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AbstractWe present and expand existing theories about why individuals may assess positive outcomes differently from negative outcomes in intertemporal choices. All of our theories—based on utility or cost considerations – predict a conventional magnitude effect for positive outcomes, that is, a negative relation between outcome size and subjective discount rates. For negative outcomes, however, implications are different for utility‐ and cost‐based approaches. We argue that the relevance of utility‐based aspects is strengthened in a money frame, leading to a conventional magnitude effect even for negative outcomes, whereas cost‐based considerations gain in importance in an interest rate frame, implying, in contrast, a "reverse" magnitude effect, that is, higher discount rates for (absolutely) higher outcome size. A web‐based experiment with 676 participants confirms our theoretical findings: the conventional magnitude effect prevails for positive outcomes in the money and the interest rate frame and negative outcomes in the money frame. However, there is a reverse magnitude effect for negative outcomes in the interest rate frame. Our results might help to better understand prevailing magnitude effects in practical applications and might also be apt to derive suggestions for better designing of intertemporal decision problems.

We evaluate the claim that individuals exhibit a magnitude effect in their discounting behaviour, where higher discount rates are inferred from choices made with lower principals, all else being equal. If the magnitude effect is quantitatively significant, it is not appropriate to use one discount rate that is independent of the scale of the project for cost–benefit analysis and capital budgeting. Using data from a field experiment in Denmark, we find statistically significant evidence of a magnitude effect that is much smaller than is claimed. This evidence surfaces only if one controls for unobserved individual heterogeneity in the population.

In his research, Sören Köcher provides valuable insights on the paradoxical effects of the magnitude of a loyalty program medium--i.e. the sheer number of points, miles, or stamps credited for every purchase and required for reward redemption--on the central consumer decisions in loyalty program memberships. In sum, the results of twelve empirical studies reveal that high magnitude currencies improve the attractiveness of medium collection but entail reluctant medium spending behavior. These findings provide important implications for a more efficient usage of loyalty programs in business practices. In addition, this dissertation discovers a violation of one of the most fundamental assumptions of rational choice theory and thus contributes to a better understanding of when and why people deviate from rational decision-making. Contents Conceptual background and literature review on loyalty programs Rational and descriptive theories of choice Empirical examination of medium magnitude effects on the central consumer decision fields in loyalty program memberships Target Groups Academics and students in the fields of marketing, consumer behavior, and customer relationship management Practitioners concerned with designing and managing loyalty programs The Author Dr. Sören Köcher received his doctorate at the Department of Marketing, TU Dortmund University under the guidance of Prof. Dr. Hartmut H. Holzmüller.

How the magnitude of an experimental effect may be measured has been a matter of concern for at least two decades. The phenomenon of effect size is still not well under stood, and it cannot be inferred from statistical significance. In recent years various ways of assessing the amount of variance accounted for have been proposed as measures of magnitude of effect. Other writers have proposed rulesfor standardizing effect size, with the interpretations of the measures depending largely on intuitions buttressed by some further general empirical norms. All the methods of assessing effect size have serious flaws that limit their usefulness. The various statistical procedures for estimating variance accounted for are based on different statistical models and can produce rather sharply differing results, depending on the model employed. All the methods suffer from the limitation that they reflect to too great an extent the particular characteristics of the study being reported and hence have limited generalizability.