Women Workforce Empowerment vs Productivity: Case from the Bangladeshi RMG Sector
A thesis submitted for the degree in
Master of Population, Reproductive Health, Gender and Development
(MPRHGD)
Submitted by:
Niloy Chakrobarty
Master of Population, Reproductive Health, Gender and Development (MPRHGD) Department of Social Relations,
East West University, Dhaka, Bangladesh ID: 2012-02-97-002
Submitted to:
Supervisor:
Dr. Rafiqul Huda Chaudhury Honorary Advisor and Coordinator
Master of Population, Reproductive Health, Gender & Development, Department of Social Relations, East West University, Dhaka
Co-supervisor:
Md. Sanaul Haque Mondal
Lecturer
Department of Social Relations,
East West University, Dhaka
Department of Social Relations
East West University
Dhaka, Bangladesh
September, 2017
Declaration
I hereby declare that this work, now submitted as thesis for the degree of Masters of
Population, Reproductive Health, Gender and Development of the East West
University, is the product of my own research. To the best of my knowledge and
belief, it contains no material previously published or written by another person,
except where due acknowledgment has been made in the text. I certify that this
thesis has not been presented to any other examination authority.
Signature:
Date:
Acknowledgements
I wish to extend my gratitude to the faculty members of Master of Population, Reproductive
Health, Gender & Development (MPRHGD) of the Department of Social Relations, East
West University for giving their time and efforts during this study. I would also like to thank
Dr. Lutfun Nahar, Associate Professor and Chairperson, Department of Social Relations,
East West University and Dr. Fouzia Mannan, Associate Professor, Department of
Sociology, East West University for their support to conduct this study.
I am immensely grateful to my research supervisor Dr. Rafiqul Huda Chaudhury, Honorary
Advisor & Coordinator, Master of Population, Reproductive Health, Gender and
Development (MPRHGD) Program, East West University for allowing me to work under his
direct supervision. This research would have been impossible without his inspiration,
supportive supervision and affectionate care.
I am especially thankful to my research co-supervisor Mr. Md. Sanaul Haque Mondal,
Lecturer, Department of Social Relations, East West University for his comments and
suggestions during the design of this study, setting data collection tools and the drafts were
extremely valuable.
I am also thankful to my dear friend and research mentor Mr. Ibrahim Khalad, Assistant
Professor, Department of Anthropology, Jahangirnagar University, Savar, Dhaka for
providing his valuable comments on the initial draft of this study. His valuable comments
have given me scope to improve the structure and quality of my work.
I would like to acknowledge the help and cooperation received from the officials of
Department of Social Relations, East West University, especially to Mr. Jakaria Habib for
providing me information from time to time on academic schedule and timeline for
completion of this study.
I would like to give my heartfelt gratitude to my colleagues working with me at Winrock
International under ‘Feed the Future Bangladesh Women’s Empowerment Activity Program’
for their supportive motivation to conduct this study. I am especially thankful to Mrs. Zainab
Akter, Chief of Party, Feed the Future Bangladesh Women’s Empowerment Activity Program
in Winrock International. Special thanks to my direct supervisor at my workplace Mr.
Shahjahan Hossain to assist me to have a better understanding on Women Empowerment in
Agriculture Index (WEAI) and approaches of empowerment measurement. Mr. A. K. M.
Saiful Islam, MIS Manager also provided me with valuable insights to design this research. I
am also thankful to him.
All research enumerators of this study who worked hard to collect data from the respondents
and the different stakeholders who were generous enough to provide me the information
deserve my gratification.
I would also like to cordially acknowledge the contribution of female garment workers – the
respondents of the questionnaire survey, for their cooperation. They were very much
enthusiastic to respond to all the questions despite their workload. The completion of the
study would not have been possible without their kind and cordial cooperation.
I am expressing deep gratitude to all of them.
Abstract
Bangladesh is the second largest Ready Made Garments (RMG) products exporter in the
world and more than 4.0 million workers (80% of them are female) are engaged in this
sector. The level of self-esteem among the female RMG workers is very low. They are also
subjected to discriminatory behavior by male co-workers and often get less than minimum
wages. In addition, they have limited scope to develop their skill and career. But improving
productivity and quality of life depends on workplace benefits and human capital
development. The objective of this research is to find out the correlation between female
workforce empowerment and factory output. Questionnaire survey has conducted to collect
the data from two garment factories: Tuba Garments Ltd (low standard factory) and Remi
Holdings Ltd (high standard factory). Women Empowerment Score (WES) and Garments
Factory Productivity Score (GFPS) have used to analyze the collected data for this study.
This study has found that the average empowerment scores for Tuba Garments Ltd and
Remi Holding Ltd are 0.33 and 0.70 respectively. On the other hand, the productivity scores
for Tuba Garments Ltd and Remi Holding Ltd are 0.62 and 0.79 respectively. It is observed
that empowerment scores for Tuba Garments Ltd are around 53% lower than Remi Holding
Ltd. On the contrary, average productivity scores for Tuba Garments Ltd are around 22%
lower than Remi Holding Ltd. But the finding of this study suggests that higher level of
empowerment does not necessarily reflect higher level of productivity for all workers. There
are some workers who are still inductive but empowered. Therefore, these are exceptions
rather than the rules. Moreover, the relationship between empowerment and productivity is
not equal for all workers. Respondents from high standard factory do not have similar level
of empowerment and productivity score and vice versa for low standard factory. In generally,
workers from high standard factory have higher score of empowerment and productivity
compared to low standard factory.
List of glossary and abbreviations
ACCORD : Accord on Fire and Building Safety in Bangladesh
BGMEA : Bangladesh Garment Manufacturer Association
DHU : Defects per Hundred Units
GFPS : Garment Factory Productivity Score
IFPRI : International Food Policy Research Institute
KPI : Key Production Indicator
LEED : Leadership in Energy and Environmental Design
NGO : Non-Government Organization
OPHI : Oxford Poverty and Human Development Initiative
RMG : Ready Made Garments
SPSS : Statistical Package for the Social Sciences
USA : United States of America
USAID : United States Agency for International Development
USGBC : United States Green Building Council
WEAI : Women’s Empowerment in Agriculture Index
WES : Women’s Empowerment Score
Table of content
Content : Page no
Declaration : i
Acknowledgement : ii
Abstract : iii
List of glossary and abbreviations : iv
Table of content : v
List of tables and figures : vi
Chapter 1: Introduction : 8-16
Introduction : 8
Objective of the research : 9
Rationality for the research : 10
Scopes of the research : 10
Conceptual framework : 11
Basic Concepts Used for this Research : 12
Limitations of the study : 15
Chapter 2: Literature review : 17-18
Women’s empowerment in RMG : 17
Five domains of women’s empowerment in agricultural sector : 17
Synchronize Five Domains and WEAI in this Study : 18
Production measures of garment industries : 18
Chapter 3: Methodology : 19-22
Study population: : 19
Methods of sample size selection and selection of respondent: : 20
Survey Methodology : 20
Data analysis : 21
Measuring the Women’s Empowerment Score (WES) : 21
Measuring the Garment Factory Productivity Score (GFPS) : 22
Ethics of the Survey : 22
Chapter 4: Results : 23-33
Characteristics of respondent: : 23
Women Empowerment Score (WES) : 26
Factory Wise Worker’s Productivity : 26
Garment Factory Wise Worker’s Productivity (GFPS) : 27
Indicator Wise Contribution to Women’s Empowerment Score : 27
Indicator wise contribution Garments Factory Productivity Score : 28
Relationship between Empowerment Score and Productivity Score : 29
Chapter 5: Conclusion : 34-
Findings of the Research : 34
Scope for Further Study : 34
Policy Implication : 34
Conclusion : 34
Bibliography : 36-37
Appendix A: Research data collection quantitative questionnaire : 38-45
(English Version)
Appendix B: Leed certification Score card of Remi Holdings Ltd.
USGBC
: 46
Appendix C: Data tables : 48-63
List of tables
Name of tables Page no. Table 1.1: The five domains of female workforce empowerment in RMG sector
Table 1.2: Garment Factory Productivity Index Table 4.1: Factory Wise Sample Size Table. 4.2: Geographical Distribution of Respondents Table. 4.3: Distribution of Educational Level of Respondents
Table. 4.4: Marital Status of Respondent.
