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

Research output: Chapter in Book/Conference proceeding › Published conference proceeding › Scientific › peer-review

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’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.

Original language	English
Title of host publication	Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1
Subtitle of host publication	WorldCIST 2025
Editors	Alvaro Rocha, Hojjat Adeli, Aneta Poniszewska-Maranda, Fernando Moreira, Isaias Bianchi
Publisher	Springer, Cham
Pages	611-623
ISBN (Electronic)	978-3-031-97119-8
ISBN (Print)	978-3-031-97118-1
DOIs	https://doi.org/10.1007/978-3-031-97119-8_47
Publication status	Published - 16 Nov 2025
MoE publication type	A4 Article in a conference publication
Event	World Conference on Information Systems and Technologies - , Brazil Duration: 15 Apr 2025 → 17 Apr 2025 Conference number: 13

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1514 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	World Conference on Information Systems and Technologies
Abbreviated title	WorldCIST 2025
Country/Territory	Brazil
Period	15/04/25 → 17/04/25

Keywords

GPT
artificial intelligence
Technology acceptance model
Fogg model

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

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

Cite this

Musazade, N., Mezei, J., & Wang, X. (2025). Exploring GPT Usage Behavior Groups for Business Case Solutions: Insights from Fogg and Technology Acceptance Models. In A. Rocha, H. Adeli, A. Poniszewska-Maranda, F. Moreira, & I. Bianchi (Eds.), Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025 (pp. 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. editor / Alvaro Rocha ; Hojjat Adeli ; Aneta Poniszewska-Maranda ; Fernando Moreira ; Isaias Bianchi. Springer, Cham, 2025. pp. 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",

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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. in A Rocha, H Adeli, A Poniszewska-Maranda, F Moreira & I Bianchi (eds), Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025. Lecture Notes in Networks and Systems, vol. 1514 LNNS, Springer, Cham, pp. 611-623, World Conference on Information Systems and Technologies, Brazil, 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. ed. / Alvaro Rocha; Hojjat Adeli; Aneta Poniszewska-Maranda; Fernando Moreira; Isaias Bianchi. Springer, Cham, 2025. p. 611-623 (Lecture Notes in Networks and Systems; Vol. 1514 LNNS).

Research output: Chapter in Book/Conference proceeding › Published conference proceeding › Scientific › peer-review

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AU - Musazade, Nurlan

AU - Mezei, Jozsef

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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.

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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. In Rocha A, Adeli H, Poniszewska-Maranda A, Moreira F, Bianchi I, editors, Emerging Trends in Information Systems and Technologies - WorldCIST 2025. Volume 1: WorldCIST 2025. Springer, Cham. 2025. p. 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

Abstract

Publication series

Conference

Keywords

UN SDGs

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Cite this