Welcome — A Methodological Partnership Begins Hello, and welcome. I'm genuinely pleased to be working alongside you on what is, from everything I can already see in your research framing, a timely and intellectually ambitious piece of doctoral scholarship. My work sits at the intersection of case study research architecture and qualitative inquiry design. Specifically, I bring deep working knowledge of Yin's replication logic and case study protocol frameworks, Stake's naturalistic and interpretive traditions, and Miles and Huberman's systematic approaches to qualitative data management and analysis — not as competing schools but as complementary traditions I'll draw on selectively depending on what your specific design decisions demand. I've guided researchers through the full spectrum of case study challenges: defending bounded system definitions under committee scrutiny, constructing airtight case selection rationales, designing triangulation architectures that hold up to methodological audit, and developing theoretical propositions through analytic generalization rather than statistical inference. What This Engagement Will Build — Complete Scope Preview Across our work together, we will construct your case study research system across every critical methodological dimension, in this sequence: Case Study Design Typology Selection and Rationale — confirming and defending your multiple case embedded design with the specific logic your phenomenon demands Case Selection Strategy and Purposive Sampling Design — building the replication logic and selection rationale for your three universities that a doctoral committee cannot unsettle Bounded System Definition and Scope Management — drawing your case boundaries with precision so your investigation has defensible edges Case Study Protocol Development and Research Instrumentation — constructing the operational document that governs your entire fieldwork Multiple Data Source Identification and Triangulation Design — mapping your four anticipated sources into a coherent triangulation architecture and identifying what may be missing Interview Data Collection Design — designing your semi-structured interview approach within the specific demands of a case study framework Observation and Document and Archival Analysis Integration — bringing your non-participant observation and policy document streams into methodological alignment with your interviews Within-Case Analysis and Pattern Identification — designing the analytical moves you make inside each university before you ever compare across them Cross-Case Analysis and Replication Logic — executing the comparative architecture that distinguishes a rigorous multiple case study from a collection of stories Theoretical Proposition Development and Analytic Generalization — translating your findings into a scholarly contribution that bridges digital transformation theory and leadership praxis Case Study Writing, Rich Description, and Findings Presentation — crafting findings chapters that meet the evidentiary and narrative standards of peer-reviewed publication Long-Term Research Capability Architecture — positioning this dissertation as a platform for ongoing bounded system investigation excellence By the time we complete this system, you will hold a complete, theoretically grounded, and publication-ready research architecture — one your committee chair can examine and immediately recognize as the work of a researcher who commands their methodology, not one who is applying it by formula. The Single Most Important Question Before I can make any of the above specific to your situation rather than generically applicable to any multiple case study, I need your answer to this: What is the precise nature of the variation across your three universities — Manchester, Birmingham, and Leeds — and have you selected them because you expect their leadership strategy and implementation outcome combinations to produce literal replication, theoretical replication, or both? To sharpen what I'm asking: Yin's replication logic — the design logic that makes a multiple case study analytically defensible rather than merely descriptive — requires that you select cases either because you predict similar results for similar reasons (literal replication) or because you predict different results for theoretically predictable reasons (theoretical replication). The answer determines your entire design typology rationale, your within-case analytical frame, your cross-case comparison architecture, and ultimately the form your theoretical contribution takes. You mentioned the three universities have "varying levels of digital maturity." That's a productive starting point — but I need to understand whether that variation is the independent variable you're using to achieve theoretical replication, or whether it's incidental background context. I also want to know whether you have preliminary evidence about the outcomes at each site — that is, whether implementation has been more or less successful at each — or whether outcome variation is something you're entering the field to discover. Your answer to this will shape every recommendation I make from this point forward. Please share as much as you currently know — including anything uncertain or still forming — and we'll build from exactly where you are.