The rate of change in the world is increasing both in scope and magnitude by rapidly developing digital technologies. The challenging problem for performance measurement and management (PMM) in the digital era is twofold: firstly, the constant change in the external environment is compelling PMM to be more dynamic. Secondly, organisations have to deal with different varieties and volumes of data to create competitive advantage. The aim of this paper is to explore how PMM models and practices should be renovated to be resilient and reflect advances in the digital economies. Literature review on the state of the art was conducted covering the issues faced by organisations in the digital economies and their relevance to PMM. A case study was conducted to explore the practitioner perceptions of dealing with the issues faced in digital economies as well as to understand how they are making changes to their PMM. The key findings from the study include: (1) Organisations should refocus their measurement efforts to incorporate evaluation of their performance over a wider network involving various stakeholders. (2) Organisations need to understand how technological developments could create competitive advantage through their strategy and deploy it to relevant positivistic and behavioural measures. ARTICLE HISTORY

This paper discusses Netsourcing strategies for vendors, a little explored area of outsourcing research, using both a resource based (RBV) perspective and a transaction cost economics (TCE) perspective. Using both theories and an infrastructural view of IT service, we present a conceptual model of vendor sourcing decisions. We then present a number of propositions based on case studies of vendor decisions. Finally we conclude by discussing the theoretical contribution of RBV and TCE and, crucially, the value of combining both theories for the study of Netsourcing, and for other areas of IS research.

Many organisations are increasingly dealing with massive amounts of data to face new competitive challenges. However, even if powerful technologies support data collection and analysis, the lack of appropriate resources and capabilities for handling socio-technical systems often hinders effective decision-making. Hence, this study aims to investigate how performance measurement systems should develop and drive appropriate resources and capabilities to enable effective decisionmaking for creating a competitive advantage in data-intensive organisations. A case study approach was adopted with seven data-intensive organisations using one-to-one semi-structured interviews, personal observation, and secondary sources such as company documentation, meetings notes, reports, etc. The findings highlight the relevance of organisational structure and cross-functional communication to cultivate senior management commitment and drive to develop data capturing and analytical capabilities to support effective decision-making. The findings also suggest that to enable superior data capturing capability, organisations should leverage on a higher degree of automation, a higher degree of awareness on data value, and data variety for providing accurate and timely information as well as developing new business insights. Similarly, to enable superior data analytics capability, organisations should develop analytical skills, data visualization, and data-driven culture to make effective decisions.

In the last few years there has been much interest in the delivery of software-as-a-service. The concept of remote application outsourcing, or application service provision (ASP), has emerged as a solution aiming to offer organizations, mainly small to medium-sized enterprises (SMEs), access to key applications that were previously unaffordable. This chapter examines this model of software delivery, focusing on the potential risks that could be associated with it. The authors identify shared risks with traditional IS/IT outsourcing and proprietary risks of this model. The chapter concludes by giving a classification of these risks.