multiple case study design the example of place marketing research

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Research Guides

Multiple Case Studies

Nadia Alqahtani and Pengtong Qu

Description

The case study approach is popular across disciplines in education, anthropology, sociology, psychology, medicine, law, and political science (Creswell, 2013). It is both a research method and a strategy (Creswell, 2013; Yin, 2017). In this type of research design, a case can be an individual, an event, or an entity, as determined by the research questions. There are two variants of the case study: the single-case study and the multiple-case study. The former design can be used to study and understand an unusual case, a critical case, a longitudinal case, or a revelatory case. On the other hand, a multiple-case study includes two or more cases or replications across the cases to investigate the same phenomena (Lewis-Beck, Bryman & Liao, 2003; Yin, 2017). …a multiple-case study includes two or more cases or replications across the cases to investigate the same phenomena

The difference between the single- and multiple-case study is the research design; however, they are within the same methodological framework (Yin, 2017). Multiple cases are selected so that “individual case studies either (a) predict similar results (a literal replication) or (b) predict contrasting results but for anticipatable reasons (a theoretical replication)” (p. 55). When the purpose of the study is to compare and replicate the findings, the multiple-case study produces more compelling evidence so that the study is considered more robust than the single-case study (Yin, 2017).

To write a multiple-case study, a summary of individual cases should be reported, and researchers need to draw cross-case conclusions and form a cross-case report (Yin, 2017). With evidence from multiple cases, researchers may have generalizable findings and develop theories (Lewis-Beck, Bryman & Liao, 2003).

Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). Los Angeles, CA: Sage.

Lewis-Beck, M., Bryman, A. E., & Liao, T. F. (2003). The Sage encyclopedia of social science research methods . Los Angeles, CA: Sage.

Yin, R. K. (2017). Case study research and applications: Design and methods . Los Angeles, CA: Sage.

Key Research Books and Articles on Multiple Case Study Methodology

Yin discusses how to decide if a case study should be used in research. Novice researchers can learn about research design, data collection, and data analysis of different types of case studies, as well as writing a case study report.

Chapter 2 introduces four major types of research design in case studies: holistic single-case design, embedded single-case design, holistic multiple-case design, and embedded multiple-case design. Novice researchers will learn about the definitions and characteristics of different designs. This chapter also teaches researchers how to examine and discuss the reliability and validity of the designs.

Creswell, J. W., & Poth, C. N. (2017). Qualitative inquiry and research design: Choosing among five approaches . Los Angeles, CA: Sage.

This book compares five different qualitative research designs: narrative research, phenomenology, grounded theory, ethnography, and case study. It compares the characteristics, data collection, data analysis and representation, validity, and writing-up procedures among five inquiry approaches using texts with tables. For each approach, the author introduced the definition, features, types, and procedures and contextualized these components in a study, which was conducted through the same method. Each chapter ends with a list of relevant readings of each inquiry approach.

This book invites readers to compare these five qualitative methods and see the value of each approach. Readers can consider which approach would serve for their research contexts and questions, as well as how to design their research and conduct the data analysis based on their choice of research method.

Günes, E., & Bahçivan, E. (2016). A multiple case study of preservice science teachers’ TPACK: Embedded in a comprehensive belief system. International Journal of Environmental and Science Education, 11 (15), 8040-8054.

In this article, the researchers showed the importance of using technological opportunities in improving the education process and how they enhanced the students’ learning in science education. The study examined the connection between “Technological Pedagogical Content Knowledge” (TPACK) and belief system in a science teaching context. The researchers used the multiple-case study to explore the effect of TPACK on the preservice science teachers’ (PST) beliefs on their TPACK level. The participants were three teachers with the low, medium, and high level of TPACK confidence. Content analysis was utilized to analyze the data, which were collected by individual semi-structured interviews with the participants about their lesson plans. The study first discussed each case, then compared features and relations across cases. The researchers found that there was a positive relationship between PST’s TPACK confidence and TPACK level; when PST had higher TPACK confidence, the participant had a higher competent TPACK level and vice versa.

