Browse

Journals By Subject

Life Sciences, Agriculture & Food
Chemistry
Medicine & Health
Materials Science
Mathematics & Physics
Electrical & Computer Science
Earth, Energy & Environment
Architecture & Civil Engineering
Education
Economics & Management
Humanities & Social Sciences
Multidisciplinary

Books

Publish Conference Abstract Books
Upcoming Conference Abstract Books
Published Conference Abstract Books
Publish Your Books
Upcoming Books
Published Books

Proceedings

Events

Events
Five Types of Conference Publications

Join

Join as Editor-in-Chief
Join as Senior Area Editor
Join as Senior Associate Editor
Join as Editorial Board Member
Become a Reviewer

Information

For Authors
For Reviewers
For Editors
For Conference Organizers
For Librarians
Article Processing Charges
Special Issue Guidelines
Editorial Process
Manuscript Transfers
Peer Review at SciencePG
Open Access
Copyright and License
Ethical Guidelines
Submit an Article
Research Article | | Peer-Reviewed

Examining the Maintenance Culture of Public Sector Property and Its Impact on Service Delivery: A PLS-SEM Approach

Kwabena Ampong*,  George Akasum Akayuri,  Samuel Apau,  Jonathan Abaitey,  Ellen Awotwi,  Emmanuel Ebo Ocran
Published in Journal of Public Policy and Administration (Volume 9, Issue 1)
Received: 7 January 2025     Accepted: 23 January 2025     Published: 11 February 2025
Views:       Downloads:
Download PDF
Abstract

The study innovatively investigates the relationship between maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery in the public sector. The study uncovers the interplay between these factors and their impact on service delivery outcomes. To achieve such outcomes, we utilize a structured questionnaire to assess variables related to maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery. Data were collected from a sample of public sector employees and stakeholders, which was then subjected to rigorous statistical analysis. The research employs a range of statistical techniques to investigate correlations, direct and mediating effects, and construct reliability. Inarguably, the use of a survey instrument and statistical analysis allowed for the quantitative assessment of the research hypotheses. The findings reveal significant correlations between maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery. It identifies employee engagement, public perception and trust as mediating variables that play crucial roles in influencing service delivery outcomes. The findings provide distinctive insights into the complex dynamics of service delivery in the public sector, emphasizing the importance of resource allocation, employee engagement, and public relations efforts. Our research contributes to the field by examining the relationships among maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery in the specific context of the public sector. It introduces the mediating roles of employee engagement and public perception and trust, adding a novel dimension to our understanding of service delivery dynamics. The study's originality lies in its empirical investigation of these complex interactions, shedding light on the factors that influence service delivery outcomes in public organizations.

Published in Journal of Public Policy and Administration (Volume 9, Issue 1)
DOI 10.11648/j.jppa.20250901.13
Page(s) 19-36
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2025. Published by Science Publishing Group
Previous article
Keywords

Maintenance Culture, Resource Allocation, Employee Engagement, Public Perception, Trust, Service Delivery, Public Sector

