Abstract

Responding to ChatGPT’s (Chat Generative Pretrained Transformer) rapid rise to extreme popularity (reaching over 100 million users within a year of its launch), this study drew on both the Uses and Gratifications Theory (UGT) and Technology Acceptance Model (TAM) to investigate the potential predictors of continued use of ChatGPT among college students in Korea. Specifically, the study identified key factors—information-seeking and entertainment motivations, perceived usefulness, perceived ease of use, social pressure, and personal innovativeness—and examined how they affect intentions to continue using ChatGPT. An online survey was distributed to 280 college students. The findings showed that information-seeking motivation, perceived usefulness, social pressure, and personal innovativeness positively impact users’ intentions to continue using ChatGPT. This paper concludes by highlighting the significant theoretical and practical implications of these findings.

Keywords:Uses and Gratification paradigm, ChatGPT, Intention to use, Motivation, Technology acceptance Model

Introduction

ChatGPT employs deep learning algorithms to comprehend and produce human-like text, supporting users in various aspects of daily life. Particularly useful for language translation [1] and writing [2] in both personal and professional settings, its most significant characteristic is its ability to understand and respond to questions naturally and conversationally [3]. Released to the public on November 20, 2022, ChatGPT quickly became the most popular generative AI application, attracting 100 million users within two months of its launch [3] and enjoying a greater adoption rate than social media platforms like Instagram and TikTok [4,5].

Research has found that younger South Korean residents enjoy using ChatGPT, with one study reporting that individuals in their teens (511,227) and 20s (523,275) comprise more than half (54.2%) of the 1.03 million South Koreans currently using ChatGPT [6].

The rapid development and significant societal influence of ChatGPT highlight the necessity of research into this application. Although researchers have devoted significant attention to motivations for ChatGPT use [7], use-related privacy concerns [8], and the application’s impact on educational settings [9], examinations of the factors that drive users to adopt and continue using this technology remain scarce. This study addresses this limitation by exploring factors that may impact ChatGPT use. Specifically, it combines the Use and Gratification Theory (UGT) and the Technology Acceptance Model (TAM) to explore the factors that affect intentions to continue using ChatGPT, focusing on motivations, perceptions of usefulness and usability, personal innovativeness and social influences as determinants of continued use.

Assuming that media users are active, goal-driven individuals, whose consumption results from deliberate choices motivated by the pursuit of gratification [10], the Use and Gratification Theory (UGT) is a logical starting point for examining ChatGPT-related motivations. Since ChatGPT-adoption studies have found that the application primarily satisfies information-seeking and entertainment motivations [7,11], this study assumed that ChatGPT users actively use the application to satisfy specific needs including information-seeking and entertainment.

The Technology Acceptance Model (TAM) is similarly helpful for examining ChatGPT use. In the information systems (IS) field, explanations of people’s choices of specific information technologies have mainly focused on instrumental beliefs as drivers of usage intentions. The TAM offers a valuable framework for examining these factors, positioning perceived usefulness (PU) and perceived ease of use (PEOU) as critical determinants of new technology adoption [12]. Previous studies have applied the TAM to examine the adoption of new technologies including SNS [13], chatbots [14], and ChatGPT [15], finding that PU and PEOU significantly affect users’ technology adoption intentions. Therefore, this study assumed that PU and PEOU affect ChatGPT usage.

Meanwhile, despite acknowledging the TAM as among the most influential theoretical contributions to understanding IS usage and acceptance, Malhotra and Galletta [16] argued that it overlooks the impact of social influence on new technology adoption and use. People often rely on their social networks when deciding whether or not to adopt new technologies. In fact, given the significant role it plays in the early adoption of technology [17], social influence likely shapes users’ intentions to engage with ChatGPT. Responding to Malhotra and Galletta’s [16] contention, this study examines the role of social influence in ChatGPT adoption.

Research has also shown that personal characteristics affect technology acceptance. In particular, studies have revealed a positive relationship between personal innovativeness and willingness to adopt new technology, suggesting that this trait significantly influences consumer acceptance of technological innovations [18]. Given that personal innovativeness presumably serves as a critical influence on user technology acceptance [19], this study assumed that members of younger generations (who tend to be highly curious and receptive to new technologies) are willing to use ChatGPT because they recognize it as a new technology. Thus, combining UGT and the TAM, the present study seeks to identify key usage-related factors—information-seeking and entertainment motivations, PU, PEOU, social influence, personal innovativeness—and investigate how these factors affect users’ intentions to continue using ChatGPT.

