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Record W7067724029

Modeling Business Process Workflow of SMEs Using Environment Based Design with a Case Study of Valtech Fabrication Incorporation

2019· dissertation· en· W7067724029 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2019
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsWorkflowProductivityRevenueBusiness process managementBusiness processProduction (economics)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

Small and Medium-Sized Enterprises (SMEs) account for over 95% of firms in most countries. In Quebec, SMEs account for 96% of all businesses. SMEs are important for economic growth and they are strong contributors to productivity. Some of the challenges of SMEs are the lack of financing, difficulties in using technology, constrained managerial capabilities, or inefficient productivity.
\nAmong challenges of SMEs, finance and inefficient productivity can be considered as two of the most important issues that slows down their growth. Finance issues can be referred to as the lack of money in investing in new technologies, hiring competent resources, and investing in new equipment. To improve the financial status of a company and increase the profit, we can either increase the revenue or decrease the expenses. The objective of this project is to target the finance issue as well as inefficient productivity of the SMEs and improve both of them by developing a workflow model. Workflow refers to a method for improving business process management, and an effective workflow can help the decision-makers in an enterprise to develop pathways leading to the reduction of costs and wastes. It employs the Environment Based Design (EBD) methodology which not only designs an effective workflow but also analyses the environment of the business to find the root causes of the issues to help the SMEs improve their finance issue by increasing the operation and production efficiency and effectiveness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.271
Teacher spread0.217 · 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.

Study designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

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