Purchase intent is the most important variable in the current research; it is the consumer’s final decision or intention as to whether or not to buy a product. It is the completion of the process after the customer has passed the through various stages of the process, including the perception of a positive retail store image. Once inside the store, customers encounter the salesperson and start analysing their personality, which has an effect on their decision to buy the product. If the salesperson’s image is positive, they are bound to create relational bonds which lead to building trust, commitment and involvement in the purchasing process. The final outcome of any purchase is buying the product. This is very important for all retailers and business managers because their whole business depends on the actual business they make.
A well-established consumer decision-making process, proposed by Engel, Blackwell and Miniard (1995) is based on six stages: (1) problem recognition, (2) search, (3) pre-purchase alternatives evaluation, (4) purchase, (5) consumption and (6) outcomes.
It is well established in the marketing and consumer behaviour literature that the consumer purchase decision process consists of five stages: (1) problem recognition, (2) information search, (3) evaluation of product options, (4) purchase decision and (5) post-purchase support (Engel & Kollat 1978; Kotler 2002).
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The purchase process starts when a consumer identifies a problem or a need. The desire to buy a product or service is largely subconscious (e.g., thirst, hunger, admiration of a neighbour’s new car), and the utility in consuming the product/service is the same whether the consumer obtains the product/service from a physical store or an online store.
In the case of computers, for example, students identify that they need a computer to process their data, work on assignments, check the university web site and get in touch with other students, university lecturers and family members. The next stage, an information search of price and product information, usually incurs search effort. A consumer who wishes to purchase a product from a brick-and-mortar store has to spend time browsing the aisles. If no suitable product is found (e.g., because of high prices or lack of favourable product attributes), the consumer must spend further effort on additional searches. In contrast, e-commerce online shopping dramatically reduces the search effort for price and product information since it all can be done with just a few clicks. The relative ease of online searching for better prices motivates consumers to shop online. Consequently, consumers who have stronger price-search intentions may find online shopping more attractive than visiting a physical store.
However, there are various advantages of a physical store compared to online shopping portals; consumers can see the product, feel the product, get more technical details, experience the reliability of a physical store, experience its image and brand equity and be helped by professional salespeople to buy the right kind of product.
The third stage of the purchase-decision process is the evaluation of product options.
This incurs evaluation effort which involves examining and comparing product attributes such as price, brand and quality. Even if the search costs for price information are reduced, consumers may find it difficult to evaluate non-price attributes. Product quality is important to different demographics of consumers. In shopping for a computer, the problem is whether to have a desktop or a laptop. If the consumer is moving from one place to another in their work, they need to have mobile access to data. Where can they get the product and how? Are they going to buy secondhand or new? Where are they going to buy? Will they buy using online shopping or a physical retail store? What sort of features and benefits are they looking
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for? Which store is more reliable and trustworthy? Which store gives after-sales service like warranties?
The next stage is the information search and pre-purchase alternatives evaluation. The information search can be linked to two types of informational influences; personal influences such as reference groups (e.g., family, friends, co-workers) and marketer- media (e.g., TV, radio, newspaper). Reference groups, persons or groups of people who significantly influence individuals’ behaviour, have been used by advertisers both as sources of information and as product endorsers. They are people who can influence significantly the audience’s information-processing and purchase behaviours (Bearden & Etzel 1982; Childers & Rao 1992). The pre-purchase alternatives evaluation can be considered as the evaluative criteria that consumers use when they purchase products or patronise stores. Given the fact that today's consumers have too many stores from which to choose in deciding where to purchase goods, tailoring store attributes to target markets is critical in company promotions. In fact, the importance of identifying key store attributes as they affect the consumers’
purchase decision-making has long been recognised by a number of researchers (Myers & Alpert 1968; Fishbein 1972; Linquist 1974–75; Mazursky & Jacoby 1986;
Hildebrandt 1988). The list of store attributes reported by these researchers can be broadly categorised into two distinct groups; viz., upscale-image attributes (prestige, attractive displays, up-to-date items) and convenience attributes (convenient location, easy parking and ease of return of goods).
