The Effect of Lean Six Sigma on the Jordanian
Pharmaceutical Manufacturing Organizations' Business
Performance
!
Prepared by:
William Hanna Al Kunsol
Supervised by:
Dr. Abdel-Aziz Ahmad Sharabati
Thesis Submitted in Partial Fulfillment of the Requirements for
Master Degree in Business Administration Department
Management Department - Business Faculty
Middle East University
Amman - Jordan
June 2015
III
IV
Acknowledgement
First of all I would like to thank GOD. This work could not have been
finished without His help. I ask him to bless all people who supported me to
complete this work.
I am sincerely grateful to my supervisor, Dr. Abdel-Aziz Ahmad Sharabati,
whose recommendations, devotion, advocacy, patience, encouragement, and
support have led me to achieve this work.
In fact, it would not be possible to complete this work without the kind
support and help of many individuals and organizations. So, I would like to extend
my sincere thanks to all of them. Specially, I am highly indebted to Ms. Mais
Dabain for her valuable information, support, to complete the thesis.
Finally, thanks for the examination committee for devoting much of their
valuable time reviewing and discussing the material of the study.
William Hanna AL Kunsol
V
Dedication
This thesis is dedicated to my precious family; my father Hanna, my mother
Lames, my sisters Nour and Rana and my brother Hazim, and my lovely friends
who helped me in each and every way it was needed and believe in me, for their
endless support throughout my life to reach this stage .
No words can make me express my gratitude and thanks, to each of the
above, I extend my deepest appreciation.
William Hanna Al Kunsol
VI
Table of Contents
Contents
Authorization .............................................................................................. Error! Bookmark not defined.
Examination Committee’s Decision............................................................. Error! Bookmark not defined.
........................................................................................................................................ III
Acknowledgement..................................................................................................................................IV
Dedication...............................................................................................................................................V
Table of Contents ...................................................................................................................................VI
List of Tables .......................................................................................................................................VIII
List of Models ........................................................................................................................................IX
List of Figures .........................................................................................................................................X
List of Appendices .................................................................................................................................XI
Abstract................................................................................................................................................. XII
.................................................................................................................................................. XIII
Chapter One: ........................................................................................................................................... 1
Introduction............................................................................................................................................. 1
1.1. Background: ..................................................................................................................................... 1
1.2. Problem Statement............................................................................................................................ 3
1.3. Study Purpose and Objectives:.......................................................................................................... 5
1.4. Study Importance:............................................................................................................................. 5
1.5. Study Hypotheses: ............................................................................................................................ 6
1.6. Study Model: .................................................................................................................................... 7
1.7. Conceptual and Procedural Definitions of Variables:......................................................................... 8
1.8. Study Limitations: .......................................................................................................................... 10
Chapter Two: ........................................................................................................................................ 11
Conceptual and Theoretical Framework and Previous Studies................................................................ 11
2. Conceptual and Theoretical Framework:............................................................................................ 11
2.1. Definitions of Variables:................................................................................................................. 11
2.1.1. Lean Manufacturing:.................................................................................................................... 11
2.1.2. Six Sigm:..................................................................................................................................... 13
2.1.3. Lean Six Sigm: ............................................................................................................................ 15
VII
2.1.5. Sustainability development: ......................................................................................................... 17
2.1.4. Business Performance:................................................................................................................. 18
2.2. Element of Variables ...................................................................................................................... 18
2.2.1. Elements of Lean Production: ...................................................................................................... 18
2.2.2. Elements of Six Sigma:................................................................................................................ 19
2.2.3. Elements of Lean Six Sigma: ....................................................................................................... 20
2.2.5. Elements of Sustainable Development: ........................................................................................ 22
2.2.6. Elements of Business Performance:.............................................................................................. 23
2.3. The Relationship between Lean Six Sigma and Business Performance: ........................................... 24
2.4. Previous Models: ............................................................................................................................ 25
2.5. Previous Studies: ............................................................................................................................ 31
2.6. Expected Contributions of the Current Study as Compared with Previous Studies: .......................... 46
Chapter Three:....................................................................................................................................... 48
Study Methodology (Methods and Procedures):..................................................................................... 48
3.1. Study Approach and Design:........................................................................................................... 48
3.2. Study Population, Sample and Unit of Analysis: ............................................................................. 48
3.3. Data Collection Methods (Tools): ................................................................................................... 49
3.4. Data Collection and Analysis:......................................................................................................... 50
Chapter Four: ........................................................................................................................................ 53
Analysis and Results ............................................................................................................................. 53
4.1. Introduction:................................................................................................................................... 53
4.2. Respondents’ Demographic Description: ........................................................................................ 53
4.3. Study Variables Analysis (Descriptive Analysis): ........................................................................... 55
4.4. Relationships between the Study Variables: .................................................................................... 67
4.5. Testing Study Hypothesis: .............................................................................................................. 68
Chapter Five:......................................................................................................................................... 75
Results’ Discussion, Conclusion and Recommendations ........................................................................ 75
5.1. Results’ Discussion:........................................................................................................................ 75
5.2. Conclusion: .................................................................................................................................... 76
5.3. Recommendations: ......................................................................................................................... 77
English References:............................................................................................................................... 79
Appendices: .......................................................................................................................................... 96
VIII
List of Tables
Table (3.1): Reliability Test:.................................................................................................................... 52
Table (4.1): Demographic Analysis ......................................................................................................... 54
Table (4.2): Mean, Standard Deviation, Importance and Ranking of Lean Six Sigma Variables: ............... 56
Table (4.3): Mean, Standard Deviation, Importance and Ranking of the Defect Items: ........................... 56
Table (4.4): Mean, Standard Deviation, Importance and Ranking of the Over Production Items:............ 57
Table (4.5): Mean, Standard Deviation, Importance and Ranking of the Waiting Time Items:................. 58
Table (4.6): Mean, Standard Deviation, Importance and Ranking of the Transportation Items: .............. 59
Table (4.7): Mean, Standard Deviation, Importance and Ranking of the Inventory Items: ...................... 60
Table (4.8): Mean, Standard Deviation, Importance and Ranking of the Motion Items:.......................... 61
Table (4.9): Mean, Standard Deviation, Importance and Ranking of the Extra Processing Items: ............ 61
Table (4.10): Mean, Standard Deviation, Importance and Ranking of the Non Utilized Talent Items:...... 62
Table (4.11): Mean, Standard Deviation, Importance and Ranking of the Sustainable Development Items:
.............................................................................................................................................................. 63
Table (4.12): Mean, Standard Deviation, Importance and Ranking of the Environmental Responsibility
Items:.................................................................................................................................................... 64
Table (4.13): Mean, Standard Deviation, Importance and Ranking of the Economic Responsibility Items:
.............................................................................................................................................................. 65
Table (4.14): Mean, Standard Deviation, Importance and Ranking of the Social Responsibility Items: .... 66
Table (4.15): Mean, Standard Deviation, Importance and Ranking of Business Performance Items: ....... 67
Table (4.16): Bivariate Pearson’s Correlation (r) Among Independent Variables, Dependent variables, and
between Independent and Dependent Variables................................................................................... 68
Table (4.17): Multi-Collinearity Test for Main Hypothesis ...................................................................... 70
Table (4.18): Results of Multiple Regressions Analysis (ANOVAa): Regressing Lean Six Sigma Variables
against Business Performance. .............................................................................................................. 71
Table (4.19): Results of Multiple Regressions Analysis (Coefficientsa): Regressing Lean Six Sigma
Variables against Business Performance: ............................................................................................... 71
IX
List of Models
Model (1): Study Model .......................................................................................................................... 7
Model (2.1): Furterer (2004) Model....................................................................................................... 26
Model (2.2): Olsen (2004) Model .......................................................................................................... 26
Model (2.3): Darabi (2007) Model......................................................................................................... 27
Model (2.4): Reijns (2010) Model ......................................................................................................... 27
Model (2.5): Amar and Davis (2010) Model .......................................................................................... 28
Model (2.6): Parast (2011) Model.......................................................................................................... 28
Model (2.7): Chang (2012) Model ......................................................................................................... 29
Model (2.8): Habidin, et. al. (2012) Model............................................................................................. 29
Model (2.9): Zamri, et. al. (2013) Model................................................................................................ 30
Model (2.10): Agus and Iteng (2013) Model .......................................................................................... 30
Model (2.11): Dahman (2013) Model .................................................................................................... 31
X
List of Figures
Figure (4.1): Normal Distribution .......................................................................................................... 69
Figure (4.2): Linearity Test.................................................................................................................... 69
XI
List of Appendices
Appendix (1): Panel of Referees Committee. ........................................................................................ 96
Appendix (2): List of Members of the Jordanian Association of Pharmaceutical Manufacturers 2015.... 97
Appendix (3): Panel of Referees Committee Letter (English Version)................................................... 98
Appendix (4): Participants Letter (English Version).............................................................................. 99
Appendix (5): Thesis Questionnaire (English Version) ....................................................................... 100
Appendix (6): Panel of Referees Committee Letter (Arabic Version) .................................................. 104
Appendix (7): Participants Letter (Arabic Arabic)............................................................................... 105
Appendix (8): Thesis Questionnaire (Arabic Version)......................................................................... 106
XII
The Effect of Lean Six Sigma on the Jordanian Pharmaceutical
Manufacturing Organizations’ Business Performance
Prepared by:
William Hanna Al Kunsol
Supervised by:
Dr. Abdel-Aziz Ahmad Sharabati
Abstract
The study aimed of investigating the effect of Lean Six Sigma dimensions on the Jordanian
Pharmaceutical Manufacturing Organizations’ Business Performance, from the perception of the
managers at the three management levels (top, medium and low).
Descriptive and analytical method was used. The population is the pharmaceutical manufacturing
organizations that are registered in Jordanian Association of Pharmaceutical Manufacturers at 2015. The
study surveyed managers working at these organizations which consist of 14 organizations. To reach the
purpose of this study, data were collected from 120 out of 300 managers during April-May, 2015, by
means of questionnaire. The questionnaire was developed and refined by literature review and panel of
referees committee. Statistical techniques such as descriptive statistics, correlation, and multiple
regressions were used to test the hypotheses.
The results show that there is an agreement on high implementation of Lean Six Sigma variables
among Jordanian Pharmaceutical Manufacturing Organizations, also the relationship between total Lean
Six Sigma and Business Performance is very strong, finally all Lean Six Sigma variables have an effect
on Business Performance of Jordanian Pharmaceutical Manufacturing Organizations except extra
processing
Key Words: Lean Six Sigma, Business Performance, Jordanian Pharmaceutical Manufacturing (JPM)
Organizations.
XIII
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1
Chapter One:
Introduction
1.1. Background:
For a long time, quality has been the human being concern. Over the last few
decades, companies experienced dramatic changes in business environment such as
increasing consumer awareness of quality, rapid technology transfer, globalization
and low cost competition. Therefore, many tools and methods were setup to clarify
the quality, beginning from Quality Inspection (QI) to Quality Assurance (QA),
and Total Quality Management (TQM) that was developed by Japanese companies.
As a result of inability of American companies to rival in global market, American
companies initiated Strategic Quality Management (SQM) that was adopted by
IBM. In fact, Toyota was the first entity to concern about quality, inventory, low
cost, and delivery time to maximize customers’ satisfaction Desale and Deodhar
(2014:286), so it used the Just in Time (JIT) system for production which initiated
by Toyota too then developed to Lean Manufacturing (LM). In the early and mid1980s, Motorola engineers decided that the traditional quality levels of measuring
defects in thousands is not accurate, therefore they developed a system that
measures the defects per million called Six Sigma system. Consequently, they
saved billions as a result of applying the Six Sigma system. As mentioned above
when the organizations used either Lean Production or Six Sigma, they were able
to improve and develop their Business Performance. The question is if we combine
both system (Lean Production and Six Sigma) together what will be the results?
Only very limited authors tackled this point, this study is trying to combine both
Lean Production with Six Sigma and study their effect on organizations’ Business
2
Performance. With adding a new element to Lean Six Sigma which is sustainable
development and study its value added to the Business Performance.
A few years ago new trend was revealed in which companies tried to merge
between Lean Production system and Six Sigma system in which called Lean Six
Sigma, where Salah, et. al. (2010:250) stated that since 1986 “The George Group”
was the first to integrate Lean with Six Sigma. Chinvigai, et. al. (2010:3) said Lean
is a philosophy of continuous improvements while Six Sigma is a way to meet
quality by measuring ability of enterprise to produce perfectly. The aim of Lean
Six Sigma is maximizing shareholders’ value (Laureani and Antony, 2010:688).
Moreover Muthukumaran, et. al. (2013:98) said that in 1997 BAE Systems tried to
combine Lean Management principles with Six Sigma, the company named their
program Lean Sigma Strategy to protect market share in aerospace industry. Dey
(2013:4) explained that despite their different roots, Lean and Six Sigma share
several fundamental common features including a focus on customer satisfaction,
continuous improvement, identification of root causes, and comprehensive
employee involvement. Jovanovic, et. al. (2013:237) stated using Lean Six Sigma
approaches in health care processes is rather a new area for research which it was
found very useful for improving health care processes by researchers and
practitioners. Muhareb and Graham-Jones (2014:1) stated as a managerial process
of continues improvement, Lean Six Sigma considered a process that can improve
products continuously in order to achieve high product quality, competitive costs
and reduced delivery times, that leads to customers’ satisfaction.
The aim of any business is to be profitable and successful but according to
global standards and criteria that should be taking sustainable development as a
critical standard in any business to maintain the planet and resources for the future
generation, from this point sustainable development should be added to Lean
3
Production, Six Sigma and Lean Six Sigma elements as it is balancing among
people, planet and profit (Leonard and Schneider 2014:120-121). Furthermore, Hai
and Mai (2014) concluded that there is a relationship between Lean production and
Corporate Social Responsibility, where the company might increase its efficiency
and minimize environmental effects at the same time.
Therefore, it seems that it is a worthwhile to combine both systems and
study their effect on organizations’ business performance, so this study will
investigate the effect of the combination of both systems on Jordanian
Pharmaceutical Manufacturing Organizations’ (JPMO) Business Performance.
1.2. Problem Statement
Measuring and managing Business Performance is a worldwide concern;
actually it is not limited to organization, industry or country. Yeh, et. al. (2011)
said applying Lean Six Sigma improve organizations’ processes. Soare (2012:193)
stated quality and research within Continuous Improvement displayed a particular
interest in recent years. Abu-Hameeda (2013:19) noted that due to the high
pressure that the production companies including the pharmaceutical ones faced,
and because the Jordanian market now is open for any pharmaceutical products,
these companies forced to use the a quality system including Lean Six Sigma to
produce a high quality goods that increase customers satisfaction that can lead
these organization to achieve the sustainability and the succeed in the markets.
Junankar, et. al. (2014:131) cleared that pharmaceutical industry has to face many
major challenges in order to provide best performance. Koripadu and Subbaiah
(2014:91) explained how Lean and Six Sigma systems can be successfully used for
taking a proactive problem solving management steps with higher profits along
with better efficiency and effectiveness.
4
Therefore the purpose of this research is to investigate the effect of Lean Six
Sigma elements on Jordanian Pharmaceutical Manufacturing Organizations’
(JPMO) Business Performance.
Problem Questions:
The study problem can be perceived by having detailed and scientific
answers to the following questions:
The main question:
1.
Do Lean Six Sigma elements (defect, over production, waiting time,
transportation, inventory, motion, extra processing, non-utilized talent and
sustainability development) affect the Jordanian Pharmaceutical Manufacturing
Organizations’ business performance?
According to Lean Six Sigma elements the main question can be divided
into the following sub-questions:
1.1.
Does defect affect the JPMOs’ business performance?
1.2.
Does over production affect the JPMOs’ business performance?
1.3.
Does waiting time affect the JPMOs’ business performance?
1.4.
Does non-utilized talent affect the JPMOs’ business performance?
1.5.
Does transportation affect the JPMOs’ business performance?
1.6.
Does inventory affect the JPMOs’ business performance?
1.7.
Does motion affect the JPMOs’ business performance?
1.8.
Does extra processing affect the JPMOs’ business performance?
1.9.
Does sustainability development affect the JPMOs’ business
performance?
5
1.3. Study Purpose and Objectives:
This study investigates the effect of Lean Six Sigma on the Jordanian
Pharmaceutical Manufacturing Organizations (JPMOs’) Business Performance.
Therefore, the current study aimed to find the effect of Lean Six Sigma elements
(defect, over production, waiting time, transportation, inventory, motion, extra
processing, non-utilized talent and sustainability development) on JPMO’ Business
Performance. The main objective of this research is to provide sound
recommendations to pharmaceutical organizations, as well as, to other industries
and decision makers regarding the influence of Lean Six Sigma indicators on
organizations’ Business Performance.
1.4. Study Importance:
The current study might be considered as initiative that presents the effect of
Lean Six Sigma on Jordanian Pharmaceutical Manufacturing Organizations. A
better understanding of the effect of Lean Six Sigma elements on the JPMOs’
business performance draws conclusions that can be beneficial not only for JPMOs
but also to other organizations, institutions and decision makers. The content also
may be of an interest to academic studies related to the reporting and decision
making concerning Lean Six Sigma.
Therefore the importance of this study comes from the following scientific and
practical considerations:
1. Highlight on the importance of Lean Six Sigma (LSS) and its applications
on the Jordanian Pharmaceutical Manufacturing Organizations (JPMO) and its
importance in achieving high performance levels that contributes to the
achievement of the long run goals.
6
2. Contribute to the development of the Jordanian Pharmaceutical
Manufacturing Organizations (JPMO) which may lead to maintain these
organizations work effectively that help on the public benefit.
3. Help other researches to talk about Lean Six sigma, and its importance
either on the same industry or for other industries.
4. Help the decision makers to gain the benefits of applying Lean Six Sigma,
and give recommendation of using Lean Six Sigma.
1.5. Study Hypotheses:
Based on the above-mentioned problem statement and its elements, and
according to the study model, the following hypothesis can be developed:
H0: Lean Six Sigma elements do not have a direct significant effect on
JPMOs’ BP, at
0.05.
The main hypothesis can be divided into nine sub-hypotheses according to
the Lean Six Sigma elements (variables) as follows:
H0.1: Defect does not have a direct significant effect on JPMOs’ BP, at
0.05.
H0.2: Over production does not have a direct significant effect on JPMOs’
BP, at
0.05.
H0.3: Waiting time does not have a direct significant effect on JPMOs’ BP, at
0.05.
H0.4: Transportation does not have a direct significant effect on JPMOs’ BP,
at
0.05.
H0.5: Inventory does not have a direct significant effect on JPMOs’ BP, at
0.05.
7
H0.6: Motion does not have a direct significant effect on JPMOs’ BP, at
0.05.
H0.7: Extra processing does not have a direct significant effect on JPMOs’
BP, at
0.05.
H0.8: Non-utilized talent does not have a direct significant effect on JPMOs’
BP, at
0.05.
H0.9: Sustainability development does not have a direct significant effect on
JPMOs’ BP, at
0.05.
1.6. Study Model:
The current research studies the effect of Lean Six Sigma elements on
Jordanian Pharmaceutical Manufacturing Organizations’ Business Performance, as
shown in the study model(1):
Model (1): Study Model
Independent Variables
Lean Six Sigma:
Defect
Over production
Waiting time
Transportation
Inventory
Motion
Extra processing
Non utilized talent
Sustainability Development
(Social, Economic and
Environmental)
Dependent Variable
Business
Performance
Source: From the researcher based on many studies such as: (Olsen, 2004; Habidin, et. al., 2012;
Zamri, et. al., 2013; Agus and Iteng, 2013; Dahman 2013)
8
1.7. Conceptual and Procedural Definitions of Variables:
Lean Manufacturing: Means creating more value for customers with fewer
resources, therefore Lean’s idea is to maximize customer value while minimizing
waste.
