This study investigates the perception and adoption of ChatGPT (a large language model (LLM)-based chatbot created by OpenAI) among Korean users and assesses its potential as the next disruptive innovation. Drawing on previous literature, the study proposes perceived intelligence and perceived anthropomorphism as key differentiating factors of ChatGPT from earlier AI-based chatbots. Four individual motives (i.e., perceived usefulness, ease of use, enjoyment, and trust) and two societal motives (social influence and AI anxiety) were identified as antecedents of ChatGPT acceptance. A survey was conducted within two Korean online communities related to artificial intelligence, the findings of which confirm that ChatGPT is being used for both utilitarian and hedonic purposes, and that perceived usefulness and enjoyment positively impact the behavioral intention to adopt the chatbot. However, unlike prior expectations, perceived ease-of-use was not shown to exert significant influence on behavioral intention. Moreover, trust was not found to be a significant influencer to behavioral intention, and while social influence played a substantial role in adoption intention and perceived usefulness, AI anxiety did not show a significant effect. The study confirmed that perceived intelligence and perceived anthropomorphism are constructs that influence the individual factors that influence behavioral intention to adopt and highlights the need for future research to deconstruct and explore the factors that make ChatGPT "enjoyable" and "easy to use" and to better understand its potential as a disruptive technology. Service developers and LLM providers are advised to design user-centric applications, focus on user-friendliness, acknowledge that building trust takes time, and recognize the role of social influence in adoption.
Engineered cementitious composites with calcined clay limestone cement (LC3-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC3-ECC compressive strength makes the prediction of LC3-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC3-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC3-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC3-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R2) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC3-ECC materials and further apply to such low-carbon, sustainable cement-based materials.
The objective of this study is to investigate factors influencing user's intention to use by expanding TAM(Technology Acceptance Model). Based on this model, this study developed a comprehensive model and user's motivation factors such as extrinsic and intrinsic motivation to describe their intention to accept WCDMA service. For this purpose those who have subscribed to and use the current mobile communication service - all of whom were 13 to 49 years old living in Seoul or other large cities - were surveyed. Structural equation model was conducted to identify and validate the relationship of overall variables relating to mobile service acceptance. The analysis results indicate that intrinsic motivations in mobile service acceptance process have significant impacts on perceived usefulness and perceived ease to use. The results of this study also proposed the way to boost mobile service user's extrinsic and intrinsic motivation for coming up with strategies on how to improve effectiveness of communication and marketing. Future directions and limitations are also discussed.
An analysis was carried out for this study to figure out if there exists any differences in the model consumers accept for commercialized MP3-playing clothing and bio-signal sensing clothing. To analyze the differences of the structural variables of the products types, t-test was conducted with SPSS 15.0 package and multi-group analysis with AMOS 5.0 to find out the differences of each path goes with product types in structural equation model. In analytical results of effective sample of 557 copies of questionnaire, consumers' were highly aware of MP3-playing clothing in perceived ease of use, while they were aware relatively high of bio-signal sensing clothing in perceived usefulness, attitudes, consumer acceptance. The perceived value which was input to find out consumers awareness about sale price of commercialized products, was proven to do very important moderating role in forming consumers' attitudes and acceptance intention. Besides, consumers showed a difference in path in accepting model goes with product types. In bio-signal sensing clothing case, 'the perceived usefulness$\rightarrow$attitudes' path which was backed up in MP3-playing clothing was rejected, and 'perceived value$\rightarrow$attitudes' path appeared relatively high with moderating role of perceived value higher than MP3-playing clothing. Considering the results above, as the smart clothing is in the initiative commercialization stage while consumers were in the inquiry stage into awareness or information necessary in the course of purchase decision-making, and so an effective commercialization strategy seems to be necessary.
Kim, Hyung-Rae;Hwang, Jong-Sun;Kim, Jeong-Woo;Lee, Seon-Ho
Economic and Environmental Geology
/
v.45
no.4
/
pp.377-384
/
2012
The main field component of the Earth's magnetic field was modeled from the tri-axial magnetometer onboard KOrean MultiPurpose SATellite-II (KOMPSAT-II) for the purpose of satellite attitude control. The model computed by the KOMPSAT-II magnetometer measurement data is compared with the International Geomagnetic Reference Field (IGRF) model of a degree of up to 13 in spherical harmonic coefficients. The previous study with KOMPSAT-I (Kim et al. 2004) indicated a good correlation of power spectrum of spherical harmonic coefficients with respect to the degree up to 5. This study, however, showed an agreement of the degree up to 8-9 of the coefficient power spectrum and a discrepancy between degrees 10 and 13. We have concluded that relevant data selection process, removal of the external field from the data in the high latitude region, an accuracy of the magnetometer all play an important role in finding a coherence with the IGRF model. This study will be extended to the secular variation model of geomagnetism if longer-period data become available.