During the evaluation stage, consumers also evaluate the perceived risk associated with their purchasing. Risk perceptions influence evaluation and choice behaviour (Ross 1975; Dowling & Staelin 1994). Research has shown that a consumer’s decision to modify, postpone or avoid a purchase decision is heavily influenced by the perceived risk (Bauer 1960; Taylor 1974). If consumers feel that the time is not right for them to buy a product because every week prices are crashing in the retail stores, they will delay their purchase decision. What if they buy the product now and the same product goes down to half price? That possibility is perceived as being too risky, and reduces the overall utility that can be obtained from the purchase. But consumers perceive a certain amount of risk in the purchasing process in terms of falling price and changing models in the high-tech industry for products like laptops. They may
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feel insecure and may decide not to avoid taking the risk. Researchers define perceived risk in terms of uncertainty and consequences (Becker 1965; Bettman 1973;
Ross 1975; Peter & Ryan 1976). These two components of risk also have been found in research on risk perceptions in non-marketing contexts (Slovic et al. 1979; Slovic 1987).
According to risk theory, perceived risk increases with a higher level of uncertainty or a greater likelihood of negative consequences (Oglethorpe & Monroe 1987); for example, if one is considering buying an unfamiliar wine for a dinner party, the perceived risk associated with the purchase could increase because one does not know how the wine will taste (uncertainty) and the guests’ reactions may be unfavourable if the wine is no good (negative consequences). Thus, whether a consumer is willing to bear a particular risk depends on a perception of the likelihood that the risk will occur and of the importance or severity of the possible negative consequences.
The interrelationships between Salesperson Likeability, Retail Store Image, Relationship Orientation, Involvement, Commitment to Retail Store and their impact on Purchase Intention will decide the effects of all the mentioned variables. On the other hand, there seems to be consensus on the positive effect of salesperson likeability and retail store image on creating a relationship orientation in customers (Drew 1991; Cronin et al. 1997, 2000; Sirohi et al. 1998; Sweeney et al. 1999). In general, the more favourable consumers’ opinions are of retail store image and salesperson likeability, the higher the positive feelings by the consumer towards taking a purchase decision. More favourable perceptions of service quality also lead to reductions of perceived risk (Sweeney et al. 1999). The reason behind this is that salespeople, being part of the evaluation of service quality, can reassure consumers and take away mental stress (Spence et al. 1970; Baker 1987; Hartline & Ferrell 1996;
Sirdeshmukh, Singh & Sabol 2002).
Once a purchase decision has been made, the product still has to be physically delivered, except in the case of digitised products/services. Since consumers tend to maximise utility subject to time constraints (Becker 1965), the efficiency of delivery is a real concern for both consumers and retailers. Online retailers often experience low customer satisfaction because of poor fulfilment of on-time delivery (Jedd 2000).
Consumers place different valuations on speedy delivery. Those who are
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sensitive may favour a traditional channel simply because it saves delivery time. To account for the effect of time spent waiting for delivery, channel preference for delivery time is included in the model. This gives a huge potential opportunity to well-established physical retail stores to improve their services on delivery and logistics.
As illustrated by Gardner (2000), the product life-cycle of high-tech items is getting shorter; this results in a delay in the purchasing process. Many consumers feel it is too risky to purchase when the products are becoming obsolete in a short period. The biggest fear is not being satisfied with their purchase in terms of value for money, or not getting all the features and benefits of new products which will arrive after the discontinuation of existing products. Therefore, it is very important for consumers to be satisfied with the entire purchasing process and their interaction with the parameters of retail store image and salesperson likeability.
The advice of salespersons as a risk-reducing strategy is particularly needed in high-risk purchasing situations (Mitchell & McGoldrick 1996; Black et al. 2002). In the laptop purchase process, which is treated as a high-involvement purchasing process, relationship orientation has an attenuating affect on risk perceptions. Favourable perceptions of a retailer’s reliability, return-handling, responsiveness, policies and problem solving are generally associated with lower risk (Wolfinbarger & Gilly 2003). As such, higher salesperson trust and likeability leads to lower risk perceptions. Although research has shown that the affects of relational bonding on behaviour are largely mediated by value perceptions (Dodds et al. 1991; Sweeney et al. 1999), other studies have found a direct link between satisfaction and purchase intentions (Cronin et al. 2000; Sirohi et al. 1998; Zeithaml et al. 1996).
