How the Internet of Things Drives Innovation for the Logistics of the Future
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2.1 Logistics as the Object of InnovationMore than five decades have passed since business logistics was first scientifically addressed in the mid-fifties, without finding a satisfactory answer to the question of the identity of logistics (What is logistics?) . From an academic point of view, the impetus for the progress of knowledge has its origins in the discussion of the terms that describe the object of analysis . From the point of view of management science, with increasing functions, tasks, and responsibilities in the field of logistics, the conceptual clarifications and definitions of logistics become increasingly important. The understanding of logistics in science and practice has developed in recent years. In the following, empirical-inductive explanatory approaches will be pursued that take up and summarize concrete problems of logistics practice (see Table 1).
Logistics is defined as the management of transport, warehousing and trans- shipments, which covers the functional management, technical, and organiza- tional design and optimization of transportation, fleet management, warehousing, handling of materials, order fulfillment, logistics network design, inventory management, and management of third-party logistics services providers . Logistics can be experienced physically and technically. This view of the industry is characterized by technical advances in the areas of automation, autonomy, energy consumption, and pollution.
Logistics is understood as a contemporary leadership concept for the develop- ment, design, management, and realization of effective and efficient flows of objects (goods, services, information, and financing) in the company-wide value- added system. Logistics links important business functions and business processes between the point of entry and delivery [9, 11]. Process integration, lean manage- ment, and IT integration approaches play an important role. The administration and modern use of master and transaction data of processes, products customers and/or suppliers in a more or less closed system (e.g. business data warehouse) will be managed via data mining, big data analytics, and deep learning approaches.Table 1 Perspective of logistics and terms used based on 
Terms in use
1 Transport, warehouse, trans-shipment 23 4Describes logistics as management of isolated business functionfirm’s integrated flow of material and informationthe overarching value chains from supplier to customerinterconnected partners of a value creation network Logistics management
Supply chain management
Value creating networks
270 H. Ruile
Logistics as Supply Chain Management (SCM) represents a further and innovative development stage. The intra-organizational perspective is replaced by a multi- tiered value chain with a consistent focus on the ultimate customer requirements and demand. In essence, supply chain management integrates supply and demand management within and across companies. SCM is a system approach to viewing the value-adding channel as a whole [8, 9, 11, 12]. The future of SCM will lie in its unique agility based on real-time capabilities. Suppliers, manufacturers, and customers can rely on information and decide on the availability of materials, capacities, and flexibility.
Logistic as management of a value-creating network (VCN). This perspective will replace supply chains with strategic business networks. Sydow  defines: A strategic network is a polycentric form of organization of economic activi- ties between market and hierarchy, which aims at the realization of competitive advantages and yet is strategically managed by one or more enterprises. It is char- acterized by complex reciprocal, rather cooperative than competitive and rela- tively stable relationships between legally independent, but mostly economically dependent enterprises.Younger schools of thought expand the linear SCM approach into a network . The holistic view of value creation networks allows development, design, realiza- tion, and optimization of economic systems . Networks are characterized by more or less free and dynamic interaction between those involved: suppliers, service providers, manufacturers, retailers, customers, consumers, competitors, regulators, and institutions. With an increasing number of participants and dynamics of reverse interaction, digital networking creates a highly complex economic system. For further discussion, we use the general term of logistics but consider all four perspectives.
2.2 Internet of ThingsThe enabling technology in our investigations is termed the “Internet of Things”, which goes back to Mark Weiser’s work at the computer science lab at Xerox PARC where he formulated the ubiquitous computing vision and described a world, where algorithms are closely embedded in our daily life . Later, in 2009, the term “Internet of Things” was coined by Kevin Ashton, RFID pioneer and co-founder of the Auto-ID center at the Massachusetts Institute of Technology . The subsequent discussion will follow the IoT definition of the International Telecommunication Union as “the global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies” . “Sensors and algorithms offer a system of interconnected smart devices, which enable real- time and intelligent communication from man to machine, machine to machine, and enterprise to enterprise. The term “thing” with regard to IoT is defined as an object of the physical world (physical things) or the information world (virtual things),How the Internet of Things Drives Innovation for the Logistics … 271which is capable of being identified and integrated into communication networks” . “With regard to the ‘Internet of Things’, this [device] is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing” .A related term for IoT is “Industry 4.0” which was introduced to the public at the Hanover Trade Fair in 2011, and presented as part of Germany’s high-tech strategy . Meanwhile, the 4.0 extension is being used in almost all economic areas and for all functions to express the significant digitally induced changes that are expected (e.g. logistics 4.0, government 4.0, health 4.0, etc.). Although the term was coined in Germany, industry 4.0 shares some commonalities with developments in other regions where it has been labeled as “Internet of Things” or “Cyber physical Internet”. The latter terms reflect primarily the technical content and not the resulting business and social transformation.Meanwhile, the German term industry 4.0 has become a transitional term for the broader understanding of digital transformation, which is defined as the digitaliza- tion of analog machine and service operations, organizational tasks, and manage- rial processes  to create added value for customers and employees [21–23]. Or in other words: “Digital transformation is the evolving pursuit of innovative and agile business and operational models—fueled by evolving technologies, processes, analytics, and talent—to create new value and experiences for customers, employees, and stakeholders” .Therefore, the terms IoT, digital transformation, and logistics will be amalgamated to “logistics 4.0” considering the aspects of IoT driven transformation processes. Thus, the definition of Logistics 4.0 by Hofmann and Rüsch : p. 25 seems to be helpful, because it includes the aspect of business model innovation [25, 26]:Products, services, infrastructure, and environment are flexibly connected via the internet or other network applications;
The digital connectivity enables an automated and self-optimized production of individual goods and services including the delivery without human interventions;
The value-creating networks are controlled decentralized while system elementsmake autonomous decisions;
Data-driven, networked business models are transforming industry structures,organization, the way of collaboration and required roles, skills and capabilities of network members.
