Exploring chatbot trust: Antecedents and behavioural outcomes

Alagarsamy, Subburaj; Mehrolia, Sangeeta

doi:10.1016/j.heliyon.2023.e16074

Cited by 15 publications

(5 citation statements)

References 119 publications

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“…Thus, the quality of the information provided by the chatbot influences "Customer Experience" and the intentions towards its use (Alagarsamy et al, 2023). Nevertheless, little research has explored the interactive role of frequency of use of chatbots and the relationship between "Information Quality" and "Customer Experience".…”

Section: Informationmentioning

confidence: 99%

Purchase intentions in a chatbot environment: An examination of the effects of customer experience

Martínez Puertas,

Illescas Manzano,

Segovia López

et al. 2024

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Research background: Chatbots represent valuable technological tools that allow companies to improve customer experiences, meet their expectations in real time, and provide them with personalized assistance. They have contributed to the transformation of conventional customer service models into online solutions, offering accessibility and efficiency through their integration across various digital platforms. Nevertheless, the existing literature is limited in terms of exploring the potential of chatbots in business communication and studying their impact on the customer's response. Purpose of the article: The main objective of this study is to examine how consumers perceive chatbots as customer service devices. In particular, the paper aims to analyze the influence of the dimensions of “Information”, “Entertainment”, “Media Appeal”, “Social Presence” and “Risk for Privacy” on the “Customer Experience” and the latter on the “Purchase Intention”, under the consideration of the Uses and Gratifications Theory. Moderations due to Chatbot Usage Frequency for some of the relationships proposed are also analyzed. Methods: An empirical study was performed through a questionnaire to Spanish consumers. The statistical data analysis was conducted with R software through the lavaan package. To test the hypotheses from the conceptual model a structural equation modelling approach was adopted. Findings & value added: The results obtained identify the main characteristics of chatbots that can support brands to effectively develop their virtual assistants in order to manage their relational communication strategies and enhance their value proposal through the online customer journey. Findings demonstrate the contribution that chatbot dimensions make to the online consumer experience and its impact on the purchase intention, with the consideration of the moderating effect exercised by the user's level of experience (novice vs. experienced) with the use of chatbots. Regarding managerial implications, this research offers recommendations for e-commerce professionals to manage chatbots more effectively. The “Entertainment” and “Social Presence” dimensions can be operationalized at a visual (e.g., appearance of the avatar and text box, use of designs aligned with the website) and textual level (e.g., style and tone of voice, use of expressions typical of the target audience) to generate a feeling of proximity with the chatbot and facilitate its adoption. “Media Appeal” requires that the chatbot be easy to use, effective, and accessible, to facilitate its usability. Finally, mitigation of “Privacy Risk” concerns should be achieved by presenting an appropriate privacy policy and requesting permission for the use of customers’ private information.

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Section: Informationmentioning

confidence: 99%

Purchase intentions in a chatbot environment: An examination of the effects of customer experience

Martínez Puertas,

Illescas Manzano,

Segovia López

et al. 2024

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“…For example, social exchange theory is used to explain customer behaviour (Casper Ferm & Thaichon, 2021), employee performance (Kuruzovich et al, 2021), inter-organisational exchange, and trust (Lioukas & Reuer, 2015), and relationships between leaders and peers work (Miao et al, 2014). In essence, social exchange theory argues that it occurs between leaders and employees during their relationships, creating trust, influence, and loyalty (Blau, 1964;Quade et al, 2020) and Zhu et al (2023), Alagarsamy and Mehrolia (2023).…”

Section: Social Exchange Theorymentioning

confidence: 99%

“…Moreover, the study focused on SMEs in the culinary and craft fields, which may limit the generalizability of the findings to other industries. Future research could explore the relationship between supportive climate, absorptive capacity, and innovative behavior in other industries and contexts (Trentin, 2023;Rodrigues & Rebelo, 2023;Alagarsamy & Mehrolia, 2023). Researchers could use alternative data collection methods, such as interviews or observations, to obtain more in-depth information.…”

Section: Absorptive Capacity and Innovative Behaviormentioning

confidence: 99%

Strengthening Innovative Behavior: The Role of Supportive Climate and Absorptive Capacity

Rozak,

Taswan,

Mansyur

et al. 2024

Business: Theory and Practice

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This study explores how to achieve innovative behavior in Indonesian SMEs in the culinary and craft sectors. We conducted a literature review and collected data from 372 SME owners. Using SEM analysis, we found that a supportive climate positively impacts both potential and realized absorptive capacity, which in turn positively impacts innovative behavior. The study’s findings contribute to social exchange theory and have implications for SME sector organizations. Limitations include the data collection method, sample size and selection, research objective, cross-sectional design, and self-reported data. Future research could address these limitations and investigate other organizational factors that may influence innovative behavior in SMEs.

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“…Chatbots represent virtual human communication interaction tools (Alagarsamy & Mehrolia, 2023;Wang et al, 2023); through the exchange of audio or text (Hsu & Lin, 2023;Smutny & Schreiberova, 2020;Xing et al, 2022). Chatbots make use of natural language processing, and today are part of the most advanced technological tools for automatic and personalised interaction (Baabdullah et al, 2022;Brustenga et al, 2018;Drouin et al, 2022;Zhou et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Application of the Chatbot in University Education: A Bibliometric Analysis of Indexed Scientific Production in SCOPUS, 2013-2023

Chamorro-Atalaya,

Olivares-Zegarra,

Sobrino-Chunga

et al. 2023

IJLTER

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Universities today are employing tools based on artificial intelligence to improve the educational service in general. The chatbot represents an online communicative interaction tool which contributes to solving daily queries required by students, teachers or graduates. However, there are few bibliometric review studies on the chatbot that show in which areas there is a greater concentration or lack of scientific production at the university level. The objective of this article is to explore and describe the research trends regarding the application of the chatbot in university education through the bibliometric analysis of publications indexed to Scopus. The research is of an exploratory-descriptive level, developed under a quantitative approach. The study covered the scientific production between the years 2013 and 2023, identifying 210 manuscripts. It was identified that there is a growing trend in scientific production, particularly in scientific articles and conference papers. The most cited article was published in 2018 and has 162 citations. Therefore, it is concluded that there is a greater concentration in the scientific production of manuscripts focused on improving the university educational service, applying significantly to the improvement of academic performance, administrative management and university wellbeing. However, there is a gap that needs to be reduced in terms of the lack of scientific studies in which the chatbot is used as a tool to identify the satisfaction of university students. In addition, there is a lack of research on the use of a regulatory framework that regulates the application of the chatbot at the university level.

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Exploring chatbot trust: Antecedents and behavioural outcomes

Cited by 15 publications

References 119 publications

Purchase intentions in a chatbot environment: An examination of the effects of customer experience

Purchase intentions in a chatbot environment: An examination of the effects of customer experience

Strengthening Innovative Behavior: The Role of Supportive Climate and Absorptive Capacity

Application of the Chatbot in University Education: A Bibliometric Analysis of Indexed Scientific Production in SCOPUS, 2013-2023

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