Understanding customer’s churn phenomenon in Ghana retail banking sectorWhen it comes to analysing customer’s churn, it is a phenomenon when an existing client ends their relationship with the company (in our case bank) and stops doing business with the bank (“Customer Churn Meaning (And What To Do About It)”, 2018). Researchers (Chandar et al., 2006) also corroborate the same that the propensity of a customer to stop doing business is one of the major challenges called by the name “customer churn”. In today’s day and age, customer satisfaction in retail banking sector is directly proportional to customer’s access to the various bank’s facilities, price strategies, products, and quality service. According to Roberts (2005), those businesses which outperform their competitors opt for protecting their services and products through customer retention. The customer churn is one of the biggest debates in the air to date wherein the researchers opine that we should not accept or reject the speculations and assumptions related to customer churn phenomenon, unless we make a note of them and critically think about the reliable and logical explanations (Ghauri & Gronhaug, 2005). The banking sector in Ghana accounts for 70% of the financial sector that’s why it plays a vital role in economic contribution and spread all across Ghana (Bawumia, 2007). Having said that, in the fierce competitive retail banking market, the phenomenon of customer’s churn, customer’s attrition, their defection due to dissatisfaction is a worthy subject to investigate in detail. The reason being, the customer plays a crucial role in improving market share, profitability, and business viability of the banks in the retail banking sector.
This thesis relies on the Integrated Behavioural Model (IBM) in order to understand the factors that causes retail bank customers to switch from their current bank to another. The integrated behavioural model is an extension of the theory of planned behaviour (TPB) which is in turn an extension of the theory of reasoned action (TRA). Let us take a brief look at TRA and TPB before getting into the details of the proposed conceptual model for this study.
Theory of reasoned action
The theory of reasoned action (TRA) was developed by Fishbein (1967) to understand behavioural intention, which is an individual having the intention to perform a certain behaviour. The model seeks to find the relationship between, behavioural intention, and:
(a) attitude towards the behaviour which has to do with the individuals believes about the outcome of the behaviour and
(b) perceived subjective norms which has to do which whether society and other people the individual deems important will approve/disapprove of the behaviour.
In other words, the theory of reasoned action says that a person decides ad commit to a particular behaviour can be predicted by their attitude towards the behaviour and what they think other people will think of them for performing that behaviour.
Fishbein (1967) provided a clear separation between attitude towards an object (a bank) and attitude towards a behaviour in relation to the objects (switching from one bank to another). TRA proved there is a much stronger relationship between attitude towards the behaviour than the behaviour itself.
While the theory of reasoned action is a very simple and intuitive model for explaining behavioural intentions, it has some limitation which makes it less practical. Chief amongst the limitations is the assumption that, people can act without limitation – which effectively neglects the impact of external factors on the performance of the behaviour (Kippax and Crawford 1993, p. 253).
Intension are simply that, intensions! They do not necessarily get implemented. At the beginning of each year, so many people have intentions of doing various things; going to the gym 3 times a week to lose weight, to quit smoking or perhaps to save more. Norcross et al. (2002) showed that only 30% of people who make new year’s resolutions where able to keep it past week 2. In effect, there is a disconnect between behavioural intention and actual behaviour (Hale, Householder and Greene (2002)). This characteristic of the theory of reasoned action motivated the development of the theory of planned behaviour.
Theory of Planned Behaviour
The theory of planned behaviour (Ajzen, 1985 and Ajzen, 1991) is seen as an extension and an improved model of the theory of reasoned action by adding a third construct, perceived behavioural control. Perceived behavioural control can be explained as the individuals own assessment of the amount of control he has in effecting that behaviour.
Behaviour and Behavioural Intentions
As seen from figure 1 above, the theory of planned behaviour says that behavioural intentions (BI) is the best predictor of behaviour (B). The behaviour in this case is switching from your primary retail banking provider to another. We define behavioural intention as the “subjective probability that he or she will engage in a given behaviour” (Committee on Communication for Behaviour Change in the 21st Century, 2002, p. 31). The antecedents of BI are:
attitude towards the behaviour (A)
subjective norms (SN) and
Perceived behavioural control (PBC)
Think of BI how serious an individual is about behaving in a certain way; how hard or how motivated are they prepared to work in order to achieve said behaviour (Ajzen, 1991).
Behavioural belief and Attitude towards the behaviour
Fishbein and Ajzen (1975)’s Expectancy-Value model explains that our attitudes as humans to any behaviour is steeped in our beliefs about said behaviour. In other words, we are motivated to perform a behaviour based on the perceived outcome from performing that behaviour. For example, we may believe that doing active exercise 30 minutes a day (the behaviour) causes your blood pressure levels to reduce, helps in weight loss and also reduces stress (outcomes). In our own example, a customer of a retail bank might believe that switching from one bank to the other (the behaviour), will lead to a better banking experience including reduced prices, customer service and a more personalised product selection (the outcome). The outcomes at accrue to the individual for performing the behaviour can be either positive or negative which in turn affects the attitude the person has towards that behaviour. Of course people can form several beliefs, however, only a handful of salient beliefs affects a person’s attitude (Ajzen, 1991).
