@article{BielHahnBilgrametal.2025, author = {Biel, Stefan and Hahn, Alexander and Bilgram, Volker and Rogers, Helen}, title = {From Hybrid to AI-First Innovation Management}, series = {IEEE Engineering Management Review}, journal = {IEEE Engineering Management Review}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, issn = {0360-8581}, doi = {10.1109/EMR.2025.3527744}, pages = {1 -- 11}, year = {2025}, abstract = {The rise of generative Artificial Intelligence (AI) in traditionally human domains of creativity signifies a profound development in product innovation management. In this article, we investigate the evolving role of innovation managers, emphasizing a transition from problem-solving to sense-making and decision-making. Additionally, we delve into organizational strategies for effective AI integration, advocating for systematic experimentation, comprehensive training, and the development of AI-first innovation frameworks for new product development (NPD). Ultimately, we propose a paradigm shift to AI-first creative processes, where AI is not merely an extension but the foundational mechanism of the innovation workflow.}, language = {en} } @incollection{HahnHofmannBilgrametal.2016, author = {Hahn, Alexander and Hofmann, Rupert and Bilgram, Volker and Schwarz, Jan Oliver and Meinheit, Andreas and F{\"u}ller, Johann}, title = {Easy Rider}, series = {Die fr{\"u}he Phase des Innovationsprozesses}, booktitle = {Die fr{\"u}he Phase des Innovationsprozesses}, publisher = {Springer Fachmedien Wiesbaden}, address = {Wiesbaden}, isbn = {9783658097219}, doi = {10.1007/978-3-658-09722-6_5}, pages = {75 -- 98}, year = {2016}, abstract = {Dieser Beitrag f{\"u}hrt anhand eines konkreten Studienbeispiels aus, wie die AUDI AG komplexe zuk{\"u}nftige Entwicklungen wie „autonomes Fahren" mittels multidisziplin{\"a}rer Studien analysiert. Die Autoren beschreiben, welche Insight- und Foresight-Methoden dabei zum Einsatz kommen und was eine erfolgreiche Durchf{\"u}hrung ausmacht. Dabei gehen sie insbesondere auf das Konzept der Trend Receiver ein. Abschließend geben sie einen Ausblick auf zuk{\"u}nftige Weiterentwicklungen der Vorgehensweise.}, language = {de} } @article{BilgramHahnFueller2023, author = {Bilgram, Volker and Hahn, Alexander and F{\"u}ller, Johann}, title = {«Golden Crowd»: Engaging the Users that Deliver on Your Crowdsourcing Goals}, series = {Marketing Review St. Gallen}, volume = {39}, journal = {Marketing Review St. Gallen}, number = {6}, publisher = {Thexis Verlag, St. Gallen}, issn = {1865-7516}, pages = {20}, year = {2023}, abstract = {Companies run branded crowdsourcing contests to achieve two main goals: generate ideas and create brand equity. This paper provides an empirical typology of contest users and reveals five distinct user types: jacks-of-all-trades, devoted brand fans, pure innovators, reward seekers and passive customers. Based on the users' characteristics we derive actionable insights on how to attract, recruit and manage the crowd for different purposes.}, language = {en} } @inproceedings{BilgramHahnJoostenetal.2024, author = {Bilgram, Volker and Hahn, Alexander and Joosten, Jan and Totzek, Dirk}, title = {Comparing the Ideation Quality of Humans With Generative Artificial Intelligence}, series = {IEEE Engineering Management Review}, volume = {52}, booktitle = {IEEE Engineering Management Review}, number = {2}, issn = {0360-8581}, doi = {10.1109/EMR.2024.3353338}, pages = {153-164}, year = {2024}, abstract = {Traditionally, ideating new product innovations is primarily the responsibility of marketers, engineers, and designers. However, a rapidly growing interest lies in leveraging generative artificial intelligence (AI) to brainstorm new product and service ideas. This study conducts a comparative analysis of ideas generated by human professionals and an AI system. The results of a blind expert evaluation show that AI-generated ideas score significantly higher in novelty and customer benefit, while their feasibility scores are similar to those of human ideas. Overall, AI-generated ideas comprise the majority of the top-performing ideas, while human-generated ideas scored lower than expected. The executive's emotional and cognitive reactions were measured during the evaluation to check for potential biases and showed no differences between the idea groups. These findings suggest that, under certain circumstances, companies can benefit from integrating generative AI into their traditional idea-generation processes.}, language = {en} } @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{JoostenKlugBilgrametal.2024, author = {Joosten, Jan and Klug, Katharina and Bilgram, Volker and Hahn, Alexander}, title = {Ideation: Die Qualit{\"a}t Menschen- und KI-generierter Ideen im Vergleich.}, series = {Transfer: Zeitschrift f{\"u}r Kommunikation \& Markenmanagement}, volume = {70}, journal = {Transfer: Zeitschrift f{\"u}r Kommunikation \& Markenmanagement}, number = {4}, issn = {2628-3409}, pages = {18 -- 23}, year = {2024}, abstract = {F{\"u}r die Marken- und Ideenentwicklung im Produkt- und Dienstleistungsbereich sind in der Regel Marketing- und Markenmanager sowie Designer verantwortlich. Gleichzeitig w{\"a}chst das Interesse am Einsatz generativer K{\"u}nstlicher Intelligenz (KI) zur Ideenfindung im Markenmanagement. Diese Studie analysiert, wie KI-generierte Ideen im Vergleich zu von Menschen generierten Ideen abschneiden. Die Ergebnisse einer blinden Expertenbeurteilung zeigen, dass KI-generierte Ideen in Bezug auf Neuheit und Kundennutzen signifikant besser bewertet werden, w{\"a}hrend sie in Bezug auf die Umsetzbarkeit {\"a}hnlich abschneiden wie von Menschen generierte Ideen. Diese Ergebnisse legen nahe, dass Markenmanager in bestimmten Kontexten von der Integration generativer KI in ihren traditionellen Ideenfindungsprozess profitieren k{\"o}nnen.}, language = {de} }