HSG CRIS

Permanent URI for this communityhttps://www.alexandria.unisg.ch/handle/20.500.14171/1

Browse

Search Results

Now showing 1 - 10 of 57

Some of the metrics are blocked by your
consent settings
How to Generate Research Impact: A Framework and Checklist for Impact-Aware Information Systems Research
(2026)
Vom Brocke Jan
;
Bergener, Katrin
;
Stein, Armin
;
Franzoi, Sandro
;
Becker, Jörg
Research impact has emerged as a defining challenge for the Information Systems discipline. While bibliometric indicators remain prevalent, they capture only a fraction of the value Information Systems research generates for organizations, policy, and society. This panel report documents the outcomes of a structured workshop held at the ERCIS Annual Workshop 2025 in St. Gallen, Switzerland, in which 55 Information Systems scholars from across the globe collectively reflected on the nature, mechanisms, and future directions of research impact. Drawing on a World Café format with three thematic breakout sessions – covering past experiences of impact generation, current process practices, and forward-looking aspirations – the workshop surfaced rich, practitioner-grounded insights. Synthesizing these insights, we develop a research impact framework that maps six core impact themes – problem relevance & societal value, stakeholder engagement & co-creation, credible actionability, adaptiveness & learning, ethics & risk awareness, and sustainability & longevity – against the four phases of Benbya et al. (2026) impact framework: planning, delivering, measuring, and communicating. The matrix serves as a practical self-assessment tool for Information Systems researchers seeking to design more impactful research. Our findings point to the importance of sustained stakeholder partnerships, problem-driven research design, and institutional ecosystems that reward societal relevance alongside academic rigor.
Type:journal article
Journal:Communication of the AIS
URL:https://aisel.aisnet.org/cais/vol58/iss1/89/
URI:https://alexandria.unisg.ch/handle/20.500.14171/126888
Some of the metrics are blocked by your
consent settings
Hybrid Upper Echelons: A Theorizing Review on AI in Executive Decision-Making
(2026)
Mehler, Alisa
;
Hein, Andreas
Artificial intelligence (AI) increasingly participates in strategic decision-making, challenging leadership theories that assume human agency at the top of organizations. Yet research on AI-enabled decision-making and upper echelons theory (UET) has largely evolved in parallel. We conduct a concept-centric literature review integrating management and information systems (IS) research to examine how AI affects executive decision-making. Our analysis identifies three mechanisms through which AI reconfigures UET: cognition reconfiguration through the mediation of information and attention, evaluation reconfiguration through the partial substitution of human judgment with algorithmic decision logic, and discretion reconfiguration through the delegation and embedding of decision authority. AI expands analytical capacity while introducing new constraints, shapes how alternatives are evaluated, and redistributes managerial discretion. We introduce the concept of hybrid upper echelons to explain how human and algorithmic actors jointly influence strategic outcomes, showing that executive influence increasingly shifts from making decisions to configuring and governing AI-enabled decision processes.
Type:conference paper
URI:https://alexandria.unisg.ch/handle/20.500.14171/125697
Some of the metrics are blocked by your
consent settings
Why Industrial Internet of Things Platforms Fail: A Structuration Theory Perspective on Platform Evolution
(2026-03-20)
Philipp Kernstock
;
Andreas Hein
;
Maximilian Schreieck
;
Helmut Krcmar
Despite their transformative potential, Industrial Internet of Things (IIoT) platforms often fail to evolve into scalable ecosystems. Research on IIoT platforms attributes failure to discrete factors such as governance misalignment or technological complexity and rarely considers how failure unfolds. This article adopts a structuration theory perspective to examine IIoT platform failure as a path-dependent process. Through a seven-year longitudinal case study of Alpha, a global industrial manufacturer, we identify four structuration mechanisms—structural embeddedness, misalignment, reproduction, and reversion—that progressively constrain platform scalability. Our findings reveal that failure is not a singular event but an emergent outcome shaped by recursive interactions between architecture, governance, and market structures, as well as strategic actions. We contribute to platform governance research by showing that IIoT platforms inherit, rather than impose, governance structures, making it crucial for firms to actively reshape contracting dependencies rather than replicating existing structures. Based on these insights, we provide recommendations for firms to design governance frameworks that foster openness, modularity, and ecosystem scalability from the outset. These insights offer a more dynamic understanding of IIoT platform evolution, informing theory and practice on overcoming the barriers to the scalability of IIoT platforms.
