Keywords

digital transformation, system dynamics, sustainability

Subject Categories

Business Administration, Management, and Operations | Management Information Systems | Organizational Behavior and Theory

Abstract

Despite significant organizational investments, more than 70% (Ellmer et al., 2025) of digital transformation initiatives fail. The existing literature evaluates transformation mechanisms as separate factors rather than as interacting, evolving feedback systems. This dissertation addresses this gap by developing and validating a system dynamics framework for sustained digital transformation. Guided by three research questions, the study examined the mechanisms that enable or constrain transformation, identified mechanisms distinctive to digital transformation contexts, and evaluated how existing change management frameworks guide transformation efforts. The study followed a six-phase methodology that combined a systematic literature review of peer-reviewed studies, empirical cases, causal loop diagram development, expert validation, stock-and-flow modeling, proof-of-concept simulation, and comparative framework analysis. The findings confirm that digital transformation shares foundational mechanisms with traditional change management, including leadership commitment, capability development, resistance, and resource constraints. However, these mechanisms operate with greater intensity and interdependence. Sixty-nine percent of the coded mechanisms are distinctive to digital transformation, including unstable equilibrium, hindrance appraisal, data assetization, and dynamic capabilities as preconditions of digital transformation. A comparative framework analysis established that existing change management frameworks do not address how digital transformation dynamics develop over time. The study developed an integrated causal loop diagram and conceptual stock-and-flow model that addresses this limitation by identifying two main trajectory patterns. The first is a reinforcing trajectory that sustains transformation momentum through leadership, capability, adoption, and learning. The second is a balancing trajectory that erodes transformation, where delayed value realization gradually weakens commitment and reduces organizational learning. The proof-of-concept simulation confirmed that the stock-and-flow model could reproduce expected transformation patterns. This framework contributes an evidence and system-based explanation of why some digital transformation efforts build momentum while others weaken over time. The framework provides the structural foundation for future empirical calibration, scenario testing, and predictive modeling.

Completion Date

2026

Semester

Summer

Committee Chair

Rabelo, Luis

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Format

PDF

Document Type

Dissertation

Language

English

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