HR Management in Transition_HU_Eastern Europe 2011

HRM in Transition
in MNC-Subsidiaries in Hungary and Eastern Europe
2009-2010

(Interim Research report)

Budapest

12 May 2011

CONTENTS
1 Introduction – summarizing conclusions 2
2 Research model and explanations 3
Section A: Subsidiaries analyzed by individual countries, total sample, and total sample without
Hungary 5
3 Characteristics of the companies participating in the survey 5
3.1 Company size and legal form 5
3.1.1 Total number of employees 5
3.1.2 Revenue 6
3.2 Mandate of the organization 10
3.3 Origin of the parent company 11
3.4 Year and form of establishment of the subsidiaries 15
3.5 Field of operation: sector-industry 17
3.6 Main directions of development of the companies in the period examined 18
3.6.1 Main strategic issues-orientations 19
3.6.2 Main competitive factors in the period examined 21
4 CHARACTERISTICS OF THE KEY INDICATORS OF THE HR FUNCTION 23
4.1 Number of HR staff 23
4.2 The main indicators representing the importance and results of the HR activity 28
4.2.1 Labor cost – operating cost ratio 28
4.2.2 Age distribution of the employees 30
4.2.3 Relative weight of the training budget 32
4.2.4 Level of fluctuation 34
4.2.5 Time lost due to absence/sickness 36
5 Foreign expats and their roles 39
5.1 Local expats 42
6 The operation of the HR department 44
6.1 The relationship between headquarters and local HR 44
6.2 Changes in the importance of HR functions 46
6.3 Typical HR competencies for success 46
6.4 Primary responsibility of decision making in the main functions of HR 48
6.5 The role of external HR service providers 51
7 Knowledge management in HR 55
7.1 Personal competency development in HR 55
7.2 Enablers of HR knowledge flows between the parent company and the subsidiaries 56
7.3 HR knowledge transfer between the parent company and the subsidiary 56
8 The future tasks of HR 58
8.1 The key business issues, trends for HR to face 58
8.2 Initiatives to improve the business focus of HR professionals 59
9 Characteristics of the responding individuals 61
9.1 Demographic characteristics and qualification 61
9.2 Position of the respondents 63

Section B: Subsidiaries organized into Hungary and in eastern europe and split by ownership 65
10 Characteristics of the companies participating in the survey 65
10.1 Company size and legal form 65
10.1.1 Total number of employees 65
10.1.2 Revenue 67
10.2 Mandate of the organization 71
10.3 Year and form of establishment of the subsidiaries 72
10.4 Field of operation: sector-industry 75
10.5 Main directions of development of the companies in the period examined 76
10.5.1 Main strategic issues-orientations 77
10.5.2 Main competitive factors in the period examined 79
11 CHARACTERISTICS OF THE KEY INDICATORS OF THE HR FUNCTION 81
11.1 Number of HR staff 81
11.2 The main indicators representing the importance and results of the HR activity 85
11.2.1 Labor cost – operating cost ratio 85
11.2.2 Age distribution of the employees 87
11.2.3 Relative weight of the training budget 88
11.2.4 Level of fluctuation 90
11.2.5 Time lost due to absence/sickness 92
12 Foreign expats and their roles 95
12.1 Local expats 98
13 The operation of the HR department 101
13.1 The relationship between headquarters and local HR 101
13.2 Changes in the importance of HR functions 102
13.3 Typical HR competencies for success 103
13.4 Primary responsibility of decision making in the main functions of HR 105
13.5 The role of external HR service providers 109
14 Knowledge management in HR 113
14.1 Personal competency development in HR 113
14.2 Enablers of HR knowledge flows between the parent company and the subsidiaries 114
14.3 HR knowledge transfer between the parent company and the subsidiary 114
15 The future tasks of HR 116
15.1 The key business issues, trends for HR to face 116
15.2 Initiatives to improve the business focus of HR professionals 118
16 Characteristics of the responding individuals 120
16.1 Demographic characteristics and qualification 120
16.2 Position of the respondents 123

1 INTRODUCTION – SUMMARIZING CONCLUSIONS
In the research project we examined the HR functions and practical applications of Multinational
Company (MNC) subsidiaries in Hungary. The current research is part of a long-term research
cooperation – the Central and Eastern European International Research Team (hereinafter CEEIRT) –
that is composed of researchers from different universities from the Central and Eastern European
(CEE) Region and aimed at examining the changing HR practices and roles in MNC subsidiaries. We
seek to understand what trends have emerged in the certain HR practical applications and roles in our
area in response to the socio-economic changes in the region and in Hungary.
In the pages that follow we summarize the relevant findings in connection with the eight most important
topics of the survey. We undertake this analysis first (Section A) by analyzing the findings by country,
total sample and total sample without the Hungarian results. Second (Section B) the analysis are
reorganized into two samples – Hungary and Eastern Europe – which have been subdivided into
American and Canadian firms, German firms, and Other firms and our findings are then based on these
6 groups.

2 RESEARCH MODEL AND EXPLANATIONS
The majority of companies in the competitive sphere in Central and Eastern European (CEE) economies
have largely completed those major legal, strategic and structural modifications that followed
privatization. They have more or less left the reconstruction of the different company functions behind.
With the intensification of competition continuous renewal is now being emphasized. In this situation, the
role of human resources becomes particularly important in the private and public sector of these
countries. There is a deficit in the HRM (Human Resource Management) literature when it comes to
identifying new patterns of Multinational Company (hereafter MNC) involvement and its impact on the
HR/HRM activities of these firms.
HRM includes the following functions:
HR Planning + Recruitment and Selection + Performance Evaluation + Training and
Development + Talent Management + Compensation and Benefits + Industrial and Labour
Relations + Employee Communication+HRMS/IT + Other HR related area(s)
This new situation requires new knowledge and a more complete understanding of how people are
managed, developed, coordinated, and controlled at MNCs, particularly in the CEE region and
specifically in your country. The basic research items can be framed around the following model:
The current financial and economic crisis originating in the developed countries has rapidly impacted the
world economy. This crisis may negatively impact employment levels at large and medium sized MNC
subsidiaries, pressuring MNC Headquarters (HQ) to drastically reduce managerial salary levels. The
crisis, however, also provides an opportunity to implement efficient global HR policy responses to
enhance the stability of the financial system and stimulate economic growth.
Our examination was carried out based on the model shown in the figure below.
Figure 1: Research model
In developing the research model shown in the figure above we implemented international results and
several of our own previous surveys. During the analysis we collated the observed picture with the
findings of other researchers conducted at the department thus, inter alia, we built on:
HR today
(2009)
Key strategic issues
Key HR issues
HR role of HQ
HR role of subsidiaries
HR capabilities & capabilities acquisition

! Models developed in the field of human resource management (Brewster et al, 2004) and
international management (Hill, 2002; Wild et al., 2003). Our own analyses carried out in
2004 involving 42 foreign owned Hungarian subsidiaries based on the integration of these
models (Poór, 2009).
! Our domestic and international experience gained during the Cranet1 HR researches being
carried out at our department. (Karoliny-Farkas-Poór, 2009; Karoliny-Poór, 2010).
! The results of our collected and published recent theoretical and empirical examinations in
the field of knowledge management such as Dobrai-Farkas 2010 and 2008, Dobrai 2008,
Dobrai-Farkas 2007, Farkas et al. 2005.)
! Also the research experience we gained over recent years during our analyses in the field of
change management (Farkas, 2004), management consulting (Poór, 2010d) and
organizational and national culture (Jarjabka, 2009).
! In addition, the most recent HR researches we conducted in relation to the global economic
crisis that broke out in 2008 (Fodor-Kiss-Poór, 2010).
In the research we covered the following areas:
! Characteristics of the subsidiaries surveyed: the most important organizational and
economic characteristics (origin of the parent company, year of establishment of the
subsidiary, main area of operation of the company – sector –, size of the organization –
based on revenue and the number of employees – and the evolution of its productivity
index, its mandate in the value chain and the main steps, directions of its development).
! Key indicators of the HR function: the number and workload of the staff employed in HR
departments, the main indicators representing the importance, results, efficiency
characteristics of the HR activity (labor cost – total cost ratio, age distribution of the
employees, relative weight of the training budget, level and rate of fluctuation and
absenteeism.)
! Most important HR characteristics of the period examined: the importance of the HR
function, foreign and Hungarian expats, distribution of roles between central and local HR,
the role of local HR in developing and operating the different HRM subsystems, most
important key competencies and fundamental sources of professional development of the
person interviewed.
! Knowledge management in the field of HR: main directions, methods and characteristics of
knowledge flows.
! The future of HR: most significant changes from a HR point of view occurring in the next 12-
24 months.
! Data of the respondents: data on the current HR department and its employees.
Most of our questions were related to the characteristics of the participating subsidiaries observed in
2009. In some cases (number of staff, revenue and HR efficiency indicators) we collected data from both
2008 and 2009.
The statements included in the report were based on the use of descriptive statistical models (frequency,
distribution, average). We also presented graphically the data obtained from processing the answers
given to several important questions.
Several case examples collected during the personal interviews – while ensuring anonymity – were also
added to our analysis.

1 CRANET is a non-profit HR research network involving 42 countries and our department is a member since 2004.

SECTION A: SUBSIDIARIES ANALYZED BY INDIVIDUAL COUNTRIES, TOTAL SAMPLE,
AND TOTAL SAMPLE WITHOUT HUNGARY
In this section the analysis is conducted by organizing the responding firms by coutnry in which
subsidiary is based in.
3 CHARACTERISTICS OF THE COMPANIES PARTICIPATING IN THE SURVEY
320 foreign owned, legally independent subsidiaries participated in the questionnaire survey.
3.1 COMPANY SIZE AND LEGAL FORM
According to the data shown in the table below, the subsidiaries participating in the survey, despite the
global financial and economic crisis, generated nearly constant revenue while maintaining the number of
full-time employees in the two years examined. Poland and the countries under the label “Rest” did not
provide data for 2008.
1. Table: Number of staff and revenue of the participating companies
2008 2009
Number of
employees
Revenue in
EUR (million)
Number of
employees
Revenue in
EUR
(million)
Total Sample 191,975 33,673 292,697 43,253
Total Sample without
Hungary
71,976 4,530 178,724 14,389
Hungary 119,999 29,143 113,973 28,864
Poland 0 0 81,578 7,002
Estonia 1,886 459 16,913 2,730
Romania 24,230 1,520 22,344 1,608
Serbia 20,203 404 23,389 868
Slovakia 21,849 1,145 20,621 1,050
Croatia 3,808 1,003 3,978 755
Rest 0 0 9,901 376
3.1.1 TOTAL NUMBER OF EMPLOYEES
Based on the following 3.1.1. and 3.1.2. subpoints we can state that the companies in the survey are
split equally between large and small enterpises based on the number of their employees (large
enterprises are above 250 persons) or on their revenue. The exceptions are companies in Estonia,
Romania, Slovakia, and Croatia. In this relationship it is important to highlight that although a minority of
the subsidiaries are SMEs based on their size (number of staff and revenue), all the Hungarian
companies analysed are part of larger international companies and thus are regarded as large
enterprises from an operational and management point of view.

2. Table: Number of staff
2008 2009Total
number of
employees
of the
company
Under
250
251-
1000
1001-
2000
2001-
5000
Over
5000
Total
Under
250
251-
1000
1001-
2000
2001-
5000
Over
5000
Total
Total Sample Frequency 79 48 15 16 10 168 154 81 37 24 14 310
Percentage
distribution
(%)
47,0% 28,6% 8,9% 9,5% 6,0% 100,0% 49,7% 26,1% 11,9% 7,7% 4,5% 100,0%
Total Sample
without
Hungary
Frequency 54 21 4 3 4 86 129 81 37 24 14 285
Percentage
distribution
(%)
62,8% 24,4% 4,7% 3,5% 4,7% 100,0% 56,6% 26,1% 11,9% 7,7% 4,5% 106,9%
Hungary Frequency 25 27 11 13 6 82 25 25 14 12 6 82
Percentage
distribution
(%)
30,5% 32,9% 13,4% 15,9% 7,3% 100,0% 30,5% 30,5% 17,1% 14,6% 7,3% 100,0%
Poland Frequency 0 0 0 0 0 0 41 26 14 7 3 91
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 45,1% 28,6% 15,4% 7,7% 3,3% 100,0%
Estonia Frequency 10 3 0 0 0 13 35 11 3 2 0 51
Percentage
distribution
(%)
76,9% 23,1% 0,0% 0,0% 0,0% 100,0% 68,6% 21,6% 5,9% 3,9% 0,0% 100,0%
Romania Frequency 12 5 0 0 2 19 13 5 1 0 2 21
Percentage
distribution
(%)
63,2% 26,3% 0,0% 0,0% 10,5% 100,0% 61,9% 23,8% 4,8% 0,0% 9,5% 100,0%
Serbia Frequency 11 5 2 1 1 20 11 5 2 1 1 20
Percentage
distribution
(%)
55,0% 25,0% 10,0% 5,0% 5,0% 100,0% 55,0% 25,0% 10,0% 5,0% 5,0% 100,0%
Slovakia Frequency 14 6 2 1 1 24 16 4 2 1 1 24
Percentage
distribution
(%)
58,3% 25,0% 8,3% 4,2% 4,2% 100,0% 66,7% 16,7% 8,3% 4,2% 4,2% 100,0%
Croatia Frequency 7 2 0 1 0 10 7 2 0 1 0 10
Percentage
distribution
(%)
70,0% 20,0% 0,0% 10,0% 0,0% 100,0% 70,0% 20,0% 0,0% 10,0% 0,0% 100,0%
Rest Frequency 0 0 0 0 0 0 6 3 1 0 1 11
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 54,5% 27,3% 9,1% 0,0% 9,1% 100,0%
3.1.2 REVENUE
With regard to the revenue we can state that while companies in the lower categories (5-50 billion HUF)
could slightly improve their situations, the larger ones (above 50 billion HUF) were able to retain their
revenue positions also during the period of the crisis.

