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Journal of Information and Optimization Sciences cover

Journal of Information and Optimization Sciences

(Since 1980)
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Journal of Information and Optimization Sciences
Open Access Research Article

The influence of input matrix variations on corporate performance : Exploring leadership dynamics

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pp. 1881–1897Vol. 45Issue 7October 2024DOI: 10.47974/JIOS-1740XML
Received:
10 Apr 2024
Published Online:
19 Nov 2024
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1740
Pages:
1881–1897

Abstract

This study examines the complex dynamics of changes in input matrix within the banking industry, with a special focus on how it affects organizational decision-making processes and performance indicators. A relevant questionnaire was prepared and solicitated many Senior management respondents from different banks, utilizing snowball sampling approaches. By utilizing component analysis, the research revealed crucial elements that contribute to the variation in the input matrix. These factors account for a significant 72.1% of the overall variance. Later, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to thoroughly evaluate the complex connections between these elements and the outputs of the organization. The findings provide detailed insights that emphasize the important impact of elements such as inconsistencies in Artificial Intelligence (AI), frequent input of data’s, errors made by humans, and cognitive biases in determining the variance of the input matrix impacting the crucial decisions. Furthermore, the study highlights the crucial role of competent leadership in mitigating the negative consequences of fluctuations in input matrix on corporate performance indicators. This research provides useful insights for the banking sector, including concrete solutions to optimize decision-making processes and improve organizational performance in dynamic and data-driven contexts.

Keywords

Artificial intelligenceBanking industryDecision makingInput matrixLeadership

Subject Classifications

36J99

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