An ontology

The efficacy of the principal–agent contract in supply-chain quality control depends not only on contract parameters but also such noncontract parameters as cost of a high-quality effort and the diagnostic error of the inspection policy. The noncontract parameters usually fluctuate and are unobservable during contract execution, which may hinder suppliers’ high-quality effort, or, in other words, result in a lower efficacy for the contract. This article proposes an ontology-based approach to facilitating a principal–agent contract by monitoring the contract’s loss of efficacy. The approach consists of ontology-based models and data-centric algorithms. The ontology-based models not only formally represent concepts and relations between concepts involved in predicting whether a contract is efficient, but also organise multichannel data such as news, marketplace reports and industry databases containing information of factors impacting the unobservable noncontract parameters’ fluctuations. Based on the ontology-based models and multichannel data, the data-centric algorithms are developed to predict whether a contract will lose efficacy. We evaluate our approach through case study, simulation and comparison against related approaches to supply-chain quality control. The case study proves that our approach is appropriate. In the simulation evaluation, a combination of our approach and principal–agent contract is more efficient than just a principal–agent contract. The comparison results against related approaches show that our approach is a novel, inexpensive and directly applicable tool for reducing both asymmetric information and moral hazard in supply-chain quality control