Asking AI to produce an MBA research theme and a proposal based on key words: on workplace despair (information from perplexity.ai)
My question 1: "Please come up with an MBA research theme, via the pragmatism lens, based on the following key word: impacts of AI on employee behavior, workplace despair, employee engagement practice in the Hong Kong grocery sector."
The reply: "That’s an excellent starting point for an MBA dissertation — your keywords bring together human behavior, technology adoption, and pragmatic managerial practice, which align perfectly with a pragmatism research philosophy. A pragmatic approach focuses on solving real-world problems by integrating both quantitative and qualitative methods to generate actionable insights.
Here’s one proposed research theme and framing that fits your keywords and philosophical focus:
Proposed Research Theme
"Balancing Efficiency and Humanity: A Pragmatic Study of How AI Adoption Influences Employee Behavior, Workplace Despair, and Engagement Practices in Hong Kong’s Grocery Sector."
Rationale
The Hong Kong grocery sector is currently undergoing digital transformation, adopting AI-driven systems for inventory, customer analytics, and checkout automation. While this transition enhances productivity, it can trigger psychological and behavioral changes among employees — such as feelings of job insecurity, reduced purpose, or “workplace despair,” especially among frontline staff.
A pragmatist researcher would investigate “what works” in maintaining employee engagement and psychological well-being during technological transformation, grounding findings in practical solutions for HR leaders and managers.
Core Research Objectives
To explore how AI integration affects frontline employees’ attitudes, motivation, and job satisfaction.
To examine the relationship between AI-driven changes and emerging patterns of workplace despair (e.g., stress, disengagement, or alienation).
To identify pragmatic engagement practices that can sustain morale and productivity amid automation pressures.
To provide actionable managerial insights for balancing AI efficiency with humane management in the grocery retail context.
Potential Research Questions
How does AI adoption reshape employees’ perceptions of autonomy, purpose, and job security in Hong Kong grocery stores?
What are the behavioral and emotional consequences of AI-driven work restructuring?
Which management practices most effectively preserve engagement and reduce workplace despair in technologically evolving retail environments?
How can a pragmatist approach help managers reconcile tension between efficiency-driven and people-centered business goals?
Suggested Mixed-Method Design (Pragmatic Approach)
Quantitative Phase: Survey grocery retail employees on engagement levels, stress, and perceived job insecurity before and after AI implementation.
Qualitative Phase: Conduct semi-structured interviews with managers and staff to understand how AI impacts daily work life and morale.
Integration: Triangulate findings to recommend practical, flexible engagement models suited to AI-integrated workplaces in Hong Kong’s retail sector."
My question 2: "Based on the proposed research theme of "Balancing Efficiency and Humanity: A Pragmatic Study of How AI Adoption Influences Employee Behavior, Workplace Despair, and Engagement Practices in Hong Kong’s Grocery Sector.", please offer a part-time MBA dissertation proposal with the following information:
The reply: "
- Dissertation Report TitleBalancing Efficiency and Humanity: A Pragmatic Inquiry into AI Adoption's Impact on Employee Behavior, Workplace Despair, and Engagement Practices in Hong Kong's Grocery Sector
2. Research Issues and Media-Reported Issues
Research Issues (with Gaps):
Limited empirical evidence on how AI-induced job redesign specifically triggers workplace despair (e.g., anxiety, alienation) among frontline grocery workers, despite broader technostress literature.
Gap in pragmatic studies integrating mixed methods to test engagement interventions tailored to Hong Kong's high-pressure retail context amid rapid AI rollout.
Insufficient exploration of managerial strategies to mitigate behavioral shifts like reduced autonomy or motivation in AI-augmented grocery operations.
Hong Kong Public Media-Reported Issues:
- AI-driven automation in retail targets admin roles, prompting widespread reskilling needs and fears of job displacement for over half of affected staff.
Employees face heightened workload pressures and psychological strain from AI tools, despite productivity gains, leading to burnout risks in dynamic retail environments.
Low trust in AI among Hong Kong consumers and staff (e.g., 35% cautious due to reliability issues) exacerbates frontline worker stress in grocery settings.
3. Research Objectives and Questions
Objectives:
Examine AI's influence on employee behavior and despair levels in Hong Kong grocery firms.
Identify key drivers of disengagement amid AI adoption in the sector.
Evaluate pragmatic engagement practices to counter behavioral negatives.
Develop actionable recommendations for managers balancing AI efficiency with employee well-being.
Questions:
- How does AI adoption shape employee behavior and contribute to workplace despair in Hong Kong grocery retail?
- What factors mediate the link between AI integration and reduced engagement practices?
- Which interventions most effectively restore engagement and mitigate despair?
4. Research Methods
Primary Methods:
Quantitative surveys of 200+ frontline grocery employees measuring despair, engagement, and behavior via validated scales (e.g., Utrecht Work Engagement Scale).
- Qualitative semi-structured interviews with 20-30 managers and staff for contextual insights on AI impacts.
Secondary Method:
Analysis of industry reports, media articles, and company documents on AI implementations in Hong Kong grocery chains.
5. Relevant Theories
Conservation of Resources (COR) Theory: Explains how AI as a resource threat depletes employee psychological reserves, fostering despair and disengagement unless offset by managerial support.
Job Demands-Resources (JD-R) Model: Frames AI as dual demands (e.g., technostress) and resources (e.g., automation relief), predicting engagement when resources buffer demands in grocery settings.
Technostress Theory: Highlights AI-induced stressors like overload and insecurity leading to negative behaviors, with pragmatic interventions to harness challenge aspects.
6. Justification
A collection of blog notes on using chatgpt for research purpose.
