Bayesian Parameter Estimation in Green Business Process Management: A Case Study in Online-Advertising

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

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Companies take their responsibilities for a sustainable planet more and more seriously. For online-retail businesses a significant share of all C02 emissions is generated by delivering goods to their clients. Now various companies are implementing a greener logistic chain into their business processes. What is a central question for these performance driven companies in this context is whether it pays to invest in additional costs for carbon neutral delivery and if the customers appreciate these steps and prefer retailers that behave in this manner. We develop and perform a non reactive A/B-test that enables us to evaluate the influence of sustainability information on the customers decision to buy a product by clicking on an ad on a search engine results page (SERP). We analyze campaign performance data generated from a European e-commerce retailer, apply a Bayesian parameter estimation to compare the two groups, and demonstrate the advantages of the given Bayesian approach in comparison to the application of Null Hypothesis Significance Testing (NHST).

OriginalspracheEnglisch
TitelINFORMATIK 2013 - Informatik angepasst an Mensch, Organisation und Umwelt
HerausgeberMatthias Hornbach
Anzahl der Seiten12
ErscheinungsortBonn
VerlagGesellschaft für Informatik e.V.
Datum2013
Seiten852-863
ISBN (elektronisch)978-3-88579-614-5
PublikationsstatusErschienen - 2013
VeranstaltungInformatik 2013 - Koblenz, Deutschland
Dauer: 16.09.201320.09.2013

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1 CD-ROM. ; 235 mm x 155 mm, 52 g

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