Abstract

Self-determination and associated self-efficacy are broad theories of human motivations that have grown in importance in many domains of psychology, particularly organizational psychology, during the last four decades. This has been in development for more than four decades, with the original focus on internal motivation and its antecedents and implications. This rapidly led to a study of the relationships among motivational factors, as well as the classification of extrinsic motivation kinds in terms of autonomy. The objectives of the following research are: to evaluate the private organizations had a more effective partnership between organizations and employees that ensures better job performance, to discover that private organizations encouraged employees to work hard, to discover that employees with Bachelor's degrees had more self-determination and improved performance in an organization. The methodology adopted was Qualitative research with data collection of 300 employees belonging to 2 private and 2 public organizations in Lahore, Pakistan.

Key Words

Self-Efficacy, Self-Determination, Psychological Performance, Organizational Behaviour

Introduction

The research investigates the significance of fans' goals in bridge methods and transformational management. According to the study, the desire for competency fulfillment and the desire for genetic similarity fulfillment are the two conditions under which the connection between transforming management and employee fulfillment, self-efficacy, and self-determination to the leader is most effective. Studies differed in how transformative management and painting pleasure mediated each other (Hussain, 2019).

In order to investigate the connections between different PE match types and employee effective organizational behavior and overall performance, researchers incorporated literature on self-willpower principles and person-environment match (PE match). Different PE match categories correspond to different forms of mental wish fulfillment; also, person-organization behaviour match or needs-abilities match directly influenced employee affective devotion. Self-determination theory (SDT) is an important psychological notion of motivation that has gained traction in a number of fields, most notably organizational psychology. The goal of the research is to examine the social and motivational factors that influence views of transformational management and to provide a proposal based on the principles of self-determination and self-efficacy. The results demonstrate how improved administrative center linkages improve self-sustaining force and self-efficacy in control capacities, both of which are related to the management of character change (Irshad, 2007).

At portraits, flow is a transient state characterized by subjective Labor force, administrative center joy, and absorption that is intimately linked to several task performance metrics. Studies on going with the flow in the context of organizational behavior have mostly concentrated on situational factors, in addition to venture portrait requirements and resources. Based on self-determination theory, this article makes the case that staff members are capable of creating their own ideal narratives on their own. Four self-determination processes—self-efficacy, task creation, growing portraits to be enjoyable, and strengths utilization—allow employees to meet their basic desires, encourage them to follow the flow, and improve their work performance (Khetran, 2019 ).

The impact of extrinsic incentives on fulfillment motivation has been controversial, and scholars have called for further study on its boundary conditions. They contend that when staff members have a high level of creative self-efficacy and see these benefits as meaningful, extrinsic incentives for creativity have the greatest influence on their innovative overall psychological performance. Employees who have more expertise with the benefits of extrinsic incentives perform better in terms of innovation (Moran, 2012).

By combining disparate points of view into a single, cohesive framework, the contemporary approach offers creative and forward-thinking literature that aims to illustrate the benefits of higher levels of intrinsic motivation and shows how these benefits vary depending on character traits. The degree of intention to succeed, task effort, persistence, and high motivation are all motivated by self-efficacy, or the conviction in one's own capacity to complete a task (Zhang, 2016 )




Research Objectives

The purpose of the research on "Effects of Self-Determination and Self-Efficacious on Employee Psychological Performance and Organizational Behaviour" is to make inferences on the following goals: 

? To discover that among workers earning between $20,000 and $30,000, task completion was associated with higher performance levels. 

? To look at how one's emotional state affects one's capacity for work, particularly for men.

? To assess whether private firms' employee-organization partnerships are more successful in ensuring higher levels of job performance.

? To learn that hard effort was rewarded in private companies.

? It was shown that workers earning between $20,000 and $30,000 had superior learning capacities, which improved their psychological outcomes.

? To find out whether workers with bachelor's degrees performed better in a company and had higher levels of self-efficacy.

? To learn that workers in a company with bachelor's degrees perform better and have more self-determination.