Type:journal article
Journal:Journal of Product Innovation Management
DOI:10.1111/jpim.70039
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/125344
Scopus© Citations 2
Some of the metrics are blocked by your
consent settings
The Anatomy of Data Ecosystems: Identifying and Analyzing Archetypes
(2024)
Kernstock, Philipp
;
König, Fabian
;
Böttcher, Timo
;
Andreas Hein
;
Krcmar, Helmut
Organizations are shifting from traditional business models towards a collaborative, data-centric paradigm, giving rise to data ecosystems. However, while opportunities for leveraging data in these ecosystems are vast, such ecosystems' structure, governance, and operation remain nebulous. Thus, our research delves into the operational intricacies of data ecosystems. Drawing upon a cluster analysis of 142 data ecosystem initiatives and integrating theoretical perspectives on data ecosystems and digital platforms, we identify five distinct archetypes characterized by variations in organizational structure, technical openness, actor interdependence, and governance. Our findings illuminate the core elements of data ecosystems and provide pragmatic insights for their application, fostering an understanding critical for designing multi-sided data platforms and governance mechanisms in public data spaces. This research contributes a comprehensive tool for academia to understand data ecosystems and a guide for industry practitioners to manage organizations within these complex structures.
Type:conference paper
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/120012
Some of the metrics are blocked by your
consent settings
Data Mesh - A Case Study Perspective on Building Industrial Data Platforms
(2024-04)
Kernstock, Philipp
;
Biermann, Konstantin
;
Sartor, Sebastian
;
Wimbauer, Anna
;
Bohnet, Julian
In an era where data is the new currency, organizations are contending to harness vast data influxes for data-driven innovation. Centralized data architectures, with extensive data warehouses and lakes, are buckling under the pressure of contextually complex and distributed demands, leading to data bottlenecks and alignment issues within organizational structures. Data Mesh emerges as a decentralized paradigm promising to surmount these hurdles by advocating domain ownership and federated governance. This research delves into the practicalities of Data Mesh through a case study of Alpha, a German manufacturing firm, revealing a transformative shift towards a data-driven modus operandi. It details Alpha's journey from siloed data storage to a unified, transparent data platform that repositions IT as an innovation linchpin. Bridging the theoretical and practical, the paper underscores Data Mesh's potential to amalgamate decentralized data ownership with central oversight, offering a roadmap for organizations to navigate the data-centric future effectively.
Type:conference paper
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/119888
Some of the metrics are blocked by your
consent settings
The AI Transformation? Unpacking the Impact of AI on Incumbent Business Models
(2024)
Weber, Michael
;
Knabl, Oliver
;
Timo Böttcher
;
Andreas Hein
;
Helmut Krcmar
Incumbent firms feel pressured to incorporate artificial intelligence (AI) in their business model (BM) to innovate and stay competitive. While transforming the BM with digital technologies is challenging, AI adds complexity through its countless applications and incomprehensible nature. Unraveling this complexity, we develop a taxonomy to describe and analyze how AI impacts incumbent BMs. The taxonomy builds on extant literature and the analysis of 46 empirical cases. Our findings reveal AI's varying roles in enhancing and transforming offerings, key operations, and financial logic. In addition, the taxonomy highlights different ways incumbents include AI capabilities and data as key enablers of the resulting BM. Despite the hype around AI, we critically reflect that most of AI's impact corresponds to well-known digital BM concepts (e.g., personalization). However, AI technology's progress might intensify the effectiveness of those BMs and spur novel opportunities within the known digital BM space.
Type:conference paper
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/119887
Some of the metrics are blocked by your
consent settings
Preface to the special issue on "Enterprise and organizational applications of distributed ledger technologies"
(2024)
Zavolokina, Liudmila
;
Hein, Andreas
;
Carvalho, •
;
Schwabe, Gerhard
;
Helmut Krcmar, •
