Investigating the Promotional Effect of Green Signals in Sponsored Search Advertising Using Bayesian Parameter Estimation
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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Information Technology in Environmental Engineering: Selected Contributions to the Sixth International Conference on Information Technologies in Environmental Engineering (ITEE2013). Springer Verlag, 2014. S. 25-37 (Environmental Science and Engineering).
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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TY - CHAP
T1 - Investigating the Promotional Effect of Green Signals in Sponsored Search Advertising Using Bayesian Parameter Estimation
AU - Blask, Tobias
N1 - Conference code: 6
PY - 2014
Y1 - 2014
N2 - Over the last years we have observed a remarkable shift of media spendings from offline brand building activities to online performance advertising as well as a noticeable increase in “green marketing” efforts and sustainability communication by companies of various branches. In this paper we bring these two research streams together. 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 from a European e-commerce retailer, apply a Bayesian parameter estimation to compare the two groups, and discuss the implications of the results.
AB - Over the last years we have observed a remarkable shift of media spendings from offline brand building activities to online performance advertising as well as a noticeable increase in “green marketing” efforts and sustainability communication by companies of various branches. In this paper we bring these two research streams together. 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 from a European e-commerce retailer, apply a Bayesian parameter estimation to compare the two groups, and discuss the implications of the results.
KW - Business informatics
KW - Search Engine
KW - Null Hypothesis Significance Testing
KW - Reliable Delivery
KW - Green Marketing
KW - Position Bias
U2 - 10.1007/978-3-642-36011-4_3
DO - 10.1007/978-3-642-36011-4_3
M3 - Article in conference proceedings
SN - 978-3-642-36010-7
T3 - Environmental Science and Engineering
SP - 25
EP - 37
BT - Information Technology in Environmental Engineering
PB - Springer Verlag
T2 - 6th International Conference on Information Technologies in Environmental Engineering - ITEE2013
Y2 - 1 July 2013 through 12 July 2013
ER -