Recent Dissertations Using Multiple Case Study Methodology

Milholland, E. S. (2015). A multiple case study of instructors utilizing Classroom Response Systems (CRS) to achieve pedagogical goals . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3706380)

The researcher of this study critiques the use of Classroom Responses Systems by five instructors who employed this program five years ago in their classrooms. The researcher conducted the multiple-case study methodology and categorized themes. He interviewed each instructor with questions about their initial pedagogical goals, the changes in pedagogy during teaching, and the teaching techniques individuals used while practicing the CRS. The researcher used the multiple-case study with five instructors. He found that all instructors changed their goals during employing CRS; they decided to reduce the time of lecturing and to spend more time engaging students in interactive activities. This study also demonstrated that CRS was useful for the instructors to achieve multiple learning goals; all the instructors provided examples of the positive aspect of implementing CRS in their classrooms.

Li, C. L. (2010). The emergence of fairy tale literacy: A multiple case study on promoting critical literacy of children through a juxtaposed reading of classic fairy tales and their contemporary disruptive variants . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3572104)

To explore how children’s development of critical literacy can be impacted by their reactions to fairy tales, the author conducted a multiple-case study with 4 cases, in which each child was a unit of analysis. Two Chinese immigrant children (a boy and a girl) and two American children (a boy and a girl) at the second or third grade were recruited in the study. The data were collected through interviews, discussions on fairy tales, and drawing pictures. The analysis was conducted within both individual cases and cross cases. Across four cases, the researcher found that the young children’s’ knowledge of traditional fairy tales was built upon mass-media based adaptations. The children believed that the representations on mass-media were the original stories, even though fairy tales are included in the elementary school curriculum. The author also found that introducing classic versions of fairy tales increased children’s knowledge in the genre’s origin, which would benefit their understanding of the genre. She argued that introducing fairy tales can be the first step to promote children’s development of critical literacy.

Asher, K. C. (2014). Mediating occupational socialization and occupational individuation in teacher education: A multiple case study of five elementary pre-service student teachers . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3671989)

This study portrayed five pre-service teachers’ teaching experience in their student teaching phase and explored how pre-service teachers mediate their occupational socialization with occupational individuation. The study used the multiple-case study design and recruited five pre-service teachers from a Midwestern university as five cases. Qualitative data were collected through interviews, classroom observations, and field notes. The author implemented the case study analysis and found five strategies that the participants used to mediate occupational socialization with occupational individuation. These strategies were: 1) hindering from practicing their beliefs, 2) mimicking the styles of supervising teachers, 3) teaching in the ways in alignment with school’s existing practice, 4) enacting their own ideas, and 5) integrating and balancing occupational socialization and occupational individuation. The study also provided recommendations and implications to policymakers and educators in teacher education so that pre-service teachers can be better supported.

Multiple Case Studies Copyright © 2019 by Nadia Alqahtani and Pengtong Qu is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Using Multiple Case Study Design and Thematic Analysis in NVivo to Analyze Value Co-Creation in Brand Alliances

• By: Ediz Edip Akçay
• Product: Sage Research Methods: Business
• Publisher: SAGE Publications Inc.
• Publication year: 2023
• Online pub date: March 21, 2023
• Discipline: Business and Management , Marketing
• Methods: Case study research , Thematic analysis , NVivo
• DOI: https:// doi. org/10.4135/9781529669305
• Keywords: alliances , branding , capabilities , competitive advantage , software Show all Show less
• Online ISBN: 9781529669305 Copyright: © 2023 SAGE Publications Ltd More information Less information

Multiple case study design is a qualitative approach that can be used to investigate a phenomenon in its real-world context. It allows the researcher to start with theory to develop research questions and explore them in different cases. While there are several approaches to analyzing findings in multiple case study designs, a six-phase approach to reflexive thematic analysis is a systematic way to evaluate the results. In this case study, readers will learn how to overcome the challenges related to data collection and analysis in a multiple case study design. The practical recommendations for choosing the participants will be discussed. Moreover, the application of reflexive thematic analysis in NVivo will be explored.

Learning Outcomes

By the end of this case study, readers should be able to:

• Explain how multiple case study design is used in qualitative analysis
• Employ reflexive thematic analysis for qualitative analysis using NVivo
• Assess the challenges in multiple case study design

Project Overview and Context

Research background.

Brand alliance is an increasingly popular business strategy to achieve a competitive advantage, which is defined as a marketing collaboration where two or more brands come together to form an alliance for a short or long period of time ( Yan & Cao, 2017 ). My professional experience in a company that facilitates brand alliances between companies from different product categories inspired me to develop my Ph.D. research around this topic. My previous research in the branding field helped me identify gaps related to value co-creation during brand alliances in a business-to-business (B2B) setting.

