Impact of Job-Related Factors on Lecturer's Performance: A Case Study in Vietnam

INTRODUCTION

When studying the performance of employees, there have been many different perspectives and approaches to introduce this concept. Employee performance is not only a topic of concern for businesses, but researchers in the fields of management and organizational psychology have also conducted related studies. In the field of management, the main research direction is how workers can achieve optimal productivity through activities that improve employee qualifications and provide the necessary conditions. Researchers view work performance as the result of a certain activity or position (Bal & De Lange, 2015). According to this approach, employee performance is the completion of the assigned work volume; this result is measured based on pre-established standards by the organization, such as output product volume costs. Costs and time, thereby evaluating the level of job completion. Thus, this perspective emphasizes the results and does not focus on the behavior that leads to the results.

Meanwhile, psychologists focus on understanding the interaction of factors such as commitment, employee motivation, job satisfaction, and personal factors on job performance results. Accordingly, the performance of employees is a collection of behaviors aimed at achieving organizational goals (Murphy, 1989). It includes all actions and behaviors that are related to organizational goals and can be measured in terms of an individual's job proficiency. Campbell (1990) proposed eight metrics to measure the performance of assigned work, largely based on a framework of eight aspects, including (1) Specific job proficiency, (2) Not proficient in a specific job, (3) Proficient in written and verbal communication, (4) Demonstrates personal effort, (5) Maintains personal discipline, (6) Facilitates benefits for peers and group work performance, (7) Supervision/leadership, (8) Management and administration.

Employee performance plays a pivotal and multifaceted role in organizational dynamics, with its significance well-documented in academic literature. As Armstrong (2006) underscores, the performance of employees is central to the achievement of organizational objectives and the maintenance of competitiveness in the modern business landscape. High-performing employees contribute significantly to increased productivity, heightened service or product quality, and enhanced customer satisfaction (Kaynak & Hartley, 2005). Moreover, their positive influence extends to organizational culture, inspiring teamwork and fostering a climate of motivation (Schneider et al., 2013). The alignment between employee performance and organizational goals is pivotal, as it directly influences key performance indicators and, consequently, organizational success (Muhammad et al., 2021). Thus, organizations that invest in employee development, facilitate regular feedback mechanisms, and cultivate an environment conducive to continuous improvement are better poised for adaptability, competitiveness, and long-term sustainability (Latham & Pinder, 2005).

The potential influence of job performance on voluntary turnover is anticipated to be mediated indirectly through intentions to quit, and it also has direct repercussions on voluntary turnover, particularly in the form of unplanned resignations. Lee and Mitchell (1994) researched the unfolding model of turnover, and the results showed that employees may react to unforeseen disruptions in the work environment, prompting contemplation of leaving their jobs. Faced with these undesirable prospects, employees may deliberate on whether to exit their organizations rather than confront unpleasant and potentially psychologically harmful circumstances.

The results of a study by Zimmerman and Darnold (2009) suggested that the relationship between performance and intent to quit is both negative and modest. Further, the results suggested that there are excluded variables that moderate the magnitude of the relationship. Only the relationship between objective ratings of performance and intent to quit was homogenous. In addition, the results of this study indicate that job performance affects turnover intentions and behaviors both directly and indirectly (Zimmerman & Darnold, 2009).

Literature Review

Job Demand-Control- Social Support Model

Job Demand -Control model was introduced by Karasek (1979) and presented an assessment of stress and stress factors in the work environment and health promotion in the workplace. In the JDC model, Karasek proposed three factors: 1) Job requirements, such as workload requirements and work time, are understood as a source of stress for workers. ; 2) Job control is understood as the employee's ability and level of job decision-making; 3) Work stress is a factor that occurs when job requirements are high and workers' job control is low (Karasek, 1979).

Karasek's Job Demands-Control Model is widely applied in research on job performance and job satisfaction of employees. Research results show that workers in conditions of high job demands and low job control will fall into a state of exhaustion. On the contrary, when job demands are low, and job control is high, it positively affects the emotional state of workers (Karasek, 1979).

Thus, the interaction of job requirements and job control has an impact on the employee's emotional state, or in other words, the employee's work pressure (Fernet et al., 2004). The Job Demands-Control Model is also applied to determine the relationship between job demands, job control, and job performance outcomes such as job satisfaction, job complaints, and job pressure (Schmidt & Diestel, 2011). Research results confirm that high job requirements and low job control, although they do not affect each other, are two factors that affect the work pressure of nurses in Germany (Schmidt & Diestel, 2011). Testing the interaction model between job requirements, job control, and work stress is a three-way interaction; each increase or decrease of each factor in the model will change the remaining factors (Hauser et al., 2011).

