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Understanding the economic challenges and impact of digital

exclusion on female migrant workers during COVID-19 pandemic:

Kuanwala Case Study

Minor Project Report

Submitted by

Saloni Rawat

For the partial fulfilment of the

Degree of Master of Arts in

SUSTAINABLE DEVELOPMENT PRACTICE

Department of Policy Studies

TERI School of Advanced

Studies

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About the Organization and the Internship

Social and Development Research & Action Group (SADRAG)

SADRAG is a not-for-profit organization having been in existence since 2004. It is currently

working in the geographical areas of North: Delhi, Noida, Greater Noida, Dadri and rural

communities of Western U.P. and in the South: Bangalore. With a firm belief in equality of

life for all, SADRAG envisions a world of dignity and self-respect especially for women

and children.

Observing the subservient social roles that bind women and hamper their growth, SADRAG

envisages a world that has no scope for gender discrimination, where men and women have

equal access to opportunities and availability of resources for growth and can participate

equally in social and community life. The children should have a free and healthy life that

goes with the community and family for mutual growth and development.

My internship entailed research-based work in a marginalized community in Dehradun.

During the internship with Social and Development Research & Action Group (SADRAG),

under the guidance of Dr. Mala Bhandari, I had the opportunity to explore and understand

the issues related to digital and economic inclusion of women through a review of literature as

well as witness the challenges and experiences of women in Kuanwala, Dehradun through

field investigation.

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Acknowledgement

I am extremely grateful for interning with the Social and Development Research & Action Group

(SADRAG) that provided me with a great opportunity to learn and sharpen my research skills.

I would like to present my sincere gratitude to Dr. Mala Bhandari for guiding me through the

Internship, sharing her valuable insights, and encouraging me to pursue research on a topic of my

interest. I also thank my supervisor, Dr. Chandan Kumar, for supporting us during the internship.

Finally, I am extremely thankful to the women of Kuanwala who hosted and helped me with the

interviews, and trusted me with their experiences and stories.

Thank you,

Saloni Rawat

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1. Introduction

Digital transformation – the consequences of digitization on economy and society – is opening up

new opportunities around the world, promising increased productivity development and higher

well-being for all populations (Pollitzer, 2018). Mobile phones, digital platforms, the internet, and

fintech solutions offer “leapfrog” opportunities that can help in reducing the gender digital divide

by providing women enhanced economic opportunities, more possibilities to earn, and access to

information, knowledge, and skills (OECD, 2018). However, there is still a large gender disparity

in digital technology access, usage, and ownership, which limits the equitable realization of the

advantages of digital transformation (GSMA, 2020; OECD, 2018). Digital technology is critical

for democratic participation, access to job prospects, health, economic security, government

benefits/schemes, and public services, social capital, and connections, and even preventing gender-

based violence, hence, bridging the gender digital divide also allows women to better cope with a

crisis (UNDP, IMF, and UN Women, 2021). ICTs like the Internet and broadband hold the

potential to better contribute to protection of women’s rights as well as their upliftment through

social, political and economic dimensions, that benefits not only women but also their communities

and the society (The UN Broadband Commission for Sustainable Development, 2017).

Unfortunately, the COVID-19 pandemic has exposed the vulnerabilities of the informal service

sector and sectors dominated by women (UN Women, 2020) that already faced the overlapping

issues of “capital, care, caste, gender, and climate” (ActionAid Association, 2020). ILO (2020)

report estimates that women in low-income and low- and middle-income countries are more

exposed to economic shocks as they work in informal sectors with no social security, no contracts,

poor wages leading to almost no savings and investments (Unni, 2020). This primarily includes

migrant workers who predominantly work informally in construction activities, small industries,

domestic work, and the hotel-restaurant industry (Aajeevika Bureau, 2020). Hence, the research

aims to understand the scope and challenges of utilizing digital technology as a means to improving

women’s workforce participation rate as well as their upward mobility in the society.

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2. Literature Review

The expansion of the service sector as a result of digitization gives opportunities for women in the

informal sector to earn a living through digital technology (UN Women et al., 2020). However,

technology alone cannot help with socio-economic development unless it takes into account the

realities of the people who will be using it (Pollitzer, 2018).

2.1 Low women’s workforce participation rate: What is the reason?

Prior to the COVID-19 pandemic, India had one of the lowest and continuously falling women's

Workforce Participation Rate (WPR), as well as a high rate of precarious informal work for which

women's inadequate skills have been highlighted as a barrier to their potential to obtain more and

better work (Mehrotra and Sinha 2019). Besides, cultural impediments on women working outside

the home, safe access to the workplace, and decreasing labor supply due to upward mobility of

poor households are also significant factors (Dewan 2019; Mehrotra and Parida 2017; Rukmini

2019). A common explanation that has also emerged in this regard is that young women and girls

with greater educational performance look for equivalent jobs, and the lack of which discourages

them from engaging in low-paying and low-value-added jobs (Desai, 2019; Mitra and Sinha,

2021).

However, an important factor that is often overlooked is that of the cost of unpaid care work for

women. This is evident in the fact that labor participation rates among newly married women,

particularly those with small children, are lower. While women have accepted their position as

primary caregivers at home, evidence from various reports suggests that if suitable opportunities

exist, more women desire to work outside their homes. According to an ILO and Gallup report

(2017), about 30% of women in India, that are engaged in household responsibilities for most of

their time, would prefer to work outside. NSSO 2014 survey data further reveals that around 60%

women above 15 years of age are engaged in domestic duties because “no other member will”.

The findings from the National Sample Survey data clearly reveal that the majority of women who

are not in the labor market are occupied with domestic responsibilities (Chandrasekhar and Ghosh

2020). In rural and urban areas, respectively, the share of women involved in care work and

domestic and allied activity was 57.4 percent and 60 percent, respectively, compared to just 0.5

percent and 0.6 percent for men in 2018–19 (Chakraborty, 2020). OECD (2021) data also shows

that around the world women spend considerably more time on unpaid care labor than males.

According to the time use survey conducted in India by NSSO, MoSPI and GOI (2019), men spend

222 minutes more on “paid and productive work” than women, but women spend 300 minutes

more on unpaid labor (household chores and caregiving) than men. It is therefore clear that while

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fulfilling family's unpaid and care demands, women face enormous opportunity costs. This task

and the time spent on it is often not recognized, leading to undervaluing and "invisibilisation" of

women's work (Mitra and Sinha, 2021).

