A note on turning an MBA concrete research
theme into a dissertation proposal prototype: an example on reskilling and
upskilling in Hong Kong banks
The concrete research theme is "Evaluating the effectiveness of reskilling and upskilling strategies for GenAI adoption in Hong Kong banks: a pragmatic approach."; it is converted into a dissertation proposal prototype. Some additional information needs to be provided to Generative AI in order to produce such a dissertation proposal prototype.
My information and query posted to
Generative AI: I am a part-time MBA
student, currently learning to do my 4-month dissertation project. My present
task is to further develop my concrete research theme into a full-fledged
proposal prototype. My research theme is as follows: Evaluating the
effectiveness of reskilling and upskilling strategies for GenAI adoption in
Hong Kong banks: a pragmatic approach.
Two chosen theories of mine to study this topic are: the
Absorptive Capacity Theory of Cohen and Levinthal (1990) and the Human Capital
Theory of Becker (1962).
The research philosophy to use is pragmatism and the
research approach to use is the mixed methods research. As to the primary
research methods, I will employ focus group with 6 participants (4 are human
resource managers in the banking sector; 1 is an IT manager in the banking
sector; 1 is a university lecturer in Human Resource Management). My
second primary research method to use is a questionnaire survey to my friends,
with about 80 survey respondents. Please produce a dissertation proposal to me with:
a project title, 4 research objectives, 4 research questions, an overall
research methodology design with 2 primary research method design and 1
secondary research method design (internet-based).
The reply: Below is a dissertation proposal prototype
tailored to your topic, philosophy, theories, and methods. The proposal is
grounded in the current Hong Kong banking context, where GenAI adoption is
advancing but still constrained by talent, resources, and training needs.
Project title
Evaluating the perceived
effectiveness of reskilling and upskilling strategies for GenAI adoption in
Hong Kong banks: a pragmatic mixed-methods study
Background and rationale
Generative
AI is becoming increasingly important in Hong Kong’s financial services sector,
and the HKMA has already highlighted the need for banks to build workforce
capability through training and manpower development. At the same time, banks
face pressure to ensure employees can adapt to new AI-enabled tasks and
responsibilities, which makes reskilling and upskilling a timely issue for
research. This study therefore focuses on perceived effectiveness,
meaning how stakeholders judge whether these strategies improve readiness,
confidence, adaptability, and learning capacity for GenAI adoption. The topic
is suitable for a pragmatic mixed-methods design because it combines practical
managerial insight with survey-based evidence.
Research aim
The
study aims to evaluate how stakeholders in the Hong Kong banking sector perceive the
effectiveness of reskilling and upskilling strategies in supporting GenAI
adoption, and to interpret those perceptions through Absorptive Capacity Theory
and Human Capital Theory.
Research objectives
1. To identify the main reskilling and upskilling strategies used or considered by Hong Kong banks in preparation for GenAI adoption.
2. To explore how HR managers, an IT manager, and a university lecturer in HRM perceive the effectiveness of these strategies in building GenAI readiness.
3. To measure survey respondents’ perceptions of how reskilling and upskilling initiatives affect their confidence, adaptability, and willingness to engage with GenAI-enabled work.
4. To interpret the findings using Absorptive Capacity Theory and Human Capital Theory to explain how learning investments may support knowledge absorption and workforce capability development.
Research questions
1. What reskilling and upskilling strategies are currently being used or proposed in Hong Kong banks for GenAI adoption ?
2. How do selected banking HR and IT practitioners, together with an HRM academic, perceive the effectiveness of these strategies ?
3. To what extent do survey respondents perceive these initiatives as improving their knowledge, confidence, and readiness for GenAI-related tasks ?
4. How do Absorptive Capacity Theory and Human Capital Theory help explain these perceived outcomes ?
Research
philosophy and approach
The
research philosophy is pragmatism,
because the study is driven by a practical problem and seeks answers that are
useful for banking workforce development. The research approach is mixed methods,
since the issue is best understood by combining qualitative perceptions with
quantitative survey results. Pragmatism supports this combination because it
values methods according to what best answers the research problem rather than
forcing a single philosophical position. In this project, the qualitative and
quantitative findings will be integrated to create a fuller picture of
perceived effectiveness.
Methodology design
The
overall design can be presented as a sequential exploratory
mixed-methods design. First, a focus group will explore
stakeholder views in depth and generate themes for the survey. Second, a
questionnaire survey will test how far those themes are shared across a wider
group of respondents. Third, an internet-based documentary review will provide
contextual evidence from recent Hong Kong banking and policy sources to support
triangulation.