The Job Demands-Control Model has identified factors that affect job satisfaction and job performance that belong to the nature of that job (Karasek, 1979). At the same time, this model also points out the multidimensional interactions between factors belonging to this job (Karasek, 1979). The model is also widely applied by researchers in many fields of industry. Through this, the researchers also proposed solutions to improve workers' stress at work and, at the same time, improve negative reactions from stress at work, thereby improving their occupational performance. individual (Karasek, 1979).

However, the limitation of the Job Requirements-Control model is that it ignores factors belonging to the organization and the people in that organization - the working environment that has an impact on the psychology and behavior of workers. Dynamic. Employees not only work alone but also need the coordination and support of other individuals in the organization (Johnson & Hall, 1988). Those individuals include colleagues, direct managers, subordinates, and work-related parties. In the process of performing their work, individual workers need to interact with other members inside and outside the organization (Johnson & Hall, 1988). This interaction can bring positive or negative states to the worker.

Researchers Johnson and Hall discovered the third organizational factor that affects workers' work pressure, which is social support related to work - Social Support (Johnson & Hall, 1988), thereby expanding the JDC model into the Job Demands-Control- Social Support Model. This study was conducted based on a random survey of 13,779 Swiss workers. Research results of Johnson and Hall (1988) added the factor of co-worker support to the model of factors affecting employee pressure. According to this model, co-worker support at work combined with job demands and job control have an impact on job outcomes (Johnson & Hall, 1988). This Johnson and Hall model is widely applied to analyze factors affecting workers' work behaviors.

Applying the Demand-Control-Social Support model at work, Del Pozo-Antunez and colleagues (2018) determined that social support for employees includes support from colleagues and colleagues. From the manager. In particular, support from colleagues impacts the accounting staff's performance results, and the author also emphasizes that support from managers directly impacts work pressure and job requirements (Del Pozo-Antunez et al., 2018). Besides, co-worker support has a positive impact, while line manager support has a negative impact on the use of social networking tools in the workplace in Thailand (Charoensukmongkol, 2014). These effects will lead to job satisfaction, job performance, and cognitive uptake (Charoensukmongkol, 2014). Accordingly, when applying this model, research results confirm that high job requirements and limited social support increase work stress. Therefore, improved changes in job demands and increased social support may contribute to improved work outcomes (Rajaleid et al., 2018).

The Job Demands-Control-Supports Model is also applied to determine how job-related factors impact worker safety performance (Turner et al., 2012). Other studies by Fila and colleagues (Fila et al., 2017) have tested the relationship of these job factors under the influence of gender, nationality, and occupation. Thus, the social support factor not only has a single influence but also has a three-way interaction in relation to work requirements and work control to affect the work pressure of workers.

However, the limitation of the Job Demand-Control-Social Support model at work is that the constituent elements of social support are incomplete. Here, the researcher has only identified the support from colleagues for the employee's job performance.

In the process of performing a worker's job, the working environment also has many other sources of influence (Baruch-Feldman et al., 2002; Abbas et al., 2023). Studies on sources of social support at work identify support from colleagues, support from leaders, support from subordinates, and support from the organization (Baruch-Feldman et al., 2002). Research by Del Pozo-Antunez and colleagues (2018) confirms that social support affects work pressure, including support from colleagues and managers for employees. In the same vein, in the research of Charoensukmongkol (2014), Lin et al. (2009), and Bowen et al. (2014) also analyzed the impact of support from colleagues and managers on work pressure. Workers' work.

Job Demand on Employees' Performance

The impact of job demands on psychological and physical strain, as well as on job performance, has been the focus of many applied occupational studies. The studies concerning the demands–strain relationship vary not so much in establishing a link between job demands and outcomes but rather in their selection of moderating variables. Researchers have included personal or job-related characteristics (Karasek, 1979; Johnson & Hall, 1988) as relevant moderators for reducing the harmful effect of job demands on workers' strain. In continuing this research effort, the present study's first goal was to identify an additional moderating job characteristic, role clarity.

The study's was to examine the link between occupational demands and job performance. Previous studies concerning the demands–performance relationship have found little or no relationship between demands and performance (Lang et al., 2007). Researchers have argued that the weak link might be due to the omission of potential intervening variables that mediate the demands–performance relationship (Lang et al., 2007; Sumantri et al., 2022).

