TY - CHAP
T1 - Statistical Implicative Analysis
T2 - A Distinguished Statistical Methodology in Evaluating Greek Students’ Attitudes Toward the Use of AI
AU - Anastasiadou, Sofia
AU - Zirinoglou, Poulcheria
AU - Seremeti, Lambrini
AU - Masouras, Andreas
AU - Komodromos, Marcos
AU - Anastasiadis, Lazaros
N1 - Publisher Copyright:
© 2025 by IGI Global. All rights reserved.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - This chapter aims to introduce statistical implicative analysis (SIA), a groundbreaking statistical methodology that is transforming data analysis in the field of marketing. SIA is utilized to ascertain students’ attitudes towards the use of artificial intelligence (AI) in entrepreneurship education. The study explores the future entrepreneurs’ intentions to embrace AI and foster innovation within the realm of digital entrepreneurship. An extensive review of the literature and theoretical frameworks was conducted to assess the determinants and conceptual constructs influencing the utilization of AI in entrepreneurship. The proposed model was evaluated using responses from 523 participants. Statistical implicative analysis was employed to validate the hypotheses. The model’s validation highlights that conceptual constructs such as performance expectancy of AI, entrepreneurial education, risk aversion, social support, business support, business climate, and perceived behavioral control have a significant impact on entrepreneurial intentions.
AB - This chapter aims to introduce statistical implicative analysis (SIA), a groundbreaking statistical methodology that is transforming data analysis in the field of marketing. SIA is utilized to ascertain students’ attitudes towards the use of artificial intelligence (AI) in entrepreneurship education. The study explores the future entrepreneurs’ intentions to embrace AI and foster innovation within the realm of digital entrepreneurship. An extensive review of the literature and theoretical frameworks was conducted to assess the determinants and conceptual constructs influencing the utilization of AI in entrepreneurship. The proposed model was evaluated using responses from 523 participants. Statistical implicative analysis was employed to validate the hypotheses. The model’s validation highlights that conceptual constructs such as performance expectancy of AI, entrepreneurial education, risk aversion, social support, business support, business climate, and perceived behavioral control have a significant impact on entrepreneurial intentions.
UR - https://www.scopus.com/pages/publications/105008053230
U2 - 10.4018/979-8-3693-3100-2.ch006
DO - 10.4018/979-8-3693-3100-2.ch006
M3 - Chapter
AN - SCOPUS:105008053230
SN - 9798369331002
SP - 133
EP - 167
BT - Real-World Tools and Scenarios for Entrepreneurship Exploration
PB - IGI Global
ER -