Article review of “Turning intent into impact”, focusing on the topic of research approaches: for MBA students

Article review of “Turning intent into impact”, focusing on the topic of research approaches: for MBA students

 

How to present this article in Harvard reference format?

Ryu, S.W., Kwon, B., Zhou, W.C. & Cortes, A.F., 2026. Turning intent into impact: HR as a change agent in corporate sustainability. Human Resource Management Review, 36, p.101162. https://doi.org/10.1016/j.hrmr.2026.101162

 

 

 

What are the key research issues the article wants to address?

The article "Turning intent into impact: HR as a change agent in corporate sustainability" addresses several key research issues:

1.    Symbolic vs. substantive corporate sustainability (CS): The article investigates when and how corporate sustainability efforts move beyond ambitious rhetoric and symbolic actions to generate substantive changes in organizational practices.

2.    Role of HR as a change agent: It focuses on the role of the human resource (HR) function in driving corporate sustainability change, conceptualizing HR as an institutional change agent who enacts disruption, creation, and maintenance of institutional elements throughout the sustainability change process.

3.    Process perspective on corporate sustainability: The research adopts a multiphase process model for corporate sustainability, involving sensitizing–unfreezing, moving, and refreezing phases, and explores how HR's contributions vary across these phases.

4.    HR engagement continuum and roles: The paper develops a proactive–defensive continuum of HR engagement and identifies phase-specific HR roles—broker versus bystander in sensitizing–unfreezing, catalyst versus executor in moving, and framer versus steward in refreezing—to explain how HR's stance impacts the depth and permanence of corporate sustainability outcomes.

5.    Institutional theory lens: Integrating a framework of institutional work, the article seeks to understand how HR interactions with institutional logics and paradoxical tensions shape the trajectory and institutionalization of sustainability practices.

6.    Practical guidance and future research directions: The article addresses the practical challenge of how organizations can align HR activities to the appropriate phase of sustainability change to promote substantive rather than symbolic outcomes and outlines areas for future empirical research to validate and extend the theoretical framework.

In summary, the article aims to clarify the microfoundations and dynamics through which HR can transform corporate sustainability intentions into impactful and enduring organizational changes.

 

What research methods have been used in this study?

The article "Turning intent into impact: HR as a change agent in corporate sustainability" primarily develops a conceptual and theoretical framework rather than employing empirical research methods. As indicated, no data was used for the research described in the article, suggesting it is a theoretical paper focusing on integrating existing literature and theories.

Specifically, the authors adopt:

·        A process view of corporate sustainability, drawing on existing organizational change models (sensitizing–unfreezing, moving, refreezing).

·        Institutional work theory to theorize HR's role in enacting institutional disruption, creation, and maintenance during corporate sustainability efforts.

·        Paradox theory to understand tensions and competing institutional logics HR must navigate.

·        Literature synthesis and conceptual development to propose a proactive–defensive continuum of HR engagement and phase-specific HR roles.

The authors indicate that future research should empirically examine their propositions using multi-wave, multi-level designs combining surveys, archival data, qualitative process tracing, and comparative case studies, but such empirical work is beyond the scope of the current article.

In summary, the study uses a conceptual and theoretical development research method rather than empirical data collection or analysis.

 

What research approaches (i.e. qualitative method, quantitative method and mixed research method) have been used in this study?

The study employs a qualitative conceptual research approach rather than quantitative or mixed methods. It develops a theoretical framework by integrating existing theories and literature on corporate sustainability, human resource management, institutional work, and paradox theory. The authors do not collect or analyze empirical data; instead, their method involves:

·        Synthesizing prior research and theoretical perspectives.

·        Conceptualizing corporate sustainability as a multiphase organizational change process.

·        Theorizing HR's roles and institutional work across these phases.

No quantitative data or mixed-method empirical research was conducted in this study. The authors suggest future empirical research could apply qualitative, quantitative, or mixed methods to test and expand their conceptual framework.

Therefore, the primary research approach used is qualitative conceptual/theoretical analysis.

 

What (reasoning) research approaches have been used in this study (i.e. inductive, deduct and abductive approaches)?

