Exploring collective leadership and coproduction: An empirical study

Replaced version without front matter with version with front matter 2021-02-08.This chapter explores coproduction through a collective leadership lens. It draws from the public administration and leadership fields and a 2019 empirical study of public service collaboration in Scotland, UK. It is suggested that tensions generated by working within a New Public Management model combined with frustrations felt from current collaborative practice have motivated an exploration into alternative conceptions of leadership and different ways of working when collaborating. The findings reveal that collaboration can be strengthened through the application of four key processual and attitudinal modifications. This approach is described as working in an emergent and relational way while applying a systems and inquiry mind-set. It is the effect of the sum of these parts that boosts the intensity of collaborative work, offering a number of benefits, including an enriched and dynamic coproduction process embedded within its practice.https://doi.org/10.4018/978-1-7998-4975-9pubpu

Anomaly Detection in Streaming Sensor Data

In this chapter we consider a cell phone network as a set of automatically deployed sensors that records movement and interaction patterns of the population. We discuss methods for detecting anomalies in the streaming data produced by the cell phone network. We motivate this discussion by describing the Wireless Phone Based Emergency Response (WIPER) system, a proof-of-concept decision support system for emergency response managers. We also discuss some of the scientific work enabled by this type of sensor data and the related privacy issues. We describe scientific studies that use the cell phone data set and steps we have taken to ensure the security of the data. We describe the overall decision support system and discuss three methods of anomaly detection that we have applied to the data