Jason Miklian

Research Methodology

Jason Miklian's research employs a diverse methodological toolkit developed through 15+ years of fieldwork in conflict zones and fragile states. His approach combines qualitative ethnographic methods with quantitative analysis, systems thinking, and emerging computational approaches. With 75+ publications across peer-reviewed journals, Miklian has contributed to expanding how we understand conflict dynamics, peacebuilding effectiveness, and the role of technology in social science.

Key Insights

  • Systems analysis captures peace as emergent property: Peace emerges from complex interactions among actors and institutions, not from isolated interventions. Systems thinking enables research on feedback loops and dynamic processes that linear causal models miss. Source: Peacebuilding, 2025
  • Large language models replicate human responses imperfectly: LLMs exhibit systematic biases that vary across models and populations. Synthetic data cannot replace human respondents but may serve legitimate functions with transparent documentation of limitations. Source: arXiv preprint, 2025
  • Mixed methods strengthen validity through triangulation: Qualitative fieldwork generates rich understanding and identifies unexpected patterns. Surveys and quantitative analysis test breadth and generalizability. The two approaches inform each other in strengthening overall research validity. Source: Miklian's methodological practice

Qualitative and Ethnographic Fieldwork

Qualitative ethnographic fieldwork is the foundation of Miklian's research practice. Extended periods of immersion in conflict-affected communities provide deep insight into how local actors—businesses, community leaders, and ordinary people—experience and navigate conflict, economic crisis, and social transformation.

Miklian's fieldwork spans multiple continents and contexts: Myanmar, Colombia, Lebanon, India, Bangladesh, and Indonesia. Rather than treating conflict as an abstract phenomenon, his ethnographic approach privileges local perspectives and lived experience. This grounding allows for nuanced understanding of how conflict operates at the granular level of daily life and community resilience.

His mixed-methods approach integrates interviews, case studies, survey data, and policy analysis. This triangulation strengthens validity and allows findings from one method to inform and deepen insights from another. The result is research that captures both breadth (through surveys and data analysis) and depth (through extended interviews and observation).

Geographic Focus

Systems Analysis in Peacebuilding

Systems analysis offers a framework for understanding peace and conflict as complex adaptive systems. Linear causal models dominate peacebuilding research, yet peace emerges from interactions among numerous actors and feedback loops. Systems thinking captures this complexity and points toward more robust research and intervention design.

In collaboration with Jörg Cechvala, Miklian published a conceptual framework arguing that peacebuilding research has relied too heavily on isolated causal relationships. Peace is neither achieved nor lost through single interventions—it emerges through dynamic interaction of social, economic, political, and technological systems.

Systems Analysis and Peacebuilding: A Conceptual Stock-Taking and Forward Research Agenda
Miklian, J., & Cechvala, J. (2025). Peacebuilding, Special Issue.
Read the systems analysis and peacebuilding article

This framework opens new research questions: How do feedback loops between conflict and economic activity shape peacebuilding outcomes? What are the system-level conditions that enable or constrain the effectiveness of specific interventions? How does technological change alter system dynamics?

AI and Synthetic Data in Social Science

The ability of large language models to generate synthetic survey data raises fundamental questions about research validity and the future of social science methodology. Can AI replicate human responses? What are the risks and opportunities of AI-generated datasets?

Miklian's recent work directly tests whether leading LLMs—GPT-4, Claude, Gemini, Llama, and Mistral—can replicate human survey responses on peace, conflict, and social cohesion. This research contributes to emerging debates about the validity of synthetic data in computational social science.

Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for Ability to Replicate Human Survey with Synthetic Data
Miklian, J. (2025). Preprint.
View the LLM synthetic data preprint

The findings have important implications: synthetic data may replicate human distributions on some variables but not others. LLM-generated responses can introduce systematic biases. Yet in some contexts, synthetic data could accelerate research, improve research ethics, or fill gaps where human data collection is infeasible. The question is not whether to use synthetic data, but when and how to do so responsibly.

Survey Methodology in Fragile States

Conducting rigorous surveys in conflict-affected regions requires careful methodological attention. Issues of access, security, trust, language, sampling frame quality, and respondent safety all complicate standard survey practice and demand context-sensitive solutions.

Miklian has led survey research in multiple conflict-affected countries, working closely with local partners to navigate these challenges. His approach prioritizes ethical research practice: informed consent, data security, transparency about research limitations, and direct benefit to communities.

Key Survey Projects

Myanmar Business Perceptions and Economic Activity During Armed Conflict
Miklian, J., & Barkemeyer, R. (2022). Journal of Asia Business Studies, 16(4).
Read the Myanmar business survey article
Citizen Perceptions of Peace and Governance in Colombia
Miklian, J., & Hoelscher, K. (2025). Strategic Business Review.
Read the citizen perceptions of peace article

These projects reveal how survey research can illuminate citizen experience and perception during and after conflict. They also demonstrate the practical and ethical challenges that make survey work in fragile states different from standard social science practice.