Table. 4.5: Garments Worker’s Membership in Trade Union
Table: 4.6. Membership Status with Trade Unions: Table 4.7: Women’s Empowerment Score of Remi Holdings Ltd and Tuba Garments Ltd
Table 4.8: Average number of production per hour per worker
Table 4.9: Average Productivity score Table 4.10: Comparison of Empowerment Score, Average Number of Defective Product and Average Rework Cost
Table. 4.11: Numeric distribution of Women’s Empowerment Score (WES)
Table 4.12: WES and GFPS of two garment factories
List of figures
Name of figures Page no.
Figure 4.1: Indicator Wise Contribution to Women’s Empowerment Score 30
Figure 4.2: Indicator wise contribution to productivity score 31
Figure 4.3: Empowerment and Productivity for the workers of Remi Holding
Ltd. and Tuba Garments Ltd.
32
Chapter: 1
Introduction
Introduction:
Bangladesh is the second largest garment exporter in the world and more than 4.0 million
workers are working in this sector (80% of whom are female) (BGMEA, 2014). But female
workers of this sector have low self-esteem (Kabeer, 2005). They are facing discrimination
by their male co-workers in the workplace and getting less than minimum wage. In addition,
they have limited scope to develop their skill and career (Majumder & Begum, 2000). But
improving productivity and quality of life depends on workplace benefits and human capital
development (Majumder & Begum, 2000).
The 1990s saw more incentives for investment in RMG sector and encourage the growth of
more locally owned firms (Bhattacharya and Rahman, 2000). It seems clear from early on
that the strategy of employing women aimed to circumvent the possibility from labour
organization. Women were seen as likely to be docile, and this, with the extreme cheapness
of their labour made an emphasis on women’s employment more likely (Kabeer, 2000).
Despite employers’ concerns about male workers, the knitwear industry has grown rapidly
on the basis of a considerably more male workforce. The implications of the changing
gender and skills of the export labour force have not been very thoroughly considered to
date. Yet it seems clear that this changing composition should have made the establishment
of more constructive worker-owner-state relationships a far more urgent matter than it has
proven to be, and the basis is to prove this is the finding out the relationship workers
contribution to profit maximizing. Participation of women in the economic sector has changed
in the last two decades in Bangladesh. Women’s employment also increased considerably
over the five-year period, growing at 4.3% each year between 2000 and 2005 (World Bank,
2008)
It is difficult to overstate the contemporary significance of the RMG sector in development of
Bangladesh. The RMG sector employed around 1.9 million workers directly (Ahmed, 2009)
which was around 4% of the total labour force (Rahman, Moazzem and Hossain, 2009). Yet
around 76% of all export earnings were made from apparel in 2008-2009 (Alam, 2009), and
a 2002 estimate was that the RMG sector contributed around 10% of gross domestic product
(GDP) (Bhattacharya, Rahman and Raihan, 2002). Its contribution for the national economy
reflects its continued growth. This industry has been facing several challenges, albeit till to
date it has proven remarkable adaptive capacity to its global market environment. The
episodes include the US Harkin Bill to prevent use of child labour in the early 1990s, the
shock to global trade which hit exports to the US (a major market for Bangladeshi garments)
after 9/11 (Hossain, 2012); and the end of the favourable Multi-Fibre Arrangement in 2005,
which exposed RMG sector of the country to more competition with global market, including
China (Ahmed, 2009).
Moreover, a process of restructuring in RMG sector is already happening, and there is
evidence of improvements in compliance and management practices to raise workers’
productivity (Hossain, 2012). There are signs that these improved managerial and
compliance practices are enabling investments in workers’ productivity, helping factories to
cope up with the uncertainties of export production in Bangladesh (political and labour
unrest, transport, energy and other infrastructural bottlenecks). Women workers of garment
factories in Bangladesh have limited chance to be introduced with their factory owners and
very few factory owners get themselves involve to discussing with their employee of their
factories. The consciousness of ‘economic and cultural class identity’ within owners and the
labours is the strong influential factor here for the distance relationship between employers
and the employees. Therefore, there is no space to create an open environment that enable
each level of employee from the ground level to top management level to express their own
opinion in the factory production, managerial crisis issues, and quick problem solving in the
production chain.
Objective of the Research:
The objective of this study is to find out the linkages between empowerment of women and
productivity in garment factories. It is assumed that higher level of women empowerment the
higher the level of productivity at factory level.
Rationality for the Research:
Several studies have carried out to investigate the position of women in garments sector as
workers. The majority of these researches were carried out to meet the requirement of
buyers on social compliance or fulfill the donor requirements. However, in-depth academic
studies are limited that explore the relationship between women’s living standards and
empowerment with garment factory productivity. The outcomes of this study will help
different stakeholders at different levels to advocate for ensuring employee’s benefits within
the organizations especially in readymade garments sector.
If women workers in the garments factories become ready to develop their capabilities, they
could contribute to increased productivity for the RMG sector. But garments factory
businessmen never think about the career development of their employees especially for
women workers. On the other hand, the majority of women workers of this industry migrated
from rural areas and have limited formal employment options because of their lower level of
education and skills that results lower rate of wages within the organization, lower
participation of women in managerial position (Majumder & Begum, 2000). Moreover,
factory owners have little knowledge to understand or identify the relationship between
capacity development of workers and productivity level in factories. Therefore, owners of the
garments are reluctant to develop employees’ capacity development and make them more
professional at work places. Women employee of the garments industry face several
challenges as being women at factory, society, family and community (such as women are
over burden in household/family task, gender based discrimination in accessing social and
economic opportunities ect) and those challenges affect factory production. Lower level of
production quality and delayed in production, makes RMG sector unsustainable to compete
with global RMG markets.
Scope of the Research:
Two garments factories have been selected for this study based on the classification made
by ACCORD (Accord on Fire and Building Safety in Bangladesh) and USGBC (United
states Green Building Council) of high standard garment factory and low standard factory. It
was assumed for this study that comparatively ‘empowered’ women workers who are
working in high standard factory are likely to be more productive than the women worker
engaged with low standard garment factories. Data for this study were collected through
structured questionnaire from 150 women garment workers. This study collected information
on five domains of women’s empowerment that includes human resource development,
worker’s status in family as women, leadership position of female garment workers,
economic status of workers and labor rights and entitlement. The Women’s Empowerment
Scores (WES) for individuals has been measured using Alkire Foster Method (Detail in
Chapter 3). The Garment Factory Productivity Scores (GFPS) has also been measured
using four productivity indicators including Total production in last seven days/worker, per
hour production/worker, Number of defective production per day/worker, and rework cost of
defective products for per 100 units/worker.
Conceptual framework:
The garment industry remains one of the largest employment sectors in Bangladesh,
particularly for women who are less skilled and migrate away from rural poverty to seek
employment for a better life, greater choices, dignity and freedom. Female garment workers
are facing numerous hardships: low wages and wage discrimination, irregular payment,
forced overtime, poor working environment, physical and sexual harassment, and wrongful
termination, among others. In addition to that, unhygienic environments, substandard water
and sanitation facilities, and a lack of health care access compromise the nutritional and
reproductive status of female garment workers, causing malnutrition and other health
problems. This research seeks to expose underlying causes of dis-empowerment female
garment workers and relation to their production level in their factories. The existing problem
situation of RMG sector for the female garment workers has been prioritised to conclude to
the five domain of empowerment for the female garment workers of Bangladesh.
Low Education of Workers:
Female are working in garment sectors as they have no alternatives (Kibria, 1995). They
have lower level of education, rights, entitlement and awareness on respective job
responsibility. They switch their job to another factory with very short interval. Labour
shortage is also a common feature RMG sector of Bangladesh.
Low Aspiration on Career Development of Workers:
More than 80% garment workers of the country are female and migrated from rural to urban
area, with a view to contribute to their families through their income (Majumder, 2013). On
the other hand, married women who have children and household responsibilities have
limited aspiration to improve their careers. Therefore, most of the female go to garments
factories for a stipulated period to earn some money, and then they usually want to go back
to their family for domestic chores.
Lack of Opportunities to Develop Career:
Garment factories have limited or no opportunities to develop their skills through skills
development trainings (Majumder, 2013). On the other hand, females are working in RMG
sector as they are the bread earner of families and it is difficult for them to develop their skill.
