Article

Can chatbots satisfy me? A mixed-method comparative study of satisfaction with task-oriented chatbots in mainland China and Hong Kong

February 2023
Computers in Human Behavior 143(3):107716

DOI:10.1016/j.chb.2023.107716

Authors:

Bo Hu

City University of Hong Kong

Wenjia Yan

City University of Hong Kong

Zhi Lin

University of Texas at Austin

Task-oriented chatbots are gradually being used across the globe. Most notably, while chatbots have for a long time penetrated users’ daily lives in mainland China, Hong Kong is still struggling to improve and promote its chatbot services. To determine whether antecedents of satisfaction and usage intention differ based on different stages of chatbot adoption and development, we conduct a comparative study based on a research model that integrates the Delone and McLean Information System success model and privacy concerns. The model is developed and examined using a mixed-method approach. After conducting focus group interviews (N = 15) in both regions, online surveys were conducted in mainland China (N = 637) and Hong Kong (N = 647), respectively. Based on qualitative exploration, we identified critical factors of perceived quality and privacy concerns. The quantitative findings further illuminate the different roles of the antecedents in the two regions. The results show that usage intention can be positively influenced by satisfaction, and satisfaction can be increased by relevance, completeness, pleasure and assurance in both regions. However, response time and empathy are factors influencing satisfaction only in mainland China. Privacy concerns cannot influence satisfaction in both regions.

Enhancing Students’ Digital Story Design: Investigating the Impact of an AI Chatbot on Performance and Intrinsic Motivation

Conference Paper

Full-text available

Sep 2024

Digital storytelling motivates students to effectively organize and express their ideas meaningfully. Students face challenges in educational digital story design and storytelling creation. High-quality digital stories require time for planning, creation, and refinement. Recently, researchers started to examine the possibility of co-writing stories with ChatGPT. This study used Cohen’s four story elements to build an AI chatbot. We investigated the effects of the AI chatbot on students’ story design performance and intrinsic motivation before and after using it via a case study design. The results showed significant differences in students’ story design performance among the pre-, mid-, and post-intervention test phases. Students reported high levels of perceived ease and usefulness of the chatbot with a positive attitude. However, there was no significant difference in intrinsic motivation to story design before and after the use. Some suggestions for improving the chatbot design and implications were discussed.

Examining the impact of Generative AI on social sustainability by integrating the information system success model and technology-environmental, economic, and social sustainability theory

Article

Full-text available

Dec 2024
Educ Inform Tech

Generative Artificial Intelligence (AI) refers to advanced systems capable of creating new content by learning from vast datasets, including text, images, and code. These AI tools are increasingly being integrated into various sectors, including education, where they have the potential to enhance learning experiences. While the existing literature has primarily focused on the immediate educational benefits of these tools, such as enhanced learning and efficiency, less attention has been given to how these tools influence broader social sustainability goals, including equitable access and inclusive learning environments. Therefore, this study aims to fill this gap by developing a theoretical research model that combines the information system (IS) success model, technology-environmental, economic, and social sustainability theory (T-EESST), and privacy concerns. To evaluate the developed model, data were collected from 773 university students who were active users of Generative AI and analyzed using the PLS-SEM technique. The findings showed that service quality, system quality, and information quality have a significant positive effect on user satisfaction. Using Generative AI tools is found to be positively affected by user satisfaction. Interestingly, the findings supported the positive role of Generative AI in promoting social sustainability. However, no significant negative correlation was found between privacy concerns and Generative AI use. The findings provide several theoretical contributions and offer insights for various stakeholders in developing, implementing, and managing Generative AI tools in educational settings.

Analisis Adopsi Continuous Auditing pada Fungsi Audit Intern di Lembaga Negara XYZ

Article

Full-text available

Jun 2024

This research is motivated by the challenges faced by the Internal Audit Function (IAF) at XYZ Government Institution in the midst of the rapid development of technology and financial transactions that have been fully digitized using the Enterprise Resource Planning / Human Resources Information System. In order to utilize financial transaction data and technology, IAF carries out digital transformation by adopting continuous auditing and developing the Pemantauan Off Site Risiko Operasional (PERISAI) application as a continuous auditing implementation tool. The purpose of this study is to analyze the suitability of the steps taken by the IAF at XYZ Government Institution in adopting continuous auditing based on the Global Technology Audit Guide (GTAG) 3: Coordinating Continuous Auditing and Monitoring to Provide Continuous Assurance (2nd edition), analyzing the success of the PERISAI application based on the user's perspective using the DeLone and McLean Information System Success Model. This research uses a case study research strategy with an exploratory study method. The data collection methods used were semi-structured interviews consisting of open and closed ended questions, documentation, and observation. The results of this study indicate that the steps taken by FAI to implement continuous auditing are not fully in accordance with the key steps for implementing continuous auditing in GTAG 3 (2nd edition), while the PERISAI application is considered successful by FAI internal auditors even though there are still some things that must be improved from the aspects of people, process, and technology used.

Efektifitas Penggunaan Analisis Stochastic Oscillator Dan Moving Average Convergence-Divergence Pada Perdagangan Saham-Saham Perbankan di Bursa Efek Indonesia

Article

Full-text available

Jun 2024

The objective of the research is to find out how effective stochastic oscillator and moving average convergence-divergence (MACD) technical analysis is in yielding capital gain and abnormal return, viewed from descriptive analysis, analysis of effects, and disparity test analysis by using some theories and previous research results. This research uses daily stock closing price data from the issuers in banking su-sector of the research period of 2015-2019. The research employs descriptive analytic approach, regression analysis and disparity test, supported by IBM SPSS version 25 software. The result of the descriptive analysis shows that buy and sell stochastic oscillator and MACD signals are effective in yielding capital gain. The result of regression analysis shows that gain signal yielded by indicator of Stochastic Oscillator and MACD has significant effects on capital gain in which the probability value (Asymp. Sig) of Stochastic Oscillator on capital gain is 0.000, and the probability value (Asymp.Sig) of MACD on capital gain is 0.000. The result of the disparity test analysis shows that there is no difference in abnormal return in the pre and post appearance of gain signal in Stochastic Oscillator and in MACD

Towards a Design Theory for Task-Oriented Conversational Agents

Conference Paper

Full-text available

Jun 2024

Conversational agents (CAs), especially in the form of chatbots, are becoming increasingly important in science and practice. Task-oriented CAs (TOCAs) in particular, which serve as language-based interfaces to software services and information systems, are becoming increasingly common, e.g., to enrich customer support and customer experience. However, other application scenarios are also increasingly being investigated. The literature already contains approaches with design knowledge for TOCAs. However, these mostly apply to specific application contexts. To provide scenario-independent design knowledge, we present the first steps towards the development of a general design theory for TOCAs that support the instantiation of corresponding information systems independent of specific application scenarios. Based on an extensive literature analysis, we present five design requirements and eleven design principles of a tentative design theory. We performed a positive evaluation with a moderated focus group of domain experts which provided us with evidence for future research.

Analisis Pengaruh User Satisfaction Terhadap Niat Penggunaan Sistem Informasi Kearsipan Dinamis Terintegrasi (SRIKANDI) pada Pemerintahan Kota Palembang: Analysis of the Influence of User Satisfaction on Intention to Use Integrated Dynamic Archival Information Systems in Palembang City Government

Article

Full-text available

Oct 2023

Transformasi digital berperan penting di Pemerintahan Indonesia dengan SRIKANDI (Sistem Informasi Kearsipan Dinamis Terintegrasi) yang diluncurkan oleh Kementerian PANRB pada 2020. Pada Februari 2023, SRIKANDI mulai diterapkan di Pemerintah Kota Palembang. Namun, fakta yang ada menunjukkan bahwa banyaknya aplikasi pemerintah yang tidak digunakan dan dinilai tidak efisien. Salah satu penyebab permasalahan tersebut terjadi dikarenakan rendahnya tingkat kepuasan pengguna. Oleh karena itu, perlu dilakukan analisis pengaruh user satisfaction terhadap niat penggunaan SRIKANDI di Pemerintahan Kota Palembang, terutama dari perspektif Aparatur Sipil Negara (ASN) sebagai pengguna SRIKANDI. Penelitian ini menggunakan teori Delone & McLean IS Success Model untuk mengukur faktor-faktor tiap dimensi kualitas, user satisfaction, intention to use, dan menambah faktor privacy concerns. Data dikumpulkan melalui kuisioner yang diberikan kepada 250 ASN di Kota Palembang. Data yang diperoleh dianalisis menggunakan aplikasi SmartPLS 4 dan teknik PLS-SEM. Hasil penelitian menunjukkan bahwa User Satisfaction berpengaruh positif pada Intention to Use. Sementara itu, User Satisfaction dipengaruhi positif secara signifikan oleh Completeness, Pleasure, dan Assurance. Availability dan Privacy Concerns tidak memiliki pengaruh signifikan terhadap User Satisfaction.

Exploring chatbot trust: Antecedents and behavioural outcomes

Article

Full-text available

May 2023

An awareness about the antecedents and behavioural outcomes of trust in chatbots can enable service providers to design suitable marketing strategies. An online questionnaire was administered to users of four major banking chatbots (SBI Intelligent Assistant, HDFC Bank's Electronic Virtual Assistant, ICICI bank's iPal, and Axis Aha) in India. A total of 507 samples were received of which 435 were complete and subject to analysis to test the hypotheses. Based on the results, it is found that the hypothesised antecedents, except interface, design, and technology fear factors, could explain 38.6% of the variance in the banking chatbot trust. Further, in terms of behavioural outcomes chatbot trust could explain, 9.9% of the variance in customer attitude, 11.4% of the variance in behavioural intention, and 13.6% of the variance in user satisfaction. The study provides valuable insights for managers on how they can leverage chatbot trust to increase customer interaction with their brand. By proposing and testing a novel conceptual model and examining the factors that impact chatbot trust and its key outcomes, this study significantly contributes to the AI marketing literature.

Exploring chatbot trust: Antecedents and behavioural outcomes

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Full-text available

May 2023

Airline chatbot: examining the response of outcome- and process-focused individuals for customer service requests

Article

Mar 2025

Purpose-This study aims to explore customer reactions to using chatbots in the airline industry and to understand the psychological factors influencing their preferences. Design/methodology/approach-Study 1 assesses attitudes toward human versus chatbot service agents in customer service interactions with social presence theory as the theoretical foundation to corroborate prior research, whereas Study 2 applies motivated action theory to analyze the impact of an individual's goal orientation traits (process and outcome) related to chatbot acceptance. Findings-Results indicate that individuals with outcome-focused personality traits show a preference for human agents when addressing customer service issues, suggesting that psychological factors significantly impact technology acceptance. Originality/value-This research contributes new insights into the understudied area of psychological predispositions affecting chatbot acceptance in service scenarios within the airline industry.

