Service-Dominant Logic Dissertation Empirical Case Studies: Research Design, Evidence Logic, and Field Applications

Author: Dr. Martin Keller, PhD (Service Systems Research, University of Amsterdam)
15+ years in qualitative and mixed-methods research on service ecosystems, institutional logics, and organizational value co-creation

The empirical study of Service-Dominant Logic (SDL) in dissertations is not just about applying a framework. It is about understanding how value is co-created across actors, institutions, and systems in real-world settings. This article presents a structured, practitioner-level approach to designing and executing empirical case studies grounded in SDL principles.

Quick Answer: What You Need to Know About SDL Empirical Case Studies

Understanding the Empirical Logic of Service-Dominant Logic

Short answer

SDL empirical research focuses on observing how value is co-created through interactions between actors in service systems, rather than measuring isolated outputs.

Explanation

Unlike traditional goods-dominant perspectives, SDL requires researchers to shift from static variables to dynamic interactions. The empirical focus is on processes such as resource integration, institutional arrangements, and service exchange mechanisms.

Example

A healthcare ecosystem study may analyze how hospitals, digital platforms, patients, and insurers co-create treatment pathways instead of evaluating hospital efficiency alone.

Traditional LogicService-Dominant Logic
Firm produces valueValue is co-created with actors
Static performance metricsDynamic interaction processes
Isolated units of analysisService ecosystems

Researchers needing structured dissertation assistance can request support for empirical SDL study design and analysis here, especially when working with complex multi-actor datasets.

Choosing the Right Case Study Design

Short answer

Case study design in SDL research depends on whether the focus is exploratory, explanatory, or theory-building.

Explanation

Most SDL dissertations use multiple-case designs to capture variation across service systems. The aim is not generalization in a statistical sense but analytical replication.

Example

A study comparing digital banking ecosystems in Finland and Germany to examine institutional differences in value co-creation mechanisms.

Design TypePurposeSDL Use Case
Single CaseDeep contextual insightHealthcare system transformation
Multiple CasePattern identificationFintech ecosystem comparison
Embedded CaseMulti-level analysisPlatform-based service networks
Teaching Insight: Strong SDL dissertations rarely rely on one case. Depth comes from comparing how value co-creation mechanisms vary across contexts.

Data Collection in SDL Empirical Research

Short answer

SDL case studies rely on multi-source qualitative and relational data rather than single-method datasets.

Explanation

The complexity of service ecosystems requires triangulation across interviews, observations, and documentary evidence. Data should capture both actor perspectives and system-level interactions.

Example Sources

Data TypePurpose
InterviewsActor interpretation of value co-creation
DocumentsInstitutional and governance context
ObservationsReal-time interaction dynamics

Specialists can help structure your SDL data collection protocol and refine interview frameworks for dissertation-level rigor.

Analyzing Service Ecosystem Data

Short answer

Analysis focuses on identifying interaction patterns, resource integration mechanisms, and institutional logics.

Explanation

Rather than coding for themes only, SDL analysis often combines thematic coding with system mapping and relational analysis. This helps identify how actors co-create value over time.

Example

A mobility platform study may reveal how users, regulators, and platform providers negotiate service access rules dynamically.

Analysis LayerFocus
MicroIndividual actor interactions
MesoOrganizational collaboration
MacroInstitutional environment
Common Mistake: Treating SDL data as isolated themes instead of interconnected systems leads to fragmented conclusions.

REAL VALUE BLOCK: How SDL Empirical Research Actually Works

Core Mechanism: SDL empirical research works by tracing how value emerges through interactions between actors exchanging operant resources (knowledge, skills, capabilities) within institutional structures.

Key Decision Factors:

What actually matters:

Common mistakes:

Teaching angle: Think of SDL as studying “how systems negotiate value over time,” not “who creates value.”

What Others Often Miss in SDL Dissertation Research

The strongest dissertations explicitly show how empirical evidence modifies or extends SDL theoretical assumptions rather than simply applying them.

Practical Checklists for SDL Empirical Studies

Checklist 1: Case Selection

Checklist 2: Data Quality

Empirical Patterns in SDL Research (Observed Trends)

These patterns reflect a shift from firm-centric analysis to ecosystem-level interpretation of value creation.

Brainstorming Questions for Dissertation Development

Methodological Pitfalls in SDL Case Studies

A strong dissertation explicitly shows how empirical evidence challenges or refines theoretical expectations rather than simply confirming them.

Integration with Dissertation Structure

SDL empirical case studies should align with broader dissertation architecture, especially theoretical framing and methodological design.

Checklist: Writing Strong SDL Empirical Chapters

FAQ: Service-Dominant Logic Empirical Case Studies

What is an SDL empirical case study?

It is a qualitative research approach that examines how value is co-created within service ecosystems through real-world interactions.

Why are case studies used in SDL research?

Because SDL focuses on dynamic, contextual interactions that cannot be captured through purely quantitative methods.

What data is typically used?

Interviews, observations, documents, and digital interaction records are commonly used to capture ecosystem behavior.

How many cases are needed?

Many dissertations use 2–5 cases to allow for comparative analysis and pattern identification.

What is a service ecosystem in SDL?

A network of interconnected actors who integrate resources to co-create value.

How do you analyze SDL data?

Through thematic coding, system mapping, and relational interpretation across multiple levels of analysis.

What is the biggest challenge in SDL research?

Capturing complex interactions without oversimplifying system dynamics.

Can SDL be applied to digital platforms?

Yes, digital ecosystems are one of the most common SDL research contexts.

What is resource integration?

The process by which actors combine skills, knowledge, and tools to create value.

What are operant resources?

Dynamic resources like knowledge and capabilities that act on other resources.

How do institutions affect SDL systems?

They define rules, norms, and constraints shaping interaction patterns.

What makes an SDL dissertation strong?

Clear theoretical grounding, rich empirical data, and multi-level analysis.

Is SDL suitable for quantitative research?

It is primarily qualitative but can be combined with quantitative methods in mixed designs.

What is a common mistake in SDL dissertations?

Treating value as a static outcome instead of a dynamic process.

How can I structure my SDL dissertation effectively?

By aligning theory, methodology, and empirical chapters into a coherent multi-level framework.

If you need structured support refining your empirical design or analysis approach, you can request expert dissertation assistance here.

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