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Record W2966092664 · doi:10.5539/mas.v13n8p9

Employer Branding: Creating a Sustainable Recruitment Plan in Large Corporates

2019· article· en· W2966092664 on OpenAlexvenueno aff
Mohannad Abu Daqar, Ahmad K. A. Smoudy, Milán Constantinovits

Bibliographic record

VenueModern Applied Science · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEmployer Branding and e-HRM
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessMarketingReputationSample (material)Position (finance)Profit (economics)ExploitEmployer brandingScale (ratio)FinanceEconomicsNew product development

Abstract

fetched live from OpenAlex

The aim of this study is to attract talented employees by using non-traditional recruitment methods, such as online professional business networks. These methods should encourage potential employees to apply and join these companies. It also allows the company to position its image in its potential customers’ minds. Hence, this research contributes to how to position an image in potential employee’s minds and motivate them to be part of the company. The main objective of this study is to investigate how to maintain a continuous demand from potential employees; accomplished by providing an outline of a sustainable recruitment plan to be applied in the larger Palestinian corporates. A questionnaire was distributed at employees and their HR managers at four large-scale corporations in West Bank, Palestine. The proposed models were analyzed on the basis of 100 responses related to four well-known large Palestinian corporates. The results indicate that 78.3% of the sample have a recruitment plan in their corporations. Moreover, most of the sample, over 50%, have job satisfaction. which can enhance and help corporations in building a good reputation. It also exploits its internal employees as a strategic marketing tool to build their real, good, and attractive employer branding. The study recommends that companies seriously consider their employees in their marketing strategy, similar to how they market their products and services. To accomplish this, they need to build a long-term relationship with employees in a way that affects the general profit of the corporate and assists the corporate to create and maintain the employer branding.

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 score0.491
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.043
GPT teacher head0.256
Teacher spread0.213 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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