{"id":11775,"date":"2026-08-04T21:24:23","date_gmt":"2026-08-04T19:24:23","guid":{"rendered":"https:\/\/anale.steconomiceuoradea.ro\/en\/?p=11775"},"modified":"2026-08-04T21:24:23","modified_gmt":"2026-08-04T19:24:23","slug":"exploring-gender-patterns-in-ai-adoption-for-accounting-estimates-a-mixed-methods-investigation","status":"publish","type":"post","link":"https:\/\/anale.steconomiceuoradea.ro\/en\/2026\/08\/04\/exploring-gender-patterns-in-ai-adoption-for-accounting-estimates-a-mixed-methods-investigation\/","title":{"rendered":"EXPLORING GENDER PATTERNS IN AI ADOPTION FOR ACCOUNTING ESTIMATES. A MIXED-METHODS INVESTIGATION"},"content":{"rendered":"

EXPLORING GENDER PATTERNS IN AI ADOPTION FOR ACCOUNTING ESTIMATES. A MIXED-METHODS INVESTIGATION<\/strong><\/p>\n

Victoria BOGDAN, M\u0103rioara BELENE\u0218I, R\u00e9ka Melinda T\u00d6R\u00d6K<\/p>\n

1 Department of Finance and Accounting, Faculty of Economic Sciences, University of Oradea, Oradea, Romania<\/em><\/p>\n

2 Accountancy, Doctoral School of Economics and Business Administration, West University of Timi\u0219oara, Timi\u0219oara, Romania<\/em><\/p>\n

vbogdan@uoradea.ro<\/u><\/em><\/p>\n

marioarabelenesi@gmail.com<\/u><\/em><\/p>\n

reka.torok81@e-uvt.ro<\/u><\/em><\/p>\n

Abstract: <\/em><\/strong>This study examines gender differences in the adoption of artificial intelligence (AI) for accounting estimates using a mixed-methods approach that combines statistical analysis with thematic interpretation. Data was collected from thirty semi-structured interviews with accounting professionals. Quantitative measures covering AI adoption intensity, technique diversity, and future expectations were analyzed using non-parametric tests and correlation mapping. These analyses found small to moderate gender effects that were statistically insignificant, reflecting considerable within-gender variation. The most notable quantitative finding was that men reported slightly higher perceived AI influence, while women used a broader range of AI techniques. Multiple Correspondence Analysis (MCA) mapped two main dimensions structuring attitudes, openness to AI integration (from traditional judgment to algorithmic support) and behavioral orientation (trust in AI versus algorithm aversion). These revealed distinct professional profiles, from strong acceptance to skepticism. Gender was associated with behavioral factors, including trust, perceived transparency, and openness to innovation. Qualitative findings further showed that women and men reached similar levels of openness to AI, but through different frameworks, women engaged more broadly with AI, emphasizing governance, ethics, and employment impacts, while men focused more on system capabilities and regulatory clarity. Overall, the mixedmethods design demonstrates that AI adoption for accounting estimates is shaped by technological perceptions, behavioral attitudes, and demographic factors, with gender differences manifesting in interpretive pathways rather than in overall adoption rates.<\/em><\/p>\n

Keywords: <\/em><\/strong>artificial intelligence; accounting estimates; gender patterns; qualitative coding; MCA.<\/em><\/p>\n

JEL Classification: <\/em><\/strong>M41; J16; O33.<\/em><\/p>\n

Download article<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

EXPLORING GENDER PATTERNS IN AI ADOPTION FOR ACCOUNTING ESTIMATES. A MIXED-METHODS INVESTIGATION Victoria BOGDAN, M\u0103rioara BELENE\u0218I, R\u00e9ka Melinda T\u00d6R\u00d6K 1 Department of Finance and Accounting, Faculty of Economic Sciences, University of Oradea, Oradea, Romania 2 Accountancy, Doctoral School of Economics and Business Administration, West University of Timi\u0219oara, Timi\u0219oara, Romania vbogdan@uoradea.ro marioarabelenesi@gmail.com reka.torok81@e-uvt.ro Abstract: This study […]<\/p>\n","protected":false},"author":123465,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ngg_post_thumbnail":0,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[18],"tags":[],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p3c4cf-33V","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/posts\/11775"}],"collection":[{"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/users\/123465"}],"replies":[{"embeddable":true,"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/comments?post=11775"}],"version-history":[{"count":1,"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/posts\/11775\/revisions"}],"predecessor-version":[{"id":11779,"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/posts\/11775\/revisions\/11779"}],"wp:attachment":[{"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/media?parent=11775"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/categories?post=11775"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/anale.steconomiceuoradea.ro\/en\/wp-json\/wp\/v2\/tags?post=11775"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}