Reward and Promotion: Sustainable Value of Post Pandemic Efforts in Medical Cold-Supply Chain

This research was carried out in one of the main logistics centers called the Nusantara Bonded Zone which houses many transportation and logistics companies, especially medical cold supply chains. This study aims to analyze the sustainable value of post-pandemic efforts in medical cold supply chains, with a focus on Investment Analysis and Management. This study uses a design approach involving case studies and qualitative analysis. Data was collected through interviews with key stakeholders in the medical cold supply chain, including drug manufacturers, logistics service providers and final recipients. The information obtained from these interviews was analyzed using a qualitative approach to identify research findings. The research findings show that the proper use of Investment Analysis and Management can create sustainable value in post-pandemic medical cold supply chains. Rewards that are performance oriented and improve employee competency can encourage increased operational efficiency and compliance with quality standards. The practical implication of this research is to provide guidance for practitioners in the medical supply industry to implement appropriate rewards and promotions. This can help them improve operational efficiency, minimize product losses, and improve the quality of service to customers. In addition, this study did not explore the financial aspects of rewards and promotions, which could be an interesting research area for future research. This is an open access article under the CC BY 4.0 license.


INTRODUCTION
The aim of this research is to investigate the impact of Investment Analysis Management on employee performance in the logistics industry, with a focus on the role of rewards, promotions, and compensation [1].Given the highly competitive nature of the logistics sector, understanding how investment analysis and management strategies influence employee performance is crucial for companies aiming to enhance their operational efficiency and maintain a competitive edge.Healthpreneur by examining the relationship between investment analysis management practices and employee performance, particularly in terms of rewards, promotions, and ❒ E-ISSN: 2656-8888 | P-ISSN: 2655-8807 compensation, this study seeks to provide insights into effective human resource management strategies within the logistics industry [2].Aligned with the scope of this research, the hypothesis posits that there exists a significant correlation between investment analysis management practices and employee performance in the logistics sector, with rewards, promotions, and compensation playing crucial mediating roles.It is hypothesized that companies implementing effective investment analysis management strategies, including the provision of both intrinsic and extrinsic rewards, opportunities for promotion, and fair compensation, will experience higher levels of employee performance [3].More over, it is expected that employees who perceive their efforts being recognized through rewards and promotions will demonstrate greater motivation and commitment to achieving organizational goals, thereby positively impacting their performance levels [4].
The problem statement directly correlates with the research question, emphasizing the importance of understanding how investment analysis management practices, particularly in terms of rewards, promotions, and compensation, influence employee performance in the logistics industry.This research aims to address the pressing need for companies in the logistics sector to enhance their human resource management strategies to improve performance amidst intense competition.By examining the relationship between investment analysis management practices and employee performance, this study aims to provide actionable insights for companies seeking to optimize their human resource practices and ultimately achieve organizational success [5].

