Short sea shipping: A statistical analysis of influencing factors on SSS in European countries

G van den Bos (Speaker), Wiegmans, B. (Speaker)

Activity: Talk or presentationTalk or presentation at a conference



SSS is already transporting approximately 38 per cent of intra-EU ton kilometers which makes it an important transport mode and this might indicate limited further growth potential. However, it appears to be clear that SSS is able to deliver solutions to the congestion and sustainability problems in Europe. The sketched problems and challenges for SSS lead to a need to analyze the SSS market in much more detail in order to indicate its growth potential through a statistical analysis of influencing factors on SSS in European countries.The central research question in the article is: ‘Which factors influence SSS in European countries?'

Data and methodology

The starting point for a study of SSS is to gain insight into markets, followed by an analysis of the ‘drivers' of successful short sea transport services. A regression analysis is performed on the country level to analyze the SSS growth potential in the respective European countries. Several different regression analyses are performed, and also different segments are analyzed. In order to check the results, a DEA analysis is performed to see which countries are efficient in SSS and which countries are less efficient. Last of all, several hypothesis are tested. Considering our effort in the data search, we are ‘satisfied' with our outcomes given the limited public SSS data availability. Due to the relatively small number of observations (n = 25 countries) used in our model estimations, the outcomes should be interpreted as a rough estimate and therefore be treated carefully.

Expected results

The univariate regression analysis indicates that the following variables influence total SSS volume in European countries: land area, coastline, total number of SSS ports, number of small SSS ports, number of large SSS ports, number of inhabitants, GDP, GDP per head, road length and rail length. An additional multivariate regression analysis indicates that more than 78% of the variance in the total SSS volume per country can be explained by variations in the number of large SSS ports and the GDP per head. Finally, future prospects for SSS indicate that most countries show potential to further increase their SSS volume.
Period13 Jul 2016
Event title14th World Conference on Transport Research
Event typeConference
Conference number14
LocationShanghai, China