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Electronic Marketplace Support for B2B Business Transactions

2010· book-chapter· en· W2478762028 on OpenAlexaff
Norm Archer

Bibliographic record

VenueIGI Global eBooks · 2010
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElectronic data interchangeBusinessThe InternetBusiness-to-businessElectronic businessBusiness modelDatabase transactionService (business)ImplementationInformation exchangeCommerceKnowledge managementMarketingTelecommunicationsComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

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 or electronic marketplaces (Wang et al., 2005). These are virtual marketplaces where buyers and sellers exchange information about prices, products, and service offerings, and negotiate business transactions. They are major components of the supply chains that they support. 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, but also because potential participants and their business partners did not perceive enough value added through the significant investment they required. 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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.113
Threshold uncertainty score0.377

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0070.011
Open science0.0030.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1130.037

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.

Opus teacher head0.011
GPT teacher head0.198
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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