The study primarily employs a deductive research approach with elements of abductive reasoning:

·        Deductive approach: The authors start from established theories and existing literature on organizational change, corporate sustainability (CS), institutional work, and HRM. They use these theoretical foundations (e.g., Lewin’s change model, institutional entrepreneurship, paradox theory) to develop a conceptual framework that explains HR’s roles and engagement continuum across the phases of the CS process. This top-down reasoning moves from general theoretical propositions to specific conceptualizations regarding HR engagement in CS.

·        Abductive elements: The study also creatively integrates multiple perspectives—such as linking institutional work typologies with HR roles and paradox theory—to explain symbolic versus substantive CS outcomes. This synthesis involves iterative theorizing and extending existing frameworks, which reflects abductive reasoning where surprising or complex phenomena lead to the formulation of new theoretical insights.

The study does not report empirical data collection or induction from observed data, so inductive reasoning is not the primary approach here. Instead, the focus is on theory development through deductive theorizing combined with abductive integration of ideas.

In sum, the research reasoning is predominantly deductive with abductive theorizing to develop and extend conceptual frameworks regarding HR as a change agent in corporate sustainability

 

Describe 3 main claims of the article in terms of Toulmin's model of argument.

Based on the provided content from the article and applying Toulmin's model of argument (which consists of Claim, Grounds, Warrant, and often Backing, Qualifier, and Rebuttal), here are three main claims from the article with their reasoning structure:

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Claim 1:

HR plays multiphase institutional roles (disruption, creation, maintenance) across different phases of corporate sustainability efforts, which shapes whether sustainability initiatives are symbolic or substantive.

• Grounds: Drawing on Lawrence and Suddaby’s (2006) typology of institutional work, the article identifies specific HR activities in the sensitizing–unfreezing (disruption & creation), moving (creation), and refreezing (maintenance) phases. It also shows HR’s influence on whether corporate sustainability (CS) efforts decouple rhetoric from practice or embed CS in core organizational processes.
• Warrant: Institutional work theory and change management models (e.g., Lewin’s phases) justify that actors like HR, through their institutional roles and engagement styles, fundamentally shape organizational change outcomes and their legitimacy (symbolic vs. substantive).
• Backing: Previous work on HRM institutional entrepreneurship for sustainability (Ren et al., 2023; Ren & Jackson, 2020) and management change theory support this claim.

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Claim 2:

A proactive HR stance (acting as broker, catalyst, framer) leads to substantive corporate sustainability outcomes by managing tensions (“both/and” logic), whereas a defensive stance (bystander, executor, steward) risks symbolic decoupling through “either/or” responses.

• Grounds: The authors develop a proactive–defensive HR engagement continuum based on paradox theory and CS tension literature, illustrating how HR’s attitude towards competing demands affects the depth of CS integration.
• Warrant: Paradox theory and institutional theory suggest that recognizing and managing tensions constructively enables deeper and more sustained institutional change, whereas avoidance or splitting responses maintain superficial compliance.
• Backing: References to Smith & Lewis (2011), Carmine & De Marchi (2023), Ehnert et al. (2014), and others substantiate the importance of managing paradoxes for genuine sustainability outcomes.

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Claim 3:

Effective corporate sustainability requires context-specific HR interventions tailored to each phase of change and supported by appropriate governance structures.

• Grounds: The framework recommends distinct HR activities for each phase (e.g., stakeholder engagement in unfreezing, integrating CS into HR systems in moving, embedding sustainability in culture during refreezing), plus governance enablers like HR representation in CS steering and sustainability metrics in board remits.
• Warrant: Organizational change literature and best practices in sustainability stress the importance of phase-appropriate interventions and governance for successful institutionalization; generic or unfocused efforts tend to fail or remain symbolic.
• Backing: Practitioner guides from CIPD and SHRM Foundation corroborate the need for diagnosis, sequencing, and governance aligned with organizational maturity and phase of CS efforts.

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These claims outline the article’s core arguments about HR’s conditional and critical role in advancing corporate sustainability beyond symbolic initiatives, grounded in institutional and paradox theory and structured in a change management process.

