CUSTOMERS BEHAVIOUR AND HOW IT AFFECTS THE GROWTH OF A BUSINESS

CHAPTER TWO

REVIEW OF RELATED LITERATURE

2.1 INTRODUCTION

This chapter reviews the literature on customers behavior and how it affects the growth of a business. It discusses issues arising from the topic of interest as viewed from different perspectives, with a view of giving a theoretical and empirical foundation to the study.

2.2 LITERATURE REVIEW

Consumer Category

Consumers are individuals and households that buy products for personal consumption. Consumer behaviour is the study of how people buy, what they buy, when they buy, and why they buy. It blends elements from psychology, sociology, socio-psychology, anthropology and economics. It attempts to understand the buyer decision making process, both individually and in groups, (Haward, 1994).

Five categories are commonly used to differentiate consumer. They include;

i. The Upper- uppers (less than 9 percent): These are the social elites who have inherited wealth and have well known family backgrounds. They tend to be conservative and often serve as reference groups for others. They live in large homes in exclusive neighbourhood and buy expensive products.

ii. Lower-Uppers (about 2 percent): These groups are the new rich, having earned their wealth; most often have more money than the upper-uppers and want to be accepted by the upper-uppers.

iii. Upper-middles (12 percent): are primarily “Career” oriented business and professional people. They are well educated, have a strong desire for success, and encourage their children to do well. They are joiners and civic minded. They buy products that signify status and belong to private clubs.

iv. Middle class (32 percent): This class is made up of average-pay-white-collar and blue-collar workers who live on the “better side of town” and try to do the proper things. Their homes are well caved-for and they buy popular products.

v. Working Class (38 percent): Consists of those persons who lead a “working class lifestyle”. They are tied closely to family for support and have a local orientation. The working class maintains sharper sex role divisions and stereotyping. They are concerned about security, live in smaller homes, drive larger cars and watch bigger television sets than the middle class.

vi. Upper-lowers (9 percent) or working poor: They work and are not on welfare.

However, exhibit standards slightly above poverty line. They are poorly educated and perform unskilled labour for low pay, but strive for a high class.

vii. Lower-lowers (7 percent) or “welfare poor”: These groups are on welfare, visibly poverty stricken and usually out of work and have the dirtiest jobs.

CONSUMER BUYING BEHAVIOR

The American Marketing Association defines consumer behavior as “the dynamic interaction of affect and cognition, behaviour, and the environment by which human beings conduct the exchange aspects of their lives” In other words, consumer behavior involves the thoughts and feelings people experience and the actions they perform in consumption processes. It also includes all the things in the environment that influence these thoughts, feelings, and actions. These include comments, from other consumers, advertisements, price information, packaging, product appearance and even government legislation’s such as Ban on importation of textile materials.

It is important to recognize from this that consumer behavior is dynamic, involves interactions, and involves exchanges. Consumer behaviour is dynamic because of the thinking, feelings and actions of individual consumers. For example, the Internet has changed the way people search for information about products and services. The fact that consumers and their environments are constantly changing highlights the importance of ongoing consumer research and analysis by marketers to keep abreast of important trends. The dynamic nature of consumer behavior makes development of marketing strategies an exciting yet, difficult task. Strategies that work at one time, or in one market may fail miserably at other times or in other markets.

Consumer behaviour involves interactions among peoples thinking, feelings and actions, and the environment. Thus marketers need to understand what products and brands mean to consumers, what consumer must do to purchase and use them and what influences shopping, purchase and consumption Further more, consumer behaviour involves exchanges between human beings. In other words, people give up something of value to others and receive something in return. Much of consumer behaviour involves people giving up money and other things to obtain products and services, that is exchanges between buyers (consumers) and sellers (marketers). In fact, the role of marketing in society is to help create exchanges by formulating and implementing marketing strategies.

