A collection of notes on research ethics considerations review on academic articles: for MBA students

A collection of notes on research ethics considerations review on academic articles: for MBA students

1. On marketing creativity.
2. On customer engagement.

Examining research ethics considerations of a study on customer engagement: for MBA students

 Examining research ethics considerations of a study on customer engagement: for MBA students

 

The note examines the article of: Dreher, F. and Ströbel, T., 2026. Customer engagement in circular economy initiatives: Insights from PUMA. Journal of Business Research, 214, p.116286.

 

What are (1) the research theme, (2) the research objectives, and (3) the research questions of the article?

 

Based on the content of the article:

1.    Research Theme: The article focuses on customer engagement in circular economy (CE) initiatives, particularly examining how customers engage with a well-known brand (PUMA) and its business partners in circular practices aimed at combating climate change. The study integrates the service-dominant (S-D) logic and customer engagement frameworks to understand multidimensional customer engagement within circular business models.

2.    Research Objectives:

• To examine how customers engage with PUMA and its business partners in circular activities aligned with the integrative customer engagement framework by Hollebeek et al. (2019).
• To empirically validate how climate change engagement emerges as a downstream effect within these customer engagement practices.
• To explore specific engagement practices customers enact in a circular economy context, based on the practices identified by Verleye et al. (2024) and how these relate to customer resource integration, knowledge sharing, and learning.
• To address the current gap in detailed understanding of how customer engagement unfolds through specific practices in circular business models and their contribution to climate-relevant outcomes.

3.    Research Questions: Although not explicitly stated as research questions, the study implicitly investigates:

• How do customers engage with a brand (PUMA) and its partners in circular economy activities?
• Which engagement practices do customers enact in the context of circularity, and how do these practices relate to the dimensions of customer engagement (resource integration, knowledge sharing, learning)?
• How do these customer engagement practices contribute to climate change mitigation and circular economy outcomes?

These align with the study’s aim to understand the multidimensionality and practical enactment of customer engagement in circular business models and climate change engagement.

Briefly describe the research methodology as well as the main research methods (both primary and secondary) of this article.

The research methodology of the article is a qualitative single case study approach focused on PUMA, a global sports apparel brand actively engaged in circular economy initiatives. This approach allows for in-depth exploration of interactions among PUMA, its business partners, and customers in a natural context, capturing the emergent and practice-based nature of customer engagement in circularity.

Main Research Methods:

·        Primary Data:

·        Conducted 31 semi-structured interviews with three participant groups: PUMA employees (12 managers from various business units plus 4 from the sustainability team), business partners (including recycling partners and retail partners), and customers (9 participants involved in the RE:SUEDE circularity project).

·        Interviews were exploratory, open-ended to allow participants to freely discuss their experiences and perceptions related to circular initiatives and customer engagement without imposing predefined theoretical categories.

·        Interviews were conducted via Microsoft Teams, transcribed verbatim, and analyzed systematically using qualitative coding with ATLAS.ti.

·        Data coding involved an abductive approach combining open coding, mapping to existing theoretical frameworks (Hollebeek et al.’s customer engagement framework and Verleye et al.’s circular engagement practices), and refinement to develop new empirically driven codes.

·        Secondary Data:

·        Theoretical frameworks and prior literature on customer engagement, circular economy practices, and climate change engagement informed both the interview design and the iterative data analysis process, allowing pairing of empirical insights with extant theories.

·        Data Analysis:

·        Used thematic analysis with categorization, abstraction, comparison, and integration to identify key customer engagement practices.

·        Employed intercoder reliability measures (Cohen’s kappa = 0.83) and member checking with participants to ensure rigor and credibility.

This methodology facilitated a nuanced understanding of multidimensional customer engagement in circular business models and its potential as a pathway toward climate change engagement.

 

Discuss the main research ethics considerations of (1) the research objectives chosen, (2) the research methodology and the research methods involved.

The main research ethics considerations related to the article’s research objectives, methodology, and methods are as follows:

1.    Ethics of the Research Objectives:

• The study aims to explore customer engagement in circular economy initiatives linked to sustainability and climate change mitigation. These objectives address socially responsible and environmentally relevant topics, aligning ethical research goals with promoting knowledge that benefits society and the environment.
• Ensuring the research promotes genuine understanding rather than exploiting participants or overstating sustainability claims is vital, particularly given the focus on corporate circular initiatives that affect public perception and trust.

2.    Ethics of the Research Methodology:

• The use of a qualitative, abductive case study methodology allows participants to share their authentic experiences in naturalistic settings, respecting their perspectives and avoiding imposition of rigid academic categories. This enhances participants’ dignity and voice while ensuring ecological validity.
• By involving multiple stakeholder groups (employees, business partners, customers), the methodology captures diverse viewpoints, avoiding bias and promoting inclusiveness.

