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Record W2317575890 · doi:10.1504/ijpmb.2016.075600

A visual process model for improved technology-based service design

2016· article· en· W2317575890 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

VenueInternational Journal of Process Management and Benchmarking · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsComputer scienceProcess managementBlueprintBusiness Process Model and NotationProcess (computing)Business process modelingService (business)Business processConceptual modelProcess modelingKnowledge managementBusiness modelCorrectnessSoftware engineeringEngineeringWork in processBusinessOperations managementDatabase

Abstract

fetched live from OpenAlex

This paper presents a new method for business process modelling in the services sector that integrates the client focus of service blueprints with the operational analytics of lean value stream mapping. The approach incorporates a simple and innovative use of colour to improve the correctness of the models. The conceptual model is analysed using the guidelines of business process modelling and benefits are demonstrated through an illustrative example. The proposed approach provides a mechanism to facilitate the effective design and implementation of technology-based innovations in service delivery by enabling a diverse set of stakeholders to participate in the modelling. This modelling approach is based on best practices from existing business process modelling notations and was developed to support change management and innovation in services. The approach results in intuitive models that can be used by novice modellers for clear communication and technology-infused service design.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.026
GPT teacher head0.289
Teacher spread0.263 · 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