? To ascertain that worker earning between $20,000 and $30,000 had a greater influence on their performance level.




Research Questions

The study's research questions are as follows: 

? Will workers earning between $20,000 and $30,000 per year perform better when tasked with fulfilling tasks?

? Will a person's emotional state affect their capacity to work, particularly for men?

? Is there a more successful collaboration between employers and workers in private businesses that guarantees improved job performance?

? Will for-profit businesses motivate staff to put in extra effort?

? Do workers making between $20,000 and $30,000 a year have greater learning capacities that improve their psychological well-being?

? Did workers with bachelor's degrees perform better in a company and have higher levels of self-efficacy?

? Will workers in a company who have bachelor's degrees be more independent and perform better?

? Will workers' performance levels be more affected by their salary between $20,000 and $30,000?




Characteristics of Self-Determination in Organizational Behaviour

The research looks at the behavioral and physiological mechanisms behind the uneven relationships between worker performance and portrait qualities (useful resources and needs for ventures). The self-dedication theory is investigated for a framework in which negative employee working expressions are positively correlated with emotional elements such as rage and infrequently excellent encouragement, while positive employee working expressions are positively correlated with process traits such as desire delight and increased portrait engagement (managed motivation). The findings of structural equation modeling (SEM) indicate that the relationship between process functions and worker psychological performance is somewhat mitigated by mental demands and portrait motivation (Yeo, 2013).

The notion of employees' process ardor is an appraisal-based theory that describes how people intensify process ardor. In order to grow and thrive in portraiture, individuals need to satisfy the three primary physiological social needs of relatedness, autonomy, and capacities and expertise, according to the self-dedication hypothesis. It has not been examined how important it is to meet fundamental mental needs in order to evaluate employee process excitement. The genuine portraits surround qualities (pictures cognitions), the vital mental wish fulfillment and the dreams associated with the portraits are all related to the employees' cognitive exams (Wang, 2012).

Literature Review

(Ali, A. 2015) According to the research, managers, firm executives, and human resource development (HRD) professionals should design interventions that support employees in meeting their basic mental health requirements and inspire specific work qualities. People and stakeholders could benefit from the organizational and private results that emerge from employees who are more involved in portraiture.

(Afridi, Khan, & Jamil, 2017) Employees with high self-determination and sometimes non-self-determination are seen to benefit most from job manipulation since it relieves strain. It could, however, increase pressure on those whose motivation is strongly shown by non-self-determination and their lack of self-determination

 (Cherian & Jacob, 2013). For those with low non-self-determination, high process manipulation exhibited the expected pressure-buffering impact on engagement, in line with a substantial three-manner interaction. Moreover, pressure increased when process control was lost. Contrary to expectations, high-process manipulation turned out to be just as helpful as low-process direct authority as a pressure relief mechanism for those who exhibit an extreme lack of self-determination

 (Gilbreath & Benson, 2004). According to the self-determination theory (SDT), there are many different motivators, and each has a different impact on a person's behavior and overall well-being. Numerous scoring schemes are often used to gauge these motives, even though there is substantial consensus about the characteristics of the many motivational categories.




Characteristics of Self-Efficacy in Organizational Behaviour 

Personal performance expectations have increased as a result of globalization, necessitating that people overcome obstacles and fulfill a broad variety of requirements. Since perceived self-efficacy affects motivation and performance in general, it is essential for people to achieve these expectations. Studies have shown that supervisors regard workers highly who exhibit high levels of perceived self-efficacy (SEP) (Abid & Ashfaq, 2015).

Self-efficacy may be used to assess job performance and how it affects motivation and overall performance, according to research on the subject among line managers, non-managerial workers, and students. To motivate staff and enhance their output, it's critical to ascertain the useful consequences of raising worker self-efficacy (Bakker, 2017).

