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Asian Business Research Journal 
Vol. 10, No. 9, 99-112, 2025 
ISSN: 2576-6759 
DOI: 10.55220/2576-6759.578 
© 2025 by the author; licensee Eastern Centre of Science and Education, USA 

 
 

 

 
Digital Communication Networks and Women's Economic Empowerment: The 
Mediating Role of Social Capital in Vietnam 

 
The Song Ha NGUYEN 
 

 
 

Hanoi – Amsterdam High School for the Gifted, VietNam. 
Email: nguyenthesongha@gmail.com   
 

 
Abstract 

This study investigates the complex relationship between digital communication networks, social 
capital formation, and women's economic empowerment within Vietnam's rapidly evolving digital 
landscape. Drawing upon social capital theory and feminist economic frameworks, the research 
examines how digital communication technologies facilitate the accumulation of bonding, 
bridging, and linking social capital, which subsequently enhances women's economic opportunities 
and outcomes. Employing a mixed-methods approach combining structural equation modelling 
(SEM) and fuzzy-set qualitative comparative analysis (fsQCA), the study analysed data from 847 
Vietnamese women entrepreneurs and micro-enterprise operators across urban and rural 
contexts. The findings reveal that digital communication networks significantly enhance women's 
economic empowerment through the mediating mechanism of social capital, with particularly 
strong effects observed in rural contexts where traditional social networks may be more 
constrained. The study demonstrates that bonding social capital primarily influences access to 
informal financial resources, whilst bridging social capital facilitates market expansion and 
business network development. Linking social capital emerges as particularly crucial for accessing 
formal institutional support and navigating regulatory frameworks. The research contributes to 
the growing literature on digital inclusion and gender empowerment by providing empirical 
evidence of the pathways through which digital technologies can address traditional barriers to 
women's economic participation in emerging economies. 

 
Keywords: Digital communication networks, Social capital, Women's economic empowerment, Structural equation modelling, Vietnam. 

 
1. Introduction 

The proliferation of digital communication technologies across emerging economies has fundamentally 
transformed the landscape of social and economic interaction, creating unprecedented opportunities for 
marginalised populations to access resources, markets, and institutional support systems (Castells, 2015; Wellman 
& Rainie, 2012). Within this digital transformation, women entrepreneurs and micro-enterprise operators 
represent a particularly significant demographic, as digital platforms may potentially address longstanding barriers 
to economic participation including limited access to financial services, restricted mobility, and constrained social 
networks (Agarwal et al., 2016; Demirgüç-Kunt et al., 2013). 

Vietnam's rapid digital transformation presents a compelling case study for examining these dynamics. The 
country has experienced remarkable growth in internet penetration, rising from 31% in 2010 to approximately 70% 
by 2017, with mobile phone ownership reaching near-universal levels across both urban and rural populations 
(Vietnam Ministry of Information and Communications, 2017). This digital expansion has occurred alongside 
significant economic liberalisation and gender equality initiatives, creating a unique environment for investigating 
the intersection of digital technologies, social capital, and women's economic empowerment. 

The theoretical foundation for understanding these relationships lies primarily within social capital theory, 
which posits that social networks constitute a form of capital that can be leveraged for economic and social 
advantage (Bourdieu, 1986; Coleman, 1988; Putnam, 2000). However, traditional conceptualisations of social capital 
have been developed primarily within offline contexts, necessitating theoretical extension to accommodate the 
unique characteristics of digitally mediated social interactions. Digital communication networks may 
fundamentally alter the mechanisms through which social capital is accumulated, maintained, and leveraged, 
potentially creating new pathways for economic empowerment whilst simultaneously reinforcing existing social 
inequalities. 

Contemporary scholarship has identified three primary dimensions of social capital: bonding capital, which 
encompasses ties within homogeneous groups; bridging capital, which involves connections across diverse social 
groups; and linking capital, which represents vertical connections to formal institutions and power structures 
(Woolcock, 2001; Szreter & Woolcock, 2004). The digital environment may distinctively influence each dimension, 
with implications for how social capital translates into economic opportunities for women entrepreneurs. 

mailto:nguyenthesongha@gmail.com
https://doi.org/10.55220/2576-6759.578


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The necessity of this research emerges from several critical gaps within existing literature. Firstly, whilst 
extensive research has examined the general relationship between digital technologies and economic development, 
limited attention has been devoted to understanding the specific mechanisms through which digital communication 
networks influence women's economic empowerment in emerging economy contexts (Hilbert, 2011; Qureshi, 
2015). Secondly, social capital research has predominantly focused on offline networks, with insufficient exploration 
of how digital platforms may transform social capital accumulation and utilisation processes (Ellison et al., 2014; 
Hampton et al., 2011). Thirdly, existing studies have largely employed single-method approaches, limiting the 
capacity to understand both the quantitative relationships and the configurational pathways through which digital 
communication networks influence economic outcomes. 

The theoretical urgency of this research is underscored by ongoing debates within development economics 
regarding the conditions under which digital technologies contribute to inclusive economic growth versus 
reinforcing existing inequalities (Graham & Mann, 2013; Toyama, 2011). Understanding how social capital 
mediates the relationship between digital access and economic empowerment is crucial for informing policy 
interventions designed to maximise the inclusive benefits of digital transformation. 

Vietnam provides an ideal context for this investigation due to several distinctive characteristics. The country's 
Confucian cultural heritage places particular emphasis on social relationships and network-based business 
practices, making social capital especially relevant for economic activity (Nguyen et al., 2009). Additionally, 
Vietnam's transition from a centrally planned to market economy has created complex institutional environments 
where informal networks often complement formal institutions in facilitating economic transactions (Fforde, 2009). 
The country's substantial gender gap in business ownership and financial inclusion, combined with rapidly 
expanding digital infrastructure, creates conditions where digital communication networks may play a particularly 
significant role in women's economic empowerment. 

The novelty of this research lies in its integration of social capital theory with digital communication 
frameworks within a gender empowerment perspective, employing complementary quantitative methodologies to 
examine both linear relationships and configurational pathways. The study advances beyond descriptive analyses of 
digital divides to provide causal insights into the mechanisms through which digital technologies influence 
economic outcomes for women entrepreneurs in emerging economies. 
 

2. Foundational Theories and Literature Review 
2.1. Foundational Theories 
2.1.1. Social Capital Theory 

Social capital theory provides the primary theoretical foundation for understanding how digital communication 
networks influence women's economic empowerment. Originating from the seminal works of Bourdieu (1986), 
Coleman (1988), and Putnam (2000), social capital theory conceptualises social relationships as a form of capital 
that can be accumulated, maintained, and leveraged for various outcomes including economic advancement, 
political participation, and social mobility. 

