Examining the Customer Experience of Using Banking Chatbots and Its Impact on Brand Love: The Moderating Role of Perceived Risk

Trivedi, Jay P.

doi:10.1080/15332861.2019.1567188

Cited by 141 publications

(104 citation statements)

References 37 publications

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“…Kim et al, 2011). The effects of the communication style applied in human-chatbot interactions in terms of social outcomes constitute a pivotal aspect, especially if we consider that chatbots assume the role of ambassadors for the brand and the company (Trivedi, 2019). In line with this, the interactions are an important element that companies need to carefully design, especially when it comes to the communicative strategy they adopt in their digital touchpoints.…”

Section: Chatbot Interaction Style and Social Outcomes (Social Presenmentioning

confidence: 99%

“It’s on its way”: Chatbots applied for online food delivery services, social or task-oriented interaction style?

Cicco

Silva

Alparone

2020

Journal of Foodservice Business Research

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Research has yet to explore the spread of chatbots into the foodservice delivery sector and its impact on the customer's experience, especially in a moment when the Internet seems to be the tool to meet needs associated with being physically apart. In order to fill this gap, the present study addresses the implications that chatbots' interaction styles have for younger consumers using this channel for conversational online food delivery (OFD) services. Specifically, this study provides theoretical and practical insights into whether the conversational design of chatbots can influence social, affective, and behavioral intent outcomes. The study adopts an experimental design to investigate the effects of a social-versus task-oriented interaction style chatbot on the level of social presence and trust (social outcomes), perceived enjoyment (affective outcome), and intention to use the conversational OFD service in the future (behavioral intent outcome). Findings from a sample of 171 participants show that the interaction with the chatbot set up with a social-oriented interaction style increased users' perception of social presence and perceived enjoyment, while it did not have any direct and significant effect on trust and intention to use. The study further supports the role of social presence, trust, and perceived enjoyment as mediators between the chatbot's interaction style and the intention to use the conversational OFD service.

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Section: Chatbot Interaction Style and Social Outcomes (Social Presenmentioning

confidence: 99%

“It’s on its way”: Chatbots applied for online food delivery services, social or task-oriented interaction style?

Cicco

Silva

Alparone

2020

Journal of Foodservice Business Research

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“…TAM explained acceptance and usages of technology-enabled innovations ( [10], [11], and [12]). TAM was extended and modified for different technology-related adoptions as the choice to utilize a technology depended on the functionality of technology and the characteristics of the user interface [13]. Research mentions that there is a relationship between the risk factor and technology usage.…”

Section: Literature Reviewmentioning

confidence: 99%

Artificial Intelligence in Financial Services: Customer Chatbot Advisor Adoption

Patil¹,

Kulkarni²

2019

IJITEE

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The growing sophistication technology has helped us exchange Information at our fingertips, eliminating the need for human support.” A platform designed to understand, learn and converse like a human and answer ad-hoc queries in real time is commonly referred to as a Chabot”. Chabot advisor is Artificial intelligence (AI) computer program that impersonates human communication in its natural format including text or spoken language using a technique such as NLP, image processing or video processing along with the end task completion as instructed by the user [1]. The purpose of the paper was to examine what are the drivers for Chabot advisor services adoption (CBA), focusing on financial services. This study presents the explanatory Chabot advisor services factors by extending the Technology Acceptance Model (TAM). The construct in the research are like perceived privacy, perceived security, enjoyment and social influence. This empirical study was conducted in Pune city in India by collecting primary data from 310 online financial services customers. Data collected was analyzed using structural equation modeling using PLSSEM.The outcome of this study is vital to financial companies like banks, policymakers, technology services adoption literature and provide customer-centric financial services.

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“…They can engage the customer as soon as she lands on the website by sending a welcome message, it can suggest products based on specific user needs, respond to the most common customer queries in a structured way and record customer satisfaction with suggestions and complaints [20]. Especially information quality, system quality and service quality of chatbots have a significant positive effect on customer experience, but these effects are negatively moderated by perceived risk [14]. CAs have the potential to allow customer service agents to provide a better customer service experience by reducing their wait time and preserving their insights from past experiences that can be leveraged in future applications [21].…”

Section: Conversational Agentsmentioning

confidence: 99%

“…While we know that CAs can provide an engaging and interactive customer experience [13,14] and therefore improve customer satisfaction, we know little about the effects on the human workforce. This knowledge is crucial to better prepare human employees for a possible change in their work practices and processes.…”

Section: Introductionmentioning

confidence: 99%

Conversational Agents - Exploring Generative Mechanisms and Second-hand Effects of Actualized Technology Affordances

Waizenegger¹,

Seeber²,

Dawson³

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Many organisations jumped on the bandwagon and implemented conversational agents (CAs) as a new communication channel. Customers benefit from shorter resolution times, ubiquitous availability, and consistent and compliant responses. However, despite the hype around CAs and the various benefits for customers, we know little about the effects of external facing CAs on the human workforce. This is crucial to better manage the possible changes in the work organisation. Adopting a critical realist stance and using the lens of technology affordances we explore a) why users increasingly actualize CA affordances and b) the first and second-hand effects of affordance actualisation on customers and human employees. We conducted semi-structured interviews with 18 experts in the field and introduce the term affordance effects pairs describing the relationships between the first and second-hand effects. We further explain which generative mechanisms lead to an increasing actualization of affordances and the associated effects.

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Examining the Customer Experience of Using Banking Chatbots and Its Impact on Brand Love: The Moderating Role of Perceived Risk

Cited by 141 publications

References 37 publications

“It’s on its way”: Chatbots applied for online food delivery services, social or task-oriented interaction style?

“It’s on its way”: Chatbots applied for online food delivery services, social or task-oriented interaction style?

Artificial Intelligence in Financial Services: Customer Chatbot Advisor Adoption

Conversational Agents - Exploring Generative Mechanisms and Second-hand Effects of Actualized Technology Affordances

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