This study makes both theoretical and practical contributions. From a theoretical perspective, it extends the theory of adoption of new technology to a new media context, focusing on ChatGPT and helping to reveal how users’ perceptions of ChatGPT (usefulness and usability) and motivations for using it (information and entertainment) affect their continued use of the application. The study also contributes to the literature on new technology acceptance and adoption, demonstrating how individual and societal factors (personal innovativeness and social influence, respectively) impact the continued usage of new technology.

To this point, few studies have simultaneously considered the motivational and perceptual factors that influence technology acceptance. Likewise, related research examining individual users’ personal characteristics and social environments has remained scarce. Given these research gaps, this study’s integrative approach is both important and meaningful, enabling it to elucidate the impacts of user motivations, perceptions, and personal (innovativeness) and societal (social influence) characteristics on their intentions to continue using ChatGPT.

From a practical perspective, this study’s findings should give developers valuable insights regarding the application’s strengths and weaknesses. These insights will help developers and businesses formulate strategies for maintaining and increasing user engagement over time and allow them to make targeted system design, functionality, and user experience improvements that will enhance overall user satisfaction and utility.

This paper is divided into five sections. Section two discusses the study’s theoretical framework (UGT and TAM) and presents the study’s guiding hypotheses. Section three explains the study’s methods. Section four describes the data analysis. Finally, section five outlines the implications of the results, identifies the study’s limitations, and makes suggestions for future research.

Literature Review

Definitions of ChatGPT

Developed by OpenAI and introduced to the public in 2022, ChatGPT is a large language model that interprets human input and generates responses that closely mimic natural language. It answers questions, provides information, engages in conversations, generates written content, and more. Several factors distinguish ChatGPT from other artificial intelligence tools. First, unlike previous AI chatbots that only provided simple answers to questions, ChatGPT can perform various tasks, including understanding conversational contexts, learning from feedback, coding, composing, translating, and writing papers. Second, ChatGPT’s training on vast quantities of text data enables it to produce highly accurate responses. Finally, ChatGPT can generate responses in real time, making it an ideal tool for users with fast language processing [1,2,3].

Following additional research and development, OpenAI introduced GPT-4, a multimodal language model capable of processing both image and text inputs, generating text outputs, and achieving human-level performance across various academic and professional benchmarks [20]. Its advantages include the abilities to understand and integrate various types of content including long passages of text, voice recordings, images, program code, and structured data.

Uses and Gratifications Theory

The Uses and Gratifications Theory is a useful conceptual framework for investigating the motivations driving user engagement with ChatGPT and the ways this technology meets their needs. Katz et al. [10] argued that, rather than being passive consumers, individuals are motivated to actively engage in the communication process and use media to satisfy their needs and desires. They identified the following five key categories of motivation for mass media use: needs for cognition (e.g., information-seeking), affection (e.g., enjoyment), social interaction (e.g., relationship management), self-focus (e.g., achieving status), and relaxation.

Embracing the assumption that people actively use media to satisfy specific needs, many studies have analyzed a variety of media and new technologies using the UGT [21, 22, 23]. For instance, researchers have used a similar approach to analyze people’s motives for using the Internet [24] and social media [25]. In this vein, Hwang and Choi [26] identified self-expression, social interaction, information, and entertainment as key factors motivating continued use of Instagram.

The UGT has also been used to examine human-computer interactions, revealing users’ reasons for engaging with AI and how AI meets their needs. Previous studies have suggested that people use chatbot- or voice assistant-AI to satisfy cognitive needs like obtaining information, affective needs like seeking emotional support, and entertainment needs [27, 28]. Lee and Cho [29] identified four motivations for using AI smart speakers— virtual interaction, information learning, play and relaxation, and practicability. Likewise, Choi and Drumwright [30] found that individuals’ motivations for using voice AI assistants (e.g., Siri and Alexa) include social interaction, personal identity, conformity, life efficiency, and information seeking.

