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Record W2885942563 · doi:10.5267/j.msl.2018.7.004

Application of social exchange theory on relationship marketing dynamism from higher education service destination loyalty perspective

2018· article· en· W2885942563 on OpenAlexvenueno aff
Ndanusa Mohammed Manzuma-Ndaaba, Yoshıfumi Harada, Norshahrizan Nordin, Aliyu Olayemi Abdullateef, Abd Rahim Romle

Bibliographic record

VenueManagement Science Letters · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsDynamismPerspective (graphical)Social exchange theoryLoyaltyMarketingBusinessService (business)Relationship marketingServices marketingLoyalty business modelMarketing managementPsychologyService qualitySocial psychologyComputer scienceEpistemology

Abstract

fetched live from OpenAlex

The recent paradigm shift from recruitment of international students to retention of students encouraged radical changes on the consumption of educational services from university serving the students for creation of mutually beneficial relationship between the students and the university. The impact of globalization hit the economy in two paradoxes; first, consumers have more choices but less satisfaction; second, service providers have more strategic options, which yield less value. Against this background, this study proposed and validated destination loyalty model to arrest the increasing students' attrition at study location. The declining state funding of higher education challenged the management of education sector to design sustainable competitive advantage strategy not only to attract but also to retain students at their study destination. A total of 498 data was solicited from international students at Malaysian public universities, partial least square structural equation modeling (PLS-SEM) was used to test the reliability and validity of items and constructs. The results show that relationship marketing dynamism of service quality, students' satisfaction, perceive image, perceived value and personal reasons were stable for international student loyalty to study destination. A new model called 2S2P was developed for emerging education destinations. Theoretical and practical implications as well as directions for future studies were documented in the paper.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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 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

Citations27
Published2018
Admission routes1
Has abstractyes

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