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Record W4213355623 · doi:10.1002/kpm.1704

Does generational thinking create differences in knowledge sharing and<scp>ICT</scp>preferences?

2022· article· en· W4213355623 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueKnowledge and Process Management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsMcGill University
FundersAGE-WELL
KeywordsPerceptionBaby boomersPsychologyContext (archaeology)Knowledge sharingVariance (accounting)Social psychologyInformation and Communications TechnologyGeneration xDyadKnowledge managementBusinessComputer science

Abstract

fetched live from OpenAlex

Abstract Organizational strategies around employee retirement are often cast in generational terms (i.e., as knowledge transferred between older and younger generations). Within this context, research suggests generational differences in knowledge sharing preferences and in supporting information and communication technology (ICT) preferences. At the same time, others argue that the concept of generations is a myth, or a stereotype‐driven perception. Therefore, the objectives of this study were (1) to examine whether there are generational differences in knowledge sharing and ICT preferences and (2) to examine whether perceptions of younger and older generations' preferences match their actual preferences. Data were collected from 138 survey participants (Baby Boomers, Generation Xers, and Millennials) and analyzed using ANOVAs, effect sizes, and confidence intervals. Additionally, 13 interviews were conducted with Baby Boomers and analyzed using content and narrative analyses. Findings showed no reliable differences between the three generations' preferences for knowledge sharing modalities (i.e., in writing and verbally) and methods (i.e., in person and through various ICTs). The most preferred methods were email, in‐person, telephony, and instant messaging. Most interestingly, while all generations had an accurate perception of Millennials' sharing preferences, they all demonstrated a distorted perception of Baby Boomers' preferences. Moreover, the broader the generation gap, the greater the discrepancy in perception. These findings support the postulation that generational differences may be a matter of perception rather than actuality. The most significant implication for research and practice is to retire generational thinking and to propose several alternative organizational strategies in managing knowledge continuity.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.035
GPT teacher head0.296
Teacher spread0.261 · 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