Bourdieu's (1986) conceptualisation of social capital emphasises its role as a resource embedded within social 
networks, which individuals can mobilise to secure benefits and opportunities. This perspective highlights the 
instrumental nature of social relationships, whereby social capital functions as a mechanism for accessing other 
forms of capital including economic, cultural, and symbolic capital. Within the context of women's economic 
empowerment, Bourdieu's framework suggests that social networks may serve as crucial conduits for accessing 
financial resources, market information, and business opportunities that might otherwise remain inaccessible 
through formal institutional channels. 

Coleman's (1988) functional approach to social capital emphasises its capacity to facilitate collective action and 
reduce transaction costs within social systems. This perspective is particularly relevant for understanding how 
digital communication networks might enable women entrepreneurs to overcome information asymmetries and 
coordination problems that traditionally constrain business development in emerging economies. Coleman's 
emphasis on trust and reciprocity as foundational elements of social capital provides insight into how digital 
platforms might either strengthen or weaken the social fabric necessary for effective network utilisation. 

Putnam's (2000) distinction between bonding, bridging, and linking social capital has become fundamental to 
contemporary social capital research. Bonding social capital encompasses ties within homogeneous groups, 
typically characterised by strong emotional connections and high levels of mutual support. For women 
entrepreneurs, bonding capital might include relationships with family members, close friends, and other women in 
similar circumstances, providing emotional support, informal financing, and shared resources during business 
development processes. 

Bridging social capital involves connections across diverse social groups, facilitating access to novel 
information, resources, and opportunities. This dimension is particularly crucial for business growth, as it enables 
entrepreneurs to access new markets, identify emerging opportunities, and develop partnerships with individuals 
and organisations from different social contexts. Digital communication networks may be especially effective at 
facilitating bridging capital by reducing the geographical and social barriers that traditionally limit cross-group 
interaction. 

Linking social capital represents vertical connections to formal institutions and individuals in positions of 
authority or power. For women entrepreneurs in emerging economies, linking capital is often crucial for accessing 
government services, obtaining business licences, securing formal credit, and navigating regulatory frameworks. 
Digital platforms may enhance linking capital by providing new channels for interaction with institutional 
representatives and creating opportunities for collective advocacy and policy engagement. 

Recent theoretical developments have extended social capital theory to accommodate digital environments, 
recognising that online social networks may possess distinctive characteristics compared to offline relationships 
(Ellison et al., 2014; Steinfield et al., 2008). Digital social capital research suggests that online networks may be 
particularly effective at maintaining weak ties, facilitating information dissemination, and enabling collective action 



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across geographical boundaries. However, questions remain regarding whether digitally mediated relationships can 
generate the same levels of trust and reciprocity that characterise face-to-face interactions. 
2.1.2. Women's Economic Empowerment Theory 

Women's economic empowerment theory provides the secondary theoretical foundation for this research, 
drawing primarily from feminist economics and development studies to understand the processes through which 
women gain greater control over economic resources and decision-making processes (Kabeer, 2001; Sen, 1999). 
This theoretical framework recognises that women's economic participation is shaped by complex interactions 
between individual agency, structural opportunities, and cultural constraints. 

Kabeer's (2001) empowerment framework emphasises three interconnected dimensions: resources, agency, and 
achievements. Resources encompass not only material assets but also human and social resources that enable 
effective action. Agency refers to the capacity to make strategic choices and act upon them, whilst achievements 
represent the outcomes of empowerment processes. This framework provides a comprehensive lens for 
understanding how digital communication networks might influence different aspects of women's economic 
empowerment. 

Within this framework, social capital can be conceptualised as a crucial resource that enhances women's agency 
by expanding their capacity to make strategic choices about economic participation. Digital communication 
networks may strengthen this resource by providing new mechanisms for social capital accumulation whilst 
simultaneously creating platforms for exercising agency through market participation, collective action, and 
institutional engagement. 

Sen's (1999) capability approach emphasises the importance of expanding individuals' capabilities to achieve 
valued functionings, including economic security, social participation, and personal autonomy. This perspective 
suggests that digital communication networks might enhance women's economic empowerment by expanding their 
opportunity sets and reducing the constraints that limit their capacity to pursue economic goals. 

Feminist economics scholarship has identified several key barriers to women's economic empowerment in 
emerging economies, including limited access to financial services, restricted mobility, time poverty due to unpaid 
care responsibilities, and social norms that discourage women's economic participation (Duflo, 2012; Pitt et al., 
2006). Digital communication networks may address some of these barriers by enabling remote market 
participation, reducing transaction costs, and providing platforms for collective action that challenge restrictive 
social norms. 

The integration of social capital theory with women's economic empowerment frameworks suggests that 
digital communication networks may enhance women's economic outcomes through multiple pathways. Social 
networks may provide access to financial resources, market information, and business opportunities whilst 
simultaneously offering emotional support and collective efficacy that enable women to overcome cultural and 
institutional barriers to economic participation. 
 

2.2. Review of Empirical and Relevant Studies 
2.2.1. Digital Communication Networks and Social Capital 

Empirical research examining the relationship between digital communication technologies and social capital 
formation has produced mixed findings, with some studies demonstrating positive effects whilst others identify 
potential negative consequences or null relationships (Burke & Kraut, 2016; Valenzuela et al., 2009). This variation 
appears to be influenced by factors including the specific digital platforms examined, the populations studied, and 
the measures employed to assess social capital outcomes. 

Steinfield et al. (2008) conducted longitudinal research examining Facebook usage among university students, 
finding that social networking site usage was positively associated with bridging social capital formation, 
particularly for individuals with lower initial social capital levels. This finding suggests that digital platforms may 
be especially beneficial for individuals who face traditional barriers to social network development, a characteristic 
that may be particularly relevant for women in patriarchal societies where social mobility is constrained. 

Hampton et al. (2011) examined the relationship between internet usage and neighbourhood social capital, 
finding that digital communication technologies can both supplement and substitute for offline social interactions 
depending on contextual factors. Their research suggests that digital platforms are most effective at enhancing 
social capital when they complement rather than replace face-to-face interactions, highlighting the importance of 
understanding how online and offline networks interact within specific cultural contexts. 

Ellison et al. (2014) conducted meta-analytic research examining social network site usage and social capital 
outcomes, identifying significant positive relationships across multiple studies and contexts. However, their 
analysis revealed that effect sizes varied considerably based on demographic factors, with women and individuals 
from collectivist cultures demonstrating stronger relationships between digital network participation and social 
capital outcomes. 

Research specifically examining social capital formation in emerging economies has highlighted the importance 
of mobile phone technologies in facilitating social network development and maintenance (Donner, 2015; Porter et 
al., 2016). Donner's (2015) comprehensive review of mobile phone research in developing countries identified 
numerous studies demonstrating positive relationships between mobile phone access and various social capital 
indicators, including participation in community organisations, trust in social institutions, and collective efficacy 
for addressing community problems. 
 

2.2.2. Social Capital and Women's Economic Empowerment 
Empirical research examining the relationship between social capital and women's economic empowerment has 

consistently demonstrated positive associations across diverse contexts and measures (Mayoux, 2001; Pitt et al., 
2006; Fletschner & Kenney, 2014). However, the mechanisms through which social capital influences economic 
outcomes appear to vary based on the specific dimensions of social capital examined and the economic indicators 
assessed. 



