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The purpose of this paper is to support potential users of thematic analysis (as outlined by Virginia Braun and Victoria Clarke). Researchers with the intention of applying thematic analysis are advised to consider the theoretical framework of their work and how differing ontological and epistemological standpoints influences their approach to thematic analysis.

This paper considers aspects of the work that has been done around thematic analysis to guide future potential users. The flexibility, recipe-like use and ease of thematic analysis are discussed, along with guidance being offered to avoid the seemingly common trip hazards of navigating the approach.

Users of thematic analysis seemingly continue to cite Braun and Clarke's thematic analysis whilst repeatedly contradicting the guidance of their work.

Readers of this paper that intend on using thematic analysis will be redirect to further learning, personal reflection and adjustments to the way in which they engage with, utilise and report their qualitative work using Braun and Clarke's approach to thematic analysis.

It is possible that past research that has been reported as using Braun and Clarke's approach to thematic analysis has been misinterpreted, misunderstood and misused. This as a result of researchers potentially having failed to embrace the need to engage in reflexive, epistemological and ontologically clear processes during the use of thematic analysis.

While Braun and Clarke's approach to thematic analysis seems to have developed a significant level of popularity and use, the finer but impactful understanding of the approach has been overlooked. Other work has been done in relation to thematic analysis but there has not been anything to support thinking and learning around the suitable, accurate and knowledgeable use of the approach.

Little is known about the extent to which management and engineering publications dedicated to the study of quality management topics make use of mixed methods, what types of studies have been conducted and how effective mixed methods have been. The aim of the current paper is to analyse how mixed methods have been used in quality management research.

To address this purpose, a bibliometric analysis was conducted of papers using mixed methods designs to investigate quality management issues and published in the SCOPUS database. CiteSpace software was used to assist in the categorisation and mapping process.

Ninety articles were identified and analysed. The results show that mixed methods are mainly used either to compare different perspectives drawn from quantitative and qualitative data or to develop better measurement instruments. Sequential mixes occur more often than concurrent approaches. Moreover, there is a link between the purpose of the study and the approaches followed to combine qualitative and quantitative methods. Yet, the contribution of the use of mixed methods to achieving the aims of the study is not easy to assess as the purposes of using mixed methods are often not clearly stated.

As one of the first papers to examine how qualitative and quantitative methods are being combined in quality management research, this study is expected to contribute to the literature by providing some insights into how mixed methods can be more effectively used in this field.

The objective of this paper is to further the understanding of netnography as a research method for supply chain academics. Netnography is a method for gathering and gaining insight from industry-specific online communities. We prescribe that viewing netnography through the lens of the supply chain will permit researchers to explore, discover, understand, describe or report concepts or phenomena that have previously been studied via survey research or quantitative modeling.

To introduce netnography to supply chain research, we propose a framework to guide how netnography can be adopted and used. Definitions and directions are provided, highlighting some of the practices within netnographic research.

Netnography provides the researcher with another avenue to pursue answers to research questions, either alone or in conjunction with the dominant methods of survey research and quantitative modeling. It provides another tool in the researchers’ toolbox to engage practitioners in the field.

The development of netnography as a research method is associated with Robert Kozinets. He developed the method to study online communities in consumer behavior. We justify why this method can be applied to supply chain research, how to collect data and provide research examples of its use. This technique has room to grow as a supply chain research method.

Cybersecurity competitions can effectively develop skills, but engaging a wide learner spectrum is challenging. This study aims to investigate the perceptions of cybersecurity competitions among Reddit users. These users constitute a substantial demographic of young individuals, often participating in communities oriented towards college students or cybersecurity enthusiasts. The authors specifically focus on novice learners who showed an interest in cybersecurity but have not participated in competitions. By understanding their views and concerns, the authors aim to devise strategies to encourage their continuous involvement in cybersecurity learning. The Reddit platform provides unique access to this significant demographic, contributing to enhancing and diversifying the cybersecurity workforce.

