A Statistical Approach to Discovering Process Regime Shifts and Their Determinants

Abstract

Systematic behavioral regime shifts inevitably emerge in real-world processes in response to various determinants, thus resulting in temporally dynamic responses. These determinants can be technical, such as process handling, design, or policy elements; or environmental, socio-economic or socio-technical in nature. This work proposes a novel two-stage methodology in which the first stage involves statistically identifying and dating all regime shifts in the time series process event logs. The second stage entails identifying contender determinants, which are statistically and temporally evaluated for their role in forming new behavioral regimes. The methodology is general, allowing varying process evaluation bases while putting minimal restrictions on process output data distribution. We demonstrated the efficacy of our approach via three cases of technical, socio-economic and socio-technical nature. The results show the presence of regime shifts in the output logs of these cases. Various determinants were identified and analyzed for their role in their formation. We found that some of the determinants indeed caused specific regime shifts, whereas others had no impact on their formation.