Sustainable Human Resource Management and Career Quality in Public Utilities: Evidence from Jordan’s Electricity Sector
Abstract
:1. Introduction
2. Literature Review
2.1. Conceptual Framework
2.1.1. Sustainable Human Resource Management (HRM)
2.1.2. Career Quality
2.1.3. Socio-Cultural Context of HRM in Jordan
2.2. HRM Practices and Career Quality
2.2.1. Strategic Planning
2.2.2. Transparent Recruitment
2.2.3. Targeted Training
2.2.4. Intrinsic Motivation
2.3. Research Gaps and Theoretical Integration
2.4. Conceptual Model
- The general hypothesis of this study asserts a statistically significant effect of HRM practices on career quality at the Jordanian Electricity Distribution Company. This general hypothesis leads to the following sub-hypotheses regarding the specific impacts of HRM practices:
- H1: Strategic workforce planning positively enhances career quality (job security/promotion equity). Justification: SET argues that long-term workforce planning signals organizational commitment, fostering employee trust and reciprocity [18,21]. At JEDCO, proactive planning (e.g., forecasting skill gaps) reduces layoff anxiety, as evidenced by [49] study in Iraqi utilities (18% reduction in layoff fears). However, bureaucratic inertia may weaken this effect compared to Western contexts.
- H2: Transparent recruitment practices positively enhance career quality (promotion equity and participation). Justification: SET emphasizes fairness as a cornerstone of trust [22]. Merit-based hiring counters tribal favoritism [8], but JEDCO’s reliance on informal networks disrupts reciprocity. AI-driven anonymized screening [24] could restore equity, as shown in Egypt’s EEHC [27].
- H3: Targeted training programs positively enhance career quality (job security and skill-based promotions). Justification: Training fulfills SET’s mutual gains principle: organizations invest in skills, employees reciprocate with adaptability [29]. JEDCO’s technicians report 30% higher job security after smart grid training [5] but bureaucratic workflows limit skill application (54% vs. 89% in South Korea).
- H4: Intrinsic motivation mechanisms (e.g., recognition) positively enhance career quality (job security and engagement). Justification: Intrinsic motivators (autonomy, purpose) align with SET’s psychological contract [25]. At JEDCO, recognition programs increased participation by 25% [40], but tribal hierarchies suppress merit-based reciprocity.
3. Methodology
3.1. Research Design
3.2. Sample and Sampling Strategy
3.2.1. Population and Sampling
3.2.2. Sampling Technique
3.3. Data Collection Procedure
3.4. Variables and Operationalization
3.5. Validity and Reliability
3.6. Data Analysis
- Descriptive Statistics: Descriptive statistics, including means, standard deviations, skewness, and kurtosis, were calculated to assess the normality of data distribution. These statistics provide insights into the characteristics of the sample and help in understanding the basic patterns within the dataset.
- Inferential Statistics: To evaluate the impact of HRM practices on career quality, hierarchical regression analyses were employed for hypothesis testing with a significance level that was set at p < 0.05 for interpreting results, ensuring robustness in the determination of significant relationships between the variables of interest. Hierarchical regression was selected over SEM due to sample size constraints (n = 173). Ref. [81] recommend regression for small-to-moderate samples to avoid overfitting. The analysis was conducted utilizing: SPSS v28.
- To mitigate common method bias, we employed procedural remedies: (1) ensuring respondent anonymity to reduce social desirability bias, (2) separating scale items for independent/dependent variables in the questionnaire, and (3) conducting Harman’s single-factor test, which revealed no dominant factor (largest variance explained = 28.7%, below the 50% threshold). While self-report data remains a limitation, these steps reduce bias risks [82]. While procedural remedies (e.g., anonymization) reduced social desirability bias, self-report data remain subjective. Future studies should triangulate supervisor ratings (e.g., performance metrics) to validate employee perceptions. Additionally, JEDCO’s refusal to disclose tribal affiliations limited moderation analysis of bias effects critical extension requiring further access.
3.7. Ethical Considerations
4. Analysis
4.1. Descriptive Statistics
4.1.1. Demographic Profile
4.1.2. Variable Distributions
- Career Quality: The mean score for career quality was moderate (M = 3.36), as seen in Table 4. This indicates that, while certain aspects are fulfilling, there is substantial room for enhancement, particularly in the realm of participatory decision-making, a theme emphasized in the existing literature [20]. Participatory decision-making at JEDCO scored moderately (M = 3.36), with employees citing limited avenues for input. This contrasts sharply with [48] study of Peru’s public sector, where telework models increased employee involvement through digital platforms. While JEDCO’s labor-intensive operations limit telework adoption, hybrid forums (e.g., digital suggestion boxes) could replicate [48] “human-centric” approach, fostering inclusivity in hierarchical settings.