The authors propose to mine Reddit posts for information about learners’ attitudes, interests and experiences with cybersecurity competitions. To mine Reddit posts, the authors developed a text mining approach that integrates computational text mining and qualitative content analysis techniques, and the authors discussed the advantages of the integrated approach.

The authors' text mining approach was successful in extracting the major themes from the collected posts. The authors found that motivated learners would want to form a strategic way to facilitate their learning. In addition, hope and fear collide, which exposes the learners’ interests and challenges.

The authors discussed the findings to provide education and training experts with a thorough understanding of novice learners, allowing them to engage them in the cybersecurity industry.

This study aims to examine the key antecedents influencing the private firm’s intention to adopt big data analytics (BDA) in developing economies. To do so, the study follows the sequential explanatory approach.

To test the hypothesized model that draws on the technology–organization–environment (TOE) framework paired with the diffusion of innovation (DOI) theory, a purposive sampling technique was applied to gather data from 156 IT and management domain experts from the private firms that intend to adopt BDA and operate in Pakistan’s service industry, including telecommunication, information technology, agriculture, and e-commerce. The data were analysed using the partial least squares structural equations modelling (PLS-SEM) technique and complemented with qualitative analysis of 10 semi-structured interviews in NVIVO 12 based on grounded theory.

The empirical findings revealed that the two constructs – perceived benefits and top management support – are the powerful drivers of a firm’s intention to adopt BDA in the private sector, whereas IT infrastructure, data quality, technological complexity and financial readiness, along with the moderators, BDA adoption of competitors and government policy and regulation, do not significantly influence the intention. In addition, the qualitative analysis validates and further complements the SEM findings.

Unlike the previous studies on technology adoption, this study proposed a unique research model with contextualized indicators to measure the constructs relevant to private firms, based on the TOE framework and DOI theory, to investigate the causal relationship between drivers and intention. Furthermore, the findings of PLS-SEM were complemented by qualitative analysis to validate the causation. The findings of this study have both theoretical and practical implications.

Proper performance assessment of residential building renovation is crucial to sustainable urban development. However, a comprehensive review of the literature in this research domain is lacking. This study aims to uncover the study trend, research hotspots, prominent contributors, research gaps and directions in this field.

With a hybrid review approach adopted, relevant literature was examined in three stages. In Stage 1, literature retrieved from Scopus was screened for their relevance to the study topic. In Stage 2, bibliographic data of the shortlisted literature underwent scientometric analyses by the VOSviewer software. Finally, an in-depth qualitative review was made on the key literature.

The research hotspots in performance assessment of residential building renovation were found: energy efficiency, sustainability, thermal comfort and life cycle assessment. After the qualitative review, the following research gaps and future directions were unveiled: (1) assessments of retrofits incorporating renewable energy and energy storage systems; (2) evaluation of policy options and financial incentives to overcome financial constraints; (3) establishment of reliable embodied energy and carbon datasets; (4) indoor environment assessment concerning requirements of COVID-19 prevention and involvement of water quality, acoustic insulation and daylighting indicators; and (5) holistic decision-making model concerning residents' intentions and safety, health, well-being and social indicators.

Pioneered in providing the first comprehensive picture of the assessment studies on residential building renovations, this study contributes to offering directions for future studies and insights conducive to making rational decisions for residential building renovations.

In recent decades, managerial desire to use internal audit services to promote well-controlled organizational processes has significantly increased in the public sector. Yet, there is rare information on how internal audits may effectively be implemented in the public sector. The present research aims to design a comprehensive internal audit effectiveness model for the public sector.