Interplay of factors determining users’ intentions to adopt chatbots for airline tickets assistance. The moderating role of perceived waiting time

Article

Full-text available

Feb 2025
AI Soc

Imdadullah Hidayat-ur-Rehman

This research seeks to perform a detailed empirical examination of the variables affecting user intent to utilize chatbots for airline ticket inquiries, using the Technology Acceptance Model (TAM) as a foundation. The study introduces a thorough framework that merges crucial elements like Perceived Social Presence, Perceived Completeness, Perceived Accuracy, Perceived Convenience, and User Satisfaction with TAM’s conventional constructs of Perceived Usefulness and Behavioural Intention to Use Chatbots. The partial least squares-structural equation modelling (PLS-SEM) method was employed to empirically verify our suggested model, with data collected via a survey distributed to prospective users in Saudi Arabia. From the 433 received responses, 396 valid ones were considered in the following analysis. The findings confirm that perceived usefulness and user satisfaction are key direct predictors of behavioural intention, while factors like Perceived Social Presence and Perceived Convenience have both direct and indirect significant impacts on behavioural intention to utilize chatbots for ticket consultation. Furthermore, Perceived Completeness and Perceived Accuracy were identified as significant influencers of perceived usefulness and user satisfaction. The study also confirmed that perceived waiting time significantly moderates the relationships between both perceived usefulness and behavioural intention, and perceived convenience and behavioural intention. This investigation not only furthers theoretical insights but also offers practical guidelines for creating effective chatbot services, thus providing significant contributions to theoretical and practical domains within the field.

AI Chatbot Adoption in Academia: Task Fit, Usefulness and Collegial Ties

Article

Full-text available

Jan 2024

Aim/Purpose: This mixed-methods study aims to examine factors influencing academicians’ intentions to continue using AI-based chatbots by integrating the Task-Technology Fit (TTF) model and social network characteristics. Background: AI-powered chatbots are gaining popularity across industries, including academia. However, empirical research on academicians’ adoption behavior is limited. This study proposes an integrated model incorporating TTF factors and social network characteristics like density, homophily, and connectedness to understand academics’ continuance intentions. Methodology: A qualitative study involving 31 interviews of academics from India examined attitudes and the potential role of social network characteristics like density, homophily, and connectedness in adoption. Results showed positive sentiment towards chatbots and themes on how peer groups accelerate diffusion. In the second phase, a survey of 448 faculty members from prominent Indian universities was conducted to test the proposed research model. Contribution: The study proposes and validates an integrated model of TTF and social network factors that influence academics’ continued usage intentions toward AI chatbots. It highlights the nuanced role of peer networks in shaping adoption. Findings: Task and technology characteristics positively affected academics’ intentions to continue AI chatbot usage. Among network factors, density showed the strongest effect on TTF and perceived usefulness, while homophily and connectedness had partial effects. The study provides insights into designing appropriate AI tools for the academic context. Recommendations for Practitioners: AI chatbot designers should focus on aligning features to academics’ task needs and preferences. Compatibility with academic work culture is critical. Given peer network influences, training and demonstrations to user groups can enhance adoption. Platforms should have capabilities for collaborative use. Targeted messaging customized to disciplines can resonate better with academic subgroups. Multidisciplinary influencers should be engaged. Concerns like plagiarism risks, privacy, and job impacts should be transparently addressed. Recommendation for Researchers: More studies are needed across academic subfields to understand nuanced requirements and barriers. Further studies are recommended to investigate differences across disciplines and demographics, relative effects of specific network factors like size, proximity, and frequency of interaction, the role of academic leadership and institutional policies in enabling chatbot adoption, and how AI training biases impact usefulness perceptions and ethical issues. Impact on Society: Increased productivity in academia through the appropriate and ethical use of AI can enhance quality, access, and equity in education. AI can assist in mundane tasks, freeing academics’ time for higher-order objectives like critical thinking development. Responsible AI design and policies considering socio-cultural aspects will benefit sustainable growth. With careful implementation, it can make positive impacts on student engagement, learning support, and research efficiency. Future Research: Conduct longitudinal studies to examine the long-term impacts of AI chatbot usage in academia. Track usage behaviors over time as familiarity develops. Investigate differences across academic disciplines and roles. Requirements may vary for humanities versus STEM faculty or undergraduate versus graduate students. Assess user trust in AI and how it evolves with repeated usage, and examine trust-building strategies. Develop frameworks to assess pedagogical effectiveness and ethical risks of conversational agents in academic contexts.

The impact of artificial intelligence implications on customer satisfaction: applied on the online banking sector in Egypt

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Oct 2023

Empirical Assessment of User Satisfaction with American and Chinese AI Chatbots

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Aug 2023

As artificially intelligent chatbots grow in popularity, exploring user satisfaction has become an important topic. This study deviates from the conventional questionnaire approach by adopting a balanced paired design. We employed 40 users to participate in usability testing to assess their satisfaction with the responses of two prominent chatbots (ChatGPT 4.0 from the US and inChat from China) over five domains (daily life, the workplace, advertising copy, current affairs commentary, and translation). We conducted a comparative analysis based on three demographic variables: gender, experience with chatbots, and generation (i.e., age). Empirical results revealed that the participants were more satisfied with inChat's responses overall and for daily life scenarios in particular than with those of ChatGPT 4.0. Further, female participants expressed higher satisfaction with inChat's commentary on current affairs than did male participants. Prior use of chatbots did not significantly influence satisfaction levels; however, Baby Boomers (i.e., those born between 1946 and 1964) showed a notably higher appreciation for inChat's translation capabilities and higher satisfaction overall compared to Generation Y (i.e., those born between 1981 and 1996).

The adoption of conversational assistants in the banking industry: is the perceived risk a moderator?

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Full-text available

Sep 2023

The world has noticed tremendous growth in information technology, particularly the Internet of Things and artificial intelligence. Nowadays, a lot of people rely on conversational assistants (CAs) and other intelligent virtual objects to check account balances, communicate more quickly, make payments, and manage their financial assets with banks or other financial institutions. This study scrutinizes how consumers espouse and utilize conversational assistants in banking amenities. To provide empirical evidence and generalize sample results in a larger context, a quantitative research approach has been utilized. A structured questionnaire was prepared, which generates 181 participants. The questionnaire was selected for its suitability in systematically capturing consumers' perceptions and intentions. According to the findings of partial least square structural equation modeling (PLS-SEM), perceived ease of use (PEOU), perceived enjoyment (PE), and perceived trust (PT) have significant impacts on users' intentions to use conversational assistants, however, perceived usefulness (PU) does not have any significant effects. Furthermore, the relationship between PEOU and intention is significantly and negatively moderated by perceived risk (PR). By enabling stakeholders to create strategies that improve customer experience and unleash the full potential of conversational assistants in banking services, these findings help to better understand consumer behavior.

User Needs and Benefits of Mental Health Chatbots: Text-Mining Analysis of Mobile Apps Reviews

Article

Apr 2025
INT J HUM-COMPUT INT

This study investigates user needs and perceived benefits of mental health chatbots by analyzing user reviews from the AppStore and Google Play Store for three different chatbots. Text-mining analysis reveals a strong preference for social interactivity, with users frequently mentioning terms like “talking” and “human,” which suggests that users value a high degree of social and hedonic expectations from these chatbots. There is also a noticeable enthusiasm for innovation and technology, as indicated by mentions of terms such as “recent” and “newest.” Cluster analysis results further highlight the importance of psychoeducation, which generally evokes positive sentiments, while perceptions around pricing show a wider range of responses. Overall, our findings underscore the importance of social features in mental health chatbots and offer valuable insights on pricing preference. These insights are intended to support developers and mental health professionals in enhancing the effectiveness and appeal of these applications.

Investigating the Relation of Philological Sciences Teachers with AI in Education

Conference Paper

Full-text available

Jan 2024

The paper aims to present an image as accurate as possible of how teaching staff perceive artificial intelligence in the current educational context due to the profound effects that AI already has and will have on civilisation, both culturally and economically. The data analysis obtained after applying a questionnaire to philological sciences teachers in a medium-sized university in an Eastern European country highlighted that a relatively homogeneous teaching body has quite a heterogeneous approach to the AI phenomenon. As a result, there are many different ways that AI is affecting education, and they can be discussed on many different levels, including the relationships between the many stakeholders, classroom instruction, scientific research, and the personal training of educators. The benefits and risks associated with implementing AI in education are clear, and it is imperative that appropriate training programs and ethical guidelines be put in place before AI is used in classrooms.

Navigating Interaction with AI chatbots: Sociolinguistic and Pragmatic Aspects of Chatbot Use by Slovak and Hungarian Speakers

Article

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Jan 2025

Klaudia Pauliková

This study investigates the dynamics of interaction between native Slovak and Hungarian speakers (n=216) with AI chatbots from a sociolinguistic and pragmatic perspective. The research employs a mix-method questionnaire and assesses speakers' perceptions and preferences in terms of language choices, levels of formality, and tone during interactions with AI chatbots. It also draws attention to conversational and politeness strategies, as well as dealing with miscommunications and errors. The findings reveal that the choice of users' language is linked to their communicative goals and tasks, with a neutral and formal tone prevailing in their interactions with chatbots. The respondents generally consider chatbots as capable of understanding messages well and employ rephrasing and prompt simplifying most frequently to avoid miscommunication. The general level of politeness among respondents is reported important and high with politeness expressions used quite frequently. Conversely, the participants report neglecting the use of emojis and point out using politeness expressions out of habit and with the endeavor to maintain a respectful tone. The findings indicate that users primarily view interactions with chatbots as functional, placing a higher value on communication efficiency than on cultural or emotional exchanges, as well as on informal and friendly discourse. Although users generally demonstrate a high level of politeness towards chatbots, it is assumed that the use of polite expressions stems more from habitual behavior and cultural influence than from a conscious effort to enhance communication with these systems.

Enhancing instructional design learning: a comparative study of scaffolding by a 5E instructional model-informed artificial intelligence chatbot and a human teacher

Article

Apr 2025
INTERACT LEARN ENVIR

To address the limitations of general-purpose artificial intelligence (AI) tools, we developed a task-oriented AI chatbot based on the 5E (i.e. “engage”, “explore”, “explain”, “elaborate” and “evaluate”) model to scaffold students’ instructional design process. We examined the impact of integrating the 5E instructional model-informed AI chatbot on students’ learning performance and perceptions. The results indicated that the AI chatbot, when combined with human teacher scaffolding, significantly improved the students’ instructional design performance relative to receiving human teacher scaffolding only. The chatbot provided valuable suggestions on instructional design frameworks, class activities and teaching topics during the “explore” phase. In the “evaluate” phase, the chatbot offered immediate feedback on the students’ design plans and proposed alternative instructional frameworks regarding areas for improvement. However, the students expressed concerns about the chatbot’s evaluation quality, noting that it needed to be better aligned with the course assessment rubric. We recommend using AI chatbots for instructional design conceptualisation, although we emphasise the critical role of human teachers in evaluating final design work and providing timely support.

