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Der offene REFI-QDA-Standard ermöglicht es, Daten zwischen verschiedenen QDA-Programmen auszutauschen, vorausgesetzt, die Softwarehersteller*innen haben den Standard in ihre Programme integriert. Um die neuen Möglichkeiten aufzuzeigen, die sich aus dieser Überwindung der Beschränkung auf einzelne Analyseprogramme ergeben, beschreiben wir die Ergebnisse eines Experiments zur Nutzung des Standards in vier verschiedenen Forschungsprojekten. Das Experiment wurde im August 2019 am Lorentz Centre (Niederlande) durchgeführt. Alle beteiligten Forscher*nnen tauschten mithilfe des Standards zuvor verarbeitete Forschungsdaten zwischen zwei Softwarepaketen zur qualitativen Datenanalyse (QDAS) aus. Unser Artikel beginnt zunächst damit, die Entstehungsgeschichte des REFI-QDA Standards zu erläutern. Anschließend stellen wir die einzelnen Forschungsprojekte samt der darin verwendeten Daten vor und erläutern die Beweggründe für deren Übertragung in eine zweite QDA-Software sowie die daraus gewonnenen Erkenntnisse. Im letzten Schritt fassen wir den Mehrwehrt des REFI-QDA-Standards zusammen und diskutieren Aspekte, die bei einem Transfer zwischen QDAS zu beachten sind.

This paper describes recent issues and developments in Qualitative Data Analysis Software (QDAS) as presented in the opening plenary at the KWALON 2016 conference. From a user perspective, it reflects current features and functionality, including the use of artificial intelligence and machine learning; implications of the cloud; user friendliness; the role of digital archives; and the development of a common exchange format. This user perspective is complemented with the views of software developers who took part in the “Rotterdam Exchange Format Initiative,” an outcome of the conference.

This article offers a step-by-step description of how qualitative data analysis software can be used for a qualitative content analysis of newspaper articles. Using NVivo as an example, it illustrates how software tools can facilitate analytical flexibility and how they can enhance transparency and trustworthiness of the qualitative research process. Following a brief discussion of the key characteristics, advantages and limitations of qualitative data analysis software, the article describes a qualitative content analysis of 230 newspaper articles, conducted to determine international media perceptions of New Zealand's environmental performance in connection with climate change and carbon emissions. The article proposes a multi-level coding approach during the analysis of news texts that combines quantitative and qualitative elements, allowing the researcher to move back and forth in coding and between analytical levels. The article concludes that while qualitative data analysis software, such as NVivo, will not do the analysis for the researcher, it can make the analytical process more flexible, transparent and ultimately more trustworthy.URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs150283

Accurate electric load forecasting can provide critical support to makers of energy policy and managers of power systems. The support vector regression (SVR) model can be hybridized with novel meta-heuristic algorithms not only to identify fluctuations and the nonlinear tendencies of electric loads, but also to generate satisfactory forecasts. However, many such algorithms have numerous drawbacks, such as a low population diversity and trapping at local optima, which are problems of premature convergence. Accordingly, approaches to increase the accuracy of forecasting must be developed. In this investigation, quantum computing mechanism is used to quantamize dragonfly behaviors to enhance the searching effectiveness of the dragonfly algorithm, namely QDA. In addition, conducting the data preprocessing by the complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) is useful to improve the forecasting accuracy. Thus, a new electric load forecasting model, the CEEMDAN-SVRQDA model, that combines the CEEMDAN and hybridizes the QDA with an SVR model, is proposed to provide more accurate forecasts. Two numerical examples from the Tokyo Electric Power Company (Japan) and the National Grid (UK) demonstrate that the proposed model outperforms other models.

Improvements to qualitative data analysis software (QDAS) have both facilitated and complicated the qualitative research process. This technology allows us to work with a greater volume of data than ever before, but the increased volume of data frequently requires a large team to process and code. This paper presents insights on how to successfully structure and manage a team of staff in coding qualitative data. We draw on our experience in team-based coding of 154 interview transcripts for a study of school meal programs. The team consisted of four coders, three senior reviewers, and a lead analyst and external qualitative methodologist who shepherded the coding process together. Lessons learned from this study include: 1) establish a strong and supportive management structure; 2) build skills gradually by breaking training and coding into “bite-sized” pieces; and 3) develop detailed reference materials to guide your coding team.