Six Sigma: Set of techniques and tools for process improvement, which is a
statistical tool that measures variation in process around its mean.
Lean Six Sigma: Process improvement program that combines two ideas
Lean Production and Six Sigma, relies on a combined team effort to increase
performance by systematically eliminating waste.
Defect: Villa (2010:340) defined it “work that contains errors, or lacks
something necessary”. A faultiness that harms worth or utility, out of specification
that require resources to correct, it will be measured by asking about the effort in
inspecting and fixing defects.
Over Production: Villa (2010:340) cleared it “making more or faster than is
required by the next process”. Producing too much than need or demand that leads
to lower prices and/or unsold goods along with the possibility of not using, it will
be measured by asking about the producing numbers of goods more than needed.
Waiting Time: Villa (2010:340) expressed it an “idle time created when
material, information, people, or equipment is not ready”. An idle time, where an
employee is unable to work because of influences he has no control over, it will be
measured by asking the long of waiting extra time for next process.
Non Utilized Talent: Villa (2010:340) stated that it is the “waste of not
leveraging people’s full talents and capabilities”. Not using people’s competencies,
creative skill abilities
9
Transportation: Villa (2010:340) explained it as it is the “movement of
patients and materials that adds no value”. Transporting items or information that
is not required to perform the process from one location to another, it will be
measured by asking movement of products and people that are not required.
Inventory: Villa (2010:340) defined it by saying that it is “any supply in
excess of what is required”. Product or information that is sitting idle, it will be
measured by asking about work in process that doesn’t being processed.
Motion: Villa (2010:340) stated that it is the “movement of people that does
not add value to the product or service”. People, information or equipment making
unnecessary movements that add no value to the products, will be measured by
asking about the people that move more than needed.
Extra Processing: Villa (2010:340) detailed it an “additional effort that
adds no value to the product or service from the customer’s viewpoint”. Effort that
adds no value to the products, it will be measured by asking about bad product
design quality.
Sustainability
Development:
The
Brundtland
commission
(World
Commission on Environment and Development 1987:8) clarified sustainability as:
“the development that meets the needs of the present without compromising the
ability of future generations to meet their own needs”. Leonard and Schneider
(2014:120-121) gave a simple definition for sustainable development as it is the
balancing the economic, social and environmental system.
Business Performance: Percentage of actual performance compared to
goals, set of management and critical procedures that allows the management of an
organization's performance to accomplish one or more preselected goals.
10
1.8. Study Limitations:
Human Limitation: This study will be carried on managers working at
Jordanian Pharmaceutical Manufacturing Organizations.
Place Limitation: This study will be carried on Jordanian Pharmaceutical
Manufacturing Organizations located in Jordan.
Time Limitation: This study will be carried out within the period between 1st
semester and 2nd semester of academic year 2014/2015.
Study Delimitation: The use of one industry limits its generalizability to
other industries. The study was carried out in Jordan; therefore, generalizing results
of one industry and/or Jordanian setting to other industries and/or countries may be
questionable. Extending the analyses to other industries and countries represent
future research opportunities, which can be done by further testing with larger
samples within same industry, and including other industries will help mitigate the
issue of generalizing conclusions on other organizations and industries. Moreover,
further empirical researches involving data collection over diverse countries
especially Arab countries are needed.
Limitations to data access refer to the fact that data gathering through the
questionnaires and annual reports is controlled to the period of these
questionnaires, which may limit the quality and quantity of the data collected. And
lack of similar studies in Jordan and other Arab countries.
11
Chapter Two:
Conceptual and Theoretical Framework and Previous
Studies
2. Conceptual and Theoretical Framework:
This chapter deals with the conceptual and theoretical framework of Lean
Six Sigma and Business Performance. It starts with reviewing different definitions
of each element. Then, the constituents of each element, after that the chapter
highlights the Business Performance indicators and measurements, followed by the
relationship between Lean Six Sigma and organizations’ Business Performance,
previous models and finally previous studies.
2.1. Definitions of Variables:
It seems that there is no clear cut definition for Lean Production or Six
Sigma, and there is no agreement upon the constituents neither for Lean Production
nor Six Sigma. Lean Production concerns about eliminating waste, while Six
Sigma is measuring tool to improve processes and performance. Merging both
methods together may be more useful than using anyone lonely.
2.1.1. Lean Manufacturing:
Many authors defined Lean Production but the main common thing between
all of them was that Lean tries to minimize waste, as Cavallini (2008:13) noted that
lean production is an administration philosophy dedicated on the decreasing of the
eight wastes. Villa (2010:340) said that Lean Manufacturing is a very powerful
tool in defining and reducing waste. Ngo (2010:25) mentioned that Lean
Manufacturing focusing on solving problems and making changes and it gains
acceptance with businesses of all sizes and markets. Soare (2012:196) defined Lean
12
as a basic, essential philosophy which sets out how to make processes properly.
Enoch (2013:575-576) stated that despite that Lean Manufacturing (LM) and Six
Sigma Methodology (SSM) are separate systems but they have common goals and
end results. The merging of Lean Manufacturing and Six Sigma Methodology into
a batch gave birth to single methodology referred to as Lean Six Sigma which
yields maximum result. Mousa (2013:1140) mentioned two points considered as
weak in lean system the first is “the lean organization may become very
susceptible to the impact of changes, and the second point that “JIT deliveries
cause congestion in the supply chain, leading to delays, pollution, shortage of
workers, etc.” Antunes, et. al. (2013:2) said the goal of Lean Management is to
improve the performance of industrial organizations by following two guidelines:
the elimination of all waste present in all processes of an organization and
placement of humans in the center of the process, taking advantage of their
capacities at all levels. Kumar and Kumar (2013:560) pronounced that in this
millennium the competition in the world market is no longer among companies but
among global supply chains
Desale and Deodhar (2014:286) said: Taiici Ohno who developed the Lean
Manufacturing system as a method of eliminating waste moved the attention of
researchers focus away from the effect of workers’ productivity on craft production
towards a more encompassing production system as a whole.
In summary Lean Manufacturing can be defined as a continuous
improvement tool used to eliminate wastes which can lead to have better
performance results and creating more value for customers with fewer resources,
therefore Lean’s idea is to maximize customer value while minimizing waste.
13
2.1.2. Six Sigm:
Six Sigma has been tackled from different perspectives such as Divoky
(2008:13) who stated that Six Sigma term was presented in the 1980”s by Motorola
in a revolutionary effort to decrease defects to the level of only a few parts per
million. Pulakanam and Voges (2010:149) said: Six Sigma system gained huge
reputation after its adoption by General Electric in the mid-1990s. Varzandeh and
Kamy (2010:511) who defined Six Sigma as a methodology that combine quality
elements and enhances its own special approach to business and supply chain
environment. Tahir (2010:101) said that the voice of customer is the main key to
start a quality process. Radhakrishnan and Sivakumaran (2010:1) stated that “Six
Sigma is a tool used to convert management problem into a statistical problem and
to find a statistical solution then convert it to a management solution”. Mandahawi,
et. al. (2010:95) mentioned that Six Sigma system is essentially used to develop the
performance of an existing process and reduce its variation to reach the final goal
which is the customer satisfaction. Pokharkar, et. al. (2010:1161) stated that Six
Sigma has three main elements: process improvement, Process design/re-design
and process management. Dileep and Rau (2010:27) stated that Six Sigma is about
results, increasing profitability through improved quality and efficiency, this
desired results accomplished through the use of two Six Sigma methodologies:
DMAIC (Define, Measure, Analyze, Improve, Control) and DMADV (Define,
Measure, Analyze, Design, Verify). Weinstein (2010:572) stated that Six Sigma is
a business development approach used to eliminate waste, increase profitability, to
reduce costs linked with humble quality, and to improve the efficiency and
effectiveness of operations.
Jaglan, et. al. (2011:461) pronounced Six Sigma system is a powerful tool
that enables companies to use simple but powerful statistical methods to meet
14
changing in customers’ expectations that help them to sustain in the market.
Radhakrishnan and Balamurugan (2011:639) mentioned despite that it was
introduced in 1980 by engineer M. Harry at Motorola AlSagheer (2011:13) stated
that Six Sigma is a multidimensional method for developing process efficiency and
attaining sustainability. Goh (2011:2) defined Six Sigma as a quality improvement
structure that has been identified in industry for more than a quarter of a century.
Yusr, et. al. (2011:1237-1238) defined Six Sigma as systematic system with
extremely disciplined to increase market share, profitability, customer satisfaction
by using statistical tools that can lead to a high performance. Kaushik (2012:53)
and Micu (2012:505) clarified that letter Sigma ( ) is a Greek alphabet that has
converted to a statistical symbol, which is used to define standard deviation. Vijay
(2012:1) defined Six Sigma as an operational method that speeds up the progresses
in the business system by several statistical features by getting the right projects
led in the right way. Zhang, et. al. (2013:184) stated Six Sigma is a continuous
improvement system depends on statistical tools to cut the process variability
leading to nearly zero defect. Ahmad (2013:346) said that Six Sigma is a
philosophy to continuously decrease variation in processes and aim at the removal
of defects from every service, product and transactional process. Kosina (2013:17)
defined it as a robust continuous improvement approach that depends on statistical
ways. Reosekar and Pohekar (2013:147) mentioned that Six Sigma is an
improvement strategy that yields dramatic reduction in defects or errors or
mistakes in any process. Kabir, et. al. (2013:1045) said that Six-Sigma is a
management philosophy dedicated on rejecting mistakes, rework and waste.
Sharma, et. al. (2013:365) mentioned that since its development at Motorola in the
1980s, many firms including GE, Sony, Honeywell, Caterpillar, and Johnson
Controls have applied Six Sigma and obtained substantial benefits, Six Sigma is a
long-term program. It won’t work well without full commitment from higher
15
management. Jayaraman, et. al (2013:228) ensured that Six Sigma is an active
approach to improve the organization’s performance. Baveja and Jain (2013:48)
showed the Six Sigma’s features that differentiate it from previous quality
improvement from previous quality tools, the features include: a clear attention on
reaching quantifiable and measurable financial earnings, an improved highlighting
on strong and passionate management support and leadership, a special structure of
"Champions," "Master Black Belts," etc. Dhawan (2013:546) described Six Sigma
as a new quality management strategy which is seen as a scientific, systematic,
statistical and smoother method to management innovation.
Khandekar and Sulakhe (2014:52) explained further that Six Sigma is a
statistical measure that measures variation in process around its mean. Mutia, et.al
(2014:125) defined Six Sigma as a statistical term that measures process in terms
of defects, it shows defects in the outputs of a process and comforts one to know
how far the processes differ from perfection. Maleki, et. al. (2013) defined Six
Sigma as a regular strategy to eliminate the errors, wastes, to understand the needs
of the clients and quality problems in order to improve processes. Aleem, et. al.
(2014:95) ensured in their study that Six Sigma emphases on the following:
“business success can be achieved through continuous effort to reduce variation in
process outputs, business processes can be measured, analyzed, improved and
controlled, and finally role of higher management is very precarious in order to
achieve best Quality Improvement results”.
In summary Six Sigma is a statistical system used to reduce of unwanted
variations which led to better performance.
2.1.3. Lean Six Sigm:
A few years ago new trend was revealed in which companies tried to merge
between Lean Manufacturing system and Six Sigma system in which called Lean
16
Six Sigma, where Hajikordestani (2007:18) defined Lean Six Sigma as the
reduction of waste in a system that is producing three or four errors per million
opportunities. Cavallini (2008:13) mentioned that Lean Six Sigma is a business
upgrading structure that integrates Six Sigma methodology with the cost saving
benefits of Lean production. While Laureani and Antony(2010:688) defined Lean
Six Sigma as a business improvement system that purposes to maximize
shareholders’ value by improving quality, speed, customer satisfaction and costs: it
achieves this through merging tools and principles of both systems: Lean and Six
Sigma. Stoiljkovi, et. al. (2011:347) stated both tools are improvement tools, but
one should focus more on those that are more relevant, if wastes need to be
reduced or productivity needs to be increased, then focus on Lean, and if product
variation needs to be measured, then Six Sigma must be applied. Lancaster
(2011:7) mentioned that lean system and Six Sigma system has the same method
which is trying to eliminate waste, but the main difference that Lean does not need
the structure of trained people and leaders to implement.
Zamri, et. al. (2013:98) stated that Lean Six Sigma is a cost decrease
mechanism. Arunagiri and Babu (2013:1) defined Lean Six Sigma as a “technique
and also an effort that is used to minimize the cost of the process by eliminating
the waste in various service sectors”. Mezouari, et. al. (2013:862) stated that Lean
Six Sigma is a set of statistical methods systematized around a rigorous project
management. Muthukumaran, et. al .(2013:99) clarified the advantages of using
Lean Six Sigma as follows: focusing on customer value stream, focusing on
creating a visual workplace, creating standard work sheets, facing work-in-process
inventory, focusing on good housekeeping, process control planning and
monitoring, focusing on reducing variation and achieve uniform process outputs,
focusing heavily on the application of statistical tools and techniques, employing a
17
structured, rigorous and well planned problem solving methodology, facing waste
due to waiting, over processing, motion, over production, etc. Enoch (2013:575)
defined Lean Six Sigma as is a well-structured model based methodology
implemented to develop performances, improve effective leadership, and attain
customer satisfaction and bottom line results. Muhareb and Graham-Jones (2014:1)
considered Lean Six Sigma as a process that improve services or products
continuously in order to obtain high product/service quality, competitive costs and
eliminate delivery times, leading to customer satisfaction .
In conclusion, Lean Six Sigma is method formed by combining two systems
Lean Production and Six Sigma aims to reduce wastes and to develop process
efficiency.
2.1.5. Sustainability development:
The awareness of sustainability development or corporate social
responsibility as some people call it is not a new term in our life. Concern for
society and environment can be tracked to the beginning of time. According to one
of the oldest known written documents, the account of Genesis by the biblical
writer Moses “The LORD God took the man and put him in the Garden of Eden to
work it and take care of it” (Genesis 2, 15), thus implying a balanced approach to
using natural resources and exercising responsibility. The Brundtland commission
(World Commission on Environment and Development 1987:8) clarified
sustainability as “the development that meets the needs of the present without
compromising the ability of future generations to meet their own needs”. Fontaine
(2013) defined corporate social responsibility (CSR) as a mechanism whereby
business monitors and ensures its active compliance with the spirit of the law,
ethical standards, and international norms. Hai and Mai (2014:30) explained the
term corporate social responsibility which was updated by European Commission
18
in 2011 as “a process whereby companies integrate social, environmental and
ethical issues into their business operations and strategy in close interaction with
their stakeholders, going beyond the requirements of applicable legislation and
collective agreements”. Leonard and Schneider (2014:120-121) gave a simple
definition for sustainable development as it is the balancing the economic, social
and environmental system.
2.1.4. Business Performance:
Set of management and critical procedures that allows the management of an
organization’s performance to accomplish one or more pre-selected goals. There
are many indicators that measure it as Darabi (2007:24) defined number of
business performance objectives and subjective measures such as financial or
market based measures like capacity utilization, market share, profitability, service
quality, customer satisfaction, retention and employees’ satisfaction.
2.2. Element of Variables
In this section the study tried to mention what elements and how other
authors and researcher measured Lean Production, Six Sigma, Lean Six Sigma and
Business Performance.
2.2.1. Elements of Lean Production:
Some authors and researchers divided the Lean Production into six elements,
others to seven and most of them considered eight elements such as Cavallini
(2008:13) who identified eight wastes over processing, defects, inventory, motion,
waiting time, over production, transportation, and lack of creativity. Awaritoma
(2010:44) noted seven wastes as follows; processing, inventory, overproduction,
waiting, defects, motion, and transportation. Subramaniyam, et. al. (2011:166)
mentioned seven elements of wastes (excess production and early production,
19
delays, movement and transport, poor process design, inventory, inefficient
performance of a process and making defective items). Mezouari, et. al. (2013:862)
stated three objectives of Lean Manufacturing: eliminate waste; speed and less
resources, and intuitive approach simple problems resolving by using the following
tools: added value analysis, value stream mapping, just in time, Kaizen and Work
methods standardization. Dey (2013:4) defined seven elements of wastes
(overproduction, inventory, defects, transport, motion, over processing and
waiting). Desale and Deodhar (2014:286) mentioned six goals of Lean
Manufacturing: increase output flexibility, reduce cycle times (productivity
improvement), decrease inventories (reduce working capital requirements),
benchmark, rise output value through a systematic consideration of customer
requirements (develop response time to customer) and reduce the share of nonvalue-adding actions.
2.2.2. Elements of Six Sigma:
It seems that almost all authors and researchers agreed on six elements of
Six Sigma such as: Antony (2009:274) found that companies are using Six Sigma
to improve: quality level, customer satisfaction, market share, employees’ moral,
organizational culture, people development and return on investment. Weinstein
(2010:572) stated that Six Sigma is a business development approach used to
eliminate waste, increase profitability, to reduce costs linked with humble quality,
and to improve the efficiency and effectiveness of operations. DeRuntz and Meier
(2010:8) clarified six metrics used to measure Six Sigma results: risk management,
revenue growth, retained revenue, increased capacity, cost reduction, and cost
avoidance. AlSagheer (2011:11) stated that core purposes of Six Sigma were
addressed through themes such as financial achievement, zero defect level and
competition. Yusr, et. al. (2011:1237-1238) defined Six Sigma as systematic
20
system with extremely disciplined to increase market share, profitability, customer
satisfaction by using statistical tools that can lead to a high performance. Yuksel
(2012:77) clarified the measures for evaluating the Six Sigma programs as follow:
avoiding cost drivers, reducing costs, increasing capacity, growing revenues and
risk management.
Reosekar and Pohekar (2013:147) mentioned that Six Sigma lead to improve
customer satisfaction, increased market share, business profitability. Huang
(2013:17) presented six benefits Six Sigma: productivity improvements, cycle time
declines, customer relations improvements, market share increases and defect and
cost reduction. Mezouari, et. al. (2013:862) stated three objectives for Six Sigma
reduce variation, analytical and rational approach, complex problems resolving and
quality by using these tools: voice of customer, tools by steps of DMAIC, statistics
and control cards. Anuradha, et. al. (2013:259) defined four key areas: driving
rapid and sustainable improvement to the business processes, utilizing rigorous
data analysis to understand and minimize variation in key processes, understanding
and managing customer requirements and aligning key processes to achieve those
requirements. Chetiya and Sharma (2014:1751) mentioned seven deliverables:
yield Improvement, system improvement, cost improvement, cycle time reduction,
quality improvement, customer satisfaction, and defect reduction.
2.2.3. Elements of Lean Six Sigma:
It appears that the authors and researchers did not agree on the elements of
Lean Six Sigma yet, where Subramaniyam, et. al. (2011:167) defined five elements
(faster time to market, reduction of poor design, reduction of over design,
reduction in material cost and reduction in product development cost). While Berty
(2011:12) introduced seven types of waste that anyone can face in production
process, and he defined the seven types as follows: transport as moving products
21
not required, inventory as work in process not being processed, motion people
moving more than needed, waiting as waiting extra time for next process, over
production as producing products more than needed and over processing as bad
product design quality and defects as an effort in inspecting and fixing defects.
Also Stoiljkovi, et. al. (2011: 349) classified seven wastes in processes as follows:
non-value added processing, inventory, overproduction, waiting, defects,
movement, and transportation. Arunagiri and Babu (2013:1) mentioned the various
types of waste that decrease the efficiency of the systems such as errors and
defects, wasted motion, unutilized talent, excess inventory processing and
complexity, transportation, delay and wait Time, overproduction. Enoch
(2013:576) identified six factors in the success of manufacturing (small and
medium-size enterprises) SMEs Lean Six Sigma implementation: strong
leadership, management commitment, adequate skilled workforce, awareness and
understanding of Lean Six Sigma, Customer satisfaction, and finally financial
viability and infrastructure.