Consumer satisfaction with a recently purchased laptop may be lower if it is learned that other laptops have received good evaluations from PC Magazine reports. If one fills the car’s gas tank for $1.30 per gallon, feelings can be upset by subsequently seeing gas being sold at S1.15 per gallon at a nearby pump station. One may even be displeased with the purchase of stock that subsequently increased in value when other stocks considered for buying increased more. In each of the above examples, there are feelings of regret about the purchase made. One might feel that a bad decision was made and that, given the opportunity to make the decision again, a different choice would be made. Studies have documented a relationship between regret and
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satisfaction; the more regret one feels following a decision, the less satisfied one tends to be with that decision (Roese & Olson 1995). Recently, researchers have begun to explore whether anticipated regret affects actual decisions. If consumers learn what situations tend to produce the greatest regret, and if regret is sufficiently aversive, then consumers should avoid those situations. Evidence suggests that people can learn to predict accurately how much regret they will feel in particular situations (Schwartz 1998; Meilers, Schwartz & Rilov 1999). Other work shows that when choosing between alternatives that are identical except for that fact that one alternative is associated with greater regret, people will choose so as to minimise regret (Zeelenberg et al. 1996; Zeelenberg & Beattie 1997).
A consumer could regret having made a purchase too early and missing a better subsequent opportunity. Alternatively, s/he may regret having waited too long to make the purchase and passing up a better prior opportunity. Although the magnitude of these comparisons may be equivalent in some cases (e.g., when the product was purchased for $100 but was available for $80 in an earlier or later week), the magnitude of the consumer’s regret may differ. Second, the control that consumers typically have over the timing of their purchases varies. In some cases, consumers have no immediate need for the product and can purchase at a price or time that they desire. In other cases, consumers have a pressing need for the product and have less control over the timing of their purchase. Each of these situations may lead to feelings of regret, but the degree of regret experienced may differ depending on the degree of control available.
Consumer satisfaction affects repeat purchases, product return rates, brand loyalty and the valence of word-of-mouth communications. Therefore, it is important for marketers to understand how they can influence the determinants of consumer satisfaction. What factors lead to consumer satisfaction? Satisfaction certainly depends to a large extent on the performance of the chosen brand; but product experiences do not completely determine satisfaction. For example, a large body of research shows that satisfaction also depends on the level of performance that the consumer expected (Oliver 1980; Churchill & Surprenant 1982).
Satisfaction also depends on information about outcomes that were not experienced.
When people evaluate their purchase decisions, they compare obtained outcomes to
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those that would have occurred had they chosen differently (Taylor 1997; Kahneman
& Miller 1986; Boulding et al. 1993). These so-called counterfactual comparisons can produce either positive or negative emotions. When people compare an obtained outcome to one that would have been superior (referred to as an ‘upward’
comparison), they often report feelings of regret and are less satisfied with the outcome. When people compare an obtained outcome to one that would have been inferior (a ‘downward’ comparison), they report feelings of relief and rejoicing and are more satisfied with their outcome (Roese & Olson 1993). Furthermore, research suggests that upward comparisons have a greater affect on satisfaction than downward comparisons (Markman et al. 1993; Roese & Olson 1995b; Meilers et al. 1999).
Satisfaction with the relationship is regarded as an important outcome of buyer–seller relationships (Smith & Barclay 1997). If the buyer is satisfied with the entire process of buying, then satisfaction leads to the final stage of purchasing products or services.
If the buyer is totally satisfied with the outcome of the purchasing process, from retail store image through to salesperson help and finally creating relational bondage with the help of trust and commitment, he will involve himself in making the final purchase decision to buy the product. If the outcome of the purchasing process is negative, then his or her search for better products and services continues. Therefore, satisfaction is absolutely critical in the purchasing process. Academics have defined relationship satisfaction as a consumer’s affective state resulting from an overall appraisal of his or her relationship with a retailer (Anderson & Narus 1990). In De Young’s (1996) research, he found that the more individualised marketing tactics resulted in higher customer satisfaction. Wulf et al. (2001) and Odekerken-Schroder et al. (2003) also have suggested that relationship bonding tactics affect relationship quality through perceived relationship investment. Therefore, different kinds and degrees of relationship bonding tactics may result in different degrees of customer satisfaction. Besides, once customers feel satisfied with the retailer’s investment in the relationship, the willingness to build a long-term relationship and the extent of satisfaction with the retailers gets higher.