While a literature review is a necessary milestone to be completed by all researchers in a timely and efficient manner, it is often one of the most difficult aspects of the research journey. Moreover, traditional approaches often leave novice researchers, to struggle with the conceptualisation of their literature review, now complicated by the overwhelming quantity of research available online. This paper presents a rationale the use of Qualitative Data Analysis Software (QDAS) programs for literature reviews. QDAS tools allow the researcher to explore large amounts of textual documents to see patterns. These programs are often overlooked by novice researchers due to their complexity and the lack of expertise provided to assist them. To combat this dilemma our paper outlines the N7+1 approach to using Nvivo11™ for literature reviews. Through this approach researchers can develop an “auditable footprint,” keep everything in one place, and go paperless.

Bee products are a well-known remedy against numerous diseases. However, from the consumers’ perspective, it is essential to define factors that can affect their sensory acceptance. This investigation aimed to evaluate the volatile and sensory profiles, and sugar composition of beeswax, beebread, pollen, and honey. According to the HS-SPME/GC-MS results, 20 volatiles were identified in beeswax and honey, then 32 in beebread, and 33 in pollen. Alkanes were found to dominate in beeswax, beebread, and pollen, while aldehydes and monoterpenes in honey. In the case of sugars, a higher content of fructose was determined in beebread, bee pollen, and honey, whereas the highest content of glucose was assayed in beeswax. In the QDA, the highest aroma intensity characterized as honey-like and sweet was found in honey, while the acid aroma was typical of beebread. Other odor descriptors, including waxy, pungent, and plant-based aromas were noted only in beeswax, honey, and pollen, respectively.

This text results from research developed in the Postgraduate Program in Education at the Tiradentes University (Unit), in partnership with the University of Aveiro, Portugal, in 2019 and 2020. The objective sought to describe how the Visualization of Data (VD) is represented in the analysis of qualitative data with the support of Qualitative Data Analysis Software (QDAS). To achieve this objective, we reached the inclusion/exclusion criteria. Seven software frequently used today, trying to understand the most frequent representations of HV in QDAS, their structuring, and how they can contribute to the phases of organisation and analysis in a scenario that can vary from small to large amounts of data. The results show that the QDAS can help the researcher visualise the qualitative data analysed with transparency through data visualisation representations that stood out in tables, charts, maps, and representations with movements. During the analysis, it was also observed that each software offers representations in different ways. The type of user/researcher interaction with the generated representations has been an exclusive phenomenon of digital technologies, which visually improves how scientific production knowledge can better circulate knowledge production.

The higher alcohols 2-phenylethanol, tryptophol, and tyrosol are a group of yeast-derived compounds that have been shown to affect the aroma and flavour of fermented beverages. Five variants of the industrial wine strain AWRI796, previously isolated due to their elevated production of the ‘rose-like aroma’ compound 2-phenylethanol, were characterised during pilot-scale fermentation of a Chardonnay juice. We show that these variants not only increase the concentration of 2-phenylethanol but also modulate the formation of the higher alcohols tryptophol, tyrosol, and methionol, as well as other volatile sulfur compounds derived from methionine, highlighting the connections between yeast nitrogen and sulfur metabolism during fermentation. We also investigate the development of these compounds during wine storage, focusing on the sulfonation of tryptophol. Finally, the sensory properties of wines produced using these strains were quantified at two time points, unravelling differences produced by biologically modulating higher alcohols and the dynamic changes in wine flavour over aging.

Purpose – This study investigates the barriers to the adoption of Virtual Reality (VR) in the tourism industry. Although VR has great potential to enhance the tourist experience, the adoption of this technology is still limited in the tourism sector. Building on the fundamental principles of the Technology-Organization-Environment (TOE) theory and its contribution to perceptions of technology adoption, this study aims to fill the knowledge gap regarding the specific barriers to VR adoption by tourism enterprises. Methodology – To achieve this objective, interviews were conducted with managers of tourism companies, and the data was analysed using qualitative methodology through MAXQDA 20 software. Conclusions – The results reveal that the main barriers identified by managers mainly include lack of knowledge about VR, particularly in the tourism sector. The perceived lack of usefulness, limited experience with the technology, and reluctance to invest in technological equipment also emerge as barriers to VR adoption. Originality of research – This study can help companies in the tourism sector to develop more effective strategies to overcome these barriers, thereby improving the tourist experience and increasing their competitiveness in the market using VR equipment.