Next Article in Journal
A Case Study on Large Deformation Failure Mechanism and Control Techniques for Soft Rock Roadways in Tectonic Stress Areas
Next Article in Special Issue
People Analytics of Semantic Web Human Resource Résumés for Sustainable Talent Acquisition
Previous Article in Journal
Incentive Mechanism for Sustainable Improvement in a Supply Chain
Previous Article in Special Issue
Sustainable Social and Individual Implications of Telework: A New Insight into the Romanian Labor Market
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Employee Motivation as a Tool to Achieve Sustainability of Business Processes

1
Faculty of Wood Sciences and Technology, Technical University in Zvolen, Ul. T. G. Masaryka 24, 960 01 Zvolen, Slovakia
2
Faculty of Management, Comenius University in Bratislava, Odbojárov 10, P.O. BOX 95, 82005 Bratislava, Slovakia
3
Faculty of Multimedia Communications, Tomas Bata University in Zlín, Univerzitní 2431, 760 01 Zlín, Czech Republic
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(13), 3509; https://doi.org/10.3390/su11133509
Submission received: 31 May 2019 / Revised: 14 June 2019 / Accepted: 25 June 2019 / Published: 26 June 2019
(This article belongs to the Special Issue Sustainable Human Resource Management)

Abstract

:
Employee performance and their new ideas, as well as their efforts to promote the company in positive ways help build the values of an enterprise. Properly motivated managers, white-collar, and blue-collar workers use their performance to affect the business efficiency, and therefore the success and sustainability of the enterprise. Selecting the right structure of motivation factors, especially those aimed at job category and gender, is the main role of enterprise management. The aim of this study is to analyze and define differences in the perception of the preferred level of motivation in terms of gender and job category. The questionnaires were given to randomly selected employees working in Slovak enterprises in order to ensure variability and randomness of respondent selection which is necessary for relevant data acquisition. Following the average, the order of the importance of motivation factors of 3720 respondents was defined. The Student’s t-test and Tukey’s HSD test were used. We confirmed that there are statistically significant differences in the perception of the motivation in terms of job category. Moreover, we proved the significant differences between genders in the job category of blue-collar workers. We did not observe differences between genders in the other job categories studied. The results reported should be accepted and implemented in motivational programs by the employees of human resource departments as a way to keep up with strategic human resource management.

1. Introduction

Sustainability in business process management is a key factor associated with the enterprise success [1,2]. Employees are considered one of the most important and leading factors in achieving sustainability [3,4,5], especially employees who move the business forward [6,7,8,9]. Managers, white-collar workers, and blue-collar workers are all involved in the company results. An employee’s performance, their new ideas, as well as their efforts to promote the company in a positive way help build the values of an enterprise [10,11,12,13] and the success or failure of a business is affected by their productivity [14,15,16,17,18,19,20,21]. Employee productivity is influenced by employee motivation [22,23,24,25]. It is a complex and purposeful process to create a working environment and atmosphere that helps satisfy the aspirations, needs, and interests of employees and stimulates their action in a desirable way [26,27].
The quality of human potential plays an important role and it is a key factor that affects the running of a company, its prosperity, as well as sustainable development. A successful business is aware of the importance of its staff and their positive motivation; they are the greatest asset helping the company meet its goals. Currently, when advances in technology, information, and globalization occur most often, the human factor is becoming the biggest competitive advantage. The importance of human resources is considered strategic [28,29,30,31,32]. They become a part of strategic management of an enterprise and a factor important for sustainability. Effective employee management is supported by motivation.
A result assessment approach to employee management must focus on ways to encourage employee creativity, improve work performance, and create conditions that support team activity within the enterprise. It is connected with the employee performance in the workplace. Therefore, it is a specific task linked to the specific enterprise [33,34,35,36,37].
The motivation process is supported by setting realistic company goals and engaging employees. A motivational program focuses on the optimal use of the available workforce to meet company goals and, at the same time, on knowing and developing the personality of the employee. An effective motivational program covers the areas with low performance in a given period or those areas which seem to be significant for work activity due to another reason. The goal of the program is to create conditions encouraging motivation of all employees in the enterprise. Motivational programs affect employees in psychologically and economically ways, whereby the importance of both ways is equal. A motivational program is used especially as part of an adaptation programs. It is a document covering the set of facts affecting and motivating employees in accordance with the task relating to manufacturing, trade, and economic intentions of the enterprise [38].
We propose that motivation will be affected, besides other sociodemographic data (age, education, seniority, company strategic direction, region, and the size of an enterprise), by gender and job category. The aim of this study is to analyze and define differences in the perception of the preferred level of motivation in terms of gender and job category. The research is part of a long-term and extensive study on employee motivation in Slovakia dealing with the individual mentioned areas. In the future, the research results will be used to define the model of employee motivation in Slovak enterprises.

2. Literature Review

There is a wide range of tools used to motivate employees. F. Taylor defined money as the most important factor motivating employees to achieve higher productivity in industry [39,40]. This form of reward results in employee satisfaction and directly affects their performance. Salary is a valuable tool that plays an important role in the improvement of employee performance, as well as organizational productivity [41]. Studies [42,43,44,45] have shown that salary, promotion, bonuses, and other types of rewards are used by most enterprises to improve employee performance. Praise, setting realistic and achievable goals, appropriate workload definition, employee engagement, appropriate empowerment, responsibility, feedback, work equipment, expressing the positive personality features of a supervisor, appropriate leadership style, correctness by senior staff and company, and providing relevant information are considered to be other important motivation factors [46,47,48,49,50,51,52,53,54].
The role of business management is to define motivational factors that are used to manage and lead employees in an effective way. Current research has shown that the occurrence of differences in employee motivation depend on the employee’s age [55,56,57,58,59,60,61]. However, in this process, the employee’s position must be taken into account. With respect to the source of motivation for managers, they represent a specific group of employees [62]. Managers are motivated by financial motivational factors, as well as recognition and freedom in decision making [63,64]. Motivational factors for managers are often classified as “push” or “pull” factors. Push factors include the need to increase the family income, work dissatisfaction in terms of salary, difficulties finding a suitable job, and the need for flexibility due to family duties and responsibilities. Pull factors include the need for independence, self-actualization, and improvement of the current state and reputation in the society. White-collar workers are motivated through rewards or recognition [65]. Employees at lower level job are also motivated by financial rewards [66,67].
When defining motivational factors, the role of enterprise management is to choose an appropriate structure of motivational factors with an emphasis on gender. Differences in motivation follow the differences in gender. Men put more effort into achieving wealth or financial well-being while women prefer work-life balance [68]. In general, women are motivated by family needs more than men whose priority is a private financial situation [69,70].

