goodness-of-fit statistics. Models (N = 417)

χ2

d.f.

RMSEA

SRMR

CFI

Model 1 Basic model Model 2 Only first-order factors Model 3 First-order factors and one general second-order factor Model 4 Three second-order factors (proposed model)

3475.223

665

0.101

0.3037

0.684

–

–

–

2947.455

654

0.092

0.2829

0.742

2 vs 1

−527.768

−11

1517.327

653

0.056

0.075

0.903

3 vs 2

−1430.128

−1

1094.390

648

0.041

0.046

0.950

4 vs 3

−422.937

−5

fit indices, following the guidelines of Hu and Bentler (1999) and Browne and Cudeck (1992). More specifically, the root mean squared error of approximation (RMSEA) of 0.05 or less indicates a great fit, while 0.08 or less indicates an adequate fit. The standardized root mean square residual (SRMR) of < 0.08 indicates to a good fit. Lastly, the

Model comparison

∆χ2

∆d.f.

Comparative fit index (CFI) of 0.90 or greater offers evidence of adequate fit. The fit statistics for each model are presented in Table 3. In model development, we considered different model specifications. Model 1 is the basic model (null model) with no path linking the independent variables and the dependent variables. Models 2 to 4 are 343

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Table 4 SEM model estimates. Hypotheses and paths

Standardized regression weight

Regression weight

S.E.

t-Value

Hypothesis testing

H1

University → lectures

0.783

1.076

0.089

Supported

University → pitch competitions

0.793

0.841

0.076

University → student associations

0.834

0.978

0.083

University → career guidance/service University → entrepreneurial attitude

0.861 0.280

1 0.274

12.109 (< 0.01) 11.127 (< 0.01) 11.786 (< 0.01)

0.069

Regulatory environment → entrepreneurship-friendly policies Regulatory environment → government funding opportunities

0.876 0.881

1 1.53

3.980 (< 0.01)

0.132

Regulatory environment → entrepreneurial attitude

0.302

0.408

0.103

Social environment → entrepreneurial experience/knowledge sharing Social environment → entrepreneurial mentorship

0.886 0.892

1 1.053

11.555 (< 0.01) 3.943 (< 0.01)

0.091

Social environment → alumni funding opportunities

0.830

1.273

0.111

Social environment → social network capital

0.829

0.933

0.092

Social environment → entrepreneurial attitude

0.246

0.303

0.084

Entrepreneurial attitude → entrepreneurial intention

0.823

1.051

0.078

H2

H3

H4

designed to test whether or not various higher order models would provide a better fit to the data. For this reason, the higher order factor models were tested separately. Model 2 builds on model 1 by adding paths between 10 first-order factors and dependent variables. Model 2 (M2: χ2 = 2947.455, d.f. = 654; CFI = 0.742; RMSEA = 0.092) fits the data slightly better than Model 1 (M1: χ2 = 3475.223, d.f. = 665; CFI = 0.684; RMSEA = 0.101). Model 3 includes one general secondorder factor (i.e., perceived value of all student-resource touchpoints) to explain the co-variances among the first-order factors. Models 3 and 2 differ by only 1 degree of freedom, but the improvement is statistically significant which supports that a high order factor model would be preferred to fit our data (M3: χ2 = 1517.327, d.f. = 653; CFI = 0.903; RMSEA = 0.056). Model 4 is the hypothesized (target) model which contains three second-order factors. This model's fit indices suggest that Model 4 fits our data better than Models 3, 2, and 1 (M4: χ2 = 1094.390, d.f. = 648; CFI = 0.950; RMSEA = 0.041). In conclusion, Model 4 (the proposed model) shows the best goodness-of-fit and is our final model.

11.550 (< 0.01) 11.489 (< 0.01) 10.126 (< 0.01) 3.620 (< 0.01) 13.400 (< 0.01)

