Literature Review – Introduction
Satisfaction of consumer needs and wants is the definitive goal for triumph in business. Hence, an effectual marketing strategy must spotlight on serving consumers/customers better than the competitors. The marketing manager should be interested in revealing the complexities of an individual buyer, the dynamics of consumer behavior and should also try to understand consumers’ individual differences so that he/she can segment the total market in terms of those differences Nisel (2001). Buyer decision making should be carefully studied by organizations and marketing managers to have a full understanding of how buyers obtain information, how they form their beliefs, and what specific product-choice criteria are sued by customers. Specific products/services can then be cultivated that will fulfill the appropriate requirements of these groups. Therefore, finding the motives that lead to differences in consumers’ decision-making processes is a critical factor for a company in accomplishing its marketing objectives in order to satisfy its customers Nisel (2001). Differences in consumers’ decision-making processes can aid the managers in classifying individuals into meaningful homogeneous subgroups.
Olson & Peter, 1994 defined consumer behaviour as “the dynamic interaction of affect and cognition, behaviour and environmental events by which human beings conduct the exchange aspects of their lives.” Every organization is interested in consumer behaviour for the sake of strategizing and streamlining their marketing mix to meeting the needs of their target market. Business entities have special interest in consumer behaviour for the reason that they can develop marketing strategies to induce consumers to purchase their products based on consumer research and analysis. For a company’s marketing strategy to hit the success mark, it will largely depend on how well the strategy is tailor measured to buyers needs and wants and how these buyers react to the strategy. Companies can find out what satisfies their customers by mandating their marketers to examine the main influences on what, where, when and how customers buy goods and services Dibb et al (2001). When these factors are well understood, companies through their marketers can better be able to predict how consumers will respond to the marketing strategies of the firm. In the null shell, the information gathered through the market research and analysis will position the firm to compete more effectively in the marketplace, afford it will greater market share and better customer service delivery which will lead to customer satisfaction. This chapter which looks at the literature review will primarily center on why buyers behave the way they behave, their purchase decision process, the influencers of their decision, gathering knowledge for purchase decision, effective segmentation by supermarket operators, how to cultivate a good behaviour for shoppers, shopping convenience among other things. This is an attempt to develop a framework for the study buyer behaviour as a determinant for purchase.
Shopping has become a part of everyday living for most people both home and abroad. Regardless of the increase of various home delivery shopping services, shopping for most reasons means physical visits to a shopping site. The place most repeatedly visited is either the supermarket or the shopping mall. In fact, going shopping is a major source of relaxation as well as a household chore according to Dholakia (1999). Oakley (1974) asserts that shopping is one of the activities with the most positive attribute of being able to talk to others while doing work. Shopping is widely regarded as a major leisure-time activity Reid and Brown (1996). Cullen (1990) emphasized that, shopping is second only to TV watching in the pantheon of British leisure. Others such as Bloch et al (1992) and Macalister (1992) have also generally and similarly supported that with statistical data.
Shopping may or may not be a leisure or recreational activity Howard (2007). Theories of recreation and its meaning are numerous and often times they come with a moral factor. Bronowski (in Howard, 2007) for instance believes that, leisure brings a promise that:
. . . “A deep sense of appreciation envelopes us and lifts us to a higher plane, where we discover that there is peace and beauty and joy in the world. And that may carry over into increasing appreciation of life itself”.
Shopping motivation may be due to buyer leisure and an important factor to this can be attributed to be attitude to time by diverse consumers on special occasions. This assertion has had some exploring work on them (Davies, 1994; Whysall, 1991, Howard, 2007).
There are a lot of scholars who have pointed out that, there is a nascent sense of time pressure on consumers/customers and these tend to be more affluent than the normal citizenry (Lewis and Bridger, 2000 and Howard, 2007). Schiller (1999) make a case that “mainstream retailing” (consisting of routinely and regularly purchased goods) is increasingly being put under a time squeeze, partly because of longer working hours and higher female participation rates in the labour market, and partly because holidays and other leisure activities are taking an increasing share of consumers’ time and money. Schiller (1999) explain “leisure shopping” “as the mirror image of mainstream retailing where the outing is not so much a means to an end as the whole point, and shopping is only part of the experience”. There is evidence of an increasing proportion of people saying that they spend time looking around the shops as a leisure activity (Mintel, 2000).
