Learning and Creativity in Virtual Communities: Nurturing Entrepreneurial Intentions of Muslim Women

Abstract

In terms of information availability, talent acquisition and entrepreneurial education, female prospective entrepreneurs encounter several hurdles and inadequacies. This study investigates how social media learning might improve entrepreneurial learning and creativity among female learners. In summary, this article examines the impact of two critical activities in social media communities (knowledge sharing and social interaction) on entrepreneurial learning and creativity, which might develop entrepreneurial ambitions among Muslim female learners. The data were collected from 253 university and college female students who used social media for entrepreneurial learning. The structural equation modelling technique was used on 233 functional responses in the study. The study instrument’s reliability and validity were also evaluated through different statistical measures before hypotheses testing. The study findings exposed that both knowledge sharing and social interactivity influenced entrepreneurial learning and creativity separately. The study also revealed that entrepreneurial learning and creativity further influenced entrepreneurial intentions. This research reveals female learners’ entrepreneurship intentions, which can be advanced using social media learning in a developing region. The primary theoretical research contribution is the identification of essential activities in virtual entrepreneurial communities, which can enhance the learning and creativity of young female learners. However, further studies need to be carried out in other developing regions among other marginalized groups to generalize these findings. Both teaching faculties and policymakers should make effective use of social media for imparting entrepreneurial education among students, which would further lead to entrepreneurial intentions among them. The researchers argue that there is an imperative need to promote female entrepreneurship intentions, especially among Muslim women, to make them self-reliant and self-employed. This makes it essential to promote entrepreneurial learning and creativity among them, which are significant factors to foster entrepreneurial intentions. Thus, this study has provided an effective and cost-efficient manner of imparting entrepreneurial education to female learners aspiring to become entrepreneurs.

Keywords

Cooperative/collaborative learning human–computer interface informal learning learning communities social media

Introduction

The predominance of social media is evident in every sphere of human life. In fact, in recent times, it has been discovered as a promising teaching instrument. Research suggests that social media is necessary not only in other spheres but is essential in also imparting education in institutes of higher learning (Price et al., 2018). Students are known to willingly adopt social media for collaboration in order to improve their learning performance in formal and informal environments (Won et al., 2015). Al-Rahmi et al. (2018) believe that the use of social media platforms for shared learning positively influence learning performance and promote group discussion among members, encouraging even below-average students to participate in content creation. There are unlimited possibilities for interaction between group members on social media networks to positively impact learning in educational settings (Vollum, 2014). A similar recent study conducted by Caldwell et al. (2020) suggests that sharing ideas in virtual communities can foster creative thinking among participating students, and this should indeed be the fundamental objective of education, especially in contemporary times (Allen et al., 2012).

Furthermore, Allen et al. (2012) suggest the use of social media in higher education to enhance the creativity and critical thinking abilities of students. Creativity empowers students to develop novel ideas that lead to innovation (Gundry et al., 2014) and entrepreneurship (Kabukcu, 2015). Creativity is believed to be an essential qualification for entrepreneurship (Laguía et al., 2019) and has a highly significant role in the new venture creation process (Chang & Chen, 2020). Researchers have identified various factors that affect entrepreneurial intentions; however, in recent times, the understanding of virtual platforms can play a decisive role in shaping the entrepreneurial mindset (Olanrewaju et al., 2020). Extensive digital reforms in education will eventually result in a significant transformation in entrepreneurship education worldwide (Ratten & Usmanij, 2020). The foremost objective of entrepreneurship education is to influence the entrepreneurial intentions of students (Molaei et al., 2014), particularly female students, as their participation is required to accelerate growth of entrepreneurship and reduce global poverty (Sidratulmunthah et al., 2018).

