Original scientific paper Economics of Agriculture 4/2017
UDC: 349.2:330.111.62:663/664
IMPACT OF TAKEOVER PROCESSES ON EMPLOYEES -EVIDENCE FROM FOOD, RETAIL AND FINANCIAL SECTOR
Jelena Andrasic1, Vera Mirovic2, Nada Milenkovic3, Branimir Kalas4, Milos Pjanic5
Summary
Takeover processes imply integration of different organizational cultures, especially in case of crossborder takeovers. Using a survey questionnaire, authors conducted a research to examine the changes and satisfaction with all interest groups in taken over companies operating in fields offood industry, retail sector and financial activity in the Serbian market. Method applied to process the data is discriminant analysis, and research results are presented tabular form as well as graphically in form of ellipses. The aim of the study is to examine the differences of impact of takeover processes on various interest groups of production company, retail chain and financial institution and assessment of their satisfaction. Study's contribution is an informative support for managers of both company acquirer and target company in future acquisition processes, because analysis of differences, change and satisfaction of employees provides a concrete answer regarding elements influencing success of takeover process in terms of management of human.
Key words: food industry, retail industry, financial institution, takeover, employees JEL: G34, F66
Introduction
In the initial phase of transition, takeover processes were done in a form of acquisition of assets - privatization of the existing state-owned companies and social enterprises.
1 Jelena Andrasic, PhD, Assistant Professor, University of Novi Sad, Faculty of Economics, Segedinski put no. 9-11, 24000 Subotica, Republic of Serbia, e-mail: [email protected]
2 Vera Mirovic, PhD, Teaching professor, University of Novi Sad, Faculty of Economics, Segedinski put no. 9-11, 24000 Subotica, Republic of Serbia, e-mail: [email protected]
3 Nada Milenkovic, PhD, Assitant Professor, University of Novi Sad, Faculty of Economics, Segedinski put no. 9-11, 24000 Subotica, Republic of Serbia, e-mail: [email protected]
4 Branimir Kalas, MsC, Teaching assistant, University of Novi Sad, Faculty of Economics, Segedinski put no. 9-11, 24000 Subotica, Republic of Serbia, e-mail: branimir. [email protected]
5 Milos Pjanic, PhD, Assitant Professor, University of Novi Sad, Faculty of Economics, Segedinski put no. 9-11, 24000 Subotica, Republic of Serbia, e-mail: [email protected]
The largest number of foreign investments came to Serbia through the privatization of social enterprises and state-owned companies operating in telecommunications, banking, food industry and trade. In the period from 2001, four fifths of the total 20 billion USD of foreign investments came from European Union countries.
Foreign direct investments play a significant role in the Serbian economy according to Buric, Ristic and Buric (2016). Foreign direct investments had a growth trend from year 2001 and reached their maximum in 2006, when they amounted to 14.3% of the GDP. Onset of the World economic and financial crisis in the summer of 2008 led to a rapid decline in investment activity worldwide and in Serbia as well. Another growth of foreign direct investments was recorded in 2011: wholesale and retail trade sector (38%), processing industry (21%) and financial activity (11%) of the total foreign investments in 2011 (Chamber of commerce and industry of Serbia, 2017).
In the period from 2001-2011 growth rate of production industry was 0.7%, where processing industry dictates growth pace to a significant extent 0.4% (food production amounts to 1.6%, while beverage production amounts to 0.5%). Food industry accounts for 18.6% of the total Industry, which is the highest percentage share according to the Chamber of commerce and industry of Serbia, 2017. Contribution of food industry to GDP is 3.3%. According to Jaksic et al. (2015) transitional processes, lasting up to two and a half decades along with the effects of the global economic crisis, are characterized by the decline in economic activity in Serbia which increased the relative importance of the agriculture in the total economy. Arrival of big multinational companies to the Serbian market in the trade sector led to a higher concentration of market share. Contribution of trade to the gross domestic product is 11.7%. Trade accounts for 34.4% of the total number of companies in Serbia and for 19.7% employees in relation to the total number of employees in Serbia in 2015 according to the Chamber of commerce and industry of Serbia (2017). As far as banking sector of Serbia is concerned, the greatest number of foreign banks entered Serbian market in the period from 2003-2006. In 2001 there were 86 banks operating in the Serbian market, and in 2003 that number was 49, while today there are 30 banks operating in the Serbian market, 23 thereof being foreign owned banks. Takeover processes led to an increase in concentration in the banking sector, so the first 10 banks ranked by the size of balance sheet sum have 72% of the market share according to the Chamber of commerce and industry of Serbia (2017).