Culture and Consumer Buying Behaviour

We could argue that a growing child normally acquires a set of values, perceptions, preferences, and behaviours from his or her parents and family during his or her formative years and subsequently other social institutions in the larger society. In essence, it could be argued that the system of human behavior and thought is not random but subject to certain standards. Consistent with this position, Hawkins et al (2004), submit that culture is acquired by man as a member of society. Over time, this now becomes the code of conduct, which must be followed by each member of that society. Similarly, Krakauer et al (2002) hold the view that culture refers to more than merely ethnicity, but a constellation of shared meanings, values, rituals, and modes of interacting with others that determine how people view and make sense of the world. Furthermore, Tylor (1871) conceptualized culture as a complex whole which includes knowledge, beliefs, arts, moral, laws, customs and any other capabilities and habits acquired by man as a member of society. This is consistent with the position of Forsyth (2009) who sees cultural influences originating from nationality, religion, class and the circles the people mix in. In most societies, there are certain beliefs and values that tend to persist because they are core, like: working, getting married, giving to charity, and being honest (Onu, 2000). These are passed on from parents to children and re-enforced by social institutions like schools, government and even mosques and churches.

There are perhaps more cultures in the world than there are nations, ethnic groups, or countries. However, one amazing thing about culture is that it always sounds strange or weird to someone who is not a part and parcel of it. This explains why for example, certain cultures would see monogamy as the norm, polygamy as unimaginable and perhaps polyandry as simply insanity. So, it means that our preference for one over another is more often than not guided or determined by the values we grew to learn rather than our personal preferences. This is because, as argued by Lee (1995), culture is governed by its own principles and not by raw intellect, and differences among people do not reflect differences in levels of intelligence.

Most people would hold on dearly to their cultural heritage particularly those that are considered as core and for this reason, they are less likely to accept changes because they have become somewhat sacred. On the contrary, people are more disposed to changing values that are secondary. For example in Nigeria, getting married and having children are values that are core and as such people hold onto them very dearly. However, the age at which people should get married and the appropriate number of children to have are secondary values. Therefore, marketers are capable of altering secondary values and not core values (White, 1997; Mbah, 2000; Kotler and Keller 2009) in the sense that in Nigeria, early marriages can be discouraged and family planning encouraged as against discouraging people from getting married or having children. Members of the same large culture could manifest different behaviours and preferences. This is because each culture contains smaller groups or subcultures which provide more specific identification or socialization for its members. In essence, a subculture is a segment of a larger culture characterized by a common set of traits according to nationality, religion, race, ethnicity, lifestyle or geographical location (Kotler, 2002).

Although all cultures exist for the gratification of groups of people, they reveal a tremendous spectrum of diversity in what a society expects of its members. They are designed to satisfy biological as well as esteem and companionship needs (Ekerete, 2001). In line with this, Howard and Sheth (1969), posit that every individual’s activities are directed by his or her own culture thereby shaping behavioural pattern which invariably influences or affects motives, brand comprehension, attitudes and intentions to use.

In marketing, cultural differences are becoming increasingly significant when targeting specific ethnic groups so as to ensure a “fit” between the product and those whom it was intended for. Since there are variations in needs and marketing opportunities, it follows that an understanding of a people’s culture is important to marketers.

Consumers buy products primarily for the purpose of attaining a variety of needs satisfaction, which normally have to be consistent with their cultural values. For this reason, among others, marketers need to be familiar with the behaviour of consumers so as to better understand what buyers are really seeking in the purchase of their products.

2.3 Factors Affecting Consumer Behaviour:

2.3.1 Cultural Factors

(a) Culture

Basically, culture is the past of every society and is the important cause of persons once and behaviours. The influence of culture on buying behaviour varies from country to country therefore, marketers have to be very careful in analysing the culture of different groups regions or even countries (Brown, 2003).

(b) Subculture

Each culture contains different subcultures such as religion, nationalities geographic regions; racial groups e.t.c. marketers can use these groups by segmenting the market into various small portions. For example marketers can design products according to the needs of a particular geographic group.

(c) Social Class

Every society possesses some form of social class which is important to the marketers because the buying behaviour of people in a given social class is similar. In this way marketing activities could be tailored according to different social classes.

Here we should note that social class is not only determined by income but there are various other factors as well such as wealth, education, occupation e.t.c.

2.3.2 Social Factors

Social factors also impact the buying behaviour of consumers. The important social factors are reference groups, family, role and status.

(a) Reference Group

Reference groups have potential in forming a person attitude or behaviour. The impact of reference groups varies across products and brands for example if the product is visible such as dress, shoes, car e.t.c. then the influence of reference groups will be high. (Reference groups also include opinion leader a person who influence others because of his special skill, knowledge or other characteristics).

