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Value Trade-Offs in Matching Functions

Abdulaziz Alshalfan et al.

International Journal of e-Business Research2025https://doi.org/10.4018/ijebr.396248article
AJG 1
Weight
0.50

What the paper says

Online labor markets (OLMs) face challenges in refining match functions to connect clients with suitable service providers. This study examines how platform-controlled factors (number of assigned providers, matching speed) and project-specific attributes (description length, requested hours) affect matching effectiveness across four outcomes: hiring probability, hiring time, billed hours, and profit per contracted project. Using data from a premium OLM platform, the study reveals important operational and financial trade-offs. Expanding the provider pool improves hiring probability and project profitability but lengthens hiring time. Faster matching boosts hiring likelihood without compromising quality. Larger requested workloads reduce hiring probability but raise profitability. These findings offer actionable insights into how calibrated matching strategies can improve OLM performance across the project lifecycle, contributing to platform governance and digital operations literature.

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Cite this paper

https://doi.org/https://doi.org/10.4018/ijebr.396248

Or copy a formatted citation

@article{abdulaziz2025,
  title        = {{Value Trade-Offs in Matching Functions}},
  author       = {Abdulaziz Alshalfan et al.},
  journal      = {International Journal of e-Business Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4018/ijebr.396248},
}

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Value Trade-Offs in Matching Functions

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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.