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Record W3196736900 · doi:10.5267/j.uscm.2021.7.009

Incidence of internal marketing and organizational commitment in the retail sector

2021· article· en· W3196736900 on OpenAlexvenueno aff
Junior Canales-Requena, Olenka Ccanto-Inga, Johann Mendizabal Lizarbe, Wagner Vicente-Ramos

Bibliographic record

VenueUncertain Supply Chain Management · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Applied Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational commitmentLoyaltyMarketingBusinessSample (material)Relationship marketingFeelingNormativeReciprocity (cultural anthropology)Loyalty business modelPsychologySocial psychologyMarketing management

Abstract

fetched live from OpenAlex

The objective of this study was to determine the impact of internal marketing on the organizational commitment of employees in the retail sector. The method used was a quantitative correlational approach, at an explanatory level with a non-experimental design. The study sample consisted of 392 workers belonging to the retail sector. The results generated by structural equations show that specific relationships have p < 0.05, i.e. all the proposed hypotheses are accepted in the proposed correlation between internal marketing and the three types of organizational commitment, among them the affective commitment, which generates emotional ties between the employee and the organization, feeling proud to remain in the same linking the values and objectives of the same as their own goals, the commitment of permanence, which implies the risks involved in separating from the organization as well as the loss of all the benefits obtained and how these would be difficult to obtain if the employee were to leave the organization. Finally, the normative commitment, which arises when the employee perceives some kind of opportunity or special benefit in the organization, thus generating a bond of moral reciprocity, i.e. a bond of loyalty. The conclusion of the study is that the use of internal marketing for personnel selection is a fundamental tool for achieving acceptable levels of the three types of commitment mentioned above. This ensures the efficiency of the company both internally and externally, with long-term results.

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)0.002
metaresearch head score (Gemma)0.014
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.290
Teacher spread0.265 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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