Cyber-entrepreneurship as an innovative orientation: Does positive thinking moderate the relationship between cyber-entrepreneurial self-efficacy and cyber-entrepreneurial intentions in Non-IT students?

Accepted Manuscript Cyber-entrepreneurship as an innovative orientation: Does positive thinking moderate the relationship between cyber-entrepreneurial self-efficacy and cyber-entrepreneurial intentions in Non-IT students? Shu-Hsuan Chang, Yu Shu, Chih-Lien Wang, Mu-Yen Chen, Wei-Sho Ho PII:

S0747-5632(19)30138-4

DOI:

https://doi.org/10.1016/j.chb.2019.03.039

Reference:

CHB 5975

To appear in:

Computers in Human Behavior

Received Date: 16 April 2018 Revised Date:

17 January 2019

Accepted Date: 31 March 2019

Please cite this article as: Chang S.-H., Shu Y., Wang C.-L., Chen M.-Y. & Ho W.-S., Cyberentrepreneurship as an innovative orientation: Does positive thinking moderate the relationship between cyber-entrepreneurial self-efficacy and cyber-entrepreneurial intentions in Non-IT students?, Computers in Human Behavior (2019), doi: https://doi.org/10.1016/j.chb.2019.03.039. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Does Positive Thinking Moderate the Relationship Between Cyber-Entrepreneurial Self-Efficacy and Cyber-Entrepreneurial Intentions in Non-IT Students?

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Department of Industrial Education and Technology, National Changhua University of Education,

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Changhua 500, Taiwan

Department of Information Management, National Taichung University of Science and Technology,

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Shu-Hsuan Chang a, Yu Shu a, Chih-Lien Wang a, Mu-Yen Chen b*, Wei-Sho Ho a

Taichung, Taiwan Corresponding author:

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Name: Mu-Yen Chen Mobile phone: +886-4-22196881 E-mail: [email protected] Address: No.129, Sec. 3, Sanmin Rd., Taichung, 40444, Taiwan

Author Shu-Hsuan Chang declares that she has no conflict of interest.

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Author Yu Shu declares that she has no conflict of interest. Author Chih-Lien Wang declares that she has no conflict of interest.

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Author Mu-Yen Chen declares that he has no conflict of interest. Author Wei-Sho Ho declares that he has no conflict of interest. Acknowledgments

This research was supported partly by the Ministry of Science and Technology (MOST) of Taiwan under grant number MOST 105-2511-S-018 -012 -MY3 and MOST 103-2511-S-018 -013 -MY2.

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Cyber-Entrepreneurship as an Innovative Orientation: Does Positive Thinking Moderate the Relationship Between Cyber-Entrepreneurial Self-Efficacy and Cyber-Entrepreneurial Intentions in Non-IT Students?

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Abstract Cyber-entrepreneurship has emerged as a nascent type of entrepreneurship in the information era. The issues of whether the lack of cyber-entrepreneurial self-efficacy (CESE) in students without an IT-related disciplinary background (non-IT students) obstructs their cyber-entrepreneurial intentions (CEIs), and how positive thinking (PT) relates to the two have become major topics of

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discussion in the higher education of cyber entrepreneurship. The present study aims to explore the effect of non-IT students’ CESE on their CEIs, and the possible moderation effect of PT between the two. A total of 364 valid samples were collected from Taiwan college students without an IT background. Hypotheses were verified using Partial least squares structural equation modeling (PLS-SEM). Our results show that cyber-entrepreneurial self-efficacy has a significant positive effect on cyber-entrepreneurial intentions while positive thinking does not, and positive thinking indeed moderates the relationship between cyber-entrepreneurial self-efficacy and cyber-entrepreneurial intentions. Based on these results, we discuss practical implications and propose relevant suggestions and recommendations for future research.

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1. Introduction

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Key words: cyber-entrepreneurial self-efficacy, cyber-entrepreneurial intentions, positive thinking, cultivating innovation

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Cyber-Entrepreneurship is an emerging approach of innovation practicing (Lian & Yen, 2017). As cyber-entrepreneurship has the advantages of having lower operating costs and lower threshold for startups compared to traditional business models, it has gradually grown to be the type of entrepreneurship that is more easily accepted by and accessible to the younger generation (Badaruddin, Arokiasamy & Yusoff, 2011; Wang, Lin, Yeh, Li & Li, 2016). Models of learning such as self-efficacy beliefs, learning conceptions, and assessment expectations have profound impacts on the learning strategies of students pursuing a higher education (Ferla, Valcke & Schuyten, 2009). Therefore, entrepreneurial settings in the environment of entrepreneurship education may have a supporting and inspiring effect on young adult students preparing for an entrepreneurial career (Greene & Saridakis, 2008; Smith & Worsfold, 2015).

