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bulletin - Prague College
BULLETIN
PRAGUE COLLEGE
CENTRE FOR RESEARCH &
INTERDISCIPLINARY STUDIES
07 19 33
CHILDREN'S BOOK
ILLUSTRATIONS:
VISUAL LANGUAGE OF
PICTURE BOOKS
Hana Hladíková
REPORT ON
THE FINANCIAL
EVALUATION:
MCDONALD'S
CORPORATION
AND YUM! BRANDS
Tamara Ayrapetova
THE FIBONACCI
SEQUENCE: NATURE'S
LITTLE SECRET
Nikoletta Minarova
61 73 93
PROGRAMMING
LANGUAGE
PARADIGMS & THE
MAIN PRINCIPLES OF
OBJECT-ORIENTED
PROGRAMMING
ETHICAL LEADERSHIP
AND LEADER MEMBER
EXCHANGE (LMX)
THEORY
BASED ON A CASE
STUDY IBM "LEADING
THE TURNAROUND"
Šejla Babič
Jan Bartoníček
GAME THEORY ITS APPLICATIONS TO
ETHICAL DECISION
MAKING
Evaluations of the contribution
that developments in the area
of ethical leadership and trust
have made to effective people
management...
Stefano Cavagnetto
Bruce Gahir
The basic theory behind
programming languages and
their history while taking a close
look at different programming
paradigms that are used today,
describing their differences...
Business & Economics
IT & Computing
Humanities
THEMATIC KEY
Art & Design
CRIS Bulletin 2014/01
3
HEAD OF CRIS
Stefano Cavagnetto
COORDINATOR
Masa Hilcisin
COMPUTING AND BUSINESS
EDITORIAL BOARD
Bruce Gahir
Dave Gannon
FINE ARTS AND DESIGN
EDITORIAL BOARD
Pascal Silondi
Simon Gray
George Allen
Jorge Boehringer
CONTENT EDITOR
Leah Adler
DESIGN & LAYOUT
Silvia Weinzettelova
To submit your work, please contact the
project coordinator of CRIS:
Masa Hilcisin <[email protected]>
© 2014 Centre for Research and
Interdisciplinary Studies, Prague College
ALL RIGHTS RESERVED. No part of this
publication may be reproduced, transmitted,
stored or used in any form by any means
without the prior written permission of the
publisher.
Names, logos, brands, and other
trademarks featured or referred to within
this publication are the property of their
respective trademark holders.
Printed in Prague, Czech Republic.
ISSN 1805-5109
4
CRIS Bulletin 2014/01
PREFACE
The Centre for Research and Interdisciplinary Studies (CRIS) was founded with the idea of developing interdisciplinary research crossing several fields and subject areas underlying the academic curricula at Prague
College, and its main purposes are:
•
To promote a medium of participation and discussions by means of regular interdisciplinary workshops and seminars.
•
To promote and to encourage the collaboration among different schools and programmes in the
design and creation of multidisciplinary courses in the college.
•
To provide a means of publishing research work for both students and staff as part of a quarterly
academic bulletin and e-journal.
•
To cooperate with other education institutions and organisations in the development of common
projects of interest.
The Centre was developed from projects initiated by Stefano Cavagnetto in the context of his role as Head
of the School of Business and the School of Computing, by Bruce Gahir, Principal Lecturer in the School
of Business and Computing, and by Pascal Silondi, Director of Libat and Principal Lecturer in Interactive
Media. Beginning in 2009, research in the following areas had been initiated:
1.
Game theory and its application to economics, business, philosophy, and international relations.
2.
The history of programming languages and history of computers.
3.
Experimental media (Prague College and the CRIS, formerly PCRC, is an associate partner for Underground City XXI an international interdisciplinary EU project).
4.
The history of cryptology and the science of enciphering.
5.
Art and mathematics: a profitable relationship in history - from classical geometry to fractals and topology.
By combining academic study with practical training, the CRIS aims to create an environment where personal
achievement goes hand-in-hand with social responsibility. Strategically, this offers students the chance to
actively collaborate in several research areas with the support of faculty members and lecturers of the college.
Since 2010 a quarterly Bulletin has been published detailing progress in relevant research activities of lecturers and students. This bulletin forms an integral part of the CRIS and provides a medium whereby the
research activities of the centre can be documented. Faculty members, lecturers and students belonging to
every school of the college are welcome to submit their work for publication.
You can find the published Bulletins of CRIS on Ebrary (electronic library), in the college library, in six
Prague libraries (Narodni knihovna, Knihovna Narodniho muzea v Praze, Ministerstvo kultury CR, Parlamentni knihovna, Mestske knihovne v Praze, Knihovna a tiskarna pro nevidome K.E. Macana), Moravska
zemska knihovna in Brno, Stredoceska vedecka knihovna in Kladno, Jihoceska vedecka knihovna in Ceske
Budejovice, Studijni a vedecka knihovna Plzenskeho kraje in Plzen, Severoceska vedecka knihovna in Usti
nad Labem, Krajska vedecka knihovna in Liberec, Studijni a vedecka knihovna in Hradec Kralove, Moravskoslezska vedecka knihovna in Ostrava, Vedecka knihovna in Olomouc, Krajska knihovna in Pardubice,
Havlickuv Brod, Zlin, and Karlovy Vary.
Deadline for the next issue is 31st December 2014.
CRIS Bulletin 2014/01
5
6
CRIS Bulletin 2014/01
THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
THE FIBONACCI
SEQUENCE: NATURE'S
LITTLE SECRET
NIKOLETTA MINAROVA
Fibonacci: a natural design, easy to recognise - yet difficult to understand. Why do flowers and plants grow in such a way?
It comes down to nature's sequential secret…This paper discusses how and when the Fibonacci sequence occurs in flora.
CRIS Bulletin 2014/01
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THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
FIBONACCI, SPIRALS AND GROWTH
FIBONACCI IN NATURE
When you sit in a garden and look around, you can easily recognise several natural designs. You see bees
buzzing around flowers with neatly arranged petals, trees whose trunks are surrounded by pinecones with
their distinctly patterned bracts, and maybe a little snail with a spirally shelled house on its back. But what
exactly makes these designs look the way they do?
It may sound weird, but it is actually a mathematical sequence, called the "Fibonacci series" which can explain
this phenomenon. Actually, this sequence of numbers, which seems to mysteriously pop up everywhere, is
not as weird as you may think. In fact, you will find that it would be weird if it was not found there at all.
The Fibonacci Sequence is a pattern of numbers generated by a particular rule (Dunlap, 1997, p. 37). It
starts with 0 and 1. These two numbers are added to get 1, then the new 1 is added to the previous 1 to
make 2. This pattern repeats itself as seen below:
0+1=1
1+1=2
1 + 2 = 3
2+3=5
3 + 5 = 8
5 + 8 = 13
0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89,…
This is known as a recursive sequence defined by the equations:
Fn represents the nth Fibonacci number.
CREATING A FIBONACCI SPIRAL
When arranged in a certain way, the Fibonacci sequence creates a special spiral pattern. This pattern can
be found in many places in nature.
1. Squares are drawn based on the Fibonacci
sequence as is seen in the picture to the
right. Graph paper should be used so that
the spiral is perfect. The 1x1 squares are
drawn first and then more squares are added based on the sequence of numbers.
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CRIS Bulletin 2014/01
THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
2. The next step is to draw curves in every
square, creating a spiral-like shape. A quarter of a circle is drawn in every square. This
spiral can be expanded by adding more
squares based on the Fibonacci sequence.
The Fibonacci spiral is a good approximation of a shape which occurs in many places in nature, such as
in snail shells or even the spiral of a hurricane (Constance, 2010, p. 1). However, it is not considered a
'true' mathematical spiral, as it is composed of fragmented segments of a circle and does not scale down
in size (Knott, 2010). The spiral creates a line from the middle of the spiral and increases by a factor of
the golden ratio, 1.618, in every square (Norton, 1999).
CREATING A FIBONACCI SPIRAL
The Fibonacci sequence occurs in the number of many flowering
plants. Think about how many plants you know which have 5,
8, or 13 petals…
As was previously mentioned, the Fibonacci sequence occurs very often in nature, not only in number form, but also as a spiral. Very often it appears
in flora, such as in the arrangement of seeds on flowering plants, the number of petals in sunflowers, or
even "phyllotaxy" which is the arrangement of leaves
around the stem (Britton, 2011). Of course, plants
and flowers do not have minds and do not actually
realise that they grow in this way. According to scientists, certain flora develop in the most efficient
way based on the biochemistry of plants as they develop new structures such as leaves or flowers which
provides an evolutionary advantage in promoting
the plant's survival (Rehmeyer, 2007).
Although this is the common belief, researchers are still not entirely sure whether this is the complete answer. Mathematicians Auguste and Louis Bravais were the first to find a mathematical proof which depicted
that a certain angle regulated the growth of plants (Smith, 2013, p. 66). They measured the angle between
successive primordia as they migrated from the centre of the apex of a flower finding that an "angle of divergence" occurred which was conditioned by Fibonacci numbers (Smith, 2013, p. 66). Their research, however, promoted more questions about why flora develop the sequence in the first place (Rehmeyer, 2007).
"Scientists have not entirely solved the
mystery, but an idea seems to be emerging…"
(JULIE REHMEYER, 2007)
CRIS Bulletin 2014/01
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THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
PINECONE PRINCIPLES
Pinecones, along with pineapples, seem to illustrate perfect examples of the Fibonacci sequence.
All pinecones develop in a spiral shape which starts from the base where it was connected to the tree (Carson, 1978, p. 134). There are usually two sets of spirals which circulate in different directions up to the top
of the pinecone (Dunlap, 1997, p. 130).In some cases, a pinecone is found not to incorporate the sequence
which is usually due to deformities caused by pests (Carson, 1978, p. 135).
The spiralled bracts going in opposing directions are adjacent Fibonacci numbers as is depicted in the images below (Simmons, 2011).
The same pinecone has 8 spirals in one direction
yet thirteen in the other (Dunlap, 1997, p.130).
The sequence is an approximation to an
irrational number meaning that the bracts of
pinecones should not line up (Collins, 2011).
If they did, the pinecone would be weakened
and susceptible to breakage (Collins, 2011).
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CRIS Bulletin 2014/01
THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
Peterson (1992) describes how a mathematical model of sunflower floret and seed development was created which illustrated how the florets are produced one by one at the flower's centre, pushing the other
florets outward. This is the same thing that happens with pinecones. Every bract settles into a position
which happens to have a specific constant angle of rotation pertinent to the position of the last bract, and
this is what creates the spiral pattern (Peterson, 1992).
Naylor (2002, p. 163) states that these spirals can be easily simulated: assume that there are k bracts in the
arrangement where the most recent is "1" and the previous bracts are 2, 3, 4, etc. so that the most further
bract is k. Given that each bract has an area of 1, then the circular face area is k and the radius is √k/π.
This makes the gap between the centre of the pinecone to each bract proportional to the square root of
its bract number. As the angle "α" between any two bracts is constant, the angle of bract k is simply kα.
SEED HEADS AND SUNFLOWERS
The Fibonacci sequence allows for the maximum number of seeds in an arrangement of seeds in the seed
heads of sunflowers (Grob et al., 2007, p. 857). There is no crowding in the centre and no spaces at the edges
meaning that the sunflower has the perfect space organisation for its seeds (Grob et al., 2007, p. 857). This
is due to a growth characteristic of sunflowers (Segerman, 2002, p. 1). Individual seeds grow at the center of
the flower and continue adding seeds pushing those on the edge outwards (Heimbuch, 2002). As it develops
in a Fibonacci arrangement, seeds are always grouped uniformly and they stay compact (Heimbuch, 2002).
To optimally fill the sunflower head with the highest amount of seeds, the most irrational number should be
used, which is phi, otherwise known as the golden ratio (Winer, 2013). The approximation for phi is as follows:
Where Fn is the nth Fibonacci number.
Using this irrational number to spread out, the seeds makes it harder to see the number of lines in the spiral
of a sunflower; however, this means that the distribution is maximally efficient (Winer, 2013). If the spaces
between different spirals were easy to see, it would signify that this space is "wasted" and therefore not
being effectively utilised (Winer, 2013).
CRIS Bulletin 2014/01
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THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
The Fibonacci metric, M(n), is defined as the number of terms in the Zeckendorf representation of n (Segerman, 2002, p. 1). Zeckendorf's theory declares states that all positive integers can be illustrated as a sum of
precise Fibonacci numbers, as long as there is an additional condition that no two adjacent Fibonacci numbers
are used (Segerman, 2002, p. 1). Colouring sunflowers according to the Fibonacci metric illustrates subtle
connections between the spiral and the sequence as is seen in the image below (Segerman, 2002, p. 3).
138
117
130
143
122
135 101
127
106
140
62
54
41
33
46
38
72
51
119
98
49
64
43
77
56
111 90
69
35
137 116
CRIS Bulletin 2014/01
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18
2
39
26
5
1
13
14
11
19
27
32
40
53
61
74
87
95
108
142
29
24
37
45
58
66
71
92
79
100
121
68
113
134
123
89
55
76
63
50
136
102
42
16
115
81
47
34
128
94
60
21
8
3
6
129
12
31
107
73
52
23
7
48
124 103 82
86
65
44
36
120 141
99
15
9
22
57
4
17
133
78
28
12
30
112
91
70
20
25
85
132
75
59
93
83
67
80
114
104
96
109
88
125
84
110
97
118
105 139
126
144
131
THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
LEAF ARRANGEMENT: PHYLLOTAXIS
Phyllotaxis is the arrangement of leaves around
a stem. There are two different main types of
leaf arrangements in the world: one is where the
leaves spring from opposite sides of each other in
a decussate pattern, and the other is the spiral pattern which displays the Fibonacci pattern (Mitchison, 1977, p. 270).
According to Mitchison (1977, p. 274) Fibonacci phyllotaxis is a mathematical requirement for the expanding apex of a plant which provides appropriate spacing for the positioning of new leaves. It is noted as a
"stable mathematical phenomenon" which seems to appear everywhere, not only in flora, but in nature
(Mitchison, 1977, p. 278). As previously discussed, similar to the distribution of seeds on a sunflower head,
the arrangement of successive leaves are separated by phi (University of Chicago, 2013, p. 1). This means
that they are optimally distributed and have the best access to sunlight which is realised by inanimate physical systems (University of Chicago, 2013, p. 1).
SEED ARRANGEMENTS IN OTHER FLOWERS
Seed arrangements can be found in all different types of flowers as is seen on this page. Like sunflowers,
which were discussed in a previous section, the majority of flowers have two sets of spirals which go in
opposite directions (Knott, 2010). The number of spirals going in both ways is almost always adjacent
Fibonacci numbers (Peterson, 2006). Very often it happens that there are 55 and 34 spirals.
CRIS Bulletin 2014/01
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THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
PRETTY PETALS AND PERFECT SPIRALS
Most people have never taken the time to look at flowers and to really notice them. If you have, you would
have realised that almost all flowers have a certain number of petals.
Lillies have 3 petals. Buttercups and wild roses have 5. Delphiniums have 8, and cinerarias have 13. Most
asters have 21 petals. While ordinary field daisies have 34 petals, other types can have 55 or 89 petals.
Some of these flowers are very specific and always have a Fibonacci number of petals while others are
not as precise with the number, but still average a Fibonacci number (Peterson, 2006). In such cases, it is
more likely that underdevelopment occurred and the flower has one or two petals less than it is meant to
(Peterson, 2006). As with most flora, the reason for these amounts of petals has to do with maximising the
efficiency of light during the growth process of plants (Knott, 2010).
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CRIS Bulletin 2014/01
THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
FIBONACCI IN ROSES
Rose petals develop in a distinct Fibonacci pattern, where each new set grows between the spaces of the
previous set (Peterson, 2006). This means that the more developed petals will not steal light from the
newer petals (Peterson, 2006).
It is obvious after some time that the average angle the petals utilise while developing is 137.5 degrees
(Johnson, 2013). This is the most effective way of giving as much needed sunlight to each petal as is necessary (Johnson, 2013). If any two adjacent rose petals are taken and divided, their value is always equivalent
to phi, the Golden Ratio (Peterson, 2006).
HOW TO CREATE RAINBOW ROSES
The Fibonacci sequence can be implemented when creating "rainbow roses" (Osterrieder, 2012). This
technique was developed by Peter van de Werken with his knowledge of plant phyllotaxy (Osterrieder,
2012). The arrangement of rose petals means that the first and sixth petal will be on the same vertical line
(Osterrieder, 2012). By cutting the stem into four equal parts and placing each part into different coloured
water, the petals change colour depending on which position in the spiral they have (Sarang, 2013).
CONCLUSION
Throughout this report, it can be seen that the mathematical properties of the Fibonacci sequence is found
in many places in nature, mainly flora. Flower petals and leaves grow in Fibonacci numbers. Sunflower
seeds grow on the seed heads in spirals correlating to the sequence as do the bracts of pinecones.
Although there has been extensive research into the topic, scientists and mathematicians are still not completely sure why this sequence seems to pop up everywhere. It has been presumed that it is just nature's
way of getting maximum resources available to it, and taking the easiest path to these goals.
CRIS Bulletin 2014/01
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THE FIBONACCI SEQUENCE: NATURE’S LITTLE SECRET
REFERENCES
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Collins, D. (2011) Mona Lisa and Fibonacci Pinecones. Available at: http://www.warren-wilson.edu/~physics/PhysPhotO
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Carson, J. (1978) 'Fibonacci Numbers and Pineapple Phylloaxy', The Two-Year College Mathematics Journal, 9(3), pp.
132-136, MAOA. [Online]. Available at: http://www.jstor.org/stable/3026682 (Accessed: 19 January 2014).
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IMAGE LIST
PAGE 6: Horniak, D. (2013) Pink Flowers [Photograph]. Photo taken exclusively for this paper. Photographer's gallery:
http://www.totem.cz/galerie.php?ot1=25&ot2=21798
PAGE 7: Grizdave (2011) Math Pine Cone. Flickr [Online]. Available at: http://www.flickr.com/photos/
grizdave/2736846377/ (Accessed: 27 December 2013).
PAGE 8, LEFT: Knott, R. (2005) Fibonacci Pine Cone [Online]. Available at: http://personal.maths.surrey.ac.uk/ext/R.
Knott/Fibonacci/fibnat.html (Accessed: 27 December 2013).
PAGE 8, RIGHT: Knott, R. (2005) Fibonacci Pine Cone [Online]. Available at: http://personal.maths.surrey.ac.uk/
ext/R.Knott/Fibonacci/fibnat.html (Accessed: 27 December 2013).
PAGE 9, TOP LEFT: Stockbyte (2008) Sunflower. Stockbyte [Online]. Available at: http://media.treehugger.com/
assets/images/2012/08/71044124-th.jpg.644x0_q100_crop-smart.jpg (Accessed: 27 December 2013).
PAGE 9, TOP RIGHT: Sefaoncul (2011) Sunflowers. iStockphoto [Online]. Available at: http://www.pbs.org/wgbh/
nova/assets/img/describing-nature-math/image-05-large.jpg (Accessed: 27 December 2013).
PAGE 9, BOTTOM: Segerman, H. (2010) The Sunflower Spiral and the Fibonacci Metric [Online]. Available at: http://
ms.unimelb.edu.au/~segerman/papers/sunflower_spiral_fibonacci_metric.pdf (Accessed: 24 January 2014).
PAGE 10, TOP: Kshitij Education India (2013) Different Types of Phyllotaxy [Online]. Available at: http://www.kshitij-school.
com/Study-Material/Class-11/Biology/Morphology-of-flowering-plants/Leaf/3.jpg (Accessed: 22 January 2014).
PAGE 10, CENTER LEFT: Hamamatsu, F. (2012) Avage Spiral [Online]. Available at: http://fractalfoundation.org/
OFCA/agavespiral.jpg (Accessed: 24 January 2014).
PAGE 10, BOTTOM LEFT: Baab1 (2008) Fibonacci Flower. Flickr [Online]. Available at: http://www.flickr.com/
photos/[email protected]/2593294045 (Accessed: 27 December 2013).
PAGE 10, BOTTOM RIGHT: Jansson, S. (2006) The Divine Proportion. Flickr [Online]. Available at: http://www.flickr.
com/photos/[email protected]/171302091 (Accessed: 27 December 2013).
PAGE 11, TOP LEFT: Werk, R. (2003) Purple Coneflower [Online]. Available at: http://www.ndsu.edu/pubweb/
chiwonlee/plsc211/student%20papers/articles03/rachel.werk/purple-coneflower.jpeg (Accessed: 20 January 2014).
PAGE 11, TOP RIGHT: Knapp, S. B. (2013) Fibonacci Flowers [Online]. Available at: http://1.bp.blogspot.com/GTPAFW1W-Nk/UXtE2PYcXVI/AAAAAAAALeg/yTJcXjJ8CPU/s1600/500Coneflower.jpg (Accessed: 20 January 2014).