3. Materials and Methods

The level of employee motivation was investigated in this study conducted in 2018. The selection of respondents was proportionally allocated throughout Slovakia. All parts of Slovakia were covered by the research sample dataset. The questionnaires were given to randomly selected employees working in Slovak enterprises in order to ensure variability and randomness of respondent selection necessary for relevant data acquisition. A total of 3720 respondents, described in Table 1, participated in the research. Descriptive statistics were used to describe the primary sampling unit.
The following 30 motivational factors were examined: atmosphere in the workplace, good work team, fringe benefits, physical effort at work, job security, communication in the workplace, name of the company, opportunity to apply one’s own ability, workload and type of work, information about performance result, working hours, work environment, job performance, career advancement, competences, prestige, supervisor’s approach, individual decision making, self-actualization, social benefits, fair appraisal system, stress, mental effort, mission of the company, region’s development, personal growth, relation to the environment, free time, recognition, and basic salary. Respondents assigned each motivational factor one of the five degrees of importance according to the Likert scale (5—very important, 4—important, 3—medium important, 2—slightly important, and 1—unimportant). The data gathered were processed using the STATISTICA 12 software. The importance of the level of motivation was investigated using the weighted arithmetic average formula. The level of motivation of all respondents was defined in terms of gender. Subsequently, the ten most important motivational factors for individual job categories of employees were defined. The motivational factors that were mentioned most occurred as the most important motivational factors over a long period in present studies [71,72,73,74,75,76,77,78]. A random variable, t, with Student t distribution was used as a test criterion for further testing. The following two hypotheses were tested at the level of significance α ≤ 0.05:
Hypothesis 1.
Statistically significant differences between genders are expected.
Hypothesis 2.
Considering gender, statistically significant differences between job categories are expected.
The likelihood of motivating employees, in terms of their gender and job category, with similar motivational programs was tested. The chi-Square or Pearson–Fisher (χ2) test was used to test the agreement or disagreement between observations. Due to the selective character of the gathered data, Tukey’s HSD (honest significant difference) at the significance level of 5% was used to test the differences between the averages of the values for the importance of motivational factors of white-collar workers. The Tukey’s HSD test is a single-step multiple comparison procedure. It is modified for various numbers of observations in individual groups. Independence between levels of factors, variance, and normality agreement was expected.

4. Empirical Results

First, the dependence of motivational factors in terms of job category was verified. Tukey’s HSD test was used. The results are presented in Figure 1.
The results in Figure 1 show that there were statistically significant differences in all job categories.
Subsequently, the importance of motivational factors in terms of gender was examined. The results are presented in Table 2.
The average values of 30 motivational factors in terms of gender are presented in Table 2. For men, the following 10 motivational factors were considered the most important: basic salary, atmosphere in the workplace, good work team, fringe benefits, fair appraisal system, supervisor’s approach, job security, communication in the workplace, working hours, and work environment. For women, the motivational factors considered most important were: basic salary, atmosphere in the workplace, good work team, supervisor’s approach, fair appraisal system, job security, fringe benefits, communication in the workplace, working hours, and work environment. The average values of these motivational factors were the highest rated.
When a detailed test at the level of α ≤ 0.05 was carried out, the occurrence of statistical dependence was confirmed for 17 out of 30 motivational factors. The statistically significant differences are highlighted in bold in Table 2. Following the results, the hypothesis, H1, was confirmed, i.e., there were statistically significant differences in the perception of the motivational level between men and women.
Furthermore, the importance of motivational factors in the case of job categories was examined in terms of gender.

4.1. The Level of Motivation in Terms of Job Category of the Manager

The job category, manager, was the first category analyzed. The results are presented in Table 3, indicating that the three most important motivational factors for men and women in the job category “manager” were the same. However, the order of importance was different. Male managers considered the basic salary the second most motivating factor, while, good work team was the second most important motivational factor for female managers.
The most important motivational factors for both men and women were chosen in order to test the dependence of motivational factors in terms of gender in the job category “manager”. Following the Student t-test at the significance level α ≤ 0.05, statistically significant differences were not confirmed, i.e., there was no significant statistical dependence between selected motivational factors and gender in the job category “manager” (Table 4). On the basis of the results in the job category of manager, there was a high degree of similarity in motivational factors with a different order of preferences in motivational factors.

4.2. The Level of Motivation in Terms of Job Category of the White-Collar Worker

In the case of white-collar workers, basic salary, atmosphere in the workplace, and good work team were the three most important motivational factors for both men and women and the order of most importance factors was the same for both men and women. Further results are presented in Table 5.
Statistically significant dependence between motivational factors and gender in the job category of white-collar workers was verified for selected motivational factors. The results in Table 6 show that there were statistically significant differences in selected motivational factors depending upon gender. These factors included atmosphere in the workplace, good work team, job security, supervisor’s approach, and fair appraisal system.
Testing the selected motivational factors with significant differences confirmed statistically are presented in Table 7.
Five motivational factors with statistically significant differences and the overview of the values of importance assigned by respondents are shown in Table 8. Absolute and relative frequencies of responses are mentioned.
Selected motivational factors were considered important or very important by both men and women in the job category of white-collar workers. The value 5 (i.e., very important) was the value with the highest frequency of responses recorded in all motivational factors.
Average values, standard deviation, 95% confidence intervals in the primary sampling unit are mentioned in Table 9. Following the results presented in Table 9 the findings are generalized.
The results presented in Table 9 indicate that the motivational factor atmosphere in the workplace was assigned a value ranging from 4.396 to 4.519 by men in the job category of white-collar worker. Women in the same job category assigned the same motivational factor an average value in the range from 4.567 to 4.639 at the 95% confidence level. The results show that atmosphere in the workplace was evaluated in a more positive way by women than men in the job category of white-collar worker. Moreover, all analyzed motivational factors were rated higher by women in the job category of white-collar worker than men in the same job category.
Expected and residual frequencies of selected motivational factors in terms of gender in the job category of white-collar worker are presented in Table 10. Residual frequencies are the difference between frequencies in the line (discovered values in Table 8) and the expected frequencies of the evaluation of selected motivational factors.
As shown in Table 10, atmosphere in the workplace tends to be evaluated by male white-collar workers as medium important, on the other hand, it is evaluated by female white-collar worker as very important. Moreover, men in the job category of white-collar worker, tend to rate analyzed motivational factors lower, with a lower degree of importance (medium important, important) than women in the same job category. Male white collar-workers tend to evaluate all analyzed motivational factors (atmosphere in the workplace, good work team, job security, supervisor’s approach, and fair appraisal system) as very important.