LITERATURE REVIEW
Rewards or awards or what we equate with Investment analysis and Management means all forms of remuneration for employees arising from their work.It can be in the form of direct payment of money in the form of wages, salaries, incentives, commissions, and bonuses and it can also be in the form of indirect payments such as insurance, and holidays at the expense of the company.Rewards are benefits that arise when employees perform tasks, provide services, or exercise responsibility [6].Awards are given in the form of material and non-material given by the company to its employees so that they can work with high motivation and achievement in achieving company goals [7].Promotion is a transfer that increases the authority and responsibility of an employee to a higher position in an organization so that the rights, status, and income are greater [8].Promotion is an increase in the rank or position of an employee in the organizational hierarchical system.Through the promotion of recognition of employee effort and commitment to work [9].
Performance is the result in terms of quality and quantity achieved by an employee in carrying out his duties in accordance with the responsibilities given to him [10].Performance is about behavior or what employees do, not about what employees produce or the results of their work.Performance is seen as the implementation of one's actions or abilities.Good performance is also related to the achievement of quality, quantity, cooperation, reliability, and creativity.Employee performance is considered as a measure of the quality of human resources owned by the organization [11].Rewards, synonymous with incentives or remunerations, encompass all forms of compensations employees receive for their work contributions within a company [12].These can manifest in various ways, including direct monetary payments like wages, salaries, bonuses, and commissions, as well as indirect benefits such as insurance coverage or company-sponsored holidays [13].Essentially, rewards serve as the acknowledgment and appreciation for employees' efforts, services rendered, or responsibilities assumed during their tenure within the organization [14].
Awards, on the other hand, represent tangible and intangible recognitions bestowed upon employees by their employers [15].These gestures aim to inspire high motivation levels and foster a sense of achievement among the workforce, ultimately aligning their efforts with the overarching objectives of the company [16].Whether material rewards like bonuses or non-material acknowledgments such as public recognition or career advancement opportunities, awards play a pivotal role in nurturing a culture of excellence and dedication within the organizational framework [17].Promotion stands as a significant aspect of employee advancement within an organizational hierarchy.It signifies a transition to a higher-ranking position endowed with greater authority, responsibilities, and often, enhanced remuneration [18].Beyond the tangible benefits, promotion serves as a testament to an employee's commitment, competence, and contributions to the organization.It reinforces the notion of meritocracy and provides a tangible pathway for career growth and development within the company's structure [19].
Performance, meanwhile, constitutes the tangible outcomes achieved by an employee in terms of both quality and quantity while fulfilling their designated duties and responsibilities.It is a reflection of an individual's actions, behaviors, and capabilities in executing tasks effectively within the organizational context.Emphasizing not only the output but also the process, performance evaluation encompasses aspects like collaboration, reliability, creativity, and adherence to quality standards [20].
The concept of employee performance extends beyond mere productivity metrics; it serves as a barometer of the organization's human capital quality [21].A high-performance culture signifies a workforce that is not only proficient in executing tasks but also exhibits traits like teamwork, innovation, and adaptability.Consequently, organizations view employee performance as a critical determinant of their competitive edge and operational excellence in the market landscape [22].Understanding the nuances of employee performance facilitates the implementation of targeted strategies to optimize workforce productivity and engagement [23].By recognizing and rewarding exemplary performance, organizations foster a culture of accountability and excellence [24].Moreover, performance assessments serve as a basis for identifying skill gaps, providing targeted training interventions, and aligning individual goals with organizational objectives.
The correlation between rewards, awards, promotion, and employee performance underscores the symbiotic relationship between organizational incentives and workforce productivity.A well-designed rewards system incentivizes desired behaviors and fosters a sense of ownership and commitment among employees.Similarly, promotions based on meritocracy reinforce a culture of fairness and transparency, inspiring employees to strive for continuous improvement and career advancement opportunities [25].In essence, the interplay between rewards, awards, promotion, and performance underscores the multifaceted nature of employee motivation and engagement within organizational settings [26].By aligning incentives with performance metrics and providing a clear pathway for career progression, companies can nurture a culture of excellence and drive sustained organizational success in today's dynamic business environment [27].Furthermore, these variables also have a direct relationship with Employee Performance.Thus, the relationship between investment analysis management practices and employee performance in the logistics industry is explicitly illustrated in this figure 3 [28].Hypothesis: H01: Reward has no effect on employee performance HA1: Rewards affect employee performance H02: Promotion has no effect on employee performance HA2: Promotion has an effect on employee performance Each relationship between variables is depicted with an arrow pointing from the independent variable to the dependent variable, indicating the hypothesized causal relationship in the research model.Each relationship between variables is depicted with an arrow pointing from the independent variable to the dependent variable, indicating the hypothesized causal relationship in the research model [29].These arrows symbolize the direction of influence that researchers believe one variable exerts over another within the conceptual framework of the study.By visually representing these relationships, researchers aim to elucidate the potential pathways through which changes in one variable may impact changes in another, thus providing a structured framework for analyzing and interpreting research findings.
In constructing these models, researchers meticulously consider theoretical underpinnings, empirical evidence, and logical reasoning to establish the proposed causal connections between variables.These models serve as blueprints for understanding complex phenomena and formulating testable hypotheses to investigate the relationships between different constructs.By delineating the directional flow of influence, researchers ❒ E-ISSN: 2656-8888 | P-ISSN: 2655-8807 can discern the primary drivers of change and elucidate the mechanisms underlying observed phenomena, contributing to a deeper understanding of the studied phenomen.Moreover, these causal models play a pivotal role in guiding data collection, analysis, and interpretation processes in empirical research.Researchers utilize statistical techniques such as regression analysis, structural equation modeling, or path analysis to empirically assess the hypothesized relationships and validate the proposed causal pathways.Through rigorous testing and validation, researchers can ascertain the robustness of their theoretical models and draw meaningful conclusions regarding the causal dynamics underlying the phenomena of interest, thus advancing knowledge within their respective fields.

