Prof. Jürg Meierhofer, Dr. sc. ETH, executive MBA iimt

ZHAW School of Engineering
IDS Institut für Data Science
Technikumstrasse 81
8400 Winterthur

+41 (0) 58 934 40 52
juerg.meierhofer@zhaw.ch

Arbeit an der ZHAW

Tätigkeit

Leiter Forschungsschwerpunkt Smart Services and Operations

Arbeits- und Forschungsschwerpunkte

Lehrtätigkeit

Studienleiter Smart Service Engineering (CAS)
Studienleiter Industrie 4.0 (MAS)
Service Operations and Management (TSM_OpMgmt)
Smart services (CM_SmartSer)
Master in Circular Economy Management
Service Engineering Basics (im Bachelor Wirtschaftsingenieurwesen)
Service Engineering Labor (im Bachelor Wirtschaftsingenieurwesen)

Lehrtätigkeit in der Weiterbildung

Berufserfahrung

head of department "Innovation Projects", senior management consultant
Die Mobiliar
12 / 2012 - 08 / 2016
head of department, head of service champion program, lean management
Swisscom
05 / 2005 - 11 / 2012
Research Fellow
ZHW
03 / 2003 - 04 / 2005
Projektleiter Mobilkommunikation
Bluewin AG
08 / 2001 - 02 / 2003
Projektleiter Mobile Services
Swisscom Mobile AG
03 / 2000 - 07 / 2001
Forschungsassistent
ETH Zürich
10 / 1994 - 02 / 2000

Aus- und Weiterbildung

Ausbildung

Executive MBA / ICT Management
Université de Fribourg, international institute of management in technology (iimt)
02 / 2002 - 12 / 2005
Dr. sc. techn. ETH / Elektrotechnik, Telekommunikation
ETH Zürich
08 / 1997 - 07 / 2000
Dipl. NDS ETH / information technology
ETH Zürich
10 / 1994 - 06 / 1998
Dipl. El.-Ing. ETH / Elektrotechnik
ETH Zürich
10 / 1989 - 05 / 1994

Weiterbildung

Hochschuldidaktische Qualifikation
ZHAW Zürcher Hochschule für Angewandte Wissenschaften
06 / 2019

Netzwerk

Mitglied in Netzwerken

ORCID digital identifier

ORCID ID: 0000-0003-1645-5686

Auszeichnungen

Best Paper Award
Spring Servitization Konferenz 2024
05 / 2024
Best Paper Award
Swiss Conference on Data Science
06 / 2022
Best Paper Award Category Service Science
Naples Forum on Service
09 / 2021

Social Media

Medienpräsenz

SRF Eco

Projekte

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

Meierhofer, J., Wulf, J., Gallina, V., Gal, B., & Eisl, S. (2025). Optimising data driven value creation in industrial services incorporating circularity. International Journal of Mechatronics and Manufacturing Systems, 17(4), 449–469. https://doi.org/10.1504/ijmms.2024.144291
Meierhofer, J., & Heitz, C. (2023). On the value of data in industrial services : how to optimize value creation by reconfiguration of operant resources. Journal of Creating Value, 9(2), 245–258. https://doi.org/10.1177/23949643231199002
Baldenweg-Bölle, U., Meierhofer, J., & Mertes, A. (2022). Co-creating service value from data in a public administration context. Swiss Yearbook of Administrative Sciences, 13(1), 35–50. https://doi.org/10.5334/ssas.163
Meierhofer, J., Schweiger, L., Lu, J., Züst, S., West, S., Stoll, O., & Kiritsis, D. (2021). Digital twin-enabled decision support services in industrial ecosystems. Applied Sciences, 11(23), 11418. https://doi.org/10.3390/app112311418
West, S., Stoll, O., Meierhofer, J., & Züst, S. (2021). Digital twin providing new opportunities for value co-creation through supporting decision-making. Applied Sciences, 11(9), 3750. https://doi.org/10.3390/app11093750

Bücher, peer-reviewed

Meierhofer, J. (2025). Data Sharing für KMU : Voraussetzungen und Instrumente für die gemeinsame Nutzung von Daten (P. Kugler, M. Dobler, J. Meierhofer, M. Strittmatter, M. Treiterer, & H. Vogt, eds.; 1. Auflage). Springer. https://doi.org/10.1007/978-3-662-71209-2

