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Qualitative research has gained in importance in the social sciences. General knowledge about qualitative data analysis, how to code qualitative data and decisions concerning related research design in the analytical process are all important for novice researchers. The purpose of this paper is to offer researchers who are new to qualitative research a thorough yet practical introduction to the vocabulary and craft of coding.

Having pooled, their experience in coding qualitative material and teaching students how to code, in this paper, the authors synthesize the extensive literature on coding in the form of a hands-on review.

The aim of this paper is to provide a thorough yet practical presentation of the vocabulary and craft of coding. The authors, thus, discuss the central choices that have to be made before, during and after coding, providing support for novices in practicing careful and enlightening coding work, and joining in the debate on practices and quality in qualitative research.

While much material on coding exists, it tends to be either too comprehensive or too superficial to be practically useful for the novice researcher. This paper, thus, focusses on the central decisions that need to be made when engaging in qualitative data coding in order to help researchers new to qualitative research engage in thorough coding in order to enhance the quality of their analyses and findings, as well as improve quantitative researchers’ understanding of qualitative coding.

The open science movement calls for transparent and retraceable research processes. While infrastructures to support these practices in qualitative research are lacking, the design needs to consider different approaches and workflows. The paper bases on the definition of ontologies as shared conceptualizations of knowledge (Borst, 1999). The authors argue that participatory design is a good way to create these shared conceptualizations by giving domain experts and future users a voice in the design process via interviews, workshops and observations.

This paper presents a novel approach for creating ontologies in the field of open science using participatory design. As a case study the creation of an ontology for qualitative coding schemas is presented. Coding schemas are an important result of qualitative research, and reuse can yield great potential for open science making qualitative research more transparent, enhance sharing of coding schemas and teaching of qualitative methods. The participatory design process consisted of three parts: a requirement analysis using interviews and an observation, a design phase accompanied by interviews and an evaluation phase based on user tests as well as interviews.

The research showed several positive outcomes due to participatory design: higher commitment of users, mutual learning, high quality feedback and better quality of the ontology. However, there are two obstacles in this approach: First, contradictive answers by the interviewees, which needs to be balanced; second, this approach takes more time due to interview planning and analysis.

The implication of the paper is in the long run to decentralize the design of open science infrastructures and to involve parties affected on several levels.

In ontology design, several methods exist by using user-centered design or participatory design doing workshops. In this paper, the authors outline the potentials for participatory design using mainly interviews in creating an ontology for open science. The authors focus on close contact to researchers in order to build the ontology upon the expert's knowledge.

The purpose of this study is to better understand distinct solution strategy types for common commissioning and startup problems (Hot Spots) in the construction of industrial facilities. The authors also sought to better understand which solution strategy types offer the best value for the effort required.

The authors used a method of qualitative coding of text-based data to identify themes, patterns and trends from a collection of 178 commissioning and startup (CSU) solution strategies for the CSU Hot Spots. Coding categories emerged after multiple iterations. The authors also mapped high-value, low-effort solution strategies across the categories. Chi-squared testing and analysis of proportion statistics help quantitatively justify this qualitative research.

The authors identified 12 distinct coding categories and showed that they follow a non-uniform distribution via statistical testing. Those strategy types which provide particularly good value for the effort required are identified (such as quality assurance and control strategies), as well as those strategy types that do not.

Research is limited to CSU for the construction of industrial facilities. The findings are also limited to a subset of the most commonly problematic CSU activities. Many findings may be beneficial for heavy civil and commercial CSU as well.

Coding categories, definitions and descriptions provide a good overview of all 178 solution strategies for CSU project professionals. Implementing certain types of solutions or solution programs may allow CSU managers to prevent multiple Hot Spots from becoming problematic or to keep problems already occurring from becoming worse. Managers will also benefit from knowledge about which strategy types are more likely to give a higher value for lower effort.

Qualitative coding and analysis of solution strategies for common CSU problems have never been conducted so rigorously in any other CSU study. This method has yielded results distinct from other CSU studies which have used quantitative methods. Insights from findings have advanced the body of knowledge surrounding problem-solving in the commissioning and startup sub-discipline.

This paper describes the approach to studying leadership within the interpretive paradigm that the author undertook for their doctoral research.

For the study, qualitative data were collected via in-depth interviews and the researcher's systematic reflections. The analytical process consisted of database design and management followed by cyclical interview and cross-interview analyses and integration of the researcher's reflections.

The paper showed that integrating various qualitative methods in pragmatic ways that better align with the research scope, along with a systematic approach to studying complex phenomena—such as leadership—generated richer and more cohesive perspectives.

This paper provides a detailed account of how the qualitative data collection and analysis methods were used, which could be replicated or adapted for future research within the interpretive paradigm.

The paper helps students and junior researchers make sense of qualitative data analysis and interpretation by offering practical tools to tackle the diverse processes of qualitative research.

This paper is based on the Author's doctoral research, recording their experience with engaging in qualitative research.

