Qualitative Research Methods - Lernzettel PDF

Introduction to advanced qualitative research methods Differences between quantitative and qualitative research Methods All research based on underlying assumptions Different academic communities share different assumptions = different philosophical positions Philosophy of sc...

Introduction to advanced qualitative research methods Differences between quantitative and qualitative research Methods All research based on underlying assumptions Different academic communities share different assumptions = different philosophical positions Philosophy of science: 1. Why – to what ends- do we engage in scientific research (level of ends) 2. Which methodological tools do we use to acquire scientific knowledge? (Level of means) Level of ends for qualitative research: o Social reality is socially constructed = mediated through systems of signs and representation (language, meaning, symbols, culture) o Researcher has to address what is meaningful to people in situation studied o Researcher’s perspective and interpretative nature of social reality matters Why qualitative research? o Uncover unexpected and explore new avenues o To expand develop new theory or expand previously developed theory o To capture inner events, backstage, insider perspective o To bridge the gulf between research and practice o To „rehumanize“ management and organization research and theory Deduction vs. induction in theory-use Level of means of qualitative research “The label qualitative methods […] is at best an umbrella term covering an array of interpretive techniques which seek to describe, decode, translate, and otherwise come to terms with the meaning, not the frequency, of certain more or less naturally occurring phenomena in the social world.” (Van Maanen, 1979, p. 520; own emphazis) Current standings of qualitative research in management studies o 20% of AMJ articles o Many best paper prizes awarded to qualitative studies o Challenges: Gaining access: It takes very long to gain access to your field, gather the data, make sense of your data, and write a qualitative piece Overcoming preconceptions: It is harder to publish a qualitative study as qualitative researchers are more scrutinized than their colleagues doing quant. Reading: "Reclaiming Qualitative Methods for Organizational Research: A Preface" by John Van Maanen: Definition of Qualitative Methods: umbrella term for various interpretive techniques aimed at understanding the meaning of social phenomena rather than their frequency. Data Collection: Qualitative research focuses on collecting data in vivo, meaning close to the point of origin, and relies heavily on the context in which behaviors occur. The act of description is fundamental to data collection in qualitative studies. Interpretive Frameworks: The document discusses the importance of interpretive frameworks in linking signs and meanings in social research. It suggests that qualitative researchers often have a more nuanced understanding of behavior that requires context and empathetic engagement. Qualitative vs. Quantitative Methods: Van Maanen argues that qualitative and quantitative methods are not mutually exclusive. While quantitative  methods dominate organizational research, there is a growing recognition of the value of qualitative approaches. Concerns in Organizational Research: The author highlights several issues in organizational inquiry, including the gap between generalized principles and specific contextual understandings, the complexity of data manipulation techniques, and skepticism about conventional data collection methods. Emerging Interest in Qualitative Research: There is a noted resurgence in the interest for qualitative research across various disciplines, recognizing the need to understand the unique cultures and experiences of the subjects being studied. Criteria for Qualitative Research: The document outlines criteria for evaluating qualitative research contributions, emphasizing the importance of practical relevance, disciplinary diversity, and the novelty of themes explored. Thematic Groupings of Papers: The preface introduces thematic groupings of papers in the special issue, focusing on ethnographic paradigms, the integration of qualitative and quantitative methods, and novel themes in organizational inquiry. Encouragement for Methodological Diversity: The overall intent of the document is to encourage a more diverse methodological approach in organizational studies, fostering deeper insights and understanding of complex social processes. Philosophical foundations of qualitative research Research = original investigation undertaken to contribute to knowledge and understanding in particular field, based on underlying assumptions about what constitutes valid research and how it should be done Underlying assumptions o Ontology: what entities do exist in the world? o Epistemology: What is knowledge and how can it be acquired? o Cognitive interests: Why – to what ends - do we engage in research? Paradigm = worldview consisting of basic philosophical assumptions, specific approaches to research and applications to research problems, carried on through socialization (all researchers become socialized into specific paradigm), imperfectly demarcated Three core paradigms in qualitative research:  (Post-)Positivism o Primary paradigm in quantitative research, but also qualitative research based on this worldview o Ontology: Objectivism o Epistemology: Empiricism o Correspondence theory of truth o Methodological focus: Measurement, objectivity, law- generalizations, verification/falsification; most closely associated with hypothetico-deductive quantitative methodologies o Logic: o & Karl Popper’s critical