Can integration difficulties affect innovation and satisfaction?
Bibliographic record
Abstract
Purpose – The difficulties in the integration of management systems (MSs) and their relationship with innovation and customer satisfaction are explored by proposing a model that links these three concepts together. Integration, innovation and customer satisfaction are relevant issues for the competitiveness of companies, especially for the ones that have implemented several MS standards. The paper aims to discuss these issues. Design/methodology/approach – Data for the study derives from a survey carried out in 76 Spanish organizations registered to at least both ISO 9001:2008 and ISO 14001:2004 standards for quality MSs and environmental MSs, respectively. An exploratory factor analysis and structural equation modeling (SEM) are utilized to assess and confirm the proposed scales validity and the relationships of the conceptual model. Findings – Based on the empirical study, the second-order SEM shows that the difficulties of integration are directly and negatively related to both of MS documentation and procedures. This level is also directly related to the innovation and satisfaction. Nevertheless, no relationships were found between the difficulties of integration and the integration level of MS human resources. Moreover, no direct relationships were found between the difficulties of integration and both the constructs of innovation and satisfaction. Also, the results showed the integration level of MS procedures was not related to the construct of innovation. Originality/value – This is one of the first studies to relate integration difficulties with innovation and customer satisfaction, with a conclusion that an organization should give more importance to the difficulties of integrated MSs that have been uncovered to have a relationship with innovation and customer satisfaction.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".