Acta Universitatis Danubius. Œconomica, Vol 16, No 1 (2020)

Analyzing Hotel Management from the Perspective of Management and Employees, and Their Impact on Tourist Satisfaction with Hotel Services in Kosovo



Alberta Tahiri1; Fari Bushi2 & Idriz Kovaçi3



Abstract: Case study: 5 star Hotel’s in Kosovo. The impact of the professional management of the Hotelier sector by the management and the positive climate created by the workers has had a very positive positive impact on their performance at work, their satisfaction with the workplace and their motivation. This has affected the high satisfaction of tourists with the services provided by the latter. The survey involved a total of 21 managers and 100 employees, while 200 tourists were also surveyed where their satisfaction was measured. The research was conducted in the top 4 Hotels in Kosovo over a period of 2 months, were data performed by using SPSS (version 25), and correlation and regression were used to confirm the hypotheses. On the other hand, demographic data are presented by number of participation and their percentage. The results show that managers’ motivation and employee satisfaction have a positive impact on enhancing employee performance ( rho=.361**, p value =.001). On the other hand in the second hypothesis The selection and selection of managers has a positive impact on the motivation of Hotel Managers. ( rho=.208*, p value =.049 ) and in the third hypothesis Hotel Workers performance depends directly on the training provided by the hotels themselves and their selection and selection at work. ( R=.330, p value = .007 Finally we say that proper management has a significant impact on the working climate of the hotels and affects the performance of the employees, and this performance is reflected in the satisfaction of the tourists with the services.

Keywords: Management; Hotels; Perspective of Management and Employees; Impact of Tourist Satisfaction

JEL Classification:





1. Introduction

Through this research we will highlight the successful Hotel Management and Tourist Satisfaction both from the perspective of management and employees. The philosophy of modern business and tourism development is geared towards tourists, guests and consumers and meets their needs and desires. According to ( Dr.Alberta Tahiri dhe Dr.Idriz Kovaçi ) we say that modern hospitality is distinguished from other related activities in the area of providing accommodation through the continuous maintenance of the quality of services and the introduction of new types of services that are not characteristic of the hospitality business in Hospitality. All these to enhance the quality of basic services, accommodation, meet the needs of today’s modern customers (customers). The catering industry in the demanding market and its dynamics have influenced this to increase the level of competition that depends on improving the quality of hotel products and services. Hotel companies that are concentrated. in quality, and thus the satisfaction of their guests, can be successful in the Hotel market. (Dr.sc. ALBERTA KELMENDI TAHIRI, Prof.dr.IDRIZ KOVAÇI, 2017)



2. Literature Review

According to various experts, they conceive of modern industry in various forms, which we will present below and which are very specific in terms of the description of the great authors. According tp (Lesley Pender and Richard Sharpley, 2005) the concept of the modern hotel industry encompasses all tourism entities that provide guest accommodation and other services for tourist consumption, and are organized into a variety of forms of doing business to meet the needs and desires of the customer and achieve set economic goals and best possible business results. (Lesley Pender and Richard Sharpley, 2005). According to (Cerović, 2003) hotel management, economically under market conditions to achieve commercial effects, offers accommodation and other hotel services, which it uses to meet the needs and motivations of guests and visitors, and to provide a standard of living for them. staff and management. (Cerović, 2003)

Accroding to (Bunja, 2008), he points out that staying in hotels at the destination of choice, the hotel industry offers tourists rest and relaxation, enables business people to make business contacts, create seminar conditions for attendees of various professional, scientific conferences, seminars and gatherings political, enables visitors to learn about natural and cultural attractions and historic monuments and food and beverage services for area residents, as well as various amusement facilities.

According to (Vrtiprah, V., Pavlić, I.(, 2005) The hotel industry, as well as modern economic activity, is an extremely important driver of economic development, especially in underdeveloped and developing countries. In fulfilling its functions, the catering industry is associated with many other economic activities (trade, transport, industry, travel agencies), and differs from other industries in that it offers its services in specific facilities.

We say that the philosophy of modern business and tourism development is geared towards tourists, guests and consumers and meets their needs and desires. Modern hospitality is distinguished from other related activities in the area of ​​providing accommodation through the continuous maintenance of service quality and the introduction of new types of services that are not characteristic of the hospitality business, all of which enhance the quality of services. basic accommodation and meet the needs of modern customers (clients). (Bunja, 2008) (Cerović, 2003) (Lesley Pender and Richard Sharpley, 2005)

The survival of the hotel industry in the demanding and dynamic market and raising the level of competition depends on improving the quality of hotel products and services. Quality-focused hotel companies, and thus the satisfaction of their guests, can be successful in the demanding tourist market. (Dr.sc. ALBERTA KELMENDI TAHIRI, Prof.dr.IDRIZ KOVAÇI, 2017)