Tauber 1972 gave two categories of shopping motives to be role playing and Social experience outside the home. The table below shows nine shopping motives which have been grouped under two main categories.
Table I Shopping Motivation
|Role playing||Social experience outside the home|
|Diversion||Communication with others with similar interests|
|Learning about new trends||Peer group attraction|
|Physical activity||Enjoying status and authority|
|Self-gratification||Pleasure of bargaining|
Source: Tauber (1972)
In his research, Dholakia, (1996) empirically determined three motives for going shopping based on factor analysis of 13 statements. These three motives were labeled as:
- Interactions with family
- Utilitarian and
- Shopping as pleasure
The shop must be attractive to meet the expectation of the target customer. Shop attractiveness may come as a result interplay of multiple of factors. A customer may find a shop attractive due to its versatility in terms of product assortment and variety, physical evidence, tailor-measured customer service, fast service recovery rate, longetivity, location convenience, one-stop shopping advantage among other things. Howard (2007) asks what she terms as the obvious question of shopping as just what makes shopping a pleasurable or leisure experience. Amongst the work on particular environments and factors have appeared some interesting ideas about browsing (Bloch et al., 1991, 1994; Lombart, 2004, Howard, 2007). Jones (1999) looked at the array of factors involved in entertaining shopping experiences. Jones observed retailer factors (prices, selection, store environment and salespeople) and customer factors (social aspects, tasks, times, product involvement and financial resources) together.
There have been a few empirical studies done to analyze the motivational aspects of consumers to explain their attraction to shopping malls (Bodkin and Lord, 1997; Ruiz, 1999; Dennis et al., 2001; Nicholls, et al., 2000, 2002, El-Adly, 2007). Ruiz (1999) puts the starting point of some shoppers’ attractiveness to shops on the motives of purely economic motives; while others are attracted due to emotional motives and other due to multi-purpose shoppers which are the combination of these motives. In Nicholls et al. (2000), he found that Chilean consumers visit malls for fundamental reason of purchasing factors and also he found USA consumers visit to shopping malls is for diverse reasons which largely revolves around entertainment. Wakefield and Baker (1998) found that the mall environment influences the desire to stay and re-patronage intentions to the mall. Bloch et al. (1994) on the other hand in his paper investigated the consequence of shopping mall physical environment on consumers’ emotional states. His research reviewed that malls were viewed by consumers as a place for shopping as the basic reasons; however, entertainment played a role among other things in the view of consumers about the shopping mall.
Nicholls et al. (2002) added to entertainment motives when he observed that today’s mall patrons tend to be more leisure driven than shoppers in the early 1990s. Finn & Louviere, 1996; and Sit et al., 2003 in their studies have given the indication that, the significance of the shopping centre image is a decisive determinant on consumer patronage decisions. Terblanche (1999) was concerned about the impact of four dimensions on shopping centre patronage. His four dimensions of shopping center patronage included, functional, recreational, socializing, and convenience dimensions. He based on these dimensions to be the perceived profit that consumers enjoy when visiting a super regional shopping centre or a shopping mall. His findings showed that recreation (entertainment) appears to be the major benefit pursued by shoppers that patronize a super regional shopping centre.
Bellenger et al., 1977; Bloch et al., 1994; and Roy, 1994 also looked at demographic and psychographic characteristics of mall patrons. Martin and Turley (2004) studied the attitudes of the young segment of shoppers towards malls, and factors arousing utilization. They found that they were more likely to be objectively rather than socially motivated to patronize. In addition to the effect of malls’ internal attributes on patronage, other attributes such as travel components that include comfort, reliability of transport mode, effort, tension, distance, and value were significant in affecting shopping centers’ patronage (Ibrahim, 2002).
