Prof. Dr. Anna Nagl

Room
G4 2.04
Telephone
Email Address
Prof. Dr. Anna Nagl

Member of the Baden-Württemberg Center of Applied Research BW-CAR of the doctoral association of institutions of higher education in Baden-Württemberg, which have been awarded the independent right to award doctorates.

Head /Director of the Competence Center for Innovative Business Models at Aalen University of Applied Sciences

Head of the M.Sc. Vision Science and Business (Optometry) program

Book author, published by Springer Gabler in 2025:
the 11th conditions of the book "Der Businessplan: Start-ups erfolgreich gründen - Mit Checklisten und Fallbeispielen"
and co-author of the 3rd edition of the book "Digitale KI-unterstützte Geschäftsmodelle - Business Model Building mit Checklisten und Fallbeispielen"

Curriculum Vitae

resumé

Publications

127 publications

Jonas Holzinger, Anna Nagl, Karlheinz Bozem, Carsten Lecon, Andreas Ensinger, Jannik Roessler, Christina Neufeld ISSN: 2071-1050,

Further information  

Anna Nagl, A. Nagl.

Anna Nagl, J. Holzinger, K. Bozem, A. Ensinger, J. Roessler, C. Neufeld, C. Lecon

Christoph Zulechner, Anna Nagl, Stefan Bandlitz, Mario Rehnert, Frank Widmer ISSN: 2748-8217,

Further information  

Thesis

completed theses

2025

AI-assisted lenses – analysis of success factors at optician stores

Bachelor, Status: completed

Course: Optometry

Confidentiality Clause

This bachelor thesis contains confidential and proprietary information of Rodenstock. This thesis may only be made available to supervisors and authorized members of the examination board. Any publication, duplication or reproduction of this thesis, even in part, is prohibited. An inspection of this work by third parties requires the expressed permission of the author and Rodenstock.

Purpose: The aim of this thesis is to identify the factors influencing the success of AI-assisted lenses from the perspective of opticians. The subjects encompass technological innovation, awareness and personal training, communication and marketing, and market targeting. Success is therefore defined as the sales volume of the particular product category. The objective of this research is to ascertain the fundamental elements necessary for the effective introduction and successful integration of this novel technology.

Methods: To gain deeper insights into opticians’ experiences and expectations regarding AI-assisted lenses, interviews were conducted. In order to obtain comparable results, interview guidelines were created for semi-structured interviews. The participants were divided into two groups: ten opticians that already sold AI-assisted lenses and the second group of ten opticians who did not sell AI-assisted lenses at this time. To exploit possible correlation between their age, degree and gender, this information was collected additionally. The interviews were recorded and denaturalized transcriptions were made afterwards. These build the basis for further analysis, which started by coding them via the software QDA Miner light. For analyzing the results, the method of iterative categorization was used, and the coded statements were transferred to Microsoft Word, where they got further structured.

Results: The data obtained was displayed in charts, offering a quick impression of the positive attitude of the opticians regarding artificial intelligence and demonstrating concerns or advantages of this product. Only the opticians of the manufacturer of AI-assisted lenses are aware of this product type and inform themselves mainly via the manufacturer. In general, the majority of the surveyed opticians consider an AI as good if it leads to precise results. In context of AI-assisted lenses it is shown that more male opticians, only the age groups up to 40-year-olds and almost every optician that has a bachelors’ degree could imagine the fact that the lenses are based on AI as helpful for selling them. Besides that, they frequently named the level of individualization as an advantage. On the other hand, three main disadvantages that were mentioned were the lack of controllability, comprehensibility and guarantee of good results. The most frequently raised concerns included the fear of a bad reputation and the shift of competence to the manufacturer.

Conclusions: The results show that the influencing factors of the success of AI-assisted lenses are manifold. The findings in current literature on the topic of acceptance of AI or AI products can be confirmed by the fact that trust is the basis for acceptance also in context of AI-assisted lenses. This trust is influenced by the level of understanding of the product and its benefits for the customer. To have a positive impact on the success of AI-assisted lenses, manufacturers should therefore lay their focus on the conviction of the opticians. One way to do this is to demonstrate the product’s quality. This could be achieved by scientific tests, which could also enhance the knowledge of opticians regarding the additional value of AI-assisted lenses.

Keywords: AI-assisted lenses; trust; acceptance; awareness; technological innovation

ongoing theses

Erfolgsfaktoren der organisatorischen Verankerung der Digitalisierung und KI in Unternehmen - eine empirische Analyse

Bachelor, Status: ongoing

Course: Optometry

Konzeption und Umsetzung eines modernen online Marketings mit Schwerpunkt LinkedIn am Beispiel des berufsbegleitenden Masterstudiengangs M.Sc. Vision Science and Business (Optometry)

Bachelor, Status: ongoing

Course: Optometry

Leitfaden für die Integration von Nachhaltigkeit und künstliche Intelligenz als wesentliche Elemente der digitalen Geschäftsmodell-Entwicklung

Bachelor, Status: ongoing

Course: Optometry

Entwicklung Preismodell und App basierend auf KI-Prognosen von Erzeugung & Verbrauch

Master, Status: ongoing

Course: Industrial Management

Künstliche Intelligenz im Marketing: Status quo und Perspektiven

Bachelor, Status: ongoing

Course: Optometry