Grounded theory analysis using axial and selective coding

By Priya Chetty on January 15, 2020

Data analysis is the process of reducing large organized data into summarized and categorized data. In the case of qualitative data, grounded theory is sometimes applied while performing the analysis. This process consists of four stages. The previous article showed how to conduct the first stage, i.e. initial or open coding in grounded theory analysis using a case example of interviews of nine shoppers regarding their shopping behaviour. In this article, the case is further analysed for the last two stages of grounded theory analysis, i.e. axial and selective coding.

Types of data analysis

Approaches of data analysis include ethnographic analysis, narrative analysis, phenomenological analysis and constant comparison method (Onwuegbuzie, Dickinson, Leech, & Zoran, 2009). The ethnographic analysis involves a culture’s demographic and human life. Narrative analysis is utilized in several fields of study. The phenomenological analysis provides an epochal approach to identify an individual’s assumptions about the phenomenon, imaginative variation. Lastly, the constant comparative method focuses on codes and conceptual relationships (Hancock, Ockleford, & Windridge, 2009). The constant comparative method is used to evaluate data related to codes and categories.

Assumptions of good code in qualitative data analysis

A good code carries five elements;

  1. a name,
  2. a definition of the theme concerns,
  3. an elaboration of translating a theme to a code,
  4. an explanation of inclusion or exclusion to the identification of theme, and,
  5. listing of positive and negative examples.

Categories are generated from the coding process and it should have characteristics like categories reflect the purpose of research and it is mutually exclusive (Kawulich, n.d.).

Coding is of three types;

  1. open coding,
  2. axial coding and,
  3. selective coding.

Open coding identifies concepts by asking questions about the data. The second stage of coding is axial coding, it is used to make connections between categories, sub-categories and coding (Kawulich B.B.).

Axial coding in grounded theory analysis

Axial coding is the second phase of ground theory analysis. The word ‘axial’ used by Strauss and Corbin  (1998) is intended to put an axis through data. This axis connects identified categories in open coding. Axial coding puts categories back together in order to explore theoretical possibilities. So axial coding identifies causal relationships, context, intervening conditions to interconnect data. So the outcome of axial coding is an approach towards the central phenomenon of the data (Punch K. F. , n.d.).

Further analysis of the case of nine shoppers ( Joan, Farideh, Doreen, Grace, Pam, Elena, Anne, Lily and Laura) involves axial and selective coding. The below table represents stage 3, i.e. axial coding in grounded theory analysis. It includes the creation of sub-categories and sub-sub-categories for each of the main categories identified in the interviews.

Category Sub-CategorySub Sub-Category
Frequency of shopping at KDSOnce in a month
Reasons for shopping at KDSSpacious space, a wide range of goods, Car Parking, nice staff, new checkout system
Amount of time spent at the storeA couple of hours
Intend to buy at KDSHousehold items, Christmas gift
Any other place apart from KDS for explorationYesDebenhams, internet, West End or Kensington, Waterston, a new store at Guildford, Market
Any products/range of products not currently stocked in KDSYesBridal Service, Wide range of goods, Quality and Styling of garments, Kitchen goods, Garden furniture, New stock of clothes
Any products/ranges currently stocked that is not considered buying from KDSYesElectrical Goods, Furniture, Apparels, Toiletries

Table 1: Formation of Axial Coding

Categories and codes of the case

Seven categories emerged from seven themes or codes:

  1. Frequency of shopping at KDS.
  2. Reasons for shopping at KDS.
  3. Amount of time spent shopping at KDS.
  4. Intend to buy at KDS.
  5. Any other place apart from KDS for exploration.
  6. Any products or range of products not currently stocked in KDS.
  7. Any products or ranges currently stocked that is not considered buying from KDS’.

From each category, sub-category is evolved as presented below.

  • The first category, ‘Frequency of shopping at KDS’ shows two sub-categories; ‘once in a month’ and ‘seasonal’. These sub-categories have been developed from responses of open coding.
  • The second category, ‘Reasons for shopping at KDS’ specifies sub-categories like spacious space, a wide range of goods, Car Parking, nice staff, new checkout system.
  • ‘Amount of time spent at the store’ category has a sub-category of ‘Couple of hours’.
  • The fourth category ‘Intend to buy at KDS’ specifies two sub-categories like Household items, Christmas gift.
  • The fifth category, ‘Any other place apart from KDS for exploration’ initiates positive response and develops sub-sub-categories like Debenhams, internet, West End or Kensington, Waterston, a new store at Guildford, Market.
  • Positive response ‘yes’ is also seen in the sixth category ‘Any products or range of products not currently stocked in KDS’. Sub-categories are developed, such as bridal services, a wide range of goods, quality and styling of garments, kitchen goods, garden furniture, new stock of clothes.
  • Last category, ‘Any products or ranges currently stocked that is not considered buying from KDS’ elicited a positive response with subcategories like electrical goods, furniture, apparels, and toiletries.