rationalism “No matter how many instances of white swans we may have observed, this does not justify the conclusion that all swans are white.” (Karl Popper, 2002) Reality only known probabilistically  Falsification instead of verification Goal: compare facts and theory to challenge prior knowledge No big sample per se necessary for falsification Interpretivism (and social constructivism) o Multiple possible interpretations are equally valid o Ontology: social reality is socially constructed o Epistemology: 1. Access to reality always mediated through system of signification (language, meaning, symbols, culture, etc.) that are contingent 2. Knowledge does not simply mirror or depict but actively brings about reality o Methodological consequences: goal of research “not to capture some preexisting or ready-made world presumed to be available out there but to understand [the] process of symbolic ‘worldmaking’ […] through which the social world is ongoingly accomplished” Critical-postmodern paradigm o Like interpretive research with additions: ▪ More radical break with modernist/positivist ideals of truth, objectivity, facticity and science ▪ Complex relationships between interests, knowledge and power ▪ Focus on critique and deconstruction ▪ Ethically based stance, suggests individual emancipation/improvements in society ▪ Closely associated methodologies: discourse analysis, narrative analysis, postmodern ethnography, postmodern historiography Reading: "Qualitative Research and the Academy of Management Journal: Challenges and Opportunities" by Sara Rynes and Robert P. Gephart Jr. (2004): Importance of Qualitative Research: The paper emphasizes the significance of qualitative research in management studies, highlighting its ability to provide rich, detailed insights that quantitative methods may overlook. Challenges in Qualitative Research: Authors note that many researchers struggle with analyzing qualitative data effectively, often due to a lack of training in qualitative methodologies compared to quantitative methods. Editorial Support for Qualitative Research: The Academy of Management Journal (AMJ) actively seeks and supports qualitative submissions, encouraging authors to submit high-quality qualitative research. Common Issues in Submissions: The paper identifies recurrent issues in qualitative submissions, such as insufficient methodological rigor, unclear research questions, and inadequate literature reviews. Recommendations for Improvement: The authors provide suggestions for enhancing the quality of qualitative research, including: Developing clear research questions and objectives. Providing thorough literature reviews to contextualize the research.  Clearly articulating the methodology used in the study. Examples of Successful Qualitative Research: The paper cites award- winning qualitative studies published in AMJ, illustrating the potential impact of well-executed qualitative research. Theoretical and Methodological Consistency: The authors stress the importance of aligning qualitative methodologies with the theoretical frameworks being employed to ensure coherent and meaningful research outcomes. Encouragement for Ongoing Research: The paper advocates for researchers to engage in ongoing qualitative research projects, which can lead to more substantial insights and contributions to the field. Future Directions: The authors call for a continued emphasis on qualitative research within management studies, encouraging scholars to explore diverse qualitative methodologies and their applications. Designing qualitative research projects Research design: o Circular process, guided by research question Developing relevant research questions  o Emerges from previous research o Aims to fill relevant gap in literature o Specific enough to guide research process o Open enough to allow surprising findings to emerge o Quantitative vs. qualitative research questions: o Qualitative research questions aim to… … reconstruct subjective interpretative schemes … identify people’s perceptions and evaluations of a certain phenomenon … examine culture, beliefs, norms, motivations, morality, imagination … analyze non-explicable routines, practices, „ways of doing“ … investigate complex processes that unfold over time … develop theoretical constructs based on data … explore phenomena about which little is known Conceptual framework o Helps to sort empirical insights o Connects insights to ongoing research debates o Enables to develop scientific explanations, concepts and models (go beyond descriptive level) o Which theory and concepts help to answer the research question? o What can we see with a certain concept that we would not see without it? Case selection o Guided by research question ▪ What is a good case to analyze the research question? ▪ How many cases are needed to analyze the research question? o Theoretical sampling: selecting cases based on theoretical criteria ▪ Typical cases or extreme cases  ▪ Comparing similar cases to search for differences ▪ Comparing different cases to search for similarities o If cases don’t fit research question and theoretical framework, question cannot be answered → start from the beginning Data collection Data analysis Developing explanations, concepts and models Reading: The Evolution and Diversity of Qualitative Research in Management Inquiry (Gehman et al., 2017) Growth of Qualitative Research: Highlights the increasing acceptance and importance of qualitative research methodologies in management studies, noting a significant rise in qualitative publications. Challenges Faced: Identifies common challenges in qualitative research, such as difficulties in data analysis, lack of methodological rigor, and the need for clearer research