I needed to have a closer look at the topic to explore insights on how the value is co-created in brand alliances. This led to the choice of a qualitative research method, namely a multiple case study design. A multiple case study design enables the investigation of the selected phenomenon (i.e. cross-category brand alliance in this research context) in its natural setting ( Bonoma, 1985 ). A cross-category brand alliance occurs when brands from different product categories form a brand alliance ( Smarandescu et al., 2013 ). Considering the lack of research on the topic in an emerging market context, I used a convenience and purposive sampling approach to choose cases from my existing professional network in Turkey.

Research Aim and Objectives

There were several studies ( Decker & Baade, 2016 ; Smarandescu et al., 2013 ) that investigated brand alliances from the customer perspective using a quantitative approach to analyze how customers perceive the brands when they are in an alliance. However, the business side of brand alliances has been scarcely researched, making it difficult to understand how brands co-create value and what types of value they co-create. Therefore, my research aimed to investigate the marketing resources and capabilities in relation to alliance outcomes in cross-category brand alliances.

I investigated the value co-creation process during cross-category brand alliances to map the marketing resources and capabilities utilized by the partner brands. Furthermore, I identified the types of values co-created in these cross-category brand alliances. The unit of analysis in the research is the dyadic relationship between alliance partner brands. Underpinning my exploration of cross-category brand alliances were the resource-based view (RBV) and service-dominant (S-D) logic. RBV claims that the internal resources of a firm are the sources of the firm’s sustained competitive advantage. To achieve sustained competitive advantage, a firm should have valuable, rare, inimitable, and non-substitutable (VRIN) resources( Kraaijenbrink et al., 2010 ). S-D logic, introduced by Vargo and Lusch in 2004, suggests that marketing activity is better explained in terms of service-for-service exchange than in terms of goods-for-goods or goods-for-money exchange. Moreover, value is not created by one stakeholder but is co-created by the stakeholders ( Vargo & Lusch, 2017 ).

I collected data through a qualitative approach, conducting semi-structured interviews with the marketing managers of the brands in the chosen cases. I analyzed the data using thematic analysis in NVivo and proposed a theoretical framework to depict the relations between partner brands' resources and capabilities and cross-category brand alliance outcomes during the value co-creation process.

The aim of the research was to investigate which marketing resources and capabilities are in relation to alliance outcomes in cross-category brand alliances. The value co-creation process during the cross-category brand alliances was investigated to map the marketing resources and capabilities utilized by partner brands. Furthermore, the types of values co-created in the cross-category brand alliances were identified.

After analyzing the data using thematic analysis in NVivo, a theoretical framework was proposed to depict the relations of partner brands’ resources and capabilities with cross-category brand alliance outcomes during the value co-creation process. Given the increasing number of brand alliances in the recent years and my experience in the field, this topic was worth exploring for my Ph.D. research.

Section Summary

• Brand alliance is an increasingly popular business strategy to achieve a competitive advantage.
• There are rare studies that investigated the value co-creation process in brand alliances from a business-to-business perspective.
• The focus of the research project was investigating which marketing resources and capabilities are utilized in cross-category brand alliances.

Research Design

In the research, I aimed to explore the value co-creation process in brand alliances by understanding the experiences of the people involved in the process, which qualitative research enabled through an interpretive approach ( Jackson et al., 2007 ).

In business-to-business research, it is difficult to set up experimental studies, and studies are mostly based on simulated business organizations. However, case study research allows researchers to investigate the real-world businesses by analyzing the context and processes involved in the researched phenomenon ( Johnston et al., 1999 ). The case study method “explores a real-life, contemporary bounded system (a case) or multiple bounded systems (cases) over time, through detailed, in-depth data collection involving multiple sources of information… and reports a case description and case themes( Creswell & Poth, 2016, p. 97 ).” Therefore, I applied a case study approach to investigate brand alliances in their natural setting. To understand whether the findings were replicated in different cases, I used a multiple case study design as suggested by Yin (2011) . In a multiple case study design, the research includes more than one single case. The researcher investigates multiple cases to find out the differences and similarities between the cases. Furthermore, the analysis can be made within each case and across cases ( Gustafsson, 2017 ). Since I was investigating cross-category brand alliances, I aimed to choose cases from different product categories.

