A note on key introductory Research Methods topics in Housing Studies

A note on key introductory Research Methods topics in Housing Studies

Highlight 5 main ideas on each of the following research methods topics in the context of Housing Studies:

1.    Ontology

2.    Epistemology

3.    Axiology

4.    Positivism

5.    Interpretivism

6.    Pragmatism

7.    Critical realism

8.    Quantitative research

9.    Qualitative research

10.                    Mixed methods research

11.                    The inductive research approach

12.                    The deductive research approach

 

Below are concise teaching notes: five main ideas for each topic, framed for Housing Studies dissertations. Research paradigms connect ontology, epistemology, axiology, and methodology, so your philosophical choices should be consistent with your research questions, data, and analysis strategy.

1. Ontology

Ontology concerns the researcher’s assumptions about the nature of reality—what exists and what can be studied.

• Nature of reality: Housing may be treated as an objective material reality (dwelling units, rents, tenure types) or as a socially constructed reality shaped by residents’ meanings and experiences.
• Objective vs. subjective reality: A study of overcrowding may measure floor area objectively, while also recognizing that “home” and “housing adequacy” are experienced differently by occupants.
• Multiple realities: Different stakeholders—tenants, landlords, planners, officials, developers—may hold different realities about the same housing problem.
• Structures and mechanisms: Housing outcomes are shaped by underlying structures such as housing markets, welfare systems, land supply, class, gender, and policy regimes.
• Implication for research: Your ontology guides whether you prioritize measurable housing indicators, residents’ lived experiences, or both.

2. Epistemology

Epistemology asks how knowledge is produced, what counts as valid knowledge, and how researchers can know the social world.

• Knowledge and evidence: In housing research, knowledge may come from surveys, administrative data, interviews, observation, policy documents, or residents’ narratives.
• Researcher–knowledge relationship: A researcher may seek detached measurement of housing conditions or interactive understanding of tenants’ experiences.
• Objectivity vs. interpretation: Statistical evidence can establish patterns, whereas interviews can explain why residents perceive insecurity, belonging, or exclusion.
• Validity criteria: Quantitative work emphasizes reliability, validity, and generalizability; qualitative work emphasizes credibility, depth, reflexivity, and transferability.
• Implication for research: Epistemology justifies your choice of survey, interview, case study, or mixed-method design.

3. Axiology

Axiology concerns the role of values, ethics, and researcher positioning in research.

• Values influence research: Choices about which housing issues matter—affordability, homelessness, safety, segregation, environmental quality—reflect social and ethical values.
• Value-free vs. value-aware research: Positivist research often aims for neutrality, while interpretive and critical approaches openly acknowledge researchers’ values and social commitments.
• Ethics with vulnerable groups: Housing research often involves tenants, homeless people, elderly residents, or low-income households; informed consent, confidentiality, and non-exploitation are essential.
• Reflexivity: Researchers should consider how their background, assumptions, and institutional position shape questions, sampling, interpretation, and recommendations.
• Social relevance: Axiology encourages research that not only describes housing problems but also considers fairness, inclusion, and potential benefits for residents and communities.

4. Positivism

Positivism assumes an external, observable reality that can be studied through systematic measurement and scientific methods.nsuworks.nova+2

• Objective reality: Housing conditions, rent levels, vacancy rates, tenure status, and household income are treated as externally observable facts.
• Measurement and quantification: Researchers use indicators such as housing-price indices, overcrowding ratios, satisfaction scores, or tenure distributions.
• Causal explanation: Positivist studies often test relationships, for example between housing affordability, neighbourhood quality, and residential satisfaction.
• Value neutrality: The researcher aims to minimize bias through standardized instruments, large samples, and transparent procedures.
• Typical housing application: A questionnaire survey of public-housing residents testing whether estate facilities, management quality, and unit size predict satisfaction.

5. Interpretivism

Interpretivism holds that social reality is subjective, multiple, and constructed through human meanings and experiences.nsuworks.nova+1

• Multiple housing realities: “Adequate housing” may mean affordability to one resident, safety to another, and proximity to work or family to another.
• Meaning-centred inquiry: The focus is on how residents interpret home, neighbourhood, displacement, insecurity, or community.
• Qualitative methods: In-depth interviews, focus groups, ethnography, life histories, and document analysis are commonly used.
• Context matters: Housing experiences cannot be separated from family circumstances, culture, income, migration status, health, and local policy.
• Typical housing application: Semi-structured interviews exploring how residents in poor-quality housing experience ontological security, privacy, and belonging.

6. Pragmatism

Pragmatism focuses on research questions and practical consequences; methods are selected according to what works best for the problem.

