Work Motive Distribution of Public Universities Lecturers in Hanoi

Abstract

Purpose: The study aims to investigate the impact of factors affecting the work motive distribution of public universities lecturers in Hanoi. Research design, data and methodology: The questionnaire survey method is applied in this research to analyze the relationship between the variables and verify the hypothesis based on the collected 306 valid questionnaires. The partial least square method structural equation model (PLS-SEM) is used to carry out structural equation modeling to study the relationship between latent variables with reliable tools (SmartPLS 3.0 software). Results: The research results show that the intrisic motivation of the lecturers, the extrisic motivation of the lecturers and the job characteristics of the lecturers all have a positive impact on the motivation of public universities lecturers in Hanoi. In which, intrinsic motivation has the greatest influence on the work motive distribution of lecturers. In addition, the research results also prove that job characteristics affect the work motive distribution of lecturers. This is a new factor in the factors affecting the work motive distribution of public universities lecturers. Conclusion: Based on the research results, the authors propose some recommendations to increase the work motive distribution of public universities lecturers in Hanoi through improving the factors affecting their work motive distribution.

1. Introduction

By 2020, Hanoi has 86 universities, accounting for 38% of the total number of universities across the country. The research on university autonomy is increasingly interested, is becoming an issue that present in all discussions, especially on higher education policy because of its importance (Wang, 2010). In the context that university autonomy is becoming an inevitable trend and a very important condition to promote universities to build their own quality and strength from within, adapt to market mechanisms, meet societal needs. Resolution No. 77/NQ-CP on piloting renewal of operating mechanism for public educational institutions was enforced, which has helped universities to be proactive in the process of operation, from new establishment to merger, division, separation of affiliated units, recruitment, extension of working time, establishment of revenue and expenditure regulations, determination of tuition fees, training scale and structure, and development of relationships business and international cooperation. To survive and develop sustainably, universities in general and public universities in particular must pay special attention to the human resource because of its impact on university performance has been a widely researched area for years. Public universities not only need to take measures to attract lecturers, but also have policies to improve work motive distribution, arouse the desire of lecturers to dedicate themselves to the cause of education, for universities development. On that basis, public universities will have both theoretical and practical grounds to develop policies to increase work motive distribution for lecturers.

This study aims to build a model to evaluate the factors affecting the work motive distribution of lecturers to conduct a survey of the factors affecting the work motive distribution of public universities lecturers at public universities in Hanoi. The research results are the basis for proposing solutions to increase the working motivation of public universities lecturers in Hanoi through improving the factors affecting their work motive distribution.

2. Theoretical Basis

2.1. The Achievement Motive Theory

The need for achievement will create the motivation to realize the work results of individuals. The need for achievement is satisfied not by the manifestations of success, which confer status, but by the process of doing the work to accomplish it successfully. The achievement drive helps individuals to excel, achieve relevant goals, and strive for success. In other words, achievement motivation helps individuals to engage in competitive behaviors and achieve high standards at work. McClelland et al. (1953) found that people with high achievement needs perform better than those with moderate or low achievement needs and noted regional and national differences in terms of achievement motivation. Through the research, McClelland identified the following three characteristics of high achievers:

(1) High need achievers have a strong desire to take on personal responsibility for performing a task or finding a solution to a problem.

(2) High need achievers tend to set moderately difficult goals and calculate the risk of the task.

(3) High need achievers have a strong desire for performance feedback.

Individuals with a high need and high achievement motivation will generally accept moderate risks, such as situations where they can take personal responsibility for finding solutions to problems and want specific feedback to their performance. As McClelland pointed out: “No matter how high a person's need for achievement, he cannot succeed if he is not given the opportunity, if the organization keeps him from proactive, or does not reward him when he does well." Therefore, if an organization wants to increase the motivation of individuals to act on performance levels, it should assign them tasks with a moderate risk of failure, giving them sufficient authority to do so, proactively complete tasks, and provide periodic specific feedback about their performance.

2.2. Self-determination Theory in Human Behavior

While no maximum length for manuscripts is prescribed, authors are encouraged to write concisely. As a guide, regular articles should be between 5,000 - 7,000 words in length. However, Full paper should be no longer than 30 pages and no more than 8000 words in total with all inclusive. The self-determination theory (SDT) of Deci and Ryan's motivation (1985, 2000) reflected that individuals oriented towards achievement motivation because they took into account basic desires for competence and autonomy. Self-determination theory has shown that the motivation of individuals when aiming for achievement motivation includes intrinsic motivation and extrinsic motivation.