ACCEPTED MANUSCRIPT Table 1. The main concepts General concept

Domain-specific concept

Behavioral Intention

Entrepreneurial Intention (EI) Entrepreneurial (ESE)

self-efficacy Cyber-entrepreneurial self-efficacy (CESE)

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Self-efficacy

Cyber-Entrepreneurial Intention (CEI)

Entrepreneurship is a complicated cognitive process involving a lot of human and material resources and various hidden risks. Under what circumstances do young people choose entrepreneurship and actually take steps to start a business? Entrepreneurial intention (EI) is an

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important core indicator reflecting the entrepreneurial process (Global Entrepreneurship Research Association, 2017). According to many studies of behavioral science, behavioral intention is a nonnegligible predictor of behavior (Venkatesh, Morris, Davis & Davis, 2003). Wang et al. (2016) found that extrinsic cyber-entrepreneurial motivations can significantly predict cyber-entrepreneurial intentions (CEIs) for IT-related business management students but not for non-IT-related ones; and intrinsic cyber-entrepreneurial motivations affect the CEIs of students of both IT- and non-IT-related majors without significant difference in effects. Cyber-entrepreneurial intentions can be considered

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as an individual’s estimation of the likelihood that he or she will start and own a new e-commerce business (Wang et al., 2016). The story of Jack Ma, the founder of Alibaba Group (Linda, 2010), demonstrated the possibility for non-IT majored entrepreneurs to successfully start an e-commerce business and highlighted the importance of cyber-entrepreneurship education for non-IT college students. Entrepreneurial self-efficacy (ESE) is one of the important predictors of entrepreneurial intentions (Laguna, 2013; Piperopoulos & Dimov, 2015). Haase & Lautenschläger (2011) believed

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that the effectiveness of entrepreneurial education is determined by its focus; namely, on experiencing entrepreneurship (the know-how and know-why) instead of simply on entrepreneurial knowledge (the know-what). The know-whys are similar to self-efficacy beliefs, they are the antecedents that drive intentions and motivations. Cyber-entrepreneurial self-efficacy (CESE) is an individual’s belief in his or her ability to create a new e-commerce business or utilize internet technologies for business use. A person’s perceived entrepreneurial feasibility (i.e., attitude and social norms) and desirability (i.e., self-efficacy) will affect their EIs and their persistence in entrepreneurial activities (Liñán, 2004); higher ESE manifests higher degrees of perseverance and concentration, and thereby influences EIs (Forbes, 2005). Regardless of disciplinary differences, entrepreneurial education enhances motivations for entrepreneurship and affects EIs (Wang et al., 2016). In our current relatively new cyber-entrepreneurial environment, it is important to examine the effect of non-IT students’ CESE on their CEIs; which is an issue even more urgent in the field of entrepreneurial education. Positive states of mind and body are conducive to learning. Psychoeducational intervention can

ACCEPTED MANUSCRIPT promote student self-efficacy, self-esteem and autonomous learning (Macaskill & Denovan, 2013). Studies have confirmed that the proactive attitude and perceived behavioral control of entrepreneurs affect their behavioral intentions (Lu & Chen, 2013). Positive thinking (PT) is a mental attitude that anticipates positive results. It not only is capable of encouraging individual growth and amplifying the mentality, belief, language and vision of success (Bekhet & Zauszniewski, 2013; Lightsey Jr & Boyraz, 2011; Seligman, 2002); is also an important factor determining psychological adaptations

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(Heimberg, Acerra & Holstein, 1985; Ingram, Smith & Brehm, 1983). Chen and Chou’s (2015) study on Taiwanese youths found that positive thinking predicts life satisfaction. In the midst of an entrepreneurial venture, a positive thinking mindset enhances the adaptability of the entrepreneur and enables him/her to face challenges and learn from mistakes (Bhide,1994; Timmons & Spinelli, 2007).

