MétaCan
Menu
Back to cohort
Record W2155681216 · doi:10.1108/09564230210431965

Contact personnel, physical environment and the perceived corporate image of intangible services by new clients

2002· article· en· W2155681216 on OpenAlexaff
Nha Nguyen, Gaston LeBlanc

Bibliographic record

VenueInternational Journal of Service Industry Management · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Identity and Reputation
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsBusinessMarketingPerceptionService (business)Order (exchange)Multilevel modelKnowledge managementPsychologyComputer scienceFinance

Abstract

fetched live from OpenAlex

The purpose of this article is to evaluate empirically the impact of contact personnel and physical environment on the perception of corporate image by new clients by using the hierarchical multiple regression analysis capable of exploring the potential presence of higher order and interaction terms. With data collected in two service industries, namely 272 new clients of a life insurance company and 238 travellers in a hotel, a linear relationship with corporate image was statistically confirmed for contact personnel, while a potential curvilinear relationship was found for physical environment. The results reveal the significant effect of both contact personnel and physical environment, as well as their interactive effects on corporate image. The managerial and research implications of the reported study are discussed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.216
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations293
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Service Industry ManagementSame topicCorporate Identity and ReputationFrench-language works237,207