3. Table: Revenue of the subsidiaries participating in the research (million EUR)

2008
Under 5
million
5-20
million
20-50
million
50-100
million
100-500
million
500-1000
million
Over
1000
million
Total
Total
Sample
Frequency 33 25 22 20 32 12 6 150
Percentage
distribution (%)
22,0% 16,7% 14,7% 13,3% 21,3% 8,0% 4,0% 100,0%
Total
Sample
without
Hungary
Frequency 25 11 18 6 7 2 0 69
Percentage
distribution (%)
36,2% 15,9% 26,1% 8,7% 10,1% 2,9% 0,0% 100,0%
Hungary Frequency 8 14 4 14 25 10 6 81
Percentage
distribution (%)
9,9% 17,3% 4,9% 17,3% 30,9% 12,3% 7,4% 100,0%
Poland Frequency 15 0 0 0 0 0 0 15
Percentage
distribution (%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
Estonia Frequency 9 4 3 1 1 0 0 18
Percentage
distribution (%)
35,7% 28,6% 21,4% 7,1% 7,1% 0,0% 0,0% 100,0%
Romania Frequency 11 7 2 0 2 1 0 23
Percentage
distribution (%)
33,3% 38,9% 11,1% 0,0% 11,1% 5,6% 0,0% 100,0%
Serbia Frequency 2 0 3 0 1 0 0 6
Percentage
distribution (%)
20,0% 0,0% 60,0% 0,0% 20,0% 0,0% 0,0% 100,0%
Slovakia Frequency 11 0 6 3 1 1 0 22
Percentage
distribution (%)
50,0% 0,0% 27,3% 13,6% 4,5% 4,5% 0,0% 100,0%
Croatia Frequency 2 0 4 2 2 0 0 10
Percentage
distribution (%)
20,0% 0,0% 40,0% 20,0% 20,0% 0,0% 0,0% 100,0%
Rest Frequency 0 0 0 0 0 0 0 0
Percentage
distribution (%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%

2009
Under 5
million
5-20
million
20-50
million
50-100
million
100-500
million
500-1000
million
Over 1000
million
Total
Total
Sample
Frequency 67 54 31 33 51 16 8 260
Percentage
distribution (%)
25,8% 20,8% 11,9% 12,7% 19,6% 6,2% 3,1% 100,0%
Total
Sample
without
Hungary
Frequency 59 39 27 21 24 7 2 179
Percentage
distribution (%)
33,0% 21,8% 15,1% 11,7% 13,4% 3,9% 1,1% 100,0%

2009
Under 5
million
5-20
million
20-50
million
50-100
million
100-500
million
500-1000
million
Over 1000
million
Total
Percentage
distribution (%)
9,9% 18,5% 4,9% 14,8% 33,3% 11,1% 7,4% 100,0%
Percentage
distribution (%)
25,0% 25,0% 6,7% 15,0% 20,0% 6,7% 1,7% 100,0%
Percentage
distribution (%)
37,5% 20,8% 20,8% 8,3% 10,4% 2,1% 0,0% 100,0%
Percentage
distribution (%)
42,9% 38,1% 4,8% 0,0% 9,5% 4,8% 0,0% 100,0%
Percentage
distribution (%)
36,4% 9,1% 27,3% 0,0% 18,2% 0,0% 9,1% 100,0%
Percentage
distribution (%)
50,0% 4,5% 27,3% 9,1% 4,5% 4,5% 0,0% 100,0%
Percentage
distribution (%)
20,0% 30,0% 10,0% 20,0% 20,0% 0,0% 0,0% 100,0%
Percentage
distribution (%)
0,0% 14,3% 28,6% 57,1% 0,0% 0,0% 0,0% 100,0%

4. Table: Productivity index of the subsidiaries examined (EUR/person)

2008 2009
Number of
employees
Revenue
in EUR
(thousand
EUR)
Average
revenue per
employee
(EUR/person)
Number of
employees
Revenue
in EUR
(thousand
EUR)
Average
revenue per
employee
(EUR/person)
Total
Sample
191,975 33,672,805 175,402 292,697 43,252,961 147,774
Total
Sample
without
Hungary
71,976 4,530,115 62,939 178,724 14,388,671 80,508
Hungary 119,999 29,142,690 242,858 113,973 28,864,290 253,256
Poland 0 0 0 81,578 7,001,580 85,827
Estonia 1,886 458,500 243,107 16,913 2,730,250 161,429
Romania 24,230 1,519,702 62,720 22,344 1,607,886 71,961
Serbia 20,203 403,900 19,992 23,389 868,000 37,111
Slovakia 21,849 1,145,463 52,426 20,621 1,050,305 50,934
Croatia 3,808 1,002,550 263,275 3,978 754,650 189,706
Rest 0 0 0 9,901 376,000 37,976
As the result of the trends in the number of employees and in the revenue reviewed above, the average
productivity index has decreased for the total sample from a low level of 175 thousand EUR/person in

2008 to 147 thousand in 2009 in the companies examined. The averages increased for Hungary by
104%, Romania (115%) and Serbia (186%) while they decreased for Estonia (66%), Slovakia (97%) and
Croatia (72%).
5. Table: Revenue per employee (thousand EUR/person)
Total
Sample
Total
Sample
without
Hungary
Hungary Poland Estonia Romania Serbia Slovakia Croatia Rest
Revenue per
employee
(thousand
EUR/person)
2008
Under 5
thousand EUR
Frequency 146 67 79 0 14 18 5 22 8 0
Percentage
distribution
(%)
97,3% 97,1% 97,5% 0,0% 100,0% 100,0% 100,0% 100,0% 80,0% 0,0%
5-10 thousand
EUR
Frequency 2 1 1 0 0 0 0 0 1 0
Percentage
distribution
(%)
1,3% 1,4% 1,2% 0,0% 0,0% 0,0% 0,0% 0,0% 10,0% 0,0%
10-20 thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
20-40 thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
40-60 thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
60-100 thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
100-150
thousand EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
Over 150
thousand EUR
Frequency 2 1 1 0 0 0 0 0 1 0
Percentage
distribution
(%)
1,3% 1,4% 1,2% 0,0% 0,0% 0,0% 0,0% 0,0% 10,0% 0,0%
Total Frequency 150 69 81 0 14 18 5 22 10 0
Percentage
distribution
(%)
100,0% 100,0% 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 0,0%
Total
Sample
Total
Sample
without
Hungary
Revenue per
employee
(thousand
EUR/person)
2009
Under 5
thousand
EUR
Frequency 254 174 80 58 47 21 11 22 8 7

Total
Sample
Total
Sample
without
Hungary
Revenue per
employee
(thousand
EUR/person)
2009
Percentage
distribution
(%)
97,7% 97,2% 98,8% 96,7% 97,9% 100,0% 100,0% 100,0% 80,0% 100,0%
5-10
thousand
EUR
Frequency 2 2 0 1 0 0 0 0 1 0
Percentage
distribution
(%)
0,8% 1,1% 0,0% 1,7% 0,0% 0,0% 0,0% 0,0% 10,0% 0,0%
10-20
thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
20-40
thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
40-60
thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
60-100
thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
100-150
thousand
EUR
Frequency 0 0 0 0 0 0 0 0 0 0
Percentage
distribution
(%)
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
Over 150
thousand
EUR
Frequency 4 3 1 1 1 0 0 0 1 0
Percentage
distribution
(%)
1,5% 1,7% 1,2% 1,7% 2,1% 0,0% 0,0% 0,0% 10,0% 0,0%
Total Frequency 260 179 81 60 48 21 11 22 10 7
Percentage
distribution
(%)
100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0%
3.2 MANDATE OF THE ORGANIZATION

We also examined how much control these organizations have over the entire value chain. This
examination was based on organizations’ responses to which mandate they operated under. These
mandates are defined as follows:
1) "Mandate 1" This is a business which markets into the local trading area products manufactured
centrally. The business is a small-scale replica of the parent.
2) "Mandate 2" This is a business operating a designated set of component parts for a multi-country
or global market. Operational activities locally will be confined to at most packaging, bulk
breaking, some final processing and warehousing distributing.

3) "Mandate 3" This is a business that does not have control of the entire value chain of a business
unit but has activities in a number of parts of the value chain. This might be a preparation of
manufacturing activities or a regional logistics brief (responsibility).
4) "Mandate 4" This is a business that develops and markets a limited product service for global
markets. Products, markets or basic technologies are similar to the parent company, but
exchanges between the subsidiary and the parent are rare.
5) "Mandate 5" This is a business that has the freedom and resources to develop lines of business
for either a local, multi-country or a global market. The subsidiary is allowed unconstrained
access to global markets and freedom to pursue new business opportunities.
The origin of the mandate model described above goes back to Porter’s (1980) value chain model.
During the analysis, after Delany (1998) and White-Poynter (1984), we classified the participants into five
groups based on how much of the value chain is covered by the range of activities of the local
subsidiary.
Based on the responses it can be stated that the mandates of 20% or more of the companies analyzed
in the total sample indicated their mandates as either mandate 4 (23%) or 5 (20%). In most regions
organizations indicated operating under several mandates with mandate 3 being indicated most often
from 23% of organizations in Romania up to 55% of organizations in Croatia. The other popular
mandates indicated were mandates 4 and 5. In Hungary 35% organizations indicated operating under
mandate 4.
6. Table: Mandates of the companies participating in the survey

Roles and
mandates
of your
subsidiary
Total
Sample
Total
Sample
without
Hungary
Mandate 1 Frequency 63 49 14 21 14 5 3 5 0 1
Percentage
distribution
(%)
19,9% 21,1% 16,7% 22,1% 28,6% 22,7% 15,0% 20,8% 0,0% 9,1%
Percentage
distribution
(%)
17,1% 20,7% 7,1% 26,3% 12,2% 18,2% 30,0% 16,7% 27,3% 0,0%
Percentage
distribution
(%)
20,3% 19,4% 22,6% 10,5% 16,3% 22,7% 25,0% 29,2% 54,5% 36,4%
Percentage
distribution
(%)
22,5% 17,7% 35,7% 16,8% 12,2% 22,7% 15,0% 25,0% 18,2% 27,3%
Percentage
distribution
(%)
20,3% 21,1% 17,9% 24,2% 30,6% 13,6% 15,0% 8,3% 0,0% 27,3%
Total Frequency 316 232 84 95 49 22 20 24 11 11
Percentage
distribution
(%)
100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0%
3.3 ORIGIN OF THE PARENT COMPANY
The subsidiaries participating in the survey in the total sample came from 35 different countries. More
than 60% of them came from the following seven countries: Germany (19%), USA (13%), Sweden (6%),

France (6.6%), Austria (5.7%), and Hungary and Finland (5.4% each), while another 13 countries
account for another nearly 27% and the remaining 13% is accounted by 15 countries.
7. Table: Origin of the parent companies of the participating companies
Total Sample
Hungary
Hungary Poland
Origin of the
parent company
Frequency
%
distribution
Frequency
%
distribution
Frequency
%
distribution
Frequency
%
distribution
Austria 18 5,7% 18 7,2% 0 0,0% 6 6,3%
Belgium 2 0,6% 1 0,4% 1 1,5% 0 0,0%
Canada 4 1,3% 4 1,6% 0 0,0% 0 0,0%
Croatia 1 0,3% 1 0,4% 0 0,0% 0 0,0%
Cyprus 1 0,3% 1 0,4% 0 0,0% 1 1,1%
Czech R. 8 2,5% 8 3,2% 0 0,0% 1 1,1%
Denmark 7 2,2% 7 2,8% 0 0,0% 2 2,1%
Estonia 5 1,6% 5 2,0% 0 0,0% 0 0,0%
Finland 17 5,4% 16 6,4% 1 1,5% 3 3,2%
France 21 6,6% 14 5,6% 7 10,8% 10 10,5%
Germany 60 19,0% 40 15,9% 20 30,8% 22 23,2%
Great Britain 14 4,4% 11 4,4% 3 4,6% 4 4,2%
Greece 1 0,3% 1 0,4% 0 0,0% 1 1,1%
Hungary 17 5,4% 17 6,8% 0 0,0% 9 9,5%
Ireland 5 1,6% 5 2,0% 0 0,0% 4 4,2%
Israel 2 0,6% 1 0,4% 1 1,5% 0 0,0%
Italy 9 2,8% 8 3,2% 1 1,5% 0 0,0%
Japan 9 2,8% 4 1,6% 5 7,7% 3 3,2%
Latvia 2 0,6% 2 0,8% 0 0,0% 0 0,0%
Luxemburg 3 0,9% 3 1,2% 0 0,0% 0 0,0%
Mexico 1 0,3% 1 0,4% 0 0,0% 1 1,1%
Netherlands 6 1,9% 3 1,2% 3 4,6% 1 1,1%
Norway 4 1,3% 4 1,6% 0 0,0% 2 2,1%
Poland 11 3,5% 11 4,4% 0 0,0% 0 0,0%
Romania 5 1,6% 5 2,0% 0 0,0% 0 0,0%
Russia 1 0,3% 1 0,4% 0 0,0% 0 0,0%
Serbia 1 0,3% 1 0,4% 0 0,0% 0 0,0%
Slovakia 1 0,3% 1 0,4% 0 0,0% 0 0,0%
Slovenia 1 0,3% 1 0,4% 0 0,0% 0 0,0%
South Africa 1 0,3% 0 0,0% 1 1,5% 0 0,0%
South Korea 4 1,3% 3 1,2% 1 1,5% 2 2,1%
Spain 4 1,3% 4 1,6% 0 0,0% 2 2,1%
Sweden 20 6,3% 18 7,2% 2 3,1% 3 3,2%
Switzerland 9 2,8% 8 3,2% 1 1,5% 6 6,3%
USA 41 13,0% 23 9,2% 18 27,7% 12 12,6%
Total 316 100,0% 251 100,0% 65 100,0% 95 100,0%

