'Going Public': The Mediatization of Decision-Making Processes

In most Western countries, the media are said to exert an increasing influence on the political game. This development, which has been described variably as a shift towards an 'audience democracy' (Manin 1995) or the 'mediatization of politics' (Mazzoleni and Schulz 1999), emphasizes the increasing importance of the media for political actors and political decision-making. In such a context, political actors need to communicate with both the media and the public in order to gain support for their policy plans and to influence decision-making. The media were noticeably absent from Kriesi's (1980) in-depth analysis of political decision-making in Switzerland. This suggests that in the early 1970s, the media did not matter or mattered far less than they do today.

Looking beneath the Surface: Differences in Decision-Making Structures across Processes

The previous chapter presented the overall decision-making structure in Swiss politics at the beginning of the 21st century. This provides us with a general picture and allows for a comparison over time with the decision-making structure in the 1970s. However, the analysis of the overall decision-making structure potentially neglects important differences between policy domains (Atkinson and Coleman 1989; Knoke et al. 1996; Kriesi et al. 2006a; Sabatier 1987). Policy issues vary across policy domains, as do the political actors involved. In addition, actors may hold different policy preferences from one policy domain to the next, and they may also collaborate with other partners depending on the policy domain at stake. Examining differences between policy domains is particularly appropriate in Switzerland. Because no fixed coalitions of government and opposition exist, actors create different coalitions in each policy domain (Linder and Schwarz 2008). Whereas important parts of the institutional setting are similar across policy domains, decision-making structures might still vary. As was the case with the cross-time analysis conducted in the two previous chapters, a stability of 'rules-in-form' might hide important variations in 'rules-in-use' also across different policy domains.

Vector Error-Correction Models in a consumer packaged goods category forecasting decision support system

A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.