questions. Editorial Support: The Academy of Management Journal (AMJ) encourages high-quality qualitative submissions and emphasizes the need for rigorous qualitative research. Recommendations for Researchers: Suggests strategies for enhancing qualitative research quality, including: Developing clear and focused research questions. Conducting thorough literature reviews to contextualize findings. Clearly articulating the methodology and data analysis processes. Case study research Logic: o “Case studies are rich, empirical descriptions of particular instances of a phenomenon that are typically based on a variety of data sources.” o Case = bounded system, can be person, group, organization, relationship, event, process, problem or other specific entity  o Examining context and other complex conditions is integral to understanding o Addresses how and why questions Key assumptions: o Can be conducted within realist or interpretive/constructivist tradition o May serve variety of purposes o Key objectives: theory building, extension of existing theory, (testing theory) Single case studies o In-depth examination of single case providing detailed understanding of specific phenomenon o Objective: developing novel theory o Types: (1) revelatory case, (2) critical case, (3) extreme case, (4) representative case or (5) longitudinal case o Decision of suitable case depends on research question o May have multiple embedded units of analysis: study of multiple aspects within single case → comprehensive understanding of case’s complexity  Multiple case studies o Examination and comparison of several cases to gain deeper understanding of specific phenomenon o Objective: produce theory that is parsimonious, generalizable and testable through propositions o Often referred to as “Eisenhardt method” o Decision of cases driven by research question o May include multiple embedded units of analysis: various aspects within each case → enhancing the generalizability of findings Procedure o Using theory in design work o theoretical lens (i.e., institutional theory or practice theory) helps to refine your research question, selecting your case(s), adapt your case study design, and defining the relevant data o use of theory helps to organize data analysis o perspective could limit ability to make discoveries, prepare to discard it after initial data collection o Gaining field access and collecting data o Gaining access via: − Personal ties (e.g., through previous or current employment or personal relationships) − Industry conferences or specific networking events  − “Cold acquisition” (e.g., sending well-drafted and specific emails) − Snowballing techniques (e.g., asking informants about other informants) o Collecting data via: − Observations − Interviews − Archival records, documents, pictures, videos, etc. → Ideally, researchers triangulate multiple data sources o Analyzing data o Presenting findings Opportunities and limitations Opportunities Limitations In-depth exploration of complex Time and resource intensive: invest phenomena within real-life context substantial time in conducting interviews, observations and document analysis Contextual understanding: capture Limited (formal) generalization: focus unique circumstances, relationships on specific contexts, so findings not and dynamics, providing more holistic easily applicable to broader & nuances understanding populations Theory development and refinement: Analytic generalization possible potential to contribute to theory development Reading: Applied Social Research Methods Series: A Collection of Research Guides (Yin, 2003) Case Study Methodology: Provides comprehensive guidance on designing and conducting case studies in social research, emphasizing the importance of a well-defined research question. Research Design: Discusses the significance of selecting appropriate cases and ensuring methodological rigor in qualitative research. Data Collection Techniques: Outlines various data collection methods, including interviews, observations, and archival research, to gather rich qualitative data. Analytical Strategies: Offers strategies for analyzing qualitative data and drawing meaningful conclusions, highlighting the iterative nature of qualitative research. Persuasion with Case Studies: A Reflection on the Challenges of Convincing Readers (Siggelkow, 2007) Case Study Persuasiveness: Discusses the challenges of persuading readers with case study research due to concerns about sample size and representativeness. Motivation and Inspiration: Highlights the role of case studies in motivating research questions and inspiring new ideas, emphasizing their value in qualitative research. Illustration of Concepts: Emphasizes the importance of using case studies to illustrate theoretical concepts and causal mechanisms, enhancing understanding. Avoiding Ex Post Obviousness: Warns against making findings that are not surprising or insightful, stressing the need for conceptual contributions that resonate with readers. Ethnographic research Origins: o Roots in anthropology o Developed from attempts to study other cultures o Management and organization studies interested in “culture with small c” o Studying lifeworld of organizational member, understanding organizing process and everyday practices Date gathering o Multiple data sources important to triangulate interpretations ▪ Observations (capture in field diaries, using thick description) ▪ Interviews ▪ Documents  Data analysis o First and second order concepts Writing o Let readers participate in lived experiences o Convey credible interpretations o Embed vignettes (excerpts of field diary) o Consider use of visual evidence (videos or photos from field) Limitations Additional considerations Reading: Producing Persuasive Findings: Demystifying Ethnographic Textwork in Strategy and Organization Research (Jarzabkowski et al., 2014) Ethnographic Textwork: Examines the role of ethnographic textwork in producing persuasive research findings, focusing on narrative construction.  