Article review of “HRM systems & employee well-being”, focusing on the topic of research approaches: for MBA students

Article review of “HRM systems & employee well-being”, focusing on the topic of research approaches: for MBA students

 

How to present this article in Harvard reference format?

Messersmith, J.G., 2026. HRM systems & employee well-being: Toward a eudaimonic perspective. Human Resource Management Review, 36, p.101149. doi:10.1016/j.hrmr.2026.101149.

 

 

What are the key research issues the article wants to address?

The article by Messersmith (2026) aims to address several key research issues:

1.    Gap Between Research and Practice on Well-Being: Despite growing interest in how HRM systems affect employee outcomes, many employees still face mental health challenges, poor engagement, and a crisis of purpose. The article highlights a gap between existing research models and the practical challenges employees face regarding well-being.

2.    Limitations of Social Exchange Models: Most existing models linking HR systems to well-being rely heavily on social exchange mechanisms, which may be insufficient for addressing deeper, eudaimonic forms of well-being. These models focus on extrinsic motivation and organizational-centric well-being measures like job satisfaction and affective commitment, which are limited in scope.

3.    Need to Focus on Eudaimonic Well-Being: The article identifies a need to shift from hedonic or affect-driven well-being (e.g., satisfaction, positive affect) toward eudaimonic well-being, which emphasizes living well, meaningfulness, and purposeful work. Eudaimonic well-being aligns more with employees' psychological needs for autonomy, competence, and relatedness as per self-determination theory (SDT), yet it is underexplored in HRM research.

4.    Development of a New Conceptual Model: The article seeks to offer a novel conceptual model grounded in SDT to explain how HR systems can be designed to promote autonomous motivation and eudaimonic workplace well-being (EWWB). This includes identifying specific HR practices that foster employees’ psychological needs, thus enabling more long-term and meaningful well-being at work.

5.    Practical Implications for Managers: The article addresses how organizations and HR leaders can support employee well-being through designing meaningful work and aligning HR practices with employees’ deeper sense of purpose, moving beyond traditional engagement or satisfaction metrics.

6.    Integration of Psychological Theory into HRM Research: It attempts to integrate eudaimonic philosophy and SDT, which have largely been discussed in psychology and philosophy, into the HRM field, thereby enriching the theoretical frameworks used to study HR systems and well-being.

In sum, the article responds to the rising mental health issues and crisis of purpose among employees by critiquing traditional HRM well-being models and proposing a new SDT-based framework for fostering eudaimonic well-being through HR systems.

 

What research methods have been used in this study?

The article by Jake G. Messersmith (2026) is a conceptual/theoretical paper rather than an empirical study. It does not employ primary data collection or quantitative/qualitative research methods typical of empirical research. Instead, the paper uses:

·        Literature Review and Theoretical Synthesis: The author reviews and synthesizes existing literature in strategic HRM, positive psychology, self-determination theory (SDT), and eudaimonic well-being to identify gaps in current research and build a new theoretical framework linking HR systems with eudaimonic workplace well-being (EWWB).

·        Conceptual Model Development: Based on this theoretical integration, the paper develops a conceptual model that articulates propositions about how specific HR practices can fulfill employees’ psychological needs (autonomy, competence, relatedness) and foster autonomous motivation and eudaimonic well-being.

·        Propositions and Theoretical Arguments: The study formulates testable propositions regarding moderators and mediators in the model, such as the role of frontline manager support and identified motivation influencing EWWB.

Therefore, the research method is best characterized as a conceptual/theoretical development through critical review, synthesis, and proposition formulation rather than empirical investigation. There are no mentions of primary data collection, statistical analyses, experiments, or surveys in the paper.

 

What research approaches (i.e. qualitative method, quantitative method and mixed research method) have been used in this study?

The study by Jake G. Messersmith (2026) employs a conceptual research approach rather than empirical research methods. Specifically, it does not use qualitative, quantitative, or mixed research methods. Instead, the paper:

• Develops a theoretical/conceptual model grounded in self-determination theory (SDT) and eudaimonic well-being by synthesizing existing literature from HRM, psychology, and related fields.
• Proposes conceptual propositions about the relationships between HR systems, psychological needs fulfillment, motivation, and employee well-being.

