Data Collection

Four main data collection techniques were employed during the study. These were observational, questionnaires, quantitative data analysis and interviews, the combination of which aligned to the mixed methods approach within the Action Research framework. The use of different data sources and applying different techniques can be said to triangulate or ground theory. Grounding of action knowledge has been described as presenting good reasons for the theory, so other people can accept it as valid (Agerfalk, 2004), who proceeds to identify three grounding processes: (1) Internal grounding which includes reconstructing and articulating assumptions that might tacitly be taken for granted; (2) External grounding which focuses on external relations and can include the use of existing explanatory theories; (3) Empirical grounding on knowledge through application and observations, including assessments of it practicability. The study tends to adopt more of an empirical grounding process. The next paragraphs provide an overview of the generic techniques and conclude with the specific ones selected for the study.

Quantitative Data Analysis

In order to evaluate the linkage between experience items and profiles and profiles with churn, two data sets (containing experience and churn data relating to 6.500 and 8,000 customers) are statistically assessed, based on propositions regarding the relationships between the constructs / data. Proposition in this sense tend to be formal statements of predictions derived from evidence from earlier research and theory or simply the result of a hunch (Breakwell, Hammond & Fife-Schaw, 1995). The propositions are tested by manipulating one, or some, of the variables (Preece, Rogers & Sharp, 2002).

The statistical methods and considerations identified are:

Correlation analysis: determines the extent to which changes in the value of an attribute (churn: whether a customer stays or leaves) are associated with changes in another attribute (experience: the individual or combined

experience of that a customer receives). The correlation coefficient is a measure of the relationship between two attributes or columns of data. The correlation coefficient values can range from -1 to +1. A value near 0 indicates little correlation between attributes; a value near +1 or -1 indicates a high level of correlation. When two attributes have a positive correlation coefficient, an increase in the value of one attribute indicates a likely increase in the value of the second attribute. For a negative correlation coefficient, one attribute shows an increase in value, the other attribute tends to show a decrease.

Linear regression: The basic goal behind simple linear regression modelling is to find the line of best fit through a two-dimensional plane of paired X and Y values (for example, churn and aggregate experience score). Once this line is found using the least-squared-error criterion, then one can perform various statistical tests to determine how well this line accounts for the observed variance in Y scores (for example how churn differs with different aggregate experience scores. A linear equation y = mx + b, has two parameters that must be estimated based on the X and Y data provided, which are the slope (m) and y intercept (b).

Logistic regression: This is an approach to prediction, like linear regression, however, with logistic regression, the variables are more likely to follow a logistic distribution (i.e. non linear). A chi-square test is used to indicate how well the logistic regression model fits the data.

Significance Tests: These are employed to show that the statistic is reliable. It doesn't mean the finding is important or that it has any decision- making utility. Significance is a statistical term that tells how sure you are that a difference or relationship exists. To say that a significant difference or relationship exists only tells half the story. We might be very sure that a relationship exists, but is it a strong, moderate, or weak relationship? After finding a significant relationship, it is important to evaluate its strength.

Significant relationships can be strong or weak. One important concept in significance testing is whether you use a one-tailed or two-tailed test of significance. When your research hypothesis states the direction of the difference or relationship, then you use a one-tailed probability. For example, poor experience scores lead to churn. A two-tailed test is not restricted to one direction (Coolican, 2009). For example there is a relationship between experience and churn (so in additional to the one tail example above, good experiences lead to more customers staying).

Observational

The alternative to laboratory studies is the use of field studies, which situates the participant in their natural real world environment, and allows the experimenter to capture interactions between systems and other people, that would not have occurred in the laboratory (Coolican, 2009). In field studies, the participant interacts in real world conditions of ambient noise, movement, interruptions, and distractions, which are hard to replicate in the laboratory and which enables results to be generalized to the real world, thus promoting external validity.

Questionnaire

Questionnaires are one of the most utilised research techniques for gathering structured information from individuals (Coolican, 2009). Usually questionnaires are constructed for a specific research topic and tend to gather various kinds of data such as current opinion or patterns of behaviour. A questionnaire was specifically designed for the customer exit interviews in Action Research Cycle One and in the diagnosis phase of Action Research Cycle Two in order to collect data from customer and employees. Details about each questionnaire are discussed in Chapter 4 and Chapter 5.

Interviews

For the Senior Management discussions, the researcher planned to use interviews to collect information from the participants. An interview is considered to be a good method for collecting qualitative data. The interview may contain both open-

ended questions and closed questions. There are many types of face-to-face interview techniques ranging from fully structured to unstructured. Coolican (2009) describes various types of interviews: non-directive; informal; semi- structured; structured but open-ended; fully structured. The study focused on structured but open-ended.

Structured but open-ended interview: The interviewer asks a pre-set of open-ended questions in a predetermined order. This keeps the interviewer focused on gathering data and avoiding a two-way conversation. In this type of interview the interviewer can avoid the looseness and inconsistency that may occur in other types of interviews. However, the respondents can still respond in any way they choose. This type is used for the Senior Management discussions and is reported in Chapter 6.

The detailed data collection information included: Customer data records analysis; Customer interviews; Prototype feedback from Telco; Telco staff interviews; researcher field notes. The specific data collection methods are depicted in the table below, along with the key knowledge generation phases of the study: Literature review; 1st Action Research Cycle (model generation); 2nd Action Research Cycle (Prototype and Loyalty Action Response). The decision to use different data collection methods fit well with both the mixed method approach and the action research methodology and flexibility and adaptability are crucial hallmarks of good practice in these areas. Details of the statistical data analysis, interview questions and transcripts of senior management interviews can be found in the appendices.

Table 3-4 – Data Collections Activities

Literature Review 1st Action Research Iteration 2nd Action Research Iteration  Qualitative review of customer experience and telecommunications literature  Field Notes  Quantitative analysis of 2 customer data sets (6,500 and 8,000 respectively) using correlation analysis, linear and logistics regression and appraised using 2 tailed significance tests.

 Questionnaire devised for gathering face to face feedback from 100 Telco & non Telco Customers.

 Field notes

 Fully structured qualitative interviews of front line staff across 4 locations.  Fully structured interviews

of a small sample of customers

 Prototype feedback  In-depth structured but

open ended qualitative interviews with 5 senior managers.

The multiple data collection activities are intended to supporting the empirical grounding of the knowledge generated. Action research is said to lend itself strongly to such pluralist approaches, which facilitate the production of both theoretical and practical knowledge (Chiasson, Germonprez & Mathiassen, 2009).