Luận văn thạc sĩ UEH the impact of perceived organizational support on job performance, the medication of job engagement a study of commercial banks in vietnam luận văn thạc sĩ

INTRODUCTION

Executive abstract

In the current landscape of international economic trends and WTO integration, Vietnam presents both opportunities and challenges for organizations, intensifying the pressure on product, service, brand, and human resource competitiveness Notably, human resources are viewed as a crucial asset that enables organizations to enhance their competitiveness and overall performance, serving as a key advantage for business development.

In Vietnam, the norms of reciprocity responsibility are widely implemented in organizations; however, many have not adequately focused on enhancing their human resource management systems, particularly regarding the relationship between perceived organizational support and job performance Consequently, there are persistent gaps in understanding and alignment between employers and employees.

The shortcomings in HR management have led to a lack of employee motivation, resulting in organizations failing to achieve their desired business outcomes.

According to previous studies such as studies of (Pfeffer J 1998); (Huselid, MA

Research indicates that human resource practices significantly impact business performance A key factor in effective human resource management is perceived organizational support (POS), which plays a crucial role in enhancing overall organizational success.

POS contributes to increase employees’ performance (POS) to help organizations reach their objectives The behavioral outcomes of POS mentioned herewith include increases, decrease in role and Job performance

Effective Human Resource (HR) management focuses on the relationship between perceived organizational support (POS) and job performance, emphasizing the importance of manpower resources in achieving organizational targets This study provides managers with strategies to motivate and encourage employees to perform effectively in a competitive labor market In an era where evolving knowledge management practices and global technological convergence reshape work dynamics, understanding POS becomes crucial in addressing the challenges posed by limited talent resources.

Research indicates that Perceived Organizational Support significantly influences Job Performance, with various mediating factors playing a crucial role in this relationship According to Kahn, these mediators enhance the connection between employees' perception of support and their overall job effectiveness.

In 1990, it was noted that individuals engage and express themselves physically, cognitively, emotionally, and mentally during their role performances This study aims to analyze the mediating factors that influence the relationship between Perceived Organizational Support and Job Performance.

Despite the recognized importance of perceived organizational support and employee engagement in driving competitive advantage, there is a notable lack of research examining their relationship with job performance, particularly in Vietnam This gap highlights the need for more studies focused on how engagement serves as a link between employee characteristics and organizational factors Furthermore, many organizations in Vietnam have yet to invest in enhancing their human resource management systems to address these critical areas.

This thesis explores "The Impact of Perceived Organizational Support on Job Performance, with Job Engagement as a Mediator, in Commercial Banks in Vietnam." The study aims to identify effective strategies for enhancing human resource management within these banks, focusing on the influence of Perceived Organizational Support and the mediating role of Job Engagement Ultimately, the research seeks to provide insights for the banking sector on addressing human resource challenges to achieve improved employee performance and favorable business outcomes.

This research aims to investigate how Perceived Organizational Support (POS) influences Job Performance (JB) in commercial banks in Vietnam, while also examining the mediation factors that affect the relationship between POS and JB.

- Relationship between perceived organizational support and job performance in banks in Viet Nam

- Investigating mediation factors that are affecting relationship between perceived organizational support and job performance in banks in Viet Nam

This article explores the positive factors influencing job performance in banks in Vietnam, emphasizing the relationship between perceived organizational support and employee performance It identifies key elements that enhance job effectiveness, highlighting the importance of supportive workplace environments in fostering employee productivity and satisfaction The findings aim to provide insights into how banks can improve their organizational practices to boost overall performance.

To enhance job performance in Vietnamese banks, it is crucial to implement strategies that boost perceived organizational support By focusing on improving business performance, banks can attract, motivate, and retain qualified employees Encouraging effective work practices will not only satisfy employees but also strengthen their commitment to the organization, ultimately leading to a more productive workforce.

With the above mentioned background, there arise question required to be studied so as to have solution as follows:

1 What is the common relationship between perceived organizational support and job performance in commercial banks in Viet Nam?

2 Which factors can be applied to improve the impact of perceived organizational support and job performance in commercial banks in Viet Nam, which are key factors?

3 Can the improvement of relation of perceived organizational support and job performance promote and develop competitive advantage and performance outcome of commercial bank in Viet Nam?

Study subjects: staffs and managers of commercial banks in Vietnam

This research focuses on the scientific basis of the relationship between perceived organizational support and job performance, specifically for managers in the banking sector By understanding these factors, managers can effectively implement strategies that enhance employee performance The study is limited in scope, concentrating on the impact of these elements within the banking industry.

LITERATURE REVIEW

Perceived organizational support (POS)

As one of definition, POS is the degree to which employees believe that their organization values their contributions and cares about their well-being (Eisenberger, Huntington & Sowa, 1986; Rhoades & Eisenberger, 2002)

Perceived Organizational Support (POS) plays a crucial role in fostering a positive dynamic between employees and their organization, as employees are motivated to enhance their performance in return for the support they receive (Rhoades & Eisenberger, 2002) Research indicates that when managers prioritize their employees' commitment, it encourages employees to reciprocate with loyalty to the organization Employees view the organization as a vital source of socioemotional resources, including respect and care, alongside tangible benefits like wages and healthcare Being valued by the organization fulfills employees' needs for approval, esteem, and belonging, while also signaling that their increased efforts will be recognized and rewarded Consequently, employees are invested in how well their employer supports them.

Organizational support theory (OST) suggests that employees develop a perception of how much their organization values their contributions and cares for their well-being, which is known as perceived organizational support (POS) This perception enhances employees' sense of obligation to assist the organization in achieving its goals, boosts their emotional commitment, and raises their expectations for performance rewards Consequently, POS leads to improved in-role and extra-role performance while reducing negative behaviors and unexpected outcomes among employees.

Research on Perceived Organizational Support (POS) has significantly expanded since the mid-1990s, with a meta-analysis by Rhoades and Eisenberger (2002) examining around 70 studies conducted up to 1999 Since then, more than 300 additional studies have been conducted, revealing clear and consistent relationships between POS and its anticipated antecedents and consequences.

Recent research by David R Hekman and colleagues (2009) indicates that professional employees are more inclined to reciprocate perceived organizational support (POS) when they have a strong identification with their organization The study highlights that both organizational and professional identification significantly impact performance behaviors Notably, the findings reveal that POS exerts the most positive effect on work performance among employees who strongly identify with their organization while having a weaker identification with their profession.

Job engagement

Job engagement has seen dramatic growth in research interest over the past few years

Briefly, work engagement can be defined as a positive, fulfilling state of mind, most commonly characterized by vigour, dedication, and absorption (Jonathon R.B

Halbesleben and Anthony R.Wheeler, 2008) Job embeddedness is defined as ‘‘the combined forces that keep a person from leaving his or her job’’ (Yao, Lee, Mitchell, Burton, & Sablynski, 2004, p 159)

“Work engagement is defined as a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption” (Schaufeli, Salanova, Gonza´lez – Roma and Bakker, 2002, p 74)

Kahn (1990) was the pioneering scholar who defined "personal engagement" as the alignment of individuals' identities with their work roles, where they actively express themselves physically, cognitively, emotionally, and mentally during their tasks He theorized that human agency operates in a holistic, consistent, and interconnected way, highlighting the importance of personal involvement in the workplace.