Segmenting the consumer market of shopping mall
Over the last three decades, there has been a substantial amount of research on market segmentation for consumer goods and services El-Adly (2007). As competition in the retail marketplace increases, the need for more precise segmentation tools becomes greater Chetthamrongchai and Davies (2000). However, segmentation research in retailing was very rare and concentrated on individual stores, not on the mall itself (Frasquet et al., 2001; Ruiz et al., 2004). Demographic variables alone provide a narrow perspective of consumer behaviour and thus market segmentation (Boedeker and Marjanen, 1993). Methods using shopping motivation as the basis for distinguishing between individuals offer a more grounded approach in classifying shoppers, Stone (1954), Tauber (1972), Westbrook and Black (1985) and Bellenger and Korgaonkar (1980). Retail market segmentation is necessary and often critical to the development of effective marketing strategies in today’s competitive marketplace Segal and Giacobbe (1994). Segal and Giacobbe (1994) further posit that, the impetus for a market segmentation strategy is basic: customers exhibit heterogeneous needs and purchase patterns, and thus respond differently to different marketing stimuli.
El-Adly (2007) suggest that there are two segmentation approaches that have been introduced in the marketing literature, a priori and cluster-based segmentation (also called post-hoc). Priory segmentation has been subject to criticism in that it focuses on the external characteristics of consumers (e.g. sex, age and social class) in describing the differences between segments’ behaviour El-Adly (2007). Harrison, (1995) asserts that, these external characteristics are not necessary determinants of buying behaviour. Thus, it is found that, just a few researchers have used this approach in shopping centre segmentation Chetthamrongchai and Davies (2000). Lee et al. (2005) as an instance studied shopping centre factors that have an influence on shopping enjoyment of male segment. They found that “shopping-centre features”, “ancillary facilities”, “value-added features” and “special events” are momentous in shaping male shoppers’ pleasure. Dennis et al. (2001) in a part of their study used different subsets of a priori segmentation pairs: male/female, higher/lower socio-economic groups, higher/lower household income, older/younger and auto/public transport. Dennis et al. (2001) however, the finally based their study on post-hoc segmentation. “Service” and “shops” were identified groups importance of motivation, which were seen as more useful than conventional a priori segmentation roots in modeling spending behaviour among shoppers.
Compared with a priori segmentation, the post-hoc or cluster-based approach has obtained much attention in shopping mall segmentation El-Adly (2007). Using this approach, a heterogeneous population is segmented on the basis of homogeneous responses from within the population (Gwin and Lindgren, 1982). In this concern, Finn and Louviere (1990) identified shopper segments based on differences in shopping mall consideration sets and investigated the differences in mall choice parameters for these segments. At the same line, Boedeker (1995) segmented shoppers on the basis of their general choice criteria of a retail outlet, into two groups the “new type shoppers” who value both the recreational and economic/convenience characteristics of a retail outlet and the “traditional shoppers” who were much lower in their desire for the recreational aspects. Mall attributes have been used by Reynolds et al. (2002) to segment malls into five segments namely enthusiasts, basic, apathetic, destination and serious. Sit et al. (2003) used the mall image attributes to segment shoppers into six market segments labeled as the “serious” shopper, the “entertainment” shopper, the “demanding” shopper, the “convenience” shopper, the “apathetic” shopper, and the “service” shopper.
Stone (1954) suggested that consumers engage in the shopping process for a variety of reasons which can be identified with one or more of four shopper-orientation profiles, namely “economic shoppers”, who view shopping as a necessary task; “personalising shoppers”, who value the social networking integral to shopping; “ethical shoppers”, who see shopping as an activity influenced by their views as to what is right or wrong, and “apathetic shoppers”, who dislike the activity. Other researchers have advanced and refined the notion of shopping motivation using the same or similar conceptualisations (Tauber, 1972; Buttle and Coates, 1984). Boedeker (1995) found that shopping profiles can be classified into two main types, “new-type shoppers” and “traditional shoppers”. Boedeker (1995) put forward that the main differences between these factions lie in their fondness for the use of leisure time and their experiences while shopping.
