Age and length of service are two important factors that can influence employee productivity, especially in companies dominated by workers with high age and work experience. The purpose of this study is to determine whether age and length of service affect employee productivity at The Royal Pita Maha. The study was conducted using a quantitative approach with multiple linear regression analysis, t-test, F-test, and determination coefficient analysis. Data collection was carried out by distributing questionnaires to 80 respondents selected from a total population of 305 permanent employees. The analysis results showed that the Age variable (X1) had a partial positive and significant effect on Productivity. The lenght of service Variable (X2) has a partial positive and significant effect on Productivity. Age and Tenure simultaneously influence Productivity. Age and Tenure together contribute to influencing Productivity by 61.7% in the strong category.
Human resources (HR) are crucial in achieving organizational goals. According to Jamaludin et al., (2024) good HR management improves discipline and productivity. Employee productivity is central to success, especially in the hospitality industry where human interaction is essential in delivering quality services (Juniarsih et al., 2021). It directly affects customer satisfaction and organizational performance (Lestari, 2020).In the context of hospitality businesses, productivity is not just measured by outputs but by consistent service quality, speed, and guest satisfaction. Productivity also indicates employee efficiency in fulfilling duties and adapting to organizational standards. Therefore, human resources must be empowered continuously through proper management, especially in businesses that rely heavily on service excellence.
In addition to skill, factors such as employee age and length of service are often considered indicators of work productivity. According to Nurmajidah, (2020) a longer length of service allows employees to develop skills and increase effectiveness. However, Juniarsih et al., (2021) warn that extended tenure may also lead to work fatigue and a decrease in motivation. Rusila & Edward, (2022) and Nico Prayudo et al., (2020) state that older employees may experience decreased physical capacity, influencing discipline and productivity. The Royal Pita Maha, a luxury hotel in Ubud, Bali, is known for its traditional design and international clientele. Most of its employees are aged 41–60 and have served for more than 15 years. While experience contributes to skill and loyalty, it may also cause physical and mental fatigue, leading to reduced motivation and lower performance over time. This demographic profile creates a unique challenge for HR management in maintaining motivation, engagement, and consistent performance levels.
Internal observations at the hotel reveal that some older employees often postpone tasks, arrive late, or leave work early. These behavioral patterns, if not addressed, may lower productivity levels and harm guest satisfaction. As a service-based industry, any reduction in employee performance directly impacts service quality and customer loyalty.Furthermore, the hotel industry requires employees to be dynamic, agile, and responsive to guest needs. When performance declines due to age or burnout, the institution may face reputational damage and reduced customer retention. It becomes essential for HR policies to acknowledge the value of senior employees while also identifying support mechanisms that can help them sustain high performance. Training, flexible scheduling, or job redesign may help alleviate fatigue while maximizing experience. Given these issues, this study aims to examine whether age and length of service have significant impacts on work productivity. The findings are expected to provide useful insights for hotel HR policies and strategies to maintain productivity in aging workforces and ensure that senior employees continue to contribute positively to service excellence.
Productivity
Productivity originates from the word "productive," which refers to the potential to generate output from a given input (Nurmajidah, 2020). Productivity is the comparison between the results of work and the resources used, and it is closely related to mental attitudes such as enthusiasm, discipline, creativity, and professionalism (Palupi & Miranda, 2021).
Work productivity reflects the effectiveness of human resource management in achieving organizational goals. Improving efficiency in time, materials, labor, and work systems plays an essential role in supporting productivity (Mega Sari, 2023)
The smaller the input required to produce output, the more productive the activity is considered. Conversely, greater input requirements indicate lower productivity. Internal and external factors such as work stress and fatigue also influence employee productivity (Nurdiawati & Safira, 2020)
Age
Age is the period since a person's existence, measured chronologically. It can also be observed through anatomical and physiological development at similar stages (Noli et al., 2021). According to Utami (2018:59), age is the length of time a person has lived since birth, while Lakshmita et al.,(2024) states that age is the time span from birth to the present. Increasing age is associated with greater maturity and strength in thinking and working (Trapulina et al., 2024).
