Advancing Explainable Artificial Intelligence and Predictive Business Analytics to Strengthen Digital Transformation, Operational Resilience, and Productivity among U.S. Small and Medium-Sized Enterprises

Md. Ali Azam, Imran Hossain and Musfikul Islam
Additional contact information
Md. Ali Azam: MBA in Management Information Systems, International American University, Los Angeles, California, USA
Imran Hossain: MBA in Management Information Systems, International American University, Los Angeles, California, USA
Musfikul Islam: MBA in Business Analytics, International American University, California, USA

Post-Print from HAL

Abstract: This research aimed to shed light on the value of Explainable Artificial Intelligence (XAI) capability and predictive business analytics for Small and Medium Enterprises (SMEs) in the United States in driving digital transformation, and how these capabilities contribute to better operational resilience and productivity for SMEs. The approach adopted to select the sample was a positivist, quantitative, cross-sectional design that involved sampling 385 SME-knowledgeable decision-makers, evenly distributed across industries, firm sizes, and the four Census Regions. Partial least-squares structural equation modeling with 10,000 bootstrap resamples, mediation, multi-group, importance–performance, endogeneity, heterogeneity, necessary-condition, and predictive-ability analyses were performed on the data. Explainable AI and predictive analytics were the top factors for advancing digital transformation, with the same β values of 0.405, and in turn, operational resilience with the same β values of 0.181 and 0.157, respectively. Combinations of digital transformation and resilience affecting productivity (β=0,294 and β=0,408), as well as the impact of digital transformation on resilience (β=0,504), had significant positive effects. The robustness tests confirmed the absence of endogeneity in the materials, with increases in the percentages for digital transformation (51.2%), resilience (56.6%), and productivity (56.4%). The transparent intelligence that is turned into productivity in the integration of a digital process and adaptable strengths of operation. That is why SMEs need to pay attention to the following themes: explainable governance, analytics integration, workforce capacity, and resilient Digital operations amid constant uncertainty.

Keywords: technology adoption; data-driven decision-making; U.S. SMEs; organizational productivity; operational resilience; digital transformation; predictive business analytics; Explainable artificial intelligence (search for similar items in EconPapers)
Date: 2024-08-03
References: Add references at CitEc
Citations:

Published in European Journal of Management, Economics and Business, 2024, 1 (1), pp.70-94. ⟨10.59324/ejmeb.2024.1(1).06⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05722649

DOI: 10.59324/ejmeb.2024.1(1).06

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().