General Motors Optimizes Vehicle Content for Customer Value and Profitability

Published Online:https://doi.org/10.1287/inte.2022.1144

References

  • Anderson S, de Palma A, Thisse J (1992) Discrete Choice Theory of Product Differentiation (MIT Press, Cambridge, MA).Google Scholar
  • Beaujon G, Wu-Smith P, Owen J, Vander Veen D (2010) Overview: Product content planning, packaging and pricing optimization. Research report, General Motors, Warren, MI.Google Scholar
  • Ben-Akiva M, Lerman S (1985) Discrete Choice Analysis (MIT Press, Cambridge, MA).Google Scholar
  • Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63(4):841–890.Google Scholar
  • Berry S, Levinsohn J, Pakes A (2004) Differentiated products demand systems from a combination of micro and macro data: The new car market. J. Political Econom. 112(1):68–105.Google Scholar
  • Cafeo J, Harbaugh M, Keenan P, Lemieux J, Rajpathak D (2019) Applicability and use of artificial intelligence in business decision modeling. Research report, General Motors, Warren, MI.Google Scholar
  • Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2013) Bayesian Data Analysis, 3rd ed. (CRC Press, Boca Raton, FL).Google Scholar
  • Greenberg E (2012) Introduction to Bayesian Econometrics, 2nd ed. (Cambridge University Press, Cambridge, UK).Google Scholar
  • Gropp W, Lusk E, Skjellum A (1994) Using MPI: Portable Parallel Programming with the Message-Passing Interface (MIT Press, Cambridge, MA).Google Scholar
  • Keenan P, Owen J (2018) Applications of the consumer choice modeling and analytics platform (CCMAP). Research report, General Motors, Warren, MI.Google Scholar
  • Keenan P, Stockbridge R (2018) Discrete choice modeling tools for content optimization – CCMAP version 1 user guide. Research report, General Motors, Warren, MI.Google Scholar
  • Keenan P, Fenyes P, Wu-Smith P (2020) Advanced features in COTS 2.0 content optimization. Research report, General Motors, Warren, MI.Google Scholar
  • Knuth D (2005) The Art of Computer Programming, vol. 4 (Addison-Wesley, Boston).Google Scholar
  • Mitchell M (1998) An Introduction to Genetic Algorithms (MIT Press, Cambridge, MA).Google Scholar
  • Nocedal J, Wright S (2006) Numerical Optimization, 2nd ed. (Springer, New York).Google Scholar
  • Pullman ME, Dodson KJ, Moore WL (1999) A comparison of conjoint methods when there are many attributes. Marketing Lett. 10(2):125–138.Google Scholar
  • Robert C, Casella G (1999) Monte Carlo Statistical Methods (Springer, New York).Google Scholar
  • Rubinstein R, Kroese D (2004) The Cross-Entropy Method (Springer, New York).Google Scholar
  • Schmidhuber J (2015) Deep learning in neural networks: An overview. Neural Networks 61(January):85–117.Google Scholar
  • Schumacher K (2022) Modeling customer utility with a neural network within a logit choice model. Research report, General Motors, Warren, MI.Google Scholar
  • Schumacher K, Keenan P (2016) Customer preference summary metrics. Research report, General Motors, Warren, MI.Google Scholar
  • Schumacher K, Keenan P, Wu-Smith P (2018) Summary of methodological research findings for content optimization market research. Research report, General Motors, Warren, MI.Google Scholar
  • Schumacher K, Keenan P, Wu-Smith P (2019) Process for studying full-vehicle content for content optimization analysis. Research report, General Motors, Warren, MI.Google Scholar
  • Silva-Risso J, Ionova I (2008) Practice prize winner—A nested logit model of product and transaction-type choice for planning automakers’ pricing and promotions. Marketing Sci. 27(4):545–566.LinkGoogle Scholar
  • Song E, Wu-Smith P, Nelson B (2020) Uncertainty quantification in vehicle content optimization for General Motors. INFORMS J. Appl. Analytics 50(4):213–268.Google Scholar
  • Stan Development Team (2021) Stan modeling language users guide and reference manual, v2.28. Accessed July 13, 2022, https://mc-stan.org/docs/2_30/stan-users-guide-2_30.pdf.Google Scholar
  • Train KE (2003) Discrete Choice Methods with Simulation (Cambridge University Press, Cambridge, UK).Google Scholar
  • Train KE, Winston C (2007) Vehicle choice behavior and the declining market share of US automakers. Internat. Econom. Rev. 48(4):1469–1496.Google Scholar
  • Wu-Smith P, Beaujon G, Donndelinger J, Owen J, Costy T (2014) CCAT: Customer choice analysis tool and process. Research report, General Motors, Warren, MI.Google Scholar
  • Yee M, Dahan E, Hauser J, Orlin J (2007) Greedoid-based non-compensatory inference. Marketing Sci. 26(4):532–549.LinkGoogle Scholar
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