Future-Relevant Technologies for Switzerland: Technological Priority Signals and Cross-Industry Robustness Based on Job Postings Analysis

Inhaltsverzeichnis

Bibliographische Infos

Cover der Ausgabe: Swiss Journal of Business Jahrgang 80 (2026), Heft 2
Open Access Vollzugriff

Swiss Journal of Business

Jahrgang 80 (2026), Heft 2

Autor:innen:
Verlag
Nomos, Baden-Baden
Copyrightjahr
2026
ISSN-Online
2944-3741
ISSN-Print
2944-3741

Kapitelinformationen

Open Access Vollzugriff

Jahrgang 80 (2026), Heft 2

Future-Relevant Technologies for Switzerland: Technological Priority Signals and Cross-Industry Robustness Based on Job Postings Analysis

Autor:innen:
ISSN-Print
2944-3741
ISSN-Online
2944-3741
Kapitelvorschau:

Die Foresight-Forschung ist ständig danach bestrebt, neue Datenquellen für ihre Technologietrendstudien zu identifizieren und zu nutzen. Zusätzlich zu den etablierten Datenquellen wie Patenten und wissenschaftlichen Publikationen haben sich auch Stellenausschreibungen als aussagekräftig für die Vorausschau erwiesen. In unserer Forschung nutzen wir Stellenausschreibungen aus der Schweiz, um Technologien zu identifizieren, die häufig im Zusammenhang mit zukunftsbezogenen Begriffen genannt werden. Dieser neuartige Ansatz liefert eine datenbasierte Perspektive auf Technologiebereiche, in denen Unternehmen in der Schweiz Zukunftspotenzial sehen und für welche sie aktiv Personal einstellen. Zusätzlich vergleichen wir die Einstellungsdynamiken für diese Technologiebereiche über Industrien hinweg, um robuste Technologien zu identifizieren, die in mehreren Sektoren zukunftsrelevant sind. Unsere Forschungsmethode umfasst verschiedene Text-Mining-Techniken und resultiert in einer datengetriebenen Trendstudie mit Wissenschafts- und Praxisrelevanz.