The secondary objective of the study by Lang et al. (2007) is to investigate the association between demands and performance. One pragmatic explanation for the frequently observed weak or non-existent correlation between demands and performance in studies could be attributed to the complexity of performance, which is influenced by various factors that are not readily captured through self-report methodologies.

 Job Control on Employees' Performance

The relationship between job control and employee performance has been a subject of significant interest and scholarly investigation within the field of organizational psychology and management. Job control, defined as the degree to which employees can influence their work processes and make decisions regarding their tasks, has been identified as a crucial factor influencing various aspects of employee performance (Karasek, 1979).

Several theoretical frameworks have been proposed to elucidate the mechanisms through which Job Control influences employee performance. One prominent theoretical lens is the Job Demands-Control model (Karasek, 1979), which posits that employees experience optimal performance when they have a balance between job demands and the control they exert over their work. High levels of job control are theorized to enhance motivation, job satisfaction, and overall well-being, leading to improved performance outcomes.

Numerous empirical studies have investigated the impact of Job Control on various dimensions of employee performance. Research findings consistently suggest a positive correlation between job control and job performance. Employees with higher levels of autonomy and decision-making authority tend to exhibit increased task performance, creativity, and job satisfaction.

Job control has also been linked to reduced stress and burnout, further supporting its positive influence on employee performance. By providing employees with the autonomy to manage their work and make decisions, organizations create an environment conducive to higher engagement and commitment.

While the overall trend supports the positive impact of job control on performance, the relationship is not uniform across all contexts. Moderating factors such as individual differences, job characteristics, and organizational culture have been identified as influencers in the job control-performance nexus. For example, the relationship may be more pronounced in knowledge-based occupations compared to routine tasks.

In conclusion, the literature overwhelmingly suggests a positive association between job control and employee performance. Organizations stand to benefit from recognizing the pivotal role that autonomy and decision-making authority play in fostering a conducive work environment. Future research should delve into the nuances of these relationships, considering moderating factors and exploring the potential boundary conditions to provide a more nuanced understanding of the impact of job control on diverse facets of employee performance.

Social Support on Employees' Performance

Social support within the workplace has emerged as a crucial factor influencing various facets of employees' professional lives. This literature review aims to explore and synthesize existing research to illuminate the impact of social support on employee performance. Understanding the intricate dynamics between social support and performance is essential for organizations seeking to enhance employee well-being and productivity.

Social support encompasses the emotional, informational, and instrumental assistance provided by colleagues, supervisors, and organizational networks. Such support serves as a buffer against stressors and contributes to the overall well-being of employees.

Workplace support is a set of actions or behaviors intended to help others in the workplace (Pelin & Osoian, 2021) performed by both co-workers and managers (Chou, 2015). This support includes counseling, emotional support, providing assistance in solving problems and tasks, or informing others about the work system in the organization. Researchers emphasize the importance of co-workers as a key source of support for employees. For example, a more experienced employee in the organization provides support to a newly hired employee or guides a newly promoted person about knowledge and experience in the work organization.

Relationships with colleagues, support, and coordination at work also affect Job Performance (Babin & Boles, 1996). Research by Pelin and Osoian (2021) shows that high support and coordination from colleagues will help workers achieve high results at work.

From the above comprehensive studies, the author proposes a hypothesis that the support of colleagues has an impact on the Job performance of lecturers.

Even though a lecturer's job has been described in the job description or job position description with clear regulations, there are still tasks performed by superiors and work assigned by the organization. Therefore, to achieve good results, it is necessary to have assignments, guidance, and support from direct leaders during work performance. This support is the manager's interaction with the employee. Therefore, it also has an impact on the employee's performance (Foy et al., 2019).

Accordingly, in the regulations of the Ministry of Education and Training, as well as regulations on the duties of lecturers, the main duty of lecturers is teaching. Teaching activities are the activities of transferring knowledge from lecturers through different teaching tools and methods to students. This knowledge transfer process takes place two-way, requiring student interaction throughout the learning process. The job performance of lecturers is largely assessed by the learning results of students, the application of knowledge of students after graduation to students' future jobs, and is recognized by businesses.

In the context of innovation and internationalization of education, universities aim to train according to social needs. That is, developing training programs, subject content, and teaching methods all take opinions from learners- especially businesses - who act as future employees.

Businesses are partners who provide suggestions and requests to educational institutions regarding their requirements for future personnel. This helps businesses significantly reduce the cost of training new personnel, helping students quickly catch up with work after graduation. Currently, businesses actively associate with universities and support lecturers in carrying out their work in many different forms.