4.3. The Level of Motivation in Terms of Job Category of the Blue-Collar Worker

The job category of the blue-collar worker was the third area studied. Basic salary was considered by male blue-collar workers as the most important motivational factor. On the other hand, female blue-collar workers considered atmosphere in the workplace the most important motivational factor. The importance of other motivational factors is presented in Table 11.
On the basis of the results of Student t-test shown in Table 12, we concluded that there were no statistically significant differences between the selected motivational factors and gender in terms of job category of the blue-collar worker. The research results in the job category of blue-collar worker show that there was a high degree of similarity in motivational factors with different order preferences of motivational factors.

5. Discussion

On the basis of the results of our research, we concluded that motivational factors such as basic salary, atmosphere in the workplace, as well as a good work team were highly motivating for all employees. However, men and women perceive the importance of these factors differently. Basic salary was a motivational factor of greater importance for men, whereas, women considered atmosphere in the workplace and a good work team more important. These findings correspond with the studies carried out in this field [68,69,70].
Further findings associated with the job category correspond with the research results of Bazydlo et al. [79] who showed that work environment, workplace comfort, and a good work team were the most motivating factors for managers. In Slovakia, employees with higher education are hired for manager positions. Their value orientation is due almost equally to their knowledge and gender equality [80,81,82,83,84]. In the case of managers, the results of our research show that a motivational program can be created regardless the gender and we did not observe any significant differences in motivational needs. The same conclusion was drawn in the case of blue-collar workers, especially when employees with primary and lower secondary education are hired for this job position. In addition, their value orientation is due almost equally to their knowledge and gender equality [80,85,86,87]. Following the analysis of motivation and education, similar results were observed.
In the case of white-collar workers, statistically significant differences in terms of gender were confirmed. Due to the statistically significant differences, the needs of individual groups had to be taken into account. Male white-collar workers tend to rate analyzed motivational factors lower as compared with women, who tend to evaluate analyzed motivational factors as very important.
There were statistically significant differences in perception of motivation among the three job categories mentioned in Figure 1. Therefore, a different motivational program must be created for each job category.
Furthermore, our research results indicate that blue-collar workers were motivated by the amount of money they receive in the form of basic salary. This was confirmed by other studies [66,67,88,89].
In general, the fact that there were statistically significant differences in motivation between men and women is considered the main finding. In terms of job categories of managers and blue-collar workers, motivational programs can be created regardless of gender. In the case of white-collar workers, motivational program must vary due to gender.

6. Conclusions

The statement that quality human resources have become an integral part of the company’s strategy has been confirmed by [90,91]. Employees play a key role in the implementation of the overall business development strategy. The efficiency of business processes, and therefore the overall success of the enterprise is affected by the performance of properly motivated employees [92,93,94,95,96,97]. Results of our research show that there were statistically significant differences in perceiving the motivation in terms of gender. In the case of mixed employee teams, this fact must be taken into consideration in the process of designing motivational programs. Despite the similarity in the order of the importance of motivational factors in terms of men and women, both of them perceived the individual motivational factors in different ways.
The aim of this study was to define the differences in the perception of the level of motivation in terms of gender and job category. The fact that there are statistically significant differences in the perception of motivation in terms of job category was proven. The significant differences in the job category of blue-collar workers in terms of gender were proven as well. In the case of two other job categories, no significant differences between genders were observed. The fact that the aim of the study was met can be stated. The results should be accepted and implemented in motivational programs by the employees of the human resource department. In the future, we plan to find correlations between other sociodemographic data (age, education, seniority, company strategic direction, region, the size of an enterprise) and use our results to define a model for employee motivation in enterprises. However, further data collection and analysis is required.

Author Contributions

Conceptualization, S.L., P.Š., D.W., and M.H.; methodology, S.L., P.Š., D.W., M.H., and M.L.; data curation, S.L., P.Š., D.W., M.H., and M.L.; writing—original draft, S.L., P.Š., D.W., and M.H.; visualization, S.L., P.Š., D.W., and M.H.

