Zdzisław Kosztołowicz
University in Kielce
Poland
Personality
and salaries
It is known
that the globalization notion [Druckner 1985, 1997, Gwiazda 2000, Huntington
1991, 1993, 1995, 1999, Sala 2003a, 2004, 2005a, 2005b, 2007a , Robertson 1992,
1995, Szymański 2001,] has been explored and investigated at many areas
such as economy, geography, sociology, psychology, political sciences etc
[Barber 1998, 2001, Domański 2001, 2004, Gierańczyk, Stańczyk
2003, Jarczewska-Romaniuk 2004, Kisiel-Łowczyc 2000, Kośmicki 2001,
Rembowska 2001, Sala 2003b, 2006a, 2006b, 2006c, 2007b, Zorska 2000, 2001a,
2001b, 2002a 2002b, Yang, 1995, Stiglitz 2004].
But undoubtedly, the main axiom can be formulated as follows:
All globalization processes are made by people
and for people.
According to that we assume that every change
in human life is valued by its psychological structure [Reykowski 1971].
Especially these processes, which have influenced on the material status of
every human. For simplicity, we take into consideration that this status is
equivalent to the people salaries.
In this
paper we investigate, on some examples, how we can predict which human factors
react on salaries which people earn.
This
investigation is based on the method of a statistical reduction. Before further
considerations we give a brief description of this method [Bryll1995]. In order
to present that one, let us consider n-element system of different elements
occurring on a certain background (called region or population map). In this
method a given n-elementary population is replaced by another one with a
smaller number of elements, say N. At the same time a reduction population to a
definite level is carried out. The region K, where the n-elements are arranged
is divided into k elementary areas called elementary layers. These layers are
grouped into so called fundamentally layers (areas) . Each of these fundamental
layer contains the same number of elementary areas (namely u). It is assumed
that k is divisible by u. It is obvious that the whole region comprehends 
fundamental areas.
Thus, the arrangement of n-elements population in the whole region K can be
characterized by comparing the arrangement in various fundamental and
elementary areas. In order to this we introduce the function 
, which is defined as the ratio of the number of fundamental
areas containing m1 elements in the first elementary area, m2
elements in the second elementary area, …, mu in the u-th elementary
area to the number of all fundamental areas. This function is determined by
counting directly the elements of the population in particular fundamental
layers and, in fact, it gives a full description of arrangement on elementary
and fundamental areas. The arrangement defined by function is compared with the
formula which express random arrangement, i.e. the arrangement such that the
probability of hitting a given elementary area by a given element is the same
for all elements and all elementary areas. So the probability 
of hitting one
elementary layer by m elements is defined by the formula:
.
Let 
be a probability that
in one fundamental area there are 
elements, in such a
way, that i-th elementary layer of given fundamental area contains mi
elements for i=1 to u. This probability can be calculated as follows:
where 
.
By a
reduction of an n-elements population (n>2) to a level N, where N<n, we
mean a random selection of n-N elements of this population. The probability 
of the event that,
after removing n-N elements from n elements, the given fundamental area, which
consists of elementary areas containing (before removing) mi
elements in i-th elementary area for i=1 to u, turns into a fundamental layer
containing Mi elements in i-th elementary areas for i=1 to u, is
equal 
where 
.
Summing up
along all fundamental areas containing more than Mi elements in i-th
elementary area for i=1 to u, we get:
(1) 
.
The above
formula expresses the probability of the event that after removing n-N elements
from the region K, we get the fundamental area, which contains in the i-th
elementary area Mi elements for i=1 to u.
It is shown
[Garncarek 1987] that the random arrangement of an n-elements of the population
reduced to a level N is identical with the random arrangement of an N-elements
population. This theorem enables us to compare of arrangements of population of
distinct cardinalities, by comparison the random arrangement with the
arrangements of the populations reduced to, in our case, level 2.
Let us
assume that u=2 i.e. every fundamental area contains exactly 2 elementary
areas.
In this
case, the algorithm of the count is very simple and indicators, referred in
this paper, are only two. First indicator is the concentration coefficient c
(2) 
,
the second
indicator is the grouping coefficient
(3) 
, where 
k is the
number of all elementary areas and 
is a probability of finding fundamentally areas such that it
contains mi elements in i elementary area on the population map
[Zięba1975].
