A business model describes, in a model-like and holistic manner, the logical connections and the way in which a company generates value for its customers. A company can operate several business models at the same time. (see also https://en.wikipedia.org/wiki/Business_model)
Added value can be understood as a process of increasing the perceived value of the product in the eyes of the consumers/customers. It is known as the value proposition. (Modified from https://en.wikipedia.org/wiki/Added_value)
The tangible dimension of value refers to physical products. The intangible dimension of value refer to qualities that can be valuable to the (end) customer, they can be: durability, ethicality, aesthetic appearance, usability or some other personal need or value. Services, by definition, are intangible (non-material)
A service model is the way that a firm offers intangible value to its customers. Different XaaS concepts describe broad category of service models, which offer customers product delivery and payment options that allow them to purchase access to products as a service. the most common ones are the three general cloud computing models: Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). See also https://en.wikipedia.org/wiki/Cloud_computing#Service_models.
Infrastructure as a Service (IaaS) are online services that provide high-level APIs used to dereference various low-level details of underlying network infrastructure like physical computing resources, location, data partitioning, scaling, security, backup etc. (From https://en.wikipedia.org/wiki/Infrastructure_as_a_service)
Software as a service (SaaS /sæs/) is a software licensing and delivery model in which software is licensed on a subscription basis and is centrally hosted. It is sometimes referred to as "on-demand software". (from https://en.wikipedia.org/wiki/Software_as_a_service)
Platform as a Service (PaaS) or application platform as a Service (aPaaS) or platform base service is a category of cloud computing services that provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure typically associated with developing and launching an app. (from https://en.wikipedia.org/wiki/Platform_as_a_service)
Product as a service covers business models where the manufacturer or brand owner retains the ownership of an asset and offers it to customers as a service. In this business model, the company offering the product has an incentive to optimize the use and life cycle of the asset.
Proprietary software is non-free computer software for which the software's publisher or another person retains intellectual property rights—usually copyright of the source code, but sometimes patent rights. (from https://en.wikipedia.org/wiki/Proprietary_software)
Open-source software (OSS) is a type of computer software whose source code is released under a license in which the copyright holder grants users the rights to study, change, and distribute the software to anyone and for any purpose. Open-source software may be developed in a collaborative public manner. According to scientists who studied it, open-source software is a prominent example of open collaboration. (from https://en.wikipedia.org/wiki/Open-source_software)
In the same way that software can be developed and commercialized using different business models according to the software ownership, digital platforms could be developed and commercialized using different business models according to the infrastructure ownership. Different infrastructure ownerships can be identified in this chapter and also their business models (like renting, pay per use…)
(From https://en.wikipedia.org/wiki/Business_ecosystem - definition by Moore) A business ecosystem is an economic community supported by a foundation of interacting organisations and individuals - the organisms of the business world. The economic community produces goods and services of value to customers, who are themselves members of the ecosystem. The member organisms also include suppliers, lead producers, competitors, and other stakeholders. Over time, they coevolve their capabilities and roles, and tend to align themselves with the directions set by one or more central companies. Those companies holding leadership roles may change over time, but the function of ecosystem leader is valued by the community because it enables members to move toward shared visions to align their investments, and to find mutually supportive roles.
By definition, by bringing together actors from different sides, platforms are defined by their stakeholders. There are core stakeholders (target customers, core suppliers, value chain partners), but it should not be forgotten that there are also actors with an indirect or external interest in the activities in the platform (competitors, existing customers not addressed through the platform). A platform also defines the relationship with and the channels with the different user groups.
The business ecosystem within a digital platform have to attract, involve and interconnect value creators on both the supply and demand sides. The platform enables the interaction (value co-creation) between two main groups: demand side (target clients = value users) and supply side (value producers).
Network effects of platform has two dimensions: direct network effects explain how a platform attracts other value creators to participate whereas indirect network effects arise from attracting other platforms to contribute.
Interactions with other digital platforms indicate how developed solutions are interoperable with legacy systems or how future interaction with other solutions is anticipated.
