Suchergebnisse

Data Science (DS) is expected to deliver value for public governance. In a number of studies, strong claims have been made about the potential of big data and data analytics and there are now several cases showing their application in areas such as service delivery and organizational administration. The role of DS in policy-making has, on the contrary, still been explored only marginally, but it is clear that there is the need for greater investigation because of its greater complexity and its distinctive inter-organizational boundaries. In this paper, we have investigated how DS can contribute to the policy definition process, endorsing a socio-technical perspective. This exploration has addressed the technical elements of DS - data and processes - as well as the social aspects surrounding the actors' interaction within the definition process. Three action research cases are presented in the paper, lifting the veil of obscurity from how DS can support policy-making in practice. The findings highlight the importance of a new role, here defined as that of a translator, who can provide clarity and understanding of policy needs, assess whether data-driven results fit the legislative setting to be addressed, and become the junction point between data scientists and policy-makers. The three cases and their different achievements make it possible to draw attention to the enabling and inhibiting factors in the application of DS.

Environmental issues are rapidly emerging as one of the most important topics in strategic manufacturing decisions. Growing public awareness and increasing government interest in the environment have induced many companies to adopt programmes aimed at improving the environmental performance of their operations. State of the art literature has proposed many models to support executives in the assessment of a company's environmental performance. Unfortunately, none of these identifies operating guidelines on how the systems should be adapted to support the deployment of different types of "green" manufacturing strategies. The present paper seeks to illustrate techniques and architecture for performance measurement systems (PMSs) to support the implementation of feasible "green" manufacturing strategies.

PurposeThe purpose of this paper is to explore the adoption of managerial innovations in the public sector, identifying the reasons why their uptake and use may fail.Design/methodology/approachThe problem is investigated empirically through a case study approach. The change processes resulting from the adoption of two managerial innovations within the same Italian Central Government Institution are illustrated in detail.FindingsBoth cases represent a failure in the adoption and use of managerial innovations, attributable to a complex interplay of external and organisational forces. The empirical investigation points out the relevancy of individuals' actions and choices. The real explanation for the failure of both projects in fact seems to be key individuals' inability: first to "make sense" of what the innovation was about and second to communicate this "sense" throughout the organisation.Research limitations/implicationsThe findings are based on data from the Italian Central Government, and as such are not extendable elsewhere. However, the mechanisms of change examined here may be of wider interest to other public sector organisations.Originality/valueThe paper analyses a real‐world attempt to deploy managerial innovations in the public sector, and the resultant impact. A theoretical framework based on institutional theory and its recent advances is used to better understand the plural factors influencing the use of managerial innovations.