A few authors tried to study the effect of sustainable development on
organizations’ business performance through Lean Production, Six Sigma and
Lean Six Sigma, such as Clegg (2007) who stated that there is a strong relationship
between six sigma and both economic and social factors. Krambia-Kapardis and
Ioannou (2011) concluded that the utilization of the tools available through Six
Sigma can prove that Six Sigma can be used to save resources and improve quality
and process. Boldt and Franchetti (2013) study aimed to investigate the application
and benefits of conducting an assessment for waste reduction, energy reduction,
and productivity improvements, where Lean Six Sigma has not been used in the
solid waste reduction or environmental protection fields to the extent that it has
been applied in manufacturing and in other sectors. Hai and Mai (2014) concluded
22
that there is relationship between Lean production and Corporate Social
Responsibility (CSR), where the company might increase its efficiency and
develop working condition and minimize environmental effects at the same time,
whereas Lean Production initiatives bring about CSR Interests, mainly in
environmental protection and working condition improvement.
The study used nine elements for Lean Six Sigma by adding the sustainable
development as a new element as there is a strong relationship between the eight
elements of the Lean Six Sigma and the new element depending on the studies
above whereas the sustainable development is trying to balance between the
economic, environmental and social responsibilities in another term balance
people, planet and profit and try to define the relationships between them and their
effect on Business Performance.
2.2.5. Elements of Sustainable Development:
It seems that there is a consensus among researchers, scholars and
practitioners about the elements of sustainable development as economic, social
and environmental responsibility such as Dakov and Novkov (2007:186), Ravet
(2012:2), Leonard and Schneider (2014:120-121). However, Fontaine (2013)
considered corporate social responsibility (CSR) as monitoring and ensuring its
active compliance with the spirit of the law, ethical standards, and international
norms. Moreover, Hai and Mai (2014:30) considered it as an integration of social,
environmental and ethical issues into their business operations and strategy.
In summary, the current study will consider the most popular definition of
sustainable development which consists of the following three dimensions (social,
economic and environmental).
23
Proposed Elements of Lean Six Sigma in the current study:
It has been noticed in the last few years the importance of protecting the
environment and the number of people and committees who are calling to preserve
the environment/planet is increasing day after day. As the aim of Lean Six Sigma
is to eliminate wastes it is important to know how to deal with these wastes in safe
manners without harming the society, people, employees, and the environment
surround us in another word sustainable development is an important variable that
must be added to the elements of Lean Six Sigma as it is very essential and critical
to balance between profit, people and planet to maintain the safety of resources and
to reduce the pollution for the future generation.
2.2.6. Elements of Business Performance:
There was not any clear definition for Business Performance as well as for
its elements where authors and researchers measured it through many perspectives
such as: Jaakkola (2006:11) who noted many ways to determine the performance
such as financial performance, market performance, customer performance or
overall performance. Darabi (2007:24) stated number of business performance
objectives and subjective measures like financial or market based measures like
capacity utilization, market share, profitability, service quality, customer
satisfaction, retention and employees’ satisfaction. Sharabati (2008:45) used
productivity, profitability and market valuation as elements to measure the
business performance.
Zu, et. al. (2008:648) in their study measured a firm
performance outcome on two broad scales, business performance and quality
performance. Quality performance contains seven items such as quality of product,
delivery, process variability, cost of scrap and reworks, equipment downtime,
customer satisfaction, cycle time. Business performance consists of sale, unit cost
of manufacturing, market share, operating income, profit, and return on assets.
24
Vilas-Boas (2009:78) mentioned three elements for business performance; Return
on Assets (ROA), Return on Sales (ROS), and Return on Equity (ROE).
Mandahawia, et. al. (2012:103) used two indicators to measure the performance in
their study production rate and Overall Equipment Effectiveness (OEE). Agus and
Iteng (2013:324) tried to study the effect of Lean Production on the business
performance by measuring the impact on return on sales and return on investment.
August (2013:4077) tried to study the implementation of Six Sigma on the
organization in terms of financial benefits, growth of the company, peoples’
equity, customer satisfaction and productivity.
Based on the above mentioned studies, the current study will consider the
following elements for each variable: defect, over production, waiting time, nonutilized talents, transportation, inventory, motions, and extra process as
independent elements to measure the Lean Six Sigma and the effect of them on the
Jordanian Pharmaceutical Manufacturing Organizations' Business Performance as
the study measured it as one dimension.
The study will measure Business Performance by asking about the
productivity, profitability and market share but Business Performance will be
analyzed as a one dimension.
2.3. The Relationship between Lean Six Sigma and Business
Performance:
Many researchers studied the relationships between Lean Production and
Business Performance, as well as between Six Sigma and Business Performance,
while very researchers studied the relationships between Lean Six Sigma and
Business Performance, for example Olsen (2004) who tried to find the relationship
between Lean Manufacturing management practices and the improving of the
25
financial performance, Parast (2011) in his study tried to investigate the effect of
Six Sigma projects on firm innovation and the effect of Six Sigma on firm
performance, Habidin, et. al. (2012) in their research analyzed the influence of the
relationship between Lean Six Sigma and organizational performance for
Malaysian automotive industries using Structural Equation Modeling (SEM),
Zamri, et. al. (2013) aimed at analyzing of the relationship between Green Lean
Six Sigma (GLSS) and Financial Performance (FP) for Malaysian automotive
industries. Agus and Iteng (2013) paper meant to study the significance of
incorporating Lean Production in the Malaysian manufacturing industry, while
they used Just-In-Time and technology & innovation as elements of the Lean
Production to see their effects on the business performance by measuring return on
sales and return on investment, the moderating effect of the length of lean
adoption.
All the studies above found a positive effect of applying Six Sigma, Lean
Production and Lean Six Sigma on the performance (financial and non-financial)
therefore the study will investigate the effect of applying the Lean Six Sigma
elements on
the business performance for the
Jordan
Pharmaceutical
Manufacturing Organizations.
2.4. Previous Models:
After reviewing related literature, it has been found that not only the
definition and classification of each element was not clear and unified, but
measurements, methods and models were not unified as well. Scholars and
practitioners have used different methods and models to measure Lean Six Sigma
and Business Performance. The following section will briefly discuss the most
widely used methods and models to measure Lean Six Sigma and Business
performance.
26
Furterer (2004) Model: A Lean Six Sigma structure settled by Furterer
(2004) that was developed based on needs local government to implement those
concepts. The majority of the authors framework’s elements were mentioned to the
Quality Award e.g. Business Excellence Model and Malcolm Baldrige National
Quality Award (MBNQA). Thus, the case study of the author research was denoted
the application of some of Lean Six Sigma tools to find solutions for the existing
problem in the Government agency.
Model (2.1): Furterer (2004) Model
Olsen (2004) Model: Tried to find the relationship between Lean
Manufacturing management practices and the improving of the financial
performance. The study tests several research schemes; the first to be examined
was the relationship between lean practice and either operations financial
performance (L-O) or business financial performance (L-B). Next, the relationship
between operations and business financial performance is tested (O-B).
Model (2.2): Olsen (2004) Model
27
Darabi (2007) Model: Studied the impact of market orientation on Business
Performance and website adoption, and built eight hypotheses on her study that can
be seen in the figure below.
Model (2.3): Darabi (2007) Model
Reijns (2010) Model: Showed in his model that there are a number of
independent variables, ‘Factors’ that were examined throughout the thesis, which
influenced the dependent variable ‘Process (re)design’ through a mediating
variable ‘Lean Six Sigma implementation’.
Model (2.4): Reijns (2010) Model
28
Amar and Davis (2010) Model: Amar and Davis (2010) have developed a
Lean Six Sigma model specifically for Indonesian SMEs context that included
training, culture change, external support, employee involvement and owner /
manager commitment and involvement.
Model (2.5): Amar and Davis (2010) Model
Parast (2011) Model: In his study tried to investigate the effect of Six
Sigma projects on firm innovation and the effect of Six Sigma on firm
performance.
Model (2.6): Parast (2011) Model
29
Chang (2012) Model: Developed his model essentially based on MBNQA
(Malcolm Baldrige National Quality Award) model which contained Total Quality
Management elements like leadership, strategic planning, human resource, process
management, education and training, quality tools, customer management, supplier
management and information and analysis. He claimed those elements as essential
factors for SMEs to apply Six Sigma and assembled them into his framework
follow the MAIC (measure - analyze - improve - control) steps.
Model (2.7): Chang (2012) Model
Habidin, et. al. (2012) Model: In their research model meant at analyzing
the influence of the relationship between Lean Six Sigma and organizational
performance for Malaysian automotive industries using Structural Equation
Modeling (SEM).
Model (2.8): Habidin, et. al. (2012) Model
LSS= Lean Six Sigma, OP = Organizational Performance OBSERVED VARIABLE: Leadership (LP), structured improvement
procedures (SIP), quality information and analysis (QIA), supplier relationship (SR), just-in-time (JIT), customer focus (CF),
focus in metric (FM), Financial (FP), customer (CP), internal business process (IBP), and innovation and learning growth (ILG)
30
Zamri, et. al. (2013) Model: Aimed at analyzing of the relationship
between Green Lean Six Sigma (GLSS) and Financial Performance (FP) for
Malaysian automotive industries as they considered leadership focus, training and
education, project management and focus in metrics as elements of Green Lean Six
Sigma.
Model (2.9): Zamri, et. al. (2013) Model
GLSS=Green Lean Six Sigma, LF=Leadership Focus, TE=Training and Education, PM=Project Management, FP=Financial
Performance, FM= Focus in Metrics.
Agus and Iteng (2013) Model: Paper meant to study the significance of
incorporating lean production (LEAN) in the Malaysian manufacturing industry,
while they used Just-In-Time and technology & innovation as elements of the Lean
Production to see their effects on the business performance by measuring return on
sales and return on investment, the moderating effect of the length of lean
adoption.
Model (2.10): Agus and Iteng (2013) Model
31
Dahman (2013) Model: In his study aimed to study suppliers’ relationship,
brokers and distributors relationships and customer relationship as an independent
variables and study their effect on business performance by measuring profitability
and market share.
Model (2.11): Dahman (2013) Model
2.5. Previous Studies:
Due to limited space the study will take only a snapshot from selected
previous studies. The section will focus on interrelationships among Lean Six
Sigma (LSS) components, and their effect on business performance.
2.
Obaidullah (2005) noticed in his study titled: “A Study of Six Sigma
Implementation and Critical Success Factors”, he studied the implementation of
Six Sigma in UK organizations and found that Six Sigma has been applied in both
manufacturing and service organizations in UK and it need an average of four to
nine month to complete full Six Sigma project, also the percentage of the
employees who have been concerned in these projects was 1-20%.
3.
Kateeb (2009) study titled: “The Extent Unplanned Six sigma using
impact in Housing bank for trade and finance”, aimed at applying the Six
Sigma on Housing Bank for Trade and Finance and notice its effect, the study used
the questionnaire as a methodology to collect the data The study sample consists of
32
(120) employee by random sample working in Housing bank for Trade and
Finance and (310) customers. The results showed that there was significant
statistical relationship between Six Sigma changes on mistake reduction,
significant statistical relationship between Six Sigma on time circle reduction, and
many other results.
4.
Percin and Kahraman (2010) study titled: “An Integrated Fuzzy
Multi-Criteria Decision-Making Approach for Six Sigma Project Selection”,
aimed at providing a good insight into the use of an integrated decision-making
methodology in the evaluation of Six Sigma projects. They used three multicriteria decision-making (MCDM) methods by applying a modified Delphi
method, Analytical Hierarchy Process (AHP) and Fuzzy Technique for Order
Preference by Similarity to Ideal Solution (FTOPSIS) methodologies. After the
evaluation criteria of Six Sigma projects were determined by a Modified Delphi
method, the weights of criteria are calculated by applying the AHP method. The
FTOPSIS method was then employed to achieve the final ranking results. A real
case application along with a sensitivity analysis was presented to show the
effectiveness of the proposed methodology.
5.
Reddy and Reddy (2010) study titled: “Process improvement using
Six Sigma – a case study in small scale industry”, aimed at process improving
using Six Sigma at bearing manufacturing facility located at Hyderabad. They
applied the Six Sigma project on improving in the rejection rate of bearing rings.
One of the basic aims of Six Sigma is to reduce variation by statistical thinking.
Various statistical tools and techniques were employed in this study to improve the
operations. The results were that rejection rate of bearing rings has been reduced
from 2.7% to 0.65% and sigma level of process increased from 4.04 to 4.44.
6.
Moosaa and Sajid (2010) study titled: “Critical analysis of Six Sigma
implementation”, aimed at analyzing the critical success and failure factors of
33
implementing Six Sigma in organizations based on case studies, as well as
available
literature.
The
paper
also
showed
useful
conclusions
and
recommendations for strategists, CEO’s and quality managers on how to
implement Six Sigma effectively. It was the result of extensive literature study as
well as many real life Six Sigma implementation processes and observations. Like
usual research outputs, case studies were not part of the paper, rather an exhaustive
review of Six Sigma application phenomenon was carried out in order to identify
key factors involved in it. It mainly identified some important practical
phenomena.
7.
DelliFraine, et. al. (2010) study titled: “Assessing the Evidence of Six
Sigma and Lean in the Health Care Industry”, aimed at assessing the Evidence
of Six Sigma and Lean in the Health Care Industry. The authors directed a
comprehensive literature review to assess the empirical evidence relating Six
Sigma and Lean Systems to improved clinical outcomes, processes of care, and
financial performance of health care organizations, the authors identified 177
articles on Six Sigma and Lean Systems published in the last 10 years. However,
only 34 of them reported any outcomes of the Six Sigma and Lean Systems
projects studied, and less than one-third of these articles included statistical
analyses to test for significant changes in outcomes. The review proved that there
were significant gaps in the Six Sigma and Lean Systems health care quality
improvement literature and very weak evidence that Six Sigma and Lean Systems
improve health care quality.
8.
Mandahawi, et. al. (2010) study titled: “Reducing waiting time at an
emergency department using design for Six Sigma and discrete event
simulation”, aimed at reducing waiting time at an emergency department using
design for Six Sigma and discrete event simulation. Design for Six Sigma (DFSS)
was used to develop a triage process for an emergency department (ED) at an
34
Jordanian hospital, Different performance measures, such as length of stay (LOS)
and waiting time (WT), are hired to evaluate the hospital’s ED performance before
and after the triage process. Discrete event simulation (DES) models were
developed using ProModel software. The models have been proved and confirmed.
The results showed that LOS will be reduced by 34% and WT by 61% after the
triage system is implemented, without any additional staff. Moreover, as a result of
the triage process, the WT sigma level is improved from 0.66 to 5.18, and the LOS
sigma level is improved from 0.58 to 3.09.
9.
Niemeijer, et. al. (2010) study titled: “Quality in Trauma Care:
Improving the Discharge Procedure of Patients by Means of Lean Six Sigma”,
aimed at improving the discharge procedure of patients by means of Lean Six
Sigma. The researchers used the process-focused method of Lean Six Sigma to
decrease hospital stay by developing the discharge procedure of patients in the care
processes and reducing waiting time and waste. The paper used the “Dutch
Appropriateness Evaluation Protocol” to recognize the probable reasons of
unfortunate hospital stay. The average length of stay of trauma patients at the
Trauma Nursing Department at the beginning of the study was 10.4 days. The
paper achieved that 30% of the length of stay was unnecessary. The central reasons
of the unfortunate hospital stay were delays in several areas. The implementation
of the improvement plan decreased almost 50% of the unfortunate hospital stay,
enabling the trauma center to take almost all trauma patients to the Trauma
Nursing Department. After the implementation of the improvements, the average
length of stay was 8.5 days.
10. Singh, et. al. (2010) study titled: “Lean implementation and its
benefits to production industry”, aimed at discussing the implementation process
of lean and its measured assistances for the production industry with the help of
value stream mapping (VSM), VSM process symbols were used to discuss the
35
purpose.
The results showed that reduction in lead time was 83.14 percent,
reduction in processing time was 12.62 percent, reduction in work-in-process
inventory was 89.47 percent, and reduction in manpower requirement was 30
percent. The rise in productivity per operator was 42.86 percent.
11. Kumaravadivel and Natarajan (2011) study titled: “Empirical study on
employee job satisfaction upon implementing Six Sigma DMAIC methodology
in Indian foundry – A case study” aimed at implementing the DMAIC (Define,
Measure, Analyze, Improve, and Control) based Six Sigma Approach to reduce the
frequency of faults and upgrade the sigma level of the sand casting process. The
paper defined a step-by-step guide, using the DMAIC Methodology. The results
showed an overall decline of defect rejection in the process and sigma level of the
process being increased from 3.32 to 3.47.
12. Antony (2011) study titled: “Reflective Practice Six Sigma vs Lean
some perspectives from leading academics and practitioners”, aimed at giving
the fundamental and critical differences between two of the most powerful
methodologies (Six Sigma and Lean) in a process excellence creativity in any
organization. The approach taken was to gather opinions from a number of leading
academics and practitioners from five different countries. It was also important to
guarantee that all participants have a good knowledge and expertise in the field of
both Lean and Six Sigma methodologies. Although both methodologies were
focused on process and quality development, Lean was formalization and
systematization of experience and judgment which was not a feature of Six Sigma.
Lean highlighted speed and waste; however Six Sigma emphasized variation,
defects and process evaluation.
13. Yeh, et. al. (2011) study titled “Applying Lean Six Sigma to improve
healthcare: An empirical study”, aimed at applying Lean Six Sigma to improve
the medical process of acute myocardial infarction. The ‘define, measure, analyze,
36
improve, and control steps’ of Six Sigma find critical-to quality factors and draw
the value stream map to seek out non-value-added activities. The cause and effect
diagram was also employed to analyze the root causes of waste and generate the
improvement project by brainstorming. Reducing waste raised the process cycle
efficiency. The results were that cycle time of the improved door-to-balloon
process decreased by 58.4%. Process cycle efficiency increased from 32.27 to
51.81%, and the average days of hospital stay reduced by 3 days. Such effects
helped save $ 4.422 million in medical resource. The study results indicated that
lean six sigma not only enhanced medical quality but also strengthened market
competitiveness.
14. Kuptasthien and Boonsompong (2011) study titled: “Reduction of
Tombstone Capacitor Problem by Six Sigma Technique: A Case Study of
Printed Circuit Cable Assembly Line”, aimed at representing the implementation
of Six Sigma technique and DMAIC improvement methodology into a mass
manufacturing of printed circuit cables. The result showed that by following the
theoretical Six Sigma technique and DMAIC steps, the defects from major
tombstone capacitor problem could be decreased from 1,154 DPPM to 314 DPPM
and increased 1st yield output from 98.4% to 99.66%.
15. Ali, et. al. (2011) study titled: “Studying and Developing Model of
Six Sigma Implementation in Companies of Yazd House of Industry and
Mine”, aimed at studying and developing model of Six Sigma implementation in
companies of Yazd House of Industry and Mine. Descriptive-survey method was
used. The research sample included 276 top managers (CEOs) chosen randomly
from among 1000 ones. To gather data a 63 material questionnaire (translated and
altered) whose validity and reliability was achieved via existing ways. Descriptive
statistics (charts, frequency, average, Frequency percent, etc) and deductive
statistics (Anova, x2, etc) were used to analyze data. The outputs showed that more
37
than 77 % of the participants suggest that all 11 factors mentioned was
significantly important for implementing Six Sigma in Companies of Yazd House
of Industry and Mine. The factors included top management and leadership, Six
Sigma teams, strategic planning, competitive benchmarking, process management,
human resource development, education and training, quality tools, information
and analysis, customer management and supplier management.
