Assessing Factors That Predict Customer's Choice of Bank in Ho ...

British Journal of Economics, Management & Trade 15(1): 1-11, 2016, Article no.BJEMT.28490 ISSN: 2278-098X

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Assessing Factors That Predict Customer’s Choice of Bank in Ho Municipality, Ghana Francois Mahama1*, Edinam Agbemava2, Solomon Yemidi3 and Kunu Etornam Kwame1 1

Department of Mathematics and Statistics, Ho Polytechnic, Ghana. 2 Department of Accountancy, Ho Polytechnic, Ghana. 3 Department of Multidisciplinary Studies, Ho Polytechnic, Ghana. Authors’ contributions

This work was carried out in collaboration between all authors. Author FM designed the study, wrote the protocol, and wrote the first draft of the manuscript. Authors EA, KEK and SY managed the literature searches and analyses of the study. All authors read and approved the final manuscript. Article Information DOI: 10.9734/BJEMT/2016/28490 Editor(s): (1) LI Hui, School of Economics and Management, Zhejiang Normal University, China. Reviewers: (1) Rebecca Abraham, Nova Southeastern University, USA. (2) Baofeng Shi, Northwest A&F University, Yangling, China. Complete Peer review History: http://www.sciencedomain.org/review-history/16082

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Original Research Article

Received 21 July 2016 Accepted 18th August 2016 Published 7th September 2016

ABSTRACT This study seeks to determine the factors predicting customers’ choice of bank in Ho, Ghana. A descriptive, cross-sectional survey was conducted among 350 randomly selected bank customers of Logistic regression analysis was used to identify the predictors of bank choice. Results show that six factors were significant in predicting customers’ choice of bank in Ho, Ghana. It is suggested that banks should take proper cognizance of these factors as a guide in designing their future strategies for competitive advantage. Also, management of banks should try to maintain customer convenience with their bank location strategically. Finally, the enhancement of security would give confidence to the customers to have a particular bank as a preference hence better secure feelings given from the banks to the customer. It would make customers be more inclined and comfortable to make transaction and choose their bank products and services because they feel it is protected and trusted. Keywords: Customers; predict; choice; bank; logistic regression. _____________________________________________________________________________________________________ *Corresponding author: E-mail: [email protected];

Mahama et al.; BJEMT, 15(1): 1-11, 2016; Article no.BJEMT.28490

consider customer attraction and loyalty as important to market share maintenance and profitability. Because of the high customer defection, the debate as to what informs customer choice is still rife. Usually, the marketing plans of organizations do fail at implementation due to improper identification of the factors or determinants that consumers consider in selecting who to deal with [6]. And as clearly expressed by [7], “we should not accept or reject assumptions and speculations, unless we study these assumptions critically and unless we find logical and reliable explanations to accept or reject them‟. Thus, though several studies investigate the issue of factors affecting selection of retail banks; very few have attempted to directly link the factors of preference to specific banks [8].

1. INTRODUCTION Banking and other financial institutions in Ghana play a critical role in building the economy through the provision of capital in diverse forms. Banks facilitate the accumulation and allocation of capital by funnelling savings into loans to governments, businesses and individuals. The recent worldwide credit crunch which carried some notable banks into oblivion has affected the performance of many banks globally. Thus, to survive in the long run, institutions have realized the need to adopt sound strategies to compete in better ways while being cautious. Just like the economy in general, banking has an interesting history: moving from tightly controlled the post-independent era, through various phases of relaxation, to the present where it is purely market-driven. With the passage of the universal banking law, all types of banking can be conducted under a single corporate banking entity and this has greatly reorganised the competitive scopes of the several banking products in Ghana [1]. The banking industry has been characterized by increasing competition since the early 1980s. This has been the result of a number of interrelated factors such as competition and deregulation that have revolutionized the distribution of many financial services [2]. In other words, an increased competition resulting from a decade of deregulation of the financial services industry has meant that banks find themselves faced with the task of differentiating their organizations and their offerings as a means of attracting customers.