Funding

This research was funded by VEGA 1/0024/17 “Computational model of motivation”, and APVV 16-0297 “Updating of anthropometric database of Slovak population”.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Dominguez, N. SME Internationalization Strategies: Innovation to Conquer New Markets; Wiley Backwell: Hoboken, NJ, USA, 2018. [Google Scholar]
  2. Graa, A.; Abdelhak, S. A review of branding strategy for small and medium enterprises. Acta Oeconomica Universitatis Selye 2016, 5, 67–72. [Google Scholar]
  3. Zaborova, E.; Markova, T. Human capital as a factor of regional development. In Proceedings of the 12th International Days of Statistics and Economics, Prague, Czech Republic, 6–8 September 2018. [Google Scholar]
  4. Vetrakova, M.; Durian, J.; Sekova, M.; Kascakova, A. Employee retention and development in pulp and paper companies. BioResources 2014, 11, 9231–9243. [Google Scholar] [CrossRef]
  5. Kucharčíková, A. Investment in the human capital as the source of economic growth. Period. Polytech. Soc. Manag. Sci. 2014, 22, 29–35. [Google Scholar] [CrossRef]
  6. Stachova, K.; Stacho, Z.; Blstakova, J.; Hlatká, M.; Kapustina, L.M. Motivation of employees for creativity as a form of support to manage innovation processes in transportation-logistics companies. Nase More 2018, 65, 180–186. [Google Scholar] [CrossRef]
  7. Jankelová, N.; Joniaková, Z.; Blštáková, J.; Némethová, I. Readiness of human resource departments of agricultural enterprises for implementation of the new roles of human resource professionals. Agric. Econ. 2017, 63, 461–470. [Google Scholar]
  8. Lizbetinova, L. The quality of communication in the context of regional development. Deturope Cent. Eur. J. Reg. Dev. Tour. 2014, 6, 22–38. [Google Scholar]
  9. Burton, K. A Study of Motivation: How to Get Your Employees Moving; SPEA honors: Bloomington, IN, USA, 2012. [Google Scholar]
  10. Potkány, M.; Gejdoš, M.; Debnár, M. Sustainable innovation approach for wood quality evaluation in green business. Sustainability 2018, 10, 2984. [Google Scholar] [CrossRef]
  11. Kohnová, L.; Papula, J.; Papulová, Z.; Suchoba, M. Preparation for smart industry, introduction and comparative study. In Proceedings of the 2nd EAI International Summit, Smart City 360 2016, Bratislava, Slovakia, 22–24 November 2016. [Google Scholar]
  12. Bartuska, L.; Hanzl, J.; Lizbetinova, L. Possibilities of using the data for planning the cycling infrastructure. Procedia Eng. 2016, 161, 282–289. [Google Scholar] [CrossRef]
  13. Stacho, Z.; Potkány, M.; Stachová, K.; Marcineková, K. The organizational culture as a support of innovation processes’ management: A case study. Int. J. Qual. Res. 2016, 10, 769–784. [Google Scholar] [CrossRef]
  14. Bryson, A.; White, M. HRM and Small-Firm Employee Motivation: Before and After the Great Recession. ILR Rev. 2019, 72, 749–773. [Google Scholar] [CrossRef]
  15. Korcsmaros, E. Forms of employment in SME sector—Example from Slovakia based on primary research. AD ALTA J. Interdiscip. Res. 2018, 8, 131–134. [Google Scholar]
  16. Myšková, R.; Hájek, P. Sustainability and corporate social responsibility in the text of annual reports—The case of the IT services industry. Sustainability 2018, 10, 4119. [Google Scholar] [CrossRef]
  17. Žuľová, J.; Švec, M.; Madleňák, A. Personality aspects of the employee and their exploration from the GDPR perspective. Cent. Eur. J. Labour Law Pers. Manag. 2018, 1, 68–77. [Google Scholar] [CrossRef]
  18. Joniaková, Z.; Blštáková, J.; Némethová, I.; Stachová, K.; Stacho, Z. Current approaches to employee training and their applications in business. In Proceedings of the Global Scientific Conference Management and Economics in Manufacturing, Zvolen, Slovakia, 5–6 October 2017. [Google Scholar]
  19. Lašáková, A.; Bajzíková, Ľ.; Dedze, I. Barriers and drivers of innovation in higher education: Case study-based evidence across ten European universities. Int. J. Educ. Dev. 2017, 55, 69–79. [Google Scholar] [CrossRef]
  20. Xu, Y.; Wang, Y.G.; Tao, X.B.; Lizbetinova, L. Evidence of Chinese income dynamics and its effects on income scaling law. Phys. A-Stat. Mech. Appl. 2017, 487, 143–152. [Google Scholar] [CrossRef]
  21. Mura, L.; Rozsa, Z. The impact of networking on the innovation performance of SMEs. In Proceedings of the 7th International Days of Statistics and Economics, Prague, Czech Republic, 19–21 September 2013. [Google Scholar]
  22. Anwar, P.M.; Budi, I. The influence of job satisfaction and motivation on the employee performance at PT. Era Media Informasi. IOP Conf. Ser. Mater. Sci. Eng. 2018, 453. [Google Scholar] [CrossRef]
  23. Schwartz, M. The motivation of employees is becoming more and more important. Stahl und Eisen 2018, 138, 61–63. [Google Scholar]
  24. Dongho, K. Employee motivation: Just ask your employees. Seoul J. Bus. 2006, 12, 19–35. [Google Scholar]
  25. Björklund, C.H. Work Motivation–Studies of its Determinants and Outcomes; Stockholm School of Economics: Shockholm, Sweden, 2001. [Google Scholar]
  26. Diefendorff, J.M.; Seaton, G.A. Work Motivation; The University of Akron: Akron, OH, USA, 2015. [Google Scholar]
  27. Ahmad, F.; Abbas, T.; Latif, S.; Rasheed, A. Impact of transformational leadership on employee motivation in telecommunication Sector. J. Manag. Policies Pract. 2014, 2, 11–25. [Google Scholar]
  28. Amberg, J.J.; McGaughey, S.L. Strategic human resource management and inertia in the corporate entrepreneurship of a multinational enterprise. Int. J. Hum. Resour. Manag. 2019, 30, 759–793. [Google Scholar] [CrossRef]
  29. Iqbal, A. The strategic human resource management approaches and organisational performance: The mediating role of creative climate. J. Adv. Manag. Res. 2019, 16, 181–193. [Google Scholar] [CrossRef]
  30. McClean, E.; Collins, C.J. Expanding the concept of fit in strategic human resource management: An examination of the relationship between human resource practices and charismatic leadership on organizational outcomes. Hum. Resour. Manag. 2019, 58, 187–202. [Google Scholar] [CrossRef]
  31. Stankevičiūté, Ž.; Savanevičiené, A. Designing sustainable HRM: The core characteristics of emerging field. Sustainability 2018, 10, 4798. [Google Scholar] [CrossRef]
