An Exploratory Taxonomy of Job Quality of the Working Poor based on Hierarchical Cluster and K-Means Cluster Analysis

Abstract

This article shows an analysis of job types which deepens the understanding of job quality of the working poor in the Northeast of China. Hierarchical cluster analysis and K-Means cluster analysis are adopted to develop taxonomy of four job types: vulnerable jobs, insecure jobs, environmental advantage jobs, and relatively saturated jobs. In these four job types, vulnerable jobs are characterized by low income, poor labor insurance, adverse working environment and little chances for future development. Environmental advantage jobs are characterized by relatively better working environment, but the conditions of other three aspects of job quality are lower than the average level of the sample. Insecure jobs are characterized by extremely poor condition on labor security and evidently higher income level. The conditions of working environment and vocational development in this job types are evidently lower than the average levels of the sample. Relatively saturated jobs are characterized by higher income, and better labor security. The working environment and vocational development are just at the average level of the sample.