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The most advanced logistics operators like Amazon and Cainiao Network now sit between the development stages of 4PL and 5PL, effectively leveraging IoT technologies, digitalisation and data analytics to improve their operating efficiency and service quality.Take the fulfilment of a Taobao order through Cainiao Network for example, when an online merchant receives a new order, its operation system will automatically generate a list of information consisting of all the essential information required for processing this order. The system uses this list of information to create a digital shipping label, which is printed and affixed on the package, substituting for traditional hand-written delivery forms. The label has a unique identity which is represented by a QR code. This code can be scanned and understood by all parties involved along the whole delivery process. During the last-mile delivery stage, the delivery man is equipped with a proprietary device that has multiple functions, such as a QR code scanner, GPS, route planning, and point of sale. This enables delivery men to report the real-time position and other relevant information about the parcel, improving the information transparency of the whole delivery process (Figure 7).5The application of logistics technologies mentioned above together with the digital nature of e-commerce transactions mean that a large amount of data will be generated in the entire transaction process. Making good use of these data is key to further improving the operational efficiency in every step of the current value chain of logistics services.6DHL Trend Research suggested one of the applications of data analytics is smarter forecasting and anticipatory shipping. Customers’ purchase history, shopping cart status and even real-time mouse clicking behaviour could inform businesses where certain products are likely to be purchased, so products can be shipped closer to potential customers, further shortening the delivery time.7 Analysis of the real-time positioning of delivery trucks and current traffic conditions enables the system to generate the optimal delivery route, cutting short the delivery time and logistics cost for the company. A study done by Frost & Sullivan showed that predictive data analytics of vehicle data, driver scorecard and driver behavioural data, and subsequent route and behavioural optimisation could save fuel costs by 10% to 25%.8For these to happen, however, it is essential to have the necessary computing infrastructure for storing and processing the data, such as cloud data storage and cloud computing technology. Therefore, to support the development of e-commerce, not only do we need land for warehouses and logistics centres, but also land for data centres.The key question we want to raise is whether the Government has done enough to cope with the rapidly changing landscape of the trading and logistics industry over the past decade and to place Hong Kong in the best position to embrace the future evolution of the industry.5 Alibaba Group. (2019). Cainiao Network - Smart Logistics Network. 6 Roland Berger. (2020). FreightTech: The future of logistics. 7 DHL Trend Research. (2019). Logistics Trend Radar. 8 Frost & Sullivan. (2016). Future of Logistics. 17