3.    Ethics of the Research Methods:

• Informed Consent: Participants were informed about the study’s purpose, their voluntary participation, the right to withdraw at any point, and how data would be used, ensuring autonomy and informed decision-making. Permission for recording and transcription was explicitly obtained.
• Confidentiality and Data Privacy: Data was anonymized by removing personal identifiers and assigning codes during transcription to protect participant identities. Audio recordings and transcripts were securely stored on encrypted, password-protected drives accessible only to the research team, ensuring data confidentiality and compliance with GDPR regulations.
• Minimizing Harm and Discomfort: Interview guides were designed to be open and exploratory without intrusive or sensitive questioning, aiming to minimize participant discomfort. Pre-testing of interview protocols with internal employees ensured clarity and appropriateness.
• Accuracy and Integrity: Transcriptions excluded fillers and stutters to focus on substantive content. Member checking involved returning summarized interpretations to participants for validation, enhancing credibility and guarding against misrepresentation.
• Intercoder Reliability: Coding disagreements were resolved through joint discussions until consensus was reached, ensuring interpretative accuracy and reliability, which reflects ethical rigour in data analysis.

Overall, the research adhered to high ethical standards in line with legal and institutional requirements, prioritizing participant rights, data protection, and the ethical pursuit of knowledge on sustainability and circular economy topics.

** the discussion is supported by chatpdf.com

 

A collection of blog notes on using chatgpt for research purpose.

A note on formulating a dissertation proposal with less risk to research participants: for MBA students

A note on formulating a dissertation proposal with less risk to research participants: for MBA students

 

I am a part-time MBA student in Hong Kong, currently attempting to come up with a dissertation proposal. My concern is that, I have difficulties to employ primary research methods that require gatekeeper informed consent form. For research methods, e.g. research interview, that might gather sensitive information are also quite likely to be infeasible. In this regard, could you suggest a few research themes and research methods that are more feasible to consider under the present environment atmosphere with many organizations and people being more cautious in participating in dissertation project works as respondents?

Yes — in your situation, the most feasible dissertation designs are those that rely on publicly available data, document analysis, or lightly structured non-sensitive data, rather than requiring access to internal organizational information or sensitive personal disclosures. In Hong Kong, this is especially practical because many useful business and governance datasets are already available through public/open sources and listed-company disclosures.

Feasible themes

·        Corporate governance and disclosure quality of Hong Kong listed companies, using annual reports, ESG reports, and HKEX disclosure materials as data.

·        Dividend policy, board diversity, risk management, or ESG reporting changes among Hong Kong listed firms, again using only published documents and market data.

·        Sectoral resilience or adaptation in Hong Kong industries such as retail, hotels, logistics, or SMEs, using newspaper reports, company websites, public filings, and market statistics rather than internal interviews.

·        Comparative analysis of public policy or market trends in Hong Kong using official statistics and secondary datasets from government/open-data sources.

·                                                                 Content analysis of business communications, for example how companies frame sustainability, crisis response, talent retention, or innovation in public statements.

Methods that fit

·             Secondary data analysis: re-analyse existing datasets, government statistics, or published market data without collecting new personal or organizationally sensitive data.

·             Document analysis: examine annual reports, ESG reports, policy documents, news releases, and corporate websites.

·             Content analysis: code public texts for themes, frequency, tone, or disclosure patterns; this works well when interview access is difficult.

·             Comparative case study using public cases: compare firms, sectors, or policy responses based on publicly available information only.

·             Desk-based literature review with conceptual development: useful if access is very limited, especially when you want to build a strong theoretical framework first.

Topic ideas

Theme	Why it is feasible	Suitable method
ESG disclosure in Hong Kong listed firms	Public reports are accessible	Content analysis + secondary data
Board diversity and governance quality	Board-related disclosures are published	Document analysis + comparative analysis
Dividend policy communication	Dividend and governance disclosures are public	Content analysis
Retail or hotel resilience in Hong Kong	Public market reports and news coverage are available	Secondary data + document analysis
SMEs’ digital transformation in Hong Kong	Can use public policies, industry reports, and website materials	Case comparison + literature review

How to avoid gatekeeper issues

A useful design rule is to frame the study around industry-level or public-firm-level questions, not internal company operations or employee-specific experiences. For example, instead of studying “how employees in Company X perceive internal restructuring,” you might study “how Hong Kong retail firms communicate restructuring and resilience in public disclosures.” This keeps the project researchable without asking a manager to authorize internal access. It also reduces the chance that you will need sensitive informed consent arrangements for participants.

Practical recommendation

For a part-time MBA dissertation, the safest route is usually: one clear industry or governance theme + one public-data method + one manageable time window. A strong combination would be:

1.    pick a Hong Kong sector you already understand,

2.    define a question that can be answered from annual reports, public statistics, and company websites,

3.    use content analysis or secondary analysis as the core method.

A very workable example is: “How have Hong Kong listed retail companies changed their ESG and resilience disclosure practices from 2021 to 2025?” using annual reports, ESG reports, and publicly available market statistics.

 

What if the university still favor students to employ 1 to 2 primary research methods in the students' dissertation projects? What would you suggest I can consider coming up with primary research method design that expose to respondents with lower risks (e.g. reputation risk, sensitive corporate information leakage risk)?