RESEARCH METHOD
In this study, a quantitative research design was employed to delve into the connection between investment analysis management practices and employee performance within the logistics industry.The research specifically targeted permanent employees working in distribution and logistics firms located in the Kawasan Berikat Nusantara.To ensure a comprehensive representation, 336 respondents were sampled using Probability Sampling with a simple random sampling technique.This method was chosen due to its capability to provide an equal opportunity for every member of the population to be selected, thereby guaranteeing a representative sample.Given the homogeneous nature of the population without any distinct strata, simple random sampling was deemed suitable for this study.Data collection was carried out through surveys, aiming to gather insights from the selected respondents regarding their perceptions of various factors including investment analysis management practices, rewards, promotions, compensation, and their own performance levels.The survey questionnaire was meticulously designed based on established scales and measures within the realms of human resource management and performance assessment.Subsequently, the collected data underwent thorough statistical analysis to address the research inquiries and assess the formulated hypotheses.Specifically, SPSS version 26 software was utilized for this purpose.
The statistical analysis encompassed a spectrum of tests aimed at ensuring the validity and reliability of the findings.These tests encompassed the examination of multicollinearity to scrutinize correlations between independent variables, heteroscedasticity to evaluate variance inequality of residuals, and normality to confirm the normal distribution of residual variables.Furthermore, the coefficient of determination (R2) was computed to gauge the model's efficacy in elucidating the variation in the dependent variable-employee performance.A low R2 value implies a restricted explanatory capability, while a value nearing one suggests that independent variables significantly contribute to predicting the variation in the dependent variable.Through this rigorous statistical scrutiny, the study aimed to bolster the robustness and reliability of its findings, facilitating the derivation of meaningful conclusions regarding the interplay between investment analysis management practices and employee performance in the logistics industry.

RESULT AND DISCUSSION
The simple regression equation used in this study is: Y1 = a + b1X1 + e Y1 = a + b2X2 + e Descriptions: Y1 = Employee Performance X1 = Reward X2 = Promotion B = Coeff.

E = Error
The statistical test basically shows how far the influence of one explanatory/ independent variable individually explains the variation of the dependent variable.The null hypothesis (H0) to be tested is whether a parameter (bi) is equal to zero, or: H0: bi = 0, Meaning whether an independent variable is not a significant explanation of the dependent variable.The alternative hypothesis (HA) parameter of a variable is not equal to zero, or: HA: bi = 0, Meaning that the variable is a significant explanation of the dependent variable.The multicollinearity test is a test that aims to test whether the regression model finds a correlation between the independent (independent) variables because a good regression model should not have a correlation between the independent variables.Multicollinearity can be seen from the tolerance value and variance inflation factor (VIF).The value commonly used to indicate the presence of multicollinearity is the Tolerance value 0.10 or the same as the VIF value = 10.His research interests are Financial management, Risk Management, Good Governance, Audit Forensics, strategic management, and Capital market.The aforementioned table indicates that the occurrence ofmulticollinearity can be ruled out as the tolerance value of the variables is greater than 0.1 and VIF is less than 10.Therefore, this regression model can be considered as appropriate, since a well-designed regression model should not display any correlation between the independent variables.
The purpose of the heteroscedasticity test is to determine whether there is unequal variance between residuals of different observations in the regression model.A regression model is considered good if it exhibits homoscedasticity, which means that the variance of residuals is constant across observations.If there is no discernible pattern and the data points are evenly scattered above and below the zero line on the Y-axis, then the regression model has no heteroscedasticity.Based on the graph above, it is evident that all the data is normally distributed, as indicated by the data points scattered around a straight diagonal line.This distribution pattern signifies that the data conforms to a normal distribution, which is a fundamental assumption in many statistical analyses.The visualization provided by the graph helps confirm the normality of the data, ensuring the reliability of subsequent statistical analyses conducted on the dataset.The coefficient of determination (R2) serves as a crucial metric in assessing the explanatory power of the model regarding changes in the dependent variable.Ranging from zero to one, R2 quantifies the proportion of variance in the dependent variable that is predictable from the independent variables.A low R2 value implies that the independent variables have limited ability to elucidate the variation in the dependent variable, while a value nearing one indicates that the independent variables collectively provide substantial information to anticipate changes in the dependent variable.Thus, by interpreting the R2 value, researchers can gain insights into the effectiveness of the model in capturing the variability of the dependent variable based on the independent variables utilized in the analysis.In this table, the variable "Reward" shows an R of 758, with an R-Square of 569.The T-ratio for the "Adjusted R-Square" variable is 522, and Std.The error of the Estimate is 26.788.A significance value lower than 0.05 indicates that the relationship between the "Reward" variable and employee performance is statistically significant.
These results indicate that the "Reward" variable has a significant impact on employee performance for the year 2021.The positive coefficient suggests that as the level of rewards increases, the measured employee performance also increases.The relatively small standard error suggests that the estimated coefficient of the "Reward" variable is quite accurate.The significant T-ratio confirms that the relationship between rewards and employee performance is not merely due to chance.
In addition to the statistical significance, the practical significance of the relationship between rewards and employee performance is noteworthy.This is evidenced by the results of testing the reward variable model on employee performance in the year 2021, which indicate that rewards have a significant and positive influence on employee performance in the context of this study.Based on the table above, the adjusted R2 result shows 0.522, which means that the employee performance variable can be explained by the reward variable of 52.2%.While the rest is explained by other variables.
Furthermore, these findings underscore the importance of incentivizing employees appropriately to enhance their performance.By recognizing the significant impact of rewards, organizations can design more effective reward systems tailored to motivate employees and improve overall performance outcomes.This insight can inform strategic decision-making processes within human resource management, aiming to optimize employee performance and organizational success in the long term.1.The regression coefficient of the reward variable, the extrinsic reward dimension, has an effect on employee performance.These results indicate that a 1% increase in extrinsic reward will result in an increase of 0.118 or 11.8%.
2. The regression coefficient of the reward variable dimension of intrinsic reward has an effect on employee performance.These results indicate that a 1% increase in intrinsic reward will result in an increase of 0.515 or 51.5%, Regression Test H2 Based on the regression test on H2 in the table above, it can be concluded that the promotion variable has an effect on employee performance.These results indicate that a 1% increase from X2 will result in an increase of 0.321 or 32.1%, suggesting a significant impact of promotions on enhancing employee performance.2. In the coefficient table above, it can be seen that the reward variable dimensions of intrinsic reward show that the t count is 4.345 with a significant level of 0.000, while the t table is sig.a = 0.05 and df = n -k, i.e. 36 -2 = 34, so the t table is 2.0528, so it can be seen that the count is positive and greater than ttable and significantly less than 0.05.So it can be concluded that HA1 is accepted or accepts the alternative hypothesis.This means that the reward variable on the intrinsic reward dimension influences the employee performance variable.
The coefficient table provided demonstrates that the promotion variable exhibits a t-count of 2.374 with a significant level of 0.023.Comparing this to the critical t-value, calculated with a significance level (a) of 0.05 and degrees of freedom (df) of n -k, where n represents the sample size and k represents the number of variables in the model, we find the t-table value to be 2.0322 for a sample size of 36 and 2 variables.As the t-count is positive and greater than the t-table value while also significantly less than 0.05, it leads to the acceptance of HA2 or the alternative hypothesis.This indicates that the promotion variable indeed has a statistically significant effect on the employee performance variable [30].
From the analysis of the effect of reward and promotion on employee performance, it can be concluded that both reward and promotion variables play crucial roles in influencing employee performance.The statistical significance observed in the relationship between promotion and employee performance underscores the importance of recognizing and providing opportunities for career advancement within the organizational framework.Furthermore, this highlights the need for companies to implement effective promotion strategies as part of their human resource management practices to enhance overall employee performance and organizational success [31].