1. Introduction
Maintenance culture, resource allocation, and service delivery are critical elements within public sector organizations that profoundly impact the quality and effectiveness of public services
[19-23]
. This background section draws upon empirical literature to provide a comprehensive understanding of the relationship between maintenance culture, resource allocation, and their collective influence on service delivery within the context of public sector organizations. Maintenance culture is a foundational aspect of public sector management
[1, 42]
. A strong maintenance culture ensures that public sector properties and assets are well-preserved, operational, and safe for use. When public sector organizations prioritize maintenance, they are better equipped to provide reliable and uninterrupted services to the public. The study by
[34]
underscores that poor infrastructure management and maintenance can lead to service protests, service interruptions, and a loss of public trust in municipal administrations. This highlights the critical role of maintenance culture in ensuring effective service delivery. Resource allocation is another key factor that affects both maintenance culture and service delivery. The study by
[48-56]
emphasizes that adequate resource allocation is essential for the capacity of health facilities to prevent and control Non-Communicable Diseases (NCDs) and provide quality primary healthcare services. Similar resource allocation challenges are observed in infrastructure management and public buildings
[10, 47]
. Inadequate resource allocation can hinder maintenance efforts, leading to deteriorating infrastructure and compromised service delivery. Empirical evidence highlights the interconnectedness of maintenance culture and resource allocation in determining the quality-of-service delivery in public sector organizations. For instance,
[33]
demonstrates that poor maintenance practices increase budgets for maintenance faults, potentially diverting resources from essential service delivery initiatives. Moreover, as identified by
[64]
, value-based maintenance practices prioritize resource allocation to critical areas, enhancing service delivery by ensuring that resources are efficiently utilized where they are most needed. Furthermore, the study by
[57]
defines service delivery as the extent to which services meet or exceed public expectations. A well-established maintenance culture and adequate resource allocation are fundamental to meeting these expectations and ensuring that services not only meet but exceed the public's needs
[43-46]
.
In public sector organizations, the effective provision of services to the public is a fundamental goal
[2-9]
. However, achieving this goal is contingent upon the interplay of various factors, with maintenance culture and resource allocation emerging as critical determinants of service delivery quality. While the empirical literature offers valuable insights into these factors individually, there remains a gap in understanding the complex relationship between maintenance culture, resource allocation, and their combined impact on service delivery within public sector organizations. Existing research has shed light on the significance of maintenance culture in ensuring the proper upkeep of public assets
[1, 42]
. Additionally, studies have emphasized the importance of resource allocation, particularly in healthcare and infrastructure management
[47, 52]
. However, there is limited empirical research that comprehensively explores how these two factors intersect and jointly influence service delivery outcomes.
Despite individual studies addressing maintenance culture and resource allocation separately, there is a dearth of research that examines how these two factors interact within public sector organizations
[24-29, 52]
. The extent to which a robust maintenance culture affects resource allocation decisions and vice versa remains relatively unexplored. While qualitative insights are available on the importance of maintenance culture and resource allocation, there is a lack of quantitative analyses that provide empirical evidence of their impact on service delivery
[11-16]
. Quantitative assessments are essential to establish the magnitude and significance of these relationships. The existing literature primarily focuses on specific sectors (e.g., healthcare, infrastructure). However, the extent to which the relationship between maintenance culture, resource allocation, and service delivery varies across different public sector contexts remains under-examined. Variations may exist due to sector-specific nuances and varying degrees of public-private partnerships. This research is motivated by the imperative to enhance service delivery in public sector organizations. Inadequate service delivery can have far-reaching consequences, including public dissatisfaction, reduced public trust, and negative socioeconomic impacts
[34, 57]
. By addressing the identified research gaps, this study aims to contribute to the existing body of knowledge. This research seeks to fill a crucial gap in the literature by examining the intricate relationship between maintenance culture, resource allocation, and their combined influence on service delivery in public sector organizations. The motivation behind this study lies in the potential to contribute to more effective public service delivery, improved public value, and enhanced public sector performance.
2. Literature Review
2.1. Theoretical Background
One theory that underpins the study on the relationship between maintenance culture, resource allocation, and service delivery in public sector organizations is the "Resource Dependency Theory" (RDT). Resource Dependency Theory, originally formulated by
[66]
, is a theoretical framework that explains how organizations depend on external resources, such as funding, information, and support, to achieve their objectives. In the context of this study, RDT offers valuable insights into how public sector organizations rely on resource allocation and maintenance culture to ensure effective service delivery. Resource Dependency Theory posits that organizations depend on resources from their external environment to survive and thrive. In the case of public sector organizations, securing financial resources, personnel, and infrastructure is critical for delivering services to the public
[66]
. Adequate resource allocation is essential to address the dependencies associated with service provision, ensuring that public sector organizations have the necessary means to fulfil their missions. Maintenance culture within public sector organizations can be seen as a mechanism to mitigate dependency risks. According to RDT, organizations adopt strategies and mechanisms to reduce their vulnerability to external resource constraints
[66]
. In this context, a strong maintenance culture can be considered a strategic mechanism that helps public sector organizations maintain their assets, infrastructure, and service delivery capacity, thereby reducing their dependency on external interventions or costly repairs. Resource Dependency Theory also emphasizes the importance of managing dependencies effectively to enhance organizational performance. In the context of this study, effective management of dependencies related to resource allocation and maintenance culture can lead to improved service delivery outcomes. Public sector organizations that proactively maintain their assets and allocate resources efficiently are better positioned to meet the expectations of the public, minimize disruptions in service delivery, and enhance their overall performance
[66]
. The underpinning theory of Resource Dependency Theory (RDT) is cited in this study to provide a theoretical framework for understanding how maintenance culture and resource allocation interact and influence service delivery within public sector organizations. RDT helps explain why these organizations prioritize maintenance culture and resource allocation
[58-63]
, as they seek to manage external dependencies and ensure the continuity of service delivery. By integrating Resource Dependency Theory into the study's conceptual framework, researchers can gain a deeper understanding of the strategic motivations behind maintenance culture and resource allocation decisions within public sector organizations and their direct implications for service delivery outcomes.
2.2. Conceptual Framework and Hypotheses Development
The conceptual framework for the study on the relationship between maintenance culture, resource allocation, and service delivery in public sector organizations is guided by a comprehensive understanding of the complex interplay among these key variables. Drawing from empirical literature and underpinned by Resource Dependency Theory (RDT) as discussed earlier, this framework provides a structured approach to examining the dynamics of maintenance culture, resource allocation, and their collective impact on service delivery. At its core, the conceptual framework recognizes maintenance culture and resource allocation as fundamental determinants of service delivery outcomes. Maintenance culture, as highlighted
[1, 42]
, is viewed as a set of organizational behaviors, practices, and attitudes that govern the upkeep of public sector assets and infrastructure. Resource allocation, on the other hand, refers to the deliberate allocation of financial, human, and material resources to support maintenance efforts and overall service delivery, as emphasized by
[47, 52]
. The framework posits that maintenance culture and resource allocation are interconnected, with maintenance culture influencing resource allocation decisions and vice versa. A strong maintenance culture can be seen as a mechanism for mitigating dependency risks associated with resource allocation, aligning with the principles of Resource Dependency Theory. In this regard, organizations with a robust maintenance culture may be better equipped to optimize the allocation of resources, ensuring that they are directed toward critical maintenance activities that support service delivery.
Service delivery outcomes, as measured by performance indicators, public satisfaction, and service quality, are positioned at the center of the framework
[30-32]
. The framework acknowledges that the joint influence of maintenance culture and resource allocation has a direct and significant impact on these service delivery outcomes. Public sector organizations with a strong maintenance culture and effective resource allocation strategies are more likely to achieve superior service delivery results, aligning with the empirical evidence presented in the literature
[33-41, 64]
. Additionally, the framework recognizes contextual variations across different public sector domains, such as healthcare, infrastructure, and cultural heritage, as highlighted in the literature
[20, 23]
. These variations may influence the strength and nature of the relationships among maintenance culture, resource allocation, and service delivery. Thus, the framework accommodates the notion that while the core relationships remain consistent, sector-specific nuances may exist. The conceptual framework encapsulates the intricate relationships among maintenance culture, resource allocation, and service delivery in public sector organizations. By integrating theoretical insights from Resource Dependency Theory and empirical findings, this framework provides a structured basis for the systematic investigation of these relationships, allowing for a nuanced exploration of how maintenance culture and resource allocation collectively shape service delivery outcomes within diverse public sector contexts.
Figure 1. Conceptual Framework of the study variables.
The study therefore hypothesis as follows;
H01: Maintenance Culture has a direct significant influence on Service Delivery in public sector organizations.
H02: Resource Allocation has a direct significant influence on Service Delivery in public sector organizations.
H03: Employee Engagement has a direct significant influence on Service Delivery in public sector organizations.
H04: Perception and Trust has a direct significant influence on Service Delivery in public sector organizations.
H05: Employee Engagement significantly mediate the relationship between Maintenance Culture and Service Delivery within public sector organizations.
H06: Employee Engagement significantly mediate the relationship between Resource Allocation and Service Delivery within public sector organizations.
H07: Public Perception and Trust significantly mediate the relationship between Maintenance Culture and Service Delivery in public sector organizations.
H08: Public Perception and Trust significantly mediate the relationship between Resource Allocation and Service Delivery in public sector organizations.
3. Research Methods
In this study investigating the relationship between maintenance culture, resource allocation, and service delivery in public sector organizations in Ghana, a quantitative research design is employed. The research design allows for the collection of numerical data that can be analyzed statistically to draw conclusions and make inferences about the relationships between the variables of interest. The sample for this study consists of employees working in various public sector organizations in Ghana. A stratified random sampling technique is used to ensure representation from different departments and levels within the organizations
[18]
. Data is collected through self-administered questionnaires distributed to the selected participants. The questionnaires are designed to capture information related to maintenance culture, resource allocation, service delivery, employee engagement, and public perception and trust.
To measure the constructs of maintenance culture, resource allocation, service delivery, employee engagement, and public perception and trust, Likert scale items are used. The Likert scale ranges from 1 (Strongly Disagree) to 5 (Strongly Agree). Each construct is measured using five statements, and respondents are asked to indicate their level of agreement or disagreement with each statement. To mitigate Common Method Bias (CMB), steps are taken to ensure the anonymity and confidentiality of respondents' data. The questionnaires are designed to be self-administered, reducing the potential for social desirability bias. Non-response bias is addressed by following up with non-respondents and comparing their characteristics with those of the respondents to assess potential biases.
The measurement model is evaluated using the Confirmatory Factor Analysis (CFA). CFA assesses the fit of the proposed measurement model to the data. Reliability and validity measures, such as Cronbach's alpha and convergent and discriminant validity, are also assessed. The structural model is evaluated using techniques such as path analysis or Structural Equation Modeling (SEM). This analysis allows for the examination of the relationships between the constructs and the testing of hypotheses. The significance and strength of the relationships are assessed through statistical tests, such as regression coefficients and p-values.
Statistical software packages, such as SPSS and SMART PLS were used for data analysis. Descriptive statistics, such as means and standard deviations, are calculated to summarize the data. Inferential statistics, such as correlation analysis and regression analysis, are conducted to examine the relationships between the variables. Ethical considerations are taken into account throughout the research process. Informed consent is obtained from the participants, ensuring they understand the purpose of the study and their rights as participants. Confidentiality and anonymity are maintained by assigning unique identifiers to the respondents and storing data securely. The study also adheres to ethical guidelines regarding the use of human subjects in research.
4. Results and Discussion
4.1. Biographical Data of Respondents
The presented data provides valuable insights into the demographic and professional characteristics of individuals working in the public sector. Notably, the gender distribution shows a higher representation of females (62.2%) compared to males (37.8%) within the public sector workforce. This gender distribution may reflect trends in the broader labor market, indicating a significant presence of women in public sector roles. Understanding the gender dynamics in the public sector is crucial for promoting gender diversity, addressing potential gender disparities, and ensuring equitable opportunities for career advancement and leadership positions. Additionally, the data reveals that a substantial proportion of respondents fall within the 25-34 years age group (68.5%). This concentration of younger professionals suggests the need for strategies to attract and retain young talents in the public sector. Encouragingly, a substantial number of respondents hold Bachelor's (47.1%) and Master's Degrees (46.9%), indicating a well-educated workforce. However, there is a lower percentage of individuals with Diploma/Certificate qualifications (6.0%). This educational profile emphasizes the importance of continuous professional development and training opportunities to enhance the skills and capabilities of public sector employees. Furthermore, the data highlights the distribution of respondents across various job positions, with Supervisory roles (37.3%) being the most prevalent, followed by Senior-level (30.2%) and Top-level positions (13.7%). These findings suggest a hierarchical structure within the public sector organizations surveyed. The distribution of years of experience in the public sector shows a significant concentration of respondents (70.3%) with 11-15 years of experience. This concentration of mid-career professionals underscores the need for career progression pathways and leadership development programs to harness their expertise and potential.
In terms of department/division representation, the data illustrates the diversity of roles within the public sector, with Operations (25.4%), IT/Technology (21.2%), and Human Resources (18.0%) being the prominent departments. Each of these departments plays a vital role in the functioning of public sector organizations, reflecting the multifaceted nature of public service delivery. Moreover, the distribution of respondents across different types of public sector organizations, including Local Government Authority (12.8%), Public Agency (18.4%), State-Owned Enterprise (24.4%), Public Health Institution (21.2%), and Educational Institution (12.0%), highlights the variety of public sector entities encompassing areas such as governance, education, healthcare, and more. Understanding the distribution across these organizations is essential for tailoring policies and practices to the specific needs and challenges faced by each sector. Overall, these findings provide a comprehensive snapshot of the public sector workforce, emphasizing the importance of gender diversity, continuous professional development, and leadership cultivation to enhance service delivery and organizational effectiveness. It also underscores the need for strategic planning and targeted interventions to address the unique characteristics and challenges associated with various types of public sector organizations.
Table 1. Biographical data of respondents.

