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Record W1564695978

User adoption of interface agents for electronic mail

2005· dissertation· en· W1564695978 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

VenueMacSphere (McMaster University) · 2005
Typedissertation
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer scienceInterface (matter)Context (archaeology)User interfaceOperabilityWorld Wide WebUser interface designHuman–computer interactionKnowledge managementUser experience designSoftware engineering
DOInot available

Abstract

fetched live from OpenAlex

This dissertation addresses the issue of user adoption of interface agents for electronic mail (email). Interface agents are reactive, continuous, collaborative, and autonomous software entities that act on a user's behalf by communicating directly with a person offering assistance and advice in performing computer-related activities. The study presents and empirically validates a model that describes user adoption behavior, offers insights on important features of this technology from the end-user perspective, reports on critical incidents of agent usage, and offers recommendations for developers and marketers. As means of investigating this phenomenon, a survey of actual users of an interface agent-based email system was conducted. Emphasis was placed on identifying user needs and key factors that influence their adoption decisions. Data analysis involved quantitative and qualitative techniques (Partial Least Squares, descriptive statistics, classical content analysis). An extended version of the Technology Acceptance Model was introduced and tested, and the user context surrounding email agent adoption was explored. Survey findings suggest that existing management information systems and social sciences theories, models, and methodologies may be fruitfully applied to investigate user adoption of novel interface agent technologies. By combining and synthesizing results of a deductive and inductive analysis of the survey data, a new, grand model of interface agents adoption and use is suggested that is the central contribution of this research. According to this model, in voluntarily usage conditions, two general types of factors influence user adoption behavior - user perceptions and agent operability. User perceptions are either positive or negative mental reflections of several properties of an agent, such as perceived enjoyment, usefulness, ease of use, intrusiveness, and attractiveness. Agent operability embraces factors pertaining to operational characteristics of an agent, such as compatibility, system interference, reliability, and personalization. Findings also suggest that to foster the diffusion of highly useful agent systems, developers and marketers need to become aware of the importance of individual user characteristics, enhance their understanding of factors influencing people's adoption decisions, and demonstrate the functionality of interface agents through non-agent technologies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0640.000

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 head0.044
GPT teacher head0.316
Teacher spread0.272 · 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