Gender Insensitive Mid-level Management:
There is little or no such initiative on gender issue at mid and top level management of RMG
sector (Kabeer, 2005). Organizational decisions in most of the cases come from top. Mid-
level managements they are the mediator between workers and factory top authority/ factory
owners. So that the rights entitlement have been continuously constraining through the mid-
level factory management interference. On the contrary, garment factory owners have a
tendency for profit maximizing without ensuring proper compliance issues. As a result,
garment factories continuously face challenges to get business successiveness with the
international competitive market.
Conflicts within Workers:
Women are working in garment factories without joining in any workers unions/trade unions,
though it is mandatory by Labour law. In the community level, workers have limited platform
to be united to raise their voices against discrimination against them (Majumder, 2013).
Garments workers have lower level of education, information, awareness and consciousness
on their rights and entitlements within the organziations. Therefore, they do not have any
collective consciousness platform to become united. Conflict within the garment workers is
very common as they have no platform such as trade unions to resolve the conflicts within
themselves.
Insecure Employment Benefits:
Insecurity of employment benefits in garments sectors is an important factor that impedes
this sector for successful business development. This is very common complaint from the
garment workers against their employers that they are not getting their wage and overtime
payment on regular basis (Kabeer, 2000). Other job benefits like contributory provident fund
facilities by the employers are limited in garment sector. Moreover, employees have limited
access to higher management of factories to put forward their complaints.
Basic Concepts Used for this Research:
Empowerment:
Empowerment of women workers in garments industry is conceptualized as women who
have higher educational background, technical skills and withdraw regular organizational
benefits. In General, garment factories have lower level of safety and social compliance such
as, safety and security standards. Women who are confident, visionary and strong
leadership capacity, they can contribute to problem solving and decision making at factory
level as well as their family, society and community level. Empowerment of worker might be
a key attribute for garment industry to make this sector more profitable and successful.
Individual worker’s personal life is linked with their professional life. Therefore, the concept
of empowerment for this study contextualized as empowerment at workplace as well as in
family, society, and community.
Empowered women workers are expected to have higher living standards and works with
confident in their workplace to achieve higher level of productivity as well as organizational
vision.
Five Domains of Female Worker’s Empowerment in the RMG Sector:
The five domains of Women’s Empowerment in Agriculture Index’ (WEAI) has been
customized for this research as follows:
Table 1.1: The Five Domains of Female Workforce Empowerment in RMG Sector
Domain Indicator Definition of Indicator Indicator score
Domain
score
Human Resource Development (Domain-1)
Level of Education
Level of literacy and numeracy skills (average value of two weight) [Example: literacy skill score (0.6) + numeracy skill score (0.4)/2=0.5]
1/5
1/20
Technical skills Does respondent have any technical skills (e.g. sewing machine operating, design, cutting, line supervision, sewing machine repairing etc.) require for quality garment factory production work
1/5
Professional training
Respondent received any professional training relevant to RMG work.
1/5
Aspiration in career growth
Respondent wish to work in garment factory for long term with her career growth
1/5
Workers’ Status in Family as Women (Domain-2)
Decision making capacity in buying and selling of family owning productive assets
Whether respondent participates in decision to buy, sell, or transfer his/her own assets
1/5 1/20
Decision making on her own marriage
Respondent has decision making capacity for her own marriage (Only for unmarried female garment workers)
1/5
Control Over Income
Sole or joint control over income and expenditures
1/5
Decision making
Sole or joint decision making for working in garment factory
1/5
Leadership (Domain-3)
Relationship with co-workers
Relationship with her male and female co-worker? [This data has been collected for further analysis, but not been included for the measurement of empowerment score, due this variable considered as insignificantly independent variable to
1/20
empowerment score]
Relationship with supervisor
Relationship with her immediate supervisor? [This data has been collected for further analysis, but not been included for the measurement of empowerment score, due this variable considered as insignificantly independent variable to empowerment score]
Relationship with factory higher management
Relationship with her factory high management?
1/5
Membership in factory trade union
Membership in trade union (worker’s organization/network).
1/5
Participation in factory level decision making and conflict management
Participation in factory level decision making?
1/10
Economic Growth (Domain-4)
Position in factory work
Respondent’s work position in factory [This data has been collected for further analysis, but not been included for the measurement of empowerment score, due this variable considered as insignificantly independent variable to empowerment score]
1/20
Years of work experience
What is your monthly wage/salary? 1/5
Amount of monthly wage
How much money does she get each month as her wage/salary?
1/10
Amount of overtime payment
How much money do you receive on overtime payment in a month? [This data has been collected for further analysis, but not been included for the measurement of empowerment score, due this variable considered as insignificantly independent variable to empowerment score]
Saving and credit status
Access to and participation in decision-making concerning credit money.
1/5
Owing productive assets
Sole or joint ownership of major household assets [This data has been collected for further analysis, but not been included for the measurement of empowerment score, due this variable considered as insignificantly independent variable to empowerment score]
Labor Rights and Entitlement (Domain-5)
Have appointment letter
Do you have receive any official appointment letter from her employer?
1/5 1/20
Leave entitlement
Is she to entitle for leave facilities with full benefits from her employer?
1/5
Regularity in wage and overtime payment
Does she get her monthly wages and monthly overtime payment on regular basis from her employer?
1/5
Safety-security standards of the factory
Does the factory have minimum safety security standards as per inspection of international buyers association? [This data has been collected for further analysis, but not been included for the measurement of empowerment score, due this variable considered as insignificantly independent variable to empowerment score]
Gender sensitive work environment
Opinion of the respondent regarding her experience about her factory’s gender sensitive environment (separate wash room for women workers, leisure time for the lactating mother, women security guards, cooperation from male colleagues etc.). This is a measuring scale question based on respondent’s opinion.
1/5
Source: Modified after IFPRI
Productivity Measuring Indicators:
The following table outlines indicators to measure productivity and operational definitions of
each indicators for the research.
Table 1.2: Garment Factory Productivity Index:
Key Production Indicator Definition of Indicator Weight Score
Production Total production in last 7 days per worker 1/25
Per hour production per worker 1/25
Defective work Defective production per day per worker 1/25
Rework cost of defective work
Rework cost of defective work for 100 unit of production per worker
1/25
Linkage between Factories High Productivity and Female Garment Worker’s
Empowerment:
More than 80% of the RMG workers are women. This industry can make a sustainable
growth through ensuring on-time delivery and maintaining quality of products. In generally,
factory management usually blames their workers for late shipment, poor quality and
inappropriate quantity of products. But ensuring quality and other commitment with buyers
are very important to maintain the reputation of the factory. Therefore, demand for skilled
and educated women workers are increasing. But very few employers invest their money to
enhance capital development of their workers.
Female worker of the garment factories have lower level of desire and esteem to develop
their career as they get engage with this sector to earn for their family as well as generating
savings for her marital purposes and become typical ‘housewife’. Therefore, factory owners
face higher rate of employee attrition. This calls for urgent initiative to fill-up the demand
through investing in human capital development of the employees.
Limitations of the Study:
Gathering information on productivity indicators’ considered as major challenge for the
study. Most of the garment factories in Bangladesh have low standard of production data
tracking system and documentation. This is because of absence of data management
experts within the organization. To minimize this limitation this study adopted recall
method to collect production information from respective respondents.
This study used Women’s Empowerment in Agriculture Index (WEAI) of IFPRI WEAI is
approach used for women's involvement in rural agricultural sectors. But this study used
five domain of empowerment for RMG workers.
Selection of sample size and sampling method of respondent from two factories was
another challenge for this study. Only two garment factories were selected purposively.
This is to minimize the cost of the study which may compromise the representation of the
factories for all garment factories.
Women who are not involved in decision making within two garment factories do not
justifying they are about also involved in household decision making. But this is not
considered in the research study.
Only four production indicators have been considered to measure the garment factory
worker’s productivity score. It could be more formative measurement if some more
relevant indicators were considered.
Chapter 2
Literature review
Women’s empowerment in RMG:
Women’s economic empowerment is about women’s ability to choose whether to work, how
much to work, and how to spend or save their incomes. Employment in the apparel sector
provides numerous opportunities to support women’s empowerment; however, it also poses
risks that can restrict women’s empowerment. Companies that strive to prevent negative
impacts, while supporting opportunities to enhance the empowerment potential of apparel
sector jobs, will deliver the greatest benefits to women workers. Women’s economic
empowerment is multifaceted and, requires the convergence of economic and noneconomic
factors, including safety, freedom from violence, and the opportunity to be heard at work and
in society.