PAGE 11, CENTER: Peterson, K. (2011) Fibonacci Flower [Online]. Available at: https://www.sciencenews.org/sites/
default/files/5907 (Accessed: 23 January 2014).
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org/sites/default/files/5906 (Accessed: 23 January 2014).
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org/sites/default/files/5910 (Accessed: 23 January 2014).
PAGE 12, TOP LEFT: Computer Images (2011) Fibonacci Rose [Online]. Available at: http://www.computerimages.
com/photo_gallery/photos16.html (Accessed: 27 December 2013).
PAGE 12, TOP RIGHT: INTVGene (2008) Rainbow Rose. Flickr [Online]. Available at: http://www.flickr.com/
photos/intvgene/2618479990/ (Accessed: 7 January 2014).
PAGE 12, BOTTOM: Wanorizan (2014) Rainbow Roses [Online]. Available at: http://alldaychic.com/rainbow-rosesdiy/ (Accessed: 18 March 2014).
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CHILDREN'S BOOK
ILLUSTRATIONS:
VISUAL LANGUAGE OF
PICTURE BOOKS
HANA HLADÍKOVÁ
High-quality picture books that merge text and illustration together in order to tell a story are eminent for healthy
mental and social growth of children. This paper is to outline the benefits picture books bring to children between the
ages three to eight, determine functions of its illustrative language, examine the process of its production, and point
out a set of elements that, according to number of professional children's book illustrators, significantly contribute to
the success of a picture book.
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APPEARANCE OF CHILDREN'S BOOKS AND THEIR BENEFITS TO CHILDREN
Until relatively recently, there were very few books meant primarily for children to read. Children had to
make do with literature that was not attuned to their level of understanding, neither in theme nor its language and vocabulary (Kiefer, 2009, p. 6). That changed in the late 19th century. Thanks to new printing
technology that made mass production of illustrated books possible and economically accessible, the middle class was also able to enter the world of readership. In addition to that, the attitude towards childhood
was altered at that time, from almost solitary to more sentimental and respectful to its different needs, preparing a perfect ground for this new genre of picture books to grow in and flourish (Revolution21, 2013).
Contrarily to its generic categorisation as children's books, picture books entertain a wide spectrum of
readers, and in many cases, even non-readers, from an early age through adulthood and beyond. Their
power to inspire is wide. Picture books and their illustrations "can hook children into a lifelong love of reading" (Reading Is Fundamental, 2010). That is essential for their further development and their ability to
perform well both in school and later in life, for the amount of information that each individual must cover
in order to become successful in any line of career is now steadily increasing. For that reason, in many
nations nowadays picture books are increasingly perceived as just an aged tool for encouraging children to
start reading on their own, abandoning its other benefits in a race to get the children to read earlier and
turn to chapter books as quickly as possible, in some cases skipping the stage of picture books entirely (Bosman, 2010; Sloat, 2013). It is due to pressure on both the parents' and industry's sides that are changing
the traditional late Victorian view on the place of children's books in children's lives.
However, picture books have much more to offer. Firstly, its pictures introduce and explain the world to
children in a comprehensive way even before they are able to read. It allows the children to get accustomed
to new words and build up their vocabulary through both verbal and visual references provided by the book.
Although a broad public generally believes differently, a vocabulary of picture books is usually very "rich, evocative and engaging" according to Pierce (2010). Many times its quality is much greater than language used
in chapter books. The reason is in its average length allowing about five to eight hundred words. Because of
that, "an author must craft each and every word, sentence and paragraph with care;" being exposed to such a
quality of language aids significantly the growth of the children's language skills (Pierce, 2010).
Picture books also broaden general knowledge and enable children to get a better understanding of themselves and their integration within a society (Reading Is Fundamental, 2010). Its reach is as wide as its variety of themes. Picture books often trigger children's imaginations, which aid children to think of new ideas
and bring new possibilities into their lives, both immediate and up-coming. Anita Silvey, for instance, states
that many leading figures of the USA she has interviewed declared that their career choice was triggered
by a children's book they read in their childhood (Library Of Congress, 2010).
Secondly, picture books require a certain amount of interaction from children; at the very least they have
to turn the pages. This trains the child's concentration and can prolong its attention span. Another benefit
is the development of the child's memory. Picture books are built in sequences that link pages together.
The sequence is usually made of both visual and verbal elements and many times produces a certain pattern
within the book. A great example of such a sequence is to be found in the book, Brown Bear, Brown Bear,
What Do You See?, written by Bill Martin Jr. and illustrated by Eric Carle, where a great rhythm of rhymes
introduces animals that are to appear on the next page (Pierce, 2010).
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The last, but not the least, reason to read picture books is perhaps the most important. Although the
theme and purpose has changed repeatedly during the short life span of this genre, the majority of the
most successful children's books are crafted to entertain, to pleasure, and to employ the child's imagination. It provides delight and entertainment that not only shows children that eventually it will be fun to
become an active reader but also connects generations and people in general through the sharing of these
engaging stories, experiences, and valuable time spent together. Anita Silvey claims that children's books
are often attached to more than just their stories, amazing new worlds, or memorable characters; more importantly they are connected to the people the young reader knew and loved in his/her childhood (Library
Of Congress, 2010). Sharing picture books with others provides children with feelings of love and security,
feelings of utmost importance in their young age.
PURPOSES OF ILLUSTRATION IN PICTURE BOOKS
Illustration, as well as cover design, is one of the marketing tools a children's book publishing company
employs to increase its chances in its highly competitive market. A picture book's artwork, both that on
a cover and inside, creates a first and second impression on a potential reader and buyer and therefore is
crucial for its sell ability. Tori Sloat (2013), however, adds that even though "illustrations may sell the book
at the beginning … to last a lifetime, the book has to begin to rely on the story and how it reads." This bond
between the book's visual and written parts is a true key to its lasting success. To harvest this connection,
the illustrator must follow the written word of an author, but also add his/her own personality, view, humour, and insight to the story.
The imperative role of illustrations within a picture book is to take the written story to a new level of entertainment. The artwork should stand for as much of the story as the words, expanding the story without
duplicating the text itself while acting as a mediator between the text and the reader, allowing the reader
"to feel the words" (Murguia, 2013; Downing, 2013; Sloat, 2013). Ann Marie Finn adds that she likes "to
use illustrations to create more of an atmosphere … and add another dimension to the story" (Finn, 2013).
She also states that picture books' illustrations that are very often full of action and interesting additions to
the story can lead to an extended attention span of children who are easily distracted otherwise. Another,
perhaps more technical, purpose of illustrations is to set a seductive rhythm, hierarchy of elements on a
page, and easy flow of the story while encouraging the reader through its layout and action depicted on its
pages to keep enjoying the narrative until its end (Meidell, 2013).
GETTING THE RIGHT BOOK INTO THE HANDS OF THE RIGHT ILLUSTRATOR
Amongst the first factors in need of consideration in the process of producing artwork for an approved
manuscript is the suitability of an illustrator and the narrative in terms of style and technique appropriate
for the publication. Both of these influence the overall mood of the story greatly and can therefore contribute to the success or failure of the publication. Martin Ursell (2013, p. 96) states that "the author illustrator is a rare thing and most children's illustrators illustrate other writer's stories not their own." For that
reason, it is imperative to select a fitting illustrator and determine the art director's expectations for the
book at the very start so no misunderstanding imperils the smooth progression of the publishing process.
Christine Tripp argues that from a certain point of view, a style and a technique of illustrations for the particular book are in fact chosen by an art director's preference of an illustrator, for the majority illustrators
have a recognisable "signature style", or even a variety of styles, from cartoonish to very realistic, using traditional media or working digitally instead (Tripp, 2013). Martin Ursell also mentions that many beginning
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illustrators ponder about "not having a style and how to get one", which he thinks to be a pointless worry
(2013, p. 51). He says that "one's 'style' is simply the way one draws. Just as we all write in a distinctive
way, drawing is no different" (Ursell, 2013, p. 51). In other words, there is no need to learn a distinguishing
personal style of drawing, for everyone already has it. In case an illustrator uses a variety of styles, one is
either selected by the art director when an offer is made to have a go on a manuscript, or, especially when
the illustrator is also the author, the choice is left to the illustrator's judgement. The final decision is often
linked to an overall mood and theme of the story. Tom Lichtenheld (2013, author's italics) gives an example of this practice, "if a story is soft and lyrical, I'll use watercolours or pastels, but if it's gritty, like Goodnight,
Goodnight, Construction Site, I'll use crayon on textured paper."
In many cases, an art director preselects several illustrators whose personal styles are in tune with the
manuscript and then asks them to produce sample illustrations. The sample can vary slightly according to
different publisher houses, but usually it is a sample spread for a provided passage of the manuscript, which
sometimes is extended with a more detailed study of the book's main character(s) (Ursell, 2013, p. 104).
Then one of the illustrators is approached with an offer of the job. The final decision is, however, made
by the artist by accepting or declining the job. Teri Sloat states that a few times she recommended the art
director to hand the job over to another illustrator "because I knew they were right for the job and I wasn't"
(2013). Also, Helen Craig points out that it "is not a good idea to illustrate a book you don't like, because
there will be no pleasure in it. And if there is no pleasure in your drawing … it transmits itself into the book"
(Creative Choices, 2009). The illustrator spends a rather large amount of time working on a book, which
can vary from a few months up to a year, and it would take much more discipline to finish the project, if the
illustrator is not enthusiastic about the story itself (Teri Sloat, 2013; AlbanyKALB, 2013).
ILLUSTRATING PROCESS
The very first step the illustrator does after accepting the job is to familiarise oneself thoroughly with the
whole manuscript. The story is a paramount source of illustrator's inspiration, and for that reason it is essential
to pay due attention to its details that can trigger an interesting insight into the story, providing the illustrator
with a good starting point. There are many ways how to bring the illustrations to life. Movement, both in
body language, face, and settings together with the expressiveness of all the above, is as important as thorough consistency of the visual language of the whole book. Moreover, the emotional content of the story
that is often communicated through the combination of composition, colour, line, or style can bring excitement, engagement, and something the reader can relate to, which makes the illustrations a very powerful part
of the reader's experience. Originality of settings, choice of flat or dimensional images, and overall feeling of
the narrative can also make a considerable impact on attracting and keeping the reader's attention in the story
(Dewdney, 2013; Finn, 2013; Murguia, 2013; Lies, 2013; Tripp, 2013; Waites, 2013; Downing, 2013; Meidell,
2013; Sloat, 2013; Lichtenheld, 2013). It can be argued that many times it is a careful combination of these
components that makes the illustrations special and dear to the reader, and each illustrator has a different way
how to engage these elements and which elements he/she puts more emphasis on.
To point out an example, Teri Sloat (2013) states that she firstly considers "the weight of the story", which
includes analysing the narrative's mood, theme, significance of characters, placement of the story, and its
natural pace. Ann Dewdney (2013), however, claims that her "design process is based entirely on both
the flow of the book and the emotional content of the pages". It is reasonable to conclude that whichever
process the illustrator chooses to follow a consideration of these elements can assist the illustrator greatly
in making important decisions such as the establishment of a balance between text and images, development of characters, overall layout, usage of white space, text division, colour scheme, or visual style.
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RELATIONSHIP BETWEEN TEXT AND IMAGE
A fine relationship between words and images is vital for picture books. Generally speaking, "what a picture adds to a story and what the words leave out, is key" (Revolution21, 2013). Both the author and the
illustrator should have this fact in mind when working on the book. Ideally, the author is considerate to the
needs of the illustrator and writes the text in a way that leaves enough room for the illustrator's creativity
to enhance the author's creation. In other words, the author should be leading the reader through the action and leave the illustrator enough space to portray the mood of the story and details of the narrative's
scenes and characters. This ensures that words and images are not to duplicate the statement of the story,
but rather complement each other (Salisbury, 2004, pp. 93-97; Paul, 2009, p. 158; Dils, 2009, pp. 26-27).
Therefore, one of the attributes of a successful picture book's illustration is often a complementary or
parallel story line enhancing the original manuscript. A wonderful example of such practice is an addition
of a cat character to the book Bears on the Stairs (Figure 1).
Fig.1. Lynne Chapman, Bears on the Stairs, 2010.
Even though it is not in the manuscript, the cat engages the reader in a whole new level by enhancing the story
in a very clever way. It brings the opportunity of somewhat humorous interaction between the bears and the
cat, reflecting the true feelings of the main character by proxy. It also enables the illustrator to subtly indicate
places of higher interest on the page (Open College of the Arts, 2011).
However, the utmost responsibility of the illustrator is to maintain consistency of both verbal and visual communication levels of the book while enriching the story without contradicting the author's manuscript. To do
so, many illustrators make a list of features and action that is encoded into the story already. Firstly, there is a
certain level of action bond that should appear in the book. If the text portrays a busy character in a heap of
action, the illustration should be complimentary in its mood. Nevertheless, there are some exceptions to this
rule; for example, clever illustrations of Marla Frazee's picture book called A Couple of Boys Have the Best Week
Ever, or Marta Altés's picture book No!. While Marta Frazee's illustrations use humour to contradict the text
itself, which in the end adds a very special feeling to the book as a whole and make it rather enjoyable, Marta
Altés's contradicting illustrations are based on presenting two different points of view to the reader, the human's and the dog's (Northurp, 2012, p. 2; Salisbury and Styles, 2012, pp. 108-110).
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Figure 2 and Figure 3 illustrate differences in both of these approaches and show rather well how the contradiction is applied to both stories. Marla Frazee challenges the reader's conception of the written truths by visual
inversions. For example, when James (the boy in blue shorts) comes to visit Eamon's family, the text implies
that he comes with just a couple of his belongings, while the image clearly shows an abundance of boxes and
bags bursting with James' stuff. Later, the text indicates the boys' decision to stay home, while the illustration
shows them running away so fast they each lost one of their shoes and little clouds of dust formed behind them.
Fig.2. Marla Frazee, A Couple of Boys Have the Best Week Ever, 2008.
Marta Altés's approach is different. The textual and visual contradiction is based on the difference of a human's and a dog's conception of desirable and undesirable behaviour of a dog. While the dog assumes his
family appreciates his frequent help with a variety of tasks and calls him No, the reader sees images of the
same situations from a human point of view, seeing how the dog is being naughty while his family is trying to
stop him by shouting 'no' at him.
Fig.3. Marta Altés, No!, 2011.
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CHARACTER DEVELOPMENT
Crafting a believable character is imperative for the success of any picture book, especially because the majority of contemporary picture books are character-driven. However, creating such a character is a rather
personal process for each artist, and therefore it varies somewhat from one illustrator to another.
First of all, the character should be based on the text of the narrative and generically recognisable characteristics. Getting to know the character thoroughly is therefore the best place to start. While some
specifications come usually from the narrative itself, the rest is based on research. The research can provide
the illustrator with both general identifiable features and delicate details of any animal or human that the
artist can then apply to his/her drawings, making the characters accurate and instantly recognisable for the
reader as a specific animal species or human being. While Will Terry states that those features of a cat
such as pointy ears, eyes, whiskers, triangular nose, and wiggly tail applied on any shape will be deciphered
by a reader as a cat, Lynne Chapman adds that it is a fine simplification and exaggeration of those features
that in fact shapes the character, so "it looks real, it looks like a cat, but actually no, it's not. It's got this
other picture book quality to it" (Will Terry, 2011; Open College of the Arts, 2011). Moreover, by making
and adhering to general lists of physical appearance, personalities, abilities, and habits of their characters,
illustrators safeguard the continuity of visual appearance of characters through the whole book.
Illustrators also often work with stereotypes. Martin Ursell (2013, p. 49) claims that "stereotypes are useful,
essential even, in communicating character" for they present the reader with something instantly known
to him/her. The artist, however, should build on stereotypes rather than make universal illustrations, for
those would lack any diverse personality; a feature essential to any picture book's character. Furthermore,
stereotypes often present only a single viewpoint which leads to failure of the book in the sense of broadening the children's horizons and encouraging their ability to form a more complex understanding of a
story, topic, or people (Adichie, 2009). For that reason, stereotypes should be used wisely and only serve
as a base to add the distinctive personality of the character that comes always from the particular story.
As for the character's gender preference, it has a tendency to cycle. While a study from 2011 revealed
male characters outnumbering female in picture books, some illustrators that were interviewed stated
that about 20 years ago, the situation was reversed and there was a significant push for including more
male characters into picture books to encourage boys to read more (Flood, 2011; Sloat, 2013; Lies, 2013).
While the lion's share of picture books nowadays are written clearly with one or the other gender of the
character in mind, there are some gender-neutral manuscripts that leave the decision up to the illustrator.
The attitude of illustrators to this topic is threefold. Firstly, there appears to be a double standard, for girls
will gladly read books with male characters, but boys do not as eagerly read 'girl' books (Open College of
the Arts, 2011; Murguia, 2013; Dewdney, 2013). For that reason, many illustrators would pick a boy to
be their leading character, as Lynne Chapman did, for instance, in Julia Jarman's picture book Bears on the
Stairs (Open College of the Arts, 2011).
Tom Lichtenheld has a completely different approach to this matter. He tries to break the general assumptions and prejudice of a need to have a male in the role of the main character. "For instance, when
I'm reading to kids and come across a character of unspecified gender, I'll make it a female. I can actually
detect a little hiccup in the children's understanding of the character because they assume it will be a male.
I've even had kids protest that it should be a boy. Go figure" (Lichtenheld, 2013).
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Secondly, the decision of the illustrator regarding the gender of a character can be influenced by personal
reasons. There is an increased inclination to put one or the other gender as a main character based on the
illustrator's own family background, especially the gender of the illustrator's own children. Other reasons
can be purely artistic. Christine Tripp (2013) for instance, would probably draw a girl, because she loves
"detail and quirkiness, and find both hairstyles and clothing can be manipulated by me, to a greater extent,
with a girl than with a boy".
Many illustrators indicated that their decision would be based on the story itself, depending on the subject
matter, action, setting, plot, and genders of the other characters in the narrative (Finn, 2013; Lies, 2013;
Waites, 2013; Downing, 2013; Meidell, 2013). While Brian Lies (2013) adds that he likes to "listen for
clues in the text – did the author IMPLY a boy or a girl?", Ann Marie Finn (2013) contributes with a great
example of this advice in use, "I used a girl as the main character as it was about someone who despaired of
their hair, so it made sense to have a girl for that".
LAYOUT
There are a few elements related to the layout that can enhance or diminish the reader's experience.
Therefore, it is essential to keep them in mind and find a good solution for each publication to give it its
best chance to succeed. To start with, many picture books work with full spread illustrations and therefore,
a bleed1 and a gutter2 must be taken into account at all times. No important parts of the illustration should
be placed near the gutter or too close to the bleed to prevent unwanted cropping or disruption in the
image. According to Christine Tripp (2013), it is quite a common mistake even for the most experienced
illustrators to do, because both pages of each full spread illustration are done as one continuing artwork
and it is easy to get consumed by one's enthusiasm. If the illustrator happens to forget about the bleed and
gutter, the illustration must be redone.
Secondly, a distance from the gutter and the
bleed line must be always kept when dealing
with the text to ensure the reader can go
through the book without any disturbance,
and while it is rarely the illustrator's duty to
deal with the text itself, it is usually his/her
responsibility to leave enough space for
the text in the layout of the artwork.
In that sense, the illustrator must respect the gutter and the bleed limitations as well as the responsible
graphic designer. To make sure that the block of text "will not overlap an important element of the illustration … and the illustration will not interfere with the viewing and readability of the text", the illustrator
needs to create an unoccupied zone within the artwork big enough to place the text into (Tripp, 2013).
The right size of such an area can be calculated by using a dummy spread with text in correct size and font
provided by the publisher. Lynne Chapman, for instance, likes to get such dummy spreads for each book
she is working on, for it allows her to judge the space easily, even though the text's placement is not yet
accurate (ShooRaynerLife, 2011).
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1
A bleed – an overlapping area that is cropped off in the process of binding
2
A gutter – line where two pages are bound together
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THE FLOW OF THE STORY
Establishing a natural, engaging flow of the narrative's story is imperative for the success of a picture book and
its ability to be beneficial to children. The flow can be affected by many factors, such as the verbal pace of
the narrative, division of the text, layout, composition of each page, and interaction of text and images. While
the verbal pace is established by the author, the text division is done either by the editor or illustrator and is
connected closely to a choice of a particular section of the text that is to be interpreted visually by the artist.
While there is no instant recipe for the right text division, there are some issues both the editor and the illustrator should have in mind. As it was already mentioned, it is the author's responsibility to lead the reader
through the action. Illustrations, on the other hand, should engage the reader's imagination and stimulate
emotional responses while leaving enough space for the reader's own interpretation of the text. A shadowy
figure, a set of eyes glowing in the darkness, empty rooms, or busy scenes can be much more powerful than
a simple visual depiction of the action already communicated through the author's writing. For that reason, it
is often beneficial to leave the illustrator free hand in picking the text to illustrate and it is also preferable by
the majority of illustrators who welcome this challenge (Salisbury, 2004, pp. 96-97; Creative Choices, 2009).
