Modeling the Success of Small and Medium Sized Online Vendors in Business to Business Electronic Marketplaces in China
Bibliographic record
Abstract
This paper explores the performance of Chinese small and medium sized enterprises (SMEs) on Business-to-Business (B2B) electronic marketplaces (EMs). Based on a content analysis of 155 cases of high performing online Chinese vendors, this paper explains the success of SME online B2B vendors within a Motivation-Capability framework. This first generation of SME B2B online vendors proved highly motivated to increase sales and developed a set of Internet leveraged organizational capabilities to compete online, including capabilities for online marketing, product innovation, eCommerce management, etc. This study differs from traditional wisdom that online marketplaces will render Guanxi (a Chinese cultural phenomenon defined as close and pervasive interpersonal relationships, Yang, 1994) irrelevant since online marketplaces are perceived to be impersonal. In fact, Guanxi still matters online, but it takes new forms. This research offers important managerial implications for B2B SME online vendors on how to leverage EMs for higher performance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".