This research is an applied mixed-methods (qualitative–quantitative) and descriptive survey study. The research population in both qualitative and quantitative sections included all internal and external audit managers and staff of Iraqi public organizations. The study sample of the qualitative section included 28 audit managers and staff selected using purposive sampling, and the study sample of the quantitative section included 399 individuals selected using convenience sampling. The data collection instruments in the qualitative and quantitative sections included semi-structured interviews and questionnaires, respectively. Data analysis was carried out using thematic analysis in Atlas.ti software in the qualitative section. Quantitative analysis and model validation were also performed using path analysis and structural equation modeling in Smart-PLS software in the quantitative section.

The results of the qualitative section led to the identification of 38 effectiveness factors among seven main categories, which were finally presented in the form of a comprehensive model. The main categories included the communication between internal and external auditors, granting independence and authority to internal auditors, providing specialized human resources, providing technological resources, developing management support, strengthening organizational culture and developing audit plans. In the qualitative section, the model was validated and confirmed. Quantitative results further showed that the compilation of audit plans and the development of management support were the most important factors.

The present study contributes to the literature by providing a comprehensive framework on internal audit with an emphasis on resource-based theory and reducing the research gap in the field of agents influencing internal audit efficacy in the public sector of developing countries. Further, the study provides insights into an under-studied developing country, Iraq.

The novel blockchain technology can be leveraged, owing to the growth in computing power and its widespread applications. This study aims to understand the challenges of adopting blockchain technology in the financial sector, organise them into a model and classify them for systematic address.

Interpretive Structural Modeling (ISM) has been carried out along with MICMAC (Matrice d’impacts croisés multiplication appliquée á un classment) analysis to hierarchically structure blockchain adoption problems and categorise the challenges into four classes-autonomous, dependent, linkage and independent for better addressing. The study also uses content analysis using NVivo software.

The digraph depicts the hierarchical challenge model. Vulnerability to financial crimes and glitches, privacy issues and geopolitical tensions due to cross-border transactions are the dependent variables. Complex architecture to comprehend, code and fix, the need for new financial intermediaries, complexity in auditing and the lack of unified governance and coordination among institutions and regulators are the independent variables. The digraph, which is also justified by the qualitative content analysis, is beneficial for stakeholders to systematically address the interdependent challenges associated with blockchain implementations in finance to foster its favourable adoption.

The challenges in the adoption of blockchain should be resolved to allow the implementation of this technology in various finance domains. This study enables organisations to carry out resource planning and systematically address these challenges to leverage the advantages of blockchain.

The results of the present study can help in promoting the proliferation of blockchain for faster, cost-effective, transparent and secure financial transactions and foster innovative and new business models for economic growth.

The development of technology has brought about significant changes in the financial sector. Blockchain is a technological advancement that aims to bring security and transparency to transactions. There has been no research leveraging ISM-MICMAC to hierarchically organise and classify the blockchain challenges in the financial sector, a critical one. The research also uses content analysis which is seldom found along with ISM-MICMAC.

We present configurational theorising as a novel approach to developing middle-range theory in two steps: (1) we illustrate configurational theorising as a new form of supply chain inquiry by connecting its philosophical assumptions with a methodological execution, and (2) we generate new insights underpinning a middle-range theory for supply chain resilience.

We synthesise information from a range of sources and invoke ‘critical realism” to suggest a five-phase configurational theorising roadmap to develop middle-range theory. We demonstrate this roadmap to explain supply chain resilience by analysing qualitative data from 22 organisations within the Australian food supply chain.

Coopetition and supply chain collaboration are necessary causal conditions, but they need to combine with either supply chain agility or multi-sourcing strategy to build supply chain resilience. Asymmetrical analyses showed that the simultaneous absence of supply chain collaboration, supply chain agility and multi-sourcing results in low supply chain resilience, but coopetition was indifferent to low supply chain resilience. Similarly, high supply chain resilience is possible with the non-presence of supply chain agility and multi-sourcing.

The configurational middle-range theorising roadmap presented and empirically tested in this paper constitutes a substantial advancement to both theory and the methodological domain.

This is the first attempt at developing a middle-range theory for supply chains by explicitly drawing on configurational theorising.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.