Furthermore, the profound association between social media and entrepreneurial opportunities has reshaped the lives of modern businesswomen in developing economies by providing favourable circumstances for personal and professional growth (Crittenden et al., 2020). However, in patriarchal societies like India, women are less likely to start a business (Shahriar, 2018). For Muslim women, things are even more complicated. However, in the only Muslim-dominated state of Jammu and Kashmir in northern India, the situation is drastically changing for women entrepreneurs (Siddiqui & Jan, 2019), with a rise in their number over the past decade. Previous research suggests that technology training programmes on social media and general digital awareness for female entrepreneurs could develop women entrepreneurship (Mack et al., 2017). A study conducted by Vivakaran and Maraimalai (2017) suggests that providing virtual platforms for education would undoubtedly lead to empowerment for Indian women entrepreneurs, thereby reducing the gender gap. However, the role of social media in improving learning and creativity that would impact the entrepreneurial intentions of Muslim women remains underexplored and needs to be investigated, especially in the current scenario. This study has investigated the ramifications of knowledge sharing and interactions in virtual communities (Beig & Khan, 2018) which can substantially impact learning and creativity, nurturing entrepreneurial intentions of women entrepreneurs. Moreover, the dynamic transformation in entrepreneurship education worldwide requires extensive research (Olanrewaju et al., 2020). Therefore, this study attempts to fill the gap in literature by providing a theoretical framework that explains the process of learning and creativity in virtual communities, thereby fostering entrepreneurial intentions. Furthermore, the theoretical model is empirically tested using appropriate statistical techniques.

This article starts with an introduction, followed by a critical literature review that incorporates the study hypotheses concerning knowledge sharing, social interaction, entrepreneurial learning, creativity and entrepreneurial intentions. Next, the section on research methodology includes the research design, study measures and demographic profile. It is followed by the results and discussion section, which covers the factor analysis, the measurement model, structural model testing and discussion on the findings. The final section comprises the conclusion, implications and suggestions for policymakers, and also the limitations and future course of action.

Literature Review

Social Media

Innovations in social media technologies have radically transformed the world (Beig & Khan, 2018). Social media has empowered an ordinary man with the capacity to create content, communicate on virtual platforms and render an opinion on almost anything, including products and services (Ahlqvist et al., 2008). According to Ahlqvist et al. (2008), social media consists of three main building blocks:

Content: Social media websites allow users to create content on virtual platforms by freely sharing pictures, text and multimedia (Kaplan & Haenlein, 2010).

Communities: Online communities are Internet-based applications that permit their users to interact with other members on these virtual platforms by sharing information (Brogi et al., 2013).

Web 2.0: Social media websites are applications built on the technological foundations of Web 2.0 that allow users to create and distribute information on virtual platforms (Kaplan & Haenlein, 2010).

People using social media platforms for promotion are engaged primarily in sharing and interaction (Kaplan & Haenlein, 2010). Likewise, Beig and Khan (2018) have classified all social media activities into two broad categories: sharing and interaction. Content sharing on social media platforms has been studied previously as user-generated content (Schivinski & Dąbrowski, 2015), knowledge sharing (Chou et al., 2014) and entertainment (Godey et al., 2016). On the other hand, previous researchers have studied interaction as communication between customers and brands (Brodie et al., 2013; Godey et al., 2016).

Knowledge Sharing

Knowledge sharing is an act of diffusing information to other members of an organization, a group or a community (Ryu et al., 2003). According to Van den Hooff and De Ridder (2004), ‘Knowledge sharing is the process by which individuals mutually exchange knowledge and jointly create new knowledge’. Online communities provide unlimited opportunities for sharing knowledge with other group members, consequently producing loads of user-generated content online. Students create user-generated content in knowledge-based online communities, while educators and facilitators create firm-generated content (Schivinski & Dąbrowski, 2015). A faculty on social media can share a lesson as a PDF or a video lecture or initiate and moderate a debate among students. Virtual communities provide a platform for individuals to update their domain knowledge, thus equipping them to face workplace problems better (Hsu et al., 2007).

Social Interaction

With the advancement in wireless communication and social media technologies, the traditional definition of social interaction is now antiquated (Godey et al., 2016). According to Beig and Khan (2018), social media provides as strong a platform for interaction as virtual communities. Users can react to the content shared by other users and create fresh content to counter a narrative or a propaganda. Interaction on a social media platform like Facebook can be alike, a share or a comment on the content shared by other users in online communities. In online social interactions, people share information about anything members would be interested in, eliciting a response (Ståhl & Kaihovirta, 2019).

