Qualitative Data Analysis: A Procedural Comparison

Purpose This paper aims to explore the potential of computer-assisted qualitative data analysis software (CAQDAS) to be used as a corruption investigation tool to help investigators in carrying out their investigative works. Design/methodology/approach By reviewing the literature on qualitative research and fraud investigation, this exploratory study identifies similarities between the two types of inquiries and thus proposing the use of CAQDAS as an innovation in the field of corruption investigation. To demonstrate how a QDA application can support corruption investigators, NVivo is used as a case study from which various key analytical tools are discussed to highlight their potential in supporting a corruption investigation. Findings As a fundamental part of anti-corruption practice in a country, corruption investigation must be planned and executed professionally and adequately. This paper highlights various stages in fraud investigation to identify areas that can be improved with the use of a CAQDAS. Based on the discussion in this paper, the author concludes that the capability of a CAQDAS to assist users in data reduction and data display has the potential to increase the effectiveness and efficiency in various stages of a corruption investigation. Research limitations/implications Based on a self-funded study, this paper only uses a simulation case with a fictitious company to illustrate how a CAQDAS application can be used to support a corruption investigation process. Future studies may benefit from using actual corruption cases in illustrating how such an application can support the investigation process. Practical implications This paper contributes to the innovation in anti-corruption practice by proposing a new framework and tool to develop corruption investigation capacity. Originality/value This paper brings a new perspective into the field of anti-corruption to stimulate innovation in the area of corruption investigation.

Computer Assisted Qualitative Data Analysis Software (CAQDAS) are tools that help researchers to develop qualitative research projects. These software packages help the users with tasks such as transcription analysis, coding and text interpretation, writing and annotation, content search and analysis, recursive abstraction, grounded theory methodology, discourse analysis, data mapping, among several other types of analysis. This paper analyses the new paradigm of self-learning that presents itself increasingly as a competence to support learning in a proactive way. It further analyses education and CAQDAS with emphasis on the use of CAQDAS in educational research and the self-learning of CAQDAS. The study conducted had two main goals: analyse the self-learning tools of CAQDAS and identify CAQDAS's users profile regarding learning. Six software packages were selected: NVivo, Atlas.ti, Dedoose, webQDA, MAXQDA, and QDA Miner. They were then reviewed, taking into account their transversality, language, (self-learning) tools, among several other factors. The results show that there is a considerable demand for information from users regarding the execution of processes in CAQDAS, and that the packages analysed do not guide the user towards the self-learning tools that best fit their learning style.

Teaching qualitative methods to students has become more frequent in social work programs. The use of computer-assisted qualitative data analysis software has also increased. Improper use of these software programs, however, can lead to misinterpretation of qualitative data. Computer-assisted qualitative data analysis software instruction has evolved in an ad hoc manner in spite of the importance of correct use of this software. This results in a lack of thorough knowledge of computer-assisted qualitative data analysis software or knowledge of the software that poorly incorporates qualitative methodology. We propose a new model that addresses these barriers by incorporating computer-assisted qualitative data analysis software instruction with qualitative inquiry via a dual instruction method. This model centers on the collaboration between the qualitative faculty instructor and a specialized computer-assisted qualitative data analysis software trainer. The result of this is integration of qualitative research knowledge with computer-assisted qualitative data analysis software skills. Both the faculty member and specialized computer-assisted qualitative data analysis software trainer have the opportunity to work with the students and collaborate with one another. This paper describes the new model, including its conception and requirements for its implementation. We discuss our own experiences implementing the model and offer individual reflections of the faculty member, the trainer, and a student from the pilot program. The results appear to be more effective and appropriate use of this software.

