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    <title>Vroomen, B.L.K.</title>
    <link>http://repub.eur.nl/res/aut/6145/</link>
    <description>List of Publications</description>
    <language>en</language>
    <image>
      <url>http://repub.eur.nl/static-eur/img/logo.png</url>
      <title>RePub, Erasmus University Rotterdam</title>
      <link>http://repub.eur.nl</link>
    </image>
    <item>
      <title>Selecting Profitable Customers for Complex Services on the Internet (Article)</title>
      <link>http://repub.eur.nl/res/pub/13792/</link>
      <pubDate>2008-01-01T00:00:00Z</pubDate>
      <description>In contrast to books and compact discs, the number of complex services offered on the Internet is still small. The decision-making process for complex services is different because it has an additional intermediate step of "indication of interest." The Web site is (a) visited and searched for information; subsequently, (b) a request for the service is made, which may lead to (c) a purchase. The authors acquired a unique data set from an online Dutch financial service provider, which offers services such as mortgage loans and insurance on the Internet on behalf of financial institutions. They also obtained information on whether the request for the service resulted in a purchase. The authors used the available information to predict the purchase using a latent class probit model. A direct managerial application of this model is the ability to identify and select profitable applicants, resulting in significant profit improvements for the company.</description>
    </item> <item>
      <title>The Effects of the Internet, Recommendation Quality and Decision Strategies on Consumer Choice (Doctoral Thesis)</title>
      <link>http://repub.eur.nl/res/pub/8067/</link>
      <pubDate>2006-11-09T00:00:00Z</pubDate>
      <description>Bj¨orn Leon Kristian Vroomen (1976) obtained his masters’ degree in econometrics in 2000 from the Erasmus University Rotterdam. In that same year he joined ERIM as a Ph.D.-candidate in order to carry out his doctoral research on the subject of consumer
decision making in relation to the Internet. His research resulted in several publications in international journals. Bjorn is affiliated with the CPB Netherlands Bureau for Economic
Policy Analysis as of September 2004.</description>
    </item> <item>
      <title>Estimating Confidence Bounds for Advertising Effect Duration Intervals (Article)</title>
      <link>http://repub.eur.nl/res/pub/13388/</link>
      <pubDate>2006-01-01T00:00:00Z</pubDate>
      <description>Duration intervals measure the dynamic impact of advertising on sales. To be more precise, the p % duration interval measures the time lag between the advertising impulse and the moment that p % of its effect has decayed. In this paper, we derive an expression for the duration interval for a dynamic model linking sales to advertising, and most important, we put forward a method to provide confidence bounds around the estimated duration interval. The method is illustrated in two examples.</description>
    </item> <item>
      <title>Selecting Profitable Customers for Complex Services on the Internet (Article)</title>
      <link>http://repub.eur.nl/res/pub/11490/</link>
      <pubDate>2005-01-01T00:00:00Z</pubDate>
      <description>In contrast to books and compact discs, the number of complex services offered on the Internet is still small. The decision-making process for complex services is different because it has an additional intermediate step of "indication of interest." The Web site is (a) visited and searched for information; subsequently, (b) a request for the service is made, which may lead to (c) a purchase. The authors acquired a unique data set from an online Dutch financial service provider, which offers services such as mortgage loans and insurance on the Internet on behalf of financial institutions. They also obtained information on whether the request for the service resulted in a purchase. The authors used the available information to predict the purchase using a latent class probit model. A direct managerial application of this model is the ability to identify and select profitable applicants, resulting in significant profit improvements for the company.</description>
    </item> <item>
      <title>Modeling consideration sets and brand choice using artificial neural networks (Article)</title>
      <link>http://repub.eur.nl/res/pub/13804/</link>
      <pubDate>2004-04-01T00:00:00Z</pubDate>
      <description>Brand choice can be viewed as a two-step process. Households first construct a consideration set, which does not necessarily include all available brands, and then make a final choice from this set. In this paper we put forward an econometric model for this two-step process, where we take into account that consideration sets usually are not observed. Our model is an artificial neural network, where the consideration set corresponds with the hidden layer of the network. We discuss representation, parameter estimation and inference. We illustrate our model for the choice between six detergent brands and show that the model improves upon one-step models, in terms of fit and out-of-sample forecasting.</description>
    </item> <item>
      <title>Forecasting Unemployment using an Autoregression with Censored Latent Effects Parameters (Article)</title>
      <link>http://repub.eur.nl/res/pub/2168/</link>
      <pubDate>2004-04-01T00:00:00Z</pubDate>
      <description>Monthly observed unemployment typically displays explosive behavior in recessionary periods, while there seems to be stationary behavior in expansions. Allowing parameters in an autoregression to vary across regimes, and hence over time, can capture this feature. In this paper, we put forward a new autoregressive time series model with time-varying parameters, where this variation depends on a linear indicator variable. When the value of this variable exceeds a stochastic threshold level, the parameters change. We discuss representation, estimation and interpretation of the model. Also, we analyze its forecasting performance for unemployment series of three G-7 countries, and we compare it with various related models.</description>
    </item> <item>
      <title>Purschasing complex services on the Internet; An analysis of mortgage loan acquisitions (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/992/</link>
      <pubDate>2003-10-27T00:00:00Z</pubDate>
      <description>In contrast to, for example, books and compact discs, the number of complex services offered on the Internet is still small. A good example of such a service concerns mortgage loans. The decision-making process differs for complex services in that they have an extra intermediate step of `indication of interest'. The web site is (1) visited and searched for information, subsequently (2) a request for the service is made, which may lead to (3) a purchase. This difference in the buying process and the complexity of the decision-making process, requires afurther investigation on purchasing complex services on the Internet. We therefore focus on online purchases of complex services, paying special attention to the determinants of a purchase of such services. To this end, we acquired a unique data set from an online Dutch financial service provider, which offers services like mortgage loans and insurances on the Internet. This data contains, besides clickstream data, also data on user-specific information like demographics. We also obtained information on whether the request for the service re-sulted in a purchase. Search behavior, product familiarity and trust appear to be useful determinants of purchase of complex services. Direct managerial applications of our model include the ability to identify customer characteristics of successful applicants, and subsequently the selection of customers.</description>
    </item> <item>
      <title>Estimating duration intervals (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/331/</link>
      <pubDate>2003-04-10T00:00:00Z</pubDate>
      <description>Duration intervals measure the dynamic impact of advertising on sales. More precise, the p per cent duration interval measures the time lag between the advertising impulse and the moment that p per cent of its effect has decayed. In this paper, we derive an expression for the duration interval for a general dynamic model linking sales to advertising. Additionally, and this is themain novelty of the paper, we put forward a method to provide confidence bounds around the estimated duration interval. An illustration to real-life data emphasizes its usefulness.</description>
    </item> <item>
      <title>Modeling Consideration Sets and Brand Choice Using Artificial Neural Networks (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/79/</link>
      <pubDate>2001-03-20T00:00:00Z</pubDate>
      <description>The concept of consideration sets makes brand choice a two-step process. House-holds first construct a consideration set which not necessarily includes all available brands and conditional on this set they make a final choice. In this paper we put forward a parametric econometric model for this two-step process, where we take into account that consideration sets usually are not observed. It turns out that our model is an artificial neural network, where the consideration set corresponds with the hidden layer. We discuss representation, parameter estimation and inference.
We illustrate our model for the choice between six detergent brands and show that the model improves upon a one-step multinomial logit model, in terms of fit and out-of-sample forecasting.</description>
    </item>
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