The paramount purpose of the pacing is to engage the reader and encourage him/her to turn to the next page
and the next page until the entire book has been read. "The urge to turn the page can be weakened if images
or spreads feel repetitive in terms of shape, colour, or scale. Each spread must be designed with its relationship
to the preceding and following pages in mind, and indeed its relationship to the flow of the book as a whole"
(Salisbury, 2004, p. 83). The layout of elements on the individual pages naturally adds greatly to this effort;
nevertheless, it is the interaction of the text and the image in relation with each other or a composition of the
parts of the illustration itself. Orientation of action or actions occurring in the illustration is also often taken
into account. This can be related both to the movement of the leading character or other parts of the illustration. For instance, a character positioned in the lower left-hand corner of the spread running toward the edge
would motivate the reader to find out what the character is running towards and subsequently initiate a page
turn (Nikolajeva and Scott, 2006, p. 152).
Likewise, a variety of angles, viewpoints, orientation of action, and composition can complement the pacing of
the book and influence a feeling and drama that comes from the narrative. The pace is usually established on a
storyboard that is made of small thumbnails of all 32 pages3 of the picture book. However, only about 24 pages
are usually dedicated to the story itself. The remaining pages are used for endpapers, a title page, a copyright
page, a dedication, and in some cases, a right-hand first page and left-hand last page of the story. An example
of a storyboard (Figure 4) for A Tale of Two Penguins picture book shows both the story division on spreads
and pacing that is, as usual, developed through thumbnail sketches, for it is friendly to making any changes in
a small amount of time. A variety of cropping, viewpoints, and layouts were used to communicate emotions,
add drama, and bring a change of pace. A graphic element of borders around smaller images was used to add
a partition firstly and eventually interaction between pages and the image itself later on. A lonely figure of a
penguin framed inside the border of left page of the second spread is in strong contrast with the opposite page
full of penguins having fun and communicates a different approach of the two main characters to the life and
celebrations. The movement is mostly oriented from left to right, encouraging the reader to move forward,
and is only reversed on two spreads where such a break of the established pattern was in tune with the action
within the story. Endpapers were used to add to the narrative; for example, the back endpaper picturing the
arrival of a package with a gift to a human home, while the story ends by the penguins sending the packages
out on the last spread of the book.
3
A majority of picture books are 32 pages long. The reason for that can be traced to the printing process. If the publication is
longer or shorter, it is always by 8 more/less pages.
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Fig.4. Hana Hladíková, A Tale of Two Penguins Storyboard, 2014.
Top: Fig.5. Jerry Pickney, The Lion and the Mouse, 2009.
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COLOUR CHOICES AND STYLE
Although the colour palette greatly affects the overall feeling of a picture book conveyed to the reader, its
selection, even though based on what the story needs, seems to be an intuitive process for a majority of
illustrators. Many times, there are a limited number of colours repeatedly occurring through the whole
book, with the rest complementing them (Finn, 2013). This approach provides a continuity and feeling of
wholeness within the book. Nevertheless, the utmost purpose of the colour is the creation of a mood. The
mood can be triggered by many sources. Colours often convey the emotional load of the picture, "such as
paintings done in tones of grey to express dreariness/unhappiness" (Lies, 2013).
A set of colours can be also picked to complement the setting of the story, or its theme, as Teri Sloat
(2013) has done in her picture book, I'm a Duck, where she worked with "springtime colours" of pastels, or
the use of yellows and browns in Jerry Pickney's book, The Lion and the Mouse (Figure 5) (Meidell, 2013).
In some cases, colours are used to communicate the time of day, different seasons, or for establishing an
area of focus within the illustration. Other times, colours are picked to create enough contrast within the
picture. For instance, if the character is dressed in blue jeans and the story calls for a sofa the character is
to sit on, the colour of the sofa should not be blue also.
IMPORTANCE OF COOPERATION WITH AN ART DIRECTOR, EDITOR…
Producing a picture book is a long process involving many people on different positions working as a team.
Because of its very competitive market, only the best work can be accepted and "a skillful art director can
bring out the best in an illustrator" (Tripp, 2013) by providing another educated opinion on the artwork.
Art directors are also equipped with "different set of experience when it comes to viewing art so they can
add from there great depth of expertise" (Meidell, 2013).
All illustrators stated that their cooperation with the art director is a critical part of their process. As it was already mentioned, the job of the art director starts even before the illustrator is chosen, and continues through
the whole time of the book creation after the cooperation with the selected illustrator is confirmed. Art directors approve the route the illustrator is taking in different stages of the illustrating process, from sketches of
characters, through storyboards, and rough sketches, to the final artwork, which gives the illustrator a sense
of security that his/her final artwork will be accepted. In addition, the art director encourages the illustrator
to produce the best artwork possible by providing helpful suggestions for changes, corrections and additions
in the artwork, honest comments throughout the whole process, and any other support the illustrator needs.
CONCLUSION
Producing quality literature for young children is an enormous responsibility. Illustrators have a great impact on the ability of picture books to function correctly and succeed on the competitive market. An
ultimate intention of this thesis was to determine the complexity of a picture book illustrator's job, point
out elements that help the illustrator to produce an engaging, successful art and illustrate the importance
of picture books for children on their journey to grow up as complex human beings. Thanks to excellent
guidance and comments of illustrators interviewed there is a lot to learn and take inspiration from.
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ACKNOWLEDGEMENTS
This paper would have not been possible to complete without the assistance from all of my interviewees, talented
children's book illustrators who were so kind to answer my questions and supported me with their kindness as well
as their knowledge. A big thank you also belongs to my advisor, Leah Adler, for her guidance and never-ending
optimism. In addition, I would really like to thank to my parents for aiding me with their love and patience.
REFERENCES
Adichie, Ch. (2009) 'Chimamanda Adichie: Danger of Single Story', TED. Available at: http://www.ted.com/talks/
chimamanda_adichie_the_danger_of_a_single_story.html (Accessed: 22 January 2014).
AlbanKALB (2013) Brown Bag Lunch Speaker's Forum: The Making of a Picture Book. Available at: http://www.youtube.
com/watch?v=C8qclTXYnC0 (Accessed: 22 October 2013).
Bosman, J. (2010) 'Picture Books No Longer a Staple for Children', New York Times, 7 October [Online]. Available at:
http://www.nytimes.com/2010/10/08/us/08picture.html?_r=4&pagewanted=1& (Accessed: 7 October 2013).
Creative Choices (2009) Helen Craig: Book Illustrator. Available at: http://www.youtube.com/watch?v=cFeBM4h49LE
(Accessed: 29 October 2013).
Dils, T. E. (2009) You Can Write Children's Books. 2nd edn. Cincinnati: Writer's Digest Books.
Flood, A. (2011) 'Study finds huge gender imbalance in children's literature', theguardian, 6 May [Online]. Available at:
http://www.theguardian.com/books/2011/may/06/gender-imbalance-children-s-literature (Accessed: 12 October
2013).
Hladíková, H. (2013) Questionnaire – answers by Ann Dewdney, 22 October 2013.
Hladíková, H. (2013) Questionnaire – answers by Ann Marie Finn, 4 November 2013.
Hladíková, H. (2013) Questionnaire – answers by Bethanie Murguia, 5 November 2013.
Hladíková, H. (2013) Questionnaire – answers by Brian Lies, 19 November 2013.
Hladíková, H. (2013) Questionnaire – answers by Christine Tripp, 21 October 2013.
Hladíková, H. (2013) Questionnaire – answers by Joan Waites, 12 November 2013.
Hladíková, H. (2013) Questionnaire – answers by Julie Downing, 9 November 2013.
Hladíková, H. (2013) Questionnaire – answers by Sherry Meidell, 28 October 2013.
Hladíková, H. (2013) Questionnaire – answers by Teri Sloat, 24 October 2013.
Hladíková, H. (2013) Questionnaire – answers by Tom Lichtenheld, 18 November 2013.
IllustrationCourse (2011) Children's book illustrator Patrice Barton on her art for „Mine!" by Shutta Crum. Available at:
http://www.youtube.com/watch?v=Gq8ip_7nrds (Accessed: 18 October 2013).
Kiefer, B. Z. (2009) Charlotte Huck's Children's Literature. 10th edn. Boston: MCGRAW-HILL Higher Education.
LibraryOfCongress (2010) Anita Silvey: 2010 National Book Festival. Available at: http://www.youtube.com/
watch?v=1Fe0gQrVyFI (Accessed: 20 October 2013).
Nikolejeva, M. and Scott, C. (2006) How Picturebooks Work. London: Taylor & Francis Ltd.
Northrup, M. (2012) Picture books for children: Fiction, folktales and poetry. ebrary Prague College [Online]. Available
at: http://site.ebrary.com/lib/pcollege/docDetail.action?docID=10635885&p00=draw+illustration (Accessed:
25.10.2013)
Open College of the Arts (2011) How to Illustrate a book – part 1. Available at: http://www.youtube.com/
watch?v=LKlME1rGoy4 (Accessed: 27 October 2013).
Paul, A. W. (2009) Writing Picture Books. Cincinnati: Writer's Digest Books.
Pierce, T. (2010) 'Five Reasons Why Children NEED Picture Books', Terry Pierce: Children's Author, 12 October. Available at:
http://terrypierce.blogspot.cz/2010/10/five-reasons-why-children-need-picture.html (Accessed: 11 October 2013).
30
CRIS Bulletin 2014/01
CHILDREN´S BOOK ILLUSTRATIONS: VISUAL LANGUAGE OF PICTURE BOOKS
Reading Is Fundamental (2010) CHOOSING GOOD BOOKS: Getting the Most Out of Picture Books. Available at: http://
www.rif.org/us/literacy-resources/articles/getting-the-most-out-of-picture-books.htm (Accessed: 17 October).
Revolution21 (2013) BBC - The Beauty of Books. Part 3: Illustrated Wonderlands. Available at: http://www.youtube.com/
watch?v=pVso9sEt31M (Accessed: 12 November 2013).
Salisbury, M. (2004) Illustrating Children's Books. New York: Barron's Educational Series, Inc.
ShooRaynerLife (2011) Illustrating books with Lynne Chapman. Available at: http://www.youtube.com/
watch?v=rqUiaRCE3ao (Accessed: 18 October 2013).
Ursell, M. (2013) Illustrating Children's Books. Ramsbury, Marlborough: The Crowood Press Ltd.
Will Terry (2011) Drawing Characters - „How To Illustrate Children's Books" - 7videos-. Available at: http://www.youtube.
com/watch?v=dWxdLNLKJvk (Accessed: 10 October 2013).
IMAGE LIST
FIGURE 1:
Chapman, L. (2010) Bears on the Stairs. London: Andersen Press Ltd., pp. 14-15, illus.
FIGURE 2:
Frazee, M. (2008) A Couple of Boys Have the Best Week Ever. [book illustration].[Online]. Available at:
http://www.amazon.com/Couple-Boys-Have-Best-Week/dp/0152060200/ref=sr_1_12?s=books&ie=UTF8&qid=
1392110131&sr=1-12&keywords=frazee+marla (Accessed: 26 November 2013).
FIGURE 3:
Altes, M. (2011) No! [book illustration].[Online]. Available at: http://www.martaltes.com/No (Accessed:
20 October 2013).
FIGURE 4:
Hladíková, H. (2013) A Tale of Two Penguins [storyboard].
FIGURE 5:
Pinkney, J. (2009) The Lion and the Mouse [book illustration]. [Online]. Available at: http://www.lexpublib.
org/page/2009-best-picture-books (Accessed: 3 December 2013).
CRIS Bulletin 2014/01
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32
CRIS Bulletin 2014/01
REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
REPORT ON THE FINANCIAL
EVALUATION:
McDONALD'S CORPORATION
AND YUM! BRANDS
TAMARA AYRAPETOVA
The aim of this paper is to perform financial analysis by using financial ratios and to comment, evaluate, and understand
the origins of the results by using the comparison of two companies chosen as a case study.
The McDonald's Corporation is the largest fast food restaurant in the world. McDonald's Corporation statistics base it in
over 119 countries and it serves more than 68 million customers daily. The company's revenues are coming not only from
its primary products like hamburgers, cheeseburgers, etc., but also from rent, royalties, and fees paid by the franchisees.
This report will look at the financial statements of the McDonald's Corporation over the past 3 years starting from 2010
through 2012. The author of the paper will apply financial ratios to analyze company's position and to identify patterns
and trends. She will then compare the results of the analysis with one of the biggest competitors of McDonald's - Yum!
Brands Inc. and the industrial averages. Yum! Brands Inc. is a US based corporation. It includes famous brands like KFC
and Pizza Hut in their chain. Currently Yum! Brands are the largest competitors McDonald's has in the fast-food industry.
To compare the two companies financial statements will be taken from Yahoo Finance (2013).
CRIS Bulletin 2014/01
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
1.GRAPHICAL COMPARISON OF GENERAL PERFORMANCE MCDONALDS & YUM! BRANDS
To start this paper, the author will first give graphical comparisons of several financial factors, which determine
the company's performance. The author will focus on total revenue, gross and net incomes of the companies
to understand if there is a tendency in the industry. The analysis consists of data from over 5 years.
Figure 1: Sales Revenue Comparison McDonald’s vs. Yum! Brands.
As one can see from the above graph, even though Yum! Brands are the second biggest chain, the total
revenues are still considerably lower in comparison to the McDonald's revenues over the same period of time.
We can see that there are trends in the movement as both of the companies experienced decline in revenues
during the years 2009-2010. One of the main reasons this could be is the crisis the US was experiencing during
that time. Looking at the gross profit and net profit we can also see the same tendency the lines do show a
decrease in profits over 2009-2010 and an increase over 2011-2012. One can also see that McDonald's has
experienced much more sufficient increase in income both gross and net in 2011 than Yum! Brands.
Figure 2: Gross Income Comparison McDonald’s vs. Yum! Brands.
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CRIS Bulletin 2014/01
REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
Figure 3: Net Income Comparison McDonald’s vs. Yum! Brands.
2. FINANCIAL ANALYSIS
In this part of the paper we will look at the financial ratios and apply them to both of the companies. The
author will firstly define the formulas used to calculate the ratios and then will comment on the results.
3.1 LIQUIDITY ANALYSIS
Liquidity ratios allow us to measure the ability of the company to meet its short-term obligations. Mainly
they highlight if the company can pay off its liabilities on the due date. In this paper we will use Current
Assets and Acid Test to see if McDonald's and Yum! Brands have THE necessary liquidity. Generally, the
higher are the result of the ratios, the better the financial health of the company is. The desired minimum
in this case would be value of 1.
The results of those ratios one can find below:
TABLE 1 - MCDONALD'S CORPORATION
2010
2011
2012
Current Assets
4 368 500
4 403 000
4 922 100
Current Liabilities
2 924 700
3 509 200
3 403 100
1,49
1,25
1,446357733
2010
2011
2012
Current Assets
2 313 000
2 321 000
1 909 000
Current Liabilities
2 448 000
2 450 000
2 188 000
0,94
0,95
0,872486289
Current Asset Ratio
TABLE 2 - YUM! BRANDS
Current Asset Ratio
CRIS Bulletin 2014/01
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
Current asset ratios shows the extent to which company is able to meet its short-term obligations, and as we
can see, McDonald's has higher results than Yum! Brands. For all 3 years, Yum! Brands shows results lower
than 1, which shows that they might have issues to pay their obligations. The reason why the results are so
low is because Yum! Brands' current liabilities are higher than the assets the company holds (see Figure 4).
Looking at the Acid Test we can see similar trend:
TABLE 3 - MCDONALD'S CORPORATION
Current Assets
Intentory
Current Liabilities
Acid Ratio
2010
2011
2012
4 368 500
4 403 000
4 922 100
109 000
116 800
121 700
2 924 700
3 509 200
3 403 100
1,46
1,22
1,41
2010
2011
2012
2 313 000
2 321 000
1 909 000
189 000
273 000
313 000
2 448 000
2 450 000
2 188 000
0,87
0,84
0,73
TABLE 4 - YUM! BRANDS
Current Assets
Intentory
Current Liabilities
Current Asset Ratio
McDonald's has values over 1, which shows that the company is in a stable position whereas Yum! Brands
are still showing results lower than 1, which shows that the company can have liquidity issues as large part
of its current assets is actually inventory/stock which cannot be used to meet the obligations.
Figure 4: Current Assets to Current Liabilities Yum! Brands.
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
This leads us to another factor to consider when looking at liquidity, which is working capital (WC).
Working capital shows us operational liquidity. The higher is WC, the lower is the chance of cash flow
problems, and the more liabilities are covered by the currently owned assets. The formula for WC is:
One can find the results for both McDonald's and Yum! Brands below:
TABLE 5 - MCDONALD'S CORPORATION
Current Assets
Current Liabilities
2010
2011
2012
4 368 500
4 403 000
4 922 100
2 924 700
3 509 200
3 403 100
1 443 800
893 800
1 519 000
2010
2011
2012
Current Assets
2 313 000
2 321 000
1 909 000
Current Liabilities
2 448 000
2 450 000
2 188 000
Working Capital
-135 000
-129 000
-279 000
Working Capital
TABLE 6 - YUM! BRANDS
If we look at the results for WC, one can see that Yum! Brands experience WC problems. These results go together with acid and current asset ratios. The liabilities Yum! Brands has dramatically exceeded their assets, which
can cause issues for them to pay their short-term liabilities. McDonald's is doing pretty good, even though the
results are not ideal in terms of coverage (not 2:1) and are showing fluctuations, for example, in the year 2011.
Figure 5: Working Capital McDonald’s vs. Yum! Brands.
CRIS Bulletin 2014/01
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
3.2 PROFITABILITY ANALYSIS
Profitability ratios help to measure a company's ability to generate earnings, profits, and cash flows by
comparing the budget invested and the cash results of sales. In this paper we will use the Return on Capital
Employed (ROCE) ratio to compare the cash earned with the cash invested. Gross Profit Margin is used to
see the percentage by which profits exceed production costs and Net Profit Margin to see the amount of
profit made after expenses and tax per sales dollar.
The results for both of the companies are represented below:
TABLE 7 - PROFITABILITY RATIOS - MCDONALD'S CORPORATION
Earnings Before Interest and Taxes
Capital Employed
ROCE
Capital Employed
Total Assets
Current Liabilities
CE
Asset Turnover
2011
2012
8 505 000
8 595 600
29 050 500
29 480 700
31 983 400
30%
29%
27%
2010
2011
2012
31 975 200
32 989 900
35 386 500
2 924 700
3 509 200
3 403 100
29 050 500
29 480 700
31 983 400
2010
2011
2012
Sales Revenue/Total Revenue
24 074 600
27 006 000
27 567 000
Total Stockholder Equity
14 634 200
11 737 000
12 489 600
1,65
2,30
2,21
2010
2011
2012
0,3570402
0,314930016
0,311807596
0,83
0,92
0,86
PM(%) * AT
30%
29%
27%
2010
2011
2012
Gross Profit
9 637 300
10 686 600
10 816 300
AT
ROCE
Profit Margin
Asset Turnover
Net Income
4 946 300
5 503 100
5 464 800
24 074 600
27 006 000
27 567 000
Gross Profit Margin
40%
40%
39%
Net Profit Margin
21%
20%
20%
Sales Revenue/Total Revenue
38
2010
8 595 600
CRIS Bulletin 2014/01
REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
TABLE 8 - PROFITABILITY RATIOS - YUM! BRANDS
2010
2011
2012
Earnings Before Interest and Taxes
1 594 000
1 659 000
2 145 000
Capital Employed
5 868 000
6 384 000
6 823 000
ROCE
27%
26%
31%
Capital Employed
2010
2011
2012
Total Assets
8 316 000
8 834 000
9 011 000
Current Liabilities
2 448 000
2 450 000
2 188 000
5 868 000
6 384 000
6 823 000
CE
Asset Turnover
Sales Revenue/Total Revenue
Total Stockholder Equity
AT
ROCE
Profit Margin
Asset Turnover
2010
2011
2012
11 343 000
12 626 000
13 633 000
1 576 000
1 823 000
2 154 000
7,20
6,93
6,33
2010
2011
2012
0,140527197
0,131395533
0,15733881
1,93
1,98
2,00
PM(%) * AT
27%
26%
31%
2010
2011
2012
Gross Profit
3 223 000
3 486 000
3 781 000
Net Income
1 158 000
1 319 000
1 597 000
11 343 000
12 626 000
13 633 000
Gross Profit Margin
28%
28%
28%
Net Profit Margin
10%
10%
12%
Sales Revenue/Total Revenue
From above tables one can see that McDonald's generally has high ROCE, Gross and Net Profit Margins over
the 3 years. However, in the year 2012 Yum! Brands have higher ROCE than McDonald's (see Figure 6) as
their earnings before tax and interest increased, whereas McDonald's capital employed increased dramatically
and the actual return stayed nearly the same as in 2011 which caused decline.
Figure 6: ROCE McDonald’s vs. Yum! Brands.