Five Domains of Women’s Empowerment in Agricultural Index (WEAI):
The ‘Women’s Empowerment in Agriculture Index’ (WEAI), launched by IFPRI, Oxford
Poverty and Human Development Initiative (OPHI), and USAID's Feed the Future in
February 2012, is the first comprehensive and standardized measure to directly capture
women’s empowerment and inclusion levels in the agricultural sector (IFPRI, 2017). The
WEAI have developed through an extensive research work in the rural agriculture sector in
Bangladesh, Uganda and Guatemala. The WEAI is an innovative tool composed of two sub-
indexes: one measures how empowered women are within five domains, and the other
measures gender parity in empowerment within the household (IFPRI, 2017). The WEAI
measures the empowerment, agency, and inclusion of women in the agriculture sector to
identify ways to overcome those obstacles and constraints. The five domain of ‘Women’s
Empowerment in Agriculture Index’ (WEAI) is given below:
1. Decisions about agricultural production (‘Production decision making’): Sole or joint
decision making power over food or cash-crop farming, livestock, and fisheries, as well as
autonomy in agricultural production.
2. Access to and decision making power over productive resources (‘Access to
productive resources’): Ownership of, access to, and decision making power over
productive resources such as land, livestock, agricultural equipment, consumer durables,
and credit.
3. Control over use of income: Sole or joint control over income and expenditures.
4. Leadership in the community (‘Community leadership’): Membership in economic or
social groups and being comfortable speaking in public.
5. Time allocation: Allocation of time to productive and domestic tasks, and satisfaction with
the time available for leisure activities (IFPRI, USAID, and OPHI 2012).
These five domains are measured using 10 indicators. Each indicator is given a value of 1 if
the respondent has exceeded a ‘Importantly, the WEAI has serve as a diagnostic tool for
identifying areas in which women and men in a particular geographic region are
disempowered.’
Measuring progress toward empowerment in agriculture sector:
Given threshold for the indicator and a value of 0 if the respondent falls below the threshold.
The weighted sum of these 10 indicators is the empowerment score or 5DE score of the
individual. A person is defined as “empowered” if her or his score is 80 percent or higher.
The Women’s Empowerment in Agriculture Index (WEAI, or the Index) is the first
comprehensive and standardized measure to directly capture women’s empowerment and
inclusion levels in the agricultural sector. It was developed jointly by the United States
Agency for International Development (USAID), the International Food Policy Research
Institute (IFPRI), and the Oxford Poverty and Human Development Initiative (OPHI).
The Index can also be used in other ways. Importantly, the WEAI can serve as a diagnostic
tool for identifying areas in which women and men in a particular geographic region are
disempowered. Policy and programming can then be targeted toward these areas. For
example, if results from one country show that women and men are extremely
disempowered with regard to access to credit, there may be a general lack of opportunities
to access credit in the area, a finding that practitioners can take into consideration when
developing future projects. In addition, the WEAI can be a research tool. Researchers could,
for instance, explore the linkages between the WEAI and well-being outcomes for
households, women, and children; assess the WEAI’s validity across different countries and
cultures; and test alternative indicators to measure the different domains of empowerment
Connection between empowerment result and higher women’s empowerment score in the agricultural sector: International Food Policy Research Institute has piloted the WEAI model to measure
empowerment of the women of southern Bangladesh, as interest to Feed the Future
1initiative by USAID. It then examines the outcomes that might result from empowerment,
which include the following indicators: level of household hunger (Household Hunger Score),
women’s nutrition (Women’s Dietary Diversity Score), maternal behavior (minimum
acceptable diet and exclusive breastfeeding), and child nutrition indicators (wasting,
underweight, and stunting). The size of the bubbles reflects the relative population size of
the Zones of Influence. All WEAI score and outcome values are for the Zone of Influence
only and are not nationally representative. Also, no regressions were run for this analysis,
and thus only associations, not causality, are inferred.
Possible results of empowerment observed in Agriculture Sector:
Household Hunger Score: A review of the countries in this study does not reveal any
consistent relationship between women’s empowerment and moderate or severe household
hunger. As with poverty, it is not clear that aggregate hunger and women’s empowerment
are necessarily related, because aggregate figures mask important differences among
households within a particular country. Further analysis at the household level is needed to
see whether women’s empowerment is associated with hunger reduction within communities
and Zones of Influence.
Maternal nutrition indicator: Women’s Dietary Diversity Score (WDDS): There is no clear
relationship between WDDS and women’s empowerment have been found. Considering the
score ranges from zero to nine, all countries have low WDDSs, ranging from a low in Kenya
(2.57) to a high in Cambodia (4.6)—both of which appear to be outliers from the group.
Maternal behavior—Minimum acceptable diet: There is a strong positive relationship
between female empowerment and the prevalence of children receiving a minimum
acceptable diet. The highest prevalence of this diet occurs in Cambodia and Honduras while
the lowest occurs in Kenya and Tajikistan.
Maternal behavior—Exclusive breastfeeding: There is a strong positive relationship
between higher female empowerment and higher rates of exclusive breastfeeding for
children under six months. Honduras and Rwanda have the highest prevalence rates of
exclusive breastfeeding while Haiti and Zambia have the lowest. (HJ Malapit, K Sproule, C
Kovarik, 2014)
Child nutrition indicators: The relationships between child nutritional outcomes and
women’s empowerment are unclear. Child nutritional status is determined by many factors,
of which women’s empowerment is only one. It may be that children’s nutritional outcomes
are affected by other
1 Detail about Feed the Future by USAID: https://feedthefuture.gov/about
Synchronize Five Domains and WEAI in this Study:
The WEAI model has been used to develop a rational linkage between agricultural high
productivity and increased level of women’s empowerment in agriculture sector. The current
study adopted the WEAI model to measure women empowerment in garments factories and
the level of productivity on daily basis.
Production Measures of Garment Industries:
In the apparel industry, professionals always talk about the product quality, defects, and
quality control systems. To the buyers- the finished products what they receive from the
factories, the goods should maintain quality compliance. At the very beginning, buyers were
not so serious to maintain the quality of products as well as the environment of the factories.
On the contrary, manufacturers never considered how much money they were losing
through repair work and rejection. But manufacturers are now so serious to maintain the
quality of products as well as working environment. Buyers are now curious to understand
the quality management systems of the factories and performance history. It is not just
maintain the quality of products, the factory owners must have to track their performance on
the basis of Key Production Indicator (KPI) to improve their quality and maintain continuously
as a measure of high productivity.
Percentage of Defective Products Level:
It is usually measured in percentages as total defective products in garments and total
garments inspected. It can be calculated batch wise or on the basis of completed order.
Generally, factory measures batch wise defective products on daily and hourly basis. Lesser
defective products indicate better quality performance.
Rework Cost:
Rework is an extra cost for the factories. The rework cost varies with the processes and
types of rework. It consumes times and increases the overhead of the factory. Rework cost
can be tracked to measure the performance of the factory. Lower rework cost indicates
better quality performance.
Chapter: 3
Methodology
Study Population:
This research has targeted female workers from two garment factories of Bangladesh: i)
Remi Holding Ltd which is considered as high standard garment factory and ii) Tuba
Garments Ltd which is recognized as low standard factory. The Accord on Fire and Building
Safety in Bangladesh (the Accord) was signed on May 15th 2013. It is a five year
independent, legally binding agreement between global brands and retailers and trade
unions designed to build a safe and healthy Bangladeshi Ready Made Garment (RMG)
Industry. ACCORD has inspected 2870 garment factories in Bangladesh and published a list
of factories which have met fire and building safety minimum standards. (Detail about
ACCORD given in the Annex.)
Selection of high standard factory:
According to ACCORD and USGBC garment factory categorization Remi Holdings Ltd has
been selected for the research as high standard garment factory. This selected high
standard factory is certified by ACCORD, simultaneously this factory also have achieved
Leed (Leadership in Energy and Environmental Design (LEED) Platinum Certification from
the worldwide certification agency of United States Green Building Council (USGBC).
According to USGBC certification inspection Remi Holdings Ltd has scored a total of 97 out
of total 110, and ranked as number one worldwide among 291 registered factories. USGBC
certification has been made based on the following criteria: (1) Sustainable Sites, (2) Water
Efficiency, (3) Energy & Atmosphere, (4) Material and Resources, (5) Indoor Environmental
Quality, (6) Innovation, and (7) Regional Priority. (Detail scorecard of Remi Holding Ltd is
given in the annex.)