No primary data collection, qualitative analyses (e.g., interviews, case studies), quantitative analyses (e.g., surveys, experiments, statistical modeling), or a combination of these (mixed methods) are conducted in this paper.

Thus, the research approach is conceptual/theoretical rather than empirical qualitative, quantitative, or mixed methods.

 

What (reasoning) research approaches have been used in this study (i.e. inductive, deduct and abductive approaches)?

The study by Messersmith (2026) primarily uses a deductive reasoning approach. This is evident because:

• The paper begins with established theories—particularly self-determination theory (SDT) and the concept of eudaimonic well-being—and uses these theoretical frameworks to develop a new conceptual model linking HR systems to eudaimonic workplace well-being (EWWB).
• It critiques existing research models (mainly social exchange theory-based HR models) and deduces that these are insufficient to explain deeper forms of well-being, then logically constructs a new theoretical framework and propositions based on SDT principles (autonomy, competence, relatedness).
• The paper moves from general theory (psychological theories of motivation and well-being) to specific propositions about HR practices, employee motivation, and well-being outcomes.

There is no indication of inductive reasoning (building theory from empirical data) or abductive reasoning (starting from surprising facts to generate new theoretical explanations) because the study does not involve data collection or analysis, but rather theoretical development based on existing literature.

Therefore, the reasoning approach is best described as deductive.

 

Describe 3 main claims of the article in terms of Toulmin's model of argument.

Using Toulmin’s model of argument, which includes components such as Claim, Grounds (evidence), and Warrant (reasoning connecting the grounds to the claim), three main claims of Messersmith’s (2026) article are as follows:

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Claim 1: Traditional HR systems models grounded in social exchange theory are insufficient to adequately address deeper, eudaimonic employee well-being.

• Grounds: Most current research links HR systems to employee well-being through social exchange mechanisms emphasizing reciprocal commitment, focusing on employee attitudes like job satisfaction and affective commitment rather than deeper psychological states. The literature often uses proxies that reflect hedonic well-being rather than eudaimonia.
• Warrant: If the theoretical basis of HR system research centers on externally motivated behavior and social exchange, this logic does not promote autonomous motivation, which according to self-determination theory (SDT) is necessary for deeper forms of well-being (eudaimonia) [T3,T2].

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Claim 2: A eudaimonic perspective based on self-determination theory provides a more robust conceptual model for understanding how HR systems can enhance employee well-being.

• Grounds: Self-determination theory explains that fulfilling basic psychological needs for autonomy, competence, and relatedness leads to eudaimonic well-being. Identified and integrated forms of motivation connect employees meaningfully to their work. Existing findings in psychology associate eudaimonia with critical positive outcomes like happiness, mental health, and life satisfaction.
• Warrant: If well-being depends on autonomous motivation and fulfillment of core psychological needs, then HR systems designed to support these needs should promote deeper, eudaimonic well-being rather than mere satisfaction or commitment [T2,T3].

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Claim 3: Specific HR practices, rooted in the eudaimonic framework, can be implemented to create organizational contexts that foster eudaimonic workplace well-being.

• Grounds: The paper proposes concrete HR practices such as selection for value congruence, job crafting, meaningful socialization, developmental performance management, autonomy-supportive leadership, and pay linked to mission—all aimed at fulfilling psychological needs [T4,T5].
• Warrant: If HR systems implement practices that satisfy autonomy, competence, and relatedness needs, they will facilitate autonomous motivation and thereby foster eudaimonic workplace well-being.

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These three claims form the backbone of the article’s argument: that moving beyond traditional social exchange-based HR models toward a self-determination theory-informed, eudaimonic framework will better support employee well-being, and that this can be operationalized through specific HR practices.

A note on research approaches: for MBA students

A note on research approaches: for MBA students

 

Describe the following research approaches in the context of doing MBA dissertation projects:

Category 1 (methods)

1.1. Qualitative research
1.2. Quantitative research

1.3 Mixed methods research

Category 2 (reasoning)
2.1 Inductive approach
2.2 Deductive approach
2.3 Abductive approach

 

Overall distinction

The two categories describe different aspects of an MBA dissertation:

• Category 1—methods: What type of evidence will you collect and analyse?
• Category 2—reasoning: How will you move between theory, data, concepts and explanations?

