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Aggregate effects of advertising decisions: a complex systems look at search engine advertising via an experimental study

Published 4 Mar 2022 in cs.AI and cs.CY | (2203.02200v1)

Abstract: Purpose: We model group advertising decisions, which are the collective decisions of every single advertiser within the set of advertisers who are competing in the same auction or vertical industry, and examine resulting market outcomes, via a proposed simulation framework named EXP-SEA (Experimental Platform for Search Engine Advertising) supporting experimental studies of collective behaviors in the context of search engine advertising. Design: We implement the EXP-SEA to validate the proposed simulation framework, also conduct three experimental studies on the aggregate impact of electronic word-of-mouth, the competition level, and strategic bidding behaviors. EXP-SEA supports heterogeneous participants, various auction mechanisms, and also ranking and pricing algorithms. Findings: Findings from our three experiments show that (a) both the market profit and advertising indexes such as number of impressions and number of clicks are larger when the eWOM effect presents, meaning social media certainly has some effect on search engine advertising outcomes, (b) the competition level has a monotonic increasing effect on the market performance, thus search engines have an incentive to encourage both the eWOM among search users and competition among advertisers, and (c) given the market-level effect of the percentage of advertisers employing a dynamic greedy bidding strategy, there is a cut-off point for strategic bidding behaviors. Originality: This is one of the first research works to explore collective group decisions and resulting phenomena in the complex context of search engine advertising via developing and validating a simulation framework that supports assessments of various advertising strategies and estimations of the impact of mechanisms on the search market.

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