- Training: This variable received the lowest average rating at (M = 3.22), as seen in Table 4. This aligns with JEDCO’s recognition that its training programs have become outdated and require immediate rejuvenation to be effective in today’s technological climate [15]. JEDCO’s training programs scored lowest among HRM practices (M = 3.22), reflecting a reactive approach to skill development. This contrasts with [16] systematic review, which advocates for “lifelong learning frameworks” integrating environmental sustainability (e.g., smart grid training). Aligning JEDCO’s programs with renewable energy upskilling, as suggested by [16], would advance SDG 8 (decent work) while preparing employees for Jordan’s energy transition.
4.2. Hypotheses Testing
- Significant Impact of Training: The analysis indicates a statistically significant positive impact of training on career quality (β = 0.15, p = 0.044). The importance of training lies in its ability to enhance the skills and competencies of employees, positioning them for better career advancement and job satisfaction, thereby aligning with [29], who reported that upskilling significantly reduced turnover rates in their analysis.
- Strong Influence of Motivation: The results underscore that motivation is a critical determinant of career quality (β = 0.48, p < 0.001). This suggests that recognition and opportunities for professional development resonate profoundly with employees, promoting higher levels of engagement and loyalty—supporting the theories outlined in [25] self-determination theory. Employees who perceive their organization as supportive tend to exhibit stronger commitment, inspiring a collaborative atmosphere conducive to innovative decision-making.
- Marginally Significant Role of Planning: Planning was found to have a marginally significant impact on career quality (β = 0.15, p = 0.067), hinting at the importance of proactive workforce strategies that align with organizational needs. This finding reflects the constraints faced by JEDCO, particularly regarding its human resources planning processes, which have lacked robustness in addressing the organization’s long-term skill requirements.
- Non-Significant Effect of Recruitment: Conversely, recruitment showed no statistically significant effect on career quality, with β = 0.14 and a t-value of 1.59. This outcome might reflect biases embedded within recruitment processes at JEDCO, corroborated by previous assertions regarding the reliance on personal networks rather than merit-based evaluations [8].
5. Discussion
5.1. Thematic Discussion
5.1.1. Training as a Driver of Career Quality
5.1.2. Motivation and Social Exchange Dynamics
5.1.3. Recruitment and Planning: Systemic Challenges
5.2. Key Findings for Career Quality
5.2.1. Training and Motivation as Pillars of Career Quality
5.2.2. Recruitment and Planning: Systemic Weaknesses
5.3. Practical Implications
5.4. Theoretical Implications
5.4.1. Validation of Social Exchange Theory (SET)
5.4.2. Divergence from Western Models
6. Conclusions
6.1. Actionable Recommendations for JEDCO
- Digital HR Analytics Dashboard: JEDCO should implement a digital HR analytics dashboard to facilitate real-time workforce planning and data-driven decision-making. This tool should provide features for skill gap analysis and turnover risk metrics, utilizing predictive analytics to ensure that HR planning aligns with national energy transition targets and that training efforts meet workforce needs effectively.
- Biannual Motivation Index: Establishing a biannual Motivation Index will enable JEDCO to systematically measure employee engagement over time. This index should include key metrics related to intrinsic and extrinsic motivation, such as employee autonomy, salary satisfaction, and transparency in promotion criteria. Quarterly pulse surveys can be used to gather insights into employee perceptions and inform targeted motivation strategies.
- Innovative Recruitment Strategies: JEDCO should revamp its recruitment process by incorporating AI-driven tools to anonymize applications and reduce biases in hiring decisions. Collaborating with platforms like LinkedIn Talent Insights can assist in developing competency frameworks that ensure new hires are well-suited to the organization’s evolving needs. Furthermore, introducing gamified training modules in partnership with educational organizations can enhance engagement and learning effectiveness. Ref. [85] advocate for AI-driven anonymized recruitment in hierarchical public sectors, a strategy piloted successfully in Egypt’s EEHC. JEDCO could replicate this approach to mitigate tribal biases, aligning hiring with SDG 8 equity targets. To operationalize “AI-driven recruitment”, JEDCO’s Aqaba region will pilot anonymized hiring in 2024. Pre- and post-intervention retention rates will be measured quarterly (baseline: 63% retention in 2023), with targets to reduce tribal bias by 25% (p < 0.05 via t-test). Given the non-significance of recruitment practices (β = 0.14, p = 0.11), we propose AI-driven anonymized screening [24] to disrupt tribal favoritism.
- Structured Mentorship Initiatives: Management must emphasize career development through comprehensive mentorship programs that align individual aspirations with organizational goals. By fostering a culture of continuous support and development, JEDCO can enhance employee satisfaction and retention.
- Proactive Training Solutions: The HR department should prioritize the establishment of structured recruitment processes that emphasize merit-based assessments over personal biases. Additionally, proactive training solutions that focus on continuous learning will prepare employees for future challenges and enhance workforce efficacy. Gamified training modules (e.g., renewable energy simulations) will be assessed using pre/post-test scores (target: 20% skill improvement; α = 0.05). Develop VR simulations for smart grid troubleshooting, replicating [29] success in upskilling technicians.
