The purpose of this chapter is to summarise the main methodologies for the measurement of productivity and productivity growth. In the context of this chapter, productivity is driven by improvements in technical efficiency and technological progress. The author therefore provides a broad overview of the techniques to identify the two drivers of productivity growth. The author also discusses the main challenges related to the measurement of productivity in sectors like retail and finance.
Vania Sena and Sena Ozdemir
This chapter wants to discuss how Big Data can limit the liability of smallness. We will start from an organisational perspective and focus on the coordinating costs that may make small firms difficult to manage. We therefore explore how the exploitation of Big Data can reduce the coordination costs and facilitate collaboration among teams. Finally, we plan to discuss the relationship between business performance and investment in Big Data, both theoretically and empirically. We hope the chapter may offer SMEs useful insights on how to exploit the Big Data they produce.
Vania Sena and Sumon Bhaumik
The Covid-19 pandemic has resulted in widespread disruptions to all sectors in the economy. Early estimates from the OBR suggest that, in the UK, social distancing measures may result in up to 35 percent drop in economic activity. Most of the current policy interventions try to stabilize the economy; however, offsetting the negative impact of the shock on the local economy short term is only half the job. However, the characteristics of COVID-19 (i.e. the fact that the current outbreak is not a one off but several outbreaks are expected for the next eighteen months) implies that building up the foundations for economic growth is intertwined with building up resilience in the economy. In other words, resilience has to become the long-term objective of the economic policy. The economic shock generated by the current outbreak is global where global does refer not only to the fact that every country will experience a contraction in aggregate demand (albeit at different points in time) but mostly (and more pertinently) to the fact that its spreads globally thanks to the interconnected supply chains that characterise modern value creation. As a result, the impact of the shock may be twice larger than expected because of the direct impact of the contraction on the national economy and of the indirect impact of the contraction through the international supply chains. The expectation is that businesses will need to face the reality of a world which will become less globalised and have to learn to strike a fine balance between local and global after the crisis is over. This means that companies will have to revisit their supply chains and markets to protect themselves in the case of a second outbreak. Our chapter plans to address the following questions: How might supply chains be reorganised in a post-Covid-19 world and what is the impact of these changes on the local economy? Using a simulation analysis (Agent Based Models), we can develop conjectures about how the UK's companies might reorganise their supply chains, as a reaction to the risks associated with long supply chains that have been highlighted by the Covid-19 crisis, and potential slowdown in cross-border movements of goods and services in the post-Covid-19 world. Methodologically, we plan to use a mix of simulation and econometric analysis to address our research questions. Simulation analysis (ABM models) will allow to model local economies and the supply chain linkages. The models will let quantify the impact of adjustments of the supply chains on the local economy and its outcomes such as employment and productivity growth.