Persuasion Techniques: Identifies techniques used to enhance the persuasiveness of ethnographic narratives, such as vivid descriptions and contextualization. Challenges in Ethnography: Discusses challenges faced by ethnographers in presenting their findings convincingly, including the need for clarity and coherence. Recommendations for Researchers: Offers practical recommendations for improving the quality and impact of ethnographic research, emphasizing the importance of storytelling. Design science research Nature: o Two major paradigms in management and organizational studies: ▪ Behavioral science: studies human or organizational behavior to understand, explain and predict it by creating and testing theory ▪ Design science: creates innovative artefacts that serve human purposes by solving technical or organizational problems o Employs techniques for data collection from qualitative and quantitative research o Pragmatic element: relevance lies in artifacts’ efficacy Artifacts o Outcome of design process o Varies depending on real-world problem o Can be managerial, socio-technical or technical by nature o Examples: Research question o Types: Design science process o Different models: five process steps by Kuechler and Vaishnavi (2008) o Outlines steps sequentially but actual process is iterative  Step 1: Problem awareness o Identifying and understanding problem space o Questions: − What is the need or what is wanted? − What is the goal, purpose or intended outcome? − What requirements, both from stakeholders and knowledge base, exist? − Who are the involved stakeholders and how do their needs and requirements differ? o Often return to this step as subsequent design steps produce knowledge that flows back Step 2: design suggestions o Iterative exploration of: ▪ Knowledge base ▪ Design suggestions ▪ Reflections within problem space o Goal: suggesting possible solutions and assess feasibility to improve problem awareness and identify best possible solution  Step 3: artefact development o Core of design science research process o Based on knowledge base, data collection and design solution, solution is developed o Usually unfolds iteratively o Can involve building: − Models, frameworks, or other representations of the artefact − Prototype of an application or tool, e.g., mock-up, or − Software code that implements a technical solution o Write notes on deign decisions to better re-construct design process Step 4: artefact evaluation o Assess efficacy whether it solves real-world problem o Produces knowledge o Knowledge flows back into design and builds foundation for design’s contribution to existing knowledge base o Differentiate evaluation by purpose (formative vs. summative) or type (artificial vs. naturalistic) Step 5: conclusion and presentation o Writing-up and presenting findings o Presentations and detailed description of: − The real-world problem, motivation, research question and adequacy of taking a design approach − The existing knowledge base that informed the design − The rigorous use of research methods − The designed artefact and its efficacy (i.e., evaluation) o Critical to understand the why of artefact’s design  Evaluating design science research o Involve designing artefact for real-world problem o Relevance and rigor o Research should make contribution beyond designed artefact: − Contributing design knowledge to design similar artefacts − Contributing to theory within the problem domain − Contributing to methods underpinning design science research Opportunities and limitations Reading: Design Science in Information Systems Research (Hevner et al., 2004) Design Science Framework: Introduces a framework for conducting design science research in information systems, emphasizing the creation and evaluation of innovative artifacts. Research Rigor: Stresses the need for rigor in both the design and evaluation processes to ensure the quality and relevance of research outcomes. Relevance Cycle: Discusses the relevance cycle, which connects design science research to real-world problems and ensures that research addresses practical needs. Guidelines for Researchers: Provides guidelines for researchers to ensure their work is both scientifically rigorous and practically relevant, fostering innovation in information systems. Critical Reflection on Using Interviews and Observations as Data Sources Types of Interviews: Structured: o Definition: Highly organized interviews with a fixed set of questions asked in a specific order. o Characteristics: ▪ Uses standardized questions with predetermined answers, allowing easy comparison across interviews.  ▪ Provides reliable and consistent data, making it useful for quantitative analysis. ▪ Reduces interviewer bias and ensures all respondents have a similar experience. o Drawback: Limited flexibility, as follow-up questions or deeper exploration of responses are constrained. Semi-structured: o Definition: Flexible interviews that have a guiding set of questions or topics but allow for spontaneous follow-ups. o Characteristics: ▪ Uses open-ended questions, giving the interviewer freedom to probe or explore unexpected topics. ▪ Balances consistency (with a general interview guide) and flexibility (with room for variation in responses). ▪ Useful for qualitative insights, as it allows for a deeper understanding of complex topics. o Drawback: Data can be more challenging to analyze and compare due to the variation in responses. Open (unstructured) o Definition: Conversational and informal interviews without a predefined structure. o Characteristics: ▪ Minimal guidance is provided, allowing the interview to flow freely based on the participant's responses. ▪ Facilitates in-depth exploration, as the interviewer can delve deeply into the participant's perspectives and experiences. ▪ Commonly used in exploratory research or when the goal is to understand subjective experiences. o Drawback: Lacks consistency, making data hard to quantify, compare, or analyze systematically. Interviewing 1. Opportunities to construct meaning with interviewee (interviewer involved in interview 2. Social practice and interviews are situated & embodied: not just listen but observe 3. Interviewees may want to impress or manage reputation o Consider: Where and when to conduct the interview (enough time; familiar and comfortable situation for interviewee; in person) Using artefacts to trigger responses, e.g. images (Abildgaard, 2018) Structured, semi-structured, or open? When interested in how people do things, ask for stories (Liuberte & Feuls 2022) Recording and taking notes (Czarniawska, 2014) How to interpret what the interviewee says? (Alvesson, 2009) How to: Make an interview guide  Formulate your questions with everyday language During interview: Ask for examples or anecdotes to enhance your understanding Take notes Record Put your interview guide aside whenever you can in order to dive deeper into the conversation Come back to the interview guide in order to check whether all themes have been covered Let the other person speak! Questions to ask yourself after interview: What are the challenges of interviewing? What were the surprises in the interview? Which questions worked well (both previously designed and spontaneous)? What do you take away from this experience for your future interviews? Observations What to focus on? o rely on your research interest/question but keep an open mind o You are the main instrument: ‘drop your tools’ (Weick, 1996) (intuitive & perception) o ask yourself: what is happening here? What is at stake? What is being accomplished? Who benefits? What to observe? o people, practices, things, technologies, non-human actors o ask what differences things or actions make o use yourself as an instrument o shadowing as ‘observation on the move’ (Czarniawska, 2014) →following something, logistics and planning Observations as data What to do when you cannot take field notes in the moment? 1. Scribble down shorthand (‘jottings’) and write out notes later (on the day itself or shortly after) 2. Recording devices 3. Memory (pay attention) How to use observations during the research? 1. Share insights in conversations (as questions)  2. Refine your interview questions or what to pay attention to in your observation 3. Consult the literature Full fieldnotes are focus on thick description (Geertz, 1973), rich & detailed, allowing you to re-enter the scene (full sentences) Ideally you try to write them the same day, or the day after Length: Some say 4 hours in the field = 4 hours of writing; 10 pages for every hour (Goffman,1989; Lindlof & Taylor, 2019): 3-5 pages → lush can be meaningful but also cumbersome, if you are overwhelmed or bored by your own fieldnotes, this might be a clue that something has gone awry Style: Loose and informal, write quickly rather than forcing a certain style; structure around themes or chronologies helps, clear headings! Optional: keep separate ‘characters files’ in which you document information on specific informants How is knowledge gained through interviews and observations? Qualitative observation: a multi-sensory approach Research methods relying on observation stressed seeing as main method of perception multi-sensory ethnography (Pink, 2015), affective ethnography (Gherardi, 2019), diffractive methodology (Kuismin, 2022; Schneider 2002) and research on ‘sensing’ (Cnossen, 2022; Willems,2018): more senses are involved in qualitative observation Sensitizing questions you can ask: o What does this space feel like (Hare, 2020)? o What is this situation reminding me of? o What seems to matter in this space/situation/organization? (matter = materializing) (Cooren, 2020) o What is my intuition telling me? o What is “hanging in the air” (Stewart, 2007)? o What micro-moments become consequential (Brummans & Vézy, 2022)?  o After that: verify and fact check with subsequent observations and speak to informants Reading: Enhancing Reflexivity in Interviews through Nexus Analysis: A Social Practice Perspective (Dordah and Horsbøl, 2021) Nexus Analysis Introduction: Introduces nexus analysis as a method to enhance reflexivity in qualitative interviews, focusing on the social practices that shape interview dynamics. Social Practice Perspective: Emphasizes understanding the context and practices that influence the interactions between researchers and participants during interviews. Reflexivity Importance: Highlights the necessity for researchers to be aware of their influence on the research process and outcomes, advocating for a more reflexive approach to data collection. Practical Guidance: Provides practical recommendations for conducting reflexive interviews, aiming to improve the quality and depth of qualitative data. Critical reflections on artifacts as data sources Artifacts & relevance in qualitative research In working and organizing, artifacts are all around us! Think about: − Documents (e.g., strategy plans, PPT slides, models, prototypes, sketches) − Visuals (e.g., pictures, visual timelines, Gantt charts, models, drawings, logos, videos) − Spatial aspects and artifacts (e.g., interior design, rooms, furniture) − Embodied aspects and artifacts (e.g., particular