Age affects work productivity because it is closely linked to a person’s physical capacity during work. Productive age, typically between 16 and 64 years, is considered ideal for optimal labor performance (Attaqi, 2022). According to the Indonesian Dictionary (KBBI), age is defined as the duration of life or existence since birth. Age can be classified into:
1. Chronological age – age counted from birth to the present
2. Mental age – based on individual mental capability
3. Biological age – based on biological maturity
In this study, age is defined as the duration of life that influences both physical ability and cognitive function in the workplace. Younger employees tend to be more energetic, while older employees bring experience, though with physical limitations
Length of Service
Length of service refers to the duration of time someone has worked at a company or organization (Juniarsih et al., 2021). According to Siagian in Orlin Artika et al., (2021), longer years of service may lead employees to neglect their duties or be absent due to boredom from working for years. Length of service is the period during which a worker has been employed in a particular place. It can positively affect performance; as longer service often results in greater experience in carrying out responsibilities. Conversely, it can also have negative impacts, as extended years of service may lead to complacency and boredom, reducing motivation (Sali, 2020). Generally, length of service can be categorized into three groups:
1. Short service: less than 6 years
2. Medium service: 6–10 years
3. Long service: more than 10 years
One key factor that influences employee productivity is work experience, which is developed over time. In general, length of service represents the level of experience someone has, based on how long they have worked in a specific field or role. The longer an employee serves in a company; the more experience they gain. This accumulated experience tends to increase productivity and the quality of work produced (Sali, 2020).
Conceptual Framework
This framework was created to facilitate the thought process for the issues to be discussed and resolved. Therefore, the following research framework was developed:
Figure 1. Conceptual Framework
Based on the background, problem formulation, theoretical foundation, and conceptual framework, the following hypotheses are proposed:
a. Age
Age is defined as the time from birth to the time of research, measured in years. Individuals over 20 years are categorized as adolescents, and ages 18–40 as early adulthood, which according to Piaget, is marked by significant intellectual and behavioural changes.
According to Kumbadewi, (2021), age, experience, wages, technology, and work environment simultaneously and partially influence productivity.
Hypotheses:
H₀₁: Age has no significant positive effect on employee productivity at The Royal Pita Maha.
Hₐ₁: Age has a significant positive effect on employee productivity at The Royal Pita Maha.
b. Length of Service
Length of service is the period of time a person has worked, measured in years. It is the time from initial employment until now.
According to Mardikaningsih, (2020), length of service has a significant positive effect on productivity.
Hypotheses:
H₀₂: Length of service has no significant positive effect on employee productivity at The Royal Pita Maha.
Hₐ₂: Length of service has a significant positive effect on employee productivity at The Royal Pita Maha.
c. Age and Length of Service
Age and length of service both influence productivity. According to Sali, (2020), longer service increases experience and productivity, while older age negatively affects performance.
Hypotheses:
H₀₃: Age and length of service do not significantly affect employee productivity at The Royal Pita Maha.
Hₐ₃: Age and length of service significantly affect employee productivity at The Royal Pita Maha.
This research employs a quantitative approach to examine the influence of age and length of service on employee work productivity. The study was conducted at The Royal Pita Maha, a luxury hotel located in Ubud, Bali, known for its traditional architecture and international clientele.The population in this study consists of 305 permanent employees, with a sample of 80 respondents determined using the Slovin formula and probability sampling technique to ensure proportional representation.
Data were collected using a closed-ended questionnaire distributed directly to respondents. Prior to analysis, the instrument was tested through validity and reliability tests. The validity test showed that all items had an r-count greater than the r-table, indicating they were valid. The reliability test resulted in a Cronbach’s Alpha score of 0.721, which confirms that the questionnaire had high internal consistency and was suitable for use.The collected data were analyzed using descriptive statistics, classical assumption tests (normality, multicollinearity, and heteroscedasticity), and multiple linear regression analysis. Additionally, t-tests, F-tests, and the coefficient of determination (R²) were applied to assess the significance and contribution of the independent variables (age and length of service) to employee work productivity.
