This paper seeks to make a contribution to business model experimentation for sustainability by putting forward a relatively simple tool. This tool calculates the financial and sustainability impact based on the SDG’s of a newly proposed business model (BM). BM experimentation is described by Bocken et al. (2019) as an iterative-multi-actor experimentation process. At the final experimentation phases some form of sustainability measurement will be necessary in order to validate if the new proposed business model will be achieving the aims set in the project. Despite the plethora of tools, research indicates that tools that fit needs and expectations are scarce, lack the specific focus on sustainable BM innovation, or may be too complex and demanding in terms of time commitment (Bocken, Strupeit, Whalen, & Nußholz, 2019a). In this abstract we address this gap, or current inability of calculating the financial and sustainability effect of a proposed sustainable BM in an integrated, time effective manner. By offering a practical tool that allows for this calculation, we aim to answer the research question; “How can the expected financial and sustainability impact of BMs be forecasted within the framework of BM experimentation?
DOCUMENT
In our in-depth case study on two circular business models we found important roles for material scouts and networks. These key partners are essential for establishing circular business models and circular flow of materials. Besides, we diagnose that companies are having difficulties to develop viable value propositions and circular strategies. The paper was presented at NBM Nijmegen 2020 and will be published at a later date
DOCUMENT
IntroductionThe growing availability of data offers plenty of opportunities for data-driven innovation of business models. This certainly applies to interactive mediacompanies. Interactive media companies are engaged in the development, provisioning, and exploitation of interactive media services and applications.Through the service interactions, they may collect large amounts of data which can be used to enhance applications or even define new propositions and business models. According to Lippell (2016), media companies can publish content in more sophisticated ways. They can build a deeper and more engaging customer relationship based on a deeper understanding of their users. Indeed, research from Weill & Woerner (2015) suggests that companies involved in the digitalecosystem that better understand their customers than their average competitor have significantly higher profit margins than their industry averages. Moreover, the same research suggests that businesses need to think more broadly about their position in the ecosystem. Open innovation and collaboration are essential for new growth, for example combining data within and across industries (Parmar et al., 2014). However, according to (Mathis and Köbler, 2016), these opportunities remain largely untapped as especially SMEs lack the knowledge and processes to translate data into attractive propositions and design viable data driven business models (DDBM). In this paper, we investigate how interactive media companies can structurally gain more insight and value from data and how they can develop DDBM. We define a DDBM as a business model relying on data as a key resource (Hartmann et al., 2016).
DOCUMENT