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Pitt et al. (2006) conducted experimental research in Bangladesh examining women's participation in 
microfinance programmes, finding that social capital accumulation through group participation significantly 
enhanced business outcomes and household welfare indicators. Their research demonstrated that bonding social 
capital, developed through regular group interactions, was particularly important for accessing informal financial 
resources and managing business risks through mutual support mechanisms. 

Fletschner and Kenney (2014) examined rural women's social networks in Paraguay, finding that bridging 
social capital was more strongly associated with agricultural innovation adoption and market participation 
compared to bonding social capital. This research suggests that different dimensions of social capital may be more 
effective for different types of economic activities, with bridging capital being particularly important for accessing 
new market opportunities and technological innovations. 

Mayoux's (2001) comprehensive review of women's empowerment programmes identified social capital 
formation as a consistent predictor of successful economic empowerment outcomes across diverse cultural contexts. 
However, her analysis also highlighted that social capital effects were often mediated by institutional factors, 
suggesting that the economic benefits of social network participation depend partially on the broader institutional 
environment within which networks operate. 

Research examining women's entrepreneurship in emerging economies has consistently identified social 
networks as crucial sources of business financing, market information, and emotional support (Al-Dajani et al., 
2015; Brush et al., 2009). Al-Dajani et al. (2015) conducted qualitative research examining women entrepreneurs in 
Jordan, finding that informal social networks were often more important than formal business support services for 
accessing the resources necessary for business development and growth. 
 

2.2.3. Digital Technologies and Women's Economic Empowerment 
Research examining the direct relationship between digital technologies and women's economic empowerment 

has expanded rapidly in recent years, with studies generally finding positive effects whilst acknowledging the 
importance of contextual factors in determining outcomes (Demirgüç-Kunt et al., 2013; Asongu & Odhiambo, 2017; 
Hilbert, 2011). 

Demirgüç-Kunt et al. (2013) analysed Global Findex data examining financial inclusion patterns across 
developing countries, finding that mobile phone ownership was significantly associated with women's access to 
formal financial services after controlling for various demographic and economic factors. Their research suggested 
that mobile banking technologies could potentially address traditional barriers to women's financial inclusion 
including limited mobility, time constraints, and discriminatory practices within formal financial institutions. 

Jack and Suri (2014) conducted influential research examining the impact of M-Pesa mobile money system in 
Kenya, finding that access to mobile financial services led to significant improvements in consumption smoothing 
and risk management, with particularly strong effects observed for women-headed households. Their research 
demonstrated that digital financial technologies could enhance women's economic security even in contexts where 
formal financial institutions remained largely inaccessible. 

Research examining digital technologies and women's entrepreneurship has identified several mechanisms 
through which digital platforms may enhance business outcomes, including reduced transaction costs, expanded 
market access, and enhanced communication with customers and suppliers (Gichuki et al., 2014; Mwobobia, 2012). 
However, these studies have generally focused on describing correlations rather than identifying causal 
mechanisms, limiting understanding of the processes through which digital technologies influence empowerment 
outcomes. 
 

2.3. Proposed Research Model 
Based on the comprehensive literature review and theoretical synthesis presented above, this research proposes 

an integrated model examining the mediating role of social capital in the relationship between digital 
communication networks and women's economic empowerment. The model incorporates three primary constructs: 
digital communication network usage, multidimensional social capital (bonding, bridging, and linking), and 
women's economic empowerment, with several control variables to account for individual and contextual factors 
that may influence these relationships. 

Digital communication network usage represents the primary independent variable, conceptualised as a 
multidimensional construct encompassing the frequency, diversity, and intensity of digital platform usage for social 
and economic purposes. This construct draws upon technology acceptance and digital divide research, 
incorporating measures of both access and usage patterns (DiMaggio et al., 2004; Van Dijk, 2020). The 
measurement framework includes indicators of social media participation, mobile communication usage, and digital 
platform engagement for business purposes, recognising that different types of digital communication may have 
varying effects on social capital formation and economic outcomes. 

Social capital constitutes the primary mediating variable, operationalised according to the three-dimensional 
framework developed by Woolcock (2001) and Szreter and Woolcock (2004). Bonding social capital is measured 
through indicators of network density, emotional support availability, and reciprocity within close social 
relationships. Bridging social capital encompasses measures of network diversity, weak tie strength, and cross-
group interaction frequency. Linking social capital includes indicators of institutional access, formal network 
participation, and connections to individuals in positions of authority or expertise. 

Women's economic empowerment represents the primary dependent variable, conceptualised as a 
multidimensional construct incorporating both economic outcomes and empowerment processes. Drawing upon 
Kabeer's (2001) empowerment framework, the construct includes measures of economic achievement (income 
generation, asset accumulation, financial security), economic agency (decision-making autonomy, business 
ownership, financial control), and economic resources (access to credit, market information, business networks). 
This multidimensional approach recognises that empowerment encompasses both the capacity to make strategic 
choices and the achievement of valued economic outcomes. 



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Figure 1. Proposed Research Model. 

 
The research model incorporates several control variables to account for factors that may influence the primary 

relationships of interest. Individual-level controls include age, education, marital status, household composition, 
and prior business experience, drawing upon entrepreneurship and development economics literature identifying 
these factors as significant predictors of women's economic participation (Brush et al., 2009; Demirgüç-Kunt et al., 
2013). Contextual controls include urban versus rural residence, regional economic development indicators, and 
local infrastructure availability, recognising that the effects of digital technologies may vary based on broader 
environmental factors. 

The theoretical model proposes several specific hypotheses regarding the relationships between constructs. 
Firstly, digital communication network usage is hypothesised to positively influence all three dimensions of social 
capital, with potentially stronger effects on bridging and linking capital compared to bonding capital, given the 
capacity of digital platforms to facilitate connections across geographical and social boundaries. Secondly, each 
dimension of social capital is hypothesised to positively influence women's economic empowerment, with 
potentially differential effects based on the specific empowerment outcomes examined. Thirdly, social capital 
dimensions are hypothesised to mediate the relationship between digital communication networks and economic 
empowerment, suggesting that digital technologies influence empowerment primarily through their effects on 
social network development and utilisation. 

The model also incorporates potential moderation effects, recognising that the strength of relationships may 
vary based on contextual factors. Urban versus rural residence is hypothesised to moderate the relationship 
between digital communication networks and social capital formation, with potentially stronger effects in rural 
contexts where traditional social networks may be more constrained. Educational attainment is hypothesised to 
moderate the relationship between social capital and economic empowerment, with potentially stronger effects for 
women with higher education levels who may be better positioned to leverage social networks for economic 
advancement. 
 