Buchbeiträge, peer-reviewed

Meierhofer, J., & Benedech, R. (2025). Den Wert von Daten bestimmen. In P. Kugler, M. Dobler, J. Meierhofer, M. Strittmatter, M. Treiterer, & H. Vogt (eds.), Data Sharing für KMU : Voraussetzungen und Instrumente für die gemeinsame Nutzung von Daten (pp. 51–56). Springer. https://doi.org/10.1007/978-3-662-71209-2_4
Wulf, J., & Meierhofer, J. (2025). Large Language Models und Datenökosysteme zur Automatisierung des technischen Kundendienstes. In P. Kugler, M. Dobler, J. Meierhofer, M. Strittmatter, M. Treiterer, & H. Vogt (eds.), Data Sharing für KMU : Voraussetzungen und Instrumente für die gemeinsame Nutzung von Daten (pp. 189–203). Springer. https://doi.org/10.1007/978-3-662-71209-2_11
Marquart, P., Vogt, H., Kugler, P., & Meierhofer, J. (2025). Fallstudie Grüninger Mühlen. In P. Kugler, M. Dobler, J. Meierhofer, M. Strittmatter, M. Treiterer, & H. Vogt (eds.), Data Sharing für KMU (pp. 255–270). Springer Gabler. https://doi.org/10.1007/978-3-662-71209-2_16
Höppli, R., Kaiser, R., Meierhofer, J., Kugler, P., & Vogt, H. (2025). Fallstudie Cleanfix : vernetzte Reinigungsroboter für Qualität und Effizienz. In P. Kugler, M. Dobler, J. Meierhofer, M. Strittmatter, M. Treiterer, & H. Vogt (eds.), Data Sharing für KMU (pp. 229–240). Springer Gabler. https://doi.org/10.1007/978-3-662-71209-2_14
Kugler, P., Vogt, H., Meierhofer, J., Dobler, M., Strittmatter, M., Treiterer, M., & Schick, S. (2024). Daten im B2B-Ökosystem teilen und nutzen : wie KMU Voraussetzungen schaffen und Hürden überwinden. In Digitale Plattformen und Ökosysteme im B2B-Bereich (pp. 209–240). Springer. https://doi.org/10.1007/978-3-658-43130-3_8
Meierhofer, J., Lindegger, R., & Brunner, R. (2022). Nutzen für BürgerInnen und Verwaltung durch einen Smart Service-orientierten Gestaltungsansatz. In L. E. Pleger & A. Mertes (eds.), Digitale Transformation der öffentlichen Verwaltung in der Schweiz : Stand, Entwicklungslinien und Praxisbeispiele (pp. 219–241). Springer. https://doi.org/10.1007/978-3-658-36591-2_10
Meierhofer, J., Stadelmann, T., & Cieliebak, M. (2019). Data products. In M. Braschler, T. Stadelmann, & K. Stockinger (Eds.), Applied data science : lessons learned for the data-driven business (pp. 47–61). Springer. https://doi.org/10.1007/978-3-030-11821-1_4
Hollenstein, L., Lichtensteiger, L., Stadelmann, T., Amirian, M., Budde, L., Meierhofer, J., Füchslin, R. M., & Friedli, T. (2019). Unsupervised learning and simulation for complexity management in business operations. In M. Braschler, T. Stadelmann, & K. Stockinger (Eds.), Applied data science : lessons learned for the data-driven business (pp. 313–331). Springer. https://doi.org/10.1007/978-3-030-11821-1_17