The first prominent and published article on choice criteria regarding banking is completed by [9], who find that there are two segments of consumers. The first segment consists of service oriented consumers who view banks as meaningfully different. The second, larger segment consists of convenience oriented consumers who classify banks as quite similar in offering undifferentiated services. The segments are derived on the following choice criteria: friends’ recommendations, reputation, availability of credit, friendliness of bank personnel and service charges on checking accounts. However, Anderson’s sampling method and determinant attribute method is questioned by [10]. In their opinion, Anderson’s method neglects the significant importance of the location aspect.

The issue of how customers select their banks has been given considerable attention by researchers [3]. Exploring such information will help banks to identify the appropriate marketing strategies that are needed to attract new customers and retain existing ones. With growing competitiveness in the banking industry [4] and similarity of services offered by banks [5], it has become increasingly important that banks identify the factors that determine the basis upon which customers choose between providers of financial services.

An investigates was also done on choice criteria among Swedish bank customersby [11]. Her findings indicate that decisions are made more randomly than one would expect. Although the majority of the respondents use more than one bank, the most important choice criteria are: bank location, availability of loans and payment of salary. In addition, especially young respondents are highly influenced by their parents. With this finding, Martenson highlights the importance of parental influences on young consumers.

Banks which are planning to cultivate this vibrant market segment must understand how individuals belonging to such segments select their banks. In the banking industry of Ghana, high customer attraction is hypothesised to be linked to high firm performance. Bankers

A study by [12] discovered quite a similar result as [9]. Locational aspects, friendliness of personnel, speed of service and convenience are of great importance, whereas media advertising is perceived as ineffective in the selection decision. Since most choice criteria are important 2


with regard to savings accounts and checking accounts, differences among demographic groups are present.

2. LITERATURE REVIEW 2.1 Concept of Behaviour

In line with these researches, the service charge policy of banks is an important determinant for choosing a particular bank. This importance is supported by [13], who discovered service to be more important than speed, access and price. The importance of service in making a bank choice identified by [14].

Consumer

Choice

According to [17] consumer behaviour is a process when people “select, purchase, use or dispose of a product, services, ideas or experiences to satisfy needs and desires”. The idea of understanding consumer behaviour in making a choice as stepwise decision making process is one that is common in marketing [18, 19]. The decision-making process itself is theoretically considered as a logical flow of activities, working from problem recognition to purchase to post-purchase evaluation. This decision-making process is affected by a number of other more complex influences. Some of these influences relate to the wider environment in which the decision is being made while others relate to the individual who makes the decision. Consumer behaviour is defined by [20] as those activities directly involved in obtaining, consuming, and disposing of products and services, including the decision processes that precede and follow these actions. Thus, in the marketing context, the term ‘consumer behaviour’ refers not only to the act of purchase itself but to any pre and post-purchase activities [21]. According to [22], pre-purchase activities include the growing awareness of a want or need, and the search for and evaluation of information about the product and brands that might satisfy it. Post-purchase activities include the evaluation of the purchased item in use, and any attempt to reduce feelings of anxiety which frequently accompany the purchase of expensive and infrequently bought items or services. Each of these has implications for choice decisions and is amenable to marketing communications and the other elements of the marketing mix. Our understanding of both consumer behaviour and the capacity of marketing activities to influence it rest on knowledge of the ways in which consumers form decisions [21].

Moreover, [15] investigates the impact of consumer financial knowledge on bank choices. Her findings indicate that consumers with low financial knowledge choose their bank purely on location or based on recommendation by others. These factors are also important to consumers with high financial knowledge, although service, interest rates and low fees are of more importance to them. As a result of these studies, the amount of choice criteria considered have grown from 15 to 22 [16]. This indicates that choice criteria of consumers are not stable and need to be updated in time in order to ensure that banks focus on the most relevant choice criteria. Hence, there is need for banks, like other service organizations, to effectively identify the important parameters that attract customers’ attention and help in their choice of banks to do business with. In addition, there is the need for banks to know how customers choose their banks and take measures to attract them before others do. Therefore, this study aims at using a binary logistic regression to model factors that predict customer’s choice of bank. While this study is predominantly based on the primary data from customers, the results cannot be generalized, since the research is based on a non-probability sampling technique. As such, the data collected may not be 100% reflection of what is truly obtainable in the target population, moreover respondents may bias information with a view towards pleasing the researcher or perhaps for self-gratification, thus, affecting the findings of this research. More so, the study was limited to only Ho Township, therefore generalizations drawn may not be applicable to the whole of Ghana. Finally, this research did not provide the information on whether a customer provided an opinion related to one particular bank, since it is unknown if the customer has accounts with two banks.

