12. Engaged, Action and Design Science Research

Introduction and Context

Business research is not always conducted from a distance, with researchers observing organisations as stable objects. Many important organisational problems are dynamic, contested and practical: a hospital must redesign patient flow, a public agency must improve service access, or a technology firm must develop a trustworthy decision-support system. In such settings, research may need to generate knowledge while also changing the situation being studied. Engaged research, action research, participatory inquiry and design science provide approaches for doing so.

These approaches share an interest in relevance, collaboration and use, but they are not interchangeable. Action research generally links systematic inquiry with planned intervention and learning. Participatory inquiry gives affected people a substantive role in defining questions, interpreting evidence and shaping action. Design science research develops and evaluates artefacts—such as methods, models, algorithms, processes or digital systems—intended to solve organisational problems and contribute design knowledge. Engaged research is the broader orientation in which academic and practitioner knowledge are deliberately connected throughout the research process.

For doctoral researchers, the central challenge is to avoid reducing these approaches to consultancy or implementation projects. A doctoral study must demonstrate a credible contribution to knowledge, a transparent research process, ethical integrity and a defensible relationship between evidence, intervention and claims. Practical usefulness is essential, but usefulness alone is not sufficient evidence of rigour.

Learning Objectives

By the end of this chapter, readers should be able to:

1. Distinguish engaged research, action research, participatory inquiry and design science research.

2. Explain the philosophical assumptions and knowledge claims associated with these approaches.

3. Design collaborative inquiry cycles and evaluate organisational artefacts or interventions.

4. Manage researcher–practitioner relationships, power, access and expectations.

5. Assess rigour, relevance, utility, ethics and transferability in intervention-oriented research.

6. Translate research findings into organisational learning and sustainable transformation.

From Research on Organisations to Research with Organisations

Traditional research often positions the researcher as an observer who collects data from organisational participants. Engaged research instead treats practitioners and other stakeholders as knowledgeable actors whose experience is relevant to problem formulation and interpretation. The researcher does not abandon analytical independence, but independence is reinterpreted as critical reflexivity rather than social distance.

Engagement can occur at several levels. A practitioner may simply provide access to data; may help refine a research question; may participate in data analysis; or may become a co-researcher with responsibility for inquiry and action. These arrangements should be specified rather than assumed. Participation is meaningful only when stakeholders possess some influence over decisions, not merely when they attend meetings or answer questions.

Engaged research is especially appropriate for “wicked” problems, where objectives are disputed, causes are interdependent and solutions must be adapted to context. It is less suitable when the research question requires controlled isolation of variables, when participation would expose vulnerable people to unacceptable risk, or when the organisation cannot provide sufficient time and authority for iterative inquiry.

Action Research: Inquiry Through Planned Change

Action research is a systematic, collaborative and reflexive process in which researchers and participants investigate a problem, implement action, examine consequences and use learning to inform further action. Its distinctive feature is the connection between knowledge production and change. The object of study is not merely the organisation’s existing condition; it is also the process through which that condition may be transformed.

A commonly used cycle contains four related activities:

• diagnosing or constructing an understanding of the problem;
• planning an intervention;
• taking action in the organisational setting; and
• evaluating outcomes and learning before the next cycle.

The cycle should not be treated as a mechanical sequence. Diagnosis may change during action, and evaluation may reveal that the original problem was misframed. Several cycles may be required because organisational learning is gradual and interventions generate unintended effects.

Action research has several variants. Participatory action research gives greater decision-making authority to participants, often with an explicit concern for voice, inclusion and social change. Collaborative action research involves shared inquiry between academic and practitioner researchers, while action learning focuses more directly on collective managerial learning through work-based problem solving. These traditions overlap, but the researcher should state which version is being used and why.

The quality of action research depends on more than whether an intervention produced a positive outcome. A credible study documents the initial condition, the reasoning behind the intervention, the evidence collected, alternative explanations, participant perspectives and the learning generated through successive cycles. It should also distinguish intended outcomes from unintended consequences.

Participatory Inquiry and the Politics of Knowledge

Participatory inquiry challenges the assumption that professional or academic knowledge is inherently superior to local and experiential knowledge. Employees, service users, community members and other stakeholders may possess knowledge that is inaccessible through formal reports or conventional measurement. Participatory methods can include co-design workshops, facilitated dialogue, stakeholder mapping, photovoice, collective sensemaking, participatory observation and collaborative data interpretation.