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It is one of the most important qualities that many successful entrepreneurs possess in times of adversity (Baron, 2000; Jensen & Luthans, 2006; Timmons & Spinelli, 2007; Zapalska, 1997). Consequently, we want to find out whether positive thinking affects the Cyber-Entrepreneurial Intention of non-IT students. This holds profound implications for the cultivation of cyber-entrepreneurial talents. The first and foremost objective of education is to help students master big concepts and establish positive values — in other words, the abilities (Wiggins & McTighe, 2006) and attitudes

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(OECD, 2016) that they can take with them. Recent empirical studies have observed inconsistencies in the results of ESE on firm performance (Amatucci & Crawley 2011; Hmieleski & Baron 2008; Miao, Qian & Ma, 2017; Prajapati & Biswas, 2011). Researchers have suggested the probable existence of a moderating relationship between dispositional optimism (Hmieleski & Baron, 2008)

e-commerce.

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and individual characteristics/traits (Chen, Greene, & Crick 1998; McGee Peterson, Mueller, & Sequeira, 2009; Rauch & Frese, 2007; Ucbasaran, Westhead & Wright, 2008). The present study aims to explore the relationship between Cyber-entrepreneurial self-efficacy, positive thinking and cyber-entrepreneurial intentions in non-IT college students in the context of cyber-entrepreneurial

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2. Theoretical framework and hypotheses 2.1. Cyber-entrepreneurial self-efficacy and cyber-entrepreneurial intentions Boyd and Vozikis (1994), incorporated the concept of self-efficacy from Bandura’s social cognitive theory (SCT) (Bandura, 1977) into the field of entrepreneurship research, and came up with the definition for Entrepreneurial self-efficacy —an individual’s belief in his or her ability to succeed as an entrepreneur and to accomplish various entrepreneurial tasks. Entrepreneurial self-efficacy does not refer to some kind of personality trait that promotes entrepreneurial behaviors and abilities; rather, it is a belief in one’s entrepreneurial ability based upon one’s own selfevaluation and assessment that takes into consideration the integration of all kinds of information (Chen et al., 1998; Tang, Kacmar & Busenitz, 2012; Schenkel, D'souza & Braun, 2014). Entrepreneurial self-efficacy is regarded as the key antecedent of entrepreneurial intentions (Chen et

ACCEPTED MANUSCRIPT al., 1998; Barbosa, Gerhardt & Kickul, 2007; Kolvereid & Isaksen,2006; Izquierdo & Buelens, 2011; Zhao, Seibert & Hills, 2005). Research on entrepreneurship has confirmed that ESE enhances students’ belief in their entrepreneurial capabilities or skills, thus influencing their entrepreneurial career intentions (BarNir, Watson & Hutchins, 2011; Boyd & Vozikis, 1994; Carr & Sequeira, 2007; Liñán, 2008; Rachmawan, Lizar & Mangundjaya, 2015; St-Jean & Mathieu, 2015; Trevelyan, 2011; Wilson, Kickul & Marlino, 2007; Zhao et al., 2005). Cyber-entrepreneurial self-efficacy is an

H1. College students’ CESE has a positive effect on their CEIs.

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2.2. Positive thinking and Cyber-entrepreneurial intentions

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individuals’ level of confidence in their cyber-entrepreneurial abilities and therefore may be predictive of cyber-entrepreneurial intentions. In light of the above, the following hypothesis is proposed:

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Fredrickson’s broaden-and-build theory of positive emotions indicated that positive thinking increases a person’s inner resources and improves life satisfaction (Fredrickson, Cohn, Coffey, Pek & Finkel, 2008). PT is the positive, optimistic and spirited outlook an individual holds in regards to self, others and everything around them (Seligman, 2002). Seligman sees optimism as having confidence in and positive expectations for the future based on previous successful experiences. He found that people are most optimistic when in assessing the situation at hand, they already know (and reasonably expect) that the future will likely unfold in a similar fashion (Seligman, 2002). In other words, optimism is the reasonable positive expectation of success. Dispositional optimism and proactivity are both traits of entrepreneurship that are correlated with entrepreneurial success (Chen,