Even after removing the care burden and household work, women were 7 times more likely to lose

their jobs during the pandemic and 11 times less likely to recover from job loss, which could be

likened to inequitable "employment arrangements" and "gender-based occupational segregation"

(Abraham et al 2020). A survey conducted by APU (2020) reveals that during the lockdown in

India, a greater number of women reported employment losses than men. It is anticipated that by

August 2020, 55 percent of temporary salaried female workers and 46 percent of self-employed

female workers had left the workforce (Abraham et al 2020).

Another challenge is the rise in informalization- the increasingly lacking implementation of labor

regulations, the rise in temporary jobs, the lack of contracts, the large-scale transition towards self-

employment, and the ambiguous definition of “work” and “worker”- they are all impeding the

realization of labor rights (Dewan, 2019). PLFS 2018-19 and NSSO 2020 data show that more

than 70% of urban female workers and over 60% of rural female workers in regular employment

had no formal job contracts (Mitra and Sinha, 2021).

2.2 Sector-wise challenges and relief measures

The central government announced an increase in daily wage rates for MGNREGA workers from

Rs. 182 to Rs. 202 during the pandemic, however, work was suspended in most places during the

lockdown, leaving only a few people to benefit from the wage increase (Naidu, 2020). This scheme

has the potential to have a big impact on the economy. However, even before the pandemic,

corruption, inadequate implementation, and underfunding limited its ability to generate jobs. In

2020–21, the annual budget allocated for MGNREGA fell by another 9,500 crores, a 13 percent

decrease, compared to 2019–20 (Shroff, 2020).

Cash transfers under the COVID-19 stimulus packages amount to around 9% of total of monthly

GDP per capita, which is significantly less than the average allocation of 26% by 115 countries,

according to a World Bank Report (Gentilini et al 2020). These cash transfers reached just about

15% of the population (Gentilini et al 2020), indicating that they do not reach a large number of

working individuals who face precarious livelihoods and lives.

Furthermore, for three months, the public distribution system (PDS) allotment for all households

under Antyodaya Anna Yojana was boosted by 1 kg pulses along with 5 kg wheat or rice per

individual, which is barely enough to compensate the losses family's incurred due to pandemic

(Naidu, 2020). For the migrants who were left out from the National Food Security Act or did not

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have a ration card, two months of free food grains were also announced, however the

implementation was not carried out appropriately (Naidu, 2020).

Construction Workers: Some relief measures were announced by the Centre according to which

18 states transferred Rs 1,000–5,000 from specified cess money under the BoCW Act to bank

accounts of registered construction workers affected by the COVID-19 outbreak. States paid a total

of Rs 2,250 crore in the form of one-time cash benefits to nearly 18 million construction employees

who were in financial hardship. In Uttarakhand, around Rs. 2000 were transferred per worker.

However, Unni (2020) notes that based on the PLFS (2017-18) estimates, there are over 26 million

construction workers that are not registered in the BoCW Act and hence will be left out from the

Direct Bank Transfer Scheme.

Street Vendors: Around 20 crore Jan Dhan women account holders would be compensated with

Rs 500 per month for three months (Unni, 2020). The benefits of loans, according to Arbind Singh,

national coordinator of the National Alliance of Street Vendors of India (NASVI), are unlikely to

bring help and solutions like direct cash transfer are urgently needed. The National Hawker

Federation's Ghosh suggested looking for interest-free loans and MUDRA loans with subsidies

(Sen 2020).

Domestic Workers: Domestic workers were more susceptible since they depended on their

employers due to a lack of social security coverage and access to credit. Other issues experienced

by domestic workers and other informal employees were a lack of rations, with only a few workers

receiving free rations and direct government benefit transfers.

Manufacturing Sector: In 2018–19, about 14% of women worked in the manufacturing industry,

and the pandemic has hit the industry hard. The industry is labor-intensive, and it frequently

employs low-paid and low-skilled women. Since there has been a reduction in effective demand,

especially for non-essential commodities, workers employed in the sector are at risk of being laid

off.

Self-employed: The majority of women in self-employment operate as unpaid helpers in family

businesses or run their own businesses without external help, and only a few have managerial roles.

Self-employment largely falls into the category of unpaid labor on family farms and businesses,

exposing its gendered nature (Mitra and Sinha, 2021).

2.3 What can digital technology do?

New industries such as overseas production as well as traditional sectors like agriculture,

manufacturing, and health, are all being transformed by digital technology. ICT is also critical for

economic and productivity growth. In LMICs, while social media and messaging remain popular,

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more people have been realizing and accessing the benefits of services like educational and health-

related information, and employment opportunities. Thus, consumption is becoming more diverse

and productive (GSMA, 2020).

Several studies suggest that the digital transformation can also solve the inadequacies in the

unorganized sector, formalize labor relations, and expand job and income-generation prospects for

women (Global Compact Network India & Deloitte, 2019). The development of the service

industry as a result of digitization gives opportunities for women in the informal sector to earn a

living by making use of digital assets. Various women's issues have also been addressed via digital

platforms since they give them more time and mobility, make it easier for them to access open

marketplaces, provide information symmetry, and connect them to specialty markets (UN Women

et al., 2020).

Mobile Banking or “shadow banking” is also a great tool to enhance financial inclusion of women.

It is a form of banking service that is convenient, cost-effective, and occurs through digital

channels outside of the formal banking system and hence offers financial services to the

“unbanked” population as well (OECD, 2018). As a result, it is crucial to utilize efficient,

sustainable, and high-quality digital financial services to improve the financial inclusion of women

while making sure that consumers are protected from false or malicious practices, and the financial

sector remains stable (OECD, 2018). Mobile money has proven to alleviate long-run poverty and

alter women's financial behavior. Women have also discovered that mobile money is a component

that makes it easier for them to establish a business. It has the potential to further impact migration

and economic prospects, as well as diminish women's reliance on several part-time jobs (Suri and

Jack, 2016).

Agriculture, healthcare, education, financial services, energy, logistics, and retail, along with

public services and labor markets, are among the newly digitalizing sectors that could generate

$10 billion to $150 billion in new economic value by 2025, as digital tools in these sectors help

improve output, save time and costs, reduce fraud, and improve demand-supply linking (McKinsey

Global Institute, 2019). Hence, by 2025, McKinsey Global Institute (2019) estimates that the

digital economy's productivity might release 60- 65 million jobs, many of which will require

relevant digital skills.