Estonia Romania Serbia Slovakia
Origin of
the parent
company
Frequency % distribution Frequency % distribution Frequency
%
distribution
Frequency
%
distribution
Austria 1 1,5% 2 6,1% 0 0,0% 5 18,5%
Belgium 0 0,0% 2 6,1% 0 0,0% 5 18,5%
Canada 4 6,1% 0 0,0% 0 0,0% 0 0,0%
Croatia 4 6,1% 0 0,0% 1 5,6% 0 0,0%
Cyprus 0 0,0% 0 0,0% 0 0,0% 0 0,0%
Czech R. 1 1,5% 0 0,0% 0 0,0% 0 0,0%
Denmark 3 4,5% 0 0,0% 0 0,0% 1 3,7%
Estonia 0 0,0% 5 15,2% 0 0,0% 0 0,0%
Finland 11 16,7% 5 15,2% 0 0,0% 1 3,7%
France 2 3,0% 5 15,2% 1 5,6% 0 0,0%
Germany 3 4,5% 7 21,2% 3 16,7% 3 11,1%
Great
Britain
2 3,0% 2 6,1% 0 0,0% 1 3,7%
Greece 0 0,0% 0 0,0% 0 0,0% 0 0,0%
Hungary 0 0,0% 0 0,0% 3 16,7% 3 11,1%
Ireland 2 3,0% 0 0,0% 0 0,0% 0 0,0%
Israel 1 1,5% 0 0,0% 0 0,0% 0 0,0%
Italy 1 1,5% 1 3,0% 2 11,1% 1 3,7%
Japan 1 1,5% 0 0,0% 0 0,0% 0 0,0%
Latvia 2 3,0% 0 0,0% 0 0,0% 0 0,0%
Luxemburg 1 1,5% 0 0,0% 0 0,0% 0 0,0%
Mexico 0 0,0% 0 0,0% 0 0,0% 0 0,0%
Netherland
s
0 0,0% 1 3,0% 0 0,0% 0 0,0%
Norway 1 1,5% 0 0,0% 1 5,6% 0 0,0%
Poland 10 15,2% 1 3,0% 0 0,0% 0 0,0%
Romania 0 0,0% 0 0,0% 5 27,8% 0 0,0%
Russia 0 0,0% 0 0,0% 0 0,0% 1 3,7%
Serbia 0 0,0% 0 0,0% 0 0,0% 1 3,7%
Slovakia 0 0,0% 0 0,0% 0 0,0% 0 0,0%
Slovenia 0 0,0% 0 0,0% 0 0,0% 0 0,0%
South
Africa
0 0,0% 0 0,0% 0 0,0% 0 0,0%
South
Korea
1 1,5% 0 0,0% 0 0,0% 0 0,0%
Spain 1 1,5% 1 3,0% 0 0,0% 0 0,0%
Sweden 11 16,7% 0 0,0% 1 5,6% 2 7,4%
Switzerlan
d
1 1,5% 0 0,0% 0 0,0% 0 0,0%
USA 2 3,0% 1 3,0% 1 5,6% 3 11,1%
Total 66 100,0% 33 100,0% 18 100,0% 27 100,0%

Croatia Rest
Origin of the parent company Frequency % distribution Frequency % distribution
Austria 1 4,3% 3 16,7%
Belgium 0 0,0% 3 16,7%
Canada 0 0,0% 0 0,0%
Croatia 0 0,0% 0 0,0%
Cyprus 0 0,0% 0 0,0%
Czech R. 6 26,1% 0 0,0%
Denmark 6 26,1% 1 5,6%
Estonia 0 0,0% 0 0,0%
Finland 0 0,0% 1 5,6%
France 1 4,3% 0 0,0%
Germany 1 4,3% 1 5,6%
Great Britain 0 0,0% 4 22,2%
Greece 0 0,0% 0 0,0%
Hungary 2 8,7% 0 0,0%
Ireland 1 4,3% 0 0,0%
Israel 0 0,0% 0 0,0%
Italy 0 0,0% 1 5,6%
Japan 0 0,0% 0 0,0%
Latvia 0 0,0% 0 0,0%
Luxemburg 0 0,0% 0 0,0%
Mexico 0 0,0% 0 0,0%
Netherlands 1 4,3% 0 0,0%
Norway 0 0,0% 0 0,0%
Poland 0 0,0% 0 0,0%
Romania 0 0,0% 0 0,0%
Russia 0 0,0% 0 0,0%
Serbia 0 0,0% 0 0,0%
Slovakia 1 4,3% 0 0,0%
Slovenia 0 0,0% 1 5,6%
South Africa 0 0,0% 0 0,0%
South Korea 0 0,0% 0 0,0%
Spain 0 0,0% 0 0,0%
Sweden 1 4,3% 0 0,0%
Switzerland 0 0,0% 1 5,6%
USA 2 8,7% 2 11,1%
Total 23 100,0% 18 100,0%

Figure 2: Origin of the parent company (% distribution) s of the participating companies
3.4 YEAR AND FORM OF ESTABLISHMENT OF THE SUBSIDIARIES
Over 40% of the foreign owners of the companies participating in the survey came to Hungary realizing
greenfield investments and over 50% of them obtained majority control in Hungarian companies during
the privatization and the following acquisitions.
In the total sample one-third of the subsidiaries were established between 1990 and 1995 (31.2%), Over
one quarter (26.0%) of the companies settled between 2001 and 2005, while 23.1% of subsidiaries were
established between 1996 and 2000 and the remaining ones (17.9%) in the new millennium.2. In each of

2 The great migration to Hungary took place in the ’90s – in contrast with for example the neighbouring Slovakia
where this occurred between 2002 and 2007. Many of the large multinational companies present in Hungary have
been operating here continuously for about one and a half decades. However, the actors of some industries (e.g.
automotive suppliers) move very fast. If the situation is not favorable, these companies walk away very quickly.
However, the decision that these companies stay or leave also depends largely on whether their main buyers stay
here or leave. The role of ”cheap manufacturing and service provider” Hungarian subsidiaries with shorter delivery
times increased during the crisis.

the categories for year of establishment the split between companies entering the market through
merger and acquisitions and through greenfield investments was fairly even – 46.1% for merger and
acquisitions and 44.5% for greenfield investments.
8. Table: Year and mode of entry of the participants
Total Sample Total Sample without Hungary
Year of
establishment
of the
subsidiary
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Before 1990 1 4 1 6 1,9% 0 2 1 3 1,3%
1990-1995 45 45 6 96 31,2% 21 32 5 58 25,1%
1996-2000 33 30 8 71 23,1% 25 19 5 49 21,2%
2001-2005 39 33 8 80 26,0% 37 28 7 72 31,2%
After 2005 24 25 6 55 17,9% 20 23 6 49 21,2%
Total 142 137 29 308 100,0% 103 104 24 231 100,0%
% distribution 46,1% 44,5% 9,4% 100,0% 44,6% 45,0% 10,4% 100,0%
Hungary Poland
Year of
establishment
of the
subsidiary
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Before 1990 1 2 0 3 3,9% 0 1 1 2 2,2%
1990-1995 24 13 1 38 49,4% 8 18 0 26 28,0%
1996-2000 8 11 3 22 28,6% 9 10 2 21 22,6%
2001-2005 2 5 1 8 10,4% 13 14 1 28 30,1%
After 2005 4 2 0 6 7,8% 4 12 0 16 17,2%
Total 39 33 5 77 100,0% 34 55 4 93 100,0%
% distribution 50,6% 42,9% 6,5% 100,0% 36,6% 59,1% 4,3% 100,0%
Estonia Romania
Year of
establishment
of the
subsidiary
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Before 1990 0 1 0 1 1,9% 0 0 0 0 0,0%
1990-1995 6 4 4 14 26,4% 1 2 0 3 14,3%
1996-2000 5 3 2 10 18,9% 3 2 0 5 23,8%
2001-2005 7 4 2 13 24,5% 3 5 0 8 38,1%
After 2005 9 3 3 15 28,3% 1 4 0 5 23,8%
Total 27 15 11 53 100,0% 8 13 0 21 100,0%
% distribution 50,9% 28,3% 20,8% 100,0% 38,1% 61,9% 0,0% 100,0%

Serbia Slovakia
Year of
establishment
of the
subsidiary
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Before 1990 0 0 0 0 0,0% 0 0 0 0 0,0%
1990-1995 0 0 0 0 0,0% 2 5 0 7 33,3%
1996-2000 3 0 1 4 18,2% 1 3 0 4 19,0%
2001-2005 4 1 3 8 36,4% 6 3 0 9 42,9%
After 2005 5 3 2 10 45,5% 0 1 0 1 4,8%
Total 12 4 6 22 100,0% 9 12 0 72 100,0%
% distribution 54,5% 18,2% 27,3% 100,0% 42,9% 57,1% 0,0% 100,0%
Croatia Rest
Year of
establishment
of the
subsidiary
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Merger,
acquisition
Greenfield
investment
Other Total
%
distribution
Before 1990 0 0 0 0 0,0% 0 0 0 0 0,0%
1990-1995 2 1 0 3 30,0% 2 2 1 5 45,5%
1996-2000 2 1 0 3 30,0% 2 0 0 2 18,2%
2001-2005 4 0 0 4 40,0% 0 1 1 2 18,2%
After 2005 0 0 0 0 0,0% 1 0 1 2 18,2%
Total 8 2 0 10 100,0% 5 3 3 33 100,0%
% distribution 80,0% 20,0% 0,0% 100,0% 45,5% 27,3% 27,3% 100,0%
3.5 FIELD OF OPERATION: SECTOR-INDUSTRY
There were 44% of the organizations examined in the total sample engaged in manufacturing and 44%
of organizations in trade, tangible and intangible services while 12% of organizations in other industries.
In the Hungarian sample 59.5% of the organizations were engaged in manufacturing and 47.5% of
organizations in trade, tangible and intangible services whle 13.8% of organizations in other. Other
details of the secoral distribution is as follows:
! Nearly 20% of the respondents operate in the service industries in the total sample while in
the Hungarian sample nearly 23% of the organizations were in the engineering industry.
! A substantial number of the participants come from the engineering industry (13.9%) and
the trade industry (13.6%) in the total sample while substantial participants in the Hungarian
sample were in FMCG (13.1%), trade (14.3%), and service (11.9%) industries.
9. Table: Sectoral distribution of the participants
Main sector of
the
subsidiary’s
activity
Heavy
industry,
mining,
energy
industry
Light
industry
Engineering
Chemical
and
pharmace
utical
industry
Consumer
goods
(FMCG)
Trade Services
Financial
institutions,
banks
Other Total
Total
Sample
Frequency 31 30 44 10 25 43 60 35 38 316
% distribution 9,8% 9,5% 13,9% 3,2% 7,9% 13,6% 19,0% 11,1% 12,0% 100,0%
Total
Sample
without
Hungary
Frequency 23 25 25 3 14 31 50 29 32 232
% distribution 9,9% 10,8% 10,8% 1,3% 6,0% 13,4% 21,6% 12,5% 13,8% 100,0%
Hungary Frequency 8 5 19 7 11 12 10 6 6 84

Main sector of
the
subsidiary’s
activity
Heavy
industry,
mining,
energy
industry
Light
industry
Engineering
Chemical
and
pharmace
utical
industry
Consumer
goods
(FMCG)
Trade Services
Financial
institutions,
banks
Other Total
% distribution 9,5% 6,0% 22,6% 8,3% 13,1% 14,3% 11,9% 7,1% 7,1% 100,0%
Poland Frequency 16 8 16 1 3 7 20 11 11 93
% distribution 17,2% 8,6% 17,2% 1,1% 3,2% 7,5% 21,5% 11,8% 11,8% 100,0%
Estonia Frequency 1 4 5 0 3 6 14 5 13 51
% distribution 2,0% 7,8% 9,8% 0,0% 5,9% 11,8% 27,5% 9,8% 25,5% 100,0%
Romania Frequency 2 3 1 0 1 9 6 0 0 22
% distribution 9,1% 13,6% 4,5% 0,0% 4,5% 40,9% 27,3% 0,0% 0,0% 100,0%
Serbia Frequency 1 5 1 0 3 3 1 5 1 20
% distribution 5,0% 25,0% 5,0% 0,0% 15,0% 15,0% 5,0% 25,0% 5,0% 100,0%
Slovakia Frequency 2 5 1 0 1 4 4 3 4 24
% distribution 8,3% 20,8% 4,2% 0,0% 4,2% 16,7% 16,7% 12,5% 16,7% 100,0%
Croatia Frequency 0 0 1 0 2 1 2 5 0 11
% distribution 0,0% 0,0% 9,1% 0,0% 18,2% 9,1% 18,2% 45,5% 0,0% 100,0%
Rest Frequency 1 0 0 1 1 1 3 0 4 11
% distribution 9,1% 0,0% 0,0% 9,1% 9,1% 9,1% 27,3% 0,0% 36,4% 100,0%
Figure 3: Sectoral distribution of the participants

