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Slides from my presentation at Better Software 2015. Code generates business value when it runs not when we write it. We must know how our code perform at runtime, how it interacts with the infrastructure, how our customers are using it to give them the opportunity to give use more money. Set SLAs, measure them, reach them and move forward to increase the business value of our software.
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Slides that correspond to the paper: Schulz, Fabian / Schlereth, Christian / Skiera, Bernd / Mazar, Nina (2015), "Advance Payment Systems: Paying Too Much Today and Being Satisfied Tomorrow", International Journal of Research in Marketing, Vol. 32, Issue 3, forthcoming. Abstract: Advance payment systems represent a pricing innovation, in which companies predict customers' future consumption for the following year and then bill a series of monthly, uniform advance payments. Any difference between predicted and actual consumption gets settled at the end of the year with a refund or extra payment. Companies thus gain earlier access to funds and lower risk of customer defaults; customers benefit from predictable monthly payments. However, customers' reactions to a refund or extra payment sequence in an advance payment system remain unclear. Three theoretical lenses offer predictions about customers' advance payment system preferences: prospect theory, with a focus on silver lining and hedonic editing principles; mental accounting; and the value of sequences. Using three empirical studies with survey and billing data of more than 20,000 customers to examine their reactions to refunds and extra payments, this paper reveals that receiving a refund reduces customers' price awareness, increases their recommendation likelihood, and reduces churn and tariff switching, as long as the refund is not too high. The findings illustrate both the consequences and the boundary conditions of the silver lining principle with large-scale field studies.
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Hier sind Folien, die ein wesentliches Ergebnis des folgenden Beitrags (in deutscher Sprache) zusammenfassen: Skiera, Bernd / Hinz, Oliver / Spann, Martin (2015), "Social Media and Academic Performance: Does Facebook Activity Relate to Good Grades?", Schmalenbach Business Review, Vol. 67, Issue 1, 54-72 We analyze how Facebook use and students’ social network positions within it relate to their academic performance. We use a unique data set obtained from a survey of students’ perceptions, actual Facebook connections to measure social network positions, and objective grades provided by the university registrar to measure academic performance. We find that Facebook activities during class relate negatively to academic performance, that students located in densely connected subnetworks earn better grades, and that in contrast to female students, male students benefit from a general use of Facebook, particularly if they are highly connected.
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Although structural modeling as a means to improve pricing decisions often appears in prestigious academic journals, its consideration in pricing textbooks remains rather limited, and knowledge about its benefits and limitations in comparison to reduced-form models is scarce among “structural nonexperts”. This presentation outlines for these “structural nonexperts” which different abilities structural and reducedform models have to improve pricing decisions. Therefore, it uses a popular textbook example that fails to consider the abilities of both models, which are the abilities to capture the effects of consumers’ responses and changes in cost structure on prices. It outlines that the major advantages of structural models are the ability to capture competitors’ reactions and the description of new market equilibriums, which come at the costs of assumptions that usually prevent structural models to further improve prices. The beauty of the simple example provided is that it enables nontechnical readers to easily understand the major differences between structural and reduced-form models.
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These slides that describe the content of the paper: Hinz, Oliver / Skiera, Bernd / Barrot, Christian / Becker, Jan (2011), "An Empirical Comparison of Seeding Strategies for Viral Marketing", Journal of Marketing, 75 (November), 55-71. Seeding strategies have strong influences on the success of viral marketing campaigns, but previous studies using computer simulations and analytical models have produced conflicting recommendations about the optimal seeding strategy. This study compares four seeding strategies in two complementary small-scale field experiments, as well as in one real-life viral marketing campaign involving more than 200,000 customers of a mobile phone service provider. The empirical results show that the best seeding strategies can be up to eight times more successful than other seeding strategies. Seeding to well-connected people is the most successful approach because these attractive seeding points are more likely to participate in viral marketing campaigns. This finding contradicts a common assumption in other studies. Well-connected people also actively use their greater reach but do not have more influence on their peers than do less well-connected people.
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Sollen Studenten Facebook während des Unterrichts benutzen? Natürlich nicht u...
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Bernd Skiera
Although structural modeling as a means to improve pricing decisions often appears in prestigious academic journals, its consideration in pricing textbooks remains rather limited, and knowledge about its benefits and limitations in comparison to reduced-form models is scarce among “structural nonexperts”. This presentation outlines for these “structural nonexperts” which different abilities structural and reducedform models have to improve pricing decisions. Therefore, it uses a popular textbook example that fails to consider the abilities of both models, which are the abilities to capture the effects of consumers’ responses and changes in cost structure on prices. It outlines that the major advantages of structural models are the ability to capture competitors’ reactions and the description of new market equilibriums, which come at the costs of assumptions that usually prevent structural models to further improve prices. The beauty of the simple example provided is that it enables nontechnical readers to easily understand the major differences between structural and reduced-form models.
Optimal Pricing: Understanding Differences between Structural Models and Redu...
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Bernd Skiera
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Bernd Skiera
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Skyline
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Gerly Treial, Alina Frolova, Nelly Naumova HM32
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