After deciding on the cases, I started to collect information about the cases from public sources such as company websites, industry reports, and social media accounts to have background information about the brand alliances they formed. However, this secondary data was not enough to enable deep insights into how value is co-created in the chosen cases. I decided to conduct semi-structured interviews not only with the marketing managers of the cases, but also with the marketing managers of the partner brands of the cases, who formed brand alliances with the case brands. On some occasions, there were also brand alliances between the cases, which provided additional insights about the value co-creation processes.

To develop the interview guide, I identified the main themes and subthemes after the literature review phase of the study. This is an important distinction between the ethnographic approach and the case study method: there is a need to consult theory in the case study method before collecting data ( Johnston et al., 1999 ). For each subtheme, I adapted questions from past studies to use in the interview guide. The interviews were planned as semi-structured to have the flexibility to ask additional questions. It was also critical to ensure all the questions were covered to achieve consistent analysis of cases.

While the interview guide was prepared in English, the native language of potential participants was another language, namely Turkish. Some of the cases were international companies that employed people with multilingual skills. However, language was still a potential barrier for participants who did not know English or who did not feel comfortable talking in a language other than their native one. Therefore, the questions were translated and back-translated by expert native speakers. I conducted a pilot interview to check the suitability and understandability of the questions. Some extra questions or words were removed and added to improve the interview guide after the pilot interview. I used the revised interview guide in further interviews with research participants. All the interviews were conducted in a face-to-face meeting environment and audio recorded with the consent of the participants. I also took notes about the visual cues of the participants during the interviews, which provided additional insights about the themes.

After the data collection, I first transcribed the interviews by listening to the audio recordings. After the transcription, the transcribed data, which were in the native language of the participants, were translated and back-translated by expert native speakers to ensure the meaning was preserved.

Once the translation and transcription of all interviews were completed, I had a vast amount of data to analyze. In addition to the interviews, I had secondary data about the cases and my observation notes during the interviews. I decided to analyze the data using the thematic analysis method and checked suitable tools to assist in this process. Thematic analysis is a useful qualitative research method for identifying, analyzing, and reporting patterns in data ( Braun & Clarke, 2006 ). Among the alternative qualitative data analysis tools, I chose NVivo considering the training opportunities I had during my Ph.D. degree. During the training, I focused on learning the steps of thematic analysis in NVivo. I used the pilot interview data to test and apply my learnings in NVivo, which gave me hands-on experience while learning how to use the tool.

The next step was choosing the thematic analysis approach to analyse the data. There are mainly three different approaches to thematic analysis which are reflexive (1) thematic analysis, (2) coding reliability thematic analysis, and (3) codebook thematic analysis. While coding reliability and codebook approaches adopt the use of a structured codebook, the reflexive approach is an accessible and flexible approach to qualitative data analysis which enables the researcher to identify themes in the collected data ( Byrne, 2022 ). After checking these different approaches to thematic analysis, I found that the six-phase reflexive thematic analysis approach developed by Braun and Clarke (2006) would be the most suitable to apply in NVivo. The six-phases they proposed are (1) familiarizing yourself with the data, (2) generating initial codes, (3) searching for themes, (4) reviewing themes, (5) defining and naming themes, and (6) producing the report. Although the names of the phases were slightly changed in their latest article ( Braun & Clarke, 2006 ), the authors established guidelines for reflexive thematic analysis which can be applied in NVivo.

By applying this approach, I first familiarized myself with the data during the transcription process. NVivo has different ways of coding such as drag-and-drop coding, right-click coding, and quick coding. It was helpful to use NVivo for coding to find commonalities and differences between the cases as the structured view presented the codes in a user-friendly dashboard. Still, it was my responsibility to generate the codes as I didn’t use the auto-coding option in NVivo. The initial codes helped me identify potential themes, which were later reviewed against the themes and subthemes of the interview guide. I created a different folder for new themes in NVivo to distinguish between the ones those informed by past studies and those that were constructed during the analysis. At this phase, it was important to develop the linkages between the themes and research questions. Later, I used the themes and subthemes to develop summary tables in the findings and discussion chapters of my Ph.D. thesis.

• The case study method is useful in a business-to-business context, as the researcher can investigate the real-world businesses by analyzing the context and processes involved in the researched phenomenon.
• Multiple case study design allows the researcher to understand if the findings are replicated in different settings.
• The six-phase approach to thematic analysis developed by Braun and Clarke (2006) is a systematic, reflexive thematic analysis method to analyze qualitative data in NVivo.

