Model to support decision-making on the implementation of SDGs in business networks
Bibliographic record
Abstract
This thesis had as main objective the development of a model to support decision making on the implementation of Sustainable Development Goals (SDGs) in business networks mainly formed by Small and Medium Enterprises (SME). In the theoretical part of the methodological development, it was carried out the survey of the SDGs and its goals, for, through a decision matrix, aligning them to the business networks. Assuring scientific robustness to the theoretical basis of the model, a systematic review of the literature was carried out with the support of Methodi Ordinatio methodology, seeking scientific discussions about SDGs in Industrial Engineering and the fundamental variables to the model construction. Also, as a methodological procedure, to establish the structure of the model, a survey of the general indicators of implementation and monitoring was carried out, as well as of the SDG Selector tool. And aligning the theory with the general objective proposed in this research, SDG Compass was analyzed - a guide that provides guidelines for the implementation of SDGs in business strategy - in a construct of Sustainability Balanced Scorecard, in order to raise the fundamental strategies for transforming global goals into requirements and attributes of operationalization. In the mathematical part of the methodological development, the multicriteria basis was selected, based on the methodology to support the decision making MACBETH. The results of the development enabled the elaboration of an index of alignment of the SDGs target, IAM-ODSempresa, capable of supporting the decision-making process of SDGs in business networks including therefore SMEs. The empirical application was carried out in business networks in Canada and Brazil and provided results both for the calibration of the proposed model and also for the analysis of the strategic orientations of business networks in two different regional contexts. Moreover, the results of the application showed that the developed model, by providing the IAMODSempresa index of alignment of the ODS goals to the business context, supports decision-making. Thus the model offers support for effectiveness in business measures aimed at achieving the proposed UN Sustainable Development Goals for humanity.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".