They are related but not identical. For example, a qualitative study is often inductive, but it can also be deductive or abductive; similarly, quantitative research is usually deductive, but it can involve exploratory and inductive analysis. Research methods should therefore be selected primarily according to the research questions, objectives and practical constraints.

Category 1: Research methods

1.1 Qualitative research

Qualitative research investigates meanings, experiences, perceptions, interpretations, interactions and organisational processes. It normally uses non-numerical data, such as interview transcripts, focus-group discussions, observations, organisational documents, company reports and online material. Its main purpose is to understand how and why a phenomenon occurs rather than to measure its frequency or statistical strength.

In an MBA dissertation, qualitative research is appropriate when the topic concerns:

• Managers’ experiences of implementing digital transformation.
• Employees’ perceptions of leadership or organisational culture.
• How small businesses respond to sustainability pressures.
• Why customers distrust artificial-intelligence-based services.
• How management accountants contribute to strategic decision-making.
• The process through which a housing policy affects service users.

Typical research questions include:

• “How do Hong Kong SMEs implement generative AI in management accounting?”
• “Why do employees resist a new performance-management system?”
• “How do managers interpret sustainability information in strategic decisions?”

Common qualitative methods include:

• Semi-structured interviews.
• Focus groups.
• Case studies.
• Observation.
• Document analysis.
• Thematic, content, narrative or discourse analysis.

A typical qualitative MBA project might involve interviewing 12–20 managers from several SMEs and analysing the transcripts thematically. The researcher may identify themes such as perceived usefulness, lack of skills, data concerns and top-management support.

Strengths

• Provides detailed and context-sensitive understanding.
• Allows participants to explain issues in their own words.
• Is useful for new, sensitive or poorly understood topics.
• Can reveal processes, motivations and unintended consequences.
• Permits refinement of questions during data collection.

Limitations

• Usually involves relatively small, non-probability samples.
• Findings may not be statistically generalisable.
• Data collection and analysis can be time-consuming.
• Researcher interpretation must be carefully justified.
• Access to senior managers or organisations may be difficult.

A qualitative dissertation should explain the sampling logic, interview protocol, data-saturation considerations, coding process, ethical safeguards and procedures used to establish credibility, such as triangulation, member checking or maintaining an audit trail.

1.2 Quantitative research

Quantitative research examines phenomena through numerical measurement and statistical analysis. It is commonly used to describe variables, compare groups, test hypotheses, estimate relationships and assess the possible effects of one variable on another. It is particularly suitable for questions such as how many, how much, how strongly and whether X is associated with Y.

In an MBA dissertation, quantitative research may be used to examine:

• The relationship between leadership style and employee performance.
• The effect of service quality on customer satisfaction.
• Whether digital capability improves SME performance.
• The association between management-accounting practices and business resilience.
• The impact of perceived housing-service quality on resident satisfaction.

A quantitative study generally proceeds through the following sequence:

1.    Review relevant literature and theories.

2.    Define the main concepts and variables.

3.    Develop hypotheses or testable propositions.

4.    Operationalise variables using questionnaire items or secondary indicators.

5.    Collect numerical data.

6.    Analyse the data statistically.

7.    Compare the findings with the hypotheses and prior studies.

For example, a dissertation might propose:

• H1: Perceived service quality has a positive relationship with resident satisfaction.
• H2: Trust strengthens the relationship between service quality and satisfaction.

The researcher could distribute a questionnaire using five-point Likert scales and analyse the responses using descriptive statistics, reliability analysis, correlation, regression, mediation or moderation analysis.

Common quantitative methods include:

• Structured questionnaires.
• Experiments or quasi-experiments.
• Secondary-data analysis.
• Financial-ratio analysis.
• Longitudinal analysis.
• Descriptive and inferential statistics.

Strengths

• Enables numerical comparison between respondents, organisations or periods.
• Can test relationships derived from theory.
• May produce findings that are generalisable when sampling is appropriate.
• Provides transparent and replicable analytical procedures.
• Is useful for measuring attitudes, behaviours and organisational outcomes.

