Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models

Nurlan Musazade; Jozsef Mezei; Xiaolu Wang

doi:10.1007/978-3-031-97119-8_47

Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models

Forskningsoutput: Kapitel i bok/konferenshandling › Publicerad konferensartikel › Vetenskaplig › Peer review

Sammanfattning

This study examines user behavior in using AI tools in solving business cases, applying the Technology Acceptance Model (TAM) and the Fogg model to analyze interaction patterns. Participants were categorized based on collaboration and exploitation levels during task execution. Results indicate that TAM effectively represents general usage experience, while the Fogg model is better in charaterizing specific usage behaviors. Excessive reliance on GPT’s perceived reliability correlated with exploitative usage, while balanced perceptions of efficiency and reliability resulted in collaborative behaviour. Findings reveal differing relationships among items and two behavior types. Despite the exploratory nature and small sample size, this research highlights the complementary value of TAM and Fogg model in understanding GPT interactions. Findings inform the design of AI systems to optimize collaborative potential while mitigating exploitative tendencies.

Originalspråk	Engelska
Titel på värdpublikation	Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1
Undertitel på värdpublikation	WorldCIST 2025
Redaktörer	Alvaro Rocha, Hojjat Adeli, Aneta Poniszewska-Maranda, Fernando Moreira, Isaias Bianchi
Förlag	Springer, Cham
Sidor	611-623
ISBN (elektroniskt)	978-3-031-97119-8
ISBN (tryckt)	978-3-031-97118-1
DOI	https://doi.org/10.1007/978-3-031-97119-8_47
Status	Publicerad - 16 nov. 2025
MoE-publikationstyp	A4 Artikel i en konferenspublikation
Evenemang	World Conference on Information Systems and Technologies - , Brasilien Varaktighet: 15 apr. 2025 → 17 apr. 2025 Konferensnummer: 13

Publikationsserier

Namn	Lecture Notes in Networks and Systems
Volym	1514 LNNS
ISSN (tryckt)	2367-3370
ISSN (elektroniskt)	2367-3389

Konferens

Konferens	World Conference on Information Systems and Technologies
Förkortad titel	WorldCIST 2025
Land/Territorium	Brasilien
Period	15/04/25 → 17/04/25

FN:s SDG:er

Detta resultat bidrar till följande hållbara utvecklingsmål:

SDG 8 – Anständiga arbetsvillkor och ekonomisk tillväxt
SDG 9 – Hållbar industri, innovationer och infrastruktur

Åtkomst av dokument

10.1007/978-3-031-97119-8_47

Citera det här

Musazade, N., Mezei, J., & Wang, X. (2025). Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models. I A. Rocha, H. Adeli, A. Poniszewska-Maranda, F. Moreira, & I. Bianchi (Red.), Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025 (s. 611-623). (Lecture Notes in Networks and Systems; Vol. 1514 LNNS). Springer, Cham. https://doi.org/10.1007/978-3-031-97119-8_47

Musazade, Nurlan ; Mezei, Jozsef ; Wang, Xiaolu. / Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models. Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025. redaktör / Alvaro Rocha ; Hojjat Adeli ; Aneta Poniszewska-Maranda ; Fernando Moreira ; Isaias Bianchi. Springer, Cham, 2025. s. 611-623 (Lecture Notes in Networks and Systems).

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title = "Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models",

abstract = "This study examines user behavior in using AI tools in solving business cases, applying the Technology Acceptance Model (TAM) and the Fogg model to analyze interaction patterns. Participants were categorized based on collaboration and exploitation levels during task execution. Results indicate that TAM effectively represents general usage experience, while the Fogg model is better in charaterizing specific usage behaviors. Excessive reliance on GPT{\textquoteright}s perceived reliability correlated with exploitative usage, while balanced perceptions of efficiency and reliability resulted in collaborative behaviour. Findings reveal differing relationships among items and two behavior types. Despite the exploratory nature and small sample size, this research highlights the complementary value of TAM and Fogg model in understanding GPT interactions. Findings inform the design of AI systems to optimize collaborative potential while mitigating exploitative tendencies.",

keywords = "GPT, artificial intelligence, Technology acceptance model, Fogg model",

author = "Nurlan Musazade and Jozsef Mezei and Xiaolu Wang",

year = "2025",

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doi = "10.1007/978-3-031-97119-8\_47",

language = "English",

isbn = "978-3-031-97118-1",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer, Cham",

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editor = "Alvaro Rocha and Hojjat Adeli and Poniszewska-Maranda, \{ Aneta\} and Fernando Moreira and Isaias Bianchi",

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Musazade, N , Mezei, J & Wang, X 2025, Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models. i A Rocha, H Adeli, A Poniszewska-Maranda, F Moreira & I Bianchi (red), Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025. Lecture Notes in Networks and Systems, vol. 1514 LNNS, Springer, Cham, s. 611-623, World Conference on Information Systems and Technologies, Brasilien, 15/04/25. https://doi.org/10.1007/978-3-031-97119-8_47

Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models. / Musazade, Nurlan ; Mezei, Jozsef ; Wang, Xiaolu.
Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025. red. / Alvaro Rocha; Hojjat Adeli; Aneta Poniszewska-Maranda; Fernando Moreira; Isaias Bianchi. Springer, Cham, 2025. s. 611-623 (Lecture Notes in Networks and Systems; Vol. 1514 LNNS).

Forskningsoutput: Kapitel i bok/konferenshandling › Publicerad konferensartikel › Vetenskaplig › Peer review

TY - GEN

T1 - Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models

AU - Musazade, Nurlan

AU - Mezei, Jozsef

AU - Wang, Xiaolu

N1 - Conference code: 13

PY - 2025/11/16

Y1 - 2025/11/16

N2 - This study examines user behavior in using AI tools in solving business cases, applying the Technology Acceptance Model (TAM) and the Fogg model to analyze interaction patterns. Participants were categorized based on collaboration and exploitation levels during task execution. Results indicate that TAM effectively represents general usage experience, while the Fogg model is better in charaterizing specific usage behaviors. Excessive reliance on GPT’s perceived reliability correlated with exploitative usage, while balanced perceptions of efficiency and reliability resulted in collaborative behaviour. Findings reveal differing relationships among items and two behavior types. Despite the exploratory nature and small sample size, this research highlights the complementary value of TAM and Fogg model in understanding GPT interactions. Findings inform the design of AI systems to optimize collaborative potential while mitigating exploitative tendencies.

AB - This study examines user behavior in using AI tools in solving business cases, applying the Technology Acceptance Model (TAM) and the Fogg model to analyze interaction patterns. Participants were categorized based on collaboration and exploitation levels during task execution. Results indicate that TAM effectively represents general usage experience, while the Fogg model is better in charaterizing specific usage behaviors. Excessive reliance on GPT’s perceived reliability correlated with exploitative usage, while balanced perceptions of efficiency and reliability resulted in collaborative behaviour. Findings reveal differing relationships among items and two behavior types. Despite the exploratory nature and small sample size, this research highlights the complementary value of TAM and Fogg model in understanding GPT interactions. Findings inform the design of AI systems to optimize collaborative potential while mitigating exploitative tendencies.

KW - GPT

KW - artificial intelligence

KW - Technology acceptance model

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PB - Springer, Cham

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Musazade N , Mezei J , Wang X. Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models. I Rocha A, Adeli H, Poniszewska-Maranda A, Moreira F, Bianchi I, redaktörer, Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025. Springer, Cham. 2025. s. 611-623. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-97119-8_47

Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models

Sammanfattning

Publikationsserier

Konferens

FN:s SDG:er

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