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Zhou, Yang, Bao & Wang, 2017; Ghenea, 2011) and can affect entrepreneurial intentions (Gartner et al, 1994). Krueger (1993) asserted that perceived desirability is one of the important factors influencing intention, because positive thinking prompts people to perceive things from a more positive and beneficial perspective. Almost all entrepreneurs possess the ability to think positively and proactively; they are always ready to act and have hope and great expectations for everything they encounter (Baron, 2000; Jensen & Luthans, 2006; Timmons & Spinelli, 2007; Zapalska, 1997). Considering the above, the following hypothesis is proposed: H2. College students’ PT has a positive effect on their CEIs. 2.3. Cyber-entrepreneurial self-efficacy, Positive thinking and Cyber-entrepreneurial intentions Entrepreneurship education involves interdisciplinary learning and a multifaceted cognitive process. An individual perceives self-efficacy through cognition, motivation, emotion, and optimism; which in turn produces behavioral outcomes such as choice, performance and persistence to regulate human functioning (Bandura, 1977). Empirical studies have found that entrepreneurial self-efficacy and positive thinking have a direct effect on entrepreneurial intentions (Boyd & Vozikis, 1994; Kickul et al., 2009 BarNir et al., 2011) and lead to actual entrepreneurial behaviors (Lu & Chen, 2013). Hannula (2002) claimed that compared to cognition, learners’ emotions have a greater effect on their learning attitudes. Lightsey (1999) observed that positive automatic thoughts (PATs)

ACCEPTED MANUSCRIPT moderate the relationship between negative events and dysphoria, and effectively alleviate feelings of dysphoria during negative events. Research have shown that psychoeducational intervention promotes autonomous learning (Macaskill & Denovan, 2013); dispositional optimism may moderate the relationship between entrepreneurial self-efficacy and firm performance (Hmieleski & Baron,

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2008); and PATs moderate the relationship between event stressfulness and meaning in life (Boyraz & Lightsey Jr., 2012). Because individuals with a positive thinking mindset, when confronted with external demands or pressure, tend to perceive problems as workable and manageable and respond to pressure proactively, they are able to minimize harm and overcome adversity to eventually live a

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meaningful life. The cyber-entrepreneurial activity explored in the present study is one that involves a tremendous amount of resources. Therefore, in the cognitive process between the future of “I believe I can accomplish various tasks in undertaking a business” and the reality of “I plan on starting a business”, the present study believes that the individual’s maintenance of an optimistic

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outlook on the external environment is crucial, and positive thinking plays an important moderating role. Accordingly, we propose the following hypothesis: H3. College students’ PT has a moderating effect on their CESE and CEIs. Based on the aforementioned reasoning, this study proposes the research model shown in Figure

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1.

Fig. 1. Research model

3. Research Methodology 3.1. Samples

Using the quota sampling method (Saunders, Lewis, & Thornhill, 2009), the present study chose college students from Taiwan as research participants. All who participated have taken e-commerce or entrepreneurship courses and were voluntary and anonymous. Initially, a total of 760 valid samples (questionnaires) were collected. The results of the independent samples t-test showed that the CEIs of non-IT students (n = 364, M = 2.654) were significantly lower than those of IT students (n = 396, M = 2.802) (see Table 2). Among non-IT students, 68% (248) were females and 32% (116) were males; and the majority of them were in Liberal arts (19%), Arts & Crafts (17%),

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CEIs

2.731

0.944

2.802

0.928

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Table 2. Descriptive Statistics for Total students and IT-related vs. Non-IT-related Students Total IT-related Non-IT-related Contract t-test n = 760 n =3 96 n = 364 M SD M SD M SD 2.654

0.956

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Notes: SD: standard deviation. CEIs = cyber-entrepreneurial intentions.

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*p <0.05 (two-tail t distribution) Table 3. Characteristics of the respondents for Non-IT students Characteristics

Number

Percentage

116 248

31.87 68.13

241 124 70 68 63

66.21 33.80 19.02 18.68 17.08

Language and Literature Education Hospitality Agronomy and Horticulture

54 41 32 25

14.84 11.26 8.79 6.87

Engineering Health and Medical Care

24 19

6.59 5.22

School system

General university University of Science and Technology Fashion, Product, Interior and Design Leisure, Tourism and Hospitality Art, and Craft

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3.2. Measures

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Majors

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Men Female

Gender

The present study adopted scales developed by renowned scholars and have been published in academic journals as our tools of measurement. The revised and translated scales were reviewed by experts to maintain excellent content validity. 3.2.1. Cyber-entrepreneurial self-efficacy The Entrepreneurial Self-Efficacy (ESE) scale developed by Chen et al. (1998) was adopted as the basis and combined with the Evaluation and Judgment dimension of the Entrepreneurial Alertness Scale developed by Tang et al. (2012). The resultant scale was modified to measure students’ CESE and subsequently reviewed by three experts. The new scale includes six sections: (1) marketing, (2) innovation, (3) management, (4) risk-taking, (5) financial control, and (6) evaluation

