EDUCATION

Columbia University, Graduate School of Business, NY
Ph.D., Marketing, 2018
M.Phil., Marketing, 2016

Tel-Aviv University, Coller School of Business Administration, Israel
M.Sc. in Management of Technology and Information Technologies, 2010
Master’s thesis: Factors Influencing Perceived Benefit and User Satisfaction in Knowledge Management Systems

Technion Institute of Technology, Faculty of Computer Science, Israel
B.Sc. in Information Systems Engineering (Cum laude), 2005


RESEARCH INTERESTS 

  • Automation

  • Machine learning

  • Field experiments

  • Bridging behavioral decision theory and marketing science

  • Digital marketing

PUBLICATIONS

  • Karlinsky-Shichor, Yael and Moshe Zviran. “Factors Influencing Perceived Benefit and User Satisfaction in Knowledge Management Systems,” Information Systems Management, 2016, 33(1), 55-73.

RESEARCH IN PROGRESS

  • “Automating the B2B Salesperson Pricing Decisions: Can Machines Replace Humans and When?” with Oded Netzer. Working paper

    • Finalist, the 2018 ISMS/MSI/EMAC Gary Lilien Marketing Science Practice Prize

    • Winner, 2017 Vithala R. and Saroj V. Rao ISMS Doctoral Dissertation Award

    • Winner of the 2016 Institute for the Study of Business Markets Doctoral Support Award Competition

    • Awarded the 2015 Deming Center Doctoral Fellowship

  • “Automation via Ensemble of Experts” with Oded Netzer

  • “Increasing Adoption of AI-based Bootstrap Models in Business Decision Making” with Yaacov Trope

  • “When are Salespeople Most Likely to Adopt Automation? Evidence from a B2B Field Experiment”

  • “The Value of Community Engagement: A B2B Field Experiment”


HONORS AND AWARDS

  • Finalist, the 2018 ISMS/MSI/EMAC Gary Lilien Marketing Science Practice Prize

  • Winner, 2017 Vithala R. and Saroj V. Rao ISMS Doctoral Dissertation Award ($5,000)

  • 2017 INFORMS Doctoral Consortium Fellow, University of South California, Los Angeles, California

  • 2017 University of Houston Doctoral Symposium, Department Representative

  • Winner, 2016 Institute for the Study of Business Markets Doctoral Support Award Competition ($5,000)

  • 2015-2016 Paul and Sandra Montrone Doctoral Fellow ($16,000)

  • 2015 Deming Center Doctoral Fellow ($10,000)

  • Graduate Student Fellowship, Columbia Business School, 2012-2017


CONFERENCE PRESENTATION

  • “Automating the B2B Salesperson Pricing Decisions: Can Machines Replace Humans and When?” Marketing Science Conference, Temple University, Philadelphia, PA, June 2018

    • Special session for ISMS Doctoral dissertation winners

    • 2018 ISMS/MSI/EMAC Gary Lilien Marketing Science Practice Prize Judging

  • “Automating the B2B Salesperson Pricing Decisions: Can Machines Replace Humans and When?” Marketing Science Conference, University of Southern California, Los Angeles, California, June 2017

  • “Salesperson vs. Model of the Salesperson: A B2B Pricing Application,” Marketing in Israel Conference, Bar-Ilan University, Israel, December 2016

  • “Factors Influencing Perceived Benefit and User Satisfaction in Knowledge Management Systems,” ILAIS, University of Haifa, Israel, July 2012

INVITED TALKS 

  • John Hopkins University, Carey Business School, December 2017

  • IDC Herzelia, Arison School of Business, November 2017

  • Tel Aviv University, Coller School of Management, November 2017

  • New York University, Stern School of Business, Trope Lab, October 2017

  • University of Michigan, Ross School of Business, October 2017

  • Penn State University, Smeal College of Business, September 2017

  • Georgia Tech, Scheller College of Business, September 2017

OTHER ACADEMIC WORK
Referee, The Mediterranean Conference on Information Systems (MCIS), 2011.