16. Yeh, et. al. (2011) study titled: “Applying Six Sigma to promote selfmanagement ability in health clubs”, aimed at to contribute to a better
understanding of self-management ability in health clubs. The DMAIC (Define,
Measure, Analyze, Improve, Control) model of Six Sigma was used to define
matters faced by employees when they conduct self-management and to construct
an evaluation system for important factors of self-management and to analyze the
reasons for poor self-management. The result showed self-management ability of
employees in health clubs was developed.
17.
(2011) study titled: “Feasibility of application of Six Sigma
and its role in improving the quality of health services in the government
hospitals in Gaza strip from the perspective of senior management”, aimed at
determining Feasibility of application of Six Sigma and its role in improving the
quality of health services in the government hospitals in Gaza strip from the
perspective of senior management by defying the availability of Six Sigma’s key
factors and the role of Six Sigma in developing the quality of the health services.
The researcher used the questionnaire to collect data and the retuning ratio of the
questionnaire was 86.5%. The results showed the administrative, human and
technical requirements as well as the confirmation of the senior management were
important to achieve the Six Sigma role, and it showed that the senior management
agreed that the application of Six Sigma had an influence on improving the quality
health services.
38
18. Bharti, et. al. (2011) study titled: “Six Sigma Approach for Quality
Management in Plastic Injection Molding Process: A Case Study and
Review”, aimed at reviewing the effect of Six Sigma tools in a plastic injection
molding industries along with a case study to improve the quality of nylon-6 bush
(KAMANI BUSH) produced by plastic injection molding process. After using the
DMAIC method, the results were as follows: process improved from 2.38
standard to 5.18 standard and the lower process capability index CPL for over
shrinkage of nylon-6 bush had developed from 0.24 to 1.225, process mean
reduced from 0.1015 to 0.0615.
19. Chakraborty and Tan (2012) study titled: “Case study analysis of Six
Sigma implementation in service organizations”, aimed at implementing Six
Sigma in service organizations to identify critical success factors (CSFs), critical-to
quality (CTQ) characteristics, tools and techniques and key performance indicators
(KPIs), and also to understand the issues emerging from the implementation
process. Exploratory empirical evidence was provided through four in-depth case
studies of organizations mainly in Singapore. They include a hospital, a public
service organization, a consultancy service and a hotel. The major results include
an understanding about the suitability of Six Sigma implementation in service
organizations. Management support and team member support appeared as primary
success factors. The CTQs include time and cost, while use of soft tools instead of
hard statistical tools are preferred by service organizations. At the project level,
KPIs are understood more as CTQs.
20. Mandahawia, et. al. (2012) study titled: “An Application of
Customized Lean Six Sigma to Enhance Productivity at a Paper
Manufacturing Company”, aimed at presenting a process development work
applied at a local paper manufacturing company based on customized Lean Six
Sigma methodologies. The DMAIC (Define, Measure, Analyze, Improve, and
39
Control) methodology and numerous lean tools were used to reorganize.
Production rate and Overall Equipment Effectiveness (OEE) are employed to
assess the performance of the cutting and the printing machines before and after
the DMAIC cycle. The results showed that the production rate increased for
printing machines by 5% and for the cutting machines by 10%. Moreover, the OEE
for the printing and cutting machines has increased by 21.6% and 48.45%.
21. Goriwondo and Maunga (2012) study titled: “Lean Six Sigma
Application for Sustainable Production: A Case Study for Margarine
Production in Zimbabwe”, is a case study used in identifying and effecting
process improvements in margarine manufacturing, The Value Stream Mapping
(VSM) tool was used to draw the Current State Map (CSM) of the margarine
making line, the results showed that The value added ration on the CSM was 39%
and was improved to 94% using the Lean Six Sigma approach. Waste reduction
measures were employed mainly using the Total Productive Maintenance approach
and affecting a pull system. The results obtained are shown in the Future State Map
(FSM) and they specified improvements in cycle times of up to 86%.
22. Chung (2013) study titled: “An Application of Six Sigma
Methodology in Agarwood Tissue Culture”, aimed at optimize agarwood
adventitious buds induced incidences and growth numbers. The study used design
of experiment (DOE) and response surface methodology (RSM). The results
showed that, the combination of 4.0 parts per million (ppm) Thidiazuron (TDZ)
and 0.5 (ppm) Benzylaminopurine (BA), without activated carbon, had the best
effect of adventitious bud induced incidence up to 21.75%, and adventitious bud
growth number up to 24.8, improvements of 35.29% and 42.78%, respectively.
The results confirmed that using the Six Sigma methodology improve the induction
of agarwood tissue culture adventitious buds, promote the blooming of agarwood
in large numbers, and further realize agarwood restoration.
40
23. Enoch (2013) study titled: “Lean Six Sigma Methodologies and
Organizational Profitability: A Review of Manufacturing SMEs in Nigeria”,
aimed at investigating the influence of Lean and Six sigma methodologies (LSS)
on the profitability of Manufacturing small and medium size enterprises (MSMEs)
in Nigeria. The population of the study contained of 450 manufacturing SMEs with
2250 employees. The sample frame was made up of 225 MSMEs with 1026 staff
selected randomly upon which copies of structured questionnaire were
administered. 1002 valid responses received were analyzed. Pearson product
moment correction (PPMC) confirmed the formulated propositions with negative
association between awareness, LSS implementation and achievement critical
success factors (CSFs) and the profitability level of MSMEs. The result showed
that LSS implementation among MSMEs in Nigeria is almost none existing and
has no influence on the profit level. The study recommended that CEOs of MSMEs
should start training on LSS to allow them to provide a strong leadership.
24. Maleki, et. al. (2013) study titled: “Reducing Waiting Time in
Patients Undergone Spinal Surgeries at Operation’s room of Shohada-yeTajrish Hospital using Six Sigma Model” aimed at evaluate the influence of Six
Sigma on reducing of waiting time for starting operation surgery for patient of
spine surgery in operating room of Shohada-ye- Tajrish Hospital in Tehran. The
study was conducted with the benefit of Six Sigma model in four stages, with
qualitative and quantitative methods. The sample size was 198 persons. Data
collection tools were: Chronometer clock, time measurement forms, and surgery
operation registration notebooks. The results showed that Average waiting time for
surgery reduction for patient with lumber laminectomy 51.4 minutes with standard
deviation of 21.2, in Cage implant 62.6 with standard deviation of 18.3, and in
Lumbar fusion surgery 51.6 with standard deviation of 20.7 has been reached after
implementation of Six-Sigma.
41
25. Zaman, et. al. (2013) study titled: “Study of feasibility of Six Sigma
implementation in a manufacturing industry: a case study”, aimed at
discussing the implementation of Six sigma approach in decreasing refusal in a
welding electrode manufacturing industry. The Six-sigma DMAIC approach was
used. The result showed reducing in the Defect Per Million Output (DPMO) from
28356.96 to 1666.67 and increasing the sigma level from 3.41 to 4.43, without any
huge capital investment.
26. Khaidir, et. al. (2013) study titled: “Six Sigma Practices and
Organizational Performance in Malaysian Healthcare Industry”, aimed at
reviewing structural analysis the Six Sigma and organizational performance (OP)
in Malaysian healthcare industry. A conceptual model using Structural Equation
Modeling (SEM) was used to study the relationship. The study exposed Six Sigma
(SS) practices enhance performance improvement in United States manufacturing
industry, and there is positive and direct strong relationship between SS and
financial performance in Malaysian automotive industry and using SS on
operations of retail pharmacy is very applicable and helping to streamline and
integrate the pharmacy process flow. Samples were selected from the list of
hospital in Malaysian. In achieving the objectives of the study, the Malaysian
private hospitals were selected as the population. The structured questionnaire as
sampling method was used. Structural Equation Modeling (SEM) techniques were
utilized to perform the required statistical analysis of the data from the survey.
Exploratory factor analysis, reliability analysis and confirmatory factor analysis to
test for construct validity, reliability, and measurements loading were performed.
Having analyzed the measurement model, the structural model was then tested and
confirmed. The statistical Package for the Social Sciences (SPSS) version 17 was
used to analyze the preliminary data and provide descriptive analyses about thesis
42
sample such as means, standard deviations, and frequencies. SEM using AMOS
6.0 will use to test the measurement model.
27. Kumara and Khandujaa (2013) study titled: “Application of Six-Sigma
Methodology in small scale industries (SSI): A Case Study”, aimed at help to
improve the six-sigma area of application in all types of organization, six-sigma
application in Hydraulic jack manufacturing industry in small scale industries
(SSI) environment, DMAIC methodology was used which is help to decrease the
rejection rate of pump head of hydraulic jack set by removing error in process &
method of operation. Statistical techniques Gauge R & R method, two sample test,
Factorial method, control charts, Process capability analysis before & after
application of six-sigma used. Applying of six-sigma in SSI helped to improve Zbench Sigma level from 2.21 sigma to 5.64 sigma and cost saving of 0.01929
million/annum.
28. Venkatesh, et. al. (2013) study titled: “Outcome of six sigma
implementation a case study of manufacturing industry”, aimed at
investigating whether Six Sigma has contributed to the improvement of the
organization in terms of growth of the company, financial benefits, peoples‘
equity, productivity and customer satisfaction, and too study whether managers
and workers differ in their opinions towards implementing Six Sigma. Sample
Population consisted of all 26 employees who were involved in Six Sigma
implementation. The respondents included both managers and workers who were
trained in Six Sigma implementation. Those who were trained in Six Sigma
included master black belt, black belts and green belts. Out of 26 employees 16
belonged to worker level and 10 belonged to managerial level. The data is
collected using questionnaire method. Questionnaire was designed around various
parameters that contributed for financial benefits and market growth. It was
observed through the study that Six Sigma has contributed to the improved
43
financial status, productivity and customer satisfaction. However its contribution
towards the welfare of the work force and growth of the company is not
significant.
29. Bashir and Al-Tawarah (2013) study titled: “Implementation of Six
Sigma on Corrective Maintenance Case Study at the Directorate of
Biomedical Engineering in the Jordanian Ministry of Health”, aimed at
presenting a process improvement study applied on the Downtime of the medical
equipment during the maintenance work in the Jordanian of Health Hospitals,
based on customized Six Sigma methodology- DMAIC- (Define, Measure,
Analyze, Improve and Control). Data was collected from different locations and
different equipment to study the problem and make the necessary actions to resolve
or reduce downtime. Obtained results indicated that the downtime reduced by 35%
by introducing a new procedure to the clinical engineer to used when dealing with
any medical equipment for maintenance work.
30. Bao, et. al. (2013) study titled: “A multicenter study of the
application of Six Sigma management in clinical rational drug use via
pharmacist intervention”, aimed at determining the core reasons of outpatient
irrational prescription drug use before and after pharmacist interventions in 6 large
scale hospitals after investigating and to promote rational clinical drug use. The 5step DMAIC method (defines measure, analyze, improve, control) in Six Sigma
management was used. The statistical software package SAS9.1.3 was used to
analyze the results. The study results were 8.56% and 4.46% (P < 0.001), the Z
value increased from 2.82 to 3.01. The study showed that Six Sigma management
will be able to mechanize and enhance hospital management, thereby eventually
improving service quality.
31. Xu, et. al. (2013) study titled: “Case Study on the Lean Six Sigma
Management for Information Technology Service Management Project of G
44
Commercial Bank”, aimed at analyzing the current state of information system in
G bank and also the its changes. The Lean Six Sigma management theory used to
optimize the management of alteration and production in the G bank’s ITSM.
Authors tried to reach the four goals with DMAIC: optimizing the process and also
improving the internal work efficiency. The second one is decreasing the variation
and the error rate and also improving the system availability. The third one is to
strengthen the business interaction and have the IT value been reflected preferably.
The fourth one, the overtime time can be decreased and employee satisfaction can
be enhanced at the same time. Specific measures were as follows: 1) Long-term
process ability had been set up; 2) The operation control plan had been updated
and implemented; 3) Process had returned to process owner for maintenance; 4)
The team final report, including the future improvement opportunities
confirmation, etc.
32. Edaily (2014) study titled: “The Possibility of Applying Six Sigma
and its Role in Cost Reduction and Increasing Competition – Applied Study of
Advanced Technology Companies of Recycling Used Materials”, aimed at
showing the important role of Six Sigma system and its use in managing Cost
decrease of defect production, in order to increasing profits and improving the
competitiveness. The researcher took "The Advanced Technologies for Consumed
Materials Recycling", as a case study on one of the Jordanian Industrial Companies
in Zarqa Governate in Jordan. The result was that the company didn’t currently
apply the Six Sigma system and its tools. Thus, this study showed that if the
company decided to adopt Six Sigma and its tools, it would positively reflect on
reducing waste production, improve efficiency and productivity, decreasing the
operational costs, and developing the overall company's competitiveness in the
market. Moreover, it is noted that, if the Six Sigma method and tools was applied,
then the level of Sigma will further increase from 3.1 to 3.9. Furthermore, the
45
waste production would be reduced from 11.55 % to 3.5 %. Logically, that would
lead to additional profits for the company by JD 61825.12.
33. Dwivedi, et. al. (2014) study titled: “Six Sigma; As Applied in Quality
Improvement for Injection Moulding Process”, aimed at defining the Black
specks’ problem, which decreases quality, due to defects in manufactured
quantities, and to suggest measures for the improvement in the Injection Moulding
operation using Six-Sigma DMAIC methodology. In order to study the problem a
research has been carried out by studying the literature review on Total Quality
Management (TQM), Six Sigma and other references for this analysis and research
method.
34. Pranoto and Nurcahyo (2014) study titled: “Implementation of
Integrated System Six Sigma and Importance Performance Analysis for
Quality Improvement of HSDPA Telecommunication Network and Customer
Satisfaction” aimed at improve quality of High Speed Downlink Packet Access
(HSDPA) network and customer satisfaction, by using the Six Sigma DMAIC
cycle and Importance Performance Analysis (IPA) as control, The result showed
that the average change in Call Setup Success Rate (CSSR) increased from 98,44%
to 99,43% and sigma level from 3.6< <3.7 to
>4,0. And the result of IPA
measurement showed performance score is 3.62 greater than importance score
3.56.
35. Junankar, et. al. (2014) study titled: “Six Sigma Technique for Quality
Improvement In Valve Industry”, aimed at decreasing operational wastages
using Six Sigma methodology (DMAIC) This study reported declining in defects
in manufacturing industry through reduction in DPMO (Defects per Million
Opportunities) from 1401 to 603.47, and the Sigma Level upgraded from 4.5 to
4.8.
46
From the literature reviews above, it can be concluded that all organizations
can be benefited from using lean manufacturing or Six Sigma, as Ngo (2010) study
provided a closer insight into the status of the applications of business
improvement programs, Lean and the combined Lean Six Sigma in New Zealand
market where thirty three manufacturing firms in New Zealand were involved, and
this study will focus on the Jordanian Pharmaceutical Manufacturing
Organizations. And Khaidir, et. al. (2013) in his study showed that effect of Six
Sigma on organizational performance by taking these four indicators for the Six
Sigma (leadership, costumer focus, structured improvement procedure and focus in
metric), while this study will investigate the eight Lean Six Sigma elements as they
were mentioned before the but it is expected that the benefit will be more if both
are used together. Therefore, the current study will explore the effect of lean Six
Sigma on the Jordanian Pharmaceutical Manufacturing Organizations' Business
Performance.
2.6. Expected Contributions of the Current Study as Compared with
Previous Studies:
1- Lean Six Sigma concept: The current study expects that it will increase
awareness about the role of Lean Six Sigma in organizations’ Performance.
2- Purpose: Most of the previous research works were conducted to
measure and manage Lean Six Sigma from the financial perspective, and to
increase the organizations’ Lean Six Sigma indicators disclosure. Few studies were
carried out to study the effect of the Lean Six Sigma elements on the
organizations’ Business Performance.
47
3- Environment: Most previous studies have been carried out in different
countries outside the Arab region. The current study will be carried out in Jordan,
as one of the Arab region countries.
4- Industry: Few researches about Lean Six Sigma carried out about
pharmaceutical industry. The current research is dedicated to pharmaceutical
industry only.
5- Methodology: Most previous studies were based on annual reports of
different organizations and industries. The current study is based on perception.
6- Variables: Most of previous studies and researchers take eight elements
of Lean Six Sigma, while in this study new element was added which is the
sustainable development.
7- Population: Most all previous researches considered public shareholders
organizations that were listed in the stock markets, while the current study covered
both public and private shareholders organizations.
8- Comparison: The current study will compare the results with the results
of previous studies mentioned earlier to highlight similarities and differences that
might be there.
48
Chapter Three:
Study Methodology (Methods and Procedures):
3.1. Study Approach and Design:
The current study is considered as a descriptive and analytical study. It aims
at studying the effect of Lean Six Sigma elements on Jordanian Pharmaceutical
Manufacturing Organizations’ business performance. It starts with literature review
and experts’ interviews to improve the currently used measurement model and
explore the Lean Six Sigma profile of the Jordanian Pharmaceutical Manufacturing
Organizations. Then, a panel of judges will be conducted to confirm the items to be
included in the questionnaire will be carried out. Finally, the survey will be carried
out and the data will be collected from the managers working at Jordanian
Pharmaceutical Manufacturing organizations, then the data will be tested through
the SPSS 20 focusing on the correlation among Lean Six Sigma variables and their
relationships with Jordanian Pharmaceutical Manufacturing Organizations’
business performance. Finally, the results were compared with previous researches
work.
3.2. Study Population, Sample and Unit of Analysis:
The pharmaceutical manufacturing organizations that are registered in
Jordanian Association of Pharmaceutical Manufacturers at 2015 in Jordan are 14
organizations. All pharmaceutical manufacturing organizations were chosen and
surveyed by using questionnaire to collect the primary data and examine the topic
of Lean Six Sigma and its effect on the organizations’ business performance, thus
negating any need for sampling.
49
Unit of Analysis: The survey unit of analysis is composing of all managers
at three levels (top, middle and low level) who are working at pharmaceutical
manufacturing organizations and they are approximately 300 managers, and who
will be available at the time of distributing the questionnaires and who will fill it.
3.3. Data Collection Methods (Tools):
The data that will be used for fulfilling the purposes of the study can be
divided into two groups: secondary and primary data as follows:
Secondary Data: Data was collected from different sources such as journals,
working papers, researches, thesis, articles and worldwide Web and Jordanian
Pharmaceutical Manufacturing organizations.
Primary Data: Data was collected by extensive survey by questionnaire
Tool of Collecting Primary Data:
The proper tool was chosen and tested to suit the current study and to match
the study hypothesis and research model. Basically the original questionnaire items
were developed relying on previous studies. Then, the questionnaire was revised
and validated by an academic panel of judges and references. Then, the
questionnaire was also reviewed and validated by professional and highly
experienced experts in the field of pharmaceutical manufacturing organizations.
Questionnaire Variables:
The questionnaire variables are divided into two parts:
1-
First part is composing of demographic characteristics related to
gender, age, academic qualification, position, department, and experience.
2as follows:
Second part is composing of both independent and dependent variables
50
a-
Independent Variables (Lean Six Sigma): Based on literature review
such as Stoiljkovi, et. al. (2011) and Arunagiri and Babu (2013), the current study
has identified nine variables that contribute to Jordanian pharmaceutical business
performance (defect, over production, waiting time, transportation, inventory, extra
motion, extra process, non-utilized talent and sustainability development
(environmental, economic and social responsibility) each variable was measured
by 5 - 6 items and the total were 57 items (from item 1 to item 57 in the
questionnaire).
b-
Dependent Variable (Business Performance):
Based on literature
review such as: Darabi (2007) and Sharabati (2008), the current study took it as
one dimension the total items were 24 items (from item 58 to item 67 in the
questionnaire).