Job engagement goes beyond mere cognitive focus, emotional expression, or task completion; it embodies a holistic investment of cognitive, emotional, and physical energies This means being actively and fully involved in the performance of one's role, leading to a deeper connection and commitment to the job.

Work engagement is a concept that has been interpreted through two main perspectives The first, proposed by Maslach and Leiter, views burnout and engagement as opposing ends of a spectrum Conversely, Bakker and Demerouti (2007) define engagement as a distinct, positive state characterized by vigor, dedication, and absorption Vigor involves high energy levels and resilience, coupled with a strong willingness to invest effort and persist through challenges Dedication reflects deep involvement in one’s work, marked by feelings of significance, enthusiasm, and pride Absorption is defined by complete concentration and enjoyment in work, where time seems to fly, making it difficult to detach from tasks.

A measure that was constructed and validated by Schaufeli, Salanova, Gonzalez-Roma and Bakker (2002), called the Utrecht Work Engagement scale, is often administered to assess engagement (Salanova, Agut,& Peiro, 2005)

The vigor subscale, consisting of five items, indicates high energy, resilience, and persistence The dedication subscale, represented by six items, reflects a strong sense of purpose, enthusiasm, inspiration, pride, and a willingness to face challenges at work Lastly, the absorption subscale measures how deeply individuals engage in their work activities.

Engagement measures derived from the work of Kahn

Rich, Lepine, and Crawford (2010) develop a measure of engagement that more explicitly assesses the three dimension of engagement that were defined by Kahn

(1990, 1992): the investment of physical, emotional, and cognitive energy into the task at work

To measure physical engagement, Rich, Lepine, and Crawford (2010) adapted six items from Brown and Leigh's (1996) work intensity scale, including the statement, "I work with intensity on my job." For emotional engagement, they derived six items from Russell and Barrett's (1999) framework, focusing on positive feelings and a sense of energy, exemplified by "I am excited about my job." Lastly, cognitive engagement was assessed using six items adapted from Rothbard (2001), which gauge how focused and engrossed individuals feel at work, such as in the item, "At work, I am absorbed by my job."

Engagement can be assessed through various measures, with some focusing on a single key aspect For instance, Peterson, Park, and Seligman (2006) created an engagement measure centered on absorption, viewing it alongside meaning and pleasure as essential components of happiness In contrast, Harter, Schmidt, and Hayes (2002) developed a broader 12-item measure that defines engagement as the clarity of expectations, the significance of the job, the trustworthiness of colleagues, and strong opportunities for development.

Engagement can be viewed as the opposite of burnout, as suggested by Maslach, Jackson, and Leiter (1996), who often utilize the Maslach Burnout Inventory for assessment According to Maslach and Leiter (1997, 2008), high engagement is characterized by low levels of exhaustion and cynicism, alongside high levels of efficacy Research supports the idea that vigor and exhaustion, as well as dedication and cynicism, are two opposing ends of a single dimension, highlighting the intricate relationship between engagement and burnout (Gonzalez-Roma, Schaufeli, Bakker).

Lloret, 2006) The Oldenburg Burnout Inventory (Demerouti, Bakker, Nachreiner, &

Ebbinghaus, 2002) is sometimes preferred instead, because the scale includes both positively and negatively worded items, more applicable to engagement

This study aims to demonstrate the significant role of job engagement—encompassing cognitive, emotional, and physical aspects—as a mediator between perceived organizational support (POS) and job performance.

Job performance (JB)

Motowidlo, Borman, and Schmit (1997, p.73) stated that, “as a construct, performance is behavior with an evaluative component, behavior that can be evaluated as positive or negative for individual or organizational effectiveness.”

According to Conway, Motowidlo, and Schmit (1999), as well as Motowidlo et al (1997), job performance can be categorized into two main types: task performance and contextual performance Task performance involves activities outlined in a formal job description that directly impact the organization's technical core In contrast, contextual performance, often known as organizational citizenship behaviors (OCB), refers to actions that, while beneficial, do not directly contribute to the core technical processes of the organization.

John P Campbell and his colleagues propose a widely accepted theory of job performance, viewing it as an individual-level variable rooted in psychology Campbell defines job performance as behavior performed by the employee, allowing for exceptions where performance may not be directly observable This includes mental activities such as decision-making and problem-solving Importantly, performance must remain within the individual's control, whether it manifests as observable actions or cognitive processes.

Dennis Organ (1988) is recognized as the father of Organizational Citizenship Behavior (OCB), which encompasses employee behaviors that are supportive, discretionary, and exceed standard job requirements He defines OCB as “individual behavior that is discretionary, not directly or explicitly recognized by the formal reward system, and that in the aggregate promotes the effective functioning of the organization” (p 4) OCBs are characterized by three key aspects: they are discretionary actions performed out of personal choice, they surpass the enforceable requirements of job descriptions, and they enhance overall organizational effectiveness According to Organ, the discretionary nature of OCB indicates that these behaviors are not mandated by formal job descriptions, and employees are not penalized for failing to exhibit them.

What is important is that these examples describe behaviors which are helpful to the organization, yet they are not behaviors considered part of the core elements of the job

2.4 Related theories and antedent researches 2.4.1 Relationship of POS- Job performance and role of mediators

Perceived organizational support, a concept that reflects the type of support Kahn

Perceived organizational support, defined by employee interactions with supervisors and organizational agents, significantly influences employees' beliefs about how much their contributions are valued and how much the organization cares for their well-being When employees feel supported, they are more likely to have positive expectations regarding the organization's responses to their efforts and mistakes, leading to reduced anxiety about potential negative consequences for their self-image and careers Conversely, low perceived organizational support creates uncertainty and fear, prompting employees to withdraw from their roles to protect themselves This aligns with research indicating a strong positive correlation between perceptions of organizational support and job engagement.

A study conducted by researchers at the University of Delaware, including Robert Eisenberger and colleagues, examined the role of perceived organizational support (POS) in the relationships between employees' affective commitment and job performance among 413 postal employees The findings revealed that POS is positively linked to employees' sense of obligation to contribute to the organization's welfare and objectives This sense of obligation was found to mediate the relationships between POS, affective commitment, organizational spontaneity, and in-role performance Additionally, the relationship between POS and felt obligation strengthened when employees embraced the reciprocity norm in the workplace These results align with organizational support theory, suggesting that POS enhances employee commitment and performance through a process of reciprocation.

2.4.2 Related theories to concepts of POS, JE, JP:

Early theories on motivation highlight a significant relationship between Perceived Organizational Support (POS), Job Engagement (JE), and Job Performance (JP) Effectively utilizing job motivation and satisfaction tools can enhance POS, employee performance, and job outcomes Research by Bruce Louis Rich, Jeffrey A Lepine, and Eean R Crawford (2010) demonstrates that Job Engagement and Job Satisfaction serve as mediators in the relationship between POS and Job Performance.