Integrating different organizational cultures represents an important part of crossborder mergers and acquisitions. Organizational culture encompasses a set of values, reasoning and believes of one group of people, and connecting organizational cultures of two companies, that were previously separate entities, represents a very important instrument influencing the efficiency of the overall business performance of the integrated company. The decision of management to include a company into an acquisition process surely affects company's human resources of both company acquirer and target company. Transactional theory is based on the possibility of reducing transaction costs of management, adjustments and other expenses that arise at the internationalization of the company (Demirbag, Glaister, & Tatoglu, 2007; Chen & Hennart, 2004; Yin &
Shanley, 2008). One of the main tasks of managers is to understand the environment in which it operates to make decisions based on the statements of accounts were in order to improve organizational competitiveness (Lima et al. 2016).
In that regard, the authors did the research on the effect of takeover processes on human resources of target company post takeover. The analysis was done using a survey questionnaire. Research sample includes 101 respondents from three fields which are affected by the takeover processes to the greatest extent in the Serbian market: production company from food industry, bank from financial sector and retail chain from trade sector. The aim of the study is examining differences regarding the effects of takeover processes on various interest groups of production company, bank and retail chain. This analysis should provide a concrete answer regarding the success of the takeover process and its effect on the employees' satisfaction in the Serbian market post takeover. Study provides an informative support to managers, as it encompasses three industries and all interest groups of companies in the Serbian market, thus satisfaction analysis of the previous period can be useful in preparing due diligence for future acquisition processes. Managing organizational climate and culture is an important part of due diligence affecting the success of takeover process, as confirmed by numerous empirical studies.
Literature Review
Human resources, organizational culture and business climate imply the analysis of prevailing values and norms especially in case of crossborder acquisition. Study of human resources includes the analysis of working conditions, salary and compensation system, improvement and advancement opportunities, adjustment of managerial approach, etc.
There are numerous examples of unsuccessful acquisitions due to managerial incompetence to solve the problem of integration of two companies with different organizational culture and climate. Effect of cultural differences on success of takeover process was subject of empirical studies done by many authors, Denison, 2011; Shook and Roth, 2011; Lodorfos and Boateng, 2006; Lin et al. 2006; Chakraberti, 2009, Rottig et al. 2014.
In more recent times, there is an emphasis on learning theory as stated by Zollo, Reuer, & Singh (2002) and choice of investment type. Studying the correlation between organizational learning, i.e. previous experiences with M&A activities and future M&A activities, authors arrived at a conclusion that experience increases probability for further M&A activities. There is an especially positive correlation between a positive experience in a certain country and repeated investment in that country as stated by Collins et al. (2009).
Companies with experience often create a position - integration manager whose job is to ease the process of adjustment of human resources of previously two separate companies according to Ashkenas and Francis (2000). Some companies hire consultants
to help managers by providing advice and assistance in bringing together organizational cultures and creating work environment that enhances business efficiency according to Fubini, Price, Zollo (2007).
In their study, Shook and Roth (2011), suggest the significance of the active role of experts in the sphere of human resources management in integration processes.
Crossborder acquisitions often produce unintended consequences on employees in terms of downsizing workforce after the integration of companies. This finding is confirmed by Mylonakis (2006), who studied taken over banks in the European market in the period from 1998-2003, and by Siegel and Simons (2006), who studied production companies in the Swedish market.
Birkwnshow et al. (2000) researched the effect of takeover process on human resources through a questionnaire, surveying both shareholders of the target company and shareholders of the company acquirer. They claim that success of acquisition depends on two parallel processes: operative integration (through operative and financial synergy) and human resources integration.
Acquisition adjustment process greatly depends on employees' readiness for change according to Holt, 2007; Jensen, 2000; Wanberg, 2000. Jones (2005) came to a conclusion that the stronger employees' perceptions of the organizational culture the greater their readiness for change.
Large number of authors dealt with studying cultural distance of country acquirer and target country, as well as choice of entrance model of a foreign investor.
