UNLOCKING SUSTAINABLE SUCCESS IN INNOVATIVE SMES: LEVERAGING A BUSINESS INTELLIGENCE MODEL WITH CONFIRMATORY FACTOR ANALYSIS

Abstract

This study's purpose is to examine how business intelligence (BI) can enhance sustainability in innovative small and medium-sized enterprises (SMEs). Business intelligence contributes to achieving sustainability by analyzing data and providing strategic insights.

The study seeks to identify an appropriate BI measurement model and analyze its impact on sustainability, particularly since there is no standard model for measuring the impact of business intelligence on sustainability in innovative SMEs in Algeria. The study aims to fill this gap by developing a suitable measurement model.

We used the First-Order Confirmatory Factor Analysis (CFA) using both Covariance-Based Structural Equation Modelling (CB-SEM) and Partial Least Squares Structural Equation Modelling (PLS-SEM) with Smart PLS software. We collected Data from a random sample of 350 innovative SMEs in Algeria.

The results showed that the appropriate BI measurement model relies on two key dimensions: strategic planning and data mining. The study found a positive relationship and a moderate effect of 51.9% between business intelligence and sustainability in SMEs.

The study recommends that SMEs adopt business intelligence to enhance their sustainability. This can help improve governance, compliance with laws, and innovation, leading to comprehensive sustainability. It is expected that this will have a positive impact on enhancing competitiveness and resilience in the market for innovative SMEs.