Research Practicalities

Because this was Ph.D. research, I had a limited time to complete the target number of interviews about the chosen cases. Although I intended to interview a total of 20 people in about five cases, this seemed impractical after I started contacting potential participants for interviews. The challenge was to arrange meetings with potential participants, who were busy marketing managers of the brands and who conducted brand alliances in the cases. An additional challenge was the changing roles and jobs of potential participants. Moreover, I was working full-time with a busy schedule at my workplace. I was doing a part-time Ph.D., which meant I needed to work on my Ph.D. research after my office hours or on weekends.

After realizing the potential challenges with the interview arrangements, I decided to start with my existing network before reaching out to other potential participants. Furthermore, I started to contact as many potential participants about the cases as I could to reach the target number of interviews. Eventually, I ended up with 11 interviews from 10 different brands for five cases, which is an acceptable number for a qualitative study according to IPA (Interpretative Phenomenological Analysis) guidelines ( Robinson, 2014 ).

During the interviews, it was critical to build rapport with the participant to make them feel comfortable before answering the questions. While I had previous encounters with some participants due to my professional experience, it was my first meeting with most of the participants for the interview. As they were devoting at least one hour of their busy schedule, they wanted to understand what the research was about and how it would be used. Moreover, they were sharing information about their company, which could be confidential or sensitive if shared with the public or with competitors.

To overcome these issues, I shared a participant information sheet with the potential participants before each interview to provide detailed information about the research, data protection and process measures, and their privacy. I also encouraged them to ask additional questions if anything was not clear before the interview. When they accepted to arrange an interview, I shared a participant agreement form with them to obtain their consent for an audio recording of the interview, and the use of their anonymized data for research purposes. They were also granted permission to withdraw from the research during or after the interview unless their anonymized data had already been used in the analysis.

Some participants were people I knew due to our professional relationships. When you are interviewing people you know, there are potential issues such as establishing trust and rapport, role conflict, and self-disclosure ( McConnell‐Henry et al., 2010 ). While having had a previous encounter sped up the process of building rapport, I needed to build the trust of the participants that I did not have any “hidden agenda” related to our professional roles. I clarified my role as a researcher at the start of the interview who aimed to collect data for Ph.D. research. Even though the confidentiality and anonymity of data were detailed in the participant agreement form, I explained the steps by which these were assured in the research, so as to establish the trust of the participants. The potential issues in interviewing people I knew were related not only to the information the participants shared, but also to the possibility of self-disclosure. To prevent over disclosure, I only asked questions based on the interview guide or based on the information shared by the participants during the interview.

Although the personal information about the participants was not used in the research, there was a need for further anonymization. The research was about real-life cross-category brand alliances, and it wouldn’t be difficult for someone living in Turkey to guess the companies mentioned in the research. To protect the identities of the research participants, their job roles and companies were anonymized in the study. As an ethical issue, anonymization should be considered carefully throughout the research process when there is a risk of sensitive, confidential information disclosure ( Clark, 2006 ). Letters from the Greek alphabet (e.g. α, β) were used to anonymize the company names. Instead of the company names, pseudonyms such as α1, β1 were used. The job roles of the participants were mentioned as a generalized roles for all participants (i.e. marketing manager of α1, marketing manager of β1). After the data analysis, any confidential or sensitive information was removed from the quotes that were used in the final version of my Ph.D. thesis.

As mentioned in the research design section, the interview guide was translated from English to Turkish by expert native speakers. Still, some participants struggled to understand the concepts in some of the questions. Thanks to my experience in the field, I provided further information about the meanings of the concepts to ensure the participants were providing the insights that the research aimed for. For translated interview guides that involve technical terms or concepts, I suggest that researchers have a note of definitions in the original language and the language of translation. The researcher can use the note of definitions to support the participant when they struggle to understand the words in the questions. Having a standard note of definitions for all interviews would also ensure consistency between the interviews.

On some occasions, some participants started to talk about a topic that was not part of the themes of the interview guide questions. Considering the participants’ time constraints, I managed to ask transition questions from the interview guide to bring the interview back on track without disturbing the flow of the interview. Although the topics they introduced were not always relevant to the themes, they were still helpful in enabling additional insights about the value co-creation processes in the brand alliances.

