Determining the Impacts of Staff Motivation on Employee Performance in the Hong Kong Disneyland Hotel.
CHAPTER ONE
BACKGROUND INFORMATION
1.1 Introduction
Motivation refers to the indefinite factor that which are either internal or external and which drives someone to do his or her duties especially. To have a positive impact on the market place and to be profitable, hotel executives need to do all their best in overcoming inherent barriers. As suggested by (Boğan & Sarıışık 2020, p58), the performance of a hospitality organization can be positively or negatively affected by the performance of the leaders. For hospitality organizations to perform effectively, there is need to employ effective leadership which will, in turn, lead to improvement of guest satisfaction, community outreach and employee relations.
The leadership management in hospitality industries needs to understand the employee’s background and his or her work values which will thus assist in developing motivational packages or strategies that will lead to improved working conditions and job satisfaction. It might as well lead to the development of new policies which might satisfy different workers’ needs. Whenever employees have been motivated, there would be good interaction between the employees and customers, which might lead to the attraction of many customers hence leading to ibncr4eassed profit in the hotel. Also, when staffs have been motivated with rewards and salary allowances, the living standards will increase and thus this research is important as it will prove to the organizational leaders how important is to motivate staffs and its impact to the organization (Hornby & Losekoot 2020, p689).
1.2 Statement of the problem
Most of the workers in other companies and organizations are being motivated for their good work done. Still, employees in the hospitality organizations have not been recognized and hence neglected and not motivated for their good services they offer to the customers. Growth, disagreements within the management, compensation and attitude are organizational circumstances which are very vital and which can affect the performance effectiveness within the hotel sector. Therefore, the research gap is that most of the general managers in hotels do not have motivational strategies to enhance the performance of employees.
1.3 Objectives of the study
1.3.1 Broad objective
To determine the impacts of staff motivation on employee performance in the Hong Kong Disneyland hotel.
1.3.2 Specific objective
- To determine the several motivational packages for employees in Hong Kong Disneyland hotel.
- To determine the best motivational package that drives the staff performance in the Hong Kong Disneyland hotel.
- To determine how these motivational packages have impacted the performance of Hong Kong Disneyland hotel.
CHAPTER TWO
LITERATURE REVIEW
The five-star hotel department is much competitive, and it thus requires employees to be creative in which the leaders much insure their creativity. Competency, transformational and good leadership leads to positive influence to the employee via motivation, thus positively impacting the growth and development of staffs and also the organization. All employees look forward to growing financially and increasing their living standards and therefore needs to be properly motivated and trained(Hornby & Losekoot 2020, p689).
2.1 Motivational theories
2.1.1 The ERG theory
ERG theory was developed by Clayton Alderfer, which proposes that the needs of humans may be grouped into three categories such as existence, relatedness and growth. The theory proposes that the more years an employee has worked in a hotel or any organization, the more needs keep on changing(Wang & Huang 2020).
2.1.2 Herzberg et al.’s two-factor theory
The two-factor theory was classified into hygiene and motivation factors. The hygiene factors were termed as dissatisfied factors, and motivational factors were classified as satisfied. The hygiene factors include company policies, supervising, basic salary, and employee relationship with supervisors and environmental work conditions. These hygiene factors are in association with the content of the job. Herzberg stated motivational factors as those which drive a person to work hard in passion (Alshmemri & Maude2017, p14).
2.1.3 Acquired-Needs Theory
This was a theory which was derived by McClelland in which he implied that employees acquire three kinds of needs as an out to their life experience. These three kinds of needs include needs such as power, achievement and affiliation needs (Kirmani 2019, p402).
2.2 Factors that affect motivation
Motivation is classified into intrinsic and extrinsic motivational forms. Intrinsic motivation involves choosing behaviour based on internal and satisfactory values, whereas extrinsic motivation involves one being motivated via external rewards. there is always a positive correlation between the employee motivation and employee performance in such a way that when an employee has been motivated, he or she feels recognized hence doing the job with a passion which in turn leads to a success of that organization. (Venturo‐Conerly 2020, p1244) implied that when an employer is motivating the employees, he or she should understand that motivation is a concern which is universal and thus as a leader, he or she should be in a position to consider some factors to understand what motivates an employee and which one does not. Some of the factors that might affect the motivational degree are superiority, working environment, the kind of work, coworkers, wages and salary. The employers or leaders need to understand how to determine employees’; needs and how to discern them whenever they change. A certain need might motivate an employee in a specific time, but it can as well motivate the employee differently at a later time.