CRIS Bulletin 2014/01
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
When we look at the Gross and Net Profit Margins, McDonald's has much higher percentages than Yum!
Brands (see Figures 7 and 8). This can be due to the better cost management systems the company
has. Gross Profit Margin shows how well the company utilises and allocates its resources. In this case,
McDonald's is also doing better. Looking at the Net Profit Margins, we can see that both of the companies
surely do well, however Yum! Brands score substantially less than McDonald's. The main reason for such
results can be that Yum! Brands have much more liabilities to pay then McDonald's. As we could see
from Figure 4, they exceed the assets the company owns; due to this, the Net Profit can be very low after
the company pays all of the expenses and its obligations. One can also see that over 3 years both of the
companies did not experience dramatic increase or decrease in their Gross and Net Profit Margins; the
numbers are nearly the same, which shows stability in their operations.
Figure 7: Gross Profit Margin McDonald‘s vs. Yum! Brands.
Figure 8: Net Profit Margin McDonald‘s vs. Yum! Brands.
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CRIS Bulletin 2014/01
REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
3.3 EFFICIENCY ANALYSIS
Efficiency ratios show how well the company is using its assets and liabilities. The analysis mainly focuses on
the measurement of efficiency by calculating turnover of receivables, fixed assets turnover, and the trade
debtor collection period along with creditor payment period. Those ratios are particularly useful when the
results are compared between competitors in the same industry. It is also true that change in these ratios
directly impact profitability of the organisation.
The results of the above ratios can be found below:
TABLE 9 - EFFICIENCY RATIOS - MCDONALD'S CORPORATION
Cost of Revenue
Inventory
Stock Turnover
2010
2011
2012
14 437 300
16 319 400
16 750 700
109 000
116 800
121 700
132,45
139,72
137,64
Total Revenue
24 074 600
27 006 000
27 567 000
Total Assets
31 975 200
32 989 900
35 386 500
0,75
0,82
0,78
1 179 100
1 334 700
1 375 300
17,88
18,04
18,21
943 900
961 300
1 141 900
14,31
12,99
15,12
2010
2011
2012
8 120 000
9 140 000
9 852 000
189 000
273 000
313 000
42,96
33,48
31,48
11 343 000
12 626 000
13 633 000
8 316 000
8 834 000
9 011 000
Fixed Asset Turnover
Net Receivables
Trade debtor collection period (days)
Accounts Payable
Trade creditor collection period (days)
TABLE 10 - EFFICIENCY RATIOS - YUM! BRANDS
Cost of Revenue
Inventory
Stock Turnover
Total Revenue
Total Assets
Fixed Asset Turnover
Net Receivables
Trade debtor collection period (days)
Accounts Payable
Trade creditor collection period (days)
1,36
1,43
1,51
317 000
398 000
412 000
10,20
11,51
11,03
1 775 000
2 130 000
2 178 000
57,12
61,58
58,31
CRIS Bulletin 2014/01
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
Looking at the first measure which is Stock Turnover, one can see that McDonald's numbers are higher
than those of Yum! Brands (see Figure 9).
Figure 9: Stock Turnover McDonald’s vs. Yum! Brands.
One can see that McDonald's has a positive trend whereas Yum! Brands has experienced a decrease in
stock turnover over the 3 year period. The higher the stock turnover, the more efficient the company is in
purchasing and selling goods. In this case, if we look at the numbers one can see that the inventory (stock)
of McDonald's is actually nearly the same as of Yum! Brands but the Cost of Revenue is extremely higher,
and this is the main reason why the results are so different.
The second measure of efficiency is fixed assets turnover (see Figure 10). Fixed assets are used to generate
more sales, which means that a higher level of fixed assets tends to generate more sales. In this case the
larger the result of the ratio is, the more amount of investment into fixed assets is recovered by the sales.
The results can be expressed in percentages. Looking at the results of McDonald's and Yum! Brands (see
Figure 10), one can see that Yum! Brands have much higher recovery on the investment into fixed assets.
Figure 10: Fixed Assets Turnover McDonald’s vs. Yum! Brands.
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CRIS Bulletin 2014/01
REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
Such difference in the results can be caused by the amount of total assets the companies own. In the case
of McDonald's, the number of total assets is much higher than the actual revenues. This tells us that with
the number of assets McDonald's has, it could produce much more than it does. Whereas with Yum!
Brands, the revenues are higher than the assets owned and there is a positive trend in sales.
Looking at the third important area, which is the trade debtor collection period used to determine the period
of time a customer is required to pay back for the goods. The higher the result of this ratio is, the bigger the
chance that the company will run into cash flow problems and will not be able to cover its sales costs.
Figure 11: Trade Debtor Collection Period McDonald’s vs. Yum! Brands.
As one can see from Figure 11, both of the companies have debtor collection periods lower than 1 month,
which is mainly due to the origins of their business. Most of the customers will pay for their products straight
away, only the payments from franchisees can come with a delay. From Figure 11 one can also see that,
McDonald's has a higher debtor collection
period in comparison to Yum! Brands; one
of the main reasons why this could happen
is that McDonald's has more headquarters
and franchisees than Yum! Brands. This
makes the number of Net Receivables
higher for McDonald's than for Yum! Brands
as the majority of their customers are end
consumers of the products.
Another criterion in efficiency analysis is trade creditor payment, which tells the settlement period for
paying the suppliers. Higher results in this ratio would mean that company is experiencing issues to find a
cash to pay its creditors/suppliers. Looking at the results of McDonald's and Yum! Brands in figure 12, one
can see that McDonald's has a much lower creditor payment period than Yum! Brands do.
CRIS Bulletin 2014/01
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
Figure 12:Trade Creditor Payment Period McDonald’s vs. Yum! Brands.
One of the reasons why Yum! Brands might have such a high creditor payment period is the amount of
liabilities they have to pay (Accounts Payable). Generally it is viewed that a standard credit period is 1
month, and in the case of Yum! Brands it is more than a month, and the result suggests that the company
either needs to reduce the amount of liabilities or it has to generate more cash by increasing sales. The
results for Yum! Brands correspond to what we have seen previously in Figure 4 and liquidity ratios.
The last metric one can consider in effectiveness analysis is Working Capital Cycle (WCC). In this paper we
will calculate working capital cycle using the following formula:
The results for both of the companies' one can find below:
TABLE 11 - WORKING CAPITAL CYCLE - MCDONALD'S CORPORATION
2010
Working Capital
Total Revenue
Working Capital Cycle
2011
2012
1 443 800
893 800
1 519 000
24 074 600
27 006 000
27 567 000
21,89
12,08
20,11
2011
2012
TABLE 12 - WORKING CAPITAL CYCLE - YUM! BRANDS
2010
Working Capital
Total Revenue
Working Capital Cycle
-135 000
-129 000
279 000
11 343 000
12 626 000
13 633 000
-4,34
-3,73
-7,47
As one can see from Figure 13 and the results, McDonald's has much more WCC than Yum! Brands. The
negative results Yum! Brands received were caused by the negative working capital. This as the result
means that efficiency of their resources is low and that they might not be able to meet their obligations. 44
CRIS Bulletin 2014/01
REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
3.4 INVESTMENT RATIOS
Investment ratios are used by investors to estimate the attractiveness of the specific investment. In this
section we will look at most widely used ratios:
(Market price of the share was taken from closing historical prices for each year ending December 1 at Yahoo Finance)
The results for the ratios one can find below:
TABLE 13 - INVESTMENT RATIOS - MCDONALD'S CORPORATION
2010
2011
2012
Annual Dividend Per Share
2,26
2,53
2,87
Market Price of the Share
76,76
100,33
88,21
Dividend Yield %
2,94
2,52
3,25
Earnings After Tax and Dividends
4 946 300
5 503 100
5 464 800
Outstanding Shares
1 054 000
1 021 100
1 003 000
4,69
5,39
5,45
EPS
Market Price of the Share
76,76
100,33
88,21
16,36
18,61
16,19
Long-term Debt
11 497 000
12 133 800
13 632 500
Capital Employed
29 050 500
29 480 700
31 983 400
40%
41%
43%
31 975 200
32 989 900
35 386 500
2 924 700
3 509 200
3 403 100
29 050 500
29 480 700
31 983 400
Price to Earnings Ratio
Capital Gearing
Capital Employed
Total Assets
Current Liabilities
CE
CRIS Bulletin 2014/01
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REPORT ON THE FINANCIAL EVALUATION: MCDONALD'S CORPORATION AND YUM! BRANDS
TABLE 14 - INVESTMENT RATIOS - YUM! BRANDS
2010
2011
2012
Annual Dividend Per Share
0,92
1,07
1,24
Market Price of the Share
49,05
59,01
66,25
Dividend Yield %
Earnings After Tax and Dividends
Outstanding Shares
1,88
1,81
1,87
1 597 000
1 319 000
1 158 000
469 000
460 000
451 000
EPS
3,41
2,87
2,57
Market Price of the Share
49,05
59,01
66,25
Price to Earnings Ratio
14,40
20,58
25,80
Long-term Debt
2 915 000
2 997 000
2 932 000
Capital Employed
5 868 000
6 384 000
6 823 000
50%
47%
43%
Total Assets
8 316 000
8 834 000
9 011 000
Current Liabilities
2 448 000
2 450 000
2 188 000
5 868 000
6 384 000
6 823 000
Capital Gearing
Capital Employed
CE
Figure 13: WCC McDonalds vs. Yum! Brands.
To start our comparison, we will firstly look at dividend yield. It shows the productivity of the investment,
being more specific, it represents how much cash flow the investor is getting per dollar invested. In the
case of McDonald's and Yum! Brands, we can see that Yum! Brands has a lower cash flow per dollar than
McDonald's (see Figure 14).
One of the main reasons why McDonald's has
higher results is because it has a higher net
income from which it can pay higher dividends.
This can be a result of efficient cost reduction
strategies and utilisation of the equipment,
which we have seen from the efficiency ratios.
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Figure 14: Dividend Yield McDonald’s vs. Yum! Brands.
Looking at the EPS of the companies we can see that Yum! Brands EPS is lower than McDonald's. This
ratio is very popular between investors as it tells how much the market is willing to pay for a company's
earnings. The higher is the ratio, the more the market wants to pay, and the more positive is the prediction
for the future growth of the share price. The reason why Yum! Brands have lower EPS can be explained by
the relationship between equity and liabilities. As the company has much more liabilities then the equity,
it therefore has more expenses and this decreases the net income the from which EPS is calculated. There
is also a negative tendency over the years. This can be explained by an increase in the number of shares as
the company grows and less increase in earnings. McDonald's in this case is more stable than Yum! Brands.
Figure 15: EPS McDonald’s vs. Yum! Brands.
The next indicator is Price to Earnings Ratio (P/E). This indicator is a tricky one as most of the investors
tend to forget that the lower is the result of this ratio, the more profitable is the investment. Generally, a
value of 12-15 counts to be good. In this case one can see that Yum! Brands are doing much better than
McDonald's (see Figure 16) in 2010; however they did much worse in 2011-2012. As this ratios links stock
share price with EPS, one of the reasons why Yum! Brands had a change the results might be an increase in
the pricing of their shares as they grow, but a less sufficient increase in their EPS.
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Figure 16: Price to Earnings Ratio McDonald’s vs. Yum! Brands.
The next indicator we will look at in this section is the Capital Gearing Ratio. This ratio shows the capital
structure of a company and its financial strength. The higher the ratio is, the more risky the investment
is since the more activities of the company are supported by borrowed funds, the more interest the
company has to pay for its debt. As one can see from Figure 17, Yum! Brands have much higher results than
McDonald's, and this corresponds to what we have seen previously as the company has a lot of liabilities
and debt. Even though McDonald's has lower results, one should notice that it still has a lot of long-term
debt, which can be covered by its capital, but not in full.
Figure 17: Capital Gearing McDonald’s vs. Yum! Brands.
Normally, the ratios for a low-gearing company would be under 25%, and everything in between 25%50% middle-gearing, and everything over 50% highly-gearing. As we can see, both McDonald's and Yum!
Brands are middle-gearing companies. In this case, McDonald's still performs better than Yum! Brands. One
of the main reasons is the long-term debt the company holds and its relationship with the capital employed.
As we have seen previously, Yum! Brands have a lot of short-term and long-term liabilities, whereas their
assets are not increasing as dramatically as needed; due to this, McDonald's is a safer investment.
It is important to remember that not always financing business through long-term debt gives negative
outcomes, as it is most of the times cheap. It would really depend on the ability of the company to raise
profits to cover this debt. In this case, both of the companies have great potential, but McDonald's has
better performance in meeting its liabilities.
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4. MCDONALD'S AND YUM! BRANDS VS. INDUSTRIAL AVERAGES
4.1 MCDONALD'S VS. YUM! BRANDS STOCK PERFORMANCE EVALUATION
In this section of the paper we will look at the performance of MCD and YUM stocks over a 3-year period.
The author will use SharpCharts from which one could see the volume of the traded stock, the opening
and closing price, the change in the price in percentage for the date of 6 Dec 2013. One can also find the
MACD (Moving Average Convergence-Divergence), Slope charts, MA (50), MA (200), and RSI.
Chart 1: MCD Stock Performance (3 years). Stock Charts (2013)
At the top of Chart 1 one can find the RSI indicator. This indicator stands for Relative Strength Index and is
a momentum oscillator. This indicator can vary from zero to 100. RSI can be of different parameters, and in
this case the author is using the default 14-day parameter; however, if one needs to increase sensitivity, he/
she should reduce it to 10 days. Since RSI is an oscillator, it determines when the market is overbought or
oversold. Generally, it is considered that if RSI is above 70, then it is overbought; if it is less than 30, then it is
oversold. If the stock is overbought, then it might experience a decline in price, whereas if it oversold, it has
potential to grow in the future. Investors use RSI to identify the best time to sell or buy financial assets. When
the asset is approaching 70, it is beneficial to sell it, whereas if the stock is approaching 30, it is time to buy. As
one can see both YUM and MCD are stable stocks.
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As one can see from Charts 1 and 2, the results for MCD and YUM are not falling into any of the categories.
In the Chart 1, one can see the blue and the red lines which stand for moving averages (MA). This indicator
helps to better analyse the price movement by eliminating 'noise' from random price fluctuations. This
indicator is based on previous prices due to sometimes it can lack accuracy. Generally, there are two types of
MAs, SMA (Simple Moving Average) and EMA (Exponential Moving Average). The main difference between
the two is that EMA gives bigger weight to more recent prices. In this report, we will consider SMA for the
period of time of 50 days and 200 days, represented respectively by blue and red lines.
As one can see, the SMA for the 50 days period is much higher than SMA for 200 days. MA (50) has the price
of $95.43 and SMA (200) only $82.35. MA for a shorter period of time will have smaller lag than MA for a
longer period such as 200 days. Therefore, short-term investors would prefer to refer to short-term MAs
whereas long-term investors generally prefer to look at a long-term MA.
Chart 2: YUM! Stock Performance (3 years). Stock Charts (2013)
Even though the prices for MA (200) is lower, it is still on the uptrend, which indicates that the security
has growth. One can also see that in the MCD case, the long-term MA and the short-term MA did not
crossover, which indicates that overall the performance is on a steady growth path. Comparing MCD, MA
(50) and (200) with the results for YUM represented in Chart 2, one can see that the averages are smaller
for YUM- MA (50) – 69.11 and MA (200) - 56.68. One can also see the same tendency that MA (50)
is larger than MA (200), and the author assumes that one of the reasons for this is the lag. Both of the
companies though have a positive uptrend over the 3 years.
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MA is not only a single indicator but also a contributor to the next measure which is Moving Average
Convergence-Divergence (MACD). This indictor, which one can see represented in both Charts 1 and 2
below the main body, is counted to be the easiest momentum indicator. What it does is it subtracts longer
moving average from the shorter moving average. The shorter the period under study, the more sensitive
are the results. In this report we will use the standard setting (12, 26,9). The investors tend to look for the
signal lines crossovers, centerline crossovers, and divergences to generate signals. Since MACD is based
on concepts of convergence and divergence, it is important to mention that convergence occurs when the
MAs move towards each other and divergence occurs when they move away from each other. As one can
see from Charts 1 and 2, both of the companies have convergence in the movement of the MAs. One
can also see that the averages are higher for YUM than for MCD as it experienced a negative performance
during the second half of the year 2012 until 2013.
The last indicator in this section, the scope, is a result of linear regression which generates the line of best fit
for a price series. This indicator is a good tool to measure the direction and strength of a trend. Investors
can also use it in combination with other tools to identify the potential point of entry to the already on-going
trend. The trend can fluctuate above and below zero. In this paper the author took the 52-week slope. As
one can see, MCD has a positive trend until the first quarter of 2012 first when it experienced a decline which
one could also see in the results of the ratios for the previous sections. From the third quarter of year 2013
until the first quarter of 2013 MCD was in negative territory; however, then it experienced growth. As for
the YUM! Brands one can see that the trend is much more positive and the period where they performed
under the positive region is shorter (only the first quarter of 2013). If we look at the average YUM has 0.18
and MCD 0.12, which means that YUM has a more positive price trend than MCD.
4.2 INDUSTRY COMPARISON
In this section of the paper, the author will compare stock performance of YUM and MCD to each other
as well as to the industry indices like S&P 500 and Down Jones. In Chart 3 one can see the comparison of
MCD and YUM, and S&P 500, and DJ Indices stock performance. S&P 500 stands for Standard & Poor's
500 Index. This index consists of 500 stocks which are chosen by market size, liquidity, etc. This index is
meant to be the leading indicator of the U.S. stock market. Previously, it was the Down Jones Index which
is also represented in Chart 3 in red; however, since DJ includes only 30 companies, S&P 500 is considered
to be the best representation. Both of the indices are appropriate for this specific comparison since we are
evaluating companies which are listed in the NYSE.
Chart 3: MCD, YUM, S&P 500, and DJ Comparison. Yahoo Finance (2013).
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When we look at Chart 3 one can see that both MCD and YUM outperform S&P 500 and DJ indices, which
shows that generally both of the companies have higher growth than the competitors and are attractive
to investors. If one compares the performance of MCD to YUM, we can see that through the years 20072012 MCD has the highest prices and the best stock performance. However, starting in 2012 we can see
that YUM is actually performing at the same level with periodic crossover. It is essential to highlight here
that both of the companies are the benchmarks of the industry and of course even when they experience a
decrease in their prices, they can outperform the competitors, as one can see from Chart 4.
Chart 4: Comparison to Direct Competitors. Yahoo Finance (2013).
In Chart 4 one can see the comparison of several stocks, which are directly competing with MCD and YUM.
Those are stock of companies – Wendy & Corporation, Burger King, and Starbucks. The chart also shows
S&P 500 represented by a light-green line. As one can see, starting end of 2007 beginning of 2008, when the
U.S. market experienced a crisis, the performance of S&P 500 and YUM and MCD are dramatically different.
As S&P 500 shows most of the companies
experienced a decline in their stock
performance; however, for MCD and YUM we
can see a positive trend. When we look at
Wendy's Corporation, we can see that starting
in the year 2007, it experienced a decline and
after this, it did not experience any major
growth and is beyond the S&P 500 index.
Whereas Starbucks after experiencing a decline in the years during the crisis, experienced growth and still
has a positive trend, even though it is still has lower stock prices than YUM and MCD. When we look at
Burger King, the data is available only starting in the year 2012, and we can see that the stock performance
is nearly the same as of S&P 500. Comparing all of the stocks one can see that MCD and YUM outperform
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4.3 FINANCIAL RATIOS MCDONALD'S AND YUM! BRANDS INDUSTRY
COMPARISON
In this section the author will compare the two companies with industrial averages for a set of ratios which
are usually used by investors to evaluate the performance of the stock. The author of the report referred
to Morning Stars' (2013) estimates, which one can find below:
FIGURE 18 - - MCD AND YUM! VALUATION
MCD
Price/Earnings
YUM
Industry Avg.
17.4
32.5
29.5
Price/Book
6.3
15.8
7.7
Price/Sales
3.5
2.8
2.5
Price/Cash Flow
13.7
17.7
11.6
Dividend Yield %
3.2
1.8
1.9
When we look at the P/E ratio, one can see that industry average for this metric is 29.5, high P/E ratio
is less attractive for investors as it means that they are paying more for the earnings. In this case, Yum!
Brands is more attractive for the value investors, who a looking for undervalued stocks, with the potential
growth, whereas McDonald's would be desirable for growth investors who are looking for the stock with
high growth rates. Yum! Brands shows higher results than the industry average and this means that the
company might face issues with solvency.
Price/Book ratio provides an understanding if the stock is overvalued or undervalued. As one can see
Yum! Brands score much higher than McDonald's and the industry average, which might mean that the
stock is overpriced or investors have high expectations. McDonald's in this case scores lower than the
industry average, which means that the stock is underpriced, due to lower growth expectation associated
with it, whereas Yum! Brands exceeds the industry average which might mean that it is overvalued.
Price/S compares the value of the stock to either its own performance in the past or to other companies.
