Search results

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.

University education in Nigeria has been in existence for over seven decades. The expansion and development are astronomical considering the number when the first university college was established. Currently, over 198 universities are spread across the length and breadth of the country. In spite of the expansion and development in this sector over time, the mode in which Nigerian scholars and researchers conduct research is often titled toward quantitative methods, thereby abandoning qualitative and mixed methods paradigms. Effort is geared toward establishing the reasons for the overrepresentation of quantitative paradigms in research space and the future of qualitative and mixed methods paradigms in Nigerian universities. A qualitative method was adopted in this study. In line with the approach, the interpretive paradigm is used to understand and make sense from the participants’ responses on the phenomenon. Narrative analysis is used to analyze the data. Findings indicated that old scholars and researchers are novices in qualitative and mixed methods research, that quantitative methods are scientific and the findings can be submitted to generalization, hence its overrepresentation. However, foreign-trained scholars and researchers are extending the future of these research approaches in Nigerian universities through the transfer of knowledge and skills.

The use of interviews for data collection is prevalent in qualitative accounting research. This paper examines vignettes – sketches of hypothetical scenarios – as a promising complementary way to conduct interviews in qualitative accounting research.

The paper is based on our experiences designing and using vignettes in five separate qualitative accounting studies, which collectively involve over 200 interviews with various participants. It discusses the opportunities the use of vignettes in interviews offers to qualitative accounting research, as well as the challenges associated with designing and using vignettes. The paper also reflects on fellow researchers’ varied reactions during seminars, workshops, and the journal review process.

Vignettes emerge as a productive and engaging complementary way for accounting researchers to obtain additional insights and perspectives not usually accessible in semi-structured interviews. The paper also provides practical insights into developing, using and publishing qualitative accounting studies using vignettes, contributing an additional behind-the-scenes view of using qualitative research methods.

The aim of this paper is to increase awareness of vignettes as a complement to the standard qualitative accounting interview. It provides guidance on how vignettes might be used productively for studying rare, new, emerging, complex, or multi-period real-world accounting phenomena. It also discusses how vignettes can promote transparency, honesty, and a greater level of detail in participants’ responses, as well as facilitate the involvement of lay people in accounting studies.

The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.

The purpose of this study is to substantiate the matrix approach to digitalization of management objects based on identification of relevant qualitative characteristics of these objects and its dichotomies, which allowing determine the quantity and quality of their main variants, as well as the relationships between them.

Methods of classification and typology are selected as study methods, and binary matrices are used as the tool to determine the main variants of management objects, assign binary codes to it and form codes of more complex management objects on its basis, depending on the content of study tasks.

The main results of study include the classification of organization components; variants for choosing qualitative characteristics of chains components; adjusted content of methodology of qualitative research of management objects; sequences of “up” and “down” digitization of these objects; actual qualitative characteristics of e components of management objects and dichotomies; and variants of forming of ciphers of these objects.

The use of study results allows to reduce the complexity of substantiating and making managerial decisions in organization and supply chains, to structure these decisions by man-agement levels and positions and to reduce costs, time and lost profits for fulfilling orders of end consumers of products and/or services.

The originality of this study is confirmed by the substantiation of choice and use of actual qualitative characteristics of management objects and its dichotomies, which allow obtaining two variants of these objects and assigning them binary codes processed using computer software for management activities.

This study aims to describe key elements that are critical to virtual qualitative research especially while working with practitioners as participants.

This paper takes a reflexive researcher approach using a case study to explore how researchers adopted a qualitative research approach using digital technology. We use five principles suggested by Boland et al. (2022) as a framework to consider and reflect on our experiences as researchers and those of our participants.

We highlight the gatekeeper’s support, trusted relationship with the organisations, interpersonal skills of interviewers, stringent measures of securing data and shared experiences of interviewee and interviewers helped complete virtual research. We recommend that four key factors such as digital competency, feasibility, flexibility and resilience should be considered while undertaking or commissioning virtual, qualitative research studies.

Social care practitioners and qualitative researchers increasingly negotiate with digital technologies to undertake their work. In this paper, we evidence how online qualitative approaches can be effective provided challenges are dealt with diligently in each stage of the research process.

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.

This study draws on the author's experiences building rapport through online chat for data collection for the author's doctoral dissertation. The author contacted ten Korean women via online chat to recruit and faced the most challenging situation; building rapport. As the Millennial generation is known as being tech-savvy or digital natives, the author actively used emoticons (pictorial representations of facial expressions using characters) with potential interviewees and completed ten interviews. Therefore, this paper offers a new qualitative interviewing method in feminist research.

The paper briefly reviews the works of literature on interviewing women on sensitive topics and building rapport before the interview. Then, the author introduced using emoticons to create rapport during the data collection process and how a non-traditional approach positively impacts the interviewer and interviewee before, during and even after the interview.

Women participants' responses and behaviors differed after building a rapport through an online chat. They were willing to share their personal stories and memories with the interviewer even though the interviewer did not ask.

This study provides a stepping stone for developing an account of the new qualitative methodological approach, specifically feminist qualitative research.

Few studies have described how qualitative researchers create a rapport in virtual space, specifically using emoticons. Also, this study suggests a new methodological approach since nonverbal communication in online chat is inevitable when interviewing people in qualitative research.

This paper aims to explore how an academic researcher and a practitioner experience scepticism for their qualitative research.

The study applies Olt and Teman's new conceptual phenomenological polyethnography (2019) methodology, a hybrid of phenomenology and duoethnography.

For the researcher-participants, the essence of living with scepticism means feeling a sense of injustice; struggling with the desire for simplicity and quantification; being in a circle of uneasiness; having a survival mechanism; and embracing healthy scepticism. They experience the essence differently and similarly in varied cultural contexts. Through duoethnographic conversations, they acknowledge that while there can be scepticism of their work, it is important to remain sceptical, persistent and curious by challenging traditional concepts. Theoretical and practical advances in artificial intelligence (AI) continue to highlight the need for clarifying qualitative researcher roles in academia and practice.

This paper contributes to the debate of qualitative versus quantitative research. Its originality is in exploring scepticism as lived experience, from an academic and practitioner perspective and applying a phenomenological polyethnography approach that blends two different traditional research paradigms.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.