Entrepreneurial Learning

Technological innovations have led to drastic changes in the learning environment and have become critical for intellectual development (Reinhold et al., 2020). In this dynamic world, with the sole aim of survival, learning new things by identifying relationships between events and surroundings, has become a compulsion (De Houwer, 2009). Despite being the most extensively explored area in psychology, a disagreement over the definition of learning among scholars persists (De Houwer et al., 2013). According to Lachman (1997), the most frequently used definition in the literature on psychology refers to learning as ‘a relatively permanent change in behaviour brought about by practice or experience’. Learning modifies human competencies by an increase in knowledge and upgradation of skills (Roediger et al., 2014). In this study, researchers are concerned with entrepreneurial education, which is defined by Politis (2005) as ‘a continuous process that facilitates the development of knowledge that is necessary for being effective in initiating and managing new ventures’. Participation in online knowledge-based communities that share information on entrepreneurship development can positively influence entrepreneurial learning in the youth of today.

Creativity

Creativity has emerged as an essential element of problem-solving (Plucker et al., 2004). It is a factor that explains the reason for the commendable accomplishments of young entrepreneurs in the twenty-first century (Kampylis & Valtanen, 2010). The genesis of creativity in psychology is from the Latin word ‘creatus’, which means to make or produce (Guilford, 1950). An idea or a product is considered creative if it is perceived as new and valuable (Sternberg & Lubart, 1995). In extant literature, creativity has been researched from various perspectives (Walia, 2019). For this study, creativity may be defined as an intellectual competence that has the propensity to produce novel ideas or products that serve some purpose. Scholars believe that creativity paves the way for innovative and valuable ideas (Mumford, 2003). In educational research, researchers are eager to determine factors that can influence the creativity of students, like examining the impact of digital game-based learning on creativity (van Hooijdonk et al., 2020; Zhang et al., 2020).

Entrepreneurial Intentions

The research field of entrepreneurial intentions is a promising one for scholars. The dynamic business environment in contemporary times makes it even more fascinating (Vuorio et al., 2018). Going forward, improvement in entrepreneurial activities shall exceedingly depend on the youth’s entrepreneurial intentions in a bid to solve economic and non-economic problems of a nation (Tiwari et al., 2017). Entrepreneurial intentions may be defined as a person’s resolve to start a new business enterprise ably supported by a plan of action. Preliminary research has been carried out concerning entrepreneurial intentions in varied contexts. Research studies mainly investigate the use of social media in entrepreneurship education, while its ramifications on entrepreneurial intentions are limited. Developing nations like India want more number of people to take up entrepreneurship as a career option in order to enhance economic growth and reduce unemployment. This factor, among others, makes it imperative to conduct extensive research on entrepreneurial intentions.

Theoretical Model

Relationship Between Knowledge Sharing and Entrepreneurial Learning

Innovations in information technology have made it possible for teachers to share ideas in online communities and to use them in the teaching process (Prestridge, 2019) (see Figure 1). In recent times, the use of social media to share domain knowledge, especially in professional studies, is a standard practice (Cabrera et al., 2020). Scholars believe that shared learning in online knowledge communities can positively impact learning performances (Al-Rahmi et al., 2018). In light of this discussion, this study maintains/highlights the fact that knowledge sharing on social media platforms shall positively impact the entrepreneurial learning of students in online communities (Teaching Entrepreneurship).

Figure 1.

Source: The authors.

Relationship Between Knowledge Sharing and Creativity

Sharing information on social media helps to build confidence and self-belief and, consequently, plays a central role in enhancing the personal creativity of users (Chai & Fan, 2017). Social media provides a platform where people can freely share their ideas and have interactive discussions without coming face to face in virtual communities (Acar et al., 2019). In their study, Khan and Khan (2019) found that knowledge sharing on social media can have a positive impact on innovations by employees. These results were similar to Allen et al. (2012) findings, suggesting that the use of social media in higher education can substantially encourage creativity among students. Acar et al. (2019) have found a significant positive relationship between students’ use of social media for self-education and creativity.

Relationship Between Social Interaction and Entrepreneurial Learning

Social media is a platform for knowledge sharing and interaction, and the opportunities to exchange ideas and information are infinite. Interaction with other members in virtual communities can help people convert their experiences into intelligence (Hu et al., 2017). In virtual communities, students can benefit by sharing content, appreciating the efforts of other members and by engaging in healthy discussions, consequently enhancing learning in educational settings (Vollum, 2014).

Relationship Between Social Interaction and Creativity

Interaction on social media contributes to a free exchange of ideas with other community members. Previous research suggests that social media must be used in higher education to boost creativity among students (Allen et al., 2012). These social interactions in virtual communities provide a genuine opportunity for members to articulate their ideas. Findings from the previous studies provide an evidence for a strong relationship between the use of social media and its influence on creativity (Acar et al., 2019).