Consumer behaviour is not only influenced by external factors like financial benefits, but also by their attitudes and expectations. These attitudes and expectations are constantly changing in response to a continuous flow of events, information and personal experiences. There is no guarantee that consumers will respond in the same way in the same situation, since they are capable of applying behaviour to changed circumstances [23]. The consumer decision-

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making process pioneered by [24] in examining consumer purchasing behaviour toward goods and services involves a five-stage decision process. This includes problem recognition, search, evaluation of alternatives, choice, and outcome. Dewey’s decision–making framework viewed the consumer as an information processor, manipulating information through the various stages of the decision process, and suggested that the process, at least theoretically, applied to the full range of consumer decisions. This framework was adopted and extended by [18,25]. A study by [25] suggested that consumers may regress to a preceding stage of the problem solving process at any point in order to redefine the initial problem, search for new information, or to re-evaluate potential problem solutions. The consumer may also discontinue the problem solving process at any stage due to changes in their desired or actual state. Furthermore, the intervention of environmental factors such as income, cultural, family, social and physical factors also constraint consumers from advancing to the first four stages in the consumer decision-making process: the problem recognition stage, the search stage, the evaluation of alternative stage, and the choice stage.

People are putting all their money in cash or buying crisis-proof products. Others spread their money between several banks or are changing their current bank. There are four factors consumers focus on when dealing with perceived risks in times of uncertainty [28]. The first thing is reputation. In times of choosing a bank, many customers feel uncertain basing their choice on many factors and generally presume that reputation can provide protection for the organization [29]. Reputation can reduce consumer’s uncertainty associated with a competitive and potentially hostile environment like a first encounter. The second factor is information gathering. In times of uncertainty it is proven that information supply is more important for consumers. With more reliable information they can make better decisions that reduce risks as much as possible. The third strategy is relying on the expertise of the salesperson or in this case the expertise of the bank. The fourth and final strategy consumers‟ use is searching for guarantees that reduce risks. When buying a service these are usually “not-good-money-backguarantees” but at least helps to rationalize all perceived negatives as positive. The way people deal with uncertainty differs from person to person. Some consumers have a risk seeking personality while others are more risk averse. Also the cultural environment influence people’s attitude towards risks and varies among cultures [30].

Analogous to [24], consumer decision-making process for goods, [26] suggested the decisionmaking process could be applied to services. The five stages of the consumer decision– making process operationalized by these researchers were: need recognition, information search, evaluation of alternatives, purchases and consumption, and post-purchase evaluation. They implied that in purchasing services, these five stages do not occur in a linear sequence as they usually do in the purchase of goods. In addition, there are a number of generalizations which have been postulated to differentiate some aspects of consumer behaviour in services from goods [26].

2.2 Marketing in the Banking Sector For a long time, the banking sector tended to perceive their business very narrowly as ‘selling the use of money’ [12]. This mindset was responsible for not implementing marketing techniques by banks, while manufacturing industries already used these techniques [9]. Since service companies had a less structured marketing department and allocated a rather small budget, they did not implement techniques to differentiate themselves from competitors or to meet customers’ needs [31]. In their opinion, the banking sector sold a commodity and ‘one bank’s product is no greener or crisper than another’s’ [9]. Therefore, the industry did not use methods like segmentation, positioning and product differentiation to meet customers’ needs more adequately. This philosophy changed when banks realized that fulfilling customer needs was more than merely providing the use of money. Increasing competition and acceptance of the trust companies were responsible for this change [12]. This mindset change also impacted the