Intrinsic motivation refers to a natural psychological process by which activities are pursued for the purpose of achieving intrinsic personal gain such as enjoyment and satisfaction of individual curiosity (Deci, 1975). Intrinsic motivation exists within the self-control of individual behavior and can affect personal competence. Personal competence here is self-developed as a product of intrinsic motivation to reinforce individual behavior (Deci & Moller, 2005).

Extrinsic motivation exists on a continuum of extrinsic regulations from high to low (Ryan & Deci, 2000). The four types of extrinsic motivation, arranged hierarchically by degree, include:

(1) Extrinsic regulation represents the traditional concept of extrinsic motivation in which behavior is believed to be regulated by extrinsic interests.

(2) Intrinsic regulation is understood as individuals internalizing or some extrinsic regulation without taking ownership of it or engaging in certain behaviors to gain the consent of others.

(3) Identity regulation reflects an individual's increasing level of involvement in an activity because the activity is perceived as having a particular value.

(4) The integrative regulation theorized to represent extrinsic motivations that are adjusted inward when recognized by the individual as being consistent with values and needs.

2.3. Job Characteristic Theory

The approach of job characteristics theory is to try to determine the objective characteristics of the job to facilitate the internal work motive distribution of the individual. Base on earlier work by Locke (1969) the current claims of the theory suggest that individuals are motivated to perform well when they experience meaningful work, they feel they have personal responsibility for work results. Five objective job characteristics were identified as important in creating, including: skill diversity, task identification, job meaning, autonomy, and feedback from the job itself (Hackman & Lawler, 1971; Hackman & Oldham, 1976).

When a job is designed to secure its status based on these characteristics, improvements in incumbents' motivation, satisfaction, and performance are increased. However, inter-individual differences in employee knowledge and skills and personal growth needs are considered to influence the impact of job characteristics on work behavior and attitudes. The strongest effects are predicted for individuals with a wide range of work-related knowledge and skills and relatively strong development needs.

The summary of previous studies' main contents shows in Table 1.

Table 1: Summary of Theoretical Background

3. Research Methods

To accomplish the objectives set out above, the study uses a combination of methods of synthesis, comparison and analysis of data, research using qualitative research methods and quantitative research methods. Primary data was collected by survey method from the survey using a research-specific questionnaire.

3.1. Research Design

On the basis of theoretical overview and related research works. The article proposes a research model with independent variables including: intrinsic motivation of lecturers, extrinsic motivation of lecturers and target variable as working motivation of university lecturers. The scale used in the study is a Likert scale with 5 levels (Strongly agree; Agree; Normal; Disagree; Strongly disagree). Indicators measuring variables are applied with adjustments in accordance with the study sample characteristics from previous studies.

With the group of intrinsic motivation of lecturers (DLBT) inheriting and developing the scale of McClelland et al. (1953); Deemer et al. (2010) included 8 observations. Extrinsic motivation of lecturers (DLBN) inherits and develops the scale of Deci (1975); Ryan and Deci (2000); Deci and Moller (2005); Deemer et al. (2010) included 8 observations. Job characteristics of lecturers (DDNN) inherit and develop the scale of Hackman and Lawler (1971); Kahn (1990) included eight observations. Work motive distribution of lecturers (DLLV) inherits and develops the scale of Stee and Porter (1983) including 9 observations.

Figure 1 is the proposed research model and Table 2 is a summary of the research hypotheses.

Figure 1: Proposed Research Model

Table 2: Summary of Research Hypotheses

3.2. Research Sample

The research sample was selected by non-probability sampling method, which is convenient sampling, relatively stratified according to public universities in Hanoi in order to increase the representativeness of the research sample including: National Economics University, Academy of Finance, Banking Academy, University of Commerce, Foreign Trade University, and University of Economics and Business, VNU.