Analytically, the expectancy-value model says that an individual’s attitude (A) is proportional to the sum of all salient beliefs (b) multiplied by the person’s evaluation (e) of the beliefs.
There are two kinds of normative beliefs: injective normative beliefs and descriptive normative beliefs. Injunctive normative beliefs are formed when we are told or it has been inferred that important persons in their lives will approve or disapprove to the performance of a certain behaviour. Some examples of important persons are spouses, parents, close friends and co-workers; but it can also be people in positions of authority whom we respect or look up to. Descriptive normative beliefs on the other hand, refer to what an individual perceives other people in a similar situation as them will do. As an example, at the end of a play when everyone stands up to applaud the actors, will typically rise up and applaud as well – a classic example of descriptive normative behaviour. (Cialdini et al., 1990; Fishbein and Ajzen, 2010)
Analogous to the expectancy-value model, “subjective norm (SN) is determined by the total set of accessible injunctive and descriptive normative beliefs. Specifically, the strength of each normative belief (n) associated with a given social referent is weighted by motivation to comply (m) with the referent in question, and the products are aggregated” (Ajzen, 2015)
Our intention to perform a specific behaviour and our actual behaviour depends on our perceived ability to actually carry out the behaviour, i.e. or perceived behavioural control(PBC) (Ajzen, 1991). Take a group of students being introduced to computer programming for the first time (they all have no prior knowledge of experience with programming). Those who have more confidence in their ability to master the skill of programming are more likely to put in the effort and work required to master the skill and actually learn the skill then those who doubt their ability to learn.
An individual’s ability to actually carry out a behaviour is influenced by various factors which may either facilitate or hinder the achievement of the behaviour (Ajzen, 2002). For PBC, these factors are:
perceived control – these are factors that are needed to achieve the behaviour and are within the control of the individual.
Perceived self-efficacy – which is the individuals own assessment of their ability to achieve the behaviour (Bandura, 1977, 1982).
A decomposed (more detail) model for the theory of planned behaviour is therefore as follows:
Conceptual Model and Hypothesis development
Figures 3 below is present the conceptual model of this research which is based on the decomposed theory of planned behaviour. I also investigate the moderating role of demographics in explaining the relationship between behavioural intentions and actual behaviour in the case of retail banking customers.
Choosing your main retail bank is analogous to going shopping. There are usually different alternatives which we have to choose between based on our personal preferences. There are currently over 30 banks in Ghana, which offers consumers a lot of choice when choosing a bank for the first time or when deciding to switch from one to another.
Attitude toward switching
From equation 1 above, an individual’s attitude towards switching from retail banking service provider is hinged on his behavioural beliefs weighted by the individual’s evaluation of the outcomes. Therefore, if the individual holds strong beliefs that switching from one retail bank to the other will yield a positive outcome, then his attitude toward switching will also be positive. Similarly, if the individual holds strongly negative beliefs about switching banks, then he will have a negative attitude towards the switching behaviour.
Thus our first hypothesis is:
H1A: Experiental beliefs will predict attitude towards retail bank customers in Ghana to switch from one bank to the other.
H1B: Instrumental beliefs will predict attitude towards retail bank customers in Ghana switching from one bank to the other.
We are social creatures and typically motivated by factors that’s makes us be “seen”, such as popularity, esteem and acceptance (Bernhiem, 1994). The main predictor of perceived norms are normative beliefs, which is, that important people or group of people in our lives will either approve or disapprove of a performing a particular behaviour (Ajzen, 1972). It we believe that people important to us, or those in authority who we are motivated to comply with will switch banks if they were in your shoes or will approve of you switching banks, then we are more likely to a subjective norm that makes its more likely for us to switch. Groups of people who may be considered as important such as family and friends, media sources (TV, radio, newspapers and internet), social media can all have an impact on the customers’ subjective norms which in turn affects the customer intention to switch or not. The hypothesis for subjective norms are:
H2A: Injunctive norms will predict subjective norms for switching from one retail banking provider to another in Ghana.
H2B: Descriptive norms will predict subjective norms for switching from on retail banking provider to another in Ghana.
Perceived Self-Efficacy and Facilitating Factors
Self-efficacy is the individuals own assessment of this ability to perform a behaviour (Ajzen, 2002). In this research, self-efficacy refers to the customer’s own assessment of their ability to switch from on retail bank to the other to enjoy similar products and services as his current retail banking services provider.