Schriftliche Konferenzbeiträge, peer-reviewed

Wulf, J., Meierhofer, J., & Pascher, N. (2026). Guided operations and maintenance with retrieval-augmented generation : system design and evaluation at a machine manufacturer [Conference paper]. Procedia CIRP, 139, 349–354. https://doi.org/10.1016/j.procir.2025.09.030
Wulf, J., West, S., Anderson, M., Mueller-Csernetzky, P., & Meierhofer, J. (2025). On the value potential of large language models in the manufacturing industry [Conference paper]. In S. West, J. Meierhofer, T. Buecheler, & G. Wally Scurati (Eds.), Smart Services Summit : Proceedings of the Sixth Conference, held in Zurich, Switzerland in October 2024. Springer. https://doi.org/10.1007/978-3-031-86958-7_10
Stieger, R., Meierhofer, J., Schäfer, A., Baumgartner, C., & Strebel, M. (2025). Social value creation by smart services. The 9th Naples Forum on Service, Sorrento, Italy, 9-12 June 2025. https://doi.org/10.21256/zhaw-34803
Smart Services Summit: proceedings of the sixth conference, held in Zurich, Switzerland in October 2024. (2025). In S. West, J. Meierhofer, T. Buecheler, & G. Wally Scurati (Eds.), 6th Smart Services Summit, Zurich, Switzerland, 24 October 2025. Springer. https://doi.org/10.1007/978-3-031-86958-7
Beppi, C., Meierhofer, J., & Wulf, J. (2025). Enhancing social and emotional value through smart services. Spring Servitization Conference, Liverpool, United Kingdom, 12-14 May 2025.
Stieger, R., Meierhofer, J., & Schäfer, A. (2025). The social value of data-driven industrial services : exploring triple bottom line impacts through smart solutions [Conference paper]. QUIS19 Proceedings, 481–484. https://doi.org/10.21256/zhaw-34816
Strittmatter, M., Meyer, J., Dobler, M., Kugler, P., Vogt, H., Soriano, M. S., Meierhofer, J., & Gladis, E. (2025, October 24). From regulation to realization : navigating the EU Data Act’s opportunities and challenges. Smart Services Summit : Smart Services for a Sustainable and Resilient Future. https://doi.org/10.21256/zhaw-35913
Wulf, J., & Meierhofer, J. (2025). The impact of large language models on task automation in manufacturing services [Conference paper]. Procedia CIRP, 134, 1089–1094. https://doi.org/10.1016/j.procir.2025.03.071
Strittmatter, M., Meyer, J., Meierhofer, J., Vogt, H., Kugler, P., & Dobler, M. (2025). The EU Data Act : opportunities and research perspectives for data-driven companies [Conference paper]. In S. West, J. Meierhofer, T. Buecheler, & G. Wally Scurati (Eds.), Smart Services Summit (pp. 21–33). Springer. https://doi.org/10.1007/978-3-031-86958-7_2
Wulf, J., & Meierhofer, J. (2025, January 30). Mitigating risks in large language model applications for manufacturing. 10. F&E-Konferenz, Rotkreuz, Schweiz, 30. Januar 2025. https://doi.org/10.21256/zhaw-33327
Smart Services Summit. (2024). In S. West, J. Meierhofer, & T. Buecheler (Eds.), 5th Smart Services Summit, Zurich, Switzerland, 27 October 2023. Springer. https://doi.org/10.1007/978-3-031-60313-6
Meierhofer, J., Pascher, N., & Wulf, J. (2024). The value of solving pains [Conference paper]. In S. West, J. Meierhofer, T. Bücheler, & G. Wally Scurat (Eds.), Smart Services Summit : Proceedings of the Sixth Conference, held in Zurich, Switzerland in October 2024 (pp. 37–48). Springer. https://doi.org/10.1007/978-3-031-86958-7_3
Stucki, M., Meierhofer, J., Gal, B., Gallina, V., & Eisl, S. (2024). Data driven value creation in industrial services including remanufacturing [Conference paper]. Procedia Computer Science, 232, 2240–2248. https://doi.org/10.1016/j.procs.2024.02.043
Wulf, J., & Meierhofer, J. (2024). Towards a taxonomy of Large Language Model based business model transformations [Conference paper]. In S. West, J. Meierhofer, & T. Buecheler (Eds.), Smart Services Summit : Building Resilience in a Changing World (pp. 119–131). Springer. https://doi.org/10.1007/978-3-031-60313-6_9