A formal quantitative study was conducted with 360 lecturers from public universities in Hanoi to assess the relevance of the model and test the original proposed research hypothesis by structural equation modeling based on partial least squares (PLS-SEM). PLS-SEM is a second generation multivariate data analysis technique commonly used to test additive and linear causal models supported by theory. The survey results obtained 328 valid votes, of which 12 were invalid, the remaining 306 valid votes were used for the official study as the sample size met the requirements according to Hair et al., 2016. The characteristics of the official study sample described in Table 2 show that the proportions of men and women are not much different, 44.4% of men and 55.6% of women, respectively. In terms of age, the majority of lecturers are from 31-40 years old, accounting for 51.0%, 41-50 years old account for 28.8%, 13.7% of lecturers are aged 22-30, and only 6.5%. lecturers are over 50 years old. Qualifications (study titles, academic degrees) in the survey sample are quite high, with up to 52.9%, 33.3%, 13.7% and 0.7% of lecturers having PhD degrees, Master, Associate Professor, Professor were surveyed. National Economics University and University of Economics and Business, VNU are the two universities with the largest number of lecturers participating in the survey with 56 lecturers (accounting for 18.3%), Banking Academy has the lowest number of lecturers participating in the survey was 45 lecturers (accounting for 14.7%). The demographic information of survey sample is shown in Table 3.

Table 3: Demographic Information of the Survey Sample

3.3. Analysis Tools

Partial least squares structural equation modeling (PLS-SEM) is an analytical technique for detecting or building predictive models. Especially for the analysis of the causal model between latent variables, this method is considered better than the general linear structural relationship model, which is very suitable for exploratory research. Compared with the covariance-based structural equation model (CB-SEM), which is evaluated by the covariance matrix, PLS-SEM is suitable for small sample analysis. PLS-SEM is mainly designed to detect whether a causal relationship has a statistically significant linear relationship. It is quite suitable for building theoretical models. This study uses PLS-SEM as a method to explore the relationship between research variables. It mainly uses PLS algorithm and Bootstrapping to perform repeated sampling 5000 times to obtain coefficients and statistical significance of the links. Besides, it also shows the correlation and multi-dimensional influence between the variables.

4. Research Results

4.1. Analyze Model Reliability and Validity

Reliability refers to the consistency of observed variables. Measurement indicators include the reliability of each scale and the internal consistency between the scales. In which, the reliability of each scale is tested by factor loading indexes. Internal consistency was tested by reliability of latent variable Composition Reliability (CR) and Cronbach's alpha. The recommended value needs to be greater than 0.7 (Hair et al., 2016). Model validity refers to the correctness of the scale and measurement indicators including convergent validity and discriminant validity. The convergent validity measures the correlation between items with the same dimension and detect the Average Variance Extraction (AVE). The recommended value should be greater than 0.5 (Hair et al., 2016). The discriminant validity aims to measure the correlation between scales with different characteristics, using the square root value of AVE to test (Hair et al., 2016).

The results from Table 4 show that the loading coefficients of the scales are all greater than 0.7, the Cronbach's alpha value and the reliability of the CR latent variable component of all factors are also greater than 0.7, which has ensured the reliability and internal consistency, the average extracted variance AVE of each factor is greater than 0.5, ensuring the requirements for the convergent validity of the factors.

Table 4: Reliability Test Results

The results in Table 5 show that other analytical parameters of the model also ensure the statistical requirements: The discriminant validity of the model is guaranteed because all values on the diagonal are larger than in the respective column (Fornell & Larker, 1981).

Table 5: The Discriminant Validity

The results in Table 6 show that all Heterotrait-Monotrait Ratio values are less than 0.9, showing that the discriminant validity is confirmed to ensure the fit of the model (Fornell & Larker, 1981).

Table 6: Heterotrait–monotrait Ratio of Correlations. (HTMT)​​​​​​​

4.2. Structural Equation Modeling Analysis

When evaluating structural equation models, the problem of multiple additions should be carefully considered. If the Variance Inflation Factor (VIF) is greater than 5, it means that multicollinearity ca n occur between the factors (Fornell & Larker, 1981). The results in Table 7 show that all the VIF values of the structural equation model in this study are less than 5, ranging from 1.005 to 1.063, indicating that there is no homogeneity between the scales in this study, that is, there is no collinearity among the study dimensions.

Table 7: Collinearity Analysis and Model Fit​​​​​​​

Besides, the SRMR, NFI and RMS_theta indexes are commonly used indicators for PLS-SEM to assess the fit of the overall model. The range of the SRMR value is from 0 to 1. When the SRMR is less than 0.08, indicating it fits the model. The range of the NFI value ranges from 0 to 1. The larger the NFI value, the better the performance obtained. When the generated NFI is greater than 0.9, indicating it fits the model (Hair et al., 2016). The RMS_theta value is only suitable for evaluating reflectance measurement models. RMS_theta values less than 0.12 indicate that the model fits well (Hair et al., 2016). The model evaluation SRMR value in this study is 0.055, showing the appropriateness of the model. Therefore, the model in this study is suitable to test the structural equation modelling.