• Problem-centred research: A housing study may begin with a practical issue, such as improving estate management, reducing homelessness, or increasing affordable-housing support.
• Methodological flexibility: Pragmatism supports combining surveys, interviews, administrative data, and case studies rather than committing to one philosophical camp.
• Usefulness of knowledge: Findings are judged by their ability to inform policy, improve services, or solve real housing problems.
• Both facts and meanings: It can incorporate measurable outcomes and residents’ interpretations of housing programmes.
• Typical housing application: A study evaluating a housing-first programme using service-use statistics and interviews with residents and frontline staff.  

7. Critical realism

Critical realism argues that an objective reality exists, but it is stratified: observable events are produced by underlying structures and mechanisms that are not directly visible.

• Reality is layered: Visible housing outcomes—eviction, overcrowding, homelessness—reflect deeper mechanisms such as market structures, welfare policy, discrimination, and institutional practices.
• Explanation over mere description: The aim is to explain how and why housing problems arise, not only to measure their frequency.
• Structures and agency: Researchers examine both structural constraints and residents’ capacity to respond, adapt, resist, or seek support.
• Retroduction: Researchers move from observed patterns to plausible underlying mechanisms, often using case studies, interviews, and policy analysis.
• Typical housing application: Explaining why low-income households remain in inadequate private rental housing by linking rent burdens, weak tenant protection, labour insecurity, and limited social housing supply.

8. Quantitative research

Quantitative research uses numerical data to describe patterns, test relationships, and sometimes make generalizable claims.

• Structured measurement: Housing variables are operationalized through scales, counts, categories, or official indicators.
• Large samples: Surveys can capture patterns across neighbourhoods, tenure groups, income bands, or districts.
• Statistical analysis: Descriptive statistics, correlation, regression, factor analysis, and other techniques identify associations and predictors.
• Deductive orientation: Research often starts from theory or hypotheses and tests them against data.
• Typical housing application: A survey examining whether rent-to-income ratio, dwelling size, and estate facilities predict residential satisfaction among public-housing tenants.

9. Qualitative research

Qualitative research explores meanings, experiences, processes, and contexts through non-numerical data such as words, images, and observations.

• Depth over breadth: It seeks rich understanding of how people experience housing rather than statistical generalization.
• Participants’ perspectives: Interviews and focus groups allow tenants, homeless people, or housing officers to explain issues in their own terms.
• Context-sensitive analysis: Themes are interpreted in relation to life history, family situation, neighbourhood, and institutional context.
• Inductive coding: Researchers often develop themes from transcripts, although qualitative work may also use deductive codes from prior theory.
• Typical housing application: A grounded-theory study of how formerly homeless residents reconstruct routines, privacy, identity, and security after moving into supportive housing.

10. Mixed methods research

Mixed methods research deliberately combines quantitative and qualitative data and analysis to achieve breadth and depth.

• Complementary strengths: Numbers show the extent of a problem; interviews explain its meaning and mechanisms.
• Triangulation: Findings from surveys and interviews can confirm, elaborate, or challenge one another.
• Design choices: Common designs include convergent parallel, explanatory sequential, and exploratory sequential designs.
• Induction and deduction: A study may use interviews to generate themes and then survey a larger sample to test them, or use theory to guide both strands.
• Typical housing application: A convergent study measuring changes in social networks among housing-first residents while interviewing them about recovery, belonging, and service experiences.

11. Inductive research approach

The inductive approach moves from specific observations to broader patterns, concepts, or theory.

• Data first, theory later: Researchers begin with fieldwork or textual data rather than a fixed hypothesis.
• Pattern recognition: Recurrent ideas in interviews or documents are grouped into codes, categories, and themes.
• Theory building: Findings may generate new concepts or a tentative model, such as a theory of housing insecurity among low-income tenants.
• Commonly qualitative: It is strongly associated with interviews, ethnography, grounded theory, and thematic analysis.
• Typical housing application: Interviewing residents about poor-quality housing and allowing themes such as “loss of control,” “stigma,” and “ontological insecurity” to emerge from the data.

12. Deductive research approach

The deductive approach moves from existing theory or general propositions to specific, testable hypotheses.

• Theory first: The researcher derives expectations from literature, policy theory, or an established conceptual framework.
• Hypothesis testing: Propositions are translated into measurable variables and examined using data.
• Structured instruments: Surveys, official statistics, experiments, and standardized measures are common.
• Confirmation or revision: Results either support, reject, or refine the initial theoretical proposition.
• Typical housing application: Testing whether, as housing-affordability theory suggests, higher rent burdens reduce residential satisfaction and increase intention to move.