Investigating the influence of perceived humanization of service encounters on value creation of chatbot-assisted services

Article

Full-text available

Oct 2024

Purpose While prior research has examined customer acceptance of humanized chatbots, the mechanisms through which they influence customer value creation remain unclear. This study aims to investigate the emerging concept of Perceived Humanization (PH), examining how hedonic motivation, social influence and anthropomorphism influence value creation through the serial mediation of PH and trust. The moderating roles of rapport and social presence are also explored. Design/methodology/approach Based on data from an online survey involving 257 respondents, this study employs Partial Least Squares Structural Equation Modeling utilizing SmartPLS3 software. Findings Hedonic motivation leads to value creation via two routes: PH and affective trust; and PH and cognitive trust. Social influence and anthropomorphism also positively impact value creation through similar pathways. Rapport moderates the impact of social influence on PH, while social presence moderates the relationship between PH and both affective and cognitive trust. A cross-cultural analysis of China, India and New Zealand highlights varying cultural dimensions influencing PH and its effects on value creation. Practical implications For practitioners in the tourism industry, the findings highlight the strategic importance of enhancing PH in chatbot interactions. By understanding and optimizing these elements, businesses can significantly improve their customer value-creation process. Originality/value This study contributes to the service marketing literature by generating a comprehensive framework for the comprehension and application of PH. Its cross-cultural perspective provides rich insights, offering valuable information for service marketers aiming to thrive in the dynamic and competitive tourism industry.

Is fintech chatbot adoption a far-off aspiration? Establishing adoption model using ISM-MICMAC approach

Article

Full-text available

Oct 2024
QUAL QUANT

The financial services sector experiences significant effects from digitalization. A crucial factor is that financial offerings heavily rely on information. Notably, fintech chatbots enhance the exchange of information by being integrated into messaging platforms, websites, and mobile apps. This integration enables users to engage with these chatbots using written or spoken conversations. While the literature has explored different enablers that facilitate the adoption of fintech chatbots, the interplay between these enablers is currently intricate and multifaceted. Due to the rising complexity, academics and practitioners have become increasingly interested in understanding the proper hierarchy of fintech chatbots’ enablers. The SPAR-4-SLR protocol of systematic literature review is used to identify the contextual enablers of fintech chatbots, which are further finalized by integrating experts’ recommendations. In response, this study applies interpretive structural modeling (ISM) and creates a five-level hierarchical structure. The dependence and driving power of the selected key enablers were then assessed using Matrice d’ Impacts Croises- Multiplication Applique a classement (MICMAC) analysis. Our results show that human-like interaction and social influence are placed at the bottom level of the ISM hierarchy model and have the highest deriving power based on the MICMAC classification. On the other hand, pleasure and adaptability rises to the highest level and has the strongest dependence power. The findings of this study could help practitioners in the finance sector and academics in the field better understand key enablers and how they interact. This can help practitioners create better strategies for accelerating the use of fintech chatbots. This study is an early attempt to identify the important fintech chatbot enablers and rank them according to their dependence and deriving power.

Understanding Users’ Acceptance of Artificial Intelligence Applications: A Literature Review

Article

Full-text available

Aug 2024

In recent years, with the continuous expansion of artificial intelligence (AI) application forms and fields, users’ acceptance of AI applications has attracted increasing attention from scholars and business practitioners. Although extant studies have extensively explored user acceptance of different AI applications, there is still a lack of understanding of the roles played by different AI applications in human–AI interaction, which may limit the understanding of inconsistent findings about user acceptance of AI. This study addresses this issue by conducting a systematic literature review on AI acceptance research in leading journals of Information Systems and Marketing disciplines from 2020 to 2023. Based on a review of 80 papers, this study made contributions by (i) providing an overview of methodologies and theoretical frameworks utilized in AI acceptance research; (ii) summarizing the key factors, potential mechanisms, and theorization of users’ acceptance response to AI service providers and AI task substitutes, respectively; and (iii) proposing opinions on the limitations of extant research and providing guidance for future research.

Establishing Credibility in AI Chatbots: The Importance of Customization, Communication Competency and User Satisfaction

Chapter

Full-text available

Jan 2024

The study aims to investigate the effects of AI chatbot communication competencies on its credibility. The problems commonly associated with AI chatbots in communication include (i) lack of natural language understanding;(ii) limited contextual understanding; (iii) inability to handle complex queries and(iv) lack of emotional intelligence. These research questions aim to further explore and understand the effects of AI chatbot's communication capabilities on its credibility, considering factors of self-disclosure, empathy, social relaxation, interaction management, assertiveness, altercentrism, expressiveness, supportiveness, immediacy, environmental control, customization, satisfaction and credibility. The methodology involved conducting a survey among 306respondents who were China Xiaohongshu users to gather data for the study. The research findings underscore the substantial contribution of communication competency to chatbot credibility, thereby emphasizing the ongoing need for continuous improvement in communication skills. Through the enhancement of credibility, chatbots can gain user trust, satisfaction, and acceptance. This research underscores the significance of communication competency in shaping successful chatbot interactions, and it lays the groundwork for future advancements in chatbot development.

Infographics in Educational Settings: A Literature Review

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Dec 2023

Infographics are visual representations of data that utilize various graphic elements, including pie charts, bar graphs, line graphs, and histograms. Educators and designers can maximize the potential of infographics as powerful educational tools by carefully addressing challenges and capitalizing on emerging technologies. However, current education systems showcase the need for development guidelines and the best practices targeted at designing and developing infographics while exploring the major economic and social impacts of infographics on education. This study examines the concept and role of infographics in education, methodologies, trends, and obstacles. It evaluates potential economic implications and gives insights to design and development experts. The study is based on a scoping literature review methodology, uncovering the conceptual background and the role of infographics. The study emphasizes the unique functions of infographics in data visualization for educational purposes and investigates the current trends and practices in infographics creation. The key challenges associated with the use of infographics are also discussed. Furthermore, the study attempts to identify the cutting-edge frameworks for infographic creation and development while evaluating their economic implications for the role of global education. Finally, the potential recommendations for creating successful infographics while focusing on professional design and development are also covered. The guided literature review will be vital for understanding and using infographics in education.

I can feel AI failure: the impact of service failure type and failure assessment on customer recovery expectation

Article

Full-text available

Sep 2023
IND MANAGE DATA SYST

Purpose Based on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level. Design/methodology/approach Three scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level. Findings Non-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level. Originality/value The findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.

Advanced Government Chatbot Featuring Multi-Source Strategy for Effective Goal-Driven Dialogues

Conference Paper

Dec 2024

Augmenting the Shopping Experience: How Quality Factors Drives Continuance Intention in Real-Time Virtual Try-On (VTO)

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Exploring the Influence of Prompt Self-Efficacy: Accurate and Customized Information, Perceived Ease of Use, Satisfaction, and Continuance Intention to Use ChatGPT

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INT J HUM-COMPUT INT

Empathic chatbots: A double-edged sword in customer experiences

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Feb 2025
J BUS RES

The impact of new generative AI chatbots on the switch point (SP): toward an artificial emotional awareness (AEA) European Journal of Innovation Management

Article

Jan 2025
Eur J Innovat Manag

Purpose This paper aims to contribute to the discussion on integrating humans and technology in customer service within the framework of Society 5.0, which emphasizes the growing role of artificial intelligence (AI). It examines how effectively new generative AI-based chatbots can handle customer emotions and explores their impact on determining the point at which a customer–machine interaction should be transferred to a human agent to prevent customer disengagement, referred to as the Switch Point (SP). Design/methodology/approach To evaluate the capabilities of new generative AI-based chatbots in managing emotions, ChatGPT-3.5, Gemini and Copilot are tested using the Trait Emotional Intelligence Questionnaire Short-Form (TEIQue-SF). A reference framework is developed to illustrate the shift in the Switch Point (SP). Findings Using the four-intelligence framework (mechanical, analytical, intuitive and empathetic), this study demonstrates that, despite advancements in AI’s ability to address emotions in customer service, even the most advanced chatbots—such as ChatGPT, Gemini and Copilot—still fall short of replicating the empathetic capabilities of human intelligence (HI). The concept of artificial emotional awareness (AEA) is introduced to characterize the intuitive intelligence of new generative AI chatbots in understanding customer emotions and triggering the SP. A complementary rather than replacement perspective of HI and AI is proposed, highlighting the impact of generative AI on the SP. Research limitations/implications This study is exploratory in nature and requires further theoretical development and empirical validation. Practical implications The study has only an exploratory character with respect to the possible real impact of the introduction of the new generative AI-based chatbots on collaborative approaches to the integration of humans and technology in Society 5.0. Originality/value Customer Relationship Management managers can use the proposed framework as a guide to adopt a dynamic approach to HI–AI collaboration in AI-driven customer service.

Retail consumers' conundrum: An in-depth qualitative study navigating the motivations and aversion of chatbots

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J Retailing Consum Serv

Does usage scenario matter? Investigating user perceptions, attitude and support for policies towards ChatGPT

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Lower than Expected but Still Willing to Use: User Acceptance toward Current Intelligent Conversational Agents

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Who are you talking to? How chatbot identity disclosure affects service satisfaction

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ESG Activity Recognition Enhances Organizational Commitment and Service-Oriented Organizational Citizenship Behavior Among Insurance Call Center Staff

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Analyzing behavioral intentions toward Generative Artificial Intelligence: the case of ChatGPT

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Apr 2024
Univers Access Inform Soc

Generative artificial intelligence (AI) is an innovative AI technology that has garnered considerable attention worldwide. This study aimed to facilitate the development of such technologies by examining the factors affecting individuals’ intentions toward generative AI (e.g., ChatGPT). Concretely, we developed a causal model by extending the expectation confirmation model with information system success theory, privacy concerns, and perceived innovativeness. Then, we tested the model by analyzing survey-based data from 252 Korean ChatGPT users. As a result, we found that antecedent variables -information quality, system quality, privacy concerns, and perceived innovativeness- play notable roles in affecting users’ intentions to continually use and recommend generative AI ChatGPT. Overall, the current research is one of the first attempts to track the variables influencing individuals’ intentions to continually use and recommend in the context of generative AI ChatGPT.

The effect of the anthropomorphic design of chatbots on customer switching intention when the chatbot service fails: An expectation perspective

Article

Feb 2024
INT J INFORM MANAGE

Running a double-blind true social experiment with a goal oriented adaptive AI-based conversational agent in educational research

Article

Jan 2024
Int J Educ Res

What drives tourists’ continuance intention to use ChatGPT for travel services? A stimulus-organism-response perspective

Article

Feb 2024
J Retailing Consum Serv

Doanh Duong

The recent surge in AI technologies, like ChatGPT, has sparked significant interest in their potential to revolutionize various industries, with the travel and tourism sector at the forefront. AI-driven chatbots now handle a range of tasks, from processing orders to providing tailored recommendations within hospitality and tourism. However, understanding what drives tourists to adopt ChatGPT for travel services has remained limited. Drawing on the Stimulus-Organism-Response model, a sample of 606 participants recruited in the crowded tourist destinations in Vietnam using a systematic sampling approach, the findings indicate the impact of anthropomorphic stimuli (perceived warmth, communication speed, and perceived competence) on tourists’ cognitive organisms (trust in ChatGPT and attitude towards ChatGPT), which, in turn, influence their behavioral responses (satisfaction and continuance usage intentions of ChatGPT for travel services). Simultaneously, it also reveals the negative moderating effect of technology anxiety on the satisfaction-continuance usage intentions relationship. From a practical standpoint, these findings hold the potential to guide practitioners and marketers in leveraging ChatGPT’s advantages within the hospitality and tourism industry.