Participation raises important questions of power. Who defines the problem? Whose language is treated as legitimate? Who can refuse a proposed intervention? Who receives recognition for the resulting knowledge? A study may be described as participatory while senior managers retain all decision rights and less powerful groups bear the risks. Doctoral researchers should therefore analyse participation as an empirical phenomenon, not merely present it as a methodological virtue.

A useful participation agreement specifies roles, decision rights, confidentiality, ownership of outputs, publication arrangements and procedures for resolving disagreement. Participants should know which aspects of the research are negotiable and which are constrained by academic, legal or ethical requirements. Transparency prevents collaboration from becoming symbolic consultation.

Design Science Research: Building and Evaluating Artefacts

Design science research addresses organisational problems by creating and evaluating artefacts that embody knowledge about how to achieve desired outcomes. An artefact may be a construct, model, method, process, framework, algorithm, prototype or information system. The artefact is not simply a product; it is a designed response to a problem, supported by reasoning about its requirements, operation and effects.

Design science commonly involves the following logic:

1. Identify and motivate a relevant problem.

2. Define objectives for a possible solution.

3. Design and develop an artefact.

4. Demonstrate its use in a relevant context.

5. Evaluate its utility, quality and possible side effects.

6. Communicate the problem, artefact, evidence and design knowledge.

The stages may be iterative. Evaluation can reveal that requirements were incomplete, leading to redesign. Design decisions should be recorded because they form part of the research contribution. A final artefact without an explicit design rationale is difficult to learn from or transfer.

Evaluation may examine functionality, usability, performance, feasibility, acceptance, robustness, fairness, cost or organisational consequences. Methods can include experiments, simulations, benchmark comparisons, field trials, expert assessment, usability testing, interviews and longitudinal observation. The choice should follow the claim being made. If the claim is that a scheduling algorithm improves efficiency under defined conditions, performance evidence is necessary. If the claim is that managers can understand and use the system, usability and adoption evidence are also required.

Design science distinguishes between the artefact and the knowledge contribution. The artefact may be locally useful, while the scholarly contribution may be a design principle, mechanism, framework or explanation of the conditions under which the artefact works. A doctoral thesis should make this distinction explicit.

Theoretical Foundations and Research Quality

These approaches are compatible with pragmatic views of inquiry, in which the value of knowledge is assessed partly through its consequences and practical adequacy. They may also draw on critical, interpretivist or realist assumptions. Interpretivist work may focus on how participants construct meaning during change. Critical approaches examine domination, exclusion and the distribution of benefits. Realist approaches may investigate mechanisms that produce outcomes under particular contextual conditions. No single philosophical label automatically guarantees quality; coherence between assumptions, questions, methods and claims is more important.

Rigour in engaged research has several dimensions. Methodological rigour concerns the quality and transparency of data collection and analysis. Process rigour concerns whether the intervention and learning cycles were systematically documented. Relational rigour concerns the honesty, reciprocity and reflexivity of relationships. Outcome rigour concerns whether claims about change are supported by appropriate evidence. Democratic or dialogical rigour concerns whether relevant perspectives were genuinely heard. Transferability concerns whether readers can judge the applicability of findings in other contexts.

The researcher should maintain an audit trail containing versions of the problem definition, meeting records, intervention decisions, data sources, analytic memos, dissenting interpretations and changes in the research design. Triangulation can involve multiple data sources, methods, observers or theoretical perspectives. Member reflection is often more valuable than simple “member checking”: participants should be invited to challenge interpretations and discuss their implications, while the researcher retains responsibility for scholarly analysis.

Managing Researcher–Practitioner Relationships

Access is not the same as partnership. Organisations may invite research because they expect a rapid solution, favourable publicity or free consultancy. Researchers may expect openness, data access and permission to publish. These expectations can conflict. An early research agreement should address objectives, time commitments, access, confidentiality, data ownership, publication, feedback, withdrawal and the treatment of negative findings.

The researcher occupies multiple roles: investigator, facilitator, analyst, critical friend and sometimes intervention designer. Role ambiguity can produce dependency or compromised judgement. Reflexive practice requires asking how the researcher’s expertise, institutional status, funding and personal interests influence the inquiry. A reflexive journal should record not only methodological decisions but also tensions, emotional responses, conflicts and moments when participants resisted the researcher’s interpretation.

