An exploratory investigation of performance criteria in managing and controlling new product development projects: Canadian SMEs' perspectives
Bibliographic record
Abstract
Purpose This paper aims to understand and document evaluation criteria used in the new product development (NPD) process of small- and medium-sized enterprises (SMEs) to support the management and control of their NPD projects. Design/methodology/approach This study combines exploratory and explanatory methodology (case studies) involving five Canadian small and medium enterprises (SMEs) that are successful in NPD. The authors conducted semi-structured interviews with nine selected managers and project managers to explore the process and evaluation criteria used to manage and control NPD projects. Findings The results highlight that cost, time and quality are key evaluation criteria used by SMEs to make decisions relative to the NPD project's success. Profitability, return on investment, expected sales and customer satisfaction are additional criteria used to evaluate NPD project's success. It has been also found that the SMEs did not consider sustainability issues in the criteria used as their focus are on the needs of stakeholders, mainly customers. Research limitations/implications Limitations: The evaluation criteria are extracted from a limited number of SMEs that have successfully carried out NPD projects and may therefore be influenced by some contextual factors. The results cannot be generalized to all SMEs or to all projects, as their characteristics may differ. Implications: This study offers a novel outlook on NPD process in SMEs, by documenting criteria related to constraints in project management. The integration of theory of constraints contributes to increasing theoretical knowledge about the management and control of NPD projects in SMEs. It provides insight into how project managers (and other decision makers) can increase the chances of project success by managing project constraints and criteria. Practical implications The evaluation criteria identified in this study can therefore be of use to SMEs managers and project leaders seeking to improve the management and control of their NPD projects. These criteria can help them better manage their limited resources and skills and allocate them to the most promising projects. They can also help them conduct their NPD process more efficiently to achieve the intended objectives, including the desired project profitability targets. Originality/value This paper offers new insight and practical implications about evaluation criteria within the stages and activities of the NPD process that needed to be considered by SMEs' managers involved in NPD projects.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".