Chatbot interactions: How consumption values and disruptive situations influence customers' willingness to interact

Article

Full-text available

Jan 2024
INFORM SYST J

Chatbots offer customers access to personalised services and reduce costs for organisations. While some customers initially resisted interacting with chatbots, the COVID‐19 outbreak caused them to reconsider. Motivated by this observation, we explore how disruptive situations, such as the COVID‐19 outbreak, stimulate customers' willingness to interact with chatbots. Drawing on the theory of consumption values, we employed interviews to identify emotional, epistemic, functional, and social values that potentially shape willingness to interact with chatbots. Findings point to six values and suggest that disruptive situations stimulate how the values influence WTI with chatbots. Following theoretical insights that values collectively contribute to behaviour, we set up a scenario‐based study and employed a fuzzy set qualitative comparative analysis. We show that customers who experience all values are willing to interact with chatbots, and those who experience none are not, irrespective of disruptive situations. We show that disruptive situations stimulate the willingness to interact with chatbots among customers with configurations of values that would otherwise not have been sufficient. We complement the picture of relevant values for technology interaction by highlighting the epistemic value of curiosity as an important driver of willingness to interact with chatbots. In doing so, we offer a configurational perspective that explains how disruptive situations stimulate technology interaction.

Diving into the technology: a systematic literature review on strategic use of chatbots in hospitality service encounters

Article

Dec 2023

Chatbots have become widely used in hotels, restaurants, and related industries. This study presents a systematic literature review (SLR) of research papers that investigate the use of chatbots in restaurants, hotels, and related services. The Scopus and Web of Science databases are utilized to ascertain the pertinent research publications concerning the utilization of chatbots in the domains of hotels, restaurants, and tourism (N = 48) from 2019 to 2023. The review has adhered to the TCM framework and using the SPAR-4-SLR protocol. The work has identified multiple theme areas and theoretical influences, and has also outlined potential avenues for future research fronts and propositions. This review aims to provide guidance for future studies focusing on the research questions and theoretical influences related to service bots in the hospitality industry. The existing research on the utilization of chatbots in the context of restaurants and hotels is very scarce. Therefore, this systematic literature review aims to offer a thorough and all-encompassing overview of this particular domain. This study will enhance the existing knowledge base and facilitate future research on the application of chatbots in various service areas.

ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMAENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMA

Article

Full-text available

Nov 2023

Sohbet robotu yapay zeka uygulamalarından biridir. İşletmeler müşterilerine bilgi vermek, web sitesi içinde yönlendirme yapmak, sorulara anında ve hızlı bir şekilde cevap verebilmek için sohbet robotundan faydalanmaktadırlar. Çalışmanın amacı, endüstriyel pazarda satış çalışanlarının satış faaliyetlerinde sohbet robotlarını kullanımına ilişkin amaç, beklentileri ve elde edilebileceği faydaları ile algılanan engelleri ve endişeleri ortaya koymaktır. Ayrıca sohbet robotlarının müşteri deneyimine sağlayacağı katkıları belirlemektir. Bu doğrultuda 10 satış çalışanı ile derinlemesine görüşmeler yapılmıştır. Görüşmelerin analizinde içerik analizi kullanılmıştır. Çalışma sonuçlarına göre, satış çalışanlarının satış faaliyetlerinde sohbet robotlarını kullanımına ilişkin amaç, beklentileri ve elde edilebileceği faydalar; ürün, lojistik, stok bilgisi sağlaması, departmanlararası veri paylaşması, temel sorularına hızlı cevap vermesi, müşteriyi ilgili kişiye yönlendirmesi, müşteri verilerinin toplanması, rutin işleri takip ederek ziyaret planlaması, şikayet takibi yapması, müşterinin firmaya kaydolmasını kolaylaştırması, farklı dil özelliklerini kullanması, e-postaları analiz ederek önceliklendirmesi ve yanıt verebilmesidir. Satış çalışanları sohbet robotunun doğru şekilde çalışmaması, kişinin izni ve bilgisi olmadan müşteriye yanlış bilgi (randevu, fiyat, temin, stok gibi) paylaşması, müşteri ile sorun yaşaması, talepleri doğru tahmin edememesi konularında endişe duymaktadırlar. Katılımcılar sohbet robotu kullanmalarında algılanan engeller; endüstriyel pazardaki işlerin ve ürünlerin teknik, müşteri kaybetme riskinin yüksek ve maliyetli olması olarak ifade etmişlerdir. Ayrıca sohbet robotunun algılama hatası vermesinin, kullanıcı duygularını anlama zorluğunun, verilen bilginin yetersizliğinin, kullanıcıların eğitim seviyelerinin düşük olmasının kullanım oranını azaltacağını düşünmektedirler.

EmoBot: Artificial emotion generation through an emotional chatbot during general-purpose conversations

Article

Full-text available

Sep 2023
COGN SYST RES

Emotion modeling has always been intriguing to researchers, where detecting emotion is highly focused and generating emotion is much less focused to date. Therefore, in this paper, we aim to explore emotion generation, particularly for general-purpose conversations. Based on the Cognitive Appraisal Theory and focusing on audio and textual inputs, we propose a novel method to calculate informative variables to evaluate a particular emotion-generating event and six primary emotions. Incorporating such a method of artificial emotion generation, we implement an emotional chatbot, namely EmoBot. Accordingly, EmoBot analyzes continuous audio and textual inputs, calculates the informative variables to evaluate the current situation, generates appropriate emotions, and responds accordingly. An objective evaluation indicates that EmoBot could generate more accurate emotional and semantic responses than a traditional chatbot that does not consider emotion. Additionally, a subjective evaluation of EmoBot demonstrates the appreciation of users for EmoBot over a traditional chatbot that does not consider emotion.

Chatbots in Digital Marketing: Enhanced Customer Experience and Reduced Customer Service Costs

Chapter

Full-text available

Jun 2023

Farid Huseynov

Artificial intelligence software called chatbots are designed to imitate human conversation. They utilize natural language processing technology to comprehend and interpret user input and produce responses based on pre-programmed rules or machine learning algorithms. Chatbots are widely utilized in sales and customer service domains. Customers appreciate the convenience of chatbots' instant responses and ability to quickly provide needed information without human intervention. Chatbots benefit businesses by handling multiple inquiries of customers and reducing the need for additional staff, and can also be used for internal purposes such as responding to employee queries and assisting with various tasks. This chapter examines the use of chatbots in marketing, customer service, and sales, covering their classification and common types, impact on customer experience and service costs, and ethical considerations. This chapter will be useful for scholars researching chatbots and professionals looking to integrate them into their marketing and customer service strategies.

Quo Vadis 2023

Book

Full-text available

Jun 2023

Proceedings of the scientific conference QUO VADIS 2023 organized by the Faculty of Mass Media Communication UCM in Trnava.

Effects of personalization and source expertise on users’ health beliefs and usage intention toward health chatbots: Evidence from an online experiment

Article

Full-text available

Oct 2022

Objective Based on the heuristic–systematic model (HSM) and health belief model (HBM), this study aims to investigate how personalization and source expertise in responses from a health chatbot influence users’ health belief-related factors (i.e. perceived benefits, self-efficacy and privacy concerns) as well as usage intention. Methods A 2 (personalization vs. non-personalization) × 2 (source expertise vs. non-source expertise) online between-subject experiment was designed. Participants were recruited in China between April and May 2021. Data from 260 valid observations were used for the data analysis. Results Source expertise moderated the effects of personalization on health belief factors. Perceived benefits and self-efficacy mediated the relationship between personalization and usage intention when the source expertise cue was presented. However, the privacy concerns were not influenced by personalization and source expertise and did not significantly affect usage intention toward the health chatbot. Discussion This study verified that in the health chatbot context, source expertise as a heuristic cue may be a necessary condition for effects of the systematic cue (i.e. personalization), which supports the HSM's arguments. By introducing the HBM in the chatbot experiment, this study is expected to provide new insights into the acceptance of healthcare AI consulting services.

A thematic analysis of broker consultation in a TF-CBT community based learning collaborative

Article

Full-text available

Aug 2022
J Child Adolesc Trauma

Background Consultation is an important implementation strategy to increase competence, knowledge, and fidelity to evidence-based practice in community settings. However, the literature has primarily focused on consultation for clinical providers, and less is known about consultation for “broker” professionals, or those who identify and refer children to mental health services. Given their critical role in connecting youth to evidence-based treatment, investigating broker knowledge and use of evidence-based screening and referral are needed. Objective To address this gap, the current study examines the content of consultation provided to broker professionals.

“I am chatbot, your virtual mental health adviser.” What drives citizens’ satisfaction and continuance intention toward mental health chatbots during the COVID-19 pandemic? An empirical study in China

Article

Full-text available

Mar 2022

Introduction In order to address the psychological problems during the COVID-19 pandemic, mental health chatbots have been extensively used by public sectors. According to Theory of Consumption Values, this paper proposed an analytical framework to investigate the determinants behind users’ satisfaction and continuance intention toward mental health chatbots. Methods The empirical study was conducted through an online survey, facilitated by the use of questionnaire posted on the WeChat platform. Seven-point Likert scale and closed-ended questions were employed. Totally 371 valid samples were collected. The research data was tested via the partial least squares structural equation modeling. Gender, age, and income were included as control variables. Results Analysis of samples collected from 371 Chinese users suggested that personalization (functional value), enjoyment (emotional value), learning (epistemic value), and the condition of the COVID-19 pandemic (conditional value) have positive influences on user satisfaction and continuance intention, but such effects were weak. The findings also revealed that user satisfaction has weakly positive impact on continuance intention. However, voice interaction (functional value) was an insignificant predictor of user satisfaction and continuance intention. Discussion This study developed a critical perspective on the role of Theory of Consumption Values in the context of mental health chatbot usage, while Theory of Consumption Value has been increasingly employed to explain the use of AI-based public services. Thus, this research devotes to the enhancement of theoretical frameworks regarding the usage of mental health chatbots.

Understanding the user experience of customer service chatbots: An experimental study of chatbot interaction design

Article

Full-text available

Feb 2022
INT J HUM-COMPUT ST

Understanding the user experience of chatbots for customer service is essential to realize the potential of this technology. Such chatbots are typically designed for efficient and effective interactions, accentuating pragmatic quality, and there is a need to understand how to make these more pleasant and engaging, strengthening hedonic quality. One promising approach is to design for more humanlike chatbot interactions, that is, interactions resembling those of skilled customer service personnel. In a randomized experiment (n = 35) we investigated two chatbot interaction design features that may strengthen the impression of a humanlike character: (a) topic-led conversations, encouraging customer reflection, in contrast to task-led conversations, aiming for efficient goal completion, and (b) free text interaction, where users interact mainly using their own words, rather than button interaction, where users mainly interact through predefined answer alternatives. Dependent variables were participant perceptions of anthropomorphism and social presence, two key concepts related to chatbot human likeness, in addition to pragmatic quality and hedonic quality. To further explore user perceptions of the interaction designs, the study also included semi-structured interviews. Topic-led conversations were found to strengthen anthropomorphism and hedonic quality. A similar effect was not found for free text interaction, reportedly due to lack in chatbot flexibility and adaptivity. Implications for theory and practice are suggested.

