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Article
Publication date: 10 September 2020

Rajasshrie Pillai and Brijesh Sivathanu

This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in…

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Abstract

Purpose

This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.

Design/methodology/approach

To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.

Findings

As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.

Practical implications

This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.

Originality/value

This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.

Details

International Journal of Contemporary Hospitality Management, vol. 32 no. 10
Type: Research Article
ISSN: 0959-6119

Keywords

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Article
Publication date: 13 August 2021

Davide Calvaresi, Ahmed Ibrahim, Jean-Paul Calbimonte, Emmanuel Fragniere, Roland Schegg and Michael Ignaz Schumacher

The tourism and hospitality sectors are experiencing radical innovation boosted by the advancements in Information and Communication Technologies. Increasingly…

Abstract

Purpose

The tourism and hospitality sectors are experiencing radical innovation boosted by the advancements in Information and Communication Technologies. Increasingly sophisticated chatbots are introducing novel approaches, re-shaping the dynamics among tourists and service providers, and fostering a remarkable behavioral change in the overall sector. Therefore, the objective of this paper is two-folded: (1) to highlight the academic and industrial standing points with respect to the current chatbots designed/deployed in the tourism sector and (2) to develop a proof-of-concept embodying the most prominent opportunities in the tourism sector.

Design/methodology/approach

This work elaborates on the outcomes of a Systematic Literature Review (SLR) and a Focus Group (FG) composed of experts from the tourism industry. Moreover, it presents a proof-of-concept relying on the outcomes obtained from both SLR and FG. Eventually, the proof-of-concept has been tested with experts and practitioners of the tourism sector.

Findings

Among the findings elicited by this paper, we can mention the quick evolution of chatbot-based solutions, the need for continuous investments, upskilling, system innovation to tackle the eTourism challenges and the shift toward new dimensions (i.e. tourist-to-tourist-to-chatbot and personalized multi-stakeholder systems). In particular, we focus on the need for chatbot-based activity and thematic aggregation for next-generation tourists and service providers.

Originality/value

Both academic- and industrial-centered findings have been structured and discussed to foster the practitioners' future research. Moreover, the proof-of-concept presented in the paper is the first of its kind, which raised considerable interest from both technical and business-planning perspectives.

Details

Journal of Tourism Futures, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2055-5911

Keywords

Content available
Article
Publication date: 12 July 2021

Xusen Cheng, Ying Bao, Alex Zarifis, Wankun Gong and Jian Mou

Artificial intelligence (AI)-based chatbots have brought unprecedented business potential. This study aims to explore consumers' trust and response to a text-based chatbot

Abstract

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.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

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Book part
Publication date: 11 June 2021

Rakibul Hasan, Park Thaichon and Scott Weaven

The main objective of this chapter is broadening the understanding of anthropomorphic artificial intelligence (AI) (e.g. avatars, humanoid robots, chatbots) in both…

Abstract

The main objective of this chapter is broadening the understanding of anthropomorphic artificial intelligence (AI) (e.g. avatars, humanoid robots, chatbots) in both physical and digital environments. The chapter strives to demonstrate how organisations can curate relationship marketing and enhance customer experience by employing anthropomorphic AI. To achieve this, the chapter extends existing understanding in three ways. First, it explains the interconnectivity between relationship marketing and customer experience. Second, it presents anthropomorphic AI along with its different characteristics and technologies. Third, it offers some real-life uses cases and examples of such AI drawing from practical insights into five selected industries. Overall, the chapter provides some food of thoughts concerning the successful application and deployment of anthropomorphic AI in marketing practices.

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Article
Publication date: 4 August 2021

Jano Jiménez-Barreto, Natalia Rubio and Sebastian Molinillo

Drawing on the self-determination theory, the assemblage theory and customer experience literature, this paper aims to develop a framework to understand motivational…

Abstract

Purpose

Drawing on the self-determination theory, the assemblage theory and customer experience literature, this paper aims to develop a framework to understand motivational customer experiences with chatbots.

Design/methodology/approach

This paper uses a multimethod approach to examine the interaction between individuals and airlines’ chatbots. Three components of self-determined interaction with the chatbot (competence, autonomy and relatedness) and five components of the customer–chatbot experience (sensory, intellectual, affective, behavioral and social) are analyzed qualitatively and quantitatively.