Weisskopf, S. A., Meierhofer, J., & Sordini, F. V. (2024). Quantitative models for sustainable smart services in the building industry [Conference paper]. In S. West, J. Meierhofer, & T. Buecheler (Eds.), Smart Services Summit : building resilience in a changing world (pp. 29–41). Springer. https://doi.org/10.1007/978-3-031-60313-6_3
Benedech, R., Moorthy, A. R., Weisskopf, S., Meierhofer, J., & Rapaccini, M. (2024). Unveiling the synergy : economic and environmental value of building management systems in the era of digital service innovation [Conference paper]. In A. Z. Bigdeli, T. Baines, & H. Akkermans (Eds.), Digital Service Innovation: Redefining Provider-Customer Interactions : Proceedings of the Spring Servitization Conference (pp. 181–192). The Advanced Services Group. https://doi.org/10.21256/zhaw-30883
Wulf, J., & Meierhofer, J. (2024). Exploring the potential of large language models for automation in technical customer service [Conference paper]. In A. Z. Bigdeli, T. Baines, & H. Akkermans (Eds.), Digital Service Innovation: Redefining Provider-Customer Interactions : Proceedings of the Spring Servitization Conference (pp. 146–157). The Advanced Services Group. https://doi.org/10.21256/zhaw-30660
Wulf, J., & Meierhofer, J. (2024, January 24). Automation of technical customer support with large language models. 9. F&E Konferenz Zu Industrie 4.0, Zürich, Schweiz, 24. Januar 2024. https://doi.org/10.21256/zhaw-33328
Meierhofer, J., & Stucki, M. (2023). Sustainable value optimization by smart services along the customer lifecycle [Conference paper]. In J. Meierhofer, S. West, & T. Buecheler (Eds.), Smart Services Summit : smart services creating sustainability (pp. 23–30). Springer. https://doi.org/10.1007/978-3-031-36698-7_3
Smart Services Summit : smart services creating sustainability. (2023). In J. Meierhofer, S. West, & T. Buecheler (Eds.), Fifth Smart Services Summit, Zurich, Switzerland, 21 October 2022. Springer. https://doi.org/10.1007/978-3-031-36698-7
Weisskopf, S., & Meierhofer, J. (2023). Industrial smart services for circular economy [Conference paper]. In A. Z. Bigdeli, M. Kohtamäki, R. Rabetino, & T. Baines (Eds.), The Role of Servitization in Grand Challenges (pp. 54–64). Aston University.
Meierhofer, J., Benedech, R. A., & Schweiger, L. (2023). Data driven decision support framework for industrial smart services design and operations [Conference poster]. In A. Z. Bigdeli, M. Kohtamäki, R. Rabetino, & T. Baines (Eds.), The Role of Servitization in Grand Challenges (pp. 220–221). Aston University.
Pezzotta, G., Arioli, V., Adrodegari, F., Rapaccini, M., Saccani, N., Rakic, S., Marjanovic, U., West, S., Stoll, O., Meierhofer, J., Holst, L., Wiesner, S. A., Bertoni, M., Romero, D., Pirola, F., Sala, R., & Gaiardelli, P. (2022). Digital servitization in the manufacturing sector : survey preliminary results [Conference paper]. In D. Y. Kim, G. v. Cieminski, & D. Romero (Eds.), Advances in Production Management Systems. Smart Manufacturing and Logistics Systems : Turning Ideas into Action : IFIP WG 5.7 International Conference, APMS 2022, Gyeongju, South Korea, September 25-29, 2022, Proceedings, Part II (Vol. 2, pp. 310–320). Springer. https://doi.org/10.1007/978-3-031-16411-8_37
Schweiger, L., Benedech, R. A., & Meierhofer, J. (2022). Development approach for value-creating service process twins based on service design methods. IEEE DASC/PiCom/CBDCom/CyberSciTech 2022 Proceedings. https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9928003
Meierhofer, J., Benedech, R. A., & Heitz, C. (2022). On the value of data : multi-objective maximization of value creation in data-driven industrial services [Conference paper]. In C. Ceballos (Ed.), Proceedings : 2022 9th Swiss Conference on Data Science (SDS) (pp. 33–39). IEEE. https://doi.org/10.1109/SDS54800.2022.00013
