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Record W1574201833

How to Plan as a Small Scale Business Owner: Psychological Process Characteristics of Action Strategies and Success [*]

2000· article· en· W1574201833 on OpenAlexaboutno aff
Michael Fresé, Marco van Gelderen, Michael Ombach

Bibliographic record

VenueJournal of Small Business Management · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingAction (physics)BusinessScale (ratio)Strategic managementProcess (computing)Computer science
DOInot available

Abstract

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A theoretical analysis of individual-level planning and action strategies used by small business owners/managers distinguishes five different strategic approaches: Complete (top-down) Planning, Critical Point, Opportunistic, Reactive, and Routine/Habit. Research on 80 owners of small start-up firms in the Netherlands showed that, as hypothesized, a Reactive Strategy was negatively related to firm success, while a Critical Point Strategy was positively related. The combination of Critical Point and Opportunistic strategies appeared most successful and the combination of Opportunistic and Reactive was found to be least successful. This study takes a psychological approach to investigate the characteristics of action strategies used by small scale business owners; these strategy characteristics are then related to the firms' success. The objective of this research is to deepen our understanding of how strategies are used and how the owner/manager's strategy-relevant behavior is related to success in the small business. Founders of new ventures always follow some strategy to reach their goals, though these strategies are not always highly rational or explicit. Research on business strategy frequently differentiates types of strategy by content and characteristics (Austin and Vancouver 1997; Dess, Lumpkin, and Covin 1997; Hart 1992; Olson and Bokor 1995; Rajagopolan, Rasheed, and Datta 1993; Rauch and Frese 2000). Content specifies which kind of strategy is used--for example, low costs, differentiation, or focus/niche strategies (Porter 1980). On the other hand, process refers to how one formulates and implements the strategy content (Olson and Bokor 1995). This study concentrates on the of action strategy. In contrast to most strategy literature which focuses on the firm level, this research investigates the action strategy as a characteristic of the founder and manager of the firm (Rajagopolan, Rasheed, and Datta 1993). The pervasive influence of founders on their firms and their dominance in making decisions make it possible to assume a high degree of equivalence between the individual and the organizational levels of analysis. Strategies have been researched in psychology under the topic of thinking and problem solving. Strategy is defined by a plan of action, that is, a sequence of means to achieve a goal (Miller, Galanter, and Pribram 1960). Thus, the concept of strategy emphasizes how to reach a goal; the of developing the goal itself lies outside the concept of strategy. The function of a strategy is to determine appropriate action in uncertain situations. A strategy presents a template that can be applied to a variety of situations, and thus helps one compensate for the limited processing capacity of the human mind (Frese and Zapf 1994; Hacker 1989; Kahneman 1973). Cognitive and action theories have differentiated the following characteristics of strategies: Complete Planning, Critical Point, Opportunistic, and Reactive Strategies (Hacker 1986; Hayes-Roth and Hayes-Roth 1979; Zempel 1994). A person using a Complete Planning Strategy plans ahead and actively structures the situation. Complete Planning Strategy implies a more comprehensive representation of the work process, a longer time-frame in which to plan ahead, a larger inventory of signals, a better knowledge and anticipation of error situations, and a more proactive orientation (Frese and Zapf 1994; Hacker 1986). The Critical Point Strategy concentrates on the most difficult, most unclear, and most important point first (Zempel 1994). Only after solving the first critical point are further steps planned. This approach constitutes an iterative problem solving strategy--one has a clear goal in mind and concentrates on the tasks relevant to it. In contrast, a person using an Opportunistic Strategy starts ou t with some form of rudimentary planning but deviates from these plans easily when opportunities arise (Hayes-Roth and Hayes-Roth 1979). …

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.263
Teacher spread0.227 · 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 designObservational
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

Citations160
Published2000
Admission routes1
Has abstractyes

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