The sums
made in above formulae should be read:
-
in
the first formula we take into account only these fundamental areas such that
first and the second elementary area contains at least one element,
-
in
the second (third) case we take these fundamental areas, where the second (the
first) elementary area contains at least two elements.
This
indicators came from the comparison the
arrangement of reduced population to level 2 and random arrangement.
Interpretations
for both indicators are similar:
if
concentration coefficient (grouping coefficient) is more than 1 then
coexistence elements in elementary area (fundamental area) is not accidental,
if
concentration coefficient (grouping coefficient) is equal to 1 then coexistence
elements in elementary area (fundamental area) is accidental,
if
concentration coefficient (grouping coefficient) is less than 1 then
coexistence elements in elementary area (fundamental area) does not occur.
To the end
we get the concentrations on population map and information about their
essentiality.
On the
other hand, we have to give a method of constructing, for any data, a
population map. Based on [Kosztołowicz 1999] and [Kosztołowicz 1993]
we recall the following procedure.
Assume that
we have a set of data value {xi; i=1 to n}. Each value is
standardized by the formula:
(4) 
, where 
is a mean value and s
is a standard deviation, which are calculated in the following way:
and 
.
Then we convert
standardized data into T1 scale by formula
(5) yi=10×zi+50, where
10 and 50
are standard deviation and mean value at T1 scale respectively
[Kosztołowicz 1999].
These
results (calculated inT1 scale) we divide into classes with respect
to the rule [Ksztołowicz 1999, Kosztołowicz 1993]:
The
subtraction between maximal and minimal results is divided by a natural number
(the length of the class), such that the number of classes is no less than 10
and no more than 20.
The lowest
result in T1 scale makes the bottom closed class, expressed by a
natural number. We obtain the top open class when we add e.g. 5 units of the T1
scale to the bottom one. The classes determine elementary layers.
Next, we
join two adjacent elementary areas along the results of increasing classes,
assigning to a lower result 1, to a higher 2, that is we form a pair (1,2).
These are fundamental areas.
Consequently,
by putting the results in appropriate elementary fields being included in
fundamental areas, we obtain the relational map.
In this paper, salaries, which are taken into
account, are published by Chief Central Statistical Office (GUS, Poland) in
“Employment and salaries in National Economy in 2002” and introduced in table
1.
Data giving
in table 1 are converted to T1 scale by formula (5)
where zi
standardized data of i-th factor for i=1 to 5 in giving province,
These
results (calculated inT1 scale) we divide into classes with respect
to the procedure of constructing the population map.
Put these
classes on one side of the rectangular (elementary classes length equal to 5,
fundamental classes length equal to 10) (table 2) and the classes of global
value on the other side. Global value is
equal the sum of all factors value for every province. The relational map
salaries (table 2) for all factors is a basic tool for our considerations.
Using the
formula ( ) we get c=1,08.
Coefficient
c informs us that agents coexistence in elementary areas is accidental. If
c>1 then the coexistence is not accidental. In our case c»1, so the coexistence is accidental.
How do
people value his salaries?
To answer
this question is needed to recall the notion of personality structure. Among
many conceptions of personality we recall the concept of J. Reykowski
[Reykowski 1971].
This
concept assumes that man is equipped with certain group of psychological
features that are related to each other and they constitute the starting point
for establishing the relation of an individual and the environment.
One of the
famous psychologists R. B. Cattell explored this notion and he distinguished 16
psychological factors [Cattell 1957, Cattell 1961, Cattell 1966]. Table 3
contains these factors description [Sanocki 1978]. Factors, which are related
to each other, construct layers (one or more). These layers are based on
personality structure. In [Kosztołowicz 1999, Kosztołowicz 2004] is
presented a method of a constructing map. This map contains 16 factors, which
create layers on this map.
In order to
establish the psychological layer we introduce a following procedure
[Kosztołowicz 1999, Kosztołowicz 2004]:
-
A
group is examined Cattell’s 16 factors personality questionnaire. In this
questionnaire every item is associated with personal agent. Every member of
this group is assigned the number of scored points for every personality factor
(empirical results).
-
Empirical
results are converted to T1 scale.
-
The
map of personality agents is made in the following manner:
in interval we place the scores in T1
scale, starting from the smallest one to the biggest and at every 5 units we
place the areas where the scores drop into.
-
There
will be layers created (factors dropping into area of the length of 5).