Smart Services Summit : smart services supporting the new normal. (2022). In S. West, J. Meierhofer, & U. Mangla (Eds.), Fourth Smart Services Summit, Zurich, 22 October 2021. Springer. https://doi.org/10.1007/978-3-030-97042-0
Dobler, M., Meierhofer, J., Frick, K., & Bentele, M. (2022). On the use of low-code and no-code tools for teaching data science in applied industrial and university settings [Conference paper]. In L. Morel, L. Dupont, & M. Camargo (Eds.), Conference Proceedings of 2022 IEEE 28th ICE/IMT & 31st IAMOT joint conference (pp. 242–249). IEEE. https://doi.org/10.1109/ICE/ITMC-IAMOT55089.2022.10033266
Meierhofer, J., Kugler, P., Vogt, H., Dobler, M., Benedech, R. A., Strittmatter, M., & Treiterer, M. (2022). Improving service value creation for manufacturing SMEs by overcoming data sharing hurdles in ecosystems [Conference paper]. In A. Bigdeli, M. Rapaccini, N. Saccani, F. Adrodegari, & T. Baines (Eds.), Achieving Net-Zero through Servitization (pp. 86–94). Aston University. https://doi.org/10.21256/zhaw-25047
Schweiger, L., Meierhofer, J., Barbieri, C., & Rapaccini, M. (2022). End-to-end digital twin approach for near-real-time decision support services [Conference paper]. In S. West, J. Meierhofer, & U. Mangla (Eds.), Smart Services Summit : smart services supporting the new normal (pp. 67–75). Springer. https://doi.org/10.1007/978-3-030-97042-0_7
Meierhofer, J., Benedech, R. A., Schweiger, L., Barbieri, C., & Rapaccini, M. (2022). Quantitative modelling of the value of data for manufacturing SMEs in smart service provision [Conference paper]. In T. Le Dinh & M. Drăgoicea (Eds.), International Conference on Exploring Service Science (IESS 2.2) (p. 4001). EDP Sciences. https://doi.org/10.1051/itmconf/20224104001
Meierhofer, J., & Heitz, C. (2021). Service customization : optimizing value creation and capture by designing the customer journey [Conference paper]. Proceedings of the 8th SDS, 32–38. https://doi.org/10.1109/SDS51136.2021.00013
Meierhofer, J., Schweiger, L., & Schreuder, L. (2021). Digital twin based decision support services in business operations [Conference paper]. In S. West, J. Meierhofer, & C. Ganz (Eds.), Smart services summit : digital as an enabler for smart service business development (pp. 117–129). Springer. https://doi.org/10.1007/978-3-030-72090-2_11
Barth, L., Sarperi, L., Dettling, M., Meierhofer, J., Bulatovic, A., & Schweiger, L. (2021). Development of a smart connected product-service-system (PSS) for the waste management ecosystem [Conference paper]. In E. Mugellini & E. Carpanzano (Eds.), Proceedings of the 2nd FTAL Conference 2021 Sustainable Smart Cities and Regions. CEUR Workshop Proceedings. https://doi.org/10.21256/zhaw-25014
Smart Services Summit : digital as an enabler for smart service business development. (2021). In S. West, J. Meierhofer, & C. Ganz (Eds.), Third Smart Services Summit, Zurich (online), 23 October - 23 December 2020. Springer. https://doi.org/10.1007/978-3-030-72090-2
Meierhofer, J., Heitz, C., & Hannich, F. (2021). Optimizing service value creation with smart, connected products [Conference paper]. In E. Gummesson, C. Mele, & F. Polese (Eds.), Proceedings of the 2021 Naples Forum on Service. https://naplesforumonservice.com/wp-content/uploads/2021/09/meierhofer-heitz-hannich-optimizing-service-value-creation.pdf
Meierhofer, J., Züst, S., Lu, J., Schweiger, L., & Kiritsis, D. (2021). Enabling decision support services in industrial ecosystems by digital twins [Conference paper]. In A. Bigdeli, T. Baines, M. Rapaccini, M. Saccani, & F. Adrodegari (Eds.), Proceedings of the Spring Servitization Conference 2021 (pp. 138–146). Aston University.
Schweiger, L., Barth, L., & Meierhofer, J. (2020). Data resources to create digital twins [Conference paper]. Proceedings of the 7th SDS, 55–56. https://doi.org/10.1109/SDS49233.2020.00020
