Purpose: The purpose of this study is to empirically analyze the effect of chatbot service quality, chatbot trust, and chatbot satisfaction on chatbot reuse intention and store reuse intention. Research design, data, and methodology: We reviewed the literature on domestic and international chatbots, established hypotheses, and analyzed them. We empirically analyzed the process model in which chatbot service quality (interaction quality, information quality) has a positive effect on chatbot trust and chatbot satisfaction, and that chatbot trust and satisfaction positively affect chatbot reuse intention and store reuse intention. A survey was conducted on 212 people who had used shopping mall chatbots and financial service chatbots after demonstrating the shopping mall chatbot video. Structural equation modeling was conducted by using AMOS 24.0 to test the proposed relationships. Results: As a result of the empirical analysis, the effects of interaction quality on chatbot trust and information quality on chatbot satisfaction were not supported, but the rest of the hypotheses were statistically significant. It was found that the information quality of chatbot service had a positive effect on chatbot trust, but did not significantly affect chatbot satisfaction. In addition, the interaction quality of the chatbot positively affects the satisfaction of the chatbot, but it does not significantly affect the trust of the chatbot. Chatbot trust was found to have a positive effect on chatbot satisfaction. Chatbot trust and chatbot satisfaction were found to have a positive influence on the intention to reuse the chatbot. And, chatbot trust and chatbot satisfaction were found to have a positive influence on store reuse intention. Conclusions: The findings of this study offer significant theoretical and managerial contributions in the context of chatbot. Chatbots should enhance customer contact quality management from the perspective of total customer experience management rather than partial function. When providing a chatbot service, it is more desirable to give priority to providing accurate information to increase trust, and at the same time to improve customer satisfaction by increasing the quality of interaction. And in order to increase the competitive advantage of companies, the purpose of introducing chatbots should be clarified and approached strategically.
Purpose - This study aims to investigate factors affecting Chatbot service acceptance attitude. For wide use of Chatbot service, firms need to find barriers or obstacles for customers, if any, not to use Chatbot service. Research design, data, and methodology - We apply value-based accept model to investigate the quality of Chatbot, to verify the meaning of service value of Chatbot and to find the relationship among variables. To test hypotheses, we conducted survey. We collected 300 questionnaires. SPSS version 2.0 is used. Regression analysis, moderating effect test is conducted. Results - 4 Qualities of Chatbot, Ease of use, Usefulness, Enjoyment, Interaction are affecting acceptance attitude, and 5 service values, only interaction does not affect emotion. Trust, Specialty, Necessity, Social, Emotion moderating Chatbot service to accepting attitude. Regarding moderating effects by personal characteristics and personal tendency, innovation resistance, innovativeness, and social effects are turned to have influence while regulatory focus, construal level does not have moderating force. Also, the auxiliary service like Chatbot service affects customers' evaluation on the main service quality. Conclusions - Service firms adopt Chatbot service for various purposes. The results imply that customers are generally recognize the merits of Chatbot, but there are some barriers such as innovation resistance characteristic especially uncomfortable.
Due to the development of IT technology and the on-going Coronavirus disease, non-face-to-face services have been activated. To overcome the inconvenience of non-face-to-face service, service providers have adopted chatbots as a way to feel like a human being. As the increasing chatbot services, chatbot builders have emerged, which can help non-developers to build them. Although its popularity has increased, its performance evaluation has not been conducted on such chatbot builders. In this paper, we implement a prototype chatbot that classifies hospital departments in the medical field using Dialogflow and Rasa, which are popular chatbot builders. By measuring the accuracy of the chatbot's classification of medical subjects, we evaluated the level of accuracy that the most used chatbot builder can have when they are used to build a chatbot service. The simulation results showed that Dialogflow had 87%, 65%, and 60%, and Rasa did 64%, 70%, and 63% in surgery dermatology, and otolaryngology, respectively.
