Posted by: Madhu Viswanathan

Dear colleagues,

This message is about videos and possible webinars on Measurement Error and Research Design.��I authored a book of the same title about two decades ago –��a most minute and intuitive dissection of measurement error and what it means for research design.����I also had the privilege of teaching a PhD seminar on this topic for several decades.��During the pandemic, I offered online workshops that aimed to enable deep understanding of measurement error and how it translates to the measurement of one thing and the measurement (or manipulation) of many things (i.e., the method). The main takeaways are as follows and relevant for researchers who use secondary or primary data.

• Deep understanding of measurement error at an intuitive (over and above statistical) level
• Confidence and ability to design measures and methods while minimizing measurement error
• Understanding the relationship between measurement and research design and translating it into conducting empirical research

Videos and materials from��online workshops��are now available on a��.

Measurement Book��n

Furthermore,��Sage has produced additional videos where I elaborate on the various topics,��which are available through institutional as well as trial subscriptions, linked below.

Measurement Error Sage Videos

Research Design Sage Videos

We seek your interest in measurement error and research design videos and possible webinars��through a brief survey (5 minutes or less):

.

Based on responses to this survey, I can offer webinars. Additionally, if within my bandwidth,��I will be honored to visit your classes virtually to provide some interaction and Q and A if you think it will be worthwhile. This is like much of what we do – a labor of love – and if my experience can be of some use, I will be happy to be there. However, I ask that the material that is viewable or readable be reviewed beforehand to make the synchronous interaction most productive. Additional background material is at the end of this message.

I will also maintain a website at��that will be functional soon.

I request your help in publicizing this communication to audiences in the social sciences who may be interested.

Sincerely,

Madhu Viswanathan

Background materials

Book

Viswanathan, Madhubalan (2005),��Measurement Error and Research Design, Sage��Publications.

Edited Book

Tucker, Eric, Geoffrey Walford, and Madhubalan Viswanathan (2010),��The Sage��Handbook of��Measurement,��Sage Publications.

Articles

Viswanathan, Madhubalan (2022), “Measurement Error and Research Design: Some�� Practical Issues In Conducting Research,”�������Ի�����(����.)��Measurement in Marketing (Review of Marketing Research, Vol. 19), Emerald Publishing��Limited, Bingley, pp.��75-94��https://doi.org/10.1108/S1548-643520220000019004

Viswanathan, Madhubalan (2008), “Measurement Error in Experimental Designs in Consumer Psychology, “Handbook of Consumer Psychology,��Editors, Haugtvedt, Herr, and Kardes, Erlbaum, 1133-1159.

Viswanathan, Madhubalan (2010), “Understanding the Intangibles of Measurement in the��Social Sciences,”��Sage��Handbook of Measurement, Editors, Eric Tucker, Madhubalan Viswanathan,��and Geoffrey Walford, 285-311, Sage.

Tucker, Eric, Madhubalan Viswanathan, and Geoffrey Walford (2010), Introduction: How��Social Scientists Generate, Modify, and Validate Indicators and Scales,��The Sage��Handbook of Measurement, Editors, Eric Tucker, Madhubalan Viswanathan, and Geoffrey��Walford, 1-5, Sage.

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Posted by: Alexander Edeling

PhDreams Episode 6: Data-Driven Academic Research with Professors Abhishek Borah and Davide Proserpio

In the sixth episode of PhDreams – The Podcast for Academic Careers in Business and Economics, the hosts from the University of Liverpool and from KU Leuven present an episode about data-driven academic research, together with theirs guests Professor from INSEAD and Professor from the University of Southern California.

Both Abhi and Davide have used incredible data in their research: Topics range from recalls in the automotive industry to improvised marketing interventions on social media (Abhi) to the impact of Airbnb on the hotel industry to fake reviews on Amazon (Davide). In this episode, they share their expertise and experiences honestly and transparently, providing young researchers (and, in fact, anyone working with data) with invaluable advice.

Tune in to learn
– that theory-first (instead of empirics-first) is often difficult, just because data is not available or very hard to get
– why one should not be discouraged by the seemingly strict scraping rules imposed by websites and journals
– about the pros and cons of multi-method papers

PLUS: Together with Abhi and Davide, the hosts answer a listener question about how to avoid wasting time on poor-quality data.

The episode is available on and .

Want to be part of the next episode? Send your listener question as a voice recording to phdreams.podcast@gmail.com!

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Posted by: ELMAR Moderator

Useful Tools for Data Science in R led by SMCS (Université Catholique de Louvain) is now available as an on-demand streaming seminar. This seminar on Useful Tools for Data Science in R introduces powerful techniques using R, Github, Copilot, and Visual Studio Code to enhance research efficiency and reproducibility. Business and organization studies researchers can leverage these skills to streamline their quantitative data analysis, manage complex datasets, and ensure robust version control for collaborative projects and model development. Adopting these tools will enable researchers to accelerate their analytical workflows, improve the transparency of their methodologies, and ultimately strengthen the impact and rigor of their empirical contributions to the field.