Accroding to (Bunja, 2008) & (DeFillippi, 2002) the modern hotel industry, namely the breadth of the range of hotel services, is conditioned by the category of hotel facility, size of the hotel facility, hotel location, weather business aspect of the hotel, complexity of the hotel organizational structure and business policy in market Modern hotel services can be classified into:

1. Accommodation services - provided in hotel accommodation units - apartments and rooms;

2. Cultural - entertainment services - hotels often host classical music concerts, or hosts of popular artists, exhibitions, have a library, conference facilities for entertainment and games, especially during bad weather, visitors are offered specially prepared entertainment programs (animation );

3. Commercial services - guests are offered the opportunity to purchase souvenirs, newspapers, various personal necessities, up to high fashion boutique and the like;

4. Trade and Services - Hotel facilities often offer hairdressing, ornamental and nail salons, photographers, watches and others; health and other services - hotels offer guests the opportunity of diagnosis, treatment, rehabilitation and more. (Bunja, 2008) (DeFillippi, 2002)

Accrding to (Berry L.L.,Parasuraman ,A., 1991)

In hotel services we mean the diversity and complexity in the course of business operations (processes) in shaping and meeting the demands and needs of customers (clients). The quality of hotel services includes all those procedures that will result in satisfied guests. This includes the following key aspects:

  1. Service culture - the company must live and radiate a clear service culture toward the outside and the interior, and control management in particular should set an example for delivering a service culture.

  2. Courtesy - all employees should have it, especially those who are in direct contact with the guests; kindness will be greatly helped if staff are put in the role of guest.standardization.

  3. Expertise - service personnel must be competent; this applies equally to their professional knowledge and their attitude towards guests.complaints

According to (Gustafsson, A., Johnson, M., 2006) & (Black, S. J., Steers, R. M.(, 1994) & (Tudor, 2006) emphasize that "Top" and "middle" hotel and tourism management determines the vision, mission, goals, strategies and culture of behavior in each hotel. Gjithashtu thonë se menaxhim serioz hoteli "i lartë", duke pasur parasysh konkurrencën e pamëshirshme dhe nevojat dhe dëshirat e reja të konsumatorit duhet të përcaktojë një "politikë speciale" për përmirësimin e cilësisë së shërbimeve hoteliere përmes "programeve të cilësisë konstruktive" që duhet të bëhen një faktor i rëndësishëm në biznesin e hotelit . Do program për të përmirësuar cilësinë e shërbimeve hoteliere duhet të përmbajë:

  1. Managing hotel work processes. Hotel services consist of a number of processes (procedures) to be constantly managed and maintained and improved in order to eliminate defects and errors in order to achieve greater customer satisfaction. ‘For example, elaborating on the Ritz-Carlton service process helps employees better understand how to provide high quality hotel services. (Gustafsson, A., Johnson, M., 2006)

  2. Satisfaction of hotel employees. At the hotel the focus of quality is transferred to service providers and the quality of services depends on the knowledge, skills, experience, appearance, behavior and other characteristics of the employees. Educated, professionally trained, highly motivated and loyal employees create and maintain the quality that affects our guests’ satisfaction. In order to achieve high quality services, it is necessary to have satisfied employees because only they can establish good relationships with guests and provide higher levels of service. Job satisfaction stems from employees’ perceptions of their work and what they get about the work performed and the work environment. ‘‘ Job satisfaction is the attitude of employees towards work, job rewards, social, organizational and physical characteristics of the environment in which they perform their jobs.(Black, S. J., Steers, R. M.(, 1994)

  3. Professional training of hotel staff. Needs for continuous improvement and additional specialized employee education are encouraged by changing guest motives and habits, changes that will come about as a result of technological developments and changes in the environment (competition).(Black, S. J., Steers, R. M.(, 1994)

  4. Development of teamwork in the hotel. The team is a small group of people who have common goals and work together to achieve them. ‘Developing team spirit and teamwork can have a positive impact on improving the quality of hotel services and the positive’ atmosphere ‘in the hotel business. (Tudor, 2006)

According to (A. Chandrakumara, and P. Sparrow, 2004) By designing, presenting and controlling a "special program" of improving hotel service quality, hotel management can have a positive impact on increasing customer and human resource satisfaction, increasing competition and market power of the hotel, rationalizing of operating costs and enhances the hotel’s reputation and value in the tourist market. Technology impacts HRM to the extent that the performance and perspective of technological development modify HR practices. National Culture of Culture plays a pivotal role in the organization’s preferences in the proper structure and development of the method for the effectiveness of human practice.

