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The metaverse has become one of the most popular concepts of recent times. Companies and entrepreneurs are fiercely competing to invest and take part in this virtual world. Millions of people globally are anticipated to spend much of their time in the metaverse, regardless of their age, gender, ethnicity, or culture. There are few comprehensive studies on the positive/negative sentiment and effect of the newly identified, but not well defined, metaverse concept that is already fast evolving the digital landscape. Thereby, this study aimed to better understand the metaverse concept, by, firstly, identifying the positive and negative sentiment characteristics and, secondly, by revealing the associations between the metaverse concept and other related concepts. To do so, this study used Natural Language Processing (NLP) methods, specifically Artificial Intelligence (AI) with computational qualitative analysis. The data comprised metaverse articles from 2021 to 2022 published on The Guardian website, a key global mainstream media outlet. To perform thematic content analysis of the qualitative data, this research used the Leximancer software, and the The Natural Language Toolkit (NLTK) from NLP libraries were used to identify sentiment. Further, an AI-based Monkeylearn API was used to make sectoral classifications of the main topics that emerged in the Leximancer analysis. The key themes which emerged in the Leximancer analysis, included \"metaverse\", \"Facebook\", \"games\" and \"platforms\". The sentiment analysis revealed that of all articles published in the period of 2021–2022 about the metaverse, 61% (n = 622) were positive, 30% (n = 311) were negative, and 9% (n = 90) were neutral. Positive discourses about the metaverse were found to concern key innovations that the virtual experiences brought to users and companies with the support of the technological infrastructure of blockchain, algorithms, NFTs, led by the gaming world. Negative discourse was found to evidence various problems (misinformation, harmful content, algorithms, data, and equipment) that occur during the use of Facebook and other social media platforms, and that individuals encountered harm in the metaverse or that the metaverse produces new problems. Monkeylearn findings revealed “marketing/advertising/PR” role, “Recreational” business, “Science & Technology” events as the key content topics. This study’s contribution is twofold: first, it showcases a novel way to triangulate qualitative data analysis of large unstructured textual data as a method in exploring the metaverse concept; and second, the study reveals the characteristics of the metaverse as a concept, as well as its association with other related concepts. Given that the topic of the metaverse is new, this is the first study, to our knowledge, to do both.

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

How should firms configure organizational capabilities to achieve competitive advantage in complex digital environments? To answer this question, we investigate parsimonious configurations for high firm performance in digital environments characterized by organized complexity. We adopt a configurational perspective accompanied by a fuzzy-set qualitative comparative analysis (fsQCA) to explicate complex nonlinear relationships among key digital and non-digital capabilities in the form of conjunction, equifinality, and asymmetry in producing the outcome. With this approach, we shift attention from individual capabilities to configurations of capabilities to develop a better understanding of the complex role of IT in the digital world. Our analyses, using a rare and unique dataset of 376 observations for organizations in healthcare, education, manufacturing, and service sectors in the United States, reveal three key findings. First, IT-enabled information analytics capability alone is neither necessary nor sufficient in any configuration for high performance; however, it is an important component of the configurations in which it plays multifaceted roles varying from an enabling role in some contexts, to no role or a counterproductive role in other contexts. Second, we document a few parsimonious configurations emergent from complex nonlinear interactions among six organizational capabilities. Interestingly, these configurations often have an isomorphic structure that produces both high financial performance and high customer performance simultaneously. Third, the structures of configurations for high performance differ from those of not-high performance, suggesting an asymmetric view of causality that underpins organizational performance. Together, the findings provide implications for further research on complexity theory in digital business strategy, and for managers to view and redesign digital business strategy as configurations of IT and organizational capabilities.