(b) Family

Buyer behaviour is strongly influence by the members of a family. Therefore marketers are trying to find the roles and influence of the husband wife and children. If the buying decision of a particular product is influenced by wife then the marketers will try to target the women in their advertisement. Here we should note that buying roles change with change in consumer lifestyles. The stages at which families find themselves is course of their life cycle (bachelor → newly married → young married couple with children→ older married couple with children→ older married couple without children→ older single individuals) affects the nature of goods and services they demand and there are likely to be marked changes in the volume of expenditure on specific products. Decisions are also likely to be arrived at in different ways at different stages in the family life cycle. A family cycle analysis must allow for variables of age group, marital status, number and ages of children, social class and sources of income (Cherlin, 2000).

(c) Family Roles and Decision Making

The assignment of roles to specific members of family has an impact in its social development and on its buying behaviour. The duty of providing funds for the welfare of the family is customarily assumed by the husband (especially in Indian traditional and rural households) the wife tends to be the custodian with responsibilities particularly related to purchasing food, and household goods. But these traditional roles assigned to family members have undergone changes as a result of socio-economic and political development. There is greater economic, political, professional and social freedom of movement. This has undoubtedly changed the traditional views on dual income or working couple families and the dominant role of the husband as sole income earner has been challenged. Greater participation in an ever-widening area of buying may be expected and marketers keep this information in their selling strategies.

(d) Roles and Status

Each person possesses different roles and status in the society depending upon the groups, clubs, family organization e.t.c to which he or she belongs. For example a woman is working for an organisation as finance manager now she is playing two roles, one of finance manager and other of mother. Therefore her buying decisions will be influenced by her role and status.

2.3.3 Personal Factors

Personal factors can also affect the consumer behaviour. Some of the important personal factors that influence the buying behaviour are lifestyles, economic situation, occupation, age, personality and self concept.

(a) Age

Age and life-cycle have potential impact on the consumer buying behaviour. It is obvious that the consumers change the purchase of goods and services with the passage of time. Family life- cycle consists of different stages such young singles, married couple’s unmarried couples e.t.c. which help marketers to develop appropriate products for each stage (Cherlin, 2000).

(b) Occupation.

The occupation of a person has significant impact on his buying behaviour. Fore example a marketing manager of an organisation will try to purchase business suits where as a low level worker in the same organisation will purchase rugged work clothes.

(c) Economic Situation

Consumer economic situation has great influence on his buying behaviour. If the income and savings of a consumer is high then he will purchase more expensive products. On the other hand a person with low income and savings will purchase inexpensive products.

(d) Lifestyles

Lifestyle of consumer is another important factor affecting the consumer buying behaviour. Lifestyles refer to the way a person lives in the society and is expressed by the things in his/her surrounds. It is determined by consumer interests, opinions activities e.t.c. and shapes his whole pattern of acting and interacting in the world (Cooley,1999).

(d) Personality

Personality is defined by Sheth et.al (1999) as a person’s consistent ways of responding to the environment in which he or she lives. Personality is created through the combing of external influence or social environment and genetic on biological traits of the individual. The combination of social with the individual results to the creation or development customer personality. Consumer personality may be product or service oriented or both. Product oriented consumers tend to patronize a product or service based on the merchandise itself, while service oriented consumers tend to seek relationships with the seller, producer often the service or manufacturer of the product. Personality changes from person to person, time to time and place to place. Therefore it can greatly influence the buying behaviour of costumers. Actually personality is not what one wears rather it is totality of behaviour of a man in different circumstances. It has different characteristic such as dominance aggressiveness self confidence e.t.c which can be useful to determine the consumer behaviour for particular product on service.

2.3.4 Psychological Factors

There are four important psychological factors affecting the consumer behaviour. These are perception, motivation, learning, beliefs and attitudes.

(a) Motivation

Motivation according to Brown (2003) is an inner drive that reflects goal oriented arousal. Motivation is also linked to the social environment and individual traits of the individual, motives are identified into four, namely achievement, power, uniqueness/ novelty, affiliation and self-esteem-motive. These kinds of motives are present in one way or other within the consumer as she/he goes through the decision making process of purchasing a product, goal, or service.

Achievement Motive- The drive to experience emotion in connection with evaluated performance.

Power Motive; The drive to have control or influence over another person group, or the world at large.

Uniqueness/Novelty Motive:

The drive to perceive our self as different from others.

Affiliation Motive

The drive to be with people, consumers sometimes express a strong motivation to reconnect and associate with groups.