The Impact of Chatbots on Customer Loyalty: A Systematic Literature Review

Article

Full-text available

Jan 2022

More and more companies have implemented chatbots on their websites to provide support to their visitors on a 24/7 basis. The new customer wants to spend less and less time and therefore expects to reach a company anytime and anywhere, regardless of time, location, and channel. This study provides insight into the influence of chatbots on customer loyalty. System quality, service quality, and information quality are crucial dimensions that a chatbot must meet to give a good customer experience. To make a chatbot more personal, companies can alter the language style. Human-like chatbots lead to greater satisfaction and trust among customers, leading to greater adoption of the chatbot. The results of this study showed that a connection between chatbots and customer loyalty is very likely. Besides, some customers suffer from the privacy paradox because of personalization. Implications of this study are discussed.

Academic and Administrative Role of Artificial Intelligence in Education

Article

Full-text available

Jan 2022

The aim of the article is to explore the academic and administrative applications of Artificial Intelligence. Teachers have the main responsibility of teaching in any educational setting. But there are various other tasks to be performed by the teachers as well. Besides academic duty, most of the teacher’s time and educational resources are dedicated to administrative works. Artificial Intelligence Applications (AIA) are not only assisting education academically and administratively but also enhance their effectiveness. AIA provides help to teachers in various types of tasks in the shape of Learning Analytics (LA), Virtual Reality (VR), Grading/Assessments (G/A), and Admissions. It minimizes the administrative tasks of a teacher to invest more in teaching and guiding students. In the current era, where there are a lot of tasks associated with the teaching profession, AIA adds a significant contribution to enhance student learning, minimize the workload of a teacher, grade/assess the students effectively and easily, and to help in a lot of other administrative tasks. The study needs to be quantitatively checked to make it generalized and acceptable.

Public Service Values and Chatbots in the Public Sector: Reconciling Designer efforts and User Expectations

Conference Paper

Full-text available

Jan 2022

See you soon again, chatbot? A design taxonomy to characterize user-chatbot relationships with different time horizons

Article

Full-text available

Oct 2021
COMPUT HUM BEHAV

Users interact with chatbots for various purposes and motivations – and for different periods of time. However, since chatbots are considered social actors and given that time is an essential component of social interactions, the question arises as to how chatbots need to be designed depending on whether they aim to help individuals achieve short-, medium- or long-term goals. Following a taxonomy development approach, we compile 22 empirically and conceptually grounded design dimensions contingent on chatbots’ temporal profiles. Based upon the classification and analysis of 120 chatbots therein, we abstract three time-dependent chatbot design archetypes: Ad-hoc Supporters, Temporary Assistants, and Persistent Companions. While the taxonomy serves as a blueprint for chatbot researchers and designers developing and evaluating chatbots in general, our archetypes also offer practitioners and academics alike a shared understanding and naming convention to study and design chatbots with different temporal profiles.

Determining Factors Affecting Acceptance of E-Learning Platforms during the COVID-19 Pandemic: Integrating Extended Technology Acceptance Model and DeLone & McLean IS Success Model

Article

Full-text available

Jul 2021

Online meeting platforms have been widely utilized during the COVID-19 pandemic due to the current shift from traditional learning. However, the acceptance of the different online meeting platforms for e-learning has been underexplored. The purpose of this study was to determine the factors for acceptance of an online learning platform among students during the COVID-19 pandemic. A total of 500 senior high school students voluntarily participated to answer constructs under the Extended Technology Acceptance Model (ETAM) and Delone and McLean IS Success Model. Several latent including user interface (UI), perceived ease of use (PEU), perceived usefulness (PU), information quality (IQ), system quality (SQ), behavioral intentions (BI), and actual use were analyzed by Structural Equation Modeling (SEM). The results indicated that PEU was found to have the greatest on actual use (AU), followed by UI and SQ towards PEU, which subsequently led to BI and AU. Finally, IQ was found to have a significant effect on PU, which led to BI and AU. The level of student acceptability considers the ease of use, user interface, system quality, information quality, leading to a positive behavioral intention for actual use. With that, it would be of best interest to consider the factors that would lead students towards accepting the platforms utilized and therefore the current education system. Moreover, this will lead to their acceptance and promote learning even with the COVID-19 pandemic. Finally, the model construct can be applied and utilized to analyze the online learning platforms in other countries.

Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot

Article

Full-text available

Dec 2021
PSYCHOL MARKET

Consumers sometimes describe their experience of interacting with artificial intelligence‐based human‐like chatbots as creepy. This study investigates the antecedents of creepiness (i.e., the chatbot's usability, privacy concerns, and user variables such as technology anxiety and the need for human interaction) and its impact on consumer loyalty. Grounded in the technology paradox, it deepens the understanding of creepiness in light of the theoretical underpinnings of the privacy paradox and privacy cynicism. Presented with the task of obtaining a car insurance quote, 430 consumers participated in a simulation involving interaction with a chatbot, followed by a questionnaire. The findings show that creepiness decreases loyalty and indirectly impacts it through trust and negative emotions. While usability reduces perceptions of creepiness, privacy concerns raised by the interaction with the chatbot increase creepiness, which is positively associated with consumer traits (i.e., technology anxiety and need for human interaction). The main contribution of the research lies in its focus on creepiness, a concept under‐researched in the marketing literature, and which can be seen from the perspective of a coping mechanism for consumers’ privacy concerns. This paper provides practical implications to orient managers in the design and implementation of chatbots, as a promising touch point to build customer loyalty.

Exploring consumers' response to text-based chatbots in e-commerce: the moderating role of task complexity and chatbot disclosure

Article

Full-text available

Jul 2021
INTERNET RES

Purpose Artificial intelligence (AI)-based chatbots have brought unprecedented business potential. This study aims to explore consumers' trust and response to a text-based chatbot in e-commerce, involving the moderating effects of task complexity and chatbot identity disclosure. Design/methodology/approach A survey method with 299 useable responses was conducted in this research. This study adopted the ordinary least squares regression to test the hypotheses. Findings First, the consumers' perception of both the empathy and friendliness of the chatbot positively impacts their trust in it. Second, task complexity negatively moderates the relationship between friendliness and consumers' trust. Third, disclosure of the text-based chatbot negatively moderates the relationship between empathy and consumers' trust, while it positively moderates the relationship between friendliness and consumers' trust. Fourth, consumers' trust in the chatbot increases their reliance on the chatbot and decreases their resistance to the chatbot in future interactions. Research limitations/implications Adopting the stimulus–organism–response (SOR) framework, this study provides important insights on consumers' perception and response to the text-based chatbot. The findings of this research also make suggestions that can increase consumers' positive responses to text-based chatbots. Originality/value Extant studies have investigated the effects of automated bots' attributes on consumers' perceptions. However, the boundary conditions of these effects are largely ignored. This research is one of the first attempts to provide a deep understanding of consumers' responses to a chatbot.

Determinants of Continuance Intention towards Banks’ Chatbot Services in Vietnam: A Necessity for Sustainable Development

Article

Full-text available

Jul 2021

To improve customer experience and achieve sustainable development, many industries, especially banking, have leveraged artificial intelligence to implement a chatbot into their customer service. By integrating DeLone and McLean’s information systems success (D&M ISS) model and the expectation confirmation model (ECM) with the factor of trust, the aim of this study was to investigate the determinants of users’ continuance intentions towards chatbot services in the context of banking in Vietnam. A total of 359 questionnaire surveys were collected from a real bank’s chatbot users and analyzed using structural equation modeling. The findings revealed that users’ continuance intentions towards the banks’ chatbot services were influenced by satisfaction, trust, and perceived usefulness, of which trust had the strongest effect. The results also indicate that information quality, system quality, service quality, and confirmation of expectations had significant effects on three drivers of continuance intention in different ways. Our study contributes to the literature by providing a more comprehensive viewpoint to understand the perceptions and reactions of chatbot users in the post-adoption stage. The results of this study also yield several key suggestions for banking service providers on how to increase their customers’ intentions to continue using chatbot services, serving as a basis for long-term and sustainable development strategies in the current digital era.

Measuring Success of Patients' Continuous Use of Mobile Health Services for Self-Management of Chronic Conditions: A Theoretical Model and Empirical Test in Patients with Hypertension (Preprint)

Article

Full-text available

Dec 2020
J MED INTERNET RES

Background Mobile health services are gradually being introduced to support patients’ self-management of chronic conditions. The success of these services is contingent upon patients’ continuous use of them. Objective This study aims to develop a model to measure the success of patients’ continuous use of mobile health services for the self-management of chronic conditions. Methods The proposed model was derived from the information systems continuance model and the information systems success model. This model contains 7 theoretical constructs: information quality, system quality, service quality, perceived usefulness, user satisfaction, perceived health status, and continuous use intention. A web-based questionnaire survey instrument was developed to test the model. The survey was conducted to collect data from 129 patients who used a mobile health app for hypertension management from 2017 to 2019. The questionnaire items were derived from validated instruments and were measured using a 5-point Likert scale. The partial least squares modelling method was used to test the theoretical model. ResultsThe model accounted for 58.5% of the variance in perceived usefulness (R2=0.585), 52.3% of the variance in user satisfaction (R2=0.523), and 41.4% of the variance in patients’ intention to make continuous use of mobile health services (R2=0.414). The continuous use intention was significantly influenced by their perceived health status (β=.195, P=.03), perceived usefulness (β=.307, P=.004), and user satisfaction (β=.254, P=.04) with the mobile health service. Information quality (β=.235, P=.005), system quality (β=.192, P=.02), and service quality (β=.494, P

The Adoption of AI Service Robots: A Comparison between Credence and Experience Service Settings

Article

Full-text available

Apr 2021
PSYCHOL MARKET

Would consumers experience the same psychological processes when adopting AI service robots in different service areas? Results of multigroup structural equation modeling (n = 517) indicate that consumers' psychological processes are not the same in different service areas. Specifically, how consumers perceive AI service robots' usefulness is shown to be a significant underlying mechanism affecting consumers' attitudes toward adopting AI service robots in a service setting with a credence attribute (e.g., a hospital), but is not significant for a service setting with an experience attribute (e.g., a café). Furthermore, regardless of the different service settings, both privacy concerns and trust toward AI technology are shown to be significant antecedents, consistent with previous literature. Our results provide empirical insights at the intersection of psychology, marketing, and AI technology on how consumers adapt to using service robots across different service areas.

Exploring the role of personality, trust, and privacy in customer experience performance during voice shopping: Evidence from SEM and fuzzy set qualitative comparative analysis

Article

Full-text available

Jan 2021
INT J INFORM MANAGE

Voice shopping is becoming increasingly popular among consumers due to the ubiquitous presence of artificial intelligence (AI)-based voice assistants in our daily lives. This study explores how personality, trust, privacy concerns, and prior experiences affect customer experience performance perceptions and the combinations of these factors that lead to high customer experience performance. Goldberg’s Big Five Factors of personality, a contextualized theory of reasoned action (TRA-privacy), and recent literature on customer experience are used to develop and propose a conceptual research model. The model was tested using survey data from 224 US-based voice shoppers. The data were analyzed using partial least squares structural equation modelling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). PLS-SEM revealed that trust and privacy concerns mediate the relationship between personality (agreeableness, emotional instability, and conscientiousness) and voice shoppers’ perceptions of customer experience performance. FsQCA reveals the combinations of these factors that lead to high perceptions of customer experience performance. This study contributes to voice shopping literature, which is a relatively understudied area of e-commerce research yet an increasingly popular shopping method.