Also the degree of interaction between technology and human resources affects the ways we work, the roles we undertake, and the interactions through which work is done (DeFillippi, 2002) , facilitates the growth of a multinational enterprise (F. Verkinderen, 25, 4, 19-29.) and it also generates simultaneous challenges between a geographically dispersed workforce. It can be concluded that technology has many advantages in business and is the nucleus of industrial growth. (T.N Garavan, J.P Wilson, C. Cross and R. Carbery R, 2008).

According to (B. Kane, and I. Palmer, 1995) which states that in an organization, HR practices are differentiated from the classification based on manufacturing and service organizations which is often used to analyze HRM practices. Human resource activities have transcended international boundaries resulting in a cross-border exchange of human resource management. Most importantly, this has been the way to pave the way to modify and practice in a different environment.



3. Resarch Methodology

This research coincides with the quantitative style of research and analyzes the importance and effects of hotel management from the perspective of management and employees, as well as the impact of the latter on the satisfaction of tourists with hotel services in Kosovo. The survey involved a total of 21 managers from four hotels, 100 employees and 200 tourists.





3.1. Research Intruments

The instrument used in this research is the questionnaire which was conducted with the three parties, as managers, employees and tourists. The same questionnaire was used for managers and employees, except demographic and demographic specifics, the rest related to Hotel Human Resource Satisfaction and Management, Job Satisfaction and Activity in the Organization, Training in the Organization, Performance Evaluation, Selection , communication with human resources and employee motivation.

3.2. Specifications of Research

Data were analyzed using SPSS version 25. Statistical parameters in this research were used mean values, standard deviation, and Alpha Cronbach’s reliability test and normality test were performed to confirm the hypotheses. Spearman correlation was used for testing the hypotheses, after being proved to have non-parametric distributions. The research was initially analyzed through demographic and descriptive analyzes, then the reliability test (Alpha Cronbach’s) and the normality test (Kolmogorov Smirnov & Shapiro Wilk). After we tested the data, we found abnormal distributions and non-parametric tests were used to validate the hypotheses.

3.3. Samples

The survey included four Hotels, Hotel Dukagjini, Hotel Emerald, Hotel Swiss and Hotel Golden, with 5 - 6 managers, 25 staff and 50 tourists from each Hotel invited.



4. Empirical Research Findings

4.1. Demographic results

From the results below we can see that a total of 21 managers from 4 5 star hotels in the Republic of Kosovo participated in the survey. Of these , 16 were males and 5 females, while the age group was 18-25 years 5 respondents or 23.8%, 11 were 26-35 years old or 52.4% and 5 were 36-45 years old or 23.8%. There were 10 respondents or 47.6% with a bachelor’s degree and 11 of them had a master’s or doctorate or 52.4%. Whereas employees see 90 employees involved, of which 54 were male or 60% and 36 female or 40%. There were 12 workers or 13.3% in the age group 18-25 years old, 51 were in the age group 26-36 years or 56.7% and 19 were in the age group 36-45 years or 21.1% and over 45 years old were 8 workers or 8.9%. with low education level were 2 employees or 2.2%, 60 were with secondary education or 66.7%, 25 with bachelor degree or 27.8% and 3 with superior (master or doctorate) or 3.3%.

Tabel 1. Participant Demographic Analysis, Manager and Worker Differences


Managers

Employee

Gender

N

%

N

%

Male

16

76.2

54

60.0

Female

5

23.8

36

40.0

Age

N

%

N

%

18-25

5

23.8

12

13.3

26-35

11

52.4

51

56.7

36-45

5

23.8

19

21.1

Over 45

-

-

8

8.9

Level of education

N

%

N

5

Lower school

-

-

2

2.2

High school

-

-

60

66.7

Bachelor

10

47.6

25

27.8

Master or PHD

11

52.4

3

3.3








4.2. Descriptive results – tourists

Regarding tourists, we see that males are 123 or 61.5%, females are 77 or 38.5%, of which 18.25 are 20.5%, 84 are 26-35 or 42%, 42 are 36-45 or 21% and over 45 are 33 tourists or 16.5%. Urban tourists were 128 tourists or 64% and 72 were rural or 36%. There were 31 or 15.5% with a low level of education, 39 with a secondary or 19.5%, 67 with a bachelor’s degree or 33.5% and 63 with a higher or 31.5%.