The dynamic link between self-efficacy and overall performance has been the focus of recent research, highlighting the significance of internal planning and study of self-efficacy research. The research also discovered that the presence of both beneficial and detrimental impacts on performance may be explained by the efficient allocation of resources (Brown, 2005)

Students' comprehension of the intricate and dynamic mechanisms underlying self-efficacy has advanced significantly, motivating them to keep collaborating. Research on the validation of self-efficacy beliefs and the documenting of their roles within the social cognition notion of self-law has shown that goal-demanding conditions result in proactive discrepancy when they are followed, and reactive discrepancy when they are achieved. While it has been shown that delusional self-efficacy and goals improve motivation and overall performance, there is a substantial body of evidence that challenges these findings (Butt, 2015).

Though no research has looked at the link between moral climate, self-efficacy, and hope, previous studies have examined the connections between these ideas. The results serve as a roadmap for the organizational behavior version and provide a distinct viewpoint on how optimism and self-efficacy affect the moral climate (Cherian, 2013).

Factors that Affect Employee Psychology

The goal of the research was to investigate the variables that affect employee engagement in a developing nation. Work-function health and process enrichment were shown to have a substantial impact on employee engagement, while incentives, colleague relations, resources, management relations, and organizational direction were found to have fewer effects. Work-function health, process enrichment, and the availability of helpful resources promoted worker satisfaction via psychological accessibility, whereas the availability of useful resources and interactions among coworkers led to worker retention through feelings of mental meaningfulness (Gangloff, 2017).

Disparities in working circumstances, such as absenteeism and labor turnover, are thought to have an impact on collaboration, reputation and identification chances, and communication. A worker may feel angry and betrayed if they believe their employer has not fulfilled their mutual obligations. The mental settlement includes views on the worker's and their employer's reciprocal responsibilities. Research to inform future empirical research mentions neural feel-making techniques (Garrin, 2014 ).

Regression analysis was used to examine the effect of agency incentive travel on retention. According to the poll, retention strategies often prioritize aspects that might increase employment costs (such as career prospects and financial benefits) above those that can increase worker satisfaction (such as work-life balance, process attributes, and sociocultural environments). The interest in career options was reflected in the worker vote, and it was shown that offering career alternatives had the greatest effect on employee loyalty (Gilbreath*, 2004 ).

Control over human resources is essential to employee retention. Researchers discovered that absenteeism, worker retention, and improved first-class performance may be achieved with the support of human resource control techniques in compensation and incentives, process security, training and development, management heritage, work environment, and organizational devotion. Employers in the US, Europe, Asia, and Australia were usually the first to use worker retention strategies (Gist, 1992 ).




 

Table 1

Frequency Distribution of Gender

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Male	173	57.7	57.7	57.7
	Female	127	42.3	42.3	100.0
	Total	300	100.0	100.0

 




A frequency table is a compact format that is specialized in nature, and it shows a series of scores in either ascending or descending order. The frequencies are arranged from general acquired data. The frequency distribution by gender (male and female) is shown in the frequency table that follows. There were 173 more male participants out of the 300 total than there were female participants (127).

Figure 1

Bar Chart of Gender

A bar chart is a representational chart where the vertical axis displays the class frequencies and the horizontal axis displays the reported classes. The heights of the bars correspond to the class frequencies. The gender variable is shown graphically in the bar chart that follows. The sample was made up of 42% female participants and 58% male participants, as the bar chart illustrates.

Figure 2



The following bar chart provides a graphical presentation of the statement that the process of learning helps respondents boost their psychological satisfaction during projects. Out of 300 respondents, 21% of participants strongly agree, 48% agree, 18.7% are neutral, 10.7% disagree and 1.7% strongly disagree. Among which the most frequently opt. the option was agreed.

 

Table 2

Q3: Encouragement by the organization inspires me to work hard and effectively.

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Strongly Disagree	15	5.0	5.0	5.0
	Disagree	43	14.3	14.3	19.3
	Neutral	54	18.0	18.0	37.3
	Agree	130	43.3	43.3	80.7
	Strongly Agree	58	19.3	19.3	100.0
	Total	300	100.0	100.0

 




The following table illustrates the frequency distribution of the statement that encouragement by an organization inspires respondents to work hard and efficiently. Among the total number of 300 participants, the participants strongly agreed were 58, agreed were 130, neutral were 54, disagreed were 43, and strongly disagreed were 15. The following bar chart shows the statement that encouragement by the organization inspires respondents to work hard and efficiently.

