Online Social Networks and Women’s Entrepreneurship: A Comparative Study between Iran and Hungary

Bouzari, Parisa; Salamzadeh, Aidin; Soleimani, Maryam; Ebrahimi, Pejman

doi:10.28934/jwee21.34.pp61-75

Cited by 10 publications

(5 citation statements)

References 15 publications

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“…As advocated by the AFT, such skills will promote fairness and equal opportunities for African women in a variety of circumstances and regions. This is reinforced in the study by Bouzari et al (2021), which revealed that online social networks (Facebook and Instagram) significantly facilitate women's participation in entrepreneurship.…”

Section: Social Motivesmentioning

confidence: 83%

Women in Nigeria: Examining the Motivations for Engaging in Social Entrepreneurship

Ihejiamaizu,

Inyang

2022

jwee

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This paper explored the motivations for women engaging in social entrepreneurship in Nigeria. Using the theoretical lens of African feminism, the paper specifically set out to explore the extent to which three factors- gender, penchant for solving social problems and economic/financial reasons influence the desire of women to engage in social entrepreneurship in a largely patriarchal society like Africa. Existing studies adopting critical feminist perspectives have shown that across the globe, there are embedded biases and institutional constraints which could separate women from men into what is considered appropriate “entrepreneuring” for their sex category (Muntean & Ozkazanc-Pan, 2016). This implies that while it is applauded that women can get self-employed in ventures that create social good, there is the risk of creating biases that unintentionally limits the potential of women toward less-lucrative/tasking self-employment. This phenomenon raised some key questions for this paper: Do women only perform better when it comes to designing enterprises for social good? Or do the narratives show that they could lead in other forms of entrepreneurship but are not because of existing constraints? Simply put, what is the drive or motivation for engaging in social entrepreneurship? Interestingly, such a study is lacking within the African context. For this research, a qualitative approach was adopted. Secondary data were obtained from the Ashoka.com repository, a reputable organization and social entrepreneurship website, profiled with stories of successful women social entrepreneurs. A total of 6 research subjects were randomly selected for the study. The sample was drawn from the list of published profiles based on the year of fellowship, country and sector of operation. Data were analysed using content analysis. The findings drawn from the analysis were discussed within the purview of African feminist theory and empirical works of other social researchers. The result showed that women social entrepreneurs are majorly motivated by the desire to solve a social problem (rather than make profit), which either stems from a personal experience or those around them. This study recommends that understanding the intrinsic motivation behind their actions can help social activist and feminist organizations supporting social entrepreneurs in their work. The paper further informs interventions that foster the design of social policies and programmes for successful women social entrepreneurship practice in Africa.

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Section: Social Motivesmentioning

confidence: 83%

Women in Nigeria: Examining the Motivations for Engaging in Social Entrepreneurship

Ihejiamaizu,

Inyang

2022

jwee

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“…The mean COV in the first study was 0.18, which dropped to 0.16 in the second study, thus showing an acceptable consensus in this study (Wong et al, 2020). Inter‐class correlation (ICC) coefficient value was confirmed in consistency terms to ensure validity (Bouzari et al, 2021; Fekete‐Farkas et al, 2021; Khajeheian & Ebrahimi, 2021). Specialists requested to rate the questionnaire according to the “average measurement of each factor.” These scores were applied to evaluate the ICC coefficient.…”

Section: Methodsmentioning

confidence: 95%

Technological barriers to creating regional resilience in digital platform‐based firms: Compound of performance sensitivity analysis and BIRCH algorithm

Salamzadeh,

Dana,

Ebrahimi

et al. 2024

Thunderbird Intl Bus Rev

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Entrepreneurial ventures face various problems contributing to the regional resilience of their districts. Among such firms are digital platform‐based businesses that could have exponential impacts—indeed, if they succeed in overcoming the barriers. Thus, this study aims to identify the major technological barriers to creating regional resilience in Iran's innovation districts. This study uses the analytical hierarchy process method and an unsupervised machine learning algorithm, as well as the Delphi technique. Online panel surveys are conducted to collect data from experts in the field of online social platforms. The findings show that digital literacy barriers and cultural barriers are the criteria with the uppermost and lowermost importance. Performance sensitivity analysis illustrates that considering the C1 and C4 criteria, the Digikala platform is more resistant to technological barriers compared to other platforms. Furthermore, based on C2 and C3 criteria, it can be stated that the Snapp platform reveals better resistance than the other platforms. The importance‐performance matrix also shows that all platforms need more attention in terms of performance. Besides, the results of the BIRCH analysis show that the present model's accuracy is 88%. Meanwhile, outputs show that experts are divided into four groups or four different thoughts.

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“…Modifications in technology, and hence consumer habits, have increased online purchasing (Garcia et al 2020). In growing regions, social media marketing, startups, and various web tools are increasingly important (Bouzari et al 2021). In the midst of the new normal brought on by the coronavirus disease 2019 (COVID-19), mobile grocery shopping apps have become a lifeline for many consumers who have chosen to shop safer (Bruwer et al 2021).…”

Section: Grocery Shopping Mobile Appsmentioning

confidence: 99%

Grocery Apps and Consumer Purchase Behavior: Application of Gaussian Mixture Model and Multi-Layer Perceptron Algorithm

Salamzadeh

Ebrahimi

Soleimani

et al. 2022

JRFM

Self Cite

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The purpose of this study is to investigate and compare the popularity of common grocery apps in Hungary as well as Iran. The data were gathered from Iranian and Hungarian users who had at least one online purchase experience using a grocery app. A Gaussian mixture model (GMM) and multi-layer perceptron (MLP) are used as supervised and unsupervised machine learning algorithms with Python programming to cluster customers and predict consumer behavior. The results revealed that Wolt in Hungary and Snappfood in Iran are the most popular grocery apps. Users in Iran are divided into three groups of users of app services and the type of full covariance has higher accuracy compared to the other three types (96%). Meanwhile, we found that the five apps used in Hungary have provided 95% accuracy from the users’ point of view based on the diagonal covariance. The MSE value (overfitting and cross-validation) is less than 0.1 in the MLP algorithm, which shows an acceptable amount of error. The results of overfitting indicate the proper fit of the MLP model. The findings of this study could be important for managers of online businesses. In the clustering section, the accuracy and value of consumer demographic information have been emphasized. Additionally, in the classification and prediction section, a kind of “customization” has been performed with an emphasis on market segmentation. This research used GMM and MLP machine learning algorithms as a creative way to cluster and classify consumers.

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Online Social Networks and Women’s Entrepreneurship: A Comparative Study between Iran and Hungary

Cited by 10 publications

References 15 publications

Women in Nigeria: Examining the Motivations for Engaging in Social Entrepreneurship

Women in Nigeria: Examining the Motivations for Engaging in Social Entrepreneurship

Technological barriers to creating regional resilience in digital platform‐based firms: Compound of performance sensitivity analysis and BIRCH algorithm

Grocery Apps and Consumer Purchase Behavior: Application of Gaussian Mixture Model and Multi-Layer Perceptron Algorithm

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