Power must be managed actively. Senior sponsors may control access, while frontline employees may experience the intervention most intensely. Confidential interviews, separate spaces for dissent, representative recruitment and careful reporting can reduce risks. Researchers should avoid promising that participation will automatically lead to organisational change; they can facilitate learning but cannot control executive decisions, budgets or political conditions.

A Practical Architecture for an Intervention-Oriented Study

A strong doctoral design usually begins with a negotiated problem statement that identifies the organisational concern, affected groups, existing evidence and boundaries of the study. The researcher then develops a theory of change: what intervention is expected to influence, through which mechanisms, under what conditions and with what possible unintended effects.

Baseline inquiry should establish the current situation using suitable qualitative, quantitative or mixed evidence. The intervention is then designed with participants, implemented at a defined scale and monitored through process and outcome indicators. Evaluation should include both evidence of results and evidence about implementation. A disappointing result is not necessarily a failed study; it may reveal that the mechanism was absent, the context was unsuitable or the intervention was not implemented as intended.

A final phase translates learning into organisational routines. This may involve revised procedures, training, governance arrangements, artefact maintenance, ownership transfer and follow-up evaluation. Sustainability should be assessed rather than assumed. An intervention that works only while the researcher is present may indicate that learning has not become embedded.

Applied Case: Designing a Fairer Workforce Scheduling System

The following is an illustrative case.

Background. A regional service organisation used spreadsheets to allocate shifts across several sites. Managers reported frequent last-minute changes, while employees perceived that desirable shifts were distributed inconsistently. Absenteeism and dissatisfaction were increasing, but the organisation lacked reliable evidence about the causes.

Problem and analysis. A doctoral researcher formed a steering group including schedulers, employees from different sites, union representatives and senior managers. Initial interviews, document analysis and scheduling data showed that the problem was not simply inefficient software. Rules differed between sites, informal preferences were invisible, and employees had little opportunity to challenge decisions. The group therefore defined success as a combination of operational efficiency, perceived fairness, transparency and compliance with employment requirements.

Approach. The study used action research and design science. In the first cycle, participants mapped the current process and identified design requirements. The researcher and a technical team developed a prototype that represented availability, qualifications, workload and transparent priority rules. A participatory workshop exposed a risk: an apparently neutral rule could disadvantage employees with caring responsibilities. The rule was redesigned to permit justified preferences without exposing sensitive personal information.

The prototype was piloted at one site. Quantitative indicators included time required to produce schedules, number of emergency changes and distribution of unpopular shifts. Interviews and anonymous feedback examined usability, trust and perceived fairness. The researcher also observed scheduling meetings and maintained an audit trail of design decisions.

Outcome. The prototype reduced administrative effort during the pilot, but the most significant learning concerned governance. Employees trusted the system only when they could understand the rules and appeal an outcome. The organisation therefore adopted a review panel, periodic fairness audits and a process for updating rules. Results were not generalised as universal proof that the artefact would work elsewhere. Instead, the thesis proposed design principles concerning transparency, contestability and stakeholder involvement in algorithm-supported scheduling.

Learning points. The case illustrates that design science requires more than developing software, and action research requires more than implementing a management decision. The intervention generated practical improvement, while the cycles of inquiry generated transferable knowledge about mechanisms and conditions. It also demonstrates why ethical assessment must continue after initial approval: new risks emerged through use of the prototype.

Ethics, Governance and Digital Responsibility

Engaged research can create ethical issues beyond those found in conventional interviews. Participation may affect employment, reputation, promotion or access to services. Participants may feel unable to refuse when the researcher is connected to management. Consent should therefore be informed, voluntary and revisable. Confidentiality arrangements must account for the possibility that small groups or distinctive comments can be identified.

Interventions require attention to distributive effects. Who benefits, who bears additional workload and who is excluded by the artefact? Digital systems introduce further concerns involving data minimisation, cybersecurity, explainability, algorithmic bias, accessibility and human oversight. An AI-supported artefact should not be presented as objective merely because it is computational. Its training data, assumptions, performance across groups and routes of appeal require scrutiny.

Governance should specify who owns an artefact, who is responsible for maintenance, how updates are approved and what happens when evidence reveals harm. Researchers must report adverse or null findings honestly. Organisational pressure to suppress inconvenient results is a threat to both scholarly integrity and responsible practice.

