Innovation in services: overview of data sources and analytical structures

Bart van Ark, Lourens Broersma and Gjalt de Jong
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Gjalt de Jong: Groningen University

No 199944, GGDC Research Memorandum from Groningen Growth and Development Centre, University of Groningen

Abstract: This paper has a twofold aim. Firstly, it presents an overview of sources of data on service innovation. We distinguish two levels of data, namely data at the macro-level and data at the micro level. Data at the macro-level are mainly obtained from primary and secondary statistical sources produced by national and international (statistical) agencies. Most macro-data do not measure the service innovation process itself, but mainly represent inputs in or output originating from the innovation process. Data at the micro-level are derived from specific innovation surveys of firms and enterprises, which have been carried out over the past decade, and cover - although to a limited extent - service sectors as well. Section 2 provides an overview of macro and micro indicators on service innovation, and it discusses the strengths and weaknesses of the various measures. The second aim of the paper is to provide analytical structures that can assist in analysing the data on service innovation. The main characteristic of the analytical structures vis-à-vis the raw data, is that analytical structures require constructs and assumptions on the relation between the various indicators in the database. At the macro-level we propose two structures, namely a productivity accounting system, which allows to analyse the contribution of the inputs in the production process, including skilled and unskilled labour, different vintages of physical equipment and technology inputs, to the output produced. Secondly, we discuss an input-output accounting framework to analyse backward linkages of intermediate input use in service industries. The input-output structure may also serve a more detailed analysis of innovation relations between industries, using R&D data. At the micro level we compare the statistical computer package, LISREL (Linear Structural Relations), as a means to analyse the data from micro-based innovation surveys with regular regression analysis, which is mostly used in analysing micro-based innovation data. Section 3 describes these analytical structures in more detail. This paper is part of the project on Structual Information Provision in Services (SIID) carried out by the University of Groningen and DIALOGIC (Utrecht) for the Minisity of Economic Affairs in The Hague (The Netherlands).; Together with an accompanying thematic paper on the conceptualisation of service innovation, it concludes the first phase of the SIID project.

Date: 1999
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