According to the JDCS model, job control moderates the impact of job demands (Johnson & Hall, 1988). When job requirements are higher, the level of job control will reduce the impact of job requirements on the employee's job performance. Job control indicates the ability and scope of control over job performance, work order, and priority (Johnson & Hall, 1988). Allows employees to proactively arrange work plans, build their work processes, and take full responsibility for that work. Therefore, when job requirements are increasingly high, but employees are given control over that job, it will help employees reduce the impact of job requirements on their performance (Johnson & Hall, 1988).

Therefore, the author proposes the hypothesis that Job control moderates the impact of Job Requirements on lecturers' performance.

As analyzed above, social support includes actions and behaviors that help others at work. Accordingly, when work requirements become increasingly strict in terms of execution time, or when the workload increases and demands require higher quality work, social support will contribute to helping people. Workers perform work more efficiently (Foy et al., 2019).

Support from colleagues helps employees clearly understand job requirements and regulations related to the job performance process. Through this, workers themselves can determine effective work processes and allocate working time appropriately (Johnson & Hall, 1988). This support from colleagues helps reduce the impact of job requirements on lecturers' performance. Besides, research also shows that support from managers helps moderate the impact of job requirements on job performance.

Therefore, the author proposes the hypothesis that social support moderates the impact of job demand on lecturers' performance.

MATERIALS AND METHODS

The author has conducted general research and research on fundamental theories collected results of domestic and foreign research related to the research topic. From there, establish research questions and propose research hypotheses and research models.

Table 1. Scale measurement

Table 1 shows the measurement scale for each variable in the model is selected from foundational theories and previous studies. The questionnaire was designed based on available scales and translated from English to Vietnamese, with adjustments to suit the survey subjects who are lecturers. The questionnaire was posted on Google form to easily send it to lecturers and receive results. The questionnaire was then used for a pilot survey with 10 lecturers and adjusted to be reasonable and clear for respondents to obtain the most accurate answers.

Because the questionnaire was collected from many research sources and translated from English to Vietnamese, the terms and implications of the questions were made clearer and accompanied by a description of the purpose of the questionnaire. After receiving feedback from the first lecturers on the questionnaire, it was specifically revised as follows:

Question 3 about business support: "Business partners are willing to support me in teaching activities" was supplemented with scientific research activities and other work activities.

Question 6 about Job Requirements: "My job faces conflicts in job requirements" was considered unclear confusing, and after discussion with experts, it was agreed upon. Change it to "I encounter many conflicts in job requirements."

After being adjusted, the questionnaire was collected based on a convenient survey method to obtain data quickly and randomly. Lecturers who receive the questionnaire will answer and send it to other lecturers. The process collected 153 valid answer sheets to include in step 3.

The received answers are coded processed for missing data, exploratory factor analysis, and validation factor analysis. The minimum sample size for exploratory factor analysis is 5 times the number of observations than the number of variables; more appropriate is 10 times, and even better is 20 times. Because the number of variables of the intended model is 4 variables, the number of votes Collect a minimum of 40 valid votes, preferably 40 votes and preferably 80 valid votes. The result of the data was 153 responses, ensuring a sufficient number for exploratory factor analysis, validation factor analysis, and model regression.

The tool used to conduct the analysis is SPSS 24.

Step 4: Analyze data and write reports.

The data results collected were coded, and SPSS 24 software was used to conduct data analysis.

RESULTS AND DISCUSSION

Frequency

Descriptive statistical analysis aims to provide overview information about the study sample in terms of numbers and percentages. Descriptive statistics applied to the analysis of the personal information of the sample include the following information.

Table 2. Sample Demographic

Table 2 indicate the demographic characteristics of respondents. Among 153 respondents, there are 51 male accounted for 33.3% and 102 Female accounted for 66,7%

Table 3. Education Level of respondents

Table 3 shows the result of descriptative indicated that there are 90 lecturers accounted for 58.8% who has master degree and 63 lecturers who are PhD accounted for 41.2%

Table 4. Experiences

Table 4 shows the answer for question about experience of lecturers, almost lecturers has 10 years and above which accounted for 121 lecturer- 79.1% followed by the number of the lecturer who has from 5 years to under 10 years and from 1 year to under 5 years experiences accounted for 25 lectuers- 16.3% and 7 lecturers- 4.6%

Table 5. Reliability test

The data collected input in SPSS and the reliability result indicated that all the variable range from 0.798 to 0.950 are accepted by the cronbach alpha higher than 0.7. The Table 5 showed the detail.