Understanding the Determinants in the Different Government AI Adoption Stages: Evidence of Local Government Chatbots in China

Article

Full-text available

Apr 2022

With the rapid development of artificial intelligence (AI), countries are increasingly adopting AI-guided chatbots to improve service on government portals. The reduction in face-to-face services under COVID-19 pandemic will further accelerate this trend. However, the adoption and performance of the existing chatbots differ. Based on the literature on e-government adoption and innovative policy innovation diffusion, this article examines both the initial and postadoption stages of chatbot usage in China’s local governments. While the first phase employs the survival model of event history analysis to explore the factors that influence the decision to adopt chatbots in local government, the second phase analyzes the determinants of those chatbots’ performance in the postadoption stage. We find that pressure factors and readiness factors play different roles in the different adoption stages. Although pressure can encourage local governments to implement chatbots, these governments’ readiness determined how well the chatbots perform after their initial adoption. The implications and limitations of the research are also discussed.

Relationship between Online Repurchase Intention and E-Satisfaction: Quantitative Research Study Based on Young People in Western Province in Sri Lanka

Article

Full-text available

Jan 2020

Anuruddika Jayathilaka

How Do AI-driven Chatbots Impact User Experience? Examining Gratifications, Perceived Privacy Risk, Satisfaction, Loyalty, and Continued Use

Article

Full-text available

Dec 2020

Drawing on prior literature on uses and gratifications, consumer research, and technology adoption, this survey study examined how artificial intelligence (AI)-driven chatbots impact the online user experience. It collected data from 1,064 consumers who used any chatbot service from top 30 brands in the U.S. The results indicated that four typical gratifications obtained from chatbot use including utilitarian (information), hedonic (entertainment), technology (media appeal), and social (social presence) gratifications positively predicted users’ satisfaction with chatbot services of their selected brand. In contrast, perceived privacy risk associated with chatbot use reduced the level of user satisfaction. Data also demonstrated that user satisfaction positively affected both continued use of chatbot services and customer loyalty. Theoretical and practical implications of this study were discussed.

Chatbot usage intention analysis: Veterinary consultation

Article

Full-text available

Nov 2020

This study uses artificial intelligence and big data technologies to develop a chatbot prototype for veterinary consultations. To understand pet owners’ behavioral intentions to use the chatbot for veterinary consultations, we modify the technology acceptance model to develop a usage intention model for the veterinary consultation chatbot. We survey members of a pet network community by using Google Forms to collect data and partial least squares structural equation modeling for analysis. The results indicate that the perceived accuracy, perceived completeness, and perceived ease of use increased pet owners' user satisfaction of veterinary consultation chatbot; the perceived convenience and pet owners' user satisfaction increased pet owners' behavioral intention to use chatbot for veterinary consultations. This study can be used as a basis for evaluation of using intelligent technologies in pet healthcare consultation and pet disease management.

The Role of Perceived Smart Tourism Technology Experience for Tourist Satisfaction, Happiness and Revisit Intention

Article

Full-text available

Aug 2020

The rapid advancement of smart tourism technology brings new opportunities for tourism development. More travel destinations are relying on smart technology to attract more tourists to visit and enrich their travel experience. The main purpose of this study was to explore whether tourists are satisfied with their smart tourism technology experience (i.e., informativeness, accessibility, interactivity, personalization, and security). This study also investigated the impact of smart tourism technology experience on tourists’ happiness and revisit intention. This study used a structural equation method to find the relationship among smart tourism technology attributes, travel satisfaction, happiness, and revisit intention. Surveys of a total of 527 participants who traveled to Macau from Mainland China were used for the analysis. The results showed that accessibility is the most important factor affecting the smart tourism technology experience and personalization the least. Smart tourism technology experience is shown to be significantly associated with travel experience satisfaction, and travel experience satisfaction has a positive effect on both tourists’ happiness and revisit intention. Finally, tourist happiness is also shown to be positively associated with revisit intention. This study provides theoretical and practical significance for the development of smart tourism in the future.

I, Chatbot: Modeling the Determinants of Users’ Satisfaction and Continuance Intention of AI-Powered Service Agents

Article

Full-text available

Nov 2020

Chatbots are mainly text-based conversational agents that simulate conversations with users. This study aims to investigate drivers of users’ satisfaction and continuance intention toward chatbot-based customer service. We propose an analytical framework combining the expectation-confirmation model (ECM), information system success (ISS) model, TAM, and the need for interaction with a service employee (NFI-SE). Analysis of data collected from 370 actual chatbot users reveals that information quality (IQ) and service quality (SQ) positively influence consumers’ satisfaction, and that perceived enjoyment (PE), perceived usefulness (PU), and perceived ease of use (PEOU) are significant predictors of continuance intention (CI). The need for interaction with an employee moderates the effects of PEOU and PU on satisfaction. The findings also revealed that satisfaction with chatbot e-service is a strong determinant and predictor of users’ CI toward chatbots. Thus, chatbots should enhance their information and service quality to increase users’ satisfaction. The findings imply that digital technologies services, such as chatbots, could be combined with human service employees to satisfy digital users.

Virtual Assistance in Any Context - A Taxonomy of Design Elements for Domain-Specific Chatbots

Article

Full-text available

Apr 2020
BUS INFORM SYST ENG+

Several domain-specific assistants in the form of chatbots have conquered many commercial and private areas. However, there is still a limited level of systematic knowledge of the distinctive characteristics of design ele- ments for chatbots to facilitate development, adoption, implementation, and further research. To close this gap, the paper outlines a taxonomy of design elements for chatbots with 17 dimensions organized into the perspectives intel- ligence, interaction and context. The conceptually groun- ded design elements of the taxonomy are used to analyze 103 chatbots from 23 different application domains. Through a clustering-based approach, five chatbot arche- types that currently exist for domain-specific chatbots are identified. The developed taxonomy provides a structure to differentiate and categorize domain-specific chatbots according to archetypal qualities that guide practitioners when taking design decisions. Moreover, the taxonomy serves academics as a foundation for conducting further research on chatbot design while integrating scientific and practical knowledge.

“I just shared your responses”: Extending Communication Privacy Management Theory to Interactions with Conversational Agents

Article

Full-text available

Jan 2020

Conversational agents are increasingly becoming integrated into everyday technologies and can collect large amounts of data about users. As these agents mimic interpersonal interactions, we draw on communication privacy management theory to explore people's privacy expectations with conversational agents. We conducted a 3x3 factorial experiment in which we manipulated agents' social interactivity and data sharing practices to understand how these factors influence people's judgments about potential privacy violations and their evaluations of agents. Participants perceived agents that shared response data with advertisers more negatively compared to agents that shared such data with only their companies; perceptions of privacy violations did not differ between agents that shared data with their companies and agents that did not share information at all. Participants also perceived the socially interactive agent's sharing practices less negatively than those of the other agents, highlighting a potential privacy vulnerability that users are exposed to in interactions with socially interactive conversational agents.

The Effect of Information Quality on Social Networking Site (SNS)-Based Commerce: From the Perspective of Malaysian SNS Users

Article

Full-text available

Jan 2020

This study aimed to examine how information quality (IQ) attributes affect perceived usefulness and customer satisfaction of SNS-based commerce from the perspective of Malaysian SNS users. Although many studies have been conducted to identify possible IQ attributes in the context of e-commerce, only a limited number of studies have tested and examined the direct effects of the IQ attributes on perceived usefulness and customer satisfaction, particularly in the s-commerce context (i.e., SNS-based commerce). The data from Malaysia respondents were collected through an online survey, using a snowball sampling technique. The hypotheses were analysed using multiple linear regression. The results indicated the perceived usefulness was significantly affected by completeness, ease of understanding, and personalization. Customer satisfaction was significantly affected by the completeness and perceived usefulness. However, neither the accuracy nor timeliness had an effect on perceived usefulness or customer satisfaction. The findings suggest that completeness is the strongest attribute of IQ.

Qualitative Data Analysis for Applied Policy Research

Chapter

Jan 2002

New Insights into Consumers' Intention to Continue Using Chatbots in the Tourism Context

Article

Oct 2022
J Qual Assur Hospit Tourism

Several industries recognize the potential of Artificial Intelligence to complete tasks. However, there is limited research on chatbots, and a gap in the research on what factors contribute to consumers' intention to continue using them. This research aims to analyze the relationship of the TAM and ISS dimensions, continuing to use satisfaction and brand attachment as mediators, and using the need for interaction with the employee as a moderating dimension. The results indicated that the role of brand attachment increases the model's explanatory power, and the need for interaction with the employee positively favors the relationship between brand attachment and satisfaction.

Qualitative HCI Research, Going Behind the Scenes

Article

Jan 2016

Consumers’ Trust Mechanism and Trust Boundary on Humanizing Customer Service Chatbots in E-commerce

Chapter

Jun 2022
Lect Notes Comput Sci

Humanizing customer service chatbots have sparked significant interest for companies across industries. These years have witnessed some controversy on trust issues of such booming application. Previous researches have proposed some antecedents of customer service chatbots adoption (e.g., anthropomorphic features, algorithm aversion, emotional state). However, consumers’ trust mechanism and trust boundary on humanizing customer service chatbots are not clear. Hence, we pay attention to personalization and contextualization grounded on above antecedents of customer service, incorporating personal habit, task creativity and social presence to investigate trust mechanism and trust boundary. We propose a research model, in which personal habit and task creativity are captured as independent variables, trust in humanizing customer service chatbots as dependent variable, and social presence as moderating variable. Hypotheses are developed and between-subjects scenario experiments are conducted to test hypotheses. Results of analysis of covariance (ANCOVA) and moderating effect test show that there exists positive effect between personal habit and trust in humanizing customer service chatbots, giving insights on complementary and substitutive influences on the interaction of independent variables and social presence for trust boundary. This paper provides practical and theoretical implications for e-commerce practitioners to improve the collaboration performance of intelligent customer service and human customer service.KeywordsTrust mechanismTrust boundaryHumanizing customer service chatbotsPersonalizationContextualizatione-commerce

AI-powered chatbot communication with customers: Dialogic interactions, satisfaction, engagement, and customer behavior

Article

May 2022
COMPUT HUM BEHAV

The present study is grounded in social exchange theory and resource exchange theory. By exploring customers' satisfaction with chatbot services and their social media engagement, it examined the effects of responsiveness and a conversational tone in dialogic chatbot communication on customers. To test the proposed mediation model, we surveyed a representative sample of customers (N = 965) living in the U.S. After examining the validity and reliability of our measurement model, we tested the hypothesized model using structural equation modeling (SEM) procedures. All proposed hypotheses were supported, indicating the significant direct effects of (1) responsiveness and a conversational tone on customers' satisfaction with chatbot services, (2) customers' chatbot use satisfaction on social media engagement, (3) customers’ social media engagement on price premium and purchase intention, and (4) purchase intention on price premium. In addition, we examined satisfaction, social media engagement, and purchase intention as significant mediators in the proposed model. Theoretical and practical implications of the study were then discussed.

