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Do Changes In High-Performance Work Systems Pay Off?A Longitudinal Investigation of Dynamic Fit

2015· article· en· W2521496613 on OpenAlex
Xiaoyu Huang, Kaifeng Jiang, Anil Kumar Verma

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcademy of Management Proceedings · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAmbidexterityWork systemsFlexibility (engineering)AdaptabilityContingencyAdaptation (eye)Perspective (graphical)Consistency (knowledge bases)Work (physics)PsychologyKnowledge managementComputer scienceEconomicsEngineeringManagement

Abstract

fetched live from OpenAlex

Using an eight-year longitudinal survey, this study investigates the stability– change paradox in human resource (HR) systems by examining how patterns of change in high-performance work systems (HPWS) relate to innovation and financial performance of organizations. The contingency perspective suggests that such change constitutes beneficial flexibility because changes in aspects of HPWS are required to attain dynamic fit. By contrast, the universalistic perspective and organizational ambidexterity suggest that HPWS provides both efficiency and flexibility, which indicates beneficial stability. An exploratory analysis supports both theoretical perspectives and reveals a positive relationship between two distinct patterns of change in the ability-motivation- opportunity dimensions of HPWS and performance outcomes. Long-run consistency in the ability-enhancing dimension (i.e., training and recruitment systems) with continuous incremental change is positively associated with high performance. Conversely, short-run stability with episodic change in the motivation- and opportunity-enhancing dimensions of HPWS (i.e., compensation and employee involvement systems) is positively related to performance. The findings suggest that organizations can benefit from both stability and flexibility in HR systems by appropriately emphasizing long-run adaptability in the ability dimension and short-run adaptation in the motivation and opportunity dimensions of HPWS.

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.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.037
GPT teacher head0.249
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