All items were measured by five-point Likert-type scale to take the
advantage of respondent's perceptions, varying from value 1 (strongly agree) to
value 5 (strongly disagree) that was used through the study questionnaire.
Panel of judges and referees: panel of judges and referees were selected
from both well-known academicians, and professional with highly experienced
leaders in the pharmaceutical manufacturing organizations.
3.4. Data Collection and Analysis:
Research data have been collected during the time period of April to the first
week of May at 2015. The targeted pharmaceutical manufacturing organizations
were 14 organizations. This study tried to survey all these organization but only 7
organizations had been reached due to several reasons such as preoccupation with
auditing from internal and external committees, the crowded manufacturing
schedule for the next three months, and the lack of cooperation of some
51
organizations. Questionnaires were handed to 180 managers out of 300 managers
working at JPMO i.e. 60%. 128 questionnaires were collected which form 71.1%
response rate of total units of analysis. Eight questionnaires were abandoned due to
incomplete statements from respondents. Consequently, the valid questionnaires
were 120 out of 128 collected questionnaires which represent 66.6% of total units
of analysis.
SPSS 20 was used to analyze the effect of Lean Six Sigma on business
performance at pharmaceutical organizations.
1. Validity Test:
Two methods were used to confirm the content validity: First content
validity, multiple sources of data (as journals, working papers, researches, thesis,
articles and worldwide Web and Jordanian Pharmaceutical Manufacturing
organizations, expert interviews) was used to set and refine the model and
measures. Second face validity, panel of judges was carried out to modify the
finale form of the questionnaire.
2. Reliability Test (Cronbach’s Alpha):
The reliability is evident by strong Cronbach’s alpha coefficients of internal
consistency. Reliability analysis for variables is show in table (3.1) below.
If Alpha Coefficients is more than 60% will be accepted (Sekran 2003). As
shown in table Cronbach's alpha coefficients for variables are ranging between
0.627 and 0.8127. Except transportation and Inventory were 0.573 and 0.557.
52
Table (3.1): Reliability Test:
No.
Variable
No. of Items
1 Defects
5
2 Over Production
5
3 Waiting Time
5
4 Transportation
5
5 Inventory
5
6 Motion
5
7 Extra Processing
5
8 Non Utilized Talent
5
9 Environmental Responsibility
6
10 Economic Responsibility
5
11 Social Responsibility
6
12 Sustainable Development
3
13 Lean Six Sigma
9
14 Business Performance
10
Cronbach's Alpha
0.765
0.684
0.701
0.573
0.557
0.812
0.642
0.683
0.744
0.665
0.683
0.627
0.808
0.748
The importance is calculated based on the following criteria: 5-1/3 = 1.33.
So low, medium and high degree of presence will be considered based on the
below:
The Importance of each item will be calculated as follows:
(5-1)/3 = 1.33.
Three levels of existence will be considered according to the following
intervals:
1-
Low degree of existence if the value lies between 1 and 2.33 (1 + 1.33
= 2.33).
2-
Medium degree of existence if the value lies between 2.34 and 3.66
(2.33+ 1.33 = 2.34-3.67).
3-
High degree of existence if the value lies between: 3.67 up to .
While the ranking will be based on t-value.
53
Chapter Four:
Analysis and Results
4.1. Introduction:
The initial goal of this research is to study the effect of Lean Six Sigma on
business performance at Jordanian pharmaceutical manufacturing organizations. In
this chapter the results and related analysis will be showed. In addition, it will
focus on the significant results with its statistical indications. First, the study
variables will be analyzed and described from statistical point of view by using
means, standard deviations, t-values, importance and ranking. Second, the chapter
will represent correlation among independent variables, then their correlation with
dependent variables. Finally, study hypothesis will be tested by multipleregressions.
4.2. Respondents’ Demographic Description:
Table (4.1) below shows the general characteristics of the respondents in
terms of gender, age, education, position, division, and years of experience:
1. Gender: Most of the respondents are males with 71 (59.2%) while female
rated 49 (40.8%). This indicates that most of the directors and managers in Jordan
are males; due the traditions and culture.
2. Age: The highest percentage of the respondents’ ages were above 35-45
(52.5%), then above 25-35 (29.2%), then ages above 45-55 (15.8%) and ages
above 55 (2.5%). This indicates that the average of the ages of directors and
manager are above 35 – 45.
54
Dimension
Gender
Age
Education
Position
Division
Years of
Experience
Table (4.1): Demographic Analysis
Frequency
71
Male
49
Female
120
Total
35
25-35
63
Above 35-45
19
Above 45-55
3
Above 55
120
Total
3
Diploma or less
86
Bachelor
29
Master
2
Doctorate
120
Total
21
High level
75
Middle level
24
Low level
120
Total
28
Production
15
R&D
14
Marketing
63
Others
120
Total
12
Less or equal 5
70
Above 5-10
26
Above 10-15
12
Above 15
120
Total
Percent
59.2
40.8
100.0
29.2
52.5
15.8
2.5
100.0
2.5
71.7
24.2
1.7
100.0
17.5
62.5
20.0
100.0
23.3
12.5
11.7
52.5
100.0
10.0
58.3
21.7
10.0
100.0
3. Education: Most of the respondents were holding the BSc degree 86
(71.7%), the master degree 29 (24.2%), then diploma 3 (2.5%) and finally the PhD
2 (1.7%).
4. Position: This study divided the position into 3 levels high, middle and
low management, most of the respondents were from the middle level 75 (62.5%),
from the upper level were 21 respondents (17.5%) and from the low level 24
respondents (20%).
5. Division: This study divided the division into 4 groups; the majority of
the respondents were from other department such as quality, finance and operation
55
as we can consider it administration 63 (52.5%), then production 28 (23.3%),
research and development15 (12.5%) and finally marketing department 14
(11.7%).
6. Years of Experience: The majority of the respondents’ experiences were
having above 5 – 10 years of experience 70 (58.3%) then those with above 10 –15
years of experience 26 (21.7%), followed by less or equal than 5 years of
experience 12 (10%) and more than 15 years of experience 12 (10%).
4.3. Study Variables Analysis (Descriptive Analysis):
This part analyzes and describes the independent and dependent variables
from statistical point of view including means, standard deviations, t-values,
ranking and importance.
Independent Variables (Lean Six Sigma):
Table (4.2) shows that the average means of the respondents’ perception
about the degree of implementing of the Lean Six Sigma variables are ranging
from 4.01 to 4.64, with standard deviation that ranges from 0.31 to 0.54. Such
results show that there is an agreement on high implementation of Lean Six Sigma
variables. The mean of the total Lean Six Sigma variables is 4.34 with standard
deviation 0.25 which indicates that there is an agreement on high presence of these
variables. Finally, the overall result indicates that there is a significant
implementation of the Lean Six Sigma among Jordanian Pharmaceutical
Manufacturing Organizations, where (t=59.08>1.96). This indicates that the
directors and managers working at Jordanian Pharmaceutical Manufacturing
Organization realize the importance of the implantation of the Lean Six Sigma
variables.
56
No
1
2
3
4
5
6
7
8
9
Table (4.2): Mean, Standard Deviation, Importance and Ranking of Lean Six Sigma
Variables:
Item
Mean Std. Deviation t-Value Importance Rank
Defects
4.64
0.37
47.93
High
2
Over Production
4.49
0.37
43.98
High
4
Waiting Time
4.40
0.43
35.84
High
5
Transportation
4.43
0.35
44.13
High
3
Inventory
4.52
0.31
53.60
High
1
Motion
4.29
0.54
26.23
High
9
Extra Processing
4.04
0.41
27.89
High
7
Non Utilized Talent
4.18
0.49
26.42
High
8
Sustainable Development
4.08
0.35
33.25
High
6
Environmental Responsibility
4.13
0.47
26.24
High
Economic Responsibility
4.10
0.49
24.64
High
Social Responsibility
4.01
0.46
24.37
High
Lean Six Sigma ( Independent variables)
4.34
0.25
59.08
High
t-Tabulated = 1.96
Defect:
Table (4.3) shows that the means of the respondents’ perception about the
degree of the implementation of defect items are ranging from 4.55 to 4.71with
standard deviation that ranges from 0.47 to 0.50. Such results indicate that there is
an agreement on high applying of defect variable items.
No.
1
2
3
4
5
Table (4.3): Mean, Standard Deviation, Importance and Ranking of the Defect Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company is keen on the quality of raw
4.71
0.47
39.76
High
1
materials
The company uses the appropriate means of
4.61
0.50
35.02
High
4
transportation
The company is committed to follow the
instructions and formulas for manufacturing
4.68
0.48
37.91
High
3
such as mixing in approved precise
proportions of materials
The company is keen to follow in time the
4.55
0.57
29.44
High
5
production processes
The company is keen to pay attention to the
4.67
0.47
38.87
High
2
cleanliness of the internal environment
Defect
4.64
0.37
47.93
High
t-Tabulated = 1.96
The average mean of the total defect variable items is 4.64 with standard
deviation 0.37, which indicates that there is an agreement on high implanting of
57
this variable. Finally, the overall result indicates that there is a significant degree of
implantation of the defect variable at Jordanian Pharmaceutical Manufacturing
Organizations, where (t=47.93>1.96). This indicates that the directors and
managers working at Jordanian Pharmaceutical Manufacturing Organization
realize the importance of reducing the defect.
Over Production:
Table (4.4) shows that the average means of the respondents’ perception
about the degree of the implementation of over production items are ranging from
4.37 to 4.65, with standard deviation that ranges from 0.47 to 0.61. Such results
indicate that there is an agreement on high applying of over production variable
items. The mean of the total over production variable items is 4.49 with standard
deviation 0.37 which indicates that there is an agreement on high implanting of this
variable. Finally, the overall result indicates that there is a significant degree of
implantation of the over production variable on the Jordanian Pharmaceutical
Manufacturing Organizations, where (t=43.98>1.96).
Table (4.4): Mean, Standard Deviation, Importance and Ranking of the Over Production
Items:
No.
Item
Mean Std. Deviation t-Value Importance Rank
The company is keen on the proper
6
4.37
0.59
25.42
High
5
appreciation of the order quantity
The company emphasizes the orders before
7
4.46
0.51
31.12
High
2
starting the production
The company is keen to ensure the
8 effectiveness and safety of the product
4.65
0.47
38.03
High
1
compared to competitors' products
The company is keen on estimating raw
9
4.53
0.57
29.07
High
3
materials required for the production
The company is keen to manage machines
10
4.45
0.61
25.72
High
4
efficiently and effectively
Over Production
4.49
0.37
43.98
High
t-Tabulated = 1.96
58
This indicates that the directors and managers know the importance of this variable
and its effect on the business performance
Waiting Time:
Table (4.5) shows that the average means of the respondents’ perception
about the degree of the implementation of waiting time are ranging from 4.30 to
4.57, with standard deviation that ranges from 0.51 to 0.72. Such results indicate
that there is an agreement on high applying of waiting time variable items. The
mean of the total waiting time variable items is 4.40 with standard deviation 0.43
which indicates that there is an agreement on high implanting of this variable.
Finally, the overall result indicates that there is a significant degree of implantation
of the waiting time variable on the Jordanian Pharmaceutical Manufacturing
Organizations, where (t=35.84>1.96). This indicates that the directors and
managers know the importance of this variable and its effect on the business
performance.
No.
11
12
13
14
15
Table (4.5): Mean, Standard Deviation, Importance and Ranking of the Waiting Time
Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company works on the availability of raw
4.30
0.72
19.65
High
5
materials in a timely manner
The company is keen on the effectiveness of
4.30
0.61
23.23
High
3
the production processes
The company emphasizes on the periodically
4.47
0.72
22.48
High
4
maintenance of machinery
The company set priorities for manufacturing
4.57
0.51
33.63
High
1
The company takes into consideration the
speeding up decision-making when the need
4.41
0.60
25.86
High
2
arises
Waiting Time
4.40
0.43
35.84
High
t-Tabulated = 1.96
Transportation:
Table (4.6) shows that the average means of the respondents’ perception
about the degree of the implementation of transportation items are ranging from
59
4.22 to 4.58, with standard deviation that ranges from 0.51 to 0.68. Such results
indicate that there is an agreement on high applying of best transportation variable
items. The mean of the total transportation variable items is 4.43 with standard
deviation 0. 35which indicates that there is an agreement on high implanting of this
variable. Finally, the overall result indicates that there is a significant degree of
implantation of the transportation variable on the Jordanian Pharmaceutical
Manufacturing Organizations, where (t=44.13>1.96). This indicates that the
directors and managers know the importance of using the appropriate
transportation.
No.
16
17
18
19
20
Table (4.6): Mean, Standard Deviation, Importance and Ranking of the Transportation
Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company is keen to provide alternatives
4.22
0.68
19.52
High
5
for transport operations in case of emergency
The company confirms the accuracy of the
4.41
0.51
30.42
High
2
packaging operations
The company is committed to the customs
4.58
0.58
29.52
High
3
procedures required to facilitate transfers
The company is keen on using appropriate
4.51
0.53
31.14
High
1
means of transportation
The company owns the appropriate skills for
4.44
0.59
26.80
High
4
workers to carry out handling during transport
Transportation
4.43
0.35
44.13
High
t-Tabulated = 1.96
Inventory:
Table (4.7) shows that the average means of the respondents’ perception
about the degree of the implementation of inventory items are ranging from 4.31 to
4.66, with standard deviation that ranges from 0.49 to 0.56. Such results indicate
that there is an agreement on high applying of best inventory methods variable
items. The mean of the total inventory variable items is 4.52 with standard
deviation 0.31which indicates that there is an agreement on high implanting of this
variable. Finally, the overall result indicates that there is a significant degree of
60
implantation of the inventory variable on the Jordanian Pharmaceutical
Manufacturing Organizations, where (t=53.60>1.96). This indicates that the
directors and managers are paying attention to apply the best ways to store their
inventory.
No.
21
22
23
24
25
Table (4.7): Mean, Standard Deviation, Importance and Ranking of the Inventory Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company is keen to provide the
appropriate storage conditions (temperature 4.54
0.50
33.77
High
2
and humidity)
The appropriate skills for workers to perform
the storage business become available in the 4.31
0.53
27.12
High
5
company
The company is keen to provide the
4.53
0.56
29.82
High
4
appropriate handling tools (forklift)
The company emphasizes the appropriate
arrangement of the material inside the 4.66
0.49
37.10
High
1
warehouse
The company is committed to conduct the
4.57
0.51
33.63
High
3
various inventories
Inventory
4.52
0.31
53.60
High
t-Tabulated = 1.96
Motion:
Table (4.8) shows that the average means of the respondents’ perception
about the degree of the implementation of motion items are ranging from 4.19 to
4.53, with standard deviation that ranges from 0.63 to 0.78 such results indicate
that there is an agreement on high applying of variable items. The mean of the total
motion variable items is 4.29 with standard deviation 0.54, which indicates that
there is an agreement on high implanting of this variable. Finally, the overall result
indicates that there is a significant degree of implantation of the motion variable on
the Jordanian Pharmaceutical Manufacturing Organizations, where (t=26.23>1.96).
This indicates that the directors and managers try to reduce the unnecessary motion
of information, people and goods.
61
No.
26
27
28
29
30
Table (4.8): Mean, Standard Deviation, Importance and Ranking of the Motion Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company is keen on having a standard
4.53
0.63
26.55
High
1
work (standardization)
The company is keen to reduce the movements
4.23
0.77
17.54
High
4
of workers that are not connected with work
The company is keen on a good arrangement
4.32
0.74
19.55
High
2
for the factory to reduce excess movements
The company is keen to use appropriate
internal means of transportation between 4.19
0.78
16.60
High
5
sections and departments
The company is keen to employ the appropriate
4.22
0.71
18.87
High
3
number of workers
Motion
4.29
0.54
26.23
High
t-Tabulated = 1.96
Extra Processing:
Table (4.9) shows that the average means of the respondents’ perception
about the degree of the implementation of extra processing items are ranging from
2.92 to 4.48, with standard deviation that ranges from 0. 51 to 1.41 such results
indicate that there is an agreement on high applying of extra processing variable
items, except item no. 31 which stated “The company is working to adjust the time
of the production process” and shows that there is no agreement on its medium
implementation and no significant implementation, where t=-.64<1.96.
Table (4.9): Mean, Standard Deviation, Importance and Ranking of the Extra Processing
Items:
No.
Item
Mean Std. Deviation t-Value Importance Rank
The company is working to adjust the time of
31
2.92
1.41
-.64
Medium
5
the production process
The company emphasizes the flow of required
32
4.20
0.61
21.46
High
3
procedures
The company is committed to the production
33
4.43
0.58
26.69
High
2
scheduling.
The company describes the working
34
4.48
0.51
31.41
High
1
procedures for workers
The company is keen on the appropriate use of
35
4.20
0.79
16.64
High
4
statistical aspects
Extra Processing
4.04
0.41
27.89
High
t-Tabulated = 1.96
62
The mean of the total extra processing variable items is 4.04 with standard
deviation 0.41, which indicates that there is an agreement on high implanting of
this variable. Finally, the overall result indicates that there is a significant degree of
implantation of the
motion
variable on the Jordanian
Pharmaceutical
Manufacturing Organizations, where (t=27.89>1.96). This indicates that the
directors and managers try to standardize the work.
Non Utilized Talent:
Table (4.10) shows that the average means of the respondents’ perception
about the degree of the implementation of non-utilized talent items are ranging
from 4.05 to 4.31, with standard deviation that ranges from 0.62 to 0.95 such
results indicate that there is an agreement on high applying of variable items. The
mean of the total non-utilized talent variable items is 4.18 with standard deviation
0.49 which indicates that there is an agreement on high implanting of this variable.
No.
36
37
38
39
40
Table (4.10): Mean, Standard Deviation, Importance and Ranking of the Non Utilized
Talent Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company works to discover talent
4.05
0.70
16.36
High
3
The company works to develop and train
4.21
0.62
21.48
High
1
employees on the skills needed
The company encourages new ideas
4.31
0.69
20.71
High
2
The company encourages creativity and
4.05
0.95
12.07
High
4
innovation through incentives system.
The Company has an available research center
4.31
0.69
20.71
High
2
that supports research and development
Non Utilized Talent
4.18
0.49
26.42
High
t-Tabulated = 1.96
Finally, the overall result indicates that there is a significant degree of
implantation of the non-utilized talent variable on the Jordanian Pharmaceutical
Manufacturing Organizations, where (t=26.42>1.96). This indicates that the
directors and managers work in Jordanian Pharmaceutical Manufacturing
63
Organizations; they know the importance of this variable and its effect on the
Business Performance.
Sustainable Development:
Table (4.11) shows that the average means of the respondents’ perception
about the degree of the implementation of sustainable development items are
ranging from 4.01 to 4.13, with standard deviation that ranges from 0.45 to 0.49,
such results indicate that there is an agreement on high applying of variable items.
The mean of the total sustainable development variable items is 4.08 with standard
deviation 0.35, which indicates that there is an agreement on high implanting of
this variable. Finally, the overall result indicates that there is a significant degree of
implantation of the sustainability development variable on the Jordanian
Pharmaceutical Manufacturing Organizations, where (t=33.25>1.96). This
indicates that the directors and managers are aware of the good effect of this
variable on the business performance.
No.
1
2
3
Table (4.11): Mean, Standard Deviation, Importance and Ranking of the Sustainable
Development Items:
Item
Mean Std. Deviation t-Value Importance Rank
Environmental Responsibility
4.13
0.47
26.24
High
1
Economic Responsibility
4.10
0.49
24.64
High
2
Social Responsibility
4.01
0.45
24.37
High
3
Sustainable Development
4.08
0.35
33.25
High
t-Tabulated = 1.96
Environmental Responsibility:
Table (4.12) shows that the average means of the respondents’ perception
about the degree of the implementation of environmental responsibility items are
ranging from 3.79 to 4.33, with standard deviation that ranges from 0.50 to 0.82.
