Abstract
ABSTRACT Information and Communication Technology (ICT) has become an important tool to promote a variety of public goals and policies. In the past years much attention has been given to the expected social benefits from deploying ICTs in different urban fields (transportation, education, public participation in planning, etc.) and to its potential to mitigate various current or emerging urban problems. The growing importance of ICTs in daily life, business activities, and governance prompts the need to consider ICTs more explicitly in urban policies. Alongside the expectation that the private sector will play a major role in the ICT field, the expected benefits from ICTs also encourage urban authorities to formulate proper public ICT policies.Against this background, various intriguing research questions arise. What are the urban policy‐makers’ expectations about ICTs? And how do they assess the future implications of ICTs for their city? A thorough analysis of these questions will provide a better understanding of the extent to which urban authorities are willing to invest in and to adopt a dedicated ICT policy.This study is focusing on the way urban decision‐makers perceive the opportunities of ICT policy. After a sketch of recent development and policy issues, a conceptual model is developed to map out the driving forces of urban ICT policies in cities in Europe. Next, by highlighting the importance of understanding the decision‐maker's “black box,” three crucial variables are identified within this box. In the remaining part of the paper these three variables will be operationalized by using a large survey comprising more than 200 European cities. By means of statistical multivariate methods (i.e., factor and cluster analysis), the decision‐makers were able to be characterized according to the way they perceive their city (the concept of “imaginable city”), their opinion about ICT, and the way they assess the relevance of ICT policies to their city. Next, a solid explanatory framework will be offered by using a log‐linear logit analysis to test the relationships between these three aspects.
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