Essentiality
of co-occurrence is investigated by concentration coefficient c and grouping
coefficient.
Let us
recall one example of such a constructed map. For details see
[Kosztołowicz1999].
We take
into account two people living in Świętokrzyskie province, working at
administration in offices of the
government administration. These people results are presented in table 4.
Table 4
|
Nb.
|
Personal
agent
|
A
|
B
|
C
|
E
|
F
|
G
|
H
|
I
|
L
|
M
|
N
|
O
|
Q1
|
Q2
|
Q3
|
Q4
|
|
1
|
Empirical results
|
13
|
11
|
21
|
20
|
24
|
18
|
18
|
14
|
14
|
20
|
14
|
13
|
18
|
8
|
17
|
24
|
|
Converted
To T1 scale
|
39,5
|
57,5
|
57
|
59,5
|
78,6
|
43,1
|
60,9
|
44,2
|
49,7
|
63,4
|
53,8
|
43,8
|
60,3
|
28,1
|
40,1
|
62,9
|
|
2
|
Empirical results
|
18
|
10
|
18
|
13
|
16
|
14
|
9
|
22
|
12
|
12
|
10
|
22
|
7
|
20
|
20
|
12
|
|
Converted
To T1 scale
|
52
|
51,6
|
50,8
|
42,5
|
51,7
|
33,4
|
43,3
|
69,4
|
43,1
|
41,7
|
42,3
|
57,4
|
20,8
|
63,2
|
47,9
|
34,9
|
According
to the upper procedure, we construct relational map in order to determinate
layers
Table 5
Person nb.
1 and 2 relational map
|
Classes
|
Classes interval
|
Personal agents nb. 1
|
Personal agents nb. 2
|
Elementary areas
|
|
20
|
[95,100)
|
|
|
2
|
|
19
|
[90,95)
|
|
|
1
|
|
18
|
[85,90)
|
|
|
2
|
|
17
|
[80,85)
|
|
|
1
|
|
16
|
[75,80)
|
F
|
|
2
|
|
15
|
[70,75)
|
|
|
1
|
|
14
|
[65,70)
|
|
I
|
2
|
|
13
|
[60,65)
|
H,M,Q1,Q4
|
Q2,
|
1
|
|
12
|
[55,60)
|
B,C,E,
|
O
|
2
|
|
11
|
[50,55)
|
N
|
A,B,C,F
|
1
|
|
10
|
[45,50)
|
|
Q3,
|
2
|
|
9
|
[40,45)
|
G,I,L,O,Q3
|
E,H,L,M,N,
|
1
|
|
8
|
[35,40)
|
A,
|
|
2
|
|
7
|
[30,35)
|
|
G,Q4
|
1
|
|
6
|
[25,30)
|
Q2
|
|
2
|
|
5
|
[20,25)
|
|
Q1
|
1
|
|
4
|
[15,20)
|
|
|
2
|
|
3
|
[10,15)
|
|
|
1
|
|
2
|
[5,10)
|
|
|
2
|
|
1
|
[0,5)
|
|
|
1
|
Based on
tables 5 and 3 we create personal characteristic giving people. We give such
characteristic for person number 1.
Characteristic
Rationalism
can tone down emotionality, sociality and irritability, reactivity. Taking this
statement into consideration we can say that high intelligence, courage and
self-confidence is connected with the lack of hypochondria. The lack of
sensibility in reaching the goal with the trust of our own abilities can be
also appeared.
Similarly,
we can describe man nb.2.
We can
characterize this person as inteligent, independent, calm, emotionally stable,
mature, caring, cooperative,
friendly, enthusiastic and warm. This layer can be disturbed by self-doubting,
apprehensivness and guilt-proning. Consequently he becomes submissive,
unsteady, socially timid, threat-sensitive, escaping from uncertain situations,
transparent.
In order to find out which personality factors
react on salaries we compare table 5 to 2.