3.6 MAIN DIRECTIONS OF DEVELOPMENT OF THE COMPANIES IN THE PERIOD
EXAMINED

In relation to the topic indicated in the subtitle, we examined how important the following three strategic
orientations were for the respondents:
! growth, market expansion, portfolio expansion,
! stability, efficiency improvement, revenue retention, adapting to the market situation,
! redundancies, rationalization.
3.6.1 MAIN STRATEGIC ISSUES-ORIENTATIONS
The majority of the respondents (35%) in the total sample indicated that they were seeking growth and
portfolio expansion during the period examined. Almost 35% of the companies surveyed were
characterized by stability. The fact that 22.5%, nearly a quarter, of the respondents chose the
redundancies and rationalization option indicates a slow recovery from the crisis. Other solutions
account for 22% of the answers. A high proportion of Polish and Croatian organizations indicated growth
and expansion plans (47.6% and 50% respectively). While the other samples mainly indicated a focus
toward seeking stability, for example 38.5% in the Hungarian sample. In the Romanian sample over one
third of the organization chose the redundancies and rationalization option.
10. Table: Main strategic issues and orientations
Main
strategic
issues,
orientations
Growth,
market
expansion,
portfolio
expansion
Stability,
efficiency
improvement,
revenue
retention,
adapting to
the market
situation
Redundancies,
rationalization
Other Total
Total
Sample
Frequency
of “yes”
answers
153 150 97 32 432
%
distribution
35,4% 34,7% 22,5% 7,4% 100,0%
Total
Sample
without
Hungary
Frequency
of “yes”
answers
122 105 73 15 315
%
distribution
38,7% 33,3% 23,2% 4,8% 100,0%
Hungary
Frequency
of “yes”
answers
31 45 24 17 117
%
distribution
26,5% 38,5% 20,5% 14,5% 100,0%
Poland
Frequency
of “yes”
answers
59 27 34 4 124
%
distribution
47,6% 21,8% 27,4% 3,2% 100,0%
Estonia
Frequency
of “yes”
answers
20 27 15 6 68
%
distribution
29,4% 39,7% 22,1% 8,8% 100,0%

Main
strategic
issues,
orientations
Growth,
market
expansion,
portfolio
expansion
Stability,
efficiency
improvement,
revenue
retention,
adapting to
the market
situation
Redundancies,
rationalization
Other Total
Romania
Frequency
of “yes”
answers
7 11 10 1 29
%
distribution
24,1% 37,9% 34,5% 3,4% 100,0%
Serbia
Frequency
of “yes”
answers
10 16 1 2 29
%
distribution
34,5% 55,2% 3,4% 6,9% 100,0%
Slovakia
Frequency
of “yes”
answers
11 14 6 0 31
%
distribution
35,5% 45,2% 19,4% 0,0% 100,0%
Croatia
Frequency
of “yes”
answers
9 5 4 0 18
%
distribution
50,0% 27,8% 22,2% 0,0% 100,0%
Rest
Frequency
of “yes”
answers
6 5 3 2 16
%
distribution
37,5% 31,3% 18,8% 12,5% 100,0%
Figure 4: Main strategic issues and orientations (%)

3.6.2 MAIN COMPETITIVE FACTORS IN THE PERIOD EXAMINED
Optimal plant/organization size was chosen most frequently (21.7%) by the respondents of the total
sample to the questions about the most important competitive factros of companies (more then one
answer could be marked in this question). Workforce competitive factor (20.7%) followed closely behind
as the next most frequent choice. The respondents also deemed financial resources (17.6%),
management (16.9%) and production technology (14.5%) to be the next important competitive factors.
Production technology reached nearly 20% frequence or more as competitive factor in the Polish sample
(19%), Serbian sample 21.3%, and the Rest sample (21.7%).
11. Table: The importance of competitive factors
Competitive
factors
Optimal
plant/
organization
size
Financial
resources
Workforce Management
Production
technology
Protected,
regulated
market
Other Total
Total
Sample
Frequency
of “yes”
answers
173 141 167 135 116 38 29 799
%
distribution
21,7% 17,6% 20,9% 16,9% 14,5% 4,8% 3,6% 100,0%
Total
Sample
without
Hungary
Frequency
of “yes”
answers
115 95 125 106 94 31 15 581
%
distribution
19,8% 16,4% 21,5% 18,2% 16,2% 5,3% 2,6% 100,0%
Hungary
Frequency
of “yes”
answers
58 46 42 29 22 7 14 218
%
distribution
26,6% 21,1% 19,3% 13,3% 10,1% 3,2% 6,4% 100,0%
Poland
Frequency
of “yes”
answers
48 36 63 51 50 11 3 262
%
distribution
18,3% 13,7% 24,0% 19,5% 19,1% 4,2% 1,1% 100,0%
Estonia
Frequency
of “yes”
answers
27 23 24 21 14 5 4 118

Competitive
factors
Optimal
plant/
organization
size
Financial
resources
Workforce Management
Production
technology
Protected,
regulated
market
Other Total
%
distribution
22,9% 19,5% 20,3% 17,8% 11,9% 4,2% 3,4% 100,0%
Romania
Frequency
of “yes”
answers
9 10 6 10 7 5 3 50
%
distribution
18,0% 20,0% 12,0% 20,0% 14,0% 10,0% 6,0% 100,0%
Serbia
Frequency
of “yes”
answers
8 9 9 7 10 2 2 47
%
distribution
17,0% 19,1% 19,1% 14,9% 21,3% 4,3% 4,3% 100,0%
Slovakia
Frequency
of “yes”
answers
12 11 9 5 6 5 2 50
%
distribution
24,0% 22,0% 18,0% 10,0% 12,0% 10,0% 4,0% 100,0%
Croatia
Frequency
of “yes”
answers
8 3 8 8 2 1 1 31
%
distribution
25,8% 9,7% 25,8% 25,8% 6,5% 3,2% 3,2% 100,0%
Rest
Frequency
of “yes”
answers
3 3 6 4 5 2 0 23
%
distribution
13,0% 13,0% 26,1% 17,4% 21,7% 8,7% 0,0% 100,0%
Figure 5: The importance of competitive factors

4 CHARACTERISTICS OF THE KEY INDICATORS OF THE HR FUNCTION
In this section we give an overview of the following HR characteristics:
! Number and workload of the HR staff,
! The main indicators representing the importance, results, and efficiency characteristics of
the HR activity (labor cost – total cost ratio, age pyramid, relative weight of the training
budget, the fluctuation rate and absenteeism).
4.1 NUMBER OF HR STAFF
The average number of employees served by one HR professional decreased from 77 in 2008 to 64 in
2009 in the companies surveyed in the total sample while in the Hungarian sample the ratio (Employees
per HR position) increased from 79 in 2008 to 88 in 2009.Increases in the ratio were also seen the
Serbian, Slovakian, and Croatian samples. Decreases in the ratio were seen by the Estonian and
Romanian samples. In these companies in the total sample nearly 43% of the total number of HR staff
carried out administrative tasks while 57% were HR professionals. In the companies in the Hungarian
sample 48% of the total number of HR staff carried out administrative tasks while 52% were HR
professionals.
12. Table: Number of employees and HR staff in the participating companies (n=63)
2008
HR staff
Number of
employees
HR
admin
staff
HR
professional
Total
number of
HR staff
Employees
per HR
position
Total Sample 191 975 1 066 1 451 2 509 77
Total Sample
without Hungary
71 976 446 546 984 73
Hungary 119 999 620 905 1 525 79
Poland 0 0 0 0 0
Estonia 1 886 15 31 38 50
Romania 24 230 204 263 467 52
Serbia 20 203 129 160 289 70
Slovakia 21 849 88 61 149 147
Croatia 3 808 10 31 41 93
Rest 0 0 0 0 0
2009
HR staff
Number of
employees
HR admin
staff
HR
professional
Total
number
of HR
staff
Employees
per HR
position
Total Sample 292 697 1 979 2 662 4 605 64
Total Sample
without Hungary
269 308 1 851 2 525 4 340 62
Hungary 23 389 128 137 265 88
Poland 81 578 743 740 1 452 56
Estonia 16 913 228 537 763 22

2009
HR staff
Number of
employees
HR admin
staff
HR
professional
Total
number
of HR
staff
Employees
per HR
position
Romania 22 344 176 227 403 55
Serbia 23 389 128 137 265 88
Slovakia 20 621 76 60 136 152
Croatia 3 978 10 31 41 97
Rest 9 901 38 53 91 109
The HR departments of the companies examined are relatively large as the number of HR staff was
higher than 5 persons in the case of more than 52% of the respondents in the total sample in 2009.
Fourteen organizations participating in the survey didn’t have an HR department, moreover they didn’t
even employ a single HR professional.
13. Table: Number of HR staff
2008
Total
number of
HR staff
None
1-4
persons
5-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
Total
Sample Frequency
6 73 35 12 9 31 166
%
distribution
3,6% 44,0% 21,1% 7,2% 5,4% 18,7% 100,0%
Total
Sample
without
Hungary Frequency
2 48 14 3 7 9 83
%
distribution
2,4% 57,8% 16,9% 3,6% 8,4% 10,8% 100,0%
Hungary Frequency 4 25 21 9 2 22 83
%
distribution
4,8% 30,1% 25,3% 10,8% 2,4% 26,5% 100,0%
Poland Frequency 0 0 0 0 0 0 0
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
Estonia Frequency 1 10 3 0 0 0 14
%
distribution
7,1% 71,4% 21,4% 0,0% 0,0% 0,0% 100,0%
Romania Frequency 0 5 4 0 2 5 16
%
distribution
0,0% 31,3% 25,0% 0,0% 12,5% 31,3% 100,0%
Serbia Frequency 0 12 2 1 2 3 20
%
distribution
0,0% 60,0% 10,0% 5,0% 10,0% 15,0% 100,0%
Slovakia Frequency 0 15 3 2 2 1 23

2008
Total
number of
HR staff
None
1-4
persons
5-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
%
distribution
0,0% 65,2% 13,0% 8,7% 8,7% 4,3% 100,0%
Croatia Frequency 1 6 2 0 1 0 10
%
distribution
10,0% 60,0% 20,0% 0,0% 10,0% 0,0% 100,0%
Rest Frequency 0 0 0 0 0 0 0
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
2009
Total
number
of HR
staff
None
1-4
persons
5-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
Total
Sample Frequency
14 126 67 24 12 52 295
%
distribution
4,7% 42,7% 22,7% 8,1% 4,1% 17,6% 100,0%
Total
Sample
without
Hungary Frequency
10 100 49 13 10 30 212
%
distribution
4,7% 47,2% 23,1% 6,1% 4,7% 14,2% 100,0%
%
distribution
4,8% 31,3% 21,7% 13,3% 2,4% 26,5% 100,0%
%
distribution
5,7% 38,6% 31,8% 5,7% 4,5% 13,6% 100,0%
%
distribution
7,1% 47,6% 14,3% 9,5% 4,8% 16,7% 100,0%
%
distribution
5,6% 33,3% 22,2% 5,6% 0,0% 33,3% 100,0%
%
distribution
0,0% 50,0% 20,0% 5,0% 10,0% 15,0% 100,0%
%
distribution
0,0% 69,6% 13,0% 8,7% 4,3% 4,3% 100,0%
%
distribution
10,0% 60,0% 20,0% 0,0% 10,0% 0,0% 100,0%

2009
Total
number
of HR
staff
None
1-4
persons
5-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
%
distribution
0,0% 72,7% 18,2% 0,0% 0,0% 9,1% 100,0%
In the total sample the average number of employees per HR professional were mostly under 100
employees for 74.9% of the organizations and 94.2% of organizations with 200 persons or less per HR
professional. In Hungary 91.6% of organizations have 200 persons or less per HR professional and this
pattern is true in the other samples. In the Romanian sample (83.3%) and in the Estonian sample
(66.7%) a large number of organizations have under 50 persons per HR employee.3
14. Table: Emloyees per HR professional
2008
Number of
employees
per HR
professional
Under 50
persons
50-100
persons
101-200
persons
201-500
persons
501-1000
persons
Over 1000
persons
Total
Total
Sample Frequency 68 55 37 5 1 0 166
%
distribution 41,0% 33,1% 22,3% 3,0% 0,6% 0,0%
100,0
%
Total
Sample
without
%
distribution 54,2% 26,5% 19,3% 0,0% 0,0% 0,0%
100,0
%
%
distribution 27,7% 39,8% 25,3% 6,0% 1,2% 0,0%
100,0
%
%
distribution 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
%
distribution 71,4% 21,4% 7,1% 0,0% 0,0% 0,0%
100,0
%
%
distribution 81,3% 6,3% 12,5% 0,0% 0,0% 0,0%
100,0
%
%
distribution 45,0% 30,0% 25,0% 0,0% 0,0% 0,0%
100,0
%

3 It is well known from management theory and practical experience that it is not reasonable to maintain a separate
HR apparatus under a certain number of employees (cca. 80-100 persons) within an organization. However, the
actual ratio also depends on the industry and the composition of the workforce.

