@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} } @article{BilgramBremVoigt2019, author = {Bilgram, Volker and Brem, Alexander and Voigt, Kai-Ingo}, title = {User-centric Innovations in New Product Development}, series = {International Journal of Innovation Management}, volume = {12}, journal = {International Journal of Innovation Management}, number = {3}, publisher = {World Scientific}, address = {London}, issn = {1363-9196}, doi = {10.1142/S1363919608002096}, pages = {419-458}, year = {2019}, abstract = {Corporate innovation management geared to long-term success calls for a strategy to grow innovations into a substantial competitive advantage. This, however, coincides with an enormous failure-rate at the market, especially in the field of breakthrough innovations. Hence, in recent times, companies are trying to alleviate the risk of lacking user-acceptance through opening their innovation processes to external actors, particularly customers. The method of integrating lead users is determined by the effective and systematic identification of leading-edge customers, which is considered to be a critical phase within this approach. With the arrival of Web 2.0 applications, there is a huge potential to improve these selection processes. Our research into online communities and weblogs scrutinised the search criteria in an online environment and revealed the following characteristics as crucial factors for the online identification of lead users: being ahead of a market trend, high expected benefits, user expertise and motivation, extreme user needs as well as opinion leadership and an online commitment.}, language = {en} } @incollection{WoehrlKorteBartletal.2023, author = {W{\"o}hrl, Andrea and Korte, Sophia and Bartl, Michael and Bilgram, Volker and Brem, Alexander}, title = {HOW TO LEVERAGE THE RIGHT USERS AT THE RIGHT TIME WITHIN USER-CENTRIC INNOVATION PROCESSES}, series = {The PDMA Handbook of Innovation and New Product Development}, booktitle = {The PDMA Handbook of Innovation and New Product Development}, editor = {Bstieler, Ludwig and Noble, Charles}, edition = {4}, publisher = {Wiley}, address = {Hoboken}, isbn = {978-1-119-89021-8}, year = {2023}, language = {en} } @article{SchoettelerLiberaBilgramSchoetteleretal.2025, author = {Sch{\"o}tteler Libera, Pedro and Bilgram, Volker and Sch{\"o}tteler, Sebastian and Mammen, Jan}, title = {ChatGPT in the Working World: A Qualitative Study}, series = {Information Resources Management Journal (IRMJ)}, volume = {38}, journal = {Information Resources Management Journal (IRMJ)}, number = {1}, publisher = {IGI Global}, doi = {10.4018/IRMJ.386593}, pages = {26}, year = {2025}, abstract = {The authors investigated how ChatGPT transforms workplace tasks by analyzing qualitative survey responses from 78 U.S. professionals in the fields of software, marketing, and academia. This study addresses a gap in understanding the malleability of generative artificial intelligence in diverse professional contexts, a need underscored by ChatGPT's rapid adoption and mixed impact on work practices. Using a qualitative survey deployed via a validated platform, the authors collected open-ended responses about tasks, challenges, and opportunities. Responses were inductively coded to compare domain-specific applications. The findings show that although ChatGPT is widely used across sectors for tasks such as content creation, research, and idea generation, certain tasks—such as coding in software, strategic communication in marketing, and knowledge acquisition in academia—diverge. The results emphasize the importance of context-sensitive integration strategies and bottom-up adoption approaches to maximize the benefits of artificial intelligence while mitigating risks.}, language = {en} } @article{SchmidtBilgramLaarmann2025, author = {Schmidt, Daniel and Bilgram, Volker and Laarmann, Felix}, title = {Wie KI das Innovationsmanagement revolutioniert}, series = {Ideen- und Innovationsmanagement}, volume = {51}, journal = {Ideen- und Innovationsmanagement}, number = {2}, publisher = {Erich Schmidt Verlag}, address = {Berlin}, issn = {2198-3151}, doi = {10.37307/j.2198-3151.2025.02.07}, pages = {66 -- 72}, year = {2025}, abstract = {K{\"u}nstliche Intelligenz (KI) entwickelt sich als „General-Purpose Technology" zum zentralen Beschleuniger von Innovationsprozessen und ver{\"a}ndert das Innovationsmanagement grundlegend - insbesondere seit dem Durchbruch generativer KI und großer Sprachmodelle. Aufbauend auf einer quantitativen Online-Umfrage unter 45 Innovationsverantwortlichen aus Deutschland, {\"O}sterreich und der Schweiz (Juli-Oktober 2024) analysiert die Studie Einstellungen, aktuelle Nutzung, Potenziale, strategische Verankerung und Barrieren von KI im Innovationsmanagement und vergleicht ausgew{\"a}hlte Ergebnisse mit einer Pr{\"a}-ChatGPT-Studie (F{\"u}ller et al., 2022). Die Befragten stehen KI mehrheitlich positiv gegen{\"u}ber, zugleich bleibt die Nutzung im Innovationsmanagement hinter der allgemeinen KI-Adoption in Unternehmen zur{\"u}ck: Viele Organisationen experimentieren, aber nur wenige skalieren systematisch. Besonders deutlich zeigt sich seit 2022 eine Verschiebung von analytischen hin zu kreativen Anwendungen (z. B. Ideengenerierung, Design, Prototyping), w{\"a}hrend evaluative und nutzerzentrierte Aufgaben (z. B. User/Concept Testing) weiterhin {\"u}berwiegend menschlich gepr{\"a}gt sind. Als wichtigste erwartete Nutzen werden Effizienzgewinne, schnellere Datenverarbeitung, k{\"u}rzere Entwicklungszyklen und Kostensenkung genannt, w{\"a}hrend Qualit{\"a}tsverbesserung nachrangig bleibt. Strategisch fehlt h{\"a}ufig eine koh{\"a}rente KI-Strategie; Investitionen sind meist moderat, sollen jedoch in den n{\"a}chsten Jahren steigen. Zentrale Hemmnisse sind mangelnde Kompetenz und Orientierung auf F{\"u}hrungsebene sowie Datenschutz- und Sicherheitsbedenken. Daraus leitet die Studie Managementimplikationen ab: KI strategisch verankern, kreative Einsatzfelder gezielt erschließen, Kompetenzen aufbauen, Pilotprojekte skalieren und Governance/Security fr{\"u}hzeitig adressieren.