3. Research Methodology 
3.1. Research Design 

This study employed a cross-sectional survey design with complementary quantitative analytical approaches to 
examine the complex relationships between digital communication networks, social capital, and women's economic 
empowerment in Vietnam. The research design integrated structural equation modelling (SEM) using partial least 
squares (PLS) approach with fuzzy-set qualitative comparative analysis (fsQCA) to provide both correlational 
insights and configurational understanding of the phenomena under investigation. 

The philosophical foundation of this research rests within a post-positivist paradigm, acknowledging the 
existence of objective social phenomena whilst recognising the complexity and contextual nature of social 
relationships (Creswell, 2014; Guba & Lincoln, 1994). This paradigmatic stance is particularly appropriate for 
examining technology-mediated social capital formation, as it enables rigorous quantitative analysis whilst 
acknowledging the multifaceted nature of empowerment processes and the potential for multiple pathways to 
similar outcomes. 

The mixed-method quantitative approach was selected to address the limitations inherent in single-method 
studies of social capital and empowerment phenomena. Structural equation modelling provides insights into the 
strength and significance of relationships between constructs whilst controlling for measurement error and 
enabling examination of complex mediation relationships (Hair et al., 2017). The PLS-SEM approach was 
specifically chosen due to its capacity to handle complex models with multiple mediating relationships and its 
robustness to non-normal data distributions, characteristics that are particularly relevant for empowerment 
research in emerging economy contexts (Hair et al., 2014). 

Fuzzy-set qualitative comparative analysis complements the SEM analysis by examining configurational 
relationships and identifying the combinations of conditions that are sufficient for achieving high levels of women's 
economic empowerment (Ragin, 2008; Schneider & Wagemann, 2012). This approach recognises that 
empowerment may result from multiple different pathways and that the effects of digital communication networks 
and social capital may depend on specific configurations of contextual factors. 
 

3.2. Data Collection 
Data collection was conducted between March and August 2017 across six provinces in Vietnam, selected to 

represent diverse geographical, economic, and cultural contexts within the country. The provinces included Ho Chi 
Minh City and Hanoi (representing major urban centres), Hai Phong and Da Nang (representing secondary cities), 
and Dong Nai and An Giang (representing rural and agricultural contexts). This geographical diversity was 



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essential for capturing variation in digital infrastructure development, economic opportunities, and cultural factors 
that might influence the relationships under investigation. 

The target population consisted of Vietnamese women aged 18-55 who were engaged in income-generating 
activities including formal employment, informal business activities, agricultural production, or micro-enterprise 
operation. This broad definition of economic participation was adopted to capture the diverse ways in which 
women contribute to household income and economic development in emerging economy contexts, recognising 
that formal entrepreneurship represents only one pathway for women's economic empowerment. 

A stratified random sampling approach was employed to ensure adequate representation across geographical 
regions, age groups, and economic activity types. The sampling frame was constructed using commune-level 
population data provided by the General Statistics Office of Vietnam, with stratification based on urban/rural 
residence, province, and age group. Within each stratum, systematic random sampling was used to select potential 
participants from comprehensive household lists maintained by local administrative committees. 

A total of 1,200 women were initially contacted for participation in the study, with 847 completing the full 
survey instrument, representing a response rate of 70.6%. Non-response analysis revealed no significant differences 
between respondents and non-respondents on available demographic characteristics including age, education, and 
geographical location, suggesting that non-response bias was unlikely to substantially affect the study findings. 

Data collection was conducted through face-to-face interviews using structured questionnaires administered by 
trained research assistants. This approach was selected to ensure high data quality and to accommodate 
participants with limited literacy levels, particularly important in rural contexts where educational attainment may 
be lower. All research assistants completed comprehensive training programmes covering interview techniques, 
questionnaire administration, and ethical considerations for research involving vulnerable populations. 

The questionnaire was initially developed in English and then translated into Vietnamese using forward and 
back-translation procedures to ensure linguistic equivalence. Pre-testing was conducted with 50 participants across 
urban and rural contexts, leading to minor modifications in question wording and response formats to enhance 
clarity and cultural appropriateness. 
 

3.3. Measurement & Validation 
The measurement framework for this study drew upon established scales from previous research whilst 

incorporating modifications necessary for the Vietnamese context and the specific focus on digital communication 
networks. All constructs were measured using multiple indicators to enable latent variable analysis and enhance 
measurement reliability and validity. 

Digital communication network usage was measured using a 15-item scale adapted from the digital divide and 
technology adoption literature (DiMaggio et al., 2004; Hargittai, 2010). The scale encompassed three dimensions: 
access and infrastructure (availability of devices and internet connectivity), usage frequency and diversity 
(frequency of different digital platform usage), and social and economic application (use of digital technologies for 
social networking and business purposes). Sample items included "How frequently do you use social media 
platforms to communicate with friends and family?" and "How often do you use mobile phones or internet for 
business-related activities?" Responses were recorded on seven-point Likert scales ranging from "never" to "very 
frequently." 

Social capital was operationalised using an adapted version of the Social Capital Assessment Tool developed by 
the World Bank, modified to incorporate digital network elements (Krishna & Shrader, 2000; Grootaert et al., 
2004). The instrument measured three dimensions of social capital through 24 items. Bonding social capital (8 
items) assessed the strength and density of relationships within homogeneous groups, with items such as 
"Members of your immediate social circle provide emotional support during difficult times" and "You can rely on 
close friends and family for financial assistance when needed." Bridging social capital (8 items) examined 
connections across diverse social groups, including items such as "Through your networks, you interact with 
people from different educational backgrounds" and "Your social connections include people from various 
occupations and industries." Linking social capital (8 items) measured connections to formal institutions and 
authority figures, with items such as "You have contacts who can help you navigate government procedures" and 
"You know people who work in banks or financial institutions who could provide advice." 

Women's economic empowerment was measured using a 21-item scale developed by synthesising established 
empowerment measures with specific indicators relevant to emerging economy contexts (Kabeer, 2001; Malhotra 
et al., 2002). The scale incorporated three dimensions aligned with Kabeer's empowerment framework. Economic 
resources (7 items) assessed access to and control over financial and material resources, with items such as "You 
have independent access to financial services" and "You control decisions about major household purchases." 
Economic agency (7 items) measured decision-making autonomy and strategic choice capacity, including items 
such as "You make decisions about how to use your personal income" and "You choose whether to start or expand 
business activities." Economic achievements (7 items) assessed economic outcomes and security, with items such as 
"Your income contributes significantly to household welfare" and "You have accumulated savings or assets in your 
own name." 

Control variables were measured using standard demographic and socioeconomic indicators. Individual-level 
controls included age (continuous variable), education (eight categories from no formal education to university 
degree), marital status (categorical), household size (continuous), and business experience (categorical). Contextual 
controls included urban/rural residence (binary), province (categorical), and household wealth index (constructed 
using principal component analysis of asset ownership indicators). 

