{"title":"ChatGPT plus 的订阅意向:用户满意度和自我效能感调查","authors":"Hyeon Jo","doi":"10.1108/mip-08-2023-0411","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.</p><!--/ Abstract__block -->\n<h3>Research limitations/implications</h3>\n<p>The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.</p><!--/ Abstract__block -->\n<h3>Practical implications</h3>\n<p>This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.</p><!--/ Abstract__block -->","PeriodicalId":48048,"journal":{"name":"Marketing Intelligence & Planning","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Subscription intentions for ChatGPT plus: a look at user satisfaction and self-efficacy\",\"authors\":\"Hyeon Jo\",\"doi\":\"10.1108/mip-08-2023-0411\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.</p><!--/ Abstract__block -->\\n<h3>Research limitations/implications</h3>\\n<p>The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.</p><!--/ Abstract__block -->\\n<h3>Practical implications</h3>\\n<p>This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.</p><!--/ Abstract__block -->\\n<h3>Originality/value</h3>\\n<p>This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.</p><!--/ Abstract__block -->\",\"PeriodicalId\":48048,\"journal\":{\"name\":\"Marketing Intelligence & Planning\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Marketing Intelligence & Planning\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1108/mip-08-2023-0411\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Marketing Intelligence & Planning","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/mip-08-2023-0411","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
Subscription intentions for ChatGPT plus: a look at user satisfaction and self-efficacy
Purpose
This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.
Design/methodology/approach
The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.
Findings
The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.
Research limitations/implications
The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.
Practical implications
This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.
Originality/value
This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.
期刊介绍:
Marketing Intelligence & Planning (MIP) facilitates communication between researchers and practitioners, providing the users of research with a wealth of robust and relevant information. At a time when some journals are losing their relevance to industry and practical requirements, MIP successfully offers a bridge between academic and practitioner thinking, while retaining a high level of scientific rigour.