A triangulation approach to impact evaluation
Bibliographic Data
| ID | 12567944 |
|---|---|
| Authors | Staffan Bjurulf (Karlstad University and Region Värmland, Sweden, corresponding author), EVERT VEDUNG (0000-0002-0748-6571, Uppsala University), C G Larsson (Larsson Consulting, Sweden) |
| Year | 2013 |
| Volume | 19 |
| Issue | 1 |
| Pages | 56-73 |
| Publication date | 2013-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Evaluation (JOURNAL) |
| Journal identifiers | ISSN: 1356-3890 • E-ISSN: 1461-7153 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/1356389012472248 |
| OpenAlex | W2153267539 |
| Language | EN |
| Citations received | 4 |
| References cited | 11 |
This article presents a viable method to overcome the challenge of producing reliable cause–effect findings in impact evaluation. The Measuring Cluster Effects through Triangulation method (MCET) involves methodological triangulation. Three designs − shadow controls, generic controls, and process tracing − are combined to shed light on causality. When these three approaches are triangulated, cause–effect findings will be more reliable. The MCET combination is a feasible alternative when randomized controlled trials and matched controls are impossible or impracticable. It is also an alternative to using a single non-experimental design, particularly in situations where expenditure is great and the causality issue is pressing. In this article, the MCET approach is illustrated by information drawn from a set of evaluations performed on the activities of the Compare Foundation, a cluster organization in Sweden in the Information and Communication Technology sector. Regionally based in Karlstad, County Värmland, and founded in 2000, the Compare cluster organization has adapted the MCET to its own activities
Cartography · Causality (physics · Cluster (spacecraft · Data mining · Data science · Geography · Management science · Operations research · Process (computing · Set (abstract data type · Shadow (psychology · Triangulation · Computer Science · Educational Assessment and Improvement · Engineering · Evaluation and Performance Assessment · Psychology · Qualitative Comparative Analysis Research
Evaluation
Practical Program Evaluation
Logic models
Rethinking Social Inquiry
Public Policy and Program Evaluation
A Contribution to Current Debates in Impact Evaluation
Contribution analysis
Capturing effects of interventions, policies and programmes in the European context
Conceptual Challenges Confronting Cluster Evaluation
Understanding Process Tracing
| Citations per year | 0.33 |
|---|---|
| Citation span | 2014 - 2021 (8) |
| Highly cited | No |