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

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 (combined experience: 147 years; M = 11.3, SD = 2.9). The file comprises seven sheets: (1) expert panel demographics and selection criteria; (2) the complete Delphi questionnaire instrument covering 47 parameters across the MDP transition function (P1–P20), reward function coefficients (P21–P24), fatigue and burnout dynamics (P25–P31), action cost structure (P32–P40), and instrument validation items (P41–P47); (3–5) individual expert responses for Rounds 1, 2, and 3, with convergence statistics per parameter (median, mean, SD, IQR, CV); (6) convergence analysis demonstrating full consensus by Round 3 — Mean IQR converged from 0.28 to 0.12 (threshold < 0.15), the count of probability parameters with IQR > 0.20 decreased from 23 to 0 out of 31 (threshold < 5), and Mean CV decreased from 0.41 to 0.18 (threshold < 0.25); and (7) final adopted parameter values with full traceability to the MDP transition function and reward specification.