CHAPTER THREE
METHODOLOGY
3.1 Research design
(Bloomfield & Fisher 2019, p27) defined research design as procedures or strategies used in carrying out research and which provides the researcher with the logical plan to use in establishing the research questions. A survey was the research design used in this research in which participants were asked to answer some questions written in a paper which is termed as a questionnaire. The questionnaire method becomes reliable when the information collected from the respondents is free from bias and large as well. The researcher decided to use the survey research design because it was the best method that could be used in assessing the relationship between the impacts of motivational packages and the performance of staffs.
3.2 Research tools
The research tools refer to those instruments or methods used in collecting data. The tools used in this research were the questionnaires, observation, face to face interviews and internet sources Ahmad & Ahmad 2016, p37).
3.3 Sampling technique, population and sample size for the study
Population refers to the total number of individuals, items or objects within a given institution, area, organization or a company (Matthay & Ellicott 2020, p100526). For this study, the researcher randomly selected few respondents from the five-star hotel in the study who were given a chance to participate in the research. That people or objects that participle in providing the information to the researcher is referred to as research subjects. The objects, items and people selected by the researcher form a large population and which participates in the researcher make up a sample size. The researcher randomly selected three hu8ndred respondents and gave them a chance to participate in the research. From this population, only two hundred and sixty staffs participate in responding to the questions. The researcher used a simple random sampling technique in his study. This technique was defined by (Li & Jones 2019, p6400) who stated that it refers to the technique in which each individual or item has an equal chance of being selected to take part in the participation.
3.4 Data for the study
The study data refers to the information which has been gathered by the researcher. For the success of this study, the researcher used both the secondary and primary types of data. (Feinstein, 2020, p460) stated that primary data refers to the information which is obtained at raw by the researcher himself. In contrast, the secondary data entails the information which has already been capture, and the researcher would like to use it for research which is called the second-hand information. The researcher used questionnaires, direct observation and face to face interview in obtaining the primary data. In contrast, audited annual reports, financial statement reports and internet sources were used to obtained secondary data. In defining the questionnaire, the researcher used open-ended questions in which both the self-administered and interviewer-administered questionnaire were used.
3.5 Data analysis and presentation
The researcher analyzed the data obtained in this researcher by logistic regression analysis using the SPSS software. The data results were prepared in tables. The researcher’s variables of interest were the motivation and job satisfaction which were analyzed after the analysis of the demographic description of the participants.
CHAPTER FOUR: RESULTS DISCUSSION AND DATA PRESENTATION
The following structure was used to present the data obtained from the field and the discussion of findings
- Socio-demographic of the respondents
- Staff motivational packages
- Impacts of the motivational packages to the staff performance
- Impacts of motivational packages on Hong Kong Disneyland Hotel
4.1 Socio-demographic of the respondents
The researcher analyzed the socio-demographic profile of the respondents in the following description
- Gender of the respondents
- Core duties of the respondents
- Department and designation of the employees
4.2 Gender of the respondents
The researcher decided to restrict the age demographic description of the participants and used gender only. The number of females was one hundred and forty while that of the male was one hundred and twenty. The number of females was found to be more than that of males which showed that the female gender was mostly preferred in working within the hotel sector. This is because women appreciate any motivation than more than men. This was also proved by (Milner & Baker 2020, p10) who conducted research in the public sector and found out that the level of women motivation was higher than that of men hence suggesting the role of gender in motivation.
| Gender | Frequency | Percentage |
| Female | 140 | 54 |
| Male | 120 | 46 |
| Total | 260 | 100 |
4.3 Core duties of the respondents
The core duties of the respondents in Hong Kong Disneyland Hotel was revealed in five titles which include the customer service representatives, supervisors, managers, directors and accountants. The customer service representatives perform duties such as cooking, serving dishes to customers, inviting customers and any other manuals worker in the five-star hotel. The supervisors ensure that the employees have done their work appropriately to achieve the set goals of the five-star hotel.
| Title | Frequency | Percentage |
| Directors | 5 | 2.0 |
| Managers | 24 | 9.2 |
| Supervisors | 88 | 33.8 |
| Customer service representatives | 136 | 52.3 |
| Accountants | 7 | 2.7 |
| TOTAL | 260 | 100 |
4.4 Motivational packages
Motivation can either be extrinsic or intrinsic. Employee motivation involves the use of elements which are useful in making the staff feel motivated to make him or her working hard and in a special way which in turn lead to the economic growth of the hotel. These motivational elements aim at recognizing the staffs for the good service they offer, for their efforts and achievements they have brought to the hotel. These elements include motivational packages such as enhanced salary increment to the staffs, fringe benefits, recognition and promotion.
| Motivational package | Frequency | Percentage |
| Enhanced salaries to the staffs | 103 | 39.6 |
| Fringe benefit | 72 | 27.7 |
| Promotion | 46 | 17.7 |
| recognition | 39 | 15.0 |
| TOTAL | 260 | 100 |
The most important motivational package that was highly preferred by the employees in Hong Kong Disneyland Hotel was the enhanced salaries.
