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本文引用的文献

1
Assessing Health Students' Attitudes and Usage of ChatGPT in Jordan: Validation Study.评估约旦健康专业学生对ChatGPT的态度及使用情况:验证性研究
JMIR Med Educ. 2023 Sep 5;9:e48254. doi: 10.2196/48254.
2
ChatGPT and the Future of Digital Health: A Study on Healthcare Workers' Perceptions and Expectations.ChatGPT与数字健康的未来:一项关于医护人员认知与期望的研究。
Healthcare (Basel). 2023 Jun 21;11(13):1812. doi: 10.3390/healthcare11131812.
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An empirical assessment of a modified artificially intelligent device use acceptance model-From the task-oriented perspective.从任务导向视角对改进的人工智能设备使用接受模型的实证评估
Front Psychol. 2022 Aug 9;13:975307. doi: 10.3389/fpsyg.2022.975307. eCollection 2022.

研究影响初创企业采用 ChatGPT 技术的因素的方案:企业家的看法和态度。

Study protocol for factors influencing the adoption of ChatGPT technology by startups: Perceptions and attitudes of entrepreneurs.

机构信息

School of Computing and Mathematical Sciences, Leicester University, Leicester, England.

Multidisciplinary Research Centre for Innovations in SMEs (MrciS), Gisma University of Applied Sciences, Potsdam, Germany.

出版信息

PLoS One. 2024 Feb 15;19(2):e0298427. doi: 10.1371/journal.pone.0298427. eCollection 2024.

DOI:10.1371/journal.pone.0298427
PMID:38358993
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10868733/
Abstract

BACKGROUND

Generative Artificial Intelligence (AI) technology, for instance Chat Generative Pre-trained Transformer (ChatGPT), is continuously evolving, and its userbase is growing. These technologies are now being experimented by the businesses to leverage their potential and minimise their risks in business operations. The continuous adoption of the emerging Generative AI technologies will help startups gain more and more experience with adoptions, helping them to leverage continuously evolving technological innovation landscape. However, there is a dearth of prior research on ChatGPT adoption in the startup context, especially from Entrepreneur perspective, highlights the urgent need for a thorough investigation to identify the variables influencing this technological adoption. The primary objective of this study is to ascertain the factors that impact the uptake of ChatGPT technology by startups, anticipate their influence on the triumph of companies, and offer pragmatic suggestions for various stakeholders, including entrepreneurs, and policymakers.

METHOD AND ANALYSIS

This study attempts to explore the variables impacting startups' adoption of ChatGPT technology, with an emphasis on comprehending entrepreneurs' attitudes and perspectives. To identify and then empirically validate the Generative AI technology adoption framework, the study uses a two-stage methodology that includes experience-based research, and survey research. The research method design is descriptive and Correlational design. Stage one of the research study is descriptive and involves adding practical insights, and real-world context to the model by drawing from the professional consulting experiences of the researchers with the SMEs. The outcome of this stage is the adoption model (also called as research framework), building Upon Technology Adoption Model (TAM), that highlight the technology adoption factors (also called as latent variables) connected with subset of each other and finally to the technology adoption factor (or otherwise). Further, the latent variables and their relationships with other latent variables as graphically highlighted by the adoption model will be translated into the structured questionnaire. Stage two involves survey based research. In this stage, structured questionnaire is tested with small group of entrepreneurs (who has provided informed consent) and finally to be distributed among startup founders to further validate the relationships between these factors and the level of influence individual factors have on overall technology adoption. Partial Least Squares Structural Equation Modeling (PLS-SEM) will be used to analyze the gathered data. This multifaceted approach allows for a comprehensive analysis of the adoption process, with an emphasis on understanding, describing, and correlating the key elements at play.

DISCUSSION

This is the first study to investigate the factors that impact the adoption of Generative AI, for instance ChatGPT technology by startups from the Entrepreneurs perspectives. The study's findings will give Entrepreneurs, Policymakers, technology providers, researchers, and Institutions offering support for entrepreneurs like Academia, Incubators and Accelerators, University libraries, public libraries, chambers of commerce, and foreign embassies important new information that will help them better understand the factors that encourage and hinder ChatGPT adoption. This will allow them to make well-informed strategic decisions about how to apply and use this technology in startup settings thereby improving their services for businesses.

摘要

背景

生成式人工智能(AI)技术,例如 Chat Generative Pre-trained Transformer(ChatGPT),正在不断发展,其用户群体也在不断扩大。这些技术正被企业用于挖掘其潜力,并将其在商业运营中的风险最小化。新兴生成式 AI 技术的持续采用将帮助初创企业获得越来越多的采用经验,帮助他们利用不断发展的技术创新格局。然而,关于初创企业采用 ChatGPT 的前期研究很少,特别是从企业家的角度来看,这凸显了迫切需要进行彻底调查,以确定影响这种技术采用的变量。本研究的主要目的是确定影响初创企业采用 ChatGPT 技术的因素,预测这些因素对公司成功的影响,并为包括企业家和政策制定者在内的各种利益相关者提供实用建议。

方法与分析

本研究试图探索影响初创企业采用 ChatGPT 技术的变量,重点是理解企业家的态度和观点。为了确定并实证验证生成式 AI 技术采用框架,研究采用了包括经验研究和调查研究的两阶段方法。研究方法设计为描述性和相关性设计。研究的第一阶段是描述性的,通过研究人员对中小企业的专业咨询经验,从模型中添加实际见解和现实世界背景。该阶段的结果是采用模型(也称为研究框架),它建立在技术采用模型(TAM)之上,突出了与子集相互连接的技术采用因素(也称为潜在变量),最终连接到技术采用因素(或其他因素)。此外,采用模型中图形突出显示的潜在变量及其与其他潜在变量的关系将被转化为结构化问卷。第二阶段涉及基于调查的研究。在这一阶段,将对一组小企业家(已提供知情同意)进行结构化问卷测试,最终将问卷分发给初创企业创始人,以进一步验证这些因素之间的关系以及各个因素对整体技术采用的影响程度。偏最小二乘结构方程建模(PLS-SEM)将用于分析收集的数据。这种多方面的方法允许对采用过程进行全面分析,重点是理解、描述和关联起作用的关键要素。

讨论

这是第一项从企业家的角度研究影响初创企业采用生成式 AI 技术(例如 ChatGPT)的因素的研究。该研究的结果将为企业家、政策制定者、技术提供商、研究人员和为企业家提供支持的机构(如学术界、孵化器和加速器、大学图书馆、公共图书馆、商会和外国大使馆)提供重要的新信息,帮助他们更好地理解鼓励和阻碍 ChatGPT 采用的因素。这将使他们能够就如何在初创企业中应用和使用这项技术做出明智的战略决策,从而改善他们为企业提供的服务。