Young (6) defines a conceptual review as the diagrammatical representation that occurs between the dependent variable and the independent variable. This research work consists of five variables such as recruitment, training, compensation, and job design that influence the dependent variable, which is organizational performance. Organization’s performance has been researched in the past broadly and found that organization performance was determined by the quality of HR performs such as training, job safety, job design, motivation in addition to job satisfaction.

As per Armstrong (2001), training is an important combination of education, coaching, and development plus strategic experience that modifies employees’ behavior in the workplace. A key factor in the success of companies and the workforce is training (7). Therefore, training must be well designed and planned, and distribution must be well executed to improve performance.

Training enhances employees’ skills, knowledge, behaviors, and other abilities for the effective performance of their jobs (8). Assuredly, training enhances performance creditably. Cheng and Ho (2001) posited that training improves employee communication, proficiency, and retention.

Compensation refers to the pay, wages, salary, and benefits that can be enjoyed by employees in the workplace (9). It is the reward system for outstanding performance in the workplace (8). The recompense system is grounded on employee performance, which improves the overall performance of the organization (10). Reimbursement policy in the workplace has a significant impact on an employee’s efficiency and the success of organizations.

Performance-based recompense positively affects employees and the performance of organizations (11). Employee satisfaction meaningfully varies with the compensation policies of the organization. According to studies, incentive pay boosts sales growth, decreases staff throughput, and has a beneficial effect on performance (12).

Standard skills, knowledge, experience, and societal and individual qualities, such as creativity and invention that are present in the capacity to carry out labor and generate economic value are referred to as “human capital.” Human capital, according to Dess and Picken (13), typically refers to a person’s abilities, skills, knowledge, and understanding of a company’s workforce and managers that are necessary for the task at hand, as well as their capacity to supplement a reservoir of knowledge, skills, and understanding that completes individual learning. This idea raises questions about how individuals might enhance organizational capability and the value of their contributions by contributing their knowledge, skills, and talents.

Yin (14) described research strategy as a comprehensive outline of how the research was carried out or conducted. This included the way data was collected, the instruments to be employed, the way the instrument was used, and the means of analyzing the collected data. This study employed a survey design to generate quantitative data and a vivid research design. Jacobs (2009) writes that descriptive research seeks to answer research questions such as “who, where, and when.”

This study’s target population is the academic and non-teaching (senior and junior) staff of Rufus Giwa Polytechnic, Owo. These types of employees will be selected based on their knowledge and experience in HR practices. The staff forte of the institution at the time the investigator arrived was 1776, namely: academic staff of 446, senior staff of 676, and junior staff of 654. The population possessed the traits and experience required to elicit the desired responses. This was shown in Table 1.

Zikmund et al. (2010) define a sampling frame as a process in which a subset of individuals is selected from the entire population to make predictions that are based on statistical inference. It is required that the sample taken be a true representation of the population under consideration. Using Taro Yamane’s (1967) formula to regulate valuable and sample size, the population size was 1776, and the sample size was 327.

where

n = the sample size

N = the population under study

e = the margin of error (0.05) substituting the formula

n = 1776/(1 + 1776(0.05)2)

n = 1776/(1 + 1776(0.0025)

n = 1776/(1 + 4.44)

n = 1776/5.44

n = 327

Therefore, the sample of the study is 327 employees of Rufus Giwa Polytechnic, Owo.

Burley’s formulation was hired to determine the sample size for each category. From the application of this formula, 82 respondents were selected from the academic staff, while 125 respondents were from senior members of staff and 120 respondents were from junior members of staff, making a total of 327 respondents, as shown in the section titled, “Sample and Sampling Techniques.”

where n = number of sample size allocated to each category

n_i = total number of each category

n = total sample size

N = population of the study

OLS regression was employed as a statistical tool to analyze and estimate the relationship between the variables involved.

A model detailing how HR management methods affect tertiary institutions’ performance was developed. The variables concentrated on recruitment, training, compensation, and job design.

The model is

TIP = f (RS, TD, CR, JD)

where

TIP = tertiary institution performance, RS = recruitment and selection, TD = training and development, CR = compensation and reward, and JD = job design.