Respondent Profile
This study involved 80 respondents out of a total of 305 permanent employees at The Royal Pita Maha. Based on the data collected through questionnaires, the majority of respondents were within the age group of 41–50 years (38.8%) and had more than 15 years of service (36.3%). This indicates that most employees are senior workers with high levels of experience (See Table 1.). Masukkan tabel Karakteristik Responden disini
No
Age
Respondents
Number People
Percentage (%)
1
21 - 30 years old
10
12,5
2
31 - 40 years old
15
18,75
3
41 - 50 years old
35
43,75
4
>50 years old
28
25
Multiple Linear Regression Analysis
Based on the analysis results, the regression equation is as follows:
(Y) = 3.743 + (X1)0.606 + 0.287X₂
Where:
Y = Work Productivity
X₁ = Age
X₂ = Length of Service
Explanation:
a. The coefficient for Age (X₁) is 0.606, meaning that for every one-unit increase in age, work productivity increases by 0.606 units, assuming other variables remain constant.
b. The coefficient for Length of Service (X₂) is 0.287, meaning that for every one-unit increase in length of service, work productivity increases by 0.287 units, assuming other variables remain constant.
This suggests that both age and length of service have a positive effect on employee productivity.
t-Test (Partial Test)
The t-test was used to determine the partial effect of each independent variable on the dependent variable. The results show:
Age (X₁):
t-count = 6.732, t-table = 1.991, significance = 0.000
Since t-count > t-table and significance < 0.05, Age has a significant partial effect on work productivity.
Length of Service (X₂):
t-count = 3.187, t-table = 1.991, significance = 0.002
Since t-count > t-table and significance < 0.05, Length of Service also has a significant partial effect on work productivity.
F-Test (Simultaneous Test)
The F-test was used to determine the simultaneous effect of Age and Length of Service on work productivity. The results are as follows:
F-count = 61.243
F-table = 3.11
Significance = 0.000
Since F-count > F-table and significance < 0.05, it is concluded that Age and Length of Service simultaneously have a significant effect on work productivity at The Royal Pita Maha.
Coefficient of Determination (R²)
The coefficient of determination (R²) is 0.617, meaning that 61.7% of the variation in employee work productivity is explained by the variables Age and Length of Service. The remaining 38.3% is influenced by other factors not included in this research model.
The Influence of Age on Work Productivity
The findings of this study indicate that age has a statistically significant and positive effect on employee productivity at The Royal Pita Maha, as evidenced by a t-value of 6.732 (p < 0.05) and a regression coefficient of 0.606. This implies that as employees age, their productivity tends to increase, potentially due to the accumulation of experience, enhanced problem-solving capabilities, and greater emotional intelligence over time.
This result is consistent with the argument of Trapulina et al., (2024), who posited that increased age correlates with improved maturity in cognitive processing and decision-making. Similarly, Attaqi, (2022)highlighted the productive age range (16–64 years) as optimal for labor market engagement. However, while age may contribute positively to cognitive performance and work discipline, it is also necessary to recognize the possible physical limitations that may accompany advanced age, particularly in labor-intensive or highly dynamic service roles. Hence, while age positively contributes to productivity, especially in service-based industries where experience and interpersonal skills are highly valued, the physical demands of hospitality work should not be overlooked.
The Influence of Length of Service on Work Productivity
The length of service also demonstrated a significant positive relationship with work productivity, supported by a t-value of 3.187 (p = 0.002) and a regression coefficient of 0.287. This suggests that employees with longer tenure are generally more productive, potentially owing to greater task familiarity, institutional knowledge, and embeddedness within organizational routines.
