Practice-based IS Research

Permanent URI for this collectionhttps://hdl.handle.net/10125/112547

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Now showing 1 - 7 of 7

How Do I Get Students to Know My IT Products? Comparing the Academic Ecosystems of Two IT Giants: IBM & SAP
(2026-01-06) Heim, Sophie; Benthake, Leonard; Landler, Philipp; Wittges, Holger; Hein, Andreas; Krcmar, Helmut
Collaboration between academia and the IT industry benefits both sides in various ways. Most companies seek to attract high-performing students. Yet only a limited number invest in enduring academic partnerships. There are many strategic considerations and pitfalls when building lasting relationships, especially when productive IT solutions are used in teaching and research. Although such relationships involve many stakeholders, details on their structure often remain opaque. By drawing on the development of e3 value models of IBM’s and SAP’s academic ecosystems and ethnographic case study data, we compare the two ecosystems. We discuss their main differences and give five recommendations on what practitioners of IT companies must consider when (re-)designing their academic ecosystem strategy. Based on the main challenges IBM’s and SAP’s academic ecosystems face, we identify two trends: centralized learning platforms and reaching more students via intermediaries as multipliers.
Project Management for Blockchain: Strategic Guidance and Lessons from Practice
(2026-01-06) Noteboom, Cherie; Sekar, Aravindh; Tech, Deb
Blockchain technology (BCT) offers powerful solutions to long-standing enterprise challenges such as inefficiencies, lack of transparency, and low stakeholder trust. By enabling secure transaction tracking and real-time data sharing, BCT can improve operational accuracy, streamline workflows, and build confidence across organizational ecosystems. However, the implementation of BCT significantly transforms conventional project management strategies and practices. We propose practical recommendations for each stage of the process group of the project life cycle- Initiating, Planning, Executing, Monitoring & Controlling, and Closing to meet the demands of decentralization, interoperability, and continuous ecosystem coordination inherent in the implementation of BCT projects. Grounded in practitioner insights, this study advances practice-based IS research by offering actionable, process-specific guidance for managing blockchain projects and contributes to project management knowledge by revealing how decentralized technologies reshape conventional lifecycle approaches.
Corporate Ecosystem Start-Ups: An Organizational Approach for Successfully Scaling Data Ecosystems
(2026-01-06) Würthner, Tanja; Weber, Patrick
The transition to cooperative, data-driven ecosystems is reshaping value creation in industries, driven by digital technologies. This paper examines the challenges and opportunities of scaling such ecosystems, focusing on a case study of a data-based solution for intralogistics developed by an industrial service provider in collaboration with ecosystem partners. The study highlights the limitations of established approaches in addressing joint governance, shared value creation, and trust essential for ecosystem success. To bridge this gap, the Corporate Ecosystem Start-Up (CESU) approach is proposed – a novel business innovation approach tailored to the unique demands of scaling solutions in data ecosystems. Drawing on insights from the practical case, the CESU approach is designed and evaluated using the criteria scope of action, risk and ownership, resources, and market access. Strategies to overcome organizational barriers and ensure alignment are described, providing a pathway to ecosystem growth. This research advances the understanding of scaling data ecosystems.
The BI Trap – A Tripping Risk on the Way to the Successful Use of Process Mining
(2026-01-06) Navratilova, Martina; Nusch, Henning; Plattfaut, Ralf; Coners, Andre
Process mining (PM) is one recent technology trend with considerable potential for process optimization. We have noticed that the PM application in literature seems to be further along than the actual implementation in practice. In theory, the optimal process mining application encompasses the entire spectrum, from process discovery to action-oriented process mining. In practice, however, full utilization is rarely observed. To investigate this further, we conducted a qualitative study and interviewed 27 users in various positions from 16 different companies. We found that companies often stagnate in the early stages of application development and are therefore unable to generate sustainable value with PM. Actual process optimizations are carried out manually or not implemented at all. Based on this, we conceptualize the “BI trap” that companies may fall into when implementing and using PM, and have developed recommendations to avoid this scenario and ensure the successful and full utilization of PM.
Islands of Innovation or Systemic Transformation? The Scaling Dilemma of Generative and Agentic AI within Organizations
(2026-01-06) Denicolai, Stefano; Bartosiak, Marcin
Generative and Agentic AI (GAAI) present organizations with both transformative opportunities and costly risks. While pilots and point solutions proliferate, many firms struggle to scale GAAI beyond experimentation, resulting in unrealized revenue potential and risks of operational, reputational, and compliance failures. This work addresses the critical management challenge of moving from fragmented initiatives to enterprise-wide capability building. Using a mixed-method empirical approach, we trace the scaling journey of successful GAAI adoption and validate a three-phase framework that captures the progression from experimentation to integration and institutionalization. By offering actionable guidelines, this paper enables practitioners to unlock value through productivity gains and revenue growth, while mitigating the risks of costly missteps. These insights provide a roadmap for realizing sustainable, enterprise-level returns from GAAI investments.
From Generic to Strategic: Managerial Challenges and Response Mechanisms for Customizing Gen AI in Companies
(2026-01-06) Diaferia, Lorenzo; Kappelhoff, Sara Luisa; Blohm, Ivo
Companies are increasingly using customization techniques to tailor standard GenAI technologies with their unique characteristics such as open-endedness and inscrutability to their specific business needs. While customization is essential for companies to derive business value with GenAI, the practical challenges that managers encounter during customization projects remain underexplored. We interviewed cross-industry AI practitioners involved in GenAI projects to investigate the challenges they face when customizing GenAI and the response mechanisms they apply to increase the effectiveness of their customization efforts. Thereby, we provide practitioners with three actionable recommendations to build capabilities for successful GenAI customization: adjust data governance to treat unstructured data as a strategic GenAI asset, implement a risk-tiered GenAI governance, and build a modular GenAI stack to retain flexibility.
Introduction to the Minitrack on Practice-based IS Research
(2026-01-06) Kettinger, Bill; Rodriguez, Joaquin; Piccoli, Gabriele; Milovich, Michael

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