Classifying and measuring the service quality of AI chatbot in frontline service

Article

Aug 2022
J BUS RES

AI chatbots have been widely applied in the frontline to serve customers. Yet, the existing dimensions and scales of service quality can hardly fit the new AI environment. To address this gap, we define the dimensions of AI chatbot service quality (AICSQ) and develop the associated scales with a mixed-method approach. In the qualitative analysis, with the coding of the interviews from 55 global organizations in 17 countries and 47 customers, we develop new multi-level dimensions of AICSQ, including seven second-order and 18 first-order constructs. Then we follow a 10-step scale development method to establish the valid scales. The nomological test result shows that AICSQ positively influences customers’ satisfaction with, perceived value of, and intention of continuous use of AI chatbots. The innovative dimensions and scales of AI chatbot service quality provide conceptual classification and measurement instruments for the future study of chatbot service in the frontline.

The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy calculus theories

Article

Mar 2022
TECHNOL FORECAST SOC

In today's digitalized world, technologies such as the Internet of Things (IoT) and smart connected objects (SCOs) are moving to the forefront and have given rise to fundamental changes in consumers’ daily lives. During the context of COVID-19, the IoT and SCOs enabled people to better deal with the pandemic situation (e.g., control their health or use fitness indicators) (Gupta et al., 2021). The purpose of this study is to explain the acceptance and usage of SCOs and therefore extend the technology acceptance model (TAM; Davis, 1989) with other theories (i.e., uses and gratification, diffusion of innovation, privacy calculus), and thus new antecedents adapted to the SCO context. More specifically, in addition to the TAM's main variables (i.e., perceived usefulness, ease of use, intention to use, real use), we investigate the roles of concepts rarely investigated in innovation and new technology research, such as well-being, social image, privacy concerns, and innovativeness. We also study the differences in the adoption of SCOs between different user adoption stages, such as the early adopters, early majority, and late majority (Rogers, 1983). The data come from 702 respondents surveyed in a longitudinal study over three years of their acceptance and real usage. Structural equation modeling shows that the TAM variables remain relevant in the SCO context. The results show that utilitarian benefits are the main reasons leading to SCO technology acceptance, and well-being and social image lead to higher usage in the long term. However, privacy concerns are the main obstacles to the adoption of SCOs.

Predicting continuance intention to fintech chatbot

Article

Apr 2022
COMPUT HUM BEHAV

As fintech chatbots become more and more popular in online banking services, most banks have discovered their business potential. To understand why fintech chatbots can be used quickly and widely to realize commercial benefits, this research uses social response theory to detect the continuous intention mechanism behind fintech chatbots. This research includes social capital (social cues) and attitudes toward fintech chatbots to describe how social cues based on social response theory evoke users' social behaviors, which in turn may affect continuous intention. Based on the potential growth model, the growth trends and relationships of these variables were analyzed based on the longitudinal data of 455 fintech chatbot users in Taiwan in three stages over six months. The results of the survey support all hypotheses and can enable vendors to understand the mechanism of how to enhance users' continuous intention for fintech chatbots.

What drives continuance intention to use a food-ordering chatbot? An examination of trust and satisfaction

Article

Dec 2021
LIBR HI TECH

Purpose Artificial intelligence (AI) customer service chatbots are a new application service, and little is known about this type of service. This study applies service quality, trust and satisfaction to predict users' continuance intention to use a food-ordering chatbot. Design/methodology/approach The proposed model and hypotheses are tested using online questionnaire responses to collect users' perceptions of such services. One hundred and eleven responses of actual users were received. Findings Empirical results show that anthropomorphism and service quality, such as problem-solving, are the antecedents of trust and satisfaction, while satisfaction has the most significant direct effect on the users' intention. Originality/value The results provide further useful insights for service providers and chatbot developers to improve services.

Customer Brand Engagement through Chatbots on Bank Websites– Examining the Antecedents and Consequences

Article

Nov 2021
INT J HUM-COMPUT INT

Chatbots are virtual conversation agents that offer innovative features to connect with customers and thus offer a promising avenue to engage customers. Currently many private and nationalized banks are deploying chatbots for connecting and communicating with customers. This technology is expected to dominate the banking sector in the future by improving customer service. However, the success of banking chatbots will be effective when customers are satisfied with the chatbots and engage in using them. To probe in to the question, this study investigates the antecedents and consequences of customer brand engagement in using banking chatbots, with the lens of diffusion of innovation theory. The antecedents include interactivity, time convenience, compatibility, complexity, observability, and trialability. The consequences are satisfaction with the brand experience and customer brand usage intention. The theorized model has been validated with 470 Indian banking chatbot customers usable responses. The results suggest that trialability, compatibility, and interactivity positively influence customer brand engagement through a chatbot, thereby influencing satisfaction with the brand experience and customer brand usage intention. The paper presents theoretical and managerial implications which enable banks to strengthen customer engagement, satisfaction and brand usage intention through chatbots.

User interactions with chatbot interfaces vs. Menu-based interfaces: An empirical study

Article

Nov 2021
COMPUT HUM BEHAV

Rapid advances in Natural Language Processing (NLP) are transforming customer service by making it possible to create chatbot applications that can understand users’ intents and response in a human-like manner. Chatbots promise to enhance customer experiences by creating more personal customer interactions than those afforded by traditional menu-based web applications. But are chatbots always superior to more traditional user interfaces (UI)? This study seeks to understand the differences in user satisfaction with a chatbot system vis-a-vis a menu-based interface system, and identify factors that influence user satisfaction. Grounded in the self-determination theory, the research model proposed here focuses on the effect of chatbot use on perceived autonomy, perceived competence, cognitive load, performance satisfaction, and system satisfaction. An experimental study was conducted, and data were analyzed using Partial Least Square Structural Equation Modeling. The findings indicate that chatbot systems lead to a lower level of perceived autonomy and higher cognitive load, compared with menu-based interface systems, resulting in a lower degree of user satisfaction. Implications of these findings for research and practice are discussed.

Analysis of the attributes of smart tourism technologies in destination chatbots that influence tourist satisfaction

Article

Nov 2021

Chatbots are an emerging technology that is disrupting the tourism industry. Despite their implementation in companies and at destinations, there is little research that evaluates chatbots’ smart tourism technologies (STTs) attributes and their influence on tourist satisfaction. This study seeks to examine the relationship between informativeness, empathy, accessibility, interactivity and chatbot user satisfaction. The research was based on an experiment and a survey conducted on a sample of 468 potential tourists who used a chatbot during their trip. Statistical tools such as exploratory factor analysis and the hierarchical regression method were used in the data analysis. The results suggest that informativeness, empathy and interactivity of destination chatbots are the attributes that influence and predict tourist satisfaction while accessibility does not. The main contribution of this study is the analysis of the attributes of STTs applied to destination chatbots, which also provides valuable information for both tourism chatbot developers and smart destination managers who wish to adopt this technology. Highlights • The communication with a chatbot resembles the dialogues they have with human agents. • Informativeness is a predictor factor in users’ satisfaction with chatbot • The empathic ability of the chatbot is a factor that predicts user satisfaction • A high level of interactivity in a human-chabot interaction predicts user satisfaction

Application of humanization to survey chatbots: Change in chatbot perception, interaction experience, and survey data quality

Article

Sep 2021
COMPUT HUM BEHAV

The use of chatbots as an online survey tool is becoming increasingly popular owing to their convenience, particularly when face-to-face interactions are difficult. However, with longer surveys, interaction experience and data quality can decrease due to several factors, such as increased fatigue. In this study, we compared how applying humanization techniques to survey chatbots can affect survey-taking experience in three aspects: respondents' perceptions of chatbots, interaction experience, and data quality. To address our research goal, two different versions of survey chatbots were compared: a humanization applied survey chatbot (HASbot) and a baseline chatbot (baselinebot). The HASbot simultaneously incorporates four humanization techniques: use of self-introduction, addressing by name, using adaptive response speed, and echoing respondents' answers. Our experimental study with 59 middle school-aged adolescents showed that compared to the baselinebot, respondents’ perceptions of the HASbot were more positive, with higher levels of anthropomorphism and social presence. In terms of interaction experience, the respondents spent more time interacting with the HASbot and showed a higher level of satisfaction. For data quality, the HASbot outperformed the baselinebot in terms of self-disclosure; however, the HASbot also elicited a higher social desirability bias. No difference was observed in the response differentiation between the two chatbots.

Meta-analysis of the DeLone and McLean models in e-learning success: the moderating role of user type

Article

Sep 2021
ONLINE INFORM REV

Purpose Reviewing the existing literature in the field of e-learning success reveals a considerable number of studies that primarily investigate the causal relationships proposed by the DeLone and McLean (D&M) information system (IS) success model. However, the various relationships in the D&M model have found different levels of support or even contradictory results within the empirical literature. To synthesize the existing knowledge in the field of e-learning success, the authors have conducted a meta-analysis of e-learning success studies using D&M to combine the quantitative results and validate the model in this field. Furthermore, a moderator analysis involving user types was performed to examine the situation under which they may have different effects. Design/methodology/approach For this purpose, through a systematic review of the studies, 44 independent studies were selected from 29 qualified related journals. In order to analyze the quantitative results of the studies, the meta-analysis of the effect sizes of the casual relationships in the D&M model has been used. Findings The findings indicated that all relationships of the model were supported. It was also revealed that the extent of effect sizes of the examined relationships depends on the type of user. Except for one relationship (user satisfaction and net benefit), all effect sizes of employees were more than those of students and teachers. Research limitations/implications This meta-analysis reviewed the relationships found in the literature on D&M constructs in e-learning contexts. This study better explains the e-learning success factors by consolidating contradictory findings in the past researches and contributes to the existing e-learning success literature. The findings can assist educational institutions and organizations in decision-making because the findings resulting from the meta-analysis are more consistent than previous primary researches. Originality/value Despite the widespread use of the D&M model in the field of e-learning success, no study has yet consolidated the quantitative findings of these studies and the current field abounds in some controversies and inconsistent findings. This paper integrates the results of empirical studies that examined the relationships within the D&M model. The main contribution of this paper, which is the first of its kind, is to apply meta-analysis to reconcile the conflicting findings, investigate the strengths of the relationships in the D&M model and provide a consolidated view.

What impacts customer experience for B2B enterprises on using AI-enabled chatbots? Insights from Big data analytics

Article

Oct 2021
IND MARKET MANAG

Many B2B firms have widely accepted AI-based chatbots to provide human-like service interaction at different customer touchpoints in recent years. One of the objectives behind introducing this technology is to provide an enhanced, live channel Customer Experience (CX) all round the clock. Researchers have focused on delivering the CX by improvising the chatbot's internal algorithm, giving limited attention to CX theories from management literature, which leaves a gap. With the proposed paper, we have investigated the influencing factors of AI-based chatbots from the lens of CX theories for B2B firms. In this paper, a model for organizing CX has been proposed using the diffusion of innovation theory, trust commitment theory, information systems success model, and Hoffman & Novak's flow model for the computer-mediated environment and verified using the social media data. The methodology used for this study is the social media analytics-based content analysis method (sentiment analysis, hierarchical clustering, topic modeling) for data preparation, followed by lasso and ridge regression for model verification. The results suggest that CX in B2B enterprises using chatbots is influenced by these bots' overall system design, customers' ability to use technology, and customer trust towards brand and system.

