Artificial intelligence-driven decision making and firm performance: a quantitative approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F04130081%3A_____%2F24%3AN0000021" target="_blank" >RIV/04130081:_____/24:N0000021 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.emerald.com/insight/content/doi/10.1108/md-10-2023-1966/full/html" target="_blank" >https://www.emerald.com/insight/content/doi/10.1108/md-10-2023-1966/full/html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1108/MD-10-2023-1966" target="_blank" >10.1108/MD-10-2023-1966</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Artificial intelligence-driven decision making and firm performance: a quantitative approach

Popis výsledku v původním jazyce

Purpose The purpose of this study is to investigate the relationship between artificial intelligence (AI) and decision making in the development of AI-related capabilities. We investigate if and how AI-driven decision making has an impact on firm performance. We also investigate the role played by environmental dynamism in the development of AI capabilities and AI-driven decision making. Design/methodology/approach We surveyed 346 managers in the United States using established scales from the literature and leveraged p modelling to analyse the data. Findings Results indicate that AI-driven decision making is positively related to firm performance and that big data-powered AI positively influences AI-driven decision making. Moreover, there is a positive relationship between big data-powered AI and the development of AI capability within a firm. It is also found that the control variables of firm size and age do not significantly affect firm performance. Finally, environmental dynamism does not have a positive and significant moderating effect on the path connecting big data-powered AI and AI-driven decision making, while it exerts a positive moderating effect on the development of AI capability to strengthen AI-driven decision making. Originality/value These findings extend the resource-based view by highlighting the capabilities developed within the firm to manage big data-powered AI. This research also provides theoretically grounded guidance to managers wanting to align their AI-driven decision making with superior firm performance.

Název v anglickém jazyce

Artificial intelligence-driven decision making and firm performance: a quantitative approach

Popis výsledku anglicky

Purpose The purpose of this study is to investigate the relationship between artificial intelligence (AI) and decision making in the development of AI-related capabilities. We investigate if and how AI-driven decision making has an impact on firm performance. We also investigate the role played by environmental dynamism in the development of AI capabilities and AI-driven decision making. Design/methodology/approach We surveyed 346 managers in the United States using established scales from the literature and leveraged p modelling to analyse the data. Findings Results indicate that AI-driven decision making is positively related to firm performance and that big data-powered AI positively influences AI-driven decision making. Moreover, there is a positive relationship between big data-powered AI and the development of AI capability within a firm. It is also found that the control variables of firm size and age do not significantly affect firm performance. Finally, environmental dynamism does not have a positive and significant moderating effect on the path connecting big data-powered AI and AI-driven decision making, while it exerts a positive moderating effect on the development of AI capability to strengthen AI-driven decision making. Originality/value These findings extend the resource-based view by highlighting the capabilities developed within the firm to manage big data-powered AI. This research also provides theoretically grounded guidance to managers wanting to align their AI-driven decision making with superior firm performance.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50204 - Business and management

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MANAGEMENT DECISION

ISSN

0025-1747

e-ISSN

1758-6070

Svazek periodika

—

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

23

Strana od-do

—

Kód UT WoS článku

001240267500001

EID výsledku v databázi Scopus

2-s2.0-85195277913