Such results indicate that there is an agreement on high applying of variable items.
The mean of the total environmental responsibility variable items is 4.13 with
standard deviation 0.47 which indicates that there is an agreement on high
64
implanting of this variable. Finally, the overall result indicates that there is a
significant degree of implantation of the environmental responsibility variable on
the Jordanian Pharmaceutical Manufacturing Organizations, where (t=26.24>1.96).
This indicates that the directors and managers pay attention to maintain a safe
environment for future generation.
No.
41
42
43
44
45
46
Table (4.12): Mean, Standard Deviation, Importance and Ranking of the Environmental
Responsibility Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company is interested in reducing the
4.33
0.50
28.90
High
1
environmental pollution
The company achieved an optimum
exploitation of resources, especially non- 4.10
0.75
15.96
High
5
renewable resources.
The company owns a variety of means to deal
with the surrounding environment-friendly 4.19
0.73
17.83
High
4
products
The company provides guidance on the use of
products and ways to get rid of them and their 4.21
0.68
19.45
High
2
residues
The Company uses non-harmful products (ecofriendly) and set forth in the Good 4.19
0.72
18.12
High
3
Manufacturing.
The company recycle some wasted materials 3.79
0.82
10.41
High
6
Environmental Responsibility
4.13
0.47
26.24
High
t-Tabulated = 1.96
Economic Responsibility:
Table (4.13) shows that the average means of the respondents’ perception
about the degree of the implementation of economic responsibility items are
ranging from 3.63 to 4.31, with standard deviation that ranges from 0.59 to 1.04.
Such results indicate that there is an agreement on high applying of variable items.
The mean of the total environmental responsibility variable items is 4.10 with
standard deviation 0.49, which indicates that there is an agreement on high
implanting of this variable. Finally, the overall result indicates that there is a
significant degree of implantation of the economic responsibility variable on the
65
Jordanian Pharmaceutical Manufacturing Organizations, where (t=24.64>1.96).
This indicates that the directors and managers know the importance of this variable
and its effect on the business performance.
No.
47
48
49
50
51
Table (4.13): Mean, Standard Deviation, Importance and Ranking of the Economic
Responsibility Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company is committed to government laws
4.21
0.59
22.47
High
1
related to economic aspect
The company is seeking to pay tax dues on
4.15
0.61
20.56
High
2
time specified
The company contributes to the local economy
4.21
0.72
18.53
High
4
by bringing hard currency
The company helps in building infrastructure
3.63
1.04
6.63
Medium
5
such as bridges…etc
The company contributes to the employment of
4.31
0.70
20.36
High
3
local labor
Economic Responsibility
4.10
0.49
24.64
High
t-Tabulated = 1.96
Social Responsibility:
Table (4.14) shows that the average means of the respondents’ perception
about the degree of the implementation of social responsibly items are ranging
from 3.88 to 4.23, with standard deviation that ranges from 0.61 to 0.84. Such
results indicate that there is an agreement on high applying of variable items. The
mean of the total social responsibility variable items is 4.01 with standard
deviation 0.45, which indicates that there is an agreement on high implanting of
this variable. Finally, the overall result indicates that there is a significant degree of
implantation of the social responsibility variable on the Jordanian Pharmaceutical
Manufacturing Organizations, where (t=24.37>1.96). This indicates that the
directors and managers know the importance of this variable and its effect on the
business performance.
66
No.
52
53
54
55
56
57
Table (4.14): Mean, Standard Deviation, Importance and Ranking of the Social
Responsibility Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company is hiring people with special
needs
The company owns programs help support
education in the community
The company owns a budget for social work as
a financial support such as community
donating to charity
The company has binding laws for moral
behavior
The company has plans for a health awareness
to the community courses
The Company follows the binding laws to
ensure the safety of workers from the product
Social Responsibility
3.88
0.73
13.07
High
4
3.91
0.78
12.73
High
5
4.03
0.73
15.57
High
3
4.18
0.70
18.38
High
2
3.87
0.84
11.28
High
6
4.23
0.61
21.99
High
1
4.01
0.45
24.37
High
t-Tabulated = 1.96
Dependent Variable (Business Performance):
Table (4.15) shows that the average means of the respondents’ perception
about the degree of implementing of the business performance dimension are
ranging from 3.92 to 4.32, with standard deviation that ranges from 0.52 to 0.70.
Such results show that there is an agreement on high implementing of business
performance dimension.
The mean of the total business performance dimension is 4.12with standard
deviation 0.34 which indicates that there is an agreement on high presence of this
dimension. Finally, the overall result indicates that there is a significant degree of
implementing of the business performance among Jordanian Pharmaceutical
Manufacturing Organizations, where (t=35.88>1.96). This indicates that the
directors and managers work in Jordanian Pharmaceutical Manufacturing
Organizations; they know the importance of the implantation of the business
performance dimension
67
No.
58
59
60
61
62
63
64
65
66
67
Table (4.15): Mean, Standard Deviation, Importance and Ranking of Business
Performance Items:
Item
Mean Std. Deviation t-Value Importance Rank
The company gets the best productivity of the
4.01
0.57
19.45
High
5
individual
The company has the least cost to produce per
3.92
0.57
17.66
High
8
unit compared with competitors
The company has the least work rotation (staff) 4.09
0.65
18.22
High
7
The quality of products match with competitors 4.25
0.58
23.61
High
2
The company has continually increase in sales 4.30
0.61
23.23
High
3
The company achieves better profit compared
4.16
0.61
20.55
High
4
with competitors
The market value of the company's shares
4.13
0.68
18.25
High
6
increase on an annual basis
Return on investment commensurate with
4.05
0.70
16.36
High
10
return on the industry
The Company manages cost effectively
4.03
0.67
16.96
High
9
The company has an exceptional position
4.32
0.52
27.98
High
1
among competitors
Business Performance
4.12
0.34
35.88
High
t-Tabulated = 1.96
4.4. Relationships between the Study Variables:
Table (4.16) shows that the relationships among Lean Six Sigma variables
are medium to strong relationships, where r ranging between 0.215 and 0.536,
except the relationship between non utilized talent and transportation, which was
weak and not significant where (r=0.119, sig.=0.195).
The table (4.16) also shows that the relationships between each variable of
Lean Six Sigma and sustainable development are strong, since r ranging between
0.320 and 0.441. The relationships among sustainable development variables are
medium, since r ranging from 0.215 to 0.270. Also, the correlation between each
Lean Six Sigma variable with business performance is strong to very strong, since
r ranging from 0.425 to 0.656. Finally, the relationship between total Lean Six
Sigma and Business Performance is very strong where r=0.880.
68
This indicates that it is important to improve all variables lean Six Sigma
variables together to maximize the organizations’ business performance
Table (4.16): Bivariate Pearson’s Correlation (r) Among Independent Variables,
Dependent variables, and between Independent and Dependent Variables.
No.
1
1
Defects
2
Over Production
3
4
5
6
7
2
3
4
5
6
7
8
9
10
11
Waiting Time
Transportation
Inventory
Correlation
Sig.
.000
Correlation
.348** .472**
Sig.
.000
Correlation
.449** .436** .422**
Extra Processing
.000
Sig.
.000
Correlation
.385** .363** .358** .385**
Sig.
.000
.000
.000
.356** .405**
Sig.
.001
.000
.000
.000
Correlation
.259** .237** .277** .266** .278** .360**
Sig.
.004
.009
*
**
.000
.458
**
**
.000
.459
.002
.003
**
.000
.002
**
.000
**
**
.278
.119
.284
.246
.450
Sig.
.000
.018
.002
.195
.002
.007
.000
Environmental
Responsibility
Correlation
.307** .350** .285** .286** .254** .365** .310** .299**
Sig.
.001
.000
.002
.002
Economic
Responsibility
Correlation
.193*
.183*
.151
.371** .362** .259** .287** .247** .238**
Sig.
.034
.045
.099
.000
.001
.007
.009
Social
11
Responsibility
Correlation
.322** .228* .250** .266** .290** .250** .205*
.203*
.215* .270**
Sig.
.000
.026
.018
Sustainable
Development
Correlation
.384** .356** .320** .441** .431** .411** .383** .355** .673** .749** .684**
10
12
Non Utilized Talent
13 Lean Six Sigma
14
Business
Performance
Correlation
**
.000
.292
Correlation
Motion
.536**
.215
9
13
Sig.
.351
8
12
Correlation
.012
Sig.
.000
.000
.000
.000
.025
.000
.000
.000
.000
.000
.000
.003
.000
.000
.000
.006
.001
.683** .710** .699** .664** .655** .683** .586** .556** .464** .393** .387** .588**
.000
.000
.001
.004
.001
Correlation
Correlation
.000
.003
.000
.000
Sig.
Sig.
.000
.006
.005
.000
.000
.000
.000
.000
.000
**
**
.656** .633** .573** .617** .621** .635** .425** .446** .459** .384** .461** .612 .880
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
4.5. Testing Study Hypothesis:
To test the hypotheses, the multiple regressions analysis is used to analyze
the effect of the Lean Six Sigma variables on Business Performance.
To be able to use multiple regressions the following assumptions should be
fulfilled: Normality, validity, reliability, multi-colleanearity, independence of
errors and correlation. R2 also indicates the fitness of the model (Sekaran 2003).
14
69
Normal Distribution (Histogram):
The histogram in the figure (4.1) shows that the data were normality
distributed, since the residuals so not affect the normal distribution.
Figure (4.1): Normal Distribution
Linearity Test:
Figure (4.2) shows that the relationship between independent and dependent
variables is linear.
Figure (4.2): Linearity Test
As far as normality, validity and reliability were assumed, so regressions
analysis can be used in the case at hand; especially after achieving the following
underlying assumptions: Durbin-Watson test to ensure independence of errors, If
70
Durbin-Watson test value is about 2 the model does not violate this assumption.
While, VIF (Variance Inflation Factor) and tolerance are used to test multi
collinearity. If VIF is less than 10 and tolerance is more than 0.2, the multicollinearity model does not violate this assumption.
Table (4.17) shows that Durbin Watson value is (d=1.455), which is around
two the residuals are not correlated with each other; therefore, the independence of
errors is not violated. Table (4.17) result also shows that the VIF values are less
than 10 and the tolerance values are more than 0.05. This indicates that there is no
multi-collinearity within the independent variables of the study.
No.
1
2
3
4
5
6
7
8
9
Table (4.17): Multi-Collinearity Test for Main Hypothesis
Tolerance
VIF
DurbinWatson
Defects
0.58
1.70
Over Production
0.56
1.77
Waiting Time
0.64
1.55
Transportation
0.61
1.63
Inventory
1.45
0.68
1.45
Motion
0.62
1.60
Extra Processing
0.69
1.43
Non Utilized Talent
0.68
1.47
Sustainable Development
0.62
1.59
The Main Hypothesis:
H01: Lean Six Sigma elements do not have a direct significant effect on
JPMOs’ BP, at
0.05.
Multiple Regressions:
Table (4.18) shows that when regressing the nine independent variables of
Lean Six Sigma together against dependent variable business performance. R2
shows the fitness of the model for multiple regressions and explains the variance of
independent variable on dependent variable. Since R2 is 81% then the independent
71
variable can explain 81% of variance on dependent variable, since (R2=0.81,
F=52.46, Sig.=0.000).
Table (4.18): Results of Multiple Regressions Analysis (ANOVAa): Regressing Lean Six
Sigma Variables against Business Performance.
Model
r
R2
Adjusted R2
F
Sig.
a
1
0.90
0.81
0.79
52.46
0.00b
Consequently, the null hypothesis is rejected and the alternative hypothesis is
accepted, which states that the Lean Six Sigma elements have a direct significant
effect at Jordanian Pharmaceutical Manufacturing Organizations’ business
performance, at ( =0.05) except extra processing and waiting time.
Table (4.19) shows the significance effect of each independent variable on
dependent variable.
Table (4.19): Results of Multiple Regressions Analysis (Coefficientsa): Regressing Lean Six
Sigma Variables against Business Performance:
Model
1
Unstandardized Coefficients Standardized
Coefficients
B
Std. Error
Beta
(Constant)
-0.21
0.22
Defects
0.17
0.04
0.23
Over Production
0.10
0.04
0.13
Waiting Time
0.07
0.03
0.10
Transportation
0.12
0.03
0.18
Inventory
0.14
0.03
0.18
Motion
0.16
0.03
0.22
Extra Processing
0.01
0.03
0.01
Non Utilized Talent
0.08
0.03
0.12
Sustainable Development
0.16
0.05
0.14
Dependent Variable: Business Performance
t
Sig.
-0.94
4.27
2.34
1.94
3.40
3.72
4.34
0.32
2.39
2.72
0.34
0.00
0.02
0.054
0.00
0.00
0.00
0.74
0.01
0.00
72
Sub-Hypothesis:
H0.1: Defect does not have a direct significant effect on JPMOs’ BP, at
010.05.
Table (4.19) shows that there is a positive direct effect of defect on business
performance, since (Beta=0. 23, t=4.27, sig. 0.00, p<0.05). Therefore, the null
hypothesis is rejected and the alternative hypothesis is accepted, which indicates
that the defect has an effect on business performance at (
0.05).
H0.2: Over production does not have a direct significant effect on
JPMOs’ BP, at 010.05.
Table (4.19) shows that there is a positive direct effect of over production on
business performance, since (Beta=0.13, t=2.34, sig. 0.02, p<0.05). Therefore, the
null hypothesis is rejected and the alternative hypothesis is accepted, which
indicates that the over production has an effect on business performance at
(
0.05).
H0.3: Waiting time does not have a direct significant effect on JPMOs’
BP, at 010.05.
Table (4.19) shows that there is a non-significant effect of waiting time on
business performance, since (Beta=0.10, t=1.94, sig.0.054, p>0.05). Therefore, the
null hypothesis is accepted.
H0.4: Transportation does not have a direct significant effect on JPMOs’
BP, at 010.05.
Table (4.19) shows that there is a positive direct effect of transportation on
business performance, since (Beta=0.18, t=3.40, sig. 0.00, p<0.05). Therefore, the
null hypothesis is rejected and the alternative hypothesis is accepted, which
indicates that the transportation has an effect on business performance at (
0.05).
73
H0.5: Inventory does not have a direct significant effect on JPMOs’ BP,
at 010.05.
Table (4.19) shows that there is a positive direct effect of inventory on
business performance, since (Beta=0.18, t=3.72, sig. 0. 00, p<0.05). Therefore, the
null hypothesis is rejected and the alternative hypothesis is accepted, which
indicates that the inventory has an effect on business performance at (
0.05).
H0.6: Motion does not have a direct significant effect on JPMOs’ BP, at
010.05.
Table (4.19) shows that there is a positive direct effect of motion on business
performance, since (Beta=0. 22, t=4.34, sig. 0. 00, p<0.05). Therefore, the null
hypothesis is rejected and the alternative hypothesis is accepted, which indicates
that the motion has an effect on business performance at (
0.05).
H0.7: Extra processing does not have a direct significant effect on
JPMOs’ BP, at 010.05.
Table (4.19) shows that there is a non-significant effect of extra processing
on business performance, since (Beta=0.01, t=0.32, sig=0.74, p>0.05). Therefore,
the null hypothesis is accepted.
H0.8: Non-utilized talent does not have a direct significant effect on
JPMOs’ BP, at 010.05.
Table (4.19) shows that there is a positive direct effect of non-utilized talent
on business performance, since (Beta=0.12, t=2.39, sig.01, p<0.05). Therefore, the
null hypothesis is rejected and the alternative hypothesis is accepted, which
indicates that the non-utilized talent has an effect on business performance at
(
0.05).
74
H0.9: Sustainability development does not have a direct significant effect
on JPMOs’ BP, at 010.05.
Table (4.19) shows that there is a positive direct effect of non-utilized talent
on business performance, since (Beta=0.14, t=2.72, sig. 00, p<0.05). Therefore, the
null hypothesis is rejected and the alternative hypothesis is accepted, which
indicates that the sustainability development has an effect on business performance
at (
0.05).
From the above table (4.19), this study closes that all Lean Six Sigma
variables have an effect on business performance at Jordanian Pharmaceutical
Manufacturing organizations except extra processing and waiting time. The defect
was holding the highest effect (Beta=0. 23, t=4.273, sig. 0.00), followed by motion
variable (Beta=0. 22, t=4.34, sig. 0. 00), then inventory (Beta=0.18, t=3.72, sig. 0.
00), transportation (Beta=0.18, t=3.40, sig. 0.00), sustainability development
(Beta=0.14, t=2.72, sig. 00), over production (Beta=0.13, t=2.34, sig. 0.02) then
non utilized talent (Beta=0.12, t=2.39, sig.01).
75
Chapter Five:
Results’ Discussion, Conclusion and Recommendations
5.1. Results’ Discussion:
Result of this study shows that there is a significant implementation of the
Lean Six Sigma element among the Jordanian pharmaceutical manufacturing
organizations at Jordan. All variables of Lean Six Sigma elements have a direct
significant effect at Jordanian Pharmaceutical Manufacturing Organizations’
business performance except extra processing and waiting time, where the degree
of implementing of the Lean Six Sigma variables are ranging from 4.01 to 4.64,
with standard deviation that ranges from 0.31 to 0.54. Such results show that there
is an agreement on high implementation of Lean Six Sigma variables. The mean of
the total Lean Six Sigma variables is 4.34 with standard deviation 0.25 which
indicates that there is an agreement on high presence of these variables. This result
is supported by the previous studies, such as: Obaidullah (2005), Moosaa and Sajid
(2010), Singh, et. al. (2010), finally Kumaravadivel and Natarajan (2011).
Results show that the relationships among Lean Six Sigma variables are
medium to strong relationships, where r ranging between 0.215 and 0.536, except
the relationship between non utilized talent and transportation, which was weak
and not significant where (r=0.119, sig.=0.195). The relationships between each
variable of Lean Six Sigma and sustainable development are strong, since r
ranging between 0.320 and 0.441. The relationships among sustainable
development variables are medium, since r ranging from 0.215 to 0.270. Moreover,
the correlation between each Lean Six Sigma variable with business performance
is strong to very strong, since r ranging from 0.425 to 0.656. Finally, the
relationship between total Lean Six Sigma and business performance is very strong
76
where r = 0.880. This result is supported the previous studies, such as: Berty
(2011), Stoiljkovi, et. al. (2011) finally Arunagiri and Babu (2013).
Results show that all Lean Six Sigma variables have an effect on business
performance at Jordanian Pharmaceutical Manufacturing organizations except
extra processing and waiting time. The defect was holding the highest effect
(Beta=0. 23, t=4.27, sig. 0.00), followed by motion variable (Beta=0. 22, t=4.34,
sig. 0. 00), then inventory (Beta=0.18, t=3.72, sig. 0. 00), transportation
(Beta=0.180, t=3.402, sig. 0.001), sustainability development (Beta=0.14, t=2.72,
sig. 00), over production (Beta=0.13, t=2.34, sig. 0.02) then non utilized talent
(Beta=0.12, t=2.391, sig.01). This result is supported previous studies, such as:
Yeh, et. al. (2011), Kuptasthien and Boonsompong (2011), Mandahawia, et. al.
Goriwondo and Maunga (2012), Enoch (2013), Maleki, et. al. (2013) and Dwivedi,
et. al. (2014).
5.2. Conclusion:
The result shows that there is an agreement among participants on high
implementation of each Lean Six Sigma variable (defect, over production, waiting
time, transportation, inventory, motion, extra processing, non-utilized talent and
sustainability development), which indicates that there is an agreement on high
presence of these variables in Jordanian Pharmaceutical Manufacturing
Organization. Moreover, the overall result indicates that there is a significant
implementation of the Lean Six Sigma among Jordanian Pharmaceutical
Manufacturing Organizations. This indicates that the managers working at
Jordanian Pharmaceutical Manufacturing Organization realize the importance of
the implantation of the Lean Six Sigma variables.