As the interviews were based on the previous brand alliances of the chosen cases, there were mentions of both positive and negative experiences that happened during the brand alliances. While the interviews were conducted separately on a one-to-one basis, it was important to preserve the confidentiality of the shared information. To ensure transparency of data collection, I needed to include one transcript when I submitted the final version of my Ph.D. thesis. After checking the transcripts, I chose the transcript that had a more neutral tone in the details to include in the appendix of the thesis.

When I started using NVivo as the data analysis tool for thematic analysis, I realized that it still takes a lot of time to code (creating nodes in NVivo 11) the data. In addition, I needed to ensure consistency between the transcripts that were originally in English and those that had been translated into English. To remove ambiguity about the order of analysis between the transcriptions, I contacted the NVivo instructor to get their ideas. They suggested starting with the English versions and moving to the translated versions while coding the data. This allowed me to correct any misunderstandings in the translation of transcripts.

• Arranging interviews with research participants in a business-to-business context can take a long time due to the busy schedules of the potential participants.
• It is not only the personal information but also the company information that should be anonymized to protect the identity of the participants.
• A pilot interview is useful to revise and finalize the interview guide, especially when the interview guide is translated into a different language.

Method in Action

Even with a structured and dedicated tool like NVivo, it took me around six months to complete the thematic analysis process, from the initial coding phase to the final report development phase. This was partly due to my personal time constraints, as I had a full-time job. Additionally, I cannot even imagine the amount of time I would have spent even on coding alone without the use of a software like NVivo. Still, anyone using NVivo should accept that there will still be a lot of time-consuming work involved in creating cases and codes.

Even though I had themes and subthemes in the interview guide that were informed by literature, I realized that the code categories (nodes in NVivo 11) I generated in NVivo did not completely match those in the interview guide. After reading more about the thematic analysis stages, I realized that I need to create codes at their latent level of meaning, rather than their semantic meaning (Braun and Clarke cited in Cooper et al., 2012 ).

At the initial coding phase of thematic analysis on NVivo, I created 20 main nodes, with several nodes connected to the main nodes. In total, 2500 pieces of content were coded among 115 thousand words at the initial coding phase. NVivo has a user-friendly dashboard that summarizes the number of connections to the interviews and sources. You can also easily see the coded pieces of content by double-clicking on the codes. This feature allows you to identify the relevant sections of the cases you have coded.

After evaluating the initial codes that were connected to the sources, I realized that some important codes were not connected to certain cases. I decided to revisit the interviews to understand why insights related to some codes were not mentioned. One of my objectives was to understand whether the findings were replicated in different cases. It wouldn’t be possible to reach this objective without the missing codes in some cases. That’s why I decided to ask additional questions to the participants of the cases which had missing insights. As it wasn’t easy to arrange new face-to-face meetings with the marketing managers, I shared the questions via email and explained the details through phone calls. After receiving the answers from the participants, I added them to the relevant cases in NVivo and coded them using the same approach as in the initial interviews.

When I had finished coding all the interviews with the supportive questions, I moved to the theme-searching phase. Braun and Clarke (2006, p.82) state that a theme “captures something important about the data in relation to the research question and represents some level of patterned response or meaning within the data set.” They also point out that themes don’t simply emerge; rather, the researcher is constructing or generating them while working with the data. Following this approach, I started to look for relations to my research questions, which aimed to identify the marketing resources and capabilities that had been utilized, and the types of values that had been co-created in the brand alliances. At the end of this phase, I generated a codebook in NVivo to identify which themes were related to which cases.

After the initial construction of themes, I moved to the fourth phase of the approach, which was reviewing themes. I shared the codebook with my supervisors to get their feedback on the initial themes. Based on their feedback, I revisited the studies which guided me in developing the themes and subthemes in the interview guide. This led me to the next phase, which was that of defining and naming themes. To ensure the themes were in line with the research questions and objectives, I realized I needed to revise the names of some themes while merging others.

At the final stage of the reflexive thematic analysis, which involved producing the report in my research, I began writing the findings and discussion chapters of my Ph.D. thesis. I used the output from the thematic analysis to name the headings and subheadings of my finding chapter, to develop summary tables related to themes. I used relevant quotes from the interviews by clicking on the theme and finding them on NVivo. Furthermore, I developed frameworks based on the thematic analysis to depict the relations of partner brands’ resources and capabilities with the cross-category brand alliance outcomes during the value co-creation process, which was one of the objectives of my Ph.D. research.

