Introduction
A successful and effective business is always based on the contribution of a good staff. This contribution is reflected in their actions toward the business. To attract employees who are both enthusiastic and loyal, businesses are constantly improving in terms of human resource development, remuneration policies, as well as remuneration for their employees. What we all realize is that when an employee feels they are working in an environment with satisfactory regimes (e.g., there are always many opportunities for development and improvement), they will do their best to complete the job, from which the results exceed expectations.
In deciding work satisfaction levels, job motivation plays a critical role. This study aims to examine the effect of job motivation on job satisfaction. The result of multiple regression analysis shows that job motivation influences job satisfaction significantly and positively. This means that it is critically necessary to boost job motivation to increase job satisfaction among employees (Omar et al., 2021).
Laurence et al. (2020) conducted a study that focuses on job creation by studying the role of enjoying work, and successful and employment-oriented users as the job creation engine. A total of 154 Google monitoring employees were surveyed. Excitement about the job and motivation are supported as incentives of job creation. An interaction effect was observed, with a low impulse to work undermining the relationship between job enjoyment and fabrication. Job creation mediated the relationship between motivation and job performance. The author complements researchers with an understanding of job creation while making the first attempt to explore the phenomenon of job creation in East Asia.
Saether (2019) conducted research analyzing the relationship between motivational forms from self-determination theory and the concept of the personal organization (PO) to provide insight into some of the factors in the innovative work behavior (IWB) of the high-tech research and development (R&D) staff. The research method is quantitative and qualitative. Survey data from R&D staff in three high-tech organizations show that employees with a higher PO level have higher autonomous (deterministic and intrinsic) motivation and employees are motivated to participate in the IWB more often. Autonomous dynamics mediate PO’s relationship with IWB. Furthermore, the fair pay (i.e., distributive equity) and the creative support of the organization are closely related to the PO, suggesting that these may be useful for managers to consider concerning employees, employee motivation, and those who are creativity cautious so as to match the values of the employee and the organization, and to support employee autonomy.
This chapter will present the theoretical basis of employee work motivation, summarizing many studies on employee motivation throughout the world as well as in Vietnam, from which the proposed research model includes seven factors: salary, promotion opportunities, peers, organizational priorities and strategies, reviews, rewards, and staffing plans.
Methodology
Sample Approach
According to Bollen (1989), the minimum sample size to undertake a study is 5 samples for one parameter. The sample size can be defined as 5:1 (5 observations per 1 variable) (Hair et al., 2006). This study was carried out with 230 survey forms in Mobile World Corporation in Ho Chi Minh City in Vietnam. Of the 230 votes that were collected, 210 votes were filtered, 20 were left blank and selected only one column in Table 1.1. The table describes statistics of sample characteristics.
Table 1.1:Statistics of sample characteristics.
| Characteristics | Amount | Percent (percent) | |
|---|---|---|---|
| Sex and Age | Male | 76 | 36.2 |
| Female | 134 | 63.8 | |
| 18–25 | 130 | 61.9 | |
| 26–35 | 51 | 24.3 | |
| 36–45 | 28 | 13.3 | |
| Above 45 | 1 | 0.5 | |
| Monthly Income | 7–9 million VND | 123 | 58.6 |
| 10–12 million VND | 47 | 22.4 | |
| 13–15 million VND | 28 | 13.3 | |
| Over 15 million VND | 12 | 5.7 | |
| Time Working | Below 1 year | 54 | 25.7 |
| 1–3 years | 144 | 68.6 | |
| > 3–5 years | 9 | 4.3 | |
| > 5 years | 3 | 1.4 | |
| Education | Certificate | 79 | 37.6 |
| Diploma | 104 | 49.5 | |
| Degree | 17 | 8.1 | |
| Master’s | 10 | 4.8 | |
We use the 5-point Likert scale to evaluate the level of consent for the related factors for 180 respondents. Therefore, this chapter also uses the 5-point Likert scale to evaluate the level of consent for all observed variables, with 1: Disagree … and 5: Agree in Table 1.2.
