Name
Title | ||
|---|---|---|
Supply chain trust diagnosis (SCTD) using inductive case-based reasoning ensemble (ICBRE): The case of general competence trust diagnosis |
Abstract | ||
|---|---|---|
General competence trust among supply chain partners, referring to the trust that a partner holds the general ability of fulfilling contracts, is a critical factor to ensure effective cooperation in a supply chain, especially in the current financial crisis. The method of supply chain trust diagnosis (SCTD) is to evaluate whether or not a partner holds such competence. This research devotes to an early investigation on diagnosing competence trust of supply chain with the method of inductive case-based reasoning ensemble (ICBRE). The so-called supply chain trust diagnosis with inductive case-based reasoning ensemble consists of five levels, that is, information level, the level of ratios of general competence states, the level of inductive case-based reasoning, ensemble level, and diagnosis result level. Knowledge for diagnosing competence trust, which composes of a case base, is hidden in data represented by ratios of general competence states. Inductive approach is combined with randomness to construct diverse and good member methods of inductive case-based reasoning. Finally, simple voting is used to integrate outputs of member inductive case-based reasoning methods in order to produce the final diagnosis on whether or not a partner holds the general ability of fulfilling contracts. We statistically validated results of the method of supply chain trust diagnosis with inductive case-based reasoning ensemble by comparing them with those of multivariate discriminant analysis, logistic regression, single Euclidean case-based reasoning, and single inductive case-based reasoning. The results indicate that the method of supply chain trust diagnosis with inductive case-based reasoning ensemble significantly improves predictive capability of case-based reasoning in this problem and outperforms all the comparative models by group decision of several decision-making agents and non-strict assumptions like statistical methods. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.asoc.2012.03.029 | Appl. Soft Comput. |
Keywords | Field | DocType |
inductive case-based reasoning,general ability,supply chain trust diagnosis,inductive case-based reasoning ensemble,case-based reasoning,supply chain,general competence trust diagnosis,single euclidean case-based reasoning,member inductive case-based reasoning,general competence state,diagnosing competence trust | Voting,Case base,Artificial intelligence,Supply chain,Linear discriminant analysis,Case-based reasoning,Machine learning,Mathematics,Randomness | Journal |
Volume | Issue | ISSN |
12 | 8 | 1568-4946 |
Citations | PageRank | References |
1 | 0.35 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Li | 1 | 290 | 12.71 |
| Jie Sun | 2 | 257 | 11.06 |
| Jian Wu | 3 | 211 | 6.75 |
| Xian-Jun Wu | 4 | 17 | 3.44 |