Bibliographic record
Abstract
Information systems that link businesses for the purpose of inter-organizational transfer of business transaction information (inter-organizational information systems, or IOIS) have been in use since the 1970s (Lankford & Riggs, 1996). Early systems relied on private networks, using electronic data interchange (EDI) or United Nations EDIFACT standards for format and content of transaction messages. Due to their cost and complexity, the use of these systems was confined primarily to large companies, but low-cost Internet commercialization has led to much more widespread adoption of IOIS. Systems using the Internet and the World Wide Web are commonly referred to as B2B (business-to-business) systems, supporting B2B electronic commerce. Technological innovations have led to several forms of B2B Internet implementations, often in the form of online exchanges. These are virtual marketplaces where buyers and sellers exchange information about prices, products, and service offerings, and negotiate business transactions. In addition to substituting proprietary lines of communication, emerging technologies and public networks have also facilitated new business models and new forms of interaction and collaboration, in areas such as collaborative product engineering or joint offerings of complex, modularized products. During the years 1999-2001 a number of online exchanges were introduced, but many of these failed (Gallaugher & Ramanathan, 2002), due mainly to an inability to attract participating business partners. Those that have survived are often owned by companies or consortia that are also exchange customers or suppliers. The objective of this overview is to describe the evolution and the characteristics of B2B Internet implementations, and to discuss management considerations, the evaluation and adoption of B2B applications, and the technical infrastructure supporting these systems. We also indicate some of the open issues that remain as the technology and its adoption continues to evolve.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.014 | 0.006 |
| Insufficient payload (model declined to judge) | 0.067 | 0.009 |
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".