Mahei Li

Mahei Li

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Dr.

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Li

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Mahei

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mahei.li@unisg.ch

Now showing 1 - 10 of 15

The Rise of Generative AI in Low Code Development Platforms – An Analysis and Future Directions

( 2024-01-06)
Olivia Bruhin
;
Ernestine Dickhaut
;
Edona Elshan
;
Mahei Li

This study investigates the relationship between Generative AI (GenAI) and Low Code Development Platforms (LCDPs), providing preliminary insights into Gen's transformative potential in this context. It is based on expert interviews and provides insight into the changing landscape of LCDPs influenced by GenAI. The findings highlight the promising benefits of GenAI in LCDPs, such as increased efficiency and decreased errors, while also emphasizing the importance of human oversight and collaboration. The findings also highlight the importance of interpersonal skills in IT, even in an increasingly automated environment. While the economic efficiency and broader implications of GenAI are still being investigated, the study lays the groundwork for future research in this rapidly evolving domain.

Type: conference paper

Journal: Hawaii International Conference on System Sciences (HICSS)

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/118148
Generative AI in Customer Support Services: A Framework for Augmenting the Routines of Frontline Service Employees

( 2024-01-06)
Philipp Reinhard
;
Mahei Li
;
Christoph Peters
;
Jan Marco Leimeister

Customer support service employees are facing an increased workload, while artificial intelligence (AI) appears to possess the potential to change the way we work. With the advent of modern types of generative AI, new opportunities to augment frontline service employees have emerged. However, little is known about how to integrate generative AI in customer support service organizations and purposefully change service employee work routines. Following multi-method qualitative research, we performed a literature review, conducted workshops, and interviewed IT support agents, managers, and AI experts. Thereby, we examine AI augmentation for frontline service employees in the context of IT support to carve out where and how GenAI can be leveraged to develop more efficient and higher-quality customer support. Our resulting framework reveals that especially adapting solutions and retaining knowledge is subject to a high degree of AI augmentation.

Type: conference paper

Journal: Hawaii International Conference on System Sciences (HICSS)

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/118181
Sense of Control for Empowerment in Hybrid Intelligence Service Systems

( 2021-12-15)
Eilers, Karen
;
Li, Mahei

Type: conference paper

Journal: International Conference on Information Systems (ICIS). Workshop: Service and Information Systems Research for a Better Future

URL: https://icis2021.aisconferences.org/

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/109624
Take the Wheel - Technology-driven Change in the Energy Sector

( 2019)
Li, Mahei
;
Müller, Jennifer
;
Ernst, Sissy-Josefina
;
Peters, Christoph

Type: conference paper

Journal: International Conference on Information Systems (ICIS)

URL: https://aisel.aisnet.org/icis2019/learning_environ/learning_environ/1/

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/99412
From Service Systems Engineering to Service Innovation - A Modeling Approach

( 2019-06-10)
Li, Mahei
;
Peters, Christoph

Due to the advent of digitization, service innovation has become even more important for both business and service research alike. Current service systems engineering approaches have employed a recombinant perspective that follows innovation mechanisms to leverage existing company resources for new service innovations. Employing these innovation mechanisms is still challenging, since there is little support on how to structure and identify these mechanisms. We propose a model-based service system engineering approach to structure existing resources into one formal model, enabling the formalization of service innovation mechanisms. The formalized service innovation mechanisms allow for a graphical illustration and enable future research to apply functions to analyze how innovation impacts entire or specific parts of service systems. Furthermore, the mathematical model enables an object-oriented value-driven perspective on service systems and is basis for graphical software tools. We contribute to literature by formalizing service innovations and its mechanisms in the context of service systems and by combining concepts of service innovation and service systems engineering. We do so by a) formalizing service innovation mechanisms and b) demonstrating the application of formal service innovations along one specific software implementation case. For practice, the service system model can with simulating the effects of service innovations.