TEACHING EXPERIENCE

Columbia Business School, Columbia University

Teaching Assistant

  • Mathematical Models in Marketing (PhD class, Spring 2014)

  • Retailing: The Design & Marketing of Luxury Products (MBA class, Fall 2014)

  • Game Theory & Business (MBA class, Summer 2013)

Coller (formerly Recanati) School of Business Administration, Tel Aviv University

Instructor

  • Managing Information in Organizations (MBA Core class, Fall 2011)

Teaching Assistant

  • Managing Information in Organizations (Fall 2010, Spring 2011)

  • Knowledge Management (Fall 2008)

  • Managing the Information Resource (Fall 2008)


DOCTORAL COURSEWORK
Marketing:

Advanced Empirical Methods - Oded Netzer
Applied Multivariate Statistics - Kamel Jedidi
Analytical Models - Miklos Sarvary
Mathematical Models in Marketing - Rajeev Kohli
Bayesian Modeling and Computation - Asim Ansari
Marketing, Models and Decisions - Donald Lehmann
Consumer Behavior: Information Processing, Memory and Attitudes - Dan Bartels
Consumer Behavior: Judgment and Decision Making - Eric Johnson

Economics:
Econometrics I - Jushan Bai
Econometrics II - Christoph Rothe
Economic Theory I&II - Paolo Siconolfi
Economic Theory III&IV - Paolo Siconolfi
Industrial Organization - Kate Ho
Math Methods for Economists - Jaromir Nosal

DRO/Statistics:
Foundations of Graphical Modeling - David Blei
Causal Inference - Jose Zubizarreta
Empirical methods in MS/OM - Marcelo Olivares


WORK EXPERIENCE

  • Project Manager Officer (2008 – 2010), SAP Labs Israel

  • Software engineer (2005 –2008), SAP Labs Israel

  • Software Developer Intern (2004 – 2005), Elbit Systems Ltd.


REFERENCES
Oded Netzer
(Dissertation Advisor)
Professor of Business Graduate School of Business Columbia University
3022 Broadway, 520 Uris Hall New York, NY 10027
Tel: +1 212-854-7647
Email: onetzer@gsb.columbia.edu

Miklos Sarvary (Doctoral Committee Member)
Carson Family Professor of Business
Graduate School of Business
Columbia University
3022 Broadway, 513 Uris Hall New York, NY 10027
Tel: +1 212-851-0165
Email: miklos.sarvary@gsb.columbia.edu

Ran Kivetz (Doctoral Committee Member)
Philip H. Geier Jr., Professor of Marketing
Graduate School of Business
Columbia University
3022 Broadway, 503 Uris Hall New York, NY 10027
Tel: +1 212-854-4555
Email: rk566@gsb.columbia.edu

Moshe Zviran (Co-author, Master Thesis Advisor)
Professor of Information Technology
Dean, Coller School of Management
Tel Aviv University
338 Recanati - Business Administration, Tel Aviv, Israel
Tel: +972 3-640-8720
Email: zviran@tau.ac.il


DOCTORAL DISSERTATION RESEARCH

“Automation, Decision Making and B2B Pricing”

In my dissertation, I investigate the potential impact of automation of experts’ decisions – specifically on salespeople making pricing decisions in a high human-interaction environment such as business-to-business (B2B) retail. In a real-time pricing field experiment with the B2B retailer I find that providing salespeople with their own model's prices increases gross profit by 10% relative to a control condition, which translates to approximately $1.3 million in yearly profits. Using secondary data from a B2B retailer I find that a bootstrap pricing model of the salesperson generates higher expected profits than those of the salesperson, despite the loss of non-codeable information available to the salesperson but not to the model. I then propose two hybrid pricing schemes that use both the model and the salesperson for pricing new quotes. One hybrid is based on deviations in human judgment and the other is a Machine Learning hybrid that predicts who will generate higher profits, the model or the salesperson, based on the quote’s characteristics. Both hybrids lead to a further significant increase in profits to the firm over pure model pricing.  Overall, my findings suggest that automation of experts’ pricing decisions in B2B settings is not only feasible but can also lead to increased profitability by complementing the expert salesperson rather than replacing her. I also investigate for what type of salespeople and under what conditions the model works best. For example, I find that inexperienced salespeople benefit more from automation and that human experts should handle unfamiliar clients and orders with unique characteristics. I also investigate alternative approaches to modeling the salesperson using machine learning methods and ways to preserve individual and organizational knowledge through different combinations and weighing of models.

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