Table 6
Comparison
- table 2 to table 5
|
Classes
|
Classes interval
|
Personal agents nb. 1
|
Personal agents nb. 2
|
Salary
|
|
20
|
[95,100)
|
|
|
|
|
19
|
[90,95)
|
|
|
|
|
18
|
[85,90)
|
|
|
|
|
17
|
[80,85)
|
|
|
|
|
16
|
[75,80)
|
F
|
|
|
|
15
|
[70,75)
|
|
|
|
|
14
|
[65,70)
|
|
I
|
|
|
13
|
[60,65)
|
H,M,Q1,Q4
|
Q2,
|
|
|
12
|
[55,60)
|
B,C,E,
|
O
|
|
|
11
|
[50,55)
|
N
|
A,B,C,F
|
|
|
10
|
[45,50)
|
|
Q3,
|
|
|
9
|
[40,45)
|
G,I,L,O,Q3
|
E,H,L,M,N,
|
1SW
|
|
8
|
[35,40)
|
A,
|
|
|
|
7
|
[30,35)
|
|
G,Q4
|
|
|
6
|
[25,30)
|
Q2
|
|
|
|
5
|
[20,25)
|
|
Q1
|
|
|
4
|
[15,20)
|
|
|
|
|
3
|
[10,15)
|
|
|
|
|
2
|
[5,10)
|
|
|
|
|
1
|
[0,5)
|
|
|
|
From the
comparison we get:
-
for
person number 1 the personal agents G, I, L, O, Q3 react on his
salaries,
It means
that his salaries are in relation with realism, practice, responsibility,
trust, open-mindness, gentleness which can be disturbed by weak will,
irresponsibility, dependance, mood and lack of perseverance,
-
for
person number 2 the personal agents E,H, L, M, N react on his salaries i.e.
It means
that his salaries are in relation with submissive, unsteady, socially timid,
threat-sensitive, escaping from uncertain situations, transparent,
self-doubting, apprehensivness and guilt-proning.
To sum up:
- it is predictable, which layer
is activated in connexion with salaries,
- the same salaries can
reactivate different layers different people.
Thanks to
that we can in a better way motivate people and predict people behaviour by
reason of its salaries.
Table 3
The 16
personality factors Questionnaire. Description of personality agents.
Low result
– in T1 scale result less then 50.
High result
– in T1 scale more or equal then 50.
|
Factor
|
Low result
|
High result
|
|
Warmth (A)
|
Reserved, impersonal, distant, formal
|
Warm, caring, soft-hearted and generous
|
|
Reasoning (B)
|
They are less able to solve verbal and
numerical problems of an academic nature
|
They are more able to solve verbal and
numerical problems of an academic nature
|
|
Emotional stability (C)
|
Reactive, easily upset, temperamental
|
Calm, stable, mature, unruffled
|
|
Dominance (E)
|
Deferential, modest, submissive
|
Assertive, forceful, competitive
|
|
Liveliness (F)
|
Serious, quiet, reflective
|
Carefree, enthusiastic, spontaneous,
energetic
|
|
Rule-Consciousness (G)
|
Expedient, non-conforming
|
Rule-conscious, dutiful
|
|
Social Boldness (H)
|
Shy, socially timid, threat-sensitive, easily
embarrassed
|
Socially bold, outgoing, gregarious,
adventuresome
|
|
Sensitivity (I)
|
Tough, realistic, logical, unsentimental
|
Emotionally sensitive, intuitive, cultured,
sentimental
|
|
Vigilance (L)
|
Trusting, unsuspecting, forgiving, accepting
|
Vigilant, suspicious, distrustful, wary
|
|
Abstractedness (M)
|
Grounded, practical, concrete
|
Abstracted, imaginative, idea oriented,
contemplative
|
|
Privateness (N)
|
Forthright, self-revealing, transparent
|
Private, discreet, non-disclosing
|
|
Apprehension (O)
|
Self-assured, unworried, complacent
|
Apprehensive, self-doubting, guilt-prone
|
|
Openness to Change (Q1)
|
Traditional, attached to familiar, resistant
to change
|
Open to change, experimenting, freethinking
|
|
Self-Reliance (Q2)
|
Group-oriented, affiliative
|
Self-reliant, solitary, individualistic
|
|
Perfectionism (Q3)
|
Tolerates disorder, unexacting, casual, lax
|
Perfectionistic, self-disciplined,
goal-oriented
|
|
Tension (Q4)
|
Relaxed, placid, tranquil, patient
|
Tense, driven, high energy, impatient
|
Bibliography
1.
Barber B., 1998, W mackach
McŚwiata, Gazeta Wyborcza, 14-15.03.
2.
Barber B., 2001, Dżihad
kontra McŚwiat, Warszawskie Wydawnictwo Literackie MUZA S.A., Warszawa.