The results also show that the relationships between Lean Six Sigma
variables is medium to strong relationships, except the relationship between non
77
utilized talent and transportation, which is weak and not significant. The
relationships between each variable of Lean Six Sigma and sustainable
development are strong too. Moreover, the relationships among sustainable
development variables are medium. Furthermore, the correlation between each
Lean Six Sigma variable and business performance is strong to very strong. In
addition, the relationship between total Lean Six Sigma and business performance
is very strong.
Finally, the current study indicates that all Lean Six Sigma variables have an
effect on Jordanian Pharmaceutical Manufacturing organizations’ business
performance, except extra processing and waiting time. The defect was having the
highest effect, followed by motion, then inventory, transportation, sustainability
development, over production and non utilized talent, respectively.
5.3. Recommendations:
In the light of the current study results the following recommendations can be
drawn:
Recommendations
for
Jordanian
Pharmaceutical
Manufacturing
Organizations:
1.
The current study recommends using Lean Six Sigma as a tool and
technique to eliminate wastes and reduce pollutions in organizations.
2.
The current study advice to conduct special training courses on how to
implement Lean Six Sigma for managers and other employees.
3.
The current study recommends to visit and analyze separately all
wastes creating manufacturing processes to be able to reduce the waste and
production cost.
4.
Manufacturing organizations should assign a Lean Six Sigma
champion as specialists to follow Lean Six Sigma profile.
78
5.
The current study recommends including sustainable development
elements within Lean Six Sigma criteria at Jordanian Pharmaceutical
Manufacturing Organization as it may affect the organizations’ Business
Performance.
Recommendations for Academics and Future Research:
6.
The current study recommends adding sustainable development
elements to lean six elements in further studies.
7.
This study is directed towards Pharmaceutical industry. Further
empirical research work is needed to test the degree to which the study findings
can be generalized to other industries.
8.
This study was conducted on Jordanian organizations. Generalizing
Jordanian results to other countries is questionable. Therefore, the study
recommends carrying out similar study in different countries especially Arab
countries
9.
Finally, there is a need to analyze data of other organizations over a
longer time in order to clearly test the assumptions of the Lean Six Sigma system.
The significant differences between organizations and/or industries could be
explored by further studies. So, it is recommended to work out researches that
compare results with other countries specially developing countries under similar
assessment and assumptions.
79
2345678 References:
Abu-Hameeda, A. (2013). “The impact of Implementing Total Quality
Management Standards in Building Differentiation Strategy of
Jordanians Pharmaceutical Manufacturing Companies“ Unpublished
Master thesis. Middle East University.
Agus, A.; and Iteng, R. (2013). “Lean Production and Business Performance: The
Moderating Effect of the Length of Lean Adoption”. Journal of Economics,
Business and Management, 1(4), 324-328.
Ahmad, S. (2013). “Service Sector Performance Management through Six Sigma”.
International journal of innovative research & development, 2(13), 346350.
Aleem, H.; Anwar, S.; Shariff, I.; and Abdul Aziz, S. (2014). “Six Sigma
Application: An Order Management System”. IOSR Journal of
Humanities And Social Science, 19(1), 95-100.
Ali, M.; Mohamadali, F.; and Milad, S. (2011). “Studying and Developing Model
of Six Sigma Implementation in Companies of Yazd House of Industry and
Mine”.
International
Business
and
Management,
3(2),
22-29.
www.cscanada.net.
AlSagheer, A. (2011). “Six Sigma for Sustainability In Multinational
Organizations”. Journal of Business Case Studies, 7(3), 7-16.
Amar, K.; and Davis, D. (2010). “Key elements of a Lean six sigma framework for
Indonesian SMEs”. Proceedings of the 1st International Conference on
Industrial Engineering and Business Management, Yogyakarta.
80
Antony, J. (2009). “Reflective practice, Six Sigma vs TQM: some perspectives of
leading
practitioners
and
academics”.
International
Journal
of
Productivity and Performance Management. 58(3), 274-279.
Antony, J. (2011). “Reflective Practice Six Sigma vs Lean some perspectives from
leading
academics
and
practitioners”.
International
Journal
of
Productivity and Performance Management, 60(2), 185-190.
Antunes, D.; Sousa, S.; and Nunes, E. (3 – 5 July 2013). “Using Project Six Sigma
and Lean Concepts in Internal Logistics.” Proceedings of the World
Congress on Engineering 2013, London, U.K, 1, 1-6.
Anuradha, Rao, D.; Khandekar, A, Arora, T.; and Kour, G. (2013). “Six Sigma
implementation in software companies using DTS”. International Journal
of Mathematical Archive, 4(9), 258-263.
Arunagiri, P.; and Babu, A. (2013). “Review on Reduction of Delay in
manufacturing process using Lean six sigma (LSS) systems”. International
Journal of Scientific and Research Publications, 3(2), 1-4.
Awaritoma, O. (2010). “Performance Management in Lean Production”.
Unpublished Master thesis, Linnaeus University.
Bao, L.; Chen, N.; Shang, T.; Fang, O.; Xu, Z.; Guo, W.; and Wang, Y. (2013) “A
multicenter study of the application of Six Sigma management in clinical
rational drug use via pharmacist intervention”. Turkish Journal of Medical
Sciences, 43(3), 362-367.
Bashir, A.; and Al-Tawarah. A. (July 2012). “Implementation of six sigma on
Corrective Maintenance Case Study at the Directorate of Biomedical
Engineering in the Jordanian Ministry of Health”. Proceedings of the 2012
81
International Conference on Industrial Engineering and Operations
Management, Istanbul, Turkey, July 3-6, 2012, 2508-2516
Baveja, N.; and Jain, A. (2013). “Role of Human Resources in Six Sigma”.
Atharva A Journal of Management Research, 5(1), 46-53.
Berty, E. (October 2011). “Cigarette Reject Rate Reduction using a Lean Six
Sigma Approach”, Unpublished Master thesis. Royal Institute of
Technology.
Bharti, P.; Khan, M.; and Singh, H. (2011). “Six Sigma Approach for Quality
Management in Plastic Injection Molding Process: A Case Study and
Review”. International Journal of Applied Engineering Research, 6(3),
303-314.
Boldt, E.; and Franchetti, M. (2013). “Total Sustainability Assessments for
Manufacturing Operations Using the Lean Six Sigma Approach”. Science
Journal of Environmental Engineering Research, 2013.
Brundtland, G.H. (1987) .World commission on environment and development:
our common future. Oxford University Press, Oxford.
Cavallini, A.G. (2008). “Lean Six Sigma as a Source of Competitive
Advantage”. Unpublished Master thesis, Brigham Young University.
Chakraborty, A.; and Tan, K. (2012). “Case study analysis of Six Sigma
implementation in service organizations”. Business Process Management
Journal, 18(6), 992-1019. www.emeraldinsight.com/1463-7154.htm.
Chang, T. (2002). “Six Sigma: a framework for small and medium sized
enterprises to achieve total quality”. Unpublished doctoral dissertation,
Cleveland State University, Ohio, USA.
82
Chetiya, A.R.; and Sharma, S. (2014). “An Analysis of Predictor Variables for
Operational Excellence through Six Sigma”. Proceedings of the 2014
International Conference on Industrial Engineering and Operations
Management Bali, Indonesia, January 7-9 2014, 1750-1757.
Chinvigai, C.; Dafaoui, E.; and El Mhamedi, A. (May 2010). “Iso 9001: 2000/2008
And Lean-Six Sigma Integration Toward To Cmmi-Dev For Performance
Process Improvement”. 8th International Conference Of Modeling And
Simulation - Mosim’10 - May 10-12, 2010 - Hammamet – Tunisia, 3-9.
Chung, C. (September 2013). “An Application of Six Sigma Methodology in
Agarwood Tissue Culture”. Open Journal of Optimization, 2(3), 80-88.
Clegg, B. (2007). “Maximising the Economic and Social Impact of Six Sigma”.
Production and Operations Management (POMS), May 4th-7th. Texas,
USA.
Dahman, T. (2013). “The Impact of Supply Chain Management to
Organization Performance”.
Unpublished Master Thesis, Middle East
University.
Dakov, I.; and Novkov, S. (2007). “Assessment of the lean production effect on the
sustainable industrial enterprise development”. Business: theory and
practice, 8(4), 183-188.
Darabi, Y. (2007). “The impact of Market orientation on business performance
and website adoption: a study among Iranian SMEs”. Unpublished
Master thesis, Lulea University of Technology.
DelliFraine, J.L.; Langabeer, J.R.; and Nembhard, I.M. (2010). “Assessing the
Evidence of Six Sigma and Lean in the Health Care Industry”. Q Manage
Health Care, 19(3), 211-225.
83
DeRuntz, B.; and Meier, R. (2010). “An Evaluative Approach to Successfully
Implementing Six Sigma”. The Technology Interface Journal, 10(3), 1-9.
Desale, S.V.; and Deodhar, S.V (March 2014). “Identification And Eliminating
Waste In Construction By Using Lean And Six Sigma Principles”.
International Journal of Innovative Research In Science, Engineering
And Technology, 3(4), 285-296.
Dey, S. (2013). “Transforming Washington DC’s Parking Meter Program Using
Lean Six Sigma Based Asset Management”, TRB 2014 Annual Meeting, 1
21.
Dhawan, S. (November - December 2013). “Professionalism among the Pupil
Teachers: A six-sigma Approach in Teacher Education”. Scholarly
research journal for interdisciplinary studies, 2(4), 544-557.
Dileep, G.; and Rau, S. (October 2010). “Patient Satisfaction As An Indicator Of
Quality Care.-A Study With Reference To Six Sigma Implementation In
Medium Scale Hospitals.” National Journal on Advances In Computing
And Management, 1(2), 27-33.
Divoky, J. (2008). “Factors Affecting Six Sigma Project Selection In The
Information Systems/Information Technology Arena”. Review of Business
Information Systems, 12(4), 13-20.
Dwivedi, V.; Anas, M., and Siraj. M. (2014). “Six Sigma; As Applied in Quality
Improvement for Injection Moulding Process.” International Review of
Applied Engineering Research, 4(4), 317-324.
Edaily, F. (2014). “The Possibility of Applying Six Sigma and its Role in Cost
Reduction and Increasing Competition – Applied Study of Advanced
84
Technology Companies of Recycling Used Materials An Empirical
Study”. Unpublished Master Thesis, Zarqa University.
Enoch, O. K. (October, 2013). “Lean Six Sigma Methodologies and Organizational
Profitability: A Review of Manufacturing SMEs in Nigeria”. American
Journal of Industrial and Business Management, 3, 573-582.
http://dx.doi.org/10.4236/ajibm.2013.36066
Published
Online
(http://www.scirp.org/journal/ajibm).
Fontaine, M. (2013). Corporate Social Responsibility and Sustainability: The New
Bottom Line? International Journal of Business and Social Science,
4(4):110-119.
Furterer, S.L. (2004). “A framework roadmap for implementation lean six
sigma in local government entities”. Unpublished doctoral dissertation.
University of Central Florida, Orlando, USA.
Goh, T.N. (2011). “Six Sigma as a Change Agent in Quality Management”. The
55th EOQ Congress and World Quality Congress, Budapest, June 20-23,
2011, 1-10.
Goriwondo, W.M.; and Maunga, N. (2012). “Lean Six Sigma Application for
Sustainable Production: A Case Study for Margarine Production in
Zimbabwe”. International Journal of Innovative Technology and
Exploring Engineering (IJITEE), 1(5), 87-96.
Gupta, N. (March-April 2013). “An Overview on Six Sigma: Quality Improvement
Program”.
International
Journal
Of
Technical
Research
And
Applications, 1(1), 29-39.
Habidin, N.F.; Yusof, S.M.,;Che Omar, C.Z., Mohamad, S.I.S.; Janudin, S. E.; and
Omar, B. (2012). “Lean Six Sigma Initiative: Business Engineering
85
Practices and Performance in Malaysian Automotive Industry”. IOSR
Journal of Engineering, 2(7), 13-18.
Hai, H.; and Mai, N. (2014). “An Exploratory Study of the Relationship between
Lean Production and Corporate Social Responsibility in Vietnamese SMEs”.
VNU Journal of Science: Economics and Business 30(2), 28-38.
Hajikordestani, R.N. (2007). “Taxonomy of Lean Six Sigma Success Factors for
Service Organizations”, Unpublished Master thesis. University of Central
Florida.
Huang, Y. (2013). Applying Linear Programming Method in Six Sigma
Approach to Develop a Truck Planning Tool. Unpublished Master thesis.
University of Wisconsin-Stout.
Jaakkola, M. (2006). “Strategic marketing and its effect on business
performance:
moderating
effect
of
country-specific
factors”.
Unpublished Master thesis, Helsinki University of Technology.
Jaglan, P.; Kaushik, P.; and Khanduja, D. (October-December, 2011). “Six Sigma:
A Road Map For Smes”. International Journal of Advanced Engineering
Technology, 2(4), 461-464.
Jawadeh, S. (2011). “Feasibility of Application of Six Sigma and its role in
improving the quality of health services in the Government Hospitals In
Gaza Strip From The perspective Of Senior management”. Unpublished
Master Thesis, The Islamic University.
Jayaraman, P.; Kannabiran, K.; and Kumar S.A.V. (2013). “A Six Sigma Approach
for Software Process Improvements and its Implementation”. International
Journal of Mining, Metallurgy & Mechanical Engineering (IJMMME),
1(3), 228-232.
86
Jovanovic, R.; Delic, M.; Kamberovic, B.; Vulanovic. S.; and Radlovacki. V.
(2013). “Planning the use of Lean Six Sigma as a framework for blood bank
management
improvements”.
International
Journal
of
Industrial
Engineering and Management (IJIEM), 4(4), 237-244.
Junankar, A.A.; Gupta, P.M.; Sayed, A.R.; and Bhende, N.V. (2014). “Six Sigma
Technique for Quality Improvement in Valve Industry”. IJREAT
International Journal of Research in Engineering & Advanced
Technology, 2(1), 1-5.
Kabir, M.; Boby, S.; and Lutfi, M. (2013). “Productivity Improvement by using
Six-Sigma”. International Journal of Engineering and Technology,
3(12), 1045-1073.
Kateeb, Muhanad. (2009). “The Extent unplanned Six Sigma using impact in
Housing bank for trade and finance”.
Unpublished Master Thesis,
Middle East University.
Kaushik, P. (2012). “Six Sigma look at in education: a managing perception”.
International Journal of Research in IT & Management, 2 (6), 49-59.
Kazemi, M.; and Nikkar, A. (2014). “Classification criteria for selecting Six-sigma
projects”. Applied mathematics in Engineering, Management and
Technology, 2(3), 397-403.
Khaidir, N.A.; Habidin, N.F.; Ali, N.; Shazali, N. A., and Noor Jamaludin, N. H.
(January – February 2013). “Six Sigma Practices and Organizational
Performance in Malaysian Healthcare Industry.” IOSR Journal of Business
and Management (IOSR-JBM), 6(5), 29-37. www.iosrjournals.org.
Khaidir, N.A.; Habidin, N.F.; Jamaludin, N.H.; Shazali, N.A.; and Ali, N. (2014).
“Investigation of Six Sigma Practices and Process Innovation for Malaysian
87
Healthcare Industry”. International Journal of Innovation and Applied
Studies, 5(2), 131-138.
Khandekar, A.S.; and Sulakhe, V.N. (January 2014). “Six Sigma – The Revival of
Tqm”. International Journal of Medical Engineering and Robotics
Researches. 3(1), 50-58.
Koripadu, M.; and Subbaiah, K.V. (February 2014). “Problem Solving
Management Using Six Sigma Tools & Techniques”. International
Journal of Scientific & Technology Research, 3(2), 91-93.
Kosina, J. (2013). “The process to estimate economical benefits of six sigma
projects. “Quality Innovation Prosperity, 17(1), 16-27.
Krambia-Kapardis, M.; and Ioannou, A. (2011). “Six sigma: The panacea to
sustainability”. Journal of Modern Accounting and Auditing, 7(2), 158-172.
Kumar, V.M.; and Kumar, M.V. (April 2013). “Six Sigma Approach to Quality
Assurance in Global Supply Chains”. International Journal of Science and
Research, 2(4), 560-562.
Kumara, V.; and Khandujaa, R. (August 2013). “Application of Six-Sigma
Methodology in SSI: A Case Study”. International Journal of Current
Engineering and Technology, 3(3), 971-976.
Kumaravadivel, A.; and Natarajan, U. (2011). “Empirical study on employee job
satisfaction upon implementing six sigma DMAIC methodology in Indian
foundry – A case study”. International Journal of Engineering, Science
and Technology, 3(4), 164-184.
Kuptasthien,N.; and Boonsompong, T. (2011). “Reduction of Tombstone Capacitor
Problem by Six Sigma Technique: A Case Study of Printed Circuit Cable
Assembly Line”. Proceedings of the 2011 IEEE ICQR, 546-550.
88
Kuptasthien,N.; and Boonsompong, T. (2011). “Reduction of Tombstone Capacitor
Problem by Six Sigma Technique: A Case Study of Printed Circuit Cable
Assembly Line”. Proceedings of the 2011 IEEE ICQR, 546-550.
Lancaster, J. (2011).
“Lean and Six Sigma in Hospitality Organizations:
Benefits, Challenges, and Implementation”. Unpublished Master thesis.
University of Nevada, Las Vegas.
Leonard, T.; Schneider J. (2004). “Integrated sustainability in the pharmaceutical
industry”. International Journal for sustainable business, 11(5), 119-128.
Maleki, M.; Riahi, L.; Dashti, T.; and Karbasian, S. (2013). “Reducing Waiting
Time in Patients Undergone Spinal Surgeries at Operation’s room of
Shohada-ye-Tajrish Hospital using Six Sigma Model”. New York Science
Journal, 6(12), 136-141.
Mandahawi, N.; Al-Shihabi, S.; Abdallah, A.A.; and Alfarah, Y.M. (2010).
“Reducing waiting time at an emergency department using design for Six
Sigma and discrete event simulation”. Int. J. Six Sigma and Competitive
Advantage, 6(1-2), 91-104.
Mandahawia, N.; Fouad, R.H.; Obeidat, S. (2012). “An Application of Customized
Lean Six Sigma to Enhance Productivity at a Paper Manufacturing
Company”. Jordan Journal of Mechanical and Industrial Engineering,
6(1), 103-109.
Mezouari, S.; Bouaouda, Z.; and Drissi, H. (2013). “Lean Six Sigma in Africa: Fad
or real solution of competitiveness.?”. International Journal of
Management & Information Technology, 6(3), 861-866.
Micu, D. (15-16 November 2012). “Six Sigma: Tools and Methodology For The
Clothing Industry”. Proceedings Of The 6th International Management
89
Conference Approaches In Organizational Management, Bucharest,
Romania, 505-510.
Moosaa, K.; and Sajid, A. (July 2010). “Critical analysis of Six Sigma
implementation”. Total Quality Management & Business Excellence,
21(7), 745-759.
Mousa, A. (2013). “Lean, six sigma and lean six sigma: Overview”. International
Journal of Scientific & Engineering Research, 4(5), 1137-1153.
Muhareb, T.M.; and Graham-Jones J. (2014). “Using Lean Six-Sigma in the
Improvement of Service Quality at Aviation Industry: Case Study at the
Departure Area in KKIA”. International Journal of Social, Human
Science and Engineering, 8(1), 1-7.
Muthukumaran, G.; Venkatachalapathy, V.S.K.; and Pajaniradja, K. (March April 2013) “Impact on integration of Lean Manufacturing and Six Sigma
in various applications - a review”. Journal of Mechanical and Civil
Engineering (IOSR-JMCE), 6(1), 98-101.