This finding aligns with the conclusions of Mardikaningsih, (2020), who noted that extended job tenure enhances mastery of tasks and operational efficiency. In the case of The Royal Pita Maha, where many employees have served for over 15 years, such long-term engagement appears to result in high levels of procedural fluency and workplace adaptation. However, this relationship may not be linear; research by Sali, (2020) and Siagian in Orlin Artika et al., (2021)has cautioned that prolonged tenure may also lead to job fatigue, complacency, or resistance to change. Thus, while tenure supports productivity, it also necessitates managerial interventions such as periodic role redesign, rotation, or retraining to sustain motivation and engagement.
The Combined Influence of Age and Length of Service on Work Productivity
When analyzed simultaneously, age and length of service were found to have a joint significant effect on work productivity, as reflected in an F-value of 61.243 (p < 0.001) and a coefficient of determination (R²) of 0.617. This indicates that 61.7% of the variance in employee productivity at The Royal Pita Maha can be explained by these two demographic factors, underscoring their combined relevance in shaping performance outcomes.
These findings are consistent with the study by Kumbadewi, (2021), which demonstrated that demographic characteristics such as age and work experience—alongside other variables—significantly affect employee behavior and performance in service contexts. Taken together, these results affirm that senior employees contribute meaningfully to organizational productivity, provided that their roles and workloads are managed effectively.
It is important to note, however, that 38.3% of productivity variation remains unexplained by the current model. This suggests the potential influence of other critical factors such as intrinsic motivation, leadership style, job satisfaction, workplace culture, or even health status. Future studies should consider incorporating these variables to provide a more holistic understanding of what drives productivity in hospitality settings.
Moreover, from a managerial perspective, these results highlight the necessity for age-inclusive HR strategies. This includes offering tailored training programs, designing ergonomically appropriate job roles, and creating performance management systems that acknowledge the strengths of both younger and older workers. In the context of an aging workforce, particularly in high-touch industries like hospitality, such proactive measures are crucial to maintaining high service standards while preserving employee well-being.
Based on the findings from the data analysis and the subsequent discussion, it can be concluded that both age and length of service significantly and positively influence employee productivity at The Royal Pita Maha. Of the two, age has a comparatively stronger impact, as reflected by its higher regression coefficient and t-value. This suggests that older employees, through their maturity, accumulated experience, and deep familiarity with work processes, tend to exhibit higher levels of productivity. When assessed simultaneously, age and tenure together explain 61.7 percent of the variation in employee performance, underscoring their combined importance as determinants of productivity in the hospitality context
Despite the positive contribution of age and tenure, it is important to acknowledge the potential risks associated with prolonged service, such as work fatigue, reduced motivation, or physical limitations. These issues, if left unaddressed, may gradually undermine productivity and affect service quality, especially in a high-touch service environment.
To sustain optimal performance across all age groups, the organization should adopt a human resource management approach that acknowledges the value of experience while addressing the physical and psychological well-being of employees. Assigning tasks that align with employees' capabilities, offering continuous training and development, and introducing job rotation schemes can help mitigate fatigue and keep employees engaged. In addition, fostering a workplace culture that motivates and recognizes the contributions of senior employees can further strengthen organizational commitment and encourage knowledge sharing across generations. Through these strategies, The Royal Pita Maha can ensure sustained productivity, operational excellence, and long-term workforce resilience.
This study focuses only on the influence of age and length of service on work productivity at The Royal Pita Maha. Future research is encouraged to expand the variables by including other factors such as motivation, job satisfaction, work environment, or leadership style, which may also contribute significantly to employee productivity. In addition, researchers may consider conducting comparative studies between different departments, hotel types, or even other hospitality sectors to enhance the generalizability of the findings. A mixed-method approach combining qualitative interviews and quantitative analysis is also recommended to provide deeper insights into the dynamics of productivity in service-based industries.
The author would like to thank all respondents, Human Resources, and The Royal Pita Maha for their support during this research process.