It determines how much investors pay for the dollar of company's sales. Therefore, the lower the ratio
is, the more attractive the stock is. This measure can be very useful only when comparing to the industry
average, and in this case, the industry average is 2.5, as we can see both Yum! Brands and McDonald's score
higher than this, but Yum! Brands is performing better than McDonald's.
P/C metric compares stock market price to cash flow generated per-share. This ratio is similar to P/E,
however a lot of investors consider it much more solid. The main reason behind this is that cash flow is
generally harder to manipulate, whereas earnings are affected by such factors like depreciation. The same
way as the P/E ratio, the lower the results, the better. The industry average for this ratio is 9.6 which both
of the companies outperform. However, McDonald's has lower scores than Yum! Brands. These results
correspond to the working capital issues Yum! Brands currently has.
When we look at the last metrics, Dividend Yield, which represents the return (in percentage) the company
pays out in dividends. The average for this metrics is 1.9%, which is higher than what Yum! Brands pays out.
McDonald's, though, exceeds this amount and it pays 3.2%. It is important to notice here that generally older
companies tend to pay higher dividends, and their dividends history tends to be more stable.
To summarise the above, the author wants to highlight that generally McDonald's is performing better
than Yum! Brands. It is more stable and has better return on the investment. As in most of the ratios, it
scored less than Yum! Brands. Even though Yum! Brands show concerns in areas of cash flow, working
capital and debt, their growth rates are high and are increasing from 2012. This might help the companies
to increase revenues to cover liabilities.
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5. CONCLUSIONS
In this paper the author has performed financial analyses for McDonald's and Yum! Brands. She has
compared the results of the liquidity, profitability, efficiency, and investment ratios as well as looked at the
industrial averages to better evaluate the companies' performance.
From the above analyses, the author can conclude that McDonald's performed much better than Yum!
Brands in all of the areas investigated. Yum! Brands are experiencing issues with working capital and
might face problems with covering their short-term and long-term liabilities. They are also less efficient
in managing their costs of production, even though they utilise their assets better than McDonald's. Yum!
Brands performed better in ROCE in 2012 due to an increase in their Gross Profit; however, they have a
lower Net Profit Margin than McDonald's. This can be explained by the expenses the company encounters
and their costs management and pricing systems. Another reason why McDonald's performed better
nearly in all profitability ratios was because of the number of liabilities Yum! Brands need to pay. As we
have seen from the liquidity ratios, those exceed their assets.
If we look at the efficiency ratios, McDonald's has higher debtor collection period and lower fixed asset
turnover than YUM, but the company still does not have problems with the Working Capital Cycle. It also
performs better in the creditor collection period, which shows that the company has enough cash to pay
to its creditors in the short-term.
When one considers investment ratios, he/she can see that McDonald's also scored better. It has a lower
P/E ratio meaning that investors pay less for the earnings they receive than Yum! Brands. Its EPS is higher
and therefore the Dividend Yield is also higher than that of Yum! Brands, and exceeds the industry average.
Its Capital Gearing Ratio shows that it is a low-gearing company and is less risky as an investment. If we look
at the stock performance one can see that McDonald's has a positive trend of growth and outperforms
the S&P 500 and DJ Indices. It also outperforms all of the competitors in its sector, including Burger King
and Wendy's Corporation. However, when we look at Yum! Brands we can see that they entered into
competition with McDonald's in 2012, and in the future it can be a very attractive stock to invest in for the
growth investors. McDonald's, on the other hand, would be an option for value investors who are seeking
for long-term investments.
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REFERENCES
Yahoo Finance (2013) Financials McDonald’s Corporation. Available at: http://finance.yahoo.com/q/is?s=MCD+Income+S
tatement&annual (Accessed: 1 November 2013).
Yahoo Finance (2013) Financials Yum! Brands. Available at: http://finance.yahoo.com/q/is?s=YUM+Income+Statement
&annual (Accessed: 1 November 2013).
Morning Star (2013) McDonald's Corporation MCD. Available at: http://financials.morningstar.com/valuation/price-ratio.
html?t=MCD&region=USA&culture=en-US (Accessed: 11 November 2013).
Morning Star (2013) Yum Brands Inc. Available at: http://financials.morningstar.com/valuation/price-ratio.
html?t=YUM&region=USA&culture=en-US (Accessed: 11 November 2013).
Yahoo Finance (2013) Historical Prices: MCD. Available at: http://finance.yahoo.com/q/hp?s=MCD+Historical+Prices
(Accessed: 11 November 2013).
Yahoo Finance (2013) Historical Prices: Yum! Brands. Available at: http://finance.yahoo.com/q/
hp?s=YUM+Historical+Prices (Accessed: 11 November 2013).
Stock Charts (2013) SharpCharts. Available at: http://stockcharts.com/h-sc/ui?s=mcd (Accessed: 7 December 2013).
McDonald’s Corporation (2013) Annual Report 2012. Available at: http://www.aboutmcdonalds.com/content/dam/
AboutMcDonalds/Investors/Investor%202013/2012%20Annual%20Report%20Final.pdf (Accessed: 29 November 2013).
Yum! Brands (2013) Annual Report 2012. Available at: http://yum.com/annualreport/pdf/2012yumAnnReport.pdf
(Accessed: 29 November 2013).
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APPENDIX 1 - MCDONALD'S CORPORATION
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APPENDIX 2 - YUM BRANDS INC.
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ETHICAL LEADERSHIP AND LEADER MEMBER EXCHANGE (LMX) THEORY
ETHICAL LEADERSHIP
AND LEADER MEMBER
EXCHANGE (LMX) THEORY
BASED ON A CASE STUDY IBM "LEADING THE TURNAROUND"
ŠEJLA BABIČ
The aim of this paper is to evaluate the contribution that developments in the area of ethical leadership and trust have
made to our understanding of effective people management within organisations. This paper is based on a case study
from Harvard Business Review (2007) called "IBM - Leading the Turnaround". The author will use Leader Member
Exchange (LMX) theory by Graen and Uhl-Bien (1995) and integrate the ideas of ethical leadership to critically evaluate
the leadership style of the CEO of IBM Louis V. Gerstner that led to the turnaround of IBM. In particular, the author will
focus on the following question: What role did trust play in the leadership style of Gerstner in the transformation of IBM?
When Gerstner became the CEO of IBM in 1993, an $8.1 billion loss on the stock market was announced by IBM; this was
one of the largest in U.S. history. Gerstner was facing a difficult job as stock market commentators were rapidly writing
off IBM as a 'slow elephant' and, as a result, IBM's workforce was not in any state to accept change. Gerstner's first task
was to analyse what was going wrong within IBM, despite having dedicated people, high technological infrastructure, and
a sound strategy, he found that IBM was suffering from its own success during the many years of operation. Its own success
was its downfall, for it had become slow moving and inward looking.
Organisationally, it had become a decentralised 'kingdom' in which none of the business units communicated with each
other. Gerstner realised that, if IBM was to be saved, he had to lead this massive organisation through cultural change. He
realised that changing the attitude and behaviour of thousands of people was hard to accomplish, but was the main key to
success. Management could not change organisational culture through words and policies alone; leaders such as Gerstner
had to create the conditions for transformation and invite employees to respond willingly.
IBM had a tradition of appointing executives from within. Indeed, Gerstner was the first CEO to be hired form outside;
this in itself was revolutionary and created widespread internal concern. Before Gerstner arrived, it was accepted that
the break-up of IBM was inevitable. The question was only what form this would take. Morale was at rock-bottom, and
Gerstner's appointment did nothing to raise spirits. It was assumed he had been brought in to 'wield the hatchet'.
Therefore, it was a real surprise when Gerstner made himself open to input from anyone in the company. It was even more
surprising when he announced that IBM's strength lay in its integration and that there would be no break-up. Immediately
spirits started to soar. Everyone knew there would be a pain, but now it seemed it would be on a much lower level, and
employees were prepared to listen for a change. While it took time to build trust, Gerstner's no-nonsense style created
confidence that someone was in charge. His actions were not popular, but they were decisive. It was this that steadily led
to a sense of trust; he did what he said he would do, and he proved himself trustworthy.
In the next section, the author will provide a background to leader-member exchange (LMX) theory and relate it to ethical
leadership so that we can explore the leadership style of Gerstner during the change at IBM.
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LEADER MEMBER EXCHANGE (LMX) THEORY AND ETHICAL LEADERSHIP
Leader-member exchange (LMX) theory by Graen and Uhl-Bien (1995) focuses on the relationship between
the leader and member. The key principle of LMX theory is that leaders develop different types of exchange
relationships with their followers and the quality of the relationship that is developed alters the impact on
outcomes of this leader and member exchange. Therefore, according to LMX theory, leadership occurs when
leaders and followers are able to develop effective relationships that result in mutual influence (Uhl-Bien, 2006).
Leadership can be described as a process that involves several factors; one of these could be the ability to
influence others and motivate them to reach a common oriented goal, like the change required at IBM
(Northouse, 2007, pp. 2-9). This would require leadership changes that foster relationships and accompany
ethical burdens and responsibilities, as making a change in people may influence not only their working lives,
but also the lives of people around them. Trust, therefore, plays a central role in developing relationships with
employees during the process of change management.
LMX theory explores how leaders and managers develop relationships with team members, and it explains
how those relationships can either contribute to the growth and assist change or hold people back in the
leadership context. In LMX theory trust is described as a leader's authentic behaviour, a leader's trustworthy
behaviour and how it is implemented in daily actions are key components of LMX exchanges.
Figure.1: LMX model illustrating the exchange process
The LMX process is based on the assumption that leaders pay attention to the traits, skills and competencies
of their followers during the exchange process (Figure 1) and assess whether they are competent and
effective to take care of a certain position or work in the organisation. From the perspective of the follower,
the main question is how trustworthy the leader is.
According to Graen and Uhl-Bien (1995) researchers have found that high-quality leader-member
exchanges produce less employee de-motivation and greater organisation commitment. Graen and UhlBien have also suggested that leadership making develops progressively over time in three phases: (1) the
stranger phase, (2) the acquaintance phase, and (3) the mature partnership phase. During the final phase
(3), the mature partnership relationship is marked by high-quality leader-member exchanges that involve a
high degree of mutual trust, respect, and obligation towards each other. Such high quality relationships will
produce high LMX during the transformational leadership phase such as the one faced at IBM.
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The quality of the exchange process will, therefore, depend upon the qualitative characteristics of the
exchange between leader and member. Such qualitative characteristics could be 'ethical values' and trust
will play a major role in this process. Such 'ethical values' can be considered as qualitative characteristics
that create high LMX in transformational leadership. We could say that 'ethical value' congruence between
the leader and the member could be defined as the degree of agreement between the leader's value
system and the member's value system, a high degree of agreement would point towards a high LMX.
Weiss (1978, pp. 711-718) has found that people aligned their values with the values of their leader if
they perceived their leader as trustful. Leaders, therefore, have an ethical responsibility and one of the
characteristics that exercise such responsibilities are accommodating the value systems of the members in
the leadership process. According to Beauchamp and Bowie (1988), this requires the essential ability of
leaders to be sensitive to the interests and concerns of others.
With such an attentive attitude, an ethical leader may foster change in others and lead people towards change
in an organisation similar to the one required at IBM. Heifetz (1994) states that in order for such effective
changes to occur successfully, leaders have to exercise their authority with a notion of responsibility, a
responsibility that requires respect for the prospective change in others. Heifetz (1994) calls this a "holding
environment" where trust, nurturance, and empathy are exercised with the aim of change. Such a change
would generally be resisted; however, Heifetz (1994) says that in such a "supportive context" followers
would generally feel secure to face the hurdles of change more effectively and to manage issues that may
arise. During the change at IBM, Gerstner was instrumental in changing the mental orientation of his
employees from a self-centric to a customer-centric point of view. Initially, this was resisted, and he had to
develop an environment of "supportive context" where employees would trust the leader (Heifetz, 1994).
Therefore, he used his authority and got employees to pay attention to the issues facing IBM. He recognised
the values in others and identified the changes required so that conflicting values would be reduced during
the high congruence process that led to a high LMX. As Heifetz (1994) says, Gerstner recognised the
benefits of the existing environment at IBM and utilised the importance of trust in a "supportive context"
where employees would feel safe to confront any hurdles the process of change.
So, for a transformational leader to lead change effectively, the needs, values, and moral of employees
have to be at the forefront. Burns (1978) in his theory of transformational leadership emphasises that
a transformational leadership requires a focus by leaders to assist employees to higher standards of
moral responsibility. He states that leadership has a moral dimension, and he characterises this as ethical
leadership. He stresses that leaders need to engage themselves with employees and assist them in their
personal struggles concerning conflicting values so that these are aligned with organisational values in
the process of effective change. It is, therefore, the responsibility of the leader to assist employees in the
assessment of their own values and through trust align these values with organisation values in the process
of change, this "connection", Burn (1978) says, that raises the level of morality in both the leader and the
employee and develops trust, an essential element of ethical leadership.
As a transformational ethical leader, according to Bass (1985), Gerstner led to initiate change at several
business processes within IBM, and these processes of change were not easy to implement for a company
that has been described as moving like a "slow elephant". Gerstner had to initiate specific conditions for
this transformation and for employees to respond to these necessary changes. Some of these changes
were to gain the support of major customers by establishing credibility, comparing expense to revenue of
IBM with those of leading competitors in the market to monitor expense reduction, re-engineer business
processes at IBM to reduce overheads, and sell off unproductive assets.
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Figure 2. Trust and the principles of leadership.
In order to carry out these changes, Burns (1978) stresses that ethical leadership requires engagement with
employees, and this process of engagement requires the identification of personal values and realigning
them with changing corporate values, a process that would create a high degree of congruence in aligned
ethical values and therefore a high LMX. Such a process involves several stages where the leader has to
recognise the importance of personal values, develop a level of trust in the managers' abilities to change
and communicate the importance of realigned corporate values. Burns emphasises that when such a
process works effectively, the leader attends to the personal motivations of the managers and re-directs
them to a better set of moral values that are congruent with corporate values.
In many ways, one can note a common theme running through the different perspectives of ethical
leadership and its relationship with LMX theory presented in the last section, the main ones being that
a high quality leader-member engagement is essential to ethical leadership. It is also essential for ethical
leaders to pay close attention to the needs of their employees; these leadership theories are similar to
those presented in the "Ethics of Caring" by Gilligan (1982). Gilligan emphasises five key principles relating
to ethical leadership with the origins of these can being traced back to the works of Aristotle. These
principles provide the foundation for the development of ethical leadership traits; these principles are
respect, service, justice, honesty, and community.
These are shown in Figure 1 which has been adapted from Northouse (2007). Briefly discussing each of
these traits, we see that leaders who respect others, approach people with trust, and acknowledge others'
values and ideas. Leaders who exercise this trait in their leadership are seen as providing service towards
others; they are considered as altruistic and are placing their followers' welfare as a priority in their plans
to implement change. This service trait has been emphasised by several authors on ethical leadership
maintaining that attending to the service of others, and developing trust is the primary building blocks of
ethical leadership.
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The importance of these traits can also be seen in the works of Senge (1990). In his work on learning
organisations, Senge emphasises that one of the most important tasks for a leader in learning organisations
is the stewardship role; the steward (servant), or the visionary of change, directs implementation during the
change process. This viewpoint has the characteristics of not being self-centered; it involves a deliberate
step taken by the leader with a motive of integrating one's vision with that of others in the organisation.
Senge, therefore, stresses that ethical leadership concerns itself with fairness and justice, with fairness
playing a role in integrating personal values with organisational values and justice demanding that the
leader place issues of fairness as a motive of their decision making.
Here we may look to the works of Beauchamp and Bowie (1998), who have outlined principles that may
guide an ethical leader in distributing the benefits and burdens relating to transformational change fairly.
The fourth principle of ethical leadership relates to the manifestation of honesty in an ethical leader. For
Gerstner, the communication of change at IBM was not an easy task; he had to represent the reality of the
situation at IBM and the challenge for him was to strike a balance between being truthful and to monitor
what information to disclose in particular stages of the transformation at IBM.
Dalla Costa (1998) makes this point clearly in his book "The Ethical Imperative" where he states that
"being honest" is more than just "not deceiving"; for an ethical leader, Della Costa points out that being
honest is governed by the characteristics such as to not promise what you cannot deliver, not misrepresent
information, not suppress obligations, not to reject accountability, and not openly accept that the
competitive pressures of business are an open reason to release our responsibility towards the respect
and dignity of others. Burns (1978) placed this characteristic of honesty at the centre of his theory of
transformational leadership. With the exercise of these four principles, the ethical leader, therefore, fosters
a community, a community created with belonging that has the characteristics of trust placed in the ethical
leader, a community that is bonded together and believes in the vision of the transformational leader such
as Gerstner. One of the eight principles that Gerstner developed at IBM to transform employees' beliefs
was that outstanding dedicated people make it all happen, particularly when the work together as a team.
THE ROLE OF TRUST IN HIGH LMX EXCHANGES
Central to these five principles of leadership is the role that trust has to play in each one of them. The
five principles of leadership presented in Figure 1 represent actions that an ethical leader follows as part
of his/her character. These actions can cause successful change when the leader has developed trust. For
example, respect of others can be exercised successfully only if the other person respects and trusts the
leader in the first place. Similar arguments can be applied for the other four principles of ethical leadership.
Gerstner at IBM exercised these five principles of ethical leadership to bring about transformational
change, and he was trusted as a leader and his team had confidence in what he was planning. We can use
the model of ethical leadership from Northouse (2007) and adapt it with the idea of trust as developed by
the author and see how this change was achieved at IBM. This can be seen in Figure 3, which shows how
Gerstner as a leader led IBM trough the necessary transformational changes.
The main component that functions actively through the five ethical leadership traits is the notion of trust.
When you trust someone, or someone trusts you, things can move more quickly and effectively. Less
obvious, but not less important, are the benefits of trusting others which are the abilities to trust customers
for greater efficiency and creativity in serving them.
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Figure 3. Relationship of the Ethical Leadership and Trust Model to change at IBM led by Gerstner.
We note that Gerstner would not have been able to lead with trust unless he was personally trustworthy and
capable of trusting. A trust relationship, therefore, has three aspects: (1) two asymmetrical roles - one who
trusts, another who is trusted, (2) the element of risk, and (3) reciprocating the roles of trustor and trustee.
Trust can be seen as a dance with two players: one who trusts, and one who is trusted. Most leaders and
managers focus more on being trusted that on trusting. Learning to juggle these is a critical skill for ethical
leadership. The best way to be trusted is to be worthy of trust, to be trustworthy. By far the most efficient
and effective strategy for being trusted is to actually be trustworthy. But what does that mean? One thing
it means is actively exercising certain personal traits. Whether from habit or personality, personal traits are
what allow others to consider us trustworthy or not. We will use the term 'virtues' to describe these traits.
It implies a consistency of character that provides a guidepost for the individual, and that can be relied upon
others. It may not be absolute, but we expect it to withstand some level of incentives, group pressure, or
business process. A virtue is something that we see as getting to the heart of a person.
According to Maister, Green and Galford (2000), there are four such traits: credibility, reliability, intimacy,
and (low) self orientation; they can be expressed, on a scale of 1 to 10, in the form of an equation, the
Trustworthiness Equation, and they cover most of the usages of "trustworthiness" in common and business
language, as well as across cultures. The Trust Equation arrays the four virtues in the form of an equation.
This format allows for discussion about interplay and impact though should not be taken too literally as a
description of something that exists outside the model.
The trustworthiness equation is:
Credibility is largely about words. We might say; I can trust what she says about this issue, meaning
we recognise her degree or her credentials, her statements are logical, she uses recognised means of
communication, there are no spelling errors in her resume, and so forth.
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Reliability applies more to actions. We might say; I can trust him to do (whatever he said he would do),
meaning he is dependable, predictable, a person of integrity; someone who honours his word, and if he
cannot honour it, takes immediate responsibility for it. Reliability is only trust equation component that
literally requires time, because it requires repeated experiences which happen over time.
Intimacy refers to a sense of security. We might say, I trust her with this information, meaning she is
sensitive to our needs, knows when and to whom to pass information along, and knows just how to treat it.
Self-Orientation is in the denominator of a trust equation, high levels of self-orientation mean low
level of trustworthiness. High self-orientation comes in two forms: selfishness and self obsession; the
latter is less obvious, therefore, more pernicious in business.
Any interaction with another human being is a potential source of fear, thus of fight or flight, but also an
opportunity to behave differently, in ways that create trust. Overcoming self-orientation is not a business
process, an analytic, or even a skill such as practicing tennis or a golf shot. It is a self-willed psychological
state in which we are ego-comfortable enough with our own selves to relate to others without fear or
desire to control.
The role that trust has to play in ethical leadership is, therefore, a crucial element in the overall character
of the ethical leader bringing about transformational change in any organisation. Credibility, reliability,
intimacy and self-orientation are, therefore, important variables that define trustworthiness in its
relationship together with the key factors of ethical leadership defined in Figure 4.
