TEST 2 - MDP Framework for Expert Knowledge Management in Software Industry — Delphi Expert Elicitation Dataset

This dataset supports the paper "Optimizing Expert Knowledge Investments in the Software Industry: A Markov Decision Process Approach to Innovation in Knowledge Management" (submitted to Journal of Innovation & Knowledge, Elsevier).
The dataset contains the complete results of a three-round modified Delphi expert elicitation study conducted to calibrate the transition probabilities and model parameters of a Markov Decision Process (MDP) framework for expert knowledge management. Thirteen domain experts (5 Chief Technology Officers and 8 Senior Engineering Managers) from the Argentine software industry participated across three rounds over six weeks.
The file comprises seven sheets: (1) expert panel demographics and selection criteria; (2) the complete Delphi questionnaire instrument covering 47 parameters; (3–5) individual expert responses for Rounds 1, 2, and 3; (6) convergence analysis including IQR, coefficient of variation, and inter-rater reliability metrics (ICC(2,k) = 0.84; Fleiss' κ = 0.71); and (7) final adopted parameter values — including both Round 3 median and mean estimators — with full traceability to the MDP transition function and reward specification used in the manuscript.
This dataset enables complete reproducibility of all model parameters from raw expert judgment to final adopted values (47 parameters × 13 experts × 3 rounds = 1,833 data points).