Association for Information Systems
AIS Electronic Library (AISeL)
UK Academy for Information Systems UK Academy for Information Systems
Conference Proceedings 2023
Spring 6-29-2023
THE USE OF OPEN, AXIAL AND SELECTIVE CODING
TECHNIQUES: A LITERATURE ANALYSIS OF IS RESEARCH
Ibrahim Alhassan
Saudi Electronic University,
David Sammon
University College Cork,
Mary Daly
University College Cork,
Arif Wibisono
Institut Teknologi Sepuluh Nopember,
Laleh Kasraian
De Montfort University,
See next page for additional authors
Follow this and additional works at: https://aisel.aisnet.org/ukais2023
Recommended Citation
Alhassan, Ibrahim; Sammon, David; Daly, Mary; Wibisono, Arif; Kasraian, Laleh; Nagle, Tadhg; Heavin,
Ciara; Dennehy, Denis; Zamani, Efpraxia; and Qaffas, Alaa, "THE USE OF OPEN, AXIAL AND SELECTIVE
CODING TECHNIQUES: A LITERATURE ANALYSIS OF IS RESEARCH" (2023). UK Academy for Information
Systems Conference Proceedings 2023. 20.
https://aisel.aisnet.org/ukais2023/20
This material is brought to you by the UK Academy for Information Systems at AIS Electronic Library (AISeL). It has
been accepted for inclusion in UK Academy for Information Systems Conference Proceedings 2023 by an
authorized administrator of AIS Electronic Library (AISeL). For more information, please contact
.
,Authors
Ibrahim Alhassan, David Sammon, Mary Daly, Arif Wibisono, Laleh Kasraian, Tadhg Nagle, Ciara Heavin,
Denis Dennehy, Efpraxia Zamani, and Alaa Qaffas
This article is available at AIS Electronic Library (AISeL): https://aisel.aisnet.org/ukais2023/20
, THE USE OF OPEN, AXIAL AND
SELECTIVE CODING TECHNIQUES: A
LITERATURE ANALYSIS OF IS
RESEARCH
Ibrahim Alhassan
Saudi Electronic University, Saudi Arabia
David Sammon
University College Cork, Ireland
Mary Daly
University College Cork, Ireland
Arif Wibisono
Institut Teknologi Sepuluh Nopember, Indonesia
Laleh Kasraian
De Montfort University, UK
Tadhg Nagle
University College Cork, Ireland
Ciara Heavin
University College Cork, Ireland
Denis Dennehy
Swansea University, UK
Efpraxia Zamani
University of Sheffield, UK
Alaa Qaffas
University of Jeddah, Saudi Arabia
, Abstract
Qualitative data analysis plays a critical role in academic research. Open, axial, and selective (OAS)
coding techniques are widely associated with qualitative data analysis in information systems (IS)
research. Therefore, this paper aims to examine the usage of OAS coding techniques and is based on
reviewing and analyzing 96 published IS studies that have operationalized the techniques. This
research follows the structural steps taken in content analysis in order to select, review and analyze
relevant literature. The research is intended to contribute to the IS research community by classifying
the papers analyzed against the different activities for operationalizing OAS coding. Our analysis
shows that the use of coding by IS scholars has increased in recent years. However, we also find that
there has been some vagueness in describing how the OAS coding techniques are executed within our
highest quality IS research outputs.
Keywords: Open Coding, Axial Coding, Selective Coding, Data Analysis, Grounded
Theory
1.0 Introduction
It is broadly appreciated that qualitative data refers to non-numeric data, where the
focus on text (as qualitative data) rather than on numbers “is the most important
feature of qualitative analysis” (Schutt, 2018, p.322). Such qualitative data opens up
the opportunity for researchers to use any number of qualitative data analysis
techniques available, as appropriate. However, irrespective of which approach is
followed, qualitative data analysis will always involve a “categorisation of data into
concepts” (c.f. Schutt, 2018, p.325) or a coding of the data. As Blair (2015, p.14)
suggests “in an attempt to help find meaning within qualitative data, researchers
commonly start by coding their data”. However, according to Elliott (2018, p.2850)
even though “coding is an almost universal process in qualitative research”, it is a
“process which goes remarkably undocumented” and as a result “there is potential
for considerable confusion regarding what coding actually is”. Therefore, there is
much to be decided on by the researcher when undertaking the art, science or indeed
dance that is qualitative data analysis (Schutt, 2018), but it is also vitally important
that the researcher appreciates that the rigor expected within a qualitative research
study relies heavily on these data analysis decisions, and specifically those decisions
made around coding. In fact, O’Reilly et al. (2012, p.251) when demystifying the
grounded theory method makes reference to Locke (2001) who comments that “the
‘goodness of the fit’ between the empirical observations and the conceptual
categories they purport to indicate” is the mark of the quality of the grounded theory.