Selection of low standard factory:
ACCORD has listed 1285 garment factory as low standard garment factory including
selected low standard garment factory for the research. From that list of low standard
factory, this study has selected one low standard factory for the purpose of comparison
between low and high standard factories with unequal status of workers empowerment and
position. For the low standard category Tuba Garment Ltd factory is selected.
This study assumes that high level of empowerment of female workers have high
productivity. Women who work at Remi Holdings Ltd. are entitled to high level of labor rights,
work standards and labor benefits and are likely to made empowerment. On the other hand
Tuba Garments Ltd is classified as low ranked where women have lower level of
empowerment as they have low standards of labor rights, work standards and labor
benefits.
Group 1: Empowered Female Garment Worker: Women working with Remi
Holdings Ltd. are classified as ‘empowered female garment workers’.
Group 2: Disempowered Female Garment Worker: Women working with Tuba
Garments Ltd. are classified as ‘disempowered female garment workers’.
The Alkire foster method:
The WES for this research study is constructed using the Alkire Foster Method developed by
Sabina Alkire, director of the Oxford Poverty and Human Development Initiative (OPHI) at
the University of Oxford, and James Foster of George Washington University and OPHI. A
method for measuring multidimensional poverty, well-being, and inequality, it measures
outcomes at the individual level (person or household) against multiple criteria (domains
and/or dimensions and indicators).
The method is flexible and can be applied to measure poverty or well-being, to target
services or conditional cash transfers, and to design and sequence interventions. Different
domains (for example, education) and indicators (for example, how many years of education
a person has) can be chosen depending on the context and purpose of the exercise.
The WEAI shows, on aggregate, level of empowered of garment factor female workers by
analyzing in which domains workers women are empowered and how these compare to dis-
empower. The Alkire Foster Method is unique in that it can distinguish between, for example,
disempowered people who are not empowered in just one domain versus those who are not
empowered across three domains at the same time.
Example of The Alkire foster method using in privation lines:
Notes: ND, not deprived; D, deprived. Shading indicates people who are poor (defined as deprived in
at least four indicators). Source: Alkire, S., & Foster, J. (2011). Counting and multidimensional
poverty measurement. Journal of public economics, 95(7), 476-487.
Methods of Sample Size Selection and Selection of Respondents:
‘Empowered’ and ‘disempowered’ female garment worker respondents have been selected
from those two garment factories. Both groups of respondents have been selected randomly
from the employees list of those two garment factories using random number table.
Sample size for this study has been determined using disproportionate allocation method
technique from those two garments factories. A total of 2200 female workers are working at
Remi Holdings Ltd and from that list 100 female has been selected for this study. On the
other hand, 270 female workers are working at Tuba Garments Ltd. and from that
employees list 50 “disempowered” female garment workers have been selected for this
study.
Survey Methodology: To collect data from ‘empowered’ and ‘disempowered’ female garments workers, this study
used structured questionnaire. Individual respondents was been considered as the unit of
analysis and, therefore survey data provides results that reflect respondent-level
empowerment score and individual level productivity score.
The questionnaires were developed for the survey have been reviewed by academic
research supervisor and co-supervisor to ensure that the questions are relevant and fulfil the
objective of this study. The draft of the questionnaire has been field tested two times. The
initial pre-testing was conducted in Dhaka with garment workers. After the first pre-test,
feedback was reviewed and necessary revisions was made on the questionnaire. A Bengali
version of the questionnaire was used for data collection.
Training and Data Collection
A total of five enumerators and one supervisor attended the training for 2 days. There was
one day field practice by which second pre-testing of the questionnaire was done. Thereafter
the questionnaire was finalised. The first day training was devoted to explaining the purpose
of the study, explaining of the ways and how a question has to be addressed. While the
second day of the training was devoted for providing hands on practical training. Purpose of
each question asked, how a question has to be examined and to build rapport with the
respondent. Face-to-face interviews have conducted to collect data. Respondent’s consent
have taken before the interview. The enumerators conduct the interviews and recorded data
with care and probe responses carefully observed to maximise reliability of collected data.
To organise the fieldwork effectively and efficiently, supervisor guides enumerators during
the training session and track of their works. After the data collection, supervisors and
enumerators was edited and crosschecked all filled up questionnaires.
Data Processing
After crosschecking, data were entered in computer using Statistical Package for Social
Sciences (SPSS).
Data analysis:
The Women’s Empowerment Score (WES) and Garment Factory Productivity (GFPS) score
has been calculated using Alkire Foster Method which was developed by Sabina Alkire and
James Foster (S Alkire and J Foster, 2011). This method is used for measuring
multidimensional poverty, well-being, and inequality outcomes at individual level (person or
household) against multiple criteria (domains and/or dimensions and indicators).
The method is flexible and can be applied to measure poverty or well-being, to target
services or conditional cash transfers, and to design and sequence interventions. Different
domains (for example, education) and indicators (for example, how many years of education
a person has) can be chosen depending on the context and purpose of the exercise.
Measuring the Women’s Empowerment Score (WES):
This study used Alkire Foster method to calculate Women’s Empowerment Score (WES).
Each domain has several measuring indicators and each indicator has been weighted. The
value of WES measure ranges from between 0 to 1. The higher the value of WES the higher
the level of empowerment, the lower the value of WES the lower the level of empowerment.
Calculation of WES and Average WES:
The Women’s Empowerment Score has been calculated for both groups of garment
workers: ‘empowered female group’ and ‘disempowered female group’ of two garment
factories. Calculation of empowerment score has been made using the following equation:
WES
WES per worker of Remi Holdings Ltd. = ;
WES per worker of Tuba Garments Ltd. =
Five domain score was calculate based on the five domain of empowerment of the female
garment workers (See: Table 1.1). Each domain contains some indicators with specific
measuring questions and that data was collected for each respondent through structured
questionnaire. Each indicator was calculated and then combined all indicator score under a
domain. Finally, with combined all domain score it was calculated as Five Domain Score.
This research assesses whether women are empowered across the five domains examined
in the WES. For the women who are disempowered, it also shows the percentage of
domains in which they meet the required threshold and thus experience sufficiency or
adequacy. The 5 Domain score captures women’s empowerment within their respective
garment factory. Although the final goal of the research is a measure of empowerment, so
the research has construct 5 Domain Score in such a way that disempowerment can be
analyzed. The advantage of this construction is that it allows us to identify the critical
indicators that must be addressed to increase empowerment. This enables decision makers
to focus on the situation of the disempowered. We begin by computing a disempowerment
index across the five domains.
Then we compute 5 domain as (Domain 1 + Domain 2 + Domain 3 + Domain 4+ Domain 5)/5
Example of indicator score calculation under a domain:
Domain 1: Human resource Development; Indicator: Leve of education
Question used for the
indicator calculation
Structured options of
response
Calculating scores
What is your level of literacy
skills (Both in Bengali and
English)
Very bad, Bad, Good, Very
Good, Excellent
Very bad= 1, Bad= 2, Good=
3, Very good= 4, Excellent=
5
What is your level of
numeracy skills?
Very bad, Bad, Good, Very
Good, Excellent
Very bad= 1, Bad= 2, Good=
3, Very good= 4, Excellent=
5
1. To calculate score for level of literacy and numeracy: Response are scored with Very
bad (=1), Bad (=2), Good (=3), Very good (=4), Excellent (=5).
2. Level of education compute: Level of education score= (literacy score + numeracy
score)/2
Example of domain score calculation:
Domain 1: Human resource Development
Indicator under Domain 1 Indicator weight Total domain weight
Level of education 5 20
Technical skills 5
Professional training 5
Aspiration in career growth 5
To calculate Domain 1 score:
Domain 1 score = (Education level score + Score in technical skills + Score in professional
training + Score in career growth aspiration)/20
Example of Women’s Empowerment Scoring (Scoring of WES):
Five domains for WES Domain weight Total WES
weight
Domain 1: Human Resource Development 20 100
Domain 2: Worker’s status in family as women 20
Domain 3: Leadership 20
Domain 4: Economic growth 20
Domain 5: Labor rights and entitlement 20
To calculate Women’s Empowerment Score (WES):
WES= (Domain 1 score + Domain 2 score + Domain 3 score + Domain 4 score + Domain 5
score)/100 or ∑ (Five domain score)/100
Measuring the Garment Factory Productivity Score (GFPS):
This study used Alkire Foster method to calculate Garment Factory Productivity Score
(GFPS). The value of GFPS measurement ranges from 0 to 1. Higher the level of GFPS is
the higher level of productivity and lower the level of GFPS is the lower level of productivity.