This paper explores the potential of computer-assisted qualitative data analysis software (CAQDAS), specifically Nvivo 14, in facilitating the qualitative evaluation of multiple case studies. The focus is on halal purchasing strategies within micro and small enterprises (MSEs) in the food industry, a critical issue from a Shariah perspective that ensures halal integrity from source to consumer. The issue highlights that MSE leaders in Malaysia’s food industry failed to optimize halal purchasing in their management practices, which undermines their ability to increase probability. The objective is to explore the strategies for optimizing halal purchasing performance of MSEs in Malaysia’s food industry, on how these businesses navigate the requirements of halal compliance in their operational practices. Through an exploratory study, 10 MSEs were examined to investigate their halal purchasing structures, involving interviews with key stakeholders such as brand owners, company directors, halal executives, and CEOs. In-depth, semi-structured interviews provided insights into company structures, challenges, and halal purchasing strategies. Thematic analysis was employed, using an inductive pattern coding approach where codes emerged organically from the data and were categorized into themes and sub-themes. Findings revealed a variety of business types, with six individually owned companies and four family-run businesses, highlighting differences in employee numbers, business longevity, and owner demographics. The study also suggests a trend of generational succession in family-owned businesses. This research demonstrates the utility of CAQDAS in managing and analyzing complex qualitative data in case study research.

Developments during the 1990s in the use of computer software for qualitative data analysis are surveyed. Salient trends are identified as are wider issues associated with software use. Also listed are some of the resources now available to potential and actual users of computer-assisted qualitative data analysis software (CAQDAS).

For many years, qualitative analysis has largely been undertaken using manual techniques. Since the late 1980s, dedicated software has been developed to aid qualitative analysis. The first generation of computer programs was largely designed to assist researchers in managing data by enabling the structuring of information from focus groups, field notes and interviews. One of the first computer-assisted qualitative data analysis software (CAQDAS) packages (developed by Australian academic Tom Richards) was called NUD*IST, which stands for Non-numerical Unstructured Data Indexing, Searching and Theorising. It was designed to provide a program like SPSS but as a non-Statistical Package for Social Scientists. Second generation CAQDAS packages introduced functions for coding text and manipulating, searching and reporting on the coded text. This assisted researchers in the retrieval of text from data, enabled scholars to code that data and develop a system of relating codes to each other using tree-like structures.

Qualitative international research is increasingly popular in marketing, management and business practice. Cultural dimensions, most importantly language, play a central role in this research context. The importance of language in the context of questionnaire design and international data gathering has long been stressed in various sources (Pike 1966; Brislin 1970; Piekkari & Welch 2004). However, the practice of qualitative data collection and analysis has not been addressed sufficiently, although new and innovative software-based tools are available to help these efforts. This paper deals with methodological and practical issues in analysing qualitative interviews with corporate elites. We illustrate conceptual challenges in setting up qualitative projects that build on interviewing corporate elites and address practical implementation issues in terms of multilingual coding, node creation and theory building by means of computerassisted qualitative data analysis software (CAQDAS). To this end a specific empirical example will be used.

Advances in technology have provided new approaches for data collection methods and analysis for researchers. Data collection is no longer limited to paper-and-pencil format, and numerous methods are now available through Internet and electronic resources. With these techniques, researchers are not burdened with entering data manually and data analysis is facilitated by software programs. Quantitative research is supported by the use of computer software and provides ease in the management of large data sets and rapid analysis of numeric statistical methods. New technologies are emerging to support qualitative research with the availability of computer-assisted qualitative data analysis software (CAQDAS).CAQDAS will be presented with a discussion of advantages, limitations, controversial issues, and recommendations for this type of software use.

This exploratory study analysed the Threshold Learning Outcomes (TLOs) specified in the Bachelor of Laws Learning and Teaching Academic Standards Statement December 2010, and the Competency Standards for Entry-Level Lawyers for Practical Legal Training, as updated by the Australasian Professional Legal Education Council and Law Admissions Consultative Committee in February 2002 (NCS). The qualitative analysis was undertaken using the NVivo computer assisted qualitative data analysis software (CAQDAS), to investigate how skills were categorised and defined in each of the documents. The results were then analysed to compare the respective categorisation and definition of skills, and to point to potential complements, overlaps, conflicts, gaps, or blind spots, between the TLOs and the NCS. The findings, and the methodology adopted, might provide insights for future instructional design, content, and delivery of Practical Legal Training programs, and for future reviews of the TLOs and NCS.