Figure 3

Bar Chart Q3.



The following bar chart provides a graphical presentation of the statement that encouragement by the organization inspires respondents to work hard and efficiently. Out of 300 respondents, 19.3% participants strongly agree, 43.3% agree, 18% are neutral, 14.3% disagree and 5% strongly disagree. Among which the most frequently opt. the option was agreed.




 

Table 4.

Q4: My emotional status impacts my ability to work.

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Strongly Disagree	45	15.0	15.0	15.0
	Disagree	75	25.0	25.0	40.0
	Neutral	43	14.3	14.3	54.3
	Agree	93	31.0	31.0	85.3
	Strongly Agree	44	14.7	14.7	100.0
	Total	300	100.0	100.0

 




The following table illustrates the frequency distribution of the statement that the emotional status of respondent impacts their ability to work. Among the total number of 300 participants, the participants who strongly agreed were 44, agree were 93, neutral were 43, disagree were 75, and strongly disagree were 45.  The following bar chart shows the statement that the emotional status of respondent impacts their ability to work.

Figure 4



The following bar chart provides a graphical presentation of the statement that the emotional status of the respondent impacts their ability to work. Out of 300 respondents, 14.7% participants strongly agree, 31% agree, 14.3% are neutral, 25% disagree and 15% strongly disagree. Among which the most frequently opt. the option was agreed.




 

Table 6

Q5: The potency of workers is dependent on the organization’s behavior.

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Strongly Disagree	24	8.0	8.0	8.0
	Disagree	53	17.7	17.7	25.7
	Neutral	61	20.3	20.3	46.0
	Agree	114	38.0	38.0	84.0
	Strongly Agree	48	16.0	16.0	100.0
	Total	300	100.0	100.0

 




The following table illustrates the frequency distribution of the statement that the potency of workers is dependent on the organization's behavior. Among the total number of 300 participants, participants who strongly agreed were 48, those who agreed were 114, neutral ones were 61, those who disagreed were 53 and those who strongly disagreed were 24. The following bar chart shows the statement that the potency of workers is dependent on the organization's behavior. 

Figure 5

Bar Chart Q5.



The following bar chart provides a graphical presentation of the statement that the potency of workers is dependent on the organization's behavior. Out of 300 respondents, 16% participants strongly agreed, 38% agreed, 20.3% were neutral, 17.7% disagreed and 8% strongly disagreed. Among which the most frequently opt. the option was agreed.




 

Table 7

Q6: Recognizing self-autonomy affects a worker’s psychology.

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Strongly Disagree	7	2.3	2.3	2.3
	Disagree	45	15.0	15.0	17.3
	Neutral	60	20.0	20.0	37.3
	Agree	128	42.7	42.7	80.0
	Strongly Agree	60	20.0	20.0	100.0
	Total	300	100.0	100.0

 




The following table illustrates the frequency distribution of the statement that recognizing self-autonomy affects a worker’s psychology. Among the total number of 300 participants, the participants who strongly agreed 60, agreed were 128, neutral ones were 60, disagreed ones were 45, and strongly disagreed were 7. The following bar chart shows the statement that recognizing self-autonomy affects a worker’s psychology.

Figure 6

The following bar chart provides a graphical presentation of the statement recognizing self-autonomy affects a worker's psychology. Out of 300 respondents, 20% participants strongly agreed, 42.7% agreed, 20% were neutral, 15% disagreed and 2.3% strongly disagreed. Among these, the most frequently opted option was agreed upon. 

Figure 7



The following bar represents income by effects of performance. It clearly indicates most of the employees having income of 30,000-40,000 have better performance. The income of 30,000-40,000 stands paramount in accepting that performance is better obtained as compared to other incomed employees. Therefore, the Null hypothesis that the Ability to accomplish tasks had improved performance levels among employees with 20,000-30,000 salaries is rejected. 

