How to implement enterprise AI transformation architecture?
How AI Investment Impacts Business Success and Market Trends in China？
How Recommendation Affects Customer Search: A Field Experiment
By conducting a large-scale experiment with over 555,800 customers on an e-commerce platform, researchers found that lower recommendation relevance leads to increased search activity, indicating a substitution effect. Different product categories show either complementary or substitution relationships, highlighting the roles of demand fulfillment and formation in channel interactions, offering valuable insights for e-commerce platform design.
Sooner or Later? Promising Delivery Speed in Online Retail
Online retailers' delivery speed promises affect customer behavior and business performance. Research finds their pros and cons and proposes an optimization model and management strategies.
Tracking In-Store Customer Journeys with IoT: How Sensor Data Transforms Retail Decisions
Mobile app adoption and IoT tracking synergistically transform offline retail by enhancing customer discovery and enabling hyper-localized store strategies, driving measurable gains in offline consumption.
Smart Targeting: How to Match the Right Policies to the Right People
Unlike traditional one-size-fits-all solutions, this research recognizes that identical treatments can produce dramatically different results across subgroups—sometimes even opposite effects. The powerful framework developed in this study precisely identifies which specific individuals will respond best to different interventions, a breakthrough that empowers organizations to efficiently deploy limited resources for maximum benefit.
E-commerce Could Uses Delivery Boxes to Boost Sales with Free Samples
Research shows adding unrelated brands' free samples to e-commerce orders significantly increases the sampled brand's sales, with effects lasting up to 14 months. This method both acquires new customers and boosts sales across the brand's entire product line. Sending samples to consumers who recently browsed related products or purchased non-essential items works best. This innovation combining offline logistics with online data creates a win-win-win for platforms, brands, and consumers.
Scalable Causal Analysis: Estimating Treatment Effects Using AI-Driven Models
This work advances causal inference by introducing a doubly robust estimator for ATE (average treatment effect) that ensures consistency, dimension-free scalability, and valid statistical inference, validated through real-world applications.
Finding Hidden Patterns in Groups Without Making Too Many Mistakes
This research introduces a breakthrough method that can automatically discover important association patterns among different population subgroups in complex data, helping researchers more accurately analyze characteristics across different populations and providing a scientific basis for personalized decision-making.
What is the economic impact of China’s Personal Information Protection Law (PIPL)?
The PIPL negatively impacted data-intensive firms, especially in B2C sectors, but those with stronger analytics and AI talent better mitigated declines in revenue, productivity, profitability, and expansion efforts.
The Value of Last-mile Delivery in Online Retail
Last-mile home delivery significantly boosts sales and customer spending on online retail platforms, despite its high costs. Using advanced machine learning models, it also highlights strategies to optimize delivery capacity while ensuring fairness and maximizing profits.
Tailoring Large Language Models for Business Use
Customizing LLMs via domain-specific theory and supervised fine-tuning (SFT) bridges gaps in expertise, trust, and satisfaction between AI and human doctors in medical consultation.
How Market Data Drives Innovation on E-Commerce Platforms
Connecting Customers and Merchants Offline: Experimental Evidence from Commercialization of Last-Mile Pickup Stations at Alibaba
Online-driven offline interactions boost online sales
IBASE: Adaptive Causal Inference by Integrating Big Data and Small Experiment
How Covid-19 Changed E-Commerce: Lessons from Alibaba
This study analyzes COVID-19's impact on e-commerce using three years of sales data from 339 Chinese cities on Alibaba's platform, revealing two key findings: first, e-commerce sales followed a pattern of decline and recovery during the pandemic, demonstrating digital resilience; second, logistics capacity emerged as the critical operational driver affecting sales fluctuations. These insights provide valuable guidance for platforms and policymakers in digital strategy planning and logistics infrastructure investment.
How AI Investment Impacts Business Success and Market Trends in China？
The Value of Last-mile Delivery in Online Retail
Last-mile home delivery significantly boosts sales and customer spending on online retail platforms, despite its high costs. Using advanced machine learning models, it also highlights strategies to optimize delivery capacity while ensuring fairness and maximizing profits.
Tracking In-Store Customer Journeys with IoT: How Sensor Data Transforms Retail Decisions
Mobile app adoption and IoT tracking synergistically transform offline retail by enhancing customer discovery and enabling hyper-localized store strategies, driving measurable gains in offline consumption.
Connecting Customers and Merchants Offline: Experimental Evidence from Commercialization of Last-Mile Pickup Stations at Alibaba
Online-driven offline interactions boost online sales
Scalable Causal Analysis: Estimating Treatment Effects Using AI-Driven Models
This work advances causal inference by introducing a doubly robust estimator for ATE (average treatment effect) that ensures consistency, dimension-free scalability, and valid statistical inference, validated through real-world applications.
What is the economic impact of China’s Personal Information Protection Law (PIPL)?
The PIPL negatively impacted data-intensive firms, especially in B2C sectors, but those with stronger analytics and AI talent better mitigated declines in revenue, productivity, profitability, and expansion efforts.
Sooner or Later? Promising Delivery Speed in Online Retail
Online retailers' delivery speed promises affect customer behavior and business performance. Research finds their pros and cons and proposes an optimization model and management strategies.
How Market Data Drives Innovation on E-Commerce Platforms
E-commerce Could Uses Delivery Boxes to Boost Sales with Free Samples
Research shows adding unrelated brands' free samples to e-commerce orders significantly increases the sampled brand's sales, with effects lasting up to 14 months. This method both acquires new customers and boosts sales across the brand's entire product line. Sending samples to consumers who recently browsed related products or purchased non-essential items works best. This innovation combining offline logistics with online data creates a win-win-win for platforms, brands, and consumers.
How Covid-19 Changed E-Commerce: Lessons from Alibaba
This study analyzes COVID-19's impact on e-commerce using three years of sales data from 339 Chinese cities on Alibaba's platform, revealing two key findings: first, e-commerce sales followed a pattern of decline and recovery during the pandemic, demonstrating digital resilience; second, logistics capacity emerged as the critical operational driver affecting sales fluctuations. These insights provide valuable guidance for platforms and policymakers in digital strategy planning and logistics infrastructure investment.
How Recommendation Affects Customer Search: A Field Experiment
By conducting a large-scale experiment with over 555,800 customers on an e-commerce platform, researchers found that lower recommendation relevance leads to increased search activity, indicating a substitution effect. Different product categories show either complementary or substitution relationships, highlighting the roles of demand fulfillment and formation in channel interactions, offering valuable insights for e-commerce platform design.
Tailoring Large Language Models for Business Use
Customizing LLMs via domain-specific theory and supervised fine-tuning (SFT) bridges gaps in expertise, trust, and satisfaction between AI and human doctors in medical consultation.
Smart Targeting: How to Match the Right Policies to the Right People
Unlike traditional one-size-fits-all solutions, this research recognizes that identical treatments can produce dramatically different results across subgroups—sometimes even opposite effects. The powerful framework developed in this study precisely identifies which specific individuals will respond best to different interventions, a breakthrough that empowers organizations to efficiently deploy limited resources for maximum benefit.
IBASE: Adaptive Causal Inference by Integrating Big Data and Small Experiment
Finding Hidden Patterns in Groups Without Making Too Many Mistakes
This research introduces a breakthrough method that can automatically discover important association patterns among different population subgroups in complex data, helping researchers more accurately analyze characteristics across different populations and providing a scientific basis for personalized decision-making.