The Interplay between Big Data and Sustainable Performance Management with Multiple-Case Studies

Abstract

This study proposed the data-driven sustainable performance management model (DD-SPMM) under a big data lens, underpinned by resource-based view (RBV), institutional theory, dynamic capability view (DCV), and contingency theory, to achieve the intent of stakeholder and paradox theories. It utilizes a confirmative research design where 171 responses were collected via questionnaires from the Telecommunication, Automation, and Banking sectors in Egypt. Only 162 responses were deemed valid. The results showed that big data has a statistically major positive impact on the SPM. Analyzing coefficient values proven that all model hypotheses were generally accepted in three sectors. More importantly, the DD-SPMM has been practically proved to have a strong level of reliability using Cronbach's alpha values and has no auto-correlation problem based on Durbin -Watson values, which increases the generalization for the model. This study contributes to the literature by having an innovative, tested SPM model under a big data lens, considering the interrelationship between model phases.