  32. Szierbowski-Seibel, K. Strategic human resource management and its impact on performance—Do Chinese organizations adopt appropriate HRM policies? J. Chin. Hum. Resour. Manag. 2018, 9, 62–76. [Google Scholar] [CrossRef]
  33. Jiang, C.; Yahiaoui, D. French multinational companies’ HRM in China: Strategic orientation and integration approaches. Asia Pac. Bus. Rev. 2019, 25, 3–18. [Google Scholar] [CrossRef]
  34. Hitka, M.; Lorincová, S.; Gejdoš, M.; Klarić, K.; Weberová, D. Management approach to motivation of white-collar employees in forest enterprises. BioResources 2019, 14, 5488–5505. [Google Scholar] [CrossRef]
  35. Panday, J. Managing emotional labor for service employees: An HRM-based approach. Hum. Resour. Manag. Int. Dig. 2018, 26, 1–4. [Google Scholar] [CrossRef]
  36. Zhao, Y. Managing Chinese millennial employees and their impact on human resource management transformation: An empirical study. Asia Pac. Bus. Rev. 2018, 24, 472–489. [Google Scholar] [CrossRef]
  37. Xing, Y.; Liu, Y.; Tarba, S.Y.; Cooper, C.L. Intercultural influences on managing African employees of Chinese firms in Africa: Chinese managers’ HRM practices. Int. Bus. Rev. 2016, 25, 28–41. [Google Scholar] [CrossRef]
  38. Hitka, M.; Lorincová, S.; Pajtinková Bartáková, G.; Ližbetinová, L.; Štarchoň, P.; Li, C.; Zaborova, E.; Markova, T.; Schmidtová, J.; Mura, L.; et al. Strategic tool of human resource management for operation of SMEs in the wood-processing industry. BioResources 2018, 13, 2759–2774. [Google Scholar] [CrossRef]
  39. Bernad, L.C.; Walsh, R.P.; Mills, M. The motivation analysis test: An historical and contemporary evalutation. Psychol. Rep. 2005, 96, 464–492. [Google Scholar] [CrossRef]
  40. Kovach, K.A. What motivates employees? Workers and supervisors give different answers. Bus. Horiz. 1987, 30, 58–65. [Google Scholar] [CrossRef]
  41. Kampkötter, P. Performance appraisals and job satisfaction. Int. J. Hum. Resour. Manag. 2015, 28, 750–774. [Google Scholar] [CrossRef]
  42. Bajziková, Ľ. The minimum wage in compensation systems in EU and the Slovak Republic. In Proceedings of the 31st International Business Information Management Association Conference, IBIMA 2018: Innovation Management and Education Excellence through Vision 2020, Milan, Italy, 25–26 April 2018. [Google Scholar]
  43. Plessis, A.J.; Douangphichit, N.; Dodd, P. HRM in relation to employee motivation and job performance in the hospitality industry. J. Int. Bus. Res. Mark. 2016, 1, 12–21. [Google Scholar] [CrossRef]
  44. Zameer, H.; Ali, S.; Nisar, W.; Amir, M. The impact of the motivation on the employee’s performance in beverage industry of Pakistan. Int. J. Acad. Res. Account. Financ. Manag. Sci. 2014, 4, 293–298. [Google Scholar] [CrossRef]
  45. Mani, V. Development of employee satisfaction index scorecard. Eur. J. Soc. Sci. 2010, 15, 129–139. [Google Scholar]
  46. Kmecová, I. Educational process and motivation factors of university students and its analysis. In Proceedings of the 31st International Business Information Management Association Conference: Innovation Management and Education Excellence through Vision 2020, Milan, Italy, 25–26 April 2018. [Google Scholar]
  47. Sanchez-Sellero, M.C.; Sanchez-Sellero, P. Determinants of job satisfaction in wood and paper industry: Study in spain and findings in other countries. Maderas-Ciencia Y Tecnologia 2018, 20, 641–660. [Google Scholar] [CrossRef]
  48. Sánchez-Sellero, M.C.; Sánchez-Sellero, P.; Cruz-González, M.M.; Sánchez-Sellero, F.J. Determinants of job satisfaction in the spanish wood and paper industries: A comparative study across spain. Drvna Industrija 2018, 69, 71–80. [Google Scholar] [CrossRef]
  49. Grenčíková, A.; Guščinskiene, J.; Španková, J. The role of leadership in motivating employees in a trading company. J. Secur. Sustain. Issues 2017, 2, 67–75. [Google Scholar] [CrossRef]
  50. Nemec, M.; Kristak, L.; Hockicko, P.; Danihelova, Z.; Velmovska, K. Application of innovative P&E method at technical universities in Slovakia. Eurasia J. Math. Sci. Technol. Educ. 2017, 13, 2329–2349. [Google Scholar] [CrossRef]
  51. Machová, R. What motivates a human? Acta Oeconomica Universitatis Selye 2014, 3, 88–101. [Google Scholar]
  52. Naile, I.; Selesho, J.M. The role of leadership in employee motivation. Mediterr. J. Soc. Sci. 2014, 5, 175–182. [Google Scholar] [CrossRef]
  53. Muogbo, U.S. The impact of employee motivation on organisational performance (a study of some selected firms in Anambra state Nigeria). Int. J. Eng. Sci. 2013, 2, 70–80. [Google Scholar]
  54. Kropivšek, J.; Jelačić, D.; Grošelj, P. Motivating employees of Slovenian and Croatian wood-industry companies in times of economic downturn. Drvna Industrija 2011, 62, 97–103. [Google Scholar] [CrossRef]
  55. Fratričová, J.; Kirchmayer, Z. Barriers to work motivation of generation Z. J. Hum. Resour. Manag. 2018, 2, 28–39. [Google Scholar]
  56. Kirchmayer, Z.; Fratričová, J. What motivates generation Z at work? Insights into motivation drivers of business students in Slovakia. In Proceedings of the Innovation management and education excellence through vision 2020, Milan, Italy, 25–26 April 2018. [Google Scholar]
  57. Cagáňová, D.; Stareček, A.; Bednáriková, M.; Horňáková, N. Analysis of factors influencing the motivation of generations Y and Z to perform in the educational process. In Proceedings of the 15th IEEE International Conference on Emerging eLearning Technologies and Applications, Starý Smokovec, Slovakia, 26–27 October 2017. [Google Scholar]
  58. Goić, S. Employees older than 50 on Croatian labour market—Need for a new approach. J. Hum. Resour. Manag. 2017, 2, 1–11. [Google Scholar]
  59. Idrees, M.D.; Hafeez, M.; Kim, J.Y. Workers’ age and the impact of psychological factors on the perception of safety at construction sites. Sustainability 2017, 9, 745. [Google Scholar] [CrossRef]
  60. Kooij, D.; Jansen, P.G.W.; Dikkers, J.E.; De Lange, A. The influence of age on the associations between HR practices and both affective commitment and job satisfaction: A meta-analysis. J. Organ. Behav. 2010, 31, 1111–1136. [Google Scholar] [CrossRef]
  61. Rabl, T. Age, discrimination, and achievement motives—A study of German employees. Pers. Rev. 2010, 39, 448–467. [Google Scholar] [CrossRef]