Scale validation procedures followed established protocols for cross-cultural research (Brislin, 1986; Van de 
Vijver & Hambleton, 1996). Content validity was assessed through expert review by Vietnamese social science 
researchers familiar with local contexts and measurement issues. Face validity was evaluated through cognitive 
interviews with 25 women from the target population, leading to minor modifications in item wording and 
response formats. 
 



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3.4. Analytical Procedure 
The analytical strategy employed a sequential approach integrating multiple quantitative techniques to provide 

comprehensive insights into the relationships between digital communication networks, social capital, and women's 
economic empowerment. All analyses were conducted using SPSS 24.0, SmartPLS 4.0, and fsQCA 3.0 software 
packages. 

Preliminary analyses included examination of data quality, missing value patterns, and assumption testing for 
multivariate analyses. Missing data analysis revealed that less than 3% of values were missing for any individual 
variable, with missing data patterns appearing to be missing completely at random based on Little's MCAR test. 
Multiple imputation procedures were employed to address missing values, with five imputed datasets generated 
and pooled results reported for all subsequent analyses. 

The measurement model assessment followed established protocols for PLS-SEM analysis (Hair et al., 2017). 
Exploratory factor analysis (EFA) was initially conducted using principal component analysis with varimax 
rotation to examine the dimensionality of constructs and identify potential problematic indicators. Subsequently, 
confirmatory factor analysis (CFA) was conducted within the PLS framework to validate the measurement model 
structure. 

Internal consistency reliability was assessed using Cronbach's alpha and composite reliability coefficients, with 
values above 0.70 considered acceptable for exploratory research (Nunnally & Bernstein, 1994). Indicator reliability 
was evaluated through examination of factor loadings, with loadings above 0.70 considered satisfactory for 
confirmatory research contexts (Chin, 1998). 

Convergent validity was assessed using average variance extracted (AVE), with values above 0.50 indicating 
that constructs explain more variance in their indicators than error variance (Fornell & Larcker, 1981). 
Discriminant validity was evaluated using both the Fornell-Larcker criterion and the heterotrait-monotrait 
(HTMT) ratio of correlations, with HTMT values below 0.85 supporting discriminant validity (Henseler et al., 
2015). 

The structural model assessment examined the relationships between constructs whilst controlling for 
measurement error. Path coefficients and their significance levels were assessed using bootstrapping procedures 
with 5,000 resamples, providing robust estimates of standard errors and confidence intervals (Hair et al., 2017). 
Effect sizes were evaluated using Cohen's guidelines, with f² values above 0.02, 0.15, and 0.35 representing small, 
medium, and large effect sizes respectively (Cohen, 1988). 

Mediation analysis was conducted using the product of coefficients approach, examining both direct and 
indirect effects of digital communication networks on economic empowerment through social capital dimensions. 
The significance of indirect effects was assessed using bootstrapped confidence intervals, with mediation confirmed 
when confidence intervals excluded zero (Hayes, 2017). 

Multigroup analysis was conducted to examine potential moderation effects of contextual factors including 
urban/rural residence, education level, and age group. PLS multigroup analysis (PLS-MGA) was employed to test 
differences in path coefficients across groups, with p-values below 0.05 indicating significant group differences 
(Henseler et al., 2009). 

Fuzzy-set qualitative comparative analysis was conducted to complement the SEM findings by examining 
configurational relationships and identifying sufficient conditions for high economic empowerment outcomes. 
Variables were calibrated using the direct method with anchor points set at 95th percentile (full membership), 50th 
percentile (crossover point), and 5th percentile (full non-membership). Necessity analysis examined individual 
conditions that were necessary for the outcome, whilst sufficiency analysis identified combinations of conditions 
that were sufficient for achieving high empowerment levels. Solution paths were evaluated based on consistency 
scores (>0.80) and coverage metrics (>0.25) following established QCA protocols (Ragin, 2008). 
 

4. Research Findings 
4.1. Measurement Model Assessment 

The measurement model assessment began with exploratory factor analysis (EFA) to examine the underlying 
structure of the measurement instruments and identify any problematic indicators that might compromise 
construct validity. Principal component analysis with varimax rotation revealed clear factor structures for all major 
constructs, with eigenvalues exceeding 1.0 and factor loadings above 0.60 for retained indicators. 

The EFA results for the digital communication networks construct yielded three distinct factors corresponding 
to the theoretical dimensions of access/infrastructure, usage frequency/diversity, and social/economic application. 
The total variance explained was 72.4%, with factor loadings ranging from 0.634 to 0.891. Two indicators with 
cross-loadings above 0.40 were removed from subsequent analyses to enhance discriminant validity. 

Social capital EFA produced three clear factors representing bonding, bridging, and linking dimensions, 
accounting for 68.9% of total variance. Factor loadings ranged from 0.612 to 0.854, with strong correspondence 
between empirical factors and theoretical constructs. One indicator from the linking social capital dimension was 
removed due to poor factor loading (0.487). 

Women's economic empowerment EFA revealed three factors corresponding to resources, agency, and 
achievements dimensions, explaining 71.6% of variance with factor loadings between 0.598 and 0.876. The factor 
structure closely matched theoretical expectations, with no indicators requiring removal based on statistical 
criteria. 
 
 
 
 
 
 
 
 



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Table 1. Reliability and Validity Assessment. 

Construct Items Cronbach's α CR AVE Factor Loadings Range 

Digital Communication Networks 13 0.912 0.926 0.542 0.634-0.891 
- Access/Infrastructure 4 0.856 0.902 0.696 0.782-0.891 

- Usage Frequency/Diversity 5 0.889 0.916 0.684 0.789-0.856 
- Social/Economic Application 4 0.834 0.887 0.663 0.634-0.847 
Social Capital 23 0.943 0.952 0.587 0.612-0.854 
- Bonding Social Capital 8 0.897 0.921 0.662 0.756-0.854 
- Bridging Social Capital 8 0.876 0.906 0.621 0.612-0.823 
- Linking Social Capital 7 0.851 0.890 0.577 0.689-0.798 
Economic Empowerment 21 0.954 0.962 0.609 0.598-0.876 
- Economic Resources 7 0.901 0.924 0.672 0.734-0.876 
- Economic Agency 7 0.886 0.913 0.638 0.689-0.834 
- Economic Achievement 7 0.879 0.908 0.619 0.598-0.823 

 
Confirmatory factor analysis within the PLS framework demonstrated satisfactory measurement model 

performance across all constructs. Internal consistency reliability, as assessed by Cronbach's alpha and composite 
reliability (CR), exceeded the recommended threshold of 0.70 for all constructs and sub-constructs, with values 
ranging from 0.834 to 0.954 for Cronbach's alpha and from 0.887 to 0.962 for composite reliability. 

Indicator reliability was confirmed through examination of outer loadings, with all retained indicators 
achieving loadings above 0.598, exceeding the minimum threshold of 0.50 for exploratory research contexts. The 
majority of indicators (89.5%) achieved loadings above 0.70, meeting the more stringent criterion for confirmatory 
research. 

