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Record W2346750472 · doi:10.1177/2277977916634237

Managing Workforce Crisis: A Case from Hotel Waterlily

2016· article· en· W2346750472 on OpenAlexaboutno aff
Deepika Upadhyay, Hari Shankar Shyam, Mukesh Chaturvedi

Bibliographic record

VenueSouth Asian Journal of Business and Management Cases · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsSalaryBusinessReputationWorkforceWork (physics)Quarter (Canadian coin)Service (business)MarketingFinanceManagementEconomicsEngineeringEconomic growthSociology

Abstract

fetched live from OpenAlex

Hotel Waterlily is listed among one of the most popular and upcoming hotels of Indore. It is a subsidiary of Sajdhaj Marriage Decorator, an event management company that specializes in wedding planning and management. Manoj Yadav is the promoter of the group. The hotel has a decent reputation in the market. The group intends to develop Hotel Waterlily as a five star property. The third and fourth financial quarters are considered to be the most business friendly quarters of the year for the hotel industry, as it garners maximum business during this period. During the last month of second financial quarter, 18 employees did not report to the hotel for work, which included 4 from Food and Beverages (F&B) production department, 12 from F&B service department and 1 each from housekeeping and store department. After initial inquiry, it was found that they all had resigned in mass. They had procured an offer letter from an emerging hotel of the city. All of them were quite seasoned employees of the hotel. They started blackmailing the management for their salary upgradation. They demanded for 25 per cent hike in their gross salary. The management tried very hard to reconcile with the contending employees amicably but these employees were not ready to accept and concur on the terms offered by the management.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.020
GPT teacher head0.212
Teacher spread0.191 · 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.

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
Published2016
Admission routes1
Has abstractyes

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