2.4 Challenges in accessing digital technology

While satellite technology, among other things, has eased the widespread use of mobile phones

and (nearly) global coverage, women continue to be disproportionately disadvantaged due to their

lower ownership and the use of mobile phones and smartphones (GSMA, 2018). According to data

from NSS-MoSPI (2017-18), only 38% of women own mobile phones, and 12.8% use computers,

while usage for men stands at 71% and 20% respectively. Furthermore, only 8.5% of the female

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population in rural India can use the internet as compared to 17.1% of the male population.

Interestingly, even when they have access, the digital gender disparity persists in usage as women

are 18% less likely than males to utilize mobile Internet. In India, there is a 10% gender disparity

in the use of mobile internet (GSMA, 2018).

Affordability is a major problem for everyone, but it impacts women and girls more

disproportionately, and it is still one of the most significant barriers to ICT (Information

Communication Technologies) adoption. Furthermore, when technology sophistication and cost

of ownership increase, the digital gender disparity is seen to widen (OECD, 2018). According to

Intel and Dalberg (2012), 25% of women that don't use the Internet are typically uninterested in

doing so, and most of them feel that internet usage is of no advantage to them (OECD, 2018).

While women largely cited disinterest and low expectations about its usefulness as reasons, lack

of faith in digital technology or the Internet might also play a significant role.

The most significant barrier to smartphone ownership and usage in India is a lack of reading and

writing skills, according to the Mobile Gender Gap Report Survey in 2019. The survey also

reported that India has the largest gender gap among all the Asian nations surveyed under the

report. Reading and literacy skills are a precondition while accessing digital tools. Web search

skills include not only reading and typing skills but also the ability to search, comprehend,

interpret, organize, and filter the content. Greater cognitive strategies, visual-spatial abilities,

problem-solving skills, self-organization, or interpersonal skills are required to keep up with the

changing requirements of the digital world that might lead to gender gaps in schools and the labor

market (Lee, 2007; Spiro et al., 2015; OECD, 2018). Thus, illiteracy makes it even more difficult

for women and girls to use online services (Social and Political Research Foundation, 2020).

Illiterate women appear to exclusively use digital services that are more known to them or are

easier to use, such as Skype and YouTube. Search engines like Google have added voice

navigation systems in local languages to improve inclusivity and accessibility in Web search

queries, in an attempt to overcome this barrier (OECD, 2018).

Other factors such as education, employment situation, and economic level simultaneously

contribute to such "technophobia." Even after receiving formal education, girls appear to lack

confidence in ICTs, which is often caused or exacerbated by societal and parental biases, as well

as parent's expectations. This results in self-censorship by young girls and lower participation in

ICTs (Global Compact Network India & Deloitte, 2019).

Female Internet users are currently using fewer services than male users and are less confident in

their use of the Internet. Although mobile money accounts are an efficient tool to increase financial

inclusion, women are less likely to own and utilize them. Especially women may receive help from

online or video-based upskilling and courses that help them make effective use of digital

technologies and obtain more benefits from them (OECD, 2018).

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Given the inequitable access to and use of skills, skill development efforts that are more gender-

responsive can potentially be agents of change for boosting societal mobility from education to the

labor market, unpaid to paid work, and lower-end jobs to higher-end jobs. However, training

programs alone are not enough. There must be a linkage between training programs and industry

requirements, especially as a greater number of girls are completing secondary level of education,

particularly in rural areas. These girls need to have access to skills training closer to their homes

(Sinha, 2019).

In developing and emerging economies, safety concerns are frequently recognized as a key factor

for families' objection to women and girls using the Internet or owning a mobile phone. Women

and girls who use the Internet face more hazards such as cyberstalking, online harassment, etc.

thus developing methods to safeguard and prevent online gender-based violence is critical (UN

Broadband Commission for Sustainable Development, 2017).

2.5 Current Initiatives and Gaps

Digital technologies are being used by India's current social policies to separate social and

economic rights from their deeply gendered roots. There are gendered implications of privatization

of social security. In 2020, the state provided a Rs 5,000 crore stimulus package for roughly 50

lakh vendors, recognizing the devastating impact of livelihood loss during the first wave of

COVID-19 (Majithia 2020). However, due to a male prejudice at the operational level, the Rs

10000 offer for all vendors as an initial working capital has not helped women vendors (Unni

2020). The Pradhan Mantri Jan Dhan Yojana program is also aimed at increasing women's

financial inclusion at a national level, including promotion of digital wallets or online banking

based on mobile transactions with the help of telecom operators and the establishment of Cash Out

Point facilities (PMJDY, 2018). However, literature suggests that assuming monetary transfers

and women's empowerment are inextricably linked can be deceptive. Cash transfers, in many

cases, may perpetuate traditional gender norms while ignoring gender inequalities within the

household (Gurumurthy, Chami and Thomas, 2016). Dewan (2019) argues that there is a need to

integrate gender in the framework of government policies at the inception stage itself as

government programs often retrogress due to a gender-neutral outlook.

Gender resource centers are being integrated through the National Rural Livelihood Mission

(NRLM) in order to empower women and promote women leaders and entrepreneurs. Some of the

main interventions have been as follows; designing skill development programs (DDU-GKY

PMKY), which seeks to improve women's ability to use technology, improving accessibility to

digital platforms and encouraging partnerships with start-ups dedicated to helping women with

financial technology solutions, and facilitating credit facilities through low-value MUDRA loans

(OECD,2018; UN Women et al., 2020; Patel, 2021).

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All of these programs are largely aimed at turning women into entrepreneurs in order to increase

women's engagement in the workforce. While these policies have been extensively promoted, the

government's official data shows that they have had little impact on the country's Female Labour

Force Participation Rate (Mitra and Sinha, 2021). The designs are highly gender-neutral and do

not have strategic initiatives that focus on providing women with the skills essential for actively

participating in the digital economy (Gurumurthy, Chami and Thomas, 2016). The National Digital

Literacy Mission (NDLM) scheme, aimed at making one individual digitally literate in eligible

households, also pays insufficient attention to the issue of skill development of women and other

underrepresented groups.

3. Research Question

Women in low-skilled jobs may face more alterations in their work than males as the digital

transformation continues to expand and penetrate all industries. This could be due to the possibility

of machines replacing (parts of) human jobs, resulting in the necessity to perform diverse duties

on the job, as women undertake more routine chores than males (OECD, 2018). Especially due to

COVID-19, women’s WPR has declined further, causing severe socio-economic impacts on

women. In such a scenario, where utilizing digital technology becomes inevitable not only while

working but also to overcome the crisis caused due to pandemic, what are the challenges that

women are facing while accessing digital technology and benefitting from it, and what can be done

to improve their digital skills?