The results of the KMO and Bartlett's test show that the KMO index = 0.795 is greater than 0.5 and Sig of the Bartlett test = 0.000 < 0.05; this proves that the application of factor analysis techniques in this case completely matches the data set.

The analysis results show that 36 observed variables are extracted into 7 main factors (groups) with high Eigenvalues and all greater than 1, of which the 7th factor has the smallest Eigenvalues: 1.145. At the same time, the total variance extracted is 69.726% > 50%, so it is considered satisfactory. Specifically, the analysis results follow.

The analysis results show that the factor loading coefficients are all greater than 0.5. Therefore, it is concluded that all 7 factors satisfy the discriminant and convergent properties.

The results of exploratory factor analysis extracted 7 factors representing the concepts to be measured. The structural measurement scales will be subject to confirmatory factor analysis (CFA) using AMOS software. The scales include Job Demand, Job control, support from colleagues, Support from superiors, Support from students, support from businesses, and Job performance.

The summary results table shows that the scales all have a composite reliability greater than 0.7 and an average extracted variance greater than 0.5, so the scale is reliable and suitable for structural model analysis. SEM structure.

According to the analysis results, all standardized and unstandardized coefficients are greater than 0.5. At the same time, the AVE values are all greater than 0.5, so it can be concluded that the factors have convergent validity.

Summary of the results of confirmatory factor analysis CFA shows that the model fits well, the variables achieve convergent validity, discriminant validity, and reliability. Therefore, the model is suitable for conducting SEM linear structural model analysis.

After conducting the CFA test, the scales in the theoretical model were evaluated and gave appropriate results. The author tested the theoretical model with hypotheses using the SEM structural model method.

According to the results of SEM analysis, all relationships have a p-value <0.05, indicating that the cause-and-effect relationships are statistically significant. The proposed hypotheses are all accepted.

Table 6. Path coefficient

Table 6 shows the results of the standardized model indicate the level of impact of the factors in the research model. From the results of SEM structural model analysis, the author draws the following conclusions:

Job Demand has a negative impact on job performance with a standardized regression weight of -0.169. Meanwhile, the remaining factors all have the same impact on job performance, including Job control with a standardized regression weight of 0.281; Co-worker support has a standardized regression weight of 0.233; supervisor support with a standardized regression weight of 0.203; Student support with a standardized regression weight was 0.145; business support with a standardized regression weight of 0.137.

At the same time, the Job Control variable and the Social Support variable act as two variables moderating the impact of job demand on job performance with weights of 0.137 and 0.166, respectively.

The job performance of lecturers is one of the top factors of concern for lecturers as well as management teams in specialized departments and the Board of Directors. The summary of the lecturer's performance results is the overall result of each lecturer. Therefore, if the managers want to improve organizational efficiency, they need to improve the professional performance of each lecturer.

The research topic has proposed a research model to determine work-related factors that impact the job performance of lecturers based on survey collection and data analysis based on 153 results obtained.

Research results show that the factors in the proposed model all have an impact on lecturer performance results with different directions and levels of impact. Specifically, the author hypothesizes that job demands have an impact on lecturers' job performance. The results of regression analysis show that job requirements have a negative impact on the professional performance of lecturers. Regarding the hypothesis that job control has an impact on lecturers' job performance, the results of analyzing the collected data show that job control has a positive impact on lecturers' job performance.

The author proposed that the Social Support variable be divided into 4  components: Support from co-workers, support from superiors, support from students, and support from partner businesses. The hypothesis is that social support from colleagues support from superiors, support from students, and support from partner businesses have an impact on lecturers' performance. Based on the analysis results from 153 respondents, these social support variables include support from colleagues, support from superiors, support from students, and support from businesses, which have a positive impact on the performance of lecturers.

In addition, the author proposes the hypothesis that Job Control plays a role as a moderating variable in the impact of Job Demand on the job performance of lecturers. Analysis results have shown that Job Control has a positive role in regulating the impact of job demand on job performance. At the same time, the author synthesized the answers of the lecturers and proposed that social support, in general, is a variable that moderates the impact of work performance requirements on professional performance. The results also show that social support has a positive moderating role in the impact between job requirements and job performance.

Regarding the intensity of impact, among the independent variables that affect the professional performance of lecturers, work control has the strongest impact on professional performance, followed by the support of colleagues and the support of superiors. With lecturers, job requirements. Business support and student support for lecturers' work performance are the two factors that have the least impact on lecturers' professional performance.