Notes that, over the past decade, a number of computer programs have been designed to assist researchers in the analysis of qualitative data. Acknowledges that all programs will help to take some of the tedium out of the clerical tasks associated with qualitative data analysis and some programs can assist researchers in developing emerging concepts and theory. Explains briefly how programs can be employed in the coding process and discusses the benefits and drawbacks of using them. Where relevant, also draws on the small but growing literature in this field.

The chapter discusses abductive thematic analysis as an innovative qualitative methodology in hospitality and tourism research. The novelty of the abductive approach is to combine the power of both deductive and inductive reasoning: it is possible to initiate the research starting from an existing theoretical, without renouncing to a creative phase where the researcher interprets the phenomenon beyond the words utilized and theorizes dependencies between concepts. The chapter further presents a case study to illustrate how abductive thematic analysis can be applied to study small hospitality and tourism businesses. The chapter further highlights the benefits of adapting thematic analysis to abductive reasoning, which is a paradigmatic position thus adding rigor to hospitality and tourism. The chapter finally highlights future avenues for development of methodology research toward adding further rigor to this novel methodology.

Discussions of the use of computer‐assisted qualitative data analysis software (CAQDAS) in social science research studies are still few and isolated. In fact, much of the literature takes an uncritical approach to CAQDAS programs based on unrealistic expectations of the software as a methodology in and of itself. This has significant implications for learning and teaching qualitative data analysis software and the way it is used in research. The study on which this article is based combined formal narrative analysis, thematic coding, and deconstruction techniques to analyse the data using a dedicated qualitative data analysis software NVivo. A discussion is given of how the qualitative analysis software was used in a social constructionist study, particularly outlining how it fitted with the methodological perspective adopted, and where, why and in what way rigour fitted with the underpinning epistemological position. Thus, this article illuminates how rigour can be integrated with relevance with the aid of the power and possibilities that qualitative research software possesses. In addition, an attempt is made to demonstrate how the use of CAQDAS enhances the validity of a qualitative project.

This paper aims to develop a holistic measure for analysing impression management and for detecting bias introduced into corporate narratives as a result of impression management.

Prior research on the seven impression management methods in the literature is summarised. Four of the less‐researched methods are described in detail, and are illustrated with examples from UK annual results' press releases (ARPRs). A method of computing a holistic composite impression management score based on these four impression management methods is developed, based on both quantitative and qualitative data in corporate narrative disclosures. An impression management bias score is devised to capture the extent to which impression management introduces bias into corporate narratives. An example of the application of the composite impression management score and impression management bias score methodology is provided.

While not amounting to systematic evidence, the 21 illustrative examples suggest that impression management is pervasive in corporate financial communications using multiple impression management methods, such that positive information is exaggerated, while negative information is either ignored or is underplayed.

Four impression management methods are described in detail, illustrated by 21 examples. These four methods are examined together. New impression management methods are studied in this paper for the first time. This paper extends prior impression management measures in two ways. First, a composite impression management score based on four impression management techniques is articulated. Second, the composite impression management score methodology is extended to capture a measure for bias, in the form of an impression management bias score. This is the first time outside the USA that narrative disclosures in press releases have been studied.

The purpose of this paper is to determine whether TAMS Analyzer and Viewshare are viable free and open source software data sharing and creation tools for those with limited funding and technological skills.

The participant observer method was used to collect experiential evidence while applying the tools to a collection of text-, image-, and video-based digital cultural records.

TAMS Analyzer was found to be a low barrier to entry tool for those with coding and qualitative data analysis experience. Those with general experience will be able to create datasets with the support of manuals and tutorials, while those with limited experience may find it difficult to use. Viewshare was found to be a low barrier to entry tool for sharing data online, and accessible for all skill levels.

TAMS Analyzer supports Mac and Linux platforms only, so a low-cost software recommendation was made for those in Windows environments.

Librarians can use these tools to address data access gaps while promoting library digital collections.

With a greater understanding of data tools, librarians can be advisors, collaborators, agents for data culture, and relevant participants in digital humanities scholarship.

The research evaluates both the capabilities of the tools and the barriers to using or accessing them, which are often neglected. The paper addresses a need in the literature for greater scrutiny of tools that are a critical component of the data ecology, and will further assist librarians when connecting scholars to tools of inquiry in an environment with limited funding and technical support.

This chapter summarizes many conceptual, theoretical, and methodological topics related to studying group communication using qualitative research methods. First, it explains five of the most common theoretical frameworks used by group communication scholars (i.e., symbolic convergence theory, bona fide group perspective, unobtrusive control theory, dialectical theory, and structuration theory). Next, it discusses best practices and issues related to different data collection methods including observations, historical case studies, ethnographies, focus groups, and interview studies. Then, the chapter describes two primary data analytic tools, various iterations of constant comparison method, and qualitative content analysis. Finally, the chapter describes several innovative qualitative methods that may lead to new understandings of group communication processes including discourse analysis and discourse tracing, as well as new approaches to collecting qualitative network data and mediated data. The chapter concludes with a discussion of future research suggestions.