Relationship Between Entrepreneurial Learning and Entrepreneurial Intentions

The introduction of online degree courses in universities and the virtual training of people worldwide have entirely revolutionized the education industry. Access to online resources, mainly social media, has completely transformed teaching and learning pedagogies (Prestridge, 2019).These platforms allow online collaborations to improve learning performances (Won et al., 2015) and influence the entrepreneurial intentions of students (Olanrewaju et al., 2020). Learning about entrepreneurship in virtual communities has the potential to encourage students to establish business ventures in the future.

Relationship Between Creativity and Entrepreneurial Intentions

Any discussion on entrepreneurship is incomplete without reviewing creativity and its role in influencing entrepreneurial intentions (Kabukcu, 2015). Creativity is exceptionally significant in influencing entrepreneurial intentions as it plays a pivotal role in new business creation (Chang & Chen, 2020). A creative mindset is the key to solving problems that entrepreneurs might face while starting a new business. Akpur (2020) suggests that creative thinking positively correlates with the academic achievements of students (Akpur, 2020). Moreover, previous research shows a strong association between creativity and entrepreneurial intentions (Chang & Chen, 2020).

Hypotheses

H1 Knowledge Sharing positively influences Entrepreneurial Learning.

H2 Knowledge Sharing positively influences Creativity.

H3 Social Interactivity positively influences Entrepreneurial Learning.

H4 Social Interactivity positively influences Creativity.

H5 Entrepreneurial Learning positively influences Entrepreneurial Intentions.

H6 Creativity positively influences Entrepreneurial Intentions.

Methodology

Research Design

This research study is based on a quantitative and causal design as the data collected were quantified and the relationship between endogenous and exogenous variables was tested. Primary (questionnaire) and secondary data sources (online and offline) were employed in this research study.

Data Collection

An online survey was used to collect data from female students enrolled in various entrepreneurship courses in three universities and five colleges in India’s Kashmir region. The respondents were intimated/approached through emails and WhatsApp groups using the snowball sampling method. Filter questions were used to get responses specifically from Muslim female students who are active in various virtual communities on different social media platforms related to entrepreneurship education. The total number of responses received was 253, of which only 233 functional responses remained after data cleaning.

Measures

The measure of ‘Knowledge Sharing’ (five items) was adopted from the studies of Chiu et al. (2006) and Yan et al. (2016). The ‘Social Interaction’ scale (three items) was adopted from the studies of Chiu et al. (2006) and Chan et al. (2019). The scale for measuring ‘Creativity’ (five items) was adopted from Zhou and George. The ‘Entrepreneurial Learning’ scale (five items) was adopted from the studies of Fu et al. (2009) and McMillan and Hwang (2002). The ‘Entrepreneurial Intentions’ scale (five items) was adopted from the study of Ahmed et al. (2020).

Demographics

The demographic profile of the respondents is presented in Table 1.

Results and Discussion

The data analysis of this study was carried out by applying the exploratory factor analysis (EFA) and structural equation modelling (SEM) technique. The validity and reliability factors were assessed using factor loadings and Cronbach’s alpha in SPSS 22.0. The testing of the hypothesis was carried out using the path analysis in SEM. EFA was run in SPSS 22.0 to explore the factors in the data structure and to examine the interrelationship between the study variables (Tabachnick & Fidell, 2007). Cronbach’s alpha score was used to assess the internal consistency of the research instrument.

Table 1.

Demographic Profile of Respondents

	Frequency	Percentage
Residence
Urban	132	56.7
Rural	101	43.3
Education
Pursuing graduation	148	63.5
Pursuing postgraduation	85	36.5
Age
18–23 years	189	81.1
24–29 years	41	17.6
30–35 years	3	1.3
Family income
Up to ₹200,000 per year	64	27.1
₹200,000–₹500,000 per year	105	45.1
₹500,000–₹1,000,000 per year	39	16.7
>₹1,000,000 per year	25	10.7
Internet usage
Up to 30 min daily	92	39.5
30 min to 1 h daily	85	36.5
1–2 h daily	34	14.6
>2 h daily	22	9.4
Social media type
Facebook	130	55.8
YouTube	76	32.6
LinkedIn	16	6.9
Others	11	4.7
Percentage of internet time spent on entrepreneurial learning
Up to 10	166	71.2
10–20	46	19.7
20–30	18	7.7
>30	3	1.3

Source: The authors.