Roles of motivation, satisfaction to POS, JE, JP can be seen in the following contents:

Motivation is a key focus in organizational behavior (OB) research, demonstrating its significant impact on enhancing employee engagement, retention, commitment, and job satisfaction By effectively supporting employees, organizations can reduce turnover and foster a more committed workforce.

Motivation is the process that influences an individual's intensity, direction, and persistence of effort toward achieving a goal (T.R Michell, 1997) Since the 1950s, three key theories have emerged that continue to shape our understanding of employee motivation: Maslow's Hierarchy of Needs (1943), McGregor's Theory X and Theory Y, and Herzberg's Two-Factor Theory (1959) These theories remain some of the most recognized frameworks for understanding what drives motivation in the workplace.

In addition to early motivation theories, several key frameworks have emerged that serve as a foundation for research in human resource management These theories, including Alderfer's ERG Theory (1969) and McClelland’s Theory of Needs (1988), provide valuable insights into the relationships between job performance, motivation, employee engagement, retention, commitment, job satisfaction, turnover, and organizational support for employees.

Motivation plays a crucial role in influencing job satisfaction and performance, as well as organizational citizenship behavior (OCB), according to Robbins and Judge (2007).

Job satisfaction refers to the positive emotions an individual experiences regarding their job, stemming from an assessment of its attributes Those who experience high job satisfaction generally have favorable feelings about their work, whereas individuals who are dissatisfied tend to harbor negative sentiments towards their job (Stephen P Robbins and Timothy A Hudge, 2007).

A comprehensive review of 300 studies indicates a strong correlation between job satisfaction and job performance Organizations with higher employee satisfaction are generally more effective than those with lower satisfaction levels, highlighting the importance of fostering a positive work environment for enhanced organizational success (T A Judge, C J Thoresen, J.E Bono, and G.K Patton, 2011).

- Hierachy of need theory of Maslow (1943)

Abraham Maslow's Hierarchy of Needs is a prominent theory of motivation that outlines five essential human needs These needs include physiological requirements such as hunger and shelter, safety needs that encompass security and protection from harm, social needs for affection and belongingness, esteem needs that involve self-respect and recognition, and ultimately, self-actualization, which is the drive to realize one's full potential and achieve personal growth.

As each of these needs becomes substantially satisfied, the next becomes dominant

Maslow categorized human needs into two groups: lower-order needs, which include physiological and safety needs, and higher-order needs, encompassing social, esteem, and self-actualization needs.

Emphasis on growth or higher order needs of A Maslow social needs (affection, self-respect, ect.) and self-actualization needs (growth, achieving one’s potential, self- fulfillment ect.)

The distinction between higher-order and lower-order needs lies in their sources of satisfaction; higher-order needs are fulfilled internally within an individual, while lower-order needs are primarily met through external factors such as salary, union agreements, and job security.

Hypothesis development

With reference to the above mentioned literature review, hypothesis for this study is developed as below:

2.5.1 Hypothesis for the relation of Perceived organizational support (POS) – Job engagement (JE)

According to Edmondson (1999), employees who perceive high levels of organizational support tend to have positive expectations regarding the organization's response to their contributions and mistakes This perception reduces their fear of negative consequences for their self-image, status, or career, encouraging them to invest fully in their work roles Consequently, employees with greater organizational support are more likely to engage physically, cognitively, and emotionally with their organizations Thus, the hypothesis regarding the relationship between perceived organizational support and employee engagement can be articulated as follows:

1 Hypothesis 1A: Perceived organizational support is positively related to Physical engagement

2 Hypothesis 1B: Perceived organizational support is positively related to cognitive engagement

3 Hypothesis 1C: Perceived organizational support is positively related to Emotional engagement

2.5.2 Hypothesis for the relation of Perceived organizational support (POS) - Job Performance (JP)

Following Eisenberger, Huntington, Hutchinson, & Sowa, 1986; Rhoades &

Eisenberger highlights that employees develop a general perception of how much their organization values their contributions and cares for their well-being, which is essential for fulfilling socioemotional needs and evaluating the benefits of increased work effort.

Perceived Organizational Support (POS) enhances both in-role and extra-role job performance while reducing unexpected employee behaviors This support fosters a sense of obligation among employees to contribute to the organization's goals Therefore, the hypothesis posits a positive relationship between POS and job performance, suggesting that increased engagement in POS leads to improved employee performance outcomes.

4 Hypothesis 1D: Perceived organizational support is positively related to Job Performance

2.5.3 Hypothesis for the relation of Job Engagement (JE) - Job Performance (JP)

According to Kahn (1990), "personal engagement" involves the alignment of an individual's self with their work roles, characterized by the simultaneous investment of cognitive, emotional, and physical energies This comprehensive involvement leads to enhanced job performance, as employees are fully engaged in their tasks Therefore, the hypothesis posits a positive relationship between job engagement and job performance.

5 Hypothesis 2A: Physical engagement is positively relate to Job Performance

6 Hypothesis 2B: Cognitive engagement is positively relate to Job Performance

7 Hypothesis 2C: Emotional engagement is positively relate to Job Performance

2.5.4 Hypothesis for the mediation role of Job engagement (JE)

Perceived Organizational Support (POS) enhances employees' affective commitment and performance through a reciprocal process, as highlighted by Eisenberger et al (2001) Building on Kahn's theories from 1990 and 1992, engagement involves investing physical, emotional, and cognitive energy into work tasks Consequently, engagement serves as a mediator in the relationship between POS and job performance, supporting the hypothesis that increased engagement positively influences performance outcomes.

8 Hypothesis 3A: Physical engagement positively meditates the relationship between Perceived organizational support and Job Performance

9 Hypothesis 3B: Cognitive engagement positively meditates the relationship between Perceived organizational support and Job Performance

10 Hypothesis 3C: Emotional engagement positively meditates the relationship between Perceived organizational support and Job Performance

All the above hypothesis are summarized in the following model

Picture 1 Research model and hypothesis

The Impact of Perceived Organizational Support on Job Performance, the Mediation of Job Engagement-

- A study of Commercial Banks in Viet Nam

This chapter outlines the theoretical framework for the research, discussing relevant theories, previous studies, hypothesis formulation, and the proposed research model To determine the validity of the hypotheses and the applicability of the proposed research model within the context of Vietnam's commercial banking sector, the research methodology will be detailed in Chapter 3.

RESEARCH METHODOLOGY

Research design

3.1.1 The approach to research in this study is quantative research

Quantitative research aims to identify the relationship between an independent variable and a dependent variable within a population This research can be categorized into two main designs: descriptive studies, where subjects are typically measured once to establish associations between variables, and experimental studies, where subjects are measured before and after a treatment to determine causality.

To accurately estimate the relationship between variables in our descriptive study, we require a sample of 200 subjects We utilize effect statistics, including correlations, relative frequencies, and differences between means, to express these relationships effectively.

3.1.2 The quantative methology is a cross-sectional survey:

Quantitative research aims to explore the relationship between an independent variable and a dependent variable within a specific population This research can be categorized into two designs: descriptive, where subjects are measured once to identify associations, and experimental, where subjects are measured before and after a treatment to establish causality.

