Uncovering Key Features for Model-Driven Engineering of Complex Performance Indicators: A Scoping Review

TL;DR

This paper conducts a scoping review to map and analyze the modeling features and frameworks used in Model-Driven Engineering for Complex Performance Indicators, addressing a gap in comprehensive understanding.

Contribution

It provides a comprehensive mapping of modeling features and compares frameworks, advancing understanding of MDE applications in CPI design and management.

Findings

Mapped key modeling features in literature

Compared coverage of different modeling frameworks

Identified gaps and future research directions

Abstract

This paper addresses challenges of designing and managing Complex Performance Indicators (CPI), which amalgamate individual indicators to measure latent, yet crucial business factors like customer satisfaction or sustainability indices. Despite their significant value, designing and managing CPI is intricate; they evolve with rapidly changing business contexts and present comprehension and explanation challenges for end-users. Model-Driven Engineering (MDE) emerges as a potent solution to overcome these hurdles and ensure CPI adoption, though its application to CPI remains an understudied research area. While prior efforts targeted specific CPI modeling objectives, a comprehensive overview of literature advancements is lacking. This study addresses this gap by conducting a scoping review yielding dual outcomes: (1) a comprehensive mapping of modeling features in the literature and (2) a comparative analysis of the coverage offered by the modeling frameworks. These outcomes enhance CPI understanding in academic and practitioner circles and offer insights for future MDE CPI advancements.