HIGH LMX
ENVIRONMENT
Figure 4: Illustrating Ethical Leadership, Trustworthiness and LMX Relationships
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LMX and ethical leadership theories make several positive contributions to our understanding of the
leadership process carried out by Gerstner at IBM. LXM theory uses the dyadic exchange relationship
as the main leadership process and emphasise that effective leadership is contingent on effective leadermember exchanges. The author has attempted to add content to this effective leader-member exchange
by using the model of ethical leadership and trust. LMX theory is also related to positive organisational
outcomes, and in a review of their research Graen and Uhl-Bien (1995) point out that it is related to
performance, organisational commitment, and many other important organisational variables. One of
the criticisms of LMX theory is that the basic ideas of the theory are not yet fully developed. For example,
it fails to explain how high-quality leader-member exchanges are created, trust and trustworthiness may
play key roles, as explained above, however, the role of different cultural values and abilities of different
people to acquire the ethical values is not really researched. There is also the problem of measurement
of leader-member exchanges in LMX theory by Graen and Uhl-Bien (1995) and Schriesheim et al. (2001).
No empirical studies have been carried out that use dyadic measures to analyse the LMX process and its
effectiveness with the ethical leadership model and further investigate the role of trust.
CONCLUSION
To conclude this paper, the author has attempted to explain the leadership process carried out at IBM
during the change management process using the LMX leadership model. This model was developed
further by the author to explain the importance of ethical leadership together with the notion of trust.
Trust was incorporated within the ethical leadership model adopted from Northouse (2007) to integrate
it with the LMX leadership process. In doing this, the transformational change that was implemented by
Gerstner at IBM was taken as an example of a practical ethical leader creating a high LMX. The emphasis
has been to develop the LMX model further by the application of ethical leadership theories to the IBM
case study on transformational change and to critically develop a discussion that shows the importance of
trust in the transformational leader leading change at IBM.
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REFERENCES
Bass, B.M. (1985) Leadership and performance beyond expectations. New York: Free Press.
Beauchamp, T.L. and Bowie, N.E. (1988) Ethical theory and business. NJ: Prentice Hall.
Bowie, N.E. (1991) 'Challenging the egoistic paradigm', Business Ethics Quarterly, pp. 1-21.
Ciulla, J.B. (1998) Ethics, the heart of leadership. Westport: Greenwood.
Ciulla, J.B. (2001) 'Carving leaders from the warped wood of humanity', Canadian Journal of Administrative Sciences,
18(4), pp. 313-319.
Ciulla, J.B. (2003) The ethics of leadership. Belmont: Wadsworth Thomson Learning.
Covey, S.R. (1990) Principle-centered leadership. New York: Fireside.
Dalla Costa, J. (1998) The ethical imperative: Why moral leadership is good business. MA: Addison- Wesley.
De Pree, M. (1989) Leadership is an art. New York: Doubleday.
De Pree, M. (1992) Leadership jazz. New York: Dell.
Gerstner, L.V., Jr. (2003) Who Says Elephants Can't Dance? Leading a Great Enterprise through Dramatic Change.
New York: Harper Business.
Gilligan, C. (1982) In a different voice: Psychological theory and women's development. Cambridge: Harvard
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Graen, G.B. and Uhl-Bien, M. (1995) 'Relationship based approach to leadership: Development on leader member
exchange (LMX) theory of leadership over 25 years', Leadership Quarterly, 6(2), pp. 219-246.
Greenleaf, R.K. (1977) Servant leadership: A journey into the nature of legitimate power and greatness. New York:
Paulist.
Heifetz, R.A. (1994) Leadership without easy answers. Cambridge: Harvard University Press.
Northouse, P.G. (2007) Leadership: Theory and Practice, 4th edn. MI: Sage Publications.
Schriesheim, C.A., Castro, S.L., Zhou, X. and Yammarino, F.J. (2001) 'The folly of theorizing "A" but testing "B": A
selective level of analysis review of the field and detailed leader member exchange', Leadership Quarterly, 12, pp.
515-551.
Senge, P.M. (1990) The fifth discipline: The art and practice of the learning organization. New York: Doubleday.
Sheppard, P. (2003) 'Leading the Turnaround: Lou Gerstner of IBM', Wharton Leadership Digest. Available at: http://
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Weiss, H. (1978) 'Social learning of work values in organizations', Journal of Applied Psychology, 63, pp. 711-718.
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APPENDIX 1 - CASE STUDY
LEADING THE TURNAROUND: LOU GERSTNER OF IBM
By Paul Sheppard, Wharton MBA Student and Deputy Editor, Wharton Leadership Digest
Lou Gerstner, retired Chairman and CEO of IBM, recently spoke at Wharton
about his experience of leading one of the most celebrated turnarounds in
corporate history.
In a pragmatic and modest speech, Gerstner was weary of drawing platitudes
of leadership that could be applied to every situation. Rather he wanted to
describe what happened at IBM and draw lessons from it.
When Gerstner took over in 1993, IBM had just announced a $8.1 billion loss; the largest in US history.
He had 100 days of cash left and IBM was already being written off by commentators as a dinosaur and an
also-ran. Not surprisingly, IBM's workforce was demoralized and hostile.
Gerstner's first task was to analyze the problem. Despite having good people, great technology and a sound
strategy, he found that IBM was suffering from a "success syndrome." Gerstner described IBM in the 1960s,
70s and 80s as "the greatest commercial institution ever created." But instead of continuing to build on this
legacy, it had become insular, inward-looking and rigid.
Organizationally, it had become a decentralized fiefdom in which none of the business units communicated with each other. Gerstner realized that his overarching task was to lead a massive organizational and
cultural change.
Gerstner quickly found ways to stop bleeding cash and identified the company's principal growth engines.
He wanted to break the assumption that customers would always buy IBM because of its past achievements. He then started to rebuild the company around the customer.
To reintegrate the organization, he sought to provide total solutions to customers. To do so, he needed
to transform almost every business process conducted by IBM. He cautioned his audience of star struck
MBAs that managing a complete turnaround was not as glamorous as they might think. He quoted one of
his senior managers who likened the implementation of the reengineering process to going to work every
day and "setting your hair alight and then putting it out with a hammer."
Painful as the process was, it was successful. The business units had been reintegrated and Gerstner made
$14 billion of cost savings. Gerstner said that he learnt three fundamental lessons from his time at IBM; the
importance of:
1. Focus. Gerstner stressed the how imperative it was for a leader to love their business and to "kill
yourself to make it successful." There is no substitute for hard work and the desire to win. CEOs
face a multitude of choices, often peddled by a multitude of self-interested advisors, but they need
to focus on exploiting competitive advantages in core businesses. Accordingly, it is the CEO's responsibility to manage consultants, investment bankers and advertising agencies so to best serve
their business rather than let them set the agenda.
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2. Execution. Gerstner said that execution is what really separates business leaders. As an ex-McKinsey
Director, Gerstner said that consultants' "dirty little secret" was that it is not that difficult to come
up with attractive strategies in public markets in which everyone has good information. The true
differentiator was how you implement them.
3. Personal leadership. Gerstner said that despite the volumes of business books written on leadership
recently, he still thought that this was the most undervalued element of institutional change. When
asked later for his advice of how MBA graduates should behave to strive to emulate his success,
Gerstner said that as a start you should always strive to do the job you are doing better than the
guy before you.
Finally, Gerstner wanted to discuss the importance and challenges of transforming corporate culture. For
him, institutional culture is not what is said but it what is done. As an example of cultural change, Gerstner
discussed abolishing IBM's notorious dress code. He said that at the time the public reception was as if he
"had sold the company to the Russians." But for Gerstner, it was common sense for IBM's salesmen to dress
as their customers were doing.
Gerstner said that changing the attitude and behavior of thousands of people is hard to accomplish but key
to success. The work environment is the crucible for individuals' productivity. Management cannot change
culture through words and policies alone. All leaders can do is create the conditions for transformation and
invite employees to respond. Not surprisingly, he attributed IBM's success to the thousands of employees
who were willing to react to his initiatives and work hard to make the elephant dance again.
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GAME THEORY - ITS
APPLICATIONS TO ETHICAL
DECISION MAKING
STEFANO CAVAGNETTO
BRUCE GAHIR
The application of game theory according to Hargreaves-Heap and Varonfakis (1995) to understand human
behaviour, and in particular ethical behaviour, is a valuable development, as game theory has gradually become one of
the key frameworks to assist us in the understanding of social sciences. Esther (1982) and Aumann and Hart (1992)
show that there are several studies that indicate the importance of a game theoretic framework in advancing our
understanding of social behaviour and evolutionary sciences. Although the application of game theory in the above
areas has largely been not formalised, its application in the fields of ethical conduct and human behaviour is at present
developed in several respects with the gradual assistance of advances in related areas such as evolutionary biology and
our understanding of group social behaviour.
Game theory tends to be dominated by its assumptions concerning the non-rational nature of the dynamics existing
within social structures and these processes are generally ignored or are sometimes difficult to model. Assumptions that
are made concerning the cognitive abilities and beliefs about individuals are generally unrealistic, and this at times is the
main criticism of game theoretic applications in our understanding of ethical behaviour. These are the lines followed by
Solomon (1999) in his discussion on game theory when it is used to model scenarios in business ethics and in general in
the business area. In particular, game theory tends to excessively emphasise the destructive obsession of the quantifiable
outcomes and an artificial concept of competition. This modelling of competition is not exhaustive of human behaviour,
but rather an oversimplification of the social dynamics in place in many different human contexts.
The first objective of this paper is to offer a brief sketch of the historical developments that have taken place in game
theory and some of its fundamental concepts through an analysis of the most important games that have found an
application to the field of ethics. A second aim is that of providing the reader with a review of developments relating
to evolutionary game theory that has deeply assisted our comprehension of ethical norms and their emergence in group
behaviour. The final part of the paper will be dealing with some conclusive remarks from a methodological point of view
on the main issues concerning applications of game theory to ethics.
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A SHORT HISTORY OF GAME THEORY
Game theory's history can be roughly divided into three different periods. The first period is characterised by
the development of the study of games linked with the development of research in probability theory and the
development of probability calculus due to Pierre de Fermat and Blaise Pascal. In the literature this moment
begins with a famous correspondence between the two French mathematicians dated 1654 (Hyksova, 2004).
About sixty years later, the mathematician James Waldegrave had an important part in the creation of the
concept that is nowadays known as an example of a mixed strategy solution of a matrix game. Waldegrave
in a written correspondence with Pierre Remond de Montmort on the 13th of November, 1713, offered his
solution for the card game Le Her. This game was quite popular in the 18th century, and it is a card game
played by two players. In the literature they are usually referred to as Peter and Paul, the dealer and the receiver, respectively (Epstein, 2009). It begins when Peter deals Paul one card that is randomly chosen from an
ordinary deck of 52 cards. After that, he then gives a card to himself. Both players cannot see the cards dealt
to each other. The purpose is to keep the card of a value that it is higher than the value of the opponent (the
king is the highest and the ace the lowest). If Paul is not happy with his card value, he can ask his adversary to
swap with him, with the only exception when Peter has a king. On the other side, if Peter, the dealer, is not
happy with the card value that he has after the exchange, he is then entitled to swap it for a card randomly
picked from the remaining pack of cards. At this point, Peter is permitted to take a new card if and only if the
new card is not a king, in which case he is must keep his own previous card. Following the exchanges, Peter
and Paul compare the two cards that they are holding. The player with the higher card value is the winner.
In the case that both Peter and Paul hold the same card value, then the deck holder is the winner, i.e. Peter.
This game was previously studied by de Montmort and Nicholas Bernoulli in terms of winning strategies.
Both scholars arrived at the conclusion that the deck holder should change each card carrying a value inferior
to 8, while the opponent should change each card carrying a value less than 7. In questionable situations de
Monmort was of the idea that no guidelines could be given, while Bernoulli thought that both players should
change. On his side Waldegrave was investigating the possibility of proving the existence of a strategy that
could maximise the probability of a player's win, independently from the strategy selected by the other opponent. Nowadays this is known as "minimax principle", and it will be discussed later on in this paper. As
remarked in Hyksova (2004), the mixed strategy proposed by Waldegrave for the solution can be formulated
in terms of Black and White chips and it can be shortened as follows: the deck holder (Peter) has to adopt the
strategy <change 8 and lower> with the probability P = 0.375 and the strategy <keep 8 and higher> with the
probability P = 0.625. On the other side the opponent, Paul, has to select the strategy <change 7 and lower>
with the probability P = 0.625 and the strategy <keep 7 and higher> with the probability P = 0.375. As pointed
out in Hyksova (2004), despite the fact that de Montmort included in his publication all the correspondence
relating to Le Her, together with Waldegrave's contribution, this solution proposed by Waldegrave stayed
ignored for a very long time.
The second period goes approximately from 1913 to 1928 and is characterised by the work of the famous
set theorist Ernst Zermelo, the French mathematician Emile Borel, and by the first researcher in this area, the
naturalised American mathematician John Von Neumann. In some sense the first theorem of game theory
was proven by Zermelo. The theorem claims that in a game of chess three different outcomes are possible:
white can force a win, black can force a win, or both sides can force at least a draw. The first modern formulation of a mixed strategy and the minimax solution was given by Borel between 1921 and 1927. He gave
the minimax solution games with two players and with three or five possible strategies. Finally, by 1928 von
Neumann proved the minimax theorem for zero-sum games, two players, and finitely many pure strategies
for each player. In particular, when mixed strategies are taken into account, this form of games have exactly
one (rational) payoff vector. From the notational point of view, these works introduced into the field of the
well-known extensive normal form for a game (Hyksova, 2004).
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The third era starts with the investigations carried out by Von Neumann and the economist Oskar Morgenstern at the beginning of the 1940s during the Second World War. In traditional accounts of the history
of game theory, it is recognised in the literature that the comprehensive monograph Theory of Games and
Economic Behavior published in 1944 by J. Von Neumann and O. Morgenstern developed the modern mathematical framework for the discipline. Undeniably, this publication represents the first important modern
milestone in the development of this branch of applied mathematics and is normally regarded as being the
starting point of game theory as an autonomous mathematical discipline. The monograph starts with a
thorough formulation of economical problems and explains what might be the potential of game theory
and its possible applications in modelling economic situations.
The work also lays down the foundations and a suitable framework of an axiomatic utility theory that is
a classic reference for further research. The monograph also includes the general formal description of
a game of strategy and an extensive study of the theory of finite two-player zero-sum games and certain
types of zero-sum cooperative games with n players. The work of Von Neumann and Morgenstern widely
contributed to the development of game theory as an independent field of research and thoroughly placed
a great emphasis on its potential applicative aspects.
A second crucial milestone in the history of game theory is symbolised by John Forbes Nash's doctoral dissertation devoted to a full mathematical investigation of the theory of non-cooperative games. The idea of
equilibrium point (today called Nash equilibrium) was discussed and its existence was demonstrated. The
most important achievements of his dissertation were published in a short note, (Nash, 1950), and in a second more exhaustive paper published a year later (Nash,1951); in the literature usually the name of Nash is
also associated to a second idea that of Nash bargaining solution regarding two-player cooperative games
for a certain type of games known as "cooperative games with no transferable payoffs". In this respect Nash
formulated a system of axioms that a solution should satisfy as a set of requirements and demonstrated the
existence of a unique solution with these requirements for the chosen set (Nash, 1951).
Definitely one of the first clear uses of game theory outside of the economic field was the application to
political sciences. Remarkable in this sense was the work of L. Shapley and M. Shubik, A Method for evaluating the distribution of power in a Committee System, published in 1954. In this paper the authors investigate
a possible solution for cooperative games in order to establish and determine the UN Security Council
members' power.
In the late 1950s after Shapley's and Shubik's work, many other publications appeared that contributed to
shape the literature of political sciences and made game theory central to the field in modelling several scenarios related to legislature, elections, politics of interest groups, lobbies, bargaining, etc. Nowadays game
theory offers the suitable terminology and methods to resolve particular and general problems. Two fundamental works should be mentioned, the first is the work by R.D. Luce and A. A. Rogow, A Game-Theoretic
Analysis of Congressional Power Distributions for a Stable Two-Party System, and the work by W. H. Riker, A Text
of the Adequacy of the Power Index, published in 1956 and in 1959, respectively.
Current monographs on political sciences regard game theory as an indispensable tool and component of
the discipline; the interested reader can see for example as reference works by J. D. Morrow and by P. Ordershook (Morrow, 1994; Ordershook, 1986). Even though game theory is not seen as the best provider
solution tool for any given problem, and indeed it cannot provide an optimal solution to all problems, political scientists regard it as a powerful tool for analysis of a given political and social situation. As remarked
in Hyksova (2002), in this framework game theory is regarded as a strong tool that "induces the decisionmaker to think rationally and without emotions; this, in itself, often yields a general acceptable solution".
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Currently game theory is one of the most important tools for the study of conflict and cooperation in the
world of living beings ranging from animals to plants as well. Game theory has been used for the analysis,
modelling, and understanding of several zoological applications, from fight to cooperation and communication of animals, and from analysis and modelling of coexistence of alternative traits to distributions
of individuals in their habitats in different species. Many applications can be found also in botany where
the theory has been applied successfully to seed dispersal, seed germination, root competition, nectar
production, and flower size differentiation. The 1960s saw the appearance of different sparse and isolated
research employing game theory to approach a few problems in biology, but most likely the cornerstone
and ground-breaking work was The Logic of Animal Conflict by John Maynard Smith and George Robert
Price. This work, published in 1973, inspired a large number of research endeavours and utilisation of game
theory in evolutionary biology and contributed to create a solid framework for the further independent
development of the field.
Maynard Smith's work Evolution and the Theory of Games appeared in 1982 summarises well the subsequent
developments of these applications and their success in evolutionary biology. Indeed, Evolution and the
Theory of Games demonstrated how game theory could help to offer the most insightful explanations
of the theory of evolution and the principles of behaviour of animals and plants when they are analysed
in a context where they can mutually interact. In the end, most likely evolutionary biology turned out to
provide as a field of research and projects development the most promising applications of game theory
(Hyksova, 2002).
INTRODUCTION TO SOME FUNDAMENTAL CONCEPTS AND THE PRISONER'S DILEMMA
Game theory can generally be explained as a framework that allows one to derive outcomes with assumed
preferences for agents concerned. These outcomes may arise due to interactions amongst agents where
certain preferences, called utilities, are key drivers.
The analysis of games depends on the outcomes and expectations of players, or agents. Situations where
the expectations of other agents depend upon expectations of one-self will be generally governed by required outcomes and performances called utilities. Let us first examine the concept of utility prevalently
used in game theory. An agent with required needs is generally defined as an economic agent. If such
agents are considered as rational then their rational decision-making process can be described following
the concept of utility. Utility here is described as a measure of an increase or decrease in the subjective
welfare that is attained as a result of desired outcomes.
'Welfare' here is defined as some form of normative index indicating a measure that depicts the well being
of an agent, for example, the welfare of different countries based on their per-capita income. In the areas
of economics and game theory, where the focus is more on the relative welfare concerning people, the
idea of 'utility' tends to denote a measure of subjective psychological fulfilment.
Game theory involves the domain of formed reasoning and as a result the idea of 'utility' requires a framework that is grounded in formal terms. The 'utility function' is therefore defined as a mapping that maps
agents ordered preferences to real numbers. Let us suppose, for example, that:
Agent A has a preference to outcome "X"
compared to outcome "Y" and outcome "Y" compared to outcome "Z".
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This scenario can be mapped using numbers and a utility mapping function as follows:
Outcome X = 3
Outcome Y = 2
Outcome Z = 1
In this example, we note that the property mapped by the utility function is order. In a game theoretic
framework, a game is any situation where agents act in a way to maximise their utility by anticipating the
response to their actions by other agents. Agents participating in games are called players. Players are assumed to have capacities that are collectively referred to as 'rationality'. A player is defined to be economically rational if and only if:
1. A player evaluates outcomes in a game and ranks these outcomes with respect to their contributions to his/her welfare.
2. A player calculates which sequence of actions leads to which outcomes.
3. A player selects actions from a set of alternatives that produce the most preferred outcomes.
In such cases we may describe an agent as 'choosing' actions from a selection of possibilities. Such a kind of
'economic rationality' may be part of the behavioural dispositions of the agent. In this case, each player in
the game is facing a choice and a strategy is defined as a pre-determined programme of play. In what are
termed as 'simple games', from the point of view of logical structure, agents are supposed to have perfect
information; for instance, chess is such a game.
In this game a player tends to choose actions by reflecting upon the series of responses and counter responses of the opponent and then considers which of these responses will result in the highest utility. Let
us illustrate this further by a famous example called the Prisoner's Dilemma (PD). Usually in the literature
the game is attributed to Merrill Flood and Melvin Dresher as the type of games that were discussed extensively at the RAND Corporation in the 1950s during the Cold War in the context of the exploration of
different strategies to be pursued in increased development relating to global nuclear weapons.