The intensity of the impact of the moderating variable of social support on the impact of job requirements on personal performance is stronger than the moderation of the variable of job control on the impact of job requirements on personal performance.

Research results on the impact of job demand on job performance agree with the results of previous studies (Lu et al., 2017). Accordingly, when job demand increases in terms of the number of tasks, the need for urgent completion time and the need to complete the job at a high level will reduce the lecturer's professional performance. In addition, job demands also include requirements for capacity development, such as learning new knowledge and skills, requiring creativity of the person performing the job. When these requirements increase, it will have a negative impact on the lecturer's professional performance.

Vietnam Universities need to clarify job performance requirements for lecturers. Each job has different characteristics and requires different results. Job factors indicate the job tasks that the performer needs to complete. The job description stipulates the tasks, responsibilities, and powers of the person performing the job, through which the person performing the job clearly understands the nature of the job and performs it effectively.

It is necessary to build or apply a work management system, allowing lecturers and staff to store and manage all scientific research activities, self-training, field visits, and participation in other activities. Other organizations. This work management system needs to be consistent with the KPI system to evaluate lecturers' work performance. At the same time, this system allows lecturers to report at any time during the school year about the work they have done. Tracking work progress and reallocating each individual's resources helps lecturers control their work better.

At the same time, leaders in the academy increase support for junior lecturers, helping lecturers clearly understand the work and tasks they are carrying out. Through training, mentoring, and discussion activities, highly professional colleagues and managers share their work experiences with lecturers and introduce effective and positive teaching methods, share professional discussions. Such timely support encourages lecturers to do their jobs better.

In addition, to encourage students to be proactive in learning activities and exchange with lecturers, lecturers need to improve teaching methods, focusing on learners. Through active teaching and learning methods, students will actively and proactively participate in lectures as well as follow the instructions of instructors. Transferring knowledge to students not only helps students achieve good learning results but also helps lecturers improve their understanding, awareness, and creativity in the process of performing their work.

The importance of support from business partners has been shown in the research model and accepted hypotheses. In the context of innovation and internationalization of education, universities aim to train according to social needs. That is, the development of training programs, subject content, and teaching methods all take opinions from learners and especially businesses - who will be the future employees.

Limitation

First, the new study limited survey participants to lecturers at 6 universities in Hanoi. Currently, according to the organizational structure and job positions, the universities still have a large number of training support staff, including experts and staff working in the following departments: Training, Scientific Research Department, Library Information Center, Training Center, Training Support Center, Health. These employees have different job characteristics but contribute to affecting the overall work performance of the lecturers, affecting the results of the learners. Therefore, future studies need to collect information and evaluate the work performance of supporting staff.

Second, the working environment and working conditions among universities may have different perspectives. Therefore, the author proposes that the next study will conduct research at all universities and compare these Universities, thereby comparing and finding solutions suitable to the characteristics of each type of university.

Third, the number of respondents was 153 who were working at University in Hanoi. The following research proposal collects more information and surveys to fully evaluate the impact of factors on the work performance of lecturers in Vietnam.

CONCLUSION

Research synthesis shows that the performance of university lecturers requires multidimensional assessment, including the completion of the volume and quality of assigned work according to the lecturer's job description, with the main tasks being teaching. Teaching, scientific research, and self-training. Besides, it is necessary to evaluate the academic performance of lecturers from the perspective of behavioral research. Behaviors provide indirect results for the overall assessment of job performance.

Lecturers have a unique job, so when researching factors affecting lecturers' professional performance, it is necessary to consider the context and working conditions of lecturers. Factors belonging to the work itself, the support and coordination of managers and colleagues are factors within the organization that affect the professional performance of lecturers.

Research on factors affecting lecturers' work results helps universities and managers at universities, in general, identify problems that lecturers encounter during their practice. Perform work and, at the same time, serve as a basis for proposing appropriate solutions and policies to improve lecturers' professional performance as well as improve the effectiveness of the organization and ensure the ability to achieve the organization's common goals.

ACKNOWLEDGMENTS: The author gratefully acknowledges the support of all the lecturers who advised the study and provide their answers.

CONFLICT OF INTEREST: The authors declare that there is no conflict of interest regarding the publication of this paper. All the aspects of the research and manuscript preparation were concluded impartially, and there are no financial or personal relationships that could influence the objectives of the study.

FINANCIAL SUPPORT: The financial support from the Banking Academy of Vietnam.

ETHICS STATEMENT: None