Integrating Public Service Motivation in the Job-Demands-Resources Model: An Empirical Analysis to Explain Employees’ Performance,Absenteeism, and Presenteeism

Public service motivation (PSM) is a focal construct in public management research, and while sound evidence exists that PSM is positively associated with several desired outcomes, knowledge on the underlying mechanisms which explain these associations and on potential negative consequences of PSM remains limited. Addressing these research gaps, this study investigates how PSM relates to relational job resources, work engagement, and outcomes. We thereby account for both direct and moderating effects of PSM and consider positive (employee performance) and negative outcomes (sickness absenteeism and presenteeism). We empirically test our model in the German public sector and find that the PSM dimensions relate differently to the assessed outcomes, providing varying support for our hypotheses. In particular, commitment to public value and compassion seem to drive the positive effect of PSM on employee performance, whereas self-sacrifice and client orientation are linked to reduced absenteeism, and only compassion is associated with increased presenteeism.     

Exploratory Space–Time Analysis of Burglary Patterns

This paper introduces two new methods for the exploratory analysis of the spatial and temporal dynamics of residential burglary patterns. The first is a conditional spatial Markov chain which considers the extent to which a location??s probability of experiencing a residential burglary in a future period is related to the prevalence of residential burglaries in its surrounding neighborhood in an initial period. The second measure extends this conditional perspective to examine the joint evolution of residential burglary in a location and its surrounding neighborhood. These methods are applied to a case study of residential burglary patterns in Mesa, Arizona over the period October 2005 through December 2009. Strong patterns of spatial clustering of burglary activity are present in each year, and this clustering is found to have an important influence on both the conditional and joint evolution of burglary activity across space and time.