{"id":465,"date":"2021-11-25T11:41:31","date_gmt":"2021-11-25T10:41:31","guid":{"rendered":"https:\/\/blog.zhaw.ch\/digital-futures-lab\/?p=465"},"modified":"2021-11-25T15:52:11","modified_gmt":"2021-11-25T14:52:11","slug":"smart-connected-products-jurg-meierhofer-and-team-win-best-paper-award","status":"publish","type":"post","link":"https:\/\/blog.zhaw.ch\/digital-futures-lab\/2021\/11\/25\/smart-connected-products-jurg-meierhofer-and-team-win-best-paper-award\/","title":{"rendered":"Smart, connected products: J\u00fcrg Meierhofer and team win Best Paper Award"},"content":{"rendered":"\n

J\u00fcrg Meierhofer, Christoph Heitz, and Frank Hannich won the Best Paper Award in the Service Science category at the Naples Forum on Service 2021<\/a> for their paper on optimising service value creation with smart, connected products. The paper was written as part of a DIZH Fellowship.<\/strong><\/p>\n\n\n\n

The paper describes a novel quantitative model for the design of the service interactions in the life cycle of customers using smart connected products \u2013 typically in industrial environments, i.e., in Industry 4.0 context \u2013 with the goal of optimising mutual service value creation for both the customer and the provider.<\/p>\n\n\n\n

The paper can be downloaded here.<\/a><\/p>\n\n\n\n

J\u00fcrg<\/a>, congratulations on the Best Paper Award! What is the paper about and what are your findings?<\/strong><\/h2>\n\n\n\n

First, I would like to thank Christoph Heitz for his inspiring thoughts for the quantitative model and Frank Hannich for embedding our model in the concept of the customer lifecycle!<\/p>\n\n\n\n

Industry and economy in general are moving to a world where products get connected with the provider over the internet-of-things. Thus, providers and their customers stay in a closer relationship potentially over the entire lifecycle \u2013 from pre-sales until the end-of-life of a product – and can continuously exchange data. This contains many interesting opportunities for additional value creation for the customer and the provider overall and in the individual phases of the customer lifecycle. However, this also creates additional costs, which need to be traded off against the benefits. Our model provides a means to do this trade-off on a quantitative basis and to achieve optimised service designs.<\/p>\n\n\n\n

How can your findings be used by others, for example by companies?<\/strong><\/h2>\n\n\n\n

The model helps companies to design and optimise data-driven value creation along the customer lifecycle in a conscious way based on quantitative measures. Companies learn in which part of the lifecycle it is worth to invest in using the data for more value creation and in which not. This is especially important for manufacturers of high value products that are expected to create value over a longer time period, in particular also after the sales moment. Manufacturers selling high value machines to business customers across the world are a typical example. In the paper, we discuss use case of a provider of professional printers used in small advertising companies.<\/p>\n\n\n\n