Calculation of GFPS and Average GFPS:
The average Garment Factory Productivity Score (GFPS) have been calculated separately
for both groups of respondents: ‘empowered female workers’ and ’disempowered female
workers’ from two garments. Calculation of average Garment Factory Productivity Score
(GFPS) has been made after the calculation of Garment Factory Productivity Score (GFPS)
for each individual respondent. Individual’s Garment Factory Productivity Score has been
(GFPS) calculated using the following equation.
GFPS
Average Garment Factory Productivity Score (GFPS) has also been calculated respectively
for both groups’ respondents using the following equation:
GFPS per worker of Remi Hodings Ltd. = ;
GFPS per worker of Tuba Garments Ltd. =
Example of productivity indicator score calculation under Garment factory
productivity index:
Production indicator 1: Total production in last 7 days/worker.
Question used for the
indicator calculation
Options of response Calculating scores
In last 7 days how many
number of product you
have delivered from your
sewing machine?
It was open ended question,
enumerators were instructed
to entre number (logically
correct) of production by
respondent in last seven
days
Frequency table of the
variable shoed height
number of production 1470 in
7 days and lowest is 617.
Between number of
production 617-800= 5, 801-
1000 = 10, 1001-1200 = 15,
1201-1300=20 and 1300≥ 25
To calculate score for last 7 day production: Responses are scored with Between number of
production 617-800 (=5), 801-1000 (=10), 1001-1200 (=15), 1201-1300(=20) and 1300≥
(=25).
Example of Garment Factory Productivity Scoring (Scoring of GFPS):
Four indicator under GFPS index Productivity
indicator weight
Total GFPS
weight
Indicator 1: Total production in last 7 days/worker 25 100
Indicator 2: Per hour production/worker 25
Indicator 3: Defective production per day/worker 25
Rework cost of defective work for 100 unit of production/worker
25
To calculate Garment Factory Productivity Score (GFPS):
GFPS= (Indicator 1 score + Indicator 2 score + Indicator 3 score + Indicator 4 score)100 or
∑ (Five domain score)/100
Ethics of the Survey Personal data such as name, address remained anonymous for the research survey.
Respondents were informed about the objective of the study and took consent to participate
in the study.
Chapter 4
Results
Characteristics of Respondents:
A total of 150 female garment workers have been randomly selected for interview using
random number table. Among them 67% are from Remi holdings Ltd. and 33% from Tuba
Garments Ltd. (Table 4.1).
Table 4.1: Factory Wise Sample Size:
Garment Factory Number (N) Percent (%)
Remi Holding Ltd. 100 67
Tuba Garments Ltd. 50 33
Total 150 100
Source: Field Survey, 2016
Geographic Distribution of Respondents:
Most of the garment workers in Bangladesh come from rural areas to search for work in
urban areas and join garment factories. The single large number of the respondents (around
33%) came from disaster prone coastal districts of southern Bangladesh (Table 4.2). They
have migrated to Dhaka from geographically vulnerable disaster prone districts, such as,
Barisal, Barguna, Khulna and Bagerhat to search for employment opportunities. Most of the
respondents from coastal districts came to Dhaka because they had limited employment
options in their locality due to adverse impact of climate change on coastal livelihoods. Many
of them lost their shelter and traditional employment after the stuck of cyclone Sidor in 2007
and Cyclone Ayla in 2009. Around 29% respondents have migrated from flood and river
bank erosion prone districts, such as Faridpur, Bogura, Madaripur and Shirajgonj (Table
4.2). A significant number of respondents came from drought prone districts (Panchagor,
Nilphamari, Rongpur and Dinajpur) that represent around 27% of total respondents (Table
4.2). The rest of the respondents (around 11%) came from Mymenshing, Noakhali,
Narayangonj and Narshindi district.
Table. 4.2: Geographical Distribution of Respondents
Geographic distribution Number (N) Percent (%)
Disaster prone costal districts 50 33
Flood and river erosion prone districts 43 29
Drought prone districts 41 27
Other districts 16 11
Total 150 100
Source: Field survey, 2016
The RMG sector has created a niche for absorbing relatively unskilled and semi-literate
young female labor of rural areas. Historically, distance has been projected as an important
determinant of number of migrants to the city (Majumder and Begom, 2000). Now
information and contact factors act as a surrogate for communication and tend to counter the
effects of distance (Majumder and Begom, 2000). Therefore, within the garment industries,
distance has little significance compared to information and contacts, income, living
standards and asset ownership as place of origin.
Educational Background of Respondents:
Majority of the respondents (around 67%) completed Grade 6 to Grade 8, followed by 22%
respondents completed Grade 1 to Grade 5 (Table 4.3). Only 7% respondents’ have
completed education Grade 8 to Grade 10 (Table 4.3). A few respondents (3%) did not
receive any formal education (Table 4.3).
Table. 4.3: Distribution of Educational Level of Respondents
Education Level Number (N) Percent (%)
Never went to school 5 3
Grade 1 – Grade 5 33 22
Grade 6 – Grade 8 101 67
Grade 8 – Grade 10 11 7
Total 150 100
Source: Field Survey, 2016
Marital Status of Respondents:
Garment employers prefer unmarried, widowed, separated, abandoned female workers
because it is obvious that currently-married women are more go on leave frequently due to
childbirth, childcare, or household chores (Majumder, 2013). Due to the burden of childcare
and household chores, married women are not able to work overtime, which is almost
mandatory for export-oriented manufacturing of garments. In addition garment employers
are reluctant to provide maternity leave and maternity benefits which is the major reason
behind their preference for unmarried female. But 72% respondents are currently married
and 27% respondents are unmarried, divorced, separated or widow (Table 4.4).
Membership in Trade Union:
Among all respondents, 51% have membership with internal Trade Union (within factory
workers) or external Trade Union (links with national level workers’ federation) and rest of
the respondents (49%) have no membership with any kind of Trade Unions or Workers’
organizations (Table 4.5).
Table. 4.4: Marital Status of Respondent.
Marital Status Number (N) Percent (%)
Unmarried 28 18
Married 108 72
Divorced/Separated/Widow 14 9
Total 150 100
Source: Field Survey, 2016
Table. 4.5: Garments Worker’s Membership in Trade Union
Membership Status of Trade Union Number (N) Percent (%)
Membership with Trade Union 77 51
No Membership withTrade Union 73 49
Total 150 100
Source: Field Survey, 2016
It is found 73% respondents from Remi Holding Ltd. and 8% from Tuba Garments Ltd have
membership with Trade Unions (Table: 4.5). Remi Holding Ltd. has a platform for workers’
association where all senior workers have membership. Workers of Tuba Garments Ltd.
have a fear of losing their job if they engage with Trade Union. As one of the respondents
from Tuba Garments Ltd. mentioned that:
‘We will be fired from the factory, if authority gets information about our membership
status with any kind of Trade Unions’.
It is evident that Remi Holdings Ltd. has an enabling environment for the workers to be
involved with Trade Unions as their organization gives them a space to raise their voices. On
the contrary, this situation is completely different for Tuba Garments Ltd.
Table: 4.6. Membership Status with Trade Unions:
Membership with Trade
Union
Remi Holdings Ltd. (%)
Tuba Garments Ltd. (%)
Yes 73 8
No 27 92
Total 100 100
Source: Field Survey, 2016
Women’s Empowerment Score (WES):
Women’s Empowerment Score (WES) has been calculated for each individual respondent
using Five Domain of Women’s Empowerment data collected through the survey. Women
Empowerment Score (WES) per worker is found to be higher (0.70) of Remi Holding Ltd
compared to the counter Tuba Garments Ltd is 0.33 (Table 4.7).The detail methods of
calculating the Women Empowerment Score (WES) has described in methodology section.
Table 4.7: Women’s Empowerment Score of Remi Holdings Ltd and Tuba Garments Ltd
Name of Garment Factory Women Empowerment Score
Remi Holdings Ltd. 0.70
Tuba Garment Ltd. 0.33
Total 1.00
Source: Field Survey, 2016
Hypothesis testing 1 (T-Test) Women’s empowerment score of High standard garment
factory is higher compared with counter Tuba Garments Ltd:
Table 4.8: Independent Samples Test: Women’s Empowerment Score (WES) for the
workers of High and low standard garment factory.
