The Electronic Journal of Business Research Methods provides perspectives on topics relevant to research in the field of business and management
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Journal Article

Innovative Methodologies in Qualitative Research: Social Media Window for Accessing Organisational Elites for interviews  pp157-167

Efrider Maramwidze-Merrison

© Nov 2016 Volume 14 Issue 2, Editor: Ann Brown, pp71 - 167

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Abstract

Reflexivity is the nature of qualitative research (Lincoln and Guba, 1985; Morgan an Smircich, 1980); implying that through reflectivity exercises researchers are able to demonstrate their research's rigour and also create a treasure trove of ideas and strategies, share the pleasures and agonies of doing qualitative research. The ever‑growing body of knowledge on the strategies for accessing research participants that researchers share, evidences the gains of reflexivity (see the newly injected literature Cunliffe and Alcadipani, 2016; Blix and Wettergren, 2015; Mikecz, 2012). Well, this article does the same; it reflects on the access methodology employed for a PhD research (Maramwidze, 2015) carried out to explore the challenges faced by Foreign Direct Investors (FDI) in the South African banking sector, which involved sampling elite respondents. Similar to other researchers' views on accessing potential research participants, in this case organisational elites, the researcher faced challenges associated with gaining access; as well as the usually high cost of conducting face‑to‑face qualitative interviews.

 

Keywords: Keywords: Reflexivity in qualitative research, organisational elites, innovative and diplomatic access strategies, social media, LinkedIn, research students, teaching research methods

 

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Journal Article

Low Cost Text Mining as a Strategy for Qualitative Researchers  pp2-16

Jeremy Rose, Christian Lennerholt

© Apr 2017 Volume 15 Issue 1, Editor: Ann Brown, pp1 - 56

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Abstract

Advances in text mining together with the widespread adoption of the Internet have opened up new possibilities for qualitative researchers in the information systems and business and management fields. Easy access to large amounts of textual material through search engines, combined with automated techniques for analysis, promise to simplify the process of qualitative research. In practice this turns out not to be so easy. We outline a design research approach for building a five stage process for low tech, low cost text mining, which includes insights from the text mining literature and an experiment with trend analysis in business intelligence. We summarise the prototype process, and discuss the many difficulties that currently stand in the way of high quality research by this route. Despite the difficulties, the combination of low cost text mining with qualitative research is a promising methodological avenue, and we specify some future paths for this area of study.

 

Keywords: big data, business intelligence, qualitative research method, social media analysis, text mining, text analytics

 

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Journal Article

Augmenting Social Media Research with Q Methodology: Some Guiding Principles  pp155-164

Charmaine du Plessis

© Sep 2019 Volume 17 Issue 3, Editor: Ann Brown, pp102 - 191

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Abstract

This paper proposes that social media studies could be complemented with Q methodology when a topic that plays out in social media is complex, controversial or sensitive to allow for deep‑seated, integrated online and off‑line perspectives. Although the Fourth Industrial Revolution brought researchers more opportunities and advantages to study topics that were previously inaccessible, using technologies for research does not come without challenges. This is especially the case with social media studies comprising large datasets and where it is not always possible to identify fake profiles, bots, spam or manipulated information without having access to advanced data analysis software. Another point is that views expressed in social media do not always represent offline perspectives. However, while Q methodology has, over the years, adapted its techniques to accommodate new technologies, more can be done to embrace a web 2.0 environment. Why and how social media studies could be augmented with Q methodology to reveal individuals’ perspectives and attitudes about topics will be examined and potential difficulties will be highlighted. Not yet a mainstream method, Q methodology combines the strengths of two robust qualitative and quantitative methods sequentially to reveal and isolate the subjective perspectives of groups of participants. This methodology could, therefore, be useful when a social media study puts forward novel ideas and findings that should be supported by offline views. In this regard, the paper provides some guidelines by referring to the five phases of a Q study and describing how a social media study could not only benefit from but also apply Q methodology to augment results. Supplementing social media research with Q methodology could be empowering and provide opportunities for further research and debate.

 

Keywords: mixed method, social media research, Q factor analysis, Q methodology, Q study

 

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Journal Issue

Volume 15 Issue 1 / Apr 2017  pp1‑56

Editor: Ann Brown

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Keywords: big data, business intelligence, qualitative research method, social media analysis, text mining, text analytics, Social Physics, crowdsourcing, multicultural, multidisciplinary, collaborative research, social sciences, Knowledge Cafés, Theory refinement, Theoretical conjectures, Research Methodology, Hermeneutics, Multiple imputation by chained equations, MICE, missing data, guidelines, review, R

 

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Journal Issue

Volume 17 Issue 3 / Sep 2019  pp102‑191

Editor: Ann Brown

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Keywords: entrepreneurs, entrepreneurial skills, mixed-methods, qualitative, quantitative, Rigour, trustworthiness, auditability, credibility, transferability, methods pedagogy, TACT, Problem-based learning, teaching research methods, first year UG business students, business research process, thematic analysis, pattern matching, case study research, deductive qualitative analysis, leading organisational change, mixed method, social media research, Q factor analysis, Q methodology, Q study, Experimental Design; Factorial Surveys; Order-effects; Omitted-Variable Bias JEL Codes: C21; C91, Research methodology; Innovation; Technology; Technological change; Management; Crowdsourcing

 

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