Common Difficulties and Limits

Several mistakes recur. First, researchers may begin with a preferred solution rather than a carefully investigated problem. Second, they may confuse stakeholder enthusiasm with evidence of effectiveness. Third, they may collect rich qualitative material without analysing how it supports a theoretical or design claim. Fourth, they may treat cycles as calendar stages rather than opportunities for disciplined learning. Fifth, they may overclaim generalisability from one organisation.

Other limitations are structural. Organisational politics can prevent full participation. Interventions may be interrupted by leadership changes, funding constraints or crises. The researcher’s presence may influence behaviour, and comparison groups may be unavailable. Multiple simultaneous changes make causal attribution difficult. These limitations should be disclosed and addressed through process data, rival explanations, repeated measurement and careful claims about context.

Emerging Directions and Best Practice

Contemporary engaged research increasingly combines participatory methods with digital trace data, rapid prototyping and responsible AI evaluation. Hybrid and distributed work make virtual participation more important, but digital access and confidentiality cannot be assumed. Living artefacts—systems or frameworks that are continually updated—require research designs capable of evaluating change over time.

Best practice is to:

• negotiate purpose, roles and publication expectations before data collection;
• treat practitioners as contributors to knowledge without abandoning critical analysis;
• document problem framing, design decisions, implementation and revision;
• evaluate both outcomes and unintended consequences;
• make power, exclusion and conflicting interpretations visible;
• align evidence with the specific claim being made;
• distinguish local utility from transferable design knowledge; and
• plan for ownership, maintenance and organisational learning after the study.

Chapter Summary

Engaged, action and design science research connect scholarly inquiry with organisational change. Action research uses iterative cycles of diagnosis, intervention, evaluation and learning. Participatory inquiry foregrounds stakeholder knowledge and examines the power relations that shape participation. Design science develops and evaluates artefacts while generating transferable design knowledge. All three approaches require philosophical coherence, transparent documentation, reflexivity and ethical governance.

Practical success is not by itself proof of research quality. Doctoral researchers must show how problems were framed, how interventions were designed, what evidence supports claims, whose interests were affected and under what conditions findings may transfer. Strong studies create a productive relationship between utility and rigour, enabling organisations not merely to receive a solution but to develop the capacity for continuing learning and transformation.

Key Terms

Engaged research: Research conducted through sustained, purposeful interaction between academic researchers and practitioners or stakeholders.

Action research: Systematic inquiry that links investigation with planned action, evaluation and learning.

Participatory inquiry: Research in which affected stakeholders influence problem definition, knowledge production and action.

Participatory action research: Action research with an explicit emphasis on shared authority, inclusion and social change.

Action learning: Work-based collective learning that uses real organisational problems as vehicles for development and improvement.

Design science research: Research that creates and evaluates artefacts to solve relevant problems and generate design knowledge.

Artefact: A designed construct, model, method, process, algorithm, prototype or system intended for a purpose.

Design principle: A transferable proposition linking design features to desired outcomes under specified conditions.

Intervention: A deliberate action intended to influence an organisational situation.

Research cycle: A connected sequence of diagnosis, planning, action, evaluation and revised learning.

Reflexivity: Critical examination of how the researcher’s position, assumptions and relationships influence inquiry.

Relational rigour: Quality arising from honest, reciprocal and critically managed researcher–participant relationships.

Audit trail: A systematic record of decisions, evidence, interpretations and changes made during research.

Theory of change: An explanation of how an intervention is expected to produce outcomes through mechanisms and conditions.

Utility: The practical usefulness or value of research or an artefact to intended users.

Transferability: The extent to which readers can judge whether findings apply in another context.

Co-design: Collaborative development of an intervention or artefact by researchers and relevant stakeholders.

Dialogical rigour: Quality achieved through genuine exchange, challenge and consideration of different perspectives.

Organisational learning: Changes in shared knowledge, routines, capabilities or assumptions that improve future action.