Limitations

• Complex ideas may be reduced to numerical indicators.
• A questionnaire may not explain why respondents hold particular views.
• Poorly designed measures can weaken validity and reliability.
• Large samples may be difficult for MBA students to obtain.
• Statistical association does not automatically establish causation.

A strong quantitative dissertation must justify the population, sampling method, sample size, measurement scales, questionnaire design, reliability and validity procedures, statistical techniques and treatment of missing or abnormal data.

1.3 Mixed-methods research

Mixed-methods research intentionally combines quantitative and qualitative evidence within one dissertation. The purpose is not merely to use two types of data, but to integrate them so that the combined study answers the research problem more effectively than either method alone. For example, a survey may identify a pattern, while interviews explain the reasons behind it.

A mixed-methods MBA dissertation might investigate employee acceptance of AI:

• Quantitative phase: Survey employees to measure perceived usefulness, trust, anxiety and intention to use AI.
• Qualitative phase: Interview selected employees to understand why some groups are enthusiastic while others are resistant.
• Integration: Compare the statistical patterns with the interview themes and develop a more complete explanation.

Common mixed-methods designs include:

Design	Sequence	Suitable purpose
Explanatory sequential	Quantitative → qualitative	Explain unexpected or important survey findings
Exploratory sequential	Qualitative → quantitative	Develop concepts or questionnaire measures, then test them
Convergent	Quantitative and qualitative at roughly the same time	Compare or combine two perspectives on the same issue
Embedded	One method is dominant and the other is included within it	Add supporting evidence to a main study

For example, an explanatory sequential study could first discover that digitalisation improves performance only in some SMEs. Follow-up interviews could then explore whether management support, employee skills or organisational culture explains this difference.

Strengths

• Combines breadth from quantitative data with depth from qualitative data.
• Enables triangulation and comparison of findings.
• Can explain statistical patterns and test qualitative insights.
• Is useful for complex management problems involving both measurable outcomes and human experiences.

Limitations

• Requires more time, skills and resources than a single-method study.
• The two components may become disconnected.
• Sampling, analysis and integration are more demanding.
• The dissertation may become too broad for an MBA timetable.
• The researcher must justify why both methods are necessary.

A mixed-methods dissertation should specify the priority of each method, the sequence of the phases, how participants or cases are selected, how each dataset is analysed and, most importantly, how the findings are integrated.

Category 2: Research reasoning

2.1 Inductive approach

Inductive reasoning moves from specific observations to broader patterns, concepts, propositions or tentative explanations. The researcher begins with data rather than a fully specified theory and develops an interpretation from recurring themes or relationships. The conclusion is plausible and evidence-supported, but it is not logically guaranteed.

The logic can be represented as:

Observations→Patterns→Concepts→Tentative explanation

In an MBA dissertation, an inductive approach is appropriate when:

• The topic is relatively new or under-researched.
• Existing theories do not adequately explain the context.
• The objective is to explore experiences or processes.
• The researcher wants to develop a conceptual framework from field evidence.

Example:

The researcher interviews managers in Hong Kong SMEs about their use of generative AI. Repeated references to cost pressure, employee experimentation, weak governance and client expectations lead to a conceptual explanation of how SMEs gradually institutionalise AI.

The researcher does not begin by testing a fixed hypothesis. Instead, concepts are developed through coding, comparison and interpretation. Grounded theory is a particularly systematic inductive strategy, although ordinary qualitative thematic analysis can also have an inductive orientation.

Induction does not mean that the researcher has no prior ideas. A literature review, professional experience and existing concepts will usually influence the research. The important point is that the final themes or explanation are developed substantially from the evidence rather than imposed entirely in advance.

2.2 Deductive approach

Deductive reasoning begins with an existing theory, conceptual model or general proposition and derives specific hypotheses or expectations that can be examined using data. It is often described as a theory-first approach.