By contrast, consumer decisions often involve the consideration of many alternatives that are provided by the purchase environment; any one of which may provide information useful for evaluating one’s purchase. This is especially true in the case of
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purchase-timing decisions. Suppose that you have been monitoring the price of LCD/LED 3D TV waiting for a good time to buy. You finally purchase when you feel the price is competitive at $3500. There are a variety of comparisons that you could make to help you evaluate your decision. You could recall that the price had been
$3300 two weeks ago, $3500 with a free 3D Blue Ray player three weeks ago and so forth. In each of these cases, you may feel regret for not having purchased earlier;
such prices can be referred to as pre-purchase prices and can be expected to affect satisfaction. As pre-purchase prices decrease, one should feel more regret and report being less satisfied with a given purchase. Purchase-timing decisions also offer consumers a second set of comparisons on which satisfaction may be based. Suppose that after the purchase of the Liquid Crystal Display/Light-emitting Diode (LCD/LED) and Three Dimensional TV (3D TV) you continue to monitor prices and note that they drop to $2000 in the following week; in this case, one may regret not having waited to purchase the dream TV. The latter prices are called post-purchase prices and, like pre-purchase prices, post-purchase prices can affect satisfaction. As post-purchase prices decrease, one should feel more regret and be less satisfied with a given purchase. Although both pre- and post-purchase prices may produce feelings of regret, the manner in which they influence satisfaction may be very different.
Do pre-purchase or post-purchase prices have a greater effect on satisfaction? No research has explicitly addressed this question; however, there are a number of empirical results that may give some guidance. Perhaps the most relevant result is a study by Simonson (1992), who studied the relationship between anticipated regret and purchase timing. Simonson asked subjects to imagine that they had to purchase a wedding present in either July or August. Subjects in the regret condition were told that they would be shown comparison prices in the two months after making their choice. They were also asked to anticipate how they would feel if they (1) bought the product on sale in July and observed a lower price in August, or (2) deferred until August and were forced to buy at higher prices than seen in July. Simonson found that people anticipated more regret in the second case, when a better price was passed over. Furthermore, subjects who anticipated learning August prices were significantly more likely to purchase in July than subjects who did not anticipate learning this information. Simonson argued that buying products on sale constitutes more of a subjective norm than deferring purchase and, therefore, upward comparisons incurred
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through waiting produce greater regret, a result previously noted by Kahneman and Miller (1986).
Another sort of literature that may yield insight is that of economic search. From an economic perspective, purchase timing decisions are simply a variant of an economic search task (Simon 1955; Stigler 1961; Hey 1981, 1982). A price is observed in the current period and compared to the expected distribution of prices. The consumer decides to purchase in the current period if the expected returns from an additional search are smaller than the costs of waiting. From this perspective, purchase-timing decisions inherently are forward looking; past prices are irrelevant unless they affect expectations (Jacobson & Obermiller 1990). Of course, search theory speaks only to purchase strategies that attempt to maximise expected value and does not incorporate hedonic information into the decision calculus (Inman et al. 1997).
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2.9 Chapter Summary
In this chapter, the development of relationship marketing has been discussd; its definitions, characteristics in the retail industry, its current and emerging trends in marketing and its effects. Transactional marketing theory was compared with relationship marketing theory and used to analyse further the benefits of relational marketing.
Technology, products and services were considered in relation to the retail sector and how the product life-cycle of technology products is affected by constant change and innovation. From extant literature, there was discussion of the development of research hypotheses, and twelve (12) specific hypotheses set for the current research.
Technology, products and services were considered in relation to the retail sector and how the product life-cycle of technology products is affected by constant change and innovation. From extant literature, there was discussion of the development of research hypotheses, and twelve (12) specific hypotheses set for the current research.