  62. Kuratko, D.; Hornsby, J.; Nafziger, D. An examination of owners’ goals in sustaining entrepreneurship. J. Small Bus. Manag. 1997, 35, 24–33. [Google Scholar]
  63. Mikkelsen, M.F.; Jacobsen, C.B.; Andersen, L.B. Managing employee motivation: Exploring the connections between managers’ enforcement actions, employee perceptions, and employee intrinsic motivation. Int. Public Manag. J. 2017, 20, 183–205. [Google Scholar] [CrossRef]
  64. Anderson, L.B.; Pallesen, T. “Not just for the money?” How financial incentives affect the number of publications at Danish Research Institutions. Int. Public Manag. J. 2008, 11, 28–47. [Google Scholar] [CrossRef]
  65. Majumder, M.; Hossain, T. Human resource management practices and employees’ satisfaction towards private banking sector in Bangladesh. Int. Rev. Manag. Mark. 2012, 2, 55–58. [Google Scholar]
  66. Manzoor, Q.A. Impact of employees’ motivation on organizational effectiveness. Eur. J. Bus. Manag. 2011, 3, 36–45. [Google Scholar] [CrossRef]
  67. Kanfer, R.; Chen, G.; Pritchard, R.D. Work Motivation: Forging New Perspectives and Directions in the Post-Millenium; Taylor & Francis: New York, NY, USA, 2008. [Google Scholar]
  68. Almobaireek, W.N.; Manolova, T.S. Entrepreneurial motivations among female university youth in Saudi Arabia. J. Bus. Econ. Manag. 2013, 14, S56–S75. [Google Scholar] [CrossRef]
  69. Inceoglu, I.; Segers, J.; Bartram, D. Age-related differences in work motivation. J. Occup. Organ. Psychol. 2012, 85, 300–329. [Google Scholar] [CrossRef]
  70. Arnania-Kepuladze, T. Gender stereotypes and gender feature of job motivation: Differences or similarity? Probl. Perspect. Manag. 2010, 8, 84–93. [Google Scholar]
  71. Lorincová, S.; Hitka, M.; Štarchoň, P.; Stachová, K. Strategic instrument for sustainability of human resource management in small and medium-sized enterprises using management data. Sustainability 2018, 10, 3687. [Google Scholar] [CrossRef]
  72. Hitka, M.; Lorincová, S.; Ližbetinová, L.; Pajtinková Bartáková, G.; Merková, M. Cluster analysis used as the strategic advantage of human resource management in small and medium-sized enterprises in the wood-processing industry. BioResources 2017, 2, 7884–7897. [Google Scholar] [CrossRef]
  73. Kampf, R.; Lorincová, S.; Kapustina, L.M.; Ližbetinová, L. Motivation level and its comparison between senior managers and blue-collar workers in small and medium-sized transport enterprises. Communications 2017, 19, 43–49. [Google Scholar]
  74. Lorincová, S.; Hitka, M.; Čambál, M.; Szabó, P.; Javorčíková, J. Motivational factors influencing senior managers in the forestry and wood-processing sector in Slovakia. BioResources 2016, 11, 10339–10348. [Google Scholar] [CrossRef]
  75. Myšková, R.; Hitka, M.; Lorincová, S.; Balážová, Ž. Regional motivation differences of service sector employees in urban and rural areas in Slovakia. Sci. Pap. Univ. Pardubic. Ser. D Fac. Econ. Adm. 2016, 37, 118–130. [Google Scholar]
  76. Hitka, M.; Závadská, Z.; Jelačić, D.; Balážová, Z. Qualitative indicators of company employee satisfaction and their development in a particular period of time. Drvna Industrija 2015, 66, 235–239. [Google Scholar] [CrossRef]
  77. Kampf, R.; Hitka, M.; Potkány, M. Interannual differences in employee motivation in manufacturing enterprises in Slovakia. Commun. Sci. Lett. Univ. Zilina 2014, 16, 98–102. [Google Scholar]
  78. Hitka, M.; Štípalová, L. Comparing of employees’ motivation level in enterprises of wood working industry with other manufacturing enterprises in Slovak Republic. Drvna Industrija 2011, 62, 185–192. [Google Scholar] [CrossRef]
  79. Bazydlo, A. What Motivates Managers? Money, Yes, but so Much More; Clark University and Center for Creative Leadership: Worcester, MA, USA, 2016. [Google Scholar]
  80. Musa, H.; Debnárová, L.; Musová, Z.; Krištofík, P. Gender equality and corporate governance in Slovakia. Ekon. Manag. 2017, 20, 98–110. [Google Scholar] [CrossRef]
  81. Nguyen, L.D.; Mujtaba, B.G.; Ruijs, A. Stress, task, and relationship orientations of Dutch: Do age, gender, education, and government work experience make a difference? Public Organ. Rev. 2014, 14, 305–324. [Google Scholar] [CrossRef]
  82. Freund, A.M. Age-differential motivational consequences of optimization versus compensation focus in younger and older adults. Psychol. Aging 2006, 21, 240–252. [Google Scholar] [CrossRef]
  83. Peterson, M. What men and women value at work: Implications for workplace health. Gend. Med. 2004, 1, 106–124. [Google Scholar] [CrossRef]
  84. Ryan, R.M.; Deci, E.L. Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemp. Educ. Psychol. 2000, 25, 54–67. [Google Scholar] [CrossRef]
  85. Hitka, M.; Kozubíková, L.; Potkány, M. Education and gender-based differences in employee motivation. J. Bus. Econ. Manag. 2018, 19, 80–95. [Google Scholar] [CrossRef]
  86. Nadeem, M.; Rana, M.S.; Lone, A.H.; Maqbool, S.; Naz, K.; Ali, A. Teacher’s competencies and factors affecting the performance of female teachers in Bahawalpur (Southern Punjab) Pakistan. Int. J. Bus. Soc. Sci. 2011, 2, 217–222. [Google Scholar]
  87. Kanfer, R.; Ackerman, P.L. Aging, adult development, and work motivation. Acad. Manag. Rev. 2004, 29, 440–458. [Google Scholar] [CrossRef]
  88. Poór, J.; Engle, A.D.; Blštáková, J.; Joniaková, Z. Internationalisation of Human Resource Management: Focus on Central and Eastern Europe; Nova Science Publishers: New York, NY, USA, 2018. [Google Scholar]
  89. Kim, S.; Jin-Dong, K.; Yoonseok, S.; Gwang-Hee, K. Cultural differences in motivation factors influencing the management of foreign laborers in the Korean construction industry. Int. J. Proj. Manag. 2015, 33, 1534–1547. [Google Scholar] [CrossRef]
  90. Klement, I.; Hurakova, T. Determining the influence of sample thickness on the high-temperature drying of beech wood (Fagus sylvatica L.). BioResources 2016, 11, 5424–5434. [Google Scholar] [CrossRef]
  91. Vetrakova, M.; Holubekova, K.; Sebova, L. Use of intercultural differences in tourism marketing. In Proceedings of the 18th International Colloquium on Regional Sciences, Hustopece, Czech Republic, 17–19 June 2015. [Google Scholar]