}, language = {de} } @incollection{HahnJoostenKlugetal.2025, author = {Hahn, Alexander and Joosten, Jan and Klug, Katharina and Bilgram, Volker}, title = {Embracing Digital Empathy}, series = {Artificial Intelligence in Business and Engineering}, booktitle = {Artificial Intelligence in Business and Engineering}, editor = {Hofbauer, G{\"u}nter}, publisher = {Kohlhammer}, address = {Stuttgart}, isbn = {978-3-17-046742-2}, pages = {51 - 67}, year = {2025}, language = {en} } @article{BremBilgramGutstein2018, author = {Brem, Alexander and Bilgram, Volker and Gutstein, Adele}, title = {Involving Lead Users in Innovation: A Structured Summary of Research on the Lead User Method}, series = {International Journal of Innovation and Technology Management}, volume = {15}, journal = {International Journal of Innovation and Technology Management}, number = {03}, publisher = {World Scientific Pub Co Pte Lt}, issn = {0219-8770}, doi = {10.1142/S0219877018500220}, year = {2018}, abstract = {Research on the lead user method has been conducted for more than thirty years and has shown that the method is more likely to generate breakthrough innovation than traditional market research tools. Based on a systematic literature review, this paper shows a detailed view on the broad variety of research on lead user characteristics, lead user processes, lead user identification and application, and success factors. The main challenge of the lead user method as identified in literature is the resource issue regarding time, manpower, and costs. Also, internal acceptance and the processing of the method have been spotted in literature, as well as the intellectual property protection issue. From the starting point of the initial lead user method process introduced by L{\"u}thje and Herstatt (2004), results are integrated into a revisited view on the lead user method process. In addition, concrete suggestions for corporate realization options are given. The article closes with limitations and future research suggestions.}, language = {en} } @article{BilgramLaarmann2023, author = {Bilgram, Volker and Laarmann, Felix}, title = {Accelerating Innovation With Generative AI: AI-Augmented Digital Prototyping and Innovation Methods}, series = {IEEE Engineering Management Review}, volume = {51}, journal = {IEEE Engineering Management Review}, number = {2}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, issn = {0360-8581}, doi = {10.1109/EMR.2023.3272799}, pages = {18 -- 25}, year = {2023}, abstract = {Easy-to-use generative artificial intelligence (AI) is democratizing the use of AI in innovation management and may significantly change the way how we work and innovate. In this article, we show how large language models (LLMs), such as generative pretrained transformer (GPT), can augment the early phases of innovation, in particular, exploration, ideation, and digital prototyping. Drawing on six months of experimenting with LLMs in internal and client innovation projects, we share first-hand experiences and concrete examples of AI-assisted approaches. The article highlights a large variety of use cases for generative AI ranging from user journey mapping to idea generation and prototyping and foreshadows the promising role LLMs may play in future knowledge management systems. Moreover, we argue that generative AI may become a game changer in early prototyping as the delegation of tasks to an artificial agent can result in faster iterations and reduced costs. Our experiences also provide insights into how human innovation teams purposively and effectively interact with AIs and integrate them into their workflows.}, language = {en} } @techreport{FuellerBilgramWahletal.2022, author = {F{\"u}ller, Johann and Bilgram, Volker and Wahl, Julian and Hutter, Katja}, title = {Autonomous Innovation - How AI is implemented in Innovation Management}, year = {2022}, abstract = {Success stories about the groundbreaking impact of artificial intelligence (AI) technology on business are omnipresent, and the benefits that might emerge for innovation management are the talk of the town. However, managers are still struggling to find the appropriate approach for applying AI in their innovation projects. At this early stage in the age of AI, companies differ in how they leverage the opportunities afforded by AI and seek guidance. Our study among 162 tech-savvy managers highlights the current state of AI usage in innovation management, reveals different implementation patterns, and provides guidance in finding the right approach to increase innovation performance using AI technology. We find that companies follow distinct implementation approaches that differ regarding strategy, organizational setup, capability building, and scaling, which results in three user groups: 39\% of participants consider themselves "AI-Leaders", the most progressive group when it comes to dealing with the technology and breaking ground in AI-driven innovation management. 30\% belong to the "AI-Pragmatists" user group that is ambitious in applying AI, while 31\% are „AI Aspirants" only rarely using AI for their innovation processes. A vast majority of the participants anticipates overall improvements in innovation performance by more than 50\%, as they expect the effectiveness and efficiency of new product development to increase significantly. However, companies still face severe implementation challenges, such as missing data access or a lack of technical expertise. Depending on their individual characteristics, companies should take deliberate strategies to advance in the autonomous innovation game.}, language = {en} } @article{BilgramFuellerKochetal.2012, author = {Bilgram, Volker and F{\"u}ller, Johann and Koch, Giordano and Rapp, Maximilian}, title = {The Potential of Crowdsourcing for Co-Marketing: How Consumers may be Turned into Brand Ambassadors}, series = {Transfer - Werbeforschung und Praxis}, journal = {Transfer - Werbeforschung und Praxis}, number = {4}, pages = {42-48}, year = {2012}, language = {en} }