Human VS AI-supported decision making in international market entry
Saketi, Hassan (2026)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202604156508
https://urn.fi/URN:NBN:fi:amk-202604156508
Tiivistelmä
Artificial intelligence (AI) is increasingly used in international business decision-making, yet empirical evidence on how AI support influences strategic decisions remain limited. The study examined differences between human-only and AI-supported decision-making in international market entry contexts.
A controlled experiment was conducted with international students who were randomly assigned to either a human-only or an AI-supported decision condition. Participants completed a structured market entry scenario and selected a target market and an entry mode. Decision quality was measured using an objective scoring index, while confidence, trust in the decision process, and satisfaction were measured using Likert-scale items. The data were analyzed using descriptive statistics, independent samples Mann-Whitney tests, Fisher’s exact tests, and moderation regression analysis.
The results show that participants in the AI-supported condition achieved significantly higher decision quality than those in the human-only condition. AI support also increased decision confidence, trust in the decision-making process, and satisfaction with the final decision. In addition, AI guidance directed attention toward qualitative factors, particularly cultural acceptance, alongside quantitative indicators, which influenced market selection patterns. Moderation analyses indicate that digital literacy and positive attitudes toward AI strengthen the positive relationship between AI-supported decision environments and decision quality, whereas international experience does not have a significant moderating effect.
In conclusion, the findings suggest that AI-supported decision systems improve both decision outcomes and decision-related perceptions in international market entry contexts. The effectiveness of AI support also depends partly on individual characteristics, particularly digital capabilities and attitudes toward AI.
A controlled experiment was conducted with international students who were randomly assigned to either a human-only or an AI-supported decision condition. Participants completed a structured market entry scenario and selected a target market and an entry mode. Decision quality was measured using an objective scoring index, while confidence, trust in the decision process, and satisfaction were measured using Likert-scale items. The data were analyzed using descriptive statistics, independent samples Mann-Whitney tests, Fisher’s exact tests, and moderation regression analysis.
The results show that participants in the AI-supported condition achieved significantly higher decision quality than those in the human-only condition. AI support also increased decision confidence, trust in the decision-making process, and satisfaction with the final decision. In addition, AI guidance directed attention toward qualitative factors, particularly cultural acceptance, alongside quantitative indicators, which influenced market selection patterns. Moderation analyses indicate that digital literacy and positive attitudes toward AI strengthen the positive relationship between AI-supported decision environments and decision quality, whereas international experience does not have a significant moderating effect.
In conclusion, the findings suggest that AI-supported decision systems improve both decision outcomes and decision-related perceptions in international market entry contexts. The effectiveness of AI support also depends partly on individual characteristics, particularly digital capabilities and attitudes toward AI.