Authors Contractor et al. (2014) analyzed 1389 acquisitions in 33 countries of India and China during eleven years' period and arrived at a conclusion that form of corporate restructuring through full, fractional and low ownership is determined by three groups of factors: (a) institutional factors, (b) cultural factors and (c) industry relatedness. Regarding cultural distance (Hofstede, 1991) measured by uncertainty avoidance index, the authors determined that with higher aversion toward risk and uncertainty, investors prefer low-level ownership through entrance models: joint ventures and strategic alliances. Regarding industry relatedness, when an acquisition of target companies in developing countries is performed in related industries (compared to unrelated or loosely related industries) there is greater probability of full over low-level ownership or majority over minority ownership.
Authors Ang and Michailova (2008) analyzed 628 crossborder alliances in 64 developing countries in the period from 1995-2004 and reached a conclusion that higher uncertainty, bigger restrictions and greater cultural distance increase the probability of choosing strategic alliance as restructuring form.
Authors Demirbag, Glaister and Tatoglu (2007), studied, on a sample of6838 companies in Turkey, determinants that affect the choice of internationalization model between full and fractional ownership. Combining determinants of transaction cost theory
and integration theory; they arrived at a conclusion that fractional ownership was a preferred model in countries with following institutional determinants: high political risk, high level of corruption, greater cultural distance and greater language distance.
Authors Somlev and Hoshino (2005) studied entrance of 751 Japanese companies into the European market by analyzing numerous variables. They concluded that: competitiveness, cultural distance and industry growth are the most important determinants in choosing investment type.
These studies are in accordance with authors Estrin, Baghdasaryan, and Meyer, 2009; Peng, 2003; Ang and Michailova, 2008; Brouthers and Keith, 2002; Pothukuchi, Damanpour and Choi, 2002; Kaufman and O'Neill, 2007, who also researched institutional and cultural distances and confirmed these hypotheses.
Data
Study of effects of takeover processes on human resources was done through a survey questionnaire. The study sample includes 101 respondents from three fields that were mostly affected by the biggest takeover wave in the Serbian market: production company from food industry, bank from financial sector and retail chain from trade sector.
Survey questionnaire was used to study changes in company's human resources after the ownership change, i.e. after the completion of the takeover process. The whole study was done in 6 thematic units. Analysis of differences between industries (production company, retail company and financial institution) was done in regard to analysis of general data, analysis of working conditions and workload, analysis of structure of interest groups, analysis of employees' salaries, analysis of employees' professional development and analysis of employees' satisfaction.
Questionnaire is conceived in such a manner as to find out whether there are any changes concerning the employees in the target company after the change in ownership structure (Milojevic, Zekic, 2015). The questionnaire was handed out to employees on all position levels: management, administrative workers, workers behind the counter and fieldworkers. The analysis of general data included general information about respondents: occupation, gender, marital status, work position, qualifications and age. Questions within working conditions and workload unit referred to examining whether there are changes in workload, working conditions, interpersonal relations and position changes post takeover. Within the unit Structures of interest groups questions referred to management changes post takeover and whether takeover brought about any reduction or increment in number of employees. The unit Employees ' salaries contained questions about changes in employees' salaries and whether there was a post-takeover introduction, increase or reduction of bonuses and compensations for the employees. Within the unit Professional development analysis focused on employees' motivation, whether tasks are performed in a team and whether there are opportunities for employees' advancements. The last unit Employees' satisfaction rated feelings of satisfaction on a scale of five, by comparing periods prior to and after the takeover
in order to have an overall result of the research - whether takeover processes had a positive or negative effect on target companies' employees.
Methodology
Analyzed determinants have nonparametric characteristics, and thus the analysis was done using a nonparametric method based on frequency of modalities through multivariate statistical analysis - Discriminant analysis. Of univariate methods Roy's test, Pearson's contingency coefficient (c) and multiple correlation coefficient (R) were used. Calculating discrimination coefficient allowed for characteristics to be differentiated between those that determine subsample specificity and those that are to be excluded from further processing, i.e. the observed area was reduced. Following thresholds for statistical significance were used in the study: p<0.05 (there is a significant difference), 0.05<p<0.1 (there is a difference and a higher risk for drawing conclusions) and p>0.1 (there is no significant difference among analyzed determinants).
Research results are shown in form of ellipses in the study appendix. In case of two or more subsamples, differences or similarities between them are shown visually. If two ellipses overlap there is no difference between them, when they are separated and don't have any points in common there is a significant difference between subsamples for observed parameters, and when the ellipses overlap partially conclusions are drawn on the basis of the analyzed data.