gestures, postures, facial expressions) − Other artifacts (e.g., measuring instruments, technologies, books) Artifacts enable or constrain action, convey meaning beyond words, are not neutral but political, are not part of the background but active contributors to action Decentering analytical position: A “turn to things” Linguistic turn → material/visual/relational turn A ‘turn to things’ (Gieryn, 2002) Interest in ‘how matter matters’ (Carlile et al., 2013) Sociomateriality (Leonardi, 2012; Orlikowski, 2007) Actor-network-theory and new materialism (Latour, 2005) Regarding the material, verbal, visual and other modes not as separable, but as co-emergent (Zilber, 2018): multimodality Findings of exemplary studies: Comi & Whyte, 2018 Demonstrating visual artifacts’ performativity: bringing an imagined future into the present and making it amenable to further work, performing different roles over time Unfolding representations, enabling professionals to produce images of the future but also perform spontaneous actions = ways of building & dwelling Their usage is sensorial Exemplary studies: Knight et al., 2018 Insights: Presentation slides help broker divergent interpretations of strategy and give rise to new strategic understandings Demonstrating how presentation slides do more than they show: They not only provide strategists/consultants with a concrete way of “seeing” strategy meanings, but they also generate novel extensions to these meanings by provoking conversations, debate, and dialogue Exemplary studies: Cnossen & Bencherki, 2018  How space plays a role in constituting new organizations and making them last Space constraining or enabling practices, and providing them with meaning Observations, field notes, interviews Exemplary studies: Leybold & Nadegger, 2023 Critically interrogating and making heard the hidden voices and struggles of stigmatized groups, through studying visual, digital artifacts Helping make the invisible visible (e.g., silenced bodies, taken-for- grantedness, taboos), unmask social reality, and make heard more voices Inherently political agenda of artifacts: power relations influence which ideas and voices are expressed through artifacts – manipulative nature of things? But artifacts can also be leveraged for resistance, offering alternative ways to express suppressed views and voices And: artifacts themselves are not neutral – things like interior design and tools in the workplace can express certain norms about which work practices are valued by themselves, too (Wasserman & Frenkel, 2015) Reading: Future Making and Visual Artefacts: An Ethnographic Study of a Design Project (Comi and Whyte, 2017) Ethnographic Approach: Utilizes ethnographic methods to study design processes and the role of visual artifacts in shaping collaborative practices. Future Making: Explores how design teams create visions of the future through their interactions and the use of visual tools. Significance of Visual Artifacts: Highlights the importance of visual artifacts in facilitating communication and decision-making within design teams. Implications for Practice: Discusses the implications of findings for design practice and organizational innovation, emphasizing the role of collaboration in future-making. Gathering data: Online data Virtual worlds are part of human life: examples Types of Online data Text-based or visual data Asynchronous or synchronous (real-time) online data “Public” or “Private” accessible data Broadcast or networked/co-created data Data from online blogs Blogs primarily feature text, some visual or embedded video Asynchronous communication, reverse chronologically sorted “publicly” available data Co-created comments by users Online data in quantitative research Traces which are stored and recorded Accumulation of digital trace data inro big datasets Online data in qualitative research As archive: o Accumulation online data and treat them as collection of documents ▪ Characteristics of this data: Multi-modality (e.g., text, emoticons, images, memes) Reverse-chronologically ordered communication instances Co-created content (e.g., comments on posts) Evaluative infrastructures (ratings, views) Identities (user statistics, user profile) o Useful for comparative case studies relying on “document analysis”, study a phenomenon ex-post o Passive role of researcher As process: o Process: Collecting data as the phenomenon unfolds in a virtual setting. For instance, by participating in online meetings via Zoom/Teams/Webex/Jitsi, conducting work on crowdwork platforms or immersing oneself in virtual worlds (e.g., games). o Characteristics:  ▪ Multi-modal data (e.g., video and text) ▪ Synchronous communication, which is less structured and not always recordable ▪ Co-created content (e.g., commenting live videos) o Fits to research designs emphasizing ethnographic or participant observation approaches; Pioneering work of Kozinets (=Netnography) (2002) o Researcher has active part of data collection/creation process Combining both approaches o Process approach to collecting data usually includes archive approach whenever possible (vice-versa possible too) (Akemu & Abdelnour, 2018; Kozinets, 2002) Advantages and challenges when using online data Reflecting upon the challenges Contextualizing online data and layered platforms o Ensure fit between the purpose of study and the type of data (Pousti et al., 2021). For instance, online data as the only data source is great to study phenomena where things happen in the open (or now moved into the open). Use theoretical lenses/concept that are compatible with relying on online data such as stakeholder management, CSR, legitimacy, brand, openness/closeness, CCO, impression management, etc. o Pay attention to