Examining the Feasibility of Large Language Models as Survey Respondents DOI
Ayato Kitadai, Kazuhito Ogawa, Nariaki Nishino

и другие.

2021 IEEE International Conference on Big Data (Big Data), Год журнала: 2024, Номер unknown, С. 3858 - 3864

Опубликована: Дек. 15, 2024

Язык: Английский

Artificial intelligence and consumer behavior: From predictive to generative AI DOI
Erik Hermann, Stefano Puntoni

Journal of Business Research, Год журнала: 2024, Номер 180, С. 114720 - 114720

Опубликована: Май 23, 2024

Язык: Английский

Процитировано

35

CONTRADICTORY ATTITUDES TOWARD ACADEMIC AI TOOLS: THE EFFECT OF AWE-PRONENESS AND CORRESPONDING SELF-REGULATION DOI Creative Commons
Jiajin Tong,

Yangmingxi Zhang,

Yutong Li

и другие.

Computers in Human Behavior Artificial Humans, Год журнала: 2025, Номер unknown, С. 100123 - 100123

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

AI and the advent of the cyborg behavioral scientist DOI Creative Commons
Geoff Tomaino, Alan Cooke,

Jim Hoover

и другие.

Journal of Consumer Psychology, Год журнала: 2025, Номер unknown

Опубликована: Март 16, 2025

Язык: Английский

Процитировано

1

Beyond WEIRD: Can synthetic survey participants substitute for humans in global policy research? DOI Creative Commons

Pujen Shrestha,

Dario Krpan,

Fatima Koaik

и другие.

Behavioral Science & Policy, Год журнала: 2025, Номер unknown

Опубликована: Фев. 8, 2025

Researchers are testing the feasibility of using artificial intelligence tools known as large language models to create synthetic research participants—artificial entities that respond surveys real humans would. Thus far, this has largely not been designed examine whether participants could mimic human answers policy-relevant or reflect views people from non-WEIRD (Western, educated, industrialized, rich, and democratic) nations. Addressing these gaps in one study, we have compared participants’ responses survey questions three domains: sustainability, financial literacy, female participation labor force. Participants were drawn United States well two nations previously included studies respondents: Kingdom Saudi Arabia Arab Emirates. We found for all nations, created by GPT-4, a form model, on average produced reasonably similar those their counterparts. Nevertheless, observed some differences between American participants: For latter, correlations full set tended be weaker. In addition, although common tendency countries show more positive less negative bias (that is, progressive financially literate relative counterparts), trend was pronounced participants. discuss main policy implications our findings offer practical recommendations improving use research.

Язык: Английский

Процитировано

0

Does One Size Fit All? The Role of Extraversion in Generating Electronic Word‐of‐Mouth Through Social Media Brand Page Engagement DOI Creative Commons
Ovidiu Ioan Moisescu, Oana Adriana Gică, Flavia‐Andreea Herle

и другие.

Psychology and Marketing, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

ABSTRACT Brands are increasingly investing in fostering consumer engagement with their social media pages to strengthen consumer–brand relationships, ultimately aiming generate positive electronic word‐of‐mouth (eWOM). Brands' marketing budgets could be used more effectively if they were tailor strategies consumers' characteristics, including relevant personality traits, such as extraversion. However, the role of extraversion driving eWOM through brand page remains underexplored. Drawing on identity theory, cultivation and trait theory personality, this paper integrates findings from two studies—a cross‐sectional survey an experiment—conducted among users world's most popular networking site (i.e., Facebook). The results show that passive active have distinct impacts eWOM, thereby highlighting mediating self‐brand connection extent which consumers incorporate a into self‐concept), extraversion's dual both antecedent moderator. Our provide managers valuable guidance by differing impact activities introverts versus extraverts.

Язык: Английский

Процитировано

0

Comments on “AI and the advent of the cyborg behavioral scientist” DOI Open Access
Paul Andrew Blythe,

Christopher Kulis,

A. Peter McGraw

и другие.

Journal of Consumer Psychology, Год журнала: 2025, Номер unknown

Опубликована: Март 16, 2025

Язык: Английский

Процитировано

0

Measuring technology acceptance over time using transfer models based on online customer reviews DOI Creative Commons
Daniel Baier, Andreas Karasenko, Alexandra Rese

и другие.

Journal of Retailing and Consumer Services, Год журнала: 2025, Номер 85, С. 104278 - 104278

Опубликована: Март 28, 2025

Язык: Английский

Процитировано

0

Using LLMs in sensory service research: initial insights and perspectives DOI Creative Commons
Monika Imschloß, Marko Sarstedt, Susanne Adler

и другие.

Service Industries Journal, Год журнала: 2025, Номер unknown, С. 1 - 22

Опубликована: Март 28, 2025

Язык: Английский

Процитировано

0

A whole new world, a new fantastic point of view: Charting unexplored territories in consumer research with generative artificial intelligence DOI
Kiwoong Yoo, Michael Haenlein, Kelly Hewett

и другие.

Journal of the Academy of Marketing Science, Год журнала: 2025, Номер unknown

Опубликована: Апрель 11, 2025

Язык: Английский

Процитировано

0

Capturing a moving target: Developing research on and with AI for Human Relations DOI
Jakob Stollberger, Smriti Anand,

Penny Dick

и другие.

Human Relations, Год журнала: 2025, Номер unknown

Опубликована: Апрель 11, 2025

Artificial intelligence (AI) has become part and parcel of scientific knowledge production since the latest iterations generative AI models (e.g., ChatGPT, DeepSeek, Claude, or Gemini) became widely available. Given rapidly evolved initial release ChatGPT in 2022, researching how AI’s capabilities impact organizations researchers make use tools can be likened to a moving target. In this editorial essay, we explore implications introduction context academic research, both as subject investigation (i.e., research on AI) tool facilitate writing, data generation, peer review process with AI). Specifically, concerning AI, consider issues around clarity regarding existing definitions concepts literature these are influenced by rapid technological evolution capabilities. regard reflect advantages disadvantages discuss Human Relations Usage Policy . Overall, our aim is not overly prescriptive conduct but encourage authors best capture target their endeavors.

Язык: Английский

Процитировано

0