Cross-sectional studies, also referred to as cross-sectional analyses or transversal studies, are research methods that observe an entire population or a representative subset at a specific point in time These descriptive studies are valuable for describing various statistical measures, including Odds ratios, absolute risks, and relative risks based on prevalence, often termed prevalence risk ratio (PRR) (Carsten Oliver Schmidt, Thomas Kohlmann, 2008; James Lee, 1994).

Cross-sectional surveys are effective tools for collecting data on a population at a specific moment in time For instance, a survey conducted in March 1999 could assess parents' opinions on Internet filtering Additionally, these surveys can explore relationships between variables, such as the correlation between parental religiousness and their views on Internet filtering (Babbie, Earl).

R Survey Research Methods Belmont, CA: Wadsworth Pub Co., 1973.)

This study employs a quantitative research methodology through a cross-sectional survey, which effectively gathers information on various variables across different contexts By assessing the relationships between these variables in a sample of subjects at a single point in time, the research aims to identify differences among selected banks and groups of people The focus is on commercial banks in Vietnam, spanning regions from the North to the South.

After survey data is conducted, statistical test is conducted to find out correlation between variables This step is mentioned in the data analysis step.

Questionnaire development

Data collection relies on questions as vehicle for extracting the primary research data

(William B Werther, Jr., Ph.D and Keith Davis, 1996), thus, questionnaires in this study are developed with respect to the general rules for questionnaire designing as follows:

The questionnaire development is the key step to set up measuring scale for the study

In this study, questionnaire, scales development is designed based on antecedent researches of:

+ Bruce Louis Rich (California State University SanMarcos) and Jeffrey A Lepine, Eean R Crawford (University of California) (2010)

+ Robert Eisenberger, Stephen Armeli, Barbara Rexwinkel, Patrick D Lynch, and Linda Rhoadesm, (University of Delaware) (2001)

In this study, two mini group discussions were held, featuring four banking experts, including two branch directors and two managers from Sacombank, Saigonbank, Agribank, and VinaSiam Bank The discussions aimed to evaluate the clarity of the survey instrument and ensure that all questions were clear and comprehensive in addressing the research topic from a banking professional's perspective Amendments were made based on the feedback provided by the bank managers.

A discussion involving four banking professionals from HR and management at commercial banks, including Sacombank, Saigonbank, Agribank, and VinaSiam Bank, was conducted to gather insights from the staff's perspective This session aimed to align with the objectives of the initial discussion, focusing on the current state of the banking sector in Vietnam and the local working environment and practices.

Based on participant feedback, certain questions in the questionnaire were revised to use clearer and more positive language Additionally, only relevant official questions were included in the study, while extraneous questions were removed to enhance focus and clarity.

Final questionnaire check was implemented with a group of HR staff working in banks

As mentioned in this study, the study model consists of 5 constructs including: The

Perceived organizational support (POS) plays a crucial role in enhancing job engagement and performance within an organization The POS scale includes six items, one of which highlights that "the Bank takes pride in my accomplishments." This recognition fosters a positive work environment, leading to increased employee engagement and improved job performance Understanding the relationship between perceived organizational support and these constructs is essential for optimizing workplace dynamics and achieving organizational goals.

The Bank genuinely prioritizes my well-being and demonstrates a strong commitment to understanding my goals and values Their high level of concern for my individual needs reinforces their dedication to providing personalized support.

POS 6 The Bank is willing to help me if I need a special favor ii The Physical engagement scale consists of 5 items as follows

PE 1 I work with intensity of my job

PE 2 I exert my full effort to my job

PE 3 I devote a lot of my energy to my job

PE 4 I try my hardest to perform well on my job

PE 5 I try as hard as I can to competes my job iii The Emotional engagement scale consists of 6 items as follows EE.1 I am enthusiastic in my job

I am energetic, interested, and proud of my job, which makes me feel positive and excited about my work Additionally, I maintain a strong cognitive engagement, as my mind is consistently focused on my tasks.

CE.2 At work, I focus a great deal of attention on my job

CE.3 At work, I am absorbed my job CE.4 At work, I concentrate on my job v The Job performance scale consists of 4 items as follows

JP 1 I meet formal performance requirements of the job

JP 2 I fulfill responsibilities specified in job description

JP 3 I perform tasks that are expected to me

JP 4 I adequately complete assigned duties.

Translation of the questionnaires

The initial draft of the questionnaire was created in English and subsequently translated into Vietnamese This translation process included references to prior research on POS and job performance, incorporating mediators relevant to the Vietnamese market, to enhance the reliability and agreement of the questionnaire items.

The questionnaire has been translated into Vietnamese to ensure that all respondents, who are Vietnamese, fully understand its contents This translation guarantees that the information conveyed in the questionnaires is accurately communicated to the participants.

The final version of questionnaire was made in Vietnamese (Appendix 1) and then was translated back into English (Observed variables)

- Questionnaires reference from previous researches

- Self transudation from English to Vietnamese

- Getting translation check from the official translator

- Translation from Vietnamese to English for checking

- Final version of questionnaire made in Vietnamese

Variable control

Self-rating data necessitates careful control of potential biases, as outlined by Bommer, Dierdoff, and Rubin (2007) Bias can significantly impact research by influencing subject selection, skewing the researcher's interpretation of data, and leading to the exclusion of data that contradicts the research hypothesis.

This study's variables were developed from prior research, expert consultations, and insights from HR and banking management professionals The final analysis focuses on quantitative variables categorized as independent, dependent, and mediation factors, specifically: 1 Perceived organizational support and 2 Job performance The relationships between these variables are assessed using three mediation variables, including 3 Physical engagement.

To ensure accurate estimates of relationships between variables, it is essential to select a representative and unbiased sample from the population High participation rates in randomly selected samples help minimize bias in the estimates This study utilized appropriate measurement scales, specifically a pool of 35 candidate scale items, employing a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) to accurately reflect the relationships being examined.

In this study, as an indispensable tool for potential biasing control and for data analysis, reliability statistics by Cronbach’s Alpha (Hair et al, 1998, Segar, 1997) is applied to test

A pilot experiment, or pilot study, is a preliminary small-scale research effort aimed at assessing feasibility, time, costs, adverse events, and effect size This initial study helps predict the necessary sample size and refine the study design before embarking on a full-scale research project.

A pilot study is typically conducted with individuals from the relevant population, excluding those who will be included in the final sample This approach helps to prevent any potential influence on the behavior of research subjects, ensuring that their responses remain unaffected by prior involvement in the study (Haralambos and Holborn 2000, p.998).

Pilot studies applied based on quantitative and qualitative methods, starting with

"qualitative data collection and analysis on a relatively unexplored topic, using the results to design a subsequent quantitative phase of the study" (Tashakkori & Teddlie

The initial phase of a pilot study includes conducting in-depth interviews or focus groups to identify key issues for a larger questionnaire survey Following this, the questionnaire undergoes a pilot test to refine aspects such as question wording, order, and response options for multiple-choice questions A final pilot is then performed to evaluate the overall research process, including various methods of distributing and collecting the questionnaires.