4.5 Effects of staff motivational packages in the performance of Hong Kong Disneyland Hotel
(Sciukauske 2020) described that when employees are satisfied, they give their best of average levels in work in matters of employee productivity and profitability. Their satisfactory would lead to increased hotel performance and increased profit. Some bad behaviours of the employees change and then start performing well in their job because they are motivated and hence satisfied. The starts reporting to work earlier becomes loyal to the hotel, possess inner satisfaction, have respect amongst themselves and become more delight to the customers, which in turn leads to the positive performance of the hotel.
Logistic regression analysis
Frequency
Linear
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | . | . |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 200.000 | 1 | 200.000 | . | . |
| Residual | .000 | 0 | . | ||
| Total | 200.000 | 1 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | 2.500 | .000 | 1.000 | . | . |
| (Constant) | 5.000 | .000 | . | . | |
Logarithmic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | . | . |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 200.000 | 1 | 200.000 | . | . |
| Residual | .000 | 0 | . | ||
| Total | 200.000 | 1 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| ln(percentage) | 124.733 | .000 | 1.000 | . | . |
| (Constant) | -357.557 | .000 | . | . | |
Inverse
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | . | . |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 200.000 | 1 | 200.000 | . | . |
| Residual | .000 | 0 | . | ||
| Total | 200.000 | 1 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| 1 / percentage | -6210.000 | .000 | -1.000 | . | . |
| (Constant) | 255.000 | .000 | . | . | |
Quadratic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | . | . |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 200.000 | 1 | 200.000 | . | . |
| Residual | .000 | 0 | . | ||
| Total | 200.000 | 1 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | 2.500 | .000 | 1.000 | . | . |
| (Constant) | 5.000 | .000 | . | . | |
| Excluded Terms | |||||
| Beta In | t | Sig. | Partial Correlation | Minimum Tolerance | |
| percentage ** 2 | .500 | .000 | .000 | .500 | .000 |
Growth
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | . | . |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | .012 | 1 | .012 | . | . |
| Residual | .000 | 0 | . | ||
| Total | .012 | 1 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .019 | .000 | 1.000 | . | . |
| (Constant) | 3.901 | .000 | . | . | |
| The dependent variable is ln(frequency). | |||||
Exponential
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | . | . |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | .012 | 1 | .012 | . | . |
| Residual | .000 | 0 | . | ||
| Total | .012 | 1 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .019 | .000 | 1.000 | . | . |
| (Constant) | 49.458 | .000 | . | . | |
| The dependent variable is ln(frequency). | |||||
Logistic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | . | . |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | .012 | 1 | .012 | . | . |
| Residual | .000 | 0 | . | ||
| Total | .012 | 1 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .981 | .000 | .368 | . | . |
| (Constant) | .020 | .000 | . | . | |
| The dependent variable is ln(1 / frequency). | |||||
frequency
Linear
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | 1.000 | .125 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 13369.953 | 1 | 13369.953 | 854986.768 | .000 |
| Residual | .047 | 3 | .016 | ||
| Total | 13370.000 | 4 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | 2.603 | .003 | 1.000 | 924.655 | .000 |
| (Constant) | -.055 | .079 | -.688 | .541 | |
Logarithmic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .947 | .896 | .862 | 21.485 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 11985.193 | 1 | 11985.193 | 25.964 | .015 |
| Residual | 1384.807 | 3 | 461.602 | ||
| Total | 13370.000 | 4 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| ln(percentage) | 37.487 | 7.357 | .947 | 5.096 | .015 |
| (Constant) | -33.344 | 19.309 | -1.727 | .183 | |
Inverse
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .807 | .650 | .534 | 39.468 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 8696.800 | 1 | 8696.800 | 5.583 | .099 |
| Residual | 4673.200 | 3 | 1557.733 | ||
| Total | 13370.000 | 4 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| 1 / percentage | -214.530 | 90.793 | -.807 | -2.363 | .099 |
| (Constant) | 96.098 | 25.688 | 3.741 | .033 | |
Quadratic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | 1.000 | .101 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 13369.980 | 2 | 6684.990 | 660410.388 | .000 |
| Residual | .020 | 2 | .010 | ||
| Total | 13370.000 | 4 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | 2.619 | .011 | 1.006 | 248.700 | .000 |