Factor Analysis

EFA was run on the data set and the value of Kaiser–Meyer–Olkin (KMO) was 0.835, which was found to be above the recommended level of 0.50 (Tavsancil, 2014). The Bartlett’s test of sphericity revealed significant results (3405.5; df = 253) and all the items loaded on their respective factors with factor loadings above the minimum level of 0.50. The total variance explained by all five factors was a sufficient percentage of 71.11%. The instrument’s reliability was assessed through Cronbach’s alpha. The reliability coefficient of the overall scale (a = 0.88) was above the minimum threshold of 0.70, which indicates reliability.

Table 2.

Convergent and Discriminant Validity

	CR	AVE	CRT	EL	HI	KS	SIT
CRT	0.834	0.504	0.710
EL	0.920	0.698	0.148	0.835
EI	0.898	0.639	0.404	0.280	0.799
KS	0.868	0.580	0.241	0.253	0.268	0.762
SIT	0.891	0.732	0.323	0.305	0.456	0.272	0.855

Source: The authors.

Note: The values in the diagonal of the matrix shown in the table are the square root of the AVE. AVE, Average variance extracted; CR, composite reliability; CRT, creativity; EI, entrepreneurial intentions; EL, entrepreneurial learning; KS, knowledge sharing; and SIT, social interaction.

Table 3.

Structural Estimates

Hypotheses	From	To	Standard Estimates	Un-standard Estimate	SE	CR	p-Value
H₁	KS	EL	0.193	0.250	0.090	2.775	0.006
H₂	KS	CRT	0.301	0.261	0.104	2.521	0.012
H₃	SIT	EL	0.179	0.266	0.072	3.691	*
H₄	SIT	CRT	0.264	0.341	0.083	4.108	*
H₅	EL	HI	0.229	0.244	0.072	3.373	*
H₆	CRT	HI	0.384	0.363	0.068	5.304	*

Source: The authors.

Note: * means p-value = 0.001.

Confirmatory Factor Analysis

The confirmatory factor analysis (CFA) was run in AMOS 22.0 (see Figure 2) to assess the adequacy of the factors. The CFA results showed a moderate data fit for the study’s theoretical framework with X²/df = 1.96 (p < 0.001), goodness of fit index (GFI) = 0.865, (root mean square error of approximation (RMSEA) = 0.06, comparative fit index (CFI) = 0.935, normed fit index (NFI) = 0.87 (Hu & Bentler, 1999). The model fit indices confirmed the extent to which a hypothesized model matches the observed data (assessment of the data–model fit). Since all the values were above the minimum threshold values, it may be taken as confirmed that there were no discrepancies between the data and the hypothesized model. All the factor loadings were significant above 0.70, which confirmed convergent validity (Fornell & Larcker, 1981). The internal consistency of the items in the instrument was assessed using the composite reliability score, which exceeded the value of 0.60 (Hair et al., 2010). The values of average variance extracted (AVE) ranged from 0.504 to 0.732 (Table 2), which confirmed construct validity. The instrument confirmed discriminant validity (Table 2) as the correlation between the factors was less than the AVE’s square root values for each factor (Anderson & Gerbing, 1988).

Figure 2.

Source: Derived from primary data.

Structural Modelling and Hypothesis Testing

SEM was run using AMOS 22.0 with the maximum likelihood estimation. The model fit indices for the structural analysis showed a moderate fit (χ²/df = 2.094 at p < 0.001, GFI = 0.857, RMSEA = 0.069, TLI = 0.916, CFI = 0.925; see Figure 3).

Figure 3.

Source: The authors.

Hypothesis Testing

The hypotheses proposed in the conceptual framework were tested using path analysis (Table 3) in SEM. Hypotheses H₁ and H₂ are supported, which implies that knowledge sharing in such online communities leads to entrepreneurial learning (β = 0.19, p < 0.05) and creativity (β = 0.17, p < 0.05), respectively. Hypotheses H₃ and H₄ are also supported, which implies that social interaction in such online communities increases entrepreneurial learning (β = 0.26, p < 0.05) and creativity (β = 0.30, p < 0.05), respectively. Besides, hypothesis H₅ is supported, which implies that creativity leads to entrepreneurial intentions (β = 0.38, p < 0.05), and H₆ is also supported, suggesting that entrepreneurial learning enhances entrepreneurial intentions (β = 0.22, p < 0.05).