Type: conference paper

Journal: European Conference on Information Systems (ECIS)

URL: https://aisel.aisnet.org/ecis2019_rp/174/

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/98563
A service system modelling approach

( 2018)
Li, Mahei

Type: conference paper

Journal: International Conference on Exporing Service Science (IESS)

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/101371
Einführung eines DSGVO-konformen Videokonferenzsystems in hessischen Schulen. Projektergebnisse des ZEVEDI Ad hoc-Vorhabens „Wechselkosten zum DSGVO-konformen VC-System des Schulportals Hessen“

(Kassel University Press (KUP), 2023)
Ernestine Dickhaut
;
Lasse Schaup
;
Mahei Li
;
Jan Marco Leimeister

Type: book

URL: https://doi.org/10.17170/kobra-202303207659

DOI: 10.17170/kobra-202303207659

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/118752
German Standardization Roadmap on Artificial Intelligence

( 2022)
German Institute for Standardisation (DIN e. V.)
;
German Commission for Electrical, Electronic & Information Technologies of DIN and VDE (DKE)
;
Ernestine Dickhaut
;
Mahei Li
;
Christoph Peters
;
many other authors (see chapter 11)
;
Wolfgang Prof. Dr. Wahlster
;
Christoph Winterhalter

On behalf of the German Federal Ministry of Economic Affairs and Climate Action, DIN and DKE started work on the second edition of the German Standardization Roadmap Artificial Intelligence in January 2022. With the broad participation and involvement of more than 570 experts from industry, science, the public sector and civil society, the strategic Roadmap for AI standardization was thus further developed. This work was coordinated and accompanied by a high-level coordination group for AI standardization and conformity The standardization roadmap implements a measure of the German government’s AI Strategy and thus makes a significant contribution to “AI – Made in Germany”. Standardization is part of the AI Strategy and is a strategic instrument for strengthening the innovation and competitiveness of the German and European economies. Not least for this reason, standardization plays a special role in the planned European legal framework for AI, the Artificial Intelligence Act. This Standardization Roadmap AI identifies the requirements in standardization, formulates concrete recommendations and thus creates the basis for initiating standardization work at national level, and especially at European and international level, at an early stage. In doing so, the Roadmap makes a significant contribution to the European Commission’s Artificial Intelligence Act, supporting its implementation. The Standardization Roadmap AI focuses on nine key topics, which are addressed in Chapter 4: → The Roadmap begins with the basic topics, such as terminologies and definitions, classifications and ethical issues. They are the basis for AI discussions and are thus the central core of the Roadmap. → The security/safety of AI systems plays a crucial role in widespread use of AI solutions. Only a more in-depth consideration of requirements for operational safety and information security, for example, can enable the comprehensive use of AI systems in business and society. → Another key topic, and the basis for the broad market success of AI, is testing and certification. This requires reliable quality criteria and reproducible test methods that can be used to verify the properties of AI systems. They are a key prerequisite for assessing the quality of AI-based applications and contribute significantly to explainability and traceability – two factors that build trust and acceptance. → Another challenge in the use of AI, especially for small and medium-sized enterprises, is the integration of AI technologies in organizations. The focus here is on sociotechnical aspects such as human-technology interaction, humane work design, and requirements for business structures and processes, which are all examined in the Roadmap. → The fields of application of AI are extremely diverse. AI technologies are used in almost all business and application areas and offer great potential. To cover a broad spectrum of applications, the Roadmap considers industry-specific challenges for the following five sectors in particular, in addition to the cross-cutting issues mentioned above: Industrial Automation, Mobility, Medicine, Financial Services and Energy / Environment. The present Roadmap outlines the work and discussion results for all nine key topics and provides a comprehensive overview of the status quo, requirements, and needs for action.

Type: book

URL: https://din.de/go/roadmap-ai

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/118321
Nutzungszentrierte Gestaltung von HI-basierten Dienstleistungen am Beispiel des IT-Supports

(Springer Gabler, 2021-08-23)
Schmidt, Simon L.
;
Li, Mahei
;
Peters, Christoph
;
Leimeister, Jan Marco
;
Bruhn, Manfred
;
Hadwich, Karsten

Type: book section

Volume: Geschäftsmodelle – Serviceinnovationen – Implementierung

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/110093
Gestaltungsdimensionen der Digitalisierung – Wie Dienstleistungssysteme den Wandel antreiben und welche Faktoren eine Rolle spielen

(Springer Gabler, 2020-10-03)
Grotherr, Christian
;
Li, Mahei
;
Schymanietz, Martin
;
Fritzsche, Albrecht
;
Semmann, Martin
;
Peters, Christoph
;
Böhmann, Tilo
;
Leimeister, Jan Marco
;
Möslein, Kathrin M.

Type: book section

URL: https://link.springer.com/chapter/10.1007%2F978-3-662-62144-8_6

DOI: 10.1007/978-3-662-62144-8_6

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/111704

Mahei Li

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