  Violations of laws and regulations about food safety, production safety,
quality standard and environmental protection, or negative consequences from
loan, guarantee and pledge contracts, may result in operating and credit risks
of firms. The above illegal or trust-breaking activities are collectively
called discreditable activities, and firms with discreditable activities are
named as discreditable firms. Identification of discreditable firms is of great
significance for investment attraction, bank lending, equity investment,
supplier selection, job seeking, and so on. In this paper, we collect
registration records of about 113 million Chinese firms and construct an
ownership network with about 6 million nodes, where each node is a firm who has
invested at least one firm or has been invested by at least one firm. Analysis
of publicly available records of discreditable activities show strong network
effect, namely the probability of a firm to be discreditable is remarkably
higher than the average probability given the fact that one of its investors or
investees is discreditable. In comparison, for the risk of being a
discreditable firm, an investee has higher impact than an investor in average.
The impact of a firm on surrounding firms decays along with the increasing
topological distance, analogous to the well-known "three degrees of separation"
phenomenon. The uncovered correlation of discreditable activities can be
considered as a representative example of network effect, in addition to the
propagation of diseases, opinions and human behaviors. Lastly, we show that the
utilization of the network effect largely improves the accuracy of the
algorithm to identify discreditable firms.