ACCEPTED MANUSCRIPT and judgment respectively. It uses a 5-point Likert scale for scoring, with answer options ranging from strongly disagree to strongly agree.; higher scores indicate higher levels of confidence. There

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are a total of 29 items. Some examples (one from each section and listed in order) are as follows: “Set and meet sales goals”, “New products and services”, “Strategic planning and develop information system”, “Take calculated risks”, “Perform financial analysis”, and “I have a gut feeling for potential opportunities”. 3.2.2. Positive Thinking

The Automatic Thoughts Questionnaire-Positive (ATP-Q) developed by Ingram, Wisnicki (1988), and Boelen (2007) was modified to measure PT for the present study. An English professor

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proofread the scale to ensure that the semantics of the items are consistent with the purpose of the study. After further reviews and revisions by the experts, the resultant scale is made into a 22-item 5-point Likert PT scale, with choices ranging from strongly disagree to strongly agree. The higher the score, the higher the degree of PT. The new scale contains five dimensions: (1) positive daily functioning, (2) positive self-evaluation, (3) others’ evaluation of self, (4) positive future expectations, and (5) positive social functioning. Some sample items, listed according to the order of the dimensions, are “I am in a great mood”, “I have many good qualities”, “I am respected by my peers”, “My future looks bright”, “and “There are many people who care about me”. 3.2.3. Cyber-entrepreneurial intentions

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The present study adapted and revised, according to our research subjects and conditions, the

3.3. Data analysis

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EIs scale developed by Liñán and Chen (2009) to form our 5-item CEIs Scale. It is a 5-point Likert scale with choices ranging from strongly disagree to strongly agree. Higher scores represent greater CEIs. Examples include “My professional goal is to become an entrepreneur” and “I will make every effort to start and run my own firm”.

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SmartPLS 3.0 (Ringle, Wende & Becker, 2015) was used for the analysis of the measurement model and structural model. First, a confirmatory factor analysis (CFA) was performed to ensure the convergent validity and discriminant validity of the measures. Next, we conducted a path analysis (Hair, Ringle, & Sarstedt, 2011) using partial least squares structural equation modeling (PLS-SEM) and bootstrapping (with 5000 repetitions) to examine the significance and predictive power (R2) of the causality between the path coefficients of the structural model, the overall model fit (standardized root mean square residual, SRMR), and whether our hypotheses are supported. Finally, Harman’s single-factor test (Podsakoff & Organ, 1986) was performed to check for common method variance (CMV). The results showed that the explanatory power of the first factor was under 50% as recommended by Podsakoff and Organ; indicating the absence of CMV in our sample data.

ACCEPTED MANUSCRIPT 4. Results 4.1. Measurement model The results of the measurement model analyses showed that (1) the factor loadings of all measures were between 0.794 ~ 0.935 (> 0.7), indicating reliability of the measures; (2) the values of composite reliability (CR) were all between 0.876 ~ 0.955 (> 0.7), indicating internal consistency;

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and (3) the values of the average variance extracted (AVE) were all between 0.612 ~ 0.899 (>0.5), indicating that the convergent validity of all measures was also established (Hair, Hult, Ringle & Sarstedt, 2016) (see Table 4). The Discriminant validity is as shown in Table 5. The square roots of the AVEs were all greater

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than their corresponding correlation coefficients (Fornell & Larcker, 1981); the Heterotrait-monotrait (HTMT) ratio of correlations all showed values smaller than 1 (Henseler, Ringle & Sarstedt, 2015); thereby establishing excellent discriminant validity.