Review Questions

Short Answer Questions

1. What distinguishes action research from research that merely studies organisational change?

2. Why is participation a question of power as well as a research technique?

3. What is an artefact in design science research?

4. Define an audit trail and explain its value.

5. Why should practical utility not be treated as sufficient evidence of doctoral rigour?

Long Answer Questions

1. Compare the purposes, processes and knowledge contributions of action research and design science research.

2. Explain how a doctoral researcher can manage conflicting expectations between practitioners and academic supervisors.

3. Discuss the role of reflexivity in maintaining rigour in engaged research.

4. Describe how an intervention-oriented study can evaluate both intended outcomes and unintended consequences.

5. Examine the ethical and governance issues associated with AI-supported organisational artefacts.

Analytical / Application Questions

1. An organisation asks a researcher to implement a preferred digital solution before investigating the problem. Using the chapter’s frameworks, how should the researcher respond?

2. A participatory project receives strong support from senior managers but little input from frontline employees. Analyse the threats to validity, ethics and usefulness, and propose corrective actions.

3. A prototype improves efficiency but is viewed as unfair by users. Design an evaluation and learning process that could determine whether the artefact should be redesigned, governed differently or withdrawn.

22. Multiple Choice Questions with Answers

Question 1

Which feature most clearly distinguishes action research from conventional organisational research?

A. It relies exclusively on quantitative data.

B. It links systematic inquiry to planned action and learning.

C. It excludes practitioners from interpretation.

D. It requires a laboratory experiment.

Correct Answer: B. It links systematic inquiry to planned action and learning.

Question 2

A design science researcher develops a scheduling algorithm and documents the conditions under which it improves fairness. What is the documented conditional knowledge best described as?

A. A design principle

B. A sampling frame

C. A control variable

D. A response rate

Correct Answer: A. A design principle

Question 3

Which situation best demonstrates meaningful participation?

A. Employees receive a finished report by email.

B. Managers select participants only to confirm an existing decision.

C. Affected stakeholders help define the problem and can challenge interpretations.

D. Participants provide data but have no information about its use.

Correct Answer: C. Affected stakeholders help define the problem and can challenge interpretations.

Question 4

Why is an audit trail particularly important in action research?

A. It eliminates the need for ethical review.

B. It documents changing decisions, evidence and learning across cycles.

C. It guarantees that the intervention will succeed.

D. It replaces the need for participant perspectives.

Correct Answer: B. It documents changing decisions, evidence and learning across cycles.

Question 5

A prototype works in one organisation but fails after transfer to another. Which conclusion is most defensible?

A. Design science cannot produce useful knowledge.

B. The first organisation’s results were necessarily fabricated.

C. The researcher should examine contextual conditions and avoid universal claims.

D. The artefact should be adopted everywhere without modification.

Correct Answer: C. The researcher should examine contextual conditions and avoid universal claims.

Question 6

What is the main purpose of a theory of change in an intervention-oriented study?

A. To specify how an intervention is expected to produce outcomes.

B. To guarantee participant agreement.

C. To replace outcome evaluation.

D. To conceal unintended consequences.

Correct Answer: A. To specify how an intervention is expected to produce outcomes.

Question 7

An AI-supported staffing system improves efficiency but disadvantages employees with caring responsibilities. What should the researcher do first?

A. Ignore the result because efficiency is the primary objective.

B. Remove all human oversight.

C. Investigate the distributional effect and redesign or govern the system accordingly.

D. Publish only the positive performance results.

Correct Answer: C. Investigate the distributional effect and redesign or govern the system accordingly.

Question 8

Which form of rigour concerns whether participants were genuinely heard and able to challenge interpretations?

A. Dialogical or democratic rigour

B. Statistical power

C. Mechanical reliability

D. Market validity

Correct Answer: A. Dialogical or democratic rigour

Question 9

Why should an action researcher distinguish implementation evidence from outcome evidence?

A. An intervention can fail because it was not implemented as intended, not because its underlying mechanism is ineffective.

B. Implementation evidence is always more important than outcomes.

C. Outcome evidence is unnecessary when participants are satisfied.

D. The distinction prevents any organisational adaptation.

Correct Answer: A. An intervention can fail because it was not implemented as intended, not because its underlying mechanism is ineffective.

Question 10

Which practice best supports organisational learning after a researcher leaves?

A. Keeping design decisions confidential from users.

B. Transferring ownership without maintenance responsibilities.

C. Embedding revised routines, governance, capability development and follow-up evaluation.

D. Ending evaluation once the prototype is launched.

Correct Answer: C. Embedding revised routines, governance, capability development and follow-up evaluation.