The role of life cycle concepts in the assessment of interorganizational alignment
Bibliographic record
Abstract
Purpose This paper aims to investigate the alignment between the information‐processing needs and capabilities during interorganizational relationships through the lenses of both the product and the business relationships life cycle concepts, and the types of information exchanged. Design/methodology/approach This paper follows up on a previous empirical study conducted in the automotive sector, investigating the electronic collaboration within the supply chain of a large European Automotive Supplier (EAS). Out of the 61 respondents from this previous study, four illustrative cases are selected to further investigate their information alignment, where each case involves one specific relationship between EAS and its business partners based on the supply chain collaboration classification provided by the German Association of the Automotive Industry (VDA). Findings The conclusion is that the phenomenon is bimodal and requires that the different information‐processing needs and capabilities associated with each stage of both the product and the business relationships life cycles should be considered. Research limitations/implications The small number of illustrative cases and the specificity of the chosen sector limit the generalizability of the results. Without considering the various types of information‐processing needs and capabilities as well as the stage of both product and business relationships life cycles, a biased conclusion could lead to inappropriate information and communication technology investments and business decisions. Originality/value The richness of the cases and the genuine integration of the life cycle concepts and the type of information with the notion of alignment help to identify some key aspects of interorganizational relationships.
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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 | 0.015 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".