Constructs 2nd-order

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Table 4. Assessment of confirmatory factor analysis Loading 1st-order items

CR

AVE

Cronbach’s α

0.781 0.709

0.944 0.918

mark

0.892

64.809

0.955 0.936

inno mana risk fina

0.872 0.933 0.901 0.832

55.154 110.223 71.254 38.167

0.924 0.913 0.926 0.945

0.753 0.679 0.716 0.812

0.890 0.881 0.901 0.923

0.870

50.015

0.928

0.721

0.903

0.948

170.120

0.954 0.916

0.807 0.612

0.940 0.892

0.908 0.856 0.870 0.906

97.658 46.408 62.116 87.124

0.905 0.876 0.947 0.905

0.613 0.639 0.899 0.760

0.874 0.811 0.887 0.842

0.951

0.797

0.935

eval PT

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daily

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CESE

t-value

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self other future social CEIs

cei_1 cei_2 cei_3

0.896 0.913 0.935

74.167 73.963 114.721

cei_4 0.919 79.797 cei_5 0.794 30.877 Note. CESE = cyber-entrepreneurial self-efficacy; PT = positive thinking; CEIs = cyber-entrepreneurial intentions; CR = Composite reliability; AVE = Average variance extracted.

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Constructs

Mean

CESE PT

3.174 0.716 3.650 0.701

Fornell-Larcker Criterion CESE

PT

Heterotrait-Monotrait Ratio (HTMT)

CEIs

CESE

PT

CEIs

0.884 0.527

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0.559 0.898 CEIs 2.654 0.956 0.555 0.206 0.590 0.220 0.893 Note: Fornelle-Larcker Criterion: Diagonal elements (bold) are the square root of the variance shared between the constructs and their measures (AVE). Off-diagonal elements are the correlations among constructs. For discriminant validity, diagonal elements should be larger than off-diagonal elements. 4.2. Structural model and hypothesis testing for moderation

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In order to test the effects of the interaction between CESE (independent variable, X) and PT (moderator variable, Z) on CEIs (dependent variable, Y) in H3, a PLS-SEM analysis was conducted

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to examine the causal relationship. The results showed that the SRMR of the overall model was 0.066 (< 0.08), demonstrating excellent fit and predictive power (R2 = 0.331). The path coefficients of moderating effects are shown in Table 6. As shown: CESE (X) had a significant positive effect (b = 0.613, t = 11.488, p< .001) on CEIs (Y), H1 is therefore supported; PT (Z) did not have a significant positive effect (b = -0.090, t = 1.486, p> .05) on CEIs (Y), H2 is therefore not supported; the interaction between CESE and PT (X*Z) had a significant positive effect (b = 0.091, t = 2.233, p< .05) on CEIs (Y), H3 is therefore supported.

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The interaction between CESE and PT is further illustrated in Figure 2. Compared to students with low PT (red line), the positive correlation between CESE and CEIs was more significant in students with high PT (green line). In other words, the positive effect of CESE on CEIs is greater in those with high PT than those with low PT; implicating the importance of CESE cultivation in

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non-IT students. It is worth noting that among those low in CESE, the ones with low PT exhibited greater CEIs than those with high PT; thus indicating the existence of PT’s moderating effect between CESE and CEIs.

Path

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Table 6. Analytical results of structural model Path coefficient

CESE (X) → CEIs (Y) PT (Z) → CEIs (Y) X*Z → Y

0.613 -0.090 0.091

SD 0.053 0.061 0.041

t-value 11.488 1.486 2.233

sig.

Hypothesis/Supported

*** ns *

H1/Supported H2/Not supported H3/Supported

Note. CESE = cyber-entrepreneurial self-efficacy; PT = positive thinking; CEIs = cyber-entrepreneurial intentions. *p< 0.05, ***p< 0.001, ns = not significant. In general, H1 (College students’ CESE has a positive effect on their CEIs) and H3 (College students’ PT has a moderating effect on their CESE and CEIs.) are supported. H2 (College students’ PT has a positive effect on their CEIs.) is not supported.

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Fig. 2. The moderating effect of PT on the relationship between CESE and CEIs.

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5. Discussion and Implications

Supporting young entrepreneurs has become an important governmental strategy for many countries to improve their economy and promote innovation. Based on social cognitive theory, positive psychology, and literature relevant to entrepreneurship, the present study explored the

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moderating effects of positive thinking (PT) between cyber-entrepreneurial self-efficacy (CESE) and cyber-entrepreneurial intentions (CEIs) in non-IT college students. We hope that by the merit of this study, we may contribute to the furtherance of the development of higher education in the field of cyber-entrepreneurship. 5.1. Cyber-entrepreneurial self-efficacy has a direct positive effect on cyber-entrepreneurial intentions, and positive thinking doesn’t The results of this study showed that cyber-entrepreneurial self-efficacy positively predicts cyber-entrepreneurial intentions in non-IT students, which is consistent with previous findings on entrepreneurial self-efficacy and entrepreneurial intentions (Boyd & Vozikis, 1994; BarNir et al., 2011; Carr & Sequeira, 2007; Liñán, 2008; Trevelyan, 2011; Wilson et al., 2007; Zhao et al., 2005). This shows that in terms of cyber-entrepreneurship, individuals with higher levels of confidence in entrepreneurship are also more willing to start a business. It further proves that to non-IT students, entrepreneurship education not only is a motivational factor (Wang et al., 2016), it also affects