N

%

Gender

Male

300

37.8%

Female

494

62.2%

25-34 years

544

68.5%

Age

35-44 years

38

4.8%

45-54 years

212

26.7%

Diploma/Certificate

48

6.0%

Educational Qualification

Bachelor's Degree

374

47.1%

Master's Degree

372

46.9%

Entry-level

149

18.8%

Job Position

Supervisory

296

37.3%

Senior-level

240

30.2%

Top-level

109

13.7%

1-5 years

102

12.8%

Years of Experience in the Public Sector

6-10 years

134

16.9%

11-15 years

558

70.3%

Administration

80

10.1%

Finance

106

13.4%

Department/Division

Human Resources

143

18.0%

Operations

202

25.4%

IT/Technology

168

21.2%

Planning and Development

95

12.0%

Government Ministry

89

11.2%

Type of Public Sector Organization

Local Government Authority

102

12.8%

Public Agency

146

18.4%

State-Owned Enterprise

194

24.4%

Public Health Institution

168

21.2%

Educational Institution

95

12.0%
4.2. Correlation of Study Variables
The correlation analysis presented here reveals significant relationships among the study variables, shedding light on the interplay between these critical factors in the context of public sector service delivery. Notably, there is a strong positive correlation (r = 0.646, p < 0.01) between "Maintenance Culture" and "Service Delivery". This finding suggests that a robust maintenance culture within public sector organizations is associated with improved service delivery outcomes. Effective maintenance practices, encompassing infrastructure and facility upkeep, appear to contribute significantly to the quality and reliability of services provided to the public. This underscores the importance of investing in maintenance strategies, training, and resources to enhance overall service delivery effectiveness within the public sector.
Furthermore, the data reveals a positive correlation (r = 0.573, p < 0.01) between "Resource Allocation" and "Employee Engagement". This correlation implies that when resources are allocated efficiently and effectively, employees tend to be more engaged in their roles within public sector organizations. Adequate resource allocation can lead to improved working conditions, access to necessary tools and technologies, and enhanced capacity to deliver services, all of which contribute to higher employee engagement levels. This positive relationship emphasizes the need for strategic resource planning and allocation practices to foster a motivated and committed workforce, which in turn can positively impact service delivery.
Additionally, there is a significant positive correlation (r = 0.725, p < 0.01) between "Public Perception and Trust" and "Employee Engagement". This finding suggests that engaged employees in the public sector may play a crucial role in shaping public perception and trust in government services. Engaged employees are more likely to provide better customer service, exhibit a higher level of professionalism, and go the extra mile to meet public expectations, all of which contribute to enhanced trust and positive perceptions among service recipients. Therefore, investing in strategies to increase employee engagement can have a cascading effect, ultimately leading to improved public trust and perception of the public sector's ability to deliver high-quality services. In conclusion, these correlations underscore the complex and interconnected nature of factors influencing public sector service delivery and emphasize the importance of fostering a culture of maintenance, efficient resource allocation, and employee engagement to enhance public perception, trust, and overall service delivery effectiveness in the public sector.
Table 2. Correlation of study variables.

1

2

3

4

5

Service Delivery (1)

Pearson Correlation

1

Maintenance Culture (2)

Pearson Correlation

.646**

1

Resource Allocation (3)

Pearson Correlation

.543**

.244**

1

Employee Engagement (4)

Pearson Correlation

.262**

.108**

.573**

1

Public Perception and Trust (5)

Pearson Correlation

.108**

.018

.300**

.725**

1

**. Correlation is significant at the 0.01 level (2-tailed).
4.3. Evolution of Outer Measurement Models
The table provides information on the construct reliability of the measurement items for several key constructs in the research study: Employee engagement, Maintenance culture, Perception and trust, Resource allocation, and Service delivery. Construct reliability is a critical aspect of measurement validity, as it assesses the consistency and reliability of the measurement items within each construct. Firstly, looking at the Composite Reliability (CR) values, all constructs demonstrate acceptable levels of reliability, with CR values ranging from 0.871 to 0.925. These values exceed the recommended threshold of 0.7, indicating that the measurement items within each construct are internally consistent and reliable measures of their respective constructs. This suggests that the constructs of Employee engagement, Maintenance culture, Perception and trust, Resource allocation, and Service delivery are reliably measured in the study.
Secondly, the Average Variance Extracted (AVE) values also provide important insights. AVE measures the amount of variance captured by the construct in relation to the variance due to measurement error. AVE values exceeding 0.5 are generally considered acceptable. In the study, all constructs meet or exceed this threshold, with AVE values ranging from 0.616 to 0.808. This indicates that a substantial portion of the variance in each construct is due to the underlying construct itself rather than measurement error, further confirming the construct validity. The high levels of construct reliability and the satisfactory AVE values suggest that the measurement items used to assess Employee engagement, Maintenance culture, Perception and trust, Resource allocation, and Service delivery in the study are robust and dependable. These results enhance the overall validity and trustworthiness of the research findings and support the use of these constructs in the analysis and interpretation of the study's results.
Table 3. Construct reliability.

CONSTRUCTS

ITEM

FL

CA

CR

AVE

Employee engagement

EMG1

0.806

0.874

0.911

0.655

EMG2

0.834

EMG3

0.838

EMG4

0.781

EMG5

0.785

Maintenance culture

MANC2

0.769

0.845

1.095

0.633

MANC3

0.743

MANC4

0.782

MANC5

0.881

Perception and trust

PPT1

0.879

0.920

0.925

0.808

PPT2

0.933

PPT3

0.917

PPT4

0.865

RAL1

0.711

RAL2

0.743

Resource allocation

RAL3

0.827

0.846

0.871

0.616

RAL4

0.823

RAL5

0.813

SD1

0.857

Service delivery

SD2

0.867

0.916

0.922

0.749

SD3

0.905

SD4

0.872

SD5

0.824
Figure 2. Model depicting results of the factor loading of the various items of the constructs.
4.4. Evaluation of the Inner Structural Model
4.4.1. Heterotrait-Monotrait Ratio
The Heterotrait-Monotrait Ratio (HTMT) is a measure used to assess discriminant validity, which evaluates whether different constructs are truly distinct from each other. The HTMT values between the constructs indicate that there is discriminant validity among the constructs, as the values are well below the threshold of 0.85. This suggests that the constructs of Employee engagement, Maintenance culture, Perception and trust, Resource allocation, and Service delivery are distinct and do not suffer from excessive overlap in their measurement. These results affirm that the measurement items for each construct are capturing unique aspects of the underlying concepts, reinforcing the validity of the measurement model.
Table 4. Heterotrait-Monotrait Ratio.

Employee engagement

Maintenance culture

Perception and trust

Resource allocation

Employee engagement

Maintenance culture

0.138

Perception and trust

0.832

0.059

Resource allocation

0.666

0.328

0.382

Service delivery

0.293

0.775

0.147

0.617
4.4.2. Fornell-Larcker Criterion
The Fornell-Larcker Criterion is a technique used to assess discriminant validity by comparing the square root of the AVE (Average Variance Extracted) for each construct with the correlations between that construct and other constructs
[65]
. In the study, the results of the Fornell-Larcker Criterion confirm the presence of discriminant validity among the constructs. These findings provide strong support for the discriminant validity of the measurement model, indicating that the constructs of Employee engagement, Maintenance culture, Perception and trust, Resource allocation, and Service delivery are conceptually distinct and do not suffer from significant overlap in their measurement. This ensures that the relationships between these constructs in the study, is indeed examining separate and meaningful dimensions of public sector management, enhancing the credibility and reliability of the research findings.
Table 5. Fornell-Larcker criterion.

