@inproceedings{MarchukBielBilgrametal.2018, author = {Marchuk, Anna and Biel, Stefan and Bilgram, Volker and Worning, Signe}, title = {Standing on the Shoulders of Giants}, year = {2018}, language = {en} } @incollection{MarchukBielBilgrametal.2020, author = {Marchuk, Anna and Biel, Stefan and Bilgram, Volker and Worning, Signe and Jensen, L{\o}gstrup}, title = {The Best of Both Worlds : Methodological Insights on Combining Human and AI Labor in Netnography}, series = {Netnography Unlimited : Understanding Technoculture Using Qualitative Social Media Research}, booktitle = {Netnography Unlimited : Understanding Technoculture Using Qualitative Social Media Research}, publisher = {Routledge}, address = {New York, NY}, isbn = {9781003001430}, doi = {10.4324/9781003001430}, pages = {21}, year = {2020}, abstract = {Rapidly growing volumes of data create opportunities. For netnographic researchers, they also create challenges. As the amount of data increases, collecting, understanding, and meaningfully combining data can become more difficult. Traditionally, the netnography research process was predominantly in the hands of humans with limited software support. We assert that advances in the field of artificial intelligence and deep learning in particular allow intelligent machines to take over more and more of the steps in netnography. The challenge is to understand what parts of netnography can be performed by machines, what is better accomplished by humans, and how both can outperform any prior approach by working together. In this chapter, we analyzed two HYVE innovation projects conducted with the company Beiersdorf. Both projects had exactly the same briefing. However, one project followed a human-driven insight process, and the other approach relied heavily on the latest technologies in the domain of machine learning. By comparing these two paths, our study reveals a new vision for a Golden Age of cooperation between human and machine netnographers that might exist in the near future of netnographic research.}, language = {en} } @article{BremBilgramMarchuk2019, author = {Brem, Alexander and Bilgram, Volker and Marchuk, Anna}, title = {How crowdfunding platforms change the nature of user innovation - from problem solving to entrepreneurship}, series = {Technological Forecasting and Social Change}, volume = {144}, journal = {Technological Forecasting and Social Change}, publisher = {Elsevier BV}, issn = {0040-1625}, doi = {10.1016/j.techfore.2017.11.020}, pages = {348 -- 360}, year = {2019}, abstract = {Crowdfunding has become a key research trend in recent years providing a new form of acquiring funding for innovation projects from users prior to the realization of the product in a 'market before the market'. In this paper, we link the concept of crowdfunding with the user innovation phenomenon and show how user innovators harness crowdfunding to complement their innovative behavior and obtain funding to build firms and produce products in a more professional way. Conducting three case studies ranging from low- to high-tech crowdfunding campaigns, we investigate how crowdfunding impacts constituent dimensions of user innovation theory such as user motivation, user role, user community, collaboration between users and user investments. In particular, we argue that crowdfunding platforms (CFPs) may give rise to a more widespread occurrence of user entrepreneurs, who found a firm to commercialize their product or service in a marketplace they have created for their own need. Hence, we show the development from traditional user innovation to crowdfunding-enabled user innovation, which democratizes not only the creation but also the more large-scale commercialization of new products and services.}, language = {en} }