This repository contains numerical implementation for the paper Intertemporal Pricing under Reference Effects: Integrating Reference Effects and Consumer Heterogeneity.

Overview

Software package for intertemporal pricing optimization under reference effects and consumer heterogeneity estimation.

Overview

This repository contains numerical implementation for the paper Intertemporal Pricing under Reference Effects: Integrating Reference Effects and Consumer Heterogeneity.

Folders

  • scripts/: Python and R files
  • illustrations/: two .png pictures illustrating logit demand, and how it depends on reference price and price
  • simulation_results: estimated coefficients in simulation stored in .csv files
  • pricing_output/: .png pictures showing pricing policy and cumulative revenue, for both simulation and MSOM (real) data
  • MSOM_data_cleaned/: extracted feature data in .csv files, ready as inputs of the estimation algorithm
  • MSOM_data_estimated/: estimated coefficients of MSOM data stored in .csv files
  • MSOM_data_optimized/: revenue comparison for real data study
  • 'MSOM_Data/`: MSOM-JD.com dataset

Scripts and Modules

Each python script in scripts/ starting with run_ is used for one run of a certain numerical experiment, while each python scipt ending with _py defines some functions to be imported by other files.

Based on the purposes of all the scripts, we further categorize them into the following modules.

  • Data preprocessing and feature extraction
    • run_data_cleaning.py, py_MSOM_cleaning.py, run_extract_features.py, run_freq_user.py, run_freq_estimate.py,
  • Heterogeneous Reference Effects Estimation
    • Functions: py_estimation.py, cross_validation.py, mmnl_simualtion.py
    • For simulated data: run_mmnl_estimation_simulation.py
    • For MSOM data: run_mmnl_estimation.py, run_mmnl_estimation_compare.py
  • Pricing Optimization:
    • Functions: optimal_pricing_policy_exp_update.py
    • For simulated data: run_pricing_optimization.py
    • For MSOM data: run_mmnl_pricing_optimization.py, run_mmnl_revenue_compare.py

Real Data and Access

The MSOM-JD.com dataset can be donwloaded from this link given appropariate acess, and general introduction to the dataset is available in this paper. To be compatible with the codes, the uncompressed .csv data files should be stored in the folder ./MSOM_Data/.

Owner
Hansheng Jiang
Ph.D. student at the University of California, Berkeley
Hansheng Jiang
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