The Market for Insurance Intermediation in Germany

Part of the Contributions to Economics book series (CE)


Service Quality Coefficient Estimate Information Quality Insurance Product Customer Segment 
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  1. 52.
    In the marketing literature it is assumed that the higher the consumers’ perceived service attitude is, the lower the gap between consumers’ expectations and their perception of actual performance. See Parasuraman, Zeithaml and Berry (1988); Zeithaml and Bitner (2003).Google Scholar
  2. 53.
    In contrast to that, Howe, Hoffman and Hardigree (1994) find that top producing insurance agents show a higher level of unethical behavioral intent. They hypothesize that this “behavior is... reinforced by the greater levels of sales commissions resulting from higher sales levels” (Howe, Hoffmann and Hardigree 1994, 504). However, they do not explicitly test for the impact of commission on behavioral intent.Google Scholar
  3. 54.
    Chidambaran, Pugel and Saunders (1997) show that the existence of different distribution systems positively influences competition in the US propertyliability insurance market. They argue that consequently inefficient distribution systems can survive, if there are barriers to mobility between insurance lines with distribution systems of different efficiency properties.Google Scholar
  4. 55.
    This seems to hold true also for the Spanish insurance market, see Azofra-Palenzuela, Castrillo-Lara and Vallelado (2002).Google Scholar
  5. 56.
    For an empirical analysis of building long-term relationships through mutual commitment between insurance companies and independent agents, see Anderson, Ross and Weitz (1998).Google Scholar
  6. 61.
    See also Etgar (1977).Google Scholar
  7. 62.
    With the implementation of the EU Directive on Insurance Mediation there will be stricter regulations also for German insurance intermediaries, see Schönleiter (2005).Google Scholar
  8. 64.
    Although factor analysis assumes interval data, Jaccard and Wan (1996, 4) summarize in a recent review of the literature on this topic that with ordinal Likert scale items “for many statistical tests, rather severe departures (from intervalness) do not seem to affect Type I and Type II errors dramatically.”Google Scholar
  9. 65.
    For descriptive statistics, see in detail Eckardt (2002b; 2002c).Google Scholar
  10. 66.
    For the assumptions of the linear OLS regression, see Greene (2000, 210–264). The estimations are corrected for heteroscedasticity where necessary.Google Scholar
  11. 67.
    Moreover, compared to other estimation methods OLS is less sensitive and thus avoids some of the problems of more sophisticated methods. See Maddala (1992, 383–387); Intriligator, Bodkin and Hsiao (1996, 353–356); Kennedy (1998, 157–182); Studenmund (2006, 474–510).Google Scholar

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© Physica-Verlag Heidelberg 2007

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