The Relationships between Motivations and Continued Use of ChatGPT

Several studies have examined users’ motivations for using ChatGPT. For instance, Baek and Kim [7] found that people use ChatGPT to get information, improve the efficiency of their work, interact with people, and get pleasure. Meanwhile, Jishnu et al. [31] found that students mainly use ChatGPT to generate academic content and gather information. Among these various motivations, previous ChatGPT adoption studies have generally found that ChatGPT users share two primary motivations: information-seeking and entertainment. For instance, Choudhury and Shamszare [32] specifically found that ChatGPT is mostly used for information retrieval and entertainment, revealing a link between intentions to use and actual use. In a similar vein, Consumer Insight (2018) reported that people mainly use AI agents for “music selection and search (57%)” and “weather information (55%)” [33]. Another survey conducted on 1,000 people in Korea identified only two uses for ChatGPT exceeding 50% response rates: “For fun or satisfying curiosity (55.5%)” and “searching for information (51.5%)” [11]. These findings suggest that the pursuit of information and entertainment is positively associated with ChatGPT users’ continued use intentions [31, 32]. Thus, this study proposed the following two hypotheses:
H1: Information-seeking motivation positively impacts intentions to continue using ChatGPT.
H2: Entertainment motivation positively impacts intentions to continue using ChatGPT.

Technology Acceptance Model (TAM)

The Technology Acceptance Model (TAM) focuses on user experience and is used to assess acceptance of new technologies. This model posits that the successful adoption of new technology depends on a favorable attitude toward two factors: perceived usefulness (PU) and perceived ease of use (PEU) [34, 35]. Defined as the degree to which an individual believes that using a specific technology will enhance their job performance [34], PU relates to people’s confidence that new technology will improve work performance. Meanwhile, PEU, which refers to the extent to which a user believes they will encounter no difficulties when using a specific technology [34], relates to the degree to which people believe that new technology does not require complex effort.

TAM studies have suggested that PU and PEU play crucial roles in the acceptance of new technologies such as web advertising [35], Live Commerce [36], mobile banking [37, 38], and social media apps [39]. Recognizing AI’s increasing permeation of universities, a study [40] examining college students’ perceptions of AI found that respondents’ positive perceptions of ChatGPT stemmed from its ease of use and convenience.

Meanwhile, some TAM-based studies have implicitly assumed that continued use is an extension of adoption and used TAM in post-adoption conditions [41, 42]. These studies confirmed that individuals’ perceptions of new technologies’ ease of use and usefulness determine their intentions to continue using the technologies. Given that people perceive ChatGPT as useful for both finding information and simplifying their work processes [43], the study assumes that PU and PEU will affect users’ intentions to continue using ChatGPT. Thus, this study proposed the following two hypotheses.
H3: PU positively impacts intentions to continue using ChatGPT.
H4: PEU positively impacts intentions to continue using ChatGPT.

Social Influence

Social influence measures the extent to which people are influenced by others in their social environments. Family members, friends, or people who are part of the same social groups are regarded as social influences. According to previous studies, support from influential others significantly affects the actions of potential adopters, as individuals tend to adjust their attitudes, behaviors, and beliefs based on their social contexts [17].

Some studies focusing on technology adoption have incorporated the concept of social influence into their research models and yielded notable empirical results (e.g., [44, 45, 47]). Taylor and Todd [46], for example, found that influences of superiors and peers play a key role in information technology adoption. In addition, friends and social networks have been identified as important determinants of mobile technology adoption [47].

Given the considerable societal attention ChatGPT has received, friends and family members likely exert considerable influence on individuals’ engagement with ChatGPT. In this regard, peer influence has been shown to impact college students’ chatbot usage, with social media and peer pressure identified as key influences on intentions to continue using ChatGPT [43]. Therefore, this study proposed the following hypothesis:
H5: Social pressure positively impacts intentions to continue using ChatGPT.