2008
Number of
employees
per HR
professional
Under 50
persons
50-100
persons
101-200
persons
201-500
persons
501-1000
persons
Over 1000
persons
Total
%
distribution 34,8% 52,2% 13,0% 0,0% 0,0% 0,0%
100,0
%
%
distribution 50,0% 0,0% 50,0% 0,0% 0,0% 0,0%
100,0
%
%
distribution 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
2009
Number of
employees
per HR
professional
Under 50
persons
50-100
persons
101-200
persons
201-500
persons
501-1000
persons
Over 1000
persons
Total
Total
Sample Frequency 130 91 57 16 1 0 295
%
distribution 44,1% 30,8% 19,3% 5,4% 0,3% 0,0%
100,0
%
Total
Sample
without
%
distribution 50,5% 27,4% 17,5% 4,2% 0,5% 0,0%
100,0
%
%
distribution 27,7% 39,8% 24,1% 8,4% 0,0% 0,0%
100,0
%
%
distribution 46,6% 27,3% 18,2% 6,8% 1,1% 0,0%
100,0
%
%
distribution 66,7% 23,8% 7,1% 2,4% 0,0% 0,0%
100,0
%
%
distribution 83,3% 5,6% 11,1% 0,0% 0,0% 0,0%
100,0
%
%
distribution 40,0% 25,0% 35,0% 0,0% 0,0% 0,0%
100,0
%
%
distribution 34,8% 52,2% 13,0% 0,0% 0,0% 0,0%
100,0
%
%
distribution 30,0% 20,0% 40,0% 10,0% 0,0% 0,0%
100,0
%

2009
Number of
employees
per HR
professional
Under 50
persons
50-100
persons
101-200
persons
201-500
persons
501-1000
persons
Over 1000
persons
Total
%
distribution 36,4% 36,4% 18,2% 9,1% 0,0% 0,0%
100,0
%
Figure 6: Number of employees per HR professional
4.2 THE MAIN INDICATORS REPRESENTING THE IMPORTANCE AND RESULTS OF
THE HR ACTIVITY
4.2.1 LABOR COST – OPERATING COST RATIO
The labor cost – operating cost ratio is one of the frequently analyzed indicators of the importance of the
HR function in the company’s life. According to assumptions, the effects of HRM have a stronger and
more direct influence on the company’s performance if this ratio is higher. About one third (34.9%) of the
subsidiaries participating in the survey fell into this category (where the labor cost ratio is higher than
30%) in the total sample. But the vast majority (65.1%) of the companies operated with a relatively low
(under 30%) labor cost ratio4. In the Croatian sample (87.5%) and in the Rest sample (90%) the majority
of companies operated with a labor cost-operating cost ratio of less than 20%

4 In the case of the respondents participating in the already referred (Farkas-Poór-Karoliny-2007) 2005 Cranet
surveys – that involved not only MNCs – the average organizational labor cost ratio in Hungary was 28% that was
right in the middle of the 19-38% band calculated in the six Central Eastern European countries examined. The
country with the highest average ratio (64%) within the entire sample was the Netherlands.

15. Table: Labor cost in % of the operating cost
2008
Labor cost in
% of the
operating
cost
Under
5 %
5-
10%
11-
20%
21-
30%
31-
40%
41-
50%
Over
50%
Total
Total
Sample
Frequency 9 32 23 17 21 15 19 136
% distribution 6,6% 23,5% 16,9% 12,5% 15,4% 11,0% 14,0% 100,0%
Total
Sample
without
Hungary
Frequency 5 16 13 5 13 7 9 68
% distribution 7,4% 23,5% 19,1% 7,4% 19,1% 10,3% 13,2% 100,0%
% distribution 5,9% 23,5% 14,7% 17,6% 11,8% 11,8% 14,7% 100,0%
% distribution 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
% distribution 6,7% 26,7% 13,3% 6,7% 20,0% 13,3% 13,3% 100,0%
% distribution 5,3% 21,1% 15,8% 5,3% 26,3% 10,5% 15,8% 100,0%
% distribution 0,0% 0,0% 22,2% 22,2% 33,3% 11,1% 11,1% 100,0%
% distribution 0,0% 35,3% 23,5% 5,9% 11,8% 5,9% 17,6% 100,0%
% distribution 37,5% 25,0% 25,0% 0,0% 0,0% 12,5% 0,0% 100,0%
% distribution 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
2009
Labor cost
in % of the
operating
cost
Under
5%
5-
10%
11-
20%
21-
30%
31-
40%
41-
50%
Over
50%
Total
Total
Sample
Frequency 14 45 38 26 24 17 25 189
%
distribution
7,4% 23,8% 20,1% 13,8% 12,7% 9,0% 13,2% 100,0%
Total
Sample
without
Hungary
Frequency 11 27 24 13 15 8 14 112
%
distribution
9,8% 24,1% 21,4% 11,6% 13,4% 7,1% 12,5% 100,0%

2009
Labor cost
in % of the
operating
cost
Under
5%
5-
10%
11-
20%
21-
30%
31-
40%
41-
50%
Over
50%
Total
%
distribution
3,9% 23,4% 18,2% 16,9% 11,7% 11,7% 14,3% 100,0%
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
%
distribution
8,8% 23,5% 23,5% 8,8% 8,8% 8,8% 17,6% 100,0%
%
distribution
5,0% 20,0% 25,0% 15,0% 15,0% 0,0% 20,0% 100,0%
%
distribution
5,9% 11,8% 23,5% 23,5% 11,8% 17,6% 5,9% 100,0%
%
distribution
4,3% 26,1% 13,0% 13,0% 26,1% 4,3% 13,0% 100,0%
%
distribution
37,5% 25,0% 25,0% 0,0% 0,0% 12,5% 0,0% 100,0%
%
distribution
20,0% 50,0% 20,0% 0,0% 10,0% 0,0% 0,0% 100,0%
4.2.2 AGE DISTRIBUTION OF THE EMPLOYEES
One of the results of human resource management actions is the age distribution of the labor force. The
results of our survey in this respect do not confirm the common view that there is no room for employees
over 45 years of age in multinational companies as about one fifth of the employees of the subsidiaries
participating in the total sample fell within this age group for the year 2009. The proportion of employees
under 25 years of age was around 15% and the body consisted of the employees between 25-45 years
of age – with a percentage of 66%. The change over time from 2008 to 2009 saw an increase in the 25-
45 year old age group and small decrease in the other 2 age categories for the total sample. This
change over time was seen in all the samples except for Serbia where the Over 45 years old age
category increased from 2008 to 2009 and the number of employees in the other 2 age categories
decreased. No information was provided for the Polish and Rest samples for 2008 or 2009.
16. Table: Age group distribution of employees (%)
2008
Age groups Under 25
Between 25 and
45
Over 45 Total
Total 15,85 63,29 20,85 100,00

2008
Age groups Under 25
Between 25 and
45
Over 45 Total
Sample
Total
Sample
without
Hungary
16,55 67,20 18,29 102,04
Hungary 15,16 61,57 23,27 100,00
Poland 0,00 0,00 0,00 0,00
Estonia 22,21 62,43 15,36 100,00
Romania 19,61 67,90 19,27 106,78
Serbia 14,55 63,64 23,64 101,82
Slovakia 15,00 68,94 16,06 100,00
Croatia 7,00 74,11 18,89 100,00
Rest 0,00 0,00 0,00 0,00
2009
Age groups Under 25
Between 25 and
45
Over 45 Total
Total
Sample
14,44 66,05 19,50 100,00
Total
Sample
without
Hungary
13,99 69,86 16,15 100,00
Hungary 14,90 62,19 22,90 100,00
Poland 0,00 0,00 0,00 0,00
Estonia 17,93 68,57 13,50 100,00
Romania 16,05 72,36 11,59 100,00
Serbia 13,64 62,27 24,09 100,00
Slovakia 12,17 70,22 17,61 100,00
Croatia 6,89 74,33 18,78 100,00
Rest 0,00 0,00 0,00 0,00

Figure 7: Age group distribution of employees (%)

4.2.3 RELATIVE WEIGHT OF THE TRAINING BUDGET
Literature considers the relative weight of the training budget (compared to the entire annual labor cost)
as an important indicator of modern and effective HR activity. In more than 73% of the companies
examined, the relative weight of the training budget was under 3% and only about one quarter of the
companies examined spent more than 3% of the annual labor budget on training employees in the total
sample for 2009.5 The overall total increased from 2008(156) to 2009 (253). A similar pattern can be
seen in the all the samples.
17. Table: Annual training budget in % of the entire annual labor cost
2008
Annual
training
budget in
% of the
entire
annual
labor cost
Under
1%
1- 2% 2- 3% 3- 5%
5-
7%
7-
10%
10 -
20%
Over
20%
Total
Total
Sample
Frequency 28 56 23 29 4 6 4 6 156
%
distribution
17,9% 35,9% 14,7% 18,6% 2,6% 3,8% 2,6% 3,8% 100,0%
Total
Sample
without
Hungary
Frequency 17 23 6 11 1 5 4 5 72
%
distribution
23,6% 31,9% 8,3% 15,3% 1,4% 6,9% 5,6% 6,9% 100,0%

5 The global average of this indicator calculated using the formerly mentioned Cranet international comparative HR database
was 3.36%, the Eastern European index was 3.15% and the Hungarian 3.54% (Karoliny-Poór, 2010).

2008
Annual
training
budget in
% of the
entire
annual
labor cost
Under
1%
1- 2% 2- 3% 3- 5%
5-
7%
7-
10%
10 -
20%
Over
20%
Total
Hungary Frequency 11 33 17 18 3 1 0 1 84
%
distribution
13,1% 39,3% 20,2% 21,4% 3,6% 1,2% 0,0% 1,2% 100,0%
Poland Frequency 0 0 0 0 0 0 0 0 0
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
Estonia Frequency 2 4 2 5 1 0 0 2 16
%
distribution
12,5% 25,0% 12,5% 31,3% 6,3% 0,0% 0,0% 12,5% 100,0%
Romania Frequency 7 6 1 2 0 1 1 1 19
%
distribution
36,8% 31,6% 5,3% 10,5% 0,0% 5,3% 5,3% 5,3% 100,0%
Serbia Frequency 0 4 1 1 0 1 2 0 9
%
distribution
0,0% 44,4% 11,1% 11,1% 0,0% 11,1% 22,2% 0,0% 100,0%
Slovakia Frequency 5 4 1 2 0 3 1 2 18
%
distribution
27,8% 22,2% 5,6% 11,1% 0,0% 16,7% 5,6% 11,1% 100,0%
Croatia Frequency 3 5 1 1 0 0 0 0 10
%
distribution
30,0% 50,0% 10,0% 10,0% 0,0% 0,0% 0,0% 0,0% 100,0%
Rest Frequency 0 0 0 0 0 0 0 0 0
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
2009
Annual
training
budget in
% of the
entire
annual
labor cost
Under
1 %
1-2 % 2-3 % 3-5 %
5-7
%
7-10
%
10 -
20 %
Over
20 %
Total
Total
Sample
Frequency 30 128 58 44 5 19 4 5 293
%
distribution
10.2% 43.7% 19.8% 15.0% 1.7% 6.5% 1.4% 1.7% 100.0%
Total
Sample
without
Hungary
Frequency 20 92 38 28 2 16 4 4 204

2009
Annual
training
budget in
% of the
entire
annual
labor cost
Under
1 %
1-2 % 2-3 % 3-5 %
5-7
%
7-10
%
10 -
20 %
Over
20 %
Total
%
distribution
9.8% 45.1% 18.6% 13.7% 1.0% 7.8% 2.0% 2.0% 100.0%
%
distribution
11.2% 40.4% 22.5% 18.0% 3.4% 3.4% 0.0% 1.1% 100.0%
%
distribution
7.7% 32.1% 35.9% 12.8% 1.3% 9.0% 0.0% 1.3% 100.0%
%
distribution
9.5% 40.5% 7.1% 26.2% 2.4% 9.5% 2.4% 2.4% 100.0%
%
distribution
30.4% 47.8% 8.7% 4.3% 0.0% 4.3% 0.0% 4.3% 100.0%
%
distribution
0.0% 55.6% 5.6% 5.6% 0.0% 16.7% 16.7% 0.0% 100.0%
%
distribution
9.1% 63.6% 9.1% 18.2% 0.0% 0.0% 0.0% 0.0% 100.0%
%
distribution
10.0% 80.0% 10.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%
Rest Frequency 0 7 1 1 0 1 0 1 11
%
distribution
0.0% 63.6% 9.1% 9.1% 0.0% 9.1% 0.0% 9.1% 100.0%
4.2.4 LEVEL OF FLUCTUATION
The level of fluctuation was under 10% in more than half of the subsidiaries participating in the total
sample for 2009 with many companies having barely measurable low values. On the other hand, nearly
one quarter of the respondents reported rather high values, between 10 and 20%. Moreover, we found
6.3% companies with levels of fluctuation higher than 30%.6 The total level of fluctuation increased from
2008 (146) to 2009 (158). The Estonian (21.4%), Serbian (36.4%), and Slovakian (27.8%) samples had
high (more than 20%) levels of fluctuation in 2009. This was seen in 2008 for these 3 countries as well.

6 An important characteristic of HR subsystems are the different fluctuation indices. These indices are calculated by means of dividing the
number of people who leave during the year by the average number of staff. According to the conservative approach, the cost of an
average employee leaving amounts to 1.5 times their annual wage cost (Boudreau, 2010). However, it is important to see that different
people’s leaving have different consequences. If a key employee leaves the company, it has a much larger impact compared to a simple
employee leaving.

