Publications and Patents by PrimeAI Data Scientists
Publications by PrimeAI Authors
❋ Juliana PinPin J. 2025 “Optimizing a nationwide supply chain for winter oilseeds in sustainable aviation fuel production: Pennycress, camelina, and carinata,” Renewable and Sustainable Energy Reviews.
❋ Dr. Jon HigbieHigbie J. 2020 “B2B Reimagined, Ep. 4: Media & Advertising,” May 7.
❋ Dr. Jon HigbieHigbie, J. 2015 “Merchandising Mindset: The Future of Hotel Revenue Management,” Hotel Business Review.
❋ Dr. Jon HigbieWilliams, J., 2013, “Pricing decisions are going to be made whether you like it or not,” an interview in O’Reilly Radar.
❋ Dr. Jon HigbieLee S., L. A Garrow, J. Higbie, P. Keskinocak, D. Koushik, 2009, “Do you really know who your customers are? A study of US retail hotel demand,” Journal of Revenue and Pricing Management, 10(1), pp. 73-86
❋ Dr. Jon HigbieQueenan C., M. Ferguson, J. Higbie, R. Kapoor, 2007, “A Comparison of Unconstraining Methods to Improve Revenue Management Systems,” Production and Operations Management, 16(6), pp. 729-746.
❋ Juliana PinPin, Juliana and Jones, Daniela and de Queiroz, Anderson Rodrigo and Hartley, Damon, “A Decision-Making Framework for Multi-Year Planning and Scalable Infrastructure in Sustainable Aviation Fuel Supply Chains.”
❋ Dr. Jon HigbieHigbie J. 2020 “Three Tips to Resolve Pricing Challenges B2B Sales,” SalesTech, Aug 6.
❋ Dr. Jon HigbieHigbie, J. 2013 “From Managing Demand to Generating Demand,” Hotel Business Review.
Higbie, J. 2011, “B2B Price Optimization Analytics,” in Revenue Management: A Practical Pricing Perspective, E. Yeoman and U. McMahon-Beattie, (eds.), pp. 120-135.
❋ Dr. Jon HigbieR. Metters, C. Queenan, M. Ferguson, L. Harrison, J. Higbie, S. Ward, B, Barfield, T. Farley, H. Kuyumcu, A. Duggasani, 2008, “The ‘Killer Application’ of Revenue Management: Harrah's Cherokee Casino & Hotel,” Interfaces, 38(3), pp. 161-224.
❋ Dr. Jon Higbie❋ Dr. Jon HigbieHigbie, J. 2018 “Apply Artificial Intelligence; Uncover Hotel Pricing and Inventory Opportunities,” Hotel Business Review.
❋ Dr. Jon HigbieWatson H. and J. Higbie, 2014, “The Intersection of BI and Revenue Management,” Business Intelligence Journal, 19(4), pp. 4-8.
❋ Dr. Jon HigbieKoushik, D., J. Higbie and C. Eister, 2012, “Retail Price Optimization at InterContinental Hotels Group,” Interfaces, 42(1), pp. 45-57.
❋ Dr. Jon HigbieHigbie, J. 2017 “The Intersect of Cloud Computing and Hotel Revenue Management,” Hotel Business Review.
❋ Dr. Jon HigbieCross, R., J. Higbie, Z. Cross, 2009, “Milestones in the application of analytical pricing and revenue management,” Journal of Revenue and Pricing Management, 10(1), pp. 8-18.
PrimeAI Team Member Patents
System for Modeling Drink Supply and Demand, US 2012/0116841 A1, May 10,2012.
Blend Plan Optimization for Concentrated Consumable Products. US 10, 026, 043 B2, July. 17, 2018.
System for Optimizing Drink Blends. US 11,048,237 B2, June 29, 2021.
System for Optimizing Drink Blends. (EP, MX, CN) WO 2012/061553, May 10, 2012.
System and Method for Simulating Drink Production. US 8.626,564 B2, Jan. 7, 2014.
Blend Plan Optimization for Concentrated Consumable Products. (MX, CN)WO 2014/093895 Al, June 19, 2014.
Customer Success Stories
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Marmic Technician Scheduling & Routing
Marmic struggled with inefficient manual technician scheduling & routing caused lost technician availability, overtime, and excessive travel costs. By using our workforce scheduling & routing optimizer, they increased revenue 10%, cut overtime by 91%, and enabled 90 days of forward visibility instead of just 48 hours.
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CheckSammy Pricing Optimization & Workforce Routing
CheckSammy’s manual routing, scheduling, and non-optimized pricing limited capacity and profitability. With our scheduling, routing, and pricing optimization, they doubled operational and revenue capacity without adding headcount or infrastructure, supporting a $150M capital raise as revenue rose and costs fell.
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Aeroméxico Dynamic Pricing
Aeroméxico’s rigid fare classes failed to reflect real customer price sensitivity across routes and seasons. Our dynamic pricing optimization algorithm improved offer relevance, demonstrated higher conversion, and lifted passenger revenue by approximately 1–3% on targeted flows.
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LexisNexis De-Identification & Risk Mitigation
LexisNexis wanted to grow revenue by offering HIPAA-compliant enriched healthcare data products and risk insights. Using our de-identification and risk-scoring platform, they scaled compliant data products, reduced privacy risk, and accelerated regulatory certification and customer onboarding cycles.
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Hotel Group Demand Forecasting & Price Optimization
A Major Hotel Group struggled with static pricing and weak demand forecasts that left rooms underpriced or empty. After deploying our forecasting and dynamic pricing optimizers, this hotel group grew revenue by 2.7% and significantly increased adoption of advanced pricing tools among global hotel managers.
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Forto Demand Planning & Pricing Optimization
Freight forwarder Forto faced inaccurate container demand forecasts and suboptimal pricing that constrained margins and growth. By using our demand forecasting and dynamic pricing optimizers, they added over $1M in monthly revenue, enabling a profitable, scalable growth trajectory.