The reviewed book concentrates on the issue of qualitative data analysis. It primarily provides practical information for students and social researchers on how to deal with textual data starting with data preparation until writing the actual report. The book proposes as a convenient and effective way to process data. But, what is additionally valuable, it suggests multiple comparative analysis techniques which would allow a researcher to go beyond simple coding and retrieving in order to achieve more plausible and in-depth interpretations. Apart from this, it introduces a reader to the analysis of biographies and narratives, as well as to computer-assisted qualitative data analysis software (CAQDAS). The book is full of practical advice, with a lot of how-to-do suggestions and useful examples, as well as indications of the possible difficulties in the analysis. Still, even if the book seems to be kept on an elementary level, it would have helped readers to better apply proposed practical advice to their research, if, before reading the book, they had acquired more general knowledge about the specificity of qualitative analysis and the various approaches used within it. URN: urn:nbn:de:0114-fqs100341

The maritime industry plays a dual role as a critical driver of global trade and a significant contributor to greenhouse gas (GHG) and air pollutant emissions, posing challenges to environmental sustainability. As key nodes in the global supply chain, ports face mounting pressure to adopt greener practices. This study synthesises insights from contemporary scientific research articles, highlighting best practices, successful case studies, and obstacles in implementing emission reduction strategies and environmentally friendly port services worldwide. A two-step mixed-methods approach was utilised, combining a systematic review of literature with qualitative data analysis. The PRISMA methodology guided the selection of 27 peer-reviewed articles from the Web of Science Core Collection, spanning the period from 2015 to 2024. Subsequently, thematic coding and comprehensive analysis were conducted using Computer-Assisted Qualitative Data Analysis Software (CAQDAS) ATLAS.ti, enabling a structured synthesis of findings related to port services and emission reduction strategies. Through this analysis, three critical themes emerged as essential for enhancing environmental sustainability in port operations: innovative technologies for emission reduction, data-driven optimization for port efficiency, and policies and governance for green ports. Drivers such as financial incentives, advanced technologies, and regulatory frameworks were identified, alongside barriers like economic feasibility, technical challenges, and organisational resistance. These themes reveal the interconnected nature of sustainability efforts and the need for collaborative strategies to overcome existing obstacles. By identifying key drivers and challenges, this research offers valuable insights for advancing sustainable practices in port operations. The findings underscore the importance of aligning technological, operational, and policy-driven measures to foster environmental efficiency while mitigating emissions. This study contributes to the growing body of knowledge on sustainable port operations, providing actionable insights for stakeholders and policymakers in the maritime industry to support the transition toward greener and more efficient port practices.

The main aim of this article is to discuss the factors a researcher should take into account when selecting the appropriate research design or method (i.e. qualitative, quantitative, and mixed-methods). The article also discusses sample size determination and sampling procedures in qualitative and quantitative research. Further, the paper has provided an examination of qualitative and quantitative data collection and analysis methods. The study used online desk research to collect data from online public access scholarly databases such as Google Scholar, ResearchGate, Academia, and many more freely accessible electronic books in research methods. Search terms that were used included, among many, the following: qualitative research, quantitative research, mixed-methods, qualitative and quantitative data collection, qualitative and quantitative data analysis; descriptive and inferential statistics. A wealth of relevant and timely scholarly literature was downloaded, read, and used to write this paper, and draw the conclusion provided. Keywords: Qualitative Research; Quantitative Research; Mixed-Methods Research; Qualitative Data Collection Techniques; Quantitative Data Collection Techniques; Qualitative Data Analysis Techniques; Quantitative Analysis Techniques; Descriptive Statistics; Inferential Statistics. DOI: 10.7176/JMCR/87-06 Publication date: November 30 th 2022