Convergent validity was established through average variance extracted (AVE) values, with all constructs 
achieving AVE values above 0.50, ranging from 0.542 to 0.696. These results indicate that constructs explain more 
variance in their indicators than is attributable to measurement error, supporting convergent validity. 
 

Table 2. Discriminant Validity Assessment - Fornell-Larcker Criterion. 

Construct 1 2 3 4 5 6 7 

1. Digital Communication Networks 0.736 
      

2. Bonding Social Capital 0.432 0.813 
     

3. Bridging Social Capital 0.567 0.398 0.788 
    

4. Linking Social Capital 0.489 0.289 0.512 0.760 
   

5. Economic Resources 0.401 0.356 0.423 0.398 0.820 
  

6. Economic Agency 0.445 0.334 0.467 0.412 0.578 0.799 
 

7. Economic Achievement 0.423 0.367 0.434 0.389 0.623 0.612 0.787 
           Note: Diagonal elements (in italics) represent the square root of AVE; off-diagonal elements represent correlations between constructs. 

 
Table 3. Discriminant Validity Assessment - HTMT Ratio. 

Construct 1 2 3 4 5 6 7 

1. Digital Communication Networks - 
      

2. Bonding Social Capital 0.498 - 
     

3. Bridging Social Capital 0.634 0.456 - 
    

4. Linking Social Capital 0.567 0.341 0.594 - 
   

5. Economic Resources 0.453 0.401 0.478 0.456 - 
  

6. Economic Agency 0.501 0.376 0.521 0.478 0.642 - 
 

7. Economic Achievement 0.478 0.423 0.487 0.445 0.689 0.687 - 

 
Discriminant validity was assessed using both the Fornell-Larcker criterion and the HTMT ratio of 

correlations. The Fornell-Larcker criterion was satisfied for all construct pairs, with the square root of AVE 
exceeding inter-construct correlations in all cases. HTMT ratios were below 0.85 for all construct pairs, with 
values ranging from 0.341 to 0.689, providing strong support for discriminant validity. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 



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Table 4. Direct Effects Results. 

Hypothesised Path Path 
Coefficient 

Standard 
Error 

t-
value 

p-
value 

95% CI 
Lower 

95% CI 
Upper 

f² Support 

DCN → Bonding SC 0.432** 0.045 9.600 0.000 0.344 0.520 0.230 Yes 

DCN → Bridging SC 0.567** 0.038 14.921 0.000 0.492 0.642 0.473 Yes 

DCN → Linking SC 0.489** 0.041 11.927 0.000 0.409 0.569 0.315 Yes 

Bonding SC → Econ 
Resources 

0.298** 0.049 6.082 0.000 0.202 0.394 0.089 Yes 

Bonding SC → Econ 
Agency 

0.234** 0.051 4.588 0.000 0.134 0.334 0.055 Yes 

Bonding SC → Econ 
Achievement 

0.267** 0.048 5.563 0.000 0.173 0.361 0.071 Yes 

Bridging SC → Econ 
Resources 

0.256** 0.047 5.447 0.000 0.164 0.348 0.066 Yes 

Bridging SC → Econ 
Agency 

0.334** 0.044 7.591 0.000 0.248 0.420 0.111 Yes 

Bridging SC → Econ 
Achievement 

0.289** 0.046 6.283 0.000 0.199 0.379 0.084 Yes 

Linking SC → Econ 
Resources 

0.223** 0.052 4.288 0.000 0.121 0.325 0.050 Yes 

Linking SC → Econ 
Agency 

0.256** 0.049 5.224 0.000 0.160 0.352 0.066 Yes 

Linking SC → Econ 
Achievement 

0.201* 0.051 3.941 0.000 0.101 0.301 0.040 Yes 

Note: DCN = Digital Communication Networks; SC = Social Capital; Econ = Economic; ** p < 0.001, * p < 0.01. 

 

4.2. Structural Model Assessment 
The structural model assessment examined the hypothesised relationships between digital communication 

networks, social capital dimensions, and women's economic empowerment whilst controlling for relevant 
covariates. The overall model demonstrated satisfactory explanatory power, with R² values indicating that the 
model explained substantial variance in all endogenous constructs. 

The direct effects analysis revealed statistically significant positive relationships between digital 
communication networks and all three dimensions of social capital. The strongest relationship was observed 

between digital communication networks and bridging social capital (β = 0.567, p < 0.001, f² = 0.473), followed by 

linking social capital (β = 0.489, p < 0.001, f² = 0.315) and bonding social capital (β = 0.432, p < 0.001, f² = 0.230). 
These findings suggest that digital communication technologies are particularly effective at facilitating connections 
across diverse social groups and formal institutional networks. 

All hypothesised relationships between social capital dimensions and economic empowerment components 
were statistically significant and positive. Bridging social capital demonstrated the strongest relationships with 

economic agency (β = 0.334, p < 0.001, f² = 0.111) and achievement (β = 0.289, p < 0.001, f² = 0.084), whilst 

bonding social capital showed the strongest relationship with economic resources (β = 0.298, p < 0.001, f² = 0.089). 
These patterns suggest differential mechanisms through which social capital dimensions influence empowerment 
outcomes. 
 

Table 5. Predictive Relevance Assessment. 

Construct R² R² Adjusted Q² 

Bonding Social Capital 0.187 0.183 0.121 
Bridging Social Capital 0.321 0.319 0.196 
Linking Social Capital 0.239 0.236 0.135 
Economic Resources 0.234 0.228 0.152 
Economic Agency 0.289 0.284 0.181 
Economic Achievement 0.256 0.250 0.155 

 
The predictive relevance assessment using Stone-Geisser's Q² criterion demonstrated satisfactory predictive 

validity for all endogenous constructs, with Q² values ranging from 0.121 to 0.196. All values exceeded zero, 
indicating that the model has predictive relevance beyond chance. The highest predictive relevance was observed 
for bridging social capital (Q² = 0.196) and economic agency (Q² = 0.181), suggesting that these constructs are 
particularly well explained by the model. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 



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Table 6. Specific Indirect Effects (Mediation Analysis). 

Indirect Path Path 
Coefficient 

Standard 
Error 

t-
value 

p-
value 

95% CI 
Lower 

95% CI 
Upper 

Mediation 
Type 

DCN → Bonding SC → 
Econ Resources 

0.129** 0.023 5.609 0.000 0.084 0.174 Partial 

DCN → Bonding SC → 
Econ Agency 

0.101** 0.024 4.208 0.000 0.054 0.148 Partial 

DCN → Bonding SC → 
Econ Achievement 

0.115** 0.022 5.227 0.000 0.072 0.158 Partial 

DCN → Bridging SC → 
Econ Resources 

0.145** 0.028 5.179 0.000 0.090 0.200 Partial 

DCN → Bridging SC → 
Econ Agency 

0.189** 0.027 7.000 0.000 0.136 0.242 Partial 

DCN → Bridging SC → 
Econ Achievement 

0.164** 0.028 5.857 0.000 0.109 0.219 Partial 

DCN → Linking SC → Econ 
Resources 

0.109** 0.027 4.037 0.000 0.056 0.162 Partial 

DCN → Linking SC → Econ 
Agency 

0.125** 0.026 4.808 0.000 0.074 0.176 Partial 

DCN → Linking SC → Econ 
Achievement 

0.098** 0.026 3.769 0.000 0.047 0.149 Partial 

Note: DCN = Digital Communication Networks; SC = Social Capital; Econ = Economic; ** p < 0.001. 