AIS Electronic Library (AISeL)
UK Academy for Information Systems UK Academy for Information Systems
Conference Proceedings 2023
Spring 6-29-2023
THE USE OF OPEN, AXIAL AND SELECTIVE CODING
TECHNIQUES: A LITERATURE ANALYSIS OF IS RESEARCH
Ibrahim Alhassan
Saudi Electronic University,
David Sammon
University College Cork,
Mary Daly
University College Cork,
Arif Wibisono
Institut Teknologi Sepuluh Nopember,
Laleh Kasraian
De Montfort University,
See next page for additional authors
Follow this and additional works at: https://aisel.aisnet.org/ukais2023
Recommended Citation
Alhassan, Ibrahim; Sammon, David; Daly, Mary; Wibisono, Arif; Kasraian, Laleh; Nagle, Tadhg; Heavin,
Ciara; Dennehy, Denis; Zamani, Efpraxia; and Qaffas, Alaa, "THE USE OF OPEN, AXIAL AND SELECTIVE
CODING TECHNIQUES: A LITERATURE ANALYSIS OF IS RESEARCH" (2023). UK Academy for Information
Systems Conference Proceedings 2023. 20.
https://aisel.aisnet.org/ukais2023/20
This material is brought to you by the UK Academy for Information Systems at AIS Electronic Library (AISeL). It has
been accepted for inclusion in UK Academy for Information Systems Conference Proceedings 2023 by an
authorized administrator of AIS Electronic Library (AISeL). For more information, please contact
.
,Authors
Ibrahim Alhassan, David Sammon, Mary Daly, Arif Wibisono, Laleh Kasraian, Tadhg Nagle, Ciara Heavin,
Denis Dennehy, Efpraxia Zamani, and Alaa Qaffas
This article is available at AIS Electronic Library (AISeL): https://aisel.aisnet.org/ukais2023/20
, THE USE OF OPEN, AXIAL AND
SELECTIVE CODING TECHNIQUES: A
LITERATURE ANALYSIS OF IS
RESEARCH
Ibrahim Alhassan
Saudi Electronic University, Saudi Arabia
David Sammon
University College Cork, Ireland
Mary Daly
University College Cork, Ireland
Arif Wibisono
Institut Teknologi Sepuluh Nopember, Indonesia
Laleh Kasraian
De Montfort University, UK
Tadhg Nagle
University College Cork, Ireland
Ciara Heavin
University College Cork, Ireland
Denis Dennehy
Swansea University, UK
Efpraxia Zamani
University of Sheffield, UK
Alaa Qaffas
University of Jeddah, Saudi Arabia
, Abstract
Qualitative data analysis plays a critical role in academic research. Open, axial, and selective (OAS)
coding techniques are widely associated with qualitative data analysis in information systems (IS)
research. Therefore, this paper aims to examine the usage of OAS coding techniques and is based on
reviewing and analyzing 96 published IS studies that have operationalized the techniques. This
research follows the structural steps taken in content analysis in order to select, review and analyze
relevant literature. The research is intended to contribute to the IS research community by classifying
the papers analyzed against the different activities for operationalizing OAS coding. Our analysis
shows that the use of coding by IS scholars has increased in recent years. However, we also find that
there has been some vagueness in describing how the OAS coding techniques are executed within our
highest quality IS research outputs.
Keywords: Open Coding, Axial Coding, Selective Coding, Data Analysis, Grounded
Theory
1.0 Introduction
It is broadly appreciated that qualitative data refers to non-numeric data, where the
focus on text (as qualitative data) rather than on numbers “is the most important
feature of qualitative analysis” (Schutt, 2018, p.322). Such qualitative data opens up
the opportunity for researchers to use any number of qualitative data analysis
techniques available, as appropriate. However, irrespective of which approach is
followed, qualitative data analysis will always involve a “categorisation of data into
concepts” (c.f. Schutt, 2018, p.325) or a coding of the data. As Blair (2015, p.14)
suggests “in an attempt to help find meaning within qualitative data, researchers
commonly start by coding their data”. However, according to Elliott (2018, p.2850)
even though “coding is an almost universal process in qualitative research”, it is a
“process which goes remarkably undocumented” and as a result “there is potential
for considerable confusion regarding what coding actually is”. Therefore, there is
much to be decided on by the researcher when undertaking the art, science or indeed
dance that is qualitative data analysis (Schutt, 2018), but it is also vitally important
that the researcher appreciates that the rigor expected within a qualitative research
study relies heavily on these data analysis decisions, and specifically those decisions
made around coding. In fact, O’Reilly et al. (2012, p.251) when demystifying the
grounded theory method makes reference to Locke (2001) who comments that “the
‘goodness of the fit’ between the empirical observations and the conceptual
categories they purport to indicate” is the mark of the quality of the grounded theory.
