Predicting and Optimizing Marketing Performance in Dynamic Markets

Autor(en)

Daniel Guhl, Friederike Paetz, Udo Wagner, Michel Wedel

Abstrakt

Our world is turbulent: ecological, social, political, technological, economic, and competitive business environments change constantly. Consumers have changing preferences, learn, build trust in brands, adopt new products, and are persuaded by advertising. Firms innovate and engage in and respond to competition. Exogenous events, such as changes in economic conditions and regulations, as well as human crises, also cause major shifts in markets. This special issue focuses on novel Marketing data and modern methodologies from different fields (e.g., Operations Research (OR), Statistics, Econometrics, and Computer Science), which help firms understand, utilize, and respond to market dynamics more efficiently. Here we propose a framework comprising analytical methods and data for dynamic markets that is useful for structuring research in this domain. Next, we summarize the history of the Marketing/OR interface. We highlight studies at the Marketing/OR interface from the last decade focusing specifically on dynamic markets and use our proposed framework to identify trends and gaps in the extant literature. After that, we present and summarize the papers of the current special issue and their contributions to the field against the backdrop of our framework and the trends in the literature. Finally, we conclude and discuss which future Marketing/OR research could tackle important issues in dynamic markets.

Organisation(en)

Institut für Marketing und International Business

Externe Organisation(en)

Humboldt-Universität zu Berlin, MODUL University Vienna, Technische Universität Clausthal, University of Maryland, College Park

Journal

OR Spectrum

Band

46

Seiten

1-27

Anzahl der Seiten

27

ISSN

0171-6468

DOI

https://doi.org/10.1007/s00291-024-00755-1

Publikationsdatum

02-2024

Peer-reviewed

Ja

ÖFOS 2012

502019 Marketing

Schlagwörter

ASJC Scopus Sachgebiete

Marketing

Link zum Portal

https://ucrisportal.univie.ac.at/de/publications/predicting-and-optimizing-marketing-performance-in-dynamic-markets(49d52ddc-db3d-4e9d-acb7-ad75beae0765).html