The variables that consumers’ use to evaluate service alternatives come in many forms. The number of variables involved, as well as the way they influence consumers’ evaluation of alternatives varies according to the type of situation [19]. According to [23] a financial crisis is one of such circumstances. In the view of [27] the economic pessimism leads to a decline in willingness to make large expenditures and debt commitments. Moreover, according to the TNS Financial Crisis Study, people are changing their financial behaviour in response to the crisis. 4


decision complexity of consumers when banks began to offer multiple possibilities to fulfil these personal needs. The consumer has to consider multiple aspects, prior to making a bank choice, whereas in the past this was not necessary. This decision-making process became of great importance to bank managers, when research justified that customers are typically loyal to their bank and stay there for a long time [32]. However, this loyalty is more driven by high switching barriers instead of loyalty in the strict sense of its meaning [33]. Nonetheless, customer loyalty creates possibilities for crossselling once the consumer has become a customer [34].

A total sample of 350 was taken from the target population. The study employed a probabilistic sampling technique, precisely simple random sampling. This sampling technique is being used because it gives equal chance to each member of the population of interest to be selected without bias.

2.3 Consumer Decision-making Process

Data analysis was done using binary logistic regression to determine the factors that were related to customers’ choice of a bank. The logistic regression model has also been used to identify variables that have been influential in customers’ choice of a bank. Specifically, the study seeks to find out if some factors () tend to influence the likelihood of customers choice of bank ().

Data for the study was obtained using structured questionnaire. The questionnaire had two sections. The first section consisted of demographic information such as age, and monthly income level of respondents. The second section dealt with factors that influence customer’s choice of Bank.

As a result of increased choices and improved product offerings by banks, financial services became intangible and rather complex. Therefore, consumers had to develop more analytical, sophisticated and systematic skills that became useful in their buying decisions [35,36]. They perceived financial services as high-risk purchases, resulting in consumers becoming more demanding [37]. These highinvolvement products need to be analysed in order to obtain a thorough understanding of the right choice, implying multiple phases need to be passed to reach the final decision. This decisionmaking process consists of steps such as problem recognition, information search, processing the information to evaluate alternatives and finally the decision itself [38]. In this context, the information-processing phase is of most interest since consumers evaluate alternatives based on their own judgements and evaluation criteria. Especially in retail stores, consumers compare characteristics of the stores, which they determine by themselves, based on their own evaluation criteria [18]. Therefore, several criteria like brand choice and location feature in the consideration set. Since the wide range of brands often creates information-processing problems for consumers, the mind tries to simplify the decision.

This type of regression model has been chosen because the outcome variable () involved in this study is a dichotomous variable. Whereas linear regression model attempts to estimate the mean (or expected) value of the outcome variable () given the values of the explanatory variables ( ′) , the objective in models with qualitative outcome variable, as in this study, is to estimate the probability of observing the outcome variable (i.e. a customers’ choice of bank) given these factors. The customers’ choice of bank can be characterised by the relation which was proposed by [39]. ) =

1 1 = 1 + 1 + ∑ )

1)

for ranging from 1 to k. ") = ) is the probability of customers’ choice of bank; # is a constant, $ is the estimated coefficients, %′ s are the independent variables. From the expression, the probability of a customers’ choice of bank increases with a unit increase in the independent variable when a coefficient of independent variable is positive. In this research work, the logistic regression technique is used to construct a model to predict and classify customer data.

3. METHODS AND ANALYTICAL TOOLS This study used descriptive, cross-sectional study design. The setting was the Ho Township in Volta Region, Ghana. There are eleven (11) banks in Ho Township. The study was conducted on customers who visited banks in Ho.

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“perceived service quality”, “availability and reliable electronic services”, “convenience of branch location”, and “Security issues of the bank”. These suggest that they have been rated high by the majority of the respondents as having been influencing their choice of bank. Other set of variables are very conspicuous in the table and must be considered for scrutiny.

