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Record W2126589862 · doi:10.1287/isre.1060.0093

The Effects of Trust-Assuring Arguments on Consumer Trust in Internet Stores: Application of Toulmin's Model of Argumentation

2006· article· en· W2126589862 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInformation Systems Research · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsUniversity of British ColumbiaUniversity of New Brunswick
Fundersnot available
KeywordsArgument (complex analysis)Argumentation theoryThe InternetComputer scienceInternet privacyBusinessWorld Wide WebEpistemology

Abstract

fetched live from OpenAlex

A trust-assuring argument refers to “a claim and its supporting statements used in an Internet store to address trust-related issues.” Although trust-assuring arguments often appear in Internet stores, little research has been conducted to understand their effects on consumer trust in an Internet store. The goals of this study are (1) to investigate whether or not the provision of trust-assuring arguments on the website of an Internet store increase consumer trust in that Internet store and (2) to identify the most effective form of trust-assuring arguments to provide guidelines for their implementation. Toulmin's (1958) model of argumentation is proposed as a basis to identify the elements of an argument and to strengthen the effects of trust-assuring arguments on consumer trust in an Internet store. Based on Toulmin's (1958) model of argumentation, three elements of arguments that commonly appear in daily communication; namely, claim, data, and backing, are identified. Data refers to the grounds for a claim, while backing is used for providing reasons for why the data should be accepted. By combining these three elements, three forms of trust-assuring arguments (claim only, claim plus data, and claim plus data and backing) are developed. The effects of these three forms of trust-assuring arguments on consumer trust in an Internet store are tested by comparing them to a no trust-assuring argument condition in a laboratory experiment with 112 participants. The results indicate (1) providing trust-assuring arguments that consist of claim plus data or claim plus data and backing increases consumers' trusting belief but displaying arguments that contain claim only does not and (2) trust-assuring arguments that include claim plus data and backing lead to the highest level of trusting belief among the three forms of arguments examined in this study. Based on the results, we argue that Toulmin's (1958) model of argumentation is an effective basis for website designers to develop convincing trust-assuring arguments and to improve existing trust-assuring arguments in Internet stores.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.084
GPT teacher head0.407
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it