Supported

Supported

Supported

(β = 0.246, t = 3.620, p < .01), supporting H3. Four types of studentresource touchpoints contribute to the perceived value of social environment resources: experience/knowledge sharing (β = 0.886), entrepreneurial mentorship (β = 0.892), c) alumni funding opportunities (β = 0.830), and d) social network capital (β = 0.829). Lastly, students' attitude toward entrepreneurship positively influences their intention of starting their own businesses (β = 0.823, t = 13.400, p < .01), supporting H4. Finer details on model estimates appear in Table 4 and Fig. 1. 5. Conclusions and discussion As a critical component of business and economic development, entrepreneurship education has become a very popular subject at educational institutions, including universities (e.g., Walter & Block, 2016), high schools (e.g., Peterman & Kennedy, 2003), and even primary schools (e.g., Huber, Sloof, & van Praag, 2014). This popularity has sparked increased scholarly attention to examine the outcomes of entrepreneurship education (Dickson, Solomon, & Weaver, 2008; Pittaway & Cope, 2007). Prior studies appear to suggest mixed effect of entrepreneurship education (Bae et al., 2014); some, in fact, question if educational curriculum alone can change people's willingness to start their own businesses (e.g., Oosterbeek et al., 2010). Our study meaningfully adds to this on-going debate by offering new field-based insights from China. We show that when other environmental resources are deliberately integrated into university-based entrepreneurship education, university curricular or extracurricular offerings are helpful in forming young people's entrepreneurial attitudes and intentions—justifying the role universities play in developing entrepreneurial activities. That said, we find that regulatory environment resources also matter. In fact, they are perceived to be more important than university-controlled resources (e.g., curriculum)—highlighting the importance of considering external environment factors in entrepreneurship education. Viewing entrepreneurship education as a service product, we advocate that service providers should take a “journey” view in delivering student experience (Lemon & Verhoef, 2016). Central to the emerging theoretical perspective of customer experience management, customer

4.3. Results First, our data suggest that students perceive university-based curricular/extracurricular resources to be valuable in enhancing entrepreneurial attitude (β = 0.280, t = 3.980, p < .01), supporting H1. Four types of student-resource touchpoints work together to shape students' perception toward university entrepreneurship curricular/extracurricular offerings: lectures (β = 0.783), pitch competitions (β = 0.793), student associations (β = 0.834), and career guidance/ service (β = 0.861). Second, the results of our analysis suggest that students perceive regulatory environment resources to be valuable to entrepreneurial attitude (β = 0.302, t = 3.943, p < .01), supporting H2. Two types of student-resource touchpoints positively contribute to the perceived value of regulatory environment resources: entrepreneurship-friendly policies (β = 0.876) and government funding opportunities (β = 0.881). Thirdly, there is evidence to support that students perceive social environment resources to be important to entrepreneurial attitude 344

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journey view acknowledges that providers' internal resources, although important, tend to cover only a portion of the customer experience journey. Education providers should seek to collaborate with external resources to align student-resource touchpoints along the entire journey (Homburg et al., 2017). Guided by customer experience management view, we identified ten student-resource touchpoints that would influence students' experience with university entrepreneurship education. Using data from a pilot entrepreneurship education program in China, we were able to find sample subjects who were systematically exposed to all these touchpoints, and therefore were able to assess their effects. Evidence from our study supports the importance of external factors in influencing the outcomes of entrepreneurship education. For entrepreneurship education providers, public policy makers, and entrepreneurial communities, our study offers a markedly different perspective—a holistic journey view. While earlier studies have examined various student-resource touchpoints, such as entrepreneurship classes (e.g., Menzies & Paradi, 2003; Oosterbeek et al., 2010), pitch competitions (Lüthje & Franke, 2002; Trivedi, 2017), experiential exercises (Coduras et al., 2008; Neck & Greene, 2011), and entrepreneurial mentorship (Eesley & Wang, 2017), these studies tend to focus on separate touchpoints. Our study focuses on the totality of multiple touchpoints (Roundy, Brockman, & Bradshaw, 2018). New arrangement of touchpoints and/or expansion of touchpoints would lead to new ideas of designing entrepreneurship education and enhancing its effects. We view the identified ten student-resource