Table 1.2:Factor and item.
| Factor | Code | Item | Mean | SE |
|---|---|---|---|---|
| Salary (SA) | SA1 | Understand how salary is calculated in the company. | 3.85 | 0.822 |
| SA2 | Salary commensurate with capacity. | 3.72 | 0.875 | |
| SA3 | Reward policy promptly and publicly. | 3.75 | 0.810 | |
| SA4 | The company’s income is high. | 3.69 | 0.791 | |
| SA5 | The company has many rewarding programs for employees. | 3.74 | 0.808 | |
| Working Promotion (WP) | WP1 | The company has different career promotion plans. | 3.81 | 0.732 |
| WP2 | The company always has many opportunities for career advancement. | 4.09 | .845 | |
| WP3 | The company’s promotion and promotion policies are fair and transparent. | 3.43 | 1.001 | |
| WP4 | Clear company promotion plans in the company. | 4.00 | 0.891 | |
| WP5 | The company promotion policy is fair. | 3.49 | 0.994 | |
| Colleague (CO) | CO1 | Colleagues are always friendly and sociable. | 4.10 | 0.910 |
| CO2 | Colleagues have high internal solidarity. | 4.13 | 0.890 | |
| CO3 | Colleagues always support, help, and motivate each other at work. | 3.94 | 0.993 | |
| CO4 | Collaboration working well. | 3.98 | 0.958 | |
| CO5 | Colleagues are willing to share work experience. | 3.78 | 0.919 | |
| CO6 | Trusted colleague. | 3.85 | 0.936 | |
| Organizational Strategy (OS) | OS1 | The necessity of creating an organizational strategic plan. | 3.88 | 0.925 |
| OS2 | There are priority policies for each organization. | 3.77 | 0.899 | |
| OS3 | Priority creates personal success. | 3.78 | 0.891 | |
| Evaluation (EV) | EV1 | The company has highly rated tools. | 4.23 | 0.769 |
| EV2 | The monitoring company is likely to lead the assessment interview. | 4.30 | 0.727 | |
| EV3 | The company is highly specialized in the field. | 4.03 | 0.779 | |
| EV4 | The company has professional and objective reviews. | 3.97 | 0.877 | |
| Reward (RE) | RE1 | The company has a timely reward policy. | 3.89 | 0.805 |
| RE2 | The company has been rewarded in many different forms. | 3.98 | 0.866 | |
| RE3 | Company rewards with company profits. | 3.89 | 0.919 | |
| RE4 | Company rewards based on performance. | 3.87 | 0.885 | |
| Personnel Plan (PP) | PP1 | The importance of workforce planning. | 4.21 | 0.840 |
| PP2 | The organization has a development management system that has a staffing plan. | 4.00 | 0.816 | |
| PP3 | Human resource planning helps to systemize work. | 4.10 | 0.827 | |
| PP4 | Human resource planning positively affects the quality of service provided. | 3.92 | 0.823 | |
| Working Motivation (WM) | WM1 | Voluntarily improve your skills to do better. | 3.88 | 0.565 |
| WM2 | The company is inspired at work. | 3.93 | 0.782 | |
| WM3 | Intent to quit work. | 4.03 | 0.731 | |
| WM4 | Willing to sacrifice personal interests to get the job done. | 3.82 | 0.849 | |
| WM5 | Get excited about your current job. | 3.75 | 0.742 |
Blinding
For the duration of the study, all study staff and respondents were blinded. No one from the outside world had any contact with the study participants.
Results
Akaike Information Criterion Selection
Akaike’s Information Criteria (AIC) was utilized to choose the best model by R software. AIC has been used in the theoretical context for model selection. When multicollinearity occurs, the AIC approach can handle multiple independent variables. As a regression model, AIC can be applied, estimating one or more dependent variables from one or more independent variables. An essential and useful measurement for deciding a complete and straightforward model is the AIC. Based on the AIC information standard, a model with a lower AIC is selected. The best model will stop with the minimum AIC value in Table 1.3 (Burnham & Anderson, 2004; Khoi, 2021).
Table 1.3:Akaike information criterion selection.
| Model | AIC |
|---|---|
| MW = f (SA, WP, CO, OS, EV, RE, PP) | –507.2 |
| MW = f (SA, WP, CO, EV, RE, PP) | –507.96 |
| MW = f (SA, WP, EV, RE, PP) | –508.61 |
In Table 1.3, R reports show the steps of searching the optimal model. The first step is to start with all seven independent variables with AIC = –507.2. The second step is to find the best model; R stops with a model of five independent variables (SA, WP, EV, RE, PP) with AIC = –508.61.
Table 1.4:The coefficients.
| MA | Estimate | Std. Error | t-value | P-value | Decision |
|---|---|---|---|---|---|
| -Intercept | 0.07572 | ||||
| SA | 0.23471 | 0.03747 | 6.264 | 0.000 | Accepted |
| WP | 0.15015 | 0.03040 | 4.940 | 0.000 | Accepted |
| EV | 0.14253 | 0.04056 | 3.514 | 0.000 | Accepted |
| RE | 0.15223 | 0.03305 | 4.607 | 0.000 | Accepted |
| PP | 0.28744 | 0.03627 | 7.924 | 0.000 | Accepted |
All variables have a p-value lower than 0.05 [8], so they are correlated with working motivation (WM), which is shown in Table 1.4. Salary (SA), working promotion (WP), evaluation (EV), reward (RE), and personnel plan (PP) impact WM.