18. Table: Fluctuation rate (%)
2008
The level
of
fluctuation
Under
1%
1- 3% 3- 5%
5-
10%
10-
20%
20-
30%
30-
40%
Over
40%
Total
Total
Sample
Frequency 18 14 16 37 33 10 5 13 146
%
distribution
12,3% 9,6% 11,0% 25,3% 22,6% 6,8% 3,4% 8,9% 100,0%
Total
Sample
without
Hungary
Frequency 13 7 8 14 14 8 2 7 73
%
distribution
17,8% 9,6% 11,0% 19,2% 19,2% 11,0% 2,7% 9,6% 100,0%
%
distribution
6,8% 9,6% 11,0% 31,5% 26,0% 2,7% 4,1% 8,2% 100,0%
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
%
distribution
14,3% 7,1% 14,3% 14,3% 14,3% 7,1% 7,1% 21,4% 100,0%
Romani
a
Frequency 5 2 3 4 3 0 0 2 19
%
distribution
26,3% 10,5% 15,8% 21,1% 15,8% 0,0% 0,0% 10,5% 100,0%
%
distribution
20,0% 0,0% 10,0% 10,0% 30,0% 20,0% 10,0% 0,0% 100,0%
%
distribution
0,0% 11,1% 5,6% 27,8% 16,7% 27,8% 0,0% 11,1% 100,0%
%
distribution
33,3% 16,7% 8,3% 16,7% 25,0% 0,0% 0,0% 0,0% 100,0%
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
2009
The level
of
fluctuation
Under
1%
1- 3% 3- 5%
5-
10%
10-
20%
20-
30%
30-
40%
Over
40%
Total
Total
Sample
Frequency 19 17 16 40 40 16 3 7 158

2009
The level
of
fluctuation
Under
1%
1- 3% 3- 5%
5-
10%
10-
20%
20-
30%
30-
40%
Over
40%
Total
%
distribution
12,0% 10,8% 10,1% 25,3% 25,3% 10,1% 1,9% 4,4% 100,0%
Total
Sample
without
Hungary
Frequency 10 7 7 17 17 11 2 4 75
%
distribution
13,3% 9,3% 9,3% 22,7% 22,7% 14,7% 2,7% 5,3% 100,0%
%
distribution
10,8% 12,0% 10,8% 27,7% 27,7% 6,0% 1,2% 3,6% 100,0%
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
%
distribution
21,4% 14,3% 0,0% 35,7% 7,1% 14,3% 0,0% 7,1% 100,0%
%
distribution
18,2% 4,5% 13,6% 13,6% 31,8% 13,6% 4,5% 0,0% 100,0%
%
distribution
18,2% 0,0% 9,1% 18,2% 18,2% 18,2% 9,1% 9,1% 100,0%
%
distribution
0,0% 11,1% 16,7% 16,7% 27,8% 16,7% 0,0%
11,1
%
100,0%
%
distribution
11,1% 11,1% 0,0% 44,4% 22,2% 11,1% 0,0% 0,0% 100,0%
%
distribution
0,0% 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0%
4.2.5 TIME LOST DUE TO ABSENCE/SICKNESS
The average number of days lost annually due to absence was under 5 in approximately 30% of the
respondent companies in the total sample for 2009. The most often chosen category (by almost 50% of
the subsidiaries) was the 5-20 days. A large number (10) of companies reported an average of 10-20
days. At the same time, we had several respondents (7.5%) who reported an average of more than 40
days of absence. The Polish sample in 2009 had a high number (63.6%) of subsidiaries with more than
20 days of absence. The distribution of frequency for sick leave can be highly influenced by national
legislation. For instance, in the case of Hungary the maximum number of days of sick leave per year is
15 days. In 2008 and in 2009 the nearly half of the subsidiaries in the Hungarian reported the number of
sick days to be between 5 to 20 days.

19. Table: The average days absent per employee per annum
2008
Absence /
sick leave
Less
than 1
day
1-3
days
3-5
days
5-10
days
10-20
days
20-30
days
30-40
days
More
than
40
days
Total
Total
Sample
Frequency 8 17 27 58 27 7 6 4 154
%
distribution
5,2% 11,0% 17,5% 37,7% 17,5% 4,5% 3,9% 2,6% 100,0%
Total
Sample
without
Hungary
Frequency 3 7 11 33 14 5 2 2 77
%
distribution
3,9% 9,1% 14,3% 42,9% 18,2% 6,5% 2,6% 2,6% 100,0%
%
distribution
6,5% 13,0% 20,8% 32,5% 16,9% 2,6% 5,2% 2,6% 100,0%
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
%
distribution
6,7% 0,0% 6,7% 53,3% 33,3% 0,0% 0,0% 0,0% 100,0%
%
distribution
10,5% 0,0% 10,5% 42,1% 21,1% 5,3% 5,3% 5,3% 100,0%
%
distribution
0,0% 20,0% 10,0% 20,0% 10,0% 30,0% 10,0% 0,0% 100,0%
%
distribution
0,0% 13,6% 22,7% 40,9% 13,6% 4,5% 0,0% 4,5% 100,0%
%
distribution
0,0% 18,2% 18,2% 54,5% 9,1% 0,0% 0,0% 0,0% 100,0%
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%
2009
Absence /
sick leave
Less
than 1
day
1-3
days
3-5
days
5-10
days
10-20
days
20-30
days
30-40
days
More
than 40
days
Total
Total
Sample
Frequency 7 22 30 54 34 18 7 14 186

2009
Absence /
sick leave
Less
than 1
day
1-3
days
3-5
days
5-10
days
10-20
days
20-30
days
30-40
days
More
than 40
days
Total
%
distribution
3,8% 11,8% 16,1% 29,0% 18,3% 9,7% 3,8% 7,5% 100,0%
Total
Sample
without
Hungary
Frequency 3 10 15 29 21 11 7 11 107
%
distribution
2,8% 9,3% 14,0% 27,1% 19,6% 10,3% 6,5% 10,3% 100,0%
%
distribution
5,1% 15,2% 19,0% 31,6% 16,5% 8,9% 0,0% 3,8% 100,0%
%
distribution
0,0% 9,1% 3,0% 6,1% 18,2% 21,2% 12,1% 30,3% 100,0%
%
distribution
6,7% 0,0% 20,0% 46,7% 26,7% 0,0% 0,0% 0,0% 100,0%
%
distribution
9,5% 0,0% 23,8% 38,1% 14,3% 4,8% 4,8% 4,8% 100,0%
%
distribution
0,0% 11,1% 11,1% 11,1% 22,2% 33,3% 11,1% 0,0% 100,0%
%
distribution
0,0% 22,2% 16,7% 27,8% 27,8% 0,0% 5,6% 0,0% 100,0%
%
distribution
0,0% 18,2% 18,2% 54,5% 9,1% 0,0% 0,0% 0,0% 100,0%
%
distribution
0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%

5 FOREIGN EXPATS AND THEIR ROLES
Usually two types of long-term emissaries are distinguished. The ones arriving from abroad from the
parent company or from a third country who are also called expatriates and the ones from the Hungarian
subsidiary appointed for a long-term deputation abroad at the parent company or subsidiaries operating
in other countries.7
! Over 70% of the subsidiaries participating in the total sample didn’t employ foreign expats in
non-managerial positions. In those few companies that employed foreign expats in non-
managerial positions permanently, the number of these expats was typically between 1 to
10 in nearly one quarter of the replies. Only eighteen out of three hundred and sixteen
respondents employed 11 or more such expats. In the Croatian sample almost all
subsidiaries did not employ expats (90.9% with no expats).
! The presence of expats employed in managerial positions is more significant, around 46.6%
of the respondents employed foreign expats in such positions in the period examined.
Where they were present, their number was typically between 1-3 (29%) but a few
respondents employed 11 or more expats (5.7%). The subsidiaries in the Estonian and
Romanian samples tended to employ less foreign expats than in the other samples (76.5%
and 63.6% respectively).
(Note: It is important to indicate that companies send an increasing number of emplyees abroad for a
short time, for different projects. Our survey did not cover this issue.)
20. Table: Number of foreign expats
In managerial position
Number
of expats
None
1
person
2-3
persons
4-5
persons
6-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
Total
Sample
Frequency 171 42 51 19 19 8 5 5 320
%
distribution
53,4% 13,1% 15,9% 5,9% 5,9% 2,5% 1,6% 1,6% 100,0%
Total
Sample
without
Hungary
Frequency 135 28 35 13 14 5 3 3 236
%
distribution
57,2% 11,9% 14,8% 5,5% 5,9% 2,1% 1,3% 1,3% 100,0%
%
distribution
42,9% 16,7% 19,0% 7,1% 6,0% 3,6% 2,4% 2,4% 100,0%
%
distribution
54,6% 11,3% 15,5% 5,2% 5,2% 5,2% 2,1% 1,0% 100,0%
%
distribution
76,5% 9,8% 5,9% 5,9% 2,0% 0,0% 0,0% 0,0% 100,0%

7 After Perlmutter (1969), multinational companies following the four personnel straregies have different priorities in
their selection and recruitment policies. The company can follow an ethnocentric, polycentric, regiocentric or
geocentric selection mechanism. In the ethnocentric orientation, key positions of the local company are held by
professionals from the parent company. In polycentric companies, local key positions are held by locals but their
promotion to higher positions is very limited. In companies following the regiocentric selection mechanism, locals
can hold key positions not only in the subsidiary but also in the center coordinating the management of the region.
In companies follwing the geocentric selection mechanism, locals can obtain position even in the top management
of the company (Poór, 2009).

Number
of expats
None
1
person
2-3
persons
4-5
persons
6-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
%
distribution
63,6% 9,1% 9,1% 0,0% 9,1% 0,0% 4,5% 4,5% 100,0%
%
distribution
40,0% 10,0% 25,0% 5,0% 15,0% 0,0% 0,0% 5,0% 100,0%
%
distribution
37,5% 16,7% 25,0% 12,5% 8,3% 0,0% 0,0% 0,0% 100,0%
%
distribution
54,5% 9,1% 27,3% 0,0% 9,1% 0,0% 0,0% 0,0% 100,0%
Rest Frequency 6 3 1 1 0 0 0 0 11
%
distribution
54,5% 27,3% 9,1% 9,1% 0,0% 0,0% 0,0% 0,0% 100,0%
In non-managerial position
Number
of expats
None
1
person
2-3
persons
4-5
persons
6-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
Total
Sample Frequency 223 25 23 14 13 7 3 8 316
%
distribution 70,6% 7,9% 7,3% 4,4% 4,1% 2,2% 0,9% 2,5% 100,0%
Total
Sample
without
%
distribution 68,2% 7,7% 8,2% 5,6% 3,9% 2,6% 0,9% 3,0% 100,0%
%
distribution 77,1% 8,4% 4,8% 1,2% 4,8% 1,2% 1,2% 1,2% 100,0%
%
distribution 71,3% 4,3% 8,5% 4,3% 3,2% 4,3% 1,1% 3,2% 100,0%
%
distribution 66,7% 13,7% 7,8% 2,0% 2,0% 2,0% 2,0% 3,9% 100,0%
%
distribution 77,3% 9,1% 0,0% 4,5% 0,0% 0,0% 0,0% 9,1% 100,0%
%
distribution 65,0% 5,0% 10,0% 10,0% 10,0% 0,0% 0,0% 0,0% 100,0%
%
distribution 50,0% 12,5% 8,3% 20,8% 4,2% 4,2% 0,0% 0,0% 100,0%
%
distribution 90,9% 0,0% 9,1% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0%
Rest Frequency 6 1 2 0 2 0 0 0 11
%
distribution 54,5% 9,1% 18,2% 0,0% 18,2% 0,0% 0,0% 0,0% 100,0%

In the majority of the samples the split between the positions of foreign expats in manager and non-
manager positions is nearly equal. The exceptions being in the Estonian sample where foreign expats
are more likely to be non-managers (83%), the Serbian sample where the foreign expats are more likely
to occupy manager positions (84.4%), the Croatian sample where the foreign expats are more likely to
occupy manager positions (83.3%), and the Rest sample where the employment of foreign expats are
seen to be in non-manager positions.
21. Table: Positions of foreign expats
Manager Non-manager Total
Total Sample 54,7% 45,3% 100,0%
Total Sample
without Hungary
50,0% 50,0% 100,0%
Hungary 68,4% 31,6% 100,0%
Poland 47,8% 52,2% 100,0%
Estonia 17,0% 83,0% 100,0%
Romania 51,5% 48,5% 100,0%
Serbia 84,4% 15,6% 100,0%
Slovakia 51,0% 49,0% 100,0%
Croatia 83,3% 16,7% 100,0%
Rest 26,5% 73,5% 100,0%
Over sixty-seven percent of the responding organizations in the total sample had foreign expats from the
parent company. The other 32.3% of foreign expats came to the subsidiaries in the total sample from
countries different from the country of the parent company. As can be seen in the table below, the
subsidiaries in the Polish (75.3%), Romanian (72.8%), and Serbian (82.5%) samples had higher levels of
foreign expats coming from the parent company then the other samples.
22. Table: Country of origin of foreign expats
Mother country Other countries Total
Total Sample 67,7% 32,3% 100,0%
Total Sample
without Hungary
69,3% 30,7% 100,0%
Hungary 63,8% 36,2% 100,0%
Poland 75,3% 24,7% 100,0%
Estonia 59,8% 40,2% 100,0%
Romania 72,8% 27,2% 100,0%
Serbia 82,5% 17,5% 100,0%
Slovakia 52,5% 47,5% 100,0%
Croatia 65,0% 35,0% 100,0%
Rest 67,3% 32,8% 100,0%

5.1 LOCAL EXPATS
Below we ouline how typically and to what positions local expats were sent to foreign companeis of
MNCs.
23. Table: Number and positions of Local expats
Number of
Local expats
None 1 person
2-3
persons
4-5
persons
6-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
Total
Sample
Frequency 240 25 25 15 9 3 0 2 319
% distribution 75,2% 7,8% 7,8% 4,7% 2,8% 0,9% 0,0% 0,6% 100,0%
Total
Sample
without
Hungary
Frequency 188 14 16 8 7 2 0 0 235
% distribution 80,0% 6,0% 6,8% 3,4% 3,0% 0,9% 0,0% 0,0% 100,0%
% distribution 61,9% 13,1% 10,7% 8,3% 2,4% 1,2% 0,0% 2,4% 100,0%
% distribution 75,3% 7,2% 6,2% 4,1% 5,2% 2,1% 0,0% 0,0% 100,0%
% distribution 90,2% 3,9% 2,0% 3,9% 0,0% 0,0% 0,0% 0,0% 100,0%
% distribution 81,8% 4,5% 0,0% 4,5% 9,1% 0,0% 0,0% 0,0% 100,0%
% distribution 80,0% 5,0% 15,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0%
% distribution 69,6% 4,3% 21,7% 4,3% 0,0% 0,0% 0,0% 0,0% 100,0%
% distribution 90,9% 9,1% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0%
Rest Frequency 9 1 1 0 0 0 0 0 11
% distribution 81,8% 9,1% 9,1% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0%
Number of
Local expats
None
1
person
2-3
persons
4-5
persons
6-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
Total Sample Frequency 228 24 30 13 14 1 6 4 320
% distribution 71,3% 7,5% 9,4% 4,1% 4,4% 0,3% 1,9% 1,3% 100,0%
Total Sample
without
Hungary
Frequency 176 14 20 7 11 0 6 2 236
% distribution 74,6% 5,9% 8,5% 3,0% 4,7% 0,0% 2,5% 0,8% 100,0%
% distribution 61,9% 11,9% 11,9% 7,1% 3,6% 1,2% 0,0% 2,4% 100,0%