New type shoppers refer to those consumers who simultaneously value both the recreational and economic/convenience characteristics of a retail outlet Chetthamrongchai and Davies (2000). They further posit that traditional shoppers tend to enjoy the experience more. Bellenger and Korgaonkar (1980) argue that, for some people, shopping may even be a very enjoyable use of time without the purchase of goods or services. These shoppers can be referred to as the recreational shoppers; they usually embark on non-planned shopping and are more likely to persist to shop even after making a purchase. Convenience shoppers on the other hand, may seek to minimize the time required for shopping Chetthamrongchai and Davies (2000). While most studies have considered shopping for any type of product, some previous studies have focused specifically on food shopping behaviour, the product sector of interest here. Cluster analysis has been used to identify market segments who share similar views (Darden and Ashton, 1974; Herrmann and Warland, 1990).
Purchase decision process
Trout and Rivkin (2000) estimate that there are now more than one million stock-keeping units (SKUs) in America, and that an average supermarket stocks 40,000 SKUs. The complexity of consumer decisions is increasing: in the 1960s a consumer chose between approximately 100 models from four car manufacturers – now there are 260 models from 20 manufacturers (Trout and Rivkin, 2000).
Lye et al (2005) in their study have done an in-depth review of both empirical and theoretical studies on consumer decision making. Lye et al (2005) comprehensive analysis of consumer decision is being adopted by this study. They analyzed the works of Kotler, 1972; Schramm, 1971; Howard (1963); Nicosia (1966); Engel et al., 1978; Engel et al. (1968); Farley and Ring, 1970; Lutz and Resek, 1972; Hunt and Pappas, 1972; San Augustine et al., 1977; Hunt and Pappas, 1972; Rau and Samiee, 1981 They posit that the simplest and perhaps earliest theoretical form of consumer decision model was the “black box” (Kotler et al., 2004, p. 244). Lye et al (2005) explained that, the black box provides a simplified model focused on exogenous variables. The black box model avoided any supposition associated with identifying processes and variables embedded in the minds of consumers. It is essentially a stimulus-response model based on early communication research, including the work of Ivan Pavlov (Kotler, 1972, p. 104). Schramm argues that:
. . . most of the communication process is in the “black box” of the central nervous system, the contents of which we understand only vaguely [. . .] we are therefore dealing with analogies and gross functions [. . .] [not] a true copy of what happens in the black box, a matter of which we cannot now speak with any great confidence (Schramm, 1971, pp. 24-5).
The early integrated models of consumer decision-making attempted to unpack the black box to provide an understanding of the internal consumer decision process for marketing purposes Lye et al (2005). Howard (1963) presented an integrative model of buyer behaviour that was modified and became the well-known Howard and Sheth model (1969). Nicosia (1966) published an influential model that used a diagram and equations to explain the decision process. However, a lack of empirical support or subsequent modifications (Engel et al., 1978) resulted in Nicosia’s model disappearing from marketing texts. The Engel et al. (1968) buyer behaviour model survives today, albeit in a modified form. Although other models have been published, these early models were ground-breaking: they evolved and two of the three have survived for over 30 years Lye et al (2005).
These integrated buyer behaviour models comes with some criticisms, and empirical testing has proved problematic (Farley and Ring, 1970; Lutz and Resek, 1972; Hunt and Pappas, 1972). However, support for parts of the models has been published (e.g. San Augustine et al., 1977). The greatest empirical challenges have been creating a clear definition of the model boundaries, identifying the relationship between the variables and determining the best proxies by which the variables can be operationalized (Hunt and Pappas, 1972; Rau and Samiee, 1981).
The purpose of the early consumer decision models was to illustrate conceptually an integrated decision model rather than develop a precise, comprehensive research roadmap. The stated purpose of the Howard-Sheth model was the “description, application, and assessment of those elements of the theory of human behaviour which they believe to be essential in understanding the range of activities that they call ‘buying’” (Rau and Samiee, 1981, p. 307). Our current powerful analytical techniques may allow us to test these “holistic” early models, but should we do so? Should we impose 35 years of empirical research on these foundational conceptual models and expect empirical validity, when their stated purpose was a conceptual description?