Personal Innovativeness

Conventional innovation diffusion studies have indicated that highly innovative people actively pursue new ideas. These people can cope with high levels of uncertainty and tend to develop more positive acceptance intentions [48, 49]. Drawing on Rogers’ theory of the diffusion of innovations, Agarwal and Prasad [50] argued that people generate beliefs about new technologies by combining information from various media; this led them to add “personal innovativeness”—defined as a person’s willingness to try using a given information technology—as a variable to Davis’ original TAM model.

Previous studies have found that people with higher degrees of innovativeness are more likely than others to develop positive perceptions of the advantages and ease of use of new technologies. For example, research has shown that people with higher levels of openness have more positive attitudes toward AI, and those with positive personalities tend to be more tolerant of AI’s negative aspects [47]. Several studies have also found positive relationships between innovativeness and new media usage. For instance, research has shown a significant relationship between Koreans’ innovativeness and the use of SNS [51]. Similarly, Park and Lee (2022) used Korea Media panel data to show that Korean consumers with higher innovativeness are more willing to use OTT services in Korea [52].

Overall, these findings suggest that personal innovativeness is positively related to the adoption and continued use of new technologies. Thus, predicting that students with higher degrees of innovativeness would be more prone to use ChatGPT, this study proposed the following hypothesis:
H6: Personal innovativeness positively impacts intentions to continue using ChatGPT.

Methods

Participants

An online survey was used to collect data. Respondents were recruited from the panels of an online survey company. Gender and academic levels were quoted with the same numbers. A total of 280 college students completed the survey. In total, 50% of the respondents were male and 50% were female. The average age of respondents was 21.4 years. Finally, the sample contained an equal distribution of participants across the academic year: freshman (25%, N=70), sophomore (25%, N=70), junior (25%, N=70), and senior (25%, N=70)..

Measures

The survey measurement items were selected from previous studies and modified to reflect ChatGPT usage. The respondents indicated the degree of their agreement with the survey items on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Table 1 provides operational definitions and measurement items for each variable.

Results

Before testing the hypotheses, Pearson correlations were calculated among the variables. Table 2 summarizes the results, showing significant relationships between intentions to continue using ChatGPT and PU (r=.758, p<.001), PEOU (r=.514, p<.01), social influence (r=.514, p<.01), personal innovativeness (r=.374, p<.01), and information-seeking (r =.482, p<.001); meanwhile, the relationship between entertainment motive and intentions to continue ChatGPT was not significant.

* p < .05, ** p<.01, *** p<.001

Next, this study used validity and reliability analyses to verify the measurement items. First, principle component factor analysis (with varimax rotation) was conducted based on a previous study [36]; the following criteria were applied [36]: (1) An eigenvalue of 1.0 or greater was necessary, (2) the factor loading was above 0.4, and (3) KMO (Kaiser-Meyer-Olkim) was above 0.6. Second, Cronbach’s ɑ, which evaluates the internal consistency of the scale, was used to verify reliability. In general, a Cronbach’s ɑ above 0.7 is considered reliable. Tables 3 & 4 shows the results.

Finally, to test the hypotheses, a regression analysis was performed using SPSS software. The independent variables were information-seeking and entertainment motivations, PU, PEU, social influence, and personal innovativeness, and the dependent variable was intention to continue using ChatGPT. Table 3 shows the results.

The analyses showed that among the UGT variables, while information-seeking motivation positively affected intentions to continue using ChatGPT (ß=.173, p<.001), entertainment motivation did not. Thus, Hypothesis 1 was supported, but Hypothesis 2 was not. Likewise, the regression analysis indicated that while PU (ß=.545, p<.001) positively affected intentions to continue using ChatGPT, PEU did not. Therefore, Hypothesis 3 was supported, but Hypothesis 4 was not. Meanwhile, social influence (ß=.129, p<.01) and personal innovativeness (ß=.133, p<.05) positively affected intentions to continue using ChatGPT, meaning Hypotheses 5 and 6 were both supported. These results indicate that the need for information, perceived utility, social influence, and individual innovativeness play determinative roles in college students’ adoption of ChatGPT.

Conclusion

Acknowledging ChatGPT’s recent rise to extreme popularity, the present study utilized the Uses and Gratifications Theory (UGT) and the Technology Acceptance Model (TAM) to investigate potential predictors of continued usage of ChatGPT. It identified important ChatGPT use-related factors and discussed their effects on intentions to continue using ChatGPT. The study found that information-seeking, PU, social influence, and personal innovativeness impact intentions to continue using ChatGPT.

