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Record W4410121993 · doi:10.47772/ijriss.2025.90400205

Navigating Organisational Change: Middle Managers’ Sensemaking Practices in a Malaysian Organisation

2025· article· en· W4410121993 on OpenAlexaboutno aff
Noor Khairin Nawwarah Khalid, Aini Maznina A.Manaf

Bibliographic record

VenueInternational Journal of Research and Innovation in Social Science · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsSensemakingOrganisational changeMiddle managementBusinessKnowledge managementOrganizational changeChange management (ITSM)Process managementPublic relationsPolitical scienceMarketingComputer science

Abstract

fetched live from OpenAlex

Sensemaking is critical for middle managers navigating organisational change, yet research on their sensemaking practices remains limited, particularly in the Malaysian context. This study examines how middle managers in a Malaysian organisation interpret and respond to change, drawing on the Communicative Constitution of Organisations The Montreal School (CCO TMS) theory. Using a qualitative approach, semi-structured interviews were conducted with 30 middle managers to explore their sensemaking strategies. The findings reveal seven key sensemaking practices: adopting a big-picture mindset, demonstrating empathy, reflecting on emotions, relying on Company Approved Procedure guidelines, engaging in storytelling, participating in change intervention programs, and utilizing internal communication channels. These practices enable middle managers to bridge the gap between senior leadership’s strategic vision and employees’ operational realities, fostering alignment and reducing resistance. The study highlights the crucial role of middle managers in facilitating successful change initiatives and underscores the importance of equipping them with communication and sensemaking resources. Organisations should prioritize structured communication strategies and leadership support mechanisms to enhance middle managers’ effectiveness in guiding teams through change.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.535
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.156
GPT teacher head0.444
Teacher spread0.288 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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