Scale-Opportunity Matrix Dataset for Prioritizing Indonesia’s Creative Economy Subsectors, 2019–2024
Description
This dataset supports an MBA research thesis and related scholarly outputs on prioritizing Indonesia’s creative-economy subsectors using macroeconomic evidence. It contains official source documents, structured data, and calculation materials for the Scale–Opportunity Matrix, a sample-relative framework for subsector comparison and evidence-informed decision support. The dataset covers sixteen statistical analytical units for 2019–2024. Applications and Game Development are combined because they form one unit in the official data. This scope is not a permanent legal taxonomy. It differs from the earlier seventeen-subsector classification, which listed Applications and Games separately, and from the twenty-one-subsector taxonomy introduced by Peraturan Presiden Nomor 37 Tahun 2026 after the empirical data were finalized. The later taxonomy is acknowledged but not retrospectively applied. The matrix uses official subsector-level gross value added (GVA) and employment data. GVA is reported at current prices (ADHB) in billion Indonesian rupiah; employment is reported as employed persons. Standardized 2024 GVA and employment levels form Scale. Standardized 2019–2024 GVA compound annual growth and apparent labor-productivity compound annual growth form Opportunity. Apparent labor productivity is GVA per employed person; it is not total factor productivity, worker efficiency, job quality, or a direct measure of firm capabilities. Opportunity represents observed historical trajectory, not a forecast. The workbook documents data organization, productivity and CAGR calculations, z-score normalization, equal-weight composite construction, median-threshold quadrant classification, and ten sensitivity specifications. Scores and classifications are descriptive and sample-relative, not automatic rankings, causal estimates, or predetermined funding instructions. The source documents were obtained through the Ministry of Creative Economy’s public-information service on 8 January 2026. The series use official statistics produced by Badan Pusat Statistik and processed in 2025 by the Ministry’s Data and Information Center, preserving provenance and supporting independent verification. This version replaces the former binary stability label with baseline-classification retention counts and rates across the ten alternative specifications. “Fully invariant” means retaining the baseline quadrant in all ten; “specification-sensitive” means changing at least once. This correction affects only the robustness-summary interpretation. No source data, indicators, standardized values, composite scores, thresholds, baseline classifications, or scenario-specific classifications have changed. The dataset supports transparency, reproducibility, and critical assessment. Final interpretation remains subject to legal mandates, institutional feasibility, distributional considerations, public values, and managerial judgment.
Files
Steps to reproduce
To reproduce the results, download the Excel calculation workbook and the supporting government GVA and Employment files, then review the worksheets in numerical order. Confirm the sixteen statistical analytical units in `01_SUBSECTOR_MASTER`, including the combined Applications and Game Development unit. Verify the 2019–2024 GVA and Employment values in `02_RAW_MACRO_GVA` and `03_RAW_MACRO_EMPLOYMENT` against the supporting source documents. Use these values to calculate annual apparent labor productivity in `04_RAW_MACRO_PRODUCTIVITY`, annual productivity changes and 2019–2024 Productivity CAGR in `05_PRODUCTIVITY_GROWTH`, and annual GVA changes and 2019–2024 GVA CAGR in `06_GVA_CAGR`. Confirm the four fixed indicators in `07_INDICATOR_SUMMARY`: 2024 GVA, 2024 Employment, 2019–2024 GVA CAGR, and 2019–2024 apparent labor-productivity CAGR. Standardize each indicator across the sixteen subsectors using z-score normalization based on the sample standard deviation in `08_Z-SCORE_NORMALIZATION`. In `09_COMPOSITE_INDICES`, calculate Scale as the equal-weight average of standardized GVA and Employment and Opportunity as the equal-weight average of standardized GVA CAGR and apparent labor-productivity CAGR. Use the median Scale and Opportunity scores to determine High and Low positions and assign the four baseline quadrant classifications in `10_QUADRANT_CLASSIFICATION`. Finally, review the ten alternative specifications in `11_SENSITIVITY_ROBUSTNESS`, covering weight variation, min–max normalization, individual-indicator removal, and mean-threshold classification. Calculate each subsector’s baseline-classification retention count and rate by comparing its ten alternative classifications with its baseline quadrant. Retain full numerical precision during calculation and round values only for presentation. The baseline classification remains the primary result, while the sensitivity outputs indicate whether each classification is invariant or dependent on one or more tested methodological choices.
Institutions
- Bandung Institute of TechnologyWest Java, Bandung