 




Table 8

Emotional status impacts the ability to work more specifically in the male gender.

Regression Analysis Summary for Emotion Predicting Performance.

95.0 Confidence %

Interval

Variables B Lower Limit Upper Limit ? ? P-value

(Constant) 2.145 1.947 2.342 21.358 .000

Positive Thinking -.215 -.519 .088 -.081 -1.396 .164

Note: R2 adjusted = .003. CI = Confidence Interval for B.




 

Table demonstrates the regression output above shows a regression model with performance level as a predictor is statistically significant, B (2.145, -.215), p <.001, Adjusted R-squared = .003. The adjusted R-squared of .003 means that 0.3% of the variance in the outcome variable is accounted for by the emotion in the table. Based on the regression output above, significant predictors include Performance level while the independent variable is Emotion, (beta= -.215, p<.001), which represents the slope of the line between the predictor of emotion and performance level. The obtained value for significance is 0.164 (p-value) which is p > 0.05, this indicates that emotion significantly does not predict the performance level, and the correlation is considered significant. The 95% CI values show that the minimum number of incomes was 1.947 (-.519) and the maximum number of employees with income was noted as 2.342 (.088) in relationship to performance level.

Figure 8



The following bar represents the male gender by effects of emotion factors to affect its performance. It clearly indicates most of the males think that emotion has an influence over performance. The male gender stands paramount in accepting that emotion is the only reason for having affected performance at work as compared to the female gender. Therefore, the Null hypothesis that Emotional status impacts the ability to work more specifically in the male gender is rejected. 

Private organizations have a more effective partnership between organizations and employees that ensures better job performance.




 

Table 9

Regression Analysis Summary for Job Type Predicting the relationship between organizations and employees’ performance.

		95.0 Confidence	% Interval
Variables	B	Lower Limit	Upper Limit	?	?	P-value
(Constant)	2.759	2.569	2.949		28.570	.000
Positive Thinking	.095	-.148	.337	.044	.768	.443

Note: R2 adjusted = - .001. CI = Confidence Interval for B.

 




The table demonstrates the regression output above shows a regression model with the relationship between organizations and employees' performance as a predictor is statistically significant, B (2.759, .095), p <.001, Adjusted R-squared = -.001. The adjusted R-squared of -.001 means that -0.1% of the variance in the outcome variable is accounted for by the job type in the table. Based on the regression output above, significant predictors include the relationship between organizations and employees' performance while the independent variable is Job Type, (beta= .044, p<.001), which represents the slope of the line between the predictor of job type and relationship between organizations and employees' performance. The obtained value for significance is 0.443 (p-value) which is p > 0.05, this indicates that job type significantly does not predict the relationship between organizations and employees' performance, and the correlation is considered significant. The 95% CI values show that the minimum number of incomes was 2.569 (-.148) and the maximum number of employees with income was noted as 2.949 (.337) in relationship to relationship.

Figure 9



The following bar represents Private jobs by effects of having a strong relationship between the organization and employees' performance. It clearly indicates most of the private jobs are likely to think that there is a better relationship between organization and performance. Private jobs stand paramount in accepting relationships. Therefore, the Null hypothesis that Private organizations had a more effective partnership between organizations and employees that ensures better job performance is rejected.




 

Table 10

4.2.4 Private organizations encourage employees to work hard.

Regression Analysis Summary for Private Organization Predicting Hard Work.

		95.0 Confidence	% Interval
Variables	B	Lower Limit	Upper Limit	?	?	P-value
(Constant)	.529	.389	.670		7.408	.000
Positive Thinking	.033	-.018	.083	.074	1.277	.203

Note: R2 adjusted = .002. CI = Confidence Interval for B.