The R² value is used to evaluate the explanatory power of the model. R² values range from 0 to 1. A higher R² value indicates the explanatory power of the model. The results at the adjusted R² in Table 8 are 0.661 (66.1%) showing that the explanatory level of the latent variables is at a high level. The function value f² represents the influence of the structure (factor) when removed from the model. Structures with f² values greater than 0.02 indicate that all linkages show a high degree of influence.

Table 8: R² and f² value

To test the hypotheses posed in the study, after the reliability, fit and explanatory values of the model were ensured, the study conducted a bootraping test with a repeat value of 5000 times. The results of the analysis are shown in Table 9 as follows:

Table 9: Results of Determining Significance Level​​​​​​​

The results in Table 9 and Figure 2 show that the associations with P-value less than 0.05 are significant associations with 95% confidence. The results show that the intrinsic motivation of the lecturers has the direct relationship and has the strongest impact on the motivation of the lecturers (β=0.545, t=15.687, p<0.05); next, the extrinsic motivation of the lecturer also has a direct relationship and has a strong impact on the work motive distribution of the lecturer (β=0.383, t=10.213, p<0.05); and finally, the job characteristics of the lecturers also have a direct relationship and impact on the work motive distribution of the lecturers (β=0,303, t=8.584, p<0.05). Thus, all of these results support the hypotheses.

Figure 2: Hypothesis Test Results of the Model​​​​​​​

4.3. Discussion

The research results show that the model of factors affecting the work motive distribution of lecturers with 3 factors affecting the work motive distribution of public universities lecturers in Hanoi has tested, the values related to the reliability and fit of the model are accepted showing that the model is suitable for conducting research.

The test results show that the intrinsic motivation of the lecturers, the extrinsic motivation of the lecturers and the job characteristics of the lecturers all have a positive impact on the work motive distribution of public universities lecturers in Hanoi. In which, intrinsic motivation has the greatest influence on the work motive distribution of lecturers. This result is consistent with previous studies, whereby individuals with good intrinsic motivation not only use deeper-level processing strategies and perform better in learning, but also psychological well-being and gain more satisfaction from some life activities (Grolnick & Ryan, 1989; Sheldon & Kasser, 1998; Ryan & Deci, 2000). In addition, the research results also prove that job characteristics affect the work motive distribution of lecturers, when a job is designed to secure its status based on these characteristics, improvements in lecturers' motivation, satisfaction, and performance are increased. This is a new factor in the factors affecting the work motive distribution of public universities lecturers. Public universities need to pay attention to appropriate professional development measures and policies to promote future lecturers' work motive distribution and arouse enthusiasm in the workplace (Robescu & Iancu, 2016). The findings is also consistent with the conclusions of many other studies such as the study of Sharma and Jyoti (2009), Tan and Hoa (2018).

5. Conclusion

By conducting the Partial least square - structural equation modelling (PLS - SEM), the research results have confirmed the reasonableness of the PLS - SEM analysis method, especially in exploratory research and requires close linkage together in the transition from a theory to a structural equation modelling. Through an investigation with 306 survey samples who are public universities lecturers in Hanoi, the research results show that the proposed research model is reliable and appropriate. The study also shows the reliability of the scales developed from this study.

The research findings will help universities gain a more comprehensive view of the work motive distribution of lecturers in the context that higher education in Vietnam is undergoing fundamental, comprehensive, and integrated innovation. According to international standards, there has been a breakthrough in quality and a strong transformation in training programs and human resource structure. With this research results, it will help universities have a basis to promote the work motive distribution of lecturers through the proposed model. Research has demonstrated that the factor of job characteristics has a positive influence on the work motive distribution of lecturers. Therefore, managers at public universities in Hanoi need to be oriented in designing suitable jobs, always giving lecturers the opportunity to express their creativity and contribute more in their expertise such as through undertaking real projects. In addition, public universities also need to create conditions for lecturers to develop personal skills and professional skills through knowledge-sharing activities initiated and organized in a faculty/subject environment.

In the process of implementation, the study still has some limitations due to limited resources, the study can only carry out the survey in Hanoi, which will more or less limit the representativeness of the research results. From the results of this study, further studies can expand other groups of lecturers over time to understand the change of work motive distribution, or expand the scope of research to all provinces in the country, future studies can also compare the demographic characteristics of the survey subjects.