Employee engagement

Maintenance culture

Perception and trust

Resource allocation

Service delivery

Employee engagement

0.809

Maintenance culture

0.170

0.795

Perception and trust

0.711

0.074

0.899

Resource allocation

0.640

0.312

0.352

0.785

Service delivery

0.286

0.771

0.137

0.515

0.865
4.4.3. Cross Loading
The cross-loading results provided in the table offer insights into the relationships between measurement items and their respective constructs, shedding light on the convergent and discriminant validity of the measurement model. Convergent validity is supported when measurement items load more strongly on their intended construct than on other constructs, while discriminant validity is supported when items do not load strongly on unrelated constructs. In this analysis, all of the measurement items exhibit higher loadings on their intended constructs than on other constructs, which is a positive indication of convergent validity.
Table 6. Cross loading.

Employee engagement

Maintenance culture

Perception and trust

Resource allocation

Service delivery

EMG1

0.806

0.181

0.402

0.703

0.307

EMG2

0.834

0.170

0.506

0.566

0.259

EMG3

0.838

0.116

0.670

0.390

0.191

EMG4

0.781

0.079

0.676

0.366

0.149

EMG5

0.785

0.092

0.806

0.389

0.175

MANC2

0.117

0.769

0.021

0.202

0.483

MANC3

0.043

0.743

0.008

0.124

0.453

MANC4

0.073

0.782

0.004

0.155

0.522

MANC5

0.193

0.881

0.110

0.343

0.785

PPT1

0.697

0.071

0.879

0.335

0.131

PPT2

0.674

0.065

0.933

0.328

0.142

PPT3

0.623

0.047

0.917

0.309

0.126

PPT4

0.549

0.084

0.865

0.289

0.089

RAL1

0.389

0.421

0.208

0.711

0.622

RAL2

0.407

0.413

0.209

0.743

0.589

RAL3

0.464

0.214

0.242

0.827

0.360

RAL4

0.522

0.174

0.306

0.823

0.324

RAL5

0.650

0.122

0.364

0.813

0.267

SD1

0.236

0.753

0.096

0.383

0.857

SD2

0.217

0.733

0.111

0.385

0.867

SD3

0.264

0.670

0.117

0.426

0.905

SD4

0.227

0.631

0.128

0.447

0.872

SD5

0.279

0.563

0.139

0.563

0.824
4.4.4. Collinearity Assessment
Table 7. Collinearity assessment.

VIF

EMG1

1.705

EMG2

2.033

EMG3

2.969

EMG4

2.622

EMG5

2.434

MANC2

2.047

MANC3

2.397

MANC4

2.649

MANC5

1.400

PPT1

2.677

PPT2

4.243

PPT3

3.592

PPT4

2.837

RAL1

1.989

RAL2

2.097

RAL3

2.293

RAL4

2.285

RAL5

1.729

SD1

2.971

SD2

3.281

SD3

3.436

SD4

3.158

SD5

2.189
The Variance Inflation Factor (VIF) values presented in the assessment provide insights into the potential multicollinearity among the variables in the model. VIF measures the extent to which the variance of an estimated regression coefficient is inflated due to multicollinearity. In the analysis, all VIF values appear to be below the commonly accepted threshold of 5, which suggests that multicollinearity is not a severe issue in the model. These findings indicate that the predictor variables in the study are not highly correlated with each other, meaning that they do not overly influence each other's coefficients when included in regression models. This is a positive result as it implies that the relationships between the predictor variables and the outcome variable can be more reliably interpreted without being significantly confounded by multicollinearity.
4.5. Hypothesis and Estimation of Path Coefficients
4.5.1. Direct Effects
The results of the hypothesis testing for direct effects in the structural equation model provide valuable insights into the relationships between the constructs in the study. Firstly, H01, which hypothesized a negative relationship between "Maintenance culture" (MAN) and "Service delivery" (SD), was rejected. The path coefficient (Beta) was found to be very close to zero (Beta = -0.007), and the associated p-value was greater than the commonly used significance threshold of 0.05 (p = 0.424). This suggests that there is no significant direct relationship between maintenance culture and service delivery in the model.
Secondly, H02, H03, and H04 were all accepted, indicating significant direct relationships between the respective independent variables (Resource allocation - RAL, Employee engagement - EMG, Perception and trust - PPT) and the dependent variable, Service delivery (SD). Specifically, H02 reveals a positive and strong relationship between resource allocation and service delivery (Beta = 0.199, p < 0.001), suggesting that allocating resources effectively contributes to better service delivery. Similarly, H03 highlights a positive and substantial relationship between employee engagement and service delivery (Beta = 0.381, p < 0.001), indicating that higher levels of employee engagement are associated with improved service delivery. Lastly, H04 uncovers a negative relationship between perception and trust and service delivery (Beta = -0.133, p = 0.009), suggesting that a decline in public perception and trust can have a detrimental impact on service delivery outcomes.
Table 8. Direct Effects Hypothesis and of Path Coefficients.

Hypothesis

Relationship

Beta

STDEV

T statistics

P values

Decision

H01:

MAN -> SD

-0.007

0.009

0.800

0.424

Rejected

H02:

RAL -> SD

0.199

0.024

8.121

0.000

Accepted

H03:

EMG -> SD

0.381

0.049

7.698

0.000

Accepted

H04:

PPT -> SD

-0.133

0.051

2.601

0.009

Accepted
4.5.2. Mediation Effect
The examination of mediation effects in the structural equation model provides a deeper understanding of the indirect relationships between the variables and their influence on service delivery. Starting with H05, which proposed that maintenance culture (MAN) has an indirect effect on service delivery (SD) through the mediation of employee engagement (EMG), the results indicate that this hypothesis is rejected. The path coefficient (Beta) is relatively small and not statistically significant (Beta = -0.012, p = 0.235). This suggests that, in the study, maintenance culture does not significantly influence service delivery through its impact on employee engagement. This finding contrasts with the broader literature, which often emphasizes the importance of maintenance culture in enhancing employee engagement and, subsequently, service delivery. Therefore, in the specific context, employee engagement may not act as a mediating mechanism between maintenance culture and service delivery.
Moving to H06, which proposed that resource allocation (RAL) has an indirect effect on service delivery (SD) through the mediation of employee engagement (EMG), the results indicate that this hypothesis is accepted. The path coefficient (Beta) is positive, substantial, and statistically significant (Beta = 0.247, p < 0.001). This finding supports the notion that resource allocation positively impacts service delivery through its influence on employee engagement. This result is consistent with the broader literature that highlights the significance of resource allocation in fostering employee engagement, which, in turn, contributes to better service delivery.
For H07, which hypothesized that maintenance culture (MAN) indirectly affects service delivery (SD) through the mediation of perception and trust (PPT), the results suggest that this hypothesis is rejected. The path coefficient (Beta) is small and not statistically significant (Beta = 0.005, p = 0.404). This indicates that, in the study, maintenance culture does not significantly influence service delivery through its impact on perception and trust. This finding deviates from the expectation that a positive maintenance culture would enhance public perception and trust, leading to improved service delivery. Lastly, H08 proposed that resource allocation (RAL) indirectly affects service delivery (SD) through the mediation of perception and trust (PPT). The results show that this hypothesis is accepted. The path coefficient (Beta) is negative and statistically significant (Beta = -0.049, p = 0.011), suggesting that resource allocation negatively influences service delivery through its impact on perception and trust. This finding aligns with the idea that inadequate resource allocation can lead to decreased public perception and trust, ultimately affecting service delivery negatively.
Table 9. Mediating Effects Hypothesis and of Path Coefficients.

Hypothesis

Relationship

Beta

STDE

T statistics

P values

Decision

H05:

MAN -> EMG -> SD

-0.012

0.010

1.188

0.235

Rejected

H06:

RAL -> EMG -> SD

0.247

0.034

7.183

0.000

Accepted

H07:

MAN -> PPT -> SD

0.005

0.006

0.834

0.404

Rejected

H08:

RAL -> PPT -> SD

-0.049

0.019

2.537

0.011

Accepted
Figure 3. Model depicting results of the path coefficients and p-values of the relationship between various constructs.
4.5.3. Measuring the Value of R2
The study’s R-squared values indicate the proportion of variance explained by the model for key constructs. Employee engagement exhibits the highest explanatory power, with an R-squared of 0.410, signifying that 41% of the variance can be attributed to the model's independent variables. Perception and trust follow with an R-squared of 0.125, explaining 12.5% of the variance. Service delivery has an R-squared of 0.090, indicating that 9% of the variance can be accounted for by the predictors. These values suggest that while the model contributes to our understanding of these constructs, there is substantial unexplained variance, underscoring the influence of other factors not included in the analysis.
Table 10. Measuring the Value of R2.

