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The study aims to promote the use of qualitative methods in service research by investigating how these methods are reported in service journals, how the level of reporting has evolved and whether methodological reporting influences the downloads or citations received by qualitative articles.

Methodological reporting practices were identified through content analysis of 318 qualitative articles published in three major service research journals and comparison with prior methodological literature. Regression analysis was used to test how the level of methodological reporting influences article downloads and citations.

The study identifies 29 reporting practices related to 9 key methodological reporting areas. The overall level of methodological reporting in published qualitative articles has increased over time. While differences in the level of reporting between service journals persist, they are narrowing. The level of methodological reporting did not influence downloads or citations of qualitative articles.

Service scholars using qualitative methods should pay attention to methodological reporting as it can improve the chances of being published. Factors such as theoretical contributions are likely to have a greater influence on article impact than methodological reporting.

No prior study has explored methodological reporting practices across different qualitative methodologies or how reporting influences article impact. For authors, reviewers and editors, the study provides an inventory of reporting practices relevant for evaluating qualitative articles, which should lower barriers for qualitative methods in service research by providing practical guidelines on what to focus on when reporting and assessing qualitative research.

This commentary discusses the value of generative artificial intelligence (AI) for qualitative research in phygital settings to understand the customer experience.

The critical and logical analysis is based on current knowledge of generative AI.

Generative AI seems very useful for qualitative research in phygital settings to understand the customer experience and should be used in qualitative research projects. Generative AI can provide much-needed validation of the subjective nature of qualitative research and can also generate insights beyond human intuition.

The study is based on current technology, which changes fast. In the future, the skills of qualitative researchers may become outdated, relegating them to the role of prompt engineers.

Technology, and especially generative AI, will be a key tool for practitioners as they conduct practical research.

Qualitative researchers should overcome potential anti-technology speciesism and embrace the potential of generative AI.

This commentary provides insights into the role of generative AI for qualitative research in phygital settings.

Large-scale text-based data increasingly poses methodological challenges due to its size, scope and nature, requiring sophisticated methods for managing, visualizing, analyzing and interpreting such data. This paper aims to propose semantic network analysis (SemNA) as one possible solution to these challenges, showcasing its potential for consumer and marketing researchers through three application areas in phygital contexts.

This paper outlines three general application areas for SemNA in phygital contexts and presents specific use cases, data collection methodologies, analyses, findings and discussions for each application area.

The paper uncovers three application areas and use cases where SemNA holds promise for providing valuable insights and driving further adoption of the method: (1) Investigating phygital experiences and consumption phenomena; (2) Exploring phygital consumer and market discourse, trends and practices; and (3) Capturing phygital social constructs.

The limitations section highlights the specific challenges of the qualitative, interpretivist approach to SemNA, along with general methodological constraints.

Practical implications highlight SemNA as a pragmatic tool for managers to analyze and visualize company-/brand-related data, supporting strategic decision-making in physical, digital and phygital spaces.

This paper contributes to the expanding body of computational, tool-based methods by providing an overview of application areas for the qualitative, interpretivist approach to SemNA in consumer and marketing research. It emphasizes the diversity of research contexts and data, where the boundaries between physical and digital spaces have become increasingly intertwined with physical and digital elements closely integrated – a phenomenon known as phygital.

This paper on the prevalence of attention deficit hyperactive disorder (ADHD) in schools holds immense significance due to its unique contribution to the existing body of knowledge. This study stands out as one of the few conducted in Uganda and the entire African continent. The purpose of this study is to establish the prevalence of ADHD symptoms in government primary schools in Wakiso District, Uganda. And also inform educational policies and interventions tailored to address the needs of children with ADHD in Uganda and globally.

The research paradigm adopted was pragmatism, an explanatory sequential mixed methods approach was used, with a quantitative sample of 1,067 participants (learners), 64 teachers who underwent a series of training to equip them with the necessary knowledge about ADHD filled questionnaires for the 1,067 learners, four teachers selected in each school, one teacher per class and a qualitative sample of 32 teachers and one key informant from 16 primary schools. Random and purposive sampling was used. The strengths and weaknesses of ADHD symptoms and normal behavior scale questionnaire was used for quantitative data collection, while qualitative data was gathered through interviews, observations and focus group discussion.

The results revealed an overall prevalence of ADHD symptoms of 11.60%, with inattention symptoms being more dominant than hyperactive/impulsivity symptoms (8.82%). There was no significant difference in prevalence between boys and girls, with primary one pupils having the highest prevalence of symptoms and primary four pupils having the lowest. Pupils aged 10–13 may be less susceptible to ADHD symptoms. The most prevalent symptoms were linked to interrupting or intruding behavior, failure to give attention to detail and inability to play quietly. Qualitative data from the key informant’s observations and teacher focus groups supported these findings.

Limited geographic scope: The study was conducted in only one district, Wakiso, in Uganda. However, this district is very densely populated with people from different cultural and economic background, making it representative of the entire country Uganda. While the response rates for both the quantitative and qualitative components were relatively high (95% and 84%, respectively), there is a possibility that those who chose to participate may have different experiences. But the response rate provided sufficient data for analysis according to the researcher.

The researcher recommends that further research is needed in other districts; also, there is a need to develop early intervention strategies for teachers and parents with ADHD children. More research is needed to better understand the primary causes and risk factors associated with ADHD in primary school children.

