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Eskalation des Commitments in Wirtschaftsinformatik Projekten: eine kognitiv-affektive Perspektive
(2024)
Projekte im Bereich der Wirtschaftsinformatik (IS-Projekte) sind von zentraler Bedeutung für die Steuerung von Unternehmensstrategien und die Aufrechterhaltung von Wettbewerbsvorteilen, überschreiten jedoch häufig das Budget, sprengen den Zeitrahmen und weisen eine hohe Misserfolgsquote auf. Diese Dissertation befasst sich mit den psychologischen Grundlagen menschlichen Verhaltens - insbesondere Kognition und Emotion - im Zusammenhang mit einem weit verbreiteten Problem im IS-Projektmanagement: der Tendenz, an fehlgehenden Handlungssträngen festzuhalten, auch Eskalation des Commitments (Englisch: “escalation of commitment” - EoC) genannt.
Mit einem kombinierten Forschungsansatz (dem Mix von qualitativen und quantitativen Methoden) untersuche ich in meiner Dissertation die emotionalen und kognitiven Grundlagen der Entscheidungsfindung hinter eskalierendem Commitment zu scheiternden IS-Projekten und deren Entwicklung über die Zeit. Die Ergebnisse eines psychophysiologischen Laborexperiments liefern Belege auf die Vorhersagen bezüglich der Rolle von negativen und komplexen situativen Emotionen der kognitiven Dissonanz Theorie gegenüber der Coping-Theorie und trägt zu einem besseren Verständnis dafür bei, wie sich Eskalationstendenzen während sequenzieller Entscheidungsfindung aufgrund kognitiver Lerneffekte verändern. Mit Hilfe psychophysiologischer Messungen, einschließlich der Daten-Triangulation zwischen elektrodermaler und kardiovaskulärer Aktivität sowie künstliche Intelligenz-basierter Analyse von Gesichtsmikroexpressionen, enthüllt diese Forschung physiologische Marker für eskalierendes Commitment. Ergänzend zu dem Experiment zeigt eine qualitative Analyse text-basierter Reflexionen während der Eskalationssituationen, dass Entscheidungsträger verschiedene kognitive Begründungsmuster verwenden, um eskalierende Verhaltensweisen zu rechtfertigen, die auf eine Sequenz von vier unterschiedlichen kognitiven Phasen schließen lassen.
Durch die Integration von qualitativen und quantitativen Erkenntnissen entwickelt diese Dissertation ein umfassendes theoretisches Model dafür, wie Kognition und Emotion eskalierendes Commitment über die Zeit beeinflussen. Ich schlage vor, dass eskalierendes Commitment eine zyklische Anpassung von Denkmodellen ist, die sich durch Veränderungen in kognitiven Begründungsmustern, Variationen im zeitlichen Kognitionsmodus und Interaktionen mit situativen Emotionen und deren Erwartung auszeichnet. Der Hauptbeitrag dieser Arbeit liegt in der Entflechtung der emotionalen und kognitiven Mechanismen, die eskalierendes Commitment im Kontext von IS-Projekten antreiben. Die Erkenntnisse tragen dazu bei, die Qualität von Entscheidungen unter Unsicherheit zu verbessern und liefern die Grundlage für die Entwicklung von Deeskalationsstrategien. Beteiligte an „in Schieflage geratenden“ IS-Projekten sollten sich der Tendenz auf fehlgeschlagenen Aktionen zu beharren und der Bedeutung der zugrundeliegenden emotionalen und kognitiven Dynamiken bewusst sein.
Massive Open Online Courses (MOOCs) open up new opportunities to learn a wide variety of skills online and are thus well suited for individual education, especially where proffcient teachers are not available locally. At the same time, modern society is undergoing a digital transformation, requiring the training of large numbers of current and future employees. Abstract thinking, logical reasoning, and the need to formulate instructions for computers are becoming increasingly relevant. A holistic way to train these skills is to learn how to program. Programming, in addition to being a mental discipline, is also considered a craft, and practical training is required to achieve mastery. In order to effectively convey programming skills in MOOCs, practical exercises are incorporated into the course curriculum to offer students the necessary hands-on experience to reach an in-depth understanding of the programming concepts presented. Our preliminary analysis showed that while being an integral and rewarding part of courses, practical exercises bear the risk of overburdening students who are struggling with conceptual misunderstandings and unknown syntax. In this thesis, we develop, implement, and evaluate different interventions with the aim to improve the learning experience, sustainability, and success of online programming courses. Data from four programming MOOCs, with a total of over 60,000 participants, are employed to determine criteria for practical programming exercises best suited for a given audience.
