Suchergebnisse

Most psychological contract research examines single-agency situations in which a breach only affects one firm. In a multiple-agency relationship, however, the individual performs work that simultaneously satisfies the requirements of two firms, allowing for the possibility that breach outcomes extend across both the breaching and the nonbreaching firms. We theorize two mechanisms through which breach outcomes extend across organizational boundaries. First, we propose spillover effects for feelings of violation and for organizational citizenship behaviors from the breaching firm to the nonbreaching firm. Second, we propose that, in cases where the individual expects the nonbreaching firm to intervene and rectify the other firm's breach as part of a regulatory obligation, there are direct and moderating effects of meeting (or failing to meet) these perceived obligations. Using professional service firms as the empirical context, we find evidence of breach outcome spillover between the two firms in the multiagency relationship and direct and moderating effects of unmet obligations to intervene by the nonbreaching firm. We also find some key differences in the nomological networks depending on whether the breaching firm was the consulting firm or the client firm. These insights highlight the importance of extending psychological contract study to multiple-agency relationships.

By integrating mapping and geospatial data into a county-level datasetfor exploratory analysis, we will demonstrate how to provide useful insightsfor waste managers and local governments regarding spatial patterns ofhousehold hazardous waste (HHW) collection and how it changes over time. We usemap-based visualization to display patterns of spatial intensity and countylocations for HHW collection in California from 2004 to 2015. We use exploratory spatial data analyticsmethods to characterize the spatial distribution of HHW collected per person.When we considered the spatial relationships, we were able to develop andestimate a geographically-weighted regression to explain how different regionalfactors influence the amount of HHW collected. These factors includedemographic characteristics, HHW management policy instruments, andenvironmental quality enforcement and consideration of these factors isnecessary to create a successful recycling program.