Number of
Local expats
None
1
person
2-3
persons
4-5
persons
6-10
persons
11-15
persons
16-20
persons
Over 20
persons
Total
% distribution 68,0% 7,2% 8,2% 4,1% 8,2% 0,0% 2,1% 2,1% 100,0%
% distribution 84,3% 7,8% 7,8% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0%
% distribution 86,4% 0,0% 0,0% 4,5% 0,0% 0,0% 9,1% 0,0% 100,0%
% distribution 80,0% 0,0% 15,0% 5,0% 0,0% 0,0% 0,0% 0,0% 100,0%
% distribution 66,7% 0,0% 12,5% 4,2% 8,3% 0,0% 8,3% 0,0% 100,0%
% distribution 90,9% 9,1% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0%
Rest Frequency 6 2 2 0 1 0 0 0 11
% distribution 54,5% 18,2% 18,2% 0,0% 9,1% 0,0% 0,0% 0,0% 100,0%
! Although more respondents sent than received employees abroad to non-managerial
positions, there was no such foreign deputation in more than 70% of the respondents in the
total sample (71.3% for non-managerial positions and 75.2% for managerial positions).
Companies that sent employees abroad sent usually 1-5 employees – 20.3% for managerial
positions and 21% for non-managerial positions.
! The proportions of companies not sending employees to managerial positions and to non-
managerial positions can be seen to be highest in 4 countries Croatia, Estonia, Romania,
and Serbia with the proportions being over 80% and in the case of Croatia reaching nearly
91%.
! If employees are sent abroad the typical number of employees were between 1 to 3
persons.

6 THE OPERATION OF THE HR DEPARTMENT
6.1 THE RELATIONSHIP BETWEEN HEADQUARTERS AND LOCAL HR
We found several different function sharing practices among the companies examined.8
! However, the typical solution that was implemented by over one quarter of the respondents
in the total sample was that the HR department of the company’s headquarters lays down
general guidelines and provides a standard framework for the work of HR departments of
the subsidiaries and requires information and reporting from them. While 20% of the
companies’ headquarters performed the auditor’s role.
! In addition, in the case of almost 20% of the companies the headquarters was responsible
for providing resources and advice when requested.
! Around 15% of the respondents marked that the headquarters provided the detailed HR
model, policies, procedures, and rules.
! On the other hand, about 15% of the HR departments of the responding subsidiaries
reported getting hands-offs treatment, almost complete freedom from the headquarters and
decentralized HR activity. While in almost 6% of companies the headquarters provided
central control.
! There are no major deviations from the distribution in the total sample by any of the
individual country samples.
24. Table: Typical functions of the HQ HR
Functions
Hands-
off,
provide
complete
freedom
Provide
resources
and advice
when
requested
Provide
general
guidelines
and
framework
for actions
Request
information
and
reports –
auditor’s
role
Provide
detailed
HR model,
policies,
procedures
and rules
Source of
all
remotely
significant
HR
decisions
Other Total
Total Sample
Frequency
of “yes”
answers
92 135 179 149 107 40 8 710
%
distribution
13,0% 19,0% 25,2% 21,0% 15,1% 5,6% 1,1% 100,0%
Total Sample
without
Hungary
Frequency
of “yes”
answers
73 111 118 95 71 33 7 508
%
distribution
14,4% 21,9% 23,2% 18,7% 14,0% 6,5% 1,4% 100,0%
Hungary
Frequency
of “yes”
answers
19 24 61 54 36 7 1 202
%
distribution
9,4% 11,9% 30,2% 26,7% 17,8% 3,5% 0,5% 100,0%
Poland
Frequency
of “yes”
answers
41 42 46 40 26 18 1 214
%
distribution
19,2% 19,6% 21,5% 18,7% 12,1% 8,4% 0,5% 100,0%

8 Taylor et al. (1966) describe the relationship between the subsidiaries and the parent company with the following
three basic systems of relations:
In the exportive system of relations, HR systems developed in the parent company are adopted without changes.
In the adaptive system of relations, local subsidiaries adapt the HR systems adopted from the parent company
according to their local needs.
In the integrative system of relations, all good and applicable solutions are attempted to be spread and
implemented in all units of the company regardless of the origin of the HR system.
Lawler (2006) concluded from his research conducted among American subsidiaries operating in Asia and Europe
that the most dominant deciding factor in the adoptation and adaptation of HR systems is the size of local
companies. The question is reasonable: which solution should be applied in a certain case? The mentioned
authors say that the system to be implemented depends on the sum of the impacts of internal and external factors
that form, influence the organization. In certain cases the national culture of the host country and the legal,
regulatory environment are considered influencing factors.

Functions
Hands-
off,
provide
complete
freedom
Provide
resources
and advice
when
requested
Provide
general
guidelines
and
framework
for actions
Request
information
and
reports –
auditor’s
role
Provide
detailed
HR model,
policies,
procedures
and rules
Source of
all
remotely
significant
HR
decisions
Other Total
Estonia
Frequency
of “yes”
answers
6 27 26 17 19 5 2 102
%
distribution
5,9% 26,5% 25,5% 16,7% 18,6% 4,9% 2,0% 100,0%
Romania
Frequency
of “yes”
answers
1 8 10 10 8 1 0 38
%
distribution
2,6% 21,1% 26,3% 26,3% 21,1% 2,6% 0,0% 100,0%
Serbia
Frequency
of “yes”
answers
7 12 14 8 5 6 1 53
%
distribution
13,2% 22,6% 26,4% 15,1% 9,4% 11,3% 1,9% 100,0%
Slovakia
Frequency
of “yes”
answers
11 12 9 10 9 2 1 54
%
distribution
20,4% 22,2% 16,7% 18,5% 16,7% 3,7% 1,9% 100,0%
Croatia
Frequency
of “yes”
answers
4 8 8 6 3 0 1 30
%
distribution
13,3% 26,7% 26,7% 20,0% 10,0% 0,0% 3,3% 100,0%
Rest
Frequency
of “yes”
answers
3 2 5 4 1 1 1 17
%
distribution
17,6% 11,8% 29,4% 23,5% 5,9% 5,9% 5,9% 100,0%
Figure 8: Typical functions of the HQ HR

6.2 CHANGES IN THE IMPORTANCE OF HR FUNCTIONS
Human resource planning was first in the ranking of HR areas considered most critical in the period
examined, being a little ahead of employee communication issues in the total sample. In the Hungarian
and Croatian samples compensation and benefits was indicated as the most critical areas of HR, while in
the Polish sample the most critical area of HR is recruitment and selection.
The respondents regarded Industrial labor relations as the least critical area of their work, followed by
recruitment and selection as the next least critical area in the total sample. The responding subsidiaries
deemed training and development, and talent management as the next least critical areas. In the
Romanian and Croatian samples the least critical area of HR work was talent management, while in the
Serbian sample the least critical areas were employee communication and industrial labor relations.
25. Table: Critical areas of HR (on a 1 to 5 scale, on average)
(Explanation: 1= critical => 5 =not critical)
The average of the answers
The ranking of the areas of HRM critical in 2009
Employee
communication
Compensation
and benefits
Human
resource
planning
Talent
management
Performance
evaluation
Training and
development
Industrial-
labor
relations
Recruitment
and
selection
Total
Sample
2,68 2,74 2,62 2,95 2,89 2,98 3,42 3,02
Total
Sample
without
Hungary
2,76 2,86 2,66 3,05 2,89 2,92 3,40 2,89
Hungary 2,48 2,42 2,52 2,71 2,87 3,15 3,46 3,36
Poland 2,70 2,81 3,01 2,88 2,84 2,79 3,49 2,67
Estonia 2,45 2,93 2,20 2,86 2,80 3,02 3,58 3,20
Romania 2,68 3,35 3,11 3,53 3,25 3,26 3,00 3,25
Serbia 3,50 3,25 2,55 3,45 3,15 3,15 3,50 2,95
Slovakia 2,96 3,00 2,29 3,25 3,17 3,25 3,58 3,13
Croatia 2,82 1,36 2,73 3,18 1,91 2,18 2,73 2,55
Rest 2,73 2,64 1,91 2,91 3,00 2,55 2,82 2,45
6.3 TYPICAL HR COMPETENCIES FOR SUCCESS
From the somewhat completed list of HRM competency areas identified by one of the most knows HR
gurus, Dave Ulrich et al. in 2009, the respondents in the total sample considered the following three to
be the most important:
! teamwork (13.2%),
! change management (13.1%),
! personal credibility (12.5%).
However in the Hungarian, Romanian, Serbian, and Rest samples personal credibility are the most
important criteria for HR competency success. Also, in the Romanian subsidiaries strategic contribution
is the second most critical area of HR competency success.

Quick decision making and business partnerships were followed, in respect of importance, by knowledge
sharing, strategic contribution and the knowledge of foreign languages. In the opinion of the respondents
of the total sample, other reasons and the use of HR information systems ranked last among very
important HR competencies in their companies in the period examined.
26. Table: The importance of the methods of personal competency development in HR
Total Sample
Hungary
Hungary Poland Estonia
Very important Very important Very important Very important Very important
Ranking of key
competencies
Frequency
%
distribution
Frequency
%
distribution
Frequency
%
distribution
Frequency
%
distribution
Frequency
%
distribution
1. Personal
credibility
(effectiveness,
efficient
connections,
communication
skills)
173 12,5% 105 11,0% 68 15,7% 31 8,2% 22 10,9%
2. Change
management
181 13,1% 125 13,1% 56 13,0% 52 13,7% 30 14,9%
3. Business
partnership
144 10,4% 93 9,7% 51 11,8% 39 10,3% 20 9,9%
4. Quick
decision
making
163 11,8% 115 12,1% 48 11,1% 51 13,4% 22 10,9%
5. Teamwork 183 13,2% 135 14,2% 48 11,1% 58 15,3% 28 13,9%
6. Strategic
contribution
(culture
management,
quick changes,
strategic
decision
making)
113 8,2% 71 7,4% 42 9,7% 25 6,6% 13 6,4%
7. HR services
(recruitment-
selection,
training,
performance
ecaluation, HR
measurement,
etc.)
98 7,1% 60 6,3% 38 8,8% 22 5,8% 15 7,4%
8. Knowledge
of foreign
languages
113 8,2% 79 8,3% 34 7,9% 31 8,2% 15 7,4%
9. Knowledge
sharing
119 8,6% 97 10,2% 22 5,1% 44 11,6% 22 10,9%
10. Use of
HRMIS (IT)
85 6,1% 68 7,1% 17 3,9% 27 7,1% 15 7,4%
11. Other 14 1,0% 6 0,6% 8 1,9% 0 0,0% 0 0,0%
Total 1386 100,0% 954 100,0% 432 100,0% 380 100,0% 202 100,0%

Romania Serbia Slovakia Croatia Rest
Very important Very important Very important Very important Very important
Ranking of key
competencies
Frequency
%
distribution
Frequency
%
distribution
Frequency
%
distribution
Frequency % distribution Frequency % distribution
1. Personal
credibility(effecti
veness, efficient
connections,
communication
skills)
18 18,0% 14 14,4% 9 10,6% 3 7,5% 8 16,0%
2. Change
management
8 8,0% 12 12,4% 9 10,6% 7 17,5% 7 14,0%
3. Business
partnership
5 5,0% 7 7,2% 13 15,3% 5 12,5% 4 8,0%
4. Quick
decision making
10 10,0% 11 11,3% 10 11,8% 4 10,0% 7 14,0%
5. Teamwork 14 14,0% 11 11,3% 11 12,9% 4 10,0% 9 18,0%
6. Strategic
contribution
(culture
management,
quick changes,
strategic
decision making)
18 18,0% 6 6,2% 5 5,9% 1 2,5% 3 6,0%
7. HR services
(recruitment-
selection,
training,
performance
ecaluation, HR
measurement,
etc.)
5 5,0% 7 7,2% 4 4,7% 5 12,5% 2 4,0%
8. Knowledge of
foreign
languages
7 7,0% 7 7,2% 10 11,8% 3 7,5% 6 12,0%
9. Knowledge
sharing
5 5,0% 9 9,3% 9 10,6% 6 15,0% 2 4,0%
10. Use of
HRMIS (IT)
10 10,0% 8 8,2% 5 5,9% 2 5,0% 1 2,0%
11. Other 0 0,0% 5 5,2% 0 0,0% 0 0,0% 1 2,0%
Total 100 100,0% 97 100,0% 85 100,0% 40 100,0% 50 100,0%
6.4 PRIMARY RESPONSIBILITY OF DECISION MAKING IN THE MAIN FUNCTIONS OF
HR
Our current survey confirms the finding also established in other studies (Cranet, 2006 and Karoliny et
al. 2009) that members of the management hierarchy have larger responsibility or control in some HR
decisions in consultation with the HR department in the total sample. Some responsibility is taken by the
local line management in the area of performance evaluation. The local HR deparment was indicated to
have responsibility in industrial labor relations and HRMS/IT responsibilities. It was found to be less likely
that the primary decision making was made by the local HR in consultation with local line management.
In some samples such as the Romanian and Croatian sample the local line management handled more
of the responsibilities than the other groups.