This study investigated the effects of the chatbot's level of anthropomorphism - closeness to the human form - and its self-disclosure - delivery of emotional exchange with the chatbot through its facial expressions and chatting message on the user's intention to accept the service. A 2 (anthropomorphism: High vs. Low) × 2 (self-disclosure through facial expressions: High vs. Low) × 2 (self-disclosure through conversation: High vs. Low) between-subject factorial design was employed for this study. An online survey was conducted and a total of 234 questionnaires were used in the analysis. The results showed that consumers used chatbot service more when emotions were disclosed through facial expressions, than when it disclosed fewer facial expressions. There was statistically significant interaction effect, indicating the relationship between chatbot's self-disclosure through facial expression and the consumers' intention to use chatbot service differs depending on the extent of anthropomorphism. In the case of "robot chatbots" with low anthropomorphism levels, there was no difference in intention to use chatbot service depending on the level of self-disclosure through facial expression. When the "human-like chatbot" with high anthropomorphism levels discloses itself more through facial expressions, consumer's intention to use the chatbot service increased much more than when the human-like chatbot disclosed fewer facial expressions. The findings suggest that chatbots' self-disclosure plays an important role in the formation of consumer perception.
Journal of Korea Artificial Intelligence Association
/
v.2
no.1
/
pp.15-24
/
2024
This study is about the effect of chatbot service quality on customer satisfaction and continuous use intention. Data collection was conducted for 13 days from October 23 to November 5, 2023, and a survey was conducted on customers who have used chatbot services. A total of 572 questionnaires were targeted, of which 545 valid data were used for analysis, excluding those that responded insincerely or did not meet the purpose of the study. The analysis results of this study are as follows: First, chatbot service quality partially had a significant effect on satisfaction. Second, customer satisfaction had a significant effect on continuous use intention. Therefore, in order to have a positive impact on continuous use intention, it is necessary to focus on marketing strategies related to chatbot service quality. Also, research focusing on data analysis and performance evaluation is crucial for enhancing chatbot services, necessitating studies that address real-time changes. Through sophisticated data analysis and variable measurement, chatbot services can be effectively improved, leading to enhanced customer satisfaction.
This study examined the impact of chatbot service quality (process quality, outcome quality, and servicescape quality) on user satisfaction and reliability by identifying the relationships between user satisfaction, reliability, immersion, and the paths of three variables influencing reuse intention. The survey was conducted of Korean users in their teens and 70s who had experience using chatbot services. A total of 218 convenience samples were extracted and the data analyzed. By the IS success and SERVQUAL model, the results of structural equation modeling revealed that the chatbot service quality did not affect user satisfaction and reliability. However, user satisfaction and reliability of the chatbot services were shown to lead to reuse intention, and user satisfaction was shown to affect immersion and immersion in reliability. The results showed that satisfaction, reliability, and immersion in the chatbot services were important factors in the chatbot reuse intention. Through the satisfaction and reliability gained through the service, the users wanted to reuse the chatbot services, especially the chatbot services that gained reliability, which will have a greater impact on reuse intention. We can use these results as marketing information to attract loyal customers by identifying the reuse intention of the chatbot service users.
Purpose: This research aims to contribute to the search for strategies on innovation in chatbot services in airline distribution industry. Personal and systemic characteristics of chatbot were derived together. The extended technology acceptance model theory was applied. The effects of perceived ease of use, usefulness, and intention to use chatbot from the user's perspective were empirically analyzed. Research design, data and methodology: Through an online survey, 309 people who have experience using chatbot services in airline distribution industry responded. AMOS 18.0 was used to analyze the data. Results: The hypothesis that personal characteristics will positively influence perceived ease and perceived usefulness was tested. Self-efficacy and user's innovativeness were shown have a significant effect on both perceived ease and perceived usefulness. System characteristics present a positive effect on perceived ease and perceived usefulness was tested. Consistency and familiarity were found to affect perceived ease and perceived usefulness. Perceived ease of use and perceived usefulness show a positive effect on intention to continue using chatbot service. Conclusions: When building an airline chatbot service in airline distribution industry, it is necessary to consider systematic characteristics, ease of use, and usability. It provided practical implications in that it have a significant impact on users' intention to use.