Findings

The findings confirm the direct influence of self-determined interaction on customer experience and the direct effects of these two constructs on participants’ attitudes toward and satisfaction with the chatbot. The model also supports the mediating roles of customer experience and attitude toward the chatbot.

Practical implications

This paper offers managers a broad understanding of individuals’ interactions with chatbots through three elements: motivation to use chatbots, experiential responses and individuals’ valuation of whether the interactions have amplified (or limited) the outcomes obtained from the experience.

Originality/value

This paper contributes to the hospitality and tourism literature with a hybrid approach that reflects on current theoretical developments regarding human- and interaction-centric interpretations of customer experience with chatbots.

Details

International Journal of Contemporary Hospitality Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-6119

Keywords

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Article
Publication date: 3 August 2021

Chang Hwa Baek, Seong-Young Kim, Sung Uk Lim and Jie Xiong

This paper aims to develop a quality evaluation model for artificial intelligence (AI)-based products/services that is applicable to startups utilizing AI technology…

Abstract

Purpose

This paper aims to develop a quality evaluation model for artificial intelligence (AI)-based products/services that is applicable to startups utilizing AI technology. Although AI-based service has risen dramatically and replaced many service offerings, in reality, startups are rarely to develop and evaluate AI services. The features of AI service are fundamentally different from the properties of existing services and have a great influence on the customer's service selection.

Design/methodology/approach

This paper reviews startups' development process, existing quality evaluation models and characteristics of services utilizing AI technology, and develops a quality evaluation model for AI-based services. A detailed analysis of a survey (application of the model) on customer satisfaction for AI speakers is provided.

Findings

This paper provides seven key features and 24 evaluation items for evaluating AI-based services.

Originality/value

This paper contributes to the growing need for methodologies that reflect the new era of AI-based products/services in quality evaluation research.

Details

International Journal of Entrepreneurial Behavior & Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2554

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Article
Publication date: 17 August 2021

Sut Ieng Lei, Haili Shen and Shun Ye

Chatbot users’ communication experience with disembodied conversational agents was compared with instant messaging (IM) users’ communication experience with human…

Abstract

Purpose

Chatbot users’ communication experience with disembodied conversational agents was compared with instant messaging (IM) users’ communication experience with human conversational agents. The purpose of this paper is to identify what affects users’ intention to reuse and whether they perceive any difference between the two.

Design/methodology/approach

A conceptual model was developed based on computer-mediated communication (CMC) and interpersonal communication theories. Data were collected online from four different continents (North America, Europe, Asia and Australia). Partial least squares structural equation modeling was applied to examine the research model.

Findings

The findings mainly reveal that media richness and social presence positively influence trust and reuse intention through task attraction and social attraction; IM users reported significantly higher scores in terms of communication experience, perceived attractiveness of the conversational agent, and trust than chatbot users; users’ trust in the conversational agents is mainly determined by perceived task attraction.

Research limitations/implications

Customers’ evaluation of the communication environment is positively related to their perceived competence of the conversational agent which ultimately affect their intention to reuse chatbot/IM. The findings reveal determinants of chatbot/IM adoption which have rarely been mentioned by previous work.

Practical implications

Practitioners should note that consumers in general still prefer to interact with human conversational agents. Practitioners should contemplate how to combine chatbot and human resources effectively to deliver the best customer service.

Originality/value

This study goes beyond the Computer as Social Actor paradigm and Technology Acceptance Model to understand chatbot and IM adoption. It is among one of the first studies that compare chatbot and IM use experience in the tourism and hospitality literature.

Details

International Journal of Contemporary Hospitality Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-6119

Keywords

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Article
Publication date: 1 June 2018

Mikko Riikkinen, Hannu Saarijärvi, Peter Sarlin and Ilkka Lähteenmäki

Recent technological and digital developments have opened new avenues for customer data utilization in insurance services. One form of this data transformation is…

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5699

Abstract

Purpose

Recent technological and digital developments have opened new avenues for customer data utilization in insurance services. One form of this data transformation is automated chatbots that provide convenient access to data leveraged through a discussion-like interface. The purpose of this paper is to uncover how insurance chatbots support customers’ value creation.