4. RESULTS AND DISCUSSION This subsection looks at the summary statistics of the respondents. A total of 350 customers completed the questionnaire. Table 1 summarizes the socio-demographic information of the respondents. From the Table 1, 172 respondents which represent 49.1% were males and 178 of them which represent 50.9% were females; in which 57.4% were between the ages of 21-30; 27.4% were between 31-40, 10.3% were between the ages of 41-50; 3.4% were less than 20 years of age; and 1.5% of them were above 50. With regards to marital status, 213 of the respondents which represent 60.9% have never married, 130 of them which represent 37.1% were married, and finally 7 of them which represent 2.0% were separated/divorced.

Table 1. Demographic information of the respondents (n=350) Variable Gender Male Female Age Less than 20 21-30 31-40 41-50 Above 50 Marital status Never married Married Separated/Divorced

The distribution of the respondents according to their level of education appears to be evenly spread among Senior High School (SHS) and Tertiary; both constituting a significantly large portion of the respondents out of the total population; implying that views leading to conclusion drawn from this study could be largely attributed to respondents with SHS and Tertiary certificate.

Frequency

Percent

172 178

49.1 50.9

12 201 96 36 5

3.4 57.4 27.4 10.3 1.5

213 130 7

60.9 37.1 2.0

The Table 3 reveals that there exist intercorrelations among the variables, implying that the indicator variables correlate quite highly with one another. This multicollinearity among the variables should be an indication that there exist similarities in the respondents’ ratings of the

Table 2 indicated that high mean values were recorded for some indicator variables such as

140

128

124

120 94

100 80 60 40 20 4 0 Basic

JHS

SHS

Tertiary

Fig. 1. Distribution of respondents by level of education

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Table 2. Descriptive statistics of indicator variables Mean 4.25 3.41 3.18 4.33 3.03 3.54 2.62 2.65 2.57 4.01 2.49 4.84 3.85

Convenience of branch location Effective and efficient Customer Services Bank Reputation Availability and reliable electronic services Low service charges Range of services/Product offerings Extended operational hours Availability of parking facilities Reasonable interest rates charge Security issues of the bank Ambience of the banking hall Perceived service quality Timely service delivery and reliability twenty factors influencing employee turnover. The correlation coefficient must be 0.3 or greater since anything lower would suggest a really weak relationship between the variables [40]. Thus, the highest correlation value of 0.68 recorded between X4 (Availability and reliable electronic services) and X12 (Perceived service quality) indicates that about 68% of the respondents rated availability and reliable electronic services and perceived service quality almost the same. More so, there is a relatively high correlation between variable X1 (Convenience of branch location) and X7 (Extended operational hours), X2 (Effective and efficient Customer Services) and X3 (Bank reputation), and X8 (Availability of parking facilities) and X9 (Reasonable interest rates charge). Although there are some few negative correlations too among the variables, showing an inverse relationship, none of them appear to be high.

Std. deviation .914 1.390 1.417 1.180 1.304 1.275 1.173 .987 1.054 1.162 1.075 1.150 1.182

a bank was convenience of location. It is also consistent with the observations of [42] which revealed that safety of fund; efficient service quality and speed of transactions have significant positive influence on customers’ bank selection decision. Thus the logistic function is given by equation (2) below: "'()*+ℎ-. ) = 1 1 + /.012 3.34563./1053.1631 3.33703.300633.6/06/)

2) Furthermore, the odd ratio ( 9:;$)) for the significant factors, shows the increase (or decrease if the ratio is less than one) in odds of being in one outcome category (choose or not choose) when the value of the predictor increases by one unit. From Table 2, the odds or risk of customer choosing a bank, is 0.967 for X1 (Convenience of branch location). This indicates that, when the bank location is convenient for the customer, the risk of choosing a bank decreases by a factor of 0.967, all other factors being equal. For X4 (Availability and reliable electronic services), the odd ratio of 1.322 indicates that risk of customer choosing a bank, is 1.322 times higher for a customer who has a problem with availability and reliable electronic service than for those who do not worry about the factor, all other factors being equal.

Table 4 shows the result of logistic regression estimates of the various factors predicting customers’ choice of bank. The significance value of the Wald statistics for each independent variable indicates that overall customer attributes can project customer bank choice (P