Tabel 2. Demographic Analysis- Tourists

Gender

N

%

Male

123

61.5%

Female

77

38.5%




Age

N

%

18-25

41

20.5%

26-35

84

42.0%

36-45

42

21.0%

Over 45

33

16.5%




Vendbanimi

N

%

Urban

128

64.0%

Rural

72

36.0%




Level of education

N

5

Lower school

31

15.5%

High school

39

19.5%

Bachelor

67

33.5%

Master or PHD

63

31.5%






4.3. Satisfaction with Services - Tourists

Below i present the results of tourists regarding their satisfaction with managerial staff where average satisfaction level is 4.40 with standard deviation of 0.491, then medical staff have an even higher level of satisfaction or 4.67 and standard deviation of 0.471 , the employees of the organization have an average of 4.88 and a standard deviation of 0.32, the services provided are an average of 4.79 and a standard deviation of 0.40, the overall cleanliness was at an average level of 4.61 and a standard deviation of 0.48, the leisure activities averaged 4.79. and standard deviation of 0.40, then accommodation with mean of 4.70 and deviation of 0.45, tourist guides with mean of 4.58 and standard deviation of 0.49, restaurant with mean of 4.67 and deviation of 0.47, mean cooking of 4.90 and standard deviation of 0.44 and transport with a mean of 4.88 and a deviation of 0.39.

Tabel 3. Tourist Satisfaction


N

Mean

Std. Deviation

Managerial staff have professional and responsible behavior.

200

4.40

0.491

The medical staff is professional.

200

4.67

0.471

The employees of the organization are professional.

200

4.88

0.326

The services provided are top notch.

200

4.79

0.408

Cleanliness is generally high.

200

4.61

0.489

The activities that are organized are high level

200

4.79

0.408

Accommodation is top notch.

200

4.70

0.459

The tour guide / guide is top notch.

200

4.58

0.495

Sales services are satisfying.

200

4.58

0.495

Restaurants offer quality services.

200

4.67

0.471

Cooking and food is enjoyable.

200

4.90

0.448

Transport is fast and secure

200

4.88

0.391

Valid N (listwise)

200







4.4. Reliabiliti analysis

ALPHA CRONBACH’S

The following results indicate that the overall level of confidence is at a high level, with senior managers having a confidence level of 0.857 and employees averaging 0.829. From this we conclude that our data can be used to support hypotheses.

Tabel 4. Alpha Cronbach’s analysis

Group

Managers

Employee

Alpha Cronach’s

Satisfaction with human resource management

0,705

0,708

Satisfaction with the workplace and work in this organization.

0,923

0,925

TRAINING IN THE ORGANIZATION

0,937

0,879

PERFORMANCE ASSESSMENT

0,964

0,885

SELECTION (EMPLOYMENT SELECTION)

0,889

0,699

Communication with human resources

0,765

0,780

Motivation

0,972

0,938

Mean

0,857

0,829



4.5. Normality test

The following results show that in all cases through the Kolmogorov-smirnov and Shapiro-Wilk test, the data have abnormal distributions, which obliges us to test our data through non-parametric statistical tests.

Tabel 4. Normality test - Kolmogorov Smirnov & Shapiro Wilk

Group

Managers

Employee

Kolmogoroc-Smirnov

Shapiro-Wilk

Kolmogoroc-Smirnov

Shapiro-Wilk

Satisfaction with human resource management

0.021

0.005

0.000

0.000

Satisfaction with the workplace and work in this organization.

0.000

0.000

0.000

0.000

TRAINING IN THE ORGANIZATION

0.000

0.000

0.000

0.000

PERFORMANCE ASSESSMENT

0.000

0.000

0.000

0.000

SELECTION (EMPLOYMENT SELECTION)

0.000

0.000

0.000

0.000

Communication with human resources

0.001

0.000

0.000

0.000

Motivation

0.000

0.000

0.000

0.000



4.6. Rezultatet E Hipotezave

H01. Motivation and employee satisfaction by managers have a positive impact on enhancing the performance of employees.

To prove the above hypothesis, I used Partial Correlation, where the dependent variable is performance, whereas independent are motivation and job satisfaction.

The results show that we have a high positive correlation ( rho=0.361, p value=.001 <0.1% ), which, statistically, motivation and job satisfaction have a positive effect on the performance of employees.

So we accept the hypothesis that Motivation and employee satisfaction by managers have a positive impact on enhancing employee performance.

Tabel 5. Correlation – First Hypothesis

Correlations

Control Variables

1

2

Performance

Motivation

Correlation

1.000

0.361

Significance (2-tailed)

.

0.001

df


87

Satisfaction

Correlation


1.000

Significance (2-tailed)


.

df


0


F igure 1. Korelacioni - Hipoteza e dytë

H02. The selection and selection of managers has a positive impact on the motivation of Hotel managers.

To validate the above hypothesis I used Spearman correlation, where the independent variable is selection and selection, whereas motivation is the dependent variable. From the research results we find that selection and selection have a high positive impact on employee motivation ( rho=0.208, p value = .049 < 0.5% ), thus we accept the hypothesis that the selection and selection of managers has a positive impact on the motivation of Hotel managers.

