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Record W2061425024 · doi:10.1108/14626000310489781

Business strategies for small firms in the new economy

2003· article· en· W2061425024 on OpenAlexaff
Terence Tse, Khaled Soufani

Bibliographic record

VenueJournal of Small Business and Enterprise Development · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsConcordia University
Fundersnot available
KeywordsDisintermediationBusinessOrder (exchange)Strengths and weaknessesDigital economyContext (archaeology)Linkage (software)The InternetIndustrial organizationNew economySmall businessMarketingEconomicsComputer science

Abstract

fetched live from OpenAlex

The development of the new economy through the advent of the Internet and the World Wide Web has created many threats and opportunities for firms in general and small businesses in particular. There appears to be an inextricable linkage among the new economy, new enterprise, and the new technology, which may have a potential effect on the way small businesses formulate their business strategies. This paper provides a theoretical approach that looks at the advantages of the digitisation of the economy and strategy formulation of small businesses taking three specific themes into account – virtualisation, molecularisation, and disintermediation. The strengths and weaknesses of various e‐commerce strategies in the context of these dimensions are discussed. Some strategies that are suitable for small companies are recommended and four principles are stated in order to assist these firms to formulate strategy in the new economy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0090.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.197
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations82
Published2003
Admission routes1
Has abstractyes

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