Determinants of Employee Turnover Intention – Comprehensive Study Notes

Introduction & Background

  • Human capital viewed as the core driver of organisational performance; high turnover undermines productivity, growth, quality and morale.

  • Global trend: professional labour markets experience persistent turnover; service industries particularly vulnerable.

  • Ethiopian Electric Power (EEP) created under Council of Ministers Regulation No.302/2013; handles generation, transmission & bulk sales of electricity and has struggled with rising attrition despite multiple retention attempts.

  • Latest head-office workforce snapshot (2019):

    • Total employees = 6 3546\,354

    • Professionals = 1 3871\,387

    • Non-professionals = 4 9674\,967

    • Installed capacity operated = 4 269  MW4\,269\;\text{MW}

Core Concepts & Definitions

  • Turnover = "termination of an individual’s employment with a given firm" (Tett & Meyer, 1993); movement of employees out of an organisation.

  • Turnover Intention = conscious, deliberate plan to leave one’s current employer.

  • Two basic turnover forms:

    • Voluntary (employee initiated)

    • Involuntary (employer initiated)

  • Further distinctions: functional vs. dysfunctional; avoidable vs. unavoidable; discharge vs. downsizing; separations vs. accessions.

  • Internal factors (controllable) vs. External factors (uncontrollable) in driving exits.

Typology of Turnover

  • Involuntary: discharge (performance/discipline), downsizing, mandated retirement, illness, death.

  • Voluntary: resignation, avoidable (pay, supervision, conditions) vs. unavoidable (spouse relocation, health).

  • Other HR movements: internal transfers, promotions ("internal turnover").

Theoretical Foundations

  • Herzberg’s Motivator–Hygiene: satisfaction driven by motivators (achievement, recognition, responsibility, advancement, growth, work itself); dissatisfaction by hygiene factors (pay, policies, supervision, conditions, security, status).

  • Three-Component Model of Commitment (Meyer & Allen, 1991): affective, continuance, normative commitment; low commitment → higher intention.

  • Mobley (1977) process model: dissatisfaction → thoughts of quitting → job search → comparison of alternatives → intention → turnover.

  • Unfolding Model (Lee & Mitchell, 1994): four decision paths triggered by positive/negative "shocks".

  • Calling theory: strong sense of calling decreases intention (Dik & Duffy, 2009).

Determinants of Turnover Intention (empirical list)

  • Intrinsic motivators: achievement, recognition, responsibility, advancement, growth, meaningful work.

  • Extrinsic / hygiene: compensation & pay equity, supervisory support, physical work conditions, interpersonal climate, organisational policies, job security, status, communication quality.

  • Additional drivers: work stress, role conflict, work–life imbalance, leadership style (transformational vs. laissez-faire), perceived organisational support, autonomy, training & development, talent-management clarity.

  • Individual variables: age (younger ↑ intention), education (higher ↑ intention), tenure, marital status, personality traits.

  • Job attitudes: satisfaction, engagement, organisational commitment.

Organisational Profile – Ethiopian Electric Power

  • Origin: 1956 (EELPA) → EEPCO → split 2013 into EEP & EEU.

  • Mandate: feasibility, design, construction, O&M of generation & transmission, wholesale to EEU, large industries, neighbouring states; allowed to lease lines, float bonds, negotiate loans.

  • Vision: first-class regional power provider, underpinning middle-income economy target (2020 plan).

  • Recent turnover table (2022/23): escalating exits despite extra hiring; cited internally as "frequent & substantial".

Research Problem Statement

  • Limited Ethiopian literature on turnover; need to pinpoint context-specific drivers inside EEP.

  • Identified gaps: role of management practices, cultural dynamics, CPD, organisational support.

  • Study factors operationalised via Herzberg list + demographics.

Research Questions

  1. Which employee attributes (age, education, sex, tenure) predict intention?

  2. Which organisational factors (policy, motivation, leadership) matter?

  3. How are work environment, pressure & job satisfaction linked to turnover?

  4. What are the implications for EEP performance?

Objectives

  • General: identify determinants of turnover intention at EEP.

  • Specific: profile intention level; test relationships among demographics, organisational factors & satisfaction; assess impact on performance; propose retention strategies.

Scope & Methodology

  • Context: EEP head-office; last two fiscal years.

  • Design: descriptive-explanatory; mixed-methods (questionnaire + semi-structured interviews).

  • Population = N=1 211N=1\,211; sample size via Yamane (1967):
    n=N1+N(e)2=1 2111+1 211(0.05)2=301n=\frac{N}{1+N(e)^2}=\frac{1\,211}{1+1\,211(0.05)^2}=301

  • Sampling: stratified random (by job group) + judgmental for ex-staff interviews.

  • Instruments: close & open-ended items, Likert 5-point; interview guide for HR, managers, leavers.

  • Analysis: SPSS 20; descriptive stats (mean, SD, %), Pearson r, multiple regression; reliability α = 0.874.

  • Ethics: informed consent, anonymity, data used only for academic purpose.

Key Empirical Results

  • Demographics (n = 286 usable responses): 60 % male; largest age cluster 25–30 yrs (24 %); 70 % BA holders; 56 % >11 yrs tenure.