27. Table: Responsibility of decision making in key functions of HR
Key functions
of HR
Local line
management
(mgt.)
Primarily
local line
mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Local line
management
(mgt.)
Primarily local
line mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Human
Resource
Planning
81 114 52 26 70 72 28 20
Recruitment 85 90 82 53 79 64 51 33
Selection 63 98 67 27 55 53 43 22
Performance
Evaluation
103 85 47 23 70 52 31 22
Training and
Development
72 117 91 32 61 84 57 27
Compensation
and Benefits
84 117 71 39 72 80 47 29
Industrial-
Labour
Relations
66 58 66 99 61 43 44 59
Employee
Communication
67 81 61 50 59 51 36 30
HRMS/IT 54 64 34 97 46 52 21 50
Other 16 24 25 32 12 21 17 26
Hungary Poland
Key functions
of HR
Local line
management
(mgt.)
Primarily
local line
mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Local line
management
(mgt.)
Primarily local
line mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Human
Resource
Planning
11 42 24 6 22 16 10 5
Recruitment 6 26 31 20 37 34 15 5
Selection 8 45 24 5 10 13 9 6
Performance
Evaluation 33
33 16 1
11
11 12 5
Training and
Development 11
33 34 5
21
39 22 10
Compensation
and Benefits 12
37 24 10
21
37 20 15
Industrial-
Labour
Relations 5
15 22 40
14
20 14 24
Employee
Communication 8
30 25 20
13
16 3 8
HRMS/IT 8 12 13 47 12 13 2 8
Other 4 3 8 6 1 4 1 1

Estonia Romania
Key functions
of HR
Local line
management
(mgt.)
Primarily
local line
mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Local line
management
(mgt.)
Primarily local
line mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Human
Resource
Planning
22 19 4 5 8 5 5 3
Recruitment 21 8 14 7 6 3 6 5
Selection 19 14 10 5 9 5 3 4
Performance
Evaluation 29
13 5 3
8
4 4 4
Training and
Development 18
17 11 4
7
5 7 2
Compensation
and Benefits 23
14 6 7
8
5 6 1
Industrial-
Labour
Relations 25
6 7 10
6
5 6 4
Employee
Communication 24
12 8 6
7
3 7 3
HRMS/IT 17 14 3 15 7 4 4 4
Other 4 5 0 3 2 1 1 5
Serbia Slovakia
Key functions
of HR
Local line
management
(mgt.)
Primarily
local line
mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Local line
management
(mgt.)
Primarily local
line mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Human
Resource
Planning
5 9 3 3 9 12 3 0
Recruitment 5 3 9 3 6 10 3 5
Selection 3 4 10 3 9 10 4 1
Performance
Evaluation 4
6 5 5
10
11 1 2
Training and
Development 4
6 8 2
6
11 4 3
Compensation
and Benefits 6
6 5 2
11
12 0 1
Industrial-
Labour
Relations 5
5 5 5
8
7 6 3
Employee
Communication 5
6 8 1
5
11 5 3
HRMS/IT 2 5 5 8 5 9 6 4
Other 1 1 9 9 3 8 3 2

Croatia Rest
Key functions
of HR
Local line
management
(mgt.)
Primarily
local line
mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Local line
management
(mgt.)
Primarily local
line mgt. but in
consultation
with the HR
department
Primarily
local HR
department
but in
consultation
with local
line mgt.
Local HR
department
Human
Resource
Planning
4 4 2 1 0 7 1 3
Recruitment 4 3 1 3 0 3 3 5
Selection 4 2 2 3 1 5 5 0
Performance
Evaluation
5 2 3 1 3 5 1 2
Training and
Development
4 2 2 3 1 4 3 3
Compensation
and Benefits
3 1 6 1 0 5 4 2
Industrial-
Labour
Relations
3 0 1 7 0 0 5 6
Employee
Communication
4 0 3 4 1 3 2 5
HRMS/IT 3 3 1 4 0 4 0 7
Other 1 0 1 1 0 2 2 5
6.5 THE ROLE OF EXTERNAL HR SERVICE PROVIDERS
Nowadays human resources are managed in many organizations with the involvement of external
service providers. Besides traditional HR consultants, an increasing number of service providers have
entered the market offering new services (e.g. labor leasing, outsourcing, interim managers, etc.).
External service providers were most often used in training and development with regards to the key HR
functions as reported by the respondents in the total sample. They were also often involved in HRMS/IT
functions and in the area of compensation and benefits. Almost none of the companies used the help of
external service providers in human resource planning and in performance evaluation. The role and use
of external service providers by the subsidiaries in the total sample were indicated to not have change. In
the Hungarian sample after the key function of training and development, the next important functions
were recruitment, compensation and benefits, and selection.
28. Table: Role and use of external service providers in the different key functions of HR
Key functions
of HR
Increased Decreased Same
External
providers
not used
External
providers
not used
Human
Resource
Planning
21 23 41 220 20 20 38 143
Recruitment 43 71 73 126 34 40 54 102
Selection 50 47 79 137 43 23 61 103
Performance
Evaluation
41 9 63 199 37 7 56 129

Key functions
of HR
External
providers
not used
External
providers
not used
Training and
Development
74 61 99 78 62 38 62 67
Compensation
and Benefits
35 34 91 152 27 26 56 120
Industrial-
Labour
Relations
35 20 85 172 27 18 64 120
Employee
Communication
41 12 74 186 37 7 53 133
HRMS/IT 39 13 79 150 29 10 50 109
Other 14 7 35 77 11 6 25 66
Hungary Poland
Key functions
of HR
External
providers
not used
External
providers
not used
Human
Resource
Planning
1 3 3 77 9 5 13 57
Recruitment 9 31 19 24 18 12 20 43
Selection 7 24 18 34 22 8 29 35
Performance
Evaluation
4 2 7 70 15 1 26 52
Training and
Development
12 23 37 11 30 8 20 35
Compensation
and Benefits
8 8 35 32 18 7 29 39
Industrial-
Labour
Relations
8 2 21 52 11 6 23 53
Employee
Communication
4 5 21 53 13 2 27 51
HRMS/IT 10 3 29 41 7 1 7 47
Other 3 1 10 11 10 2 9 33
Estonia Romania
Key functions
of HR
External
providers
not used
External
providers
not used
Human
Resource
Planning
5 4 10 30 2 5 4 11
Recruitment 9 12 14 14 3 5 3 11
Selection 8 5 9 26 5 2 6 9
Performance
Evaluation
8 3 8 30 5 1 6 9
Training and
Development
9 12 14 14 6 7 5 4
Compensation
and Benefits
2 5 7 35 4 6 5 7

Estonia Romania
Key functions
of HR
External
providers
not used
External
providers
not used
Industrial-
Labour
Relations
5 3 10 30 3 1 11 7
Employee
Communication
9 0 5 35 6 0 11 5
HRMS/IT 10 2 15 22 5 2 8 7
Other 1 0 2 7 0 0 4 4
Serbia Slovakia
Key functions
of HR
External
providers
not used
External
providers
not used
Human
Resource
Planning
2 1 1 16 0 4 7 13
Recruitment 2 3 5 10 1 4 6 13
Selection 2 3 6 9 2 4 4 14
Performance
Evaluation
4 1 5 10 2 1 8 12
Training and
Development
5 2 7 6 4 6 7 6
Compensation
and Benefits
0 3 6 11 0 5 5 13
Industrial-
Labour
Relations
1 1 6 12 1 7 9 7
Employee
Communication
2 1 2 15 5 4 4 11
HRMS/IT 2 1 4 13 2 3 10 8
Other 0 4 5 11 0 0 2 6
Croatia Rest
Key functions
of HR
External
providers
not used
External
providers
not used
Human
Resource
Planning
0 0 1 10 2 1 2 6
Recruitment 0 1 2 8 1 3 4 3
Selection 0 1 3 7 4 0 4 3
Performance
Evaluation
0 0 1 10 3 0 2 6
Training and
Development
4 2 4 1 4 1 5 1
Compensation
and Benefits
0 0 1 10 3 0 3 5
Industrial-
Labour
Relations
1 0 1 9 5 0 4 2
Employee
Communication
0 0 1 10 2 0 3 6

Croatia Rest
Key functions
of HR
External
providers
not used
External
providers
not used
HRMS/IT 1 0 3 7 2 1 3 5
Other 0 0 0 5 0 0 3 0

7 KNOWLEDGE MANAGEMENT IN HR
Knowledge management means the management and sharing of the collective knowledge (know-how,
skills and intellectual skills) of an organization’s employees in an integrated way. In connection with the
practice of the indicated topic in the field of HR we examined the following three areas:
! methods of personal competency development in HR,
! enablers of HR knowledge flows,
! directions of HR knowledge flows.
7.1 PERSONAL COMPETENCY DEVELOPMENT IN HR
The respondents in the total sample found training at headquarters and cross-cultural training to be the
least important methods among the listed methods of personal competency development in the field of
HR and they thought that formal learning and mobility to play unimportant roles too. Mobility being either
mobility between parent and subsidiary or between subsidiaries.
Respondents ranked local training and informal training the most important methods among the
examined tools of personal HR competency development in their companies in the period examined.
In the Hungarian sample cross-cultural training was found to be the least important method followed by
the two types of mobility with local training and informal training being the most important methods of
personal competency development in HR. In the Croatian sample local training and informal training
were indicated by companies to be the least important methods while the mobility categories and cross-
cultural training were the most important methods.
29. Table: The importance of the methods of personal competency development in HR
(on a 1-5 scale, on average)
Methods of
gaining
competencies
Local
training
Informal
learning
Formal
learning
Training
in HQ
Mobility
between parent
and subsidiary
Mobility
between
subsidiaries
Cross-
cultural
training
Other
Total Sample 2,9 2,9 3,2 3,3 3,2 3,2 3,3 2,9
Total Sample
without
Hungary
3,1 3,1 3,3 3,2 3,0 3,0 3,2 3,0
Hungary 2,4 2,4 2,7 3,3 3,7 3,8 3,9 2,6
Poland 3,7 3,2 3,7 3,2 3,0 2,7 2,9 2,7
Estonia 2,5 3,0 3,1 3,2 2,8 2,9 3,2 2,5
Romania 2,9 3,0 3,1 3,8 3,1 3,2 3,8 4,3
Serbia 2,9 3,3 3,3 3,0 3,0 3,7 3,4 3,3
Slovakia 2,0 2,7 2,7 3,0 2,8 3,3 3,6 3,6
Croatia 3,7 3,7 3,2 3,1 2,7 2,6 2,7 4,0
Rest 2,1 2,6 2,6 4,2 4,4 3,8 3,2 4,0

7.2 ENABLERS OF HR KNOWLEDGE FLOWS BETWEEN THE PARENT COMPANY
AND THE SUBSIDIARIES
In respect of the enablers of efficient knowledge flows, i.e. the transfer of knowledge about HR practices
and techniques, between the parent company and the subsidiary, the respondents considered the
content and kind of knowledge to be least important among the factors examined in the total sample
followed by the ability to transfer knowledge and form of knowledge transfer. The most important enabler
indicated in the total sample was the motivation to transfer knowledge. In the Polish and Croatian
samples all forms of HR knowledge transfer were indicated to be less critical than in the other samples.
30. Table: Enablers of HR knowledge transfer (on a 1-5 scale, on average)
Knowledge flow
enablers
Ability to
transfer
knowledge
Motivation to
transfer
knowledge
Form of
knowledge
transfer
Content/Kind of
knowledge
Total Sample 3,1 2,9 3,1 3,2
Total Sample
without Hungary
3,3 3,1 3,2 3,3
Hungary 2,5 2,6 2,7 3,0
Poland 3,9 3,7 3,7 3,7
Estonia 2,7 2,5 2,5 2,7
Romania 2,8 2,6 3,1 3,0
Serbia 3,0 3,1 3,0 3,4
Slovakia 2,7 2,7 2,8 2,7
Croatia 3,6 3,5 3,4 3,7
Rest 2,5 1,9 2,9 2,6
7.3 HR KNOWLEDGE TRANSFER BETWEEN THE PARENT COMPANY AND THE
SUBSIDIARY
The respondents in the total sample ranked knowledge flows between subsidiaries and knowledge flows
to parent company the least important HR knowledge flows among the 4 types of HR knowledge flows
provided. Knowledge flow within your subsidiary was second. The most important HR knowledge flow
was assigned to knowledge flows from the parent company. In the Polish and Croatian samples the least
important HR knowledge flow was indicated to be the knowledge flows within their subsidiary while
knowledge flows between subsidiaries being the most important. In the Hungarian sample the
respondents ranked slightly higher the knowledge flows within their subsidiaries.

31. Table: HR knowledge flows (on a 1-5 scale, on average)
Knowledge
flows in HR
Knowledge flows
within your
subsidiary
Knowledge flows
from parent
Knowledge flows between
subsidiaries
Knowledge flows to
parent
Total Sample 2,8 2,7 3,1 3,1
Total Sample
without
Hungary
3,1 2,8 3,1 3,0
Hungary 2,0 2,5 3,2 3,4
Poland 4,1 2,9 3,5 3,0
Estonia 2,2 2,8 2,3 2,8
Romania 2,7 2,8 3,2 3,4
Serbia 2,9 2,6 3,6 3,2
Slovakia 2,0 2,4 2,7 2,7
Croatia 3,6 3,0 3,2 2,7
Rest 2,0 3,0 2,6 3,0

HR Management in Transition_HU_Eastern Europe 2011

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