Governance of interaction with other digital platforms is crucial especially for B2B platform operations. Application programming interfaces (APIs) and other technical boundary resources enable interoperability and co-operative resources set the rules of participating and sharing within the platform.
In digital platforms the filtering is typically based on algorithms, i.e. software-based tools enable the proper and relevant fit of the exchange between producers and users.
According to the new paradigm of sustainability, the importance of the user is increasing. The user is at the same time a customer, a citizen and a worker. The well-being of the user could therefore become a winning strategy both for B2B as well as B2C companies. More detailed modelling behaviour can help the development of innovative solutions, aiming at user comfort, safety, performance, style; this requires new competitive focus for the development of these innovative solutions and new business models to support a quick and dynamic response to market changes.
The rise of the transport cost, the need for higher efficiency and productivity, the customer demand for greener product, the higher instability of raw material and energy prices and the shortening of the lead-time production will push for a more critical assessment of the delocalisation strategy towards low cost countries. Service-led personalised products will require a new paradigm for western countries re-industrialisation (Globalisation 2.0), moving back (re-shoring) manufacturing of selected products.
The “servitization wave” of manufacturing has already spread out to the advanced countries and many leading high-capital investment sectors (e.g. aerospace and automotive) are already competing in the international markets providing to their customers a composition of services for product operation (e.g. maintenance, reliability, upgrades), and end-of-life use (e.g. re-manufacturing, recycling, disposal). Especially SMEs are trying to compete in the international markets with their niche solutions, adding innovative services to their value propositions. Such innovative business models are based on a dynamic network of companies, continuously moving and changing in order to afford more and more complex compositions of services. In such a context, there is a strong need to create distributed, adaptive, and interoperable virtual enterprise environments supporting these undergoing processes. In order to do so, new tools must be provided for enabling and fostering the dynamic composition of enterprise networks. In particular, SMEs call for tools and instruments which follow them in their continuously re-shaping process, enabling collaboration and communication among the different actors of the product-service value chains. New IPR methods are also needed.
As products are today virtually designed and tested before being engineered for production, new business models need also to have tools to support the company to design and test them before they are implemented through products, services and manufacturing processes. The complexity of these tools is higher than that of tools for product development, due the need for holistic modelling of product and processes.
At the core of all potential industrial use case scenarios of platforms are data. When formerly isolated data are shared, suddenly a new set of factors arises, both in terms of new external factors, but also in terms of business/microeconomic implications. Therefore, at the core of every digital platform must be a legally, organizationally and commercially viable concept for data sharing/trading/exchange.
When shaping this model, the following questions must be answered:
What is the legal arrangement for data “ownership”? Can users classify their data, is staggered approach possible (closed, traded or open data)? What are legal means that the platform uses to ensure the confidentiality of data ? (Trade Secrets, data base directive)
Transparency: Can users monitor/control the sharing of data with third parties? Are there “expiration dates” for data use?
Is the legal setting a fixed standards (“general conditions”) or is it a flexible, individual approach? Are model contracts available?
Are there sectorial regulatory requirements concerning data?
How far is portability and change of platform possible?
Who is responsible in the case of breaches of confidentiality?
How is fairness/ a level playing field between the platform and smaller players ensured ?
In general data liabilities refer to potential damages in relation to data characteristics (reliability and veracity promised, periodicity and velocity) and the stage in the process of data exploitation. for example in relation to quality of data, data, security breaches, delivery, data analytics misuse or misrepresentation, loss of stored data, access or retrieval of data, etc. In addition, the failure to follow and fulfill contractual obligations outlined in a given contract might lead to liabilities (see next section on industrial contract types for an outline).
Example of Liability Clause: Except in respect of death or personal injury caused by the Supplier’s negligence, the Supplier shall not be liable to the Customer by reason of any representation (unless fraudulent), or any implied warranty, condition or other Term, for any loss of profit or any indirect, special or consequential loss or damage (whether caused by the negligence of the Supplier, its servants or agents or otherwise) in relation to the supply of the Goods (or any failure to supply them) or their resale by the Customer, or otherwise arising out of or in connection with the agreement.