T abela 6. Correlation – Second Hypothesis

Correlations


1

2

Spearman’s rho

Selection of managers

Correlation Coefficient

1.000

0.208*

Sig. (2-tailed)

.

0.049

N

90

90

Motivation

Correlation Coefficient

0.208*

1.000

Sig. (2-tailed)

0.049

.

N

90

90

*. Correlation is significant at the 0.05 level (2-tailed).

Figure 2. Korelacioni - Hipoteza e dytë



H03. Hotel staff performance depends directly on the training provided by the hotels themselves and their selection and selection.

To validate the above hypothesis, I used multiple linear regression, where we present the results below. In the first case we have the dependence of the performance of the employees on the training (β = 0.330, p =.003 ) which implies that at 1% confidence level, employee performance is dependent on training, while selection and selection (β = -0.119, p =.243 ) indicates that there is no dependency and that this does not affect the performance of workers. From these results we conclude that the performance of Hotel staff is statistically significant depending directly on the training provided by the hotels themselves and their selection and selection.

Tabela 7. Regression-Third hypothesis

Independent vaiable

Modeli 1

B

S.H.

β

Sig.

Trainings

0.260

0.085

0.308

0.003

Selection

-0.106

0.090

-0.119

0.243

R

0.330

0.109

0.089

F

5.333

ANOVA (Sig.)

0.007

Dependent variable: Performance



Figure 3. Korelacioni - Hipoteza e tretë

5. Conclusion and recommendation

This research provides a realistic overview of the state of Kosovo’s Hotel Services, a positive impetus for the country’s development. The first results show that we have high satisfaction from the aspect of Hotel Managers as well as employees. In a broader context, we see that both parties have expectations and have good cooperation. On the other hand, we find that tourists are satisfied with the services provided and this satisfaction is a very positive signal for Kosovar Hotel.The average level of tourist satisfaction indicates that the services provided are at a high and professional level. Demographic analyzes point to a gender diversity in employment, with more males than females in the role of managers and workers, with age and education levels relatively similar. The hypotheses show an interesting overview of the impact on the sector. From the first hypothesis we see that we have a correlation ( rho=.361**, p value =.001 ) between the relationship between motivation and job satisfaction with performance at work. So, motivating the employees and their satisfaction with the work they do, leads to a positive performance at work and this is satisfactory in Kosovar Hotel.

On the other hand, from the second hypothesis we have a correlation between Selection and selection and motivation at work ( rho=.208**, p value =.049 which means that if we are careful about the selection of employees, we will have good motivation in the employees which affects their performance at work. In the third hypothesis I performed a regression showing a positive impact of training on job performance, but not selection and selection, although in general context we have a correlation. As a final conclusion, there is a positive climate of cooperation between managers and workers in Kosovo, which has a positive impact on their performance and motivation for work, while on the other hand this has resulted in a high level of tourist satisfaction. with the services provided We recommend that this positive spirit of cooperation be promoted and that even better conditions are created for Hotel Tourism to reach its pinnacle of success. Also, in the future we propose to conduct direct visits, interviewing owners, investors and thus create an even broader picture of this field.





Reference

Berry, L.L. & Parasuraman ,A. (1991). Marketing Services. New York: The Free Press.

Black, S. J. & Steers, R. M.(. (1994). Organizational Behaviour, Fifth Edition,. New York: Harper Collins College Publishers.

Bunja, D. (2008). Organizacija poslovanja u hotelijerstvu i turizmu. Zagreb: Školska knjiga.

Cerović, Z. (2003). Hotelski menadment. Fakultet za hotelski i turistčki menadment.

Chandrakumara, A. & Sparrow P. (2004). Work Orientation as an Element of National Culture and Its Impact on HRM Policy –Practice Design Choices, International Journal of Manpower, 25, 6, 564-589.

DeFillippi, R. (2002). Organisational Models for Collaboration in New Economy. Human Resource Planning, 25, 4, 7-18.

Dr.sc. Alberta Kelmendi Tahiri & Prof.Dr.Idriz Kovaçi. (2017). Menaxhimi Në Turizëm Qasje Teorike Menaxheriale. Pejë: Qendra Kërkimore, Pejë.

Garavan T.N.; Wilson; J.P, Cross C. & Carbery R. R. (2008). Mapping The context and Practice of Training, Development and HRD IN European Call Centers , Journal of European Industrial Training, 32, 8, 612-728.

Gustafsson, A. & Johnson, M. (2006). Natjecanje u uslunoj ekonomiji, Zagreb,Mate d.o.o.

Kane, B. & Palmer I. (1995). Strategic HRM or Managing Employment Relationship?. International Journal of Manpower, 16, 5, 6-21.

Lesley Pender & Richard Sharpley (2005). The Management of Tourism. London-THusand Oaks-New Delhi: SAGE Publications.