The continuation and recommendation intention of artificial intelligence-based voice assistant systems (AIVAS): the influence of personal traits

Article

May 2021
INTERNET RES

Purpose Based on the post-acceptance model of information system continuance (PAMISC), this study investigates the influence of the early-stage users' personal traits (specifically personal innovativeness and technology anxiety) and ex-post instrumentality perceptions (specifically price value, hedonic motivation, compatibility and perceived security) on social diffusion of smart technologies measured by the intention to recommend artificial intelligence-based voice assistant systems (AIVAS) to others. Design/methodology/approach Survey data from 400 US AIVAS users were collected and analyzed with Statistical Product and Service Solutions (SPSS) 18.0 and the partial least square technique using advanced analysis of composites (ADANCO) 2.1. Findings AIVAS technology is presently at the early stage of market penetration (about 25% of market penetration in the USA). A survey of AIVAS technology users reveals that personal innovativeness is directly and indirectly (through confirmation and continuance) associated with a stronger intention to recommend the use of the device to others. Confirmation is associated with all four ex-post instrumentality perceptions (hedonic motivation, compatibility, price value and perceived security). Among the four, however, only hedonic motivation and compatibility are significant predictors of satisfaction, which lead to use continuance and, eventually, intention to recommend. Finally, technology anxiety is found to be indirectly (but not directly) associated with a lower intention to recommend. Originality/value This is the first study conducted on the early-stage AIVAS users that evaluates the influence of both personal traits and ex-post instrumentality perceptions on users' intention for continuance and recommendation to others.

Resistance to facial recognition payment in China: The influence of privacy-related factors

Article

Jun 2021
TELECOMMUN POLICY

As mobile payment technology is at a nascent stage, the use of facial recognition payment (FRP) services is gradually penetrating the lives of Chinese people. Although the FRP system may have advantages over other payment technologies, a civil lawsuit over refusing to submit facial information and a series of illegal activities related to selling facial information have raised the public's privacy concerns, which might further engender Chinese users' resistance towards FRP. Based on privacy calculus theory and innovation resistance theory, this study builds a research model of FRP and examines it by using a cross-sectional study with 1200 Chinese users. The findings demonstrate that the perceived effectiveness of privacy policy has significant relationships with privacy control, perceived privacy risk, perceived benefits, and resistance. Both privacy control and perceived privacy risk are significantly related to privacy concerns. There is also a significant relationship between the perceived privacy risk and resistance to FRP. Meanwhile, privacy concerns positively affect user resistance, while perceived benefits negatively affect user resistance. In contrast to previous research, the perceived privacy risk has a positive impact on the perceived benefits. This study offers cutting-edge contributions to both academia and industry.

Understanding information systems success: a hybrid view

Article

Mar 2021

The information systems (IS) success model, introduced in 1992, provided IS research with a comprehensive set of dependent variables for project success. While the model addresses both process and variance considerations, the latter has dominated the research. Concurrently, the benefits of hybrid theories have been discussed in the literature, and there have been calls for an integrated view of IS success that includes the process perspective. We build on this momentum by presenting a hybrid model based on a longitudinal case study of the development and implementation of a patient-flow decision-support system at a large not-for-profit hospital. Our model remains true to the DeLone and McLean framing but elaborates on the process elements. The hybrid model expands our ability to analyse multiple dimensions of IS success and integrates diverse research findings into the IS success model, providing a revised version for future research to extend.

‘Okay google, what about my privacy?’: User's privacy perceptions and acceptance of voice based digital assistants

Article

Jul 2021
COMPUT HUM BEHAV

Conversational Artificial Intelligence (AI) backed Alexa, Siri and Google Assistants are examples of Voice-based digital assistants (VBDA) that are ubiquitously occupying our living spaces. While they gather an enormous amount of personal information to provide bespoke user experience, they also evoke serious privacy concerns regarding the collection, use and storage of personal data of the consumers. The objective of this research is to examine the perception of the consumers towards the privacy concerns and in turn its influence on the adoption of VBDA. We extend the celebrated UTAUT2 model with perceived privacy concerns, perceived privacy risk and perceived trust. With the assistance of survey data collected from tech-savvy respondents, we show that trust in technology and the service provider plays an important role in the adoption of VBDA. In addition, we notice that consumers showcase a trade-off between privacy risks and benefits associated with VBDA while adopting the VBDA such technologies, reiterating their calculus behaviour. Contrary to the extant literature, our results indicate that consumers' perceived privacy risk does not influence adoption intention directly. It is mediated through perceived privacy concerns and consumers’ trust. Then, we propose theoretical and managerial implications to conclude the paper.

“In A.I. We Trust?” The Effects of Parasocial Interaction and Technopian versus Luddite Ideological Views on Chatbot-Based Customer Relationship Management in the Emerging “Feeling Economy”

Article

Feb 2021
COMPUT HUM BEHAV

Despite the hype surrounding Artificial Intelligence (AI), the potential of AI in customer relationship management (CRM) remains underexplored in academia. A between-subjects experiment examined the effects of the type of relationship (virtual assistantship versus virtual friendship) consumers build with AI-enabled chatbots on brand personality perception, parasocial interaction (PSI), and CRM. The main effects of the relationship type on brand personality perception appeared for competent brand personality, but not for sincere brand personality. The consumer-chatbot relationship type had effects on CRM-related outcomes (behavioral intention, satisfaction, and trust) through competent brand personality. Consumers who interacted with a friend chatbot experienced stronger PSI with the chatbot, and the relationship type had an influence on brand personality perception through PSI. This mediating effect of PSI was observed for both brand personalities - competence and sincerity. The moderating role of ideological views (technopians versus luddites) in explaining the effect of the relationship type on brand personality perception was detected for sincere brand personality. AI designers and marketers need to develop AI user interface (UI) and user experience (UX) along with marketing strategies that not only can appeal to technopians ready to adopt innovative AI customer representatives but also can ultimately help alleviate luddites’ AI anxiety in the emerging “feeling economy” envisioned by Rust and Huang.

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

Article

Jan 2021

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.

Service transformation under industry 4.0: Investigating acceptance of facial recognition payment through an extended technology acceptance model

Article

Jan 2021
Tech Soc

Technological development has drastically changed customers' daily lives by offering them new ways to shop. It also creates more opportunities for business to achieve sustainable success; however, both scholars and managers are still having relative difficulty in fully grasping customer behavior in terms of technology acceptance during the Industry 4.0. This study aims to investigate the possible factors that drive Chinese customers' willingness to utilize facial recognition payment. The findings showed that factors such as perceived enjoyment, facilitating conditions, personal innovativeness, coupon availability, perceived ease of use (PEOU), perceived usefulness (PU), and users' attitude are main drivers of customers' decisions to use facial recognition payment. Also, we found that gender differences exist in the adoption of facial recognition payment. Facilitating conditions have stronger effects on men's attitude towards usage, while coupon availability shapes female users' perception of usefulness more powerfully. By testing the extended technology acceptance model (TAM), this study seeks to gain more insight into technological change within society. Overall, investigation of the drivers of customer intention to use facial recognition payment, and exploration of their internal relationships will fulfil theoretical requirements and lead to a better understanding of customers' technology acceptance behavior, which in turn will provide greater theoretical and practical guidance for scholars and managers.

When it comes to Satisfaction … It depends: An empirical examination of social commerce users

Article

May 2020
COMPUT HUM BEHAV

Although reports on the success of social commerce indicate an astronomical growth in the next decade, understanding the complexities of the antecedents of its continuous use by consumers is limited. This study attempts to bridge this gap by using a mature IS continuance model in the social commerce context. The study also significantly extends this continuance model by theorizing and testing non-linear effects. The IS continuance model argues that all the links among confirmation, perceived usefulness, satisfaction, and continuance in the model are positive and linear. However, there is a strong theoretical basis to suggest that some relationships in the model are complex and non-linear, especially the antecedents and consequences of satisfaction. Perceived usefulness is modeled as a second order construct of social, hedonic, and utility benefits to more richly account for contexts relevant to making continuous use decisions for social commerce. Data from 531 current social commerce users provide support to our assertions. The results revealed quadratic relationships between perceived usefulness and satisfaction and between satisfaction and continuance use intentions. Perceived usefulness has a positive relationship with satisfaction for females and experienced social commerce users but an inverse-U relationship for males and inexperienced users. Satisfaction in turn has a positive relationship with continuance use intentions for females but an inverse-U relationship for males.

Privacy Concerns in Chatbot Interactions

Chapter

Jan 2020
Lect Notes Comput Sci

Chatbots are increasingly used in a commercial context to make product- or service-related recommendations. By doing so, they collect personal information of the user, similar to other online services. While privacy concerns in an online (website-) context are widely studied, research in the context of chatbot-interaction is lacking. This study investigates the extent to which chatbots with human-like cues influence perceptions of anthropomorphism (i.e., attribution of human-like characteristics), privacy concerns, and consequently, information disclosure, attitudes and recommendation adherence. Findings show that a human-like chatbot leads to more information disclosure, and recommendation adherence mediated by higher perceived anthropomorphism and subsequently, lower privacy concerns in comparison to a machine-like chatbot. This result does not hold in comparison to a website; human-like chatbot and website were perceived as equally high in anthropomorphism. The results show the importance of both mediating concepts in regards to attitudinal and behavioral outcomes when interacting with chatbots.

Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases

Article

Sep 2019

Examining empathy and responsiveness in a high-service context

Article

Aug 2019
Int J Retail Distrib Manag

Purpose The delivery of high-quality service is critical for the success, or otherwise, of many retailers. However, despite calls to examine the efficacy of the dimensions of quality in different service contexts, it is still largely unknown how dimensions such as empathy and responsiveness interact to determine consumers’ perceptions of service quality. Recent research also suggests that loyalty strategies may not be equally effective across all services contexts. The purpose of this paper is, therefore, to contribute to the service quality literature by providing a better understanding of how marketing strategy is effectively operationalised into improved services and consumer loyalty in physical stores. Design/methodology/approach Consumers from ten stores of one pharmacy retailer were surveyed. The retailer provides high-service levels at present and is examining ways of how to deliver a better quality service to its prescription and non-prescription account holding consumers. By examining consumer loyalties in high-services contexts in pharmacy retailing, the authors also propose how retailers in other sectors can learn to operationalise services quality into increased loyalties. Findings The findings of this research demonstrate that empathy, rather than responsiveness, is more important in a high service delivery context such as pharmacy retailing. Non-prescription account holding and non-store loyal consumers also do not perceive that high service responsiveness is compromised by offering of a highly empathetic (and possibly more time consuming) service by the retailer. Originality/value These findings present specific implications for retailers in the development of consumer loyalty in a high-service context. Moreover, the findings of this research also illustrate how retailers can more effectively target their investments in service design to enhance service quality and consumer loyalty.

Can chatbots satisfy me? A mixed-method comparative study of satisfaction with task-oriented chatbots in mainland China and Hong Kong

Abstract

No full-text available

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