無料セミナー : 2018年10月23日『5G、OTTがもたらすデジタルトランスフォーメーション2025年までの展望』 IDATE DigiWorld共同開催
Innovative Use Cases of IoT in the Transport and Logistics Sector
|発行||Frost & Sullivan||商品コード||689260|
|出版日||ページ情報||英文 55 Pages
|輸送・物流部門におけるIoTの革新的な利用例 Innovative Use Cases of IoT in the Transport and Logistics Sector|
|出版日: 2018年08月17日||ページ情報: 英文 55 Pages||
当レポートでは、輸送・物流部門におけるモノのインターネット (IoT) の革新的な利用例10件について分析しています。
Revenue Generating Business Models
While the level of interest in the Internet of Things (IoT) has been on the rise among enterprises on a global scale in the transport and logistics sector, many of them face challenges in defining use cases that enable them to generate new sources of revenue. There is a need to gain new capabilities in terms of domain expertise and technical know-how. Some enterprises have invested substantially in analytics platform and vertical expertise, others have entered into cross industry collaboration with enterprises outside their industry. At the same time, if enterprises decide to rapidly implement IoT without changing their operating model, they face challenges in delivering the new solution. Regardless of how they go about doing it, IoT has enabled them to gain new insights that they did not have in the past to bring about new service offering that differentiate them from their competitors. The report looks at 10 use cases of how enterprises in the transport and logistics sector have done it.
In summary, these companies have gained from IoT in the following ways. (1) Audi enhances its customers' experience while using sensors installed in cars to collecting real time information on traffic flow and drivers' behaviour. (2) With DriveNow, BMW diversifies from selling cars to renting cars on members' usage. (3) INRIX adopts a variety of ways to collect data on real time traffic patterns in the USA. And it developed capabilities rapidly through acquisitions to deliver more data. (4) The Land Transport Authority of Singapore adopts a three-layer stack to alleviate traffic condition by resolving congestion together with the private sector companies. (5) Navistar's prognostic solution has been used for pricing of vehicle components for over 200,000 trucks in the USA. It uses big data analytics to determine the lowest cost of truck configuration for fleet operators. (6) Ryanair use big data analytics to understand consumers' purchasing behaviour as they no longer go for the cheapest tickets. (7) Taxi Stockholm aids the tourism sector and generates revenue by providing tourists with hotspot heat maps with a smartphone app. (8) UPS uses small data to make incremental changes in their operational processes. (9) Volvo gives authorized repaid mechanics to access vehicle data to support servicing and components requirements. (10) The E-bike Management system by SITAEL was developed in an effort to reduce the number of cars on the road.