Tudor, G. S. (2006). Maneder i pobjednički tim: čarolija timskog rada. 3. izd. Zagreb: M.E.P. Consult.

Verkinderen, F. & Altman, Y. (2002). Leisureplanet.com – Organization and HRM in the New Economy. Human Resource Planning, 25, 4, 19-29.

Vrtiprah, V. & Pavlić, I.(. (2005). Menaderska ekonomija u hotelijerstvu. Dubrovnik: Sveučilište u Dubrovniku.





Appendix – SPSS Outputs

FREQUENCIES VARIABLES=DEMO1 DEMO2 DEMO4 DEMO5 TVA1 TVA2 TVA3

/ORDER=ANALYSIS.

Frequencies

Notes

Output Created

09-DEC-2019 22:14:50

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

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Weight

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Split File

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N of Rows in Working Data File

21

Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data.

Syntax

FREQUENCIES VARIABLES=DEMO1 DEMO2 DEMO4 DEMO5 TVA1 TVA2 TVA3

/ORDER=ANALYSIS.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02


[DataSet1] C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav


Statistics


Gender

Age

Place of living

Level of education

Work job:

Position in the company:

How have you been recruited in the organization where you work now?

N

Valid

21

21

21

21

21

21

21

Missing

0

0

0

0

0

0

0




Frequency Table

Gender


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

16

76.2

76.2

76.2

Female

5

23.8

23.8

100.0

Total

21

100.0

100.0



Age


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

18-25 age

5

23.8

23.8

23.8

26-35 age

11

52.4

52.4

76.2

36-45 age

5

23.8

23.8

100.0

Total

21

100.0

100.0



Place of living


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Urban

21

100.0

100.0

100.0


Level of education


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Bachelor’s Degree

10

47.6

47.6

47.6

Superior level (master’s or doctorate))

11

52.4

52.4

100.0

Total

21

100.0

100.0



Work job:


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Head office of the company

15

71.4

71.4

71.4

Local company office

6

28.6

28.6

100.0

Total

21

100.0

100.0



Position in the company:


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Top menaxher

9

42.9

42.9

42.9

Sektorial

7

33.3

33.3

76.2

Administrate

5

23.8

23.8

100.0

Total

21

100.0

100.0



How have you been recruited in the organization where you work now?


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Online

8

38.1

38.1

38.1

Recommandation

10

47.6

47.6

85.7

I’m self-employed

3

14.3

14.3

100.0

Total

21

100.0

100.0




FREQUENCIES VARIABLES=DEMO1 DEMO2 DEMO3 DEMO4 TVA1 TVA2 TVA3

/ORDER=ANALYSIS.

Frequencies

Notes

Output Created

09-DEC-2019 22:15:23

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data.

Syntax

FREQUENCIES VARIABLES=DEMO1 DEMO2 DEMO3 DEMO4 TVA1 TVA2 TVA3

/ORDER=ANALYSIS.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.57



[DataSet2] C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Statistics


Gender

Age

Place of living

Level of education

Work job:

Position in the company:

How have you been recruited in the organization where you work now?

N

Valid

90

90

90

90

90

90

90

Missing

0

0

0

0

0

0

0



Frequency Table

Gender


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

54

60.0

60.0

60.0

Female

36

40.0

40.0

100.0

Total

90

100.0

100.0



Age


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

18-25 age

12

13.3

13.3

13.3

26-35 age

51

56.7

56.7

70.0

36-45 age

19

21.1

21.1

91.1

Mbi 45 age

8

8.9

8.9

100.0

Total

90

100.0

100.0



Place of living


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Urban

59

65.6

65.6

65.6

Rural

31

34.4

34.4

100.0

Total

90

100.0

100.0



Level of education


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Low level of education (primary education or less)

2

2.2

2.2

2.2

Secondary level (high school)

60

66.7

66.7

68.9

Bachelor’s Degree

25

27.8

27.8

96.7

Superior level (master’s or doctorate))

3

3.3

3.3

100.0

Total

90

100.0

100.0




Work job:


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Head office of the company

50

55.6

55.6

55.6

Local company office

33

36.7

36.7

92.2

Field (field staff, we don’t have our own office)

7

7.8

7.8

100.0

Total

90

100.0

100.0




Position in the company:


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Employee

90

100.0

100.0

100.0


How have you been recruited in the organization where you work now?


Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Online

42

46.7

46.7

46.7

Recommandation

40

44.4

44.4

91.1

I’m self-employed

5

5.6

5.6

96.7

Other

3

3.3

3.3

100.0

Total

90

100.0

100.0




DATASET ACTIVATE DataSet1.

RELIABILITY

/VARIABLES=TVO12.1 TVO12.2 TVO12.3 TVO12.4 TVO12.5 TVO12.6 TVO12.7 TVO12.8 TVO12.9 TVO12.10

TVO12.11

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.