Group Statistics for t-test: Women’s Empowerment Score (WES):
Name of the garment factory N Mean Std. Deviation Std. Error Mean
Remi Holdings Ltd 100 .7043 .13211 .01321
Tuba Garments Ltd 50 .3338 .17200 .02432
Independent sample test result table:
Levene's Test for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the
Difference Lower Upper
Equal variances assumed 1.634 .203 14.599 148 .000 .37050 .02538 .32035 .42065
Equal variances not assumed
13.385 78.778 .000 .37050 .02768 .31540 .42560
The workers group (N=100) of Remi Holding Ltd was associate with a women’s
empowerment score (WES) M= 0.70 (SD=0.132). By comparison the workers group (N=50)
of Tuba Garments Ltd was associated with a numerically smaller WES M= 0.33 (SD=0.172).
To test the hypothesis that the workers of Remi Holding (High standard factory) and workers
of Tuba Garments Ltd (Low standard factory) were associated with significantly different
mean volume of WES, as independent sample t-test were performed. As we can see in
Table 4.5, the workers of Remi holdings Ltd and the workers of Tuba Garments Ltd.
distributions were sufficiently normal for the purpose of conducting a t-test. Additionally, the
assumption of homogeneity of variance was tested and satisfied via independent t-test. Thus
WES of workers group of high standard factory significantly large mean volume than WES of
workers group of low standard garment factory.
Factory Wise Worker’s Productivity:
The average number of production per hour per worker for Remi Holdings Ltd. is 24 and for
Tuba Garment Ltd.is 13 (Table 4.9). This means the average number of production per hour
per worker for Remi Holdings Ltd. is almost double compared to Tuba Garments Ltd. The
detail methods of calculating the average number of production per hour per worker has
described in methodology section.
Table: 4.9: Average number of production per hour per worker
Name of Garment Factory Average number of production per hour per worker
Remi Holdings Ltd. 24
Tuba Garment Ltd. 13
Source: Field Survey, 2016
Garment Factory Wise Worker’s Productivity (GFPS):
Individual worker’s productivity scores have also calculated through adding scores of all
indicators. The Average Productivity Score for Remi Holdings Ltd. is 0.79 and for Tuba
Garment Ltd.is 0.62 (Table 4.10). The detail methods of Average Productivity Score has
described in methodology section.
Table 4.10: Average Productivity score:
Name of Garment Factory Average Productivity Score
Remi Holdings Ltd. 0.79
Tuba Garment Ltd. 0.62
Source: Field Survey, 2016
Hypothesis testing 2 (T-Test) Garment Factory Productivity Score (GFPS) of High
standard garment factory is higher compared with counter Tuba Garments Ltd:
Table 4.11: Independent Samples Test: Garment Factory Productivity Score (GFPS) for the
workers of High and low standard garment factory.
Group Statistics for t-test: Garment Factory Productivity Score (GFPS):
Name of the garment factory N Mean
Std.
Deviation Std. Error Mean
Remi Holdings Ltd 100 .7865 .11696 .01170
Tuba Garments Ltd 50 .6230 .14329 .02026
Independent sample test result table: Levene's Test
for Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the
Difference Lower Upper
Equal variances assumed
6.837 .010 7.475 148 .000 .16350 .02187 .12028 .20672
Equal variances not assumed
6.988 82.551 .000 .16350 .02340 .11696 .21004
The workers group (N=100) of Remi Holding Ltd was associate with a Garment Factory
Productivity score (GFPS) M= 0.79 (SD=0.1169). By comparison the workers group (N=50)
of Tuba Garments Ltd was associated with a numerically smaller WES M= 0.62
(SD=0.1432). To test the hypothesis that the workers of Remi Holding (High standard
factory) and workers of Tuba Garments Ltd (Low standard factory) were associated with
significantly different mean volume of GFPS, as independent sample t-test were performed.
As we can see in Table 4.11, the workers of Remi holdings Ltd and the workers of Tuba
Garments Ltd. distributions were sufficiently normal for the purpose of conducting a t-test.
Additionally, the assumption of homogeneity of variance was tested and satisfied via
independent t-test. Thus GFPS of workers group of high standard factory significantly large
mean volume than GFPS of workers group of low standard garment factory.
Indicator Wise Contribution to Women’s Empowerment Score:
A significant variation in measuring Women’s Empowerment Score (WES) of both factories
observes for ‘Labor rights and entitlement’ domain. The share of ‘Labor rights and
entitlement’ in WES measurement for Remi Holding Ltd. is 26%, whereas for Tuba
Garments Ltd is 9% (Figure 4.1). It is quite evident from the findings that ‘Labor rights and
entitlement’ for Remi Holdings Ltd. is almost 3 times higher than the Tuba Garments Ltd.
This finding clearly depicts that the status of ‘Labor Rights and Entitlement’ is higher in ‘high
standard factory’ compare to ‘low standard factory’. ‘Economic growth of female garment
workers’ for Tuba Garments Ltd has the highest contribution to WES and shared around
32%. On the other hand, the contribution of ‘Economic growth of female garment workers’
domain for Remi Holdings Ltd is 24% (Figure: 4.1). This indicates ‘Economic growth of
female garment workers’ is a significant contributor of WES for both groups of respondents.
‘Workers Knowledge and skills’ is an important domain for both garments factories. The
contribution of ‘Worker’s knowledge and skills’ in WES measurement for Remi Holding Ltd.
is 24%, whereas for Tuba Garments Ltd is 25% (Figure 4.1). In both cases this domain plays
a significant role for productivity. ‘Worker’s status in the family as women’ is higher for Tuba
Garments Ltd. (20%) compared to Remi Holding Ltd (16%) (Figure 4.1). ‘Leadership
position’ is the not very a powerful domain for both garments workers. The share of
‘Leadership position’ in WES measurement for Remi Holding Ltd. is 10%, whereas for Tuba
Garments Ltd is 14% (Figure 4.1). This indicates that ‘Leadership Position’ for both
garments factories is not an influential factor for factory productivity.
Figure 4.1: Indicator Wise Contribution to Women’s Empowerment Score
Source: Field Survey, 2016
Indicator wise contribution Garments Factory Productivity Score (GFPS):
‘Rework cost’ is one of the most significant domains contributing to Garment factory
productivity score (GFPS). ‘Rework cost’ of GFPS is the highest percentage for Remi
holding Ltd. which is 29% and slightly lower for Tuba Garments Ltd which is 24% (Figure
4.2). The number of ‘Defective production per day per worker’ is higher for Remi Holding Ltd.
than the Tuba garments Ltd. The percentage of ‘Defective production per day per worker’ for
Remi Holding Ltd. is 22% while 38% for Tuba Garment Ltd. If we compare ‘Defective
production per day per worker’ with ‘Rework cost’, we can easily identify that workers from
Tuba Garment Ltd. have lower defective work than rework cost of Remi Holding Ltd.
‘Number of total production in last 7 days’ for Remi Holdings Ltd. is 24% and almost similar
figure for Tuba Garments Ltd. which is 22% (Figure 4.2). This indicates number of total
production per worker in last 7 days for both garments factories is very close. The ‘Number
of production per hour per worker’ for Remi Holdings Ltd is 25%for Tuba Garments Ltd. is
16% (Figure 4.2). This means ‘number of production per hour per worker’ for Remi Holding
Ltd is much higher than the workers of Tuba Garments Ltd.
Figure 4.2: Indicator wise contribution to productivity score
Source: Field survey, 2016.
Relationship between Empowerment Score and Productivity Score:
The average empowerment score and average productivity score for the workers of Remi
Holding Ltd. and Tuba Garments Ltd are illustrated separately in the Figure 4.3. The
empowerment scores for Remi Holdings Ltd. is more than double than Tuba Garments Ltd.
The average empowerment score for Remi Holding Ltd. and Tuba Garments Ltd. is 0.70 and
0.33 respectively. On the other hand, the productivity scores for Tuba Garments Ltd and
Remi Holding Ltd are 0.62 and 0.79 respectively. It shows, workers from high standard
factory have higher score of empowerment and productivity compared to low standard
factory. It is observed that empowerment scores for Tuba Garments Ltd are around 53%
lower than Remi Holding Ltd. On contrary, average productivity scores for Tuba Garments
Ltd are around 22% lower that Remi Holding Ltd.