Purpose - The purpose of this study was to investigate the effects of the chatbot's characteristics (ease of use, social presence, playfulness, usefulness) on service value, customer satisfaction and reuse intention when consumers purchased fashion products in the mobile shopping environments. Research design, data, and methodology - Data were collected from Korean consumers from ages 20 to 59 who have experienced using chatbot in a mobile shopping for fashion products. After a pilot survey to 53 customers, the preliminary questionnaire was revised for the final test, and the final questionnaire was administered to 1500 customers. Out of these, 300 were collected. After deleting 48 incomplete ones, 252 questionnaires were used in the statistical analysis. Frequency analysis and exploratory factor analysis using SPSS 23.0 and confirmatory factor analysis and structure equation analysis using AMOS 18.0 were employed for data analyses. Results - First, four factors were extracted for the chatbot's characteristics: ease of use, social presence, playfulness and usefulness. Second, regarding the effect of chatbot's characteristics on service value when purchasing fashion products in the mobile shopping environment, ease of use, playfulness and usefulness of chatbot significantly affected service value. Social presence did not have significant effects on service value. Third, in terms of the effect of the chatbot's characteristics on customer satisfaction when purchasing fashion products in the mobile shopping environment, social presence, playfulness and usefulness of chatbot significantly had an effect on customer satisfaction. Ease of use did not have a significant effect on customer satisfaction. Fourth, service value of chatbot when purchasing fashion products in mobile shopping environment was found to have an effect on customer satisfaction with chatbot. Fifth, service value of chatbot on reuse intention when purchasing fashion products in the mobile shopping environment was found to have an effect on reuse intention of chatbot. Sixth, customer satisfaction with chatbot had a significant impact on the reuse intention of the chatbot when purchasing fashion products in the mobile shopping environment. Conclusions - The present study provide dimensions on the chatbot's characteristics and these may provide helpful data for further studies in this area and for marketers as well.
Journal of the Korean BIBLIA Society for library and Information Science
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v.34
no.2
/
pp.183-203
/
2023
This study was conducted to analyze the characteristics of the artificial intelligence chatbot service of the library and compare the usability of the chatbot service applied to the library, and to propose a plan to improve the usability of the artificial intelligence chatbot service in the library. In order to achieve this research purpose, usability comparison factors were extracted through previous studies on the usability evaluation of artificial intelligence chatbot services, and based on case studies, artificial intelligence chatbot services applied to libraries were classified into their own website-based and SNS-based chatbot services according to the platform. Experiments, questionnaires, and interviews were conducted to evaluate the usability of website-based and SNS-based chatbot services applied to the library. Based on the results of the usability evaluation, implications and improvement plans for the artificial intelligence chatbot service of the library were derived.
This study examined whether the social support (emotional support, information support) provided by customers through chatbot service affects the satisfaction of chatbot service felt by customers and whether the satisfaction of chatbot service affects loyalty and intention to continue using chatbot service. In order to confirm the moderating effect of social presence of chatbot service, a total of 300 effective data were obtained by conducting an online survey divided into a group that recognizes social presence highly and a group that recognizes low. As a result of the analysis, the path from emotional support to satisfaction of chatbot service was supported in the group that recognized social presence highly, and the path from emotional support to satisfaction of chatbot service was not supported in the group that recognized social presence low, and the difference was confirmed in the hypothesis path coefficient. This is interpreted as the social presence affecting human emotional response.This study can provide implications for the function of social presence of chatbot service in that it applied information support and emotional support, which are two factors of social support, to chatbot service, and demonstrated the relationship between satisfaction, loyalty, and continuous use according to the degree of social presence of chatbot users.
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