Women Workforce Empowerment vs Productivity: Case from the ... · It is difficult to overstate the contemporary significance of the RMG sector in development of Bangladesh. The RMG

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.

Bibliography

Alkire, S., & Foster, J. (2011). Counting and multidimensional poverty measurement.

Journal of public economics, 95(7), 476-487.

Alkire, S., & Foster, J. (2011). Understandings and misunderstandings of multidimensional

poverty measurement. Journal of Economic Inequality, 9(2), 289-314.

Alkire, S., Meinzen-Dick, R., Peterman, A., Quisumbing, A., Seymour, G., &Vaz, A.

(2013). The women’s empowerment in agriculture index. World Development, 52, 71-91.

Bose, M. L., Ahmad, A., & Hossain, M. (2009). The role of gender in economic activities

with special reference to women’s participation and empowerment in rural Bangladesh.

Gender, Technology and Development, 13(1), 69-102.

Cororaton, C. B. (1997). Productivity analysis in garments and textile industries (No. DP

1997-09).

Council, U. G. B. (2004). Leadership in energy and environmental design. Building Design

and Construction, version, 4.

Das, D. (2016). Development of Women Empowerment index for the Indian apparel

industry (Doctoral dissertation, University of Missouri--Columbia).

DuruAhanotu, N. (1998). Empowerment and production workers: a knowledge-based

perspective. Empowerment in Organizations, 6(7), 177-186.

Malapit, H. J., Sproule, K., Kovarik, C., Meinzen-Dick, R. S., Quisumbing, A. R., Ramzan,

F & Alkire, S. (2014). Measuring progress toward empowerment: Women's empowerment

in agriculture index: Baseline report. Intl Food Policy Res Inst.

Malapit, H. J., Sproule, K., Kovarik, C., Meinzen-Dick, R., Quisumbing, A., Ramzan, F., &

Alkire, S. (2014). Measuring progress toward empowerment. Women‟ s Empowerment in

Agriculture Index: Baseline Report. USAid: http://www. ifpri.

org/sites/default/files/publications/weaireport2013. pdf, last accessed, 13(09), 2014.

Narayanan, Sudha, et al. "The ‘Discouraged Worker Effect’in Public Works Programs:

Evidence from the MGNREGA in India." (2017).

Nezu, R. (2001). Measuring Productivity OECD Manual.

Kabeer, N. (2005). Gender equality and women's empowerment: A critical analysis of the

third millennium development goal 1. Gender & Development, 13(1), 13-24.

Lian, C. P. (2006). Production Operation System–Key Performance Indicator (Doctoral

dissertation, University of Southern Queensland).

Oxaal, Z., & Baden, S. (1997). Gender and empowerment: definitions, approaches and

implications for policy (No. 40). Bridge, Institute of Development Studies.

Paul-Majumder, P., & Begum, A. (2000). The gender imbalances in the export oriented

garment industry in Bangladesh. The World Bank, Development Research Group/Poverty

Reduction and Economic Management Network, Washington, DC.

Quisumbing, A. R. (2003). Household decisions, gender, and development: a synthesis of

recent research. International Food Policy Research Institute.

Rao, S. (2016). Indicators of gendered control over agricultural resources: A guide for

agricultural policy and research.

Sraboni, E., Malapit, H. J., Quisumbing, A. R., & Ahmed, A. U. (2014). Women’s

empowerment in agriculture: What role for food security in Bangladesh?.World

Development, 61, 11-52.

Union, I. G., & Union, U. G. (2013). Accord on Fire and Building Safety in Bangladesh.

Accord, IndustriALL Global Union and UNI Global Union.

Yu, W., Alam, M., Hassan, A., Khan, A. S., Ruane, A., Rosenzweig, C., ...&Thurlow, J.

(2010). Climate change risks and food security in Bangladesh. Routledge.

Zohir, S. C., & Paul, P. (1996). Garment workers in Bangladesh: economic, social and

health condition (No. 18). Bangladesh Unnayan Gobeshona Protishthan.

International Food Policy Research Institute (IFPRI). (2017). WEAI Resource Center.

Retrieved from http://www.ifpri.org/topic/weai-resource-center