Literature Review and Conceptual Stock-Taking

Conceptual reviews synthesize scattered literatures and clarify theoretical terrain. They create intellectual order from fragmentation, identify gaps and contradictions, and chart research agendas for emerging questions.

Miklian has authored and co-authored several literature reviews that map conceptual territory and advance theoretical understanding:

SMEs and Exogenous Shocks: A Conceptual Review
Miklian, J., & Hoelscher, K. (2021). International Small Business Journal, 39(2).
Read the SME exogenous shocks review
Business and Peace: A 20-Year Literature Review
Miklian, J., Fort, T., & Katsos, J. (2024-2025). Business Horizons.
Comprehensive review of scholarship linking business activity to conflict and peace outcomes.
Research in the Time of COVID-19: Adapting Qualitative Methods
Miklian, J., & Jeppesen, S. (2020). Forum for Development Studies, 47(2).
Read the COVID-19 research methods article

These reviews serve multiple purposes: they clarify how a field has evolved, identify lacunae in existing scholarship, and establish conceptual frameworks that guide future research. Conceptual reviews are especially valuable in applied fields like peacebuilding where research needs to inform practice.

Participatory and Design Research

Participatory and design research methods put communities and stakeholders at the center of knowledge production. Rather than extracting data from communities, these approaches view research as a collaborative process that can generate insights and build capacity.

Miklian's participatory work explores how technology and governance can be designed with rather than for communities. This approach is especially relevant for peacebuilding: communities most affected by conflict should have voice in designing the technologies and institutions meant to support their recovery.

In the Relational Sandbox: Deep Democracy and Technology
Miklian, J. (2025). Nordes 2025 workshop.
View the deep democracy and technology workshop

This work brings design and technology literatures into conversation with peacebuilding scholarship. The central question is deceptively simple: How can we design technologies and governance systems that reflect the values and needs of the people most affected by conflict and fragility?

Related Research Areas

  • Business and Peace — How economic actors navigate conflict and contribute to peace
  • Polycrisis — Multiple crises, cascading impacts, and systems resilience
  • Fragile States — Governance, resilience, and development in contexts of state fragility
  • AI Governance — Technology, ethics, and governance of artificial intelligence systems
  • SDGs & Climate — Sustainable development and climate action in conflict-affected regions
  • The Vortex — Exploring complex global dynamics and emergent risks

Frequently Asked Questions

What is Jason Miklian's primary research method?
Qualitative ethnographic fieldwork is the foundation of Miklian's research. This approach involves extended immersion in conflict-affected communities, complemented by interviews, case studies, surveys, and policy analysis. This mixed-methods approach allows for both depth of understanding and breadth of evidence.
How does systems analysis apply to peacebuilding?
Systems analysis recognizes that peace emerges from complex interactions among multiple actors and institutions, not from isolated interventions. Rather than focusing on single causal relationships, systems thinking captures feedback loops and dynamic processes that characterize peace and conflict. This approach opens new research questions about how interventions interact within broader systems.
Can large language models replace human survey respondents?
Miklian's research tests whether LLMs can replicate human survey responses. The answer is nuanced: some models can replicate distributions on certain variables, but systematic biases often emerge. LLMs cannot replace human respondents, but synthetic data may have legitimate uses in specific contexts—provided researchers understand the limitations and are transparent about methodology.
What are the main challenges of conducting research in conflict zones?
Research in conflict-affected regions requires attention to security, access, trust, informed consent, and ethical responsibilities to communities. Sampling frames may be incomplete. Respondents may fear repercussions. Language barriers can create misunderstanding. These challenges require context-sensitive methodology and close collaboration with local partners.
What is the role of synthetic data in social science?
Synthetic data generated by AI offers potential benefits: accelerating research, improving research ethics, filling gaps where human data collection is difficult. However, synthetic data can introduce systematic biases and may not capture the complexity of human experience. The question is not whether to use synthetic data, but when and how to use it responsibly.
How does Miklian combine qualitative and quantitative methods?
Miklian uses mixed methods to triangulate findings and strengthen validity. Qualitative fieldwork generates rich understanding and identifies unexpected patterns. Surveys and quantitative analysis test the breadth and generalizability of qualitative insights. The two approaches inform each other: qualitative research shapes survey design, while quantitative findings guide deeper qualitative investigation.
What is a conceptual literature review and why is it important?
A conceptual review synthesizes scattered literatures and clarifies theoretical terrain. Rather than summarizing all available research, it identifies gaps, contradictions, and patterns across bodies of knowledge. Conceptual reviews create intellectual order and chart research agendas. They are especially valuable in applied fields where research must inform practice.
What makes survey methodology different in fragile and conflict-affected states?
Surveys in fragile contexts face distinctive challenges: insecurity limits respondent access; incomplete sampling frames reduce representativeness; respondents may lack trust or fear repercussions; language barriers complicate communication. Effective survey research in these contexts requires close partnership with local organizations, transparency about limitations, and ethical prioritization of respondent safety and well-being.