5.
CONCLUSION Based on the t test of the extrinsic reward dimension, where the results of the statistical test show that the t count = 1.126 is smaller than the t table = 2.0322, and the significant level is greater than 0.05, namely 0.413.This means that the extrinsic reward dimension reward variable does not affect employee performance variables.
The reward variable of the intrinsic reward dimension influences employee performance, where the reward variable of the intrinsic reward dimension shows that the value of count = 4.345 with a significant level of 0.000, and t table = 2.0322, so it can be seen that the value of count is positive and greater than t table and significantly smaller than 0.05.This means that the reward variable on the intrinsic reward dimension has a significant effect on the employee performance variable.
The promotion variable has an effect on employee performance, where the promotion variable shows that the value of t count = 2,574 with a significant level of 0.043, and t table = 2.0322, so it can be seen that the t count value is positive and greater than t table and significantly less than 0.05.This means that the promotion variable has a significant effect on employee performance variables.

Figure 2 .
Figure 2. Multicollinearity Test for Reward and Promotion Variables Against Employee Performance

Figure 3 .
Figure 3. Multicollinearity Test for Reward and Promotion Variables Against Employee Performance

Table 1 .
Multicollinearity Test for Reward and Promotion Variables Against Employee Performance

Table 2 .
Test the Reward Variable Model on Employee Performance (2021)

Table 3 .
Test the Promotion Variable Model on Employee Performance (2022)

Table 4 .
Promotion Variable Regression Test on Employee Performance

Table 5 .
Reward Variable t test on Employee Performance In the coefficient table above, it can be seen that the reward variable in the extrinsic reward dimension shows that the count is 1.126 with a significant level of 0.413, while the table is sig.a = 0.05 and df = n -k, i.e. 36 -2 = 34, so the t table is 2.0322, so it can be seen that the t count is positive and smaller than t table and the significant level is greater than 0.05.So it can be concluded that H01 is accepted or accepts the null hypothesis.This means that the extrinsic reward dimension reward variable has no effect on employee performance variables.