Pilot study also aims to identify potential practical problems and improve the internal validity of a questionnaire

This study employs a pilot questionnaire tested on a small group of experts in HR Management and Banking Management, closely resembling the target population HR Directors and Bank Managers are selected for the pilot study, as their diverse perspectives and insights can enrich the findings.

We are conducting a pilot study involving Vinasiam Bank, where I have worked for over a decade, along with Sacombank, Saigonbank, and Agribank Our primary contacts for this study will be the HR managers and senior HR staff at each bank The pilot study will be executed individually at each bank and with each contact, and the results will be compiled for final analysis and selection.

Target population

The target population is the population of individuals which we are interested in describing and making statistical inferences about (Johan Hedal, Susie Jentoft 2011)

The target population refers to the complete group we aim to study and draw conclusions from In the context of a survey, it encompasses all units for which the collected data will be utilized to make inferences (Cox and Cohen).

In survey design, the first step is to establish clear study objectives, followed by the definition of the target population, which comprises the specific units to which the survey findings will be generalized.

Details of target population of this study:

- Geographical area: Ha Noi Capital, Da Nang City, Dong Nai Province, Binh Duong Province Ho Chi Minh City

- Education: College / vocational degree, university degree and higher levels

- Position: staff, experts, senior staff, Deputy Directors, Managers, Deputy managers

- Eligibility: functional employees, mangers who are working for Sacombank, Saigonbank, Agribank, Vinasiam bank.

Sample size

This study investigates the influence of perceived organizational support on job performance, focusing on the mediation role of job engagement within commercial banks in Vietnam Utilizing quantitative research methods, the research involved a questionnaire survey to directly interview participants from a defined sample size.

200 person who are working in commercial banks in Viet Nam

A quality sample must ensure both accuracy and precision, as highlighted by Donald & Pamela (2003) It should exhibit minimal systematic bias in variance while keeping the sampling error within acceptable limits tailored to the objectives of the study.

Determining the appropriate sample size to accurately represent a population remains a debated topic in the literature Various formulas exist for calculating sample size, yet their application can be complex The ideal sample size is influenced by the desired precision and confidence level in estimating population parameters, along with the inherent variability within the population (Canava et al., 2001).

The study aimed for a sample size of 200, based on prior research, such as Tho & Trang (2008) and Trong & Ngoc (2005) To achieve this, 300 self-administered questionnaires were distributed by bank employees, resulting in 250 returns Ultimately, 50 questionnaires were deemed usable, leading to an effective response rate of 47.2%.

Selecting the sample and collecting data

Sampling involves selecting a subset of elements from a population to make inferences about the whole group Key factors to consider when determining the scope and methodology of sampling include cost, result accuracy, data collection speed, and the availability of population elements (Donald & Pamela, 2003).

The first step in sampling is that the population should be correctly defined A population is the total collection of elements from which we wish to draw some conclusion

After identifying the population, researchers will choose an appropriate sampling available Two most common sampling techniques are probability sampling and non- probability sampling

Steps of sample selection: Define target population > Construct sampling frame >

Determine how to select sample members > decide how to covert sample estimates into population estimates

This study focuses on employees of commercial banks in Vietnam, acknowledging the challenge of identifying the entire customer population or creating a comprehensive sampling frame Due to constraints in time, budget, and expertise, the research employs a non-probability sampling method, specifically convenience sampling.

This study employs a non-probability sampling method, which, while being the least reliable, is the most cost-effective and practical for the research The sample consists of 200 individuals, specifically HR managers and banking employees from the head office and branches of Sacombank, VinaSiam Bank, and Agribank.

Interviewers can interview any staff who agrees to take part in the interview

Choosing a suitable and satisfactory sample is crucial for controlling variables and minimizing measurement errors that could distort study results It is essential to ensure that the sample is unbiased and representative of the broader population A higher participation rate in a randomly selected sample significantly reduces the likelihood of bias in estimating relationships To maintain this integrity, sample selection in this study adhered to specific principles aimed at preventing bias.

- Selection bias: Avoiding this bias by ensuring that select samples can present for the population of the study

- Confounding: subjects of the study are separated into different group to ensure no confounding

- Information bias: Scale applied for different group must be utility

Data for this study was gathered using a survey technique, which offers a quick, efficient, and accurate method for assessing information about a population, particularly when secondary data is unavailable (Zikmund, 1997).

After having decides sample, we apply both ways face- to- face interviews and sending questionnaires (mainly) to collect data.

Methods of data analysis

After collecting having data, data were screened, variables were encoded and input for further processing

With a sample size of N = 200, if Skewness and kurtosis of measured variables distributed in the interval (-2, +2) the data can be considered to meet the suggested cut- off for normal distribution

In statistics, reliability is the consistency of a measure A measure is said to have a high reliability if it produces consistent results under consistent conditions

+ Reliability Statistics by Cronbach’s Alpha (Hair et al, 1998, Segar, 1997)

Cronbach's (Alpha 1951) is a coefficient of reliability It is commonly used as a measure of the internal consistency or reliability of a psychometric test score for a sample of examinees

This study examines the impact of Perceived Organizational Support on Job Performance, specifically through the mediation of Job Engagement To achieve this, we adapted the measurement scale developed by Bruce Louis Rich (2010) and Robert Eisenberger et al (2001), making necessary adjustments after discussions with bank experts and staff to ensure relevance to the context of commercial banks in Vietnam and local cultural considerations.

3.9.4 Confirmatory factor analysis (CFA) & Structural equation modeling (SEM)

Confirmatory factor analysis (CFA) is performed using Amos 16 to evaluate the measurement instrument Once the measurement model demonstrates a good fit with the sample data, researchers can confidently assess the findings related to the proposed structural model (Byrne, 2001).

Structural Equation Modeling (SEM) is a versatile and intricate technique for analyzing causal relationships by integrating statistical data with qualitative causal assumptions Its application spans various fields, notably management, as demonstrated by Tharenou, Latimer, and Conroy (1994).

The necessity of applying Structural Equation Modeling (SEM) in research lies in its ability to integrate various techniques, including multi-variable regression and reciprocal relationship analysis, enabling the estimation of complex relationships within a model SEM, also referred to as analysis of covariance structures or causal modeling, combines factor analysis with multiple regressions In SEM, variables are categorized as measured (observed) variables, known as indicators, and factors, which are latent variables SEM is divided into two components: the measurement model, which connects measured variables to latent variables, and the structural model, which establishes relationships among latent variables.

Structural Equation Modeling (SEM) distinguishes itself from traditional statistical techniques by enabling the simultaneous estimation of relationships among all factors within a comprehensive model It facilitates the assessment of causal relationships among latent constructs through the application of goodness-of-fit (GOF) indices for both measurement and structural models Additionally, SEM is capable of measuring both recursive and non-recursive relationships, as well as direct and indirect relationships, including error and disturbance factors.

Using Confirmatory Factor Analysis (CFA), the Structural Equation Modeling (SEM) approach allows for the flexible identification of the most suitable model from various proposals The robust and sophisticated features of SEM make it an ideal choice for our research, particularly when exploring intricate relationships among factors and mediators.

