Governance of Interorganizational Information Systems: A Resource Dependence Perspective
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we examine why firms seek to control and own interorganizational information systems, or IOS. Practitioners have largely cited the issues related to control and ownership of IOS, referred to as IOS governance in this paper, as the key reason behind the failure of many IOS initiatives. We distinguish between two IOS governance modes, transactional and financial, and develop a mediated-moderation model to explain the factors influencing the governance choices. In our model, the key motivators of IOS governance are the criticality and the replaceability of the resources that firms procure, which affect IOS governance through their influence on the degree of operational integration existing between partners. We hypothesize that while resource criticality will increase the needs for financial and transactional governance because of its positive impact on operational integration, resource replaceability will negatively influence governance needs because of its negative impact on operational integration. Furthermore, technological uncertainty associated with the resources is argued to negatively impact the extent of IOS governance exercised by firms by weakening the positive impact of resource criticality and strengthening the negative impact of resource replaceability on operational integration respectively. We empirically test our model using data gathered from a survey of 159 United States manufacturing firms. Results show that resource criticality positively affects the extent of financial and transactional IOS governance by increasing the need for operational integration, whereas resource replaceability negatively affects them by reducing the need for operational integration. Furthermore, technological uncertainty creates disincentives for IOS governance primarily by weakening the positive influence of resource criticality on operational integration, while no statistically significant effect of technological uncertainty on the relationship between resource replaceability and operational integration was discerned.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.068 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it