R-square

R-square adjusted

Employee engagement

0.410

0.409

Perception and trust

0.125

0.123

Service delivery

0.090

0.088
4.5.4. The Effect Size (ƒ2)
The study's effect size (f-square) measurements reveal the practical significance of various relationships among constructs. The relationship between employee engagement and service delivery exhibits a moderate effect size of 0.079, signifying a notable impact of employee engagement on service delivery outcomes. Conversely, maintenance culture has minimal effects on both employee engagement (0.002) and perception and trust (0.002). Perception and trust, in turn, show a small effect size of 0.010 in their influence on service delivery. Notably, resource allocation demonstrates substantial effects with an effect size of 0.646 on employee engagement and 0.137 on perception and trust, underscoring its significant impact within the studied context. These effect sizes collectively illuminate the practical importance of the examined relationships in the research.
Table 11. The effect size (ƒ2).

f-square

Employee engagement -> Service delivery

0.079

Maintenance culture -> Employee engagement

0.002

Maintenance culture -> Perception and trust

0.002

Perception and trust -> Service delivery

0.010

Resource allocation -> Employee engagement

0.646

Resource allocation -> Perception and trust

0.137
4.5.5. Goodness-of-Fit Index
The goodness-of-fit indices comparing the estimated model to a saturated model indicate that the estimated model provides a generally good fit to the data. The Standardized Root Mean Square Residual (SRMR) suggests a reasonable fit with a value of 0.006. Discrepancy-based fit indices, such as d_ULS and d_G, indicate that the estimated model is an improvement over the saturated model, with higher values for d_ULS (0.083 vs. 0.025) and d_G (0.458 vs. 0.144) in favor of the estimated model. Additionally, the Chi-square value for the estimated model (3121.460) is lower than that of the saturated model (3368.065), further supporting a better fit. The Normed Fit Index (NFI) also favors the estimated model, with an NFI of 0.959 compared to 0.951 for the saturated model. Overall, these indices collectively suggest that the estimated model offers a good fit to the data and represents an improvement over the saturated model in explaining the relationships among the study variables.
Table 12. Goodness-of-Fit Index.

Saturated model

Estimated model

SRMR

0.001

0.006

d_ULS

0.025

0.083

d_G

0.144

0.458

Chi-square

3368.065

3121.460

NFI

0.951

0.959
4.5.6. Q2 PLS-SEM Predictions
The Q²predict values for the three key constructs in the PLS-SEM model are as follows. Employee Engagement (Q²predict = 0.405). The PLS-SEM model demonstrates moderate predictive power for employee engagement. This implies that the model can reasonably predict variations in employee engagement based on the specified relationships and variables. Practically, this suggests that the model's predictions for employee engagement are relatively reliable. Perception and Trust (Q²predict = 0.120). The model shows a lower but still acceptable level of predictive power for perception and trust. While it may not be as accurate in predicting variations in perception and trust compared to employee engagement, it can still provide reasonably accurate predictions for this construct. Service Delivery (Q²predict = 0.155). Similar to employee engagement, the PLS-SEM model exhibits moderate predictive power for service delivery. This means that the model can make reasonably accurate predictions regarding variations in service delivery based on the specified relationships and variables.
Table 13. Q2 PLS-SEM predictions.

Q²predict

RMSE

MAE

Employee engagement

0.405

0.773

0.602

Perception and trust

0.120

0.941

0.754

Service delivery

0.155

0.922

0.742
4.6. Discussion of Results
The finding that resource allocation (RAL) has a positive and significant direct effect on service delivery (SD) is consistent with the broader literature on public sector management. The literature has consistently emphasized the importance of adequate resource allocation and management in ensuring the availability of necessary resources for service delivery
[61]
. This result supports the notion that proper resource allocation practices are essential for enhancing service delivery in the public sector. The significant positive relationship between employee engagement (EMG) and service delivery (SD) in the study aligns with the research by
[27]
, which noted that talent management and employee engagement are crucial for better service delivery in the public sector. This finding is also supported by the broader literature on talent management and its impact on service quality.
The negative relationship between perception and trust (PPT) and service delivery (SD) in the study contradicts the expected positive relationship between public perception and service quality. The literature by
[56]
emphasizes the importance of regional and municipal authorities in developing the public sector's physical activity and sports work, including providing services to the population. A positive public perception and trust are typically seen as crucial factors in service delivery, as highlighted in other studies
[21]
. Therefore, this result is somewhat opposing to the literature, suggesting that a decline in public perception and trust can have a negative impact on service delivery, which warrants further investigation. The study did not find a significant direct relationship between maintenance culture (MAN) and service delivery (SD). This finding aligns with the literature's mixed perspective on the role of maintenance culture in service delivery. While proper maintenance practices are emphasized as crucial for service quality
[7, 17]
, the lack of a significant direct relationship in the study suggests that other factors, such as resource allocation and employee engagement, may have a more direct impact on service delivery in the specific context.
The results of the study concerning the mediation effects provide insights into how the relationships between variables align or deviate from the empirical literature discussed earlier. These findings shed light on the nuanced dynamics of service delivery in the public sector, highlighting both supporting and opposing evidence in relation to the literature.
The study rejected the hypothesis (H05) proposing that employee engagement (EMG) significantly mediates the relationship that exists between maintenance culture (MAN) and service delivery (SD). This finding deviates from the broader literature that emphasizes the role of a positive maintenance culture in fostering employee engagement
[27]
. It suggests that, in the specific context, the connection between maintenance culture and employee engagement may not be as pronounced or mediating as expected. The study accepted the hypothesis (H06) that of employee engagement (EMG) significantly mediates the relationship that exists between resource allocation (RAL) and service delivery (SD). The meaning is that resource allocation (RAL) has an indirect positive effect on service delivery (SD) through the mediation of employee engagement (EMG). This result aligns with the literature's emphasis on the significance of resource allocation in influencing employee engagement, which, in turn, affects service delivery
[27]
. This finding supports the notion that when resources are effectively allocated, it positively impacts employee engagement, leading to improved service delivery
[23-32]
. The study rejected the hypothesis (H07) that perception and trust (PPT) significantly mediates the relationship that exists between maintenance culture (MAN) and service delivery (SD). This result is somewhat opposing to the broader literature, which often suggests that a strong maintenance culture enhances public perception and trust, contributing to better service delivery
[56]
. It implies that in the specific context, the mediating role of perception and trust between maintenance culture and service delivery is not supported. The study accepted the hypothesis (H08) that perception and trust (PPT) significantly mediates the association between resource allocation (RAL) and service delivery (SD). Hence, resource allocation (RAL) indirectly affects service delivery (SD) through the mediation of perception and trust (PPT). This finding aligns with the literature's perspective that inadequate resource allocation can negatively impact public perception and trust, ultimately affecting service delivery negatively
[21]
. It supports the idea that proper resource allocation can lead to positive public perception and trust, which, in turn, enhances service delivery
[35-40]
.
5. Conclusions
This study investigated the factors influencing service delivery in the public sector, focusing on maintenance culture, resource allocation, employee engagement, and public perception and trust. The findings revealed that effective resource allocation positively impacts service delivery directly and indirectly through its influence on employee engagement and public perception and trust. Employee engagement emerged as a crucial mediator between resource allocation and service delivery, highlighting the significance of talent management and employee engagement practices in the public sector. However, the study did not find strong support for the direct impact of maintenance culture on service delivery or its mediation through employee engagement or public perception and trust. This suggests that, in the specific context of the study, maintenance culture may not be as influential as resource allocation and employee engagement in determining service delivery outcomes. The research underscores the importance of effective resource management and employee engagement in public sector organizations to optimize service delivery. It also emphasizes the need for context-specific analysis, as the dynamics of these factors may vary across different organizational settings. Further research in diverse public sector contexts is recommended to gain a comprehensive understanding of effective service delivery strategies.
5.1. Theoretical, Practical and Managerial Implications
This study contributes to the advancement of service delivery theory by examining the intricate relationships among maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery outcomes. It enhances our understanding of these complex dynamics within the public sector. The study underscores the significance of considering the specific context when analyzing how these factors influence service delivery. It emphasizes that the impact of these variables can vary across different public sector organizations and regions, highlighting the need for context-specific research and acknowledging the nuanced nature of service delivery dynamics. The research adds to the theoretical framework by revealing the mediating roles of employee engagement and public perception and trust. It deepens our understanding of how these variables mediate the relationship between resource allocation and service delivery, shedding light on the intricate interactions that drive outcomes in the public sector.
Public sector organizations should strategically allocate resources to improve service delivery. Effective resource allocation should not only support day-to-day operations but also focus on initiatives that enhance employee engagement and build and maintain public trust. Managers should prioritize talent management practices that foster employee engagement. Programs aimed at enhancing motivation, skill development, and growth opportunities for employees can lead to improved service delivery outcomes. Recognizing the critical role of public perception and trust, organizations should invest in robust public relations and communication strategies. Transparency, responsiveness, and effective communication are essential to cultivate and sustain public trust, which in turn positively influences service delivery.
Managers should formulate resource allocation strategies aligned with the organization's service delivery objectives. This may involve prudent budget planning, prioritization of key service areas, and continuous monitoring and evaluation of resource utilization. Investment in employee engagement initiatives is paramount. Managers should create a work environment that promotes employee engagement, invest in skill development, and offer growth prospects. Engaged employees are more likely to contribute positively to service delivery. Establishing systems for continuous monitoring and evaluation is vital for managers. Regular assessments can pinpoint areas for improvement in resource allocation, employee engagement, and public trust-building efforts, guiding informed decision-making and course corrections.
5.2. Limitations and Future Research Directions
This study has explored the intricate relationships between maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery in the public sector. While providing valuable insights, it is essential to acknowledge certain limitations, including the use of cross-sectional data, self-reported measures, and potential issues of generalizability. Future research directions include the pursuit of longitudinal studies, qualitative investigations, comparative analyses, and intervention studies to deepen our understanding of these relationships and their dynamics over time and across diverse public sector contexts. Additionally, the application of advanced causal modelling techniques and the incorporation of external assessments can further contribute to the field's knowledge and assist public sector managers in enhancing service delivery outcomes.
Abbreviations

