Going up the Ladder: Multiplicity Sampling to Create Linked Macro-to-Micro Organizational Samples

We argue that researchers should use representative samples to address many issues and that long-standing interest in the connections between macrolevel and microlevel processes is also central to organizational analysis. Our literature review suggests that designs that link organizations to suborganizational units or members have deficiencies involving atypicalness of cases studied or inadequate and unreliable data on organizations derived from more representative samples of individuals. Instead we advocate using a form of multiplicity sampling in which the probability of an organization's inclusion in the sample is proportional to the number of workers it employs. To illustrate this design, we use data from a study of the impact of technology and technological change on workers and their work outcomes. In our study, we first obtained a representative sample of workers, who provided data on their current or most recent places of employment. We then interviewed informants within those organizations to obtain organizational data. We demonstrate that our sample of establishments does not differ significantly in size or industrial affiliation from the distributions reported in archival data when the survey data are provided by the CEOs of the establishments but that workers and managers are less reliable sources of these data. We discuss the limitations of this design, as well as its potential to inform a number of issues critical to organizational analysis and macro-to-micro relationships.