Chatbot Evaluation as Knowledge Application: a Case Study of PT ABC

Sensuse, Dana Indra; Dhevanty, Venniesa; Rahmanasari, Ernestina; Permatasari, Desy Intan; Putra, Bimo Eka; Lusa, Sofian; Misbah, Muhammad; Prima, Pudy

doi:10.1109/iciteed.2019.8929967

Cited by 10 publications

(10 citation statements)

References 6 publications

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“…Nowadays, customers are sophisticated users of new technologies and text messaging in particular, which has led to businesses incorporating messaging to solve customers' problems. Sensuse et al (2019) affirm that chatbots have faster response compared to customer care personnel. They can run uninterruptedly, hence, the customer is assured of a quick answer at any time.…”

Section: Discussionmentioning

confidence: 80%

“How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment

Rizomyliotis

Kastanakis

Giovanis

et al. 2022

Journal of Business Research

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Section: Discussionmentioning

confidence: 80%

“How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment

Rizomyliotis

Kastanakis

Giovanis

et al. 2022

Journal of Business Research

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“…Nguyen (2019) also tried to examine whether a chatbot could improve the consumer experience when the chatbot possesses the capability of understanding. Research also has shown that chatbot agents that understand and use humans' humor are ranked more likable, cooperative, and capable as well as provide better solutions and performance than those that do not understand it (Sensuse et al 2019;Thies et al 2017). The dimension of understandability in this study is distinct from the information understandability (or ease of understanding) as one of the information quality dimensions proposed by Lee et al (2002) or Wang and Strong (1996).…”

Section: Chatbot Quality Dimensionsmentioning

confidence: 66%

“…Kalia et al (2017) discovered that the reliability of chatbots can be ensured if a meaningful response is provided in a conversation. Sensuse et al (2019) also found that chatbots that are reliable could enhance the effectiveness of job performance and motivate further development.…”

Section: Chatbot Quality Dimensionsmentioning

confidence: 96%

What makes you continuously use chatbot services? Evidence from chinese online travel agencies

et al. 2021

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Thanks to artificial intelligence, chatbots have been applied to many consumer-facing applications, especially to online travel agencies (OTAs). This study aims to identify five quality dimensions of chatbot services and investigate their effect on user confirmation, which in turn leads to use continuance. In addition, the moderating role of technology anxiety in the relationships between chatbot quality dimensions and post-use confirmation is examined. Survey data were gathered from 295 users of Chinese OTAs. Partial Least Square (PLS) was used to analyze measurement and structural models. Understandability, reliability, assurance, and interactivity are positively associated with post-use confirmation and technology anxiety moderates the relationships between four chatbot quality dimensions and confirmation. Confirmation is positively associated with satisfaction, which in turn influences use continuance intention. This study examines how chatbot services in OTAs are considered by users (human-like agents vs. technology-enabled services) by investigating the moderating role of technology anxiety.

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“…This model is based on the socio-technical approach and includes the technological and human components of using the system. There are six criteria for measuring the performance of IS, including system quality, information quality, service quality, intention to use, user satisfaction, and net benefit [16]. System quality, information quality, and service quality are main dimensions specifically used to evaluate the system, where intention to use and user satisfaction are thus impacted by these aspects [17].…”

Section: Delone and Mclean Success Modelmentioning

confidence: 99%

Knowledge Management System Evaluation Using DeLone McLean Model: A Case Study of IT Service Desk Bank XYZ

Desiana Nurul Maftuhah,

Lia Ellyanti,

Dana Indra Sensuse

et al. 2023

j. nas. pendidik. teknik. inform.

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Bank XYZ is one of the biggest banks in Indonesia. It has IT Service Desk function under Information Technology Division that specifically handles complaints or problems related to IT. Knowledge management in IT service desk can help to increase the availability of information and knowledge for the IT service desk team who must provide explanations to users. IT Service Desk of Bank XYZ has built knowledge management system using open-source platform since 2017. It is called SDKPedia which was developed inhouse by IT Service Desk team and never been evaluated since it was built. The objective of this study is to evaluate SDKPedia as knowledge management system used in IT Service Desk Bank XYZ. Evaluation was carried out based on Delone and McLean assessment criteria. Survey is distributed to IT Service Desk worker and 31 valid feedback is used in this study. To determine the indications that have a substantial impact and result in a net advantage for SDKPedia, the PLS-SEM algorithm is utilized. Service quality is the only exogen latent variable that affected intension of use. While the other two exogen latent variable are system quality and information quality, did not have significant impact for intention to use or user satisfaction. Considering the findings of this study, several improvements can be made by the IT Service Desk manager to make the quality of SDKPedia better. The points that need more attention are information quality and system quality.

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Chatbot Evaluation as Knowledge Application: a Case Study of PT ABC

Cited by 10 publications

References 6 publications

“How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment

“How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment

What makes you continuously use chatbot services? Evidence from chinese online travel agencies

Knowledge Management System Evaluation Using DeLone McLean Model: A Case Study of IT Service Desk Bank XYZ

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