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Record W4413855846 · doi:10.60076/indotech.v3i2.1387

Enhancing Cross-Functional Collaboration in Hybrid Projects: The Role of Business Analysis Standards in Bridging Predictive and Agile Practices

2025· article· en· W4413855846 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.

Bibliographic record

VenueIndonesian Journal of Education And Computer Science · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsRegional Municipality of Niagara
Fundersnot available
KeywordsBridging (networking)Agile software developmentProcess managementBusinessKnowledge managementComputer scienceSoftware engineeringComputer security

Abstract

fetched live from OpenAlex

Hybrid project approaches that integrate both predictive and agile methods demand successful cross-functional teamwork to deliver successful project outcomes. The research explores how business analysis standards such as the BABOK Guide and the PMI Guide to Business Analysis help improve team collaboration in hybrid project environments. The systematic literature review in the study examines the role BA standards play in supporting stakeholder alignment and shared understanding while bridging communication gaps between technical and non-technical team members. The research indicates that BABOK enhances stakeholders' ability to collaborate while the PMI Guide offers a strategic approach to integrate business analysis with overall project objectives. Business Analysis standards improve project results and teamwork effectiveness even though challenges like resistance to change and tool adaptability remain in agile environments. The study delivers practical recommendations for organizations aiming to boost team coordination and communication in hybrid project environments by utilizing structured business analysis methods.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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