Discussion

The results of this study show that all the hypotheses were supported. The findings showed that entrepreneurial learning might be a possible outcome of knowledge sharing in virtual communities. This implies that content and ideas related to entrepreneurship, shared in such communities, enhance the entrepreneurial learning of the participants. Earlier studies also suggest that a collaborative culture among students improves their learning by way of gaining novel information and proficiency (Qian & Clark, 2016). Similarly, the path analysis revealed that knowledge sharing among members in virtual entrepreneurial learning communities also enhances creativity. Research indicates that the educational environment (knowledge sharing) may stimulate the creativity of students (Huang & Liu, 2019). In particular, online learning has been directly and positively related to the learner’s ability to discover creative ideas (Lau & Lee, 2015). Hence, in such communities, sharing the content needs to be encouraged by the administrators and members so as to increase entrepreneurial learning and to foster creativity. Results revealed that the social interaction among members in such online communities influences entrepreneurial learning and creativity. A significant number of studies show that social interaction is closely related to individual learning (Mercer & Howe, 2012). It is also intricately linked with online learning (Richardson & Swan, 2003) as dynamic online interaction creates a favourable educational environment (Tu & Corry, 2003) wherein the communication among members, the discussions and idea dissemination related to entrepreneurship lead to entrepreneurial learning and creativity. Finally, results also suggest that there is a positive and statistically significant influence of both, entrepreneurial learning and creativity, on entrepreneurial intentions. Creativity has been found to be associated with entrepreneurship intentions in earlier studies (Hmieleski & Corbett, 2006). Online learning (e.g., social media tools) has been found to impact entrepreneurial choices affirmatively (Bandera et al., 2018). The findings of this study are essential for female students aspiring to become entrepreneurs. Women entrepreneurship has been vastly benefitted by contemporary information and communications technology (ICT) (Duncombe & Heeks, 2005). Women entrepreneurs in developing regions face turbulent environments and other challenges such as poverty, skill deficiencies and lack of entrepreneurial education (Goyal & Yadav, 2014). For these reasons, women feel the need to develop their knowledge and skills (Díaz-García & Jiménez-Moreno, 2010). These factors make it imperative to encourage the use of social media in order to augment their entrepreneurial knowledge.

Conclusion and Implications

Conclusion

To the best knowledge of the authors, this article is the first to explore the role of social media communities in fostering entrepreneurial intentions by influencing learning and creativity among female students. The primary purpose of this study is to help academicians and policymakers understand the importance of social media in accomplishing the same. Social media platforms are being increasingly recognized as innovative tools for imparting and enhancing entrepreneurial education. This is linked to the social interactions and knowledge dissemination in such networks that benefit learners. This study conducted an empirical analysis of virtual communities on social media platforms. The current work also reveals that learning can be imparted through knowledge sharing and social interaction in online cooperative culture. The results showed that activities (knowledge sharing and social interaction) in such communities influence both creativity and learning, thereby enhancing learners’ entrepreneurial intentions. Thus, the use of social media should be encouraged among students to improve their understanding and creativity and to develop a more aligned entrepreneurship orientation. Therefore, this empirical study could be extended to other social media platforms that have the potential to significantly affect stakeholders.

Practical Implications

This article highlights how social media can infuse creativity among learners, ultimately leading to entrepreneurial intentions. At the same time, it also draws attention to the two essential activities of knowledge sharing and interaction in social media communities. These activities are necessary for imparting education and fostering creativity among learners. This research has made a valid contribution to the entrepreneurial ecosystem by suggesting a cost-effective mechanism of how budding entrepreneurs, especially women, can gain from such online platforms. This study can also benefit teachers who can supplement traditional teaching methods with social media learning. Moreover, with the global business environment turning digital, entrepreneurial learners also need to develop their networking skills on social media. This will augment entrepreneurship education with more dynamic digital and innovative platforms. Even entrepreneurship study programmes make use of social media for imparting learning (Lapolla, 2014). Entrepreneurial studies indicate that social networks are related to opportunity identification (Klyver & Schøtt, 2011), which may help entrepreneurship development through information support (Amodu & Aka, 2017). Promoting social media as an educational tool among the teaching fraternity is valuable and advisable (Gruzd et al., 2018). Both, entrepreneurial intention and behaviour, are influenced by social media networks (Keegan & Rowley, 2017). This study will help trainers and teachers encourage the use of social media for teaching and promoting the practical aspects of entrepreneurship. It can also provide guidelines to universities and colleges on the effective use of social media for inducing entrepreneurship behaviour in students.