 




The table demonstrates the regression output above shows a regression model with Hard Work as a predictor is statistically significant, B (.529, .033), p <.001, Adjusted R-squared = .002. The adjusted R-squared of .002 means that 0.2% of the variance in the outcome variable is accounted for by the private organization in the table. Based on the regression output above, significant predictors include Hard Work while the independent variable is private organization, (beta= .074, p<.001), which represents the slope of the line between the predictor of hard work and private organization. The obtained value for significance is 0.203 (p-value) which is p > 0.05, this indicates that private organizations significantly do not predict the hard work, and the correlation is considered significant. The 95% CI values show that the minimum number of private organizations was .389 (-.018) and the maximum number of employees with income was noted as .670 (.083) in Hard Work

Figure 10



The following bar represents Private jobs by the effects of working hard. It clearly indicates most of the private jobs are likely to think that they do hard work. Private jobs stand paramount in accepting hard work as compared to public jobs. Therefore, the Null hypothesis that private organizations encourage employees to work hard is rejected (Hussain, 2020). 

The table demonstrates the regression output above shows a regression model with learning as a predictor is statistically significant, B (2.485, .315), p <.001, Adjusted R-squared = .041. The adjusted R-squared of .041 means that 0.4% of the variance in the outcome variable is accounted for by the income in the table. Based on the regression output above, significant predictors include learning while the independent variable is income, (beta= .210, p<.001), which represents the slope of the line between the predictor of learning and income. The obtained value for significance is 0.000 (p-value) which is p < 0.05, this indicates that income significantly predicts employee learning, and the correlation is considered significant. The 95% CI values show that the minimum number of income was 1.998 (.148) and the maximum number of employees with income was noted as 2.972 (.481) in learning.

Figure 10



The following bar represents Private jobs by the effects of working hard. It clearly indicates most of the private jobs are likely to think that they do hard work. Private jobs stand paramount in accepting hard work as compared to public jobs. Therefore, the Null hypothesis that private organizations encourage employees to work hard is rejected (Hussain, 2020). 

The table demonstrates the regression output above shows a regression model with learning as a predictor is statistically significant, B (2.485, .315), p <.001, Adjusted R-squared = .041. The adjusted R-squared of .041 means that 0.4% of the variance in the outcome variable is accounted for by the income in the table. Based on the regression output above, significant predictors include learning while the independent variable is income, (beta= .210, p<.001), which represents the slope of the line between the predictor of learning and income. The obtained value for significance is 0.000 (p-value) which is p < 0.05, this indicates that income significantly predicts employee learning, and the correlation is considered significant. The 95% CI values show that the minimum number of income was 1.998 (.148) and the maximum number of employees with income was noted as 2.972 (.481) in learning.

Figure 11



The following bar represents income by effects of learning ability that boost their psychological performances. It clearly indicates most of the employees with income of 20,000-30,000 are more likely to think that they have better learning abilities that boost their psychological performances. The income of 20,000-30,000 stands paramount in accepting that statement as compared to other income employees. Therefore, the Null hypothesis that Employees with 20,000-30,000 incomes had better learning abilities that boost their psychological performances is rejected.




 

Table 11

4.2.6 Employees with Bachelor’s degrees had more self-efficacy and improved performance in an organization.

Regression Analysis Summary for Education Predicting Self-Efficacy.

		95.0 Confidence	% Interval
Variables	B	Lower Limit	Upper Limit	?	?	P-value
(Constant)	2.559	2.114	3.005		11.303	.000
Positive Thinking	.108	-.045	.262	.080	1.389	.166

Note: R2 adjusted = .003. CI = Confidence Interval for B.

 




The table demonstrates the regression output above shows a regression model with self-efficacy as a predictor is statistically significant, B (2.559, .108), p <.001, Adjusted R-squared = .003. The adjusted R-squared of .003 means that 0.3% of the variance in the outcome variable is accounted for by the education in the table. Based on the regression output above, significant predictors include self-efficacy while the independent variable is education, (beta= .080, p<.001), which represents the slope of the line between the predictor of self-efficacy and education. The obtained value for significance is 0.166 (p-value) which is p > 0.05, this indicates that education significantly does not predict self-efficacy, and the correlation is considered significant. The 95% CI values show that the minimum number of educations was 2.114 (-.045) and the maximum number of employees with education was noted as 3.005 (.262) in education.

