HMDVA81
Assignment 4
Due 6 August 2025
,HMDVA81
Assignment 4
Due 6 August 2025
Question 1: Is this study typical of a quantitative, a qualitative, or a mixed-method
study? Give reasons for your answer.
Answer
The study is typical of a mixed-method research design because it deliberately
combines both quantitative and qualitative approaches to investigate the multifaceted
impact of remote work on employee well-being and productivity. This integration is not
incidental but methodologically intentional, aligning with established criteria for mixed-
method research.
Reasons for Classification
Multimodal Data Collection: Quantifying Behavior, Qualifying Experience
The study collects quantitative data through structured surveys using Likert scales to
measure variables such as hours worked, task completion rates, and stress levels. At
the same time, it employs qualitative methods like focus group discussions to explore
employees’ subjective experiences, such as perceptions of flexibility or feelings of
isolation. This dual approach aligns with mixed-method methodology, where both
measurable outcomes and contextual meanings are investigated.
Complementarity in Research Aims: From Numbers to Nuance
The research is designed to achieve both breadth and depth. Quantitative data yields
generalizable insights (e.g., percentage of employees reporting improved productivity),
while qualitative data provides explanatory depth (e.g., themes around digital autonomy
or trust in management). These are complementary objectives, where one method
addresses the “what” and the other investigates the “why,” in line with the framework
described by Teddlie and Tashakkori (2009).
, Methodological Integration: Converging Threads of Insight
A defining characteristic of mixed-method studies is the integration of findings. In this
case, survey results are not presented in isolation but are triangulated with qualitative
themes to reinforce or challenge interpretations. For example, employees who report
higher productivity quantitatively may also express satisfaction with flexible scheduling
in qualitative interviews. Such cross-validation enhances reliability and conceptual
depth.
Critical Analysis: Distinguishing from Single-Method Designs
This study goes beyond merely collecting two types of data. It demonstrates
methodological coherence through aligned research questions and integrated analysis.
Unlike a purely quantitative study that stops at statistical correlations, or a qualitative
study that relies solely on narrative interpretation, this approach draws upon the
strengths of both to build a comprehensive understanding. However, it also demands
rigorous alignment; if research questions, samples, or timing are mismatched, the
validity of the integration could be compromised.
Conclusion
The study meets the defining criteria of a mixed-method approach by purposefully
combining quantitative measurement and qualitative interpretation, aligning them with
research objectives, and synthesizing findings into a cohesive analysis. This design is
especially well-suited for studying complex organizational phenomena like remote work,
where both numerical trends and personal experiences are critical to understanding
impact.
Assignment 4
Due 6 August 2025
,HMDVA81
Assignment 4
Due 6 August 2025
Question 1: Is this study typical of a quantitative, a qualitative, or a mixed-method
study? Give reasons for your answer.
Answer
The study is typical of a mixed-method research design because it deliberately
combines both quantitative and qualitative approaches to investigate the multifaceted
impact of remote work on employee well-being and productivity. This integration is not
incidental but methodologically intentional, aligning with established criteria for mixed-
method research.
Reasons for Classification
Multimodal Data Collection: Quantifying Behavior, Qualifying Experience
The study collects quantitative data through structured surveys using Likert scales to
measure variables such as hours worked, task completion rates, and stress levels. At
the same time, it employs qualitative methods like focus group discussions to explore
employees’ subjective experiences, such as perceptions of flexibility or feelings of
isolation. This dual approach aligns with mixed-method methodology, where both
measurable outcomes and contextual meanings are investigated.
Complementarity in Research Aims: From Numbers to Nuance
The research is designed to achieve both breadth and depth. Quantitative data yields
generalizable insights (e.g., percentage of employees reporting improved productivity),
while qualitative data provides explanatory depth (e.g., themes around digital autonomy
or trust in management). These are complementary objectives, where one method
addresses the “what” and the other investigates the “why,” in line with the framework
described by Teddlie and Tashakkori (2009).
, Methodological Integration: Converging Threads of Insight
A defining characteristic of mixed-method studies is the integration of findings. In this
case, survey results are not presented in isolation but are triangulated with qualitative
themes to reinforce or challenge interpretations. For example, employees who report
higher productivity quantitatively may also express satisfaction with flexible scheduling
in qualitative interviews. Such cross-validation enhances reliability and conceptual
depth.
Critical Analysis: Distinguishing from Single-Method Designs
This study goes beyond merely collecting two types of data. It demonstrates
methodological coherence through aligned research questions and integrated analysis.
Unlike a purely quantitative study that stops at statistical correlations, or a qualitative
study that relies solely on narrative interpretation, this approach draws upon the
strengths of both to build a comprehensive understanding. However, it also demands
rigorous alignment; if research questions, samples, or timing are mismatched, the
validity of the integration could be compromised.
Conclusion
The study meets the defining criteria of a mixed-method approach by purposefully
combining quantitative measurement and qualitative interpretation, aligning them with
research objectives, and synthesizing findings into a cohesive analysis. This design is
especially well-suited for studying complex organizational phenomena like remote work,
where both numerical trends and personal experiences are critical to understanding
impact.
