Shanghai Fuller Information Technology Co., Ltd.

• Peak daily order processing capacity per warehouse: over 1.64 million orders Shanghai Fuller Information Technology Co., Ltd. is a leading Chinese provider of logistics software. Fuller’s logistics management software has been widely adopted across industries including fashion, retail, manufacturing, pharmaceuticals, e-commerce, fast-moving consumer goods (FMCG), maternal & infant care, cold chain logistics, and third-party logistics (3PL), and has become the preferred solution for industry-leading enterprises. Fuller’s business spans 20 countries worldwide; its software is deployed in over 2,200 distribution centers, managing more than 20 million square meters of warehouse space, with a peak daily order processing capacity per warehouse exceeding 1.64 million orders. Fuller serves a large portfolio of high-quality clients across diverse sectors, including SF Express, China Post Express & Logistics, Bestseller (Li-Ning Group), Semir, Samsonite, Shijie (Meiyijia), FamilyMart, Pan Asia Automobile, Chery Automobile, Bull Electric, Yangtze River Pharmaceutical, Qilu Pharmaceutical, Tasly Pharmaceuticals, Piaon Pharmaceutical, Procter & Gamble, Mengniu Dairy, Bright Dairy, COFCO Coca-Cola, Sinochem Agri, Zhengming Logistics, DHL, and Kintetsu World Express (KWE). Fuller offers a comprehensive SCE (Supply Chain Execution) management solution, comprising: — WMS (Warehouse Management System), focused on enhancing granular warehouse management, operational efficiency, and inventory accuracy; — TMS (Transportation Management System), emphasizing transportation visibility, route optimization, and collaborative execution to improve transport performance; — OCP (Order Collaboration Platform), centered on order-driven workflows, end-to-end order tracking, and multi-system integration to elevate overall supply chain efficiency; — DATAHUB, a data exchange platform enabling seamless integration and interoperability among internal and external enterprise systems. Leveraging its mature software products and deep industry expertise, Fuller has developed tailored solutions for over a dozen verticals—including e-commerce, apparel, pharmaceuticals, retail, FMCG, cold chain, high-tech, manufacturing, and 3PL—addressing sector-specific supply chain management needs and helping clients tackle challenges such as performance enhancement, cross-functional collaboration, lean management, and massive-order processing. In August 2020, Fuller was once again honored with the “LT Logistics Technology Award – Company of the Year”, widely regarded as the “Oscars of China’s logistics industry”. In March 2018, Fuller was named among the “Top 25 APAC Logistics Technology Solution Providers 2018” by APAC CIO Outlook magazine for delivering innovative, integrated smart logistics solutions and maintaining an international outlook. In December 2017, Fuller secured strategic investment from Honeywell—a diversified, high-tech, interconnected industrial enterprise ranked among the Fortune 100 (NYSE: HON)—and jointly established an overseas joint venture to serve global customers. From 2015 to 2017, Fuller FLUX won the “Company of the Year” award at the LT Logistics Technology Awards for three consecutive years—the award often dubbed the “Oscars of China’s logistics industry”; Fuller’s CEO, Ms. Zunli Shi, received the “Person of the Year” award twice during this period. From 2014 to 2020, Fuller was selected for seven consecutive years—and ranked first in the logistics software category for six consecutive years—in the “China’s Most Recognized Logistics Brands” list, a user-voted ranking jointly organized by China Logistics Brand Network and other institutions. From 2014 to 2020, Fuller FLUX’s innovative and vibrant corporate culture earned consistent industry acclaim, resulting in its repeated recognition by the logistics media outlet Logistics Zhiwen as “Best Employer in China’s Logistics Industry”. From 2018 to 2020, Fuller Technology collaborated successively with Bright Fresh Logistics and the Shanghai Municipal Commission of Commerce to ensure food safety and delivery reliability for catering services at the China International Import Expo.

Chapter 11 Study Notes — Stock Market Valuation

Economic booms or recessions affect stock prices through their impact on the risk-free rate, risk premium, and corporate earnings. It is widely accepted that stock prices are negatively correlated with both the risk-free rate and the risk premium, and positively correlated with earnings growth. In this section, we convert macroeconomic forecasts into corporate cash flow forecasts and integrate these forecasts with an appropriate discounted cash flow (DCF) model to estimate the intrinsic value of the stock market from a theoretical price-earnings (P/E) ratio perspective. 1. Stock Market Valuation Investors commonly use the market P/E ratio to assess the prospects for future stock returns. Fuller and Hsieh developed a valuation model known as the H-model. In this model, the dividend growth rate over a finite horizon is assumed to decline linearly until it stabilizes at a constant long-term rate—akin to an annuity or terminal-stage growth rate. The model incorporates: (i) the expected dominant dividend growth rate in the terminal stage (gₛ); (ii) the number of years (N) over which the dividend growth rate declines linearly; and (iii) the expected long-term dividend growth rate prevailing at the beginning of the terminal stage—or at the end of year N (gₗ). Assuming the initial annual dividend at time zero is D₀, the discount rate for the annuity is r, and the estimated intrinsic value at time zero is V₀, the H-model is expressed as follows. The H-model was originally designed as a convenient framework for modeling cases where a high initial dividend growth rate gradually transitions to a lower, stable long-term growth rate. For valuing mature, developed equity markets—where no supernormal growth exists—the Gordon Growth Model is more commonly applied than the H-model. 2. Forecasting Methods for Stock Returns There are two primary approaches: top-down and bottom-up. In top-down forecasting, macroeconomic forecasts are used to predict aggregate returns for broad-market equity indices. These forecasts can then be refined down to specific market sectors and industry clusters. Key steps include: Market Analysis: Examine valuations across different equity markets to identify those offering excess expected returns. — Compare relative valuation metrics of individual equity markets against their historical averages to identify relatively undervalued or overvalued markets. — Analyze trends in relative valuation metrics across markets to gauge market momentum. — Compare the expected returns of equity markets anticipated to deliver excess returns against expected returns of other asset classes (e.g., bonds, real estate, commodities). Industry Analysis: Assess domestic and global economic cycles to identify industries expected to outperform within the strongest-performing equity markets. — Compare relative growth rates and expected profit margins across industries. — Identify industries likely to benefit positively from trends in interest rates, exchange rates, and inflation. Company Analysis: Within the best-performing industries of the strongest-performing equity markets, select the highest-potential individual stocks. Bottom-up forecasting begins with micro-level fundamental analysis of individual companies. Analysts use this information to forecast returns for each stock. Specific steps include: Company Analysis: Identify the fundamental reasons why certain stocks may outperform the broader market—without relying on current macroeconomic conditions. — Determine why a company’s product, technology, or service is expected to succeed. — Evaluate the company’s management team, historical performance, business model, and growth prospects. — Compute the expected return for each stock using a discounted cash flow (DCF) model. Industry Analysis: Aggregate the expected returns of individual stocks within an industry to identify the strongest-performing sectors.

H.B. Fuller (FUL) Could Be 27% Undervalued Following Its $850 Million Notes Offering

1 day ago

H.B. Fuller priced an $850 million note offering to fund its AMS acquisition despite a share price decline. Analysts view the stock as 27% undervalued, though increased leverage poses risks.

Simply Wall Street

2026-10-11

H.B. Fuller (FUL) Could Be 27% Undervalued Following Its $850 Million Notes Offering

H.B. Fuller (FUL) Could Be 27% Undervalued Following Its $850 Million Notes Offering

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