communicative culture in online settings. For example, sensitive firm audience interaction may not occur via the blog but in closed private settings such as e-mails or DMs. Online data prevents gaining insights what happens behind the ‘digital veil’. o Some platforms provide more functionalities and behavioral options for more experienced users than for ‘beginners’ – this aspect needs to be considered when doing observations on platforms. o For certain research questions you will need additional data sources (e.g., interviews, for example, Gegenhuber et al., 2021) Ethical issues o You need to think about on how to „ethical data collection, data analysis and reporting“ when you design a qualitative study using online data (Pousti et al., 2021, p. 364)  o Primary goal: Avoiding harm! (e.g., Levina & Vaast, 2016) o Considerations (Whiting & Pritchard, 2017): ▪ Degree of human participation (archive vs data as part of the process) ▪ Public vs. private data (platform infrastructure vs. perception of users) ▪ Seeking informed consent and from whom (users, platform provider, feasibility) ▪ Anonymization vs. attribution (challenges of ‘cloaking’) Gathering and processing data o Gathering the data: ▪ Manuel downloading of data as a pdf-files. Make trial download on transfer it to MAXQDA and make sure text selection works to ensure proper coding process. ▪ Automated scraping of data. o Processing the data: ▪ − In my research I coded hundreds of blog posts and thousands of comments manually (seevGegenhuber & Dobusch, 2017; Gegenhuber & Naderer, 2019). Up to a certain point manual analysis isvpossible and gives you an in-depth understanding of the phenomenon. ▪ At some point, a digital data set may simple be too large. In this case, automating some parts of the analysis may be useful (e.g., sentiment analysis and topic modelling – see advanced topics slides at the end). In any case, it makes sense to qualitatively dig into the data set to get an initial insight what is going on. Reading: Making an Impression Through Openness: How Open Strategy-Making Practices Change in the Evolution of New Ventures (Gegenhuber and Dobusch, 2017) Concept of Open Strategy: Open strategy-making is defined as a practice that increases transparency and involves external stakeholders in strategic processes, challenging traditional closed approaches. Impression Management: The study explores how new ventures utilize open strategy as a means of impression management to enhance their legitimacy and attract support from various stakeholders, including customers, investors, and the media. Modes of Engagement: Identifies three distinct modes of open strategy: Broadcasting: Sharing relevant strategic information with external audiences. Dialoguing: Engaging in conversations with stakeholders to solicit feedback and opinions. Including: Actively involving external audiences in decision-making processes.  Temporal Dynamics: The emphasis on these modes evolves over time; during the launch phase, dialoguing is crucial for gaining initial support, while broadcasting becomes more prominent as the venture matures, reflecting a shift in audience engagement strategies. Analyzing data based on grounded theory Definition: Grounded theory is an inductive approach to help build theory based on actors’ interpretations of relevant phenomena. Inductive approach: empirically attempts to avoid imposing theoretical explanations from the outset Unit of analysis: actors’ views and understandings of phenomena Typical data sources: semi-structured interviews, observation, also documents, newspaper articles, blog posts, etc. → theories are grounded in data Data analysis Guiding principles: o Partial simultaneity of data collection and analysis (start analyzing right after collecting data) o Constant comparison (similarities & differences of codes) Overall procedure: o First-order analysis ▪ Open coding: developing & assigning categories to pieces of data & reflect informants’ words and experiences as closely as possible ▪ Either analytical code (description of what’s going on) pr in- vivo code (wording in field) ▪ Developing first-order categories: merging categories that are similar in character & relabel them that continues to reflect actors’ views and understandings (reflections of broader patterns of what actors in the field have said and done → not theoretical ▪ Getting lost is part of the process (many codes → 25-30 categories) o Second-order analysis ▪ Axial coding: “what’s going on here, theoretically”, drawing on literature → make sense of similarities and differences between first-order categories ▪ Developing second-order themes: merging first-order categories similar in theoretical terms, assigning labels that convey a theoretical understanding ▪ Selective coding: grouping second-order themes to aggregate dimensions (context, enablers, mechanisms, outcomes)  o Model development ▪ Ordering second-order themes around aggregate dimensions ▪ Elaborating interrelationships between second-order themes ▪ Dialogue between data and literature ▪ Go back to data and prior literature Some merits and pitfalls Merits Pitfalls Developing rigorous and credible Risk of creating stylized images of theoretical conclusions from messy research process (non-linearity, qualitative data creative leaps)  Popularity of grounded theory led to Factor-analytic style: slicing complex stronger position of qualitative studiesphenomena into decontextualized, in management research quantifiable pieces De-facto standard grounded theory suppresses plurality of approaches to qualitative research Reading: Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology (Gioia et al., 2012) Gioia Methodology Overview: A systematic approach to qualitative