The impact of a proposal for innovation measurement in the software industry
Paper in proceeding, 2020

Measuring an organization's capability to innovate and assessing its innovation output and performance is a challenging task. Previously, a comprehensive model and a suite of measurements to support this task were proposed.
In the current paper, seven years since the publication of the paper titled Towards innovation measurement in the software industry, we have reflected on the impact of thework.
We have mainly relied on quantitative and qualitative analysis of the citations of the paper using an established classification schema.
We found that the article has had a significant scientific impact (indicated by the number of citations), i.e., (1) cited in literature from both software engineering and other fields, (2) cited in grey literature and peerreviewed literature, and (3) substantial citations in literature not published in the English language. However, we consider a majority of the citations in the peer-reviewed literature (75 out of 116) as neutral, i.e., they have not used the innovation measurement paper in any substantial way. All in all, 38 out of 116 have used, modified or based their work on the definitions, measurements or the model proposed in the article. This analysis revealed a significant weakness of the citing work, i.e., among the citing papers, we found only two explicit comparisons to the innovation measurement proposal, and we found no papers that identify weaknesses of said proposal.
This work highlights the need for being cautious of relying solely on the number of citations for understanding impact, and the need for further improving and supporting the peer-review process to identify unwarranted citations in papers.

Citation analysis






Nauman Bin Ali

Blekinge Tekniska Högskola, BTH

Henry Edison

Lero - The Irish Software Engineering Research Centre

Richard Torkar

University of Gothenburg

Stellenbosch Institute for Advanced Study (STIAS)

International Symposium on Empirical Software Engineering and Measurement

19493770 (ISSN) 19493789 (eISSN)

978-145037580-1 (ISBN)

14th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2020
Virtual; online, Italy,

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Other Engineering and Technologies not elsewhere specified

Software Engineering



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