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Using logic model and visualization to conduct portfolio evaluation

Author

Listed:
  • Wu, Huang
  • Shen, Jianping
  • Jones, Jeffrey
  • Gao, Xingyuan
  • Zheng, Yunzheng
  • Krenn, Huilan Y.

Abstract

Portfolio evaluation is the evaluation of multiple projects with a common purpose. While logic models have been used in many ways to support evaluation, and data visualization has been used widely to present and communicate evaluation findings, adopting logic models for portfolio evaluation and using data visualization to share findings simultaneously is surprisingly limited in the literature. With the data from a sample portfolio of 209 projects which aims to improve the system of early care and education (ECE), this study illustrated how to use logic model and data visualization techniques to conduct a portfolio evaluation by answering two evaluation questions: “To what extent are the elements of a logic model (strategies, sub-strategies, activities, outcomes, and impacts) reflected in the sample portfolio?” and “Which dominant paths through the logic model were illuminated by the data visualization technique?” For the first question, the visualization technique illuminated several dominant strategies, sub-strategies, activities, and outcomes. For the second question, our visualization techniques made it convenient to identify critical paths through the logic model. Implications for both program evaluation and program planning were discussed.

Suggested Citation

  • Wu, Huang & Shen, Jianping & Jones, Jeffrey & Gao, Xingyuan & Zheng, Yunzheng & Krenn, Huilan Y., 2019. "Using logic model and visualization to conduct portfolio evaluation," Evaluation and Program Planning, Elsevier, vol. 74(C), pages 69-75.
    • Handle: RePEc:eee:epplan:v:74:y:2019:i:c:p:69-75
    DOI: 10.1016/j.evalprogplan.2019.02.011
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    References listed on IDEAS

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    Cited by:

    1. Tavana, Madjid & Khosrojerdi, Ghasem & Mina, Hassan & Rahman, Amirah, 2019. "A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process," Evaluation and Program Planning, Elsevier, vol. 77(C).

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