Selective coding to identify the relationships between categories

Selective coding is the third stage of grounded theory analysis. In this phase, the analyst selects one central aspect of data as a core category or final category and put his or her concentration on it. The aim of selective coding is to integrate and pull together developing analysis. So a core category will be developed as an emergent concept. This stage displays those categories where more data are essential which denote more theoretical sampling. This stage is also called systematic densification and saturation of the theory.

Formation of selective coding is based on axial coding. The framework of data analysis represents that selective coding is the last stage of qualitative data analysis. It is presented as-

Formation of selective coding
Figure 1: Formation of selective coding (Cho & Lee, 2014)

Selective coding is derived from acquired conceptual details of data collection and open coding, axial coding and from axial coding theory is developed for precision and consistency. This concept is emerged in selective coding and thus ends the grounded theory method.

The emergence of the final category from the original and refined category in grounded theory analysis

An original category is derived from axial coding, follows refined category and final category. Original category assimilates category and sub-categories of axial coding, refined category specifies majority respondents’ opinion and final category emerges the core concept of theory. The activity of the final category is to connect the main purpose of research.

In the case of the above example, the original category, like ‘Frequency of shopping at KDS’ has two sub-categories, ‘once in a month’, ‘Seasonal’. The refined category is ‘once in a month’.

The second original category, ‘Amount of time spent at the store’ gives refined category ‘couple of hours’.  The core concept of the first two original categories is ‘Regular Purchasing’. 

Third original category ‘reasons of shopping at KDS’ has clustered sub-categories like Good Service Quality, Spacious Space, Wide Range of Goods, Car Parking,  Nice Staff and refined categories are Car Parking, Nice Staff.

Fourth original category, ‘intend to buy at KDS’ determines subcategories Household items and Christmas gifts. Refined category,’ Household items’ entails a new concept, ‘Service Quality of Store’ and this core concept is also derived from the third original category.

Fifth, sixth and seventh original category have a positive response in terms of refined category and these categories evolve concept like, ‘Lack of loyalty for dissatisfaction with product range’.

This is presented in the table below.

Original CategoryRefined CategoryFinal Category
Frequency of shopping at KDS
– Once in a month, Seasonal
Once in a monthRegular Purchasing
Amount of time spent at the store
– An Hour
– A couple of hours
A couple of hours
Reasons for shopping at KDS
– Good Service Quality
– Spacious Space
– Wide Range of Goods
– Car Parking
– Nice Staff – New Checkout system
Car Parking, Nice StaffService, Quality of the Store
Intend to buy at KDS
– Household items
– Christmas gifts
Household items
Any other place apart from KDS for explorationYesLack of loyalty for dissatisfaction with a product range
Any products or range of products not currently stocked in KDS?Yes
Any products or ranges currently stocked that is not considered buying from KDS? Yes

Table 2: Formation of Selective Coding


  • Cho, J. Y., & Lee, E.-H. (2014). Reducing Confusion about Grounded Theory and Qualitative Content Analysis: Similarities and Differences. The Qualitative Report, 19, 1–20.
  • Hancock, B., Ockleford, E., & Windridge, K. (2009). An Introduction to Qualitative Research. National Institute for Health Research, 4–37.
  • Kawulich, B. B. (n.d.). Data Analysis Techniques in Qualitative Research. 96–113.
  • Onwuegbuzie, A. J., Dickinson, W. B., Leech, N. L., & Zoran, A. G. (2009). A Qualitative Framework for Collecting and Analyzing Data in Focus Group Research. International Journal of Qualitative Methods, 8(3).

Priya is the co-founder and Managing Partner of Project Guru, a research and analytics firm based in Gurgaon. She is responsible for the human resource planning and operations functions. Her expertise in analytics has been used in a number of service-based industries like education and financial services.

Her foundational educational is from St. Xaviers High School (Mumbai). She also holds MBA degree in Marketing and Finance from the Indian Institute of Planning and Management, Delhi (2008).

Some of the notable projects she has worked on include:

  • Using systems thinking to improve sustainability in operations: A study carried out in Malaysia in partnership with Universiti Kuala Lumpur.
  • Assessing customer satisfaction with in-house doctors of Jiva Ayurveda (a project executed for the company)
  • Predicting the potential impact of green hydrogen microgirds (A project executed for the Government of South Africa)

She is a key contributor to the in-house research platform Knowledge Tank.

She currently holds over 300 citations from her contributions to the platform.

She has also been a guest speaker at various institutes such as JIMS (Delhi), BPIT (Delhi), and SVU (Tirupati).