Research results
Data was processed using discriminant analysis. Discriminant analysis is a more complex analysis compared to multivariate analysis MANOVA, since calculating discrimination coefficient and contribution of determinants to the overall study makes the overall study complete and allows for more complex conclusions to be drawn.
Table 1. Significance of difference among analyzed units for three groups of industry
Units F test sig.
General data 8.997 .000
Working conditions and workload 7.554 .000
Structure of interest groups 77.718 .000
Employees' salaries 17.146 .000
Professional development 1.730 .145
Employees' satisfaction 7.737 .000
Source: Author's calculation
Based on the given table it can be concluded that there is a substantial difference and a clearly defined limit (p<0.05) with five analyzed units: general data (.000), working conditions and workload (.000), structure of interest groups (.000), employees' salaries (.000) and employees' satisfaction (.000). There was no substantial difference with the determinant professional development (.145).
Table 2. Significance of difference between respondents' industries compared to the general data analysis
General data c R F P k.dsk
age .248 .224 2.591 .080 .101
gender .326 .345 6.609 .002 .128
marital status .096 .076 .281 .756 .035
qualifications .462 .472 14.075 .000 .314
occupation .510 .556 21.896 .000 .437
Source: Author's calculation
Legend: k.dsk is discrimination coefficient. Threshold for statistical significance: p<0.05 (there is a significant difference), 0.05<p<0.1 (there is a difference and a higher risk for drawing conclusions), p>0.1 (there is no significant difference)
Based on the analysis of general data, it can be concluded that there is a significant difference with the following determinants: gender (.002), qualifications (.000) occupation (.000), and age (.080). However, no significant difference was observed with marital status determinant (.756).
Discrimination coefficient indicates that contribution to discrimination among respondents' industry in regard to general data analysis was the biggest with: occupation (.437), qualifications (.314), gender (.128), age (.101), marital status (.035). Latent determinant is: marital status (.756). Latent determinant is the one which did not show difference among industries, but descriminant analysis included it into the structure according to which there is a substantial difference among industries.
Table 3. Significance of difference between respondents' industries in regard to working conditions and workload analysis
Conditions c R F P k.dsk
Working conditions .414 .449 12.370 .000 .216
Workload .269 .278 4.105 .019 .116
Position .355 .361 7.365 .001 .051
Interpersonal relations .429 .424 10.741 .000 .191
Source: Author's calculation
Discrimination coefficient indicates that contribution to discrimination among respondents' industries in regard to working conditions and workload analysis was biggest with: working conditions (.216), interpersonal relations (.191), workload (.116), and position (.051).
Based on the given table a significant difference can be observed among all analyzed determinants: working conditions (.000), workload (.019), position (.001) and interpersonal relations (.000).
Table 4. Characteristics and homogeneity of respondents' industries in regard to working conditions and workload analysis
Conditions Retail company Financial institution Production company dpr %
Working conditions same Worse same, worse 37.631
Interpersonal relations better worse, better same 33.275
Workload bigge Bigger smaller 20.209
Position new, better new, better same 8.885
n/m 32/36 22/31 29/34
% 88.89 70.97 85.29
Source: Author's calculation
Based on the given table and determinants' contribution to characteristics (dpr %) it can be concluded that the greatest contribution to creating a difference is with: working conditions (37.63%), interpersonal relations (33.28%) and workload (20.21%). Homogeneity with retail company is 88.89% (32/36), with financial institution 70.97% (22/31) and with production company it is 85.29% (29734), meaning that respondents' within the same industry had, for the most part, the same answers when it comes to Working conditions and workload, which allows great precision in drawing conclusions.
More respondents answered that working conditions remained at the same level in the retail and production companies, whereas they worsened in the financial institution. Interpersonal relations in the retail company improved, while other changes were not significant. In the financial institution interpersonal relations worsened, workload became greater; there was an increase in number of employees and promotion of existing employees. In the production company, interpersonal relations remained the same, workload diminished and employees generally remained at their positions.
Table 5. Significance of difference among respondents' industries in regard to analysis of structure of interest groups
Structure c R F P k.dsk
Change of management .389 .421 10.671 .000 .048
Number of employees .676 .874 159.620 .000 3.089
Source: Author's calculation
Discrimination coefficient indicates that contribution to creating a difference among respondents' industries in regard to structure of interest groups analysis was big with both determinants, i.e. they both had a big difference: number of employees (3.089) and change of management (.048).
Based on the shown table it can be observed that there is a substantial difference among respondents in regard to analyzed data with: management (.000) and number of employees (.000).
