Algorithmic fatigue, human talent adaptation, and perceived digital competitiveness among general and financial services professionals: a configurational analysis

Vollständiger Abstract

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Introduction Digital transformation has intensified the use of platforms, automated systems, artificial intelligence tools, online reporting, and algorithmic performance metrics in general and financial services. This study examines how algorithmic fatigue, human talent adaptation, digital organizational support, digital dynamic capabilities, and responsible algorithmic governance combine to explain high perceived digital competitiveness. Methods A quantitative, non-experimental, cross-sectional, exploratory-configurational design was used. From an institutional population of 581 Business Administration students, 128 employed participants working in general or financial services met the inclusion criteria. A 60-item, five-point Likert instrument measured six constructs. Analyses in R included descriptive statistics, reliability, Spearman correlations, an auxiliary linear model, and fuzzy-set qualitative comparative analysis (fsQCA). Results Human talent adaptation was the only potentially necessary condition for high perceived digital competitiveness. Three sufficient pathways emerged: digital dynamic capabilities, responsible algorithmic governance, and the combination of human talent adaptation and digital organizational support, which was the most consistent pathway. Algorithmic fatigue acted as a risk condition but could coexist with high perceived digital competitiveness when compensatory resources were present. Discussion The findings indicate that perceived digital competitiveness arises through alternative combinations of human, organizational, technological, and governance resources, supporting a configurational rather than a single universal pathway interpretation.