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Record W4387642129 · doi:10.1177/09728201231200948

Aldous Glare Trade & Exports: The Dilemma of Establishing an Assessment Centre

2023· article· en· W4387642129 on OpenAlexaff
Kishinchand Poornima Wasdani, Abhishek Vijaygopal, Riju Antony

Bibliographic record

VenueAsian Journal of Management Cases · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsAttritionBusinessMarketingDilemmaOfficerOperations managementManagementEngineeringEconomics

Abstract

fetched live from OpenAlex

Aldous Glare Trade & Exports (AGTE) operates as a B2B technology reseller, offering computers, laptops, accessories, mobile phones and smart TVs. Founded in 1995 in Kochi, India, AGTE started with three members and with a capital of USD 4,000. Over time, it gained recognition, establishing sister concerns: ITnet and Alps Distributors for B2C goods and high-end computer sales. With a four-layered structure—CEO, functional heads, and senior and junior executives—AGTE employed 60 people. The HR manager handled human resources (HR) for AGTE, ITnet and Alps Distributors. It expanded with sales offices in Bengaluru, Thiruvananthapuram, and Kochi. By 2016, AGTE achieved USD 27 million turnover. In 2018, AGTE adopted an automated customer relationship management (CRM) system, though employee familiarity was incomplete. Customer complaints surged in April–December 2018, citing delivery and helpline issues. Directors set a USD 100 million turnover by 2025, allocating USD 300,000 for an assessment centre managed by the Chief Operating Officer Mohan Joseph. It aimed to curb the attrition of senior staff members and enhance CRM proficiency and sales certifications. AGTE aimed to transition from ad hoc training to structured recruitment training, overseen by Mohan Joseph and HR Manager Charles D’Souza. Challenges included seamless integration, past issue resolution and attrition management of senior staff members, balancing established practices with innovative strategies aligned with AGTE’s mission.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.847

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 communication0.0010.002
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 head0.041
GPT teacher head0.296
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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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