TIP_t = B₀ + B_i RS_t + B₂TD_t + B₃CR_t + B4SD_t + μ_t

The samples used for analysis were gathered from three separate categories of staff at Rufus Giwa Polytechnic, Owo, namely academic staff, senior staff, and junior staff.

Table 2 shows a rate of response of 25.31% for the academic staff category, 38.27% for the senior staff category, and 36.42% for the junior staff category. The total percentage of the returned questionnaire is 99.08%, while the percentage of questions left unanswered is 0.92%. This percentage of returned copies of the questionnaire is considered adequate for this study. Godwin (15) believes 70% and above are measured as conventionally acceptable for social science research.

Table 3 shows the descriptive statistics that brought the normality test of respondents’ bio-data into action. It depicts scattering and central tendency in variables such as mean, median, standard deviation, minimum and maximum, and sum. The mean of the descriptive biodata is gender (1.27), age (2.82), marital status (1.83), education attainment (2.53), employment status (2.73), job status (1.94), and length of service (1.94).

This section attempts to analyze data that bothers respondents’ social profiles. The demographic characteristics concerned here are gender, age, marital status, length of service, education attainment, employment status, and job status.

Table 4 shows the responses of the staff based on their gender: 235 staff members representing 72.5% are males, while 89 staff members representing 27.5% are females. However, Table 4 shows more male respondents than their female counterparts. This implies that there was no gender discrimination among sampled respondents from the Rufus Giwa Polytechnic, Owo. The graphical representation in this regard is provided in Figure 1.

Table 5 displays the age of the respondents. It shows that 37 respondents, representing 11.4%, fall between the age range of 20 and 30 years; 103 respondents, representing 31.8%, fall between the age range of 31 and 40 years; 64 respondents, representing 19.8%, fall between the age range of 41 and 50 years; and 120 respondents, representing 37%, fall between the age range of 51 and 60 years. This indicates that active and dynamic staff dominated the institution, whose opinions are germane and cannot be influenced. The graphical representation in this regard is provided in Figure 2.

Table 6 indicates 270 respondents, or 83.3%, are married, while 54 respondents, or 16.7%, are single. The study depicts that Rufus Giwa Polytechnic, Owo, is dominated by the married, and who are considered mature enough to give an unbiased response. The graphical representation in this regard is provided in Figure 3.

Table 7 indicates that 13 respondents representing 4.01% are Ph.D. degree holders, 103 respondents representing 32.79% have Master degrees, and 188 respondents representing 58.03% have B.Sc. or HND, respectively, while 20 respondents representing 6.17% have NDs or NCEs. It shows that more first-degree holders and master’s degree holders were employed in the institution and thus formed the bulk of the respondents. The graphical representation in this regard is shown in Figure 4.

Table 8 displays the employment status of the staff: 295 respondents, or 91.05%, are on the permanent appointment, 14 respondents, or 4.32%, are on part-time appointments, 4 respondents, or 1.24%, are on contract appointments, and 11 respondents, or 3.39%, are on temporary appointment. The result shows that more than 94% of the respondents secured permanent appointments and their opinions will be considered adequate for the study. The graphical representation in this regard is shown in Figure 5.

Table 9 shows the job status for the academic staff category of 82, representing 25.31%, the senior staff category of 124, representing 38.27%, and the junior staff category of 118, representing 36.42%. The overall percentage of returned questionnaires is 99.08%, with unreturned questionnaires accounting for 0.92%. The responses were at a higher rate, good for the study. The graphical representation in this regard is provided in Figure 6.

Table 10 indicates that 94 respondents, representing 29%, fall between the ranges of 1 and 10 years, while 138 respondents, representing 42.6%, fall between the ranges of 11 and 20 years, and 92 respondents, representing 28.4%, fall between the ranges of 21 and 30 years. This implies that Rufus Giwa Polytechnic, Owo, has some recently employed staff both in the academic and administrative cadres. The graphical representation in this regard is shown in Figure 7.

The hypotheses formulated were tested at a 0.05 significance level using a regression model. The outcomes are shown in Table 11.