(b) Self-esteem Motive

Credit for success, explain away failures, (consumers) see themselves as better than most others.

The level of motivation affects buying behaviour of customers. Every person has different needs such as physiological needs, biological needs, and social needs e.t.c.

The nature of the needs is that some of them are most pressing while others are least pressing. Therefore a need becomes a motive when it more pressing to direct the person to seek satisfaction.

(c) Perception

Selecting, organising and interpreting information in a way to produce a meaningful experience of the world is called perception. There are three different exceptional processes which are selective attention, selective distortion and selective retention. In case of selective attention, marketers try to attract the customer attention.

Whereas in case of selective distortion, customers try to interprete the information in a way that will support what the customer already believe. Similarly in the case of selective retention marketers try to retain information that supports their levels.

(d) Beliefs and Attitudes.

Consumer possesses specific belief and attitude towards various products. Since each belief and attitude make up brand image and affect consumer buying behaviour therefore marketers are interested in them. Marketers can change the belief and attitudes of customers by launching special campaigns in this regard (Frost,

2006).

DETERMINANTS OF FIRM GROWTH

Firm Size and Growth

There is enough evidence to indicate that firm growth is significantly related to firm size and age (P. Dunne & Hughes, 1994; T. Dunne, 1988; T. Dunne et al., 1989; Evans, 1987a; Liedholm, 2002; Shiferaw, 2006). These studies have confirmed that firm growth decreases with firm size for firms of the same age, and decreases with firm age for firms of the same size. In addition, it was found that the variability of firm growth decreases with firm age for firms of the same size, and, to a weaker extent, with firm size for firms of the same age (Brock & Evans, 1989).

There is increasing empirical evidence to suggest that firm growth decreases with firm size for firms of the same age and decreases with firm age for firms of the same size. This contradicts Gibrat’s ‘Law of Proportionate Effects” in which a firm’s growth rate is independent of its size. However, this is increasingly questioned, with empirical works indicating that there is conflicting correlation in the size-growth relationship. It was Evans (1987a) who set out to test the extent to which the independence of firm growth and firm size applies in the small firm sector in the U.S. He concluded that Gibrat’s Law must be rejected for the small firm sector. He found that growth and size are negatively correlated, even allowing for the exiting of slow growth firms. The result is confirmed by Dunne et. al. (1989) who found strong evidence that mean growth rates decline with size for both single-unit and multi-unit manufacturing plants in the U.S. Similarly, a study of small single plant independent manufacturing companies in the U.K. comes to the conclusion that size and growth are negatively correlated (Storey et al., 1987). In another study of UK firms, Dunne and Hughes (1994) suggest that the smallest companies grow faster than the larger ones.

Using panel data of manufacturing firms in Ethiopia, Shiferaw (2006) found that small firms grow faster than large firms even after controlling for sample attrition. Liedholm (2002) came to the conclusion that small enterprise growth is inversely related with initial size in six developing countries of Africa. Therefore, the smaller SMEs at start-up added more job expansion per firm than did their larger scale counterparts (Liedholm & Mead, 1999:37). A similar result is also found in a study of micro enterprises in Southern African countries (McPherson, 1996). Nevertheless, Dunne and Hughes (1994) observe from their study that there is a threshold effect. According to them the mean growth of firms in different size bands is fairly stable beyond this threshold. Empirical evidence from manufacturing industry in Ethiopia indicates that the growth rate does not depend on initial size among large firms (Shiferaw, 2006). In an empirical analysis of a large sample of 4,000 Italian firms it was found that firm growth is independent of initial size for large firms, but this is not the case for small and medium sized firms (Becchetti & Trovato, 2002). You (1995:454) thus notes that there is a clear negative relationship between size and growth among smaller firms, while Gibrat’s Law holds, if at all, only for large firms. In addition, there is a possibility that the size-growth relationship may have changed over time, with the advantage in growth terms moving from larger firms in the 1950s to smaller ones in the 1960s and 1970s (P. Dunne & Hughes, 1994). Johnson (2007) suggested that policy changes may have something to do with this shift. According to him there was much more emphasis on assisting larger firms in the 1950s, whereas the policy focus switched to small firms in the 1970s and onwards, especially in the developed countries.

In studies about the size-growth relationship there is the possibility of sample bias.

