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Record W3021055544 · doi:10.1108/jsm-03-2019-0141

Services under new management: the myth of a fresh start

2020· article· en· W3021055544 on OpenAlexaff
Tim Jones, Susan Myrden, Peter A. Dacin

Bibliographic record

VenueJournal of Services Marketing · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsQueen's UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsRelevance (law)MarketingReputationQuality (philosophy)OriginalityValue (mathematics)PerceptionService (business)BusinessSign (mathematics)Consumer behaviourPsychologyService qualityAdvertisingSocial psychologyComputer scienceSociologyPolitical science

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to examine the consumer-side effects of “under new management” (UNM) signs. The authors integrate cue-utilization theory and relevance theory to guide hypotheses about the conditions under which these signs are and are not beneficial. Design/methodology/approach Two consumer-based experiments were used to examine the quality and reputation effects of restaurants signaling a management change on potential and existing customers. Findings The results suggest that positive and negative effects are possible. The direction of these effects is contingent upon consumers’ prior experience, type of service (i.e. search/experience) and the relevance of the signal. Research limitations/implications The study is limited to one industry (i.e. restaurants) and examines the effects of market signals on perceived quality and reputation. In addition, this research brought forth the notion of “signal relevance” and suggested that it may be explicitly tied to attributions. However, this assertion must examine multiple signals (relevant/irrelevant) and their contingent effects on consumer perceptions. Practical implications The findings advise businesses to use caution when using signals such as an “UNM” sign, as they appear to have different effects depending on the experience of the consumer with the service and the relevance of the signal. Originality/value This research contributes to the literature on cue utilization theory to understand the effects of marketplace cues on consumer perceptions. It contributes to marketing theory and practice by proposing a model of cue effects based on prior customer experience, type of service and cue relevance.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.231
Teacher spread0.210 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2020
Admission routes1
Has abstractyes

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