The finding that PU positively affects intentions to continue using ChatGPT supports the notion that individuals who perceive a new system as useful are more likely to use it, confirming that perceived utility relates to use behavior in the ChatGPT context. This could be because college students view ChatGPT as a tool that helps search for information and ideas, translate text, and provide alternative questions to enhance their understanding of subjects [53]. The participants in this study regarded ChatGPT usage as helpful for boosting productivity and improving learning efficiency.

The respondents also indicated that they view ChatGPT as a tool for information retrieval, emphasizing their need for efficient task and assignment completion. Efficient access to information is an established motivation in ChatGPT-related UGT studies. For instance, Baek and Kim [7] identified information seeking and task efficiency as the key elements for intentions to continue using ChatGPT. Our finding that information seeking plays a key role in determining continued use intentions supports their finding that ChatGPT offers clear answers to complex questions, eliminating the need for search queries. The participants in this study seemed to agree that ChatGPT’s ability to offer vital information and generate responses to almost all kinds of questions and tasks gives it immense power over the ways they see, experience, and interact with the world.

However, the result that entertainment motivation does not impact continued use of ChatGPT runs counter to previous findings that ChatGPT users use the application for entertainment. Strzelecki [9] found that students view AI chat as an enjoyable and entertaining tool because its dialogue-based interface engages them and facilitates a wide range of conversations. These contradictory results suggest that students may lack sufficient experience with ChatGPT and are not yet familiar with its uses.

Meanwhile, this study found a significant relationship between personal innovativeness and intentions to continue using ChatGPT. People with technological efficacy have high risk reduction abilities and positive attitudes toward new technologies. Numerous previous studies have shown that individual tendencies impact new technology adoption [47]. In particular, research has shown that since members of younger generations often actively use new technologies and are not afraid of experiencing new things, technological efficacy level may impact new technology usage [54]. Thus, this study’s finding that college students’ innovativeness levels influence their intentions to continue using ChatGPT aligns with the findings of previous studies.

Lastly, this study found a significant relationship between social influence—defined as perceived pressure from social networks (including friends and family members)—and intentions to continue using ChatGPT. According to Malhotra and Galletta [16], social influences that generate feelings of internalization and identification in users positively influence acceptance of new technologies. Given that potential adopters of ChatGPT are exposed to informal social networks comprised of circles of friends, family members, and other important connections, the findings of this study suggest that college students may identify with their peers or family members who use ChatGPT, and this feeling may facilitate adoption of this technology. In this regard, this study’s results support previous findings regarding the effects of friendship networks on social assimilation [55, 56].

This study’s findings that personal innovativeness and social influence affect ChatGPT usage intentions contribute to scholarly understanding of both individual- and societal-level preparation for the rapid development and deployment of generative AI. In other words, by helping to elucidate the AI adoption process, this study highlights the importance of considering both individual characteristics (such as personal innovativeness) and social settings (social influence).

In addition, this study’s findings have key practical implications. First, they suggest that ChatGPT users may not be entirely driven to keep using the platform for entertainment purposes. Thus, rather than focusing on entertainment value, designers and marketers should highlight the functional advantages—such as rapid task completion—of AI technologies. Second, the finding that compared to other factors, PU is the most significant predictor of intentions to continue using ChatGPT suggests that greater attention should be given to the application’s technological and functional aspects.

Despite these theoretical and practical implications, this study had several limitations that highlight possible directions for future research. First, while it provides early insights regarding user motivations (focusing on information seeking and entertainment motivations among early adopters of ChatGPT), since the study’s participants were college students, its findings only shed light on the current state of ChatGPT adoption among educated early and potential adopters. Thus, future studies should verify the accuracy of its key findings with more established use patterns and employ longitudinal approaches to assess the evolution of diverse motivations. Second, given that this study used a limited sample from a narrow geographical region, future research should consider samples from different countries and cultures. Finally, the study explored the factors that motivate Korean college students to continue using ChatGPT at an early stage of the technology’s development. Future studies should consider testing similar trends with participants of different ages, occupations, and stages in life.

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