Most of the data sets used in the studies are made up of relatively larger firms, no matter how they are measured (Johnson, 2007). Moreover, there is the problem of sample attrition, since small, slow growing firms may be more likely to fail than large, slow growing firms. An analysis of growth that is concerned with survivors alone will be biased towards finding an inverse relationship between size and growth. The poor growth of large firms will simply involve them sliding down the size distribution for a considerable period before dying, whereas for small firms with a similar growth record they are more likely to be forced to exit.

Thus, studies of the size-growth relationship may be biased toward finding that in the small size bands, growth of survivors is faster than in the larger size bands because the slow or negative growers have been weeded out by death (Johnson, 2007).

Firm Age and Growth

Age is an important variable to explain the growth of small firms. The average growth rate is found to have a negative relationship to the age of firms in the U.K and U.S (P. Dunne & Hughes, 1994; T. Dunne et al., 1989; Evans, 1987a). In fact, the model of firm life-cycle based on learning developed by Jovanovic in 1982, also predicted that younger firms grow faster. This influential model considers the learning process in which firm growth decreases with age. Yet, Pakes and Ericson (1998) found that Jovanovic’s passive learning model is not robust to more general specifications of the technology and learning process. They proposed an active learning model and found evidence that the size distribution of firms is stochastically increasing over time in manufacturing industry, but not in retail trade. The implications of the learning model is that the growth and survival prospects of new firms will depend on their ability to learn about their environment, and to link changes in their strategy choices to the changing configuration of that environment. The slower is the process of learning and the more turbulent is the market environment, the more likely it is that firms will fail to cope (P. A. Geroski, 1995). As discussed above, there is a clear indication that age is negatively related to the growth of small firms from empirical studies. Dunne et. al. (1989) find that the mean growth rate for non-failing manufacturing plants in the U.S. declines with age for both plants owned by single and multi-plant firms. In the U.K., Dunne and Hughes (1994) observe that younger companies grew faster than older companies for a given size. Their analysis indicates that age is statistically significant and inversely related to growth for the whole sample, and in different size classes of the sample. According to Liedholm and Mead (1999), there are limited empirical studies examining the age-growth relationship in developing countries. These include countries such as India (Little, Mazumdar, & Page, 1987) and Colombia (Cortes, Berry, & Ishaq, 1987). All these studies found an inverse relationship between the age of the firm and its growth rate for each of the sub-sectors examined. Nevertheless, the negative age-growth relationship is not always clear. For example, Reid (1993) found that age was negative but insignificant to growth in his study of small firms in Scotland in the 1980s. Thus, it is suggested that there could be a positive effect of age in the early years, and then a negative effect in later years (Johnson, 2007).

In the analyses of the age-size-growth relationship there is strong evidence to suggest that the variability of firm growth decreases with firm age for firms of the same size, and, to a weaker extent, with firm size for firms of the same age (P. Dunne & Hughes, 1994; T. Dunne, 1988; T. Dunne et al., 1989; Evans, 1987a, 1987b). The variability of growth rates will be largest among young firms which are often smaller. This variance declines as the firm becomes more mature. In Jovanovic’s learning model, younger firms are seen to have inexperienced management and thus make more mistakes (Jovanovic, 1982). In the smaller firm categories, there is a greater preponderance of younger, inexperienced management. Larger firms also tend to be more diversified and are thus able to spread their risk across sectors and projects (Johnson, 2007).

You (1995) observes that the life cycle models of firm growth based on learning, explain much about the age-size-growth-survival relationship. In these models, firms tend to enter small and grow large through learning. Owing to the greater uncertainty facing younger and smaller firms, they experience greater turbulence – a higher probability of death, a higher growth rate variance, and, in general, a higher average growth rate - than older and larger firms. However, he observes that existing life-cycle models rely on a much too simplistic conception of the nature of the uncertainty faced by firms. Thus, he claims that any dynamic analysis of firms should not disregard the fact that the capabilities of firms evolve over time instead of being given at some level. In fact, Brock and Evans (1989:102) mention that learning considerations are important in the examination of firm growth. In their opinion, individuals must learn about their general abilities as entrepreneurs, learn how to operate particular technologies or ways of doing things. They then predict that the relative importance of these various kinds of learning will vary over the life cycle of the firm and across different industries. Hence, they see that integrating these kinds of learning considerations with capital adjustment considerations will prove to be important.