In the fast-evolving landscape of digital technologies, distributed ledger technologies (DLTs)—commonly known as blockchain—have emerged as a highly disruptive force that holds the potential to change how transactions are conducted fundamentally and assets are managed. Drawing comparisons with the revolutionary impact of the internet’s foundational TCP/IP protocol, DLTs have opened up new horizons regarding security, speed, and decentralization. DLTs offer unique features such as improved accountability, pseudonymity, and the ability to operate in a decentralized network environment. These features have implications far beyond the initial context of cryptocurrencies, initially exemplified by Bitcoin (Nakamoto, 2009), a cryptocurrency that introduced a new way of conducting transactions without a central authority, thus lowering costs and improving efficiency.
Type:journal article
Journal:Electronic Markets
Volume:34
Issue:1
DOI:10.1007/s12525-023-00688-7
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/119424
Scopus© Citations 2
Some of the metrics are blocked by your
consent settings
Streamlining the Operation of AI Systems: Examining MLOps Maturity at an Automotive Firm
(2024)
Weber, Michael
;
Schniertshauer, Johannes
;
Ag, Audi
;
Przybilla, Leonard
;
Hein, Andreas
Developing and operating AI systems based on machine learning (ML) has unique challenges that render traditional practices inappropriate (e.g., managing data drift). To that end, MLOps emerged as a novel paradigm for managers and teams to develop and operate such ML systems successfully. Organizations currently employ different maturity levels for MLOps, whereas higher maturity typically corresponds to more automated, streamlined, and reliable workflows. However, we have limited insight into factors influencing MLOps maturity in ML projects. Therefore, we conducted a case study on MLOps maturity in three ML projects at an automotive firm. We identified several contextual factors that facilitate or inhibit MLOps maturity, such as the ML model's complexity, the quality of new data, and the appropriateness of available MLOps tools. Our study contributes to research on managing and organizing AI by providing factors that explain the different adoption of MLOps in practice.
Type:conference paper
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/119423
Some of the metrics are blocked by your
consent settings
Unpacking Digital Transformation Tensions through Workers' Perceptions: A Technological Frame and Paradox Theory Approach
(2024)
Viljoen, Altus
;
Przybilla, Leonard
;
Hein, Andreas
;
Keilbach, Anna
;
Krcmar, Helmut
This study proposes that actors' perceptions of digital transformation (DT), constructed through technological frames, can explain organizational tensions that firms experience during DT initiatives. We conducted a qualitative case study with a large manufacturer over 12 months, analyzing how different hierarchical employee groups' technological frames shape their perception of DT. The results illustrate that actors' perceptions of DT comprise three dimensions (reasons for DT, contributions to DT, and communication during DT initiatives), and how these perceptions explain four different organizational tensions in DT. We contribute to theory on DT by showing how classifying actors' perceptions of DT through technological frames and paradox theory enables an understanding of how organizational tensions in DT may originate on the individual level.
Type:conference paper
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/119422
Some of the metrics are blocked by your
consent settings
Building open government data platform ecosystems: A dynamic development approach that engages users from the start
(2023)
Hein, Andreas
;
Engert, Martin
;
Ryu, Sunghan
;
Schaffer, Norman
;
Hermes, Sebastian
Open government data (OGD) platform ecosystems hold immense potential for promoting transparency, civic engagement, economic growth, and improved governmental offerings. The prevailing strategy to building OGD platform ecosystems follows a sequential approach where the OGD platform is built first and the ecosystem is built second, resulting in low engagement. In this paper, we derive insights into an alternative approach to developing OGD platform ecosystems from TourismData, a state-owned tourism initiative in Germany. We report on the phases between 2018 and 2022 and derive four dynamic and incremental phases from which we derive three learnings: context specificity, continuous adaptation, and organic expansion. Our findings have theoretical and practical implications for developing high-engagement OGD platform ecosystems that include and engage ecosystem actors from the start and, hence, take advantage of the generative potential of OGD. This approach illustrates the importance of developing OGD platform ecosystems with high contextual relevance to ensure that data can be used to enable meaningful interactions between ecosystem actors and promote continuous adaptation and expansion.
Type:journal article
Journal:Government Information Quarterly
Volume:40
Issue:4
DOI:10.1016/j.giq.2023.101878
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/119421
Scopus© Citations 29

HSG CRIS

Browse

Filters

Settings

Sort By

Results per page

Search Results