  • Personal fit: 74 % agree they are right person for job; yet 47 % believe highly qualified staff have stronger exit intentions; 46 % say younger staff more likely to quit.

  • Job Satisfaction:

    • 49 % admit job satisfaction strongly affects turnover.

    • 44 % satisfied with current job; 31 % force themselves to work.

    • 47 % happy with placement by skills, but 46 % feel excluded from decision-making.

    • 51 % report manageable stress/time.

  • Organisational Environment:

    • 50 % disagree that they work in unclean environment; 44 % say supervisor relations good.

    • 26 % feel environment pushes them to leave; 49 % like overall conditions; 49 % have needed tools.

  • Salary & Reward (strongest dissatisfier):

    • 76 % claim low pay drives exits; 58 % reject idea that they are paid per experience; 63 % say salary poor relative to work.

    • 66 % dissatisfied with net worth; 70 % deny reward matches performance; 66 % say recognitions inadequate.

  • Leadership:

    • 45 % agree managers give clear goals; 43 % say leaders highly effective.

    • 37 % say leaders provide growth chances; 38 % get regular feedback.

  • Peer Influence: >50 % indicate peers shape life & encourage work; 62 % receive feedback from friends.

  • Policy: 65 % recognise existence; 48 % find it understandable; 36 % neutral on whether it resolves challenges; 36 % fear lack of policy creates risks.

  • Family: 50 % get family support; 49 % discuss work at home; 38 % say family does NOT push them to leave.

  • Correlation highlights (p < 0.01):

    • Salary–Turnover Intention (r ≈ 0.52 strong)

    • Organisation Environment–Salary (r ≈ 0.52)

    • Leadership–Salary (r ≈ 0.45)

    • Job Satisfaction positively correlated with all independent factors (0.29–0.42 range).

Effects & Costs of Turnover

  • Direct: advertising, recruitment, selection, onboarding, training, overtime, temp cover.

  • Indirect: lost productivity, customer dissatisfaction, tacit knowledge leakage, low morale, supervisory time; empirical savings example: Caterpillar saved $8.8 m\$8.8\,\text{m} after reducing attrition.

Retention & Mitigation Strategies Discussed

  • Compensation overhaul: competitive pay, performance-linked increments, retention bonuses.

  • Career paths: clear promotion ladders, succession planning, cross-training, CPD.

  • Participative management: involve staff in decisions, seek feedback loops.

  • Recognition systems: non-monetary awards, public appreciation, fair appraisals.

  • Work-life initiatives: flexible rosters, manageable workloads, wellness programs.

  • Policy revision: update HR manuals to reflect global best practice & local culture; transparent grievance channels.

  • Leadership development: coaching supervisors in transformational, supportive behaviours.

Research Gaps Identified

  • Scarcity of Ethiopian, utility-sector longitudinal data.

  • Need integrated multi-factor frameworks, sector-specific variables, and employee voice studies.

  • Limited examination of mental-health / well-being links to turnover.

Conceptual Framework Recap (EEP Study)

  • Independent blocks: personal characteristics, job satisfaction, organisational/work environment, salary & reward, leadership, peer pressure, policy, family.

  • Dependent variable: Turnover Intention\text{Turnover Intention}.

Conclusions Drawn by Study

  • Salary & reward dissatisfaction is principal trigger of intention at EEP.

  • Job mis-placement (skills ≠ role), limited growth, low involvement in decisions reinforce desire to quit.

  • Work environment relatively acceptable; leadership moderately positive but growth support weak.

  • Family & peer influence mixed but less dominant than pay-related issues.

Recommendations Offered

  • Immediate salary-scale revision and establishment of transparent, merit-based reward & recognition schemes.

  • Ensure job placement matches qualifications; formal JD reviews.

  • Institutionalise employee participation in decision-making forums.

  • Launch structured career development & training opportunities.

  • Introduce individual & team incentives tied to measurable outputs.

  • Systematically monitor turnover metrics and undertake exit-interview analytics.

  • Continuous policy updates in line with global HRM standards and EEP’s strategic direction.

Key Formulae & Quantitative References

  • Yamane sample-size determination:
    n=N1+N(e)2n=\frac{N}{1+N(e)^2} (used with N=1 211,  e=0.05N=1\,211,\; e=0.05 → n=301n=301)

  • Reliability (Cronbach’s α) across 48‐item scale: α=0.874\alpha=0.874 (high internal consistency).

Glossary of Selected Terms

  • Turnover (voluntary / involuntary / functional / dysfunctional)

  • Unavoidable vs. Avoidable exits

  • Hygiene vs. Motivator factors

  • Affective / Continuance / Normative commitment

  • Work–Life Balance (WLB)

  • Perceived Organisational Support (POS)

Real-World & Ethical Implications

  • High attrition risks derailing Ethiopia’s power-sector ambitions; impacts national grid reliability, regional export contracts, and economic growth targets.

  • Ethical obligation: provide safe, fair, rewarding employment; minimise psychosocial harm; align HR policies with equity & justice.