Table 6. Characteristics and homogeneity of respondents' industries in regard to analysis of structure of interest groups
Structure Retail company Financial institution Production company dpr %
Number of employees same, smaller bigger smaller, same 98.470
Change of management complete,without change partial without change, complete 1.530
n/m 32/36 30/31 33/34
% 88.89 96.77 97.06
Source: Author's calculation
Based on the given table and contribution of determinants to characteristics (dpr %) it can be concluded that the biggest contribution is with: number of employees (98.47%), management (1.53%). Homogeneity for retail company is 88.89%, for financial institution 96.77% and for production company 97.06%. Based on contribution of 98.47% for the number of employees and exceedingly high sample homogeneity, a conclusion about changes in number of employees post takeover can be drawn with an especially high certainty.
The biggest changes were observed with analysis of structure of interest groups, thus by interpreting results which are significant it can be concluded that in the retail company number of employees remained at the same level, in the financial institution that number increased, whereas in production company there was a reduction in number of employees.
In the retail company management was completely changed, in the financial institution it changed partially, whereas in the production company the majority of respondents answered that management was not changed.
Table 7. Analysis of difference among respondents' industries in regard to the analysis of employees' salary
Employee's salary c R F p k.dsk
Salary .311 .325 5.863 .004 .121
Bonuses and compensations .551 .613 29.726 .000 .566
Source: Author's calculation
Discrimination coefficient indicates that the biggest contribution to discrimination among respondents' industries in regard to employees' salaries was with, i.e. the difference was the biggest with: bonuses and compensations (.566), salary (.121).
Based on the given table it can be observed that there is a substantial difference with determinants: salary (.004) and bonuses and compensations (.000).
Table 8. Characteristics and homogeneity of respondents' industries in regard to employees' salaries
Employee's salary Retail company Financial institution Production company dpr %
Bonuses and compensations No they existed yes, they existed 82.387
Salary Higher higher lower 17.613
n/m 25/36 25/31 19/34
% 69.44 80.65 55.88
Source: Author's calculation
Based on the given table and contribution of determinants to characteristics (dpr %) it can be concluded that there is the biggest contribution with: bonuses and compensations (82.39%), salaries (17.61%). Homogeneity for the retail company is 69.44%, for financial institution 80.65% and production company 55.88%.
Analysis of employees' salaries showed that majority of respondents in the retail company and financial institution answered that there was an increase in salaries, whereas majority of respondents in production company answered there was a reduction in salaries post takeover. Bonuses and compensations were not implemented in the retail company; they were pre-existent in the financial institution, while in the production company they were implemented post takeover.
Production companies in the Serbian market were mostly taken over by large companies whose salary systems mostly included basic salary and overachievement bonuses.
Table 9. Analysis of difference among respondents' industries in regard to analysis of employees' professional development
Development c R F p
Professional development .192 .195 1.957 .147
Work motivation .170 .168 1.445 .241
Task completion .080 .078 .299 .742
Source: Author's calculation
The table shows no substantial difference among industries with analyzed determinants: possibilities for professional development (.147), work motivation (.241), manner of completing tasks (.742).
Based on the analysis of employees' professional development, it can be concluded that there weren't differences among employees of production company, financial institution and retail company. With all three companies, in terms of professional development majority of respondents answered that, after takeover, companies invest much more into employees' education, or that they don't feel a difference; in terms of post-takeover work motivation there are more opportunities for advancements or they
don't feel a difference; while in terms of task completion the majority of respondents answered that employees' suggestions are more appreciated and that more demanding tasks are performed in a team.
Table 10. Analysis of difference among respondents' industries in regard to the analysis of employees' satisfaction
Satisfaction c R F P k.dsk
Satisfaction prior to takeover .305 .316 5.373 .006 .179
Satisfaction after takeover .372 .358 7.140 .001 .169
Source: Author's calculation
Discrimination coefficient indicates that contribution among respondents' industries in regard to employees' satisfaction analysis was biggest with, i.e. the difference was the biggest with: satisfaction prior to takeover (.179), satisfaction after takeover (.169).
The presented table shows a substantial difference with both determinants: satisfaction prior to takeover (.006) and satisfaction after takeover (.001).
