A brief teaching note on abductive reasoning (information from perplexity.ai)
My question 1: "Highlight 6 main ideas of abductive reasoning in the context of research approach."
The reply: "Here are six main ideas of abductive reasoning in the context of research approach based on the gathered information:
Starts with surprising observations or facts: Abductive reasoning begins with noticing something unexpected or puzzling in the data or phenomenon that requires explanation rather than starting from a hypothesis or theory.
Seeks the simplest and most likely explanation: It aims to generate the best possible hypothesis that explains the observations in a straightforward and coherent way, known as "inference to the best explanation".
Is iterative and flexible: The process involves moving back and forth between theory and data, refining hypotheses as new evidence emerges, and allowing adjustment in light of new findings.
Is creative and exploratory: Abductive reasoning demands imagination and innovation to develop novel hypotheses or insights, pushing beyond existing theories or generalizations.
Is provisional and contextual: Conclusions derived are working hypotheses open to revision and heavily depend on the context and specific details of the situation under study.
Combines theory and empirical data: It is used to develop logical, grounded theories by integrating data analysis with theoretical reflection, particularly in qualitative research.
These ideas highlight abductive reasoning as a dynamic, imaginative, and context-sensitive approach that generates plausible explanations by iteratively linking empirical observations to theory."
My question 2: "Clarify the topic a bit more with reference to the following two research themes:
The reply: "Abductive reasoning in research can be clarified with reference to the two given research themes as follows:
For the Housing Studies theme on "impacts of negative equity in residential property on domestic violence in Shamshuipo in 2025":
Abductive reasoning starts with observing surprising or complex real-world phenomena such as a potential link between negative equity and domestic violence.
The researcher explores existing theories on housing stress, financial hardship, and social behavior, but remains open to new or modified explanations emerging during data collection.
The researcher iteratively moves between theory and empirical data (interviews, surveys, case studies) to develop plausible hypotheses explaining how negative equity may influence domestic violence locally.
The approach embraces the researcher's contextual knowledge and sensitivity to local social dynamics in Shamshuipo, facilitating original insights beyond pre-existing general theories.
For the MBA theme on "influence of Hong Kong stock market performance on office managerial staff's job engagement in banking sector in 2025":
Abduction begins with observing an unexpected or complex pattern between macroeconomic indicators (stock market fluctuations) and individual job engagement.
Existing management and behavioral theories provide initial interpretive frames, but the researcher is willing to adapt or challenge these based on empirical findings from surveys or interviews.
The iterative process allows the emergence of novel insights on how external economic factors impact psychological and behavioral outcomes in a specific occupational context.
The researcher's background and knowledge of Hong Kong’s financial environment and banking culture enrich the analysis and theory development.
In both cases, abductive reasoning helps integrate theory and empirical evidence via an iterative, context-sensitive process that encourages creative hypothesis generation and theory modification to explain complex, nuanced phenomena in their specific social and economic contexts."
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