  92. Jigjiddorj, S.; Tsogbadrakh, T.; Choijil, E.; Zanabazar, A. The mediating effect of employee loyalty on the relationship between job satisfaction and organizational performance. In Proceedings of the 11th International Scientific Conference “Economics, Management and Technology in Enterprises 2019”, Zvolen, Slovakia, 9–10 May 2019. [Google Scholar]
  93. Stachová, K.; Papula, J.; Stacho, Z.; Kohnová, L. External partnerships in employee education and development as the key to facing industry 4.0 challenges. Sustainability 2019, 11, 345. [Google Scholar] [CrossRef]
  94. Korcsmaros, E.; Simova, M. Factors affecting the business environment of SMEs in Nitra region in Slovakia. Oeconomia Copernicana 2018, 9, 309–331. [Google Scholar] [CrossRef] [Green Version]
  95. Papula, J.; Kohnová, L.; Papulová, Z. Impact of national culture on innovation activities of companies: A case of Germany, Austria, Switzerland and the Czech Republic. Econ. Ann.-XXI 2018, 169, 26–30. [Google Scholar] [CrossRef]
  96. Zaborova, E.N.; Glazkova, I.G.; Markova, T.L. Distance learning: Students’ perspective. Sotsiologicheskie Issledovaniya 2017, 2, 131–139. [Google Scholar]
  97. Kmecová, I. Didactic efficiency of the textbooks of technical education. In Proceedings of the Joint International IGIP-SEFI Annual Conference 2010, Trnava, Slovakia, 19–22 September 2010. [Google Scholar]
Figure 1. Testing the dependence of the average values between job categories. Note: WCW (white-collar worker), BCW (blue-collar worker).
Figure 1. Testing the dependence of the average values between job categories. Note: WCW (white-collar worker), BCW (blue-collar worker).
Sustainability 11 03509 g001
Table 1. Characteristics of respondents by job category.
Table 1. Characteristics of respondents by job category.
Job CategoryMaleFemaleTotal
Absolute FrequencyRelative FrequencyAbsolute FrequencyRelative FrequencyAbsolute FrequencyRelative Frequency
Manager22512.041829.8340710.94
White-collar worker58831.46116562.94175347.12
Blue-collar worker105656.5050427.23156041.94
Total186950.24185149.763720100.00
Source: Authors’ compilation.
Table 2. Testing the dependence of the average values between genders.
Table 2. Testing the dependence of the average values between genders.
Motivational FactorMaleFemalep-Level
Atmosphere in the workplace4.4814.5900.000015 ***
Good work team4.4784.5720.000864 ***
Fringe benefits4.4144.4070.014822 **
Physical effort at work3.8683.7700.000003 ***
Job security4.3754.4410.074098
Communication in the workplace4.2994.3770.015881 **
Name of the company3.9713.9780.220068
Opportunity to apply one’s own ability4.0444.0820.121283
Workload and type of work4.0944.1850.000284 ***
Information about performance result4.0144.0530.135037
Working hours4.2624.2660.582611
Work environment4.2204.2320.005689 **
Job performance4.1394.1850.009677 **
Career advancement4.0604.0250.042093 **
Competences3.9503.9170.083130
Prestige3.8713.7780.002051 **
Supervisor’s approach4.3944.4620.017969 **
Individual decision-making4.0144.0500.014293 **
Self-actualization4.0174.0550.065170
Social benefits4.2134.2040.099271
Fair appraisal system4.4044.4600.279517
Stress 4.0894.2060.000226 ***
Mental effort4.0274.1010.006000 **
Mission of the company3.8923.9190.004789 **
Region’s development3.8043.8220.224187
Personal growth4.0564.0830.025756 **
Relation to the environment3.9143.8540.030853 **
Free time4.1374.0960.346869
Recognition4.1634.2130.031894
Basic salary4.5764.5920.073355
Note: Single, double, and triple asterisks (*, **, ***) indicate significance at 5%, 1%, and 0.1% level. Source: Authors’ compilation.
Table 3. Average values of selected motivational factors in the job category “manager”.
Table 3. Average values of selected motivational factors in the job category “manager”.
No.MaleFemale
Motivational FactorAverageMotivational FactorAverage
1Atmosphere in the workplace4.569Atmosphere in the workplace4.654
2Basic salary4.560Good work team4.604
3Good work team4.542Basic salary4.604
4Fair appraisal system4.533Supervisor’s approach4.533
5Supervisor’s approach4.507Fair appraisal system4.522
6Job security4.476Job security4.484
7Communication in the workplace4.427Communication in the workplace4.478
8Fringe benefits4.413Individual decision making4.396
9Individual decision making4.369Fringe benefits4.385
10Personal growth4.369Selfactualization4.363
Note: Single, double, and triple asterisks (*, **, ***) indicate significance at 5%, 1%, and 0.1% level. Source: Authors’ compilation.
Table 4. Testing the dependence of the most important motivational factors in terms of gender in the job category “manager”.
Table 4. Testing the dependence of the most important motivational factors in terms of gender in the job category “manager”.
Motivation Factorp-Level
Atmosphere in the workplace0.585
Good work team0.332
Fringe benefits0.066
Job security0.879
Communication in the workplace0.931
Supervisor’s approach0.373
Individual decision making0.573
Self-actualization0.334
Fair appraisal system0.198
Personal growth0.447
Basic salary0.994
Source: Authors’ compilation.
Table 5. Average values of selected motivational factors in the job category “white-collar worker”.
Table 5. Average values of selected motivational factors in the job category “white-collar worker”.
No.MaleFemale
Motivational FactorAverage Motivational FactorAverage
1Basic salary4.573Basic salary4.628
2Atmosphere in the workplace4.457Atmosphere in the workplace4.603
3Good work team4.457Good work team4.596
4Fringe benefits4.425Fair appraisal system4.493
5Supervisor’s approach4.374Supervisor’s approach4.481
6Fair appraisal system4.357Job security4.434
7Communication in the workplace4.320Fringe benefits4.426
8Job security4.316Communication in the workplace4.400
9Working hours4.219Working hours4.276
10Work environment4.204Recognition4.264
Source: Authors’ compilation.
Table 6. Testing the dependence of the most important motivational factors in terms of gender in the job category “white-collar worker”.
Table 6. Testing the dependence of the most important motivational factors in terms of gender in the job category “white-collar worker”.
Motivational Factorp-level
Atmosphere in the workplace0.000 ***
Good work team0.001 ***
Fringe benefits0.226
Job security0.025 **
Communication in the workplace0.095
Supervisor’s approach0.004 **
Working hours0.519
Work environment0.694