This study evaluates the model's relevance and fit by analyzing various goodness-of-fit (GOF) indices, including the P value.

The P value, linked to a test statistic, represents the probability of observing that statistic; a smaller P value indicates a stronger rejection of the null hypothesis, with values of 05 or less signifying a significant relationship Additionally, the Chi-Squared (χ2) statistic serves as a key measure for assessing differences between observed and estimated covariance matrices, functioning as a function of sample size and the disparity between the observed and model covariance matrices.

CMIN/ df (χ2/df): Chi-square adjusted following degree of freedom

The degree of freedom (df) indicates the mathematical capacity available for estimating model parameters The chi-square (χ2) statistic reflects the overall model's significance at a 0.05 level (Joserkog & Sorbom, 1989), but it is sensitive to large sample sizes and test strength Therefore, the ratio χ2/df is preferred for assessing model adequacy Some researchers suggest that a ratio of 1 < χ2/df < 3 is acceptable (Hair et al., 1998), while others advocate for minimizing χ2 (Segar & Grover, 1993), with a recommended threshold of χ2/df < 3:1 (Chin &).

In empirical studies, models are evaluated for fit based on the chi-square to degrees of freedom ratio (χ2/df), with a threshold of less than 5 for sample sizes greater than 200 and less than 3 for smaller sample sizes (Kettinger and Lee, 1995) Additionally, the Comparative Fit Index (CFI) is utilized to assess model adequacy.

The Comparative Fit Index (CFI) is an enhanced version of the normed fit index (NPI) that evaluates model fit by comparing relevant indicators It heavily relies on the average size of correlations within the data; if these correlations are low, the CFI value will also be low A CFI score of 90 or above is considered optimal for indicating good model fit Additionally, the Tucker-Lewis Index (TLI), also known as the Non-normed Fit Index (NNFI), serves as another important metric for assessing model adequacy.

The TLI, which predates the CFI, is conceptually similar as it involves a mathematical comparison between a specified theoretical measurement model and a baseline null model A model that demonstrates a good fit utilizes the Goodness-of-Fit Index (GFI), which aims to generate a fit statistic that is less sensitive to sample size GFI values range from 0 to 1, with higher values indicating a better fit.

Indices: CFI, TLI, CFI, having value> 0.9, is taken to indicate good fit If these values are at 1, we say the model is perfect (Segar,Grover, 1993) & (Chin & Todd,

1995) ã Root Mean Square Error of Approximation (RMSEA)

The RMSEA (Root Mean Square Error of Approximation) addresses the tendency of the chi-squared goodness-of-fit (GOF) test to reject models with large samples or numerous observed variables It evaluates how well a model represents a population rather than just the sample used for estimation By incorporating model complexity and sample size into its calculations, RMSEA provides a more accurate fit assessment, with lower values indicating a better model fit.

The Root Mean Square Error of Approximation (RMSEA) is a crucial index for assessing the relevance of a model in relation to the population In Information Systems research journals, a model is deemed a good fit if RMSEA and RMR values are below 0.05; however, values under 0.08 may still be acceptable (Taylor, Sharland, Cronin, and Bullard, 1993) Additionally, Modification Indices (MI) play a significant role in model evaluation.

The CFA test results utilizing AMOS are conducted following principles that adjust relationships with a Modification Index (MI) greater than 4, which serves as an adjustment coefficient for the change in chi-square (χ²) per degree of freedom.

MI suggests remedies to discrepancies between the proposed and estimated model

RESULT OF DATA ANALYSIS

Descriptive statistics

In a study involving staff from commercial banks in Vietnam, 210 self-administered surveys were distributed, resulting in 203 responses However, three questionnaires were discarded due to incomplete answers or identical scoring Ultimately, the final sample comprised 200 valid questionnaires, with 55% from Vinasiam Bank, 11% from Sacombank, and 11% from Vietcombank.

- Education: classified levels: College/vocational degree, university degree and higher levels

- Position: classified levels: staff, expert/senior staff, Deputy Director/Manager, Deputy Manager

- Work seniority from 1 to 37 years

- Research market: Commercial banks in Ha Noi, Ho Chi Minh City, and provinces of Viet Nam

Table 1 Descriptive statistic of Sample characteristics

Gender * Last position * Ages recoded 200 100.0% 0 0% 200 100.0%

Gender * Education * Ages recoded Crosstabulation

Master or higher levels Total

Gender * Last position * Ages recoded Crosstabulation

Deputy director, Manager, Deputy manager Total

Picture 2 Descriptive statistic of Sample characteristics

Normal Distribution Examining

This study analyzed data from a sample size of N = 200 using a 7-point Likert scale The results indicated that the measurable variables exhibited a normal distribution, as evidenced by skewness and kurtosis values falling within the interval of [-2, +2], aligning with the established cut-off criteria for normality.

The analysis using a 7-point Likert scale reveals minimal variation in the average values of measured variables within the same latent variable Notably, employees express dissatisfaction with Perceived Organizational Support, reflected in a low mean score of 4.58 to 5.04 In contrast, both Physical Engagement and Job Performance demonstrate higher satisfaction levels, with mean scores ranging from 5.82 to 6.12 and 5.94 to 6.06, respectively.

Table 2 Normal distribution of measured variables

Valid Missing Mean Median Mode Skewness Kurtosis

(Please see the histograms of normal distribution of measured variables in the attached Appendix No 1)

Reliability

Table 3 Reliability Statistics by Cronbach’s Alpha (Scales : POS, PE, EE, CE,JP)

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

As seen in above tables, all items satisfy with:

-Corrected Item-Total Correlation : >0 4 (Hệ số tương quan biến tổng) -Cronbach's Alpha if Item Deleted : < Cronbach's Alpha

Therefore, it is suggested that scales are reliable

Concept No of observed variable

The constructs in the table exhibit reliability coefficients ranging from 0.918 to 0.929, surpassing the recommended threshold of 0.7 established by Hair et al (1998) This confirms that the scale demonstrates a high level of reliability.

Confirmatory factor analysis (CFA)

i Unidimensionality validity (Tính đơn hướng/ đơn nguyê n)

Extraction Method: Principal Component Analysis

In this study, component extracted for each factor is at 1, this explain the evidence of Unidimensionality validity

(Please see detail in Appendix No 4) ii Convergent validity (Giá trị hội tụ)

The construct reliability and average variance extracted for each construct is shown in the following table:

Constructs No of observed variable

The results presented in Appendix No 5 and Appendix No 6 demonstrate strong convergent validity for the model All item loadings exceed 0.5, with significant t-values and p-values below 0.05 for each indicator Additionally, the construct reliability is greater than 0.7, and the average variances extracted range from 0.590 to 0.828, surpassing the minimum criterion of 0.5 These findings confirm the measurement model's evidence of convergent validity, as supported by Bagozzi and Yi (1988).