Lye et al (2005) asked what they call the fundamental question of whether the existing decision models reflect the reality of current decision making. They answered both in the affirmative and in the negative citing that, in the affirmative, decision models have been found to reflect decision-making within the context of a single decision that is under examination within the empirical research. In the negative they cited lack of generalization across decision contexts.
The psychology world of the decision maker is seen to be influenced by a set of expectations that are in turn a function of the background of dependent on product – and company specific factors as well as on the process of joint decision making. Howard and Sheth also called attention to the critical factors in organizational buying.
Consumer Decision theory
Consumer decision theory has been developed simultaneously in the psychology, organizational behaviour and marketing disciplines, with each trying to understand the decision-making of individuals, albeit for different purposes and from different perspectives Lye et al (2005). There are three main sets of groupings of consumer decision theory; they are;
(1) Normative decision theory (von Neumann and Morgenstern, 1947; Savage, 1954). The normative decision theory gives a prescription of how the person making the decision should behave to obtain maximum utility (Edwards, 1954; Simon, 1955; Fischhoff et al., 1983; Beach, 1998). The expected utility theory (von Neumann and Morgenstern, 1947) and subjective expected utility theory (Savage, 1954) are examples of the normative decision theory. Fischer et al., (2000) asserts that “the normative decision theory permits decision makers to be uncertain about the occurrence of events in the external environment, but assume that decision makers know their own preferences with certainty”.
(2) Simon (1955) has challenged the normative decision theory. He argued that the decision maker has only bounded rationality (March, 1978) and is seeking to “satisfice”, not maximize. Based on that, the behavioural decision theory has been formed (Payne et al., 1988, 1993). Payne et al in both of researches has found that consumers are adaptive decision makers and their preferences are highly dependent on person-, context-, and task-specific factors (Tversky, 1969; Lichtenstein and Slovic, 1971; Simonson, 1989; Slovic, 1995; Luce et al., 1997; Luce, 1998; Swait and Adamowicz, 2001). This constructive view of decision-making differentiates between behavioural and normative decision theory (Payne et al., 1992). In reality, not all decision makers have well-established preferences. Hence researchers argued that consumer preference uncertainty leads to contingent use of decision strategies (Payne, 1976, 1982; Christensen-Szalanski, 1978; Payne et al., 1995) and contingent weighting of attribute importance (Tversky et al., 1988; Fischer et al., 2000) by consumers. Behavioural decision research has identified many decision strategies. “Satisficing” (Simon, 1955) is arguably the most well known behavioural strategy.
(3) The third theory is the naturalistic decision theory (Klein et al., 1993). This has evolved out of the principle that decision behaviour should be observed in its natural settings and decision models be developed from the observed real-life decision behaviour (Beach, 1998). Naturalistic decision theory approaches decision making from both a process and outcome perspective Lye et al (2005). Lye et al (2005) posits that, the naturalistic theory begins with a “situation assessment” and offers multiple paths to a purchase decision depending on the consumer’s assessment of that decision situation.
Each decision theory category has developed in response to a need to understand the consumer decision process within the “black box”, with many different decision strategies providing insight into how consumers make decisions Lye et al (2005).
Consumer Decision Strategies
Consumers in making purchase decisions go through processes which will eventually will them to the choice of a decision alternative (Svenson, 1979, Lye et al., 2005). The strategies that consumers go through can be categorized by using two factors which are the compensatory versus non-compensatory comparisons; and alternative-based versus attribute-based (Bettman et al., 1998) comparisons. Lye et al., (2005) have tabulated the comparative summary of normative and behavioural decision theories which I present in table I below.
Table I: Classification of decision strategies
|Alternative||Additive models||Equal weighting models|
|Attribute||Additive difference models||Differential weighting models|
|Majority of confirming dimensions||Lexographic|
|Elimination by aspects|
Lye et al., 2005
All normative decision strategies fall within the “additive” group, reflecting a process of analyzing each option in detail. Compensatory strategies require consumers to make a trade-off between differing values on multiple attributes (Stevenson and Naylor, 1990). Compensatory strategies require extensive information processing because substantial detail is gathered to analyze the trade-offs Lye et al (2005). Non-compensatory strategies do not involve trade-off – rather, they focus on whether or not an attribute meets a predetermined cut-off level (Stevenson and Naylor, 1990). Alternative-based processing refers to a consumer selecting a product/brand and examining all of its attributes before considering the next product (or alternative) Lye et al (2005).
