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Record W4296127837 · doi:10.1080/08853134.2022.2116334

Relationship conflict in stores: a longitudinal study of intra-store conflict on salespeople’s helping, customer-oriented behavior, and customer purchase behavior

2022· article· en· W4296127837 on OpenAlexaff
Michel Tremblay

Bibliographic record

VenueJournal of Personal Selling and Sales Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsMarketingPsychologyBusinessProfit (economics)Social psychologyAdvertisingMicroeconomicsEconomics

Abstract

fetched live from OpenAlex

Although the service-profit chain model has been studied widely, little is known about the processes and conditions of store-level relationship conflict to an increase or decrease in customer purchase behavior. Accordingly, this study aims to investigate the cumulative effects of relationship conflict on changes in unit-level helping, the effect of salespeople’s helping behavior on customer-oriented behavior (COB), and the subsequent impact on changes in customer purchase. To test these relationships, data points were collected from 1,523 salespeople observations and 13,005 customers across 116 pooled stores assessed in six waves over more than 6 years. The findings revealed that stores with a long history of low relationship conflict consistently displayed high helping behavior. Results show that helping growth depends on the degree of conflict intensity and asymmetry; the intensity of relationship conflict led to an increase in helping behavior when conflict asymmetry is high and to a decrease of such behaviors when conflict asymmetry is low. Results also showed that store-level helping behavior had a positive effect on COB, which in turn had a cumulative positive effect on changes in customer purchase behavior.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.301
Teacher spread0.238 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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