Andreas Lanz

Andreas Lanz holds a Ph.D. in Business Administration from the University of Mannheim. His research projects lie primarily in the intersection between marketing, economics, and information systems, and are geared towards helping managers make better-informed decisions utilizing granular data from online platforms, particularly user-generated content networks. Recently, he published a paper on the effectiveness of influencer marketing on such networks in the Journal of Marketing Research. Given his expertise, Andreas teaches Business Analytics in the MBA as well as Grande École Program and serves on various corporate boards.

EDUCATION

• 2017 Ph.D. in Business Administration, University of Mannheim - Germany
• 2013 M.A. in Business Administration, University of Zurich - Switzerland

ACADEMIC APPOINTMENTS

Academic responsabilities at HEC

• 2020- Member of GREGHEC, the joint research laboratory CNRS-HEC Paris HEC Paris
• 2019- Assistant Professor, Marketing HEC Paris

External Academic Responsabilities

• 2014-2019 Visiting ResearcherInterdisciplinary Center (IDC), Herzliya
• 2013-2017 Ph.D. CandidateUniversity of Mannheim

AWARDS & HONORS

• 2020 Rigour Relevance Research Award from the Swiss Academy of Marketing Science
• 2018 Runner-Up in the Doctoral Dissertation Competition of the European Marketing Academy (EMAC) / Sheth Foundation

RECENT PUBLICATIONS

SCIENTIFIC ARTICLES

Social Capital Accumulation Through Social Media Networks: Evidence from a Randomized Field Experiment and Individual-Level Panel Data MIS Quarterly, Forthcoming, (in coll. with Michael Weiler, Simon Stolz, Christian Schlereth, Oliver Hinz)

Climb or Jump: Status-Based Seeding in User-Generated Content Networks, Journal of Marketing Research, June 2019, vol. 56, n° 3, pp 361–378, (in coll. with Jacob GOLDENBERG, Daniel SHAPIRA, Florian STAHL)

WORKING PAPERS

Helpful or Harmful? Negative Behavior Toward Newcomers and Welfare in Online Communities Cahier de Recherche du Groupe HEC , 2021

Adaptive Grids for the Estimation of Dynamic Models Cahier de Recherche du Groupe HEC , 2020

'Small Data': Efficient Inference with Occasionally Observed States Cahier de Recherche du Groupe HEC , 2020