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Business model renewal & the value of a digital solution

A case study of digital transformation in manufacturing companies

Written by E. Dolk, F. Magnusson

Paper category

Master Thesis


Business Administration>Supply Chain & Logistics




Master Thesis: Business model terminology The business model lacks a clear definition, partly because different authors attribute different components to the business model (Bouwman et al., 2018). This is also because different authors use the term, even if they are not referring to the same thing (Osterwalder et al., 2005). Bowman et al. (2018) defines a business model as the logic of an organization or network of organizations to create and obtain value for consumers and enterprises. According to this, Schallmo (2013) means that the business model describes what benefits are provided to customers and partners, and how these benefits are returned to the company as revenue. Bouwman et al. (2018) means that the business model is composed of business model components, such as value proposition and revenue model, while Schallmo (2013) means that the business model is composed of many different dimensions and elements. The ultimate goal is to form dimensions and elements in a mutually reinforcing way to make it more difficult for competitors to replicate business models. The dimensions and elements described by Schallmo (2013) are as follows: • The customer dimension includes customer segmentation, channels, and relationships. • The benefit dimension composed of products, services and values. • Including value-added dimensions of resources, skills and processes. •Partner dimensions, including partners, partner channels, and partnerships. • A financial dimension composed of income and expenses. 2.1.1. Digital transformation of business model In order to give a clear definition of digital transformation of business model, Schallmo (2016) used his previous definition of business model and combined the definition of digital transformation (DT). This led to the following definition: The DT of a business model involves a single business model element, the entire business model, the value-added chain, and the network of different participants in the value-added network. The degree of DT includes incremental (marginal) and fundamental (fundamental) changes in business models. The reference unit for novelty is mainly customers, but DT can also influence its own business, partners, industries, and competitors. In the DT of the business model, enabling factors and technologies (such as big data) are used to generate new applications or services (such as on-demand forecasting). These enablers require skills to collect and exchange data and the ability to analyze, calculate, and evaluate options. The evaluated options are used to initiate new processes in the business model. 2.2. Creating value with digital solutions. Some studies describe services as a value creation perspective, rather than market categories (Edvardsson et al., 2005). The origin of value creation is in this service-centric view, which is derived from the use of products and services by customers through the application of their knowledge and skills (Vargo et al., 2008). This means that the customer is responsible for creating value, while the supplier acts as a co-creator of value (Grönroos 2008). However, value co-creation occurs only when suppliers and customers interact in the value creation process (Grönroos & Voima 2013; Vargo et al. 2008). The quality of this interaction is the key to value co-creation (Grönroos & Voima 2013; Vargo et al. 2008). Research conducted has shown that digitization is playing an increasing role in supporting customer interaction and value co-creation (Lerch & Gotsch 2015). 2.2.1. Digital capabilities. Through the study of four large manufacturing companies established in Europe, they all have outstanding performance in providing advanced services supported by digital platforms in their respective industries, Wincent et al. (2017) studied the digital capabilities necessary to support the co-creation of value with customers, and how these digital capabilities enable companies to interact and participate in value co-creation activities. This has led to three different categories of digital capabilities; intelligence, connectivity, and analysis. Intelligent ability refers to the ability to use hardware components to perceive and record information with little human intervention. This has two elements; first, it enhances the intelligent functions of the product or machine to enable it to respond to changes in its environment (Wincent et al. 2017). Second, it provides the ability to collect information about product usage and the condition of certain components (Wincent et al. 2017). Connectivity is the ability to connect digital products through wireless communication networks (Wincent et al. 2017). This enables data to be stored in a virtual platform, thereby reducing the need for on-site storage and processing power, thereby increasing efficiency and reducing costs. Another advantage related to connectivity is the connectivity between products; either the connection between one product and another, or the connection between many products at the same time. This represents the potential to realize new value creation scenarios through synchronized monitoring, control and optimization activities (Wincent et al., 2017). Finally, analytical capabilities are the ability to transform data into insights and into insights through a large amount of information obtained from smart products and networks. Turn these into actionable instructions for the company (Wincent et al., 2017). Vincent et al. (2017) identified two elements related to analytical capabilities. Read Less