NCD

Non-Communicable Diseases

RDT

Resource Dependency Theory

CMB

Common Method Bias

CFA

Confirmatory Factor Analysis

SEM

Structural Equation Modeling

CR

Composite Reliability

AVE

Average Variance Extracted

HTMT

Heterotrait-Monotrait Ratio

VIF

Variance Inflation Factor

MAN

Maintenance Culture

SD

Service Delivery

RAL

Resource Allocation

EMG

Employee Engagement

PPT

Perception And Trust
Conflicts of Interest
The authors declare no conflicts of interest.
References
[1] Afolabi, S., Babalola, O., Olaniyan, O., and Aseyan, B. (2022). Maintenance culture in selected public buildings within Ibadan Metropolis. European Journal of Development Studies, 2(3), 58-69.

https://doi.org/10.24018/ejdevelop.2022.2.3.100

[2] Agbozo, E., Medvedev, A. (2020). Towards a multi-channel service delivery model in the data-driven public sector. Business Informatics, 14(1), 41-50.

https://doi.org/10.17323/2587-814x.2020.1.41.50

[3] Alegana, V., Maina, J., Ouma, P., Macharia, P., Wright, J., Atkinson, P. and Tatem, A. (2018). National and sub-national variation in patterns of febrile case management in Sub-Saharan Africa. Nature Communications, 9(1).

https://doi.org/10.1038/s41467-018-07536-9

[4] Almalki, A., Al-Hanawi, M. (2018). Public private partnerships and collaboration in the health sector in the kingdom of Saudi Arabia: a qualitative study. Global Journal of Health Science, 10(6), 10.

https://doi.org/10.5539/gjhs.v10n6p10

[5] Argaw, M., Mavundla, T., and Gidebo, K. (2020). Community and health care providers’ perception on quality of private sector outpatient malaria care in North West Ethiopia: a qualitative study.

https://doi.org/10.21203/rs.3.rs-32063/v1

[6] Arimoro, A. (2019). Public-private partnership and the right to property in Nigeria. African Human Rights Law Journal, 19(2).

https://doi.org/10.17159/1996-2096/2019/v19n2a10

[7] Asmara, A., Rahayu, A. (2020). Innovation in delivering public health service: practice in Banyuwangi regency – Indonesia. GATR Global Journal of Business Social Sciences Review, 8(1), 12-21.

https://doi.org/10.35609/gjbssr.2020.8.1(2)

[8] Bojang, M. (2020). Beyond new public management paradigm: the public value paradigm and its implications for public sector managers. Journal of Public Value and Administrative Insight, 3(2), 1-10.

https://doi.org/10.31580/jpvai.v3i2.1381

[9] Breesam, H., Jawad, Z. (2021a). Application of stakeholder theory in procedures for maintenance work for government buildings in Iraq. IOP Conference Series Materials Science and Engineering, 1090(1), 012073.

https://doi.org/10.1088/1757-899x/1090/1/012073

[10] Breesam, H., Jawad, Z. (2021b). Factors affecting maintenance procedures for public buildings. IOP Conference Series Materials Science and Engineering, 1090(1), 012120.

https://doi.org/10.1088/1757-899x/1090/1/012120

[11] Burger, R., Christian, C., Gerdtham, U., Haal, K., Hompashe, D., Smith, A. and Schutte, A. (2020). Use of simulated patients to assess hypertension case management at public healthcare facilities in South Africa. Journal of Hypertension, 38(2), 362-367.

https://doi.org/10.1097/hjh.0000000000002258

[12] Chigudu, D. (2019). The African tradition and the nexus between public sector ethics and culture: a critical analysis. The Journal of Social Sciences Research, (510), 1428-1434.

https://doi.org/10.32861/jssr.510.1428.1434

[13] Chintalapati, P., Nyaga, C., Walters, J., Koehler, J., Javernick-Will, A., Hope, R., and Linden, K. (2022). Improving the reliability of water service delivery in rural Kenya through professionalized maintenance: a system dynamics perspective. Environmental Science & Technology, 56(23), 17364-17374.

https://doi.org/10.1021/acs.est.2c00939

[14] Dejaco, M., Cecconi, F., Moretti, N., Mannino, A., and Maltese, S. (2019). Building and district data organization to improve facility and property management. 255-265.

https://doi.org/10.1007/978-3-030-33570-0_23

[15] Dent, P. (2019). Managing public sector property assets: valuation issues. 125-140.

https://doi.org/10.4324/9780429432873-6

[16] Ebekozien, A., Duru, O., and Dako, O. (2021). Maintenance of public hospital buildings in Nigeria – an assessment of current practices and policy options. Journal of Facilities Management, 20(1), 120-143.

https://doi.org/10.1108/jfm-11-2020-0088

[17] Elliott, J. (2020). Public management and the private sector. 176-212.

https://doi.org/10.4324/9781003070986-7

[18] Saunders, M., Thornhill, A., and Lewis, P. (2012). Research methods for business students. 6th Ed. Harlow: Financial Times Prentice Hall. Ercsey, I. and Józsa, L. (2021). The examination of the consequences of the service value in the cultural services. Acta Oeconomica Universitatis Selye, 10(1), 6-18.

https://doi.org/10.36007/acta.2021.10.1.1

[19] Fengwei, X. (2022). Research on ancient building health monitoring technology based on real-time situation awareness.

https://doi.org/10.1117/12.2661752

[20] Govender, K., Girdwood, S., Letswalo, D., Long, L., Meyer-Rath, G., and Miot, J. (2020). Primary healthcare seeking behaviour of low-income, uninsured patients across the public and private health sectors in South Africa.

https://doi.org/10.21203/rs.3.rs-74088/v1

[21] Hashim, H., Sapri, M., and Azis, S. (2019). Strategic facilities management functions for public private partnership (PPP) healthcare services in Malaysia. Planning Malaysia, 17(9).

https://doi.org/10.21837/pmjournal.v17.i9.584

[22] Hofstetter, M., Koppen, B., and Bolding, A. (2021). The emergence of collectively owned self-supply water supply systems in rural South Africa – what can we learn from the Tshakhuma case in Limpopo? Water SA, 47(2 April).