Table 11. Characteristics and homogeneity of respondents' industries in regard to employees' satisfaction analysis
Satisfaction Retail company Financial institution Production company dpr %
Satisfaction prior to takeover Unsatisfied with my job Satisfied with my job - 51.437
Satisfaction after takeover Unsatisfied with my job, Satisfied with my job Very unsatisfied with my job, unsatisfied with my job, very satisfied with my job Satisfied with my job 48.563
n/m 30/36 21/31 28/34
% 83.33 67.74 82.35
Source: Author's calculation
Based on the given table and contribution of determinants to characteristics (dpr %) it can be concluded that the biggest contribution is with: satisfaction prior to takeover (51.44%) and satisfaction after takeover (48.56%). Homogeneity for retail company is 83.33%, for financial institution 67.74% and for production company 82.35%.
Employees' satisfaction analysis in the retail company shows that interest groups expressed a high level of dissatisfaction prior to takeover, whereas post takeover there was a significant change in their level of satisfaction at work. In the financial institution there was extensive worsening of employees' satisfaction, ranging from "satisfied with my job" prior to takeover to very unsatisfied with my job* unsatisfied with my job* post
takeover. In the production company majority of respondents answered "satisfied with my job", while prior to takeover none of the answers stood out as significant, i.e. all answers related to employees' satisfaction were equally present.
Conclusion
Beside the changes they create in company's business performances, takeover processes also lead to changes with human resources of target company and company acquirer. Regardless of whether takeover processes are motivated by creating synergy or value of control, managerial decisions lead to changes in all segments of business, and each of those changes regardless if it is directed towards profit increase or cost cuts, downsizing, increasing workload, selling unprofitable parts of company and other activities, has an effect on employees and their satisfaction. Takeover processes with all three industries had a positive impact on increasing employees' motivation, since there are more opportunities for their advancement and companies, according to employees' ratings, invest much more into employees' education post takeover.
Based on research results it can be concluded that the most satisfaction post takeover was reported by production company's employees, who confirmed that there was downsizing post takeover but on the other hand, there was an implementation of bonuses and compensations that were not existent prior to the arrival of foreign investors. This creates better involvement and dedication of employees in order to achieve higher salary. Although there was an increase in number of employees in the financial institution post takeover, employees expressed less satisfaction mostly due to worsened interpersonal relations and increased workload. Employees in retail industry did not report significant change in their level of satisfaction prior to and after the takeover. Managing organizational climate and culture represents an important segment of due diligence, affecting the success oftakeover as confirmed by numerous empirical studies. One of the solutions to help with post-acquisition adjustment is hiring an integration manager whose prevailing role is to reconcile attitudes and behaviour models of employees in previously two separate companies. Also, hiring consultants experienced in acquisition processes could help managers in post-acquisition adjustment. Further research should be directed toward the initial phase - acquisition planning, where it would be necessary to review the very elements that managers consider important when planning integration, and then compare them to the results of post-acquisition assessment of impact on human resources, because such overall analysis of planning period and post-acquisition adjustment period could provide useful guidelines for future acquisition processes.
Appendix
Figure 1. Ellipses for chosen industries - discriminant determinants: Working conditions and Interpersonal relations
odns-1 — _ _
Legend: retail company (1); financial institution (2); production company (3); same (usrd-1); better (usrd-2); worse (usrd-3); same (odns-1); better (odns-2); worse (odns-3). In the graph (1) the abscissa (horizontal axis) is Working conditions (usrd), and ordinate (vertical axis) is Interpersonal relations (odns). Source: Authors'work
Figure 2. Ellipses for chosen industries - discriminant determinants: Working conditions and Workload
Legend: retail company (1); financial institution (2); production company (3); same (usrd-1); better (usrd-2); worse (usrd-3); bigger (obps-1); smaller (obps-2); same (obps-3). In the graph (2) the abscissa (horizontal axis) is Working conditions (usrd), and ordinate (vertical axis) is Workload (obps).Source: Authors'work