Meierhofer, J., Dobler, M., Frick, K., & Schweiger, L. (2020). Smart service patterns for small manufacturing enterprises [Conference paper]. In A. Bigdeli & T. Baines (Eds.), Proceedings of the Spring Servitization Conference : Advanced Services for Sustainability and Growth (pp. 88–95). Aston University.
West, S., Meierhofer, J., Stoll, O., & Schweiger, L. (2020). Value propositions enabled by digital twins in the context of servitization [Conference paper]. In A. Bigdeli & T. Baines (Eds.), Proceedings of the Spring Servitization Conference : Advanced Services for Sustainability and Growth (pp. 152–160). Aston University.
Meierhofer, J., & West, S. (2020). Data-driven decision support by digital twins in manufacturing [Conference paper]. Proceedings of the 7th SDS, 53–54. https://doi.org/10.1109/SDS49233.2020.00019
Meierhofer, J., West, S., Rapaccini, M., & Barbieri, C. (2020). The digital twin as a service enabler : from the service ecosystem to the simulation model [Conference paper]. In H. Nóvoa, M. Drăgoicea, & N. Kühl (Eds.), IESS 2020 : Exploring Service Science (pp. 347–359). Springer. https://doi.org/10.1007/978-3-030-38724-2_25
Meierhofer, J., & West, S. (2019). Service value creation using a digital twin. Naples Forum on Service, Service Dominant Logic, Network & Systems Theory and Service Science: Integrating Three Perspectives for a New Service Agenda, Ischia, Italy, 4-7 June 2019. http://www.naplesforumonservice.it/uploads/files/2018/Proceedings/NFS2019-Meierhofer-est.pdf
Meierhofer, J., Kugler, P., & Etschmann, R. (2019). Challenges and approaches with data-driven services for SMEs : insights from a field study [Conference paper]. Proceedings of the Spring Servitization Conference : Delivering Services Growth in the Digital Era, 39–49.
Schweiger, L., & Meierhofer, J. (2019). Data-driven servitization of SMEs : assessment of success factors based on a multiple case study [Conference paper]. Servitization 2019: 8th International Conference on Business Servitization (ICBS 2019), November 21-22, 2019 : Book of Abstracts, 85–88.
nd Smart Services Summit. (2019). In J. Meierhofer & S. West (Eds.), Second Smart Services Summit, Zurich, Switzerland, 13 September 2019. Swiss Alliance for Data-Intensive Services. https://doi.org/10.21256/zhaw-26321
West, S., Barbieri, C., Rapaccini, M., & Meierhofer, J. (2019). Are practitioners and literature aligned about digital twin? [Conference paper]. In G. Kovács & M. Kuula (Eds.), Operations adding value to society (pp. 2781–2790). Aalto University Business School.
Meierhofer, J. (2018). Data driven servitization for SMEs in manufacturing. Proceedings of the Spring Servitization Conference : Driving Competition through Servitization.
Meierhofer, J., & Herrmann, A. (2018). End-to-end methodological approach for the data-driven design of customer-centered digital services [Conference paper]. In G. Satzger, L. Patrício, M. Zaki, N. Kühl, & P. Hottum (Eds.), IESS 2018: Exploring Service Science (Vol. 9, pp. 208–218). Springer. https://doi.org/10.1007/978-3-030-00713-3_16
Meierhofer, J. (2017). Service value creation using data science [Conference paper]. In E. Gumesson, C. Mele, & F. Polese (Eds.), Service Logic, Network and Systems Theory and Service Science: Integrating three Perspectives for a New Service Agenda. Youcanprint Self-Publishing. http://www.naplesforumonservice.it/uploads//files/Meierhofer.pdf
Meierhofer, J., & Meier, K. (2017). From data science to value creation [Conference paper]. In S. Za, M. Drăgoicea, & M. Cavallari (Eds.), Exploring Services Science : 8th International Conference, IESS 2017, Rome, Italy, May 24-26, 2017, Proceedings (pp. 173–181). Springer. https://doi.org/10.1007/978-3-319-56925-3_14
Meierhofer, J. (2017). A design approach to service transformation in small firms [Conference paper]. Proceedings of the Spring Servitization Conference : Internationalisation through Servitization, 69–75.