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Posted by: Andrew Mitrak

Title: The CMO Game

Link:

Description: An educational game that simulates the tradeoffs involved in bringing a product to market, teaching players about product positioning, marketing channels, brand vs. performance marketing, pressures from sales and finance, and budget management.

Players have 12 months and a $5M budget to launch a product and climb from Director of Marketing to the C-Suite. But your CEO has aggressive goals, and if you fail to meet them, it’s game over.

The CMO Game is 100% free to play and to share with students. No login is required, and there are no in-app purchases. It works in web browsers on both mobile and desktop. A full game takes approximately 10-20 minutes to complete.

Quotes about The CMO Game:��

, CMO of Sur La Table: “Mitrak’s game sparks the right conversations by not giving you marketing answers, but better questions to ask… which is where real learning starts.”

, a marketing executive and Senior Affiliate Instructor at The University of Washington, plans to use The CMO Game in his Advanced Marketing course, calling it a “great way to break the ice in the first class.”

Contact: Andrew Mitrak hello@marketinghistory.org

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Posted by: Christian Geiser

Dear Colleagues,

I’m excited to announce my new on-demand course on No-Code Structural Equation Modeling.

The course is now open for pre-registration at a discounted price until February 27, 2026. For further information, please visit:

Feel free to share this information with anyone who might be interested.

Best,

Christian Geiser

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Posted by: Rebecca Hamilton

Episode 25 of “How I Wrote This” – Persevering from “Idea Nugget” to Publication with Yuechen Wu, Jared Watson, and Ali Faraji-Rad

A single demographic statistic about car leasing. That’s all it took to spark a fascinating research journey into how the perceived stability of our romantic relationships shape the products we choose to rent versus own. In , ��joins JMR Co-Editor to reveal the story behind “.” From that initial nugget of curiosity to navigating the challenges of the review process, Yuechen and co-authors and share how persistence—and friendship—can transform a curious observation into groundbreaking consumer research.

Listen on , , or wherever you get your podcasts.

Update on ���Ѹ�’s Research Transparency Policy and Data Sharing

���Ѹ�’s , implemented when our term began on July 1, 2023, requires that upon conditional acceptance of their paper, authors provide access to their data, code and methodological materials to the Coeditors and Data Editor via ���Ѹ�’s . To date, our Data Editor, Francesco Zanibellato, has worked with the authors of 91 papers to verify their data and materials prior to final acceptance. This has been a collaborative process, with both authors and the journal benefitting from the validation of results and correction of errors before articles are published.

Although we encourage authors of accepted papers to make their methodological materials and data accessible to all readers, this is not required by the policy. ���������t 45% of JMR articles use confidential or proprietary data, a proportion that has not changed before (45%) vs. after (48%) the policy. After the implementation of ���Ѹ�’s Research Transparency Policy, the authors of 27% of papers reviewed by our Data Editor (starting with Volume 61 in 2024) have elected to share their data publicly, via ���Ѹ�’s Dataverse or other repositories, compared with 19% in Volume 60, 11% in Volume 59, and 7% in Volume 58.

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Posted by: Rafaela Canova Davide

𝗛𝗼𝘁 𝗢𝗳𝗳 𝘁𝗵𝗲 𝗣𝗿𝗲𝘀𝘀: 𝗗𝗼𝗰𝗦𝗜𝗚 𝗙𝗮𝗹𝗹 𝟮𝟬𝟮𝟱 𝗡𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿!

We’re excited to share the 𝗗𝗼𝗰𝗦𝗜𝗚 𝗙𝗮𝗹𝗹 𝟮𝟬𝟮𝟱 𝗡𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿, featuring the latest updates from the world’s largest global marketing PhD community. Click

𝗜𝗻 𝘁𝗵𝗶𝘀 𝗶𝘀𝘀𝘂𝗲, 𝘆𝗼𝘂’𝗹𝗹 𝗳𝗶𝗻𝗱:

Message from our chair: Reflections, Vision and Gratitude
A recap of our impactful Summer ��������� 2025 events
A sneak peek at the Winter ��������� 2026 programming and initiatives
Key insights and the winners from the Fall 2025 Member Engagement & Global Survey
Job Market insights from our 2024–25 “Who Went Where” Survey
Insights about our new initiatives: Webinar Series and Weekly Digest, and much more!

You’ll also discover scholarly spotlights, Marketing PhD webinar resources, and upcoming events designed to support and empower you at every stage of your doctoral journey.

Thank you to our dedicated officer team, mentors, and the for making this academic year a true milestone of collaboration, growth, and impact.

What would we do without and at ���������? THANK YOU for all that you do for us!

Special thanks to for not only leading the editorial vision and design of this newsletter issue but also being the steward of overhauling our newsletter. Thank you so much, Safa!