The name "Prisoner's Dilemma" was given by the Canadian mathematician Albert Tucker (Poundstone,
1992). In 1950, Tucker presented the ideas of Flood and Dresher to an audience of psychologists at Stanford University, and in order to make these concepts more accessible to an audience of non-mathematicians, proposed a situation that describes a scenario where the police have arrested two possible suspects
(Axelrod, 1984). They believe that these suspects have committed an armed robbery. However, the police
are in an unfortunate situation as they lack evidence to support their claim about their robbery being committed together by these two possible suspects. However, the police have enough evidence to convict
each of the suspects for one year for theft of the getaway car that was used. So, during the questioning
process the following proposals are made to both the suspects by the police:
1. If Suspect A (SA) confessed to the robbery claiming that Suspect B (SB) was involved and SB does
not confess to his collaboration with SA, then SA will go free and SB will be convicted to twenty
years, a similar situation also results if SB confesses and SA remains silent.
2. If both SA and SB confess then, each of them will get five years.
3. If neither SA nor SB confesses, then they each will be convicted for one year because of the car theft.
These options are represented in the matrix in Figure 1.
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5,5
0,20
20,0
1,1
Figure 1: Pictorial representation of the Prisoner's Dilemma.
If we represent these options in term of utility functions representing Suspect A as player one and Suspect
B as player two, then we have the following situation:
Go free = 4
Sentenced for 1 year = 3
Sentenced for 5 years = 2
Sentenced for 20 years = 0
If we now utilise these numbers to express each player's payoffs in the different options represented above,
we can represent them on a single matrix as follows:
2,2
4,0
0,4
3,3
Figure 2: A Prisoner’s Dilemma matrix of payoffs.
We note that each cell in the matrix provides a payoff to both players, and player 1's payoff appears as a
first numbers in each of the pairs. So for example, (2, 2) represents five years in prison for each suspect,
this matrix can therefore be compared with the one in Figure 1.
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The situation is therefore such that each player is able to evaluate their two possible actions by comparing
and contrasting the personal payoffs that each will receive, and these are represented by the numbers in
each pair shown in the cells of the matrix in Figure 2. Now, let us consider the situation from the point of
view of player 2. If player 2 confesses, then based on the utilities and options in the matrix, player 1 gets a
payoff of 2 due to confessing and a payoff of 0 if he refuses to confess; therefore player 1 is better of confessing independently from what player 2 does in this situation. So, in a similar way player 2 also comes to
an evaluation that points to confessing. So, we note that if both players confess then both will be convicted
for 5 years, and in this case, we say that confessing strictly dominates refusing to confess for both players,
so the dominant strategy is to confess.
First of all, let us notice that both players can arrive at this outcome by using a mechanical process called iterated elimination. Using the matrix in Figure 2 we can see that for player 1 the payoffs for each of the cells in
the top row are higher in value than those in the bottom row; therefore for player 1 the utility maximising
strategy is not to choose the options in the bottom row, this means, denying to confess, independently from
what player 2 does. So, as player 1 will not play the bottom row strategy, we can simply erase the bottom
row or shift along the orange arrows to the higher pay off options along the matrix as indicated in Figure 2.
It is now obvious from Figure 2 that player 2 will also not refuse to confess because the payoff from confessing
is higher than refusing to do so. Again, in this case as before we can erase the one cell column on the right of
the matrix or again move along the orange shaded arrows which will now converge to the point of the light
green shaded equilibrium cell. Through this iterative procedure we can determine almost mechanically the
dominant strategy, in this case that is represented by the strategy pair <confess, confess> for both suspects.
The order in which the rows are deleted in the above process does not really matter; we would arrive at the
same solution even if we had started by deleting the right column first. The strategies chosen by agents reflect
the ones that lead to higher payoffs and these point to the situation of joint confession as the solution for this
PD game where both players are being motivated by being economically rational. When the PD is generally
discussed, one often hears that the police inspector must separate the suspects into different rooms, and this
is done with the aim of preventing any mutual communication between the suspects. Because in the case
of possible communication the suspects would surely realise that each of them is better off if both refuse to
confess, and this means that they could make an agreement to do so; collusion is therefore barred in this PD
example. We will discuss later examples where cooperation can be introduced in such PD type examples.
In general, the PD models a scenario where there are advantages from cooperation (each player would prefer
the strategy <refuse, refuse> than they both select the strategy <confess, confess> but every player has an incentive to a 'free ride' (namely to select the second strategic option) independently from the behaviour of the
other player. Despite the attractiveness of the name of the game, its value goes well beyond comprehending the incentives for prisoners to select the strategy <confess, confess>, but because there are numerous
situations that have analogous logical structures. Every time each of two players has two possible strategies,
let's say R (denoting the strategy 'Remain silent') and C (denoting the strategy to 'Confess'), the first player
prefers (C, R) to (R, R) to (C, C) to (R, C), and the second player prefers (R, C) to (R, R) to (C, C) to (C, R), the
dilemma represents the situation that the player is facing. A classic example in economy where the situation
can be easily modelled using a variant of the PD is the model of a duopoly where two companies manufacture
an identical good, for which every company charges either a low price or a high price. In this situation every
company aims at the highest possible profit. In this case, the two strategies 'Charge High Price' and 'Charge
Low Price' correspond to the strategies 'Remain Silent' and 'Confess'. A reader interested on several different
examples derived from the PD and a discussion in depth about the assumptions around the incentives for this
type of games can consult Osborne (2002).
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Let us now suppose that the two suspects do value each others' future lives; if this is the case, then we
could reasonably assume that such a condition will be reflected in their respective utility functions and also
in their payoffs, and it is therefore the logic of the way the PD situation is set up that produces the inefficient outcome and not the psychological makeup of the two suspects. Following the terminology of game
theory, the optimal (2, 2) position is referred to as the equilibrium position, technically known as the Nash
Equilibrium (NE) from the name of the mathematician John Forbes Nash. Given the strategies of all other
players in the game, we say that a set of strategies is a Nash Equilibrium (NE) when no player could improve
their payoff. Therefore, if iterative elimination takes us to a unique outcome, this is the game's unique NE.
Before going on, let us see some of the assumptions that play a crucial role in the Nash equilibrium theory.
As in the case of the rational decision maker, it is assumed that every player select the best possible action
offered. Of course, in a given game scenario the best possible available action depends for each player on
the actions selected by other players. This implies that when a player will choose an action, that player will
have in mind the actions that the other players will select. This means that each player will create a belief
based on the actions of the other players.
Of course the obvious question here is how this can be done, on which basis can such a belief be created?
The main assumption here is that each player has a certain set of beliefs that is based upon their experience
in the past in playing the game and that this experience is sufficient and extensively rich enough to know
how their opponents in the game will behave. Nobody tells the player how the other players will behave
and which course of actions will be chosen; however, the past involvement of the player leads to some level
of certainty about these future actions (Osborne, 2002).
This point is quite subtle but very important. The assumption is that every participant in the game has
experience in playing it; one can assume that the player views every round of the game in isolation. The
result of this is twofold. On one side, the specific player does not familiarise with the behaviour of specific adversaries, and as a consequence, does not make the actions of the strategy chosen depending on
the actions of the specific opponent they are facing. On the other side, the player does not expect that
the current actions deriving from the selected strategy will affect the other participant's future behaviour
(Osborne, 2002).
The best way to imagine this situation is to consider the following idealised situation. "For every player in
the game there is a population of many decision-makers who may, on any occasion, take that player's role.
In each play of the game, players are selected randomly, one from each population. Thus each player engages in the game repeatedly, against ever-varying opponents" (Osborne, 2002). Thus it is the experience
of the player that guides the player to certain beliefs concerning the actions of characteristic opponents
and not any detailed group of opponents.
To sum up, the concept outlined above has two components. First, each player selects an action consistently with the model of rational choice adopted, given the set of beliefs about the actions of the other players. Second, the beliefs of each player concerning the actions of the other players are correct. As remarked
in Osborne (2002), these two elements are the founding conceptual elements embodied in the notion of
Nash equilibrium described above.
Having elaborated upon some basic concepts and their role in game theory we will turn now to a specific
application in the field of ethics.
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GAME THEORY AND ETHICAL DECISION MAKING
We can date back the application of game theory to ethics around 1954 when the philosopher Richard
Braithway gave a lecture titled "Theory of games as a tool for the moral philosopher". He argued that
several of the problems encountered in the areas that discuss distributive justice in ethics have similar
structures as the bargaining problem. The application of game theory to ethics was not really an original
development during this period, elements of game theory analysis of certain ethical problems can be found
in the works of several philosophers such as Thomas Hobbes and David Hume, while further details of this
work can be found in Gauthier (1969), Kavka (1986), Hampton (1986), Van der Schraaf (1998). Several
years after the work of Braithway, Brain Barry published his work "Political Argument", followed by David
Lewis' work "Convention" (Barry, 1965; Lewis, 1969) that provided further details to Braithway's ideas.
However, it is not until the late 1960s when the first publication in a series by David Gauthier appeared
providing formalised detail to the bargaining situation and its application to ethics. Surveying the literature,
concerning the applications of game theory to ethics, one can generally classify the areas being discussed
into three main parts:
1.The functionalist approach - where the focus of game theory is to establish the functions of morality.
2. The contractariarism approach - where game theory is used to formalise social contract theory.
3. The evolutionary approach - where evolutionary game theory is utilised to recover and establish
the origin of moral norms.
Below we shall discuss these separate approaches further in some detail, elaborate on their outcomes, and
present some of the problems that authors have commented upon.
THE FUNCTIONALIST APPROACH
A good example to consider when discussing the functionalist approach is the "Gunner" example presented by Edna Ullmann-Margalit, in her work "The Emergence of Norms", the interested reader can see
Ullman-Margalit (1977).
In this work Ullman-Margalit argues for the emergence of moral norms and argues that such norms provide agents with a framework to cooperate and coordinate their actions in certain scenarios and situations
where the following of self-interest would otherwise prevent such a situation from occurring. She takes the
example of two artillery men facing a choice to either stay and use their weapons and fight against the enemy or flee for their safety. If both decide to stay and face the enemy, they may have a high chance of being
injured in the attack, but there is a high probability that they will stop the enemy from advancing further.
However, if one artillery man stays and the second one flees, the brave artillery man is certain to die in battle while the other one will escape safely. So, each artillery man has a choice of either fleeing or staying and
fighting, this is represented in Figure 3 as a matrix.
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2,2
0,3
3,0
1,1
Figure 3: Illustrating the Ullmann-Margalit Example.
The choices are represented as rows for artillery man 1 (A1) and columns for artillery man 2 (A2). We
note that, as before in Figure 2, each cell in the matrix is shown to represent the particular outcome of each
possible pair of choices facing the artillery men.
The first number represents how A1 could rank his outcome taking into account the relative possible
outcomes of others, ranks are here represented as numbers denoting utility, and the second number in
the pair represents the ranking of A2. Let us now consider the situation of A1, suppose that A2 decides to
stay and face the enemy, to defend his position, in this case it is best for A1 to flee, he will survive without
getting hurt. The matrix shows that he will obtain a higher ranking which is 3 rather than 2, (3 > 2) ). A
similar situation results if we consider A2 fleeing, then it is best for A1 to flee also, he will survive the battle,
although he may face imprisonment for fleeing in the face of the enemy attack.
So, for each individual artillery man it would be at an advantage to flee, despite the actions of the other.
Following the reasoning of iterative elimination carried out with the PD example, we note that from the
point of view of utility maximisation, both artillery men would be better off if they stayed in their respective
positions and faced the enemy, even though this may seem paradoxical showing that the outcome of individual rational action is being suboptimal. Ullmann-Margalit argues that in this example rationality appears
to point to outcomes that are not optimal, morality binds the individual gunners to stay and fight, to face
the enemy and defend their positions, so it seems as if the function of morality is to assist us in preventing
the failures of rationality.
Ullmann-Margalit claims that it is the function of the artillery men that binds them to stay and not to follow
the rational choice of fleeing and saving their lives. We note that there are several criticisms that can be
made towards such a functional approach towards our understanding of moral behaviour. First, there are
recognised hurdles with the functionalist approach when it is utilised to explain areas of moral behaviour
in the social sciences. One needs to be aware of the fact that if a practice or an institution follows certain
functions this does not necessarily explain the origin or the maintenance of such a function. For example,
the function of the public education system may be to provide an opportunity for the citizens of the state
to obtain an education. However, until there is a causal connection between the apparent function and its
bringing about into existence and maintaining the education system, no real explanation has been provided
by following such reasoning.
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Similarly, one may argue that even though moral norms may contribute to bringing about certain outcomes that are not realisable through uncoordinated individual rational action, no real explanation can said
to be existing unless one demonstrates that somehow the function of providing education plays a motivating force in contributing towards human action and is therefore causally effective in the consequences that
may arise with possible beneficial outcomes, that are also optimal in a game theoretic framework.
Secondly, it is questionable if morality corresponds to mutually advantageous outcomes. We are often
morally motivated to act in ways that cause disadvantages to people around us. A common example taken
is the prohibition against slavery that is willingly entered into by an individual. Such a situation may have
certain advantages to the slave as he will be able to acquire enough funds to settle due debts and for the
master also as he would have some assistance for housework on a daily basis; however this is not only prohibited morally but is also illegal.
Thirdly, the functionalist viewpoint tends to assume that the moral demands appear to be in conflict with
our individual rational decision making abilities, according to the above artillery example the morality of
both artillery men is supposed to correct the pending sub-optimal option that results due to so-called
'rational deliberation'. However on the functionalist account of morality, moral agents appear to act irrationally as the artillery men exclude any considerations of guilt-avoidance or regret or even their patriotic
feelings towards their country and fellow soldiers, this tends to beg the question, "Why be moral?"; functionalism does not appear to provide us with any answer to this question.
This leads us to the fourth and final criticism. The objectives of functionalism seem to be to provide us
with explanations for the emergence and persistence of moral norms by observing the functions that are
performed by agents. However, morality as a guide to action, the normative approach is not really focused
upon. Clearly, one can argue and question if there is any difference between (i) ascertaining what the
function(s) of morality are and (b) questioning whether a certain group of norms are to be followed in a
situation facing the agent, but we are at a loss on how this question can be answered if a functionalist approach is taken as our viewpoint.
We note that in the artillery example discussed above, the question of moral motivation arises as a kind
of deliberation that exists outside of individual rational choice, that is not really entertained as part of the
rational choice process. Is there any way that we can understand morality as part of individual rational
choice? The approach that has been used and the one that we will discuss below regards morality as the
intended interaction between ideal circumstances and rational agents. This follows similar ideas to those
developed in the 'social contract' where morality arises as a consequence of a kind of bargaining process.
As a result of this, the introduction of game theory, primarily those areas concerned with bargaining and
cooperative game theory have generated interest in the development of social contract theory. The works
of John Harsanyi, Richard Braithwaite, John Rawls, Brian Berry and David Gauthier have formulated versions of such a theory (Harsanyi, 1955; Braithwaite, 1955; Barry, 1965; Rawls, 1971; Gauthier, 1986).
By utilising areas of bargaining theory into a game theoretic framework, there has been an attempt to show that:
1. When rational agents are in an idealised bargaining situation, they will tend to find an agreement
on a distribution of benefits of cooperations amongst themselves.
2. There is a particular form to this distribution.
3. This distribution determines what is just.
4. Rational agents will agree with the conditions of the bargaining process.
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Let us discuss how such a bargaining situation is characterised in the artillery example above. Without any
co-operation, the artillery men are bound to flee and face captivity for the remainder of their lives. If we
now suppose that it may be possible for the two artillery men to come to some kind of binding agreements
(however, the problem is that it is not obvious how the benefits of such a co-operative agreement could be
distributed) then we could consider an example where the artillery men could come to a situation where they
decide to flee with a probability of 1/3 and stay and face the enemy with a probability of 2/3. The numbers
(0, 1, 2, 3 ) in the matrix in Figure 3 only represent the rankings of the outcomes, by assigning probabilities we
are now providing greater information concerning the relative rankings of the different outcomes.
The utility of "2", for example, that stands for the co-operative outcome and means that the artillery man
is in a position where he is indifferent between this particular outcome and the alternative "0" which stands
for the worst outcome with a probability 1/3 and "3" which is the best outcome with a probability 2/3. In
this case, we can define what is called a 'Bargaining Area' which represents a range of different outcomes.
Suppose now, that the artillery men are provided with a pair of dice and they agree to throw both dice and
be governed by the following conditions:
1. If a total is equal to 6 or less, then A1 will flee therefore achieving his utility ranking of 3.
2. If both dice total more than 6 then A1 will stay and face the enemy thereby achieving the worst
utility ranking of 0.
The expected utility of this deal for A1 can now be calculated as follows:
5/12 (3) + 7/12 (0) = 1.25
While A2 can expect 3 – 1.25 = 1.75 from this situation. Thus the artillery men can realise an entire range
of outcomes forming the shaded green area called the bargaining area as shown in figure 4.
Figure 4: Illustrating the Bargaining Area.
From this bargaining area we note that the optimal outcome of the agreement between both gunners
will be (2, 2). Each outcome that provided the artillery men an expected utility of greater that 1 appears
to be rationally acceptable. The application of bargaining theory to ethical reasoning, therefore, provides
further detail to PD type cases, we now consider how this has been developed further by the work of David
Gauthier in explaining the contractarian approach.
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THE CONTRACTARIANISM APPROACH
The most influential areas of contractarian theory are those developed by David Gauthier presented in his
seminal work, "Morals by Agreement" (Gauthier, 1986). This work utilises extensively game and bargaining
theory ideas, some of which have been touched above and attempts to provide us with an answer to the
question posed earlier, namely "Why be moral?". In this respect, we could say that Gauthier's contractarian
theory does contain several differences compared with the work developed by Rawls, Harsanyi, and others,
we discuss some of these ideas presented by Gauthier briefly here.
The first part of this work provides us with a general account of "practical reason" and the "condition of humankind" in relation to moral motivation; Gauthier (1986) then continues to discuss the "principles of conduct"
that rational agents should agree upon – a kind of contract similar to the social contract. The third part of his
work is a much discussed account concerning "practical rationality"; indeed this part is essential to Gauthier's
argument as it aims to demonstrate that everyone under "normal circumstances" has some reason to accept
the constraints imposed by those principles, this part essentially presents the answer to the question "Why be
moral?". Finally, Gauthier argues that the principles of conduct, that he details, are indeed principles of morality.
Gauthier points out that we tend to misconceive practical rationality. He argues that the main aim of rationality is not to determine our principles of decision making – for example, to select the best option at every time
when we are faced with choices. Gauthier asserts that our aim should be to reason in ways that are utility
maximising. He develops his arguments in "Morals by Agreement" in terms of "dispositions to choose" and
precisely by utilising the idea of "constrained maximisation" - the disposition to co-operate with others even
when circumstances dictate that defecting is the more advantageous option as in the arbitrary example.
If we assume, as Gauthier does, that agents are at an advantageous position in certain circumstances when
acting in certain ways that are not maximising utilities, the question we then face is to explain how to act as
such a 'constrained maximiser' is economically rational. Gauthier argues that in certain circumstances if our
tendencies to choose are rational, then it follows that our choices determined by these tendencies are also
rational. For Gauthier, if a course of action is better, from a constrained point of view, then any other action
that may follow may also be rational to adopt given certain conditions. However, to carry out such an action
may not be in the best interests of all concerned.
Gauthier, therefore, seeks to establish that if a mode of deliberation is rational, then acting accordingly can
also be rational, even if such an action requires performances that are not considered to be optimal from
the game theoretical point of view. If Gauthier's arguments carry substance, we note that it can, therefore,
be rational to adhere to certain norms even though they may require following some course of actions that
are not the best from the point of view of utility maximisation. Gauthier's work has been developed further
by different revisionist accounts of practical rationality (see Gauthier (1994), (1996), (1998a and b), and for
revisionist accounts the interested reader can see for example McClennen (1990)). Gauthier's defence of
'constrained maximisation' represents a significant revision of standard game theoretic approaches to such
decision making problems. Most game theorists argue that Gauthier's idea concerning "modes of deliberation" under "constrained maximisation" conditions can be modelled in a more complex kind of decision game
theory (Binmore, 1994).
However, there are doubts whether a game theoretic approach to our comprehension of the bargaining
process can assist us to predict the outcome of the deliberation of rational agents involved in required decisions given certain conditions. Such approaches to our understanding of the decision making process tends
to assume that there is a unique outcome with rational motivations to such deliberations, while this may be
plausible under certain circumstances, generally this is far from obvious in most situations.
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Gauthier's development may be acceptable in explaining the emergence of fundamental norms arising
from hypothetical situations in which large groups of agents are bargaining over principles. Nonetheless,
one could say that it is questionable whether this is an appropriate methodology to follow in modelling
the process of rational choice leading to the emergence of particular moral norms being followed. At this
point, it is an appropriate to consider an alternative viewpoint being offered by Evolutionary Game Theory
(EGT). EGT is a third mode in which game theory has been developed to its application to ethics.
