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Record W2811840016

Low-Cost Versus Frugal Innovation Building Blocks & the Fundamentals of Jugaad Business Modeling (Podstawy innowacji niskokosztowych w porownaniu z innowacjami oszczednosciowymi oraz fundamenty tworzenia modeli biznesowych typu jugaad)

2017· article· pl· W2811840016 on OpenAlexaboutno aff
Jamal Boukouray

Bibliographic record

VenueKagoshima Daigaku Kogakubu Kenkyu Hokoku · 2017
Typearticle
Languagepl
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness modelSharing economyIndustrial organizationRevenueBusinessBridge (graph theory)MarketingEconomicsComputer scienceFinance
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we seek to present the first holistic and frugal business model ever designed to bridge the digital divide in Greenfield Africa. Based on an extensive implication in the Connecting Africa and OLPC Projects, Airtel Telecom Group (a Canadian company) partners decided to go one step further in their quest to revamp state owned telcos and postal service providers who were on the brink of collapse. Unlike low-cost models developed by well-known heavyweights like SFR, Ryanair, Blue Jet, Easyjet, Walmart, etc., a frugal and sustainable business model like the one discussed in this paper has a lot more to do with Jugaad Innovation frameworks which led to many affordable and responsible breakthroughs in healthcare, education, housing, broadband, transportation, alternative energies, etc.; therefore, our main goal is to (a) distinguish between frugal and costkilling models, (b) explain the characteristics of jugaad-based framework and philosophy versus revenue-driven business models, (c) explain the importance of sustainable and organic business models in developing markets versus imported plug & play recipes. At last, we will describe the fundamental building blocks of juggad innovation business models and their impact on growth perspectives for MNCs and entrepreneurs willing to break into greenfield markets.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0050.001
Scholarly communication0.0050.006
Open science0.0040.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.063
GPT teacher head0.298
Teacher spread0.235 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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