Weitere Publikationen

Meierhofer, J., Goller, I., Laneve, F., & Remke, S. (2025). Mit Methode vom Use Case zum Business Case. KunststoffXtra, 2025(11-12), 14–15. https://doi.org/10.21256/zhaw-35008
Burri, C., & Meierhofer, J. (2025). Data Value Creator 4.0 – Wertgenerierung durch datenbasierte Optimierung. topsoft Fachmagazin, 15(2), 44–45. https://doi.org/10.21256/zhaw-33862
Wulf, J., Meierhofer, J., & Hannich, F. (2025). Architecting human-AI cocreation for technical services : interaction modes and contingency factors. arXiv. https://doi.org/10.48550/arxiv.2507.14034
Vogt, H., Meierhofer, J., & Kugler, P. (2025). Einleitung: Herausforderungen und Handlungsbedarf für KMU. In P. Kugler, M. Dobler, J. Meierhofer, M. Strittmatter, M. Treiterer, & H. Vogt (eds.), Data Sharing für KMU : Voraussetzungen und Instrumente für die gemeinsame Nutzung von Daten (pp. 3–8). Springer. https://doi.org/10.1007/978-3-662-71209-2_1
Wulf, J., & Meierhofer, J. (2024). Utilizing large language models for automating technical customer support. arXiv. https://doi.org/10.48550/arXiv.2406.01407
Meierhofer, J., & Stucki, M. (2024). Ökologischer & wirtschaftlicher Nutzen mit industriellen Smart Services. asut-Bulletin, 2024(01). https://asut.ch/asut/bulletin/view.xhtml?bulletinId=52&articleId=831
Wulf, J., & Meierhofer, J. (2024). Wie LLMs die Automatisierung im Kundendienst fördern. ServiceToday, 38(Sonderausgabe 2024), 82–83. https://bc-production.pressmatrix.com/de/profiles/3df31a994fc2/editions/2ed85b567c8dfa546626/pages/page/42
Meierhofer, J., & Stucki, M. (2023). Ökologischer & wirtschaftlicher Nutzen mit industriellen Smart Services. ServiceToday, 37(1), 71–72. https://doi.org/10.21256/zhaw-27574
Benedech, R. A., Vogt, H., Meierhofer, J., Kugler, P., Strittmatter, M., Dobler, M., Meyer, J., & Treiterer, M. (2023). Data Sharing Framework für KMU. ResearchGate. https://www.researchgate.net/publication/376811588_Data_Sharing_Framework_fur_KMU
Wulf, J., & Meierhofer, J. (2023). Towards a taxonomy of Large Language Model based business model transformations. arXiv. https://doi.org/10.48550/arXiv.2311.05288
Wulf, J., & Meierhofer, J. (2023). Large Language Models in Industrieunternehmen. Technische Rundschau, 23(9), 48–50. https://doi.org/10.21256/zhaw-28949
Wulf, J., & Meierhofer, J. (2023). Pioneering a new era of automated customer service with large language models (LLMs). Medium. https://medium.com/@jocwulf/pioneering-a-new-era-of-automated-customer-service-with-large-language-models-llms-1cc4aacbeb03
Wulf, J., & Meierhofer, J. (2023). Unlocking the business potential of large language models : real-world applications and obstacles. LinkedIn Pulse. https://www.linkedin.com/pulse/unlocking-business-potential-large-language-models-real-world-wulf/
Meierhofer, J., & Stucki, M. (2022). Mit Smart Services zu mehr Nachhaltigkeit. KunststoffXtra , 2022(11-12), 54–56. https://doi.org/10.21256/zhaw-26269
Meierhofer, J. (2022). Wie produzierende KMU den Wert ihrer Daten erkennen können. topsoft Fachmagazin, 12(1), 10–11. https://doi.org/10.21256/zhaw-24559
Meierhofer, J. (2022). Den Wert von Daten bestimmen. KunststoffXtra , 1-2(2022), 30–32. https://doi.org/10.21256/zhaw-24530
Vogt, H., Kugler, P., Meierhofer, J., & Benedech, R. A. (2021). Enabling smart services for manufacturing SMEs by data-driven value creation. The Spring Servitization Conference 2021, Birmingham, United Kingdom, 10-12 May 2021. https://41753ba1-a36e-4b60-91bd-ac6d4d925510.filesusr.com/ugd/d939c0_74856e92e8204cb498892d7dd1af4f84.pdf
Meierhofer, J., & Heinatz Bürki, G. (2021). Databooster : ein Katalysator für Serviceinnovation. ServiceToday, 35(3), 62. https://doi.org/10.21256/zhaw-23050
Zimmermann, A., Meierhofer, J., von dem Berge, K., & Schweiger, L. (2021). Servicekultur als Katalysator für Serviceinnovationen. ServiceToday, 35(2), 72–73. https://doi.org/10.21256/zhaw-22653
Meierhofer, J., Etschmann, R., & Dobler, M. (2020). Data Science veranschaulichen : Demonstrator. In J. Meierhofer & P. Kugler (eds.), Data4KMU : Data Science für KMU leicht gemacht. Aktuelle Erkenntnisse und Lösungen (pp. 127–141). ZHAW Zürcher Hochschule für Angewandte Wissenschaften, School of Engineering. http://bzi40.eu/informationen/publikationen/studien/382-abschlussbericht-data4kmu/file