4. Research Objectives

1) To determine whether women have the skills necessary to navigate the workplace in a

digital economy or not

2) To understand impact of digital intervention on improved economic opportunities and

social empowerment of female migrant workers

3) To discuss the scope and challenges of utilizing digital platforms to increase women's labor

force participation

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5. Methodology

The study aims to understand the livid experiences for which the most appropriate design is

qualitative research. It is empirical and thus, helps to make sense of the gathered data by testing it

against ideas, theories and hypotheses by explaining it either through the participant’s point of

view, the etic approach, or through the researcher’s perspective, the emic approach. This helps to

produce research that is guided by theory while expressing the subject’s perspectives to best

understand the social realities and problems. (Smith, 1987)

Further, the research method used is descriptive and aims to elucidate and interpret the findings of

the current state. It helps to best describe the accounts, phenomenon, conditions, practices, and

challenges to communicate the participants’ experiences (Creswell, 2007).

The sample population will consist of female migrant workers from Kuanwala, Dehradun. Within

Kuanwala, the localities of Kuanwala I (IMCL Factory area), Kuanwala II (Choona-Bhatta Factory

area) and Nirmal Basti have been chosen. A sample size of 50 individuals will be selected for this

purpose. The population will be selected through purposeful sampling based on the researcher’s

judgment to get in-depth and unique experiences (Taherdoost, 2016).

Rationale: Kuanwala is an industrial area located in the outskirts of Dehradun city, that formally

came under Nagar Nigam in 2019. It has a total population of 1,779 with 15.85% population of

Scheduled Castes (SC). Most of the families have migrated here from villages in Uttar Pradesh

and Bihar; and predominantly work in factories like IMCL (Indian Made Commercial Liquor)

Factory, Choona-Bhatta Factory, Textile Industry, Industry showrooms, or at brick kilns and

construction sites. Being an industrial area, the residents have been directly facing the adverse

effects of pollution in the form of contaminated air with a foul smell, a phenomenon that has

previously given rise to the ‘Environmental Justice’ movement that argues how minority

populations have had been suffering disproportionately due to pollution suggesting that social

inequities are linked to environmental issues (Banzhaf et al., 2019).

Additionally, some of the families live within the factory housing in a single room, often times

with no washroom facility, and share a community tap water. They also do not have a healthcare

facility in the vicinity. Such living conditions are especially difficult considering the COVID-19

pandemic situation wherein the residents cannot maintain appropriate physical distancing norms

since they are living in close proximity, and have to travel long distances for health-related

services. For women, these problems increase tenfold as they have to bear the burden of care work,

lack of privacy at home, unsafe work environment, and hygiene and health issues among other

things. Furthermore, Anand and Thampi (2020) estimate that Scheduled Castes (SCs) earn roughly

55% less than the other caste categories (excluding Scheduled Tribes (STs), and Other Backward

Classes (OBCs)), with the disparity being greater in urban areas than rural areas. According to

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Oxfam (2020) research, women workers in India are paid less regardless of their employment

status (casual vs. regular/salaried), sector (organized vs. unorganized), or location (urban vs. rural).

Occupational segregation, along with explicit and implicit biases, contributes to income disparities

across caste and gender boundaries (Kapil, 2019). These income disparities then force families to

marry their daughters at a younger age as they consider them a burden. Consequently, women get

stuck in a vicious cycle of illiteracy, low skills, low wages, and low employment rates.

To understand impact of digital interventions on improved economic opportunities and social

empowerment of female migrant workers, and to determine whether women have the skills

necessary to navigate the workplace in a digital economy or not, focus was put on secondary

sources in the form of research papers, journals, articles, and news reports along with insights from

the primary data collection through interviews of the sample population. For the last objective, to

discuss the scope and challenges of utilizing digital platforms to increase women's labor force

participation in Kuanwala, primary data collection through structured interviews of the proposed

population was referred.

6. Primary Research

6.1 Demographic Details

Age:

Figure 1: Age

Around 48% women of the respondents belong

to the 30-35 years age group, while 18% belong

to 25-30 years, 16% to 20-25 years and 14% to

35-40 years age brackets.

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Literacy Level:

Literacy and education levels are basic indices

of development. Literacy is a crucial component of an

individual's development since it allows them to better

understand their social, economic, political and

cultural surroundings. The literacy levels adapted

from Census data for the purposes of this research

study are as follows: Illiterate, Below Primary,

Primary, Middle, Secondary, High Secondary,

Graduate and above.

40% of the respondents are ‘Illiterate’, while 10% have ‘Below Primary’, 14% have ‘Primary’,

12% have ‘Middle’, 14% have ‘Secondary’, 6% have ‘High Secondary’, and 4% have ‘Graduate

and above’ levels of education.

Caste:

76% of the respondents belong to Scheduled Castes

and 10% to Other Backward Castes category.

Migrant:

The migrant population has been chosen on the

basis of “last place of residence”. 42% of the

respondents have been living in Kuanwala for

“more than 15 years”, 30% have been living for

“10-15 years”, 22% have been living for “5-10

years” and 6% have been living for “less than 5

years”

Figure 2: Literacy level

Figure 3: Caste

Figure 4: Migrant Status

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Housing:

Figure 5: Housing

The housing situation and assets available in

the household reflect the people's living

conditions. Depending on the nature of the

material used in walls and roof, ownership

status houses have been classified as: Kuccha,

Semi-pukka, Rented Room/house, Community

housing, Own house.

38% of the respondents lives in ‘Rented room/house’, while 26% live in their ‘own house’, 22%

live in ‘semi-pakka house’, 12% live in ‘Community housing’, and the remaining 2% live in

‘Kuccha house’.

Amenities and assets:

Figure 6: No. of Bathrooms Figure 7: Private Access to water

The quality of life of people also depends on the amenities and assets available to them. For this

purpose, questions related to number of rooms, bathroom and latrine facility, electricity, private

water connection, assets like refrigerator, TV, mobile, bicycle, motorbike etc. have been asked.

10% of the respondents have ‘No bathroom’ while 4% of them have ‘2 bathrooms’, 2% have access

to ‘Community bathroom’ and other 2% have more than ‘3 bathrooms’. Around 72% have a private

access to water connection while the remaining 28% use community tap.