touchpoints as the first steps toward designing innovative and effective entrepreneurship education programs. With the rising importance of emerging economies, this study is a meaningful step to better understand Chinese consumers and their behaviors as related to service goods. China is presently the second largest economy (UNCTD, 2017). According to the Boston Consulting Group (2017), the mere growth of China's services market in five years (2016–2021) will be equivalent to creating a new market the size of the U.K. Although important, the different cultural, social, and economic characteristics of emerging markets such as China make these markets challenging to manage (Jiang et al., 2018; Khanna, Palepu, & Sinha, 2005; Wright, Filatotchev, Hoskisson, & Peng, 2005). This research extends what is established in Western research (i.e., customer experience management) to China where the cultural and social/economic orientation places great emphasis on the roles of policy makers and social networks. Within this context, our empirical results stress the importance of regulatory environment resources and social environment resources in entrepreneurship development. Whether this conclusion can be generalized to other cultures and market systems is, by itself, an interesting future research question (Crecente-Romero, Giménez-Baldazo, & Rivera-Galicia, 2016). Lastly, the ultimate goal of entrepreneurship education is entrepreneurial activities. In this study, we only measured people's entrepreneurial attitude and intention. Future research, perhaps with access to longitudinal and behavioral data, may further examine entrepreneurship education's behavioral outcomes.

Appendix 1. Constructs and measurement items Second-order factor Perceived value of university entrepreneurship curricular or extracurricular resources

Perceived value of regulatory environment resources

First-order factor

Items

Supporting literature

Lecture

Lv1: Entrepreneurship courses and lectures gave me a better underWalter & Block, 2016; standing of the role of entrepreneurs in society. Jansen et al., 2015 Lv2: Innovative practical course gave me a deeper understanding of the process of innovation and entrepreneurship. Lv3: Innovative entrepreneurship courses and lectures enriched my entrepreneurial innovation knowledge. Pitch competitions Cv1: Participating in entrepreneurial competitions could help me Jansen et al., 2015 understand the spirit of innovation and entrepreneurship better. Cv2: Participating in entrepreneurial competitions could improve my entrepreneurial abilities. Cv3: Participating in entrepreneurial competitions could help me build the confidence of starting a business. Student associations Av1: Participating in community activities could enhance my confidence Jansen et al., 2015 of the starting a business. Av2: The experience of community activities could help to improve my sense of innovation and entrepreneurship. Av3: Being a leader in a community could improve my entrepreneurial and management skills. Career Gv1: Career plan guidance could help me establish my entrepreneurial Walter & Block, 2016; Du guidance/service goals earlier. & Wang, 2015 Gv2: Career plan guidance could strengthen my understanding of employment and entrepreneurship. Gv3: Career plan guidance allowed me to enhance basic business skills and knowledge. Entrepreneurship-friendly Pv1: Government policy support for innovation and entrepreneurship Mason & Brown, 2011; policies activities enhanced my confidence in entrepreneurship. Singer, Amorós, & Pv2: Government policy support for enterprise incubation center could Arreola, 2014 reduce my cost and risk to start my own business. Pv3: Government policy support helped me to simplify my business startup procedure. Pv4: Government provides consulting service for college students could improve my understanding of entrepreneurial. Government funding oppor- Fv1: Financial support from government could help me reduce my Friedman, 2011 tunities entrepreneurial risk. Fv2: Financial support from government made me more confident to my entrepreneurial ideas and activities. Fv3: Government's financial support helps me to spend more time on entrepreneurial activities without financial pressure.

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Entrepreneurial experience or knowledge sharing

Entrepreneurial mentorship

Alumni funding opportunities

Social network capital

Ev1: The experience sharing of alumni and industry professions inspired Lerner & Malmendier, my sense of innovation. 2013; Ev2: I learned entrepreneurial knowledge and skills from alumni and Eesley & Roberts, 2012; industry professions' experience sharing. Gompers, Kovner, Lerner, Ev3: The experience sharing of alumni and industry professions helped & Scharfstein, 2010 me to identify and capture business opportunities. Mv1: The mentoring of alumni and industry professions could help me Eesley & Wang, 2017 understand the market better. Mv2: The mentoring of alumni and industry professions could improve my management capacity. Mv3: The mentoring of alumni and industry professions could help me to solve the difficulties in starting a business. Ov1: Funding from alumni and industry professions made me feel more Standish-Kuon & Rice, confident to my entrepreneurial ideas. 2002; Ov2: Funding from alumni and industry professions could reduce my Eesley & Wang, 2017 entrepreneurial risk. Ov3: Funding from alumni and industry professions made it easier for me to start a business. Nv1: Networking with alumni and industry professions could help me Shane & Cable, 2002; build a company more smoothly. Eesley & Wang, 2017 Nv2: I could get investment through the contacts of alumni and industry professions. Nv3: Networking with alumni and industry professions could help me discover entrepreneurial opportunities. Nv4: My company could tap into new markets through the contacts of alumni and industry professions.

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