Effect of Work Environment on Performance of Academic Staff of Public Universities in North Central Nigeria

Effect of Work Environment on Performance of Academic Staff of Public Universities in North Central Nigeria

Abiola Idowu, Ajibade Bolanle Aderonke^*

Department of Business Administration, Faculty of Management Sciences, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.

^*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.906000446

Received: 12 June 2025; Accepted: 16 June 2025; Published: 23 July 2025

ABSTRACT

The study examined the effect of work environment on performance of academic staff of public universities in North-Central, Nigeria in order to address the declining academic staff performance of public universities due to unfavorable work conditions as evident in severally extant studies. Work environment was measured by both physical and psychological work environment. The study adopted the descriptive survey design which included the administration of structured questionnaire among the target population. The population of the study comprised academic staff of 13 universities in North Central, Nigeria. Sample size was determined using Yamane sample size model with an attrition of 30%. 381 questionnaire were returned and used for the analysis representing 76% response rate. Data were analyzed using both descriptive and inferential statistics. Findings indicate that, the physical work environment is an important factor in determining the job performance of academic staff with R Value of 58.6%, adjusted R² of .342 and a beta of 58.6% at a significant value of 0.000<0.05. This result indicates a significant positive effect of physical work environment (PWE) on performance of academic staff. On the psychological work environment, a very strong relationship exist between it and job performance of academic staff, as evidenced by the R value of 96.9% and significant value of 0.000<0.05. The study therefore concluded among others that, both physical and psychological work environment contribute significantly to improving performance of academic staff of public universities in North Central, Nigeria. It was recommended that, both physical and psychological environment be prioritized in the management of public universities in North Central Nigeria to directly address the declining academic standards and enhance their rankings among world-class Universities.

Keywords: Academic Staff, Performance, Public University, Work Environment

INTRODUCTION

Performance of employees has its great importance both for organizations and the individual workers involved. Lecturers’ performance in any university is as crucial as the pillars of buildings which stand the whole of it. University performance is primarily determined by academic staff activities such as academic, research and publication, conference, innovation and community service (Abdulkareem, Yusuf & Ogbudinkpa, 2017). Lecturers who are regarded as nation builders and always given a great position in educated and dignified societies have received complain from stakeholders in recent years concerning their performance which many people think is affected largely by their workplace or environment (Shaheen, Sajid, & Batool, 2013).

The work environment comprises of factors influencing academic staff performance that can both be seen and touched (physical work environment) and those attributes that cannot be seen and touch (psychological work environment). Attributes in work environment that this study has categorized among the physical work environment include insufficient or obsolete laboratory equipment, inadequate lecture rooms, poor classroom infrastructure, non-ventilated lecture rooms, and non-conducive office spaces for staff, lack of well-equipped hospital on campus, poor accommodation, lack of basic technological facilities, required to compete in the fast-growing computerized age. The non-physical (psychological) work environment attributes can be seen from quantitative and emotional demands of the work, influence of employee at work, possibilities for development, Degree of Freedom at Work and meaning of work, quality of leadership and social support delay in payment of money for seminars and conferences that are meant to enhance knowledge and skills (Hamid, Ghafoor & Shah, 2012; Odunayo et al., 2020).

For academic staff to perform their job creditably, the constituents of good work environment must be provided in adequate quantity and quality. The academic goals achievement parameter like quality teaching, research publication, community service, is largely dependent on the adequate environment of work (Bello, 2011). The provision of facilities like interactive smartboards, internet facilities, e-library, etc, is very crucial in the attainment of a quality academic programme and staff performance. This study is therefore, primarily conducted because of all the challenges confronting both the academic staff in university education in Nigeria, unsatisfactory working environment (Obateru, 2013; Salau et al., 2018), under-funding, rising absenteeism and brain-drain (Ige, 2014; Okoro, Omeluzor, &Bamidele, 2014) have been recognized as most critical and worrisome (Adeyemi & Ekundayo, 2010; NUC, 2015; Nwagwu, 2015).

Data released in 2010 shows that Nigeria had twenty-seven (27) federal universities and thirty-three (33) State universities. Prior to the establishment of the nine universities by President Jonathan, the country’s academic staff numbered 99,464, consisting of 27,394 academic staff and 72,070 non-teaching staff. According to Obasi (2007), the internal driving forces of private universities include the inability of public universities to cope with the increase in admission demands; the inability of governments to finance expansion; the concomitant lowering of standards in public universities; frequent closure and unstable academic schedule due to staff and student unrest. The external driving forces are rooted in prevailing neoliberal economic policies, globalization, and the information and communication technology (ICT) revolution, all of which have influenced higher education around the world.

The overall essence of this study is that, it will focus on the work environment aspects of university education which is important for National development. The policy makers and administrator in the educational sector will also benefit from the findings of this as this study will further enrich the provisions of the legal framework regulating the academic staff performance in terms of scientific research and innovation, teaching and supervision, and consultancy.

The reason for declining ranking of the Nigeria universities global ranking is a cause for concern and one that needs assessment. Unfortunately, today, in the global ranking of universities, Nigerian universities are not progressing admirably and are not known to have been. None of the 170 public and private universities in Nigeria were among the best 1,000 universities on the planet regardless of making a few forward leap and research grants. Sadiku (2017) discussed physical facilities of Nigerian Universities as being over-stretched and decaying. Oyewole, Arogundade and Sadiku (2019) also asserted that, even when the appropriate university programmes are in place, if the necessary resources are not there, the academic staff cannot perform. The devaluation of work ethics in universities is no longer news as many unethical issues like indiscipline, sexual harassment; extortion and bribery have been reported as seen and read in both traditional and social media. Empirical studies such as; Bamiro and Adedeji, (2010), Aiyedun, Aiyedun & Ogunode, (2021) have alluded to the assertion that bad work environment has limited the ability of the academic staff of the Nigerian universities to effectively and efficiently perform their duties, particularly the traditional roles of academic and research.

To the best of the researcher’s knowledge, the aforementioned concerns have not been addressed holistically by any previous empirical study. Partly, Odunayo et al., (2020) looked at work environment and staff retention, Also, Oyewole, et al., (2019) investigated the relationship between work environment and provision of instructional facilities on academic staff in South-West Nigeria while Michael and Stephen (2019) looked at work environment (power supply) and job performance in both public and private universities in Nigeria.   It is on these backdrops and study gap between those extant studies and what the present study intends that the researcher seeks to evaluate the influence of work environment on performance of academic staff in public Universities in North Central, Nigeria.

The broad objective of this study is to evaluate the effect of work environment on performance of academic staff in public universities in North Central, Nigeria. The specific objectives of the study are to:

1. Evaluate the effect of physical work environment on performance of academic staff in public Universities in North-Central, Nigeria
2. Determine the effect of psychological work environment on performance of academic staff in public Universities in North-Central, Nigeria

The following null research hypotheses are formulated in this study.

H0₁: Physical work environment has no significant effect on performance of academic staff in public Universities in North-Central, Nigeria

H0₂: Psychological work environment has no significant effect on performance of academic staff in public Universities in North-Central, Nigeria

LITERATURE REVIEW

Work Environment

The work environment can be described as the space and forces surrounding the work place of people. Work environment seems to have both positive and negative effects on the psychological and welfare of employees. Effective work environment encourages the happier employee with their job that ultimately influence the growth of an organization as well as growth of an economic. According to Anandini (2019), good working environment make employees feel comfortable at work. The creation of a good product or service will not be carried out effectively if it is not supported by a satisfactory work environment in an organization. This is supported by research conducted by Sedarmayanti (2009) and Wibawa and Indrawati (2014), who state that the work environment has a positive and significant impact on employee performance.

According to Ruchi and Surinder (2014), work environment may be divided into three broad components namely Physical environment, Psychological and social. While the physical environment is made up of ventilation and temperature, infrastructure and interior, amenities, the psychological environment comprises of fatigue, boredom, monotony, attitude and behaviour of supervisor and colleagues and the social environment is simply made of clusters of people working together and their behaviour. This study has further focuses on both physical environment and psychological environment as categorized by (Ruchi & Surinder, 2014).

Physical Work Environment

Akporehe (2011), posited that the physical environment includes infrastructural facilities such as school building, laboratories, libraries, staff offices, etc. when the conditions are appropriate, it has a positive influence on attitude to the job; but when absent, morale and commitment is low. Noah and Steve (2012) established that to manage the work environment effectively, it entails making it attractive, comfortable and motivating to students and employees to give them a sense of pride and purpose in what they do. Hence, the physical environment is an important determining factor in motivating staff for improved productivity. According to Akporehe (2011), the physical challenges facing universities today are crumbling infrastructure, sprawling campuses, lack of funding, poor lighting, poorly planned classrooms. In the same vein,

Psychological Work Environment

The psychosocial work environment refers to the set of work conditions under which employees perform their activities in organizations (ILO, 1986). Psychological working environment is a term used for the work part that deals with the nature and conditions under which the work is performed. The components of this environment are important to be identified and managed because they impact on the experience of health and wellbeing of employees. As such, traditionally, the psychosocial context at work has been described in terms of stressful conditions, also known as psychosocial risks, that have the potential to impair employee mental health (Gonzalez-Mule and Kim, 2019).

Kukiqi (2017), proposed that a psychological work environment can be established if job needs are taken into account when constructing the work system. The psychological work environment includes those aspects of the workplace that are significant for workers’ behaviour. Emotions, moods, psychological symptoms, and emotional disturbances are regarded to be influenced by behaviours. Attitudes, beliefs, decision-making, and behaviours such as effectiveness, absence, and motivation are all examples of knowledge. This is the case of, for example, role ambiguity, time pressure, and workload (Karasek, 1979).

Work Environment and Job Performance

The work environment is considered the situation in the universities in which the main teaching and research functions are carried out. Sadiku (2017), discussed the physical structures of Nigerian universities as excessive and decomposed. It is not enough for these physical resources available in universities, but they must be of good quality before significant work can be carried out by the available human resource. This implies that the quality of academic programmes is adversely affected. According to Okebukola (2002) and Ajayi (2007), effective teaching and learning processes cannot be guaranteed with inadequate instructional materials.

Oyedeji (2012) also, stated that there is a close significant relationship between the infrastructural development and goals achievement variables of the tertiary institutions like; research publications, students’ academic performance, lecturers job performance, school discipline, and community services. To support this exploration, Bello (2011) also concluded that infrastructural facilities are crucial for students’ academic performance and lecturers’ job effectiveness. Oyedeji (2012) stated that the adequacy of the instructional facilities provided in the schools is indicators of measuring the quality and standard of education. According to him, poor and inadequate educational institutions have a significant negative impact on the academic performance.  All these aforementioned are pointers to the positive influence of physical work environment on academic staff performance in universities.

Theoretical Review-Theory of Workplace Comfort by Visher (2007)

Most of the workers spend at least 8 hours daily in their life at their workplace. A well designed, furnished with optimum environment comfort office workplace is said that it will bring an achievement at the objectives of the organization and corporate goals to both the employees and clients. The issue arises when the factors of environment comfort influence their cognitive abilities and reducing their work performance. There is possible relationship that exists between the surrounding’s office environment quality and the productivity of the employees (Leaman, 1995).

As in stated by DOSH [2010], most of the employees work comfortably in office at the temperature of between 23°C to 26°C. Humidity level is also taken concerned in order to produce a better environment comfort in an office building. In a situation of lower humidity level, employees will be more uncomfortable from the resultant of dryness in skin as well as the difficulty in breathing from mouth or nose (Sehgal, 2012). As for lighting level, it is a key factor for all the employees to get their job done. Without proper lighting, employees are impossible to finish their tasks comfortably. It is proven that when employees have their ability to control the lighting quality, they create a positive effect in their performance.

Contextual performance is the behaviour which enhance to the overall effectiveness through the physical and psychological aspects in a workplace. It promotes the growth of the organization’s network and does not contribute through the organization’s core technical process. Contextual performance could be the surrounding environment in the office workplace, integration and cooperation with teammates and volunteering to perform any task which is not mainly part of the job (Motowildo, Borman, & Schmit, 1997). The potential of unsuitable environment comfort in an office building will lead to various possible health issues. Ronald et al., (2003) highlighted that when employees are found to suffer from various symptoms such as eye irritation and running nose, dizziness, ease in feeling fatigue, dry skin and difficulty in concentrating over a period of time, it is indirectly reported in reduction of productivity.

Gap in Literature

The studies on work environment situated in universities environment that have addressed the dimensions of the present study is none extant from reviewed studies. Few studies on work environment such as (Michael & Stephen, 2017; Oyewole et al., 2019; Adenipekun et al., 2021; Kwizera et al., 2021; Aboagye et al., 2020; Timothy et al., 2020; Aiyedun et al., 2021)) are from developed and developing countries in America, Europe and Asia (Jayaweera, 2015; Chua et al, 2016; Rashida et al., 2021; Saidi et al., Putri et al., 2019; Shaari et al, 2022). Not much studies to the best of researcher’s knowledge has considered work environment dimensions such as physical environment, psychological environment, social relations, working conditions, and organizational culture as this current study.

METHODOLOGY

Nigeria through the collection of field survey data. The population is 10121 as shown in table 3.1.

The study focused on public Universities in North-Central States, Nigeria. The study used descriptive design. This design was considered suitable because the study comprehensively demonstrates the causal effect of work environment on performance of academic staff of public Universities in North-Central,

Table 3.1: Number of Academic Staff in Public Universities in North Central, Nigeria

Source: Nigerian University System Statistical Digest, 2020

The study adopted Taro Yamane (1967) formula for the sample estimation from the population of 10,121.

The formula for the estimation of the sample is shown below:

n     =  N/(1 + N (e) ² )

Where:

N = total population, n= sample estimate, and e= level of significance.

n     =   10, 121/(  1 + 10, 121(0.05) ²)

n     =     10, 121/ (1 + 10, 121(0.0025))

n     =      10, 121/  26.3025                  = 385

Following the categorization/grouping of the population, the most suitable sampling technique is stratified sampling. This study distributed 501 copies of questionnaire because 30 percent (116) was added to the minimum computed sample size of 385 to take care of non-response bias in line with Isreal (2013) recommendation.

Table 3.2: Sample size of the Study by Cadre Using Proportion

Source: Researcher’s Computation, 2025

Physical work environment is measured using five (5) items scale relevant to university work environment adapted from Naikote & Bakkabulindi (2011). The psychological work environment is measured using the Copenhagen Psychosocial Questionnaire (COPSOQ) adopted from Kristensen, Hannerz, Høgh, & Borg (2005); the COPSOQ contains about 30 scales measuring psychological aspects of work such as quantitative demands, cognitive demands, emotional demands, influence at work, commitment, etc. Academic staff performance is measured by performance measures dimension for lecturers adapted from Anyango (2023); the performance measure has four sub-constructs namely, quality of teaching, research supervision, research writing and publication, and community outreach.

The study employed both descriptive and inferential statistical methods. To test hypothesis one, simple linear regression was used to assess the effect of physical work environment on each dimension of the performance of academic staff in line with the four hypotheses stated below. The level of significance for the hypothesis was 0.05. The hypotheses are as follows:

H_01a:          Physical work environment has no significant effect on quality of teaching of academic staff in public universities in North Central, Nigeria

H_01b:          Physical work environment has no significant effect on research supervision of academic staff in public universities in North Central, Nigeria

H_01c:          Physical work environment has no significant effect on research writing and publication of academic staff in public universities in North Central, Nigeria

H_01d:          Physical work environment has no significant effect on community outreach of academic staff in public universities in North Central, Nigeria

H₀₂:     Psychological work environment has no significant effect on performance of academic staff in public Universities in North-Central, Nigeria

The regression model is given as:

Y= α_{o +} β₁X₁ + β₂X₂ + β₃X₃+ β₄X₄+ β₅X₅+ β₆X₆ + β₇X₇ + β₈X₈+ β₉X₉+ β₁₀X₁₀ +β₁₁X₁₁  +µ………….(3.0)

PERFAS = α_o+ β₁QUANTD + β₂EMOTD + β₃INF + β₄POSS + β₅FREE + β₆MEAN + β₇COMM + β₈PRED + β₉QUALEAD + β₁₀SOCIOPORT + β₁₁FEEDBK + β₁₂SENSECOM +µ……………………….……..

(3.1)

Where, α₀ = constant; β = beta co-efficient; PERFAS = Performance of Academic Staff; QUANTD = Quantitative Demands; EMOTD = Emotional Demands; INF = Influence at Work; POSS = Possibilities for Development; FREE = Degree of Freedom at Work; MEAN = Meaning of Work; COMM = Commitment to the Workplace; PREDICT = Predictability; QUALEAD = Quality of Leadership; SOCIOPORT = Social Support; FEEDBK = Feedback at Work; SENSECOM = Sense of Community.

RESULTS AND DISCUSSION

The response rate is 76% and was good enough for the analysis. This is depicted in Table 4.1.

Table 4.1:       Response Rate

Source: Research Survey (2025)

Distribution of Respondents by Lecturer Cadre

The frequency table below shows the distribution of the respondents based on their cadre.

Table 4.3:       Distribution of Respondents by Lecturer Cadre

Source: Research Survey (2025)

The distribution of the respondents by Lecturer cadre in Table 4.4 showed that the majority of respondents were Lecturer I and below with 182 respondents representing 47.8%. There were 66 Professors representing 17.3%, 51 Readers representing 13.4% and 82 Senior Lecturers representing 21.5%. This implies that those that were ready and available for the survey were junior cadre lecturers.

Distribution of Respondents by Work Experience

The frequency table displays below shows the distribution of the respondents based on their work experience.

Table 4.4:Distribution of Respondents by Work Experience

Source: Research Survey (2025)

The distribution of the respondents by work experience in Table 4.6 showed that the majority of respondents had work experience more than 15 years with 135 respondents representing 35.4%. There were 123 respondents that had experience between 11-15 years representing 32.3%; 92 (24.1%) respondents had 6-10 years’ work experience; while 18 (4.7%) respondents indicated that they have 1-5 years work experience. Incidentally, 13 respondents representing 3.4% did not indicate their work experience.

Distribution of Respondents by University

The frequency table below shows the distribution of the academic staff based on their universities.

Table 4.5: Distribution of Respondents by University

Source: Research Survey (2025)

The distribution of the respondents by university in Table 4.7 showed that the highest respondents from the university is University of Jos (UNIJOS) with 82 respondents representing 21.5%; the next highest is University of Ilorin (UNILORIN) with 58 respondents representing 15.2%; the next highest is Federal University of Technology (FUTMINNA) with 40 respondents representing 10.5%. Kwara State University (KWASU) and Federal University of Agriculture Makurdi (FUAM) had 35 respondents representing 9.2% each. Benue state University (BENSU) had 26 respondent representing 6.8%, while University of Abuja (UNIABUJA), Ibrahim Badamosi Babangida University Lapai (IBBUL) and Nasarawa state University Keffi (NASUK) had 18 respondents representing 4.7% each. Federal University Lokoja (FULO) had 17 respondents representing 4.5% and Prince Abubakar Audu University, Anyigba, Kogi state (PAAUK) had 16 respondents representing 4.2%. The university with the least respondents was Plateau State University, Bokkos (PSUB) with 10 respondents representing 2.6%, followed by Federal University Lafia (FULA) with 8 respondents representing 2.1%. This implies that the lecturers who responded to the survey are well spread across the North Central universities in Nigeria.

Result of Test of Hypotheses

Hypothesis One

There is no significant effect of physical work environment on performance of academic staff in public Universities in North-Central, Nigeria

The effect of two variables, physical work environment and performance of academic staff of public universities was analyzed using simple linear regression. The effect of all the dimensions of physical work environment (PWE) on aggregate job performance of academic staff of public universities in North Central Nigeria. The aggregated four dimensions of job performance of academic staff are (Quality of Teaching (JPT), Research supervision (JPRS), Research writing and publication (JPRWP), Community outreach (JPCO). Physical work environment contains (5) perspectives namely – lighting, telephone facilities, space for meeting with students, space for academic resources, space for private reading and research. Data was obtained from 381 responses.

Table 4.6a: Effect of Physical work Environment on Quality of Teaching 

1. Predictors: (Constant), PWE
2. Dependent Variable: JPQT

The R value of 0.615 is the correlation coefficient, indicating the strength and direction of the relationship between physical work environment and quality of teaching as a performance measure. An R value of 0.615 suggests a moderate positive relationship. R Square value of 0.378 called the coefficient of determination means that 37.8% of the variance in the teaching quality is explained by the physical work environment variables in the model While the adjusted R square of 0.370 is the modified version of R Square that adjusts for the number of predictors in the model. It is slightly lower (0.370) because it accounts for possible overfitting when multiple predictors are used. It can therefore be concluded that, the model is strong in explaining the variation in quality of teaching as shown by the 61.5%. The model is statistically significant at p-value of 0.000 which is less than 0.05 significant level. The physical work environment variables together explain a substantial portion of the variation in the quality of teaching while the F-value (45.597) suggests a strong model fit.

The constant value of 16.590 with p-value of 0.000 is the predicted value of the quality of teaching when all dimensions of physical work environment are zero. It is statistically significant. The lighting Facilities (B = 0.370, p = .126) has a small, positive effect, but it is not statistically significant (p=0.126 > 0.05), meaning it does not strongly predict the quality of teaching. The telephone Facilities (B = 0.632, p = .027) has a significant positive effect (p < 0.05), meaning better telephone facilities are associated with an increase in the quality of teaching. The space for meeting students (B = 0.723, p = .011) has a moderate, positive, and statistically significant effect, meaning it contributes meaningfully to the quality of teaching. The space for academic resources (B = 1.526, p = .000) has the strongest positive effect (Beta = .278), and is highly significant, indicating that more space for academic resources strongly influences the quality of teaching. Finally, space for private reading and research (B = 1.416, p = .000) also has a strong and significant effect, meaning more space for reading and research is an important predictor of quality of teaching. The overall implication of this finding is that, there is a significant effect of physical work environment on quality of teaching and more emphasis should be place on providing conducive space for research and meeting with students in Public Universities in North Central Nigeria.

Table 4.6b:  Effect of Physical Work Environment on Research Supervision

1. Predictors: (Constant), PWE
2. Dependent Variable: JPRS

In the Model Summary section, the R value of 0.513 suggests a moderate positive correlation between the predictors (physical work environment variables, PWE) and the dependent variable (JPRS, likely referring to some aspect of research supervision). The R Square value of 0.263 indicates that about 26.3% of the variance in JPRS can be explained by the physical work environment factors included in this model. The Adjusted R Square value of 0.254 slightly adjusts for the number of predictors in the model and suggests a similar level of explanatory power.

ANOVA table, the F-statistic of 26.817 with a corresponding significance value (Sig.) of 0.000 indicates that the overall model is statistically significant. This means that at least one of the physical work environment predictors has a meaningful relationship with JPRS. Specifically, the F-statistic tests whether the regression model is a good fit for the data, and the low p-value (less than 0.05) provides strong evidence that the predictors, collectively, do contribute significantly to explaining the variation in research supervision. In the Coefficients table, the unstandardized and standardized coefficients for each predictor are provided, offering insight into how each individual variable influences JPRS. The constant value of 15.789 represents the estimated JPRS when all predictors are zero, which is a baseline value for the model. The B values (unstandardized coefficients) reflect the change in the dependent variable for a one-unit change in the predictor variable, holding other variables constant. For example, lighting facilities have a B value of 0.592, indicating that improvements in lighting are associated with a 0.592 increase in JPRS, with a statistically significant p-value of 0.042.

Other predictors, like telephone facilities (B = 0.658, p = 0.056) and space for academic resources (B = 0.730, p = 0.029), also have positive relationships with JPRS, but telephone facilities have a p-value just above the typical significance threshold of 0.05, suggesting a borderline relationship. Notably, the predictors with the strongest relationships to JPRS are space for meeting students (B = 1.140, p = 0.001) and space for private reading and research (B = 1.300, p = 0.001), both showing high B values and very low p-values. These variables appear to be particularly influential in enhancing the research supervision experience. In general, the results suggest that a well-equipped and spacious physical environment, including proper lighting, meeting space, and private research areas, plays a significant role in research supervision outcomes.

Table 4.6c: Effect of Physical Work Environment on Research Writing and Publication

1. Predictors: (Constant), PWE
2. Dependent Variable: JPRWP

The “Model Summary” table reveals that the correlation between the physical work environment (PWE) variables and the dependent variable, Research Writing and Publication (JPRWP), is moderate, with an R value of 0.478. This indicates that there is a positive relationship between the predictors and JPRWP, although it’s not a very strong one. The R Square value of 0.228 means that about 22.8% of the variance in research writing and publication outcomes can be explained by the variables related to the physical work environment. The Adjusted R Square value of 0.218 is a slight adjustment for the number of predictors included in the model, and it shows that the model’s explanatory power remains relatively modest.

In the ANOVA table, the F-statistic of 22.181 and the p-value of 0.000 indicate that the overall model is statistically significant. This result suggests that at least one of the physical work environment predictors significantly contributes to explaining the variation in research writing and publication, making the model a useful tool for understanding these factors. The high F-statistic relative to the residual sum of squares shows that the regression model fits the data well and that the relationship between the predictors and JPRWP is meaningful and not due to random chance.

Looking at the Coefficients table, the unstandardized and standardized coefficients provide valuable insights into the individual contributions of each physical work environment variable. The constant value of 18.159 indicates the baseline level of JPRWP when all predictor variables are set to zero. For the individual predictors, the unstandardized coefficients (B values) show the amount of change in JPRWP for a one-unit change in each predictor, holding other factors constant.

Among the predictors, space for private reading and research (B = .224) has the highest standardized coefficient, meaning that it has the most substantial impact on research writing and publication. The p-value of 0.000 for this variable indicates that this effect is statistically significant, suggesting that having space for private reading and research is strongly associated with better research writing and publication outcomes. Similarly, space for academic resources (B = 0.834, p = 0.013) and space for private reading and research (B = 0.857, p = 0.023) both have positive and significant effects on JPRWP, though their influence is slightly smaller than that of space for meeting students.

On the other hand, lighting facilities (B = 0.567, p = 0.054) and telephone facilities (B = 0.368, p = 0.289) show weaker associations with JPRWP. While lighting facilities have a p-value close to the typical significance threshold (0.05), it is still not quite significant, suggesting a weaker influence compared to the other factors. Telephone facilities, with a p-value of 0.289, have no statistically significant relationship with JPRWP, indicating that this particular variable does not contribute meaningfully to improving research writing and publication outcomes in the context of this study.

In summary, the physical work environment has a notable but moderate impact on research writing and publication, with certain factors like spaces for private reading research areas having a stronger and more statistically significant influence. However, other variables like lighting and telephone facilities play a lesser role in influencing research writing and publication success.

Table 4.6d: Effect of Physical Work Environment on Community Outreach

1. Dependent Variable: JPCO
2. Predictors: (Constant), PWE

The “Model Summary” table for the regression analysis of Physical Work Environment (PWE) on Community Outreach (JPCO) reveals a very strong relationship between the predictors and the dependent variable. The R value of 0.917 indicates a strong positive correlation between the physical work environment and community outreach efforts. This suggests that as the conditions of the physical work environment improve, community outreach is likely to increase as well. The R Square value of 0.840 is particularly high, meaning that 84% of the variance in community outreach can be explained by the physical work environment factors in this model. This is a substantial proportion, highlighting the importance of these factors in shaping community outreach outcomes. Additionally, the Adjusted R Square value of 0.838 accounts for the number of predictors and shows only a slight decrease, reinforcing the model’s strong explanatory power.

In the ANOVA table, the F-statistic of 393.948 with a p-value of 0.000 confirms that the overall model is highly significant. This result indicates that the predictors, as a group, are very effective in explaining variations in community outreach. The very low p-value further solidifies the strength of the model, showing that the physical work environment variables have a significant influence on the outcomes related to community outreach.

The Coefficients table provides a closer look at how each physical work environment factor contributes to community outreach, both in terms of magnitude and statistical significance. The constant value of 8.039 represents the baseline level of community outreach when all predictors are set to zero, offering a reference point for the regression model. Among the predictors, space for academic resources (B = 2.089, p = 0.000) has the largest unstandardized coefficient, meaning that improvements in access to academic resources are associated with a significant increase in community outreach. With a p-value of 0.000, this variable is extremely significant, and its strong positive effect suggests that greater availability of resources directly supports better community engagement and outreach activities.

Other variables such as space for meeting students (B = 1.447, p = 0.000), lighting facilities (B = 1.189, p = 0.000), and space for private reading and research (B = 1.487, p = 0.000) also exhibit strong positive relationships with community outreach. These predictors all have p-values of 0.000, making them highly significant. The relatively high Beta values (ranging from 0.223 for lighting facilities to 0.380 for space for academic resources) indicate that these factors have varying but substantial impacts on community outreach. For instance, space for meeting students (Beta = 0.263) and space for private reading and research (Beta = 0.251) show that physical spaces conducive to collaboration and individual work are key drivers in enhancing outreach. Interestingly, telephone facilities (B = 0.918, p = 0.000) also contribute positively to community outreach, with a moderately high unstandardized coefficient, indicating that better communication facilities are also crucial. The Beta value of 0.153 suggests that while the effect is positive, it is not as strong as the impact of physical space or academic resources, though it remains highly significant.

Table 4.6e: Summary of Physical Work Environment on Job Performance of Academic Staff

1. Dependent Variable: JPAS
2. Predictors: (Constant), PWE

The R value of 0.586 indicates a moderate positive correlation between the physical work environment and job performance. This suggests that the quality of the physical work environment influences the job performance of academic staff, though the relationship is not overwhelmingly strong. The R Square value of 0.344 means that approximately 34.4% of the variance in job performance can be explained by the physical work environment factors. While this is a moderate proportion, it suggests that there are other factors influencing job performance that are not captured in the model. The Adjusted R Square value of 0.342 takes into account the number of predictors and shows that the model remains relatively robust despite the inclusion of just one predictor (PWE). The Standard Error of the Estimate is 15.85883, which represents the average deviation of the observed job performance values from the predicted values, and indicates a moderate level of variability.

In the ANOVA table, the F-statistic of 198.604, accompanied by a p-value of 0.000, indicates that the regression model is highly significant. This suggests that the physical work environment is a meaningful predictor of academic staff job performance. Given the high F-statistic and the low p-value, we can confidently conclude that the model is a strong fit for the data, and the physical work environment does indeed have a significant impact on job performance. The Coefficients table provides detailed information about the impact of the physical work environment (PWE) on job performance (JPAS).

The unstandardized coefficient for PWE is 3.474, meaning that for each one-unit increase in the physical work environment (as measured by the specific factors included in the model), job performance is expected to increase by 3.474 units. This positive relationship indicates that improving the physical work environment is associated with better job performance among academic staff. Furthermore, the standardized coefficient (Beta) of 0.586 tells us that PWE has a moderate and significant influence on job performance, making it a strong predictor of JPAS. The t-value of 14.093 is quite high, and the p-value of 0.000 indicates that the relationship is statistically significant at conventional levels (e.g., 0.05 or lower).

In summary, the results from this regression analysis suggest that the physical work environment is an important factor in determining the job performance of academic staff. Improvements in PWE are likely to lead to noticeable improvements in their job performance, and this relationship is both statistically and practically significant. The moderate R-square value indicates that while PWE is an important contributor to job performance, other factors are also at play in determining academic staff performance.

Hypothesis Two

Psychological work environment has no significant effect on performance of academic staff in public Universities in North-Central, Nigeria

To test this hypothesis, the respondents’ scores on psychological work environment and performance of academic staff were computed and subjected to multiple regression analysis.

Table 4.7: Effect of Psychological work environment on performance of academic staff

Predictors: (Constant), PSWEFW, PSWEQD, PSWEPD, PSWECW, PSWEIW, PSWESS, PSWEP, PSWEDF, PSWEQL, PSWEED, PSWEMW

Dependent Variable: JP

The Model Summary table indicates a very strong correlation between the psychological work environment factors and job performance, as evidenced by the R value of 0.969. This suggests that there is a very strong positive relationship between the two variables, meaning that changes in the psychological work environment are likely to result in significant changes in academic staff job performance. The R Square value of 0.939 reveals that approximately 93.9% of the variance in job performance can be explained by the psychological work environment variables included in the model. This is an exceptionally high proportion, highlighting the significant influence of these factors on academic staff performance. The Adjusted R Square value of 0.937 is very close to the R-square value, suggesting that the model is well-specified and does not overstate the explanatory power of the predictors.

The ANOVA table provides evidence that the regression model as a whole is statistically significant. The F-statistic of 516.421 with a p-value of 0.000 confirms that the predictors in the model collectively have a significant effect on job performance. This is a strong indication that the psychological work environment is an important determinant of academic staff performance, and the low p-value suggests that the model is unlikely to have occurred by chance. The Coefficients table details the contribution of each individual predictor to job performance.

In terms of individual predictors, Quantitative Demands (B = 3.982, p = 0.000), Emotional Demands (B = 3.926, p = 0.000), and Influence at Work (B = 3.721, p = 0.000) all show very strong positive relationships with job performance. These variables have Beta values of 0.310, 0.265, and 0.249, respectively, suggesting that they each contribute significantly to improvements in academic staff performance. Predictability (B = 2.927, p = 0.000) and Social Support (B = 1.894, p = 0.000) also have strong positive effects on job performance, with Beta values of 0.190 and 0.129, respectively. Interestingly, Possibilities for Development (B = -0.516, p = 0.040) shows a negative relationship with job performance, implying that a lack of development opportunities might negatively affect job performance. Although its Beta value is small (-0.034), the significant p-value indicates that this effect should not be overlooked.

Some factors have weaker relationships with job performance. Commitment to the Workplace (B = 0.492, p = 0.088) and Quality of Leadership (B = 0.230, p = 0.372) have p-values greater than 0.05, suggesting that they do not significantly contribute to explaining variations in academic staff job performance within the context of this model. The lack of significance for Quality of Leadership might suggest that other aspects of the work environment, such as autonomy, support, and predictability, are more important for influencing performance. Degree of Freedom at Work (B = 0.819, p = 0.002) and Meaning of Work (B = 0.821, p = 0.007) both show positive and significant relationships with job performance. These factors have Beta values of 0.057 and 0.052, respectively, indicating that they are important but to a lesser extent compared to some other factors.

DISCUSSION OF FINDINGS

The effect of physical work environment on performance, the results from the tables indicate a significant positive relationship between the physical work environment (PWE) and academic staff performance. These findings align with the conclusions drawn by studies such as Chua et al., (2016) & Aboagye et al., (2021), which argue that an improved physical work environment encompassing factors like space, lighting, and availability of resources has a notable effect on productivity and performance. Similarly, research by Katabaro & Yan (2019) and Aboagye et al., (2021) supports the idea that physical space and resources in academic settings can facilitate better engagement and performance from staff.

However, this finding contrasts with some studies, such as that of Al-Omar & Okasheh (2017) and Oyewole et al., (2019), which found no significant impact of the physical work environment on academic performance. These conflicting findings may stem from differences in the scope of work environments examined, with some focusing on broader organizational structures rather than individual physical factors.

Secondly, the effect of psychological work environment analysis on performance of academic staff in public universities in north central Nigeria including elements such as emotional demands, influence at work, and social support, shows that this variable significantly influences academic performance. This is supported by Shaari et al., (2022), who found a robust link between a supportive psychological work environment and staff performance in higher education. Similarly, the research by Saidi et al., (2019) supports the importance of psychological factors such as stress management and social support in enhancing academic staff effectiveness.

On the contrary, some studies like those of Al-Omar & Okasheh (2017) argue that psychological work environment factors do not always have a significant effect on performance, particularly when other external factors (e.g., work ethics or organizational culture) are not adequately managed. Thus, while the findings in this study are compelling, the lack of consensus in the literature indicates that the psychological work environment’s influence on performance may be contingent on other contextual factors.

CONCLUSION

Based on the results of the tests of hypotheses from the data collected and the interpretation of results, the study concluded that some work environment dimensions (physical work environment and psychological work environment) are important considerations that can affect performance of academic staff in public universities in North central, Nigeria.

The study concluded that provision of space for academic resource and spaces for meeting with student in terms of classroom facilities are important factors that affect performance of academic staff of public universities. Also, the study concluded that quantitative demand of the job and high degree of freedom are important psychological factors that influence performance of academic staff in public universities in North Central Nigeria

RECOMMENDATIONS

Consequent on the study results, findings and conclusion, the study made the following recommendations that could best help university management and policy makers on the best approaches to improving workplace environment and also influence performance of academic staff in public universities not only in North Central, Nigeria but in other geo-political regions of the country and beyond.

1. The main task of academic staff of universities is teaching and research. Government should prioritize these factors in the provision of infrastructures and amenities in universities and other institutions of higher learning. The provision of space for academic resource and spaces for meeting with student in terms of classroom facilities are important factors that affect performance of academic staff of public universities. Academic resources in the 21^st century that can enhance research should include technology and internet based infrastructures.
2. University authorizes should ensure a high level of freedom for academic staff to explore and take initiative for their work and tasks as the study discovered that quantitative demand of the job and high degree of freedom are important psychological factors that influence performance of academic staff in public universities in North Central Nigeria

Contribution to Knowledge

1. The study has empirically established that the main task of an academic staff of a university is teaching and research as the findings in relationship between physical work environment and performance found that space for teaching and space for resource and research were the significant factors that affects performance of lecturers.
2. This study has empirically demonstrated the contribution of individual dimension of work environment on performance of academic staff in University system which was found lacking from the previous studies reviewed.

REFERENCES

1. Abdulkareem, R. L., Yusuf, H. A., & Ogbudinkpa, C. I. (2017). Relationship between performance appraisal criteria and lecturers‟ productivity in Universities in South-West Geo-Political Zone, Nigeria. Asia Pacific Journal of Education, Arts and Sciences, 4(2), 79-86.
2. Adeyemi, T. O., & Ekundayo, H. T. (2010). Managing students’ crisis in tertiary institutions in Nigeria. Journal of Research in National Development, 8(1), 102–114.
3. Aiyedun, E. A., Aiyedun, T. G., & Ogunode, N. J. (2021). Factors hindering the progress of Nigerian Universities in the Global ranking of universities. International Journal of Development and Public Policy, 1(5), 183-187.
4. Ajayi, I. A. (2007). Issues in School Management, Lagos: Bolabay Publications Gonzalez-Mule, E., and Kim, M. (2019). A Meta-analytic test of additive and multiplicative models of stress. Acad. Manag. Proc. 2019:18416. doi: 10.5465/ ambpp.2019.18416
5. Akporehe, D. A. (2011). The impact of environment on productivity in secondary schools. African Journal of Education and Technology, 1(1), 116-122.
6. Al-Omari, K., & Okasheh, H. (2017). The Influence of Work Environment on Job Performance: A Case Study of Engineering Company in Jordan. International Journal of Applied Engineering Research, 12(24), 15544-15550.
7. Anandini, D. (2018). Pengaruh Lingkungan Kerja dan Stres Kerja Terhadap Kinerja Karyawan PT. Duta Wirya (Doctoral dissertation, Universitas Muhammadiyah Surakarta).
8. Bamiro, O. A., & Adedeji, S. O. (2010). Sustainable financing of higher education in Nigeria. Ibadan: Ibadan University Press.
9. Bello, T. O. (2011). Public-Private Partnership, Infrastructural Development and Academic Goals Achievement in Nigerian Universities. A Seminar paper presented at University of Ilorin.
10. Chua, S. J. L., Ali, A. S., & Lim, M. E. L. (2016). Physical environment comfort impacts on office employee’s performance. MATEC Web of Conferences 66, 00124, 1 – 4.
11. Ige, A. M. (2014). Towards the stemming of the tide of strikes in tertiary institutions in Nigeria: Stakeholders’ roles and responsibilities. European Journal of Academic Essays, 1(7), 18–26.
12. ILO (1986). Psychosocial Factors at Work: Recognition and Control: Occupational Safety and Health Series. Geneva: International Labor Office
13. Jayaweera, T. (2015). Impact of work environmental factors on job performance, mediating role of work motivation: A Study of hotel sector in England. International Journal of Business and Management, 10(3), 271 – 278.
14. Karasek, R. A. (1979). Job demands, job decision latitude, and mental strain – Implications for job redesign. Admin. Sci. Q. 24, 285–308. doi: 10.2307/2392498.
15. Kristensen T. S., Hannerz, H., Høgh, A., & Borg, V. (2005). The Copenhagen Psychosocial Questionnaire—a tool for the assessment and improvement of the psychosocial work environment. Scand J Work Environ Health, 31(6), 438 – 449.
16. Kukiqi, E. (2017). Environmental conditions and work satisfaction in institutions in the Republic of Kosovo.
17. Leaman, A., Raw, G., & Garston, W. (1995). Further Findings from the Office Environment Survey: Productivity. In 5th International Conference on Indoor Air Quality and Climate.
18. Michael, F. L., Saidi, N. S. A., Sumilan, H., Lim, S. L. O., Jonathan, V., Hamidi, H., & Ahma, A. I. A. (2019). The relationship between working environment and employee performance. Journal of Cognitive Sciences and Human Development. 5(2), 14 – 22.
19. Motowildo, S. J., Borman, W. C., & Schmit, M. J. (1997). A Theory of Individual Differences in Task and Contextual Performance. Human Performance, 10(2): 71-83.
20. Naikote, B., & Bakkabulindi, F. E. K. (2011). Work environment and perception of institutional policies as correlates of lecturers’ productivity in Uganda Christian University. Makerere Journal of Higher Education, 3(1), 1-12.
21. Noah, Y., & Steve, M. (2012). Work environment and job attitude among employees in a Nigerian work organization. Journal of Sustainable Society, 1(2), 36–43.
22. NUC. (2015). Retrieved May 22, 2016 from http://www.nuc.edu. ng/pages/universities.asp?ty=3 (Accessed 2022)
23. NUC. (2019). Retrieved June 5, 2019 from https://www.thenigerianvoice. com/news/278758/full-list-of-ranking-of-nigerianuniversities-by-nuc.html (Accessed 2022).
24. Nwagwu, N. A. (2015). One hundred years of Education in Nigeria: Developmental challenges, achievements and prospects. African Journal of Studies in Education, 10(1), 41–68.
25. Obasi, I. N. (2007). Analysis of the emergence and development of private universities in Nigeria (1999-2006). Journal of Higher Education in Africa (JHEA/RESA), 5(2/3), 39- 66.
26. Obateru, T. (2013, December 1). ASUU strike: Our losses, frustrations, by students, parents, businessmen. Vanguard. https:// www.vanguardngr.com/2013/12/asuu-strike-losses-frustrations- students-parents-businessmen.
27. Odunayo, S., Rowland, W., Adewale, O., Anthonia, A., Hezekiah, F., Maxwell, O., & Peyemi, O. (2020).The impact of workplace environments on retention outcomes of public Universities in Southern Nigeria. SAGE Open, 1-16.
28. Okebukola, P. A. (2002). The State of University Education in Nigeria. Abuja: National Universities Commission.
29. Okoro, C. C., Omeluzor, S. U., & Bamidele, I. A. (2014). Effect of brain drain (human capital flight) of librarians on service delivery in some selected Nigerian universities. SAGE Open, 4, 1–11.
30. Oyedeji, N. B. (2012). Principles and Practices of Educational Management. Lagos: ARAS Press.
31. Oyewole, B. K., Arogundade, K. K. & Sadiku, B. O. (2019). Work Environment and Provision of Instructional Facilities as Correlates of Academic Staff Job Performance in Nigerian Universities. Journal of Education Research and Rural Community Development, 1(1), 46-57.
32. Putri, E. M., Ekowati, V. M., Supriyanto, A. S., Mukaffi, Z. (2019). The effect of work environment on employee performance through work discipline. International Journal of Research Grant Hallayah, 7(4), 132 – 140.
33. Rashida, M. R., Normy R. A., & Nurul A. M. Y. (2021). Perceived high performance work systems (HPWS) and employee service performance in the Automotive Industry. Asian Journal of Business and Accounting: 14(2), 231-254
34. Ronald, C.K., Catherine, B., Arne, B., Patricia, B., Paul, D.C., David, M., Nicolaas, P.P., Gregory, S., Paul, S., Tevfik, B.U., & Phillip, W. (2003). The World Health Organization Health and Work Performance Questionnaire (HPQ). American College of Occupational and Environmental Medicine. 45, 156 – 174.
35. Ruchi, J., & Surinder, K. (2014). Impact of work environment on job satisfaction. International Journal of scientific and research publications, 4(1).
36. Sadiku, B. O. (2017). University Funding and Utilization as Correlates of Academic Staff Job Performance in South-west, Nigeria. Unpublished Ph.D Dissertation, Ekiti State University, Ado-Ekiti, Nigeria.
37. Salau, O. P., Worlu, R. E. K., Osibanjo, A. O., Oludayo, O. A., & Falola, H. O. (2018). Survey data on work environments and productivity of academic staff of selected public universities in Nigeria. Data in Brief, 19, 1912–1917.
38. Sedarmayanti, (2009). Sumber Daya Manusia dan Productivities Kerja. Bandung: Mandar Maju
39. Sehgal, S. (2012). Relationship between Work Environment and Productivity. International Journal of Engineering Research and Applications (IJERA). 2(4), 1992 – 1995.
40. Shaari, R., Sarip, A., & Ramadhinda, S. (2022). A study of the influence of physical work environments on employee performance. International Journal of Academic Research in Business and Social Sciences, 12(12), 1734 – 1742.
41. Shaheen, I., Sajid, M. A., & Batool, Q. (2013). Factors affecting the motivation of academic staff (a case study of University College Kotli, UAJ&K). International Journal of Business and Management Invention, 2(1), 105-112.
42. Wibawa, I. G. A. K. A., & Indrawati, A. D. (2014). Pengaruh Kompensasi dan Lingkungan Kerja Terhadap Kinerja Karyawan. E-Journal Manajemen, 4(1), 246-254.