Critical Factors Influencing the Maturity of Business Analytics of Software and Apparel Industries in Sri Lanka

In today's data-driven business environment, Business Analytics Maturity (BAM) reflects an organization’s capability to leverage data for strategic decisions. In Sri Lanka’s key export sectors, software, and apparel, this study identifies six critical factors influencing BAM: technology-supporting infrastructure, data management, organizational culture, top management support, competitive pressure, and government regulations. Using a quantitative approach and data from 147 respondents, Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed competitive pressure and government regulations as the strongest drivers, followed by organizational culture and data management. While top management support and technology infrastructure showed less direct effects their foundational role is acknowledged. This research offers insights for enhancing analytics adoption in emerging economies, advancing competitiveness, and compliance while enriching BAM literature for future studies.

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Publication Details

Published
2025-02-19
DOI
https://doi.org/10.1109/icarc64760.2025.10963021
Primary Topic
Big Data and Business Intelligence
Type
article
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article

Critical Factors Influencing the Maturity of Business Analytics of Software and Apparel Industries in Sri Lanka

Janaka Wijayanayake, Nipuni De Silva, Shan Jayasinghe
Big Data and Business Intelligence
article

Critical Factors Influencing the Maturity of Business Analytics of Software and Apparel Industries in Sri Lanka

Janaka Wijayanayake, Nipuni De Silva, Shan Jayasinghe
article en

Abstract

In today's data-driven business environment, Business Analytics Maturity (BAM) reflects an organization’s capability to leverage data for strategic decisions. In Sri Lanka’s key export sectors, software, and apparel, this study identifies six critical factors influencing BAM: technology-supporting infrastructure, data management, organizational culture, top management support, competitive pressure, and government regulations. Using a quantitative approach and data from 147 respondents, Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed competitive pressure and government regulations as the strongest drivers, followed by organizational culture and data management. While top management support and technology infrastructure showed less direct effects their foundational role is acknowledged. This research offers insights for enhancing analytics adoption in emerging economies, advancing competitiveness, and compliance while enriching BAM literature for future studies.

University of Kelaniya (LK), Southampton Solent University (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 89%
Big Data and Business Intelligence
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