• Qualitative analysis tools such as NVivo help the researcher with a structured approach for coding and developing themes in thematic analysis.
• The themes do not emerge in the data, the researcher needs to construct the themes while working with the data.
• The researcher can use NVivo to construct themes in the data by analyzing the codes and by evaluating the relation of codes to the research questions.

Practical Lessons Learned

As I aimed to investigate cross-category brand alliances in my research, a multiple case study design was the most suitable approach to compare and contrast cases from different product categories. Moreover, analyzing multiple cases allowed me to validate insights that occurred in different categories. However, working with multiple cases increased the difficulty of finding interview participants for each case. To improve this aspect, I would recommend identifying as many cases as possible at the initial stage, instead of focusing on a limited number of cases. After that, the researcher can contact all the potential participants in the identified cases and narrow down the list to involve the cases in that the participants accept the interview request. This approach would shorten the time the researcher spends reaching the number of interviews needed for data collection.

While I started with a purposive sampling approach to choose the participants in the cases, it was a correct decision to include convenience sampling when I struggled to arrange meetings with the potential participants. Contacting the potential participants in my network sped up the process of arranging initial interviews. I suggest that researchers reach as many potential participants as they can before starting their data collection if they are planning to conduct interviews.

Even though I chose thematic analysis as the data analysis method, I struggled to find the correct approach to apply it. Many articles had vague explanations for generating codes and moving to the theme-searching stage. However, Braun and Clarke’s (2006) six-phase approach to reflexive thematic analysis provided a systematic approach to analyzing the data. Based on my experience applying this reflexive thematic analysis approach in multiple case study designs, I would suggest that researchers spend more time in the first phase, which is that of familiarizing yourself with the data. When you have familiarised yourself with the data you collected, making linkages between the cases becomes easier in the further phases of generating initial codes and searching for themes.

I was lucky to complete the interviews long before the pandemic, which gave me the opportunity to conduct them in a face-to-face environment. Having face-to-face meetings provided additional insights into the participants’ reactions to the questions, and their approach to answering them. In addition, it was easier to build rapport after meeting in a place where they were accustomed to having meetings. However, conducting interviews in an online environment such as Zoom could provide the opportunity to transcribe the interviews automatically. Later, I learned that there were tools such as Google Cloud’s speech-to-text and Transcribe software, which are dedicated audio-transcription tools. I would recommend trying audio-transcription tools to save time in transcribing the data if the researcher has a time constraint and has the budget to pay for their service. Still, the accuracy levels of such tools should be tested before making the decision to invest money and time in the tools. Moreover, transcribing the data yourself would contribute more to the “familiarising yourself with the data” phase of the thematic analysis.

Despite attending comprehensive training about NVivo, I didn’t have enough time to try and learn all the features of the software. My main focus was on learning NVivo to apply thematic analysis to the data I had started to collect. After starting to use NVivo to analyze the data, I watched many tutorial videos about NVivo’s other features. In one of them, I learned that NVivo could also be used in the literature review stage of the research by importing the articles to the software. It has features that allow you to highlight the sections of the articles and take notes about them, which can be useful for later reference. I found out that using NVivo for the literature review stage of research could potentially enhance it. Additionally, the notes on the articles would be useful for linking them to the codes and themes generated in the thematic analysis stage. NVivo also allows users to import audio files for analysis, which is another feature I would suggest researchers learn and try if they collect audio data for analysis.

Although NVivo software is dedicated to qualitative analysis, it requires the researcher to manually work on the data to generate codes and develop themes. While NVivo also has auto-coding features, it has some limitations. There are other automated qualitative analysis tools, such as Leximancer and ATLAS.ti, that researchers use for thematic analysis. Although I had the opportunity to receive training about NVivo, I didn’t have much time nor a sufficient budget to look for more alternatives while choosing an analysis software. However, I would suggest researchers to explore more qualitative analysis tools to analyze the data. Using a more sophisticated automated coding tool could provide additional insights to support the manual coding process for researchers.

• The researcher should prepare an extensive list of potential cases and participants in a multiple case study design before choosing the cases to ease the process of sampling.
• An audio-transcription tool can be helpful to shorten the time between data collection and analysis if the researcher has a time constraint
• Learning how to use the analysis software should start as soon as possible after the researcher decides 0n the analytical method.

