Using chatbots in e-retailing: how to mitigate perceived risk and enhance the flow experience

Purpose: Chatbots represent an undeniable player between online retailers and customers as they boost operational efficiency and bring cost savings to businesses while offering convenience for customers in terms of timing and immediacy. However, as chatbots represent a new-born online touchpoint in retailing, especially when it comes to online pre-purchase and purchase experience, this study examines whether and how effort expectation, facilitating condition, performance expectancy, social influence, trust, perceived risk and flow affect consumers' intention to use chatbots for online shopping. The purpose of this paper is to address this issue. Design/methodology/approach: A total of 226 respondents participated in an online survey. Participants were asked to try a new online service and interact with a chatbot designed using Chatfuel, a platform within the Facebook Messenger setting. Structural equation modelling was used to test the proposed research model regarding the intention to use chatbots. Findings: This study discusses the importance of offering useful and trustworthy conversational agents for online shopping and argues and explains the insignificant paths amongst other studied factors and intention to use chatbots concluding with the need to explore more drivers for such contemporary technologies. Moreover, the findings indicate that trust turns out to be an important predictor of behavioural intention towards chatbots, in addition to its role in mitigating perceived risk and enhancing flow experience. Originality/value: Given the lack of empirical evidence related to chatbots applied for business purposes, this paper fills a gap in this research field and provides a deeper understanding of what leverages consumers' intention to use chatbots for online shopping.Chatbots, E-Retailing, Flow, Social Influence, Trust, Perceived Riskinfo:eu-repo/semantics/acceptedVersio

Assertion and Testimony

[The version of this paper published by Oxford online in 2019 was not copy-edited and has some sense-obscuring typos. I have posted a corrected (but not the final published) version on this site. The version published in print in 2020 has these corrections.] Which is more fundamental, assertion or testimony? Should we understand assertion as basic, treating testimony as what you get when you add an interpersonal addressee? Or should we understand testimony as basic, treating mere assertion -- assertion without testimony -- as what you get when you subtract that interpersonal relation? In this chapter, I’ll argue for the subtractive approach and for the more general thesis that its treatment of the interpersonal element in assertion makes understanding that interpersonal element the key to understanding how assertion expresses belief. My theory of belief-expression in assertion treats it as internalizing the transmission of belief in testimony. How we understand that internalizing move depends on how we conceptualize the interpersonal element in testimony. Since what I’ll call the Command Model does not give us the conceptual resources to make this move, we should adopt an alternative that I’ll call the Custodial Model, on which a testifier aims not to convince her addressee but to reason with him – to give him reasons to believe what she tells him grounded in her trustworthiness in thus attempting to influence him. The subtractive approach to assertion thus rests on a key distinction between the aims of reasoning and persuasion

Words by convention

Existing metasemantic projects presuppose that word- (or sentence-) types are part of the non-semantic base. We propose a new strategy: an endogenous account of word types, that is, one where word types are fixed as part of the metasemantics. On this view, it is the conventions of truthfulness and trust that ground not only the meaning of the words (meaning by convention) but also what the word type is of each particular token utterance (words by convention). The same treatment extends to identifying the populations through which the conventions prevail. We consider whether this proposal leads to new underdetermination challenges for metasemantics, and make a case that it does not

Summary Report of The First International Competition on Computational Models of Argumentation

Computational models of argumentation are an active research discipline within Artificial Intelligence that has grown since the beginning of the 1990s (Dung 1995). While still a young field when compared to areas such as SAT solving and Logic Programming, the argumentation community is very active, with a conference series (COMMA, which began in 2006) and a variety of workshops and special issues of journals. Argumentation has also worked its way into a variety of applications. For example, Williams et al. (2015) described how argumentation techniques are used for recommending cancer treatments, while Toniolo et al. (2015) detail how argumentation-based techniques can support critical thinking and collaborative scientific inquiry or intelligence analysis. Many of the problems that argumentation deals with are computationally difficult, and applications utilising argumentation therefore require efficient solvers. To encourage this line of research, we organised the First International Competition on Computational Models of Argumentation (ICCMA), with the intention of assessing and promoting state of the art solvers for abstract argumentation problems, and to identify families of challenging benchmarks for such solvers. The objective of ICCMA’15 is to allow researchers to compare the performance of different solvers systematically on common benchmarks and rules. Moreover, as witnessed by competitions in other AI disciplines such as planning and SAT solving, we see ICCMA as a new pillar of the community which provides information and insights on the current state of the art, and highlights future challenges and developments. This article summarises the first ICCMA held in 2015 (ICCMA’15). In this competition, solvers were invited to address standard decision and enumeration problems of abstract argumentation frameworks (Dunne and Wooldridge 2009). Solvers’ performance is evaluated based on their time taken to provide a correct solution for a problem; incorrect results were discarded. More information about the competition, including complete results and benchmarks, can be found on the ICCMA website

A Cognitive Model for Conversation

International audienceThis paper describes a symbolic model of rational action and decision making to support analysing dialogue. The model approximates principles of behaviour from game theory, and its proof theory makes Gricean principles of cooperativity derivable when the agents’ preferences align

A Formal Model for Trust in Dynamic Networks

We propose a formal model of trust informed by the Global Computing scenario and focusing on the aspects of trust formation, evolution, and propagation. The model is based on a novel notion of trust structures which, building on concepts from trust management and domain theory, feature at the same time a trust and an information partial order

Towards a complete multiple-mechanism account of predictive language processing [Commentary on Pickering & Garrod]

Although we agree with Pickering & Garrod (P&G) that prediction-by-simulation and prediction-by-association are important mechanisms of anticipatory language processing, this commentary suggests that they: (1) overlook other potential mechanisms that might underlie prediction in language processing, (2) overestimate the importance of prediction-by-association in early childhood, and (3) underestimate the complexity and significance of several factors that might mediate prediction during language processing

An integrated theory of language production and comprehension

Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation (such as semantics, syntax, and phonology). We show (a) how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, (b) how they interweave production and comprehension processes, and (c) how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal

Incorporation by Reference and Independent Legal Significance in the New York Law of Wills

In the substantive law of wills two theories of law are traditionally relied upon to permit consideration of extrinsic documents in the construction or expansion of a will. These two theories are the common law doctrines of incorporation by reference and independent legal significance. It is the purpose of this comment to analyze these theories of law in a dual aspect, first, to define the doctrines, applying them to their logical legal conclusions, and second, to assess the validity of various writings under existing New York law

Knowledge-yielding communication

A satisfactory theory of linguistic communication must explain how it is that, through the interpersonal exchange of auditory, visual, and tactile stimuli, the communicative preconditions for the acquisition of testimonial knowledge regularly come to be satisfied. Without an account of knowledge-yielding communication this success condition for linguistic theorizing is left opaque, and we are left with an incomplete understanding of testimony, and communication more generally, as a source of knowledge. This paper argues that knowledge-yielding communication should be modelled on knowledge itself. It is argued that knowledge-yielding communication occurs iff interlocutors coordinate on truth values in a non-lucky and non-deviant way. This account is able to do significant explanatory work: it sheds light on the nature of referential communication, and it allows us to capture, in an informative way, the sense in which interlocutors must entertain similar propositions in order to communicate successfully