A note on lifecycle costing and lifecycle analysis in advanced management accounting

A note on lifecycle costing and lifecycle analysis in advanced management accounting

 

Regarding the subject of advanced management accounting, I have come across the two terms, i.e. lifecycle costing and lifecycle analysis. I can tell that lifecycle costing as associated to the concept of product life cycle, while lifecycle analysis appears to be related to the topic of environmental management accounting. Could you clarify these two terms to me and offer a more coherent way to understand these two terms?

 

Your instinct is broadly correct: lifecycle costing is primarily a cost-management and profitability technique, whereas lifecycle analysis—more precisely, life cycle assessment (LCA)—is primarily an environmental-impact assessment technique. They share a “cradle-to-grave” perspective, but answer different managerial questions.

Core distinction

Term	Usual full name	Main question	Primary discipline	Typical output
Lifecycle costing	Life-cycle costing (LCC)	“What will this product or asset cost, and earn, over its whole life?”	Management accounting / cost management	Total lifetime costs, revenues, profitability, target-cost insights
Lifecycle analysis	Life cycle assessment (LCA)	“What environmental burdens does this product create across its life?”	Environmental management / sustainability accounting	Resource use, emissions, waste, carbon and other environmental impacts

Lifecycle costing

Lifecycle costing accumulates and manages costs from the earliest product idea through design, production, marketing, after-sales service, and final withdrawal or disposal. Its purpose is to ensure that lifetime revenues exceed lifetime costs, rather than judging profitability only from manufacturing costs recorded in a particular accounting period.

Typical cost categories include:

• Research, development, design and tooling.
• Materials, labour, overheads, set-up and production maintenance.
• Distribution, advertising, warranty and customer service.
• End-of-life disposal, decommissioning or environmental clean-up.

For example, an electric appliance may have low manufacturing costs but high warranty, servicing, energy-related customer costs, and disposal obligations. Lifecycle costing makes these later and upstream costs visible before pricing, target-costing, make-or-buy, and product-withdrawal decisions are made. It is especially important because many costs are committed early in design, even though they are incurred later.

Lifecycle analysis / assessment

Lifecycle analysis, more commonly called life cycle assessment (LCA), evaluates the environmental inputs and outputs of a product system across its life: raw-material extraction, manufacturing, transport, use, reuse or recycling, and disposal. It quantifies resource consumption and emissions, then assesses potential impacts such as climate change, water pollution, resource depletion, and human-health effects.

In an environmental management accounting context, LCA supplies physical and environmental information—kilograms of CO2-equivalent, litres of water, waste volumes, energy use—that can then inform eco-design, supplier selection, carbon reporting, ESG disclosure, and environmental cost management.

A coherent way to connect them

Think of both as applications of life-cycle thinking, but with different measurement lenses:

Life-cycle thinking→ {Lifecycle costing: monetary costs and revenues &

Lifecycle assessment: physical environmental impacts} 

A useful teaching formulation is:

Lifecycle costing asks whether the product is financially sustainable over its life; lifecycle assessment asks whether it is environmentally sustainable over its life.

They can also be integrated. An LCA may identify that a packaging redesign reduces plastic waste and carbon emissions; lifecycle costing then estimates whether the redesign lowers total lifetime cost, raises price acceptance, reduces regulatory or disposal costs, or improves long-term profitability. Environmental life-cycle costing extends conventional LCC by attempting to attach monetary values to selected environmental externalities, although this is more complex and less standardized than ordinary LCC.

Simple illustration

For a reusable coffee cup:

• Lifecycle costing: compare development, materials, production, distribution, warranty, returns, cleaning guidance, and end-of-life costs against expected sales revenue and residual value.
• Lifecycle assessment: compare raw-material extraction, manufacturing energy, transport, repeated use, washing, recycling, and landfill impacts against a disposable-cup alternative.
• Integrated decision: if the reusable cup has higher upfront production cost but lower lifetime environmental impact and better customer retention, management can use both LCC and LCA to justify its design, price, and sustainability positioning.

Terminology caution

“Lifecycle analysis” is sometimes used loosely. In advanced management accounting, it is safest to distinguish:

• Life-cycle costing (LCC): financial/cost management technique.
• Life cycle assessment (LCA): environmental impact assessment technique.
• Life-cycle cost analysis (LCCA): often used in engineering, infrastructure, and public procurement for comparing whole-life ownership costs of assets or projects.

So, for an advanced management accounting course, present lifecycle costing as part of strategic cost management and target costing, and lifecycle analysis/LCA as part of environmental management accounting and sustainability performance measurement.