(Please see details in Appendix No 5, and Appendix No 6) iii Discriminant validity (Giá trị phân biệt) Using Excel to conduct if the correlation coefficient is different from 1

Correlations: (Group number 1 - Default model) n 0

SE= CR= r SQRT((1-r2)/(n-2)) (1-r)/SE P-value

Result of Discriminant validity evaluation: Correlation coefficients between concepts all JP is 0.38

Standardized regression weight of POS -> JP is 0.64

- The difference of standardized regression weights 0.64 against 0.38 indicates that Job engagement plays an important mediation role to improve relation of POS -

>JB, and this result supports our expected model

Table 10 Summary of Standardized regression weights of SEM with and without mediation factors

The model fit test results, conducted through Confirmatory Factor Analysis (CFA) using AMOS, indicate a good fit Key absolute fit measures, including Chi-square, Chi-square/df, Goodness of Fit Index (GFI), and Root Mean Square Error of Approximation (RMSEA), alongside incremental fit indices like Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI), were utilized to assess and adjust the model These adjustments are grounded in both theoretical and practical implications.

After the adjustment, CFA results showed that the indicators evaluating theoretical structural model are significantly improved and appropriate to market data i For Measurement model

Before improvement: P=.000; χ2/df $2; GFI=.745; TLI=.862; CFI=.897; RMSEA = 108

After improvement: P=.000; χ2/df =2.102; GFI=.889; TLI=.950; CFI=.961; RMSEA = 074

* Components extracted for each construct (factor) in measurement model test:

- Construct POS : POS2, POS3, POS6

- Construct PE : PE1, PE2, PE4, PE5

- Construct CE : CE1, CE2, CE4

- Construct EE : EE3, EE4, EE6

- Construct JP : JP1, JP2, JP4 ii For structural model

P=.000, χ2/df =2.556; GFI=.868; TLI=.930; CFI=.944; RMSEA = 0881

*Constructs extracted in structural equation model test: POS, PE, CE, EE, JP

The standardized estimates and fit indices indicate that all indices meet or closely approach the required cut-off values for model fit, with P-values less than 0.05 and GFI, TLI, and CFI values equal to or greater than 0.9, while CMIN/df is less than or equal to 2 and RMSEA is less than or equal to 0.08.

This chapter presents the analysis results and findings of the study, encompassing descriptive statistics, normal distribution assessments, reliability evaluations, confirmatory factor analysis (CFA), structural equation modeling (SEM), and a summary of model testing The results outlined in this chapter serve as the foundation for the subsequent chapter, which will provide conclusions and recommendations.

CONCLUSIONS AND RECOMMENDATIONS

Summary of all hypotheses

Finally, all hypotheses from the research model were significantly supported and final result of hypotheses test is summarized as below:

The Impact of Perceived Organizational Support on Job Performance, the Mediation of Job Engagement -

- A study of Commercial Banks in Viet Nam

The research model has 96 degree of freedom, χ 2 /df =2.556; GFI=.868; TLI=.930;

The final structural equation model (SEM) reveals statistically significant relationships among constructs, with p-values less than 5% Notably, the relationship between perceived organizational support (POS) and job behavior (JB) approaches zero, indicating mediation effects from factors such as personal engagement (PE), employee engagement (EE), and employee commitment (EC).

As the results, the measurement scales of concepts of the research model, the study model are significantly satisfactory theoretical implication, consistent with market data; and all hypotheses are accepted

Summary of hypotheses and structural equation analysis results

1 Hypothesis 1A: Perceived organizational support is positively related to Physical engagement Strongly supported

2 Hypothesis 1B: Perceived organizational support is positively related to cognitive engagement Strongly supported

3 Hypothesis 1C: Perceived organizational support is positively related to Emotional engagement Strongly supported

4 Hypothesis 1D: Perceived organizational support is positively related to Job performance Not supported

5 Hypothesis 2A: Physical engagement is positively relate to Job performance Supported

6 Hypothesis 2B: Cognitive engagement is positively relate to Job performance Supported

7 Hypothesis 2C: Emotional engagement is positively relate to Job performance Supported

8 Hypothesis 3A: Physical engagement positively meditates the relationship between Perceived organizational support and Job performance

9 Hypothesis 3B: Cognitive engagement positively meditates the relationship between Perceived organizational support and Job performance

10 Hypothesis 3C: Emotional engagement positively meditates the relationship between Perceived organizational support and Job performance Supported

Conclusions and implications

The analysis and findings in Chapter 4 confirm that the research questions of this study have been positively addressed This indicates that the proposed model is applicable to commercial banks in Vietnam, with minor adjustments needed to align it with the local environment.

5.2.1 Practical significant of this thesis

Through a survey of relationship of “Perceived organizational support and job performance” in commercial banks in Vietnam, this study provides the following specific Practical significant:

- Expressly answering questions of the study as mentioned at the content 1.3 of this study:

* There is the common relationship between perceived organizational support and job performance in commercial banks in Viet Nam

To enhance the impact of perceived organizational support on job performance in commercial banks in Vietnam, it is crucial to identify and focus on key factors such as effective communication, employee recognition, and supportive leadership By fostering a positive work environment and encouraging professional development, banks can strengthen employee engagement and motivation Additionally, implementing regular feedback mechanisms can further improve relationships between management and staff, ultimately leading to increased productivity and job satisfaction Prioritizing these factors will significantly contribute to the overall success of commercial banks in Vietnam.

Enhancing the relationship between perceived organizational support and job performance can significantly foster competitive advantage and improve performance outcomes for commercial banks in Vietnam.

- Providing better understands and improvement:

* Where employees perceive banks is delivering value to them and where it's not

* Employees' perceptions of their banks, leadership, working environment, climate and culture

* The drivers of employees' perception, engagement and performance

* Specific actions and initiatives that is likely to have the most powerful impact on improving relationship between perceived organizational support and job performance

* Banks’ responsiveness to the concerns and issues that matter most to banks’ workforce

This study highlights effective strategies to enhance the relationship between perceived organizational support and job performance in Vietnamese banks, providing leaders with a clearer understanding of how HR management impacts business outcomes By emphasizing the importance of investing in human resource management systems, the research encourages bank leaders to recognize the necessity of such investments As a result, banks can attract and retain qualified talent, ultimately leading to improved staff performance and overall business results.

This study investigates the factors that enhance the relationship between perceived organizational support and job performance in Vietnamese banks The findings provide valuable insights into how these factors positively influence employee performance, contributing to the overall effectiveness of banking institutions in Vietnam.

Adjustment of measure-scale of factors positively improving relationship between perceived organizational support and job performance in commercial banks in Viet Nam

This article presents a model tailored for human resource management in commercial banks in Vietnam, serving as a foundational framework for future research on specialized HR management practices within the country's banking sector.

Indication that employees' perception of the organization's commitment to them (POS) contributes to organizational objectives through Job performance

The findings indicate a positive correlation between POS (Perceived Organizational Support) and job engagement, which encompasses physical, cognitive, and emotional involvement This engagement fosters a commitment to the organization's welfare and motivates individuals to act in its best interest Additionally, heightened job engagement is linked to improved job performance, particularly in enhancing affective job outcomes.

The findings suggest that job engagement serves as a mediating factor in the relationship between perceived organizational support (POS) and job performance, highlighting its importance in enhancing the connection between POS and job performance through its key components.