| percentage ** 2 | .000 | .000 | -.007 | -1.623 | .246 |
| (Constant) | -.134 | .081 | -1.667 | .237 | |
Growth
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .944 | .892 | .856 | .559 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 7.729 | 1 | 7.729 | 24.777 | .016 |
| Residual | .936 | 3 | .312 | ||
| Total | 8.665 | 4 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .063 | .013 | .944 | 4.978 | .016 |
| (Constant) | 1.973 | .354 | 5.567 | .011 | |
| The dependent variable is ln(frequency). | |||||
Exponential
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .944 | .892 | .856 | .559 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 7.729 | 1 | 7.729 | 24.777 | .016 |
| Residual | .936 | 3 | .312 | ||
| Total | 8.665 | 4 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .063 | .013 | .944 | 4.978 | .016 |
| (Constant) | 7.193 | 2.549 | 2.822 | .067 | |
| The dependent variable is ln(frequency). | |||||
Logistic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .944 | .892 | .856 | .559 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 7.729 | 1 | 7.729 | 24.777 | .016 |
| Residual | .936 | 3 | .312 | ||
| Total | 8.665 | 4 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .939 | .012 | .389 | 79.542 | .000 |
| (Constant) | .139 | .049 | 2.822 | .067 | |
| The dependent variable is ln(1 / frequency). | |||||
frequency
Linear
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | 1.000 | .024 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 2529.999 | 1 | 2529.999 | 4298007.999 | .000 |
| Residual | .001 | 2 | .001 | ||
| Total | 2530.000 | 3 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | 2.602 | .001 | 1.000 | 2073.164 | .000 |
| (Constant) | -.045 | .034 | -1.344 | .311 | |
Logarithmic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .992 | .985 | .977 | 4.377 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 2491.681 | 1 | 2491.681 | 130.050 | .008 |
| Residual | 38.319 | 2 | 19.159 | ||
| Total | 2530.000 | 3 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| ln(percentage) | 65.504 | 5.744 | .992 | 11.404 | .008 |
| (Constant) | -141.041 | 18.200 | -7.750 | .016 | |
Quadratic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1.000 | 1.000 | 1.000 | .007 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | 2530.000 | 2 | 1265.000 | 29038897.113 | .000 |
| Residual | .000 | 1 | .000 | ||
| Total | 2530.000 | 3 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | 2.587 | .003 | .994 | 880.407 | .001 |
| percentage ** 2 | .000 | .000 | .006 | 5.102 | .123 |
| (Constant) | .131 | .036 | 3.669 | .169 | |
Growth
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .993 | .985 | .978 | .066 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | .573 | 1 | .573 | 132.881 | .007 |
| Residual | .009 | 2 | .004 | ||
| Total | .581 | 3 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .039 | .003 | .993 | 11.527 | .007 |
| (Constant) | 3.122 | .091 | 34.305 | .001 | |
| The dependent variable is ln(frequency ). | |||||
Exponential
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .993 | .985 | .978 | .066 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | .573 | 1 | .573 | 132.881 | .007 |
| Residual | .009 | 2 | .004 | ||
| Total | .581 | 3 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .039 | .003 | .993 | 11.527 | .007 |
| (Constant) | 22.699 | 2.066 | 10.987 | .008 | |
| The dependent variable is ln(frequency ). | |||||
Logistic
| Model Summary | |||
| R | R Square | Adjusted R Square | Std. Error of the Estimate |
| .993 | .985 | .978 | .066 |
| The independent variable is percentage. | |||
| ANOVA | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Regression | .573 | 1 | .573 | 132.881 | .007 |
| Residual | .009 | 2 | .004 | ||
| Total | .581 | 3 | |||
| The independent variable is percentage. | |||||
| Coefficients | |||||
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | |||
| percentage | .962 | .003 | .371 | 294.494 | .000 |
| (Constant) | .044 | .004 | 10.987 | .008 | |
| The dependent variable is ln(1 / frequency ). | |||||
CHAPTER FIVE
CONCLUSION
In conclusion, this research found out that four themes had emerged from the data collected by the researcher which included themes such as workplace motivation, satisfaction in their job, work performance which is positive and positive social expectations. Each of the four themes had different aspects of motivation. As far as motivation is concerned, and from what the researcher found, motivation led to job satisfaction, whereas job satisfaction leads to positive hotel performance. The positive performance led to personal fulfilment and social expectations. The hotel industry is a sector which is highly demanding and the staffs, managers and all protocols involved within the hotel have to endures schedules which will have to meet the expectations of the hotel and that of the guest.
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