Reliability

Notes

Output Created

09-DEC-2019 22:16:36

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

21

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=TVO12.1 TVO12.2 TVO12.3 TVO12.4 TVO12.5 TVO12.6 TVO12.7 TVO12.8 TVO12.9 TVO12.10

TVO12.11

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.07


[DataSet1] C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

21

100.0

Excludeda

0

0.0

Total

21

100.0

a. Listwise deletion based on all variables in the procedure.




Reliability Statistics

Cronbach’s Alpha

N of Items

0.705

11


RELIABILITY

/VARIABLES=KVP1 KVP2 KVP3 KVP4 KVP5 KVP6 KVP7 KVP8 KVP9 KVP10 KVP11 KVP12 KVP13 KVP14 KVP15 KVP16

KVP17 KVP18

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:16:46

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

21

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=KVP1 KVP2 KVP3 KVP4 KVP5 KVP6 KVP7 KVP8 KVP9 KVP10 KVP11 KVP12 KVP13 KVP14 KVP15 KVP16

KVP17 KVP18

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.01


Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

21

100.0

Excludeda

0

0.0

Total

21

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.923

18


RELIABILITY

/VARIABLES=TNO1 TNO2 TNO3 TNO4 TNO5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability


Notes

Output Created

09-DEC-2019 22:16:55

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

21

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=TNO1 TNO2 TNO3 TNO4 TNO5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.06



Warnings

Scale has zero variance items.


Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

21

100.0

Excludeda

0

0.0

Total

21

100.0

a. Listwise deletion based on all variables in the procedure.



Reliability Statistics

Cronbach’s Alpha

N of Items

0.937

5


RELIABILITY

/VARIABLES=VLP1 VLP2 VLP3 VLP4 VLP5 VLP6 VLP7 VLP8 VLP9 VLP10 VLP11 VLP12 VLP13 VLP14

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:17:12

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

21

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=VLP1 VLP2 VLP3 VLP4 VLP5 VLP6 VLP7 VLP8 VLP9 VLP10 VLP11 VLP12 VLP13 VLP14

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.07



Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

21

100.0

Excludeda

0

0.0

Total

21

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.964

14



RELIABILITY

/VARIABLES=PSP1 PSP2 PSP3 PSP4

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:17:22

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

21

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=PSP1 PSP2 PSP3 PSP4

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.04


Warnings

Scale has zero variance items.


Scale: ALL VARIABLES


Case Processing Summary


N

%

Cases

Valid

21

100.0

Excludeda

0

0.0

Total

21

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.889

4

RELIABILITY

/VARIABLES=KBN1 KBN2 KBN3 KBN4 KBN5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:17:30

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

21

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=KBN1 KBN2 KBN3 KBN4 KBN5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.02


Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

21

100.0

Excludeda

0

0.0

Total

21

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.765

5


RELIABILITY

/VARIABLES=KSM1 KSM2 KSM3 KSM4 KSM5 KSM6 KSM7 KSM8 KSM9 KSM10

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:17:39

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\DB_MANAGER_HOTELS.sav

Active Dataset

DataSet1

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

21

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=KSM1 KSM2 KSM3 KSM4 KSM5 KSM6 KSM7 KSM8 KSM9 KSM10

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.02


Warnings

Scale has zero variance items.


Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

21

100.0

Excludeda

0

0.0

Total

21

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.972

10


DATASET ACTIVATE DataSet2.

RELIABILITY

/VARIABLES=OVO6.1 OVO6.2 OVO6.3 OVO6.4 OVO6.5 OVO6.6 OVO6.7 OVO6.8 OVO6.9 OVO6.10 OVO6.11

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:19:27

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=OVO6.1 OVO6.2 OVO6.3 OVO6.4 OVO6.5 OVO6.6 OVO6.7 OVO6.8 OVO6.9 OVO6.10 OVO6.11

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.04


[DataSet2] C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

90

100.0

Excludeda

0

0.0

Total

90

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.708

11



RELIABILITY

/VARIABLES=KVP1 KVP2 KVP3 KVP4 KVP5 KVP6 KVP7 KVP8 KVP9 KVP10 KVP11 KVP12 KVP13 KVP14 KVP15 KVP16

KVP17 KVP18

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:19:40

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=KVP1 KVP2 KVP3 KVP4 KVP5 KVP6 KVP7 KVP8 KVP9 KVP10 KVP11 KVP12 KVP13 KVP14 KVP15 KVP16

KVP17 KVP18

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.03


Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

90

100.0

Excludeda

0

0.0

Total

90

100.0

a. Listwise deletion based on all variables in the procedure.