Meierhofer, J. (2020). Data Science und Services. In J. Meierhofer & P. Kugler (eds.), Data4KMU : Data Science für KMU leicht gemacht. Aktuelle Erkenntnisse und Lösungen (pp. 69–79). ZHAW Zürcher Hochschule für Angewandte Wissenschaften, School of Engineering. http://bzi40.eu/informationen/publikationen/studien/382-abschlussbericht-data4kmu/file
Meierhofer, J., & Kugler, P. (2020). Data4KMU : Data Science für KMU leicht gemacht. Aktuelle Erkenntnisse und Lösungen. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. http://bzi40.eu/informationen/publikationen/studien/382-abschlussbericht-data4kmu
Meierhofer, J., & Homberger, P. (2020). Digitale Service Innovation in Wertschöpfungsnetzwerken : Anwendung im Getränkemarkt. ServiceToday, 34(4), 78–79. https://doi.org/10.21256/zhaw-20827
Meierhofer, J. (2020). Die Konvergenz von Digitalisierung und Servitisierung in der Industrie 4.0. Aktuelle Technik, 2020(8), 32. https://doi.org/10.21256/zhaw-20432
Meierhofer, J., & Heitz, C. (2020). Data-Driven Management zur Steigerung des Kundennutzens. Netzwoche, 2020(07), 11. https://www.netzwoche.ch/news/2020-04-22/data-driven-management-zur-steigerung-des-kundennutzens
Meierhofer, J., & Lév, J. (2019). Daten-basierter Service-Nutzen entlang der Customer Journey. ServiceToday, 33(2), 86–87. https://doi.org/10.21256/zhaw-3243
Meierhofer, J. (2019). Service Transformation und Service Engineering (AP3). In C. Thiel (ed.), Nutzenbasierter Digitalisierungsnavigator : wie KMU ihre Digitalisierungsstrategie selbst entwickeln können (pp. 47–61). IBH-Lab KMUdigital. https://bzi40.eu/informationen/publikationen/paper/298-nutzenbasierter-digitalisierungsnavigator-wie-kmu-ihre-digitalisierungsstrategie-selbst-entwickeln-koennen
Meierhofer, J., & Berliat, R. (2019). Smart Service Innovation. ServiceToday, 33(4), 96–97. https://doi.org/10.21256/zhaw-18545
Meierhofer, J. (2019). Big Data und Machine Learning in Industrie 4.0 : Perspektiven für Service-Modelle. KunststoffXtra, 9(12), 19–21. https://issuu.com/sigwerbgmbh/docs/web_kx_12-2019/1?ff&showOtherPublicationsAsSuggestions=true&backgroundColorFullscreen=%23e8edf0
Meierhofer, J., Heinatz Bürki, G., & Heitz, C. (2019). Data Science für KMU. Unternehmer Zeitung, 25(10), 20–23.
Heitz, C., Heinatz Bürki, G., & Meierhofer, J. (2019). Zusammen in die Zukunft : fit für Data Science. KMU Rundschau, 2019(2), 34–35. https://issuu.com/prestigemedia/docs/kmurundschau_2019_02
Meierhofer, J. (2018). Herausforderungen, Chancen und Perspektiven mit Industrie 4.0. Aktuelle Technik, 2018(12), 20–21.
Meierhofer, J. (2018). Datenbasierte Service-Innovation. Spot.on Marketing.
Meierhofer, J., & Heinatz, G. (2018). Wie sich die Dienstleistungswirtschaft durch Daten wandelt. SocietyByte, 2018. https://doi.org/10.21256/zhaw-3949
Meierhofer, J. (2018). Industrie 4.0 : Perspektiven durch neue Service-Modelle. topsoft Fachmagazin, 8(1), 18–19. https://issuu.com/topsoft/docs/tsm18-1
Meierhofer, J., & Lév, J. (2016). Innovationshelfer Mensch, Papier, Schere : Innovation // Um erfolgreich disruptive Innovation zu schaffen, muss zuerst der strategische Fokus und das Ziel der Digitalisierung definiert werden. Entscheidend ist die Frage: Womit schaffen wir den grössten Mehrwert für Unternehmen und Kunden? Computerworld, 18–19.
Meierhofer, J., Heitz, C., & Steiner, A. (2004). Simulation based case studies for management training in the fields of production and supply chain Management. Automation and Logistics for Manufacturing in Switzerland. https://doi.org/10.21256/zhaw-1884
Meierhofer, J., & Steiner, A. (2004). Quantitative assessment and capacity planning of business processes in the service sector. Automation and Logistics for Manufacturing in Switzerland.
Steiner, A., Hosang, J., & Meierhofer, J. (2004). Vehicular traffic data analysis and its benefits to prevent traffic congestion. Proceedings of the IPLnet 2004 Workshop.

Mündliche Konferenzbeiträge und Abstracts

Kugler, P., Vogt, H., & Meierhofer, J. (2023). Data sharing in ecosystems : a multi-perspective view. 8. F&E-Konferenz Zu Industrie 4.0, Rotkreuz, Switzerland, 24 January 2023.
Meierhofer, J. (2018). Challenges and approaches for product-service-transformation of SMEs [Conference presentation]. Servsig Proceedings : Opportunities for Services in a Challenging World, 102–106. https://www.ieseg.fr/wp-content/uploads/2018/02/SERVSIG-2018-Proceedings.pdf

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