Based on over five million executions and scoring runs from students' task submissions, we deduce exercise difficulties, students' patterns in approaching the exercises, and potential flaws in exercise descriptions as well as preparatory videos. The primary issue in online learning is that students face a social gap caused by their isolated physical situation. Each individual student usually learns alone in front of a computer and suffers from the absence of a pre-determined time structure as provided in traditional school classes. Furthermore, online learning usually presses students into a one-size-fits-all curriculum, which presents the same content to all students, regardless of their individual needs and learning styles. Any means of a personalization of content or individual feedback regarding problems they encounter are mostly ruled out by the discrepancy between the number of learners and the number of instructors. This results in a high demand for self-motivation and determination of MOOC participants. Social distance exists between individual students as well as between students and course instructors. It decreases engagement and poses a threat to learning success. Within this research, we approach the identified issues within MOOCs and suggest scalable technical solutions, improving social interaction and balancing content difficulty.
Our contributions include situational interventions, approaches for personalizing educational content as well as concepts for fostering collaborative problem-solving. With these approaches, we reduce counterproductive struggles and create a universal improvement for future programming MOOCs. We evaluate our approaches and methods in detail to improve programming courses for students as well as instructors and to advance the state of knowledge in online education.
Data gathered from our experiments show that receiving peer feedback on one's programming problems improves overall course scores by up to 17%. Merely the act of phrasing a question about one's problem improved overall scores by about 14%. The rate of students reaching out for help was significantly improved by situational just-in-time interventions. Request for Comment interventions increased the share of students asking for help by up to 158%. Data from our four MOOCs further provide detailed insight into the learning behavior of students. We outline additional significant findings with regard to student behavior and demographic factors. Our approaches, the technical infrastructure, the numerous educational resources developed, and the data collected provide a solid foundation for future research.
The dynamic landscape of digital transformation entails an impact on industrial-age manufacturing companies that goes beyond product offerings, changing operational paradigms, and requiring an organization-wide metamorphosis. An initiative to address the given challenges is the creation of Digital Innovation Units (DIUs) – departments or distinct legal entities that use new structures and practices to develop digital products, services, and business models and support or drive incumbents’ digital transformation. With more than 300 units in German-speaking countries alone and an increasing number of scientific publications, DIUs have become a widespread phenomenon in both research and practice.
This dissertation examines the evolution process of DIUs in the manufacturing
industry during their first three years of operation, through an extensive longitudinal single-case study and several cross-case syntheses of seven DIUs. Building on the lenses of organizational change and development, time, and socio-technical systems, this research provides insights into the fundamentals, temporal dynamics, socio-technical interactions, and relational dynamics of a DIU’s evolution process. Thus, the dissertation promotes a dynamic understanding of DIUs and adds a two-dimensional perspective to the often one-dimensional view of these units and their interactions with the main organization throughout the startup and growth phases of a DIU.
Furthermore, the dissertation constructs a phase model that depicts the early stages of DIU evolution based on these findings and by incorporating literature from information systems research. As a result, it illustrates the progressive intensification of collaboration between the DIU and the main organization. After being implemented, the DIU sparks initial collaboration and instigates change within (parts of) the main organization. Over time, it adapts to the corporate environment to some extent, responding to changing circumstances in order to contribute to long-term transformation. Temporally, the DIU drives the early phases of cooperation and adaptation in particular, while the main organization triggers the first major evolutionary step and realignment of the DIU.
Overall, the thesis identifies DIUs as malleable organizational structures that are crucial for digital transformation. Moreover, it provides guidance for practitioners on the process of building a new DIU from scratch or optimizing an existing one.