https://doi.org/10.17159/wsa/2021.v47.i2.10921

[23] Joe, W., Perkins, J., Kumar, S., Rajpal, S., and Subramanian, S. (2018). Institutional delivery in India, 2004–14: unravelling the equity-enhancing contributions of the public sector. Health Policy and Planning, 33(5), 645-653.

https://doi.org/10.1093/heapol/czy029

[24] Kabwama, S., Wanyenze, R., Kiwanuka, S., Namale, A., Ndejjo, R., Monje, F., and Alfvén, T. (2022). Interventions for maintenance of essential health service delivery during the covid-19 response in Uganda, between March 2020 and April 2021. International Journal of Environmental Research and Public Health, 19(19), 12522.

https://doi.org/10.3390/ijerph191912522

[25] Khaemba, Y. and Nyariki, K. (2022). Role of public administration practices on service delivery in Kiminini sub-county, Trans-Nzoia County, Kenya. The International Journal of Business & Management.

https://doi.org/10.24940/theijbm/2022/v10/i11/bm2211-008

[26] Kozjek, T., Franca, V. (2020). Talent management in the public sector. Central European Public Administration Review, 18(2), 53-71.

https://doi.org/10.17573/cepar.2020.2.03

[27] Lam, T. (2019). A sustainable procurement approach for selection of construction consultants in property and facilities management. Facilities, 38(1/2), 98-113.

https://doi.org/10.1108/f-12-2018-0147

[28] Langham, J., Paulsen, N. (2018). Applying the experience effectiveness (xe) framework in the Canadian public sector. Design Management Journal, 13(1), 53-69.

https://doi.org/10.1111/dmj.12042

[29] Legenkova, M. (2020). Features of accounting for particularly valuable property in the public administration sector. Scientific Review Theory and Practice, 10(5), 804-810.

https://doi.org/10.35679/2226-0226-2020-10-5-804-810

[30] Liu, S., Arifin, M. (2021). Preventive maintenance model for national school buildings in Indonesia using a constraint programming approach. Sustainability, 13(4), 1874.

https://doi.org/10.3390/su13041874

[31] Marchildon, G., Allin, S. (2023). Public and private interfaces in Canadian healthcare. 48-C3. P105.

https://doi.org/10.1093/oso/9780197571101.003.0003

[32] Matse, N., Mashwama, N., Thwala, W., and Aigbavboa, C. (2022). A theoretical assessment of the impacts of poor maintenance of public infrastructure. IOP Conference Series Materials Science and Engineering, 1218(1), 012018.

https://doi.org/10.1088/1757-899x/1218/1/012018

[33] Mazele, O., Amoah, C. (2021). The causes of poor infrastructure management and maintenance in South African municipalities. Property Management, 40(2), 192-206.

https://doi.org/10.1108/pm-06-2021-0042

[34] Ndanyi, M. (2019). Performance management and health service delivery in the local governments of Uganda. Journal of African Studies and Development, 11(6), 84-93.

https://doi.org/10.5897/jasd2019.0529

[35] Nemec, J., Svidroňová, M., and Kovács, É. (2019). Welfare co-production: Hungarian and Slovak reality. Nispacee Journal of Public Administration and Policy, 12(2), 195-215.

https://doi.org/10.2478/nispa-2019-0019

[36] Nichols, G., Findlay-King, L., and Forbes, D. (2020). The community asset transfer of leisure facilities in the UK: a review and research agenda. Voluntas International Journal of Voluntary and Nonprofit Organizations, 31(6), 1159-1172.

https://doi.org/10.1007/s11266-020-00263-0

[37] Nielsen, M., Jordanoski, Z. (2023). Digital transformation, governance and coordination in times of crisis: an analysis of Australia, Denmark and the republic of Korea. Digital Government Research and Practice.

https://doi.org/10.1145/3604569

[38] Nkoana, P., Moodley, V., and Mashige, K. (2023). Keratoconic patient profile and management at public sector facilities in South Africa. African Vision and Eye Health, 82(1).

https://doi.org/10.4102/aveh.v82i1.780

[39] Nkyabonaki, J. (2019). Effectiveness of the public service code of ethics in controlling corrupt behaviour in the public service: opinion from the grassroots at Toangoma ward-Temeke municipal council. Journal of Asian and African Studies, 54(8), 1195-1212.

https://doi.org/10.1177/0021909619862835

[40] Oanh, C. (2020). The implementation of community engagement in public service delivery in the UK and policy implication to Vietnam. VNU Journal of Foreign Studies, 36(3).

https://doi.org/10.25073/2525-2445/vnufs.4561

[41] Ogunbayo, B., Aigbavboa, C. (2022). Stakeholders’ behaviour in the maintenance management of public buildings: a bane to maintenance culture.

https://doi.org/10.1063/5.0092312

[42] Ogunbayo, B., Aigbavboa, C., Thwala, W., Akinradewo, O., Ikuabe, M., and Adekunle, S. (2022). Review of culture in maintenance management of public buildings in developing countries. Buildings, 12(5), 677.

https://doi.org/10.3390/buildings12050677

[43] Olanrewaju, A., Teo, Y., and Mohamed, F. (2021). Obstacles of implementing green maintenance management in hospital buildings. Proceedings of International Structural Engineering and Construction, 8(1).

https://doi.org/10.14455/isec.2021.8(1).aaw-09

[44] Olukanni, D., Nwafor, C. (2019). Public-private sector involvement in providing efficient solid waste management services in Nigeria. Recycling, 4(2), 19.

https://doi.org/10.3390/recycling4020019

[45] Palikhe, A. (2023). Student's perception regarding quality of public service marketing on service delivery. Kenya Journal, 4(1), 1-20.

https://doi.org/10.3126/kanyaj.v4i1.57018

[46] Patience, J., Nel, D. (2021). Municipal infrastructure management and its impact on service delivery in the city of Ekurhuleni. Africa’s Public Service Delivery and Performance Review, 9(1).

https://doi.org/10.4102/apsdpr.v9i1.508

[47] Portela, C. (2020). Urban utilities and opportunities for the private sector in local energy services in Switzerland. Competition and Regulation in Network Industries, 21(2), 193-218.

https://doi.org/10.1177/1783591720916347

[48] Putri, A., Latief, Y., Sagita, L., and Machfudiyanto, R. (2021). Developing standard operational procedures for maintenance and repair of mechanical and electrical component in government building to improving safety planning. Journal of Physics Conference Series, 1858(1), 012082.

https://doi.org/10.1088/1742-6596/1858/1/012082

[49] Radzuan, N., Ali, I., Sudirman, M., Isa, A., and Hassin, M. (2022). Assessment on the maintenance service delivery characteristics (msdcs): case study of the public schools in Perak, Malaysia. International Journal of Academic Research in Business and Social Sciences, 12(10).

https://doi.org/10.6007/ijarbss/v12-i10/14808

[50] Richard, J., Muna, W. (2018). Effects of county budgeting forums on service delivery in Kenya: the case of Kajiado County. American Journal of Public Policy and Administration, 3(1).

https://doi.org/10.47672/ajppa.366

[51] Rogers, H., Akiteng, A., Mutungi, G., Ettinger, A., and Schwartz, J. (2018). Capacity of Ugandan public sector health facilities to prevent and control non-communicable diseases: an assessment based upon who-pen standards. BMC Health Services Research, 18(1).

https://doi.org/10.1186/s12913-018-3426-x

[52] Rozanov, A., Barannikov, A., Belyaeva, O., and Smirnov, M. (2020). Public sector crisis management.

https://doi.org/10.5772/intechopen.77623

[53] Sala, R., Bertoni, M., Pirola, F., and Pezzotta, G. (2021). Data-based decision-making in maintenance service delivery: the d3m framework. Journal of Manufacturing Technology Management, 32(9), 122-141.

https://doi.org/10.1108/jmtm-08-2020-0301

[54] Sarvari, H., Cristofaro, M., Chan, D., Noor, N., and Amini, M. (2020). Completing abandoned public facility projects by the private sector: results of a Delphi survey in the Iranian water and Wastewater Company. Journal of Facilities Management, 18(5), 547-566.

https://doi.org/10.1108/jfm-07-2020-0046

[55] Shatsky, A., Sergeevna, P., and Zanina, K. (2020). Approaches to regulation of population security with sport facilities. Social’naya Politika I Sociologiya, 19(4), 68-75.

