Reproduction Package for Consolidating Rather Than Guiding Bioeconomy Visions Center on Existing Technological Trajectories in Swedish Forestry

This repository contains the reproduction package for: Kreutzer, P. J. (2025). Consolidating Rather Than Guiding: Bioeconomy Visions Center on Existing Technological Trajectories in Swedish Forestry. This study is included as a chapter in the PhD dissertation, Trees Like Cabbages – Innovation Towards a Forest-Based Bioeconomy, Lund University, 2026. Contents The package includes all code and data needed to reproduce the figures, tables, and inline statistics reported in the paper. The analysis pipeline is implemented in Python and the manuscript is authored in Quarto. The repository contains: - The manuscript source files (paper.qmd, _code_setup.qmd, _appendix-data.qmd) - The Python analysis package (swinno_bioeconomy_directionality/), which computes bioeconomy innovation shares, interrater reliability statistics, and all figures - Classification data derived from the SWINNO database (Swedish innovations, 1970--2021), including manually coded bioeconomy vision labels and eco-innovation types - External reference data for interrater reliability assessment and firm-level collaboration networks How to Reproduce The package uses https://pixi.sh to manage all dependencies, including Python, Quarto, and a TeX Live distribution. To reproduce: pixi install -e repro pixi run -e repro reproduce This executes four tasks in sequence: computing bioeconomy innovation shares, calculating interrater reliability statistics, generating all manuscript figures, and rendering the final PDF via Quarto and LuaLaTeX. The package has been tested on macOS (ARM).Dependencies are solved for macOS, Linux, and Windows.On Windows, I recommend running inside WSL (Windows Subsystem for Linux) for full compatibility. Data Sources Innovation data are drawn from the SWINNO database, a literature-based innovation output database covering significant innovations commercialized in Sweden.The bioeconomy vision classifications were coded manually by the author, with an independent interrater reliability check conducted by a research assistant.Firm-level collaboration data are derived from SWINNO's producer and collaborator records.