Fair appraisal system0.007 **
Basic salary0.292
Note: Single, double, and triple asterisks (*, **, ***) indicate significance at the 5%, 1%, and 0.1% level. Source: Authors’ compilation.
Table 7. Testing the selected motivational factors in terms of gender in the job category “white-collar worker”.
Table 7. Testing the selected motivational factors in terms of gender in the job category “white-collar worker”.
Motivational FactorStatistical Indicator
Atmosphere in the workplacePearson’s chi-square22.3240
Degree of freedomdf = 4
p-levelp = 0.000173 ***
Good work teamPearson’s chi-square18.3508
Degree of freedomdf = 4
p-levelp = 0.001054 **
Job securityPearson’s chi-square11.1819
Degree of freedomdf = 4
p-levelp = 0.024594 **
Supervisor’s approachPearson’s chi-square15.3366
Degree of freedomdf = 4
p-levelp = 0.004052 **
Fair appraisal systemPearson’s chi-square13.9748
Degree of freedomdf = 4
p-levelp = 0.007376 **
Note: Single, double, and triple asterisks (*, **, ***) indicate significance at 5%, 1%, and 0.1% level. Source: Authors’ compilation.
Table 8. The population proportion of individual score values of selected motivational factors in terms of gender in the job category “white-collar worker”.
Table 8. The population proportion of individual score values of selected motivational factors in terms of gender in the job category “white-collar worker”.
Motivational FactorGenderValues of ImportanceTotal
1
Unimportant
2
Slightly Important
3
Medium Important
4
Important
5
Very Important
Atmosphere in the workplaceMale3855173349588
1%1%9%29%59%100%
Female36533277761165
0%1%5%28%67%100%
Total61410850011251753
Good work teamMale3741204333588
1%1%7%35%57%100%
Female16493517581165
0%1%4%30%65%100%
Total4139055510911753
Job securityMale51277192302588
1%2%13%33%51%100%
Female10121073696671165
1%1%9%32%57%100%
Total15241845619691753
Supervisor’s approachMale11253222300588
0%2%9%38%51%100%
Female718823596991165
1%2%7%31%60%100%
Total8301355819991753
Fair appraisal systemMale61957183323588
1%3%10%31%55%100%
Female1218863177321165
1%2%7%27%63%100%
Total183714350010551753
Source: Authors’ compilation.
Table 9. Descriptive statistics and 95% confidence intervals for selected motivational factors in terms of gender in the job category “white-collar workers”.
Table 9. Descriptive statistics and 95% confidence intervals for selected motivational factors in terms of gender in the job category “white-collar workers”.
Motivational FactorGenderN AverageStandard DeviationConfidence Interval
−95.00%+95.00%
Atmosphere in the workplaceMale5884.4570.7614.3964.519
Female11654.6030.6274.5674.639
Good work teamMale5884.4570.7224.3994.516
Female11654.5960.6054.5614.631
Job securityMale5884.3160.8394.2484.384
Female11654.4340.7714.3904.479
Supervisor’s approachMale5884.3740.7474.3144.435
Female11654.4810.7454.4384.524
Fair appraisal systemMale5884.3570.8614.2874.427
Female11654.4930.7844.4484.538
Source: Authors’ compilation.
Table 10. Expected and residual frequencies of selected motivational factors in terms of gender in the job category “white-collar worker”.
Table 10. Expected and residual frequencies of selected motivational factors in terms of gender in the job category “white-collar worker”.
Motivational FactorFrequencyGenderValues of Importance
1
Unimportant
2
Slightly Important
3
Medium Important
4
Important
5
Very Important
Atmosphere in the workplaceExpected Male2536168377
Female4972332748
Residual Male13195−28
Female−1−3−19−528
Good work teamExpected Male1430186366
Female3960369725
ResidualMale231118−33
Female−2−3−11−1833
Job securityExpected Male5862188325
Female1016122373644
ResidualMale04154−23
Female0−4−15−423
Supervisor’s approachExpected Male31045195335
Female52090386664
ResidualMale−22827−35
Female2−2−8−2735
Fair appraisal systemExpectedMale61248168354
Female122595332701
ResidualMale07915−31
Female0−7−9−1531
Source: Authors’ compilation.
Table 11. Average values of selected motivational factors in the job category “blue-collar worker”.
Table 11. Average values of selected motivational factors in the job category “blue-collar worker”.
No.MaleFemale
Motivational FactorAverage Motivational FactorAverage
1Basic salary4.580Atmosphere in the workplace4.540
2Atmosphere in the workplace4.475Basic salary4.524
3Good work team4.475Good work team4.506
4Fringe benefits4.408Job security4.440
5Fair appraisal system4.403Supervisor’s approach4.393
6Job security4.385Fringe benefits4.371
7Supervisor’s approach4.382Fair appraisal system4.363
8Working hours4.267Communication in the workplace4.288
9Communication in the workplace4.259Working hours4.242
10Social benefits4.252Social benefits4.212
Source: Authors’ compilation.
Table 12. Testing the dependence of the most important motivational factors in terms of gender in the job category “blue-collar worker”.
Table 12. Testing the dependence of the most important motivational factors in terms of gender in the job category “blue-collar worker”.
Motivational Factorp-Level
Atmosphere in the workplace0.256
Good work team0.609
Fringe benefits0.139
Job security0.604
Communication in the workplace0.408
Supervisor’s approach0.351
Working hours0.625
Fair appraisal system0.339
Social benefits0.651
Basic salary0.117
Source: Authors’ compilation.

Share and Cite

MDPI and ACS Style

Lorincová, S.; Štarchoň, P.; Weberová, D.; Hitka, M.; Lipoldová, M. Employee Motivation as a Tool to Achieve Sustainability of Business Processes. Sustainability 2019, 11, 3509. https://doi.org/10.3390/su11133509

AMA Style

Lorincová S, Štarchoň P, Weberová D, Hitka M, Lipoldová M. Employee Motivation as a Tool to Achieve Sustainability of Business Processes. Sustainability. 2019; 11(13):3509. https://doi.org/10.3390/su11133509

Chicago/Turabian Style

Lorincová, Silvia, Peter Štarchoň, Dagmar Weberová, Miloš Hitka, and Martina Lipoldová. 2019. "Employee Motivation as a Tool to Achieve Sustainability of Business Processes" Sustainability 11, no. 13: 3509. https://doi.org/10.3390/su11133509

APA Style

Lorincová, S., Štarchoň, P., Weberová, D., Hitka, M., & Lipoldová, M. (2019). Employee Motivation as a Tool to Achieve Sustainability of Business Processes. Sustainability, 11(13), 3509. https://doi.org/10.3390/su11133509

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop