Research Designs & Practices in the Study of Public Organizations
Mixed Methods in Public Administration Research
Guidelines to Rigorous Qualitative Research
Rigor in Research: Deductive vs. Inductive Inquiry
Mixed Methods
Epistemology
Lincoln & Guba's (1986) criteria of trustworthiness
Naturalistic, inductive qualitative inquiry
Postpositivistic framework
Dominant philosophical stance in public management
Rich history of qualitative research integration, particularly organizational sciences
Widen pathways for qualitative studies toward influencing public management scholarship
Broader impact in public management if qualitative and quantitative methods are compatible and complementary
The world is complex
Messy domains of inquiry
Qualitative Research: Contributions to Public Management
Advance new theory & discovering nuance in existing theory
Define mechanisms underlying statistical associations
Develop new constructs, frameworks, & typologies
Organizational ethnography
Theory development in public management
Accountability in the public sector
Theories of goal-directed networks
Agency & stewardship theories
Nature of public participation
Foundation to quantitative research on the differences between managers and front-line workers
Public Service Motivation (PSM) - foundation to public management
Explicate how & why: transactions with agencies & service providers - Transaction Cost Economics (TCE)
Discuss the "mythology" of contracting - deeper mechanisms behind TCE
Explain the role of the environment in moderating managerial control vs. success
Inductive vs. Deductive Inquiry; NOT Qualitative vs. Quantitative
Eisenhardt & Graebner (2007)
Quality principles between inductive & deductive inquiry
Deductive: starts with premise, then investigates external validity
Inductive: starts with specific cases to describe phenomena and draw rich insight
Relevance of Advancing Theory
Inquiry-Driven Design
Gap-Driven Inquiry
Principle of inquiry-driven design
Importance of scholarship that advances theory
Criticality of gap-driven inquiry
Relevant findings beyond the study case is foundational to quality conceptualizations
Both inductive & deductive traditions are inquiry driven
Methodological appropriateness is valuable to both inductive & deductive research
Identify & address a gap in the literature
Investigate things that are overlooked, under-appreciated, or misunderstood
Generalizability
Elements of Rigor
Deductive
Inductive
Test the presence of a prior relationship in the population based on a sample
Most cases must conform to a pattern to infer a relationship, as long as the sample is representative
Research Design
Replication
Data Analysis & Interpretation
Should we care about understanding the experience of the individual/event?
Use a systematic method to interpret what is true (in rich detail)
Narrow in on specific types of phenomenon
Is a given interpretation credible given the evidence?
Analyst must draw inference & interpretation from existing qualitative information
Does the research add new insights of a phenomenon of interest to the field?
How trustworthy are the causal factors and significance within the cases?
Sample size (how many is enough?)
Qualitative saturation (dataset is robust/captures important variability)
Data Collection Protocols & Procedures
Sampling
Provide clear & concise descriptions of analysis process & findings
Rigor is best conceptualized via functionality
Clearly describe relevant data for a research question and how the data are obtained
Questions represent a clear conceptual linkage to the research question & a key consideration in the analysis & finding interpretation
Qualitative Comparative Analysis (QCA)
Narrative Policy Framework (NCF)
Framework for Mixed Methods Analysis
Variety in the order of inductive/deductive mixture
Creswell et al. (2003): deductive inquiry for hypothesis testing first, then inductive inquiry during second phase to analyze underlying mechanisms in great depth through qualitative
Considerations of rigor
Dual burden to all the requirements of rigorous design from both inductive & deductive models
Ideally reflect complementarity between approaches & maximize different advantages in inductive vs. deductive designs
Yanow & Schwartz-Shea (2014)
Combination of both qualitative & quantitative analysis
Ospina et al. (2018)
All the tools & techniques that are used to carry out research
Quantitative methods & deductive approach are typically alighned
Qualitative methods & inductive/abductive approaches are normally aligned
Selecting a Mixed Methods Design
Triangulation
Blanket justification for preferring a mixed over a single method
Useful to unpack underlying principle of any MM
Summary of findings from other scholars
Corroborate/complement findings to increase result validity
Gain multi-level understanding of the phenomenon
Connecting & Analyzing Primary Studies
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis)
MMs & Public Administration
Scholarship
Majority of studies adopt MMs, while a portion of them explicitly refer to the use of MMs
Summary of MMs
Sequencing Methods
Sequential
Quali-quantitative (Exploratory)
Parallel
Connecting Methods
Case selection
Themes (hypotheses)
Same sample
Interviews protocol
Themes (survey)
Themes (variables)
Purposive sample
Same data source
Findings combination