- Employee Involvement in Career Development: Employees are encouraged to take an active role in their career development by providing constructive feedback to management regarding their experiences and aspirations. Participation in online learning platforms for certifications in emerging technologies, such as renewable energy, can further facilitate personal growth and competency enhancement.
- Resource Allocation for HR Development: Senior leadership and the board should advocate for resource allocation towards strengthening HR practices and career development initiatives, recognizing their critical role in JEDCO’s success. Developing comprehensive motivational strategies to effectively acknowledge and reward employee contributions is also essential.
- Engagement with Investors and Stakeholders: Investors and stakeholders should remain vigilant about the ongoing improvements needed in HR practices, encouraging management to adopt effective strategies that enhance career quality and organizational performance. Acknowledging the benefits of investing in employee development can yield sustainable growth and improved operational efficiency, solidifying JEDCO’s position in the market.
- Communication with Customers and the Public: Finally, it is important to educate customers and the public about how enhancements in HRM practices can lead to improved service reliability. Informing the community about the connections between effective HRM and customer satisfaction reinforces JEDCO’s commitment to serving both its customers and the wider community.
6.2. Limitations and Future Research
6.3. Sustainability and SDG Alignment
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Definition | Measurement | |
---|---|---|---|
Dependent | Career Quality | Employee perceptions of job security, promotion equity, and participatory decision-making. | 10-item 5-point Likert scale [11] |
Independent | Planning | Strategic alignment of workforce needs with organizational goals. | 9-item 5-point Likert scale [49] |
Recruitment | Fairness and transparency in hiring processes. | 8-item 5-point Likert scale [52] | |
Training | Effectiveness of skill development programs. | 6-item 5-point Likert scale [58] | |
Motivation | Intrinsic and extrinsic incentives influencing performance. | 8-item 5-point Likert scale [25] |
Construct | Cronbach’s α | CR | AVE | HTMT |
---|---|---|---|---|
Career Quality | 0.92 | 0.93 | 0.62 | 0.79 |
Planning | 0.94 | 0.95 | 0.60 | 0.80 |
Recruitment | 0.94 | 0.94 | 0.58 | 0.82 |
Training | 0.91 | 0.92 | 0.57 | 0.83 |
Motivation | 0.88/0.90 | 0.90 | 0.59 | 0.81 |
Variable | Frequency | Percentage | |
---|---|---|---|
Gender | Male | 161 | 93.1% |
Female | 12 | 6.9% | |
Experience | <5 Years | 17 | 9.8% |
5–10 Years | 44 | 25.4% | |
10–15 Years | 44 | 25.4% | |
>15 Years | 68 | 39.3% | |
Education | Higher Education | 13 | 7.5% |
Undergraduate | 86 | 49.7% | |
Diploma | 29 | 16.8% | |
Secondary School | 45 | 26.0% | |
Job Role | Manager | 21 | 12.1% |
Head Department | 34 | 19.7% | |
Engineer | 21 | 12.1% | |
Administrative | 37 | 21.4% | |
Technician | 60 | 34.7% |
Variable | Mean | SD | Skewness | Kurtosis |
---|---|---|---|---|
Career Quality | 3.36 | 0.73 | −0.39 | −0.07 |
Planning | 3.39 | 0.80 | −0.59 | 0.66 |
Recruitment | 3.26 | 0.84 | −0.49 | 0.07 |
Training | 3.22 | 0.85 | −0.23 | −0.26 |
Motivation | 3.34 | 0.78 | −0.53 | 0.25 |
Variable | B | SE | Β | T | p |
---|---|---|---|---|---|
Constant | 0.56 | 0.15 | – | 3.79 | 0.00 |
Planning | 0.14 | 0.08 | 0.15 | 1.84 | 0.07 |
Recruitment | 0.12 | 0.08 | 0.14 | 1.59 | 0.11 |
Training | 0.13 | 0.06 | 0.15 | 2.03 | 0.04 |
Motivation | 0.45 | 0.06 | 0.48 | 7.83 | 0.00 |
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Al-Oun, S.; Al-Khasawneh, Z. Sustainable Human Resource Management and Career Quality in Public Utilities: Evidence from Jordan’s Electricity Sector. Sustainability 2025, 17, 4866. https://doi.org/10.3390/su17114866
Al-Oun S, Al-Khasawneh Z. Sustainable Human Resource Management and Career Quality in Public Utilities: Evidence from Jordan’s Electricity Sector. Sustainability. 2025; 17(11):4866. https://doi.org/10.3390/su17114866
Chicago/Turabian StyleAl-Oun, Salem, and Ziad (Mohammed Fa’eq) Al-Khasawneh. 2025. "Sustainable Human Resource Management and Career Quality in Public Utilities: Evidence from Jordan’s Electricity Sector" Sustainability 17, no. 11: 4866. https://doi.org/10.3390/su17114866
APA StyleAl-Oun, S., & Al-Khasawneh, Z. (2025). Sustainable Human Resource Management and Career Quality in Public Utilities: Evidence from Jordan’s Electricity Sector. Sustainability, 17(11), 4866. https://doi.org/10.3390/su17114866