Education Implications

The present study aligns with the rising interest academicians are currently showing in how social media might boost entrepreneurial learning. The findings can help them understand/realize the impact of social media in increasing learning capacity and creativity. The influence of digital technologies (e.g., social media) is quite powerful in educational entrepreneurship (Rothaermel et al., 2007). Social media communities can promote a collaborative culture among learners to achieve learning objectives and to cultivate creativity. The social interactions and knowledge sharing in such entrepreneurship communities can help members imbibe entrepreneurship values. The findings indicate that creativity is enhanced in such communities. This implies that learners become proficient at problem-solving and making critical judgement, both of which are essential requirements for entrepreneurs. Research indicates that interacting with entrepreneurs and guest speakers (First, 2001) enhances self-efficacy, which leads to entrepreneurial intentions (Bosma et al., 2012). Thus, educationists can avail the services of entrepreneurs and specialized experts to interact with students on social media communities. Teachers at higher educational levels also use social networks to impart learning (Hickerson & Kothari, 2017). As a medium of instruction in online education, social media has been incorporated into many entrepreneurship programmes (Lapolla, 2014). This defines the scope for delivering entrepreneurial education through social media platforms at universities and colleges. At the same time, government and public policymakers can look at the options and feasibility of using social networks for promoting entrepreneurship among the young population. In cooperation with government agencies, academicians can design social media pages and communities on various social media platforms to share entrepreneurial knowledge with learners.

Recommendations for Policymakers

This research article offers suggestions for public policymakers in education and entrepreneurship. The government should emphasize the use of social media for academic purposes, and especially for entrepreneurial education. Entrepreneurial education can be taught to the students through specific social media platforms. For example, dedicated Facebook pages can be operated by the government and specialized agencies to inculcate an entrepreneurial spirit in learners. Lectures from industrial and academic experts could be delivered on such platforms. Students can develop professional relationships with others and also learn from them. The role of universities in promoting entrepreneurship in contemporary times is rising (Anderson et al., 2010). Many government projects also use information-sharing networks (e.g., Auto-ID Labs, Cleantech Cluster Association, OpenScience Project and Human Genome Project) to collaborate with universities, industries and financiers (Fernández-Pérez et al., 2014). Thus, the government should also change the existing educational framework and environment to foster business orientation through social networks among students. Since entrepreneurship and economic success are positively linked, the government should help develop an entrepreneurial spirit among students in higher educational institutes. Research suggests that females are impacted lesser by social networks as compared to their male counterparts, which should prompt the government to focus on providing more opportunities for women on social networks. They should also encourage female students to participate in diverse social media platforms (Fernández-Pérez et al., 2014) so as to be exposed to relevant information. This can ultimately help create entrepreneurial intentions among female learners. The government can also launch special entrepreneurial programmes on social media platforms that should be academically recognized and award credits to students. Successful entrepreneurs could be hired as administrators of such social media communities to coach and inspire students and to infuse in them an entrepreneurship spirit.

Limitations and Suggestions for Future Research

This article offers theoretical and practical suggestions. But at the same time, it has certain limitations, which further studies can address in order to advance this research domain. The survey method used in this study to collect responses may have induced social desirability prejudices in the data. Future research can reduce this bias by employing qualitative and quantitative methods of data collection. This study is a cross-sectional research type, which is another constraint, as entrepreneurial intentions could change due to personal incidents in one’s life (Krueger, 2007). A similar problem would exist while measuring creativity and learning (Huang, 2020). Future studies could address these limitations using longitudinal research designs, cross-case analysis and a mixed-method approach. This study used a smaller sample size spanning a small geographical area due to current restrictions. Future researchers can increase the sample size and include a more significant geographical study area to generalize the results. Future research could also include other variables that may influence entrepreneurial intentions.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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