Mutia, P.M.; and Nyambegera, S.M. (2014). “Six Sigma Approach for Quality
Improvement and its Future in Kenyan Organizations: a Research Agenda”.
International journal of Science Commerce and Humanities, 2(1), 125136.
Ngo, S.T.Q.N. (2010). “The Relationship between Lean Six Sigma and
Organizational Performance: An Empirical Investigation”. Unpublished
Master thesis. Lincoln University.
Niemeijer, G.C.; Trip, A.; Ahaus, K. T. B., Does, R. J. M. M., and Wendt, K. W.
(September 2010). “Quality in Trauma Care: Improving the Discharge
90
Procedure of Patients by Means of Lean Six Sigma”. The Journal of
Trauma Injury, Infection, and Critical Care, 69(3), 614-619.
Obaidullah, H. K.K. (2005). “A Study of Six Sigma Implementation and Critical
Success Factors”. Pakistan’s 9th International Convention on Quality
Improvement, 1-12.
Olsen, E.O. (2004). “Lean Manufacturing Management: the relationship
between practice and firm level financial performance”. Unpublished
doctoral dissertation, The Ohio State University.
Parast, M.M. (2011). “The effect of Six Sigma projects on innovation and firm
performance”. International Journal of Project Management, 29 (1), 4555.
Percin, S.; and Kahraman, C. (October 2010). “An Integrated Fuzzy Multi-Criteria
Decision-Making Approach for Six Sigma Project Selection”. International
Journal of Computational Intelligence Systems, 3(5), 610-621.
Pokharkar, D.; Jadhav, V.; Gholve, S.; and Vilasrao Kadam. (2010). “Six Sigma:
Golden Opportunity for Pharmaceutical Industry”. International Journal of
PharmTech Research, 2(2), 1160-1164.
Pranoto, S.; and Nurcahyo, R. (2014). “Implementation of Integrated System Six
Sigma and Importance Performance Analysis for Quality Improvement of
HSDPA
Telecommunication
Network
and
Customer
Satisfaction”.
Proceedings of the 2014 International Conference on Industrial
Engineering and Operations Management Bali, Indonesia, January 7 – 9
2014, 1544-1553.
91
Pulakanam, V.; and Voges, K.E. (November 2010). “Adoption of Six Sigma by
organizations: What Has Empirical Research Discovered?” International
Review of Business Research Papers, 6(5), 149-163.
Radhakrishnan, R. and Balamurugan, P. (November 2011). “Construction of
Control Charts Based On Six Sigma Initiatives for the Number of Defects
and Average Number of Defects per Unit”. Journal of Modern Applied
Statistical Methods, 10(2), Article 22, 639-645.
Radhakrishnan, R.; and Sivakumaran, P. K. (2010). “Construction and Selection of
Tightened-Normal-Tightened Schemes of Type TNT-(n1, n2; c) indexed
through Six Sigma Quality Levels”. Proceedings of the 2010 International
Conference on Industrial Engineering and Operations Management
Dhaka, Bangladesh, January 9-10 2010, 1-6.
Ravet, D. (2012). Lean production: the link between supply chain and sustainable
development in an international environment. Colloque Franco-Tcheque
Trends in international business, June 2011, Lyon, France. 1-20.
Reddy, G.P.P.; and Reddy, V.V. (2010). “Process improvement using Six Sigma –
a case study in small scale industry”. Int. J. Six Sigma and Competitive
Advantage, 6(1-2), 1-11.
Reijns, T.J.F. (2010). “The advantages and limitations of Lean Six Sigma in
process (re)design: Combining continuous improvement methods to
align the product characteristics with the customer’s requirements”.
Unpublished Bachelor Thesis, Tilburg University.
Reosekar, R.S.; and Pohekar, S.D. (August 2013). “Design and Development Of
Six Sigma Implementation Framework For Indian Industries”. International
92
Journal of Engineering, Business and Enterprise Applications (Ijebea),
5(2), 147-152.
Rusko, M.; and Kralikova, R. (2011). “Application of Six Sigma Method To EMS
Design”, research papers, faculty of materials science and technology in
Trnava Slovak University of technology in Bratislava, 30, 39-44
Rusko, M.; and Kralikova, R. (2011). “Application of Six Sigma Method To EMS
Design”, research papers, faculty of materials science and technology in
Trnava Slovak University of technology in Bratislava, 30, 39 – 44.
Salminen, J. (2005). “Measuring performance and determining success factors
Unpublished Doctoral Dissertation, Helsinki
of construction sites”.
University of Technology.
Sekaran, U. (2003). Research Methods for Business: A Skill Building
Approach. 4th Edition. John Wiley and Sons (ASIA) Pte Ltd. Singapore.
Sharabati, A.A. (2008). The Effect of Intellectual Capital on the Performance
of
Pharmaceutical
Manufacturing
Organizations
in
Jordan.
Unpublished Doctorate thesis. Amman Arab University.
Sharma, S.; Bhardwaj, D.; and Kumar. V. (July 2013). “Six Sigma Approach:
Application, Benefits and Scope.” International Journal of Medical
Engineering and Robotics Researches, 2(3), 365-370.
Singh, B.; Garg, S.K.; Sharma, S.K.; and Grewal, C. (2010). “Lean implementation
and its benefits to production industry". International Journal of Lean Six
Sigma, 1(2), 157-168.
Soare, P. (15-16 November 2012). “Opportunities For Driving Continuous
Improvement Through TQM, Lean And Six Sigma Within Business Process
Management”. Proceedings of the 6th International Management
93
Conference "Approaches In Organisational Management", Bucharest,
Romania. 193-202.
Stoiljkovi, V.; Trajkovi, J.; and Stoiljkovi, B. (2011). “Lean six sigma sample
analysis process in a microbiology laboratory”. J Med Biochem, 30(4),
346–353.
Subramaniyam, P.; Srinivasan, K.; and Prabaharan, M. (2011). “An Innovative
Lean Six Sigma Approach for Engineering Design”. International Journal
of Innovation, Management and Technology, 2(2), 166-170.
Sunal, G.; and Evangeliou, E. (2012). ”Six Sigma in Project Management
Implementation of Six Sigma at Klesman Electric”. Unpublished Master
thesis.
Tahir, T. (2010). “The voice of customer (voc table): understanding customer
needs for six sigma process.” Technical Journal of LBSIMDS, 1(1), 101106.
Varzandeh, J.; and Kamy, F. (February 2010). “Comparative and Strategic Role of
ERP in “Six Sigma” Quality”. Proceedings of ASBBS, 17(1), 511-517.
Venkatesh, N.; Sumangala, C.; and DSouza, L. (August 2013). “Outcome of six
sigma
implementation
a
case
study
of
manufacturing
industry”.
International Journal of Innovative Research in Science, Engineering
and Technology, 2(8), 4076-4082. www.ijirset.com
Vijay, S.M. (2012). “Integration of six sigma with project management”.
International Journal of Advanced Engineering Technology, 3(1), 29-32.
Vilas-Boas, R.D. S. (2009). “International diversification: entry mode, location
decision and performance”. Unpublished Doctoral Dissertation, University
of Salamanca.
94
Villa, D. (2010). “Automation Lean, Six Sigma: Synergies For Improving
Laboratory Efficiency”. Med Biochem, 29(4), 339-348.
Waghmare, A.C.; Parikh, R.H.; Gajbhiye, P.R.; Athavale, S.A.; and Pal, S.D.
(2013). “Application Of Six Sigma Technique For Quality And Safety
Improvement In A Hot Rolling Industry”. Global Journal of Engineering,
Design and Technology, 2(3), 8-11.
Weinstein, L. (2010). “A discussion of the suitability of Six Sigma techniques in
non-profit arts and culture-oriented organizations”, Asia Pacific Journal of
Arts and Cultural Management, 7(1), 569-583.
Xu, Y.; Zhang, F.; and Ye.; X. (2013). “Case Study on the Lean Six Sigma
Management for Information Technology Service Management Project of G
Commercial
Bank”.
Technology
and
Investment,
4(2),
76-84.
http://dx.doi.org/10.4236/ti.2013.42009.
Yeh, C.W.; Shyu, C.S.; Hsu, C.H.; and Cheng, K. M. (2011). “Applying six sigma
to promote self-management ability in health clubs”. African Journal of
Business Management, 5(4), 1365-1373.
Yeh, H.L.; Lin, C.S.; Su, C.T.; and Wang, P.C. (December 2011). “Applying lean
six sigma to improve healthcare: An empirical study”. African Journal of
Business
Management,
5(31),
12356-12370.
http://www.academicjournals.org/AJBM
Yuksel, H. (2012). “Evaluation of the Success of Six Sigma Projects by Data
Envelopment
Analysis”.
International
Journal
of
Business
and
Management, 7(13), 75-84.
Yusr, M. M.; Othman, A.; and Mokhtar, S. S. (2011). “Innovation and six sigma
foundation from the perspective of the absorptive capacity theory”.
95
International Conference on management (ICM) proceeding, 12331274.
Zaman, M.; Pattanayak, S.K.; and Paul, A. (2013). “Study of feasibility of six
sigma implementation in a manufacturing industry: a case study”.
International Journal of Mechanical and Industrial Engineering
(IJMIE), 3(1), 96-100.
Zamri, F.; Hibadullah, S. N.; Fuzi, N. M.; and Desa, A. F. (2013). “Green Lean Six
Sigma and Financial Performance in Malaysian Automotive Industry”.
Business Management and Strategy, 4(1), 97-106.
Zhang, Q.; Irfan, M.; Zhu, X.; and Khattak, M. (2013). “Six Sigma in Synergy with
Risk Management”. European Journal of Business and Management,
5(12), 184-188.
Zu, X.; Fredendall, L.; and Douglas, T. (2008). “The evolving theory of quality
management: The role of Six
Management, 26(5), 630-650.
Sigma”.
Journal of Operations
96
Appendices:
Appendix (1): Panel of Referees Committee.
No.
Name
Qualification
Organization
1
Prof. Mohammad Al No’imi
Ph. D. Management
Middle East University
2
Prof. Kamil Moghrabi
Ph. D. Management
Middle East University
3
Dr. Mohammad Khir Abu Zeid
Ph. D. Management
Middle East University
4
Dr. Amjad Tweqat
Ph. D. Management
Middle East University
5
Dr. Ali Abbas
Ph. D. Management
Middle East University
6
Dr. Abdul Bari Dorah
Ph. D. Management
Middle East University
7
Dr. Ahmad Ali Saleh
Ph. D. Management
Middle East University
8
Dr. Nidal Al Salihi
Ph. D. Management
Middle East University
9
Dr. Haitham Hijazi
Ph. D. Management
Middle East University
10
Dr. Hanadi Salameh
Ph. D. Marketing
Middle East University
11
Dr. Ahmad Al Zamel
Ph. D. Marketing
Middle East University
12
Dr. Ghazi Samawi
Ph. D. Management
GJU
13
Dr. Wa’d Nsoor
Ph. D. Management
Hashemite University
14
Dr. Mahmoud Al Omari
15
Eng. Mohammad A. Tarabia
16
Mais Dabain
GM of research and
innovation center at JPM
Executive Manufacturing
Manager
Consultant
97
Appendix (2): List of Members of the Jordanian Association of
Pharmaceutical Manufacturers 2015.
No.
1
2
3
4
5
6
7
8
Company
The
Arab
Pharmaceutical
Manufacturing Co. LTD (APM)
Dar Al Dawa Development and
Investment Co. (DAD)
Hikma Pharmaceuticals (HIKMA)
Jordanian
Pharmaceutical
Manufacturing Co. PLC (JPM)
Arab Center for Pharmaceutical and
Chemical (ACPC)
United Pharmaceutical (UPM)
Amman Pharmaceutical Industries Co.
(API)
Ram Pharmaceutical Industries Co. Ltd
(RAM)
Year Established
Type
Public
1975
Public
1977
Pubic
1978
Public
1983
Public
1989
Private
1989
Private
1992
Private
9
Hayat Pharmaceutical Industry (HPI)
1993
Public
10
Middle
East
Manufacturing Co
(MIDPHARMA)
1993
Public
11
Pharma International (INTER)
1994
Private
12
Jordan
Sweden
Sterilization Co
1996
Private
13
TQ PHARMA
2007
Private
14
Jordan River Pharmaceutical Industries
Co. (JoRiver)
1999
Private
Pharmaceutical
Medical
and
98
Appendix (3): Panel of Referees Committee Letter (English Version)
The Effect of Lean Six Sigma on the Jordanian Pharmaceutical Manufacturing
Organizations’ Business Performance.
Dear Professor:
The lean six sigma is considered as a tool for modern measurement and
management of business performance to achieve efficiency and effectiveness. It's
also one of the best tools that are used to measure the quality of products, in which
managers of manufacturing companies and other institutions are trying to find the
best ways to measure and assess the quality of their products and linking it to the
financial and non-financial performance, in order to improve and develop the
overall business performance.
The purpose of this master thesis is to know the effect of Lean Six Sigma on
the Jordanian pharmaceutical Manufacturing Organizations’ business performance.
You have been chosen and invited to participate as one of the panel judge
for this master thesis questionnaire. Your guidance and participation in this
research is highly appreciated.
Please put down your suggestions and recommendations onto the
questionnaire, adding any comments you wish about any particular issues that you
consider of importance. It is important to state that the design and analysis of this
study concentrates on the firm.
Again, thank you for your participation and guidance, and if you have any
questions or concerns please do not hesitate to contact (079) 5684078.
Thank you in advance for your help.
Researcher: William Al Kunsol
Supervisor: Dr. Abdulaziz AlSharbati
99
Appendix (4): Participants Letter (English Version)
The Effect of Lean Six Sigma on the Jordanian Pharmaceutical Manufacturing
Organizations’ Business Performance.
Dear Participant:
The lean six sigma is considered as a tool for modern measurement and
management of business performance to achieve efficiency and effectiveness. It's
also one of the best tools that are used to measure the quality of products, in which
managers of manufacturing companies and other institutions are trying to find the
best ways to measure and assess the quality of their products and linking it to the
financial and non-financial performance, in order to improve and develop the
overall business performance.
The purpose of this master thesis is to know the effect of Lean Six Sigma on
the Jordanian pharmaceutical Manufacturing Organizations’ business performance.
I hope that you will assess the paragraphs of this questionnaire, which his
words are measured by Fifth Likert scale (1 to 5) and give your suggestions about
it, and add any comments about the topics that you feel is important for this topic
and / or for the pharmaceutical industry, and I'm ready to take your
recommendations into consideration when rewriting and revising the questionnaire.
We appreciate your participation and guidance for the benefit of this study.
I reiterate my thanks for your participation and your guidance, and if you
have any question or comment, please call (00962795684078).
Thank you for your attention.
Researcher: William Hanna Al-Kunsol
Supervisor: Dr. Abdulaziz AlSharbati
100
Appendix (5): Thesis Questionnaire (English Version)
Questionnaire of the Effect of Lean Six Sigma on the Jordanian Pharmaceutical
Manufacturing Organizations’ Business Performance.
Part one: Demographic information
Gender:
Male
Age (years):
Education:
25 – 35
above 35 – 45
Diploma or less
Position
High level
Division:
Production
Years of experience:
Female
Bachelor
above 45 - 55
above 5
Master
Doctorate
Middle level
R&D
Less or equal 5
Low level
Marketing
Above 5 – 10
Others
Above 10 – 15
Above 15
The following 67 items tap into Lean Six Sigma and its effect on company's business
performance. Please, answer these questions based on actual and current situation and not on
beliefs.
[1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree] based on how you
feel about the statement.
Defects:
1. The company is keen on the quality of raw materials
2. The company uses the appropriate means of transportation
The company is committed to follow the instructions and formulas for
3. manufacturing such as mixing in approved precise proportions of
materials
4. The company is keen to follow in time the production processes
The company is keen to pay attention to the cleanliness of the internal
5.
environment
Over Production:
6. The company is keen on the proper appreciation of the order quantity
7. The company emphasizes the orders before starting the production
8. The company is keen to ensure the effectiveness and safety of the
product compared to competitors' products
9. The company is keen on estimating raw materials required for the
production
10. The company is keen to manage machines efficiently and effectively
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
101
Waiting Time:
11 The company works on the availability of raw materials in a timely
manner
12 The company is keen on the effectiveness of the production processes
13 The company emphasizes on the periodically maintenance of
machinery
14 The company set priorities for manufacturing
15 The company takes into consideration the speeding up decision-making
when the need arises
Transportation:
16. The company is keen to provide alternatives for transport operations in
case of emergency
17. The company confirms the accuracy of the packaging operations
18. The company is committed to the customs procedures required to
facilitate transfers
19. The company is keen on using appropriate means of transportation
20. The company owns the appropriate skills for workers to carry out
handling during transport
Inventory:
21 The company is keen to provide the appropriate storage conditions
(temperature and humidity)
22 The appropriate skills for workers to perform the storage business
become available in the company
23 The company is keen to provide the appropriate handling tools (forklift)
24 The company emphasizes the appropriate arrangement of the material
inside the warehouse
25 The company is committed to conduct the various inventories
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1
1
2
2
3
3
4
4
5
5
1
1
2
2
3
3
4
4
5
5
1
2
3
4
5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
Motion:
The company is keen on having a standard work (standardization)
26. The company is keen to reduce the movements of workers that are not
connected with work
27. The company is keen on a good arrangement for the factory to reduce
excess movements
28. The company is keen to use appropriate internal means of
transportation between sections and departments
29. The company is keen to employ the appropriate number of workers
1 2 3 4 5
1 2 3 4 5
Extra processing
30. The company is working to adjust the time of the production process
31. The company emphasizes the flow of required procedures
32. The company is committed to the production scheduling.
33. The company describes the working procedures for workers
34. The company is keen on the appropriate use of statistical aspects
1
1
1
1
1
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
2
2
2
2
2
3
3
3
3
3
4
4
4
4
4
5
5
5
5
5
102
Non Utilized Talent:
35. The company works to discover talent
The company works to develop and train employees on the skills
36. needed
37. The company encourages new ideas
The company encourages creativity and innovation through incentives
38. system.
The Company has an available research center that supports research
39. and development
Sustainable Development:
Environmental Responsibility
40. The company is interested in reducing the environmental pollution
The company achieved an optimum exploitation of resources,
41. especially non-renewable resources.
The company owns a variety of means to deal with the surrounding
42. environment-friendly products
The company provides guidance on the use of products and ways to
43. get rid of them and their residues
The Company uses non-harmful products (eco-friendly) and set forth
44. in the Good Manufacturing.
45. The company recycles some materials
Economic Responsibility
The company is committed to government laws related to economic
46. aspect
47. The company is seeking to pay tax dues on time specified
The company contributes to the local economy by bringing hard
48. currency
49. The company helps in building infrastructure such as bridges…etc
50. The company contributes to the employment of local labor
Social Responsibility
51. The company is hiring people with special needs
The company owns programs help support education in the
52. community
The company owns a budget for social work as a financial support
53. such as community donating to charity
54. The company has binding laws for moral behavior
The company has plans for a health awareness to the community
55. courses
The Company follows the binding laws to ensure the safety of workers
56. from the product
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
103
Business Performance:
57. The company gets the best productivity of the individual
The company has the least cost to produce per unit compared with
58. competitors
59. The company has the least work rotation (staff)
60. The quality of products match with competitors
61. The company has continually increase in sales
62. The company achieves better profit compared with competitors
63. The market value of the company's shares increase on an annual basis
64. Return on investment commensurate with return on the industry
65. The Company manages cost effectively
66. The company has an exceptional position among competitors
1 2 3 4 5
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
104
Appendix (6): Panel of Referees Committee Letter (Arabic Version)
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