Table 1.5:Model test.
| VIF | SA | WP | EV | RE | PP | |
|---|---|---|---|---|---|---|
| 1.424989 | 1.199228 | 1.544997 | 1.714816 | 1.441121 | ||
| Autocorrelation | Durbin-Watson = 1.8423 | test for autocorrelation | ||||
| p-value = 0.1192 | ||||||
| Model Evaluation | Adjusted R-squared = 0.7294 | F-statistic 113.6 | p-value: 0.00000 | |||
Variance Inflation Factor
The multicollinearity phenomenon occurs when there is a high degree of correlation between the independent variables in the regression models. Gujarati and Porter (2009) showed some signs of multicollinearity in the model when the variance inflation factor (VIF) coefficient is greater than 10 (see Table 1.5).
According to Table 1.5, VIF for the independent variables is less than 10 (Miles, 2014), so there is no collinearity between the independent variables.
Autocorrelation
The Durbin-Watson Test shows that there is no autocorrelation from the model in Table 1.4 because the p-value = 1.8423 is greater than 0.05 (Durbin & Watson, 1971) in Table 1.5.
Model Evaluation
According to the results from Table 1.5, SA, WP, EV, RE, and PP the impact of WM is 72.94 percent in Table 1.5. The analysis shows the following regression equation is statistically significant (Greene, 2003):
MW = 0.07572 + 0.23471SA + 0.15015WP + 0.14253EV+ 0.15223RE + 0.28744PP
Solutions
The results of the AIC Algorithm for WM showed that five independent variables: SA, WP, EV, RE, and PP have a positive impact on WM because their p-value is greater than 0.05. The impact level of these four variables on the dependent variable WM in descending order is as follows: personnel plan (0.28744), salary (0.23471), reward (0.15223), working promotion (0.15015), and evaluation (0.14253). The Mobile World Corporation must regularly pay attention to motivating issues for employees so that they can work spiritually and contribute to the company more effectively.
The Mobile World Corporation needs to pay more attention to working conditions and a better working environment for its employees so that employees can work in the most comfortable environment possible. It would then be possible to maximize their capabilities and devote more to the Mobile World Corporation.
The Mobile World Corporation needs to organize more confidential conversations with employees to motivate them and increase solidarity among each other, so leaders can understand employees’ aspirations and give them a chance to express their opinion.
The Mobile World Corporation encourages a balance between work and family life and takes note of employees’ birthdays, employees’ family members’ status, etc. so they consider the company like a second family.
Mobile World Corporation has a salary and bonus policy for employees working overtime. The sales lines beyond 50 km should support more gas and food expenses so that employees will have a sense of comfort and dedication.
Mobile World Corporation creates rewarding policies to motivate employees to work better; besides, managers often pay attention to the attitude and working motivation of each employee so that they stay on for a long time and are dedicated to their job.
Conclusion
Researching the motivating factors for employees is a job that is essential for all businesses. This helps businesses understand the essential factors that motivate employees to work more efficiently and reduce the pressure during the work process. Since then, there are reasonable policies and ways to impact and motivate employees to achieve high efficiency. This research creates a very good competitive advantage if businesses capture and apply it well. WM showed that it was influenced by SA, WP, EV, RE, and PP. Accordingly, all five factors discussed earlier have a positive impact on WM. Besides, the AIC Algorithm also shows the influence of five independent factors on the dependent factor. The results of the study analysis are quite like the results of some previous studies cited earlier.
Further Research
When employees are motivated, they work harder than expected to deliver the best results, which is an important feature of company development in the present as well as in the future.
If the company handles this well, employees are always motivated to work with them for a long time, rather than actively looking for new jobs, and always recommend the company as the best place to work. Mobile World Corporation does not spend a lot of time training or on training costs for new employees.
As mentioned in the earlier part of this study, the goal of this study is to keep the company’s employees motivated by making them feel that the working environment is the best for long-term employment. However, motivation needs to have a measure of work efficiency, so it is necessary to study the factors that affect employees’ performance as well as the factors that affect the intention to quit. Then, the factors built into the original model may play a different role in the correlation relationship for these two factors, and at the same time, motivation will be considered as a factor affecting the employee’s work performance and the intention of quitting.
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