The logic can be represented as:

Theory→Hypotheses→Data collection→Testing

A deductive MBA dissertation may proceed as follows:

1.    Select a theory, such as the Technology–Organisation–Environment framework.

2.    Identify relevant constructs, such as technological readiness, organisational support and competitive pressure.

3.    Develop hypotheses about their relationships with AI adoption.

4.    Design a questionnaire to measure the constructs.

5.    Test the hypotheses using statistical analysis.

6.    Determine whether the results support or fail to support the theoretical expectations.

Example hypotheses could include:

• Technological readiness is positively associated with AI adoption.
• Top-management support is positively associated with AI adoption.
• Perceived implementation risk is negatively associated with AI adoption.

Deduction is especially common in quantitative research because variables can be operationalised and hypotheses can be statistically tested. However, it can also be used in qualitative research—for example, when interview questions and coding categories are derived from an existing theory.

A hypothesis that is not supported does not necessarily mean that the dissertation has failed. It may indicate that the theory does not apply fully to the selected population, that contextual factors matter, or that the measures require improvement.

2.3 Abductive approach

Abductive reasoning moves back and forth between empirical evidence and theoretical explanations in order to develop the most plausible interpretation of a surprising, incomplete or contradictory finding. It is often called inference to the best explanation.

The logic can be represented as:

Initial theory↔Empirical evidence↔Revised explanation

An abductive dissertation does not follow a completely linear “theory first” or “data first” process. Instead, the researcher may:

1.    Begin with an initial literature-based framework.

2.    Collect preliminary data.

3.    Notice findings that the framework does not explain.

4.    Return to the literature to identify alternative concepts.

5.    Collect or analyse further evidence.

6.    Refine the explanation.

7.    Use the revised framework to interpret the complete dataset.

Example:

A survey suggests that employees with high perceived usefulness of AI nevertheless show low intention to use it. Interviews reveal that employees are worried that AI adoption will lead to job displacement. The researcher returns to the literature, introduces perceived employment threat as an additional concept, and develops a revised explanation involving both usefulness and insecurity.

Abduction is particularly suitable for:

• Case-study research.
• Organisational problem-solving.
• Exploratory mixed-methods designs.
• Research involving unexpected findings.
• Studies where existing theories are useful but incomplete.
• Practical MBA projects seeking to explain a business problem rather than merely test or generate theory.

Abduction should not be used simply as a vague label for “using both theory and data.” The dissertation should explain what triggered the iterative movement, how alternative explanations were considered and why the final explanation is more convincing than competing interpretations.

How the categories fit together

The following combinations are common, but they are not compulsory:

Methods category	Common reasoning approach	MBA dissertation example
Qualitative	Inductive	Develop themes from interviews about managers’ sustainability practices
Qualitative	Deductive	Use institutional theory to analyse interview data
Qualitative	Abductive	Revise an explanation after an unexpected case-study finding
Quantitative	Deductive	Test hypotheses about service quality and customer satisfaction
Quantitative	Inductive	Explore previously unknown statistical patterns in secondary data
Mixed methods	Abductive or combined inductive–deductive	Use interviews to develop survey measures and then test them

The key distinction is:

• Qualitative, quantitative and mixed methods describe the nature and combination of the data and analytical procedures.
• Inductive, deductive and abductive approaches describe the logic by which the researcher connects theory and evidence.
• Research design describes the overall structure, such as a case study, survey, experiment or sequential mixed-methods design.
• Methods are the specific techniques, such as interviews, questionnaires, document analysis, regression and thematic coding.

Practical selection guide

Choose a qualitative and mainly inductive approach when your central question is about meanings, experiences, processes or reasons and the topic requires detailed contextual understanding.

Choose a quantitative and mainly deductive approach when you have clearly defined variables, an established theoretical framework, measurable constructs and a question involving relationships, differences or effects.

Choose a mixed-methods and often abductive approach when the problem has both measurable and interpretive dimensions—for example, when you need to identify the scale of a problem and explain the organisational reasons behind it.

For a manageable MBA dissertation, the best approach is usually the one that creates a clear alignment between:

Research question→objectives→theory→data→analysis→conclusion

A method should not be selected merely because it appears more sophisticated. A focused qualitative case study can be stronger than an over-ambitious mixed-methods project, and a carefully designed questionnaire can be more appropriate than interviews when the dissertation is specifically testing relationships between measurable constructs.

*** Also study article review, focusing on research approaches: doc 1; doc 2.