3.
Bryll
G., J. Boss; An assessment of the state of grain mixture with the use of the
method of statistical reduction; Chemical Engineering Science, vol.50, no. 7,
pp. 1173-1179, 1995
4. Cattell R. B.; 1957, Personality and
motivation. Structure and measurement; New York, World Book Co., 1957,
5. Cattell R. B.;1961, Theory of situational instrument, second
order and refraction factors in personality structure research; Psychological
Bulletin, 58, p.160-174,
6. Cattell R. B.;1966, The scree test for the number of factors;
Multivariate Beh. Res. 1, p.140-161,
7.
Domański B., 2001,
Kapitał Zagraniczny w przemyśle Polski, Instytut Geografii I
Gospodarki Przestrzennej UJ, Kraków. (in polish).
8.
Domański R., Nowe kierunki
badawcze w regionalistyce. Nowe doświadczenia polityki regionalnej,
Biuletyn KPZK PAN, z 204. (in polish).
9.
Druckner P. F., 1985,
Odejście od cyklu depresji, Życie Gospodarcze, 8, z dnia 24.02. (in
polish).
10. Druckner P. F., 1997, The Global
Economy and the National-State, Foreign
Affairs, vol. 75 no 5.
11. Fukuyama F., 1992, The End of
History and the Last Man, The Free Press, New York.
12.
Z.
Garncarek; Formalizm matematyczny metody redukcji statystycznej (Mathematical
formalism of the method of statisitical reduction); Zeszyty Naukowe WSP Opole,
Ser. Mat. 25 pp.39-52, 1987,
13. Barber B., 1998, W mackach McŚwiata, Gazeta Wyborcza, 14-15.03.
14. Giddens A., 1997, Anthony Giddens on
Globalization. UNRIST News, no 15.
15. Giddens A., 2000, Runway World. How
Globalization Is Reshaping our Lives, Routledge, New York.
16.
Gierańczyk W., Stańczyk
A., 2003, Korporacje międzynarodowe w przestrzeni globalnej, Prace Komisji
Geografii Przemysłu Polskiego Towarzystwa Geograficznego nr 5. (in
polish).
17. Gwiazda A., 2000, Globalizacja i regionalizacja gospodarki
światowej, Wydawnictwo Adam Marszałek, Toruń. (in polish).
18. Huntington S. P., 1991, The Third
Wave. Democratization in the Late Twentieth Century, University of Oklahoma
Press, Norman-London.
19. Huntington S. P., 1993,
The Clash of Civilizations, in: Foreign Affairs , vol. 72, no 3.
20. Huntington S. P., 1995, Trzecia fala demokracji,
Warszawa. (in polish).
21. Huntington S. P., 1997, Zderzenie cywilizacji i
nowy kształt ładu światowego, Warszawa. (in
polish).
22.
Jarczewska- Romaniuk A., 2004,
Przedsiębiorstwa Międzynarodowe, Oficyna Wydawnicza BRANTA,
Bydgoszcz- Warszawa. (in polish).
23. Kisiel-Łowczyc A. B., 2000, Współczesna gospodarka
światowa, Wydawnictwo Uniwersytetu Gdanskiego, Gdańsk. (in polish)..
25. Kosztołowicz M., Kosztołowicz T., Suchańska M.; 1999,
Metoda redukcji statystycznej w badaniu struktur osobowościowych
uczniów; WSP Kielce (materiały z ogólnopolskiej konferencji
nt. Pomiar w kształceniu i samokształceniu), p.161-175, (in polish)
26. Kosztołowicz M., Szerla
M.;2004, Evaluation of postoperative
pain with the statistic reduction method; University of Computer
Telecommunications in Kielce, p.
201-206, Kosztołowicz M.;1993, Pojęcie aksjomatu w dydaktyce na
przykładzie aksjomatu dydaktycznego Kerschensteinera; w:
Teraźniejszość i przyszłość badań
pedagogicznych na tle zmian w edukacji; WSP Kielce, (in polish)
27. Reykowski J.; 1971, O
niektórych integracyjnych I regulacyjnych funkcjach osobowości;
Psychologia wychowawcza, nr 3, (in
polish),
28. Robertson R., 1992, Globalization:
Social Theory and Global Culture, London, p. 396.