research that emphasizes the development of new concepts and grounded theory through rigorous data analysis. Data Structure Importance: Stresses the necessity of creating a data structure to illustrate the connection between raw data and emergent theory, enhancing the credibility of qualitative findings. First-Order and Second-Order Analysis: Differentiates between: First-Order Analysis: Informant-centric terms and codes derived from the data. Second-Order Analysis: Researcher-centric themes and concepts that emerge from the first-order analysis. Iterative Process: Emphasizes the iterative nature of qualitative research, involving continuous engagement with both data and theory to refine concepts and relationships. Analyzing process data Process studies: Focus on how and why things emerge, develop, grow or terminate over time Considering phenomena dynamically (movement, activity, events, change and temporal evolution) Processes Strategies for analyzing processes Narrative strategy o Developing thick descriptions o Composing story of what happened  o Synthesizing corpus of raw data in empirical narrative o Empirical narrative is detailed and context-sensitive o High in accuracy, low on simplicity & generality (close to data) Quantification strategy Alternate templates strategy Visual mapping strategy o What happened when? o Use of graphical displays: matrices, timelines, etc. o Reduction of potentially large quantities to visual forms o Revealing patterns of precedence, parallelism/co-evolution & passage of time o Moderate on accuracy, simplicity & generality Temporal bracketing strategy o Structuring description of events (e.g. narratives, timelines) around phases o Identifying turning points or key events o Phases more or less separable units that can be compared o (how do activities in one phase lead to changes in another? How can passage from one phase to another be explained?) o Moderate on simplicity & generality, accuracy depends on adequacy of decomposing processes into phases Synthetic strategy Grounded theory strategy o Deconstructing process data into comparable incidents  o Developing categories, themes and dimensions by comparing incidents o High on accuracy, low to moderate on simplicity, generality depends on level of theoretical abstraction No analysis strategy will produce theory without an uncodifiable creative leap Process model Reading: What Makes a Process Theoretical Contribution? (Cloutier and Langley, 2020) Defining Process Theory: Differentiates process theory from variance theory, focusing on the dynamic unfolding of phenomena over time through activities and events. Typology of Theorizing Styles: Proposes four styles of process theorizing: Linear: Sequential stages of a process, often borrowed from existing models. Parallel: Interrelated processes that influence each other, highlighting co-evolution or bifurcation. Recursive: Ongoing cycles of adaptation and feedback loops, emphasizing the continuous nature of processes.  Conjunctive: Breaking down dualisms and integrating diverse elements of human experience to formulate strong process theoretical contributions. Challenges in Process Theorizing: Discusses the difficulties of developing process theories without empirical data and the need for innovative approaches to theorizing. Theorizing from qualitative data Theorizing and the facts, evidence, theory triad What is a theory and what are forms or styles of theorizing? Theory: set of well-developed categories that are systematically interrelated through statements of relationship to form theoretical framework that explains or predicts relevant phenomenon Style of theorizing: distinctive approach or way of thinking in which scholars develop and present their theories Three forms of explanatory theorizing Propositional theorizing Identifying categories or variables in causal & probabilistic relationships Develop graphical model, capturing key variables + relationships If-then argumentations  Example simple propositional relation: case of organizational failure o Black-box model of presumed causal relation Expanding model with moderator & mediator Configurational theory Form of simplification Holistic explanation: seeks explanation of topic by grouping attributes of a kind into ideal types Interdependencies of attributes: focuses on mutually interdependent attributes that group together differently in each configuration Limited number of possible configurations: assumes that only limited number of configurations are viable Configuration 1: the laggard (organizational failure)  Configuration 2: the imperialist (organizational failure) There may be further configurations Process theorizing Temporality: recognizes that phenomena are not static but unfold over time Dynamics and change: focuses on dynamics and change Mechanisms: seeks to identify mechanisms & processes of becoming Types: Example organizational failure: mechanisms of change the villain Reading: What Theory Is and Can Be: Forms of Theorizing in Organizational Scholarship (Cornelissen et al., 2021) Theoretical Contributions: Explores various forms of theorizing in organizational research, including variance and process theories, and their implications for understanding organizational phenomena. Conceptual Clarity: Stresses the importance of clarity in theoretical contributions to enhance understanding and applicability in organizational contexts. Innovative Theorizing: Encourages scholars to innovate in their theorizing approaches, particularly in developing process models that capture the dynamic nature of organizational life. Interdisciplinary Insights: Advocates for drawing on insights from various disciplines to enrich organizational theory and broaden the scope of research.