Household food security is faced with two important problems, namely how to expand income sources and how to properly distribute their income for life necessities. The purpose of this study was to analyze the comparison of the distribution patterns of household income and expenditure of wetland farmers with dry land and to analyze the determinants that affect the household food security of wetland and dryland farmers in Lombok Island. The research design used a cross-sectional study with a survey method. The collected data will be analyzed using qualitative and quantitative data analysis methods. In general, the qualitative data analysis used is policy analysis (program evaluation), institutional analysis, potential analysis, and priority determination of community-level problems. Qualitative data analysis was carried out through the process of filtering data, categorizing, concluding, and retesting. Quantitative data analysis used a logistic regression model. The results of the study concluded that: The sources of income of farmers in wetlands are more varied than those of dryland farmers. Meanwhile, wetland farmers household expenditures are relatively the same as wetland farmers. The food security of wetland farmer households (90%) is better than farmer households in dryland (83.3%). Meanwhile, wetland farmer household food insecurity is lower than wetland farmer households. The distribution pattern of wetland farmer household income comes from rice, and maize cultivation, while in dryland areas, it is sourced from rice, corn, and soybean farming. Distribution patterns Household expenditure of wetland and dryland farmers is divided into expenditures for food and non-food. The factors that determine household food security in dry and wetland areas are farmer household income.

BackgroundA focus on patient’s and service user’s perspectives regarding long-term antipsychotic treatment led to a declaration from the Norwegian Ministry of Health in 2015 to offer treatment without psychotropic medication in mental health as a voluntary option in all four health care regions. In the northernmost region, a 6-bed inpatient ward unit was established, uniquely designed to give people with severe mental illness the possibility to choose such treatment. Only voluntary admissions were accepted. The aim of the present study was to explore the motivation for applying for medication free treatment among patients with several years of treatment history due to psychosis.MethodWe performed nineteen semi-structured, in-depth interviews with persons having at least one admission at the medication free treatment ward during the period 01.01.17 – 17.10.2021. The interviews were recorded, transcribed and analysed using computer-assisted qualitative data analysis software (NVivo). Systematic Text Condensation was applied, with analysis of data from the first interview. Exploration of connections, similarities and nuances was performed through axial coding with continuous comparison of data and memo writing, followed by focused coding identifying core concepts.ResultsAll participants had a diagnosis of severe mental illness and a history of use of antipsychotics throughout many years. The motivation to apply for medication free treatment was complex. Negative experiences with medication were described, but also positive. Many had tried to taper off before, but described this as a lonely and difficult process. Five core concepts were formed and developed from the participants’ narratives: 1) Medication experiences, 2) Developing illness, 3) Treatment in general, 4) Social life and 4) Growing up.ConclusionThe concept of medication free treatment represents a salutogenetic hope for change, closely linked to self-efficacy and an experience of mastery. Potential conflicts concerning guidelines or evidence on medication does not come forward as important. Support from family and professionals is crucial, in contrast to the feeling of being alone when hoping for change. Motivational factors are closely linked to the concept of recovery, where interaction happens on both an individual and a structural level.

Farmer regeneration is a way to replace old farmers who are no longer productive with young farmers who are more productive. The disinterest of village youth in becoming farmers has resulted in a lack of interest in village youth in supporting farmer regeneration. This research aims to analyze the farmer regeneration process and analyze the influence of the variables of knowledge, perception, attitudes and interests of village youth simultaneously and partially in supporting farmer regeneration in Sukamulya Village. The research method used in this research is a mix method approach, namely a method that combines quantitative and qualitative methods. The sampling method used was a probability sampling method with a simple random sampling technique with a total of 44 village youth whose parents were farmers. This research uses primary data and secondary data. The data analysis techniques used are quantitative data analysis and qualitative data analysis. Quantitative data analysis uses multiple linear regression analysis. Meanwhile, qualitative data analysis uses data reduction, data presentation, and drawing conclusions. The results of this research are that the farmer regeneration process in Sukamulya Village has not been running optimally, this is due to the negative perception of youth towards farmers. Farmers' children are disinterested because their parents do not own agricultural land. Apart from that, Field Agricultural Instructors (PPL) play less of a role in growing young people's interest in entering the agricultural sector in order to create farmer regeneration. The results of the partial significance test show that the variable of interest (X4) has a significant effect on the farmer regeneration variable (Y) with a value of Sig. equal to 0.000 < 0.05, while the variables knowledge (X1), perception (X2), attitude (X3) do not have a significant effect on the farmer regeneration variable (Y) because the Sig. > 0.05.