Journal of the Korea Society of Computer and Information
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v.11
no.6
s.44
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pp.87-97
/
2006
This study aims to identify the effect that the perceived usefulness and perceived ease of use have on learner flow in e-learning community. Based on literature review and Technology Acceptance Model(TAM), a potential model and five hypotheses were suggested. Questionnaire was carried out among 62 members of one e-learning community for preparatory teacher Cronbach alpha of the questionnaire was.88. The collected data were analyzed through correlation analysis and path analysis. The results of this research are as follows. Three hypotheses were adopted: Perceived usefulness will affect on attitudinal flow, Perceived ease of use will affect on attitudinal flow. and Attitudinal flow will affect on behavioral flow. Two hypotheses were rejected;. Perceived usefulness will affect on perceived ease of use and Perceived ease of use will affect on behavioral flow. The model revised through the results of path analysis had good-fitness. That is. overall fit measures (RMSEA, CFI. NNFI). indexes that show the suitability of the model were quite good. Findings of this study suggested the important strategies for designing e-learning community in order to promote learner flow.
Mobile technology is accelerating innovative changes across all fields of our society as well as business environments. Especially, demands on mobile government (M-government) services have been increased gradually since e-government has improved national administration services dramatically. However, high-quality services which are acceptable to may users are not actually supplied because technical issues such as security on mobile e-government services have not solved and governance policy was not established yet. Previous studies show that most researches are devoted to technical ones or limited to theoretical exploratory study. As a result, developing useful guidelines which are practically and theoretically proved is one of the very important research issues. This study reviews the previous research works such as concept of mobile, e-government, M-government, technical trends of mobile, market situations, present status, and various case studies. And then we develop a research model with five factors, twenty four variables and seventy six measurement for measuring the influencing factors to adoption of M-government services. The model is composed of total 16 hypotheses, 22 variables, and 76 measurements. The model is analyzed by using statistical package SPSS (18.0) and AMOS (18.0) together with structural equation method based on 294 samples. The results show that the model is valid and there are statistically significant influence between ease of use and usefulness, ease of use and user's satisfactions, usefulness and intent of re-use, and user's satisfactions and intent of re-use, excepting usefulness and user's satisfaction, ease of use and intent of re-use did not affect significant influences. Especially, service quality, system quality, and relationship quality are identified as influencing factors to adaption of M-government service. The results are expected to provide a theoretical research framework which generate new research issues in M-government service area. It also can provide an useful guidelines to practical experts in successfully implementing M-government services. Further research directions are as follows. User's intents have to be studied in details by classifying users by individual, enterprise, and government as well as developing a new hypothetical model. Since M-government service is at the initial stage, longitudinal studies have to be conducted to trace the peoples' need in order to develop new high-quality mobile services.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.2
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pp.283-289
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2021
Many people with disabilities have shown interest in artificial intelligence speakers that serves as the main hub of the smart home. Therefore, the purpose of this study was to identify the intention of people with disabilities to use such speakers. The focus is on those with physical disabilities, a segment that accounts for the largest number of disability types. Based on the theoretical model of technology acceptance, the effect of perceived ease of use and perceived usefulness of artificial intelligence speakers by people with disabilities was analyzed using Structural Equation Modeling (SEM). Research has confirmed that the technology acceptance model is suitable for identifying the intention to use artificial intelligence speakers by people with disabilities, and specifically that the perceived ease of use has a significant impact on usefulness. Furthermore, the perceived ease of use for people with disabilities did not have a statistically significant effect on their intent to use whereas the perceived usefulness was shown to have a significant effect on the same. This study is meaningful as a foundation for developing customized artificial intelligence speaker services and improving the use of artificial intelligence speakers by people with disabilities.
With the proliferation of electronic commerce, online transactions have become a norm. Its enormous potential, however, can be truly realized if consumers feel comfortable facing invisible sellers over the Internet, a virtual business channel. Trust has been identified as a key component in many e-Commerce studies. The purpose of this study is to find out which factors play a major role in building buyer trust and how the build-up trust affects buyer's purchase intention in online used car transactions. Based on the information asymmetry, TAM (Technology Acceptance Model), and the trust theory, our research model includes factors such as a buyer's propensity-to-trust, institutional characteristics (inspection and warranty policy), word-of-mouth referral, perceived size, and perceived benefits as independent variables. The model also includes trust as a mediate variable, purchase intention as a dependent variable, and perceived quality risk as a moderate variable. The research model is tested by analyzing 448 sample data gathered from used car websites. The result shows that the trust has significant effects on the online purchase intention, and institutional characteristics have been identified as one of the most significant factors for trust building in used car websites. For those who perceive quality risk high, actual purchasing behavior occurs only when they have trust on the used car websites, indicating that trust plays a vital role as a mediate variable. This study suggests that buyer trust on the used car websites is important to increase buyer's online purchase behavior.
This research has reviewed the major composition concepts and the positive research results in the selected studies which were theoretically based on IDT (Innovation Diffusion Theory), IRM (Model of Innovation Resistance), TAM(Technology Acceptance Model), and IAPA(Information Asset Protection Activity) in order to improve the theoretical explanation of major characterized factors influencing on the introduction of MST (Mobile Security Technology). The characterized factors for the adaptation of MST and 17 hypotheses on the MST study models in order to test the effects on the intention to use are empirically verified by utilizing the analysis method of structure equation model. As a result of a study, First, the most influential characterized factors of IRM are shown as compatibility, complexity, relative advantage, information asset protection in order. Second, the characterized factors affecting intention to use are shown as relative advantage, compatibility, innovation resistance, performance expectancy. The results of this study are relevantly significant to establish the theoretical foundation of the study on the adaptation of MST and The verification of the characterized factors provide strategic implication for the introduction of MST and policy direction which alleviates informational gap between new MST and previous Security Technology to diffusion agency.
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