You can satisfy a university requirement for 1–2 primary methods while keeping respondent risk very low by choosing designs that collect non-sensitive, non-identifiable data and avoid probing internal or reputational matters. Below are concrete, practical options (each linked to low risk, feasibility, and short note on ethics/gatekeepers).

Direct answer

·        Use low-risk primary methods such as structured anonymous surveys, brief public-facing intercept surveys, short expert-validation questionnaires with non-sensitive prompts, or lightweight vignette experiments; pair one primary method with a desk-based method (document/secondary data or content analysis) to meet the “1–2 primary” requirement while keeping risk minimal.

Low-risk primary method options (what they are, why low-risk, feasibility)

·        Anonymous online questionnaire (closed questions only). Collects aggregate, non-identifiable responses about opinions or perceptions on public topics (e.g., industry trends, attitudes to ESG disclosure). Low reputational risk because answers are anonymous and you avoid asking for firm-internal facts; easy to recruit via alumni lists, LinkedIn, or panels. Ethical forms are usually straightforward if anonymity is explicit.

·        Short structured surveys of consumers / customers (intercept or online panel). Ask about consumer behaviour, brand perceptions or willingness to pay—no internal corporate data, low sensitivity, fast to run, and no gatekeeper needed for firms if you recruit customers in public channels.

·        Vignette-based online experiment. Present short, fictional scenarios (vignettes) about public-firm behaviour (fictional company names or anonymised descriptions) and ask respondents for choices or ratings. This elicits causal or normative insight without exposing real companies or employees to reputational risk.

·        Expert-validation questionnaires with constrained topics. Send a short, structured questionnaire (3–8 items) to industry experts asking for general judgements (e.g., rank importance of drivers of retail recovery). Keep questions high-level and non-identifiable; ask for voluntary participation and offer anonymized reporting. This usually requires only minimal ethics paperwork because no sensitive firm data are requested.

·        Observation of public behaviour or content (structured naturalistic observation). Observe footfall patterns in public retail areas or code in-store window displays (no interaction, public setting). This is unobtrusive and typically low-risk for participants.

How to frame primary methods to reduce risk and gatekeeper needs

·        Ask about public-facing topics, not internal operations. For example: “How do consumers perceive retailers’ post-pandemic communications?” rather than “How did Manager X decide to restructure store Y?”.

·        Avoid collecting identifiers or linking responses to specific firms or individuals (use forced anonymity and aggregate reporting). This reduces privacy and reputational risk and simplifies ethics approval.

·        Use hypothetical or fictional stimuli (vignettes) if you need to study reactions to sensitive actions; respondents react to the scenario rather than identifying real people or companies.

·        Limit interview depth and scope: if you must do interviews, use very short (15–20 minute) semi-structured interviews focused on high-level industry perspectives rather than past actions or confidential decisions; obtain informed consent and offer anonymized quotes only.

·        Use opt-in recruitment from public channels or professional networks rather than asking a manager to introduce employees (avoids gatekeeper consent for accessing internal staff).

Practical pairings (one primary + one desk method) — low risk and defensible

·        Anonymous online survey of consumers + content analysis of firm annual reports (answers consumer perceptions vs. published disclosure).

·        Short vignette experiment with business students or alumni + secondary market/financial data analysis (tests responses to disclosure scenarios vs. actual market trends).

·        Expert short questionnaire (industry association members) + comparative document analysis of policy texts or corporate reports (validates expert judgments against documents).

·        Naturalistic observation of retail footfall patterns (public spaces) + desk-based analysis of industry sales statistics (links observed behaviour to published data).

Ethics and practical tips to improve chances of approval

·        Make anonymity explicit, collect no names/IDs, and report only aggregated results; document storage and deletion plans in your ethics form.

·        Use brief information sheets and one-click consent for online surveys; keep language simple and highlight voluntary nature.

·        If recruiting experts or alumni, use personal networks but emphasize independence and anonymized reporting; many gatekeepers accept this when no firm-confidential questions are asked.

·        Use existing datasets (HK government, HKEX, industry reports) to reduce primary data needs and justify limited, low-risk primary methods as complementary rather than central.

·        Discuss your low-risk design with your supervisor and attach a short rationale to ethics application showing how you avoid sensitive topics and reduce risk to participants (this often eases committee concerns).

Example low-risk dissertation design (concrete)

·        Topic: “How do Hong Kong consumers perceive retail firms’ ESG communications after COVID-19?”

·        Primary method: anonymous online consumer survey (10–12 closed items + 1 optional comment), recruited via social media and alumni list; consent via checkbox; no firm-specific questions.

·        Secondary/desk method: content analysis of ESG sections of annual reports for a matched sample of listed retail firms (2021–2025).

·        Risk management: anonymized responses, no employee/manager interviews, fictional vignettes if testing reactions to sensitive corporate actions.

** the discussion is supported by perplexity.ai

 

A collection of blog notes on using chatgpt for research purpose.