3 IoT Driven Innovation Framework3.1 IoT Solution ArchitectureBecause IoT and related business transformation have been defined so far, we propose an IoT architecture that integrates the definitions and consists of the five building blocks described below. The IoT architecture becomes an overarching and integrative272
Table 2 IoT solution architecture based on [17, 21]H. RuileLayerDescriotionExamplesBusiness applicationBusiness process
AnalyticsAnalysis of data in order to create usable knowledge
ConnectivityData enrichment by integrating data fro different applications and sources
Communication networkInteroperable information and communication technologies
DeviceEquipment with the mandatory capabilities of communication
12 34 5Resource planning; source, make, and delivery planning, execution and control (system)Big data analysis, artificial intelligence, machine learningCloud computing, data crawler, sementic web, block chainLAN/WAN, 5G, TCP/IP Drone, self-driving vehiclesframework that logically connects technologies and organization. The architecture presented in Table 2 combines a technical IoT architecture  with a business model approach .The IoT architecture consists of five complementary layers that transform tech- nology building blocks into new business processes and business models. In layer 1–3 we rely on the definition of ITU . However, in the ITU definition the business layers are not considered. Therefore, we added the definition of digital transformation to create an integrated framework.Layer 1 represents devices: front-end technology such as sensors, actuators and RFID chips, smart computers embedded in mobile devices, or intelligent autonomous objects (e.g. drones, robots, vehicles, smart stores, smart infrastruc- ture). Information technology on level 1 creates, stores, processes and transfers data anytime and anywhere autonomously.
Layer 2 consists of internal and external communication infrastructures. Networks that allow collecting, process, and disseminate valuable information, gathered from distributed devices. The required hardware consists of a secure data network infrastructure of scalable nodes (access points, storage) and linkages (wired and wireless).
Layer 3 represents cloud-enabled services that provide SaaS (Software-as-a- Service), PaaS (Platform-as-a-Service), IaaS (Infrastructure as a Service), DaaS (Data-as-a-Service), and more. Layer 3 aggregates the “big data” and makes them available to create business applications.
Layer 4 encompasses the business applications. Such an application uses the available data to simplify and improve existing processes; for instance, block chain and data analytics can help generate and capture value along the full product life by ensuring better coordination between all partners.
Layer 5 defines the application in existing business functions such as purchasing, logistics, transport, warehousing, and production. The business functions embody
How the Internet of Things Drives Innovation for the Logistics … 273methods and tools that are used to efficiently fulfill their tasks and responsibilities (e.g. planning and execution systems, risk management, etc.).3.2 Integrated Innovation Value Chain ModelBusiness development, logistics, purchasing, and marketing functions are continu- ously integrated into new products, services, and business models through the use of new digital technologies. The transformation of technology into logistic applications becomes difficult due to the cross-functional character. The objective of the innova- tion model is to describe the overarching value chain and impact of IoT technology into business applications in order to enhance existing or create new business models within firms. The development and availability of IoT technologies is not sufficient to trigger innovation in products, processes, services, or business models. Technology has no value in itself. The value of technology comes with the width and depth of the application. However, how many value-added steps are necessary in between?Groher and Ruile  proposed an integrated innovation system for logistics. The innovation value chain model describes a stepwise transformation of technology into business values within a business-to-business environment. They identified the following four parties across the value chain: research and technology development, tool development and tool integration, application at logistics service providers, and value creation on the side of shippers. The innovation value chain model does not consider the internal transformation: how people in organizations get to know the tools and how they use them in a specific context to achieve organizational advan- tage. A prerequisite for the successful use of a new technology and the tool is a learning-oriented organization . “The adoption of new systems and processes is likely to improve effectiveness in the delivery of the logistics service. Organizational learning will also lead to reductions in the costs of transaction that will contribute to greater effectiveness in the delivery of the logistics service” : p. 71. We integrate organizational learning into the structured problem-solving cycle  to obtain the IoT-driven value chain.The integrated innovation value chain model describes a stepwise transformation of technology into business value (see Fig. 1):Step 1: from technology to digital tools. Digital tools are software programs assisting people in their functional task and responsibility. Software tools for plan- ning and controlling are well known: transport management system (TMS), ware- house management systems (WMS), resource/material planning (ERP), customer and supplier relationship management systems (CRM, SRM), and so on.
Step 2: from digital tools to learning organization. Management tasks are based on a structured problem-solving cycle: identify, analyze, find and select a solution, plan and implement, and finally evaluate. Logistics management is supported by these advanced tools and should increase efficiency of the management processes.
Step 3: from a learning organization to specific supply chain processes. According the SC reference model , we define the application areas within supply chain
274 H. RuileFig. 1 Integrated value chain framework for IoT driven innovation in logistics based on [31, 32]processes: plan, source, make, deliver, and return. Each of the process functions have developed their own expertise and tools. It is expected that cross-functional integration and competitive networking enable organizations to adapt and leverage IoT-Solutions to achieve logistics objectives .Step 4: from SC processes to the business model. The business model integrates supply chain management into the overall strategic alignment with the product, customer, and business improvement model . According to Gassmann , business model innovation is achieved when two or more elements of the business model have been changed in a coordinated and integrated way. The alignment of supply chain design and market requirement is well investigated and documented . Organizations with high SC alignments achieve higher capitalization in the market.
Step 5: from the business model to order-winning criteria. Criteria for winning customer orders are cost, delivery, quality, and flexibility. A tailor-made business model (product, customer and value chain) is essential to meet the criteria for winning customer orders .
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How the Internet of Things Drives Innovation for the Logistics of the Future
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