ACCEPTED MANUSCRIPT intentions by stimulating and encouraging cyber-entrepreneurial self-efficacy. Some examples are positive encouragement and experience-sharing by successful entrepreneurs, i.e., mentoring (Rachmawan, Lizar & Mangundjaya, 2015; St-Jean & Mathieu, 2015). However, our study showed that positive thinking of non-IT students cannot directly predict their cyber-entrepreneurial intentions, a finding inconsistent with those of earlier studies on the effects of PT or proactive personality on entrepreneurial intentions (Crant, 1996; Douglas &

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Shepherd, 2002; Gartner et al, 1994; Miao, 2015). As demonstrated by empirical research, many previously failed entrepreneurs lack the incentive to try again, indicating that experiences of failure activate the defense mechanism in people and hinder them from choosing a path that may lead to failures again (Cardon & McGrath, 1999; Shepherd, 2003). Positive thinking is not an unrealistically

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blind optimism, but a positive action following a rational assessment of the status quo (Seligman, 2002). Whereas unrealistic optimism treats optimism as a skewed assessment of the future, with overly positive views of self, underestimation of the possibility of occurrences of negative events, and the self-enhancing tendency that sees positive events as more likely to happen to self than to others (Taylor & Brown, 1988; Weinstein, 1980). Studies have found adaptive/functional optimism to be the best predictor of life satisfaction, and dysfunctional optimism most predictive of procrastination (Chou & Chen, 2017). This suggests the existence of both positive and negative

development of intentions.

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functions in positive psychological traits, the dialectics between the two functions, the possible positive significance and value existent in negative traits, and that even positive traits may bring about negative behavioral outcomes (Lazarus, 2003; Lomas & Ivtzan, 2016). This result seems to imply that there may be different dimensions to PT; e.g., defensive pessimism may impede the

5.2. The moderating effect of positive thinking

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Most importantly, the moderation of positive thinking between cyber-entrepreneurial

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self-efficacy and cyber-entrepreneurial intentions is confirmed in the study. This echoes the previous findings on the moderations of PATs, psychoeducational intervention, and dispositional optimism in the relationship (Boyraz & Lightsey Jr., 2012; Hmieleski & Baron, 2008; Lightsey Jr., 1999, Macaskill & Denovan, 2013). What stands out in the findings of our study is that while cyber-entrepreneurial self-efficacy is high, students with high positive thinking have comparably higher cyber-entrepreneurial intentions than those with low positive thinking; however, when self-efficacy is low, students with high positive thinking actually show lower cyber-entrepreneurial intentions than those with low positive thinking. One probable explanation of this is that when one’s cyber-entrepreneurial self-efficacy is low, high positive thinking may enable one to realistically assess the situation and see one’s limitations (such as not having sufficient IT-related knowledge and abilities) and the difficulties in starting a business; and therefore shrink from the pursuit of cyber-entrepreneurship and consider other career options. As to whether these two seemingly contradictory effects of positive thinking on non-IT students are to be considered functional or

ACCEPTED MANUSCRIPT dysfunctional optimism in the dialectics of Chinese culture is something worth pondering for the educators. The results of an entrepreneurship education study indicated that even when students were highly satisfied with the teachings and the curriculum design and were learning well, their EIs did not become higher; implicating that as they learned more about entrepreneurship from the courses, they may have realized more about the unsuitability/undesirability of an entrepreneurial career to

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them (Chen et al., 2015). Self-fulfilling mechanism (Bagozzi, 1992) may be the reason behind this intention-behavior connection; that is, one’s intention triggers one’s “will do”/ “must do” mindset and determines corresponding behaviors (Conner & Armitage, 1998; Sheeran, 2002). Kapepes and Oettingen (2014) found that with mental contrasting (mentally contrasting the desired future with the