Literaturverzeichnis

  1. Bakhshi, H., Downing, J. M., Osborne, M. A., & Schneider, P. (2017). The Future of Skills: Employment in 2030. Pearson and Nesta. https://media.nesta.org.uk/documents/the_future_of_skills_employment_in_2030_0.pdf Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  2. Bassani, G., Minola, T., & Vismara, S. (2016). Technology Foresight for Regional Economies: A How-to-Do Guide. In D. Audretsch, E. Lehmann, M. Meoli, & S. Vismara (Eds.), International Studies in Entrepreneurship. University Evolution, Entrepreneurial Activity and Regional Competitiveness (Vol. 32, pp. 385–392). Springer International Publishing. https://doi.org/10.1007/978-3-319-17713-7_18 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  3. Baumgartner, S., & Peter, M. K. (2022). Strategic Foresight and Innovation Management: A Comparative Study across International Swiss Banks. Athens Journal of Business & Economics, 8(4), 309–328. https://doi.org/10.30958/ajbe.8-4-1 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  4. Blind, K., Cuhls, K., & Grupp, H. (1999). Current Foresight Activities in Central Europe. Technological Forecasting and Social Change, 60(1), 15–35. https://doi.org/10.1016/S0040-1625(98)00021-3 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  5. Block, C., Wustmans, M., Laibach, N., & Bröring, S. (2021). Semantic bridging of patents and scientific publications – The case of an emerging sustainability-oriented technology. Technological Forecasting and Social Change, 167, 120689. https://doi.org/10.1016/j.techfore.2021.120689 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  6. Bonaccorsi, A., Chiarello, F., Fantoni, G., & Kammering, H. (2020). Emerging technologies and industrial leadership. A Wikipedia-based strategic analysis of Industry 4.0. Expert Systems with Applications, 160, 113645. https://doi.org/10.1016/j.eswa.2020.113645 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  7. Brancatelli, C., Marguerie, A., & Brodmann, S. (2020). Job Creation and Demand for Skills in Kosovo: What Can We Learn from Job Portal Data? (Policy Research Working Paper No. 9266). World Bank. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3616475 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  8. Brasse, J., Förster, M., Hühn, P., Klier, J., Klier, M., & Moestue, L. (2024). Preparing for the future of work: a novel data-driven approach for the identification of future skills. Journal of Business Economics, 94(3), 467–500. https://doi.org/10.1007/s11573-023-01169-1 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  9. Cagnani, G. R., Da Costa Oliveira, T., Mattioli, I. A., Sedenho, G. C., Castro, K. P. R., & Crespilho, F. N. (2023). From research to market: Correlation between publications, patent filings, and investments in development and production of technological innovations in biosensors. Analytical and Bioanalytical Chemistry, 415(18), 3645–3653. https://doi.org/10.1007/s00216-022-04444-2 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  10. Camuffo, A., Gambardella, A., Kazemi, S., Malachowski, J., & Pandey, A. (2026). Variance-Aware LLM Annotation for Strategy Research: Sources, Diagnostics, and a Protocol for Reliable Measurement. arXiv – Cornell University. https://arxiv.org/abs/2601.02370 https://doi.org/10.48550/arXiv.2601.02370 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  11. Carnevale, A. P., Jayasundera, T., & Repnikov, D. (2014). Understanding Online Job Ads Data: A Technical Report. Georgetown University Center on Education and the Workforce. https://cew.georgetown.edu/wp-content/uploads/2014/11/OCLM.Tech_.Web_.pdf Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  12. Cozzens, S., Gatchair, S., Kang, J., Kim, K.‑S., Lee, H. J., Ordóñez, G., & Porter, A. (2010). Emerging technologies: quantitative identification and measurement. Technology Analysis & Strategic Management, 22(3), 361–376. https://doi.org/10.1080/09537321003647396 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  13. Deloitte. (2021, 11 March). Emerging technologies in Switzerland. Deloitte AG. https://www.deloitte.com/ch/en/Industries/technology/perspectives/emerging-technologies.html. Date of query: 07.07.2025 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  14. Firpo, T., Baumann, J., Teubner, T., & Danilov, A. (2021). Digital talent: Mapping the demand for digital skills in Tunisia. Einstein Center Digital Future/Digital Transformation Center Tunisia. https://anastasiadanilov.de/wp-content/uploads/2021/07/Firpo-et-al.