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Record W2570885528

Innovation success: an empirical study of software development projects in the context of the open source paradigm

2007· article· en· W2570885528 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsWestern University
Fundersnot available
KeywordsKnowledge managementNew product developmentLicenseEmpirical researchContext (archaeology)Software developmentDistributed developmentComputer scienceEngineeringProcess managementSoftwareBusinessMarketing
DOInot available

Abstract

fetched live from OpenAlex

New product development (NPD) performance is a relevant subject within operations management, particularly in the software industry. Though project managers have long tried to improve the software NPD process, a new paradigm has recently attracted their attention: the Open Source Software (OSS) model. OSS is developed collaboratively—mainly by dispersed teams of volunteers—under licensing terms that make the complete source code publicly available and allow redistribution of modified versions. In contrast to prevalent norms, OSS thrives not by enclosing intellectual property (IP) but rather by opening it through the project's license. The first research question is therefore: How do OSS licenses impact development performance? Secondly, OSS enables the collaboration of users as co-developers, prompting the question: How does the community-level structure of an OSS development project impact development performance? Finally, a developer is the locus of key decisions for the project, leading to the third question: How does the collaboration structure of the core development team impact development performance? This is an empirical field study of working OSS projects using archival data from electronic sources. NPD performance was measured using project productivity, product quality, and product popularity. Social network analysis was used for the measurement of the collaboration structure of core developer teams. The analysis was done using regression and time series techniques. Besides improving over extant work from the research design standpoint, this dissertation offers several contributions. The impact on performance of the project's IP policy in the form of license choice was confirmed and an association between the relative size of the external community and performance was found. Also, this study showed that product quality suffers when NPD projects are crowded, but that the amount of boundary spanning activity was positively associated with product quality. This is also the first study to operationalize and test the concept of temporal dispersion in distributed teams. Other contributions refer to the practical design of NPD project teams and their task allocation policy. Keywords: New Product Development, Innovation, Software Projects, Open Source Software, Productivity, Quality, Social Network Analysis Linear Regression, Time Series, Empirical Research, Archival Data Analysis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.354
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations13
Published2007
Admission routes1
Has abstractyes

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