This study stands out as one of the few conducted in Uganda and the entire African continent on ADHD. By addressing this research gap, the paper adds valuable insights to the field of ADHD research, shedding light on the prevalence of ADHD symptoms, which can be used to investigate the impact of ADHD on academic performance within the Ugandan education system further. The findings of this study have the potential to inform educational policies and interventions tailored to address the needs of children with ADHD in Africa and beyond.

The purpose of this mixed-methods study was to explore how medical secretaries experience digital transformation in a Swedish healthcare organisation, with a focus on workplace climate and health.

Data were collected using a sequential exploratory mixed-methods design based on grounded theory, with qualitative data collection (a Quality Café and individual interviews) followed by quantitative data collection (a questionnaire).

Four categories with seven underlying factors were identified, emphasising the crucial need for effective organisation of digital transformation. This is vital due to the increased knowledge and skills in utilising technology. The evolving roles and responsibilities of medical secretaries in dynamic healthcare settings should be clearly defined and acknowledged, highlighting the importance of professionality. Ensuring proper training for medical secretaries and other occupations in emerging techniques is crucial, emphasising equal value and knowledge across each role. Associations were found between some factors and the health of medical secretaries.

This study adds to the knowledge on digital transformation in healthcare by examining an important occupation. Most data were collected online, which may be a limitation of this study.

Several aspects of the medical secretaries’ experiences were identified. Knowledge of these is valuable for healthcare managers to make digital transformation more effective while avoiding excessive strain on medical secretaries.

Medical secretaries are expected to contribute to the digitalisation of healthcare. However, minimal research has been conducted on the role of medical secretaries in workplace digitalisation, focusing on workplace roles and its dynamics.

Building permitting is mostly a manual, labor intensive and time-consuming process. Initiatives for streamlining the process are not always helpful since they often fail to address the core problems within the process. A framework for modeling the permitting process can be useful to identify bottlenecks, core challenges and best practices. Hence, the authors aim to demonstrate and validate a previously suggested workflow for permit process modeling using the permitting process in Israel as a test case.

The authors implement qualitative expert interviews for data acquisition. The collected data are then processed for a qualitative data analysis. The results of the analysis are then validated using a focus group workshop in the field of building permits. In the test case the focus group consisted of Israeli experts.

The authors present a detailed overview of the as-is building permit process in Israel and the existing challenges. Through this test case, the authors found that the framework is applicable in different countries and that it can provide valuable insights into the core problems within the process. In addition, application of the same framework in different countries can provide comparable results that would allow the authors to identify best practices.

The major contribution of this work is the development and validation of a framework for building permitting process modeling which can be used to identify existing challenges and bottlenecks in the process. Implementing a structured and unified approach provides an opportunity to easily compare processes in different countries to identify best practices.

Effective facility management (FM) can reduce environmental effects on buildings throughout their life cycle. This study aims to investigate the challenges in implementing building information modelling (BIM) for FM in government buildings in Thailand.

Eight government-building facility experts were interviewed using an in-depth interview method to identify FM challenges. The collected qualitative data were analysed via thematic analysis to ensure data saturation. The final questionnaire was designed with 45 FM problems, classified into management, technical and human resource problems, to collect quantitative data from 54 government FM officers. The data were used to prioritise the severity and frequency of the FM problems using the severity index (SI) and relative importance index (RII).

Management problems have the highest impact, with an average SI of 0.285, followed by human resource (average SI = 0.266) and technical (average SI = 0.264) problems.

This study identifies the government-building FM problems in Thailand that are critical to the development of a BIM execution plan (BEP) guideline. The findings can facilitate strategy development for government-building operations and management in line with the public procurement and supply administration of Thailand. These findings can serve as a guideline to inform the development of a BIM Roadmap for integration into the national digital roadmap and the Thailand 4.0 policy to mitigate construction-related environmental and climate issues.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

In the current era of technological advancement, the architectural, engineering and construction (AEC) industry is undergoing a radical transformation, prompting researchers to explore new breakthroughs that can revolutionise the construction process. This paper delves into the use of cutting-edge technologies such as building information management (BIM), blockchain and the Internet of Things (IoT), along with advanced management techniques such as work breakdown structure (WBS) and Agile thinking, to enhance the industry’s efficiency, productivity, quality and cost-effectiveness. Moreover, the pressing need for a sustainable, secure and transparent sector amplifies the significance of the proposed research.

This study’s research approach comprises an intensive literature review to construct a conceptual framework, followed by an exploratory questionnaire to validate the framework.

This paper demonstrates how blockchain combined with a WBS and a BIM platform may boost collaboration in order to experience efficient and trusted workflow scenarios that can overcome many of the challenges given in a traditional building technique. The research findings emphasise the benefits of the proposed new mentality approach, which incorporates all of the previously described tools/techniques to the business.

This paper highlights the advantages of leveraging a combination of blockchain, WBS and BIM platforms to boost collaboration and enable efficient and trustworthy workflow scenarios that can surmount the difficulties inherent in traditional AEC industry collaboration methods.

This study provides original insights into the challenges and opportunities of using blockchain for AEC collaboration, by exploring the potential of decentralised blockchain networks to improve the security, efficiency and transparency of collaborative data sharing and management.