-2021.pdf Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  15. Gerken, J. M., Moehrle, M. G., & Walter, L. (2015). One year ahead! Investigating the time lag between patent publication and market launch: insights from a longitudinal study in the automotive industry. R&D Management, 45(3), 287–303. https://doi.org/10.1111/radm.12085 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  16. Gilmore, N., Koskinen, I., Burr, P., Obbard, E., Sproul, A., Konstantinou, G., Bilbao, J., Daiyan, R., Kay, M., Corkish, R., Macgill, I., Lovell, E., Menictas, C., & Bruce, A. (2023). Identifying weak signals to prepare for uncertainty in the energy sector. Heliyon, 9(11), e21295. https://doi.org/10.1016/j.heliyon.2023.e21295 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  17. Goldfarb, A., Taska, B., & Teodoridis, F. (2023). Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings. Research Policy, 52(1), 104653. https://doi.org/10.1016/j.respol.2022.104653 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  18. Han, X., Zhu, D., Lei, M., & Daim, T. (2021). R&D trend analysis based on patent mining: An integrated use of patent applications and invalidation data. Technological Forecasting and Social Change, 167, 120691. https://doi.org/10.1016/j.techfore.2021.120691 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  19. Hershbein, B., & Kahn, L. B. (2018). Do Recessions Accelerate Routine-Biased Technological Change? Evidence from Vacancy Postings. American Economic Review, 108(7), 1737–1772. https://doi.org/10.1257/aer.20161570 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  20. Hsieh, C.‑H., Lin, C.‑H., Lu, L. Y., Contreras Cruz, A., & Daim, T. (2024). Forecasting patenting areas with academic paper & patent data: A wind power energy case. World Patent Information, 78, 102297. https://doi.org/10.1016/j.wpi.2024.102297 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  21. Kindras, A., Meissner, D., & Vishnevskiy, K. (2019). Regional Foresight for Bridging National Science, Technology, and Innovation with Company Innovation: Experiences from Russia. Journal of the Knowledge Economy, 10(4), 1319–1340. https://doi.org/10.1007/s13132-015-0296-x Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  22. Laurell, C., & Sandstrom, C. (2022). Social Media Analytics as an Enabler for External Search and Open Foresight—The Case of Tesla’s Autopilot and Regulatory Scrutiny of Autonomous Driving. IEEE Transactions on Engineering Management, 69(2), 564–571. https://doi.org/10.1109/TEM.2021.3072677 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  23. Li, N., Kang, B., & Bie, T. de (2025). LLM4Jobs: Unsupervised occupation extraction and standardization leveraging Large Language Models. Knowledge-Based Systems, 316, 113302. https://doi.org/10.1016/j.knosys.2025.113302 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  24. LinkUp. (2026, 01 January). Our data. JobDig, Inc. https://www.linkup.com/data. Date of query: 20.01.2026 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  25. Maier, H. R., Guillaume, J., van Delden, H., Riddell, G. A., Haasnoot, M., & Kwakkel, J. H. (2016). An uncertain future, deep uncertainty, scenarios, robustness and adaptation: How do they fit together? Environmental Modelling & Software, 81, 154–164. https://doi.org/10.1016/j.envsoft.2016.03.014 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  26. Martino, J. P. (2003). A review of selected recent advances in technological forecasting. Technological Forecasting and Social Change, 70(8), 719–733. https://doi.org/10.1016/S0040-1625(02)00375-X Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  27. McPhail, C., Maier, H. R., Westra, S., Kwakkel, J. H., & van der Linden, L. (2020). Impact of Scenario Selection on Robustness. Water Resources Research, 56(9), Article e2019WR026515. https://doi.org/10.1029/2019WR026515 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  28. Mikova, N., & Sokolova, A. (2019). Comparing data sources for identifying technology trends. Technology Analysis & Strategic Management, 31(11), 1353–1367. https://doi.org/10.1080/09537325.2019.1614157 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  29. Mühlroth, C., & Grottke, M. (2018). A systematic literature review of mining weak signals and trends for corporate foresight. Journal of Business Economics, 88(5), 643–687. https://doi.org/10.1007/s11573-018-0898-4 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  30. Müller-Stewens, G., & Müller, A. (2010). Strategic Foresight – Trend- und Zukunftsforschung als Strategieinstrument. In M. Reimer & S. Fiege (Eds.), Perspektiven des Strategischen Controllings (pp. 239–257). Gabler. https://doi.org/10.1007/978-3-8349-8805-8_15 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  31. Niggli, M., & Rutzer, C. (2023). Digital technologies, technological improvement rates, and innovations “Made in Switzerland”. Swiss Journal of Economics and Statistics, 159(1). https://doi.org/10.1186/s41937-023-00104-z Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  32. Niknejad, N., Ismail, W., Bahari, M., Hendradi, R., & Salleh, A. Z. (2021). Mapping the research trends on blockchain technology in food and agriculture industry: A bibliometric analysis. Environmental Technology & Innovation, 21, 101272. https://doi.org/10.1016/j.eti.2020.101272 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  33. Norouzi, E., Hertling, S., & Sack, H. (2025). ConExion: Concept Extraction with Large Language Models. arXiv – Cornell University. https://arxiv.org/pdf/2504.12915 https://doi.org/10.48550/arXiv.2504.12915 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  34. Peter, M. K. (2019). The Evolving Approach to Strategic Corporate Foresight at Swiss Bank PostFinance in the Age of Digital Transformation. In D. A. Schreiber & Z. L. Berge (Eds.), Futures Thinking and Organizational Policy (pp. 113–132). Springer International Publishing. https://doi.org/10.1007/978-3-319-94923-9_6 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  35. Rohrbeck, R., Battistella, C., & Huizingh, E. (2015). Corporate foresight: An emerging field with a rich tradition. Technological Forecasting and Social Change, 101, 1–9. https://doi.org/10.1016/j.techfore.2015.11.002 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  36. Scheuffele, M., Bayrle-Kelso, N., & Brecht, L. (2024). Data-Driven Foresight in Life Cycle Management: An Interview Study. In D. Schallmo, A. Baiyere, F. Gertsen, C. A. F. Rosenstand, & C. A. Williams (Eds.), Springer Proceedings in Business and Economics. Digital Disruption and Transformation (pp. 131–151). Springer International Publishing. https://doi.org/10.1007/978-3-031-47888-8_7 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  37. Scheuffele, M., Fetkenheuer, N., & Brecht, L. (2025). Introducing a Data-Driven Approach for Validating the Practical Relevance of Emerging Innovation Fields — Trend Insights on Technologies and Twin Transformation. International Journal of Innovation Management, 29(05n06), Article 2540012. https://doi.org/10.1142/S1363919625400122 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  38. Segev, A., Jung, S., & Choi, S. (2015). Analysis of Technology Trends Basedon Diverse Data Sources. IEEE Transactions on Services Computing, 8(6), 903–915. https://doi.org/10.1109/TSC.2014.2338855 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  39. Sioziou, K., Zervas, P., Giotopoulos, K., & Tzimas, G. (2024). Comparative Analysis of Large Language Models in Structured Information Extraction from Job Postings. In L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, & C. Jayne (Eds.), Communications in Computer and Information Science. Engineering Applications of Neural Networks (Vol. 2141, pp. 82–92). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-62495-7_7 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  40. Stelzer, B., Meyer-Brötz, F., Schiebel, E., & Brecht, L. (2015). Combining the scenario technique with bibliometrics for technology foresight: The case of personalized medicine. Technological Forecasting and Social Change, 98, 137–156. https://doi.org/10.1016/j.techfore.2015.06.008 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  41. Swiss Academy of Engineering Sciences SATW. (2023, 15 December). Technology Outlook: National Trends. Swiss Academies of Arts and Sciences. https://technology-outlook.satw.ch/en/national-trends?setLang=1. Date of query: 07.07.2025 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  42. Tsesmelis, M., Percia David, D., Maillart, T., Dolamic, L., Tresoldi, G., Lacube, W., Barschel, C., Ladetto, Q., Schärer, C., Lenders, V., Cuche, K., & Mermoud, A. (2022). Cybersecurity Technologies: An Overview of Trends & Activities in Switzerland and Abroad. SSRN Electronic Journal. Advance online publication. https://doi.org/10.2139/ssrn.4013762 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  43. Watts, R. J., & Porter, A. L. (1997). Innovation forecasting. Technological Forecasting and Social Change, 56(1), 25–47. https://doi.org/10.1016/S0040-1625(97)00050-4 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  44. Wider, W., Gao, Y., Chan, C. K., Lin, J., Li, J., Tanucan, J. C. M., & Fauzi, M. A. (2023). Unveiling trends in digital tourism research: A bibliometric analysis of co-citation and co-word analysis. Environmental and Sustainability Indicators, 20, 100308. https://doi.org/10.1016/j.indic.2023.100308 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173
  45. Zhang, G., Feng, Y., Yu, G., Liu, L., & Hao, Y. (2017). Analyzing the time delay between scientific research and technology patents based on the citation distribution model. Scientometrics, 111(3), 1287–1306. https://doi.org/10.1007/s11192-017-2357-3 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-2-173

Zitation

Download RIS Download BibTex

Downloads

Download Kapitel (PDF) Download kompl. Werk (PDF)

Hinweis

Dieses Werk ist urheberrechtlich geschützt und darf nur nach den Vorgaben der Nutzungs- und Lizenzvereinbarung genutzt werden. Jede darüber hinaus gehende Nutzung des Werkes ist ausdrücklich untersagt und wird verfolgt.

Per E-Mail teilen

Medien