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Record W2765796655

Equity investment decisions for technology based ventures

2014· article· en· W2765796655 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Technology Management · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVenture capitalNew VenturesPrivate equityEquity (law)BusinessInvestment (military)FinanceOrder (exchange)MarketingSocial venture capitalEntrepreneurship
DOInot available

Abstract

fetched live from OpenAlex

One major challenge facing early stage technology based companies is obtaining timely capital to aid their growth. This study sought to advance understanding of the decision making criteria currently used by Canadian equity investors to evaluate technology based companies which are seeking early stages of financing (seed, start–up or first stages). Sixty individuals belonging to one of three equity investor types participated: business angels (BAS, n=20), private venture capitalists (PVCs, n=20) and public venture capital funds (PVCFs, n=20). Data were collected using questionnaires administered through on–site personal interviews. Analyses reported here focus on group differences among decision making criteria as investors evaluated the business worthiness of one of their recent specific technology based business ventures. A total of 95 criteria were derived from previous investment literature and these subsequently received a priori assignment to one of these five categories: (1) characteristics of the entrepreneur(s), (2) characteristics of the market targeted by the venture, (3) characteristics of the venture offering, (4) investor(s) requirements and (5) characteristics of the investment proposal from the venture to the investor(s). Stability of ranked importance ordering for these five categories was tested using Friedman two–way ANOVA by ranks. Results revealed significant stability among the five categories within groups of each investor type: for BAS, the order of importance was (1,3,2,4,5); for PVCs, it was (1,2,3,4,5) and for PVCFs, it was (1,2,3,5,4). Next, specific key criteria as applied by these types of investors were located. For example, key criteria for BAS included: the entrepreneurs' familiarity with product and market; their familiarity with customer requirements; their ability to anticipate need for change; and evidence of truthfulness in their proposal. For PVCs, key criteria included: the entrepreneurs' ability to bring about change; attractive growth potential of market; cash out potential expected by the investors; and expected rate of return on investment to the investors. For PVCFs, key criteria included: evidence of truthfulness in the proposal; the entrepreneurs' familiarity with customer requirements; and their management commitment to success.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.753
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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