Figure 11



The following bar represents income by effects of learning ability that boost their psychological performances. It clearly indicates most of the employees with income of 20,000-30,000 are more likely to think that they have better learning abilities that boost their psychological performances. The income of 20,000-30,000 stands paramount in accepting that statement as compared to other income employees. Therefore, the Null hypothesis that Employees with 20,000-30,000 incomes had better learning abilities that boost their psychological performances is rejected.




 

Table 11

4.2.6 Employees with Bachelor’s degrees had more self-efficacy and improved performance in an organization.

Regression Analysis Summary for Education Predicting Self-Efficacy.

		95.0 Confidence	% Interval
Variables	B	Lower Limit	Upper Limit	?	?	P-value
(Constant)	2.559	2.114	3.005		11.303	.000
Positive Thinking	.108	-.045	.262	.080	1.389	.166

Note: R2 adjusted = .003. CI = Confidence Interval for B.

 




The table demonstrates the regression output above shows a regression model with self-efficacy as a predictor is statistically significant, B (2.559, .108), p <.001, Adjusted R-squared = .003. The adjusted R-squared of .003 means that 0.3% of the variance in the outcome variable is accounted for by the education in the table. Based on the regression output above, significant predictors include self-efficacy while the independent variable is education, (beta= .080, p<.001), which represents the slope of the line between the predictor of self-efficacy and education. The obtained value for significance is 0.166 (p-value) which is p > 0.05, this indicates that education significantly does not predict self-efficacy, and the correlation is considered significant. The 95% CI values show that the minimum number of educations was 2.114 (-.045) and the maximum number of employees with education was noted as 3.005 (.262) in education.

Figure 12



The following bar represents the education by effects of self-efficacy and improved performance level. It clearly indicates most of the employees with bachelor's degrees agree with the purposes. Employees with bachelor's degrees stand paramount in accepting that self-efficacy and improved performance in an organization as compared to other education. Therefore, the Null hypothesis that employees with Bachelor's degrees had more self-efficacy and improved performance in an organization is rejected.




 

Table 12

4.2.7 Employees with Bachelor’s degrees had more self-determination and improved performance in an organization.

Regression Analysis Summary for Education Predicting Self-Determination.

		95.0 Confidence	% Interval
Variables	B	Lower Limit	Upper Limit	?	?	P-value
(Constant)	2.496	2.055	2.937		11.131	.000
Positive Thinking	.128	-.020	.276	.098	1.706	.089

Note: R2 adjusted = .006. CI = Confidence Interval for B.

 




The table demonstrates the regression output above shows a regression model with self-determination as a predictor is statistically significant, B (2.496, .128), p <.001, Adjusted R-squared = .006. The adjusted R-squared of .006 means that 0.6% of the variance in the outcome variable is accounted for by the education in the table. Based on the regression output above, significant predictors include self-determination while the independent variable is education, (beta= .098, p<.001), which represents the slope of the line between the predictor of self-determination and education. The obtained value for significance is 0.089 (p-value) which is p > 0.05, this indicates that education significantly does not predict self-determination, and the correlation is considered significant. The 95% CI values show that the minimum number of educations was 2.055 (-.020) and the maximum number of employees with education was noted as 2.937 (.276) in self-determination.

Figure 13



The following bar represents the education by effects of self-determination and improved performance level. It clearly indicates most of the employees with bachelor's degrees agree with the purposes. Employees with bachelor's degrees stand paramount in accepting that self-determination and improved performance in an organization as compared to other education. Therefore, the Null hypothesis that employees with Bachelor's degrees had more self-determination and improved performance in an organization is rejected. 




 

 

 

Table 13

4.2.8 Employees with an income of 20,000-30,000 had more effects on their performance level.

Regression Analysis Summary for Low-Income Predicting Performance.

		95.0 Confidence	% Interval
Variables	B	Lower Limit	Upper Limit	?	?	P-value
(Constant)	3.215	2.766	3.664		14.094	.000
Positive Thinking	.051	-. 102	.204	.038	.652	.515

Note: R2 adjusted = - .002. CI = Confidence Interval for B.

