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  • Author or Editor: András Nemeslaki x
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Our basic storyline is how the business and economics higher education landscape has changed with the introduction of the Bologna programs. We borrowed the fashionable long tail concept from e-business, and used it for modeling the new landscape of internationalization of universities. Internationalization, mobility, and the appearance of the internet generation at the gates of our universities in our opinion has brought us to a new e-era which, appropriately to our web analogies we might as well call Education 2.0.In our paper first we show the characteristics of the long tail model of the Bologna-based European higher education and potential messages for strategy making in this environment. We illustrate that benchmarking university strategies situated in the head of the long tail model will not always provide strategic guidance for universities sitting in the tail. For underlining some key concerns in the Hungarian niche, we used Corvinus University as a case study to illustrate some untapped challenges of the Hungarian Bologna reform. We explored three areas which are crucial elements of the “tail” strategy in our opinion: a) the influence of state regulation, b) social situations and impacts and c) internal university capabilities.

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In economic and social sciences it is crucial to test theoretical models against large and reliable databases. The general research challenge is to build up a well-structured database that suits the given research question well and that is cost efficient at the same time. In this paper we focus on crawler programs that proved to be an effective tool for data base building in very different problem settings. We present three structurally different research models where crawler programs can be applied successfully: exploration, classification and time series analysis. In the case of exploration we present findings about the Hungarian web agency industry where no previous statistical data was available about their operations. For classification we show how the top visited Hungarian web domains can be divided into predefined categories of e-business models. In the third research we used a crawler to gather the values of specific pre-defined records containing ticket prices of low cost airlines from one single site. Based on the experiences we highlight some conceptual conclusions and opportunities for crawler based research in e-business.

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