𝗛𝗮𝗽𝗽𝘆 𝗿𝗲𝗮𝗱𝗶𝗻𝗴—𝗮𝗻𝗱 𝘄𝗲 𝗹𝗼𝗼𝗸 𝗳𝗼𝗿𝘄𝗮𝗿𝗱 𝘁𝗼 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗶𝗻𝘀𝗽𝗶𝗿𝗶𝗻𝗴 𝘆𝗲𝗮𝗿 𝗮𝗵𝗲𝗮𝗱!

𝗔𝗠𝗔 𝗗𝗼𝗰𝗦𝗜𝗚 𝗪𝗲𝗯𝗶𝗻𝗮𝗿 | 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗦𝗰𝗵𝗼𝗹𝗮𝗿𝘀: 𝗖𝗮𝘂𝘀𝗮𝗹 𝗙𝗼𝗿𝗲𝘀𝘁𝘀 𝗮𝗻𝗱 𝗖𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁 𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝗺𝗲𝗻𝘁 𝗳𝗿𝗼𝗺 𝗨𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗗𝗮𝘁𝗮 𝗯𝘆 𝗣𝗿𝗼𝗳. 𝗞. 𝗦𝘂𝗱𝗵𝗶𝗿

As marketing data becomes richer, noisier, and increasingly unstructured, scholars are turning to machine learning, causal inference, and high-dimensional statistical tools to answer classical marketing questions in new ways.

This session introduces doctoral students to two practical sets of machine learning tools that expand the empirical possibilities of marketing research. We begin with Random Forests and Causal Forests—core methods for uncovering nonlinear relationships, capturing heterogeneity, and estimating heterogeneous treatment effects in both observational and experimental settings. We then turn to modern techniques for transforming unstructured content—text, images, audio, and video—into meaningful variables that broaden the range of constructs and phenomena marketing scholars can examine. The session will emphasize an intuitive understanding of these methods and how to interpret their results to advance theoretical insight.

Date: Friday, Jan 23, 2026
Time: 13:00 -14:00 ET
Location: Zoom
RSVP:

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗦𝗽𝗲𝗮𝗸𝗲𝗿:

Dr. is the James L. Frank ’32 Professor of Marketing at Yale School of Management and Founder–Director of the Yale China India Insights Program. A leading figure in quantitative marketing, he has pioneered structural empirical methods and advanced research in customer management, salesforce compensation, organizational buying, and AI-driven analytics.

His work spans machine learning, causal inference, field experiments, and game theory, and has earned top honors including the Bass Award, Little Award, Lehmann Award, and recognition as an ISMS Fellow (2023). Dr. Sudhir served as Editor-in-Chief of Marketing Science (2016–2021) and has held visiting appointments at MIT, Cambridge, INSEAD, Toronto, HKUST, and Microsoft Research.

Have a question for Dr. K. Sudhir? Submit it in advance via the registration form. We’ll prioritize questions related to the webinar’s focus.

Hosted by , supporting PhD students in their research journeys. For questions, reach out to our chair, and the organizing team for Special Projects & Partnerships, , and .

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Posted by: Christian Geiser

Dear Colleagues,

I’m pleased to announce our new on-demand course “Single-Case Mediation Analysis with R,” taught by Dr. Milica Miocevic.

The course is now open for pre-registration at a discounted price until December 12th, 2025. For further information, please visit:

Feel free to share this information with anyone who might be interested.

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Posted by: Geoffrey Hubona

Asynchronous, Online, Self-Paced, “Hands-On,” 14-Hour, Introduction to Python Course with Exercises taught by a University Professor.

Please visit

This online Introduction to Python Programming course is designed for students, academics, and practitioners interested in learning how to write programs using the Python programming language. The course targets “beginner” Python programmers who have little or no previous Python programming experience. The course is taught in an online, “hands-on” format using a current version of Python in conjunction with the IDLE interactive shell (sometimes called an Integrated Development Environment (IDE)).

This is an asynchronous, online, self-paced course consisting of six consecutive sessions, each covering a different topic and each lasting approximately 2 1/3 hours. Participants are provided permanent visual access to all video recordings (hosted on an unlisted YouTube channel), all of the downloadable Python code (“script”) that is demonstrated, all example Python programs, and solutions to the weekly Python exercises. All audio and video desktop sessions have been recorded in high-quality (.mpeg) files, which are currently hosted on YouTube.

The registration fee (for Full-time students is USD $55.20; for all others, it is USD $81.87 plus sales tax if applicable in your physical location).

ALSO INCLUDED, to assist you further, is permanent access to these 24 additional asynchronous resources, included in your registration fee. online research methods courses on R programming, PLS-SEM, and data analytics authored by Dr. Hubona at no additional cost:

The post Introduction to Python Programming appeared first on ���������.

Posted by: Christian Geiser

Dear Colleagues,

I’m happy to announce our latest on-demand course Measurement Invariance Testing with R, taught by Dr. Nataly Beribisky.

The course is now open for pre-registration at a discounted price until November 14, 2025. For further information, please visit:

Feel free to share this information with anyone who might be interested.

Best wishes,

Christian Geiser

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