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Durham Research Online
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Multilevel marketing : optimizing marketing effectiveness for high-involvement goods in the automotive industry.

Niemand, T. and Kraus, S. and Mather, S. and Cuenca-Ballester, A.C. (2020) 'Multilevel marketing : optimizing marketing effectiveness for high-involvement goods in the automotive industry.', International entrepreneurship and management journal. .

Abstract

With a surge in communication channels increasing the complexity of today’s media landscape, companies face new challenges concerning the allocation of their advertising budget. As consumers become increasingly more autonomous in gathering information from the channels they deem most suitable, they encounter several touchpoints on their customer journey. Marketers struggle with the assessment of channel effectiveness. Despite a rise in research on the topic of attribution, findings and methodology vary greatly regarding variables and outcomes. The question of how to determine suitable attribution modeling that optimizes advertising effectiveness thus remains unanswered. This article aims at assessing which factors influence channel effectiveness in the context of high-involvement goods. Based on a unique dataset from a multinational car manufacturer, a Structural Vector Autoregressive model has been formulated revealing channel interactions, lagged effects of advertising and conversion funnel stages as being highly influential factors concerning channel effectiveness.

Item Type:Article
Full text:Publisher-imposed embargo
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1007/s11365-020-00669-8
Publisher statement:This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Date accepted:24 April 2020
Date deposited:26 April 2020
Date of first online publication:16 May 2020
Date first made open access:27 May 2020

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