Qualitative comparative analysis (QCA) allows researchers to study how configurations of conditions lead to outcomes and, thereby, richly explain the dynamics of complex digital phenomena. To advance discussion on QCA in the information systems (IS) discipline, we introduce its fundamental concepts and offer guidelines for authors on how to apply QCA to advance IS research. We also provide checklists for reviewers of QCA papers. We illustrate how to apply our guidelines through two exemplar studies. In the first exemplar study, we focus on IT-business strategic alignment to study the influence that different forms of alignment have on firm performance. In the second exemplar study, we use the perspective of the integrated technology acceptance model to explain an individual’s intention to use a digital assistant. The contrasting results from both studies highlight how to use QCA to derive robust and reproducible results. By doing so, we contribute to encouraging IS scholars to use QCA to develop sophisticated models that accurately depict real-world IS phenomena.

Digital technologies are radically changing how established organizations design novel services. Digital transformation (DT) strategies are executed to manage the transition from product-centric to service-centric business models based on digital technologies. However, little is known about what configurations of DT strategies lead to successful digital service innovation (DSI) in established organizations. We employ fuzzy-set Qualitative Comparative Analysis on a set of 17 case studies of DT strategies from established organizations with different industry backgrounds. We identify several distinct configurations of DT strategies that lead to successful and unsuccessful DSI. Based on these configurations, we deduce that the threat of digital disruption negatively impacts an organization’s innovation activities. Furthermore, we find that strategic partnerships can be leveraged by organizations that face an imminent threat of digital disruption while organizations with competitive advantages may rely on “do-it-yourself” approaches. Lastly, we find that the involvement of a C-level executive is a necessary requirement for successful DSI. Our results contribute to theory by integrating research on DSI and DT, providing a perspective on DSI failure, and employing a configurational research approach that allows us to highlight interdependencies between factors as well as insights into the individual factors. Furthermore, we provide actionable recommendations for executives.

Purpose The COVID-19 pandemic and recent disruptive events are affecting firms’ operations and supply chain networks on a large scale, causing disturbances in supply, demand, production and logistics activities. Although supply chain resilience (SCR) research has received large attention in recent years, the purpose of this paper is to offer an original contribution by exploring how complex configurations and interactions between SCR strategies and capacities can lead to resilience. Design/methodology/approach This study investigates the configurations of SCR strategies and capacities using a fuzzy-set qualitative comparative analysis. Findings First, the findings reveal different SCR strategy configurations through the lens of absorptive, reactive and restorative capacities to achieve resilience. Second, this study applies the contingent resource-based view (CRBV) perspective to interpret how organizations can achieve resilience before, during and after a disruptive event. Third, it offers an analysis of different groups of organizations, based on the adoption of different SCR strategies and capacities. Originality/value This study identifies a set of equifinal SCR strategies and capacity configurations that can be implemented to cope with a disruptive event and lead to resilience. It also enriches the research addressing the consecutive phases of SCR investments, developing the CRBV perspective. In our results, five solutions describe organizations that invest in absorptive capacities, representing an ex ante readiness.

The purpose of this article is to provide guidance to scholars regarding key aspects of writing qualitative manuscripts. The aim is to offer practical suggestions as opposed to examining epistemological or theoretical issues and debates related to qualitative family research. The authors begin by providing guideposts in writing the major sections of a qualitative article (Introduction, Method, Results, and Discussion). In doing so, they address issues such as composing a literature review, providing sufficient details on the qualitative data analysis, and effectively communicating the contribution of the work. They end by providing some general suggestions for scholars seeking professional development in qualitative research methods and analysis.

Qualitative comparative analysis (QCA) appears to offer a systematic means for case-oriented analysis. The method not only offers to provide a standardized procedure for qualitative research but also serves, to some, as an instantiation of deterministic methods. Others, however, contest QCA because of its deterministic lineage. Multiple other issues surrounding QCA, such as its response to measurement error and its ability to ascertain asymmetric causality, are also matters of interest. Existing research has demonstrated the use of QCA on real data, but such data do not allow one to establish the method's efficacy, because the true causes of real social phenomena are always contestable. In response, the authors analyze several simulated data sets for which true causal processes are known. They find that QCA finds the correct causal story only 3 times across 70 different solutions, and even these rare successes, on closer examination, actually reveal additional fundamental problems with the method. Further epistemological analyses of the results find key problems with QCA's stated epistemology, and results indicate that QCA fails even when its stated epistemological claims are ontologically accurate. Thus, the authors conclude that analysts should reject both QCA and its epistemological justifications in favor of existing effective methods and epistemologies for qualitative research.