The findings indicate a positive relationship between Perceived Organizational Support (POS) and affective job engagement Notably, job engagement serves as a mediator in the relationship between POS and job performance, further enhancing the positive connection between POS and overall job performance.

The findings support social exchange interpretations of employee-employer relationships that emphasize reciprocity-based obligations

To enhance HR management, banks should focus on elements that positively influence the connection between perceived organizational support and job performance It is recommended that banks develop effective HR management strategies that strengthen this relationship, particularly by considering the role of engagement as a mediating factor.

Specific measures, manipulating practical and effective solutions in terms of improving relationship between perceived organizational support and job performance in banks are proposed as follows:

For priority of proposal: To improve relation between POS and job performance, physical engagement, cognitive engagement and emotion engagement should be paid attention on priority order respectfully

For specific solutions: Banks should develop good, appropriate policies and create good working environment in related to the improvement of:

- Really caring about employee’s well-being, valuing their contribution to its well- being, willing to help them if they need a special favor

- Motivating employee to working with intensity of their job; encouraging employee to exert their full effort to their job; try their hardest to perform well on job

- Emotional, feeling of employee to be energic at their job interested in and excited about their job

- Cognizance of employee on focusing, concentrating in their job, long staying with banks

The proposed policies address key areas of employee satisfaction and dissatisfaction, focusing on hygiene issues such as compensation, salary, benefits, welfare, appraisal, incentives, gain-sharing, and safety policies Additionally, motivator issues are emphasized, including training, career development, and fostering positive employer-employee relations, along with support from employee counselors to enhance overall workplace satisfaction.

These proposed policies should be deliberately studied and manipulated suitably for each specific case and context in HR management at banks.

Limitations and recommendations

This research focuses on the relationship between perceived organizational support (POS), job engagement, and job performance, specifically examining in-task performance However, it does not explore other potential relationships, such as the connection between POS and felt obligation or POS and positive mood in relation to job performance These limitations arise from the scope of the study.

* The complexity of the research (limit of time, finance, local culture, support of relevant organizations)

* Specific context of Viet Nam which is not convenience to conduct multi-factor researches by students

The study's findings may be limited in representativeness due to a sample size predominantly drawn from local commercial banks, suggesting a need for caution in generalizing results across the banking sector Additionally, certain variables were excluded during the model testing, potentially influenced by the unique context of Vietnam compared to previous research countries and the restricted sample size of 200 respondents Future research should aim to include a larger and more diverse sample of banks to enhance the validity of the findings.

This chapter concludes that the research questions have been positively answered, demonstrating that the proposed model is applicable to commercial banks in Vietnam It outlines solutions to enhance the relationship between Perceived Organizational Support (POS) and Job Performance (JB), highlighting the mediating roles of Physical, Cognitive, and Emotional Engagement in this relationship The findings offer significant practical and theoretical implications that benefit both employers and employees within the banking sector through effective HR management.

This chapter also reports limitations and recommendations which is necessary for further research

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APPENDIX No 1 HISTOGRAMS OF NORMAL DISTRIBUTION

Total 200 100.0 a Listwise deletion based on all variables in the procedure

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Mean Variance Std Deviation N of Items

Total 200 100.0 a Listwise deletion based on all variables in the procedure

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Mean Variance Std Deviation N of Items

Total 200 100.0 a Listwise deletion based on all variables in the procedure

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Mean Variance Std Deviation N of Items

Total 200 100.0 a Listwise deletion based on all variables in the procedure

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Mean Variance Std Deviation N of Items

Total 200 100.0 a Listwise deletion based on all variables in the procedure

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Mean Variance Std Deviation N of Items

(TÍNH ĐƠN HƯỚNG/ ĐƠN NGUYÊN)

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .884

Extraction Method: Principal Component Analysis

Initial Eigenvalues Extraction Sums of Squared Loadings Compone nt

Cumulativ e % Total % of Variance Cumulative %

Extraction Method: Principal Component Analysis

Principal Component Analysis a 1 components extracted

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .871

Extraction Method: Principal Component Analysis

Initial Eigenvalues Extraction Sums of Squared Loadings Component

% of Variance Cumulative % Total % of Variance Cumulative %

Initial Eigenvalues Extraction Sums of Squared Loadings Component

% of Variance Cumulative % Total % of Variance Cumulative %

Extraction Method: Principal Component Analysis

Principal Component Analysis a 1 components extracted

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .887

Extraction Method: Principal Component Analysis

Initial Eigenvalues Extraction Sums of Squared Loadings Component

% of Variance Cumulative % Total % of Variance

Extraction Method: Principal Component Analysis

Principal Component Analysis a 1 components extracted

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .853

Extraction Method: Principal Component Analysis

Initial Eigenvalues Extraction Sums of Squared Loadings Component

Extraction Method: Principal Component Analysis

Principal Component Analysis a 1 components extracted

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .829

Extraction Method: Principal Component Analysis

Initial Eigenvalues Extraction Sums of Squared Loadings Component

Extraction Method: Principal Component Analysis

Principal Component Analysis a 1 components extracted

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate JP.2 < - JP 887 JP.1 < - JP 838 JP.4 < - JP 888 JP.3 < - JP 821

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate POS.6 < - POS 843 POS.5 < - POS 878 POS.4 < - POS 871 POS.3 < - POS 805 POS.2 < - POS 752 POS.1 < - POS 736

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate PE.3 < - PE 809 PE.4 < - PE 864 PE.2 < - PE 881 PE.1 < - PE 774 PE.5 < - PE 866

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate EE.4 < - EE 896 EE.3 < - EE 886 EE.2 < - EE 686 EE.5 < - EE 884 EE.6 < - EE 895 EE.1 < - EE 676

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate CE.3 < - CE 808 CE.2 < - CE 868 CE.1 < - CE 856 CE.4 < - CE 909

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate JP.2 < - JP 887 JP.1 < - JP 838

APPENDIX No 5 CONVERGENT VALIDITY - CALCULATING CR and AVE

Lamda = Li: Standardized factor loading e i: measurement error = [1 – (standardized loading) 2 ]

POS - The Perceived organizational support Standardized Regression Weights: (Group number 1 - Default model)

Lamda Lamda^2 1-Lamda^2 (Total lamda)^2

PE - The Physical engagement Standardized Regression Weights: (Group number 2 - Default model)

Lamda Lamda^2 1-Lamda^2 (Total lamda)^2

EE - The Emotional engagement Standardized Regression Weights: (Group number 3 - Default model)

Lamda Lamda^2 1-Lamda^2 (Total lamda)^2

CE The Physical engagement & Cognitive engagement Standardized Regression Weights: (Group number 4 - Default model)

Lamda Lamda^2 1-Lamda^2 (Total lamda)^2

JP - The Job performance Standardized Regression Weights: (Group number 5 - Default model)

Lamda Lamda^2 1-Lamda^2 (Total lamda)^2

GOF INDICES (Joseph F Hair, Jr William C Black Barry J Babin, Rolph E Anderson

Multivaria teData Analysis, 7/e Copyright 2010 by Pearson Prentice Hall All rights reserved.)