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present reality), the higher one’s expectation of success, the stronger one’s mental future-reality association; conversely, the lower one’s expectation of success, the weaker one’s future-reality association. Mental contrasting is a self-regulatory strategy that brings to mind both one’s wish for the future and the obstacles existing in one’s present reality (Kapepes & oettingen, 2014). Kapepes and Oettingen (2014) asserted that once this future-reality association is strengthened, people will commit to fulfilling their attainable wishes, understand how their reality prevent them from realizing their desired future, and take steps to overcome obstacles standing in their way. In other words, the

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cognitive association between future and reality can help students forget about unrealistic dreams, go after the more likely realizable ones, self-regulate and adjust, and gradually guide themselves on a wise pursuit of their dream future. It should be noted that positive thinking occurs in the process of mental contrasting, and is thus a topic worth further exploring and also the present study’s

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contribution to the cultivation of talents in higher education. All things considered, entrepreneurship education should try to promote and enhance the confidence of non-IT students by putting more emphasis on the cultivation of positive thinking, such as self-reflection (Wang, Chen, Lin & Hong, 2017) and experiential and collaborative learning (Bissola, Imperatori & Biffi, 2017), so students may develop greater confidence and courage to face the challenges of entrepreneurship.

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6. Conclusions

This study explores non-IT students’, who took innovative course Entrepreneurship and E-commerce, mental set about cyber-entrepreneurship. Based on the theoretical foundations of social cognitive theory and positive psychology, the present study explored the effects of the relationship between cyber-entrepreneurial self-efficacy (CESE), positive thinking, and cyber-entrepreneurial intentions (CEIs) in the context of entrepreneurship education. We found that those with high cyber-entrepreneurial self-efficacy also have high cyber-entrepreneurial intentions and positive thinking moderates the relationship between the two; when people with high positive thinking have low cyber-entrepreneurial self-efficacy , they are less inclined to start a business (low CEIs); but when people with low positive thinking feel the same (low CESE), they are comparably more inclined to still start a business (higher CEIs). Our findings contribute empirically, in research and in practice, to the understanding of students’

ACCEPTED MANUSCRIPT cyber-entrepreneurial self-efficacy in the higher education of entrepreneurship. More specifically, different from relevant studies (Boyd & Vozikis, 1994; Kickul et al., 2009 BarNir et al., 2011; Lu & Chen, 2013), this study focus on cyber-entrepreneurship and found out the relations between traditional entrepreneurial self-efficacy and intention is also found in the cyber-entrepreneurship. Past studies discovered how positive thinking effect entrepreneurial intentions (Gartner et al, 1994), however the same relation is not found in the domain of cyber-entrepreneurship. Furthermore, this

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study discovers the special role (moderator) of positive thinking which has not been explored in the past literatures. With a better understanding of the role of positive thinking in cyber-entrepreneurship such innovative approach of start up a business, both entrepreneurship educators and cyber-entrepreneurs

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can have a deeper insight into the changes/differences in the self-efficacy of students, and raise awareness of the importance of incorporating positive psychoeducation into the courses of entrepreneurial education and propose new CEI-enhancing strategies such as positive self-efficacy-promotion. One limitation of the present study is that all of our participants were college students in Taiwan, so our results may not be generalizable to students of other culture, race and/or geological locations. Future researchers may want to look into the cultural influences on cyber-entrepreneurial

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self-efficacy, explore educational and learning strategies that promote positive thinking, and examine the differences between general and domain-specific positive thinking. The results of this study on the moderating effect of positive thinking has significance in that it expanded the direction of research in entrepreneurship education to include areas such as the possibility of mental contrasting

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activity (between the ideal future and the present reality) affecting intentional behavior. Base on the results of this study, future research studies should aim towards (a) examining the topics with qualitative approach to obtain further information about how and why of the individual differences in positive thinking and cyber-entrepreneurial self-efficacy. (b) Including individual

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elements like SES, culture background, gender and as antecedent variable to construct a more complete model to understand college students’ cyber-entrepreneurship intention. (c) Exploring to what extend the innovation intention will influence the cyber-entrepreneurial intentions.

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ACCEPTED MANUSCRIPT Highlights

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Explore non-IT students’ cyber-entrepreneurial self-efficacy (CESE) Explore non-IT students’ cyber-entrepreneurial intentions (CEIs) Positive thinking (PT) moderates the relationship between CESE and CEIs CESE affects CEIs while PT does not

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