Jacek Pawlak

Inverse discrete choice modelling: theoretical and practical considerations for imputing respondent attributes from the patterns of observed choices

ABSTRACT The growing availability of geotagged big data has stimulated substantial discussion regarding their usability in detailed travel behaviour analysis. Whilst providing a large amount of spatio-temporal information about travel behaviour, these data typically lack semantic content characterising travellers and choice alternatives. The inverse discrete choice modelling (IDCM) approach presented in this paper proposes that discrete choice models (DCMs) can be statistically inverted and used to attach additional variables from observations of travel choices. Suitability of the approach for inferring socioeconomic attributes of travellers is explored using mode choice decisions observed in London Travel Demand Survey. Performance of the IDCM is investigated with respect to the type of variable, the explanatory power of the imputed variable, and the type of estimator used. This method is a significant contribution towards establishing the extent to which DCMs can be credibly applied for semantic enrichment of passively collected big data sets while preserving privacy.

Factors affecting outcomes of EU-supported investments in innovation among SMEs in the Greater Poland (Wielkopolska) region, Poland

Purpose The European Union offers support mechanisms to help small and medium sized enterprises (SMEs) to innovate and grow. Given the substantial contribution of SMEs to national economies, the present paper explores what factors tend to be associated with the success of EU-supported innovation by SMEs in Poland during its early post-accession period. Design/methodology/approach A conceptual model relating the type of innovation, investment purpose, funding type and financial readiness, location and collaboration possibilities, company size and sector of operation to changes in the capital base, employment, unit price and revenue is proposed. This model is operationalised and estimated as a structural equations model and estimated using a sample of 110 SMEs surveyed in 2008 in the Greater Poland (Wielkopolska) region in Poland. Findings Two approaches to the successful use of innovation support have been observed among the studied companies. The first approach implements market innovations to establish a presence in foreign markets and to move the product or service up the value chain. The second approach uses the funding to de-risk workforce expansion and increase production capacity. Originality/value The paper provides the first systematic disaggregate level analysis of an early post-accession context where impacts of EU support for SME innovation are decomposed into effects of specific investment conditions and innovation type on changes in capital base, employment, unit price and ultimately revenue. The insights provided here are valuable for managers developing business and innovation strategies on the one hand, but also for policymakers responsible for creating an entrepreneurship friendly environment in emerging economies.