Deer Creek Land Development (DCLD)
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.
Bibliographic record
Abstract
Purpose The purpose of this paper is to describe and analyse the experiences of a small business, Deer Creek Land Developments (DCLD), which has been very successful in negotiating the competitive pressures in a mature industry over time and has built sustainable competitive advantage. The firm has been quite successfully navigating the ups and downs of the market. The case provides an excellent example of how small businesses can open their business models to respond to changes in the external environment, such as an economic downturn, and/or simply to grow. Design/methodology/approach The paper uses a single case study approach. Detailed interviews of the owner and the manager were used to collect data for the case study. Findings DCLD's success is found to be hinged on its ability to consistently enhance operational efficiencies, move to higher valuations by adopting an open business model that exploits core in‐house capabilities and those acquired through contractors and partner organizations. Practical implications The paper provides several interesting insights useful for small business managers and entrepreneurs. Small businesses can use openness of both types, as demonstrated in the case, to create strategic differentiation and also to reduce operating costs. Originality/value This paper initiates a rich field enquiry, which provides some interesting insights to small business managers. The case study is used to demonstrate how a small business can effectively use an open business model to negotiate competitive and environmental pressures.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it