ONLY MIXED METHODS RESEARCH

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Introduction

“Everything about nothing” and “nothing about everything” could be the drastic characterization of quantitative and qualitative research methods, respectively. The former reflects a typical narrow topical focus but extensive empirical sample and the latter extreme describes a usually limited empirical base but a wide topical focus. Combining them could be a good idea and so, Mixed Methods Research (MMR) was born (cf. Campbell and Fiske, 1959). 

What is Mixed Methods Research?  

 Although there are several definitions of MMR, a general, yet concise, description is that MMR endorses an approach in which the researcher collects, analyses and interprets both quantitative and qualitative data, integrates the two approaches and then draws meta-inferences that provide additional insights not possible from each approach alone (Cresswell, 2015). Hence, MMR should generally not be confused with ‘‘multiple methods’’ research where various forms of qualitative data (from, e.g., interviews and participant observations) or different quantitative data (from, e.g., surveys and experiments) are collected and analysed. 

Rationales for Mixed Methods Research 

MMR combines the strengths of quantitative and qualitative methodologies, offering several potential advantages to researchers. One important rationale for MMR is triangulation, where results from quantitative and qualitative approaches may be used to corroborate one another, thereby enhancing confidence in the findings (Doyle et al., 2009; 2016). Additionally, MMR facilitates expansion by enabling researchers to explain quantitative results through qualitative insights, providing richer contextual understanding. 

MMR is also particularly useful in exploratory studies, where qualitative data can guide the development of instruments or help identify variables and formulate hypotheses for further quantitative analysis. Moreover, by integrating both methodologies, MMR allows for a more comprehensive understanding of phenomena, addressing gaps that may arise when using either method independently. Another benefit lies in offsetting each methodology’s limitations by leveraging the other’s strengths (Creswell, 2015). Finally, MMR can illustrate quantitative findings with qualitative data, creating a more nuanced interpretation of results (Bryman, 2006). 

Examples of Mixed Methods Research Designs 

A variety of designs are available within MMR, offering researchers flexibility in addressing different research questions. While some designs may appear unnecessarily complex, three basic designs can be seen as examples of how to use MMR for academic investigations: convergent, explanatory sequential, and exploratory sequential (Doyle et al., 2016; Harrison et al., 2020). Although only examples of possible designs, they are adaptable to diverse research contexts and can address various methodological and analytical needs. 

The Convergent Design 

The convergent design is frequently employed when the goal is to achieve a comprehensive understanding of phenomena. In this approach, quantitative and qualitative data are collected concurrently, with findings analyzed independently before being merged to draw overarching conclusions or meta-inferences (Creswell and Plano Clark, 2011). This design is efficient as it allows data collection to occur simultaneously, which is particularly valuable when access to the study population is time-sensitive. By integrating independent results, the convergent design can provide a well-rounded perspective on the research question (Doyle, 2015). 

The Explanatory Sequential Design 

The explanatory sequential design typically begins with a quantitative phase, where data are collected and analyzed to identify trends or relationships. This phase is followed by a qualitative phase, designed to explore and explain the quantitative findings in greater depth. The sequential nature of this design allows for targeted qualitative data collection informed by the initial quantitative results, making it straightforward to implement (Creswell and Plano Clark, 2011). However, this design may face challenges if the original population becomes inaccessible over time, especially when the initial quantitative phase is protracted. 

The Exploratory Sequential Design 

In contrast, the exploratory sequential design begins with qualitative data collection and analysis, which informs the subsequent quantitative phase. This approach is particularly useful for developing new instruments, identifying variables, or generating hypotheses for further testing (Creswell and Plano Clark, 2011). The quantitative phase serves to validate or generalize the findings from the qualitative stage to a broader population. Like the explanatory sequential design, this approach benefits from its clear structure but may encounter similar issues regarding participant accessibility over time.  