Multiple case study design is an effective qualitative research approach for investigating a chosen phenomenon in its natural setting. It provides the opportunity to replicate the research in different contexts by collecting data through interviews, observations, focus groups, and secondary research. While qualitative research tends to involve subjective interpretations in its essence, thematic analysis can improve the rigor of the study in a multiple case study design. I benefited from using the six-phase approach to reflexive thematic analysis ( Braun & Clarke, 2006 ) to achieve the objectives of my Ph.D. research. This approach has systematic and structured phases which can be implemented using NVivo as the tool to support thematic analysis. The approach also enhanced the rigor and transparency of my methodology by setting the guidelines I followed in my data analysis.

For studies in a business-to-business context, thematic analysis using a multiple case study design would be especially useful. This type of analysis allows to a researcher to explore relationships and processes in the business environment within their specific contexts. Furthermore, the insights and recommendations developed as an output of the case study method would have the potential to influence marketing managers, for example when the case findings are used for training purposes. The case study evidence is seen as more persuasive than quantitative findings because of its vivid, personal, and concrete nature ( Johnston et al., 1999 ) However, a researcher who is investigating a business-to-consumer phenomenon might choose to use a quantitative approach to test the relationships between variables using a larger sample.

For a researcher who decides to apply thematic analysis, I would suggest using a supportive software such as NVivo, which eases the process of coding and developing themes. Although I did not use the auto-coding option in NVivo, the software helped me identify the missing pieces in the cases at the initial coding phase and develop the main themes and subthemes in the later phases of the thematic analysis. To summarise, thematic analysis using NVivo in a multiple casestudy designs is an efficient qualitative research method, especially for researchers who investigate a phenomenon in a business-to-business setting.

Classroom Discussion Questions

• 1. Why is a case study design more suitable to investigate a phenomenon in a business-to-business context?
• 2. How would you ensure the anonymity of the participants in qualitative research in a business-to-business context?
• 3. What would be the benefit of manual transcription of interviews in six-phase approach to thematic analysis?

Multiple-Choice Quiz Questions

1. Which is not a reason to anonymize the company names in the data analysis?

Incorrect Answer

Feedback: This is not the correct answer. The correct answer is B.

Correct Answer

Feedback: Well done, correct answer

2. Which one is a distinction between the case study method and ethnographic research?

Feedback: This is not the correct answer. The correct answer is C.

3. Which qualitative analysis software generates the topic models automatically?

Feedback: This is not the correct answer. The correct answer is A.

4. Which thematic analysis approach does NOT adopt the use of a structured codebook?

5. Which one is the first phase in Braun and Clarke’s six-phase approach to reflexive thematic analysis?

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Volume 17, issue 1, March 2021

Special section: future of place branding.

• Mihalis Kavaratzis
• Magdalena Florek

9 articles in this issue

Advocates or adversaries? Explicating within-border foreign publics’ role in shaping soft power through megaphoning and echoing

• Kelly Vibber
• Jeong-Nam Kim
• Content type: Original Article
• Published: 23 November 2019
• Pages: 1 - 18

The anatomy of place branding: relating place transformation to community identity

• Eko Nursanty
• Published: 17 December 2019
• Pages: 19 - 35

The role of place in city centre retailing

• Lisa Källström
• Simon Persson
• Jakob Westergren
• Published: 30 December 2019
• Pages: 36 - 49

Multiple case study design: the example of place marketing research

• Marek Ćwiklicki
• Kamila Pilch
• Published: 05 February 2020
• Pages: 50 - 62

Special Section: The future of place branding

• Content type: Editorial
• Published: 11 January 2021
• Pages: 63 - 64

Public value-driven place branding. The way forward?

• Marta Hereźniak
• Justyna Anders-Morawska
• Published: 06 October 2020
• Pages: 65 - 77

Differentiation of regional attractiveness for gaining talents in the context of place branding theory

• Yauheniya Barkun
• Ewa Glińska
• Katarzyna Dębkowska
• Published: 27 September 2020
• Pages: 78 - 92

Place branding (r)evolution: the management of the smart city’s brand

• Magdalena Grebosz-Krawczyk
• Published: 22 April 2020
• Pages: 93 - 104

Crossroads between city diplomacy and city branding towards the future: case study on the film cities at UNESCO Creative Cities Network

• Niedja de Andrade e Silva Forte dos Santos
• Published: 04 July 2020
• Pages: 105 - 125

For authors

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From David E. Gray \(2014\). Doing Research in the Real World \(3rd ed.\) London, UK: Sage.