29. Robertson R., 1995, Glocalization:
tim-space and homogeneity- heterogeneity, in: Featherstone M. (red), Global
Modernities, Sage Publication.
30. Rembowska K., 2001,
Kulturowa płaszczyzna interpretacyjna geografii społeczno-
ekonomicznej w: w: Rogacki H. (red.), Koncepcje teoretyczne i metody badań
geografii społeczno- ekonomicznej i gospodarki przestrzennej, Bogucki
Wydawnictwo Naukowe, Poznań. (in polish).
31. Sala S., 2003,
Przemiany strukturalne polskiego rolnictwa w obliczu integracji europejskiej,
w: Czudec A. [red.] Regionalne uwarunkowania ekonomicznego rozwoju rolnictwa i
obszarów wiejskich, UR, Rzeszów 2003, s. 328 – 338. (in polish).
33. Sala S., 2004, Rozwój i znaczenie korporacji
transnarodowych w gospodarce światowej, w: Pierwsza Ogólnopolska Metodyczna Konferencja
Naukowa nt. "Przedsiębiorczość a współczesne
wyzwania cywilizacyjne", Kraków 27 – 28 wrzesień 2004r.
(in polish).
36. Sala S., 2006, Polskie firmy na tle zagranicznych korporacji w dobie
globalizacji, w: Z. Zioło i T. Rachwał [red.], Efekty restrukturyzacji polskiej przestrzeni
przemysłowej, Prace Komisji Geografii Przemysłu PTG Nr 9,
Komisja Geografii Przemysłu PTG i Zakład Przedsiębiorczości
i Gospodarki Przestrzennej Instytutu Geografii AP w Krakowie, Warszawa –
Kraków, s. 170-180. (in polish).
37. Sala S., 2006, Procesy globalizacji a obszary metropolitalne, w:
Makieła Z. Fedan R. [red.] Rzeszowski i Krakowski obszar metropolitalny,
Kraków, s.27-42, (in polish).
38. Sala S., 2006, Transnational corporations.
Theirs development and role in global economy, Theoretical and metodological
problems of human geography, Lviv Ivan
Franko National University Publishing Center, Lviv.
39.
Sala S., 2007 Wpływ
procesów globalizacji na państwo [w:] Kiniorska I., Sala S. (red.) 2007: Rola geografii
społeczno-ekonomicznej w badaniach regionalnych, Nauki geograficzne w
badaniach regionalnych, tom III, IG AŚ Kielce, Oddział Kielecki PTG,
Kielce, s. 167-176. (in polish).
40. Sala S., 2007, Proces of
globalisation and them consequences, w: E.M.Hectepob [red.] Geology and
civilization, V International Conference Geology at School and University,
Sankt-Petersburg, s. 16-18,
41. Sanocki W.; 1978,
Kwestionariusze osobowości w psychologii; PWN Warszawa, (in polish),
42. Szymański W., 2001, Globalizacja, wyzwania i zagrożenia,
Wydawnictwo Difin, Warszawa. (in polish).
43.
Stiglitz J.,
2004, Globalizacja, Wydawnictwa Naukowe PWN, Warszawa. (in
polish).
44. Yang X., 1995, Globalization of the
Automobile Industry: the United States, Japan and the People’s Republic of
China. Praeger Publishers, Westport, p. 2.
45. Zięba A., 1975, Badanie
rozmieszczenia populacji; Zeszyty Naukowe
WSP w Opolu, Matematyka XVIII,
(in polish).
46. Zorska A., 2000, Ku globalizacji?, Przemiany w korporacjach
transnarodowych i w gospodarce światowej, Państwowe Wydawnictwo
Naukowe, Warszawa. (in polish).
47. Zorska A., 2001a, Globalization and
Regionalization. The Impact of TNCs on Integration of Central Europe, in: Bunz
H., Kukliński A (red), Globalization. Experiences and Prospects, Friedrich
Ebert Sfiftung, Warsaw. (in polish).
48. Zorska A., 2001b, Poland and
Globalization: from an Edge to the Core, in: Poland International Economic
Report, WSE, Warsaw. (in polish).
49.
Zorska A., 2002, Korporacje
międzynarodowe w Polsce, Wydawnictwo Difin, Warszawa. (in polish).
50.
Zorska A.(red.), 2002b, Korporacje
międzynarodowe w Polsce, Wydawnictwo Difin, Warszawa. (in polish).