It is important to match the choice of MMR design to the rationale for the study. Researchers are encouraged to select the design that aligns with their research objectives, data collection constraints, and analytical goals to ensure coherence and integration throughout the study. With this SI, we would like to promote methodological inclusivity within the MMR frame of reference and welcome any such manuscripts suitable for publication in JGM.   

List of Topic Areas

• MMR combines the strengths of quantitative and qualitative methodologies
• One important rationale for MMR is triangulation, where results from quantitative and qualitative approaches may be used to corroborate one another
• Additionally, MMR facilitates expansion by enabling researchers to explain quantitative results through qualitative insights, providing richer contextual understanding.
• MMR is also particularly useful in exploratory studies, where qualitative data can guide the development of instruments or help identify variables and formulate hypotheses for further quantitative analysis.
• Moreover, by integrating both methodologies, MMR allows for a more comprehensive understanding of phenomena, addressing gaps that may arise when using either method independently.

Topic/Area of MMR 

There must be a match between the submitted MMR manuscript and what JGM publishes, i.e. research on global employees who cross borders physically and/or virtually for work purposes. These include corporate and self-initiated expatriates, as well as other forms of global employees, such as frequent international business travellers, short-term assignees, and migrant workers. For more details on the remit of JGM, please visit: 
https://emeraldgrouppublishing.com/journal/jgm?id=jgm 

Submissions Information

To be considered for the Special Issue, manuscripts must be submitted no later than October 1, 2025, 5:00 pm Central European Time. Manuscripts submitted earlier will not be processed until the deadline. Submitted papers will undergo a double-blind peer review process and will be evaluated by at least two reviewers and the Guest Editorial Team (GET). The final acceptance is dependent on the review team’s judgments of the paper’s contribution to the special issue topic.  Please remove any information that may potentially reveal the identity of the authors to the reviewers. Once accepted, manuscripts will immediately be published online as citable in-print articles. The complete SI publication is planned for September 2026. For inquiries regarding the special issue, please contact Professor Jan Selmer at [email protected]

Submissions are made using ScholarOne Manuscripts. Registration and access are available here.
Author guidelines must be strictly followed. Please see here.
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”. 
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key Deadlines

Submission deadline: October 1, 2025. 
Accepted manuscripts will immediately be published online as citable in-print articles. 
SI publication: September 2026 

Guest Editors

Jan Selmer, Aarhus University, Denmark 
Jakob Lauring, Aarhus University, Denmark  
Yu-Ping Chen, Concordia University, Canada  
Mihaela Dimitrova, WU Vienna, Austria 
David S. A. Guttormsen, University of South-Eastern Norway, Norway  
Luisa Helena Pinto, University of Porto, Portugal  
Margaret Shaffer, University of Oklahoma, USA  
Sebastian Stoermer, Technische Universität Dresden, Germany 

References

• Bryman A (2006) Integrating quantitative and qualitative research: How is it done? Qualitative Research, 6(1): 97–113. 
• Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105.  
• Creswell, J. W. (2015). A Concise Introduction to Mixed Methods Research. Thousand Oakes, CA.: Sage Publications. 
• Creswell, J.W. and Plano Clark, V.L. (2011). Designing and Conducting Mixed Methods Research, 2nd edn. Thousand Oaks, CA: Sage Publications. 
• Doyle, L. (2015) Mixed methods. In: Henly, S.J. (ed.) Routledge International Handbook of Advanced Quantitative Methods in Nursing Research. Abingdon: Routledge, pp. 411–422. 
• Doyle, L., Brady, A. M., & Byrne, G. (2009). An overview of mixed methods research. Journal of Research in Nursing, 14(2), 175-185. 
• Doyle, L., Brady, A. M., & Byrne, G. (2016). An overview of mixed methods research–revisited. Journal of Research in Nursing, 21(8), 623-635. 
• Harrison, R. L., Reilly, T. M., & Creswell, J. W. (2020). Methodological rigor in mixed methods: An application in management studies. Journal of Mixed Methods Research, 14(4), 473-495.