The consumer as an adaptive decision maker and does not have a master list of preferences, creating challenges when they choose in an unfamiliar environment Lye et al., (2005). Payne et al. (1993), proposing an accuracy-effort framework, found that consumers are adaptive decision makers. No single strategy is the more efficient across all decision environments (Payne et al., 1995), and therefore consumers constantly adjust their behaviour and their decision strategy in a way that represents reasonable accuracy-effort trade-offs (March, 1978; Payne et al., 1990).
Bettman et al. (1998) have proposed an extension of the accuracy-effort framework. They made a case that, in addition to maximizing decision accuracy and minimizing cognitive effort, consumers would also want to minimize negative emotion and maximize ease of justification for the purchase made; i.e. a combination of four meta-goals contributes to consumers’ contingent decision behaviour. Empirical research has revealed that consumers use a decision strategy based on task complexity (Payne, 1976; Olshavsky, 1979), cognitions (Pennington and Hastie, 1986, 1988; Shanteau, 1988; Hammond, 1990) and “feelings” or emotion (Garbarino and Edell, 1997; Luce et al., 1997). Research reveals the consumer may be an adaptive decision maker, utilizing different strategies in purchase decisions Lye et al., (2005).
Rational buyer behavior is based on the decision process, which involves the set of rules that the buyer employs to match his motives and his means of satisfying those motives (Howard and Sheth, 1969). Different studies have shown that consumers showing differences in their characteristics have different needs and wants, so the variation becomes observable in the decisions they take during buying a product (Zeithaml, 198; Zeithaml, 1988; Stanton et al., 1994). In view of that, a number of buyer behaviour models have been developed and discussed in the literature. I will therefore at this point give the state of affairs in the marketing and economics literature concerning behaviour models.
Buyer behaviour models
The buyer behaviour models on the present day’s literature are extensive and divergent in their methodology and usefulness. Nicosia (1968) and Engel et al. (1978) are among the very ones that are mostly used by researchers and in an attempt to arrive at a more purposeful model, there has been modification and improvement since they were introduced. The foundations of current consumer decision theory were laid in the 1960s with the Nicosia (1968), Engel et al. (1968) and Howard and Sheth (1969) integrated models of consumer decision making. Despite increasing purchase complexity, two of these models have been remarkably resilient and have remained as the basis for current marketing texts and marketing education (for examples, see Kotler et al., 2004; Sheth and Krishnan, 2005).
The Nicosia model (1968) has its focus on the processes that proceeds purchases and followed by the act; and not necessarily on the act of purchasing itself, `The act of purchasing is only one component of a complex ongoing process; a process of many interactions amongst many variables” Vignali et al, (2001). Vignali et al, (2001) asserts that, the firm’s attributes lead to a message being sent out to the consumer, who in turn translates the message based on their own attributes and needs.
The Nicosia (1968) model assumes that no prior consumer knowledge or experience with the product exists. Researchers such as Loudon, 1988; Chisnall, 1992; and Solomon, 1994 believe that, the search and evaluation processes considered in this model are “over-rational” Vignali et al, (2001). They alluded to “high-cost” products as opposed to “low-cost” products. Therefore, the use of this model to study food buyer behaviour is limited. Howard and Sheth (1968) also developed a model which was more or less a “black box” model. This model ended up categorizing three variables which determine and influence an individual’s buying decision. These categories are; institutional environmental characteristics; societal environmental characteristics; personal characteristics. This model involves information processing, perception and purchasing processes which are a result of motives Vignali et al, (2001).
The next commonly used model is the Engel, Kollat Blackwell model (1978) which originated in 1968. This model in 1973 went through some development and was further revised in 1978. The model por