An empirical assessment of logistics/supply chain management in two Latin American countries
Bibliographic record
Abstract
The Bowersox Daugherty (1987) logistics strategy typology (Process Strategy, Market Strategy, and Information Strategy) is an important conceptual framework for studying logistics/supply chain management strategy and its role on logistics/supply chain management outcomes. The purpose of this research is to empirically apply the typology in Peru and compare the findings with the previous research conducted in Guatemala. The three Bowersox/Daugherty dimensions are used to define the construct Overall Logistic Strategy (OLS), and then, the OLS was used to measure Organizational Competitiveness (COMP) through two intervening variables LCE (Logistics Coordination Effectiveness) and CSC (Customer Service Commitment). The results indicate that generally the logistics strategy in Peru is fundamentally similar to Guatemala’s. In other words, the direction of the relationships among the conceptualized constructs tested in the SEM model was significant and explained a sizable variation in COMP in both countries. This provided additional support for the robustness of the structural model in different cultural environments. However, some differences are apparent. First, the importance of the three independent variables and three dependent variables appear to be greater to the Peruvian respondents than Guatemalan respondents. Second, on closer inspection Peruvian logistics data indicates relatively greater emphasis on information, coordination, customer service, and relatively less emphasis on cost efficiency, than Guatemalan managers. Managerial insights and suggestions for future research and discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".