Redefining the Strategic Integrated Employee Reward Mix in Remote Contexts: Insights From the Lebanese Workforce

Carole Serhan et al.

Strategic Change2026https://doi.org/10.1002/jsc.70072article
AJG 2
Weight
0.50

What the paper says

Remote work has reshaped employee expectations and the meaning of organizational rewards. This study examines how organizations in Lebanon can redesign strategic reward systems to sustain employee motivation, equity perceptions, and job satisfaction in remote/hybrid settings. Lebanon provides a critical case because economic volatility and constrained pay growth increase reliance on non‐monetary rewards and heighten fairness concerns in distributed work. Using semi‐structured qualitative interviews with 20 employees across key sectors, thematic analysis revealed four areas of transformation: (1) a shift from presence‐based to performance‐based recognition, (2) increased demand for flexible and customizable benefits, (3) the central role of technology in communication and reward visibility, and (4) the emergence of human‐centric and culturally‐appropriate practices. Findings support Herzberg's Two‐Factor Theory, Self‐Determination Theory, Equity Theory, and Media Richness Theory, leading to a proposed Strategic Integrated Reward Mix tailored to developing market contexts. The article offers a context‐grounded interpretation of reward transformation in Lebanon and provides practical recommendations for HR leaders and policymakers.

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https://doi.org/https://doi.org/10.1002/jsc.70072

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@article{carole2026,
  title        = {{Redefining the Strategic Integrated Employee Reward Mix in Remote Contexts: Insights From the Lebanese Workforce}},
  author       = {Carole Serhan et al.},
  journal      = {Strategic Change},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/jsc.70072},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.