An Exploration of Owner-Manager Problem Solving Practices in Small Firms: The Central Vancouver Island Experience
Bibliographic record
Abstract
A significant amount of research in the field of small business management has correlated small firm performance with the sophistication of overall management skills (see, for example, Gasse, 1997; Gadenne, 1998; Zinger, leBrasseur and Zannibi, 2001; Balderson, 2003) and more particularly problem solving skills. Yet, even though problem solving skills are at the core of the small business management process (Jennings and Beaver, 1997), there has been little research to date that has focused on understanding the actual approach small business owner-managers take to solve the problems they encounter as the present study has done, through the utilization of an interpretive research design applied to a sample of small firms. The primary purpose of this exploratory study is to investigate the nature of problem solving practices adopted by 11 small business owner-managers on Central Vancouver Island, Canada, by identifying the types of problems encountered in the years following their establishment, the actions taken to solve these problems and the outcomes of these actions for the firm. It examines the characteristics of the problemm solving approaches utilized by owner-managers as they encountered problems, and identifies how they perceived the impact of the approach taken on the continued survival of their firm. The methodological approach taken in this study is positioned within an emergent body of research in the field of small business and entrepreneurship that applies an interpretive paradigm to uncover the complex facets of how individuals develop their capabilities and management practices (Chell and Allman, 2003) with a particular emphasis on the small business owner-manager. The interpretive assumptions guiding the research process have allowed new understandings to emerge about problem solving in small firms within the wider context of managerial capability as a critical contributor to small business survival. More specifically, the critical incident technique method (Flanagan, 1954; Chell, 1998), along with an approach to data analysis and coding that draws from grounded theory (Glaser, 1992; Glaser and Strauss, 1999; Strauss and Corbin, 1998), are combined and applied as a qualitative research strategy. This strategy has not previously been used in relation to the study of problem solving in small firms. This interpretive paradigm allows the exploration of how small business owner-managers attach meaning to their subjective experiences and the implications of these perceptions for the business outcomes of the firm, specifically as they relate to solving critical business problems. As a result, the interpretive methods applied in the course of this study make a novel contribution to the field, since they have yielded new interpretations on the nature of problem solving processes in the sample of small firms studied. The findings presented here reveal the intuitive, improvised and non-linear nature of how problems are actually solved in these small firms, in contrast to a number of well-known theoretical research frameworks that propose well-defined and delineated steps in the problem solving process. The results of this study make a valuable contribution to building new theory in this area of inquiry by demonstrating how more dynamic processes occur in practice. An alternative way to conceptualize problem solving in small firms is presented in Chapter 6, A Holistic Framework for Problem Solving in Small Firms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".