Background Healthy Start (HS) is a government scheme in England, Wales and Northern Ireland that offers a financial payment card and free vitamins to families experiencing low income. Pregnant women and families with children < 4 years can use the HS card to buy fruit, vegetables, cow’s milk, infant formula and pulses. HS was fully digitalised in March 2022. While digitalisation has improved the user experience for many families, in the context of the cost-of-living crisis and increasing dietary inequalities, it is important to understand why HS is not reaching more families. This study aimed to (i) assess the perceptions and experiences of HS from stakeholders across the system including those who promote, implement and are eligible for HS, and (ii) identify recommendations to improve the scheme’s effectiveness and uptake. Methods The study design was a post-implementation rapid qualitative evaluation using stakeholder interviews. Data were collected between January and June 2023 via semi‐structured interviews (50% online; 50% in person) with 112 stakeholders, including parents ( n  = 59), non‐government organisations ( n  = 13), retailers ( n  = 11) and health and community professionals ( n  = 29) at national and local levels. Findings were confirmed by a sub-sample of participants. Results Six core themes cut across stakeholders’ perceptions and experiences, and stakeholders collectively outlined seven recommendations they felt could be acted upon to maximise uptake and efficiency of HS, with actions at both national and local levels. A novel finding from this study is that raising awareness about HS alone is unlikely to result automatically or universally in higher uptake rate. Recommendations include: continuing to provide this scheme that is universally valued; the need for many families to be provided with a helping hand to successfully complete the application; reframing of the scheme as a child’s right to food and development to ensure inclusivity; improved leadership, coordination and accountability at both national and local levels. Conclusions HS provides benefits for child development and family wellbeing. The study’s recommendations should be actioned by national and local governments to enable all families eligible for the scheme to benefit from this nutritional safety net.

Background Qualitative Comparative Analysis (QCA) is a method for identifying the configurations of conditions that lead to specific outcomes. Given its potential for providing evidence of causality in complex systems, QCA is increasingly used in evaluative research to examine the uptake or impacts of public health interventions. We map this emerging field, assessing the strengths and weaknesses of QCA approaches identified in published studies, and identify implications for future research and reporting. Methods PubMed, Scopus and Web of Science were systematically searched for peer-reviewed studies published in English up to December 2019 that had used QCA methods to identify the conditions associated with the uptake and/or effectiveness of interventions for public health. Data relating to the interventions studied (settings/level of intervention/populations), methods (type of QCA, case level, source of data, other methods used) and reported strengths and weaknesses of QCA were extracted and synthesised narratively. Results The search identified 1384 papers, of which 27 (describing 26 studies) met the inclusion criteria. Interventions evaluated ranged across: nutrition/obesity ( n  = 8); physical activity ( n  = 4); health inequalities ( n  = 3); mental health ( n  = 2); community engagement ( n  = 3); chronic condition management ( n  = 3); vaccine adoption or implementation ( n  = 2); programme implementation ( n  = 3); breastfeeding ( n  = 2), and general population health ( n  = 1). The majority of studies ( n  = 24) were of interventions solely or predominantly in high income countries. Key strengths reported were that QCA provides a method for addressing causal complexity; and that it provides a systematic approach for understanding the mechanisms at work in implementation across contexts. Weaknesses reported related to data availability limitations, especially on ineffective interventions. The majority of papers demonstrated good knowledge of cases, and justification of case selection, but other criteria of methodological quality were less comprehensively met. Conclusion QCA is a promising approach for addressing the role of context in complex interventions, and for identifying causal configurations of conditions that predict implementation and/or outcomes when there is sufficiently detailed understanding of a series of comparable cases. As the use of QCA in evaluative health research increases, there may be a need to develop advice for public health researchers and journals on minimum criteria for quality and reporting.