This research assumes that higher level of empowerment for female garment workers is
likely to have higher level productivity. The ‘average number of production per hour per
worker for Remi Holdings Ltd and Tuba Garments Ltd. is 24 and 13 respectively (Table 4.8).
This indicates ‘average number of production per hour per worker for Remi Holding Ltd. is
about 46% higher than Tuba Garments Ltd. The average Women Empowerment Score
(WES) for Remi Holding Ltd. is 0.70 and ‘average number of production per hour per
workers’ is 24. On the contrary, the average Women Empowerment Score (WES) and
‘average number of production per hour per worker is 0.33 and 13, respectively.
Figure 4.3: Empowerment and Productivity for the workers of Remi Holding Ltd. and Tuba
Garments Ltd.
Source: Field Survey, 2016
The empowerment scores for Remi Holdings Ltd. is 53% higher than Tuba Garment Ltd.,
whereas, the average number of production per hour per workers for Tuba Garment Ltd. is
46% lower than Remi Holdings Ltd. This data clearly portrays high correlation between
empowerment score and average number of production per hour per worker. This type of
relationship is also observed between productivity score and empowerment score for the
relationship is not so significantly correlated for indicators of productivity score.
Table 4.12: Comparison of Empowerment Score, Average Number of Defective Product and
Average Rework Cost
Productivity Indicators Remi Holding Ltd Tuba Garments Ltd
Average empowerment Score 0.79 0.62
Average productivity Score 0.70 0.33
Average number of defective product (per 100 unit production)
per worker 7.6 4.2
Average rework cost for (per 100 unit products) per worker
Tk. 466 Tk. 416
** Tk.= Bangladeshi Taka (Tk. 100 = $1.27USD); Source: Field Survey, 2016
The average number of defective work per 100 unit of production per worker is higher for
Remi Holdings Ltd. compared Tuba Garments Ltd. which is 7.6 and 4.2 respectively, which
is 45% lower than Remi Holdings Ltd.(Table 4.10). On the other hand, the average rework
cost of defective product per 100 unit product per workers for Remi Holdings Ltd. and Tuba
Garments Ltd. Tk. 466 and Tk. 416 respectively (Table 4.10).This indicates rework cost for
Remi Holdings Ltd. is 11% higher than the Tuba Garments Ltd.
Table 4.13 shows individuals Women Empowerment Score (WES) of both factories. This
table illustrate some workers from Tuba Garments Ltd. have higher also empowerment
score. The empowerment score of 4 respondents from Tuba Garments Ltd. is as right as
0.81 (Table 4.13). On the other hand, 5 respondents from Tuba Garments Ltd. have a score
of 0.16 which is the lowest of all scores.
Table. 4.13: Numeric distribution of Women’s Empowerment Score (WES).
Women’s Empowerment Score (WES)
Number of Workers
Remi Holdings Ltd. Tuba Garments Ltd.
0.15 0 5
0.20 0 5
0.23 0 5
0.24 0 10
0.29 0 5
0.32 0 5
0.44 0 5
0.45 9 0
0.45 0 6
0.49 9 0
0.63 9 0
0.66 9 0
0.69 9 0
0.70 9 0
0.76 9 0
0.81 10 4
0.82 9 0
0.83 9 0
0.87 9 0
Total 100 50
Source: Field Survey, 2016
This study find out workers from low standard factory might have higher level of
empowerment with high level of skills and expertise although they have lower level of
empowerment. On the contrary, lower level of empowerment status might be observed in
high standard factory although most of them have high level of empowerment status.
Table 4.14: WES and GFPS of two garment factories:
WES GFPS
0.45 0.50 0.60 0.65 0.70 0.75 0.80 0.90 0.95
0.15 5*
0.20 5*
0.23 5*
0.24 5* 5*
0.29 5*
0.32 5*
0.44 5*
0.45 9+
0.45 6*
0.49 9+
0.63 9+
0.66 9+
0.69 9+
0.70 9+
0.76 9+
0.81 10+, 4*
0.82 9+
0.83 9+
0.87 9+
*= Number of workers from Tuba Garments Ltd, += Number of workers from Remi Holding Ltd.
Source: Prepared from Field Survey, 2016
According to Table 4.14, 40% respondents from Tuba Garments Ltd. have less than 0.30
empowerment score with a productivity score of less than 0.50 (Table 4.12). While 20%
respondents from Tuba Garments Ltd. have less than 0.5 empowerment score but score is
more than 0.8. In fact, 38% respondents from Tuba Garments Ltd. have a productivity score
of more than 0.8. On the other hand, 9% of the respondents from Remi Holdings Ltd. have
an empowerment score of less than 0.5 and productivity score is 0.6. It is obvious, 46%
respondents from Remi Holdings Ltd. have empowerment score ranges from 0.66 to 0.87
and productivity score is more than 0.8.
The data shows here 9 workers of Remi Holdings Ltd. have height level of empowerment
score at 0.87 as well as high productivity score at 0.95. 9 workers of Remi Holdings Ltd.
have the same level of GFPS but their WES is lower at 0.82 than 9 other workers mentioned
earlier. Around 10% respondents from Tuba Garments Ltd. have a productivity score 0.65
but their empowerment 0.15. The cross-sectional study shows that higher empowerment
score does not ensure higher level productivity score. Moreover, control of empowerment on
productivity will not equal for all workers. All respondents from high standard factory do not
have higher level of empowerment and higher level of productivity. Furthermore respondents
from low standard factory do not have similar level of empowerment and productivity. In
General, most of the respondents from high standard factory have higher level of
empowerment and productivity compare to low standard factory. The analysis suggest that
productivity has become influenced by various levels of empowerment for both factories, but
degree of influence varies with person to person of both garment factories.
Chapter: 5
Conclusion
Findings of the Research:
This study has found that the average empowerment scores for Tuba Garments Ltd and
Remi Holding Ltd are 0.33 and 0.70 respectively. On the other hand, the productivity scores
for Tuba Garments Ltd and Remi Holding Ltd are 0.62 and 0.79 respectively. Respondents
from high standard factory have higher score of empowerment and productivity compared to
low standard factory. It is observed that empowerment scores for Remi Holding Ltd. is
around 53% higher than Tuba Garments Ltd. The average productivity scores for Remi
Holding Ltd. are around 22% higher than that of Tuba Garments Ltd.
It can be concluded that the relationship between women’s empowerment and garment
factory productivity output is related, yet this correlation will not always follow this rule. From
this evidence we cannot simply put a statement those two variables are positively correlated.
Scope for Further Study:
This study is based on the questionnaire survey with female garments workers. There
are some other factors such as social, cultural and political which were not considered
for this investigation.
Gender parity is one of the key concepts related with women's empowerment issue.
Inclusion of gender parity context might bring more interesting findings in future
research.
Policy Implication:
The objective of this research is to show the relationship between female workers
empowerment and garment factory productivity. This research shows that women’s
empowerment (female garment worker) and high level of factory productivity are correlated
with some exceptions. The findings of this research will help activists to argue more actively
and canvas with the factory owners for developing human capital and improving living
standards of female garment workers. This will not only improve the quality of living
standards of factory workers but also will contribute to higher productivity of garment
factories that will be ultimately beneficial for garment factory owners.
Conclusion:
How then do we empower, especially the women workers working in the garment factories in
Bangladesh? This question will certainly be a reality in near future. The solution may come
out as training of workers and teamwork. If we apply them correctly we can easily ensure a
success for most of garments companies.
Organization can create an empowered environment, if they allow their work on accessing
information, resources and trainings and a follow-up with measurement and reinforcement.
However, empowering employee is a continuing process. Companies that take the first step
to create an environment conductive to empowerment will likely to be the leaders of
industrial sector.
Female workers empowerment is a very complex undertaking even for the most experienced
firms. The impact of empowerment is definite as it can greatly influence the ability of the
firms to compete today’s increasingly competitive world. The finding of this study shows that
Remi Holding Ltd. is getting direct benefit as their worker’s has higher level of
empowerment. These benefits are enjoyed without any spending of firm. Cost-benefit
analysis will help garment factory management to determine the optimum level of
empowerment. Workers’ empowerment relies upon effective coach, and managers’ help
workers to accept more responsibilities. Manager should seek to understand issues and
perspectives of workers before moving on to problem solving. Even though empowerment is
not a solution for all problems within the organization, but it can motivate workers to increase
productivity and efficiency as the study unearth through questionnaire survey.
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