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Social Security:

Figure 8: Social Security

All the respondents responded “none” when asked about social security in the form of PF, Health,

Maternity Benefits, Pension etc. None of the respondents had a Jan Dhan Account which means

that they lost out on Direct Benefit Transfer relief schemes. 22% respondents also did not have a

ration card and hence did not receive PDS benefits.

Time Use:

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Time Use data expresses how people utilize their time on different activities throughout the day.

It is divided into paid work, unpaid work, care work, personal care, leisure, and unspecified time

(OECD, 2021). For this research study, unpaid work and care work have been put in the same

category- “unpaid work”; and personal care and leisure have also been added in the same category-

“personal care”. Unpaid Work includes taking care of domestic animals, looking after the family,

cooking food, cleaning, collecting water. The time-use data presented is the best approximate data

based on the interviewee’s responses.

Evidently, women are spending more no. of hours on paid work and unpaid work than skill

enhancement or learning and personal care.

Of those involved in paid work, around 38% are working for “8-12 hours” and 8% are even

working for “more than 12 hours”. This is one of the drawbacks of informal or unorganized sector.

In case of unpaid work, that also includes care work, 28% spend “4-8 hours”, 52% spend “8-12

hours”, and 6% spend “more than 12 hours”.

98% respondents spend around “1-4 hours” on personal care and leisure.

Consequently, 76% women do not spend any time on skill enhancement or learning, with only

14% spending “0-1 hours”, 6% spending “1-2 hours”, and 2% spending “2-4 hours” and “more

than 4 hours” each.

6.2 Employment Details

Economic Activity:

The economic activities have been divided under the following major sectors: “Agriculture”,

“Manufacturing and Allied Industries”, “Construction” and “Service”.

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36.1% of the respondents are involved in ‘Manufacturing and allied industries’ for their source of

employment while 27.8% of respondents are involved in ‘Construction’, 19.4% is involved are

‘Service’ and 16.7% are involved in ‘Agriculture’.

In case of their partners, around 58.7% are involved in ‘Construction’ while 26.1% in ‘Service’,

8.7% in ‘Agriculture’ and the remaining are involved in ‘Manufacturing and allied industries’.

Employment Status:

Regarding the employment status of the respondents’ and their partners’, more women have clearly

left the workforce. If we examine the situations of “pre-COVID-19 (January-March 2020)” and

“after COVID-19 first wave (September 2020- February 2021)”, number of women who were

unemployed and left the workforce increased 26% to 52%. As estimated by several reports, there

was a surge in unemployment rate “during COVID-19 first wave (April-May 2020)” and around

92% women left the workforce. There is no change between “after COVID-19 first wave

(September 2020- February 2021)” and “during COVID-19 second wave (April-June 2021)” for

women, indicating that number of women that had re-entered the workforce continued to work

even during COVID-19 second wave.

For the partners of the respondents, all of them were working “pre-COVID-19 (January-March

2020)”, and 91% of them lost their jobs “during COVID-19 first wave (April-May 2020)”. 87%

of them reentered the workforce “after COVID-19 first wave (September 2020- February 2021)”,

and 15% were still unemployed. Out of 87%, 61% continued to work even “during COVID-19

second wave (April-June 2021)”. The unemployment rate is evidently higher for women than men

throughout the pandemic.

19

Method of Salary Payment:

Figure 9

28% of the respondents receive ‘Regularly Monthly

Salary’, while 54% of them receive ‘Piece Rate

Payment’, 10% receive ‘Regular Weekly Payment’,

and the remaining 4% receive ‘Daily payment’.

Contract-Based Work:

51% of the respondents are employed through or work with a contactor while the remaining 49%

are not, and a 100% of the respondents do not have any written contract.

This informalization results in their labor right not being acknowledged. This further creates higher

chances of exploitation, poor workplace conditions and no fixed salary or wages.

Wages during and before the lockdown:

20

Of the 22.2% respondents who did not receive their wages for the work they did before lockdown,

19.4% were “unsure of receiving it” while 2.8% were “sure of receiving it”. Remaining 77.8%

received the wages for the work they did before the lockdown.

Further, 82.9% of the respondents did not receive salary for the duration of the lockdown from

their employer, while 17.1% did. Those who did receive were either employed in public

institutions or as domestic helpers.

Skills:

The respondents have a variety of skills. Majority of them, around 35.4%, have ‘Stitching/

Tailoring’ skills, 16.7% have ‘Craft’ related skills, 11.5% are good in ‘Cooking’, 8.3% of the

respondents know ‘Achar Making’, 8.3% also know ‘Toy Making’. 5.2% of them have

‘Grooming’ skills, other 5.2 % have ‘Embroider/ Crochet’ skills, and 4.2% have ‘Knitting’ skills.

2.1% of them know ‘Candle Making’ while 1% of them is good in ‘Driving’, 1% has ‘Athletic’

skills, and another 1% has ‘Computer skills’. Such skillsets open up opportunities for

entrepreneurial ventures that can be utilized more efficiently with the help of digital tools.

21

6.3 Digital Literacy

Personal Phone:

34% of the respondents have their personal phone while 66% do not have their own phone. Out of

all the respondents who have their own phone, 81.6% has a smartphone while 18.4% did not.

Additionally, 84.8% of the respondents' partners have a personal phone while the remaining 15.2%

do not.

Shared Phone:

4% of the respondents share it with their husbands,

while 25% share it with both their children and husband,

and 46% of them share it with their children. Most of the

respondents who are sharing their phones, do not even

have joint ownership. In case of most of the respondents

who are sharing their mobile phone with their children,

the children claim ownership especially due to the shift

towards online education and them being more digitally

literate than their mothers.

Usage:

Figure 11

Figure 10

22

Respondents were asked to rank the following services from 1-5 in terms of how much they use

it: Entertainment, Communication, Learning, Financial Transaction, and Employment.

All the respondents use the communication service through phone calls the most, while 42%

women use entertainment services the most. Learning, Financial Transaction and Employment

were ranked low as most women did not use these features. Interestingly, women with low literacy

levels, still preferred to watch “skill-enhancement videos” that they can imitate and learn, over

“entertainment videos”.

Social Networking Platforms:

64% of the respondents use social networking apps

while 34% of them do not use social networking

apps and the remaining are not sure.