Design/methodology/approach

Three complementary theoretical perspectives – artificial intelligence, service logic, and reverse use of customer data – are briefly discussed and integrated into a conceptual framework. The suggested framework is further shown through illustrative case examples that characterize different ways of supporting customers’ value creation.

Findings

Chatbots represent a new type of interaction through which companies can influence customers’ value creation by providing them with additional resources. Based on the proposed conceptual framework and the illustrative case examples, four metaphors are identified that characterize how insurance chatbots can support customers’ value creation.

Research limitations/implications

The study is conceptual in nature, and the case examples are used for illustrative purposes. No representative data from those users who will eventually determine whether chatbots are of value was used.

Practical implications

Using the suggested framework, which is aligned with provider service logic, insurance companies can consider what kind of a role they wish to play in customers’ value-creating processes.

Originality/value

Automated chatbots provide convenient access to data leveraged through a discussion-like interface. This study is among the earliest to address their value-creating potential in insurance.

Details

International Journal of Bank Marketing, vol. 36 no. 6
Type: Research Article
ISSN: 0265-2323

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Article
Publication date: 8 October 2021

Abhishek Behl, Brinda Sampat and Sahil Raj

Gig workers form the backbone of any crowdsourcing platform where they showcase their talent and choose a job of their choice and freedom. The study explores the role of…

Abstract

Purpose

Gig workers form the backbone of any crowdsourcing platform where they showcase their talent and choose a job of their choice and freedom. The study explores the role of information quality (IQ) and social-mediated dialogue (SMD) in evaluating gig worker engagement and productivity on crowdsourcing platforms. The authors also propose to understand how gig worker productivity could be improved under the moderating effect of game elements.

Design/methodology/approach

A conceptual model was developed and empirically tested by integrating media richness theory and dialogic public relation theory. Data were collected from gig workers that are involved in crowdsourcing activities for the past three years. An overall sample of 346 gig workers contributing to at least one of the crowdsourcing platforms was collected. The authors tested the hypotheses using Warp PLS 7.0. Warp PLS 7.0 uses partial least square (PLS) structured equation modeling (SEM) and has been used widely to test path analytical models.

Findings

Results reveal that the information quality plays an essential role in the SMD, thereby fostering gig workers' productivity and engagement, which could be improved in the presence of game elements due to their nature of supporting rewards. However, engagement in the platform leading to improved productivity was not supported.

Practical implications

The study lays practical foundations for crowdsourcing platforms as it sets the importance of both IQ and dialogic communication channels. The two-way communication between gig workers and the platforms via accurate, timely, valuable and reliable information forms the key to the task's success. The introduction of the right game element will help to achieve better engagement and productivity.

Originality/value

This study also offers a new dimension to media richness theory and dialogic public relation theory in crowdsourcing platforms. The results would help platform designers and gig employers understand gig workers' quality and performance in a platform economy. The study uniquely positions itself in the area of crowdsourcing platforms by using game elements.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

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Article
Publication date: 19 October 2020

Tak Yee Cheung, Zengyu Ye and Dickson K.W. Chiu

People with visual impairment comprise the second high disability population in Hong Kong, but only two existing information centers provide information services for…

Abstract

Purpose

People with visual impairment comprise the second high disability population in Hong Kong, but only two existing information centers provide information services for visually impaired people, which is inadequate. Therefore, this study aims to provide a more in-depth understanding of the information services for visually impaired people in Hong Kong.

Design/methodology/approach

People with visual impairment comprise the second high disability population in Hong Kong, but only two existing information centers provide information services for visually impaired people, which is inadequate. Therefore, this study aims to provide a more in-depth understanding of the information services for visually impaired people in Hong Kong.

Findings

IAC's main problems include limited collection, inconsistent multiple digital platforms for user access, limited service hours and limited promotion. Some technological suggestions were proposed, which include: expanding its electronic and special collections, establishing a one-stop digital platform, AI-based chatbot for automated caring chats and reference services, and extending its social network marketing.

Originality/value

Scant studies focus on the information services and management of special libraries for visually impaired people, especially in East Asia. On the other hand, there are limited case studies analyzing libraries with value-chain analysis.

Details

Library Hi Tech, vol. 39 no. 2
Type: Research Article
ISSN: 0737-8831

Keywords

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