Reliability Statistics

Cronbach’s Alpha

N of Items

0.925

18


RELIABILITY

/VARIABLES=TNO1 TNO2 TNO3 TNO4 TNO5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:19:53

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=TNO1 TNO2 TNO3 TNO4 TNO5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.06




Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

90

100.0

Excludeda

0

0.0

Total

90

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.879

5


RELIABILITY

/VARIABLES=VLP1 VLP2 VLP3 VLP4 VLP5 VLP6 VLP7 VLP8 VLP9 VLP10 VLP11 VLP12 VLP13 VLP14

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:20:01

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=VLP1 VLP2 VLP3 VLP4 VLP5 VLP6 VLP7 VLP8 VLP9 VLP10 VLP11 VLP12 VLP13 VLP14

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.04


Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

90

100.0

Excludeda

0

0.0

Total

90

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.885

14


RELIABILITY

/VARIABLES=PRZ1 PRZ2 PRZ3 PRZ4

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:20:09

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=PRZ1 PRZ2 PRZ3 PRZ4

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.00


Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

90

100.0

Excludeda

0

0.0

Total

90

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.699

4


RELIABILITY

/VARIABLES=KBN1 KBN2 KBN3 KBN4 KBN5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.



Reliability

Notes

Output Created

09-DEC-2019 22:20:17

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=KBN1 KBN2 KBN3 KBN4 KBN5

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.01



Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

90

100.0

Excludeda

0

0.0

Total

90

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.780

5


RELIABILITY

/VARIABLES=VKS1 VKS2 VKS3 VKS4 VKS5 VKS6 VKS7 VKS8 VKS9 VKS10

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Reliability

Notes

Output Created

09-DEC-2019 22:20:27

Comments


Input

Data

C:\Users\Msii\Desktop\Al. T\002 - Punimi_2\Database\EMPLOYEE.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

90

Matrix Input


Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data for all variables in the procedure.

Syntax

RELIABILITY

/VARIABLES=VKS1 VKS2 VKS3 VKS4 VKS5 VKS6 VKS7 VKS8 VKS9 VKS10

/SCALE(‘ALL VARIABLES’) ALL

/MODEL=ALPHA.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.02



Scale: ALL VARIABLES

Case Processing Summary


N

%

Cases

Valid

90

100.0

Excludeda

0

0.0

Total

90

100.0

a. Listwise deletion based on all variables in the procedure.


Reliability Statistics

Cronbach’s Alpha

N of Items

0.938

10


Tests of Normality


Kolmogorov-Smirnova

Shapiro-Wilk

Statistic

df

Sig.

Statistic

df

Sig.

Satisfaction with human resource management

0.205

21

0.021

0.852

21

0.005

Satisfaction with the workplace and work in this organization.

0.265

21

0.000

0.787

21

0.000

TRAINING IN THE ORGANIZATION

0.422

21

0.000

0.599

21

0.000

PERFORMANCE ASSESSMENT

0.326

21

0.000

0.676

21

0.000

SELECTION (EMPLOYMENT SELECTION)

0.422

21

0.000

0.599

21

0.000

Communication with human resources

0.252

21

0.001

0.787

21

0.000

Motivation

0.422

21

0.000

0.599

21

0.000

a. Lilliefors Significance Correction


Tests of Normality


Kolmogorov-Smirnova

Shapiro-Wilk

Statistic

df

Sig.

Statistic

df

Sig.

Satisfaction with human resource management

0.188

90

0.000

0.857

90

0.000

Satisfaction with the workplace and work in this organization.

0.263

90

0.000

0.791

90

0.000

TRAINING IN THE ORGANIZATION

0.388

90

0.000

0.637

90

0.000

PERFORMANCE ASSESSMENT

0.209

90

0.000

0.831

90

0.000

SELECTION (EMPLOYMENT SELECTION)

0.300

90

0.000

0.765

90

0.000

Communication with human resources

0.283

90

0.000

0.792

90

0.000

Motivation

0.381

90

0.000

0.668

90

0.000

a. Lilliefors Significance Correction




1Management and Tourism, University of Applied Sciences in Ferizaj, Republic of Kosovo, Address: St. Universiteti, p.n. 70000 Ferizaj, Republic of Kosovo, Corresponding author: alberta.tahiri@ushaf.net.

2Management and Tourism, University of Applied Sciences in Ferizaj, Republic of Kosovo, Address: St. Universiteti, p.n. 70000 Ferizaj, Republic of Kosovo, E-mail: idriz.kovaci@ushaf.net.

3University of Applied Sciences in Ferizaj, Republic of Kosovo, Address: St. Universiteti, p.n. 70000 Ferizaj, Republic of Kosovo, E-mail: fari.bushi@ushaf.net.

AUDŒ, Vol. 16, no. 1/2020, pp. 45-81

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