https://doi.org/10.17922/2071-3665-2020-19-4-68-75

[56] Shittu, A. (2020). Public service and service delivery. 1-8.

https://doi.org/10.1007/978-3-319-31816-5_4005-1

[57] Stanley, P., Swann, B. (2021). Organisational culture and its impact on service delivery. 169-190.

https://doi.org/10.4324/9781315378459-10

[58] Suwantika, A., Zakiyah, N., Abdulah, R., and Diantini, A. (2023). Assessment of childhood immunization services at private healthcare facilities in Indonesia: a case study in a highly-populated city. Frontiers in Public Health, 11.

https://doi.org/10.3389/fpubh.2023.1093387

[59] Taponen, S., Kauppi, K. (2020). Service outsourcing decisions – a process framework. Journal of Global Operations and Strategic Sourcing, 13(2), 171-194.

https://doi.org/10.1108/jgoss-02-2019-0012

[60] Theuri, M., Macharia, S., and Kamau, A. (2020). An assessment of the influence of working environment on service delivery in the public health sector in Nyeri County, Kenya. Management and Economics Research Journal, 6, 1.

https://doi.org/10.18639/merj.2020.961199

[61] Thusi, X., Chauke, R. (2023). Strategies for retaining scarce skills and reducing turnover in the South African public sector. International Journal of Management Entrepreneurship Social Sciences and Humanities, 6(1), 120-134.

https://doi.org/10.31098/ijmesh.v6i1.1242

[62] Wilson, K. (2018). Collaborative leadership in public library service development. Library Management, 39(8/9), 518-529.

https://doi.org/10.1108/lm-08-2017-0084

[63] Wong, W., Olanrewaju, A., and Lim, P. (2021). Importance and performance of value-based maintenance practices in hospital buildings. Sustainability, 13(21), 11908.

https://doi.org/10.3390/su132111908

[64] Wushe, T., Shenje, J. (2019). The antecedents of employee engagement and their effect on public sector service delivery: the case study of government departments in Harare. SA Journal of Human Resource Management, 17.

https://doi.org/10.4102/sajhrm.v17i0.1082

[65] Fornell, C., Larcker, D. F. (1981), “Evaluating Structural Equation Models With Unobservable Variables and Measurement Error,” Journal of Marketing Research, 18 (February), 39–50.
[66] Pfeffer, J., Salancik, G. R. (1978). The External Control of Organizations: A Resource Dependence Perspective. University of Illinois at Urbana-Champaign's Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship, Available at SSRN:

https://ssrn.com/abstract=1496213

Cite This Article
Plain Text BibTeX RIS

  • APA Style

    Ampong, K., Akayuri, G. A., Apau, S., Abaitey, J., Awotwi, E., et al. (2025). Examining the Maintenance Culture of Public Sector Property and Its Impact on Service Delivery: A PLS-SEM Approach. Journal of Public Policy and Administration, 9(1), 19-36. https://doi.org/10.11648/j.jppa.20250901.13

    Copy | Download

    ACS Style

    Ampong, K.; Akayuri, G. A.; Apau, S.; Abaitey, J.; Awotwi, E., et al. Examining the Maintenance Culture of Public Sector Property and Its Impact on Service Delivery: A PLS-SEM Approach. J. Public Policy Adm. 2025, 9(1), 19-36. doi: 10.11648/j.jppa.20250901.13

    Copy | Download

    AMA Style

    Ampong K, Akayuri GA, Apau S, Abaitey J, Awotwi E, et al. Examining the Maintenance Culture of Public Sector Property and Its Impact on Service Delivery: A PLS-SEM Approach. J Public Policy Adm. 2025;9(1):19-36. doi: 10.11648/j.jppa.20250901.13

    Copy | Download 

  • @article{10.11648/j.jppa.20250901.13,
  author = {Kwabena Ampong and George Akasum Akayuri and Samuel Apau and Jonathan Abaitey and Ellen Awotwi and Emmanuel Ebo Ocran},
  title = {Examining the Maintenance Culture of Public Sector Property and Its Impact on Service Delivery: A PLS-SEM Approach},
  journal = {Journal of Public Policy and Administration},
  volume = {9},
  number = {1},
  pages = {19-36},
  doi = {10.11648/j.jppa.20250901.13},
  url = {https://doi.org/10.11648/j.jppa.20250901.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jppa.20250901.13},
  abstract = {The study innovatively investigates the relationship between maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery in the public sector. The study uncovers the interplay between these factors and their impact on service delivery outcomes. To achieve such outcomes, we utilize a structured questionnaire to assess variables related to maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery. Data were collected from a sample of public sector employees and stakeholders, which was then subjected to rigorous statistical analysis. The research employs a range of statistical techniques to investigate correlations, direct and mediating effects, and construct reliability. Inarguably, the use of a survey instrument and statistical analysis allowed for the quantitative assessment of the research hypotheses. The findings reveal significant correlations between maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery. It identifies employee engagement, public perception and trust as mediating variables that play crucial roles in influencing service delivery outcomes. The findings provide distinctive insights into the complex dynamics of service delivery in the public sector, emphasizing the importance of resource allocation, employee engagement, and public relations efforts. Our research contributes to the field by examining the relationships among maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery in the specific context of the public sector. It introduces the mediating roles of employee engagement and public perception and trust, adding a novel dimension to our understanding of service delivery dynamics. The study's originality lies in its empirical investigation of these complex interactions, shedding light on the factors that influence service delivery outcomes in public organizations.},
 year = {2025}
}

    Copy | Download 

  • TY  - JOUR
T1  - Examining the Maintenance Culture of Public Sector Property and Its Impact on Service Delivery: A PLS-SEM Approach
AU  - Kwabena Ampong
AU  - George Akasum Akayuri
AU  - Samuel Apau
AU  - Jonathan Abaitey
AU  - Ellen Awotwi
AU  - Emmanuel Ebo Ocran
Y1  - 2025/02/11
PY  - 2025
N1  - https://doi.org/10.11648/j.jppa.20250901.13
DO  - 10.11648/j.jppa.20250901.13
T2  - Journal of Public Policy and Administration
JF  - Journal of Public Policy and Administration
JO  - Journal of Public Policy and Administration
SP  - 19
EP  - 36
PB  - Science Publishing Group
SN  - 2640-2696
UR  - https://doi.org/10.11648/j.jppa.20250901.13
AB  - The study innovatively investigates the relationship between maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery in the public sector. The study uncovers the interplay between these factors and their impact on service delivery outcomes. To achieve such outcomes, we utilize a structured questionnaire to assess variables related to maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery. Data were collected from a sample of public sector employees and stakeholders, which was then subjected to rigorous statistical analysis. The research employs a range of statistical techniques to investigate correlations, direct and mediating effects, and construct reliability. Inarguably, the use of a survey instrument and statistical analysis allowed for the quantitative assessment of the research hypotheses. The findings reveal significant correlations between maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery. It identifies employee engagement, public perception and trust as mediating variables that play crucial roles in influencing service delivery outcomes. The findings provide distinctive insights into the complex dynamics of service delivery in the public sector, emphasizing the importance of resource allocation, employee engagement, and public relations efforts. Our research contributes to the field by examining the relationships among maintenance culture, resource allocation, employee engagement, public perception and trust, and service delivery in the specific context of the public sector. It introduces the mediating roles of employee engagement and public perception and trust, adding a novel dimension to our understanding of service delivery dynamics. The study's originality lies in its empirical investigation of these complex interactions, shedding light on the factors that influence service delivery outcomes in public organizations.
VL  - 9
IS  - 1
ER  -

    Copy | Download

Author Information
Download PDF
  • Abstract
  • Keywords

  • Document Sections

    1. 1. Introduction
    2. 2. Literature Review
    3. 3. Research Methods
    4. 4. Results and Discussion
    5. 5. Conclusions
    Show Full Outline
  • Abbreviations
  • Conflicts of Interest
  • References
  • Cite This Article
  • Author Information

About Us

Science Publishing Group (SciencePG) is an Open Access publisher, with more than 300 online, peer-reviewed journals covering a wide range of academic disciplines.

Learn More About SciencePG

Products

Information

Important Link

Copyright © 2012 -- 2025 Science Publishing Group – All rights reserved.