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Journal of Marketing News, June 2022

Introduction

A Webinar on Web Scraping and more

POSTING TYPE: Journal News

Author: Christine Moorman


the Journal of Marketing, Volume 86, Issue 4 – July


Isabel Eichinger, Martin Schreier, and Stijn M.J. van Osselaer


Pankhuri Malhotra and Siddhartha Bhattacharyya


Yi Yang, Kunpeng Zhang, and P.K. Kannan


Lingrui Zhou, Katherine M. Du, and Keisha M. Cutright


Abhi Bhattacharya, Neil A. Morgan, and Lopo L. Rego


Thomas P. Scholdra, Julian R.K. Wichmann, Maik Eisenbeiss, and Werner J. Reinartz


Vilma Todri, Panagiotis (Panos) Adamopoulos, and Michelle Andrews


Stephan Ludwig, Dennis Herhausen, Dhruv Grewal, Liliana Bove, Sabine Benoit, Ko de Ruyter, and Peter Urwin

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Recently Accepted Papers Forthcoming in the Journal of Marketing: for a full list


Maren Becker, Thomas P. Scholdra, Manuel Berkmann, and Werner J. Reinartz


Fine F. Leung, Flora F. Gu, Yiwei Li, Jonathan Z. Zhang, and Robert W. Palmatier


Johannes Boegershausen, Hannes Datta, Abhishek Borah, and Andrew T. Stephen


Giuseppe Musarra, Matthew J. Robson, and Constantine S. Katsikeas


Jinjie Chen, Alison Jing Xu, Maria A. Rodas, and Xuefeng Liu

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Register to attend the next Journal of Marketing Webinar: June 23, 2022 from 12-1PM Eastern

Fields of Gold: Scraping Web Data for Marketing Insights

Marketing scholars increasingly use web scraping and Application Programming Interfaces (APIs) to collect data from the internet. Yet, despite the widespread use of such web data, the idiosyncratic and sometimes insidious challenges in its collection have received limited attention. How can researchers ensure that the datasets generated via web scraping and APIs are valid? While existing resources emphasize technical details of extracting web data, the authors, (Erasmus University), (Tilburg University,  (INSEAD), and (University of Oxford), propose a novel methodological framework focused on enhancing its validity. In particular, the framework highlights how addressing validity concerns requires the joint consideration of idiosyncratic technical and legal/ethical questions along the three stages of collecting web data: selecting data sources, designing the data collection, and extracting the data.

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