 




The table demonstrates the regression output above shows a regression model with performance as a predictor is statistically significant, B (3.215, .051), p <.001, Adjusted R-squared = -.002. The adjusted R-squared of - .002 means that 0.2% of the variance in the outcome variable is accounted for by the low income in the table. Based on the regression output above, significant predictors include performance while the independent variable is low income, (beta= .038, p<.001), which represents the slope of the line between the predictor of performance and low income. The obtained value for significance is 0.515 (p-value) which is p > 0.05, this indicates that low income significantly does not predict performance, and the correlation is considered significant. The 95% CI values show that the minimum number of low-income was 2.766 (-.102) and the maximum number of employees with low income was noted as .3.664 (.204) in performance.

Figure 14

The following bar represents income by effects of performance level. It clearly indicates most of the employees with an income of 20,000-30,000 are more likely to think that they have a better performance level. The income of 20,000-30,000 stands paramount in accepting that statement as compared to other income employees. Therefore, the Null hypothesis that employees with income of 20,000-30,000 had more effects on their performance level is rejected.

Conclusion

In organizational behavior and psychological performance of employees, the interaction between self-efficacy and self-determination plays a major role. Self-determination is based on the intrinsic motivation and autonomy of employees which leads to ownership and commitment in what they do because it fosters a sense of control by employees over their tasks and decisions, resulting in high levels of engagement plus job satisfaction — not to mention the overall psychological well-being. The drive coming from this intrinsic motivation pushes them to go beyond mere compliance— leading innovation as well as being proactive in problem-solving.

Belief in their abilities is key to success, which is further reinforced by self-efficacy. When employees show high self-efficacy, they become able to handle challenges more easily and demonstrate determination as well as a positive perspective; this confidence not only elevates personal output but also fosters team spirit and support within the workplace. In such cases, these employees are likely to volunteer for leadership roles and guide their colleagues— both professionally and personally— thus helping to foster a positive organizational culture.

Self-determination, together with self-efficacy, forms a combined force that enhances performance at the psychological level and in turn has a positive influence on the behavior of organizations. Organizations that foster these attributes by developing skill-based leadership, providing chances for skill development and contribution recognition should anticipate enhanced employee performance — low turnover — and enriched workplace culture — to whom it may concern.

So, fostering self-determination and self-efficacy in the employees is not only a good strategy but also results in benefits to both individuals and the organization. Through these psychological constructs, organizations can enable their people to bring out all that they are capable of which means that they will be successful in the long term— as well as having an edge over their competitors in the market. 

Conclusion

In organizational behavior and psychological performance of employees, the interaction between self-efficacy and self-determination plays a major role. Self-determination is based on the intrinsic motivation and autonomy of employees which leads to ownership and commitment in what they do because it fosters a sense of control by employees over their tasks and decisions, resulting in high levels of engagement plus job satisfaction — not to mention the overall psychological well-being. The drive coming from this intrinsic motivation pushes them to go beyond mere compliance— leading innovation as well as being proactive in problem-solving.

Belief in their abilities is key to success, which is further reinforced by self-efficacy. When employees show high self-efficacy, they become able to handle challenges more easily and demonstrate determination as well as a positive perspective; this confidence not only elevates personal output but also fosters team spirit and support within the workplace. In such cases, these employees are likely to volunteer for leadership roles and guide their colleagues— both professionally and personally— thus helping to foster a positive organizational culture.

Self-determination, together with self-efficacy, forms a combined force that enhances performance at the psychological level and in turn has a positive influence on the behavior of organizations. Organizations that foster these attributes by developing skill-based leadership, providing chances for skill development and contribution recognition should anticipate enhanced employee performance — low turnover — and enriched workplace culture — to whom it may concern.

So, fostering self-determination and self-efficacy in the employees is not only a good strategy but also results in benefits to both individuals and the organization. Through these psychological constructs, organizations can enable their people to bring out all that they are capable of which means that they will be successful in the long term— as well as having an edge over their competitors in the market. 

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