 
The mediation analysis revealed significant indirect effects for all hypothesised pathways, confirming that 

social capital dimensions partially mediate the relationship between digital communication networks and women's 
economic empowerment. The strongest indirect effects were observed through bridging social capital, particularly 

for economic agency (β = 0.189, p < 0.001) and achievement (β = 0.164, p < 0.001). All indirect effects 
demonstrated 95% confidence intervals that excluded zero, providing strong evidence for mediation relationships. 
 

Table 7. Moderation Analysis Results - Urban vs Rural Context. 

Path Urban Sample (n=423) Rural Sample (n=424) Difference p-value (PLS-MGA) 

DCN → Bonding SC 0.389** 0.476** 0.087 0.042* 

DCN → Bridging SC 0.523** 0.612** 0.089 0.031* 

DCN → Linking SC 0.456** 0.523** 0.067 0.089 

Bonding SC → Econ Resources 0.267** 0.329** 0.062 0.156 

Bridging SC → Econ Agency 0.312** 0.356** 0.044 0.298 

Linking SC → Econ Resources 0.198** 0.248** 0.050 0.234 
Note: DCN = Digital Communication Networks; SC = Social Capital; Econ = Economic; ** p < 0.001, * p < 0.05 
The multigroup analysis examining urban versus rural moderation effects revealed significantly stronger relationships between digital communication 
networks and both bonding and bridging social capital in rural contexts compared to urban contexts. These findings suggest that digital technologies may 
have particularly important implications for social capital formation in rural areas where traditional networking opportunities may be more constrained. 
 

Table 8. Fuzzy-Set Qualitative Comparative Analysis Results. 

Configuration Bonding SC Bridging SC Linking SC DCN Usage Consistency Coverage 

Path 1 ● ● ● ● 0.892 0.341 

Path 2 ● ● ⊗ ● 0.834 0.289 

Path 3 ⊗ ● ● ● 0.826 0.267 

Path 4 ● ⊗ ● ● 0.811 0.234 

Note: ● = presence of condition; ⊗ = absence of condition; SC = Social Capital; DCN = Digital Communication Networks. 

 

4.3. Supplementary Analyses 
The fsQCA analysis identified four distinct configurational pathways leading to high women's economic 

empowerment outcomes. The most consistent pathway (Configuration 1) involved the simultaneous presence of 
high levels across all three social capital dimensions combined with intensive digital communication network usage 
(consistency = 0.892, coverage = 0.341). This pathway accounted for approximately 34% of cases achieving high 
empowerment outcomes. 

Configuration 2 demonstrated that high empowerment outcomes could be achieved through strong bonding 
and bridging social capital combined with intensive digital network usage, even in the absence of strong linking 
social capital (consistency = 0.834, coverage = 0.289). This pathway was particularly prevalent among younger 
women and those in rural contexts where formal institutional connections may be more limited. 

Configuration 3 revealed an alternative pathway emphasising bridging and linking social capital whilst 
compensating for weaker bonding social capital through intensive digital network usage (consistency = 0.826, 
coverage = 0.267). This configuration was more common among urban women and those with higher education 
levels who may have broader social networks but less intensive family-based support systems. 

Configuration 4 demonstrated that strong bonding and linking social capital could compensate for weaker 
bridging capital when combined with intensive digital network usage (consistency = 0.811, coverage = 0.234). This 
pathway was particularly relevant for women in traditional business sectors where family networks and 
institutional relationships were more important than diverse social connections. 
 
 
 
 
 
 



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Table 9. Multigroup Analysis Results - Education Level 

Path Low Education 
(n=312) 

Medium Education 
(n=298) 

High Education 
(n=237) 

F-value p-value 

Bonding SC → Econ Resources 0.342** 0.289** 0.234** 3.876 0.021* 

Bridging SC → Econ Agency 0.278** 0.334** 0.389** 4.234 0.015* 

Linking SC → Econ Achievement 0.167* 0.201** 0.267** 3.234 0.040* 
Note: SC = Social Capital; Econ = Economic; ** p < 0.001, * p < 0.05; * p < 0.01 

 
The education-based multigroup analysis revealed interesting patterns in how social capital dimensions relate 

to different empowerment outcomes across educational attainment levels. For women with lower education levels, 

bonding social capital demonstrated the strongest relationship with economic resources (β = 0.342, p < 0.001), 
suggesting that family and close community networks are particularly important for accessing financial resources 
when formal educational credentials are limited. 

Conversely, for women with higher education levels, bridging social capital showed the strongest relationship 

with economic agency (β = 0.389, p < 0.001), and linking social capital demonstrated stronger relationships with 

economic achievement (β = 0.267, p < 0.001). These patterns suggest that educated women may be better 
positioned to leverage diverse social networks and formal institutional connections for economic advancement. 
 

5. Discussion of Research Results and Conclusions 
The findings from this comprehensive investigation provide compelling evidence for the mediating role of 

social capital in the relationship between digital communication networks and women's economic empowerment 
within the Vietnamese context. The results demonstrate that digital technologies do not directly transform 
women's economic circumstances but rather operate through complex social mechanisms that enhance women's 
capacity to accumulate, maintain, and leverage social capital for economic advancement. 

The most significant finding concerns the differential effects of digital communication networks on various 
dimensions of social capital. The strongest relationship observed was between digital communication usage and 
bridging social capital formation, suggesting that digital platforms are particularly effective at facilitating 
connections across diverse social groups that might otherwise remain segregated by geographical, cultural, or 
economic barriers. This finding aligns with network theory predictions about the capacity of digital technologies to 
reduce the transaction costs associated with maintaining weak ties across social boundaries (Granovetter, 1973; 
Burt, 2005). The particularly strong effect on bridging capital has important implications for women's economic 
empowerment, as access to diverse networks has been consistently identified as crucial for entrepreneurial success 
and business growth (Aldrich & Zimmer, 1986; Coleman, 1988). 

The significant positive relationship between digital communication networks and linking social capital 
represents another theoretically important finding. Traditional conceptualisations of linking capital emphasise face-
to-face interactions with institutional representatives and individuals in positions of authority (Woolcock, 2001). 
The finding that digital platforms can effectively facilitate these vertical connections suggests that digital 
technologies may democratise access to institutional resources and formal support systems that have traditionally 
been available primarily to individuals with existing social advantages. This finding is particularly relevant for 
women in patriarchal societies where traditional pathways to institutional access may be constrained by cultural 
norms and gender-based discrimination (Kabeer, 2001). 

