Vadim Grinevich

Policies to enhance the ‘hidden innovation’ in services: evidence and lessons from the UK

More than 75% of the UK economy is based on services. Knowledge-based services generate more than five times as much value added for the UK economy as advanced manufacturing. Yet, there are persistent gaps in understanding the innovative performance of services. Using Fourth UK Community Innovation Survey (CIS4) data and the results of a detailed case study analysis, this article helps to fill this gap by analysing what innovation in services means and how it can be measured. The traditional indicators of innovation inputs (such as levels of R&D expenditures) and innovation outputs (such as the number of patents) suggest that services are less innovative than other branches of the economy. We take into account a larger spectrum of innovation indicators, both in terms of innovation inputs and outputs, to analyse whether the intensity, nature and economic impact of innovation significantly varies between the manufacturing and service sectors in UK, and between different parts of the services sector such as knowledge-intensive business services and traditional services. The results of the empirical analysis identify the ‘hidden parts’ of innovation in services, that is, the innovative activities and successful innovative outputs that are traditionally underestimated by the use of metrics based on R&D and patents. We suggest a wide range of policy measures specifically targeted at enhancing innovation in services; the UK service economy needs more focus on learning and the training of personnel, and a new balance of policy to support both R&D and non-R&D innovation activities.

LUISA: A Land-Use Interaction with Social Accounting Model; Presentation and Enhanced Calibration Method

Random utility modelling has been established as one of the main paradigms for the implementation of land-use spatial interaction (LUSI) models. We present a detailed formal description of a LUSI model that adheres to the random utility paradigm through the explicit distinction between utility and cost across all processes that represent the behaviour of agents. The model is rooted in a social accounting matrix, with the workforce and households accounts being disaggregated by socioeconomic type. Similarly, the land account is broken down by domestic and nondomestic land-use types. The model is developed around two processes. Firstly, the generation of demand for inputs required by established production; when appropriate the implicit production functions are assumed to depend on costs of inputs, which give rise to price-elastic demands. And, secondly, the spatial assignment of demanded inputs to locations of their production; here sequences of decisions are used to distribute demand both spatially and aspatially, and to propagate costs and utilities of production and consumption that emerge from imbalances between supply and demand. The implementation of this generic model is discussed in relation to the case of the UK. The model has been developed for testing the sustainability of integrated economic, spatial development policies, and output information for estimating urban form and the potential for decentralised technologies. The inputs include area-wide socioeconomic forecasts and the allocation policy of urban land. The outputs include the spatial allocation of activities and prices of labour, goods and services, land, and floorspace. They are combined with the land inputs to estimate the changes in the density of urban form and activities. These outputs can then be used to estimate the demands for infrastructure services and the potential for decentralised infrastructure supply. We focus primarily on the calibration process and its methodological implications, including a method of refining the calibration and demonstrate how this improves the spatial representation of the utility of land.

Academic entrepreneurship in the creative arts

The extensive literature on academic entrepreneurship has focused almost entirely on science and engineering, while little is known about the extent of it in other disciplines, most notably the creative arts. We analyse the context, motivations, and variety of academic entrepreneurship in the creative arts using a recently completed survey of UK academics, providing microdata on 1108 academics. The data are complemented using institutional data taken from the Higher Education–Business and Community Interaction Survey, and data on individual submissions to the Research Assessment Exercise 2008. We highlight four characteristics of academic environment in the creative arts that strongly influence the nature of the entrepreneurship in the field: the practice-based nature of the research; the role of networks, particularly networks linked to teaching; the importance on nonmonetary rewards; and the role of geography. Our results indicate that academic entrepreneurship in the creative arts is varied and extensive, and that it could be better supported by policy.

Academic Entrepreneurship and the Geography of University Knowledge Flows in the UK

Knowledge flows between universities and industry have long been recognised as important determinants of regional economic development. However, a major unresolved issue is the exact nature of the mechanisms through which knowledge flows take place. We analyse the spatial patterns of knowledge exchange activities by considering a wide range of mechanisms including joint research, consultancy services, personnel exchange and informal advice. The analysis is based on a recently completed survey of UK academics, providing micro-data on over 22,000 academics across all subject areas. Our results show that the geography of academic entrepreneurship varies widely by type of activity.

Academic Interactions with Private, Public and Not-for-Profit Organisations: The Known Unknowns

An increased emphasis on the role of innovation in economic development has focused attention on the university as an important contributor to the innovation process. Universities are engaged in research and education and, therefore, provide critical resources for innovation such as skills and knowledge. They are one of the main organisational elements of the innovation system (Cooke et al. 1997; Lundvall 1992; Nelson 1993) and one which is involved, through market and non-market linkages, with other innovation agents including business, government and nongovernmental organisations.

Upscaling strategies in the sharing economy

This paper examines what enables and constrains upscaling, understood as expanding the customer base and the target geographies, in the sharing economy from an integrated business, technological an...