Primary method 1
The
first primary method is a focus group with
6 participants: 4 HR managers from the banking sector, 1 IT manager from the
banking sector, and 1 university lecturer in Human Resource Management. This
group composition is appropriate because it brings together operational,
technical, and academic perspectives on how GenAI training is understood and
judged. The discussion can be semi-structured and organised around training
design, perceived learning outcomes, implementation barriers, and factors that
make training seem effective. The focus group is especially useful for defining
the dimensions of perceived effectiveness before finalising the survey
instrument.
Primary method 2
The
second primary method is a questionnaire survey with
about 80 respondents drawn from your friends. The survey should use mostly
closed-ended Likert-scale items to capture perceptions of training usefulness,
confidence improvement, adaptability, and GenAI readiness. Because the sample
is convenience-based, the survey should be framed as exploratory and
descriptive rather than statistically representative. The questionnaire can be
informed by the focus group findings so that both methods speak to the same
core concept of perceived effectiveness.
Secondary method
The
secondary method will be an internet-based documentary
review of published materials such as HKMA reports,
banking industry statements, professional body publications, and recent policy
documents relating to GenAI and workforce development in Hong Kong. This method
will help you compare your primary findings against current sector thinking and
official guidance. It will also strengthen the dissertation’s contextual
validity by showing whether the perceptions gathered from participants align
with broader industry developments. Sources from HKMA and related institutions
are particularly relevant because they directly address AI capability-building
in Hong Kong banking.
Theoretical lens
Absorptive
Capacity Theory is relevant because it explains how organizations and employees
recognize, absorb, and apply new knowledge, which fits the learning demands of
GenAI adoption. Human Capital Theory is relevant because it frames training as
an investment in employee skills and productivity, making it ideal for
analysing reskilling and upskilling initiatives. Together, these theories
support a practical explanation of why some training activities are perceived
as more effective than others. They also help connect individual learning
outcomes to organizational adaptation in banks.
Expected contribution
This
dissertation is expected to contribute in three ways. First, it will provide a
practical account of how GenAI-related training is perceived by banking and HR
stakeholders in Hong Kong. Second, it will show how two established theories
can be used to interpret workforce readiness in an emerging technology context.
Third, it will offer useful guidance for banks designing reskilling and
upskilling strategies that are not only technically sound but also positively
perceived by employees.
Suggested final wording
You
may want to use this polished one-sentence summary in your proposal:
This study adopts a
pragmatic mixed-methods design to evaluate the perceived effectiveness of
reskilling and upskilling strategies for GenAI adoption in Hong Kong banks,
drawing on Absorptive Capacity Theory and Human Capital Theory to explain how
learning investments shape workforce readiness.
Proposed structure
You can frame the proposal around these sections:
· Introduction and background.
· Research problem and rationale.
· Literature review and theoretical framework.
· Research objectives and questions.
· Methodology.
· Ethical considerations.
· Expected contribution.
· Proposed timetable.
My query to generative AI: Please suggest 4 academic references and 4
non-academic references for this dissertation project in Harvard reference
format.
The reply: Here are 4 academic and 4 non-academic references
you can use as a starting bibliography for your dissertation, formatted in
Harvard style. I selected them to match your topic on perceived effectiveness
of reskilling/upskilling for GenAI adoption in Hong Kong banks, your pragmatist
mixed-methods design, and your two theories.
Academic references
Becker,
G.S. (1962) ‘Investment in human capital: A theoretical analysis’, Journal of Political Economy,
70(5, Part 2), pp. 9–49.
Cohen,
W.M. and Levinthal, D.A. (1990) ‘Absorptive capacity: A new perspective on
learning and innovation’, Administrative Science
Quarterly, 35(1), pp. 128–152.
Johnson,
R.B. and Onwuegbuzie, A.J. (2004) ‘Mixed methods research: A research paradigm
whose time has come’, Educational Researcher,
33(7), pp. 14–26.
Tashakkori,
A. and Teddlie, C. (2003) Handbook of mixed methods in
social and behavioral research. Thousand Oaks, CA: Sage.
Non-academic references
Hong
Kong Institute of Bankers and Hong Kong Monetary Authority (2025) Professional Duty: Generative AI Framework
for Banking. Hong Kong. Available at: https://www.hkib.org/
Hong
Kong Monetary Authority (2024) HKMA urges Hong Kong banks
to upskill workforce on AI. Hong Kong. Available at: https://coingeek.com/hkma-urges-hong-kong-banks-to-upskill-workforce-on-ai/