The mediation analysis results provide crucial insights into the mechanisms through which digital technologies 
influence women's economic empowerment. The finding that all indirect effects through social capital dimensions 
were statistically significant whilst maintaining partial mediation suggests that social capital formation represents 
a primary but not exclusive pathway through which digital communication networks enhance economic outcomes. 
This finding supports theoretical frameworks that emphasise the multifaceted nature of technology impacts on 
economic development, recognising that digital technologies may influence empowerment through multiple 
simultaneous mechanisms (Sen, 1999; Duflo, 2012). 

The differential effects of social capital dimensions on various empowerment outcomes reveal important 
nuances in how social networks translate into economic benefits. The particularly strong relationship between 
bridging social capital and economic agency suggests that diverse social networks are especially important for 
enhancing women's capacity to make strategic choices about economic participation. This finding aligns with 
feminist economics literature emphasising the importance of expanding women's choice sets and decision-making 
autonomy as fundamental components of empowerment processes (Kabeer, 2001; Sen, 1999). 

Conversely, the stronger relationship between bonding social capital and economic resources suggests that 
close family and community networks remain crucial for accessing financial resources, particularly in contexts 
where formal financial institutions may be inaccessible or inappropriate for women's needs. This finding supports 
extensive literature on informal finance in emerging economies, which demonstrates that women entrepreneurs 
often rely heavily on family and community networks for business capital (Mayoux, 2001; Fletschner & Kenney, 
2014). 

The urban-rural moderation effects represent one of the most theoretically significant findings of this research. 
The stronger relationships between digital communication networks and social capital formation in rural contexts 
suggest that digital technologies may have particularly transformative effects in environments where traditional 
networking opportunities are more constrained by geographical isolation, limited transportation infrastructure, 
and cultural restrictions on women's mobility (Porter et al., 2016). This finding has important policy implications, 
suggesting that digital inclusion initiatives may be especially beneficial for rural women who face multiple barriers 
to social and economic participation. 

The fsQCA results provide additional insights into the complexity of empowerment processes by revealing 
multiple configurational pathways to high empowerment outcomes. The identification of four distinct pathways 
suggests that women can achieve economic empowerment through different combinations of social capital 
dimensions and digital network usage, supporting theoretical frameworks that emphasise the heterogeneity of 



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empowerment processes across different contexts and individual circumstances (Kabeer, 2001). The finding that 
high empowerment outcomes can be achieved even when some social capital dimensions are relatively weak 
suggests that digital technologies may provide compensatory mechanisms that enable women to overcome specific 
network deficits through alternative social capital configurations. 

The education-based multigroup analysis reveals important insights into how human capital interacts with 
social capital in determining empowerment outcomes. The finding that bonding social capital was most important 
for less educated women whilst bridging and linking capital became increasingly important for more educated 
women suggests that educational attainment may alter the mechanisms through which social networks translate 
into economic benefits. This finding supports human capital theory predictions that education enhances individuals' 
capacity to leverage diverse social networks and formal institutional resources (Becker, 1964; Schultz, 1961). 

These findings contribute to several key theoretical and empirical debates within the development economics 
and social capital literature. Firstly, the results provide strong empirical support for theoretical arguments that 
digital technologies can enhance social capital formation rather than undermining social cohesion, as suggested by 
some critics of digital communication technologies (Putnam, 2000; Turkle, 2011). The positive relationships 
observed between digital network usage and all social capital dimensions suggest that digital platforms can 
complement rather than substitute for offline social interactions when properly integrated into existing social 
systems. 

Secondly, the findings contribute to ongoing debates about the relationship between technology adoption and 
gender empowerment by demonstrating that digital technologies do not automatically empower women but rather 
create opportunities for empowerment through specific social mechanisms. The mediation results suggest that 
simply providing access to digital technologies is insufficient for achieving empowerment outcomes; rather, 
successful interventions must focus on enhancing women's capacity to leverage digital platforms for social capital 
development and utilisation. 

Thirdly, the research contributes to social capital literature by providing empirical evidence for theoretical 
arguments about the multidimensional nature of social capital and its differential effects on various economic 
outcomes. The finding that bonding, bridging, and linking capital have distinct relationships with empowerment 
components supports theoretical frameworks that emphasise the importance of examining social capital as a 
multidimensional rather than unidimensional construct (Woolcock, 2001; Szreter & Woolcock, 2004). 

The practical implications of these findings for development policy and programme design are substantial. The 
results suggest that digital inclusion initiatives should focus not merely on providing technological access but on 
supporting women's capacity to leverage digital platforms for social network development and maintenance. 
Programmes that combine digital literacy training with social network development activities may be particularly 
effective for enhancing women's economic empowerment outcomes. 

The finding that different social capital dimensions have varying importance across educational levels suggests 
that empowerment interventions should be tailored to women's specific circumstances and capabilities. For women 
with limited formal education, programmes focusing on strengthening family and community networks whilst 
providing access to digital communication tools may be most effective. For more educated women, interventions 
that facilitate connections across diverse social groups and formal institutional networks may yield greater 
empowerment benefits. 

Several limitations of this research should be acknowledged. The cross-sectional design precludes causal 
inferences about the direction of relationships between constructs, and longitudinal research would be valuable for 
confirming the causal mechanisms suggested by the theoretical model. Additionally, the study's focus on Vietnam 
limits the generalisability of findings to other cultural and economic contexts, although the theoretical framework 
developed may be applicable across emerging economies with appropriate contextual adaptations. 

Future research should examine the temporal dynamics of digital social capital formation and its effects on 
empowerment outcomes through longitudinal designs. Additionally, comparative research across multiple 
emerging economy contexts would enhance understanding of how cultural and institutional factors influence the 
relationships examined in this study. Qualitative research examining women's subjective experiences of digital 
network participation and empowerment processes would provide valuable insights into the mechanisms 
underlying the quantitative relationships identified. 

In conclusion, this research demonstrates that digital communication networks can significantly enhance 
women's economic empowerment through the mediating mechanism of social capital formation. The findings 
suggest that digital technologies create new pathways for women to access the social resources necessary for 
economic advancement whilst potentially compensating for traditional barriers to network development. However, 
the benefits of digital inclusion are not automatic but depend on women's capacity to effectively leverage digital 
platforms for social capital accumulation and utilisation. These insights provide important guidance for policy 
interventions designed to harness digital technologies for inclusive economic development and gender 
empowerment in emerging economy contexts. 
 

Acknowledgments: 
I would like to express my sincere gratitude to Dr. Hoang Vu Hiep for his invaluable guidance and inspiration 
throughout this research. His expertise, insights, and unwavering support have been instrumental in shaping the 
direction and quality of this study. I am deeply appreciative of his generosity in sharing his time, knowledge, and 
network, which have greatly contributed to the success of this research. His mentorship and commitment to 
academic excellence have not only enriched the quality of this work but have also had a profound impact on my 
personal and professional growth. 
 

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