THE EVOLUTIONARY GAME THEORY APPROACH
Some important insights into how certain kinds of game equilibria can lead to the evolution of choices
were offered by the development of Evolutionary Game Theory (EGT) and its application to ethics. Gintis
(2000, 2009) states that "evolutionary game theory is a universal language for the unification of behavioural sciences". There are several good examples of such unifying works; Binmore (1998, 2005a) models
social history as a series of convergent situations that arise due to efficient equilibria encountered in different transaction games.
EGT has also been successfully applied to the field of evolutionary biology where species and/or genes are
treated as agents/players from a game theoretical viewpoint. In EGT, moves amongst a choice of possible
options are not arrived at by economically rational agents. Instead, agents are disposed to particular strategies by their very nature, and the success and failure of a particular strategy is determined by the number of
copies of itself that it will have to play in the games of succeeding generations, given a population in which
other kinds of strategies that an agent acts are also distributed at particular frequencies. In this approach,
the players represent strategies and the individuals are the executors of these strategies who get the benefits/costs associated with the different outcomes. To elaborate on this further, our discussion will now
follow the work of Skyrms (2004), who introduces the idea of "replicator dynamics". As an example, let us
first consider how natural selection works for any animal that may have heritable features.
From evidence provided in biological studies, it can be seen that any animal that may have heritable features that are likely to increase its expected number of offspring in a given environment, has the tendency
of leaving a greater number of off-spring than others. So long as the environment remains stable, this offspring are more likely to inherit the features in question, and therefore the proportion of these features
in the population will gradually increase with successive generations. A natural question arising now is the
following: how does game theory assist us to explain such evolutionary dominance?
One important characteristic of an organism's environment is to maximise reproductive fitness by adopting certain strategies that provide optimal solutions given the strategies of other populations. In EGT we
no longer think of agents as choosing strategies when they leave one game to enter another; the focus
is not to find the equilibrium of games, instead the aim is to seek equilibria that are further explored as
they gradually alter over time. We therefore model strategies as competing against each other and we
say that one strategy is more efficient than the other if it has more copies of itself in the next generation;
this allows us to investigate the modification and change in a distribution of strategies in the population at
the moment the sequence of games unfolds (Skyrms, 2004). So, we note that instead of understanding
morality as the consequence of complex processes involving bargaining between informed agents following rationality, the focus now in EGT is rather to move away from such an approach and see morality as
an unintended consequence of interactions between agents that arises due to repeated interactions between small groups. As a result of this, rather than assuming full information and rationality as a condition
amongst agents, EGT requires less taxing assumptions concerning cognitive and deliberative skills of agents
compared with earlier game theoretic models.
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Let us now consider the following example to illustrate these ideas further. The example comes from
Rousseau who describes the state of nature as being similar to a stag hunt (Rousseau 1964, pp. 166-167).
Skyrms (2004) also considers a more contemporary treatment of a similar game situation and considers
the stag hunt as modelling the social contract.
Imagine two hunters, who are faced with a hunting decision, they either choose to hunt for rabbits (during
their hunt their chances of hunting for rabbits are not influenced by the actions of others around them)
or they can choose to hunt for stag. However, since both hunters prefer to have venison for dinner, and if
they were to hunt for stag they will only be successful if the other hunter also agrees to hunt for stag. So,
the options open to them are to hunt for stags or to hunt for rabbits. Figure 5 illustrates the utility matrix
for the different options. We noted earlier that in the PD case, there is a conflict between individual rationality and mutual benefit; in a similar way in the stag hunt example what is rational for one hunter to choose
will depend upon his beliefs about what the other one will choose.
3,3
0,2
2,0
2,2
Figure 5: Illustrating the Example of the Stag Hunt.
Let the two hunters be represented by the numbers 1 and 2 as in the diagram. So, the pair (Stag, Stag) will
represent the utility ranking (3, 3) where both hunters hunt for stag. We note that there are two rational
outcomes to the stag hunt:
1. Either both hunters hunt the stag as a team.
2. Each hunts rabbits by himself.
Each would prefer to cooperate in hunting the stag, but if the other player's motives or actions are uncertain, the rabbit hunt is a risk-free alternative. If they both go for option 1, they have to both cooperate to
hunt and catch the stag. When we solved the PD, we saw that one strategy was better regardless of what
the other player was doing. Let us see if this dominant solution concept works here. If hunter 2 goes for a
stag then hunter 1 should go for a stag as well since 3 > 2. But if hunter 2 is going after rabbits then hunter
1 should hunt rabbits as well since 2 > 0. So, we note that sometimes hunter 1 prefers hunting stag and
other times he prefers hunting rabbits; thus our dominant solution concept is not sufficient for this game
and consequently we must introduce another method for attaining a solution to the game.
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Remembering that conditions for attaining the Nash equilibrium are as follows:
1. A game is said to be in NE when no player has any incentive to deviate from his strategy given the
strategies of all other players.
2. At least one NE exists in all finite games.
In our example let us look at the (stag, stag) outcome, and we note that this is a NE point following the
iterative reasoning developed earlier. Now we note that if we consider (rabbit, rabbit) this too is a NE
because hunter 1 would prefer to hunt for rabbits if the second hunter is hunting for rabbits as well. These
examples illustrate that cooperation in game theoretic modelling is an important aspect to consider as the
evolution of cooperation in such models is an important indicator for determining more than one NE.
We note from our discussion above that EGT can be utilised to explain how cooperation may emerge
amongst rational agents to assist in reaching their aims. Skyrms (1996) and other authors have also shown
that agents with self-interested motives may also develop reasoning frameworks such as the 'Golden Mean'
and versions of Gauthier's 'constrained maximisation' idea under relevant circumstances. These developments tend to support the view that evolution tends to favour the emergence of certain patterns of behaviour that tend to conform to moral norms and also the development of cognitive frameworks that tend to
support characteristics related to moral reasoning.
Most of the authors who have developed the evolutionary approach using game theory point to several
advantages of such an approach compared to the ones we discussed earlier, and these advantages can be
briefly listed as follows:
1. In EGT norms arise as unintended consequences due to repeated actions of the rational agents.
2. There is no consequential connection among the efficiency of outcomes and morality in the evolutionary game theory paradigm. We could therefore say that one advantage with respect to Gauthier's claims for 'constrained maximisation' is that since in EGT the focus is on equilibrium and not
determining efficient situations concerning utility maximisation, the 'function' of moral norms are
to select stable equilibria. So, following the norm is individually rational.
However, there are also several reasons that point us to be more careful concerning the claims and successes relating to the evolutionary approach. As the functionalist approach, the focus of EGT is one explanation to explain the emergence of norms and their stability, but it does not supply us with any kind
of framework to criticise and evaluate these moral norms. It is, therefore, not clear and evident to what
extent such a paradigm offers to us an alternative to the moral theories already available. Another important criticism that has been pointed at the application of EGT to ethical decision making is the idea of the
rational agent; this criticism can be thought of as a general criticism relating to the application of the whole
of game theory to our understanding of ethical norms. A rational agent is a kind of one-dimensional entity
who is supposed to determine preference rankings over possible outcomes. However, differences of character and other psychological variables concerning the agent are not really considered in the application
process. Recent developments in game theory have made efforts to incorporate the notion of the player's
"reputation" to explain the emergence of cooperation in iterated plays of games such as that seen in the
PD case, while further examples of this can be found in Kreps and Wilson (1982).
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CONCLUSION
The aim of this paper has generally been two-fold. First, to provide a concise historical introduction to the
field of game theory leading to the discussion of the Prisoner's Dilemma and the use of pay off matrices.
Secondly, three approaches where the application of game theory to ethical decision making are considered and their criticisms lead us to the development of Evolutionary Game Theory. The functionalist approach presents the argument developed by Ullmann-Margalit that the function of morality is to assist us
in preventing failures of rationality. However, the five examples presented following this discussion show
us that the emergence of norms could be explained by a more evolutionary approach. Careful reasoning
indicates that an evolutionary game theory approach to ethical decision making may provide us with a suitable framework that explains the emergence of norms used to guide agent behaviour during the ethical
decision making process; however, such a frame work does not assist us in formulating an evaluation of
such norms for individual agents.
Despite the successful application of evolutionary game theory to decision making, a critical area that will
require further development is to consider collection of agents forming a group, for example, a board of
directors; in such a case the emergence of norms guiding ethical decision making will depend upon several
different psychological factors concerning not only a single agent but the group of agents in question.
Such differences will need to be incorporated into any kind of evolutionary game theoretic approach when
considering collective ethical decision making.
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PROGRAMMING
LANGUAGE PARADIGMS
& THE MAIN PRINCIPLES
OF OBJECT-ORIENTED
PROGRAMMING
JAN BARTONÍČEK
This paper's goal is to briefly explain the basic theory behind programming languages and their history while taking a close
look at different programming paradigms that are used today as well as describing their differences, benefits, and drawbacks.
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GENERAL DEFINITION OF PROGRAMMING LANGUAGES
Programming language is so-called 'formal' language, created to make communication between the
computer and its programmer easier. The very first computers were programmed using switches and
plugboards, but this concept quickly evolved into software programming. To start with, programmers used
machine code, which was hard to read and debug, and the invention of programming languages came to
make these tasks easier.
Programming language is a set of commands, strings of characters readable by programmers but easily translatable
to machine code; it has syntax, grammar, and semantics. Syntax is a set of rules that define how the commands
have to be arranged to make sense and to be correctly translatable to the machine code. Grammar is a set of
rules of using different punctuation, quotation marks, semicolons, and other symbols to divide and clarify the
syntax of a particular language. The last component of programming language is semantics, a set of meanings
assigned to every command of the language and is used to properly translate the programme to machine code.
Programming languages are often divided into three generations:
The first generation of programming languages were used to directly control the
processor and were written mainly in binary or machine code. It was very hard to
write the programmes and even harder to debug them.
The second generation of languages are also called low-level languages, and they
use symbolic addresses and simple instructions to make programming easier and
faster. These languages have access very close to the hardware itself, and they are
still used to write highly-optimised code for specific hardware.
The third generation of languages use a high level of abstraction, using advanced
commands, variable names, and pointers. These languages are mostly hardware
independent and portable (Nasir, 1996).
BRIEF HISTORY OF PROGRAMMING LANGUAGES
The very first device to be called a computer was the Pascaline, an automatic mechanical calculator invented by Blaise Pascal in the year 1642. It was able to perform addition, but because of its complicated nature,
it did not gain popularity. In 1833, Charles Babbage, a mathematician, devised plans for his "analytical engine", a steam powered machine able to carry out almost any mathematical operation. It was programmed
by exchanging gears in the machine that made it extremely impractical. The design was so advanced that it
was not possible to build it with the level of technology at the time. Ada Augusta King, Countess of Lovelace, called Ada Lovelace for short, was a pioneer in the computing field. She made major enhancements
to the analytical machine, such as subroutines and conditional execution.
The next big advancement in computing came a hundred years later with the publication of Alan Turing's
paper called "On computable numbers, with an application to the Entscheidungsproblem" in the year
1936. In it, Alan Turing proposed a theoretical machine, later named the Universal Turing Machine, which
consisted of a read/write head with memory for holding instructions and an infinite tape comprised of cells
able to hold one symbol each. The head was capable of moving above the tape, read its contents, alter it,
and write new data to the tape. This paper introduced basic concepts of computing and its publication
marks the start of a rapid development in computer technology (Armbruster et al., 2001a).
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Not long after the Turing's paper, the first digital computers started to be constructed. The first one to
be finished was the ENIAC (Electrical Numerical Integrator and Calculator) in the year 1942. It was programmed using switches and plugboards, which was extremely impractical and time-consuming.
Interested in the success of ENIAC, a mathematician working at the Institute of Advanced Study, John von
Neumann, started to work on improving the ideas behind computers, and he introduced ideas that are
now collectively called the "Von Neumann architecture". He stated that computers should be static in their
hardware design and their only part subject to change should be their software, making them much easier
and quicker to reprogramme (Armbruster et al., 2001b).
Another revolutionary woman, Grace Murray Hopper, while working on the UNIVAC, ENIAC's competitor, constructed a first compiler, a machine or later a block of code that was able to translate commands
into machine code. She introduced the first programming language, called Assembly, which used slightly
more readable commands in a three-address machine code ([ADD 00X 00Y 00Z] that would be used to
add together X and Y and assign the output to Z).
The next major step in development of programming languages was the announcement of FORTRAN
(FORmula TRANslation). It was designed by scientists at IBM and featured a revolutionary compiler with
ability to optimise the compiled code. It became the very first successful high-level programming language.
The first programming language that implements Object-oriented principles is Smalltalk released in the
year 1970. In fact, it is purely Object-oriented, which means no data or functions can exist outside of objects (Armbruster et al., 2001c).
One of the widely used languages of today is C++, which was created as an Object-oriented version of C, a
very popular language invented in 1972 for development of the UNIX system. C++ inherited a wide variety
of features from C, including its ability to use low-level commands to create fast and tuned programmes.
Two of the three major languages of today were both released in the year 1991, first one being Java, focusing on object-oriented approach and simplicity of the language, relying on extension libraries. The second
one is called Python and it features a simple and English-like syntax, which makes it easy to use and effective. The last major language is C#, developed as a modernization to the C language. It was made public
in the year 2000 as a part of the Microsoft's .NET Framework project. It is a high-level, multi-paradigm
language focused on the effectiveness of program creation. (Armbruster et al., 2001d)
PROGRAMMING PARADIGMS
By the word paradigm, we understand a set of patterns and practices used to achieve a certain goal. In this
essay, the word 'approach' is used as a synonym to 'paradigm'. For an idea to become a paradigm, it should
be picked up globally in many independent organisations and societies. There are many programming
paradigms in use today, but only the three major paradigms are in this essay's discussion.
PROCEDURAL PARADIGM
Procedural paradigm is the approach to programming that was used from the beginning of computing. In
this paradigm, the programme comprises of a list of instructions for the computer to execute in the order
in which they were written, unless stated otherwise. It is a simple approach, and tends to be easily readable
when the programme is reasonably short. Larger programmes written with a procedural paradigm in mind
can be very hard to read, manage, and debug. Most procedural languages have flow control structures, IF
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statements used to branch the code execution, FOR and WHILE for repeated execution, and GOTO for
'jumping' between lines of code.
When talking about a procedural paradigm, we cannot forget to mention its subset, called a structural paradigm which omits the GOTO command, meaning that the execution of the programme has to go through
the entire programme without skipping any commands.
Programming languages based on procedural approach includes most of the early languages like Assembly,
FORTRAN, and some more recent languages, for example, C and PHP.
Following is an example of procedural implementation of factorial function in pseudo-code, an English-like
code used for language agnostic representation of programmes:
START
Initialize n, f = 1
Read n from the user
For i between 1 and n do:
f = f *i
Return f
END
FUNCTIONAL PARADIGM
Functional paradigm is fundamentally different from the procedural paradigm in the way programmers
develop their programmes. As opposed to the procedural approach, in which the programmers define the
way the programme functions, in the functional approach, the programmer defines the desired outcome
and cannot define the way the functions are executed. Functional programming relies on the concept of
λ-calculus (lambda-calculus), which defines a way to convert any computable (as defined in Turing's paper
"On computable numbers") function to a mathematical function expressible in functional languages. The
most important functional programming language is LISP (LISt Processing). Some more examples of functional languages are Scheme (a dialect of LISP), Haskell, and Mathematica.
The following is an example of functional implementation of a sum function in Haskell (Computerphile, 2013):
sum :: [int] --> int
sum [n] = n
sum(n, ns) = n + sum ns
OBJECT-ORIENTED PARADIGM
The Object-oriented paradigm was developed by Alan Kay while he was working on Smalltalk. It was developed to make large projects easier to manage and share the workload among coworkers and is simplified
thanks to the modularity of objects.
The main focus of the Object-oriented paradigm is an object. Object is a way of grouping data structures
and functions that can be carried out on the data, which are called methods (Oracle, 2013a). Using the
proper typing of the data and methods, the programmer can achieve a high level of encapsulation. For
further description of object, see the graphic below.
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Object-oriented programming is based on four main concepts:
THE CONCEPT OF CLASS
Class is a template from which objects are created. It contains the description of all the data structures
and all methods of the resulting objects. Most classes have their constructors, methods, which initialise
the created objects' variables depending on the data given.
THE CONCEPT OF INHERITANCE
Inheritance is the ability of classes to inherit data structures and methods from other classes (Oracle,
2013b). For example, we can imagine a parent class vehicle and its child classes: Car, Bicycle, and Motorcycle. For further description of inheritance, see the graphic below:
Class Vehicle
method Drive(), method Steer(), method Brake()
variable numberOfWheels
Class Car,
inherits Vehicle
Class Bicycle,
inherits Vehicle
Class Motorcycle,
inherits Vehicle
numberOfWheels = 4
numberOfWheels = 2
numberOfWheels = 2
method AddFuel(),
method
ChangeGear()
method Pedal(),
method
ChangeGear()
method
ThrottleUp(),
method
ChangeGear()
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An object created from the class Bicycle shown in the graphic will have not only the methods and variables
declared in the Bicycle class, but all the methods and variables inherited from the Vehicle class. The complete class Bicycle without the use of inheritance is shown in the graphic below.
Class Bicycle
method Drive(), method Steer(), method Brake(), method Pedal(),
method ChangeGear()
variable numberOfWheels = 2
THE CONCEPT OF ENCAPSULATION
Encapsulation is a property of a well-written object. The programming language provides the programmer with tools to prevent other objects or programmes to access the data held within the object directly,
allowing him to specify the ways the data can be manipulated using public methods, which are used to
validate input data before storing it.
Closely related to encapsulation is the notion of modularity. Modularity of objects, the isolation of the
working code from the outside world, is used to make larger programs easier to develop and manage.
The programmer does not need to understand how a certain object works, he only needs to know which
methods to use for accomplishing his goals. For example, the programmer does not understand how the
engine of a Motorcycle from the previous example works, but he knows that he needs to call the method
ThrottleUp() in order to increase the speed.
THE CONCEPT OF POLYMORPHISM
Polymorphism is the ability of objects to process multiple data types in the same object. This ability is based
on one of the notions used in most programming paradigms called function overloading, which allows the
programmer to specify different functions under the same name, whose execution will be dependent only
on the data type of a given argument. For example, the programmer would write two different functions
under the name Print() for outputting information to the screen. First one would be defined as Print(int
input) and it would handle printing integers and the second one would be defined as Print(string input) and
it would handle printing strings of characters. This allows the programmer to use the function Print() to
print integers and strings of characters instead of using two different functions PrintInt() and PrintString().
OBJECT-ORIENTED LANGUAGES
The first programming language to implement features of the Object-oriented paradigm was Smalltalk.
One of the main contributors to its development, Alan Kay, is the creator of the Object-oriented paradigm.
It was released in the year 1970. It is purely object based, which means that no data or methods can exist
outside of an object. The next programming language focused on the Object-oriented paradigm was a set
of extensions for C collectively called 'C with Classes', which later led to the development of one of the
most influential Object-oriented language of today, C++.
Another well-known Object-oriented language is Java, widely used today for creation of programmes ranging from servlets for interactive websites to mobile and computer games. It focuses on cross-platform
compatibility using Java Virtual Machine to run the same code on a wide range of different types and
architectures of hardware. Although practical for portability, this approach makes Java programmes less
effective in resource usage and slower than other programming languages.
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CONCLUSION
Although it is not without its quirks, the Object-Oriented paradigm is the most frequently used paradigm
of today. It owes its popularity to the simplicity of large project management using object modularity and
encapsulation. Every programming paradigm has its own advantages and disadvantages for many usage
scenarios and that is why most of the currently used programming languages support multi-paradigm approach, which allows the programmer to choose the best development practice for his specific needs.
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(Accessed: 10 October 2013).
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html (Accessed: 10 October 2013).
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EDITORIAL IMAGES
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(Accessed: 29 July 2014).
PAGE 3 (TOP LEFT) & PAGE 32: macfromlondon/123RF.COM (2014) Stock Photo - LONDON, UK - 1ST MARCH
2014 The outside of a McDonalds Store during the day in central London. [Online]. Available at: http://www.123rf.com/
photo_26359889_london-uk--1st-march-2014-the-outside-of-a-mcdonalds-store-during-the-day-in-central-london.html
(Accessed: 25 July 2014).
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illustration of game theory strategy [Online]. Available at: http://www.123rf.com/photo_10287741_backgroundconcept-wordcloud-illustration-of-game-theory-strategy.html (Accessed: 29 July 2014).
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[Online]. Available at: http://www.123rf.com/photo_10012041_background-concept-wordcloud-illustration-ofsource-code-programming.html (Accessed: 29 July 2014).
100
CRIS Bulletin 2014/01
PRAGUE COLLEGE
Polská 10
120 00 — Prague 2, Vinohrady
Czech Republic
Tel.: (+420) 222 101 020
(+420) 222 722 544
Fax: (+420) 222 718 813
www.praguecollege.cz
[email protected]
ISSN 1805-5109
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