Respondents were asked about the following

platforms: Facebook, Instagram, YouTube,

WhatsApp, Telegram, Twitter, Email, Paytm/

Google Pay/ Phone Pay, Yes Madam, Uber/ Ola,

Google Maps, Just Dial, Mahila E-Haat and Swayam.

Most of them know about Facebook, YouTube, WhatsApp, Google and some of them even knew

about Paytm/ Google Pay/ PhonePay, Ola/Uber, Twitter and Google Maps. However, in terms of

usage, 48.7% used Facebook, 76.9% used YouTube, 74.4% used Google,12.8% used Paytm/

Google Pay/ PhonePay, and 2.6% used Google Maps.

None of the respondents knew about platforms like Just Dial, Yes Madam, Mahila E-Haat and

Swayam that provide income and skill-enhancement opportunities.

Abilities and Digital Skills:

Figure 13

Figure 12

23

Figure 14

Respondents were asked to rate their abilities to use smartphones, making and receive phone calls,

ability to use the Internet (Internet literacy), typing skills, web search skills, ability to use the

computer (computer literacy) from 1-5 (1=lowest, 5=highest).

Most of the respondents can make or receive calls successfully, but are not confident about or

equipped with the other skills. Only 28% of the respondents feel that they can successfully use a

smartphone. Around 40% do not have typing skills and 30% do not have web-search skills. Only

2% of respondents have computer skills. In terms of internet literacy, a mixed response was

received, as some respondents are able to surf the internet through voice features and reading skills,

while others are dependent on family members.

88% respondents can take digital photos, 62% can record digital videos, and 50% can record digital

sounds. In terms of higher digital skills of editing photos, videos and sounds, and downloading

applications, more than 70-78% of respondents were not confident.

Platforms for employment opportunities and skill-enhancement:

84% of the respondents do not know about the employment opportunities with the help of digital

tools while 12% of them are not completely sure and the remaining 4% know of some opportunities

under which they cited ‘YouTube’.

24

70% of the respondents do not know about the platforms that can help them in developing/

enhancing their skills while 30% of them who knew about such platforms cited ‘YouTube’ and

‘Google’ as learning platforms through which they search and are able to learn through Audio-

Visual content.

Support while accessing digital technology:

100% of the respondents were not aware about the Digital Saksharta Abhiyan (DISHA) or National

Digital Literacy Mission (NDLM) Scheme and 100% of the respondents do not receive support

from any organization while accessing digital technology while 92% of the respondents do not

receive support from any organization to enhance or learn new skills. The remaining 8% that have

received support have mentioned about a Self-Help Group or SHG that was formed a few years

back but got dissolved once the community came under Nagar Nigam and nobody took leadership.

“Do you want to improve your skills to use internet and smartphones efficiently?”

Figure 15

25

80% of the respondents want to improve their skills to use the internet and smartphones efficiently

while 12% do not want to improve their skills and the remaining 8% were not sure.

The 12% who stated that they “did not want to improve” did not feel that internet skills or using a

mobile phone can help them with economic opportunities. They also expressed some

disassociation with digital tools and were dismissive about accessing them. They felt that it is

something their children can better learn. Their words indicated that they were either

uncomfortable while using mobile phones, or associate ‘shame’ with spending their time while

watching videos. The 8% who were unsure felt that they can improve if it is required of them and

if they find an appropriate job opportunity for it.

Challenges in accessing Digital Technology

Figure 16

The respondents faced several challenges while accessing digital technology but the most common

challenge was of illiteracy or lack of skills. 16.2% lack appropriate skills, 14.5% have “difficulty

in typing” as they do not know how to write as well, while 12.8% face “difficulty in reading”.

14% share their phone with other members and hence are not able to access it, 8.4% do not have

time, while another 8.4% have “lack of information” around usefulness of digital tools.

6.7% have “nobody to teach or help”, 5% are not allowed to use the internet, 4.5% are not

interested in it, and 2.8% feel it is unsafe. They also felt that they will be bothering their family

members if they constantly ask for help.

3.9% respondents do not use mobile phones and internet as they are expensive, 2.2% lack internet

connection and 0.6% face a lack of network coverage.

26

As mentioned in the literature, to overcome these challenges, especially literacy-related, women

often use voice-typing or voice-search features to access the different digital platforms, and video

content is also popular among them. A generational gap is also evident in women’s perception of

the benefits of technology. The hesitancy in adopting digital tools, especially platforms related to

financial transactions, also stems from having low confidence in self and a fear of the consequences

of making a mistake. Additionally, early marriage or child marriage is a rising trend in the

community that is discouraging young girls from continuing their studies or pursuing their

interests. Ironically, there are also cases (around 6%) wherein the girls have been made to drop out

after middle school for being good in management and accountancy, and are now managing the

family store/ shop/ business.

“I am about to get married and I don't have a personal phone. No one allows me to use it.”-

Shabnam, 21 years old, 8th pass

“I fear that I might press the wrong buttons etc. I try to use the phone only when my daughters

are with me.”- Umravati, 38 years old, Illiterate

“I try to take out time after I come back home from work but my parents will marry me if I try

jobs that are uncertain.”- Kunti, 22 years old, 8th pass

“I want to learn more as I really feel helpless right now, if someone can teach me how to use

phone in a better manner, I really want to work. I can only ask for help from my children but

they are busy.”- Nirmala, 34 years old, 5th pass

However, there are also instances wherein women have been learning with the help of digital tools

and are also carrying out financial transactions through digital platforms.

“I helped my mother-in-law to expand her kitchen service. We recently started taking orders

through phone calls and WhatsApp, and have been carrying out financial transactions through

PhonePay”- Shivani Yadav, 25 years old, MA pass

“I have been carrying out transactions through Google Pay and Paytm in our store as it is more

convenient.”- Seema, 20 years old, 8th pass

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7. Way Forward

Kuanwala is a close-knit community with families that get influenced by each other. Community-

led programs, adult literacy programs, and skill development initiatives are the need of the hour.

Households do not recognize the potential their daughters, wives, and daughters-in-law have, and

thus they neither allow them to work or learn, nor do they want to spend any additional resources

on them. Many women are unemployed even when the family’s financial condition is not good

because over the years the community and the women themselves have internalized the belief that

they are not qualified to work anywhere. As a result, lack of skills and illiteracy end up being the

biggest challenge in improving digital inclusion.

Removing barriers to adult education is critical for all, especially for women. This necessitates

more flexible options for adults to improve their skills, as well as coordination across actors and

institutions, such as employers, CSOs, and training and educational institutes. In order for women,

and men, to profit from the job prospects provided by digital technologies, efforts must be made

to guarantee that job flexibility does not come at the expense of job quality (UN Broadband

Commission for Sustainable Development, 2017).

Furthermore, women's engagement in (digital) labor markets would be aided by a greater sharing

of unpaid housework and child care. Actions aiming at raising awareness, challenging gender

stereotypes and norms, as well as policies promoting gender-neutral parental leaves and child care

services provision, would help to alter internalized societal norms, attitudes, and behavior around

childcare and housework. Closing the gender gap, including the digital one, necessitates initiatives

that address the structural reasons for the divide. Increased numbers of girls and women studying

STEM will do little to close inequalities if these individuals face the same biases in the workplace

(GSMA, 2020; GPFI, 2020; UN Broadband Commission for Sustainable Development, 2017;

OECD, 2018).

To embolden the digital strategy for gender justice, alternate social, political, and economic

discourses must be created in the information society (Gurumurthy, Chami and Thomas, 2016).

The idea of enabling accessibility includes the material means, abilities, and attitudes needed to

engage in the information society's social paradigm (GSMA, 2020). Women's ownership and

control of local media processes must be encouraged through policies that provide gender-

responsive public access spaces at the community level and establishing digital literacy programs

with a citizenship focus. This entails a focus on the link between women's online inclusion and

their equal standing in economic and political roles in the society, as well as freedom from

surveillance and intrusions into their privacy (Gurumurthy, Chami and Thomas, 2016). In this

regard, digital initiatives in many parts of India can be referred, such as:

28

• The Khabar Lahariya initiative in Bundelkhand is a women led community news reporting

initiative that encourages women to become reporters who use different digital tools to

capture and write news reports, and highlight the concerns of marginalized women in rural

UP that are not covered by mainstream media.

• Through the Young Women's Leadership Program, Feminist Approach to Technology

focuses on equipping young women from marginalized communities with technical skills

as well as critical digital literacy.

• IT for Change has prioritized the creation of new knowledge, information and data cultures

via women-run open access points that emphasize marginalized women's citizenship.

• TARA AKSHAR program by Development Alternatives is a 56 days adult literacy

program that incorporates and utilizes ICT to provide women with basic literacy skills.

• Jubilant Bhartia Foundation along with iDream Social ed-tech Foundation provide e-

content in local languages under their digital literacy program. While it is currently aimed

at providing primary education to children, it has recognized the resources required to

target women from rural and marginalized communities.

• SADRAG (Social and Development Research & Action Group) have developed a Digital

Bank model through which they are linking potential digital tool donors with people from

the marginalized communities, to work on the challenge of affordability. This is followed

up by a basic training on using the tools and monitoring its condition for 2 months and

replacing it if required.

• Skill Sakhi initiative of Government of Maharashtra with UNDP provides young women

with access to digital technology, addressing the knowledge gap on skill development and

creating local changemakers.

These efforts highlight the necessity for a national digital policy framework that addresses

women's status through a citizenship approach by focusing on women's rights and the entitlements

that address their marginalization and distress in the context of a global information society

(Gurumurthy, Chami and Thomas, 2016).

Fortunately, Gender-Responsive Budgeting in the Union Budget 2021-2022 has allowed for

allocation of Rs 120 crore (almost 40%) of the allocations to Pradhan Mantri Gramin Digital

Saksharta Abhiyan/ NDLM, a digital literacy program for rural areas, in recognition of the need to

be digitally included. This is the first time that Gender Budget has included a portion of the

PMGDISHA in its statement due to which women's access to opportunities offered by digital

platforms may improve (Mitra and Chaudhry, 2021).

However, Gender-Responsive budgeting strategies should be applied to all disbursements in all

ministries and departments; subsidies for all public goods, including food, water, health, energy,

education, and transportation should be increased; gender-diverse monitoring and evaluation

techniques should be developed and applied; and public service distribution should be improved

(Desai, 2019; Mitra and Sinha, 2021). Government schemes and programs that cater to providing-

29

better household infrastructure like toilets, piped water supply, housing, electricity, LPG etc.;

childcare facilities like the National Crèche Scheme (NCS) and Integrated Child Development

Services (ICDS); provision of prevention and mitigation strategies for gender-based violence

through helplines and shelter homes; access to education and healthcare; investments in decent

work environment for women, re-integration of women in labor force through wage incentives,

training programs, skill development initiatives- are all crucial towards encouraging and

facilitating a good environment for women to learn, develop skills and participate in the workforce

(Dewan, 2019).

8. Conclusion Digital technology offers vast opportunities for women empowerment and for equitable female

participation in the labor market, financial market, and entrepreneurship. Existing government

schemes and programs, such as social security programs, can be revamped to promote women’s

economic and digital inclusion as well. By utilizing digital technology more widely for

management, payment, and monitoring, the initiatives may improve women's digital participation

while also lowering program costs. There is also scope for further research on replicating the

successful digital models like SADRAG and case studies like Khabar Laharia, at a larger scale.

Furthermore, additional research on the vulnerability of female labor force participation in

developing countries that rely on low-skilled labor is critically needed.

Enabling girls and women via targeted education and re-skilling programs, as well as reforming

normative constraints, can expedite their learning and improve their skill sets. Consequently,

women will be able to emerge as equal stakeholders in the workforce, households, and

communities.

30

9. Annexure

INTERVIEW SCHEDULE

I) DEMOGRAPHIC DETAILS:

1. Name

2. Age

3. Sex

4. Address

5. Occupation

6. Education:

• Illiterate

• Primary

• High School

• Matriculation and above

7. How long have you been working?

8. Distance to work location:

9. Family Background:

• Marital status:

• Head of the Household:

• Main household occupation:

• Total household members (M/F):

• Type of household: Nuclear/Joint/Extended/Others

• Household annual income:

Name of family members Relation with the respondent Age Education Occupation

10. Religion:

• Hindu

• Muslim

• Christian

• Buddhist

• Sikh

• Other

11. Caste:

• SC

31

• ST

• OBC

• General

• Other

12. Which of the following ID documents do you have?

• Bank Account

• Jan Dhan Account

• Ration Card

• Voter Card

• Aadhar Card

• Other (please specify)

13. Native Place:

14. How many years have you been living in the current place?

• None

• Less than 5

• 5-10 years

• 10-15 years

• More than 15

II) HOUSING/ TIME-USE:

15. What form of housing do you live in?

• Kuchha

• semi-pakka

• rented room/house

• Community housing

• Own house

16. Do you share the rented accommodation with others who are not family members?

17. How many rooms are there?

18. How many bathrooms are there?

19. Do you have access to water for drinking and cleaning?

20. Do you have a rent agreement?

21. Did you have to vacate housing? If yes, what were the reasons?

22. What were the assets the household had?

• TV

• refrigerator

• bicycle

• motorbike

• mobile or smartphone

• AC or cooler

• pump set

• inverter

• land or plot in the city or native place

• Any other

32

23. Do you have a ration card? Which color?

24. Do you avail PDS benefits according to your ration card?

25. No. of hours spent on:

• paid work:

• skill enhancement or learning:

• unpaid work:

• personal care:

• leisure:

• other:

III) EMPLOYMENT

26. Nature of Employment (SELF):

• Primary Sector (Major time in a year) (1-Agriculture, 2- Manufacturing/ allied industry, 3-

Construction, 4-Service)

• Secondary Sector (Minor time in a year) (1-Agriculture, 2 Manufacturing/allied industry, 3-

Construction, 4- Service)

27. Type of Occupation (SELF):

• Construction Labour

• Brick Kilns

• Domestic Labour

• Street Vendor

• Waste Recycler

• Agriculture Labour

• Sugarcane Harvesters

• IMCL (Indian Made commercial Liquor) Factory Worker

• Other Industrial Workers

• Others (please specify)

28. Nature of Employment (PARTNER):

• Primary Sector (Major time in a year) (1-Agriculture, 2- Manufacturing/ allied industry, 3-

Construction, 4-Service)

• Secondary Sector (Minor time in a year) (1-Agriculture, 2 Manufacturing/allied industry, 3-

Construction, 4- Service)

29. Type of Occupation (PARTNER):

• Construction Labour

• Brick Kilns

• Domestic Labour

• Street Vendor

• Waste Recycler

• Agriculture Labour

• Sugarcane Harvesters

• IMCL (Indian Made commercial Liquor) Factory Worker

• Other Industrial Workers

33

• Others (please specify)

30. Employment Status:

• Pre-Covid-19 (January-March 2020)- Employed/Unemployed

• During Covid-19 first wave (April-May 2020)- Employed/Unemployed

• After Covid-19 first wave (August-October 2020)- Employed/Unemployed

• During Covid-19 second wave (April-June 2021)- Employed/Unemployed

31. Partner’s Employment Status:

• Pre-Covid-19 (January-March 2020)- Employed/Unemployed

• During Covid-19 first wave (April-May 2020)- Employed/Unemployed

• After Covid-19 first wave (August-October 2020)- Employed/Unemployed

• During Covid-19 second wave (April-June 2021)- Employed/Unemployed

32. Are you employed through a contractor?

33. Do you have a written contract?

34. Do you receive regular wages?

35. If yes, who pays your wages- Contractor or employer?

36. What is your annual household income, including primary and secondary employment?

37. Method of payment:

• regular monthly salary

• regular weekly payment

• daily payment

• piece rate payment

• others

38. Were you able to save some money?

39. If you were a migrant, were you able to send some remittances home? If yes, how much?

40. Did you buy any insurance policy/plans?

41. Availability of social security benefits

• PF

• Health

• Maternity Benefits

• Pension

• None

42. Have you received wages for the work you did before the lockdown began?

• Yes

• No, but sure of receiving it

• No, and unsure that it will be received

43. Has your employer paid salaries for the duration of the lockdown?

• Yes

• Yes, but partial (till when)

• No

44. How has the employer behaved with you during the lockdown period?

• Job assurance post lockdown

• Has provided other support but no job assurance

34

• No support or job assurance

• No contact

• Other (please specify)

45. What additional skills do you possess?

stitching/tailoring, grooming, cooking, technician, driving, any crafts, any others

46. What additional skills do your family members possess?

stitching/tailoring, grooming, cooking, technician, driving, any crafts, any others

47. While in an economic crisis, did you look for any alternate livelihood options?

48. While in an economic crisis, did your family members look for any alternate livelihood options?

IV) DIGITAL LITERACY

49. Do you have a personal phone?

50. If not, do you share it with someone?

51. Who do you share it with?

52. Is it a smartphone?

53. What do you mostly use the mobile phone for (Rate 0-5)?

• Entertainment

• Communication

• Learning

• Financial Transaction

• Employment

54. Do you use social networking apps?

55. Do you know about the following platforms?

• Facebook

• Instagram

• YouTube

• WhatsApp

• Telegram

• Twitter

• Email

• Paytm/ Google Pay/ Phone Pay

• Yes Madam

• Uber/ Ola

• Google Maps

• Just Dial

• Mahila E-Haat

• Swayam

• Other

56. Which of the above have you used?

57. How would you rate the following from 1 to 5 (1=lowest, 5=highest)?

• Ability to use smartphones?

• Making and receiving phone calls?

• Internet literacy (the ability to use the Internet)?

• Typing skills?

35

• Web search skills?

• Computer literacy (the ability to use the computer)?

58. Yes/No

• Can you take and edit digital photos?

• Can you record and edit digital sounds?

• Can you record and edit digital videos?

• Can you download apps?

59. Do you know about the employment opportunities available with the help of digital tools?

60. If yes, what are they?

61. Do you know about platforms that can help you develop/enhance your skills?

62. If yes, list them:

63. Do you know about the Digital Saksharta Abhiyan (DISHA) or National Digital Literacy Mission (NDLM)

Scheme?

64. If yes, from where did you hear about it?

65. Do you avail benefits from the scheme?

66. Do you avail economic benefits from any other scheme?

67. Do you receive support from any organizations while accessing digital technology?

68. If yes, then what kind of support?

69. Do you receive support from any organizations to enhance or learn new skills?

70. If yes, then what kind of support?

71. Do you want to improve your skills to use internet and smartphones efficiently?

72. What are the challenges you faced while accessing digital tools?

• Lack of time

• Lack of skills

• Expensive

• Lack of information

• Lack of internet connectivity

• Lack of network coverage

• Electricity challenges

• Shared with other members

• Not allowed to use internet by family members

• Difficulty in reading

• Difficulty in typing

• Nobody to teach or help me to use mobile internet

• Unsafe

• Not enough in my own language on the internet

• Lack of relevant content

• Others

73. How did you cope with the above challenges? Give one

36

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