Figure 3. Ellipses for chosen industries - discriminant determinants: Interpersonal relations and Workload
Legend: retail company (1); financial institution (2); production company (3); same (odns-1); better (odns-2); worse (odns-3); bigger (obps-1); smaller (obps-2); same (obps-3). In the graph (3) the abscissa (horizontal axis) is Interpersonal relations (obps), and ordinate (vertical axis) is Workload (obps).Source: Authors'work
Figure 4. Ellipses for chosen industries - discriminant determinants: Number of employees and Change of management
Legend: retail company (1); financial institution (2); production company (3); same (brzp-1); bigger (brzp-2); smaller (brzp-3); without chane (strr-1); partial (strr-2); complete (strr-3). In the graph (4) the abscissa (horizontal axis) is Number of employees (brzp), and ordinate (vertical axis) is Change of management (strr).Source: Authors'work
Figure 5. Ellipses for chosen industries - discriminant determinants: Bonuses and compensations and salary
Legend: retail company (1); financial institution (2); production company (3); yes (kmpz-1); no (kmpz-2); they existed (kmpz-3); same (zrda-1); lower (zrda-2); higher (zrda-3). In the graph (5) the abscissa (horizontal axis) is Bonuses and compensations (kmpz), and ordinate (vertical axis) is Salary (zrda).Source: Authors 'work
Figure 6. Ellipses for chosen industries - discriminant determinants: Professional development and Task completion
Legend: retail company (1); financial institution (2); production company (3); bigger (prfr-1); smaller (prfr-2); same (prfr-3); team (trad-1); own (trad-2); without change (trad-3). In the graph (5) the abscissa (horizontal axis) is Professional development (prfr), and ordinate (vertical axis) is Task completion (trad).Soruce: Authors'work
Figure 7. Ellipses for chosen industries - discriminant determinants: Satisfaction prior to takeover and Satisfaction after takeover
StSR-1
Legend: retail company (1); financial institution (2); production company (3);Very unsatisfied with my job (stsR-1); unsatisfied with my job (stsR-2); not satisfied or unsatisfied (stsR-3); Satisfied with my job (stsR-4); Very satisfied with my job (stsR-5); Very unsatisfied with my job (stsP-1); unsatisfied with my job (stsR-2); not satisfied or unsatisfied (stsP-3); Satisfied with my job (stsP-4); Very satisfied with my job (stsP-5); In the graph (6) the abscissa (horizontal axis) is Satisfaction prior to takeover (stsR), and ordinate (vertical axis) is Satisfaction after takeover (stsP). Source:Authors'work
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UTICAJ PREUZIMANJA NA ZAPOSLENE - NA PRIMERU PREHRAMBENOG, TRGOVINSKOG I FINANSIJSKOG SEKTORA
Jelena Andrasic6, Vera Mirovic7, Nada Milenkovic8, Branimir Kalas9, Milos Pjanic10
Rezime
Procesi preuzimanja podrazumevaju integrisanje razlicitih organizacionih kultura, narocito ako su u pitanju prekogranicna preuzimanja. Na osnovu anketnog upitnika, sprovedeno je istrazivanje autora, kako bi se ispitale promene i satisfakcija kod svih interesnih grupa preduzeca koja su preuzeta iz oblasti prehrambene industrije, trgovinske delatnosti i finansijske delatnosti na trzistu Srbije. Metod koji je primenjen prilikom obrade podataka jeste diskriminativna analiza, a rezultati istrazivanja su pored tabelarnog prikaza predstavljani i graficki, putem elipsi. Cilj istrazivanja jeste ispitivanje razlika o uticaju procesa preuzimanja na razlicite interesne grupe proizvodnog preduzeca, trgovinskog lanca i finansijske institucije i ocena njihove satisfakcije. Doprinos istrazivanja je u informativnoj podrsci menadzerima i preduzeca sticatelja i ciljnog preduzeca u buducim akvizicionim procesima, jer analizom razlika, promene i sastifakcije zaposlenih pruza se konkretan odgovor o elementima koji uticu na uspesnost procesa preuzimanja sa stanovista upravljanja ¡judskim resursima.
Kljucne reci: prehrambena industrija, trgovinska delatnost, finansijska institucija, preuzimanje, zaposleni
6 Docent dr Jelena Andrasic, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinski put br. 9-11, 24000 Subotica, Republika Srbija, E-mail: [email protected]
7 Docent dr Vera Mirovic, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinski put br. 9-11, 24000 Subotica, Republika Srbija, E-mail: [email protected]
8 Docent dr Nada Milenkovic, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinski put br. 9-11, 24000 Subotica, Republika Srbija, E-mail: [email protected]
9 Branimir Kalas, Asistent, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinski put br. 9-11, 24000 Subotica, Republika Srbija, E-mail: [email protected]
10 Docent dr Milos Pjanic, Univerzitet u Novom Sadu, Ekonomski fakultet u Subotici, Segedinski put br. 9-11, 24000 Subotica, Republika Srbija, E-mail: [email protected]