MétaCan
Menu
Back to cohort
Record W4388930756 · doi:10.5539/ijms.v15n2p71

Impact of E-marketing Capabilities and E-marketing Orientation on Sustainable Firm Performance of SME in KSA Through E-relationship Management

2023· article· en· W4388930756 on OpenAlexvenueno aff
Bandar Khalaf Alharthey

Bibliographic record

VenueInternational Journal of Marketing Studies · 2023
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)MarketingBusinessMarketing managementMarketing strategyCustomer orientationComputer science

Abstract

fetched live from OpenAlex

This study aims to investigate the impact of e-marketing orientation and e-marketing capabilities on sustainable business performance through e-customer relationship management. Employing a positivistic and deductive approach with an experimental technique, this research utilizes a cross-sectional design, collecting 152 responses via a Google Docs questionnaire. Smart PLS3 analysis reveals that sustainable business performance significantly hinges on e-marketing capabilities and orientation, with e-customer relationship management acting as a mediator. Notably, this study underscores strong interrelationships among all variables and highlights noteworthy positive influence of social media marketing on SME performance in Kingdom of Saudi Arabia. While this research acknowledge need for future studies to broaden the variable scope, its implications offer valuable assistance to SME top management for achieving long-term performance objectives. The distinctive contribution of this study lies in its examination of sustainable SME performance in KSA through the lenses of e-marketing and e-relationship management, enriching the understanding of these factors in fostering enduring success.

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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.014
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.023
GPT teacher head0.317
Teacher spread0.294 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Marketing StudiesSame topicOrganizational and Employee PerformanceFrench-language works237,207